Short-term fluctuating and long-term divergent selection on sympatric Monkeyflowers: insights from repeated reciprocal transplants

Short-term fluctuating and long-term divergent selection on sympatric Monkeyflowers: insights from repeated reciprocal transplants | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (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];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Short-term fluctuating and long-term divergent selection on sympatric Monkeyflowers: insights from repeated reciprocal transplants View ORCID Profile Caroline M. Dong , View ORCID Profile Bolívar Aponte Rolón , Juj K. Sullivan , View ORCID Profile Diana Tataru , Max De Leon , Rachael Dennis , Spencer Dutton , Fidel J. Machado Perez , Lissette Montano , View ORCID Profile Kathleen G. Ferris doi: https://doi.org/10.1101/2024.06.26.600870 Caroline M. Dong 1 Tulane University, Department of Ecology and Evolutionary Biology , New Orleans, LA 2 Grinnell College, Department of Biology , , IA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Caroline M. Dong For correspondence: dongca{at}grinnell.edu Bolívar Aponte Rolón 1 Tulane University, Department of Ecology and Evolutionary Biology , New Orleans, LA 3 Iowa State University, Department of Agricultural and Biosystems Engineering , Ames, IA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Bolívar Aponte Rolón Juj K. Sullivan 1 Tulane University, Department of Ecology and Evolutionary Biology , New Orleans, LA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Diana Tataru 1 Tulane University, Department of Ecology and Evolutionary Biology , New Orleans, LA 4 Utah State University, Department of Biology , , UT Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Diana Tataru Max De Leon 1 Tulane University, Department of Ecology and Evolutionary Biology , New Orleans, LA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Rachael Dennis 1 Tulane University, Department of Ecology and Evolutionary Biology , New Orleans, LA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Spencer Dutton 1 Tulane University, Department of Ecology and Evolutionary Biology , New Orleans, LA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Fidel J. Machado Perez 1 Tulane University, Department of Ecology and Evolutionary Biology , New Orleans, LA 5 University of California Merced, Life and Environmental Sciences Department , , CA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Lissette Montano 1 Tulane University, Department of Ecology and Evolutionary Biology , New Orleans, LA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Kathleen G. Ferris 1 Tulane University, Department of Ecology and Evolutionary Biology , New Orleans, LA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Kathleen G. Ferris Abstract Full Text Info/History Metrics Preview PDF ABSTRACT Sympatric species are often locally adapted to distinct microhabitats. However, temporal variation may cause local maladaptation and species boundary breakdown, especially during extreme climatic events. Repeated reciprocal transplants can reveal the interplay between spatially and temporally varying patterns of natural selection. To examine long-term patterns of selection between sympatric Monkeyflowers occupying dramatically different niches, Mimulus guttatus and M. laciniatus, we performed three replicated transplants and combined them with previous experiments to leverage a dataset of five single-year transplants spanning a decade. We performed phenotypic selection analyses on parents and hybrids in each species’ habitat in Yosemite NP, CA during years of drastically differing snowpack. If there is ecological isolation, then we predicted divergent phenotypic selection between habitats in line with species’ differences and local adaptation. We found interannual fluctuations in phenotypic selection, sometimes in unpredicted directions. However, a combined-year analysis detected longer-term differences in the magnitude of selection between habitats on flowering time, a key temporally isolating and adaptative trait, suggesting that selection may reinforce species boundaries despite short-term fluctuations. Finally, we found temporal variation in local adaptation with M. laciniatus locally adapted in low snowpack years, while an extreme snowfall event contributed to overall local maladaptation of M. guttatus . INTRODUCTION Closely related species often occupy distinct habitats within areas of geographic overlap ( Coyne and Orr 2004 ; Rundle and Nosil 2005 ; Schluter 2009 ). Species boundaries in sympatry can be maintained by adaptation to differing environments that generate pre- and post-zygotic isolation via selection against immigrants (e.g. habitat isolation) and intermediate hybrids (e.g. extrinsic post-zygotic isolation; Rundle & Nosil, 2005 ). However, identifying the individual traits contributing to reproductive isolation is difficult because as speciation progresses, multiple forms of reproductive isolation accumulate between divergent lineages which hinders the measurement of individual barriers ( Coyne and Orr 2004 ). Once species are partially isolated, neutral processes also cause the accumulation of phenotypic divergence. Thus, experimental manipulation is necessary to determine whether habitat isolation is a key barrier, and which traits are involved in divergent adaptation ( Ramsey et al. 2003 ; Hall and Willis 2006 ; Lowry et al. 2008 ). Measuring phenotypic selection on closely related sympatric species in a reciprocal transplant between native environments can identify whether divergent adaptation is important for reproductive isolation and speciation ( Lowry et al. 2008 ; Anderson et al. 2015. If so, we expect each species to have higher fitness in its habitat and phenotypic selection in the direction of species’ differences ( Anderson et al. 2015a ), indicating habitat isolation and local adaptation to current conditions. Despite these predictions of local adaptation, maladaptation to native habitats is often observed in reciprocal transplants ( Hereford 2009 ; Kooyers et al. 2019 ; Dittmar and Schemske 2023 ). This could be due to the prevalence of temporal fluctuations in selection ( Siepielski et al. 2009 ) which can influence the strength of reproductive isolation and species boundaries ( Tataru et al. 2023 , 2024 ). Additionally, current environmental conditions may have changed from the conditions of original divergence ( Coyne and Orr 2004 ; Rundle and Nosil 2005 ). If species are no longer adapted to their current niches due to climate change, then we expect to find local maladaptation ( Crespi 2000 ) and selection for the non-local species’ phenotype ( Wilczek et al. 2014 ; Kooyers et al. 2019 ; Anderson and Wadgymar 2020 ). In this scenario, spatially varying selection may act contrary to reproductive isolation and in the absence of strong intrinsic barriers, could erode species boundaries by driving each towards the other’s phenotypic optimum. Variation in selection in longitudinal studies is usually measured on a seasonal or inter-annual timescale, which is a short-term measurement of population evolution. This leads to the question of how short-term fluctuations affect long-term evolutionary change in species and populations ( Wadgymar et al. 2017 ; Kelly 2022 ; Dittmar and Schemske 2023 ; Oakley et al. 2023 ). A synthesis of phenotypic selection studies by Kingsolver & Diamond (2011) found that while temporal variation in selection is common, it does not significantly inhibit long-term directional selection. Therefore, even with fluctuations in the direction of selection, there may be an average directional or stabilizing trend over a longer timescale. For example, Wadgymar et al. (2017) found that interannual fluctuations in the direction of selection on the perennial plant Boechera stricta gave rise to long-term patterns consistent with stabilizing selection and local adaptation. In Arabidopsis thaliana , Lee et al. (2024) found long-term divergent selection on cold tolerance between populations in Italy and Sweden despite interannual fluctuations. However, due to the arduousness of temporally replicating reciprocal transplant experiments, it is not currently well understood how short versus longer-term patterns of natural selection compare and impact species’ divergence and reproductive isolation. Another understudied agent of evolutionary change is episodic selection stemming from sudden and extreme environmental events. Long-term studies capturing the evolutionary responses to these dramatic ecological changes are rare yet critical to understand their impact on species boundaries ( Coltman et al. 1999 ; Pemberton et al. 2022 ). For instance, through their long-term study of the Galapagos finches, Grant and Grant (1993) were able to illustrate how an extreme El Niño year altered selection on beak size and rates of interspecific gene flow. Strong episodes of selection such as this can impact biodiversity by affecting the evolutionary trajectory of species adaptation and reproductive isolation ( Grant and Grant 1993 ). Studies such as this are vital because extreme climatic events are predicted to become more frequent with continuing anthropogenic climate change ( Bailey and van de Pol 2016 ). The Mimulus guttatus species complex is well-suited for studying how natural selection shapes species boundaries and reproductive isolation ( Wu et al. 2008 ). Mimulus guttatus and M. laciniatus (syn. Erythranthe guttata and E. laciniata ) occur in contrasting microhabitats throughout central and southern Sierra Nevada, CA. Mimulus guttatus inhabits moist meadows and seeps while M. laciniatus occupies rocky outcrops characterized by shallow soils, intense light, extreme temperatures, and a short growing season ( Ferris et al. 2014 ; Ferris and Willis 2018 ). Mimulus laciniatus , an obligate summer annual, has a smaller stature, lobed leaves, self-fertilization with reduced floral size, and early rapid flowering ( DeMarche et al. 2013 ; Ferris and Willis 2018 ). In contrast, M. guttatus populations are facultatively annual, later-flowering, predominantly outcrossing, round-leaved, and larger in size and flower morphology ( Awadalla and Ritland 1997 ; Ferris et al. 2014 ). Despite ecological divergence, reproductive isolation is incomplete ( Vickery 1964 ; Ferris et al. 2017; Tataru et al. 2024 ). Previous studies show evidence of local adaptation to contrasting microhabitats, but it remains unclear how environmental variation alters the strength or direction of selection over time ( Ferris and Willis 2018 ). Early flowering, a drought escape strategy, functions as a key pre-mating barrier in the Mimulus guttatus species complex ( Hall and Willis 2006 ; Lowry et al. 2008 ; Ferris et al. 2017; Mantel and Sweigart 2019 ). Larger plant sizes may be advantageous in meadows where herbivory is higher. Lobed leaves may improve temperature and water regulation through a reduced boundary layer ( Nicotra et al. 2011a ) and are unique to Mimulus species found in rocky habitat ( Ferris et al. 2014 ; Ferris and Willis 2018 ; Ferris 2019 ). Yet how selection on these and other traits (e.g. mating system and flower morphology) fluctuates through time is unknown. Both species exhibit phenotypic plasticity with M. guttatus exhibiting greater plasticity in plant size and flowering time than M. laciniatus ( Ferris & Willis 2018 ). Such plasticity may be adaptive in heterogenous environments like M. laciniatus’ patchy granite outcrops ( Via & Lande 1985 ). Here, we investigate spatial and temporal variation in natural selection between M. guttatus and M. laciniatus using single-year reciprocal transplants repeated across five years under contrasting climatic conditions ( Figure 1 ). In this study, we add three years of new results to two previously published years which spanned years of historically low ( Ferris and Willis 2018 ) and high snowpack ( Tataru et al., 2023 ). Weaker divergent selection on a key isolating barrier, flowering time, was found during the high snowpack year, potentially eroding species differentiation. We replicated transplants during low snowpack years (2021, 2022) and an exceptionally high snowpack year (2023; Figure 1a,b ). We address the following questions: (1) How do environmental variables affect fitness in each species’ habitat and induce phenotypic plasticity? (2) Does the strength and direction of selection on adaptive and reproductively isolating phenotypes fluctuate? (3) How do short versus long-term patterns of selection compare? (4) Are M. guttatus and M. laciniatus locally adapted to their respective microhabitats? (5) How does episodic selection affect the trajectory of species divergence? By examining both interannual variation and overarching signatures of selection, we were able to elucidate the effects of a changing climate on the maintenance of biodiversity in this system. Download figure Open in new tab Figure 1. Temporal and spatial scale of the experimental design. Annual changes in a) snow water content and b) accumulated precipitation during experimental years of low snowpack (2013, 2021, 2022) and comparatively higher snowpack (2019 and 2023). Data are averaged from the California Department of Water Resources data stations GIN, WHW, and TUM, located nearby experimental sites along Tioga Road in Yosemite National Park (cdec.water.ca.gov). The c) spatial layout of experimental sites: meadow 1 and 2 (M1 and M2; filled circles) and granite 1 and 2 (G1 and G2; open circles). Nearby parental source populations for experimental crosses are shown: M . guttatus YVO (filled square) and M . laciniatus WLF (open triangle). Photos of representative meadow and granite habitats are shown in the insets. MATERIALS AND METHODS Repeated reciprocal transplant design Reciprocal transplants used hybrids created from inbred lines of M. guttatus (YVO 18; 37.723366, -119.746433; 5,395 ft elevation) and M. laciniatus (WLF 47; 37.841533, - 119.59385; 7993 ft elevation; Figure 1c ). Advanced generation hybrids were used because recombination over multiple generations breaks up parental haplotypes, increasing phenotypic variation and enabling inferences about selection on individual traits (Figure S1; Nagy, 1997 ; Hall & Willis, 2006 ; Groh & Coop, 2024 ). F 1 hybrids (WLF 47 maternal x YVO 18 paternal) were self-fertilized to generate F 2 seeds used in 2021. Five hundred F 2 hybrids were propagated with single-seed descent to produce F 3 seeds used in 2022 and 300 F 6 lines used in 2023, with some hybrid lines lost likely due to inbreeding depression. In 2021 and 2022, seeds from 200 hybrid maternal families were pooled for transplants. To avoid inbreeding depression in parental genotypes in 2023, inbred lines were intercrossed within each parental population, as M. guttatus is susceptible to inbreeding depression ( Willis 1999 ), which may impact inferences about local adaptation. The 2013 and 2019 experiments used F 4 hybrids from the same parental populations (see Ferris & Willis 2018 ; Tataru et al 2023 ). Our transplants were conducted in 2021, 2022, and 2023 in Yosemite National Park, CA, replicating experiments from 2013 and 2019 at four sites ( Figure 1c ): two granite outcrops (Granite 1 [37.810700, -119.485200; 8,436 ft elevation], Granite 2 [37.843702, -119.573120; 8,117 ft elevation]) and two meadows (Meadow 1 [37.767781, -119.772720; 6,605 ft elevation], Meadow 2 [37.755968, -119.803031; 6,163 ft elevation]). We used precisely the same microhabitats within each site, experimental design, and parental source populations. Sample sizes, maternal families, and hybrid generation differed annually within logistical constraints (Table S1). Seedlings were transplanted in small blocks to capture fine-scale environmental variation and mimic granite habitat patchiness. In 2021 and 2022, each site had 50 randomized blocks (4×6 formation, 1-inch spacing) of 18 and 24 individuals, respectively. In 2021, blocks contained six F 2 hybrids and six of each parent, with Granite 2 having 75 blocks, totaling 4,050 plants. In 2022, blocks contained 16 F 3 hybrids with four of each parent, totaling 4,800 plants. In 2023, local parental genotypes originating from each site were planted only in their origin site, to compare fitness with the nearby source parents (WLF and YVO). We used 2–3 intrapopulation parental crosses and original inbred lines, distributed evenly across blocks and sites, which did not differ in mean seed count and were combined for downstream analyses (Table S2). Each site had 60 blocks (5×7 formation) of 35 individuals, composed of 3 – 4 of parental genotypes (YVO, WLF, and local), and 16 – 23 F 6 hybrids per block, with 1,200 of each parent and 3,000 F 6 hybrids per habitat totaling 8,400 plants. We cold-stratified parental M. laciniatus and hybrid seeds for 10 days and parental M. guttatus seeds for 5 days at 4°C in the dark in plastic flats filled with soil (Sunshine Mix #4 Professional Growing Mix, Sun Gro) to break dormancy and synchronize germination for one week in greenhouses at the University of California (UC) Davis (2021) and UC Merced (2022 – 2023). Following germination upon the emergence of cotyledons, individuals were planted into block designs described above. Mortality within the first week was attributed to transplant shock, dead germinants were replaced and not included in subsequent analyses. Environmental & phenotypic data collection To assess microhabitat variation, environmental measurements were taken weekly from experimental blocks. We measured soil moisture (%) using the SM150T sensor (Dynamax), soil surface temperature (°F) using a laser thermometer, and light intensity (µmol m-2 s-1) using a MQ-200X Sunlight Quantum Meter (Apogee Instruments). Light and temperature were not measured in 2013 ( Ferris and Willis 2018 ). We recorded survival, herbivory (presence/absence), and putatively adaptive phenotypes under selection: flowering time, plant height, herkogamy, flower size, leaf shape ( Ferris et al. 2014 ; Ferris and Willis 2018 ; Tataru et al. 2023 ). At first flowering, we recorded the date and measured plant height (mm), stigma and anther lengths (mm), and corolla width (mm). Flowering time was calculated as days from transplant to first flower. Herkogamy (i.e. stigma-anther separation) was calculated by subtracting stigma length from longest anther length, a metric of outcrossing ability. To assess leaf shape, the first true leaf was collected one-week post-flowering. Leaves were scanned and analyzed for leaf lobing index using ImageJ ( Schneider et al. 2012 ; Ferris et al. 2015 ). Testing for effects of environmental factors on fitness To find associations between environmental variables and plant survival within each habitat, we pooled data across sites and used binomial mixed models with survival as the dependent variable and soil moisture, time, soil temperature and light levels with their interactions as fixed independent variables, and block nested within site as a random effect. Survival was structured as the number of survivors in each block at a time point relative to the number of individuals originally planted in each block. We performed model selection for the best-fit model using AIC selection criteria using R packages nlme v3.1 ( Pinheiro and Bates 2000 ; Pinheiro et al. 2023) and MuMIn v1.47.5 ( Bartoń 2018 ). To test whether foliar herbivory differs between habitats, we used a generalized linear model with a binomial distribution with herbivory as the dependent variable and habitat as the fixed independent variable with block nested within site as a random effect. To understand the effect of herbivory on plant fitness, we used generalized linear models with a Poisson distribution and fitness (i.e. seed count) as the dependent variable while herbivory and habitat and their interactions were fixed independent variables with block nested within site as a random effect using the R package lme4 v1.1.32 ( Bates et al. 2015 ). Phenotypic plasticity analyses We used parental inbred lines to investigate each species’ phenotypically plastic response to the environmental variation between species’ habitats within individual years. These spatial contrasts provide a coarse-grained test ( Levins 1968 ) of how genotypes may respond to differing environmental conditions. Plasticity was analyzed using generalized linear mixed models with phenotype as the dependent variable, habitat as a fixed effect and block nested within site as a random effect. Further, we examined phenotypic plasticity between habitats and years (2013-2023) using generalized linear mixed models with phenotype as the dependent variable, habitat and year with their interaction as fixed effects and block nested within site as a random effect. We also compared hybrid trait means between habitats which are not true measures of plasticity since they represent both genetic and environmental differences. Phenotypic selection analyses To measure lifetime fitness for our phenotypic selection analyses, we counted fruit and seed number. Plants that produced flowers but did not produce fruit or seed were indicated with a value of zero. For annual plants, fruit and seed number are a good approximation of fecundity which we use in our selection analyses. We calculated the correlation between fruit and seed number using Kendall’s correlation analysis. We found that selection gradients ( β values) derived from fruit number (2013) were similar to those from seed number (all other years) in both strength and direction (Table S4, Table S5) likely due to a positive correlation between seed and fruit number (Table S6). Therefore, we compare fruit and seed number derived selection gradients across years. To understand temporal fluctuation in the strength and direction of selection on traits in each habitat, we used multivariate phenotypic selection analyses on datasets of hybrid individuals across all five years of transplants. To investigate linkage between traits, we calculated correlations between traits from hybrid individuals, grouped separately by habitat and year, using linear mixed models with traits as dependent and fixed variables with block nested within site as a random effect. We found generally weak correlations ( r < 0.50) between traits, except between plant height & leaf area and leaf area & flower width (Table S3). Therefore, leaf area was removed from the following phenotypic selection analyses. To properly compare selection gradients from all years, data published in 2013 and 2019 were re-analyzed using the same multivariate linear selection model as the recent transplants ( Ferris and Willis, 2018 ; Tataru et al . 2023 ). Quantitative traits measured in each experiment (leaf lobing, plant height, outcrossing, flower width, flowering time) were standardized to a normal distribution with a mean of 0 and standard deviation of 1 to enable comparison of selection on qualitatively different traits and with previously published studies ( Lande & Arnold 1983 ). Traits were standardized within each year for all analyses except the combined analysis (described below). In our phenotypic selection model, seed count (i.e. fecundity) was the dependent variable with plant height, flowering time, flower width, herkogamy, and leaf lobing as fixed independent variables, with block nested in site and habitat as a random effect. We did not include quadratic or correlational selection terms in our models to simplify our interpretation of the results (Anderson et al. 2015 b ). We did not conduct phenotypic selection analysis of fitness combined across life history stages using an ASTER model approach because our dataset did not include trait data on individuals that died before flowering. To account for overdispersion of zeros in our fecundity data we divided it into two components: the probability of setting any seed (reproducing) vs. the number of seeds set by plants that fruited (fecundity). We used two types of generalized linear mixed models using the R package glmmTMB v1.1.8 ( Brooks et al. 2017 ; Magnusson et al. 2017 ) to analyze these two fitness components separately: the probability of setting seed with a binomial distribution, and a zero-truncated Poisson distribution to assess whether trait values were associated with the number of seeds produced. Sites were pooled within habitats. To extend the comparison to the 2013 experiment which used only fruit number, we repeated all analyses using fruit number as the dependent variable. We repeated phenotypic selection analyses on a combined dataset of hybrid genotypes pooled across all years (2013–2023) using fruit number as the dependent variable with plant height, flowering time, flower width, and leaf lobing as fixed independent variables, and block nested in site and year as random effects. Herkogamy was omitted from the combined dataset due to its absence in 2013. Raw trait data were combined across years and then standardized. To visualize the fitness-phenotype relationships, we plotted selection gradients using the R package visreg ( Breheny and Burchett 2017 ). To assess whether slopes were statistically different for individual traits between meadow and granite habitats, we compared slopes of models using a bootstrap approach (1000 iterations) to derive 95% confidence intervals and p -values. To assess whether temporally fluctuating phenotypic selection is related to environmental fluctuation, we used the combined dataset to run generalized linear models including interactions between traits and snowpack. We used the snow water content accumulated (inches) by April 1 st of each year ( Figure 1a ). The models included fruit as the dependent variable, phenotypic traits (flowering time, flower width, leaf lobing, plant height) and their interaction with snowpack as fixed independent variables and then block nested in site and year as random effects. Assessing local adaptation of M. laciniatus vs. M. guttatus To assess parental species’ local adaptation, we used three metrics of fitness for parental genotypes: survival to flowering (‘survival’), mean seeds per reproductive individual (‘fecundity’), and mean seeds per planted individual (‘total fitness’). For long term patterns, we calculated arithmetic means of each metric across years (2013, 2019, 2021, 2022, 2023) for each habitat and species. Data from 2013 was omitted from averaged fecundity and total fitness because only fruit number was counted. Because it is not known whether these species have seed banks, impacting long-term fitness, we also calculated geometric means across years (Figure S5). To test for genotype by environment (GxE) interactions, we fit linear mixed-effects models for fecundity and total fitness, and generalized linear mixed-effects models for survival, with genotype, habitat, and their interaction as fixed effects and block nested within site as a random effect. Finally, to assess whether the extreme high snowpack of 2023 altered long-term patterns, we compared mean parental fitness in each habitat with ( Figure 5 ) and without data from 2023 (Figure S4). All models described above are summarized in Table S7. RESULTS Environmental variation causes spatial and temporal variation in survival Fine-scale environmental variation was significantly associated with survival trends in both habitats across years and fluctuated both spatially and temporally with snowpack ( Figure 2 , Table S8). Soil moisture availability throughout the season varies significantly between M. laciniatus’s granite and M. guttatus’s meadow habitat in each year with moisture in granite outcrops declining rapidly after an early season plateau, while in meadows there is a gradual, linear decline throughout the growing season. The amount of soil moisture available and the shape of the soil moisture curve fluctuated from year to year with higher snowpack years (2019, 2023) showing shallower declines in soil moisture over time in each habitat ( Figure 2 ). Light intensity and temperature were higher on average in M. laciniatus’s granite environment except in the extreme high snowpack year of 2023 where temperatures were cooler than usual and similar between habitats throughout the growing season ( Figure 2 ; Table S8). Download figure Open in new tab Figure 2. Seasonal changes in (a,b) survival (%), (c,d) soil moisture (%), (e,f) light intensity (µmol m-2 s-1), and (g,h) soil surface temperature (°F) in each block per site in meadow and granite habitats in low snowpack years (2013, 2021, 2022) and high snowpack years (2019, 2023). Data from 2013 and 2019 are published in Ferris and Willis 2018 and Tataru et al . 2023 and re-analyzed here. Across 2021-2023 in both meadow and granite habitats, time (days; p < 0.0001), soil moisture ( p < 0.0001), and soil surface temperature ( p < 0.0001), were almost always significantly associated with survival, with decreasing soil moisture and increasing temperature over time associated with decreased survival (Table S8). Interestingly in 2023, time ( p > 0.05) was not significant associated with survival in meadow habitat. This is likely because in this exceptionally high snowpack year, approximately half of meadow individuals were alive until first snowfall at the end of the growing season ( Figure 2a ). In M. laciniatus’s granite habitat, we found that light intensity ( p < 0.0001) also significantly affected survival in 2021-2023. Soil moisture and soil surface temperature impacted survival over time in the same directions as described for M. guttatus’s meadow habitat in all three recent years. In 2023, soil moisture ( p > 0.05) was not significantly associated with survival in granite habitat. In summary, we found that soil moisture and temperature most significantly impacted survival in both habitats and light intensity additionally impacted survival in granite habitat. Further, 2021–2023 differed from 2019 where soil moisture was the only significant environmental factor ( Tataru et al ., 2023 ). Similar to 2013 and 2019, herbivory pressure differed significantly between habitats with greater herbivory in M. guttatus’ s meadows in 2021 (meadow 22%, granite 1.97%; p = 0.042), 2022 (meadow 37.75%, granite 2.58%; p < 0.01), and 2023 (meadow 23.17%, granite 8.74%; p = 0.032). In 2021 and 2023, herbivory and the interaction between herbivory and habitat significantly affected total fitness but did not in 2022. Overall, herbivore pressure varied spatially, but its effect on fitness varied temporally. Episodic selection: an extreme climatic event dramatically shifted the growing season The extreme high snowpack year (2023) differed from other years in several aspects. The growing season was delayed by six weeks or more in both habitats, with surveys not beginning in granite until previous years’ surveys had ended ( Figure 2a,b ). Soil moisture declined more gradually in both habitats in 2023 than any previous year ( Figure 2c,d ), while light intensity and surface temperatures were lower ( Figure 2e-h ). In granite, there was no characteristic temperature spike in 2023 that usually coincided with mortality ( Figure 2h ). Unlike previous years, many plants had not senesced in meadows at the end of the growing season: 41.7% (Meadow 1) and 50.7% (Meadow 2) alive at the last survey before snowfall ( Figure 2a ). Of the individuals remaining in Meadow 1, many had not flowered indicating a significant life-history delay (0% local genotype, 31.0% hybrids, 44.1% M. guttatus , 70.7% M. laciniatus ). Meadow 2 was similar (0% local genotype, 47.3% hybrids, 40.4% M. guttatus ) except most individuals of M. laciniatus flowered (92.0%). The 2023 growing season was 36-70 days longer than previous years in granite habitats (Granite 2013-2022: 33-87 days; 2023: 112-113 days) but comparable to other years in meadows (Meadow 2013-2022: 74-160 days; 2023: 119-146 days). Phenotypes are adaptively plastic between habitats Parental genotypes exhibited consistent phenotypic plasticity between habitats within years, with the non-native species generally shifting toward the phenotype of the local species. In nearly all three years, M. laciniatus grew more M. guttatus -like in meadow habitat with significantly longer flowering time, taller plant height, larger leaf area (Tables S9, S10, S11). This is similar to patterns from 2013 except for flower size ( Ferris & Willis 2018 ). Conversely, in its nonnative granite habitat, M. guttatus shifted toward M. laciniatus -like traits with significantly shorter flowering time and smaller plant height (2021 and 2023) and smaller leaf area and increased leaf lobing (2022 and 2023; Tables S9, S10, S11). Furthermore, flowering time, plant height, flower width, leaf area displayed significant habitat by year interactions (all p < 0.000), indicating plasticity over time, whereas leaf lobing and outcrossing did not (Table S12). Hybrid means also differed between habitats with shorter flowering time, smaller plant height, smaller leaf area in granite habitat, in the direction of the M. laciniatus (Tables S9, S10, S11). In 2019, hybrids in granite differed by having larger flowers and larger leaf area relative to meadow ( Tataru et al. 2023 ). However, we do not interpret hybrid differences as plasticity as they may instead reflect differences in habitat-dependent selection resulting in differing genetic composition. Interannual fluctuation versus long-term directional selection We found temporal and spatial fluctuations in the strength and direction of selection on each quantitative trait ( Tables 1 , 2 ; Figure 3 ). Our binomial models revealed how phenotypes affected whether plants reproduced whereas the zero-truncated Poisson models revealed how selection acted among individuals that did reproduce (number of seeds). Based on observed trait differences between species, we predicted selection in M. laciniatus’s harsh granite habitat for early flowering time, smaller flowers, increased leaf lobing, shorter plants, and decreased stigma-anther distance (herkogamy), with the inverse direction of selection in M. guttatus’s meadow habitat ( Figure 3a-e ). We found that selection fluctuated across years in habitats and was at times in the opposite direction of our expectations. Selection on the probability of reproduction (binomial models) was typically stronger and more consistent in direction with predictions than selection on fecundity (zero-truncated Poisson models), suggesting that selection acting early in the life cycle on survival and flowering may be more vital than selection acting on fecundity ( Figure 3 ). View this table: View inline View popup Download powerpoint Table 1. Binomial analysis relating phenotypes to fitness, with fitness defined as whether or not a plant produced fruit (2013) or seeds (2019, 2021, 2022, 2023). A combined dataset of all years used fruit number for fitness. The strengths of selection for linear selection gradients are represented as β values. Asterisks indicate significance of selection in a trait: * p < 0.05, ** p < 0.01, *** p < 0.001. Herkogamy was excluded from the combined analysis due to its absence from the 2013 dataset. Phenotypic data from 2013 and 2019 are published in Ferris and Willis 2018 and Tataru et al . 2023 and re-analyzed here. View this table: View inline View popup Download powerpoint Table 2. Zero-truncated Poisson analysis relating phenotypes to fitness, with fitness defined as the number of seeds produced, on individual experimental years of 2013, 2019, 2021, 2022, and 2023 and on a combined dataset of all years. The strengths of selection for linear selection gradients are represented as β values. Asterisks indicate significance of selection in a trait: * p < 0.05, ** p < 0.01, *** p < 0.001. Herkogamy was excluded to from the combined analysis due to its absence from the 2013 dataset. Phenotypic data from 2013 and 2019 are published in Ferris and Willis 2018 and Tataru et al . 2023 and re-analyzed here. Download figure Open in new tab Figure 3. Visual representation of selection gradients (β) of phenotypic traits measured for hybrids during experimental years in granite (open circles) and meadow (filled circles) habitats. Shown are (a-e) predicted values in each habitat based on native species trait differences and estimated values from (f-j) binomial models and (k-o) zero-truncated Poisson models. Significance of each β value is indicated with asterisks (* p < 0.05, ** p < 0.01, *** p < 0.001) and negative graph areas are shaded grey for clarity. All β values are based on seed number, except for values from 2013 which are based on fruit number, as seed number was not recorded. Data from 2013 and 2019 are published in Ferris and Willis 2018 and Tataru et al . 2023 and re-analyzed here. Across all years, selection favored earlier flowering time in both habitats; with early flowering time often under stronger negative selection in the granite habitat as expected in the binomial analysis ( Figure 3f,k ). Selection on flower width fluctuated but was often in the direction expected with larger flowers more favorable in meadow than in granite in the binomial analysis ( Figure 3g ). Zero-truncated models of fecundity selection on flowering time and flower width varied but, in most years, there was still stronger selection for early flowering in granite habitats and stronger selection for larger flowers in meadow as expected ( Figure 3k, l ). Plants with more lobed leaves were more likely to reproduce in granite habitat in low snowpack years, aligning with predicted species differences ( Figure 3h ). In high snowpack years, the selection was reversed with more lobed leaves being advantageous in meadow habitat ( Figure 3h ). Selection on leaf lobing also fluctuated temporally in fecundity selection, where there was often selection for more lobed leaves in meadow, but not granite, contrary to predictions. Taller plants were favorable across habitats and years but contrary to predictions there was often stronger positive selection for height in granite ( Figure 3i,n ). For herkogamy, we found selection in the direction predicted in high snowpack years (2019, 2023), with shorter stigma-anther separation associated with higher fecundity in granite and greater stigma-anther separation favorable in meadow, but reversed in the low snowpack year 2021 ( Figure 3o ). Phenotypic selection analyses where models excluded herkogamy in all years were largely similar (Figure S2). We found that these temporal fluctuations in phenotypic selection were statistically associated with variation in snowpack. In meadow habitat, there was a significant plant height by snowpack interaction in the zero-truncated Poisson model ( p < 0.0001), and snowpack significantly interacted with both plant height and leaf lobing in the binomial analysis (both p < 0.05). In granite habitat, flowering time and flower width both had significant interactions with snowpack in the zero-truncated Poisson (both p < 0.001) while there was a plant height by snowpack interaction in the binomial model (p < 0.0001). Although we found interannual fluctuations in the strength and direction of selection on all traits, when we combined data across years, we saw long term patterns of directional selection ( Table 1 , Table 2 ; Figure 4 , Figure S3). In both zero-truncated Poisson and binomial analyses, we found long-term selection for earlier flowering time, smaller flowers, more lobed leaves and taller plants in both habitats. Selection was significantly stronger in the granite habitat for early flowering time (binomial: p < 0.0001), lobed leaf shape (Poisson: p < 0.0001), and larger plant sizes (Poisson: p < 0.0001). Therefore, while inter-annual fluctuations in the strength and direction of selection are common in this system, we still find longer-term differences in the strength of selection in the direction of species’ differences in both flowering time and leaf shape. Download figure Open in new tab Figure 4. Patterns of cumulative selection with all years combined in meadow (left) and granite (right) habitat in a zero-truncated Poisson analysis on (a,b) flowering time (days from planting), (c,d) width of first flower (mm), (e,f) leaf lobing index, and (g,h) plant height at flowering (mm to apical meristem). Y-axes show adjusted relative fitness (fruit number), statistically corrected for other variables included in the models, and the x-axes show unstandardized trait values for biological relevance. Data from 2013 and 2019 are published in Ferris and Willis 2018 and Tataru et al . 2023 and re-analyzed here. Local adaptation fluctuates temporally with long-term maladaptation of M. guttatus We found temporal fluctuation in the signature of local adaptation in both habitats. In 2013, a drought year, we found a clear signature of local adaptation in total fitness, but this was not true for other years in our study ( Figure 5 ). There was also often a difference in local adaptation between the individual components of fitness: survival and fecundity. Mimulus laciniatus had higher survival to flowering than M. guttatus in both habitats in all years, except in 2019 when there was low overall survival of parental genotypes ( Figure 5a-e ). With all five years combined, M. laciniatus had higher average survival in both habitats ( Figure 5f ). Patterns of fecundity differed between years with parental species having higher fecundity in their native habitats in 2021, like in 2013, indicating local adaptation and selection against immigrants ( Figure 5g-k ). However, in 2022, M. laciniatus had higher fecundity in both habitats ( Figure 5j ), and in 2023, we found reciprocal local maladaptation where M. guttatus had higher fecundity than M. laciniatus in granite and vice versa in meadows ( Figure 5k ). Download figure Open in new tab Figure 5. Survival to flowering (a-f), fecundity (mean seed number per reproductive individual; g-l), and total fitness (mean seed number per planted seed; m-r) of Mimulus guttatus (filled square, solid line) and M. laciniatus (open triangle, dashed line) in granite and meadow habitats, from each experimental year and the average (arithmetic mean) across years (f, l, r). Calculations of fecundity and total fitness for 2013 are based on fruit number because seed number was not recorded; 2013 was omitted from averaged fecundity and total fitness. Values from 2013 and 2019 are from Ferris and Willis 2018 and Tataru et al . 2023 . With all years combined, we found overall evidence of local maladaptation in mean fecundity ( Figure 5l ); however, removing the extreme snowpack year of 2023 reveals local adaptation in fecundity (Figure S4). A significant genotype by environment interaction GxE was detected for total fitness in every year except 2019, and for survival and total fitness when all years were combined (Table S13). Detection of GxE in survival and fecundity varied more across individual years (Table S13). For total fitness, M. laciniatus had higher fitness and home-site advantage in low snowpack years (2013, 2021, 2022; Figure 5m,o,d ), but M. laciniatus and M. guttatus performed equally well in granite during high snowpack years (2019, 2023; Figure 5n,q ). Total fitness in meadow was not as predictable based on snowpack with M. laciniatus having higher total fitness in recent years (2021-2023) but lower fitness in 2013 and 2019. Overall, M. laciniatus had higher total fitness in both habitats ( Figure 5r , Figure S4). Geometric mean fitness analyses reinforced these patterns. A single year of very low or zero fitness would drive extinction in the granite habitat in the absence of a seed bank (Figure S5), and M. laciniatus would still maintain higher geometric-mean total fitness than the native M. guttatus in meadow habitat (Figure S5). DISCUSSION In this study, we investigated spatial and temporal variation in selection on two sympatric Monkeyflower species, M. guttatus and M. laciniatus . We compared multiple large-scale replicated reciprocal transplants conducted in low (2013, 2021, 2022) and high (2019, 2023) snowpack years including one extreme year resulting in episodic selection ( Figure 1a , b). We found that key environmental variables such as soil moisture, temperature, and light intensity fluctuated over space and time, impacting fitness and phenotypic plasticity. Using experimental hybrids, we found fluctuating selection on phenotypic traits involved in reproductive isolation and microhabitat adaptation. Within each year, phenotypic selection was sometimes contrary to our predicted directions, but we saw a longer-term trend of differences in the magnitude of selection in the direction of species’ differences in both flowering time, a key reproductive isolating trait, and leaf shape. Our results also indicate that local adaptation of the parental species fluctuates across years but on average, M. guttatus is maladapted to its meadows and that habitat isolation may therefore be asymmetric and temporally dependent. Finally, we find that episodic selection, caused by an extreme snowfall event, may disrupt local adaptation and impact species boundaries. Inter-annual fluctuation in natural selection does not erase signatures of long-term divergence Temporal and spatial variation in selection has been well studied for its role in maintaining genetic variation within species ( Keep et al. 2021 ; Leidinger et al. 2021 ; Kelly 2022 ; Johnson et al. 2023 ). However, few studies have empirically tested how fluctuating selection influences the strength of reproductive isolation between sympatric species (but see Campbell and Powers 2015 ). Here, we consider this by comparing the relative strengths and direction of phenotypic selection on experimental hybrids between native Mimulus habitats and examine how these patterns changed over five repeated transplant experiments. Although there were interannual fluctuations in selection ( Figure 3 ), we detected interesting longer-term patterns aligned with species differences, particularly for leaf lobing and flowering time, a key pre-zygotic isolating barrier in the M. guttatus species complex ( Lowry et al. 2008 ; Figure 4 ). Previous studies have found that later-flowering M. guttatus tend to exhibit higher fecundity ( Mojica and Kelly 2010 ; Mojica et al. 2012 ), especially in a longer, high snowpack growing season with lowered desiccation risk. In our study, flowering time selection was negative in both habitats, yet in three out of four years with comparable phenotypic selection data between habitats, there was stronger selection for earlier flowering time in M. laciniatus’ granite habitat as predicted by species differences ( Figure 3k ). The high snowpack year of 2019 was the exception with stronger fecundity selection for early flowering in M. guttatus’ meadows than in granite habitat ( Figure 3k ), indicating a temporary relaxation of divergent selection. Selection on leaf lobing also fluctuated across years, where selection favored the direction of species differences in our binomial analyses in low snowpack years whereas in high snowpack years the direction reversed to be opposite our predictions ( Figure 3h ). This pattern of the direction of selection on leaf shape switching with snowpack is supported by the significant interaction between leaf lobing and snowpack in our across-year model (Table S7). The precise adaptive function of leaf shape variation in this system is not known but may be related to temperature or drought tolerance as leaf shape affects the leaf boundary layer and the rates of heat and gas exchange with the air (Nicotra et al. 2011). Two other rocky outcrop species in the M. guttatus complex have also evolved lobed leaves, M. filicifolius and some populations of serpentine adapted M. guttatus ( Ferris et al. 2015 ). Further, repeated altitudinal clines in leaf shape have been found in M. laciniatus populations (Love and Ferris 2023). These repeated evolutionary patterns, along with evidence of selection for lobed leaves in granite in some years, suggest that lobed leaf shape is indeed adaptive in these species, even though the direction of selection is not stable across time. Annual selection on flower width fluctuated unpredictably across years and our combined analysis revealed weak selection for smaller flowers ( Figure 3 , Figure 4 , Table 1 , Table 2 ). This runs counter to species differences as M. guttatus typically has larger flowers than M. laciniatus . Flower size affects reproductive success and can contribute to population differentiation and reproductive isolation ( Bradshaw et al. 1995 ; Brunet 2009 ; Schiestl and Schluter 2009 ; Venail et al. 2010 ; Krizek and Anderson 2013 ). Flower size is often correlated with plant size indicating that early flowering, small stature, and small flowers are linked ( Troth et al. 2018 ). Previous work has demonstrated antagonistic pleiotropy in M. guttatus where later flowering alleles also increase plant and flower size ( Mojica et al. 2012 ; Monnahan and Kelly 2015 ). Although plants with larger flowers have increased fecundity, they simultaneously reduce viability, resulting in net selection for smaller flowers ( Mojica and Kelly 2010 ). In contrast, our findings of selection for early flowering, small flowers, and larger plants in both habitats across years suggests that in our species’ these traits are genetically distinct ( Tables 1 , 2 ). Although we initially predicted selection for smaller plant sizes in granite based on M. laciniatus’s short stature, our findings suggest that larger plants always have higher fecundity. This is in line with broader evidence that body size at reproduction is a key determinant of fecundity across taxa ( Aarseen and Taylor 1992 ; Aarssen and Jordan 2001 ; Kingsolver and Pfennig 2004 ). Despite selection for larger sizes, average plant height remained smaller in granite than in meadow habitats (Table S9, Table S10, Table S11), likely reflecting ecological constraints imposed by limited water and nutrient availability in rocky outcrops. Finally, we found weak selection on herkogamy, suggesting that selection on stigma-anther separation is no longer as strong as during the earlier stages of speciation ( Harder and Johnson 2009 ). Across these traits, our combined dataset revealed longer-term differences in patterns of selection on flowering time, plant size, and leaf shape between habitats ( Table 1 , Table 2 ; Figure 4 , Figure S3). We detected stronger selection for early flowering time in granite than meadow habitat which aligns with our predictions based on species’ differences, likely contributing to temporal reproductive isolation as seen in other Mimulus species ( Hall and Willis 2006 ; Lowry et al 2008 ). This pattern of spatial variation in selection is consistent with findings from other systems; for example, Ågren et al. (2017) demonstrated that selection on flowering time varies temporally in Italian and Swedish A. thaliana populations but that overall, there is stronger selection for earlier flowering in Italy. Further, we found a distinct signature of differential selection on leaf lobing in predicted directions with positive selection for lobing in the granite outcrops, but nearly no selection on leaf shape in M. guttatus ‘s meadow habitat. Lobed leaf shape is thought to be involved in adaptation to dry, exposed habitats like M. laciniatus’s rocky outcrop environment (Nicotra et al. 2011; Ferris et al 2015 ; Ferris 2019 ) and therefore appears to be involved in habitat isolation between these species ( Ferris and Willis 2018 ; Tataru et al. 2023 ). Taken together, the signatures of divergent selection on flowering time and leaf shape across multiple transplants suggests ongoing adaptive differentiation and that fluctuating selection has not erased long-term maintenance of species boundaries ( Chapurlat et al. 2020 ). M. guttatus is locally maladapted Organisms are expected to have a fitness advantage over other genotypes in their home environment because spatial heterogeneity should favor the evolution of local adaptation ( Hastings 1983 ). However, temporal changes in environmental conditions are theorized to constrain adaptation if there are opposing selection pressures over time ( Stearns 1992 ) which may negatively impact reproductive isolation and species boundaries. We predicted that if habitat isolation is an important reproductive isolating barrier between our sympatric Mimulus , then there would be a fitness advantage of the local species in each habitat. Instead, we found that local adaptation fluctuated temporally ( Figure 5m-q ) with evidence of average local maladaptation of M. guttatus ( Figure 5r ). Annual fluctuations in snowpack were predictive of relative fitness of the parent species in granite with M. laciniatus and M. gutta tus performing equally well in high snowpack years (5n,q), but in low snowpack years the drought adapted M. laciniatus had the home-site advantage ( Figure 5m,o ,p). Although local adaptation is thought to be ubiquitous in natural populations ( Hereford 2009 ), fitness trade-offs are not always found in reciprocal transplants ( Bennett and Lenski 2007 ; Lowry et al. 2009 ). For example, in his classic metanalysis Hereford (2009) found evidence of weak trade-offs associated with adaptation of populations suggesting that local adaptation is often not costly. It is possible that our reciprocal transplant did not detect existing trade-offs due to logistical constraints or that there are weak to no fitness trade-offs associated with adaptation for M. laciniatus across environments ( Fry, 1996 ; Leimu & Fischer, 2008 ). It is also possible that M. guttatus lines used in the transplant were negatively affected by inbreeding depression, as a largely outcrossing species. However, this is unlikely as intrapopulation crosses and inbred lines performed similarly in the 2023 experiment (Table S3). Alternatively, an increase in dramatic interannual environmental fluctuations due to anthropogenic climate change may mean that M. guttatus is no longer at its adaptive optima. Our results could indicate an adaptive lag where, due to recent rapid climate change and increasing drought, the adaptive landscape of M. guttatus’s habitat has changed to be more M. laciniatus -like and M. guttatus ’s evolutionary response has not kept pace ( Lane et al. 2012 ; Mills et al. 2013 ; Kooyers et al. 2019 ). This pattern of adaptive lag and local maladaptation has been found in other populations of M. guttatus ( Kooyers et al. 2019 ). Over time, this could erode species boundaries by allowing colonization of M. guttatus’s meadow by M. laciniatus potentially increasing hybridization or lead to population extinction. Asymmetry in local adaptation, or a lack of trade-offs, has been found in other transplant experiments ( Hereford 2009 ; Gosden et al. 2015 ; Latreille and Pichot 2017 ; Toll and Willis 2018 ). In a repeated reciprocal transplant between serpentine and sandstone adapted populations of Leptosiphon parviflorus, Dittmar & Schemske (2023) found that while serpentine populations had a temporally consistent local fitness advantage, sandstone populations only had a local advantage in two out of four years. While stable spatial heterogeneity should favor the evolution of local adaptation, temporal fluctuation in the environment should select against local specialization and for phenotypic plasticity ( Kawecki & Ebert 2004 ). The average fitness advantage of M. laciniatus across environments could be due to adaptive plasticity, specifically adaptation to a history of environmental heterogeneity in the rocky outcrop habitat ( Ghalambor et al. 2015 ). We found that both M. guttatus and M. laciniatus exhibit plasticity in the direction of the local species’ phenotype in each habitat (Table S9, Table S10, Table S11). Mimulus laciniatus’s occupation of a harsh, highly variable environment ( Figure 2 ) may have driven the evolution of adaptive plasticity ( Via and Lande 1985 ) allowing it to thrive in both habitats. However, M. guttatus was more plastic than M. laciniatus in all phenotypes except fitness indicating that plasticity is unlikely to account for M. laciniatus’s performance advantage across habitats and the lack of fitness trade-offs. Episodic selection weakens species divergence The high snowpack of 2023 delayed the onset of spring in mid to high elevations by 4–6 weeks and altered soil moisture, light intensity, and surface temperature regimes ( Figure 2 ). This shift contributed to local maladaptation between parental species ( Figure 5j ), as signatures of local adaptation in fecundity reappeared when 2023 was excluded (Figure S2). In M. guttatus’s meadow habitat, the delay was detrimental to hybrids and M. guttatus by delaying flowering phenology and reducing fitness. Additionally, no local meadow genotypes flowered before snowfall, suggesting negative impacts on native populations. However, many individuals remained alive at the first snowfall indicating potential facultative perenniality. Delayed flowering may have resulted from shorter day lengths failing to meet critical photoperiod thresholds ( Friedman and Willis 2013 ; Fishman et al. 2014 ; Kenney and Sweigart 2016 ), the absence of end-of-season drought stress due to persistently high soil moisture ( Kooyers et al. 2015 ; Mantel and Sweigart 2019 ), and unusually low light intensity ( Figure 2 ). In contrast, M. laciniatus was less affected, likely because it flowers rapidly under shorter daylengths ( Friedman and Willis 2013 ; Ferris and Willis 2018 ; Love and Ferris 2024 ). In granite habitats, the delayed season in 2023 fostered unusually favorable environments for the non-native M. guttatus with high water availability, lower light intensity and surface temperatures, and a longer growing season than is typical in granite ( Figure 2 ). This led to higher M. guttatus survival in granite (12% of total planted; 24 individuals) compared to previous years (0-2% of total planted). Although M. guttatus still had lower survival than M. laciniatus , it had remarkably high fecundity ( Figure 5e,k ) producing total fitness comparable to M. laciniatus for the first time ( Figure 5q ). Unlike the meadow habitat, all plants had senesced and many set seed before snowfall. This suggests that drought stress, rather than photoperiod, is more important as a flowering cue in M. lacinaitus’s habitat. High-elevation populations of M. laciniatus may also possess increased plasticity in critical photoperiod ( Love and Ferris 2024 ). Our results demonstrate how extreme climatic events may disrupt species boundaries. The atypical conditions of 2023 produced unusually strong selection opposite of predicted directions on key traits involved in adaptation and reproductive isolation: flowering time, flower size and leaf lobing ( Figure 3 ). In the long term, such episodic selection may shift parental ranges, promote hybrid swarms or a new hybrid species ( Grant and Grant 1993 ), or alter adaptive potential ( Campbell-Staton et al. 2017 ). The rarity and unpredictability of extreme climatic events complicate predictions about the evolutionary response to climate change. More longitudinal field studies are needed to understand long-term evolutionary consequences of extreme climatic events and changing climatic patterns on plant species on their native ranges ( Anderson 2016 ; Bailey and van de Pol 2016 ). For instance, do these events drive evolutionary change and does this outweigh selection acting during ‘normal’ periods? For species with limited ranges, such as the Sierra Nevada endemic M. laciniatus , will these events influence extinction risk of populations? Conclusions Our repeated reciprocal transplants reveal how fluctuating selection influences species’ boundaries. The foreign advantage of M. laciniatus in the non-native meadow habitat across years suggests either low adaptation costs to the granite habitat or recent maladaptation of M. guttatus due to environmental shifts. Furthermore, longer-term divergent selection on flowering time and leaf shape should reinforce temporal and habitat isolation between these species. However, the lack of consistent divergent selection on other key traits could lead to eventual species fusion. Finally, a bout of episodic natural selection due to extreme snowfall shifted population dynamics with potential long-term impacts on species’ range, abundance, and gene flow. Our study illustrates the strength of integrating field experiments across multiple spatial and temporal scales to gain a deeper understanding of the maintenance of biodiversity under environmental change ( Wadgymar et al. 2017 ; Dittmar and Schemske 2023 ; Oakley et al. 2023 ). COMPETING INTERESTS None declared. DATA AVAILABILITY STATEMENT The data that support the findings of this study will be openly available in [repository name] at http://doi.org/[doi], reference number [reference number], upon acceptance of the manuscript. Supplementary Information Download figure Open in new tab Download figure Open in new tab Fig S1 Density histograms of hybrid and parental values for phenotypic traits in 2021, 2022, and 2023. Download figure Open in new tab Fig S2 Visual representation of selection gradients (β) of phenotypic traits measured for hybrids during experimental years in granite (open circles) and meadow (filled circles) habitats. The models do not include herkogamy. Shown are values from (f-j) binomial models and (k-o) zero-truncated Poisson models. Significance is indicated with asterisks (* p < 0.05, ** p < 0.01, *** p < 0.001) and negative graph areas are shaded grey for clarity. All β values are based on seed number, except for values from 2013 which are based on fruit number, as seed number was not recorded. Data from 2013 and 2019 are published in Ferris and Willis 2018 and Tataru et al . 2023 and re-analyzed here. Download figure Open in new tab Fig S3 Patterns of cumulative selection with all years combined in meadow and granite habitats in a binomial analysis. Download figure Open in new tab Fig S4 Combined survival to flowering, fecundity, and total fitness excluding 2023. Download figure Open in new tab Fig S5 The average (geometric mean) of a) survival, b) fecundity, and c) total fitness across experimental years for Mimulus guttatus (filled square, solid line) and M. laciniatus (open triangle, dashed line) in granite and meadow habitats. 2013 was omitted from averaged fecundity and total fitness. Values from 2013 and 2019 are from Ferris and Willis 2018 and Tataru et al . 2023 . View this table: View inline View popup Download powerpoint Table S1 Hybrid genotypes and generations used each experimental year, with sample sizes of each genotype planted at each site with total experimental sample sizes. View this table: View inline View popup Download powerpoint Table S2 Intrapopulation parental crosses used in the 2023 experiment. View this table: View inline View popup Download powerpoint Table S3 Hybrid trait correlations in meadow and granite habitats for 2021-2023. View this table: View inline View popup Download powerpoint Table S4 Binomial analysis on whether or not a plant produced fruits. View this table: View inline View popup Download powerpoint Table S5 Zero-truncated Poisson analysis on number of fruit produced if any were produced. View this table: View inline View popup Download powerpoint Table S6 Strength of correlations between fruit number and seed number. View this table: View inline View popup Download powerpoint Table S7. Summary of models described in methods. View this table: View inline View popup Download powerpoint Table S8 Model selection for best fit models of plant survival and environmental variables. View this table: View inline View popup Download powerpoint Table S9 Trait means, standard error, standard deviation, and coefficient of variation from 2021. View this table: View inline View popup Download powerpoint Table S10 Trait means, standard error, standard deviation, and coefficient of variation from 2022. View this table: View inline View popup Download powerpoint Table S11. Trait means, standard error, standard deviation, and coefficient of variation from 2023. View this table: View inline View popup Download powerpoint Table S12. Generalized linear mixed models examining phenotypic plasticity between years and habitat. Models included the phenotypic trait as the dependent variable, habitat and year with their interaction as fixed effects and block nested within site as a random effect. View this table: View inline View popup Table S13. Significance of genotype (G), environment (E), and genotype by environment (GxE) interactions for each fitness term. Footnotes Major revisions of statistical analyses including survival and environmental variables, herbivory, phenotypic plasticity, phenotypic selection. REFERENCES ↵ Aarseen , L. W. , and D. R. Taylor . 1992 . Fecundity allocation in herbaceous plants . Oikos 65 : 225 – 232 . OpenUrl CrossRef Web of Science ↵ Aarssen , L. W. , and C. Y. Jordan . 2001 . Between-species patterns of covariation in plant size, seed size, and fecundity in monocarpic herbs . Ecoscience 8 : 471 – 477 . OpenUrl ↵ Ågren , J. , C. G. Oakley , S. Lundemo , and D. W. Schemske . 2017 . Adaptive divergence in flowering time among natural populations of Arabidopsis thaliana : Estimates of selection and QTL mapping . Evolution 71 : 550 – 564 . OpenUrl CrossRef PubMed ↵ Anderson , J. T . 2016 . Plant fitness in a rapidly changing world . New Phytologist 210 : 81 – 87 . OpenUrl CrossRef PubMed ↵ Anderson , J. T. , V. M. Eckhart , and M. A. Geber . 2015a . Experimental studies of adaptation in Clarkia xantiana: III: Phenotypic selection across a subspecies border . Evolution 69 : 2249 – 2261 . OpenUrl CrossRef PubMed Anderson , J. T .. 2015b . Experimental studies of adaptation in Clarkia xantiana: III: Phenotypic selection across a subspecies border . Evolution 69 : 2249 – 2261 . OpenUrl CrossRef PubMed ↵ Anderson , J. T. , and S. M. Wadgymar . 2020 . Climate change disrupts local adaptation and favours upslope migration . Ecology Letters 23 : 181 – 192 . OpenUrl CrossRef PubMed Anderson , J. T. , J. H. Willis , and T. Mitchell-Olds . 2011 . Evolutionary genetics of plant adaptation . Trends in Genetics 27 : 258 – 266 . OpenUrl CrossRef PubMed Web of Science ↵ Awadalla , P. , and K. Ritland . 1997 . Microsatellite variation and evolution in the Mimulus guttatus species complex with contrasting mating systems . Molecular Biology and Evolution 14 : 1023 – 1034 . OpenUrl CrossRef PubMed Web of Science ↵ Bailey , L. D. , and M. van de Pol . 2016 . Tackling extremes: Challenges for ecological and evolutionary research on extreme climatic events . Journal of Animal Ecology 85 : 85 – 96 . OpenUrl PubMed ↵ Bartoń , K. 2018 . MuMIn: Multi-Model Inference . R package version 1.42.1. https://CRAN.R-project.org/package=MuMIn . ↵ Bates , D. , M. Mächler , B. M. Bolker , and S. C. Walker . 2015 . Fitting linear mixed-effects models using lme4 . Journal of Statistical Software 67 : 1 – 48 . OpenUrl CrossRef ↵ Bennett , A. F. , and R. E. Lenski . 2007 . An experimental test of evolutionary trade-offs during temperature adaptation . Proceedings of the National Academy of Sciences of the United States of America 104 : 8649 – 8654 . OpenUrl Abstract / FREE Full Text ↵ Bradshaw , H. D. , S. M. Wilbert , K. G. Otto , and D. W. Schemske . 1995 . Genetic mapping of floral traits associated with reproductive isolation in monkeyflowers (Mimulus) . Nature 376 : 762 – 765 . OpenUrl CrossRef Web of Science ↵ Breheny , P. , and W. Burchett . 2017 . Visualization of Regression Models Using visreg . The R Journal 9 : 56 – 71 . OpenUrl ↵ Brooks , M. E. , K. Kristensen , K. J. van Benthem , A. Magnusson , C. W. Berg , A. Nielsen , H. J. Skaug , et al. 2017 . Modeling Zero-Inflated Count Data With glmmTMB . bioRxiv preprint. bioRxiv . ↵ Brunet , J . 2009 . Pollinators of the Rocky Mountain columbine: Temporal variation, functional groups and associations with floral traits . Annals of Botany 103 : 1567 – 1578 . OpenUrl CrossRef PubMed ↵ Campbell , D. R. , and J. M. Powers . 2015 . Natural selection on floral morphology can be influenced by climate . Proceedings of the Royal Society B: Biological Sciences 282 . ↵ Campbell-Staton , S. C. , Z. A. Cheviron , N. Rochette , J. Catchen , J. B. Losos , and S. V. Edwards . 2017 . Winter storms drive rapid phenotypic, regulatory, and genomic shifts in the green anole lizard . Science 357 : 495 – 498 . OpenUrl Abstract / FREE Full Text ↵ Chapurlat , E. , I. Le Roncé , J. Ågren , and N. Sletvold . 2020 . Divergent selection on flowering phenology but not on floral morphology between two closely related orchids . Ecology and Evolution 10 : 5737 – 5747 . OpenUrl ↵ Coltman , D. W. , J. A. Smith , D. R. Bancroft , J. Pilkington , A. D. C. MacColl , T. H. Clutton-Brock , and J. M. Pemberton . 1999 . Density-dependent variation in lifetime breeding success and natural and sexual selection in Soay rams . American Naturalist 154 : 730 – 746 . OpenUrl CrossRef PubMed Web of Science ↵ Coyne , J. A. , and H. A. Orr . 2004 . Speciation. Sinauer Associates. Sinauer Associates, Sunderland , Massachusetts . ↵ Crespi , B. J . 2000 . The evolution of maladaptation . Heredity 84 : 623 – 629 . OpenUrl CrossRef PubMed Web of Science ↵ DeMarche , M. L. , K. J. Rice , and J. P. Sexton . 2013 . Niche partitioning between close relatives suggests trade-offs between adaptation to local environments and competition . Ecology and Evolution 3 : 512 – 522 . OpenUrl ↵ Dittmar , E. L. , and D. W. Schemske . 2023 . Temporal Variation in Selection Influences Microgeographic Local Adaptation . American Naturalist 202 : 471 – 485 . OpenUrl CrossRef PubMed ↵ Ferris , K. G . 2019 . Endless forms most functional: uncovering the role of natural selection in the evolution of leaf shape . American Journal of Botany 106 : 1532 – 1535 . OpenUrl PubMed Ferris , K. G. , L. L. Barnett , B. K. Blackman , and J. H. Willis . 2017a . The genetic architecture of local adaptation and reproductive isolation in sympatry within the Mimulus guttatus species complex . Molecular Ecology 26 : 208 – 224 . OpenUrl CrossRef Ferris , K. G. , L. L. Barnett , B. K. Blackman , and J. H. Willis . 2017b . The genetic architecture of local adaptation and reproductive isolation in sympatry within the Mimulus guttatus species complex . Molecular Ecology 26 : 208 – 224 . OpenUrl CrossRef ↵ Ferris , K. G. , T. Rushton , A. B. Greenlee , K. Toll , B. K. Blackman , and J. H. Willis . 2015 . Leaf shape evolution has a similar genetic architecture in three edaphic specialists within the Mimulus guttatus species complex . Annals of Botany 116 : 213 – 223 . OpenUrl CrossRef PubMed ↵ Ferris , K. G. , J. P. Sexton , and J. H. Willis . 2014 . Speciation on a local geographic scale: The evolution of a rare rock outcrop specialist in Mimulus . Philosophical Transactions of the Royal Society B: Biological Sciences 369 : 27 – 29 . OpenUrl ↵ Ferris , K. G. , and J. H. Willis . 2018 . Differential adaptation to a harsh granite outcrop habitat between sympatric Mimulus species . Evolution 72 : 1225 – 1241 . OpenUrl CrossRef PubMed ↵ Fishman , L. , A. L. Sweigart , A. M. Kenney , and S. Campbell . 2014 . Major quantitative trait loci control divergence in critical photoperiod for flowering between selfing and outcrossing species of monkeyflower (Mimulus) . New Phytologist 201 : 1498 – 1507 . OpenUrl CrossRef PubMed ↵ Friedman , J. , and J. H. Willis . 2013 . Major QTLs for critical photoperiod and vernalization underlie extensive variation in flowering in the Mimulus guttatus species complex . New Phytologist 199 : 571 – 583 . OpenUrl CrossRef PubMed ↵ Fry , J. D . 1996 . The Evolution of Host Specialization: Are Trade-Offs Overrated? The American Naturalist 148 : S84 – S107 . OpenUrl CrossRef Web of Science Galen , C . 2000 . High and dry: Drought stress, sex-allocation trade-offs, and selection on flower size in the alpine wildflower Polemonium viscosum (Polemoniaceae) . American Naturalist 156 : 72 – 83 . OpenUrl CrossRef PubMed Web of Science ↵ Ghalambor , C. K. , K. L. Hoke , E. W. Ruell , E. K. Fischer , D. N. Reznick , and K. A. Hughes . 2015 . Non-adaptive plasticity potentiates rapid adaptive evolution of gene expression in nature . Nature 525 : 372 – 375 . OpenUrl CrossRef PubMed ↵ Gosden , T. P. , J. T. Waller , and E. I. Svensson . 2015 . Asymmetric isolating barriers between different microclimatic environments caused by low immigrant survival . Proceedings of the Royal Society B: Biological Sciences 282 . ↵ Grant , B. R. , and P. R. Grant . 1993 . Evolution of Darwin’s Finches Caused by a Rare Climatic Event . Proceedings of the Royal Society B: Biological Sciences 251 : 111 – 117 . OpenUrl CrossRef ↵ Groh , J. S. , and G. Coop . 2024 . The temporal and genomic scale of selection following hybridization . Proceedings of the National Academy of Sciences of the United States of America 121 : 1 – 11 . OpenUrl CrossRef PubMed ↵ Hall , M. C. , and J. H. Willis . 2006 . Divergent Selection on Flowering Time Contributes To Local Adaptation in Mimulus Guttatus Populations . Evolution 60 : 2466 . OpenUrl CrossRef PubMed Web of Science ↵ Harder , L. D. , and S. D. Johnson . 2009 . Darwin’s beautiful contrivances: evolutionary and functional evidence for floral adaptation . New Phytologist 183 : 530 – 545 . OpenUrl CrossRef PubMed Web of Science ↵ Hastings , A . 1983 . Can spatial variation alone lead to selection for dispersal? Theoretical Population Biology 24 : 244 – 251 . OpenUrl CrossRef Web of Science ↵ Hereford , J . 2009 . A quantitative survey of local adaptation and fitness trade-offs . American Naturalist 173 : 579 – 588 . OpenUrl CrossRef PubMed Web of Science ↵ Johnson , O. L. , R. Tobler , J. M. Schmidt , and C. D. Huber . 2023 . Fluctuating selection and the determinants of genetic variation . Trends in Genetics 39 : 491 – 504 . OpenUrl CrossRef PubMed ↵ Kawecki , T. J. , and D. Ebert . 2004 . Conceptual issues in local adaptation . Ecology Letters 7 : 1225 – 1241 . OpenUrl CrossRef Web of Science ↵ Keep , T. , S. Rouet , J. L. Blanco-Pastor , P. Barre , T. Ruttink , K. J. Dehmer , M. Hegarty , et al. 2021 . Inter-annual and spatial climatic variability have led to a balance between local fluctuating selection and wide-range directional selection in a perennial grass species . Annals of Botany 128 : 357 – 369 . OpenUrl PubMed ↵ Kelly , J. K . 2022 . The genomic scale of fluctuating selection in a natural plant population . Evolution Letters 6 : 506 – 521 . OpenUrl PubMed ↵ Kenney , A. M. , and A. L. Sweigart . 2016 . Reproductive isolation and introgression between sympatric Mimulus species . Molecular ecology 25 : 2499 – 2517 . OpenUrl CrossRef ↵ Kingsolver , J. G. , and S. E. Diamond . 2011 . Phenotypic selection in natural populations: What limits directional selection? American Naturalist 177 : 346 – 357 . OpenUrl CrossRef PubMed Web of Science ↵ Kingsolver , J. G. , and D. W. Pfennig . 2004 . Individual-level selection as a cause of cope’s rule of phyletic size increase . Evolution 58 : 1608 – 1612 . OpenUrl CrossRef PubMed Web of Science ↵ Kooyers , N. J. , J. M. Colicchio , A. B. Greenlee , E. Patterson , N. T. Handloser , and B. K. Blackman . 2019 . Lagging adaptation to climate supersedes local adaptation to herbivory in an annual monkeyflower . American Naturalist 194 : 541 – 557 . OpenUrl CrossRef PubMed ↵ Kooyers , N. J. , A. B. Greenlee , J. M. Colicchio , M. Oh , and B. K. Blackman . 2015 . Replicate altitudinal clines reveal that evolutionary flexibility underlies adaptation to drought stress in annual Mimulus guttatus . New Phytologist 206 : 152 – 165 . OpenUrl CrossRef PubMed ↵ Krizek , B. A. , and J. T. Anderson . 2013 . Control of flower size . Journal of Experimental Botany 64 : 1427 – 1437 . OpenUrl CrossRef PubMed ↵ Lande , R. , and S. J. Arnold . 1983 . The Measurement of Selection on Correlated Characters . Evolution 37 : 1210 – 1226 . OpenUrl CrossRef PubMed Web of Science ↵ Lane , J. E. , L. E. B. Kruuk , A. Charmantier , J. O. Murie , and F. S. Dobson . 2012 . Delayed phenology and reduced fitness associated with climate change in a wild hibernator . Nature 489 : 554 – 557 . OpenUrl CrossRef PubMed Web of Science ↵ Latreille , A. C. , and C. Pichot . 2017 . Local-scale diversity and adaptation along elevational gradients assessed by reciprocal transplant experiments: lack of local adaptation in silver fir populations . Annals of Forest Science 74 . ↵ Lee , G. , B. J. Sanderson , T. J. Ellis , B. P. Dilkes , J. K. McKay , J. Ågren , and C. G. Oakley . 2024 . A large-effect fitness trade-off across environments is explained by a single mutation affecting cold acclimation . Proceedings of the National Academy of Sciences 121 . ↵ Leidinger , L. , D. Vedder , and J. S. Cabral . 2021 . Temporal environmental variation may impose differential selection on both genomic and ecological traits . Oikos 130 : 1100 – 1115 . OpenUrl ↵ Leimu , R. , and M. Fischer . 2008 . A meta-analysis of local adaptation in plants . PLoS ONE 3 : 1 – 8 . OpenUrl CrossRef PubMed ↵ Levins , R . 1968 . Evolution in Changing Environments . Princeton University Press , Princeton, New Jersey . ↵ Love , J. M. , and K. G. Ferris . 2024 . Local adaptation to an altitudinal gradient: The interplay between mean phenotypic trait variation and phenotypic plasticity in Mimulus laciniatus . Perspectives in Plant Ecology, Evolution and Systematics 63 : 125795 . OpenUrl ↵ Lowry , D. B. , M. C. Hall , D. E. Salt , and J. H. Willis . 2009 . Genetic and physiological basis of adaptive salt tolerance divergence between coastal and inland Mimulus guttatus . New Phytologist 183 : 776 – 788 . OpenUrl CrossRef PubMed Web of Science ↵ Lowry , D. B. , R. C. Rockwood , and J. H. Willis . 2008 . Ecological reproductive isolation of coast and inland races of Mimulus guttatus . Evolution 62 : 2196 – 2214 . OpenUrl CrossRef PubMed Web of Science ↵ Magnusson , A. , H. J. Skaug , A. Nielsen , C. W. Berg , K. Kristensen , M. Maechler , K. J. van Bentham , et al. 2017 . glmmTMB: Generalized Linear Mixed Models using Template Model Builder . R package version 0 . 1 . 3 . OpenUrl ↵ Mantel , S. J. , and A. L. Sweigart . 2019 . Divergence in drought-response traits between sympatric species of Mimulus . Ecology and Evolution 9 : 10291 – 10304 . OpenUrl ↵ Mills , L. S. , M. Zimova , J. Oyler , S. Running , J. T. Abatzoglou , and P. M. Lukacs . 2013 . Camouflage mismatch in seasonal coat color due to decreased snow duration . Proceedings of the National Academy of Sciences of the United States of America 110 : 7360 – 7365 . OpenUrl Abstract / FREE Full Text ↵ Mojica , J. P. , and J. K. Kelly . 2010 . Viability selection prior to trait expression is an essential component of natural selection . Proceedings of the Royal Society B: Biological Sciences 277 : 2945 – 2950 . OpenUrl CrossRef PubMed Web of Science ↵ Mojica , J. P. , Y. W. Lee , J. H. Willis , and J. K. Kelly . 2012 . Spatially and temporally varying selection on intrapopulation quantitative trait loci for a life history trade-off in Mimulus guttatus . Molecular Ecology 21 : 3718 – 3728 . OpenUrl CrossRef PubMed Web of Science ↵ Monnahan , P. J. , and J. K. Kelly . 2015 . Naturally segregating loci exhibit epistasis for fitness . Biology Letters 11 . ↵ Nagy , E. S . 1997 . Selection for native characters in hybrids between two locally adapted plant subspecies . Evolution 51 : 1469 – 1480 . OpenUrl CrossRef PubMed Web of Science ↵ Nicotra , A. B. , A. Leigh , C. K. Boyce , C. S. Jones , K. J. Niklas , D. L. Royer , and H. Tsukaya . 2011a . The evolution and functional significance of leaf shape in the angiosperms . Functional Plant Biology 38 : 535 – 552 . OpenUrl PubMed Nicotra , A. B. , A. Leigh , C. K. Boyce , C. S. Jones , K. J. Niklas , D. L. Royer , and H. Tsukaya . 2011b . The evolution and functional significance of leaf shape in the angiosperms . Functional Plant Biology 38 : 535 – 552 . OpenUrl PubMed ↵ Oakley , C. G. , D. W. Schemske , J. K. McKay , and J. Ågren . 2023 . Ecological genetics of local adaptation in Arabidopsis: An 8-year field experiment . Molecular Ecology 32 : 4570 – 4583 . OpenUrl ↵ Pemberton , J. M. , L. E. B. Kruuk , and T. Clutton-Brock . 2022 . The Unusual Value of Long-Term Studies of Individuals: The Example of the Isle of Rum Red Deer Project . Annual Review of Ecology, Evolution, and Systematics 53 : 327 – 351 . OpenUrl CrossRef ↵ Pinheiro , J. , and D. Bates . 2000 . Mixed-Effects Models in S and S-PLUS . Springer , New York . Pinheiro , J. , D. Bates , and R Core Team . 2023 . nlme: Linear and Nonlinear Mixed Effects Models . R package version 3.1-163. ↵ Ramsey , J. , H. D. Bradshaw , and D. W. Schemske . 2003 . Components of reproductive isolation between the monkeyflowers Mimulus lewisii and M. cardinalis (Phrymaceae) . Evolution 57 : 1520 – 1534 . OpenUrl CrossRef PubMed Web of Science ↵ Rundle , H. D. , and P. Nosil . 2005 . Ecological speciation . Ecology Letters 8 : 336 – 352 . OpenUrl CrossRef Web of Science ↵ Schiestl , F. P. , and P. M. Schluter . 2009 . Floral isolation, specialized pollination, and pollinator behavior in orchids . Annual Review of Entomology 54 : 425 – 446 . OpenUrl CrossRef PubMed Web of Science ↵ Schluter , D . 2009 . Evidence for ecological speciation and its alternative . Science 323 : 737 – 741 . OpenUrl Abstract / FREE Full Text ↵ Schneider , C. A. , W. S. Rasband , and K. W. Eliceiri . 2012 . NIH Image to ImageJ: 25 years of Image Analysis . Nature Methods 9 : 671 – 675 . OpenUrl PubMed ↵ Siepielski , A. M. , J. D. Dibattista , and S. M. Carlson . 2009 . It’s about time: The temporal dynamics of phenotypic selection in the wild . Ecology Letters 12 : 1261 – 1276 . OpenUrl CrossRef PubMed Web of Science ↵ Stearns , S . 1992 . The evolution of life histories . Oxford University Press , Oxford, UK . ↵ Tataru , D. , M. De Leon , S. Dutton , F. Machado-Perez , A. Rendahl , and K. G. Ferris . 2024 . Fluctuating selection in a Monkeyflower hybrid zone . bioRxiv 1 – 33 . ↵ Tataru , D. , E. C. Wheeler , and K. G. Ferris . 2023 . Spatially and temporally varying selection influence species boundaries in two sympatric Mimulus . Proceedings of the Royal Society B: Biological Sciences 290 . ↵ Toll , K. , and J. H. Willis . 2018 . Hybrid inviability and differential submergence tolerance drive habitat segregation between two congeneric monkeyflowers . Ecology 99 : 2776 – 2786 . OpenUrl PubMed ↵ Troth , A. , J. R. Puzey , R. S. Kim , J. H. Willis , and J. K. Kelly . 2018 . Selective trade-offs maintain alleles underpinning complex trait variation in plants . Science 361 : 475 – 478 . OpenUrl Abstract / FREE Full Text ↵ Venail , J. , A. Dell’Olivo , and C. Kuhlemeier . 2010 . Speciation genes in the genus Petunia . Philosophical Transactions of the Royal Society B: Biological Sciences 365 : 461 – 468 . OpenUrl CrossRef PubMed ↵ Via , S. , and R. Lande . 1985 . Genotype-environment interaction and the evolution of phenotypic plasticity . Evolution 39 : 505 – 522 . OpenUrl CrossRef PubMed Web of Science ↵ Vickery , R. K . 1964 . Barriers to gene exchange between members of the Mimulus guttatus complex (Scrophulariaceae) . Evolution 18 : 52 . OpenUrl CrossRef Web of Science ↵ Wadgymar , S. M. , S. C. Daws , and J. T. Anderson . 2017 . Integrating viability and fecundity selection to illuminate the adaptive nature of genetic clines . Evolution Letters 1 : 26 – 39 . OpenUrl PubMed ↵ Wilczek , A. M. , M. D. Cooper , T. M. Korves , and J. Schmitt . 2014 . Lagging adaptation to warming climate in Arabidopsis thaliana . Proceedings of the National Academy of Sciences of the United States of America 111 : 7906 – 7913 . OpenUrl Abstract / FREE Full Text ↵ Willis , J . 1999 . The role of genes of large effect on inbreeding depression in Mimulus guttatus . Evolution 53 : 1678 – 1691 . OpenUrl CrossRef PubMed Web of Science Wright , S. I. , S. Kalisz , and T. Slotte . 2013 . Evolutionary consequences of self-fertilization in plants . Proceedings of the Royal Society B: Biological Sciences 280 . ↵ Wu , C. A. , D. B. Lowry , A. M. Cooley , K. M. Wright , Y. W. Lee , and J. H. Willis . 2008 . Mimulus is an emerging model system for the integration of ecological and genomic studies . Heredity 100 : 220 – 230 . OpenUrl CrossRef PubMed Web of Science View the discussion thread. Back to top Previous Next Posted November 18, 2025. Download PDF Email Thank you for your interest in spreading the word about bioRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following Short-term fluctuating and long-term divergent selection on sympatric Monkeyflowers: insights from repeated reciprocal transplants Message Subject (Your Name) has forwarded a page to you from bioRxiv Message Body (Your Name) thought you would like to see this page from the bioRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share Short-term fluctuating and long-term divergent selection on sympatric Monkeyflowers: insights from repeated reciprocal transplants Caroline M. Dong , Bolívar Aponte Rolón , Juj K. Sullivan , Diana Tataru , Max De Leon , Rachael Dennis , Spencer Dutton , Fidel J. Machado Perez , Lissette Montano , Kathleen G. Ferris bioRxiv 2024.06.26.600870; doi: https://doi.org/10.1101/2024.06.26.600870 Share This Article: Copy Citation Tools Short-term fluctuating and long-term divergent selection on sympatric Monkeyflowers: insights from repeated reciprocal transplants Caroline M. Dong , Bolívar Aponte Rolón , Juj K. Sullivan , Diana Tataru , Max De Leon , Rachael Dennis , Spencer Dutton , Fidel J. Machado Perez , Lissette Montano , Kathleen G. Ferris bioRxiv 2024.06.26.600870; doi: https://doi.org/10.1101/2024.06.26.600870 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Evolutionary Biology Subject Areas All Articles Animal Behavior and Cognition (7652) Biochemistry (17752) Bioengineering (13936) Bioinformatics (42084) Biophysics (21501) Cancer Biology (18655) Cell Biology (25586) Clinical Trials (138) Developmental Biology (13410) Ecology (19949) Epidemiology (2067) Evolutionary Biology (24378) Genetics (15639) Genomics (22562) Immunology (17779) Microbiology (40505) Molecular Biology (17219) Neuroscience (88825) Paleontology (667) Pathology (2845) Pharmacology and Toxicology (4840) Physiology (7666) Plant Biology (15182) Scientific Communication and Education (2048) Synthetic Biology (4305) Systems Biology (9840) Zoology (2274)