Population monitoring for Oregon silverspot butterfly to support recovery efforts: a comparison of three methods

Population monitoring for Oregon silverspot butterfly to support recovery efforts: a comparison of three methods | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Population monitoring for Oregon silverspot butterfly to support recovery efforts: a comparison of three methods Izzy Bur, Erica Henry, Richard Van Buskirk, Cheryl Schultz This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9216540/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Reliable population size estimates are fundamental to conservation, yet many at-risk species lack robust monitoring programs. Commonly used methods often do not account for imperfect detection and may lead to biased estimates that limit inference about population size and existing conservation strategies. Oregon silverspot butterfly illustrates this challenge, as the effectiveness of ongoing augmentation programs remains unclear due to limitations in index count approaches currently used for baseline annual monitoring. We surveyed three Oregon silverspot populations from 2022 to 2024 using mark-release-recapture (MRR) and distance sampling and compared resulting population size estimates with concurrent index counts to evaluate their relative reliability for long-term monitoring. MRR was also used to estimate adult apparent daily survival to extrapolate weekly abundances from distance sampling to population size and evaluate demographic differences between wild and captive-reared butterflies. Distance sampling produced population size estimates that aligned most closely with MRR when adult lifespan approximated the weekly sampling interval, whereas index counts generally tracked directional trends in abundance but lacked measures of detectability and uncertainty. Adults had long but variable lifespans, and captive-reared butterflies had lower apparent daily survival rates than wild individuals across all sites and years. Because captive-reared butterflies make up a large proportion of survey detections in heavily augmented populations, interpreting population trends and recruitment is challenging when origin is not distinguished. Implications for insect conservation: Distance sampling offers advantages over index counts for estimating abundance, but reliable assessment of population growth in augmented systems hinges on differentiating between wild and captive-reared butterflies. mark-release-recapture distance sampling Pollard walk survival captive rearing augmentation Figures Figure 1 Figure 2 Figure 3 Introduction A common challenge in conservation is finding reliable ways to monitor populations. Estimates of population size are at the core of many conservation goals and objectives including providing a quantitative foundation for assessing population trends and extinction risk (Fox et al. 2022 ), identifying conservation priorities (Flockhart et al. 2015 ), planning effective management (Örvössy et al. 2013 ), and evaluating the success of recovery efforts (Vrabec et al. 2019 ). Without reliable monitoring, the efficacy of conservation strategies remains largely unknown, potentially leading to ineffective or harmful management decisions or failure to detect population declines (Harding et al. 2001 ; Scheele et al. 2019 ). Despite the importance of monitoring, many at-risk species, particularly insects like butterflies, lack systematic monitoring programs and protocols (Henry et al. 2015 ; Schultz et al. 2019 ). Even when programs exist, they may rely on methods that fail to provide the precision needed to guide conservation decision-making (Kral et al. 2018 ), such as evaluating the contribution of captive rearing programs. Because population size estimates are necessary for guiding the recovery of at-risk species, it is crucial that conservation professionals have reliable methods for monitoring populations long-term (Schultz and Hammond 2003 ). Transect counts or Pollard walks (Pollard 1977 ; Pollard and Yates 1993 ), are commonly used for monitoring butterfly populations because they are easy to implement, cost-effective, and non-invasive (Taron and Ries 2015 ). This method involves regular counts of individuals along fixed transects, providing a population index, and is particularly valuable for long-term studies where consistent, standardized monitoring is needed. Several butterfly monitoring programs have used this method at large scales for tracking butterfly communities, including the United Kingdom Butterfly Monitoring Scheme (Pollard and Yates 1993 ). While they are useful for evaluating broad population changes over time, index counts have limitations. They provide relative indices of abundance rather than estimates of population size, since they do not account for detection probability (i.e., the probability of detecting an individual in a study area) or for variation in adult survival or lifespan, which can influence how many individuals are available for detection at a given time. Indices are prone to bias when detection rates vary across observers, environments, and species (Anderson 2001 ; Kéry and Plattner 2007 ; Pellet 2008 ; Isaac et al. 2011 ; Kral-O’Brien et al. 2020 ), and when transects are not representative or randomly placed (Harker and Shreeve 2008 ; Isaac et al. 2011 ). As a result, indices may only correlate with abundance under certain assumptions (Williams et al. 2002 ; Haddad et al. 2008 ), yet they continue to be widely used for monitoring, even when more robust population estimation methods are available (Kral et al. 2018 ). Mark-release-recapture (MRR) and distance sampling address these limitations by incorporating detection probability into population estimates (Williams et al. 2002 ). MRR involves capturing, marking, and releasing individuals in a population and use recapture probabilities to estimate population size. This method also provides demographic information on survival and detection probability to offer insight into population dynamics. However, MRR is labor-intensive and logistically challenging, and the potential risks of damaging habitat and handling sensitive species limit its feasibility for long-term monitoring (Holmes and Arnold 2015 ; Turlure et al. 2018 ). In contrast, distance sampling estimates population density by modeling detection probabilities based on distances at which individuals are observed from a transect line or point (Buckland et al. 2001 ). This is advantageous because it allows estimation of abundance even when not all individuals are directly observed and enables distance sampling to combine the rigor of MRR with simpler data collection methods, making it effective for scalable population surveys (Kral et al. 2018 ). However, both methods rely on key assumptions—including accurate distance estimation in distance sampling (Buckland et al. 2001 ; Thomas et al. 2010 ) and homogenous capture probability in MRR (Williams et al. 2002 )—that can result in biased estimates if violated. Incorporating more rigorous monitoring methods may allow conservation managers to make more informed decisions, but in many cases limited knowledge of species biology and the lack of independent benchmarks make it difficult to evaluate their reliability. Both MRR and distance sampling are commonly used in butterfly studies, but direct comparisons of estimates generated from these two methods remain limited for butterflies, unlike other taxa including reptiles (Kacoliris et al. 2009 ; Anton et al. 2013 ) and mammals (Corlatti et al. 2017 ; Daura-Jorge and Simões-Lopes 2017 ; Crowther et al. 2020 ). Distance sampling and MRR have been used in the same butterfly system across different years (Hamm 2013 ) but lack data for simultaneous, within-year comparisons. Several studies have compared indices with MRR, with some finding that indices are correlated with MRR estimates (Collier et al. 2008 ; Haddad et al. 2008 ; Zaman et al. 2015 ), whereas others found no correlation (Harker and Shreeve 2008 ; Shuey and Szymanski 2012 ; Norman et al. 2024 ), while others have found that integrating data from MRR into population models can improve estimates derived from simpler methodologies (Schultz and Dlugosch 1999 ; Gross et al. 2007 ; Haddad et al. 2008 ; Holmes and Arnold 2015 ). Comparisons of indices with distance sampling often emphasize the methodological benefits of distance sampling, particularly its ability to account for detection probability (Brown and Boyce 1998 ; Bried and Pellet 2012 ; Patterson et al. 2023 ). Fender’s blue butterfly ( Icaricia icarioides fenderi ) was monitored for multiple years using both methods before switching to only distance sampling (Collins et al. 2011 ). Other studies have found that Pollard walks correlate with relative abundance estimates from distance sampling and are more practical for implementation at large scales (Isaac et al. 2011 ). Direct comparisons of population estimates generated from indices, distance sampling, and MRR within the same system have also not been explored, and the potential for using multiple methods simultaneously to improve long-term monitoring provides a unique research opportunity using a butterfly case study. Many at-risk species have conservation programs that reintroduce or augment populations by releasing captive-reared individuals but lack comprehensive post-release monitoring to assess population size and vital rates necessary for evaluating the success of these strategies (Schultz et al. 2008 ; Ewen et al. 2012 ). For example, Taylor’s checkerspot butterfly ( Euphydryas editha taylori ) populations in Washington are augmented with captive-reared individuals and monitored using distance sampling methods (USFWS 2024 ), but most individuals are not tracked after release, making it difficult to determine the contribution of captive-reared butterflies to population size estimates. Indices or distance sampling can document population trends over time, but without the ability to distinguish between captive-reared and wild individuals on surveys, they cannot quantify the direct impact of augmentation on recruitment or determine whether observed trends are driven by captive-released butterflies. In contrast, MRR can separately track individual butterflies and estimate population demography, but it requires frequent and robust data collection to reliably estimate recruitment (Chandler et al. 2018 ). Given these trade-offs, conservation programs must balance feasibility with the need for robust methods that directly support specific conservation goals (Kral et al. 2018 ). Oregon silverspot butterfly ( Argynnis = Speyeria zerene hippolyta ), listed as Threatened under the U. S. Endangered Species Act (USFWS 1980 ), highlights the need for improved monitoring methods. Historically, Oregon silverspot’s range extended from the coast of southern Washington to northern California, but development in the coastal zone, fire suppression, and subsequent natural succession and invasion of non-native grasses has resulted in the loss of coastal meadow habitat and extirpation of populations (Sims 2017 ; USFWS 2001 ). Today, only five wild populations and two experimental populations remain in Oregon and California, all of which persist at low or very low population sizes. Index counts, which have been used as baseline annual monitoring for Oregon silverspot since 1990, indicate that populations are failing to recover despite annual releases of captive-reared individuals for augmentation since 2000 (USFWS 2020a ). The lack of data on population size, combined with the inability to distinguish between wild and captive-reared individuals in monitoring efforts, limits the capacity to evaluate and refine these conservation strategies to improve recovery outcomes. To address these gaps, our study aims to (1) estimate population size of Oregon silverspot butterflies using MRR and distance sampling, (2) use MRR as a baseline to cross-validate distance sampling estimates with current index count methods, and (3) explore demographic differences between captive-reared individuals released for augmentation and wild individuals. While MRR has been previously investigated in one Oregon silverspot population (Henry et al. 2024 ), distance sampling has not, despite its increasing use for at-risk butterflies (Hamm 2013 ; Belitz et al. 2019 ; USFWS 2019 ; USFWS 2020b ; USFWS 2024 ), including other fritillaries (Powell et al. 2007 ; McFarland et al. 2017 ; Williams and Alexander 2023 ), and its potential for large-scale implementation. Our goal is to develop practical, robust methods for tracking populations of wild and captive-reared individuals over time to evaluate the success of conservation actions. Methods Study system Oregon silverspot butterflies are found in early successional and montane meadow complexes along the Oregon coast. Some sites are coastal terraces moderated by ocean temperatures, while other sites are higher-elevation montane meadows that freeze and receive snow in the winter. The butterfly’s host plant, early blue violet ( Viola adunca ), grows in open grasslands with low-growing vegetation, but ecological succession can reduce habitat quality and violet abundance. Adults require nectar plants and are commonly observed nectaring on goldenrod (So lidago spp.), aster ( Aster spp.), thistle ( Cirsium spp.), pearly everlasting ( Anaphalis margaritacea ), and yarrow ( Achillea millefolium ) (USFWS 2001 ). Nectar plant composition differs across sites and habitat patches. Oregon silverspot completes one life cycle each year, with the adult flight season occurring late June through September for approximately 10 weeks. Adults begin eclosing between late June and mid-July and continue through August or September. Emergence times typically differ between occupied sites, as montane sites can remain under snow into April. Males often emerge several weeks before females (USFWS 2001 ), and females may undergo a period of reproductive diapause before becoming active later in the summer when oviposition peaks (Sims 2017 ). Females lay eggs directly on violets or surrounding vegetation; eggs hatch approximately one week after oviposition and first instar larvae enter diapause soon after emerging (Sims 2017 ). In the spring, larvae become active again coinciding with new violet growth and complete six instars before pupating and eclosing as adults (USFWS 2001 ). To support conservation efforts, the smaller Oregon silverspot populations have been augmented since 2000 in most years through releasing captive-reared individuals, usually as pupae or as third or fourth instar larvae, but the effectiveness of this strategy is poorly understood (USFWS 2020a ). Gravid females are collected from wild populations to provide eggs for captive rearing programs at Woodland Park Zoo (Seattle, WA) and Oregon Zoo (Portland, OR). We surveyed three Oregon silverspot populations on the south-central Oregon coast: Nestucca Bay National Wildlife Refuge (Nestucca), Mt. Hebo, and Rock Creek. Nestucca is a restored site managed by U.S. Fish and Wildlife Service (USFWS) in Tillamook County, OR (45.1659, -123.9537). The site consists of one contiguous meadow that is ~ 15 ha along with nearby hiking paths and roadways (Fig. I). Following restoration from former cow pasture, which began in 2011 in collaboration with the Institute of Applied Ecology, an experimental population of Oregon silverspot was reintroduced through yearly releases of captive-reared individuals that started in 2017. Since the population’s establishment, yearly index counts have ranged between 17–107. Mt. Hebo is located in Tillamook County, OR (45.2148, -123.7565), and managed by U.S. Forest Service (USFS; Siuslaw National Forest). A montane meadow complex extends ~ 2 km along the ridgeline near the summit, which is 970m in elevation. This complex consists of ~ 12 meadows totaling 28 ha connected by a gravel roadway and collectively occupies an area of ~ 332 ha (Fig. SI). Meadows are separated by a matrix of conifer forest dominated by Douglas fir. Mt. Hebo supports the largest remaining wild population of Oregon silverspot, with yearly index counts ranging between 453-2,033 since 2017. Rock Creek is a remnant salt-spray meadow system located on the south-central coast in Lane County, OR (44.1772, -124.1155). Instead of discrete meadows, Rock Creek is a complex of ~ 12 ha of coastal terrace and sub-montane meadows spread over ~ 42 ha of area (Fig. SII), divided into units managed by USFS (Siuslaw National Forest) and Oregon Parks and Recreation Department. Yearly index counts have ranged between 15–160 since 2017. All sites typically receive annual releases of captive-reared butterflies for population augmentation, with release totals varying but ranging from several hundred to over 1,000 individuals released at different stages (larva, pupa, and adult). Fig. I Locations of distance sampling transects, index count transects, and point counts at Nestucca Field methods Mark-release-recapture (MRR) Oregon silverspot populations were surveyed using MRR methods at Rock Creek in 2022, Mt. Hebo in 2023, and Nestucca in 2024. Because of concerns about the potential impacts from handling or trampling habitat, we were only permitted to survey one site per year with MRR. During each MRR study, a team of observers visited the site daily over the entire flight period to capture, mark, and resight butterflies. Wild butterflies were marked upon capture, and captive-reared butterflies were marked after eclosion, prior to release into the wild. Captive-reared individuals were released into the field at three different stages. Third and fourth instar larvae were released into enclosures in May, pupae were released into separate enclosures approximately one week before eclosion, and adults were released directly into the field. Adults eclosing from all captive-reared stages were marked before release at the site. To mark butterflies, we used Gelly Roll 2.0 metallic gel pens on the dorsal side of the right forewing, and ultra fine-tip sharpies on the ventral side of both hindwings following protocols developed by Henry et al. ( 2024 ) for Oregon silverspot in 2021 (Fig. II). By marking butterflies on the dorsal side of the forewing, we were able to resight basking and nectaring individuals using binoculars rather than relying solely on captures for identification. To differentiate captive-reared from wild butterflies, we marked wild butterflies with dark blue gel pen, and captive-origin butterflies with silver. Enclosure or capture date, time, and location were recorded for all newly marked or resighted butterflies using the Avenza Maps app. Sex and source (captive larva-released, captive pupa-released, captive adult-released, wild) were tracked with each butterfly ID. We conducted daily surveys, beginning before the first Oregon silverspot was observed (wild or within enclosures) and continuing until after the last individual was recorded. Meadows at each site were surveyed for a set duration. In 2022 at Rock Creek, we allocated survey time based on staff availability and relative butterfly abundance in each meadow, with those supporting higher butterfly activity receiving approximately two to three times more survey effort than those with little to no activity (MacKenzie and Royle 2005 ). In 2023, we developed a survey protocol to allocate time based on meadow area (ha), violet cover, butterfly density and available staff time (Methods SI). We used violet cover data generated by the U.S. Forest Service in a large-scale meadow mapping project conducted across Mt. Hebo in 2022 (Ashford et al. 2022, unpublished) to coarsely estimate violet cover across meadows. In 2024, we used this same protocol to generate meadow and road survey times at Nestucca. Fig. II Dorsal (left) and ventral (right) marks on Oregon silverspot butterflies (Photos by Océane Caporal and Izzy Bur) Distance sampling (dup: abstract ?) Oregon silverspot populations were surveyed using distance sampling methods at Rock Creek, Mt. Hebo, and Nestucca from 2022 to 2024. Observers visited each site weekly throughout the flight period, walking established transects and recording all Oregon silverspots detected and the perpendicular distance of each from the transect. Distances were estimated to the nearest half meter. Survey transects were established in 2022 using ArcGIS Pro (Esri Inc. 2022) and delineated using a Trimble Geo 7x. Transects were randomly placed without bias toward starting location or habitat features, spaced 30 m apart following modified Pollard survey methods, and ran parallel to fully cover meadows. Transects were re-established each year with some additional transects added in 2023 and 2024 following habitat restoration or observation of butterflies in new areas (Table SI). Distance sampling surveys were conducted in the same areas as MRR each year to allow for direct comparison of methods. Index counts Index counts were conducted by USFWS at Rock Creek and Mt. Hebo from 2022 to 2023, and at Nestucca from 2022 to 2024. A modified Pollard walk was conducted along established transects at each site, where observers walked at a pace of 20m/min and recorded all butterflies within 15 m of the transect (Patterson 2023, unpublished). It is assumed observers can confirm observations of butterflies at distances up to 15 m. This method contrasts with a standard Pollard walk, where only butterflies within 5 m of the transect are recorded (Pollard 1977 ; Pollard and Yates 1993 ). Transects extended around meadows or along hiking paths, and at Nestucca, point counts were also conducted from fixed vantage points to supplement transect counts (Fig. I). Surveys were conducted weekly over the duration of the flight period, and weeks that were missed (due to staffing, weather, logistical challenges, etc.) were interpolated from the previous and following week’s counts. Weekly indices were summed across weeks to calculate a seasonal index. Data analysis Mark-release-recapture (MRR) MRR analyses were conducted using RStudio (Posit Team 2025 ) and the RMark package (Laake 2025 ). RMark is an interface for Program MARK (White and Burnham 1999 ) that allows for the use of MARK functions in R. We developed an approach combining a POPAN model (Schwarz and Arnason 1996 ), which is an extension of a Jolly-Seber model (Jolly 1965 ; Seber 1965 ), and a Cormack-Jolly-Seber (CJS; Cormack 1964 ) model. Both POPAN and CJS are open population models that allow individuals to enter or leave the population through births, deaths, immigration, or emigration. CJS estimates two parameters: φ (apparent daily survival, the probability of a butterfly surviving to the next day given that it’s still present in the study area) and p (detection probability, the probability of recapturing a butterfly given that it is alive and present in the study area). Survival is “apparent”, because we cannot differentiate between individuals leaving a population through death or emigration. POPAN estimates φ and p , along with two additional parameters: pent (recruitment, the probability that individuals enter the population at each time step), and N super (population size). Since pent and N super are already known for captive-reared butterflies (i.e., release dates and totals released on each date), we used a CJS model to estimate φ and p for these groups, and a POPAN model to estimate all four parameters for wild butterflies. We fixed pent and N super for captive groups, then estimated φ and p for each sex and source combination and pent and N for wild males and females. Captive-reared butterflies that were retained for breeding or egg-laying before being released as adults were excluded from apparent survival estimation. Capture histories were first created from the MRR data that denote whether each butterfly was captured or resighted during each sampling occasion. The data were then processed using a POPAN model and grouped by sex and source (captive larva-released, captive pupa-released, or wild). We fixed pent and N super for captive butterfly groups using the total number of butterflies released on each date, and removed the intercept (-1) to only produce estimates for wild butterflies. Sex and source were included in φ and p formulas to compare survival and detection probability estimates between groups. We included time in pent to account for flight period phenology, and sex in N super to estimate population size for wild males and females separately. Models were then fit to the processed data and design matrix for each site, including the Hessian matrix to compute standard errors and confidence intervals for parameter estimates. We used a simplified model to estimate seasonal φ and population size (Eq. 1 ), and a group-specific model to estimate φ separately for each sex and source group (Eq. 2 ): $$\:\varvec{\varPhi\:}\left(1\right)\varvec{p}\left(1\right)\varvec{p}\varvec{e}\varvec{n}\varvec{t}\left(-1+\varvec{t}\varvec{i}\varvec{m}\varvec{e}\right){\varvec{N}}_{\varvec{s}\varvec{u}\varvec{p}\varvec{e}\varvec{r}}\varvec{}\left(-1+\varvec{s}\varvec{e}\varvec{x}\right)$$ 1 $$\:\varvec{\varPhi\:}(\varvec{s}\varvec{e}\varvec{x}\times\:\varvec{s}\varvec{o}\varvec{u}\varvec{r}\varvec{c}\varvec{e})\varvec{p}(\varvec{s}\varvec{e}\varvec{x}\times\:\varvec{s}\varvec{o}\varvec{u}\varvec{r}\varvec{c}\varvec{e})\varvec{p}\varvec{e}\varvec{n}\varvec{t}(-1+\varvec{t}\varvec{i}\varvec{m}\varvec{e}){\varvec{N}}_{\varvec{s}\varvec{u}\varvec{p}\varvec{e}\varvec{r}}\varvec{}(-1+\varvec{s}\varvec{e}\varvec{x})$$ 2 RMark produces a model summary text file which includes parameter estimates for φ, p, pent , and N super for each group. Due to small sample sizes at Rock Creek, a weighted average of φ was calculated across 2022 and 2021 using data from Henry et al. ( 2024 ). A simulation-based approach was used to estimate total population size at each site. 1,000 simulations of wild male and female population sizes were generated, drawing values from normal distributions centered on estimates of N super for each group, with standard deviations based on the model-derived standard errors (model: φ(1) p (1) pent (-1 + time) N super (-1 + sex)). In each simulation, total population size was calculated as the sum of simulated wild males, simulated wild females, and a fixed number of captive individuals. Mean total population size and 95% confidence intervals were then calculated from the simulated distributions. This approach allowed us to incorporate uncertainty in wild male and female estimates while ensuring a more robust estimate of total population size. Distance sampling Distance sampling analysis requires fitting a detection function to a set of detection data (counts of butterflies and their perpendicular distances from the transect line). The detection function describes the probability of detecting a butterfly at distance y from the transect and allows for estimation of the average detection probability within a defined survey width. Using the fitted detection function, butterfly density and abundance can be estimated from the number of detections, the length of all transects, the size of the surveyed area, and effective strip width (ESW). The ESW is the distance at which the number of butterflies missed equals the number detected by the observer. Detection probability declines with distance and approaches zero at distances greater than twice the ESW. Transect length and ESW are used to estimate density (butterflies per m²), which is then multiplied by area to estimate abundance at each site each week. Distance sampling data analysis was conducted using RStudio (Posit Team 2025 ) and the Distance package (Miller et al. 2019 ). We prepared distance data for each site and year combination and truncated distances at 15 m (halfway between transects). Because there were often too few sightings to estimate a robust detection function for each survey day (< 40 detections; Buckland et al. 2001 ), a global detection function was used for each site and year. At Rock Creek, detections from all three years were pooled to estimate a single global detection function for 2022 and 2023 due to insufficient sample sizes. Half-normal key detection functions were fit separately for each site and year without additional adjustment terms. Expansions were excluded due to limited sample sizes to avoid overfitting. Hazard rate key functions were omitted due to higher model complexity and likelihood for overfitting, and uniform key was excluded due to poor fit and biological improbability (see Buckland et al. 2001 for discussion of function selection). We estimated abundance on each survey date and generated 1000 bootstrap replicates. Because Oregon silverspot lifespan exceeds the weekly sampling interval, we used the following approach by Schultz and Dlugosch ( 1999 ) to estimate population size for each site and year (Eq. 3 ): $$\:\varvec{N}=\frac{1}{\varvec{l}}\sum\:_{\varvec{i}=1}^{\varvec{w}}{\varvec{n}}_{\varvec{i}{\varvec{t}}_{\varvec{i}}}\:\varvec{w}\varvec{h}\varvec{e}\varvec{r}\varvec{e}\:{\varvec{t}}_{\varvec{i}}=\frac{\left({\varvec{d}}_{\varvec{i}+1}-\:{\varvec{d}}_{\varvec{i}-1}\right)}{2}$$ 3 where l = average lifespan for Oregon silverspot at each site (Rock Creek = 19 days, Mt. Hebo = 8.9 days, Nestucca = 16.8 days), ni = Oregon silverspot abundance in survey i , ti = the time interval represented by survey i , di = Julian date of survey i , and w = the number of surveys. Results Mark-release-recapture Oregon silverspot flight periods (i.e., confirmed dates that butterflies were seen) at each site between 2022 and 2024 were as follows: Rock Creek (July 7-September 6, 2022; July 4-September 12, 2023; June 25-September 4, 2024), Mt. Hebo (July 26-September 19, 2022; July 25-September 22, 2023; August 2-September 13, 2024), and Nestucca (July 12-September 6, 2022; June 27-September 13, 2023; June 25-September 14, 2024). We marked a total of 119 butterflies at Rock Creek in 2022, 1,310 butterflies at Mt. Hebo in 2023, and 525 butterflies at Nestucca in 2024. We resighted 65% of marked butterflies at Rock Creek with 308 total resights, 58% of marked butterflies at Mt. Hebo with 1,434 total resights, and 60% of marked butterflies at Nestucca with 991 total resights. Sex ratios in wild populations were biased toward males across sites. Wild population size estimates from MRR were 11 (10–12) females and 28 (25–36) males at Rock Creek, 515 (488–547) females and 1616 (1558–1679) males at Mt. Hebo, and 31 (27–42) females and 61 (56–69) males at Nestucca. Captive-reared butterflies made up the majority of the population at Rock Creek and Nestucca, with 87 released at Rock Creek in 2022 (69%) and 451 released at Nestucca in 2024 (83%), while only 22 captive reared butterflies were released at Mt. Hebo in 2023 (1%). Including captive-reared butterflies, total population sizes based on MRR were estimated to be 126 (120–132) at Rock Creek in 2022, 2154 (2064–2246) at Mt. Hebo in 2023, and 543 (530–557) at Nestucca in 2024. Estimated apparent daily survival pooled across sexes and sources differed between sites, equating to average lifespans of around 37.2 (32.8–42.2, n = 119) days at Rock Creek, 8.9 (8.6–9.3, n = 1312) days at Mt. Hebo, and 16.8 (15.6–18.1, n = 456) days at Nestucca (Table I). Weighted lifespan at Rock Creek, based on combined 2021 and 2022 data, was 19.0 (18.9–19.1, n = 415) days. Across all sites and years, wild butterflies had higher survival rates than captive-reared butterflies (larva-released and pupa-released, adult-released omitted), and females had higher survival rates than males. Captive pupa-released butterflies had lower adult survival rates than larva-released butterflies. Table I Total butterflies marked and resighted by site, sex, and source Year Site Source Sex Total marked Total resighted Total resights Apparent daily survival Lifespan (days) 2022 Rock Creek Larva F 9 6 10 0.957 (0.955–0.959)* 22.9 (21.9–24.1)* M 7 2 15 0.926 (0.921–0.931)* 13.0 (12.2–13.9)* Pupa F 42 27 87 0.929 (0.928–0.929)* 13.5 (13.4–13.7)* M 29 23 112 0.893 (0.892–0.895)* 8.8 (8.7-9.0)* Wild F 9 4 16 0.962 (0.960–0.964)* 25.8 (24.5–27.1)* M 23 15 68 0.944 (0.943–0.945)* 17.4 (17.1–17.7)* 2023 Mt. Hebo Larva F 9 3 3 0.926 (0.924–0.929) 13.1 (12.6–13.5) M 13 4 9 0.852 (0.846–0.857) 6.2 (6.0-6.5) Wild F 312 178 362 0.969 (0.959–0.977) 31.8 (23.7–42.9) M 978 581 1060 0.882 (0.773–0.943) 8.0 (3.9–17.0) 2024 Nestucca Larva F 14 8 18 0.957 (0.954–0.959) 22.8 (21.4–24.2) M 15 9 45 0.956 (0.940–0.968) 22.5 (16.2–31.2) Pupa F 171 103 280 0.940 (0.938–0.942) 16.2 (15.6–16.8) M 182 102 301 0.925 (0.921–0.929) 12.8 (12.1–13.5) Adult + F 37 15 23 NA NA M 32 13 30 NA NA Wild F 25 22 75 0.970 (0.967–0.972) 32.5 (30.0-35.4) M 49 43 218 0.955 (0.949–0.961) 21.9 (19.2–25.0) *Weighted average between 2021 and 2022 values. See Henry et al. ( 2024 ) for 2021 Rock Creek MRR overview. + Captive-reared butterflies released as older adults excluded from analyses Distance sampling From 2022 to 2024, 1334 Oregon silverspots were detected on distance surveys at Mt. Hebo, 439 at Nestucca, and 137 at Rock Creek. Population size estimates ranged from 1132–2462 at Mt. Hebo, 175–511 at Nestucca, and 39–187 at Rock Creek. Detections peaked in 2023 at Mt. Hebo and in 2024 at Rock Creek and Nestucca, while distance-estimated population size peaked in 2023 at Mt. Hebo and Nestucca and in 2024 at Rock Creek (Fig. SXI). Weekly abundance estimates are shown in Fig. SIII. Index counts In total, 562 Oregon silverspots were recorded on index count surveys in 2022, 633 in 2023, and 107 in 2024 (Nestucca only). Mt. Hebo had the highest counts, with 453 in 2022 and 546 in 2023. Rock Creek had the lowest counts, with 50 in 2022 and 15 in 2023. At Nestucca, 59 butterflies were recorded in 2022, 72 in 2023, and 107 in 2024. Method comparison Distance sampling underestimated population size relative to MRR at Rock Creek (70% lower) and Nestucca (47% lower), whereas estimates were similar at Mt. Hebo and had overlapping confidence intervals (Fig. III). Index counts generally reflected directional trends in abundance estimated from distance sampling at Mt. Hebo and Nestucca (2022–2023) when confidence intervals did not overlap across consecutive years, while estimates at Rock Creek (2022–2023) and Nestucca (2023–2024) had greater uncertainty and did not show a clear trend. Fig. III Population size estimates from distance sampling, mark-release-recapture (MRR), and index counts, with corresponding captive release totals at each site and year Discussion The utility of index counts, distance sampling, and MRR for monitoring is largely based on conservation objectives. Simple count methods may be appropriate in some contexts, but there has been a lack of comparison of estimates produced from these methods in the same butterfly system. We found that distance sampling and MRR produced population size estimates of similar magnitude, with distance sampling aligning most closely with MRR when the survey interval closely matched butterfly lifespan, while index counts generally tracked directional trends in abundance but do not account for detectability or uncertainty. MRR also revealed captive-reared butterflies had lower apparent daily survival than wild individuals across all sites and years, and adult lifespan varied among populations, with individuals at some sites living several weeks on average. These long and variable lifespans complicate population size estimation from weekly sampling when survival is not explicitly modeled, particularly in augmented populations where captive-reared individuals may comprise the majority detections. Together, our results suggest that effective monitoring should incorporate detectability and survival to provide reliable estimates of population size, alongside a strategy for quantifying recruitment in augmented populations. Mark-release-recapture (MRR) MRR is generally considered the most reliable method for estimating butterfly population size, as it combines robust sampling protocols with rigorous statistical models (Williams et al. 2002 ; Lettink and Armstrong 2003 ), provided that sampling intensity is sufficiently high (Haddad et al. 2008 ). In our study, daily surveys minimized the likelihood of marked individuals emigrating before being resighted and resulted in high resight rates that were representative of the population. Because these key assumptions were well met, we used MRR as the reference for comparison with other estimates. Given that MRR is labor- and time-intensive, it is generally not used as a routine monitoring strategy (Haddad et al. 2008 ; Kral et al. 2018 ), and studies are typically conducted over periods of only one to a few years (Nowicki et al. 2005 ; Fred and Brommer 2009 ; Örvössy et al. 2013 ; Wang et al. 2022 ; Hinneberg et al. 2023 ). However, rare long-term MRR datasets have shown that butterfly populations can vary widely from year to year, with fluctuations driven by environmental conditions and population size in the previous season (Cabrera et al. 2025 ). This variability makes it challenging to interpret estimates from a single year of MRR in the context of multi-year trends, particularly if year-specific anomalies drove atypical population dynamics. For example, climatic variability has been shown to affect lifespan across years (Sielezniew et al. 2023 ), and historic high temperatures in 2023 at Mt. Hebo may have increased adult mortality (Ragab et al. 2025 ), which could be reflected in our estimates of adult daily survival. Even with reliable estimates for one flight period, it’s uncertain how well they represent broader population dynamics. At the same time, data are often limited for rare species, and conservation must proceed even in the absence of robust, long-term datasets. Estimates from each MRR study suggest that Oregon silverspots may live for several weeks, setting this species apart from shorter-lived butterflies that only live as adults for a few days on average (Celik 2012 ; Bubová et al. 2016 ; Franzén et al. 2024 ). Females had longer lifespans than males, which may reflect the time required for egg development after eclosion in Speyeria and related fritillaries (Sims 1984 ; Zimmermann et al. 2009 ). Lifespan varied across sites, and apparent daily survival was lowest at Mt. Hebo where higher elevation results in a shorter flight period (Casacci et al. 2015 ), and higher at Rock Creek and Nestucca where extended flight periods and the potential for female reproductive diapause (Henry et al. 2024 ) may contribute to longer lifespans. Captive-reared butterflies had shorter apparent lifespans than wild butterflies across all sites and years, and individuals released as pupae had shorter lifespans than those released as larvae (see also Henry et al. 2024 ). This may indicate lower fitness post-release (Lewis and Thomas 2001 ; Davis et al. 2020 ; Tenger-Trolander 2023 ), particularly if individuals are released without sufficient time to acclimatise to field conditions (Armstrong and Seddon 2008 ), and reduced fecundity if releases are misaligned with wild phenology (Henry et al. 2024 ). Captive-reared Oregon silverspots have been observed mating and ovipositing post-release, and recruitment has occurred at Nestucca (a formerly extirpated site) following reintroductions, but the degree of reproductive success is unknown. It’s possible that captive-reared and released Oregon silverspots have lower survival rates while their offspring (e.g. wild butterflies at Nestucca) have higher fitness and fecundity, similar to Chinook salmon ( Oncorhynchus tshawytscha ; Dayan et al. 2024 ), though further investigation is needed. Our MRR analysis, which combined POPAN and CJS models, provides a framework for estimating wild population size alongside demographic rates for captive-reared and wild individuals. To our knowledge, no previous studies have applied this joint approach to populations with both groups. Most studies either use POPAN models to estimate total population size (Haddad et al. 2008 ; Zimmermann et al. 2011 ; Franzén et al. 2024 ; Cabrera et al. 2025 ) or CJS models to estimate survival rates and detection probability, either for an entire population (Parile et al. 2021 ) or separately for captive and wild individuals (Henry et al. 2024 ). Previous studies have used MRR in populations with both captive-reared and wild individuals, but do not distinguish between the groups (Adamski and Ćmiel 2022). Combining approaches allows for reliable wild population size estimates in augmented populations by explicitly accounting for captive-reared butterflies. At Nestucca and Rock Creek, heavily skewed ratios of captive-reared to wild individuals indicate that most of the population consists of captive-reared individuals released that year, suggesting they also make up the majority of detections on distance and index surveys. Because these simpler methods typically do not distinguish between captive-reared and wild butterflies during monitoring, it is difficult to assess the contribution of augmentation on population growth. Distance sampling A key challenge in distance sampling is extrapolating daily or weekly abundance estimates to seasonal population size for butterflies with long lifespans. Counts or abundances may be summed across surveys when the sampling interval is greater than adult lifespan (Pollard and Yates 1993 ), but this approach overestimates population size if adults live long enough to be counted on multiple surveys. Adjusting population size using average adult lifespan (Schultz and Dlugosch 1999 ) provides a simple solution, although estimates may still align best when adult lifespan roughly matches the survey interval. For example, distance sampling estimates overlapped with MRR estimates at Mt. Hebo, where the average lifespan was 8.9 days, but were lower than MRR estimates at Nestucca and Rock Creek, where average lifespans were 16.8 and 19 days. This method has been used to estimate Fender’s blue population size over multiple years (Fitzpatrick 2015, unpublished) with an average lifespan of 9.5 days (Schultz 1995 ; Schultz and Dlugosh 1999), comparable to our estimates for Mt. Hebo. Approaches such as Insect Count Analyzer (INCA) similarly incorporate death rates and emergence times in population estimation (Longcore et al. 2003 ) and have also been used with at-risk butterflies (Fitzpatrick 2015, unpublished; Haddad et al. 2008 ). Alternatively, metrics such as peak single day abundance (PSDA) have been used as a proxy for population size for Taylor’s checkerspot butterfly in the absence of lifespan estimates (USFWS 2024 ). Provided that lifespan does not vary substantially among years and the population is sampled across the entire flight period, either of these approaches would likely be satisfactory for approximating population size of Oregon silverspot. Future population estimation might utilize an Integrated Population Model (IPM) as a more robust approach for combining abundance and demography data (Besbeas et al. 2002 ), but its application may still be limited by single-year datasets. Low densities and sparse detections required us to adapt our approach to estimating population size. In addition to pooling detections across sites and years, we pooled detections across all three years at Rock Creek to estimate population size in 2022 and 2023 due to insufficient sample sizes (< 40; Buckland et al. 2001 ). This approach assumes that potential differences in detection probability across years does not introduce significant bias in abundance estimates—a concept referred to as “pooling robustness” (Buckland et al. 2004 ; Rexstad et al. 2023 )—and allowed us to estimate population size at Rock Creek despite having too few observations to fit a site- and year- specific detection function. Pooling robustness may not hold if detection probability differed substantially from 2022 to 2024 at Rock Creek, but pooling across years was preferred over pooling across sites to better capture site-specific detectability patterns, given known spatial variation in detectability (Isaac et al. 2011 ). Distance sampling over multiple years at a site would allow for the use of a more robust global detection function or pooled functions across site-surveyor analogs, both of which have been used with Fender’s blue at Fern Ridge (Kelsey King, personal communication, 2025). For very sparse populations, distance sampling is generally less effective because sufficient detections are required to reliably estimate density (Buckland et al. 2001 ; Bart et al. 2004 ), and double-observer sampling has been investigated as an alternative that reduces the number of detections needed but requires more surveyors (Henry and Anderson 2016 ). Further investigation of global detection functions and their robustness would be valuable for improving monitoring of at-risk species with low population densities. Index counts Index counts are often used as proxies for population size, but are prone to bias if detection probability varies over space and time (Pollard and Yates 1993 ; Anderson 2001 ; Haddad et al. 2008 ; Harker and Shreeve 2008 ). We found that index counts broadly scaled to the relative size of each population (i.e., counts were lowest at the smallest population and highest at the largest population) and generally reflected distance sampling population trends when population growth or decline could be determined. Without accounting for uncertainty, however, the highest index count did not always correspond to the largest population size. This may indicate that variation in detectability was outweighed by differences in abundance (Isaac et al. 2011 ), such that index counts reliably tracked large fluctuations in population size but were less effective at estimating finer-scale population changes, where incorporating detectability improved estimates. This may also reflect the limitations of the current sampling scheme—survey routes extend around meadow margins and areas that are expected to have large numbers of butterflies. Changes in vegetation structure or nectar availability from year to year may affect distribution and residence time in natal patches (Luoto et al. 2001 ; Schultz et al. 2012 ), resulting in fluctuating detectability of adults over time (Pellet et al. 2012 ). However, our distance sampling data also show that the highest number of detections did not always correspond to the largest population size, suggesting that counts may not scale reliably with population size even in well-designed surveys. Developing an index count survey that systematically samples habitat may improve reliability relative to the current approach, but still lacks the inferential strength needed for conservation decision-making compared with alternative survey methods (Kral et al. 2018 ). Conservation implications Our results demonstrate that method choice directly influences the biological conclusions that can be drawn for conservation decision-making. Although monitoring resources are often limited, the additional effort required for distance sampling provides substantially more information on population size and detectability than commonly used index count strategies. Even short-term, targeted MRR studies produce valuable demographic data that can be leveraged to refine distance sampling estimates and inform monitoring design. Distance sampling could be further adapted to separately estimate wild population size in augmented populations if captive-reared and wild butterflies are distinguished during surveys. This could be achieved through visible markings on captive released individuals or by temporarily pausing releases to exclusively estimate wild population size and recruitment. As captive rearing and augmentation programs continue to grow, reliable monitoring will be essential for quantifying the contribution of these efforts to population growth and informing ongoing management strategies. Declarations Funding: This work was funded by U.S. Fish and Wildlife Service under Cooperative Agreement No. F22AC00345-00 Competing interests : The authors declare no competing interests. Author Contribution Conceptualization: I.B., E.H., R.V.B., C.S.; Data collection: I.B., E.H., R.V.B.; Data curation: I.B., E.H.; Analysis development: I.B., E.H., C.S.; Analysis implementation: I.B.; Expert review of results and code: E.H., C.S.; Funding acquisition and project administration: E.H., R.V.B., C.S.; Writing—original draft: I.B.; Writing—review and editing: I.B., E.H., R.V.B., C.S. Acknowledgement We thank our agency collaborators at U.S. Fish and Wildlife Service, U.S. Forest Service, and Oregon Parks and Recreation Department for making this work possible, including Samantha Derrenbacher, David Thompson, Michele Zwartjes, Kate Iaquinto, Khem So, Julia Johanos, DeAnna Williams, Iain Emmons, Halle Renn, Sarah Kaufman, Crystal Barnes, Micah Ashford, Aileen Macias, Teagan Miller, Chase Cessna, Emma Lundgren, Julia Izzo, Marie-Therese Offner, and Sophie Lyons. Thank you to the field technicians and volunteers who counted and marked thousands of butterflies, including Emma Dombrow, Bree Sheffield, Kate Glover, Torin Bevins, Brooke Fritzler, Jasper Cameron, Makazlynn Schulz, Shelline Nerup, Chloe Hendricks, Emily Kresin, Devin Simmers, Parrish Noce, Larry Hurst, Sierra Hagen, Kate Underwood, Océane Caporal, Kole Meinhart, John Lyssenko, Daniel Gonzalez, Brooke Stewart, Renay McInturf, Brittany White, and Bryant and Jamie Bainbridge. A special thanks to the teams at Oregon Zoo and Woodland Park Zoo—including Julia Low and Erin Sullivan—for their dedication to rearing Oregon silverspot butterflies. Finally, thank you to John Bishop and Seth Rudman at Washington State University for reviewing earlier drafts of this manuscript, and Diego Murillo and Alison Logan for their administrative support of this research. Data Availability Data and code will be available on Dryad upon acceptance References Adamski P, Cmiel A (2022) The long-term effect of over-supplementation on recovered populations: Why restraint is a virtue. Oryx 56(4):564–571. https://doi.org/10.1017/S0030605321000296 Anderson DR (2001) The need to get the basics right in wildlife field studies. Wildl Soc Bull 29(4):1294–1297. http://www.jstor.org/stable/3784156 Anton J, Rotger A, Igual J, Tavecchia G (2013) Estimating lizard population density: An empirical comparison between line-transect and capture-recapture methods. Wildl Res 40(7):552–560. https://doi.org/10.1071/WR13127 Armstrong DP, Seddon PJ (2008) Directions in reintroduction biology. Trends Ecol Evol 23(1):20–25. http://doi.org/10.1016/j.tree.2007.10.003 Bart J, Droege S, Geissler P, Peterjohn B, Ralph C (2004) Density estimation in wildlife surveys. Wildl Soc Bull 32(4):1242–1247. https://doi.org/10.2193/0091-7648(2004)032 [1242:DEIWS]2.0.CO;2 Belitz M, Monfils M, Cuthrell D, Monfils A (2019) Life history and ecology of the endangered Poweshiek skipperling Oarisma poweshiek in Michigan prairie fens. J Insect Conserv 23(3):635–649. https://doi.org/10.1007/s10841-019-00158-6 Besbeas P, Freeman SN, Morgan BJT, Catchpole EA (2002) Integrating mark-recapture-recovery and census data to estimate animal abundance and demographic parameters. Biometrics 58(3):540–547. https://doi.org/10.1111/j.0006-341X.2002.00540.x Bried JT, Pellet J (2012) Optimal design of butterfly occupancy surveys and testing if occupancy converts to abundance for sparse populations. J Insect Conserv 16(4):489–499. https://doi.org/10.1007/s10841-011-9435-2 Brown J, Boyce M (1998) Line transect sampling of Karner blue butterflies ( Lycaeides melissa samuelis ). Environ Ecol Stat 5(1):81–91. https://doi.org/10.1023/A:1009620105039 Bubová T, Kulma M, Vrabec V, Nowicki P (2016) Adult longevity and its relationship with conservation status in European butterflies. J Insect Conserv 20:1021–1032. https://doi.org/10.1007/s10841-016-9936-0 Buckland ST, Anderson DR, Burnham KP, Laake JL, Borchers DL, Thomas L (2001) Introduction to distance sampling: Estimating abundance of biological populations. Oxford University Press. https://doi.org/10.1093/oso/9780198506492.001.0001 Buckland ST, Anderson DR, Burnham KP, Laake JL, Borchers DL, Thomas L (2004) Advanced distance sampling: Estimating abundance of biological populations. Oxford University Press. https://doi.org/10.1093/oso/9780198507833.001.0001 Cabrera SRS, Belitz M, Emmel TC, Khazan ES, Standridge MJ, Rossetti K, Daniels JC (2025) Long-term population dynamics of an endangered butterfly are influenced by hurricane-mediated disturbance. Biol Conserv 302:110969. https://doi.org/10.1016/j.biocon.2025.110969 Casacci LP, Cerrato C, Barbero F, Bosso L, Ghidotti S, Paveto M, Pesce M, Plazio E, Panizza G, Balletto E, Viterbi R, Bonelli S (2015) Dispersal and connectivity effects at different altitudes in the Euphydryas aurinia complex. J Insect Conserv 19(2):265–277. https://doi.org/10.1007/s10841-014-9715-8 Celik T (2012) Adult demography, spatial distribution and movements of Zerynthia polyxena (Lepidoptera: Papilionidae) in a dense network of permanent habitats. Eur J Entomol 109(2):217–227. https://doi.org/10.14411/eje.2012.028 Chandler RB, Engebretsen K, Cherry MJ, Garrison EP, Miller KV (2018) Methods Ecol Evol 9(10):2115–2130. https://doi.org/10.1111/2041-210X.13068 . Estimating recruitment from capture-recapture data by modelling spatio-temporal variation in birth and age-specific survival rates Collins M, Runge MC, Rinehart K, Crone EE, Dillon J, Fitzpatrick G, Hicks T, Messinger W, Schultz CB, Brewer DC (2011) Monitoring design for Fender’s blue butterfly. Case Study from Structured Decision Making Workshop, January 24–28, 2011. National Conservation Training Center, Shepherdstown, West Virginia Collier N, Mackay D, Benkendorff K (2008) Is relative abundance a good indicator of population size? Evidence from fragmented populations of a specialist butterfly (Lepidoptera: Lycaenidae). Popul Ecol 50(1):17–23. https://doi.org/10.1007/s10144-007-0056-2 Corlatti L, Nelli L, Bertolini M, Zibordi F, Pedrotti L (2017) A comparison of four methods to estimate population size of Alpine marmot ( Marmota marmota ). Hystrix-Italian J Mammalogy 28(1):61–67. https://doi.org/10.4404/hystrix-28.1-11698 Cormack RM (1964) Estimates of survival from the sighting of marked animals. Biometrika 51(3/4):429–438. https://doi.org/10.2307/2334149 Crowther MS, Dargan JR, Madani G, Rus AI, Krockenberger MB, McArthur C, Moore BD, Lunney D, Mella VSA (2020) Comparison of three methods of estimating the population size of an arboreal mammal in a fragmented rural landscape. Wildl Res 48:105–114. https://doi.org/10.1071/WR19148 Daura-Jorge FG, Simões-Lopes PC (2017) Mark-recapture vs. line-transect abundance estimates of a coastal dolphin population: A case study of Tursiops truncatus from Laguna, southern Brazil. Latin Am J Aquat Mamm 11:133–143. https://doi.org/10.5597/lajam00222 Davis A, Smith F, Ballew A (2020) A poor substitute for the real thing: Captive-reared monarch butterflies are weaker, paler and have less elongated wings than wild migrants. Biol Lett 16(4). https://doi.org/10.1098/rsbl.2019.0922 Dayan D, Sard N, Johnson M, Fitzpatrick C, Couture R, O’Malley K (2024) A single generation in the wild increases fitness for descendants of hatchery-origin Chinook salmon ( Oncorhynchus tshawytscha ). Evol Appl 17(4). https://doi.org/10.1111/eva.13678 Esri Inc (2022) ArcGIS Pro (Version 3.0) Ewen JG, Armstrong DP, Parker KA, Seddon PJ (2012) Monitoring for reintroductions. Reintroduction Biology. John Wiley & Sons, Ltd. https://doi.org/10.1002/9781444355833 Flockhart D, Pichancourt J, Norris D, Martin T (2015) Unravelling the annual cycle in a migratory animal: Breeding-season habitat loss drives population declines of monarch butterflies. J Anim Ecol 84(1):155–165. https://doi.org/10.1111/1365-2656.12253 Fox R, Dennis E, Brown A, Curson J (2022) A revised red list of British butterflies. Insect Conserv Divers 15(5):485–495. https://doi.org/10.1111/icad.12582 Franzén M, Johansson H, Askling J, Kindvall O, Johansson V, Forsman A, Sunde J (2024) Long-distance movements, large population sizes and density-dependent dispersal in three threatened butterfly species. Insect Conserv Divers. https://doi.org/10.1111/icad.12766 Fred MS, Brommer JE (2009) Resources influence dispersal and population structure in an endangered butterfly. Insect Conserv Divers 2:11–18. https://doi.org/10.1111/j.1752-4598.2009.00059.x Gross K, Kalendra E, Hudgens B, Haddad N (2007) Robustness and uncertainty in estimates of butterfly abundance from transect counts. Popul Ecol 49(3):191–200. https://doi.org/10.1007/s10144-007-0034-8 Haddad N, Hudgens B, Damiani C, Gross K, Kuefler D, Pollock K (2008) Determining optimal population monitoring for rare butterflies. Conserv Biol 22(4):929–940. https://doi.org/10.1111/j.1523-1739.2008.00932.x Hamm C (2013) Estimating abundance of the federally endangered Mitchell’s satyr butterfly using hierarchical distance sampling. Insect Conserv Divers 6(5):619–626. https://doi.org/10.1111/icad.12017 Harding E, Crone E, Elderd B, Hoekstra J, McKerrow A, Perrine J, Regetz J, Rissler L, Stanley A, Walters E, NCEAS Habitat Conservation Plan Working Group (2001) The scientific foundations of habitat conservation plans: a quantitative assessment. Conserv Biol 15(2):488–500. https://doi.org/10.1046/j.1523-1739.2001.015002488.x Harker RJ, Shreeve TG (2008) How accurate are single site transect data for monitoring butterfly trends? Spatial and temporal issues identified in monitoring Lasiommata megera . J Insect Conserv 12(2):125–133. https://doi.org/10.1007/s10841-007-9068-7 Henry E, Anderson C (2016) Abundance estimates to inform butterfly management: Double-observer versus distance sampling. J Insect Conserv 20(3):505–514. https://doi.org/10.1007/s10841-016-9883-9 Henry E, Haddad N, Wilson J, Hughes P, Gardner B (2015) Point-count methods to monitor butterfly populations when traditional methods fail: A case study with Miami blue butterfly. J Insect Conserv 19(3):519–529. https://doi.org/10.1007/s10841-015-9773-6 Henry E, Sheffield B, Schultz C (2024) Experimental management and mark-release-recapture methods fill critical knowledge gaps for an at-risk butterfly. J Insect Conserv 28(5):951–958. https://doi.org/10.1007/s10841-024-00562-7 Hinneberg H, Kőrösi Á, Gottschalk T (2023) Providing evidence for the conservation of a rare forest butterfly: Results from a three-year capture-mark-recapture study. Basic Appl Ecol 73:27–39. https://doi.org/10.1016/j.baae.2023.09.001 Holmes T, Arnold R (2015) Generalized generation population size estimation of endangered insects via parsimonious, flexible integration of transect counts with mark-release-recapture data. Ann Entomol Soc Am 108(2):160–171. https://doi.org/10.1093/aesa/sau007 Isaac N, Cruickshanks K, Weddle A, Rowcliffe J, Brereton T, Dennis R, Shuker D, Thomas C (2011) Distance sampling and the challenge of monitoring butterfly populations. Methods Ecol Evol 2(6):585–594. https://doi.org/10.1111/j.2041-210X.2011.00109.x Jolly GM (1965) Explicit estimates from capture-recapture data with both death and immigration-stochastic model. Biometrika 52(1–2):225–248. https://doi.org/10.1093/biomet/52.1-2.225 Kacoliris FP, Berkunsky I, Williams JD (2009) Methods for assessing population size in sand dune lizards ( Liolaemus multimaculatus ). Herpetologica 65(2):219–226. https://doi.org/10.1655/08-036R1.1 Kéry M, Plattner M (2007) Species richness estimation and determinants of species detectability in butterfly monitoring programmes. Ecol Entomol 32(1):53–61. https://doi.org/10.1111/j.1365-2311.2006.00841.x Kral K, Harmon J, Limb R, Hovick T (2018) Improving our science: The evolution of butterfly sampling and surveying methods over time. J Insect Conserv 22(1):1–14. https://doi.org/10.1007/s10841-018-0046-z Kral-O’Brien K, Karasch B, Hovick T, Moranz R, Harmon J (2020) Morphological traits determine detectability bias in North American grassland butterflies. Ecosphere 11(12). https://doi.org/10.1002/ecs2.3304 Laake J (2025) RMark: R Code for Mark Analysis (Version 3.0.0) [Computer software]. CRAN Lettink M, Armstrong DP (2003) An introduction to using mark-recapture analysis for monitoring threatened species. Department Conserv Tech Ser 28A:5–32 Lewis OT, Thomas CD (2001) Adaptations to captivity in the butterfly Pieris brassicae (L.) and the implications for ex situ conservation. J Insect Conserv 5(1):55–63. https://doi.org/10.1023/A:1011348716934 Longcore T, Mattoni R, Zonneveld C, Bruggeman J (2003) Insect Count Analyzer: a tool to assess responses of butterflies to habitat restoration. Ecol Restor 21:60–61. https://doi.org/10.3368/er.21.4.311 Luoto M, Kuussaari M, Rita H, Salminen J, Bonsdorff T (2001) Determinants of distribution and abundance in the clouded apollo butterfly: a landscape ecological approach. Ecography 24(5):601–617. https://doi.org/10.1111/j.1600-0587.2001.tb00494.x MacKenzie DI, Royle JA (2005) Designing occupancy studies: General advice and allocating survey effort. J Appl Ecol 42(6):1105–1114. https://doi.org/10.1111/j.1365-2664.2005.01098.x McFarland KP, Lloyd JD, Hardy SP (2017) Density and habitat relationships of the endemic White Mountain Fritillary ( Boloria chariclea montinus ) (Lepidoptera: Nymphalidae). Insects 8(2). https://doi.org/10.3390/insects8020057 Miller DL, Rexstad E, Thomas L, Marshall L, Laake JL (2019) Distance Sampling in R. J Stat Softw 89(1):1–28. https://doi.org/10.18637/jss.v089.i01 Norman H, Säwenfalk D, Kindvall O, Franzén M, Askling J, Johansson V (2024) Novel grid-based population estimates correlate with actual population sizes of the marsh fritillary ( Euphydryas aurinia ), while transect and larvae counts are less reliable. Ecol Entomol 49(2):180–190. https://doi.org/10.1111/een.13292 Nowicki P, Witek M, Skórka P, Settele J, Woyciechowski M (2005) Population ecology of the endangered butterflies Maculinea teleius and M. nausithous and the implications for conservation. Popul Ecol 47:193–202. https://doi.org/10.1007/s10144-005-0222-3 Örvössy N, Korösi A, Batáry P, Vozár A, Peregovits L (2013) Potential metapopulation structure and the effects of habitat quality on population size of the endangered False Ringlet butterfly. J Insect Conserv 17(3):537–547. https://doi.org/10.1007/s10841-012-9538-4 Parile E, Piccini I, Bonelli S (2021) A demographic and ecological study of an Italian population of Polyommatus ripartii : The ESU Polyommatus exuberans . J Insect Conserv 25(5):783–796. https://doi.org/10.1007/s10841-021-00344-5 Patterson S, Harris J, Dinsmore S, Kinkead K (2023) Evaluating differences in density estimation for central Iowa butterflies using two methodologies. PeerJ 11. https://doi.org/10.7717/peerj.16165 Pellet J (2008) Seasonal variation in detectability of butterflies surveyed with Pollard walks. J Insect Conserv 12(2):155–162. https://doi.org/10.1007/s10841-007-9075-8 Pellet J, Bried J, Parietti D, Gander A, Heer P, Cherix D, Arlettaz R (2012) Monitoring butterfly abundance: Beyond Pollard walks. PLoS ONE 7(7). https://doi.org/10.1371/journal.pone.0041396 Pollard E (1977) A method for assessing changes in the abundance of butterflies. Biol Conserv 12(2):115–134. https://doi.org/10.1016/0006-3207(77)90065-9 Pollard E, Yates TJ (1993) Monitoring butterflies for ecology and conservation: The British butterfly monitoring scheme, 1st edn. Chapman & Hall Posit Team (2025) RStudio: Integrated Development Environment for R. Posit Software. PBC, Boston, MA. http://www.posit.co/ Powell A, Busby W, Kindscher K (2007) Status of the regal fritillary ( Speyeria idalia ) and effects of fire management on its abundance in northeastern Kansas, USA. J Insect Conserv 11(3):299–308. https://doi.org/10.1007/s10841-006-9045-6 Ragab SH, Tyshenko MG, Halmy MW (2025) Impact of climate change on the habitat range of monarch butterfly ( Danaus plexippus ). Sci Rep 15. https://doi.org/10.1038/s41598-025-17443-x Rexstad E, Buckland S, Marshall L, Borchers D (2023) Pooling robustness in distance sampling: Avoiding bias when there is unmodelled heterogeneity. Ecol Evol 13(1). https://doi.org/10.1002/ece3.9684 Scheele B, Legge S, Blanchard W, Garnett S, Geyle H, Gillespie G, Harrison P, Lindenmayer D, Lintermans M, Robinson N, Woinarski J (2019) Continental-scale assessment reveals inadequate monitoring for threatened vertebrates in a megadiverse country. Biol Conserv 235:273–278. https://doi.org/10.1016/j.biocon.2019.04.023 Schultz CB (1995) Status of the Fender's blue butterfly ( Icaricia icarioides fenderi ) in Lane County, Oregon: a year of declines. Report to the US Fish and Wildlife Service and the Oregon Natural Heritage Program, Portland, Oregon. 58 pp Schultz CB, Dlugosch KM (1999) Nectar and hostplant scarcity limit populations of an endangered Oregon butterfly. Oecologia 119(2):231–238. https://doi.org/10.1007/s004420050781 Schultz CB, Haddad NM, Henry EH, Crone EE (2019) Movement and Demography of At-Risk Butterflies: Building Blocks for Conservation. Ann Rev Entomol 64:167–184. https://doi.org/10.1146/annurev-ento-011118-112204 Schultz CB, Hammond P (2003) Using population viability analysis to develop recovery criteria for endangered insects: Case study of the Fender’s blue butterfly. Conserv Biol 17(5):1372–1385. https://doi.org/10.1046/j.1523-1739.2003.02141.x Schultz CB, Russell C, Wynn L (2008) Restoration, reintroduction, and captive propagation for at-risk butterflies: A review of British and American conservation efforts. Isreal J Ecol Evol 54(1):41–61. https://doi.org/10.1560/IJEE.54.1.41 Schultz CB, Franco AMA, Crone EE (2012) Response of butterflies to structural and resource boundaries. J Anim Ecol 81(3):724–734. https://doi.org/10.1111/j.1365-2656.2011.01947.x Schwarz CJ, Arnason AN (1996) A general methodology for the analysis of capture-recapture experiments in open populations. Biometrics 52(3):860–873. https://doi.org/10.2307/2533048 Seber GAF (1965) A note on the multiple-recapture census. Biometrika 52(1–2):249–260. https://doi.org/10.2307/2333827 Shuey J, Szymanski J (2012) Modified Pollard transects do not predict estimated daily population size for the secretive butterfly, Neonympha mitchellii mitchellii French. J Lepidopterists Soc 66(4):221–224. https://doi.org/10.18473/lepi.v66i4.a6 Sielezniew M, Bystrowski C, Deoniziak K, Dziekańska I, Kostro-Ambroziak A, Wołowicz A, Nowicki P (2023) Inter-annual variation in adult demography, but no sex bias in a large lowland population of the threatened Clouded Apollo Parnassius mnemosyne butterfly. Eur Zoological J 90(2):648–659. https://doi.org/10.1080/24750263.2023.2247436 Sims SR (1984) Reproductive diapause in Speyeria (Lepidoptera: Nymphalidae). J Res Lepidoptera 23:211–216. https://doi.org/10.5962/p.266759 Sims SR (2017) Speyeria (Lepidoptera: Nymphalidae) Conservation. Insects 8(2):45. https://doi.org/10.3390/insects8020045 Taron D, Ries L (2015) Butterfly monitoring for conservation. In Butterfly conservation in North America: Efforts to help save our charismatic microfauna (pp. 35–58). https://doi.org/10.1007/978-94-017-9852-5_3 Tenger-Trolander A (2023) Environmental and genetic effects of captivity—Are there lessons for monarch butterfly conservation? Curr Opin Insect Sci 59:101088. https://doi.org/10.1016/j.cois.2023.101088 Thomas L, Buckland S, Rexstad E, Laake J, Strindberg S, Hedley S, Bishop J, Marques T, Burnham K (2010) Distance software: Design and analysis of distance sampling surveys for estimating population size. J Appl Ecol 47(1):5–14. https://doi.org/10.1111/j.1365-2664.2009.01737.x Turlure C, Pe’er G, Baguette M, Schtickzelle N (2018) A simplified mark-release-recapture protocol to improve the cost effectiveness of repeated population size quantification. Methods Ecol Evol 9(3):645–656. https://doi.org/10.1111/2041-210X.12900 USFWS (1980) Federal Register. Vol. 45, No. 129, pp 44935–44939 USFWS (2001) Oregon silverspot ( Speyeria zerene hippolyta ) revised recovery plan. U.S. Fish and Wildlife Service, Portland, Oregon USFWS (2019) Karner blue butterfly ( Lycaeides melissa samuelis ) 5-year review summary and evaluation. U.S. Fish and Wildlife Service, Bloomington, Minnesota USFWS (2020a) Oregon silverspot butterfly ( Speyeria zerene hippolyta ) 5-year status review summary and evaluation. U.S. Fish and Wildlife Service, Newport, Oregon USFWS (2020b) Fender’s blue butterfly ( Icaricia icarioides fenderi ) species status assessment report. U.S. Fish and Wildlife Service, Portland, Oregon USFWS (2024) Taylor’s checkerspot butterfly ( Euphydryas editha taylori ) 5-year review summary and evaluation. U.S. Fish and Wildlife Service, Lacey, Washington Vrabec V, Bubová T, Kulma M, Krása A, Nowicki P (2019) How Euphydryas maturna survived extinction in the Czech Republic: Status of a relic population after intensive conservation management. J Insect Conserv 23(2):393–403. https://doi.org/10.1007/s10841-019-00145-x Wang Z, Li Y, Jain A, Pierce N (2022) Agent-based models reveal limits of mark-release-recapture estimates for the rare butterfly, Bhutanitis thaidina (Lepidoptera: Papilionidae). Insect Sci 29(2):550–566. https://doi.org/10.1111/1744-7917.12949 White GC, Burnham KP (1999) Program MARK: Survival estimation from populations of marked animals. Bird Study 46(sup1). https://doi.org/10.1080/00063659909477239 . S120-S139 Williams A, Alexander K (2023) Microhabitat requirements of the uncompahgre fritillary butterfly ( Boloria improba acrocnema ) and climate change implications. J Insect Conserv 27(6):971–986. https://doi.org/10.1007/s10841-023-00513-8 Williams BK, Nichols JD, Conroy MJ (2002) Analysis and management of animal populations: modeling, estimation, and decision making. Academic, San Diego, CA. https://pubs.usgs.gov/publication/5200256 Zaman K, Tenney C, Rush C, Hill R (2015) Population ecology of a California endemic: Speyeria adiaste clemencei . J Insect Conserv 19(4):753–763. https://doi.org/10.1007/s10841-015-9797-y Zimmermann K, Konvička M, Fric ZF, Čihaková V (2009) Demography of a common butterfly on humid grasslands: Argynnis aglaja (Lepidoptera: Nymphalidae) studied by mark-recapture. Pol J Ecol 57(4):715–727 Zimmermann K, Fric ZF, Jiskra P, Kopečková M, Vlašánek P, Zapletal M, Konvička M (2011) Mark-recapture on large spatial scale reveals long distance dispersal in the Marsh Fritillary, Euphydryas aurinia . Ecol Entomol 36(4):499–510. https://doi.org/10.1111/j.1365-2311.2011.01293.x Additional Declarations No competing interests reported. Supplementary Files BurJICOsupplement.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 15 Apr, 2026 Reviewers agreed at journal 13 Apr, 2026 Reviewers invited by journal 13 Apr, 2026 Editor assigned by journal 25 Mar, 2026 Submission checks completed at journal 25 Mar, 2026 First submitted to journal 24 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9216540","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":623881869,"identity":"98a58b69-3726-4662-b628-4ab55400220e","order_by":0,"name":"Izzy Bur","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2klEQVRIie3OMQrCMBiG4T9E4lLsGhd7hV8EUQRXr2EJ6OgBHKyLLoJrT1I6FgLNkgN0VArOdXMS2wyCS9RNMO8QMuThC4DL9YOx5iARgA/h6UvSjQR+MdUQzD4lHV9dOEnlaqAE42Q3hWB2sFsG2YITLceJLhsioK/1G0KivH4pcVis8oIkFPrxYm4nlOwMGcSC1WTzAWGUGYLcEAkBF5mdeIyOQr1Ersv2LbwrDz1pJ8FRnYtrOkF/LyhWet0L9tvISupa/Pn3+uKhfcNEq9fdtxsul8v1bz0AXKlBDYjKfK4AAAAASUVORK5CYII=","orcid":"","institution":"School of Biological Sciences, Washington State University","correspondingAuthor":true,"prefix":"","firstName":"Izzy","middleName":"","lastName":"Bur","suffix":""},{"id":623881870,"identity":"cab49d5b-49da-4c37-89bf-c4bb8289ff09","order_by":1,"name":"Erica Henry","email":"","orcid":"","institution":"Washington Department of Fish and Wildlife","correspondingAuthor":false,"prefix":"","firstName":"Erica","middleName":"","lastName":"Henry","suffix":""},{"id":623881871,"identity":"3e176ee0-4458-49cb-881b-6ecc3489b22a","order_by":2,"name":"Richard Van Buskirk","email":"","orcid":"","institution":"Department of Environmental Studies, Pacific University","correspondingAuthor":false,"prefix":"","firstName":"Richard","middleName":"Van","lastName":"Buskirk","suffix":""},{"id":623881872,"identity":"8071657f-9478-4d56-b8ea-1a5d0017a624","order_by":3,"name":"Cheryl Schultz","email":"","orcid":"","institution":"School of Biological Sciences, Washington State University","correspondingAuthor":false,"prefix":"","firstName":"Cheryl","middleName":"","lastName":"Schultz","suffix":""}],"badges":[],"createdAt":"2026-03-24 23:53:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9216540/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9216540/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107871279,"identity":"ef119ce4-3f3a-47ac-bc1f-9ed8fb7d0e0a","added_by":"auto","created_at":"2026-04-27 07:48:01","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":236873,"visible":true,"origin":"","legend":"\u003cp\u003eLocations of distance sampling transects, index count transects, and point counts at Nestucca\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9216540/v1/c78d5adab24298ae8835ec7b.jpeg"},{"id":107577570,"identity":"c01dc561-d601-4141-a986-acfbbb438dae","added_by":"auto","created_at":"2026-04-22 21:06:58","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1714272,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eDorsal (left) and ventral (right) marks on Oregon silverspot butterflies (Photos by \u003c/em\u003eOcéane\u003cem\u003eCaporal and Izzy Bur)\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9216540/v1/d520985780ab07130b48bdca.jpeg"},{"id":107706587,"identity":"d768a0ae-77ac-4eff-881f-cd50ca241384","added_by":"auto","created_at":"2026-04-24 09:18:25","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":109270,"visible":true,"origin":"","legend":"\u003cp\u003ePopulation size estimates from distance sampling, mark-release-recapture (MRR), and index counts, with corresponding captive release totals at each site and year\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-9216540/v1/6f3cb140822bb8d823b244b3.png"},{"id":107873026,"identity":"d9f356c7-54e7-42d3-8f21-4c816a51bd49","added_by":"auto","created_at":"2026-04-27 08:01:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2526466,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9216540/v1/a5a5541c-cddf-4b48-a086-6606b50c9b77.pdf"},{"id":107577568,"identity":"cb0f3a69-ac5d-43ee-b853-3183281703f6","added_by":"auto","created_at":"2026-04-22 21:06:58","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":526717,"visible":true,"origin":"","legend":"","description":"","filename":"BurJICOsupplement.docx","url":"https://assets-eu.researchsquare.com/files/rs-9216540/v1/33b4447bf5d8290763e5b75f.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Population monitoring for Oregon silverspot butterfly to support recovery efforts: a comparison of three methods","fulltext":[{"header":"Introduction","content":"\u003cp\u003eA common challenge in conservation is finding reliable ways to monitor populations. Estimates of population size are at the core of many conservation goals and objectives including providing a quantitative foundation for assessing population trends and extinction risk (Fox et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), identifying conservation priorities (Flockhart et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), planning effective management (\u0026Ouml;rv\u0026ouml;ssy et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), and evaluating the success of recovery efforts (Vrabec et al. \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Without reliable monitoring, the efficacy of conservation strategies remains largely unknown, potentially leading to ineffective or harmful management decisions or failure to detect population declines (Harding et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Scheele et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Despite the importance of monitoring, many at-risk species, particularly insects like butterflies, lack systematic monitoring programs and protocols (Henry et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Schultz et al. \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Even when programs exist, they may rely on methods that fail to provide the precision needed to guide conservation decision-making (Kral et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), such as evaluating the contribution of captive rearing programs. Because population size estimates are necessary for guiding the recovery of at-risk species, it is crucial that conservation professionals have reliable methods for monitoring populations long-term (Schultz and Hammond \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2003\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTransect counts or Pollard walks (Pollard \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e1977\u003c/span\u003e; Pollard and Yates \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e1993\u003c/span\u003e), are commonly used for monitoring butterfly populations because they are easy to implement, cost-effective, and non-invasive (Taron and Ries \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). This method involves regular counts of individuals along fixed transects, providing a population index, and is particularly valuable for long-term studies where consistent, standardized monitoring is needed. Several butterfly monitoring programs have used this method at large scales for tracking butterfly communities, including the United Kingdom Butterfly Monitoring Scheme (Pollard and Yates \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e1993\u003c/span\u003e). While they are useful for evaluating broad population changes over time, index counts have limitations. They provide relative indices of abundance rather than estimates of population size, since they do not account for detection probability (i.e., the probability of detecting an individual in a study area) or for variation in adult survival or lifespan, which can influence how many individuals are available for detection at a given time. Indices are prone to bias when detection rates vary across observers, environments, and species (Anderson \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; K\u0026eacute;ry and Plattner \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Pellet \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Isaac et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Kral-O\u0026rsquo;Brien et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and when transects are not representative or randomly placed (Harker and Shreeve \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Isaac et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). As a result, indices may only correlate with abundance under certain assumptions (Williams et al. \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Haddad et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), yet they continue to be widely used for monitoring, even when more robust population estimation methods are available (Kral et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMark-release-recapture (MRR) and distance sampling address these limitations by incorporating detection probability into population estimates (Williams et al. \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). MRR involves capturing, marking, and releasing individuals in a population and use recapture probabilities to estimate population size. This method also provides demographic information on survival and detection probability to offer insight into population dynamics. However, MRR is labor-intensive and logistically challenging, and the potential risks of damaging habitat and handling sensitive species limit its feasibility for long-term monitoring (Holmes and Arnold \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Turlure et al. \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In contrast, distance sampling estimates population density by modeling detection probabilities based on distances at which individuals are observed from a transect line or point (Buckland et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). This is advantageous because it allows estimation of abundance even when not all individuals are directly observed and enables distance sampling to combine the rigor of MRR with simpler data collection methods, making it effective for scalable population surveys (Kral et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). However, both methods rely on key assumptions\u0026mdash;including accurate distance estimation in distance sampling (Buckland et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Thomas et al. \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) and homogenous capture probability in MRR (Williams et al. \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2002\u003c/span\u003e)\u0026mdash;that can result in biased estimates if violated. Incorporating more rigorous monitoring methods may allow conservation managers to make more informed decisions, but in many cases limited knowledge of species biology and the lack of independent benchmarks make it difficult to evaluate their reliability.\u003c/p\u003e \u003cp\u003eBoth MRR and distance sampling are commonly used in butterfly studies, but direct comparisons of estimates generated from these two methods remain limited for butterflies, unlike other taxa including reptiles (Kacoliris et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Anton et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and mammals (Corlatti et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Daura-Jorge and Sim\u0026otilde;es-Lopes \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Crowther et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Distance sampling and MRR have been used in the same butterfly system across different years (Hamm \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) but lack data for simultaneous, within-year comparisons. Several studies have compared indices with MRR, with some finding that indices are correlated with MRR estimates (Collier et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Haddad et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Zaman et al. \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), whereas others found no correlation (Harker and Shreeve \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Shuey and Szymanski \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Norman et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), while others have found that integrating data from MRR into population models can improve estimates derived from simpler methodologies (Schultz and Dlugosch \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Gross et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Haddad et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Holmes and Arnold \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Comparisons of indices with distance sampling often emphasize the methodological benefits of distance sampling, particularly its ability to account for detection probability (Brown and Boyce \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1998\u003c/span\u003e; Bried and Pellet \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Patterson et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Fender\u0026rsquo;s blue butterfly (\u003cem\u003eIcaricia icarioides fenderi\u003c/em\u003e) was monitored for multiple years using both methods before switching to only distance sampling (Collins et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Other studies have found that Pollard walks correlate with relative abundance estimates from distance sampling and are more practical for implementation at large scales (Isaac et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Direct comparisons of population estimates generated from indices, distance sampling, and MRR within the same system have also not been explored, and the potential for using multiple methods simultaneously to improve long-term monitoring provides a unique research opportunity using a butterfly case study.\u003c/p\u003e \u003cp\u003eMany at-risk species have conservation programs that reintroduce or augment populations by releasing captive-reared individuals but lack comprehensive post-release monitoring to assess population size and vital rates necessary for evaluating the success of these strategies (Schultz et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Ewen et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). For example, Taylor\u0026rsquo;s checkerspot butterfly (\u003cem\u003eEuphydryas editha taylori\u003c/em\u003e) populations in Washington are augmented with captive-reared individuals and monitored using distance sampling methods (USFWS \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), but most individuals are not tracked after release, making it difficult to determine the contribution of captive-reared butterflies to population size estimates. Indices or distance sampling can document population trends over time, but without the ability to distinguish between captive-reared and wild individuals on surveys, they cannot quantify the direct impact of augmentation on recruitment or determine whether observed trends are driven by captive-released butterflies. In contrast, MRR can separately track individual butterflies and estimate population demography, but it requires frequent and robust data collection to reliably estimate recruitment (Chandler et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Given these trade-offs, conservation programs must balance feasibility with the need for robust methods that directly support specific conservation goals (Kral et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOregon silverspot butterfly (\u003cem\u003eArgynnis\u0026thinsp;=\u0026thinsp;Speyeria zerene hippolyta\u003c/em\u003e), listed as Threatened under the U. S. Endangered Species Act (USFWS \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e1980\u003c/span\u003e), highlights the need for improved monitoring methods. Historically, Oregon silverspot\u0026rsquo;s range extended from the coast of southern Washington to northern California, but development in the coastal zone, fire suppression, and subsequent natural succession and invasion of non-native grasses has resulted in the loss of coastal meadow habitat and extirpation of populations (Sims \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; USFWS \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Today, only five wild populations and two experimental populations remain in Oregon and California, all of which persist at low or very low population sizes. Index counts, which have been used as baseline annual monitoring for Oregon silverspot since 1990, indicate that populations are failing to recover despite annual releases of captive-reared individuals for augmentation since 2000 (USFWS \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e). The lack of data on population size, combined with the inability to distinguish between wild and captive-reared individuals in monitoring efforts, limits the capacity to evaluate and refine these conservation strategies to improve recovery outcomes.\u003c/p\u003e \u003cp\u003eTo address these gaps, our study aims to (1) estimate population size of Oregon silverspot butterflies using MRR and distance sampling, (2) use MRR as a baseline to cross-validate distance sampling estimates with current index count methods, and (3) explore demographic differences between captive-reared individuals released for augmentation and wild individuals. While MRR has been previously investigated in one Oregon silverspot population (Henry et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), distance sampling has not, despite its increasing use for at-risk butterflies (Hamm \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Belitz et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; USFWS \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; USFWS \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e; USFWS \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), including other fritillaries (Powell et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; McFarland et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Williams and Alexander \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and its potential for large-scale implementation. Our goal is to develop practical, robust methods for tracking populations of wild and captive-reared individuals over time to evaluate the success of conservation actions.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy system\u003c/h2\u003e \u003cp\u003eOregon silverspot butterflies are found in early successional and montane meadow complexes along the Oregon coast. Some sites are coastal terraces moderated by ocean temperatures, while other sites are higher-elevation montane meadows that freeze and receive snow in the winter. The butterfly\u0026rsquo;s host plant, early blue violet (\u003cem\u003eViola adunca\u003c/em\u003e), grows in open grasslands with low-growing vegetation, but ecological succession can reduce habitat quality and violet abundance. Adults require nectar plants and are commonly observed nectaring on goldenrod (So\u003cem\u003elidago\u003c/em\u003e spp.), aster (\u003cem\u003eAster\u003c/em\u003e spp.), thistle (\u003cem\u003eCirsium\u003c/em\u003e spp.), pearly everlasting (\u003cem\u003eAnaphalis margaritacea\u003c/em\u003e), and yarrow (\u003cem\u003eAchillea millefolium\u003c/em\u003e) (USFWS \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Nectar plant composition differs across sites and habitat patches.\u003c/p\u003e \u003cp\u003eOregon silverspot completes one life cycle each year, with the adult flight season occurring late June through September for approximately 10 weeks. Adults begin eclosing between late June and mid-July and continue through August or September. Emergence times typically differ between occupied sites, as montane sites can remain under snow into April. Males often emerge several weeks before females (USFWS \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2001\u003c/span\u003e), and females may undergo a period of reproductive diapause before becoming active later in the summer when oviposition peaks (Sims \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Females lay eggs directly on violets or surrounding vegetation; eggs hatch approximately one week after oviposition and first instar larvae enter diapause soon after emerging (Sims \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In the spring, larvae become active again coinciding with new violet growth and complete six instars before pupating and eclosing as adults (USFWS \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). To support conservation efforts, the smaller Oregon silverspot populations have been augmented since 2000 in most years through releasing captive-reared individuals, usually as pupae or as third or fourth instar larvae, but the effectiveness of this strategy is poorly understood (USFWS \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e). Gravid females are collected from wild populations to provide eggs for captive rearing programs at Woodland Park Zoo (Seattle, WA) and Oregon Zoo (Portland, OR).\u003c/p\u003e \u003cp\u003eWe surveyed three Oregon silverspot populations on the south-central Oregon coast: Nestucca Bay National Wildlife Refuge (Nestucca), Mt. Hebo, and Rock Creek. Nestucca is a restored site managed by U.S. Fish and Wildlife Service (USFWS) in Tillamook County, OR (45.1659, -123.9537). The site consists of one contiguous meadow that is ~\u0026thinsp;15 ha along with nearby hiking paths and roadways (Fig. I). Following restoration from former cow pasture, which began in 2011 in collaboration with the Institute of Applied Ecology, an experimental population of Oregon silverspot was reintroduced through yearly releases of captive-reared individuals that started in 2017. Since the population\u0026rsquo;s establishment, yearly index counts have ranged between 17\u0026ndash;107. Mt. Hebo is located in Tillamook County, OR (45.2148, -123.7565), and managed by U.S. Forest Service (USFS; Siuslaw National Forest). A montane meadow complex extends\u0026thinsp;~\u0026thinsp;2 km along the ridgeline near the summit, which is 970m in elevation. This complex consists of ~\u0026thinsp;12 meadows totaling 28 ha connected by a gravel roadway and collectively occupies an area of ~\u0026thinsp;332 ha (Fig. SI). Meadows are separated by a matrix of conifer forest dominated by Douglas fir. Mt. Hebo supports the largest remaining wild population of Oregon silverspot, with yearly index counts ranging between 453-2,033 since 2017. Rock Creek is a remnant salt-spray meadow system located on the south-central coast in Lane County, OR (44.1772, -124.1155). Instead of discrete meadows, Rock Creek is a complex of ~\u0026thinsp;12 ha of coastal terrace and sub-montane meadows spread over ~\u0026thinsp;42 ha of area (Fig. SII), divided into units managed by USFS (Siuslaw National Forest) and Oregon Parks and Recreation Department. Yearly index counts have ranged between 15\u0026ndash;160 since 2017. All sites typically receive annual releases of captive-reared butterflies for population augmentation, with release totals varying but ranging from several hundred to over 1,000 individuals released at different stages (larva, pupa, and adult).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eFig. I\u003c/b\u003e \u003cem\u003eLocations of distance sampling transects, index count transects, and point counts at Nestucca\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eField methods\u003c/h3\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eMark-release-recapture (MRR)\u003c/h2\u003e \u003cp\u003eOregon silverspot populations were surveyed using MRR methods at Rock Creek in 2022, Mt. Hebo in 2023, and Nestucca in 2024. Because of concerns about the potential impacts from handling or trampling habitat, we were only permitted to survey one site per year with MRR. During each MRR study, a team of observers visited the site daily over the entire flight period to capture, mark, and resight butterflies. Wild butterflies were marked upon capture, and captive-reared butterflies were marked after eclosion, prior to release into the wild. Captive-reared individuals were released into the field at three different stages. Third and fourth instar larvae were released into enclosures in May, pupae were released into separate enclosures approximately one week before eclosion, and adults were released directly into the field. Adults eclosing from all captive-reared stages were marked before release at the site. To mark butterflies, we used Gelly Roll 2.0 metallic gel pens on the dorsal side of the right forewing, and ultra fine-tip sharpies on the ventral side of both hindwings following protocols developed by Henry et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) for Oregon silverspot in 2021 (Fig. II). By marking butterflies on the dorsal side of the forewing, we were able to resight basking and nectaring individuals using binoculars rather than relying solely on captures for identification. To differentiate captive-reared from wild butterflies, we marked wild butterflies with dark blue gel pen, and captive-origin butterflies with silver. Enclosure or capture date, time, and location were recorded for all newly marked or resighted butterflies using the Avenza Maps app. Sex and source (captive larva-released, captive pupa-released, captive adult-released, wild) were tracked with each butterfly ID.\u003c/p\u003e \u003cp\u003eWe conducted daily surveys, beginning before the first Oregon silverspot was observed (wild or within enclosures) and continuing until after the last individual was recorded. Meadows at each site were surveyed for a set duration. In 2022 at Rock Creek, we allocated survey time based on staff availability and relative butterfly abundance in each meadow, with those supporting higher butterfly activity receiving approximately two to three times more survey effort than those with little to no activity (MacKenzie and Royle \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). In 2023, we developed a survey protocol to allocate time based on meadow area (ha), violet cover, butterfly density and available staff time (Methods SI). We used violet cover data generated by the U.S. Forest Service in a large-scale meadow mapping project conducted across Mt. Hebo in 2022 (Ashford et al. 2022, unpublished) to coarsely estimate violet cover across meadows. In 2024, we used this same protocol to generate meadow and road survey times at Nestucca.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eFig. II\u003c/b\u003e \u003cem\u003eDorsal (left) and ventral (right) marks on Oregon silverspot butterflies (Photos by\u003c/em\u003e Oc\u0026eacute;ane \u003cem\u003eCaporal and Izzy Bur)\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDistance sampling (dup: abstract ?)\u003c/h3\u003e\n\u003cp\u003eOregon silverspot populations were surveyed using distance sampling methods at Rock Creek, Mt. Hebo, and Nestucca from 2022 to 2024. Observers visited each site weekly throughout the flight period, walking established transects and recording all Oregon silverspots detected and the perpendicular distance of each from the transect. Distances were estimated to the nearest half meter. Survey transects were established in 2022 using ArcGIS Pro (Esri Inc. 2022) and delineated using a Trimble Geo 7x. Transects were randomly placed without bias toward starting location or habitat features, spaced 30 m apart following modified Pollard survey methods, and ran parallel to fully cover meadows. Transects were re-established each year with some additional transects added in 2023 and 2024 following habitat restoration or observation of butterflies in new areas (Table SI). Distance sampling surveys were conducted in the same areas as MRR each year to allow for direct comparison of methods.\u003c/p\u003e\n\u003ch3\u003eIndex counts\u003c/h3\u003e\n\u003cp\u003eIndex counts were conducted by USFWS at Rock Creek and Mt. Hebo from 2022 to 2023, and at Nestucca from 2022 to 2024. A modified Pollard walk was conducted along established transects at each site, where observers walked at a pace of 20m/min and recorded all butterflies within 15 m of the transect (Patterson 2023, unpublished). It is assumed observers can confirm observations of butterflies at distances up to 15 m. This method contrasts with a standard Pollard walk, where only butterflies within 5 m of the transect are recorded (Pollard \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e1977\u003c/span\u003e; Pollard and Yates \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e1993\u003c/span\u003e). Transects extended around meadows or along hiking paths, and at Nestucca, point counts were also conducted from fixed vantage points to supplement transect counts (Fig. I). Surveys were conducted weekly over the duration of the flight period, and weeks that were missed (due to staffing, weather, logistical challenges, etc.) were interpolated from the previous and following week\u0026rsquo;s counts. Weekly indices were summed across weeks to calculate a seasonal index.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003eMark-release-recapture (MRR)\u003c/h2\u003e \u003cp\u003eMRR analyses were conducted using RStudio (Posit Team \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) and the RMark package (Laake \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). RMark is an interface for Program MARK (White and Burnham \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) that allows for the use of MARK functions in R. We developed an approach combining a POPAN model (Schwarz and Arnason \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e1996\u003c/span\u003e), which is an extension of a Jolly-Seber model (Jolly \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e1965\u003c/span\u003e; Seber \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e1965\u003c/span\u003e), and a Cormack-Jolly-Seber (CJS; Cormack \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1964\u003c/span\u003e) model. Both POPAN and CJS are open population models that allow individuals to enter or leave the population through births, deaths, immigration, or emigration. CJS estimates two parameters: φ (apparent daily survival, the probability of a butterfly surviving to the next day given that it\u0026rsquo;s still present in the study area) and \u003cem\u003ep\u003c/em\u003e (detection probability, the probability of recapturing a butterfly given that it is alive and present in the study area). Survival is \u0026ldquo;apparent\u0026rdquo;, because we cannot differentiate between individuals leaving a population through death or emigration. POPAN estimates φ and \u003cem\u003ep\u003c/em\u003e, along with two additional parameters: \u003cem\u003epent\u003c/em\u003e (recruitment, the probability that individuals enter the population at each time step), and \u003cem\u003eN\u003c/em\u003e\u003csub\u003e\u003cem\u003esuper\u003c/em\u003e\u003c/sub\u003e (population size). Since \u003cem\u003epent\u003c/em\u003e and \u003cem\u003eN\u003c/em\u003e\u003csub\u003e\u003cem\u003esuper\u003c/em\u003e\u003c/sub\u003e are already known for captive-reared butterflies (i.e., release dates and totals released on each date), we used a CJS model to estimate φ and \u003cem\u003ep\u003c/em\u003e for these groups, and a POPAN model to estimate all four parameters for wild butterflies. We fixed \u003cem\u003epent\u003c/em\u003e and \u003cem\u003eN\u003c/em\u003e\u003csub\u003e\u003cem\u003esuper\u003c/em\u003e\u003c/sub\u003e for captive groups, then estimated φ and \u003cem\u003ep\u003c/em\u003e for each sex and source combination and \u003cem\u003epent\u003c/em\u003e and \u003cem\u003eN\u003c/em\u003e for wild males and females. Captive-reared butterflies that were retained for breeding or egg-laying before being released as adults were excluded from apparent survival estimation.\u003c/p\u003e \u003cp\u003eCapture histories were first created from the MRR data that denote whether each butterfly was captured or resighted during each sampling occasion. The data were then processed using a POPAN model and grouped by sex and source (captive larva-released, captive pupa-released, or wild). We fixed \u003cem\u003epent\u003c/em\u003e and \u003cem\u003eN\u003c/em\u003e\u003csub\u003e\u003cem\u003esuper\u003c/em\u003e\u003c/sub\u003e for captive butterfly groups using the total number of butterflies released on each date, and removed the intercept (-1) to only produce estimates for wild butterflies. Sex and source were included in φ and \u003cem\u003ep\u003c/em\u003e formulas to compare survival and detection probability estimates between groups. We included time in \u003cem\u003epent\u003c/em\u003e to account for flight period phenology, and sex in \u003cem\u003eN\u003c/em\u003e\u003csub\u003e\u003cem\u003esuper\u003c/em\u003e\u003c/sub\u003e to estimate population size for wild males and females separately. Models were then fit to the processed data and design matrix for each site, including the Hessian matrix to compute standard errors and confidence intervals for parameter estimates. We used a simplified model to estimate seasonal φ and population size (Eq.\u0026nbsp;\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), and a group-specific model to estimate φ separately for each sex and source group (Eq.\u0026nbsp;\u003cspan refid=\"Equ2\" class=\"InternalRef\"\u003e2\u003c/span\u003e):\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:\\varvec{\\varPhi\\:}\\left(1\\right)\\varvec{p}\\left(1\\right)\\varvec{p}\\varvec{e}\\varvec{n}\\varvec{t}\\left(-1+\\varvec{t}\\varvec{i}\\varvec{m}\\varvec{e}\\right){\\varvec{N}}_{\\varvec{s}\\varvec{u}\\varvec{p}\\varvec{e}\\varvec{r}}\\varvec{}\\left(-1+\\varvec{s}\\varvec{e}\\varvec{x}\\right)$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:\\varvec{\\varPhi\\:}(\\varvec{s}\\varvec{e}\\varvec{x}\\times\\:\\varvec{s}\\varvec{o}\\varvec{u}\\varvec{r}\\varvec{c}\\varvec{e})\\varvec{p}(\\varvec{s}\\varvec{e}\\varvec{x}\\times\\:\\varvec{s}\\varvec{o}\\varvec{u}\\varvec{r}\\varvec{c}\\varvec{e})\\varvec{p}\\varvec{e}\\varvec{n}\\varvec{t}(-1+\\varvec{t}\\varvec{i}\\varvec{m}\\varvec{e}){\\varvec{N}}_{\\varvec{s}\\varvec{u}\\varvec{p}\\varvec{e}\\varvec{r}}\\varvec{}(-1+\\varvec{s}\\varvec{e}\\varvec{x})$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eRMark produces a model summary text file which includes parameter estimates for φ, \u003cem\u003ep, pent\u003c/em\u003e, and \u003cem\u003eN\u003c/em\u003e\u003csub\u003e\u003cem\u003esuper\u003c/em\u003e\u003c/sub\u003e for each group. Due to small sample sizes at Rock Creek, a weighted average of φ was calculated across 2022 and 2021 using data from Henry et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA simulation-based approach was used to estimate total population size at each site. 1,000 simulations of wild male and female population sizes were generated, drawing values from normal distributions centered on estimates of N\u003csub\u003esuper\u003c/sub\u003e for each group, with standard deviations based on the model-derived standard errors (model: φ(1)\u003cem\u003ep\u003c/em\u003e(1)\u003cem\u003epent\u003c/em\u003e(-1\u0026thinsp;+\u0026thinsp;time)\u003cem\u003eN\u003c/em\u003e\u003csub\u003e\u003cem\u003esuper\u003c/em\u003e\u003c/sub\u003e(-1\u0026thinsp;+\u0026thinsp;sex)). In each simulation, total population size was calculated as the sum of simulated wild males, simulated wild females, and a fixed number of captive individuals. Mean total population size and 95% confidence intervals were then calculated from the simulated distributions. This approach allowed us to incorporate uncertainty in wild male and female estimates while ensuring a more robust estimate of total population size.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eDistance sampling\u003c/h3\u003e\n\u003cp\u003eDistance sampling analysis requires fitting a detection function to a set of detection data (counts of butterflies and their perpendicular distances from the transect line). The detection function describes the probability of detecting a butterfly at distance \u003cem\u003ey\u003c/em\u003e from the transect and allows for estimation of the average detection probability within a defined survey width. Using the fitted detection function, butterfly density and abundance can be estimated from the number of detections, the length of all transects, the size of the surveyed area, and effective strip width (ESW). The ESW is the distance at which the number of butterflies missed equals the number detected by the observer. Detection probability declines with distance and approaches zero at distances greater than twice the ESW. Transect length and ESW are used to estimate density (butterflies per m\u0026sup2;), which is then multiplied by area to estimate abundance at each site each week.\u003c/p\u003e \u003cp\u003eDistance sampling data analysis was conducted using RStudio (Posit Team \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) and the Distance package (Miller et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). We prepared distance data for each site and year combination and truncated distances at 15 m (halfway between transects). Because there were often too few sightings to estimate a robust detection function for each survey day (\u0026lt;\u0026thinsp;40 detections; Buckland et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2001\u003c/span\u003e), a global detection function was used for each site and year. At Rock Creek, detections from all three years were pooled to estimate a single global detection function for 2022 and 2023 due to insufficient sample sizes. Half-normal key detection functions were fit separately for each site and year without additional adjustment terms. Expansions were excluded due to limited sample sizes to avoid overfitting. Hazard rate key functions were omitted due to higher model complexity and likelihood for overfitting, and uniform key was excluded due to poor fit and biological improbability (see Buckland et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2001\u003c/span\u003e for discussion of function selection). We estimated abundance on each survey date and generated 1000 bootstrap replicates. Because Oregon silverspot lifespan exceeds the weekly sampling interval, we used the following approach by Schultz and Dlugosch (\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) to estimate population size for each site and year (Eq.\u0026nbsp;\u003cspan refid=\"Equ3\" class=\"InternalRef\"\u003e3\u003c/span\u003e):\u003cdiv id=\"Equ3\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ3\" name=\"EquationSource\"\u003e\n$$\\:\\varvec{N}=\\frac{1}{\\varvec{l}}\\sum\\:_{\\varvec{i}=1}^{\\varvec{w}}{\\varvec{n}}_{\\varvec{i}{\\varvec{t}}_{\\varvec{i}}}\\:\\varvec{w}\\varvec{h}\\varvec{e}\\varvec{r}\\varvec{e}\\:{\\varvec{t}}_{\\varvec{i}}=\\frac{\\left({\\varvec{d}}_{\\varvec{i}+1}-\\:{\\varvec{d}}_{\\varvec{i}-1}\\right)}{2}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e3\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cem\u003el\u003c/em\u003e\u0026thinsp;=\u0026thinsp;average lifespan for Oregon silverspot at each site (Rock Creek\u0026thinsp;=\u0026thinsp;19 days, Mt. Hebo\u0026thinsp;=\u0026thinsp;8.9 days, Nestucca\u0026thinsp;=\u0026thinsp;16.8 days), \u003cem\u003eni\u003c/em\u003e\u0026thinsp;=\u0026thinsp;Oregon silverspot abundance in survey \u003cem\u003ei\u003c/em\u003e, \u003cem\u003eti\u003c/em\u003e\u0026thinsp;=\u0026thinsp;the time interval represented by survey \u003cem\u003ei\u003c/em\u003e, di\u0026thinsp;=\u0026thinsp;Julian date of survey \u003cem\u003ei\u003c/em\u003e, and \u003cem\u003ew\u003c/em\u003e\u0026thinsp;=\u0026thinsp;the number of surveys.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eMark-release-recapture\u003c/h2\u003e \u003cp\u003eOregon silverspot flight periods (i.e., confirmed dates that butterflies were seen) at each site between 2022 and 2024 were as follows: Rock Creek (July 7-September 6, 2022; July 4-September 12, 2023; June 25-September 4, 2024), Mt. Hebo (July 26-September 19, 2022; July 25-September 22, 2023; August 2-September 13, 2024), and Nestucca (July 12-September 6, 2022; June 27-September 13, 2023; June 25-September 14, 2024). We marked a total of 119 butterflies at Rock Creek in 2022, 1,310 butterflies at Mt. Hebo in 2023, and 525 butterflies at Nestucca in 2024. We resighted 65% of marked butterflies at Rock Creek with 308 total resights, 58% of marked butterflies at Mt. Hebo with 1,434 total resights, and 60% of marked butterflies at Nestucca with 991 total resights. Sex ratios in wild populations were biased toward males across sites. Wild population size estimates from MRR were 11 (10\u0026ndash;12) females and 28 (25\u0026ndash;36) males at Rock Creek, 515 (488\u0026ndash;547) females and 1616 (1558\u0026ndash;1679) males at Mt. Hebo, and 31 (27\u0026ndash;42) females and 61 (56\u0026ndash;69) males at Nestucca. Captive-reared butterflies made up the majority of the population at Rock Creek and Nestucca, with 87 released at Rock Creek in 2022 (69%) and 451 released at Nestucca in 2024 (83%), while only 22 captive reared butterflies were released at Mt. Hebo in 2023 (1%). Including captive-reared butterflies, total population sizes based on MRR were estimated to be 126 (120\u0026ndash;132) at Rock Creek in 2022, 2154 (2064\u0026ndash;2246) at Mt. Hebo in 2023, and 543 (530\u0026ndash;557) at Nestucca in 2024.\u003c/p\u003e \u003cp\u003eEstimated apparent daily survival pooled across sexes and sources differed between sites, equating to average lifespans of around 37.2 (32.8\u0026ndash;42.2, n\u0026thinsp;=\u0026thinsp;119) days at Rock Creek, 8.9 (8.6\u0026ndash;9.3, n\u0026thinsp;=\u0026thinsp;1312) days at Mt. Hebo, and 16.8 (15.6\u0026ndash;18.1, n\u0026thinsp;=\u0026thinsp;456) days at Nestucca (Table I). Weighted lifespan at Rock Creek, based on combined 2021 and 2022 data, was 19.0 (18.9\u0026ndash;19.1, n\u0026thinsp;=\u0026thinsp;415) days. Across all sites and years, wild butterflies had higher survival rates than captive-reared butterflies (larva-released and pupa-released, adult-released omitted), and females had higher survival rates than males. Captive pupa-released butterflies had lower adult survival rates than larva-released butterflies.\u003c/p\u003e \u003cp\u003e \u003cb\u003eTable I\u003c/b\u003e \u003cem\u003eTotal butterflies marked and resighted by site, sex, and source\u003c/em\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSite\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSource\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal marked\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal resighted\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTotal resights\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eApparent daily survival\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLifespan (days)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eRock Creek\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLarva\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.957 (0.955\u0026ndash;0.959)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e22.9 (21.9\u0026ndash;24.1)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.926 (0.921\u0026ndash;0.931)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e13.0 (12.2\u0026ndash;13.9)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePupa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.929 (0.928\u0026ndash;0.929)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e13.5 (13.4\u0026ndash;13.7)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.893 (0.892\u0026ndash;0.895)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8.8 (8.7-9.0)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWild\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.962 (0.960\u0026ndash;0.964)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e25.8 (24.5\u0026ndash;27.1)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.944 (0.943\u0026ndash;0.945)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e17.4 (17.1\u0026ndash;17.7)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eMt. Hebo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLarva\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.926 (0.924\u0026ndash;0.929)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e13.1 (12.6\u0026ndash;13.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.852 (0.846\u0026ndash;0.857)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.2 (6.0-6.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWild\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.969 (0.959\u0026ndash;0.977)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e31.8 (23.7\u0026ndash;42.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e978\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e581\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.882 (0.773\u0026ndash;0.943)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8.0 (3.9\u0026ndash;17.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003e2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eNestucca\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLarva\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.957 (0.954\u0026ndash;0.959)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e22.8 (21.4\u0026ndash;24.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.956 (0.940\u0026ndash;0.968)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e22.5 (16.2\u0026ndash;31.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePupa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.940 (0.938\u0026ndash;0.942)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e16.2 (15.6\u0026ndash;16.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e182\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.925 (0.921\u0026ndash;0.929)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e12.8 (12.1\u0026ndash;13.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAdult\u003csup\u003e+\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWild\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.970 (0.967\u0026ndash;0.972)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e32.5 (30.0-35.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.955 (0.949\u0026ndash;0.961)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e21.9 (19.2\u0026ndash;25.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e*Weighted average between 2021 and 2022 values. See Henry et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) for 2021 Rock Creek MRR overview.\u003c/p\u003e \u003cp\u003e \u003csup\u003e+\u003c/sup\u003eCaptive-reared butterflies released as older adults excluded from analyses\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eDistance sampling\u003c/h2\u003e \u003cp\u003eFrom 2022 to 2024, 1334 Oregon silverspots were detected on distance surveys at Mt. Hebo, 439 at Nestucca, and 137 at Rock Creek. Population size estimates ranged from 1132\u0026ndash;2462 at Mt. Hebo, 175\u0026ndash;511 at Nestucca, and 39\u0026ndash;187 at Rock Creek. Detections peaked in 2023 at Mt. Hebo and in 2024 at Rock Creek and Nestucca, while distance-estimated population size peaked in 2023 at Mt. Hebo and Nestucca and in 2024 at Rock Creek (Fig. SXI). Weekly abundance estimates are shown in Fig. SIII.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eIndex counts\u003c/h2\u003e \u003cp\u003eIn total, 562 Oregon silverspots were recorded on index count surveys in 2022, 633 in 2023, and 107 in 2024 (Nestucca only). Mt. Hebo had the highest counts, with 453 in 2022 and 546 in 2023. Rock Creek had the lowest counts, with 50 in 2022 and 15 in 2023. At Nestucca, 59 butterflies were recorded in 2022, 72 in 2023, and 107 in 2024.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eMethod comparison\u003c/h2\u003e \u003cp\u003eDistance sampling underestimated population size relative to MRR at Rock Creek (70% lower) and Nestucca (47% lower), whereas estimates were similar at Mt. Hebo and had overlapping confidence intervals (Fig. III). Index counts generally reflected directional trends in abundance estimated from distance sampling at Mt. Hebo and Nestucca (2022\u0026ndash;2023) when confidence intervals did not overlap across consecutive years, while estimates at Rock Creek (2022\u0026ndash;2023) and Nestucca (2023\u0026ndash;2024) had greater uncertainty and did not show a clear trend.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eFig. III\u003c/b\u003e \u003cem\u003ePopulation size estimates from distance sampling, mark-release-recapture (MRR), and index counts, with corresponding captive release totals at each site and year\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe utility of index counts, distance sampling, and MRR for monitoring is largely based on conservation objectives. Simple count methods may be appropriate in some contexts, but there has been a lack of comparison of estimates produced from these methods in the same butterfly system. We found that distance sampling and MRR produced population size estimates of similar magnitude, with distance sampling aligning most closely with MRR when the survey interval closely matched butterfly lifespan, while index counts generally tracked directional trends in abundance but do not account for detectability or uncertainty. MRR also revealed captive-reared butterflies had lower apparent daily survival than wild individuals across all sites and years, and adult lifespan varied among populations, with individuals at some sites living several weeks on average. These long and variable lifespans complicate population size estimation from weekly sampling when survival is not explicitly modeled, particularly in augmented populations where captive-reared individuals may comprise the majority detections. Together, our results suggest that effective monitoring should incorporate detectability and survival to provide reliable estimates of population size, alongside a strategy for quantifying recruitment in augmented populations.\u003c/p\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eMark-release-recapture (MRR)\u003c/h2\u003e \u003cp\u003eMRR is generally considered the most reliable method for estimating butterfly population size, as it combines robust sampling protocols with rigorous statistical models (Williams et al. \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Lettink and Armstrong \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2003\u003c/span\u003e), provided that sampling intensity is sufficiently high (Haddad et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). In our study, daily surveys minimized the likelihood of marked individuals emigrating before being resighted and resulted in high resight rates that were representative of the population. Because these key assumptions were well met, we used MRR as the reference for comparison with other estimates. Given that MRR is labor- and time-intensive, it is generally not used as a routine monitoring strategy (Haddad et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Kral et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), and studies are typically conducted over periods of only one to a few years (Nowicki et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Fred and Brommer \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; \u0026Ouml;rv\u0026ouml;ssy et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Hinneberg et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, rare long-term MRR datasets have shown that butterfly populations can vary widely from year to year, with fluctuations driven by environmental conditions and population size in the previous season (Cabrera et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). This variability makes it challenging to interpret estimates from a single year of MRR in the context of multi-year trends, particularly if year-specific anomalies drove atypical population dynamics. For example, climatic variability has been shown to affect lifespan across years (Sielezniew et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and historic high temperatures in 2023 at Mt. Hebo may have increased adult mortality (Ragab et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), which could be reflected in our estimates of adult daily survival. Even with reliable estimates for one flight period, it\u0026rsquo;s uncertain how well they represent broader population dynamics. At the same time, data are often limited for rare species, and conservation must proceed even in the absence of robust, long-term datasets.\u003c/p\u003e \u003cp\u003eEstimates from each MRR study suggest that Oregon silverspots may live for several weeks, setting this species apart from shorter-lived butterflies that only live as adults for a few days on average (Celik \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Bubov\u0026aacute; et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Franz\u0026eacute;n et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Females had longer lifespans than males, which may reflect the time required for egg development after eclosion in \u003cem\u003eSpeyeria\u003c/em\u003e and related fritillaries (Sims \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e1984\u003c/span\u003e; Zimmermann et al. \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Lifespan varied across sites, and apparent daily survival was lowest at Mt. Hebo where higher elevation results in a shorter flight period (Casacci et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), and higher at Rock Creek and Nestucca where extended flight periods and the potential for female reproductive diapause (Henry et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) may contribute to longer lifespans. Captive-reared butterflies had shorter apparent lifespans than wild butterflies across all sites and years, and individuals released as pupae had shorter lifespans than those released as larvae (see also Henry et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This may indicate lower fitness post-release (Lewis and Thomas \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Davis et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Tenger-Trolander \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), particularly if individuals are released without sufficient time to acclimatise to field conditions (Armstrong and Seddon \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), and reduced fecundity if releases are misaligned with wild phenology (Henry et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Captive-reared Oregon silverspots have been observed mating and ovipositing post-release, and recruitment has occurred at Nestucca (a formerly extirpated site) following reintroductions, but the degree of reproductive success is unknown. It\u0026rsquo;s possible that captive-reared and released Oregon silverspots have lower survival rates while their offspring (e.g. \u003cem\u003ewild\u003c/em\u003e butterflies at Nestucca) have higher fitness and fecundity, similar to Chinook salmon (\u003cem\u003eOncorhynchus tshawytscha\u003c/em\u003e; Dayan et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), though further investigation is needed.\u003c/p\u003e \u003cp\u003eOur MRR analysis, which combined POPAN and CJS models, provides a framework for estimating wild population size alongside demographic rates for captive-reared and wild individuals. To our knowledge, no previous studies have applied this joint approach to populations with both groups. Most studies either use POPAN models to estimate total population size (Haddad et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Zimmermann et al. \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Franz\u0026eacute;n et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Cabrera et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) or CJS models to estimate survival rates and detection probability, either for an entire population (Parile et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) or separately for captive and wild individuals (Henry et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Previous studies have used MRR in populations with both captive-reared and wild individuals, but do not distinguish between the groups (Adamski and Ćmiel 2022). Combining approaches allows for reliable wild population size estimates in augmented populations by explicitly accounting for captive-reared butterflies. At Nestucca and Rock Creek, heavily skewed ratios of captive-reared to wild individuals indicate that most of the population consists of captive-reared individuals released that year, suggesting they also make up the majority of detections on distance and index surveys. Because these simpler methods typically do not distinguish between captive-reared and wild butterflies during monitoring, it is difficult to assess the contribution of augmentation on population growth.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eDistance sampling\u003c/h2\u003e \u003cp\u003eA key challenge in distance sampling is extrapolating daily or weekly abundance estimates to seasonal population size for butterflies with long lifespans. Counts or abundances may be summed across surveys when the sampling interval is greater than adult lifespan (Pollard and Yates \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e1993\u003c/span\u003e), but this approach overestimates population size if adults live long enough to be counted on multiple surveys. Adjusting population size using average adult lifespan (Schultz and Dlugosch \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) provides a simple solution, although estimates may still align best when adult lifespan roughly matches the survey interval. For example, distance sampling estimates overlapped with MRR estimates at Mt. Hebo, where the average lifespan was 8.9 days, but were lower than MRR estimates at Nestucca and Rock Creek, where average lifespans were 16.8 and 19 days. This method has been used to estimate Fender\u0026rsquo;s blue population size over multiple years (Fitzpatrick 2015, unpublished) with an average lifespan of 9.5 days (Schultz \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Schultz and Dlugosh 1999), comparable to our estimates for Mt. Hebo. Approaches such as Insect Count Analyzer (INCA) similarly incorporate death rates and emergence times in population estimation (Longcore et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) and have also been used with at-risk butterflies (Fitzpatrick 2015, unpublished; Haddad et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Alternatively, metrics such as peak single day abundance (PSDA) have been used as a proxy for population size for Taylor\u0026rsquo;s checkerspot butterfly in the absence of lifespan estimates (USFWS \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Provided that lifespan does not vary substantially among years and the population is sampled across the entire flight period, either of these approaches would likely be satisfactory for approximating population size of Oregon silverspot. Future population estimation might utilize an Integrated Population Model (IPM) as a more robust approach for combining abundance and demography data (Besbeas et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2002\u003c/span\u003e), but its application may still be limited by single-year datasets.\u003c/p\u003e \u003cp\u003eLow densities and sparse detections required us to adapt our approach to estimating population size. In addition to pooling detections across sites and years, we pooled detections across all three years at Rock Creek to estimate population size in 2022 and 2023 due to insufficient sample sizes (\u0026lt;\u0026thinsp;40; Buckland et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). This approach assumes that potential differences in detection probability across years does not introduce significant bias in abundance estimates\u0026mdash;a concept referred to as \u0026ldquo;pooling robustness\u0026rdquo; (Buckland et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Rexstad et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u0026mdash;and allowed us to estimate population size at Rock Creek despite having too few observations to fit a site- and year- specific detection function. Pooling robustness may not hold if detection probability differed substantially from 2022 to 2024 at Rock Creek, but pooling across years was preferred over pooling across sites to better capture site-specific detectability patterns, given known spatial variation in detectability (Isaac et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Distance sampling over multiple years at a site would allow for the use of a more robust global detection function or pooled functions across site-surveyor analogs, both of which have been used with Fender\u0026rsquo;s blue at Fern Ridge (Kelsey King, personal communication, 2025). For very sparse populations, distance sampling is generally less effective because sufficient detections are required to reliably estimate density (Buckland et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Bart et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2004\u003c/span\u003e), and double-observer sampling has been investigated as an alternative that reduces the number of detections needed but requires more surveyors (Henry and Anderson \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Further investigation of global detection functions and their robustness would be valuable for improving monitoring of at-risk species with low population densities.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eIndex counts\u003c/h2\u003e \u003cp\u003eIndex counts are often used as proxies for population size, but are prone to bias if detection probability varies over space and time (Pollard and Yates \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Anderson \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Haddad et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Harker and Shreeve \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). We found that index counts broadly scaled to the relative size of each population (i.e., counts were lowest at the smallest population and highest at the largest population) and generally reflected distance sampling population trends when population growth or decline could be determined. Without accounting for uncertainty, however, the highest index count did not always correspond to the largest population size. This may indicate that variation in detectability was outweighed by differences in abundance (Isaac et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), such that index counts reliably tracked large fluctuations in population size but were less effective at estimating finer-scale population changes, where incorporating detectability improved estimates. This may also reflect the limitations of the current sampling scheme\u0026mdash;survey routes extend around meadow margins and areas that are expected to have large numbers of butterflies. Changes in vegetation structure or nectar availability from year to year may affect distribution and residence time in natal patches (Luoto et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Schultz et al. \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), resulting in fluctuating detectability of adults over time (Pellet et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). However, our distance sampling data also show that the highest number of detections did not always correspond to the largest population size, suggesting that counts may not scale reliably with population size even in well-designed surveys. Developing an index count survey that systematically samples habitat may improve reliability relative to the current approach, but still lacks the inferential strength needed for conservation decision-making compared with alternative survey methods (Kral et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eConservation implications\u003c/h2\u003e \u003cp\u003eOur results demonstrate that method choice directly influences the biological conclusions that can be drawn for conservation decision-making. Although monitoring resources are often limited, the additional effort required for distance sampling provides substantially more information on population size and detectability than commonly used index count strategies. Even short-term, targeted MRR studies produce valuable demographic data that can be leveraged to refine distance sampling estimates and inform monitoring design. Distance sampling could be further adapted to separately estimate wild population size in augmented populations if captive-reared and wild butterflies are distinguished during surveys. This could be achieved through visible markings on captive released individuals or by temporarily pausing releases to exclusively estimate wild population size and recruitment. As captive rearing and augmentation programs continue to grow, reliable monitoring will be essential for quantifying the contribution of these efforts to population growth and informing ongoing management strategies.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis work was funded by U.S. Fish and Wildlife Service under Cooperative Agreement No. F22AC00345-00\u003c/p\u003e \u003cp\u003e \u003cem\u003eCompeting interests\u003c/em\u003e: The authors declare no competing interests.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization: I.B., E.H., R.V.B., C.S.; Data collection: I.B., E.H., R.V.B.; Data curation: I.B., E.H.; Analysis development: I.B., E.H., C.S.; Analysis implementation: I.B.; Expert review of results and code: E.H., C.S.; Funding acquisition and project administration: E.H., R.V.B., C.S.; Writing\u0026mdash;original draft: I.B.; Writing\u0026mdash;review and editing: I.B., E.H., R.V.B., C.S.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe thank our agency collaborators at U.S. Fish and Wildlife Service, U.S. Forest Service, and Oregon Parks and Recreation Department for making this work possible, including Samantha Derrenbacher, David Thompson, Michele Zwartjes, Kate Iaquinto, Khem So, Julia Johanos, DeAnna Williams, Iain Emmons, Halle Renn, Sarah Kaufman, Crystal Barnes, Micah Ashford, Aileen Macias, Teagan Miller, Chase Cessna, Emma Lundgren, Julia Izzo, Marie-Therese Offner, and Sophie Lyons. Thank you to the field technicians and volunteers who counted and marked thousands of butterflies, including Emma Dombrow, Bree Sheffield, Kate Glover, Torin Bevins, Brooke Fritzler, Jasper Cameron, Makazlynn Schulz, Shelline Nerup, Chloe Hendricks, Emily Kresin, Devin Simmers, Parrish Noce, Larry Hurst, Sierra Hagen, Kate Underwood, Oc\u0026eacute;ane Caporal, Kole Meinhart, John Lyssenko, Daniel Gonzalez, Brooke Stewart, Renay McInturf, Brittany White, and Bryant and Jamie Bainbridge. A special thanks to the teams at Oregon Zoo and Woodland Park Zoo\u0026mdash;including Julia Low and Erin Sullivan\u0026mdash;for their dedication to rearing Oregon silverspot butterflies. Finally, thank you to John Bishop and Seth Rudman at Washington State University for reviewing earlier drafts of this manuscript, and Diego Murillo and Alison Logan for their administrative support of this research.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData and code will be available on Dryad upon acceptance\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAdamski P, Cmiel A (2022) The long-term effect of over-supplementation on recovered populations: Why restraint is a virtue. Oryx 56(4):564\u0026ndash;571. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1017/S0030605321000296\u003c/span\u003e\u003cspan address=\"10.1017/S0030605321000296\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnderson DR (2001) The need to get the basics right in wildlife field studies. Wildl Soc Bull 29(4):1294\u0026ndash;1297. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.jstor.org/stable/3784156\u003c/span\u003e\u003cspan address=\"http://www.jstor.org/stable/3784156\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnton J, Rotger A, Igual J, Tavecchia G (2013) Estimating lizard population density: An empirical comparison between line-transect and capture-recapture methods. Wildl Res 40(7):552\u0026ndash;560. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1071/WR13127\u003c/span\u003e\u003cspan address=\"10.1071/WR13127\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArmstrong DP, Seddon PJ (2008) Directions in reintroduction biology. Trends Ecol Evol 23(1):20\u0026ndash;25. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://doi.org/10.1016/j.tree.2007.10.003\u003c/span\u003e\u003cspan address=\"10.1016/j.tree.2007.10.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBart J, Droege S, Geissler P, Peterjohn B, Ralph C (2004) Density estimation in wildlife surveys. Wildl Soc Bull 32(4):1242\u0026ndash;1247. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2193/0091-7648(2004)032\u003c/span\u003e\u003cspan address=\"10.2193/0091-7648(2004)032\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e[1242:DEIWS]2.0.CO;2\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBelitz M, Monfils M, Cuthrell D, Monfils A (2019) Life history and ecology of the endangered Poweshiek skipperling \u003cem\u003eOarisma poweshiek\u003c/em\u003e in Michigan prairie fens. J Insect Conserv 23(3):635\u0026ndash;649. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10841-019-00158-6\u003c/span\u003e\u003cspan address=\"10.1007/s10841-019-00158-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBesbeas P, Freeman SN, Morgan BJT, Catchpole EA (2002) Integrating mark-recapture-recovery and census data to estimate animal abundance and demographic parameters. Biometrics 58(3):540\u0026ndash;547. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.0006-341X.2002.00540.x\u003c/span\u003e\u003cspan address=\"10.1111/j.0006-341X.2002.00540.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBried JT, Pellet J (2012) Optimal design of butterfly occupancy surveys and testing if occupancy converts to abundance for sparse populations. J Insect Conserv 16(4):489\u0026ndash;499. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10841-011-9435-2\u003c/span\u003e\u003cspan address=\"10.1007/s10841-011-9435-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrown J, Boyce M (1998) Line transect sampling of Karner blue butterflies (\u003cem\u003eLycaeides melissa samuelis\u003c/em\u003e). Environ Ecol Stat 5(1):81\u0026ndash;91. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1023/A:1009620105039\u003c/span\u003e\u003cspan address=\"10.1023/A:1009620105039\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBubov\u0026aacute; T, Kulma M, Vrabec V, Nowicki P (2016) Adult longevity and its relationship with conservation status in European butterflies. J Insect Conserv 20:1021\u0026ndash;1032. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10841-016-9936-0\u003c/span\u003e\u003cspan address=\"10.1007/s10841-016-9936-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBuckland ST, Anderson DR, Burnham KP, Laake JL, Borchers DL, Thomas L (2001) Introduction to distance sampling: Estimating abundance of biological populations. Oxford University Press. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/oso/9780198506492.001.0001\u003c/span\u003e\u003cspan address=\"10.1093/oso/9780198506492.001.0001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBuckland ST, Anderson DR, Burnham KP, Laake JL, Borchers DL, Thomas L (2004) Advanced distance sampling: Estimating abundance of biological populations. Oxford University Press. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/oso/9780198507833.001.0001\u003c/span\u003e\u003cspan address=\"10.1093/oso/9780198507833.001.0001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCabrera SRS, Belitz M, Emmel TC, Khazan ES, Standridge MJ, Rossetti K, Daniels JC (2025) Long-term population dynamics of an endangered butterfly are influenced by hurricane-mediated disturbance. Biol Conserv 302:110969. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.biocon.2025.110969\u003c/span\u003e\u003cspan address=\"10.1016/j.biocon.2025.110969\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCasacci LP, Cerrato C, Barbero F, Bosso L, Ghidotti S, Paveto M, Pesce M, Plazio E, Panizza G, Balletto E, Viterbi R, Bonelli S (2015) Dispersal and connectivity effects at different altitudes in the \u003cem\u003eEuphydryas aurinia\u003c/em\u003e complex. J Insect Conserv 19(2):265\u0026ndash;277. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10841-014-9715-8\u003c/span\u003e\u003cspan address=\"10.1007/s10841-014-9715-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCelik T (2012) Adult demography, spatial distribution and movements of \u003cem\u003eZerynthia polyxena\u003c/em\u003e (Lepidoptera: Papilionidae) in a dense network of permanent habitats. Eur J Entomol 109(2):217\u0026ndash;227. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.14411/eje.2012.028\u003c/span\u003e\u003cspan address=\"10.14411/eje.2012.028\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChandler RB, Engebretsen K, Cherry MJ, Garrison EP, Miller KV (2018) Methods Ecol Evol 9(10):2115\u0026ndash;2130. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/2041-210X.13068\u003c/span\u003e\u003cspan address=\"10.1111/2041-210X.13068\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Estimating recruitment from capture-recapture data by modelling spatio-temporal variation in birth and age-specific survival rates\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCollins M, Runge MC, Rinehart K, Crone EE, Dillon J, Fitzpatrick G, Hicks T, Messinger W, Schultz CB, Brewer DC (2011) Monitoring design for Fender\u0026rsquo;s blue butterfly. Case Study from Structured Decision Making Workshop, January 24\u0026ndash;28, 2011. National Conservation Training Center, Shepherdstown, West Virginia\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCollier N, Mackay D, Benkendorff K (2008) Is relative abundance a good indicator of population size? Evidence from fragmented populations of a specialist butterfly (Lepidoptera: Lycaenidae). Popul Ecol 50(1):17\u0026ndash;23. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10144-007-0056-2\u003c/span\u003e\u003cspan address=\"10.1007/s10144-007-0056-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCorlatti L, Nelli L, Bertolini M, Zibordi F, Pedrotti L (2017) A comparison of four methods to estimate population size of Alpine marmot (\u003cem\u003eMarmota marmota\u003c/em\u003e). Hystrix-Italian J Mammalogy 28(1):61\u0026ndash;67. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4404/hystrix-28.1-11698\u003c/span\u003e\u003cspan address=\"10.4404/hystrix-28.1-11698\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCormack RM (1964) Estimates of survival from the sighting of marked animals. Biometrika 51(3/4):429\u0026ndash;438. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2307/2334149\u003c/span\u003e\u003cspan address=\"10.2307/2334149\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCrowther MS, Dargan JR, Madani G, Rus AI, Krockenberger MB, McArthur C, Moore BD, Lunney D, Mella VSA (2020) Comparison of three methods of estimating the population size of an arboreal mammal in a fragmented rural landscape. Wildl Res 48:105\u0026ndash;114. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1071/WR19148\u003c/span\u003e\u003cspan address=\"10.1071/WR19148\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDaura-Jorge FG, Sim\u0026otilde;es-Lopes PC (2017) Mark-recapture vs. line-transect abundance estimates of a coastal dolphin population: A case study of Tursiops truncatus from Laguna, southern Brazil. Latin Am J Aquat Mamm 11:133\u0026ndash;143. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5597/lajam00222\u003c/span\u003e\u003cspan address=\"10.5597/lajam00222\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDavis A, Smith F, Ballew A (2020) A poor substitute for the real thing: Captive-reared monarch butterflies are weaker, paler and have less elongated wings than wild migrants. Biol Lett 16(4). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1098/rsbl.2019.0922\u003c/span\u003e\u003cspan address=\"10.1098/rsbl.2019.0922\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDayan D, Sard N, Johnson M, Fitzpatrick C, Couture R, O\u0026rsquo;Malley K (2024) A single generation in the wild increases fitness for descendants of hatchery-origin Chinook salmon (\u003cem\u003eOncorhynchus tshawytscha\u003c/em\u003e). Evol Appl 17(4). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/eva.13678\u003c/span\u003e\u003cspan address=\"10.1111/eva.13678\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEsri Inc (2022) ArcGIS Pro (Version 3.0)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEwen JG, Armstrong DP, Parker KA, Seddon PJ (2012) Monitoring for reintroductions. Reintroduction Biology. John Wiley \u0026amp; Sons, Ltd. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/9781444355833\u003c/span\u003e\u003cspan address=\"10.1002/9781444355833\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFlockhart D, Pichancourt J, Norris D, Martin T (2015) Unravelling the annual cycle in a migratory animal: Breeding-season habitat loss drives population declines of monarch butterflies. J Anim Ecol 84(1):155\u0026ndash;165. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/1365-2656.12253\u003c/span\u003e\u003cspan address=\"10.1111/1365-2656.12253\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFox R, Dennis E, Brown A, Curson J (2022) A revised red list of British butterflies. Insect Conserv Divers 15(5):485\u0026ndash;495. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/icad.12582\u003c/span\u003e\u003cspan address=\"10.1111/icad.12582\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFranz\u0026eacute;n M, Johansson H, Askling J, Kindvall O, Johansson V, Forsman A, Sunde J (2024) Long-distance movements, large population sizes and density-dependent dispersal in three threatened butterfly species. Insect Conserv Divers. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/icad.12766\u003c/span\u003e\u003cspan address=\"10.1111/icad.12766\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFred MS, Brommer JE (2009) Resources influence dispersal and population structure in an endangered butterfly. Insect Conserv Divers 2:11\u0026ndash;18. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1752-4598.2009.00059.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1752-4598.2009.00059.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGross K, Kalendra E, Hudgens B, Haddad N (2007) Robustness and uncertainty in estimates of butterfly abundance from transect counts. Popul Ecol 49(3):191\u0026ndash;200. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10144-007-0034-8\u003c/span\u003e\u003cspan address=\"10.1007/s10144-007-0034-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHaddad N, Hudgens B, Damiani C, Gross K, Kuefler D, Pollock K (2008) Determining optimal population monitoring for rare butterflies. Conserv Biol 22(4):929\u0026ndash;940. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1523-1739.2008.00932.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1523-1739.2008.00932.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHamm C (2013) Estimating abundance of the federally endangered Mitchell\u0026rsquo;s satyr butterfly using hierarchical distance sampling. Insect Conserv Divers 6(5):619\u0026ndash;626. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/icad.12017\u003c/span\u003e\u003cspan address=\"10.1111/icad.12017\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHarding E, Crone E, Elderd B, Hoekstra J, McKerrow A, Perrine J, Regetz J, Rissler L, Stanley A, Walters E, NCEAS Habitat Conservation Plan Working Group (2001) The scientific foundations of habitat conservation plans: a quantitative assessment. Conserv Biol 15(2):488\u0026ndash;500. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1046/j.1523-1739.2001.015002488.x\u003c/span\u003e\u003cspan address=\"10.1046/j.1523-1739.2001.015002488.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHarker RJ, Shreeve TG (2008) How accurate are single site transect data for monitoring butterfly trends? Spatial and temporal issues identified in monitoring \u003cem\u003eLasiommata megera\u003c/em\u003e. J Insect Conserv 12(2):125\u0026ndash;133. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10841-007-9068-7\u003c/span\u003e\u003cspan address=\"10.1007/s10841-007-9068-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHenry E, Anderson C (2016) Abundance estimates to inform butterfly management: Double-observer versus distance sampling. J Insect Conserv 20(3):505\u0026ndash;514. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10841-016-9883-9\u003c/span\u003e\u003cspan address=\"10.1007/s10841-016-9883-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHenry E, Haddad N, Wilson J, Hughes P, Gardner B (2015) Point-count methods to monitor butterfly populations when traditional methods fail: A case study with Miami blue butterfly. J Insect Conserv 19(3):519\u0026ndash;529. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10841-015-9773-6\u003c/span\u003e\u003cspan address=\"10.1007/s10841-015-9773-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHenry E, Sheffield B, Schultz C (2024) Experimental management and mark-release-recapture methods fill critical knowledge gaps for an at-risk butterfly. J Insect Conserv 28(5):951\u0026ndash;958. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10841-024-00562-7\u003c/span\u003e\u003cspan address=\"10.1007/s10841-024-00562-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHinneberg H, Kőr\u0026ouml;si \u0026Aacute;, Gottschalk T (2023) Providing evidence for the conservation of a rare forest butterfly: Results from a three-year capture-mark-recapture study. Basic Appl Ecol 73:27\u0026ndash;39. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.baae.2023.09.001\u003c/span\u003e\u003cspan address=\"10.1016/j.baae.2023.09.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHolmes T, Arnold R (2015) Generalized generation population size estimation of endangered insects via parsimonious, flexible integration of transect counts with mark-release-recapture data. Ann Entomol Soc Am 108(2):160\u0026ndash;171. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/aesa/sau007\u003c/span\u003e\u003cspan address=\"10.1093/aesa/sau007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIsaac N, Cruickshanks K, Weddle A, Rowcliffe J, Brereton T, Dennis R, Shuker D, Thomas C (2011) Distance sampling and the challenge of monitoring butterfly populations. Methods Ecol Evol 2(6):585\u0026ndash;594. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.2041-210X.2011.00109.x\u003c/span\u003e\u003cspan address=\"10.1111/j.2041-210X.2011.00109.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJolly GM (1965) Explicit estimates from capture-recapture data with both death and immigration-stochastic model. Biometrika 52(1\u0026ndash;2):225\u0026ndash;248. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/biomet/52.1-2.225\u003c/span\u003e\u003cspan address=\"10.1093/biomet/52.1-2.225\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKacoliris FP, Berkunsky I, Williams JD (2009) Methods for assessing population size in sand dune lizards (\u003cem\u003eLiolaemus multimaculatus\u003c/em\u003e). Herpetologica 65(2):219\u0026ndash;226. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1655/08-036R1.1\u003c/span\u003e\u003cspan address=\"10.1655/08-036R1.1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eK\u0026eacute;ry M, Plattner M (2007) Species richness estimation and determinants of species detectability in butterfly monitoring programmes. Ecol Entomol 32(1):53\u0026ndash;61. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1365-2311.2006.00841.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1365-2311.2006.00841.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKral K, Harmon J, Limb R, Hovick T (2018) Improving our science: The evolution of butterfly sampling and surveying methods over time. J Insect Conserv 22(1):1\u0026ndash;14. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10841-018-0046-z\u003c/span\u003e\u003cspan address=\"10.1007/s10841-018-0046-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKral-O\u0026rsquo;Brien K, Karasch B, Hovick T, Moranz R, Harmon J (2020) Morphological traits determine detectability bias in North American grassland butterflies. Ecosphere 11(12). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/ecs2.3304\u003c/span\u003e\u003cspan address=\"10.1002/ecs2.3304\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLaake J (2025) RMark: R Code for Mark Analysis (Version 3.0.0) [Computer software]. CRAN\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLettink M, Armstrong DP (2003) An introduction to using mark-recapture analysis for monitoring threatened species. Department Conserv Tech Ser 28A:5\u0026ndash;32\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLewis OT, Thomas CD (2001) Adaptations to captivity in the butterfly \u003cem\u003ePieris brassicae\u003c/em\u003e (L.) and the implications for ex situ conservation. J Insect Conserv 5(1):55\u0026ndash;63. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1023/A:1011348716934\u003c/span\u003e\u003cspan address=\"10.1023/A:1011348716934\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLongcore T, Mattoni R, Zonneveld C, Bruggeman J (2003) Insect Count Analyzer: a tool to assess responses of butterflies to habitat restoration. Ecol Restor 21:60\u0026ndash;61. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3368/er.21.4.311\u003c/span\u003e\u003cspan address=\"10.3368/er.21.4.311\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLuoto M, Kuussaari M, Rita H, Salminen J, Bonsdorff T (2001) Determinants of distribution and abundance in the clouded apollo butterfly: a landscape ecological approach. Ecography 24(5):601\u0026ndash;617. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1600-0587.2001.tb00494.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1600-0587.2001.tb00494.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMacKenzie DI, Royle JA (2005) Designing occupancy studies: General advice and allocating survey effort. J Appl Ecol 42(6):1105\u0026ndash;1114. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1365-2664.2005.01098.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1365-2664.2005.01098.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcFarland KP, Lloyd JD, Hardy SP (2017) Density and habitat relationships of the endemic White Mountain Fritillary (\u003cem\u003eBoloria chariclea montinus\u003c/em\u003e) (Lepidoptera: Nymphalidae). Insects 8(2). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/insects8020057\u003c/span\u003e\u003cspan address=\"10.3390/insects8020057\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiller DL, Rexstad E, Thomas L, Marshall L, Laake JL (2019) Distance Sampling in R. J Stat Softw 89(1):1\u0026ndash;28. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.18637/jss.v089.i01\u003c/span\u003e\u003cspan address=\"10.18637/jss.v089.i01\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNorman H, S\u0026auml;wenfalk D, Kindvall O, Franz\u0026eacute;n M, Askling J, Johansson V (2024) Novel grid-based population estimates correlate with actual population sizes of the marsh fritillary (\u003cem\u003eEuphydryas aurinia\u003c/em\u003e), while transect and larvae counts are less reliable. Ecol Entomol 49(2):180\u0026ndash;190. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/een.13292\u003c/span\u003e\u003cspan address=\"10.1111/een.13292\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNowicki P, Witek M, Sk\u0026oacute;rka P, Settele J, Woyciechowski M (2005) Population ecology of the endangered butterflies \u003cem\u003eMaculinea teleius\u003c/em\u003e and \u003cem\u003eM. nausithous\u003c/em\u003e and the implications for conservation. Popul Ecol 47:193\u0026ndash;202. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10144-005-0222-3\u003c/span\u003e\u003cspan address=\"10.1007/s10144-005-0222-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e\u0026Ouml;rv\u0026ouml;ssy N, Kor\u0026ouml;si A, Bat\u0026aacute;ry P, Voz\u0026aacute;r A, Peregovits L (2013) Potential metapopulation structure and the effects of habitat quality on population size of the endangered False Ringlet butterfly. J Insect Conserv 17(3):537\u0026ndash;547. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10841-012-9538-4\u003c/span\u003e\u003cspan address=\"10.1007/s10841-012-9538-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eParile E, Piccini I, Bonelli S (2021) A demographic and ecological study of an Italian population of \u003cem\u003ePolyommatus ripartii\u003c/em\u003e: The ESU \u003cem\u003ePolyommatus exuberans\u003c/em\u003e. J Insect Conserv 25(5):783\u0026ndash;796. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10841-021-00344-5\u003c/span\u003e\u003cspan address=\"10.1007/s10841-021-00344-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePatterson S, Harris J, Dinsmore S, Kinkead K (2023) Evaluating differences in density estimation for central Iowa butterflies using two methodologies. PeerJ 11. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.7717/peerj.16165\u003c/span\u003e\u003cspan address=\"10.7717/peerj.16165\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePellet J (2008) Seasonal variation in detectability of butterflies surveyed with Pollard walks. J Insect Conserv 12(2):155\u0026ndash;162. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10841-007-9075-8\u003c/span\u003e\u003cspan address=\"10.1007/s10841-007-9075-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePellet J, Bried J, Parietti D, Gander A, Heer P, Cherix D, Arlettaz R (2012) Monitoring butterfly abundance: Beyond Pollard walks. PLoS ONE 7(7). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0041396\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0041396\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePollard E (1977) A method for assessing changes in the abundance of butterflies. Biol Conserv 12(2):115\u0026ndash;134. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/0006-3207(77)90065-9\u003c/span\u003e\u003cspan address=\"10.1016/0006-3207(77)90065-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePollard E, Yates TJ (1993) Monitoring butterflies for ecology and conservation: The British butterfly monitoring scheme, 1st edn. Chapman \u0026amp; Hall\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePosit Team (2025) RStudio: Integrated Development Environment for R. Posit Software. PBC, Boston, MA. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.posit.co/\u003c/span\u003e\u003cspan address=\"http://www.posit.co/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePowell A, Busby W, Kindscher K (2007) Status of the regal fritillary (\u003cem\u003eSpeyeria idalia\u003c/em\u003e) and effects of fire management on its abundance in northeastern Kansas, USA. J Insect Conserv 11(3):299\u0026ndash;308. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10841-006-9045-6\u003c/span\u003e\u003cspan address=\"10.1007/s10841-006-9045-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRagab SH, Tyshenko MG, Halmy MW (2025) Impact of climate change on the habitat range of monarch butterfly (\u003cem\u003eDanaus plexippus\u003c/em\u003e). Sci Rep 15. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41598-025-17443-x\u003c/span\u003e\u003cspan address=\"10.1038/s41598-025-17443-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRexstad E, Buckland S, Marshall L, Borchers D (2023) Pooling robustness in distance sampling: Avoiding bias when there is unmodelled heterogeneity. Ecol Evol 13(1). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/ece3.9684\u003c/span\u003e\u003cspan address=\"10.1002/ece3.9684\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eScheele B, Legge S, Blanchard W, Garnett S, Geyle H, Gillespie G, Harrison P, Lindenmayer D, Lintermans M, Robinson N, Woinarski J (2019) Continental-scale assessment reveals inadequate monitoring for threatened vertebrates in a megadiverse country. Biol Conserv 235:273\u0026ndash;278. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.biocon.2019.04.023\u003c/span\u003e\u003cspan address=\"10.1016/j.biocon.2019.04.023\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchultz CB (1995) Status of the Fender's blue butterfly (\u003cem\u003eIcaricia icarioides fenderi\u003c/em\u003e) in Lane County, Oregon: a year of declines. Report to the US Fish and Wildlife Service and the Oregon Natural Heritage Program, Portland, Oregon. 58 pp\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchultz CB, Dlugosch KM (1999) Nectar and hostplant scarcity limit populations of an endangered Oregon butterfly. Oecologia 119(2):231\u0026ndash;238. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s004420050781\u003c/span\u003e\u003cspan address=\"10.1007/s004420050781\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchultz CB, Haddad NM, Henry EH, Crone EE (2019) Movement and Demography of At-Risk Butterflies: Building Blocks for Conservation. Ann Rev Entomol 64:167\u0026ndash;184. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1146/annurev-ento-011118-112204\u003c/span\u003e\u003cspan address=\"10.1146/annurev-ento-011118-112204\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchultz CB, Hammond P (2003) Using population viability analysis to develop recovery criteria for endangered insects: Case study of the Fender\u0026rsquo;s blue butterfly. Conserv Biol 17(5):1372\u0026ndash;1385. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1046/j.1523-1739.2003.02141.x\u003c/span\u003e\u003cspan address=\"10.1046/j.1523-1739.2003.02141.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchultz CB, Russell C, Wynn L (2008) Restoration, reintroduction, and captive propagation for at-risk butterflies: A review of British and American conservation efforts. Isreal J Ecol Evol 54(1):41\u0026ndash;61. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1560/IJEE.54.1.41\u003c/span\u003e\u003cspan address=\"10.1560/IJEE.54.1.41\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchultz CB, Franco AMA, Crone EE (2012) Response of butterflies to structural and resource boundaries. J Anim Ecol 81(3):724\u0026ndash;734. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1365-2656.2011.01947.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1365-2656.2011.01947.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchwarz CJ, Arnason AN (1996) A general methodology for the analysis of capture-recapture experiments in open populations. Biometrics 52(3):860\u0026ndash;873. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2307/2533048\u003c/span\u003e\u003cspan address=\"10.2307/2533048\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSeber GAF (1965) A note on the multiple-recapture census. Biometrika 52(1\u0026ndash;2):249\u0026ndash;260. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2307/2333827\u003c/span\u003e\u003cspan address=\"10.2307/2333827\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShuey J, Szymanski J (2012) Modified Pollard transects do not predict estimated daily population size for the secretive butterfly, \u003cem\u003eNeonympha mitchellii mitchellii\u003c/em\u003e French. J Lepidopterists Soc 66(4):221\u0026ndash;224. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.18473/lepi.v66i4.a6\u003c/span\u003e\u003cspan address=\"10.18473/lepi.v66i4.a6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSielezniew M, Bystrowski C, Deoniziak K, Dziekańska I, Kostro-Ambroziak A, Wołowicz A, Nowicki P (2023) Inter-annual variation in adult demography, but no sex bias in a large lowland population of the threatened Clouded Apollo \u003cem\u003eParnassius mnemosyne\u003c/em\u003e butterfly. Eur Zoological J 90(2):648\u0026ndash;659. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/24750263.2023.2247436\u003c/span\u003e\u003cspan address=\"10.1080/24750263.2023.2247436\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSims SR (1984) Reproductive diapause in \u003cem\u003eSpeyeria\u003c/em\u003e (Lepidoptera: Nymphalidae). J Res Lepidoptera 23:211\u0026ndash;216. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5962/p.266759\u003c/span\u003e\u003cspan address=\"10.5962/p.266759\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSims SR (2017) \u003cem\u003eSpeyeria\u003c/em\u003e (Lepidoptera: Nymphalidae) Conservation. Insects 8(2):45. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/insects8020045\u003c/span\u003e\u003cspan address=\"10.3390/insects8020045\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTaron D, Ries L (2015) Butterfly monitoring for conservation. In Butterfly conservation in North America: Efforts to help save our charismatic microfauna (pp. 35\u0026ndash;58). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/978-94-017-9852-5_3\u003c/span\u003e\u003cspan address=\"10.1007/978-94-017-9852-5_3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTenger-Trolander A (2023) Environmental and genetic effects of captivity\u0026mdash;Are there lessons for monarch butterfly conservation? Curr Opin Insect Sci 59:101088. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.cois.2023.101088\u003c/span\u003e\u003cspan address=\"10.1016/j.cois.2023.101088\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThomas L, Buckland S, Rexstad E, Laake J, Strindberg S, Hedley S, Bishop J, Marques T, Burnham K (2010) Distance software: Design and analysis of distance sampling surveys for estimating population size. J Appl Ecol 47(1):5\u0026ndash;14. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1365-2664.2009.01737.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1365-2664.2009.01737.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTurlure C, Pe\u0026rsquo;er G, Baguette M, Schtickzelle N (2018) A simplified mark-release-recapture protocol to improve the cost effectiveness of repeated population size quantification. Methods Ecol Evol 9(3):645\u0026ndash;656. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/2041-210X.12900\u003c/span\u003e\u003cspan address=\"10.1111/2041-210X.12900\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUSFWS (1980) Federal Register. Vol. 45, No. 129, pp 44935\u0026ndash;44939\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUSFWS (2001) Oregon silverspot (\u003cem\u003eSpeyeria zerene hippolyta\u003c/em\u003e) revised recovery plan. U.S. Fish and Wildlife Service, Portland, Oregon\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUSFWS (2019) Karner blue butterfly (\u003cem\u003eLycaeides melissa samuelis\u003c/em\u003e) 5-year review summary and evaluation. U.S. Fish and Wildlife Service, Bloomington, Minnesota\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUSFWS (2020a) Oregon silverspot butterfly (\u003cem\u003eSpeyeria zerene hippolyta\u003c/em\u003e) 5-year status review summary and evaluation. U.S. Fish and Wildlife Service, Newport, Oregon\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUSFWS (2020b) Fender\u0026rsquo;s blue butterfly (\u003cem\u003eIcaricia icarioides fenderi\u003c/em\u003e) species status assessment report. U.S. Fish and Wildlife Service, Portland, Oregon\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUSFWS (2024) Taylor\u0026rsquo;s checkerspot butterfly (\u003cem\u003eEuphydryas editha taylori\u003c/em\u003e) 5-year review summary and evaluation. U.S. Fish and Wildlife Service, Lacey, Washington\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVrabec V, Bubov\u0026aacute; T, Kulma M, Kr\u0026aacute;sa A, Nowicki P (2019) How \u003cem\u003eEuphydryas maturna\u003c/em\u003e survived extinction in the Czech Republic: Status of a relic population after intensive conservation management. J Insect Conserv 23(2):393\u0026ndash;403. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10841-019-00145-x\u003c/span\u003e\u003cspan address=\"10.1007/s10841-019-00145-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang Z, Li Y, Jain A, Pierce N (2022) Agent-based models reveal limits of mark-release-recapture estimates for the rare butterfly, \u003cem\u003eBhutanitis thaidina\u003c/em\u003e (Lepidoptera: Papilionidae). Insect Sci 29(2):550\u0026ndash;566. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/1744-7917.12949\u003c/span\u003e\u003cspan address=\"10.1111/1744-7917.12949\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWhite GC, Burnham KP (1999) Program MARK: Survival estimation from populations of marked animals. Bird Study 46(sup1). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/00063659909477239\u003c/span\u003e\u003cspan address=\"10.1080/00063659909477239\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. S120-S139\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWilliams A, Alexander K (2023) Microhabitat requirements of the uncompahgre fritillary butterfly (\u003cem\u003eBoloria improba acrocnema\u003c/em\u003e) and climate change implications. J Insect Conserv 27(6):971\u0026ndash;986. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10841-023-00513-8\u003c/span\u003e\u003cspan address=\"10.1007/s10841-023-00513-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWilliams BK, Nichols JD, Conroy MJ (2002) Analysis and management of animal populations: modeling, estimation, and decision making. Academic, San Diego, CA. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubs.usgs.gov/publication/5200256\u003c/span\u003e\u003cspan address=\"https://pubs.usgs.gov/publication/5200256\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZaman K, Tenney C, Rush C, Hill R (2015) Population ecology of a California endemic: \u003cem\u003eSpeyeria adiaste clemencei\u003c/em\u003e. J Insect Conserv 19(4):753\u0026ndash;763. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10841-015-9797-y\u003c/span\u003e\u003cspan address=\"10.1007/s10841-015-9797-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZimmermann K, Konvička M, Fric ZF, Čihakov\u0026aacute; V (2009) Demography of a common butterfly on humid grasslands: \u003cem\u003eArgynnis aglaja\u003c/em\u003e (Lepidoptera: Nymphalidae) studied by mark-recapture. Pol J Ecol 57(4):715\u0026ndash;727\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZimmermann K, Fric ZF, Jiskra P, Kopečkov\u0026aacute; M, Vlaš\u0026aacute;nek P, Zapletal M, Konvička M (2011) Mark-recapture on large spatial scale reveals long distance dispersal in the Marsh Fritillary, \u003cem\u003eEuphydryas aurinia\u003c/em\u003e. Ecol Entomol 36(4):499\u0026ndash;510. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1365-2311.2011.01293.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1365-2311.2011.01293.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-insect-conservation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jico","sideBox":"Learn more about [Journal of Insect Conservation](http://link.springer.com/journal/10841)","snPcode":"10841","submissionUrl":"https://submission.nature.com/new-submission/10841/3","title":"Journal of Insect Conservation","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"mark-release-recapture, distance sampling, Pollard walk, survival, captive rearing, augmentation","lastPublishedDoi":"10.21203/rs.3.rs-9216540/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9216540/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eReliable population size estimates are fundamental to conservation, yet many at-risk species lack robust monitoring programs. Commonly used methods often do not account for imperfect detection and may lead to biased estimates that limit inference about population size and existing conservation strategies. Oregon silverspot butterfly illustrates this challenge, as the effectiveness of ongoing augmentation programs remains unclear due to limitations in index count approaches currently used for baseline annual monitoring. We surveyed three Oregon silverspot populations from 2022 to 2024 using mark-release-recapture (MRR) and distance sampling and compared resulting population size estimates with concurrent index counts to evaluate their relative reliability for long-term monitoring. MRR was also used to estimate adult apparent daily survival to extrapolate weekly abundances from distance sampling to population size and evaluate demographic differences between wild and captive-reared butterflies. Distance sampling produced population size estimates that aligned most closely with MRR when adult lifespan approximated the weekly sampling interval, whereas index counts generally tracked directional trends in abundance but lacked measures of detectability and uncertainty. Adults had long but variable lifespans, and captive-reared butterflies had lower apparent daily survival rates than wild individuals across all sites and years. Because captive-reared butterflies make up a large proportion of survey detections in heavily augmented populations, interpreting population trends and recruitment is challenging when origin is not distinguished. Implications for insect conservation: Distance sampling offers advantages over index counts for estimating abundance, but reliable assessment of population growth in augmented systems hinges on differentiating between wild and captive-reared butterflies.\u003c/p\u003e","manuscriptTitle":"Population monitoring for Oregon silverspot butterfly to support recovery efforts: a comparison of three methods","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-22 21:06:54","doi":"10.21203/rs.3.rs-9216540/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"183208411493173600696629395828931625016","date":"2026-04-15T21:21:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"16255738113554515120831192378199936610","date":"2026-04-14T02:01:39+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-13T15:18:14+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-25T09:19:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-25T09:18:43+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Insect Conservation","date":"2026-03-24T23:43:42+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-insect-conservation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jico","sideBox":"Learn more about [Journal of Insect Conservation](http://link.springer.com/journal/10841)","snPcode":"10841","submissionUrl":"https://submission.nature.com/new-submission/10841/3","title":"Journal of Insect Conservation","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"4bafa539-034a-4b7a-87b0-db71d3c27c78","owner":[],"postedDate":"April 22nd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-22T21:06:54+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-22 21:06:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9216540","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9216540","identity":"rs-9216540","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}