Recovery of saltmarsh macroinfauna after the Deepwater Horizon Oil Spill

Recovery of saltmarsh macroinfauna after the Deepwater Horizon Oil Spill | 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 Recovery of saltmarsh macroinfauna after the Deepwater Horizon Oil Spill Manisha Pant, John Fleeger, David Johnson, Rita Riggio, Aixin Hou, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5582083/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 Mar, 2025 Read the published version in Estuaries and Coasts → Version 1 posted 5 You are reading this latest preprint version Abstract To examine invertebrate resiliency after the 2010 Deepwater Horizon oil spill, we monitored the recovery of macroinfauna in replicated reference, moderately and heavily oiled salt marshes in Barataria Bay Louisiana for 8.5 y after the spill. Plants suffered near 100% mortality in heavily oiled marshes, profoundly altering the sedimentary environment. Plants in moderately oiled marshes did not suffer extensive mortality but experienced reduced above- and belowground plant biomass. A community analysis based on 40 macroinfaunal taxa was conducted during early, 2011–2012, middle, 2013–2017 and late, 2017–2018, stages of recovery. The early stage was marked by very low taxonomic diversity and low total macroinfaunal abundance in all marshes, while the middle stage was denoted by relatively high diversity and very high abundances in heavily oiled marshes where densities far exceeded reference and regional means. The community in the heavily oiled marshes diverged from reference and moderately oiled marshes during the middle recovery period when the crustaceans Apocorophium louisianum and Leptochelia rapax , the polychaete Alitta succinea , and oligochaetes dramatically increased in abundance, while at the same time, abundance increases of the polychaetes Manayunkia aestuarina, Streblospio gynobrachiata , and Capitellidae sp. lagged behind increasing trends at reference and moderately oiled sites. Macroinfaunal community similarity in moderately oiled marshes differed from reference and heavily oiled marshes in all three recovery stages but did not differ from reference sites on the last collection date. Heavily oiled community similarity not only differed from moderately oiled and reference marshes in all three recovery stages but remained different from reference sites on the last collection date. These observations indicate that moderately oiled marshes recovered by about 8 years, but that heavily oiled marshes require more than a decade to achieve resiliency. macroinfauna resiliency Deepwater Horizon oil spill salt marsh Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Coastal wetlands provide critical ecosystem services throughout the world (Engle 2011 ). Human-caused oil spills threaten these valuable ecosystems. Anthropogenic oceanic releases of oil have surged tenfold over background since 1990 and are predominantly located nearshore (Dong et al. 2022 ). An extreme example followed the explosion of the Deepwater Horizon (DWH) platform in the northern Gulf of Mexico on 20 April 2010, which led to the judge-decreed release of 3.19 million barrels of crude oil over 87 days from the Macondo well (United States v. BP, 2014). Nearly 800 km of coastal wetlands in Louisiana, USA, were contaminated (Nixon et al. 2016 ). Oil residues that enter coastal wetlands are a major concern, not only because of the immediate injury to biota and the services they provide (Rabalais and Turner 2016 ), but also because fine-grained sediment, waterlogged soils, and sedimentary accretion can result in the burial of oil residues where decomposition is very slow, and subsequently, oil may resurface during storm events (Bam et al. 2018 ). Indeed, elevated total petroleum hydrocarbons have been detected consistently in DWH-impacted sites for over eight years post-spill (Deis et al. 2020 ; Turner et al. 2019 ), as has been documented in other petroleum-impacted salt marshes (Bergen et al. 2000 ; Reddy et al. 2002 ). Chronically elevated levels of petroleum hydrocarbons in coastal wetlands are a concern because they may lead to decadal-long impacts on biota (Culbertson et al. 2008a ; Culbertson et al. 2007 ; Culbertson et al. 2008b ). The responses to oiling in DWH-impacted salt marshes have been studied in a diverse array of biota over varying periods of time (Beyer et al. 2016 ; Rabalais and Turner 2016 ; Roth and Baltz 2009 ; Zengel et al. 2016a ; Zengel et al. 2022b), and results indicate a wide variation in recovery trajectories. For example, macrophytes in oiled marshes experienced a chronic, multiyear decline in above- and belowground biomass that is predicted to last longer than a decade (Zengel et al. 2022b), potentially degrading critical foundation species functions (e.g., protection against erosion, moderation of light levels reaching the sediment surface). One factor that influenced this long-term effect was variation in the recovery rates of the two regionally dominant macrophyte species as Spartina alterniflora began to regrow after near complete mortality in heavily oiled sites by 18–24 mo post spill while revegetation by Juncus roemerianus was minimal after almost nine years (Lin et al. 2016 ; Zengel et al. 2022b). Similarly, densities of meiofauna, including juvenile bivalves, amphipods, ostracods, juvenile gastropods, the polychaete Manayunkia aestuarina and the kinorhynch Echinoderes coulli , remained depressed 42 months after the spill in heavily oiled compared with reference marshes, although many other taxa (e.g., nematodes and benthic copepods) recovered relatively rapidly (~ 2–3 years) (Fleeger et al. 2015 ; Fleeger et al. 2018 ). Recovery of macroinvertebrates also varied, e.g., the greenhead horsefly, Tabanus nigrovittatus recovered by five years (Husseneder et al. 2018 ), and fiddler crabs were affected up to four years (Zengel et al. 2016b ). On the contrary, periwinkle snail, Littoraria irrorata , density and size structure had not recovered completely at oiled sites almost nine years post-spill (Deis et al. 2020 ), and amphipods in heavily oiled marshes increased greatly in densities from near zero values but were not considered recovered because densities in heavily oiled marshes far exceeded regional and companion reference means 7 years post-spill (Fleeger et al. 2020 ). These chronic impacts on macrophytes and invertebrates as well as impacts on benthic microalgal biomass (Fleeger et al. 2015 ), decomposers (Cagle et al. 2024 ; Formel et al. 2022 ), the macrophyte microbiome (Lumibao et al. 2018 ), and the reduced trophic niche width observed in seaside sparrows at oiled sites (Moyo et al. 2021 ) suggest significant alterations of ecological function in oiled marshes. Macroinfauna, such as polychaetes and amphipods, are important consumers among the saltmarsh benthos. They facilitate nutrient cycling and decomposition (Kristensen et al. 2014 ), graze benthic microalgae and particulate organic matter and are prey for higher trophic level shrimp and fishes (Beseres and Feller 2007 ; Fry et al. 2003 ; Nelson et al. 2019 ). Macroinfauna affects the composition of microbial communities (Lacoste et al. 2018 ), and because some microbes enhance plant growth (Bledsoe and Boopathy 2016 ), they may indirectly affect plant communities. Given these important roles and a broad range in sensitivity to environmental perturbations, macroinfauna frequently serve as indicators of marsh health, productivity, and resiliency following disturbance. Macroinfauna community analyses have long been used to assess the impacts and resiliency from hydrocarbon contamination (e.g., Reuscher et al. 2017 ; Sanders et al. 1980 ). In addition, various indices derived from macrofauna (e.g., the relative densities of the total number of polychaetes and amphipods, Dauvin et al. 2016 ), are frequently used as an indicator of ecological quality in soft sediment ecosystems contaminated by crude or refined oils. Among the adult macroinfauna in DWH-impacted salt marshes, no species-level analyses have been conducted and only total amphipod and total macroinfaunal responses have been documented for more than 6 years post-spill (Fleeger et al. 2020 ; Fleeger et al. 2022 ). The factors that drive change in benthic populations and communities after oil spills are complex and varied (Barron et al. 2020 ; Fleeger et al. 2019 ). Not only can oiling induce profound change in the environment (for example, if foundation species are disproportionately affected by oiling), but physiological tolerance to hydrocarbons varies greatly among species even in the same environment (Monteiro et al. 2019 ). Furthermore, macroinfaunal species traits such as mobility, vertical position in the sediment (i.e., surface vs subsurface dwellers), and life history/mode of reproduction may influence the ability to avoid contamination, control initial exposure to oil, or influence the rate of repopulation after an oil-induced population bottleneck. The DWH spill created a variable landscape of exposure to oil residues (Michel et al. 2013 ) as designations immediately after the spill ranged from no visible oil to heavily oiled (in which surface oil residues covered 50–100% of the sediment with thicknesses of ~ 1 cm, Zengel et al. 2015 ). Plant mortality was very high in areas that experienced the heaviest oiling, and many environmental factors were immediately altered in the absence of foundation species (Cagle et al. 2020 ; Fleeger et al. 2019 ). Over time and as recovery progressed, heavily oiled marshes revegetated, and environmental factors continued to change. Marshes categorized as moderately oiled experienced injuries to plants without significant mortality and oiling-induced environmental changes occurred but were less striking. Here we examine longer term recovery and resiliency of the community of macroinfauna within these changing environments by comparing recovery in moderately oiled marshes with recovery in areas that were heavily oiled. We hypothesized that macroinfaunal communities at these oiled marshes would not differ from reference marshes after 8.5 years post-spill. Materials and Methods An oiling effects and recovery assessment following the DHW was conducted at various sites in the microtidal intertidal zone within 3 m of the open shoreline in northern Barataria Bay, Louisiana, USA. Such marsh edge environments are known to be biologically diverse (Baltz et al. 1993 ) and to modify surrounding environmental conditions (Kawaida et al. 2024 ). We established sites with the explicit objective of determining effects and recovery of biota exposed to different oiling intensities. Sites were located over an area 8 km x 5 km, between coordinates N 29.44060°–29.47459°, W 89.88492°–89.94647° and were assigned to three oiling categories (Lin et al. 2016 ). These sites were partially interspersed and randomly stratified, where seven showed no visible oiling and were designated “companion reference” (RF), seven were “moderately oiled” (MD) and seven were “heavily oiled” (HV). Because oil was primarily transported into the bay by south and southeastern winds, heavily oiled sites generally occurred on south- and southeast-facing shorelines, while moderately oiled sites generally occurred on adjacent tangential shorelines (Cagle et al. 2024 ). Companion reference sites were located along north- and south-facing shorelines ~ 0.5–4 km from oiled stations. Barataria Bay typically experiences high rates of shoreline retreat due to wind and wave action (Deis et al. 2019 ), and oiling has been shown to increase erosion of the marsh surface (Lin et al. 2016 ; Zengel et al. 2022a ). Three heavily oiled sites experienced severe shoreline retreat by 6-y after the spill and were relocated to immediately adjacent areas with the same oiling zone (subsequent total petroleum hydrocarbon measurements revealed similar values at these sites compared to heavily oiled sites that were not eroded away). Maps showing the sampling site locations are available in several publications, e.g., Cagle et al. ( 2024 ). The macroinfaunal community was sampled at approximately 6-mo intervals on 16 occasions from 1.5 (18 mo) to 8.5 y (102 mo) after the spill. Macroinfauna were sampled with a hand-held corer (inner diameter = 3.5 cm). Two cores were taken to a depth of 2 cm at haphazardly selected locations at each site, and both cores were combined into a single sample cup and fixed in 4% formalin. Sample cups were shaken to break up soil clumps and to ensure complete mixing of sample and formalin. Formalin was replaced and a solution of Rose Bengal was added after ~ 24 h. Prior to sorting, samples were rinsed through a 0.5-mm sieve. A stereo-dissecting microscope was used to identify and enumerate fauna to the lowest possible taxon. Density was standardized to the number of individuals m − 2 based on the corer diameter. Data Analysis Samples from our biannual collections were merged across different time periods for data exploration and statistical analysis. Samples from all collections within each calendar year (from 2011–2018 with 21–63 core samples per year) were combined to create plots of the number of taxa, the densities of total macroinfauna and most abundant individual species, as well as the densities of the sum total of polychaetes and amphipods over time. Based on these plots (Fig. 1 ) and on a previous analysis of the abundance of total macroinfauna and amphipods (Fleeger et al. 2020 ), statistical analyses of the macroinfaunal community were conducted to quantify recovery trajectories by categorizing samples into three time periods. The early recovery period was designated from 18–30 mo (2011–2012, 62 core samples) post-spill during which time the diversity and abundance increased steadily, a middle period was designated from 36–85 mo (2013–2017, 210 core samples) when diversity reached consistently high levels while density was highly variable with highest abundances at HV, and a late period was designated from 90–102 mo (2017–2018, 63 core samples) when diversity declined and densities in oiled sites were lower and more consistently similar to RF. A total of 40 sediment-dwelling taxa was defined as the macroinfaunal community. Non-metric Multidimensional Scaling (nMDS) was conducted to compare communities at 18–30, 36–85 and 90–102 mo post-spill and among oiling categories using Package Vegan (version 2.6–6.1, Oksanen et al. 2024 ) in statistical software R (version 4.4.0; R Core Team 2024 ). The nMDS was based on a distance matrix calculated using Bray-Curtis dissimilarity index on community data that were first standardized using Hellinger transformation. For clarity, we show only the centroids for each recovery period-oil level group. A similar analysis was conducted on samples from the final collection date, 102 mo post-spill, to compare macrofaunal communities across the oiling categories. For these samples, we used log transformation because this transformation resulted in the lowest stress value. Analysis of Similarity (ANOSIM) was used in a 2-way crossed design with replication to test for community differences among the three recovery periods and oiling categories using PRIMER software (Clarke & Gorley 2006 ). A separate one-way ANOSIM was conducted on the last collection date to compare faunal similarity among the oiling categories. Results Annelids and crustaceans were the most abundant and diverse taxa. Overall, 12 species of polychaetes (and oligochaetes as a single taxon) and 11 crustacean taxa were identified (Table 1 ). The polychaetes Manayunkia aestuarina (which comprised 18.1% of the total macroinfauna across all samples), Alitta succinea (7.9%), Polydora cornuta ( 5.2% ), Boccardia hamata (3.8%), Capitellidae sp. (2.1%), and Streblospio gynobrachiata (2.0%), and Oligochaeta (14.8%) were the most common and abundant annelids. The amphipod Apocorophium louisianum (28.5%) was the most abundant crustacean overall followed by the tanaid, Leptochelia rapax (11.3%). The diversity and abundance of total macroinfauna were at near zero values in HV marshes in 2011 (Fig. 1 ) and were at their lowest values across time in MD and RF marshes. Only one species, M. aestuarina , was found with one specimen in 3 of the 7 HV samples in 2011. Among oiling categories, macroinfauna richness (expressed as the number of taxa per core) increased from means of < 1–4 in 2011 to 7–8 in 2015–2017. The mean abundance of total macroinfauna in 2011 was 7874 (± 2251 standard error) at RF, 2773 (± 667) m − 2 at MD and 222 m − 2 (± 105) at HV. Abundances in all oiling categories then steadily increased and peaked in 2015 at MD and 2016 at RF and HV. Compared to densities in 2011, peak densities at RF and MD were 10–25 x higher and 2 orders of magnitude higher at HV. The pattern of temporal changes in the densities of the sum total of polychaetes and amphipods was similar in our companion reference marshes as well as oiled sites (Fig. 2 ). Amphipod density in all oiling categories, including RF, remained very low, below about 1000 m − 2 , in the early recovery period but increased to peaks between 10,000–60,000 m − 2 in 2015–2016. Polychaete density increased earlier (beginning in about 2013) than amphipods and steadily from their lowest values in 2011 in all oiling categories with peak densities of about 25,000 m − 2 at MD and RF in 2015–2016. Polychaete density at HV averaged from 15,000–20,000 m − 2 between 2013–2018 (Fig. 2 ). The relative abundance of polychaetes and amphipods varied over time primarily because of the large increases in amphipods that took place in 2016–2017. Table 1 Percentage of each taxon (%), mean (x̅, number m −2 ) and standard error (st) of the most abundant species within each oiling level and across time after the DWH spill. The percentage for each taxon of all macroinfauna for each oiling level and time period is given as % of fauna. 18–30 mo post-spill M. aestuarina S. gynobrachiata A. succinea Capitellidae sp. Oligochaeta A. louisianum L. rapax % of fauna HV % 8.6 13.2 4.0 4.0 27.6 6.9 4.6 69.0 x̅ 371.4 569.5 173.3 173.3 1188.6 297.1 198.1 St 548.9 1979.5 474.7 342.3 2106.8 1146.0 687.4 MD % 7.8 4.9 9.6 5.8 9.4 17.4 25.3 80.3 x̅ 910.0 572.0 1118.0 676.0 1092.0 2028.0 2938.0 St 1839.4 1261.4 2005.3 1054.9 1563.6 6159.4 8075.7 RF % 30.7 2.4 8.3 13.4 16.6 5.2 13.4 90.0 x̅ 2203.8 173.3 594.3 965.7 1188.6 371.4 965.7 St 3136.9 342.3 1189.0 1398.1 1595.5 660.7 1605.2 36–85 mo post-spill M. aestuarina P. cornuta A. succinea Oligochaeta A. louisianum L. rapax HV % 8.0 6.8 11.8 16.2 39.9 9.3 91.9 x̅ 3885.1 3298.3 5749.7 7896.6 19492.6 4531.4 St 16440.9 6796.6 5849.0 11387.2 55818.1 8928.9 MD % 30.5 2.3 6.2 14.3 19.8 10.4 83.5 x̅ 7406.3 564.6 1500.6 3476.6 4798.9 2518.3 St 18168.3 1841.7 2109.1 5128.3 18344.5 5660.9 RF % 32.7 3.8 1.7 14.6 18.9 14.2 85.9 x̅ 11900.6 1381.7 609.1 5296.6 6886.3 5162.9 St 19391.6 4147.6 885.2 6950.8 22559.2 7221.3 90–102 mo post-spill M. aestuarina P. cornuta B. hamata A. succinea Oligochaeta A. louisianum L. rapax HV % 1.0 7.2 9.6 15.1 13.3 35.6 11.4 93.2 x̅ 421.0 2971.4 3937.1 6215.2 5472.4 14683.8 4704.8 St 690.2 4256.8 5780.1 5676.0 10004.6 26166.3 6736.9 MD % 10.8 4.6 8.6 14.4 8.7 28.5 8.9 84.5 x̅ 1931.4 817.1 1535.2 2575.2 1560.0 5101.0 1584.8 St 6881.2 1705.5 2628.3 2239.5 1619.5 10285.8 2299.1 RF % 11.9 7.4 13.1 3.6 15.0 29.6 9.7 90.3 x̅ 3689.5 2302.9 4061.0 1114.3 4655.2 9186.7 3021.0 St 7956.0 6952.4 9932.7 1368.8 7109.9 23155.7 4033.3 There was substantial variation in the recovery trajectories of individual taxa among oiling categories. Four taxa, A. louisianum , A. succinea , L. rapax and oligochaetes primarily contributed to post-spill increases at HV with highest densities in 2016 and 2017, ranging from 3–5 times greater than RF at the same period (Fig. 3 ). Densities for these taxa in MD did not display strong peaks over time and values were more similar to those in RF. However, three taxa, M. aestuarina , S. gynobrachiata , Capitellidae sp., at HV remained at very low abundances over time at HV (50–75% lower than RF; Table 1 and Fig. 4 ). Densities of these species at MD more closely tracked variations at RF. The nMDS centroid plot shows that samples from all three oiling categories during the early recovery period were loosely clustered along with RF samples from the middle period (left side, Fig. 5 ). RF during the late period did not cluster with any other oiling category or time period (lower middle, Fig. 5 ). Samples from MD and HV for the middle and late periods were loosely clustered (right side, Fig. 5 ). Two-way crossed ANOSIM revealed that there were significant differences in similarities among all oiling categories and across the three recovery periods (Table 2 , p values ≤ 0.005). Table 2 Results of 2-way crossed ANOSIM conducted on the three recovery periods and oiling categories. Comparison R Statistic p value HV, MD 0.147 0.001 HV, RF 0.217 0.001 MD, RF 0.084 0.001 18–30, 36–85 mo 0.36 0.001 18–30, 90–102 mo 0.293 0.001 36–85, 90–102, mo 0.1 0.005 The nMDS plot for samples taken on the final collection date, 102 mo after the spill, placed HV samples mostly on one side (left side, Fig. 6 ), and RF samples were mostly on another side (lower and right side, Fig. 6 ). Samples from MD tended to be intermediate between both RF and HV samples. Corresponding ANOSIM indicated that similarities between HV and MD (p = 0.473) and similarities between MD and RF (p = 0.170) did not differ. However, HV and RF similarities significantly differed (p = 0.003). Discussion Ecological resilience is defined as the capacity of a community to absorb and recover from disturbance without affecting the function and stability of the community or broader ecosystem (McCloy et al. 2022 ). Our results show that resiliency of the macroinfaunal community following the DWH was dependent on both oiling intensity and time. The community in heavily oiled marshes differed from our companion reference sites throughout the study period when grouped into early, middle, and late recovery periods (Table 2 ). Furthermore, the community in heavily oiled marshes remained significantly different than our reference marshes on our last collection date, 8.5 years post-spill. The finding that macroinfauna at these heavily oiled sites will likely take longer than a decade to recover is comparable to findings from the same study sites for macrophyte and microbial communities as well as the periwinkle snail population (Cagle et al. 2024 ; Deis et al. 2020 ; Zengel et al. 2022b). The community in the moderately oiled marshes, with more modest but measurable oiling effects on macrophytes (Lin et al. 2016 ), also differed from reference marshes in each of the three recovery periods but did not differ from reference marshes 8.5 years post-spill suggesting that resiliency was achieved after about 8 years. A similar distinction between the microbial communities at heavily and moderately oiled marshes from the same study sites and time frame was shown by Cagle et al. ( 2024 ) as microbial indicator species known to respond to chronic oil contamination were significantly more common at heavily than moderately oiled sites. The recovery trajectories of individual species also strongly depended on oiling intensity. Although species composition in 2011 was similar in all three oiling categories (Fig. 5 ), the community in heavily oiled marshes diverged from moderately oiled and reference marshes during the middle recovery period when A. louisianum , A. succinea , L. rapax and oligochaetes dramatically increased in abundance (Fig. 3 ), while at the same time, abundance increases of M. aestuarina , S. gynobrachiata , and Capitellidae sp. in heavily oiled marshes lagged behind increasing trends in moderately oiled and reference marshes (Fig. 4 ). Not only did peak densities in heavily oiled marshes (Table 1 , Fig. 3 ) exceed those at our companion reference sites, densities were also much higher than would be expected based on regional averages. Baumann et al. ( 2020 ) and Fleeger et al. ( 2020 ) conducted meta-analyses of the densities of total macroinfauna and amphipods in the Gulf of Mexico marsh edge environment and estimated mean densities of 28,000 (± 5838) m − 2 for total macroinfauna and 1300 (± 180) m − 2 for amphipods respectively; peak values in heavily oiled marshes for macroinfauna were 100,000 (± 33,000) m − 2 and 60,000 (± 2900) m − 2 for amphipods. At moderately oiled sites, most taxa, including all polychaetes and amphipods (Fig. 2 ) and the species that failed to recover in heavily oiled marshes (Fig. 4 ), tended to change over time in concert with variation in reference marshes. Also, abundance peaks at moderately oiled sites for individual species were much lower than at heavily oiled marshes and more similar to patterns at reference sites. These observations suggest that ecosystem function or processes differed greatly with oiling intensity especially during the middle recovery period. The extreme oiling impacts on macrophytes in heavily oiled marshes likely contributed to a severely altered ecosystem function. The marsh edge along heavily oiled shores experienced the greatest reductions in total plant cover, total aboveground biomass, and belowground biomass and are predicted to take longer than a decade to fully recover (Zengel et al. 2022b). Our heavily oiled sites were essentially unvegetated during the early recovery period but progressively regained plant cover during the middle recovery period (Lin et al. 2016 ). The absence of vegetation (or low levels of plant biomass) at our heavily oiled sites would alter the soil environment in many ways compared to the vegetated moderately oiled and reference sites that would indirectly affect macroinfauna, e.g., by influencing dissolved organic matter, gas exchange, bulk density, and the microbial community (Kawaida et al. 2024 ). One important factor that may have contributed to high densities in heavily oiled marshes was food supply. Many macroinfaunal species consume benthic microalgae (Galván et al. 2008 ), and light reaching the sediment would be increased in the absence of vegetation (or before aboveground biomass fully recovered). Reductions in shading stimulate benthic microalgae in the vegetated marsh (DeLaune et al. 1984 ; Whipple et al. 1981 ; Whitcraft and Levin 2007 ), and benthic microalgal biomass in 2016 averaged about 4 times higher in heavily oiled compared to moderately oiled marshes during the middle recovery period (Fleeger et al. 2019 ). At the same time, the abundances of some meiofauna (Fleeger et al. 2019 ) and adult amphipods (Fleeger et al. 2022 ) were positivity correlated with microalgal biomass. Another factor potentially important to ecosystem function associated with macrophyte responses to oiling is variation in tidal currents and wave action (generated by winds and boat wakes along the microtidal shoreline). Flow velocities over unvegetated mudflats are well known to be much higher than in adjacent vegetated marshes because plant structure baffles flow (Bouma et al. 2005 ). Furthermore, heavily oiled marshes, with the loss of belowground roots and rhizomes, experienced reduced shear strength and were subject to shoreline retreat (Zengel et al. 2022a ), which may have further exposed our heavily oiled sites on the marsh edge to stronger waves, higher flow velocities and more frequent disturbance of the soil surface. In addition, fetch distances across Barataria Bay were longest at our heavily oiled sites compared to our moderately oiled and reference sites (Deis et al. 2019 ) which would also increase wave intensity. It is therefore likely that the highest flow velocities occurred in heavily oiled marshes during the middle recovery period coinciding with exceptionally high abundances. Macroinfauna are generally very sensitive to sediment dynamics such as burial or surface disturbances (often experimentally mimicked by raking, Whomersley et al. 2010 ) associated with high flow velocities. Zhou et al. ( 2024 ) found that disturbance by raking is erosive of surface sediments in mudflats and influences the mobility traits of macroinfauna such that species with fewer mobile traits are negatively impacted at high levels of erosion/disturbance while species with high mobility exhibit a greater abundance. Differences in mobility may have contributed to the lack of resiliency at our heavily oiled sites of the polychaetes M. aestuarina and S . gynobrachiata as both are tube dwellers with relatively low mobility. Furthermore, an experimental study in a related species, Manayunkia speciosa , experienced high rates of dislodgement from sediment under high flow conditions (above critical erosion velocity, Malakauskas et al. 2013 ). Alternatively, tube dwelling macroinfauna in salt marshes has been positively correlated with below-ground plant biomass (da Cunha Lana and Guiss 1992 ), and the slow recovery of roots and rhizomes in DWH heavily oiled marshes was implicated as a factor that contributed to the slow recovery of juvenile M. aestuarina (Fleeger at al. 2019). In contrast, amphipods in the Family Corophiidae, including A. louisianum , that achieved very high densities are highly mobile as adults and juveniles, and are attracted to areas with high benthic algal biomass (Sakamaki and Richardson 2009 ; Weerman et al. 2011 ). In addition, another high-density species abundant in heavily oiled marshes, A. succinea , is capable of pelagic dispersal as adults (Santos and Simon 1980 ). Our companion reference sites were selected due to the absence of visible oiling and because total petroleum hydrocarbon concentrations were significantly lower than at moderately and heavily oil sites in 2011 (Lin et al. 2016 ). However, it is unreasonable to assume that these sites were not impacted by hydrocarbon contamination from the DWH spill. Offshore oil residues from the DWH spill were driven by winds and tides through tidal passes and surged into Barataria Bay in the summer of 2010. Turner et al. ( 2019 ) reported dissolved aromatic hydrocarbon concentrations in the nearshore and bay in the late summer of 2010 that were 100 x that found in May. In addition, Turner et al. concluded that the distinction between oiled and unoiled sites became blurred over time as oil residues were redistributed with tides and storm events. Thus, oil residues, including dissolved aromatics, spread over an area much wider than was initially visibly oiled. Even relatively brief exposures to the water-soluble fraction of aromatics derived from crude oil are known to cause mortality to many infaunal groups (Indiketi et al. 2022 ; Monteiro et al. 2019 ). Our faunal data also support the hypothesis that oil spill-related effects occurred at our companion reference sites. We observed uncharacteristically low values of diversity and density in 2011 in reference marshes as the density of total macroinfauna was ~ 80% lower than expected regional values (Fleeger et al. 2020 ). Amphipods especially are well known to be intolerant (Monteiro et al. 2019 ; Scarlett et al. 2007 ; van Eenennaam et al. 2018 ; Widbom and Oviatt 1994 ) and were at near zero values at heavily oiled sites and very low at moderately oiled and reference sites in 2011. The relative abundance of polychaetes and amphipods are also suggestive of initial mortality in 2011 followed by recovery of the community as polychaetes (the more tolerant taxon), increased in abundance before amphipods (the less tolerant taxon) (Dauvin et al. 2016 ). The density of M. aestuarina , a surface-deposit feeding, tube-dwelling polychaete (Galván et al. 2011 ), that would be readily exposed to dissolved aromatic hydrocarbons from the water column was about 2000 m − 2 in 2011 in reference marshes while densities from a broad range of locations at the marsh edge are typically five times higher (Bell 1982 ; Johnson et al. 2007 ). Finally, the density of total macroinfauna at our reference sites increased to regional averages after about 3 y post-spill, a similar recovery trajectory of macroinfauna after the Prestige oil spill (Junoy et al. 2014 ). Although our companion reference sites were likely impacted, the lower levels of exposure to sediment-associated hydrocarbons compared to moderately and heavily oiled sites and the relatively rapid return to regional means suggests our reference sites can serve as standards for resiliency in the changing environment due to oiling (e.g., in an increasing erosive environment caused by oiling). The long recovery time for macroinfauna in heavily oiled marshes should not be unexpected given the profound environmental changes associated with foundational plant mortality and the slow pace of plant recovery. However, a similar slow recovery from other saltmarsh oil spills has been reported (Mendelssohn et al. 2012 ) and novel interactions (Murawski et al. 2023 ; Powers et al. 2013 ; Wiens et al. 2001 ) and unexpected indirect ecological effects are commonly reported after oil spills (Fleeger et al. 2022 ; Henkel et al. 2012 ; Lewis et al. 2020 ; Peterson 2001 ) that could further impede resiliency. Although the residence time of hydrocarbons buried in saltmarsh soils is measurable in decades, along with continuing effects on saltmarsh fauna (Culbertson et al. 2007 ), our results suggest that it is unlikely that macroinfaunal resiliency will be directly related to hydrocarbon concentrations. Although heavily oiled marshes experienced elevated concentrations of total petroleum hydrocarbon concentrations throughout study period (and an altered microbial community with indicator species associated with hydrocarbon contamination, Cagle et al. 2024 ), hydrocarbon concentration did not significantly explain meiobenthic community variation (that included juvenile macroinfauna) during the middle recovery period (Fleeger et al. 2019 ). Our results show that the macroinfauna in moderately oiled marshes exhibited resiliency about 8 years post-spill while the community in heavily oiled marshes remained altered relative to companion reference sites. Abundance trends and functional species traits in heavily oiled marshes both differed from reference and moderately oiled sites over time. Our results from heavily oiled marshes reflect a dynamic response by macroinfauna with large variations in densities and diversity that would have been difficult to predict given scant knowledge of the macroinfauna along the saltmarsh edge (only one study before the DWH of macroinfauna in Louisiana marshes was conducted along the marsh edge, McFarlin et al. 2015 ). The recovery of macrophytes, the microbial community and periwinkle snails in heavily oiled marshes will also likely take more than a decade (Cagle et al. 2024 ; Deis et al. 2020 ; Zengel et al. 2022b), suggesting that ecosystem function was broadly altered for years after the spill. Furthermore, heavily oiled sites along the marsh edge that experienced severe oil-induced erosion will be unable to recover to the pre-spill community because these shorelines were permanently lost to open water. In fact, three of our seven fixed sites on the marsh edge were subject to loss due to oil-induced erosion. Zengel et al. ( 2022a ) reviewed studies of erosion induced by oiling from DWS and concluded that erosion (including linear shoreline retreat) in oiled marshes was increased by ~ 100–200% over 2–3 years post-spill suggesting that the DHW contributed to an abrupt, and in some locations, permanent regional declines in the abundance of diversity of saltmarsh macroinfauna. Declarations Ethics approval and consent to participate Louisiana State University requires approval for research with vertebrate animals, as per policies from its IACUC committee. No vertebrates were used in this study. Consent for publication Not applicable. Availability of data and material The datasets generated during and/or analyzed during the current study are available in the GRIIDC repository, https://www.griidc.org/ Competing interests The authors declare that they have no competing interests. Funding This research was made possible by grants from The Gulf of Mexico Research Initiative. Authors' contributions MP sorted samples, identified invertebrates, conducted statistical analyses and contributed prose and editorial comments. JF drafted the manuscript and oversaw most of the sample collection, sorting and data archiving. DJ supervised sample, sorting and identification of invertebrates for two years of the project. RR collected samples in the field, sorted samples and compiled data for much of the project. AH was a participant in all funding applications, experimental design and an active participant in data interpretation and editing of the manuscript. DD was a participant in all funding applications, experimental design and an active participant in data interpretation and editing of the manuscript. Acknowledgements Not applicable. References Baltz, D.M., C. Rakocinski, and J.W. Fleeger. 1993. Microhabitat use by marsh-edge fishes in a Louisiana estuary. Environmental Biology of Fishes 36: 109-126. Bam, W., L.M. Hooper-Bui, R.M. Strecker, P.L. Adhikari, and E.B. Overton. 2018. Coupled effects of oil spill and hurricane on saltmarsh terrestrial arthropods. Plos one 13: e0194941. Barron, M.G., D.N. Vivian, R.A. Heintz, and U.H. Yim. 2020. Long-Term Ecological Impacts from Oil Spills: Comparison of Exxon Valdez, Hebei Spirit, and Deepwater Horizon. Environmental Science & Technology 54: 6456-6467. Baumann, M.S., G.F. Fricano, K. Fedeli, C.E. Schlemme, M.C. Christman, and M.V. Carle. 2020. Recovery of salt marsh invertebrates following habitat restoration: Implications for marsh restoration in the northern Gulf of Mexico. Estuaries and Coasts 43: 711-1721. Bell, S.S. 1982. On the population biology and meiofaunal characteristics of Manayunkia aestuarina (Polychaeta: Sabellidae: Fabricinae) from a South Carolina salt marsh. Estuarine, Coastal and Shelf Science 14: 215-221. Bergen, A., C. Alderson, R. Bergfors, C. Aquila, and M. Matsil. 2000. Restoration of a Spartina alterniflora salt marsh following a fuel oil spill, New York City, NY. Wetlands Ecology and Management 8: 185-195. Beseres, J.J., and R.J. Feller. 2007. Importance of predation by white shrimp Litopenaeus setiferus on estuarine subtidal macrobenthos. Journal of Experimental Marine Biology and Ecology 344: 193-205. Beyer, J., H.C. Trannum, T. Bakke, P.V. Hodson, and T.K. Collier. 2016. Environmental effects of the Deepwater Horizon oil spill: A review. Marine Pollution Bulletin 110: 28-51. Bledsoe, R., and R. Boopathy. 2016. Bioaugmentation of microbes to restore coastal wetland plants to protect land from coastal erosion. International Biodeterioration & Biodegradation 113: 155-160. Bouma, T.J., M.B. De Vries, E. Low, L. Kusters, P.M.J. Herman, I.C. Tánczos, S. Temmerman, A. Hesselink, P. Meire, and S. van Regenmortel. 2005. Flow hydrodynamics on a mudflat and in salt marsh vegetation:: identifying general relationships for habitat characterisations. Hydrobiologia 540: 259-274. Cagle, G., Q. Lin, S.A. Graham, I. Mendelssohn, J.W. Fleeger, D. Deis, D.S. Johnson, J. Zhou, and A. Hou. 2020. Planting Spartina alterniflora in a salt marsh denuded of vegetation by an oil spill induces a rapid response in the soil microbial community. Ecological Engineering 151: 105815. Cagle, G.A., H. Chen, J.W. Fleeger, D. Deis, Q. Lin, and A. Hou. 2024. Spatial heterogeneity and oil pollution structured the soil microbial community in salt marshes in Barataria Bay, Louisiana, USA, eight years after the Deepwater Horizon oil spill. Ecological Indicators 160: 111884. Clarke K, Gorley R (2006) Primer v6: user manual/tutorial. Primer-E, Plymouth Culbertson, J.B., I. Valiela, Y.S. Olsen, and C.M. Reddy. 2008a. Effect of field exposure to 38-year-old residual petroleum hydrocarbons on growth, condition index, and filtration rate of the ribbed mussel, Geukensia demissa. Environmental Pollution 154: 312-319. Culbertson, J.B., I. Valiela, E.E. Peacock, C.M. Reddy, A. Carter, and R. VanderKruik. 2007. Long-term biological effects of petroleum residues on fiddler crabs in salt marshes. Marine Pollution Bulletin 54: 955-962. Culbertson, J.B., I. Valiela, M. Pickart, E.E. Peacock, and C.M. Reddy. 2008b. Long-term consequences of residual petroleum on salt marsh grass. Journal of Applied Ecology 45: 1284-1292. da Cunha Lana, P., and C. Guiss. 1992. Macrofauna–plant-biomass interactions in a euhaline salt marsh in Paranaguá Bay (SE Brazil). Mar Ecol Prog Ser 80: 57-64. Dauvin, J.C., H. Andrade, J. de-la-Ossa-Carretero, Y. Del-Pilar-Ruso, and R. Riera. 2016. Polychaete/amphipod ratios: An approach to validating simple benthic indicators. Ecological Indicators 63: 89-99. Deis, D.R., J.W. Fleeger, D.S. Johnson, I.A. Mendelssohn, Q. Lin, S.A. Graham, S. Zengel, and A. Hou. 2020. Recovery of the salt marsh periwinkle ( Littoraria irrorata ) 9 years after the Deepwater Horizon oil spill: Size matters. Marine Pollution Bulletin 160: 111581. Deis, D.R., I.A. Mendelssohn, J.W. Fleeger, S.M. Bourgoin, and Q. Lin. 2019. Legacy effects of Hurricane Katrina influenced marsh shoreline erosion following the Deepwater Horizon oil spill. Science of The Total Environment 672: 456-467. DeLaune, R.D., C.J. Smith, W.H.J. Patrick, J.W. Fleeger, and M.D. Tolley. 1984. Effect of oil on salt marsh biota: Methods for restoration. Environ. Pollut 36: 207-227. Dong, Y., Y. Liu, C. Hu, I.R. MacDonald, and Y. Lu. 2022. Chronic oiling in global oceans. Science 376: 1300-1304. Engle, V.D. 2011. Estimating the Provision of Ecosystem Services by Gulf of Mexico Coastal Wetlands. Wetlands 31: 179-193. Fleeger, J.W., K.R. Carman, M.R. Riggio, I.A. Mendelssohn, Q.X. Lin, A. Hou, D.R. Deis, and S. Zengel. 2015. Recovery of salt marsh benthic microalgae and meiofauna following the Deepwater Horizon oil spill linked to recovery of Spartina alterniflora . Marine Ecology Progress Series 536: 39-54. Fleeger, J.W., D.S. Johnson, S. Zengel, I.A. Mendelssohn, D.R. Deis, S.A. Graham, Q. Lin, M.C. Christman, M.R. Riggio, and M. Pant. 2020. Macroinfauna responses and recovery trajectories after an oil spill differ from those following saltmarsh restoration. Marine Environmental Research 155. Fleeger, J.W., D.S. Johnson, S.A. Zengel, I.A. Mendelssohn, D.R. Deis, and S.A. Graham. 2022. A Macroinfaunal Ecosystem Engineer May Facilitate Recovery of Benthic Invertebrates and Accompanying Ecosystem Services After an Oil Spill. Estuaries and Coasts 45: 582-591. Fleeger, J.W., M.R. Riggio, I.A. Mendelssohn, Q. Lin, D.R. Deis, D.S. Johnson, K.R. Carman, S.A. Graham, S. Zengel, and A. Hou. 2019. What promotes the recovery of salt marsh infauna after oil spills? Estuaries and Coasts 42: 204-217. Fleeger, J.W., M.R. Riggio, I.A. Mendelssohn, Q. Lin, A. Hou, and D.R. Deis. 2018. Recovery of saltmarsh meiofauna six years after the Deepwater Horizon oil spill. Journal of Experimental Marine Biology and Ecology 502: 182-190. Formel, S.K., K.L. Mighell, D. Kandalepas, E. Jarrell, B.M. Bernik, V. Elango, J.H. Pardue, M.J. Blum, and S.A. Van Bael. 2022. Spatial and temporal comparisons of salt marsh soil fungal communities following the deepwater horizon spill. Wetlands Ecology and Management 30: 239-256. Fry, B., D.M. Baltz, M.C. Benfield, J.W. Fleeger, A. Grace, H.L. Haas, and Z.J. Quiñones-Rivera. 2003. Chemical indicators of movement and residency for brown shrimp ( Farfantepenaeus aztecus ) in coastal Louisiana marshscapes. Estuaries 26: 82-97. Galván, K.A., J.W. Fleeger, and B. Fry. 2008. Stable isotope addition reveals dietary importance of phytoplankton and benthic microalgae to saltmarsh infauna. Marine Ecology Progress Series 359: 37-49. Galván, K.A., J.W. Fleeger, B.J. Peterson, D.C. Drake, L.A. Deegan, and D.S. Johnson. 2011. Natural abundance stable isotopes and dual isotope tracer additions help to resolve resources supporting a saltmarsh food web. Journal of Experimental Marine Biology and Ecology 410: 1-11. Henkel, J.R., B.J. Sigel, and C.M. Taylor. 2012. Large-Scale Impacts of the Deepwater Horizon Oil Spill: Can Local Disturbance Affect Distant Ecosystems through Migratory Shorebirds? Bioscience 62: 676-685. Husseneder, C., J.-S. Park, and L.D. Foil. 2018. Recovery of horse fly populations in Louisiana marshes following the Deepwater Horizon oil spill. Scientific Reports 8: 13777. Indiketi, N., M.C. Grenon, P. Groleau, É. Veilleux, G. Triffault-Bouchet, and P. Couture. 2022. The effects of dissolved petroleum hydrocarbons on benthic organisms: Chironomids and amphipods. Ecotoxicology and Environmental Safety 237. Johnson, D.S., J.W. Fleeger, K.A. Galván, and E.B. Moser. 2007. Worm holes and their space-time continuum: Spatial and temporal variability of macroinfaunal annelids in a northern New England salt marsh. Estuaries and Coasts 30: 226-237. Junoy, J., C. Castellanos, R. Bernardo-Madrid, R. Riera, and J.M. Viéitez. 2014. Macroinfaunal recovery on the beach most severely affected by the 'Prestige' oil spill (O Rostro, Galicia, north-west Spain). Journal of the Marine Biological Association of the United Kingdom 94: 17-24. Kawaida, S., M. Horinouchi, K. Kurata, and K. Toda. 2024. Differences in benthic assemblage structures between vegetated and unvegetated habitats in a salt marsh in Lake Shinji, western Japan. Fisheries Science, 2024, 1-14. Kristensen, E., M. Delefosse, C.O. Quintana, M.R. Flindt, and T. Valdemarsen. 2014. Influence of benthic macrofauna community shifts on ecosystem functioning in shallow estuaries. Frontiers in Marine Science, 2014, 1-14. Lacoste, É., A. Piot, P. Archambault, C.W. McKindsey, and C. Nozais. 2018. Bioturbation activity of three macrofaunal species and the presence of meiofauna affect the abundance and composition of benthic bacterial communities. Marine environmental research 136: 62-70. Lewis, J.P., J.H. Tarnecki, S.B. Garner, D.D. Chagaris, and W.F. Patterson. 2020. Changes in Reef Fish Community Structure Following the Deepwater Horizon Oil Spill. Scientific Reports 10. Lin, Q., I.A. Mendelssohn, S. Graham, A. Hou, J.W. Fleeger, and D.R. Deis. 2016. Response of salt marshes to oiling from the Deepwater Horizon Spill: Implications for plant growth, soil surface-erosion, and shoreline stability. Science of the Total Environment 557-558: 369-377. Lumibao, C.Y., S. Formel, V. Elango, J.H. Pardue, M. Blum, and S.A. Van Bael. 2018. Persisting responses of salt marsh fungal communities to the Deepwater Horizon oil spill. Science of The Total Environment 642: 904-913. Malakauskas, D.M., S.J. Willson, M.A. Wilzbach, and N.A. Som. 2013. Flow variation and substrate type affect dislodgement of the freshwater polychaete, Manayunkia speciosa. Freshwater Science 32: 862-873. McCloy, M.W., R.K. Andringa, and J.K. Grace. 2022. Resilience of avian communities to urbanization and climate change: An Integrative Review. Frontiers in Conservation Science 3: 918873. McFarlin, C.R., T.D. Bishop, M.W. Hester, and M. Alber. 2015. Context-dependent effects of the loss of Spartina alterniflora on salt marsh invertebrate communities. Estuarine, Coastal and Shelf Science 163: 218-230. Mendelssohn, I.A., G.L. Andersen, D.M. Baltz, R.H. Caffey, K.R. Carman, J.W. Fleeger, S.B. Joye, Q. Lin, E. Maltby, and E.B. Overton. 2012. Oil impacts on coastal wetlands: implications for the Mississippi River Delta ecosystem after the Deepwater Horizon oil spill. BioScience 62: 562-574. Michel, J., E.H. Owens, S. Zengel, A. Graham, Z. Nixon, T. Allard, W. Holton, P. Reimer, A. Lamarche, M. White, N. Rutherford, C. Childs, G. Mauseth, G. Challenger, and E. Taylor. 2013. Extent and Degree of Shoreline Oiling: Deepwater Horizon Oil Spill, Gulf of Mexico, USA. Plos One 8. Monteiro, L., W. Traunspurger, F. Lynen, and T. Moens. 2019. Effects of the water-soluble fraction of a crude oil on estuarine meiofauna: A microcosm approach. Marine Environmental Research 147: 113-125. Moyo, S., H. Bennadji, D. Laguaite, A.A. Pérez-Umphrey, A.M. Snider, A. Bonisoli-Alquati, J.A. Olin, P.C. Stouffer, S.S. Taylor, and P.C. López-Duarte. 2021. Stable isotope analyses identify trophic niche partitioning between sympatric terrestrial vertebrates in coastal saltmarshes with differing oiling histories. PeerJ 9: e11392. Murawski, S.A., P.T. Schwing, W.F. Patterson, T.T. Sutton, P.A. Montagna, R.J. Milligan, S.B. Joye, L. Thomas, J.P. Kilborn, C.B. Paris, R. Faillettaz, D.S. Portnoy, and S. Gilbert. 2023. Vulnerability and resilience of living marine resources to the Deepwater Horizon oil spill: an overview. Frontiers in Marine Science 10. Nelson, J.A., D.S. Johnson, L.A. Deegan, A.C. Spivak, and N.R. Sommer. 2019. Feedbacks between nutrient enrichment and geomorphology alter bottom-up control on food webs. Ecosystems 22: 229-242. Nixon, Z., S. Zengel, M. Baker, M. Steinhoff, G. Fricano, S. Rouhani, and J. Michel. 2016. Shoreline oiling from the Deepwater Horizon oil spill. Marine Pollution Bulletin 107: 170-178. Oksanen J, Simpson G, Blanchet F, Kindt R, Legendre P, Minchin P, O'Hara R, Solymos P, Stevens M, Szoecs E, Wagner H, Barbour M, Bedward M, Bolker B, Borcard D, Carvalho G, Chirico M, De Caceres M, Durand S, Evangelista H, FitzJohn R, Friendly M, Furneaux B, Hannigan G, Hill M, Lahti L, McGlinn D, Ouellette M, Ribeiro Cunha E, Smith T, Stier A, Ter Braak C, Weedon J (2024). _vegan: Community Ecology Package_. R package version 2.6-6.1, https://CRAN.R-project.org/package=vegan Peterson, C.H. 2001. The "Exxon Valdez" oil spill in Alaska: Acute, indirect and chronic effects on the ecosystem. Adv. Mar. Biol 39: 1-103. Powers, S.P., F.J. Hernandez, R.H. Condon, J.M. Drymon, and C.M. Free. 2013. Novel Pathways for Injury from Offshore Oil Spills: Direct, Sublethal and Indirect Effects of the Deepwater Horizon Oil Spill on Pelagic Sargassum Communities. Plos One 8. Rabalais, N.N., and R.E. Turner. 2016. Effects of the Deepwater Horizon Oil Spill on Coastal Marshes and Associated Organisms. Oceanography 29: 150-159. Reddy, C.M., T.I. Eglinton, A. Hounshell, H.K. White, L. Xu, R.B. Gaines, and G.S. Frysinger. 2002. The west falmouth oil spill after thirty years: The persistence of petroleum hydrocarbons in marsh Sediments. Environmental Science & Technology 36: 4754-4760. Reuscher, M.G., J.G. Baguley, N. Conrad-Forrest, C. Cooksey, J.L. Hyland, C. Lewis, P.A. Montagna, R.W. Ricker, M. Rohal, and T. Washburn. 2017. Temporal patterns of Deepwater Horizon impacts on the benthic infauna of the northern Gulf of Mexico continental slope. Plos One 12. R Core Team (2024). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. Roth, A.M.F., and D.M. Baltz. 2009. Short-Term Effects of an Oil Spill on Marsh-Edge Fishes and Decapod Crustaceans. Estuaries and Coasts 32: 565-572. Sakamaki, T., and J.S. Richardson. 2009. Dietary responses of tidal flat macrobenthos to reduction of benthic microalgae: a test for potential use of allochthonous organic matter. Marine Ecology-Progress Series 386: 107-113. Sanders, H.L., J.F. Grassle, G.R. Hampson, L.S. Morse, S. Garner-Price, and C.C. Jones. 1980. Anatomy of an oil spill: long-term effects from the grounding of the barge Florida off West Falmouth, Massachusetts. J. Mar. Res 38: 265-380. Santos, S.L., and J.L. Simon. 1980. Response of soft-bottom benthos to annual catastrophic disturbance in a South Florida estuary. Mar. Ecol. Prog. Ser 3: 347-355. Scarlett, A., S.J. Rowland, M. Canty, E.L. Smith, and T.S. Galloway. 2007. Method for assessing the chronic toxicity of marine and estuarine sediment-associated contaminants using the amphipod Corophium volutator. Marine Environmental Research 63: 457-470. Turner, R.E., N.N. Rabalais, E.B. Overton, B.M. Meyer, G. McClenachan, E.M. Swenson, M. Besonen, M.L. Parsons, and J. Zingre. 2019. Oiling of the continental shelf and coastal marshes over eight years after the 2010 Deepwater Horizon oil spill. Environmental Pollution 252: 1367-1376. van Eenennaam, J.S., S. Rahsepar, J.R. Radovic, T.B.P. Oldenburg, J. Wonink, A.A.M. Langenhoff, A.J. Murk, and E.M. Foekema. 2018. Marine snow increases the adverse effects of oil on benthic invertebrates. Marine Pollution Bulletin 126: 339-348. United States v. BP Exploration & Prod., Inc. (In re Oil Spill by the Oil Rig “Deepwater Horizon”), 21 F. Supp. 3d 657 (E.D. La. 2014) Weerman, E.J., P.M.J. Herman, and J. van de Koppel. 2011. Macrobenthos abundance and distribution on a spatially patterned intertidal flat. Marine Ecology Progress Series 440: 95-103. Whipple, S.A., J.W. Fleeger, and L.L. Cook. 1981. The influence of tidal flushing, light exposure and natant macrofauna on edaphic chlorophyll a in a Louisiana salt marsh. Estuarine, Coastal and Shelf Science 13: 637-643. Whitcraft, C.R., and L.A. Levin. 2007. Regulation of benthic algal and animal communities by salt marsh plants: Impact of shading. Ecology 88: 904-917. Whomersley, P., M. Huxham, S. Bolam, M. Schratzberger, J. Augley, and D. Ridland. 2010. Response of intertidal macrofauna to multiple disturbance types and intensities - An experimental approach. Marine Environmental Research 69: 297-308. Widbom, B., and C.A. Oviatt. 1994. THE WORLD-PRODIGY OIL-SPILL IN NARRAGANSETT BAY, RHODE-ISLAND - ACUTE EFFECTS ON MACROBENTHIC CRUSTACEAN POPULATIONS. Hydrobiologia 291: 115-124. Wiens, J.A., T.O. Crist, R.H. Day, S.M. Murphy, and G.D. Hayward. 2001. A canonical correspondence analysis of the effects of the Exxon Valdez oil spill on marine birds. Ecological Applications 11: 828-839. Zengel, S., B.M. Bernik, N. Rutherford, Z. Nixon, and J. Michel. 2015. Heavily oiled salt marsh following the Deepwater Horizon oil spill, Ecological comparisons of shoreline cleanup treatments and recovery. Plos One 10. Zengel, S., C.L. Montague, S.C. Pennings, S.P. Powers, M. Steinhoff, G. Fricano, C. Schlemme, M.N. Zhang, J. Oehrig, Z. Nixon, S. Rouhani, and J. Michel. 2016a. Impacts of the Deepwater Horizon oil spill on salt marsh periwinkles ( Littoraria irrorata ). Environmental Science & Technology 50: 643-652. Zengel, S., Z. Nixon, J. Weaver, N. Rutherford, B.M. Bernik, and J. Michel. 2022a. Accelerated marsh erosion following the Deepwater Horizon oil spill confirmed, ameliorated by planting. Scientific Reports 12: 13802. Zengel, S., S.C. Pennings, B. Silliman, C. Montague, J. Weaver, D.R. Deis, M.O. Krasnec, N. Rutherford, and Z. Nixon. 2016b. Deepwater Horizon oil spill impacts on salt marsh fiddler crabs ( Uca spp.). Estuaries and Coasts 39: 1154-1163. Zengel, S., J. Weaver, I.A. Mendelssohn, S.A. Graham, Q. Lin, M.W. Hester, J.M. Willis, B.R. Silliman, J.W. Fleeger, G. McClenachan, N.N. Rabalais, R.E. Turner, A.R. Hughes, J. Cebrian, D.R. Deis, N. Rutherford, and B.J. Roberts. 2022b. Meta-analysis of salt marsh vegetation impacts and recovery: a synthesis following the Deepwater Horizon oil spill. Ecological Applications 32: e02489. Zhou, Z., T.J. Grandjean, J. de Smit, J. van Belzen, G.S. Fivash, B. Walles, O. Beauchard, J. van Dalen, D.B. Blok, and L. van IJzerloo. 2024. Sediment dynamics shape macrofauna mobility traits and abundance on tidal flats. Limnology and Oceanography . Cite Share Download PDF Status: Published Journal Publication published 24 Mar, 2025 Read the published version in Estuaries and Coasts → Version 1 posted Reviewers agreed at journal 09 Dec, 2024 Reviewers invited by journal 06 Dec, 2024 Editor invited by journal 05 Dec, 2024 Editor assigned by journal 04 Dec, 2024 First submitted to journal 04 Dec, 2024 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-5582083","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":387250411,"identity":"8c775a4e-946f-47d0-a206-33421ba9e962","order_by":0,"name":"Manisha Pant","email":"","orcid":"","institution":"William \u0026 Mary Counseling Center","correspondingAuthor":false,"prefix":"","firstName":"Manisha","middleName":"","lastName":"Pant","suffix":""},{"id":387250412,"identity":"b8d189c7-f669-4bb0-a710-4eb7b5fbc0e3","order_by":1,"name":"John Fleeger","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAsElEQVRIiWNgGAWjYFACxocHGBhsZMBsHuK0MBsAtaTxkKzlMAla5NubGQ58qDjPIz8jgfHB2zYitDD2HGY4OOPMbR6DGwnMhnOJ0cIskX/gMG8bUItEAps0LzFa2CSSGQ7//XcO5DD230Rp4QFpYWw4wMNwI4GNmSgtEjxAv/QcS+YxOPOwWXLOOSK0AEOM8cGPGjs5+fbkgx/elBGhBQkwNpCmfhSMglEwCkYBbgAAwY4zzuFOQTwAAAAASUVORK5CYII=","orcid":"","institution":"Louisiana State University","correspondingAuthor":true,"prefix":"","firstName":"John","middleName":"","lastName":"Fleeger","suffix":""},{"id":387250413,"identity":"5cdf4d50-3cba-410a-9bf9-2fbd2df737c9","order_by":2,"name":"David Johnson","email":"","orcid":"","institution":"Viriginia Institute Marine Science William and Mary","correspondingAuthor":false,"prefix":"","firstName":"David","middleName":"","lastName":"Johnson","suffix":""},{"id":387250414,"identity":"e973cec7-20da-43b0-842c-9a64985fd031","order_by":3,"name":"Rita Riggio","email":"","orcid":"","institution":"Louisiana State University and A\u0026M College: Louisiana State University","correspondingAuthor":false,"prefix":"","firstName":"Rita","middleName":"","lastName":"Riggio","suffix":""},{"id":387250415,"identity":"4be082a2-6a7c-440b-b29c-c35d6352b695","order_by":4,"name":"Aixin Hou","email":"","orcid":"","institution":"Louisiana State University and A\u0026M College: Louisiana State University","correspondingAuthor":false,"prefix":"","firstName":"Aixin","middleName":"","lastName":"Hou","suffix":""},{"id":387250416,"identity":"c98e4bb9-da22-42eb-8996-780f149cea9a","order_by":5,"name":"Donald Deis","email":"","orcid":"","institution":"AtkinsRealis","correspondingAuthor":false,"prefix":"","firstName":"Donald","middleName":"","lastName":"Deis","suffix":""}],"badges":[],"createdAt":"2024-12-04 19:10:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5582083/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5582083/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s12237-025-01520-5","type":"published","date":"2025-03-24T15:57:10+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":70943395,"identity":"051c7a2b-5d00-4095-b357-bf6c33663837","added_by":"auto","created_at":"2024-12-09 12:26:23","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":93407,"visible":true,"origin":"","legend":"\u003cp\u003eDiversity (mean number of taxa) and abundance (number m\u003csup\u003e-2\u003c/sup\u003e) of all macroinfauna by year after the 2010 DWH oil spill.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5582083/v1/e3228d13757358ff045c2f81.png"},{"id":70943397,"identity":"12c92837-ee1d-4c29-8137-2127798ed6f9","added_by":"auto","created_at":"2024-12-09 12:26:23","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":100958,"visible":true,"origin":"","legend":"\u003cp\u003eAbundance (number m\u003csup\u003e-2\u003c/sup\u003e) of all polychaetes and amphipods at RF, MD and HV by year after the 2010 DWH oil spill.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5582083/v1/ba2ca62dcbe93143e17e160c.png"},{"id":70943554,"identity":"66e5b902-cf61-452e-8440-59e4587ba89f","added_by":"auto","created_at":"2024-12-09 12:34:23","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":141502,"visible":true,"origin":"","legend":"\u003cp\u003eAbundance (number m\u003csup\u003e-2\u003c/sup\u003e) of \u003cem\u003eA. louisianum\u003c/em\u003e, \u003cem\u003eA. succinea\u003c/em\u003e, \u003cem\u003eL. rapax\u003c/em\u003e and oligochaetes at RF, MD and HV by year after the 2010 DWH oil spill.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5582083/v1/b492356a2292b2dbccdd651c.png"},{"id":70943404,"identity":"a47a7c98-195a-44cc-995b-524e241ab582","added_by":"auto","created_at":"2024-12-09 12:26:23","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":113014,"visible":true,"origin":"","legend":"\u003cp\u003eAbundance (number m\u003csup\u003e-2\u003c/sup\u003e) of \u003cem\u003eM. aestuarina\u003c/em\u003e, \u003cem\u003eS. gynobrachiata\u003c/em\u003e, and Capitellidae sp. by year after the 2010 oil spill.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5582083/v1/bac7d813b845a80ea450485c.png"},{"id":70943396,"identity":"078d8acc-b949-443c-a7f2-c3be3133c9b5","added_by":"auto","created_at":"2024-12-09 12:26:23","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":66520,"visible":true,"origin":"","legend":"\u003cp\u003enMDS centroid plot for three recovery periods and oiling categories.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-5582083/v1/fd9f78b39a23c8a8a9a7702b.png"},{"id":70943418,"identity":"5bfcb08e-6d6e-4188-9c4f-34767765aa8b","added_by":"auto","created_at":"2024-12-09 12:26:23","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":71595,"visible":true,"origin":"","legend":"\u003cp\u003enMDS plot for oiling categories from 102 mo post-spill.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-5582083/v1/19b3ecd6d50b7dd0b3887c08.png"},{"id":79604920,"identity":"2f741de1-9877-40b3-9fa7-39066825ddcd","added_by":"auto","created_at":"2025-03-31 16:09:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1351366,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5582083/v1/c4f1669b-a7bb-48a1-bbbe-9356745e14ec.pdf"}],"financialInterests":"","formattedTitle":"Recovery of saltmarsh macroinfauna after the Deepwater Horizon Oil Spill","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCoastal wetlands provide critical ecosystem services throughout the world (Engle \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Human-caused oil spills threaten these valuable ecosystems. Anthropogenic oceanic releases of oil have surged tenfold over background since 1990 and are predominantly located nearshore (Dong et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). An extreme example followed the explosion of the Deepwater Horizon (DWH) platform in the northern Gulf of Mexico on 20 April 2010, which led to the judge-decreed release of 3.19\u0026nbsp;million barrels of crude oil over 87 days from the Macondo well (United States v. BP, 2014). Nearly 800 km of coastal wetlands in Louisiana, USA, were contaminated (Nixon et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Oil residues that enter coastal wetlands are a major concern, not only because of the immediate injury to biota and the services they provide (Rabalais and Turner \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), but also because fine-grained sediment, waterlogged soils, and sedimentary accretion can result in the burial of oil residues where decomposition is very slow, and subsequently, oil may resurface during storm events (Bam et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Indeed, elevated total petroleum hydrocarbons have been detected consistently in DWH-impacted sites for over eight years post-spill (Deis et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Turner et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), as has been documented in other petroleum-impacted salt marshes (Bergen et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Reddy et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Chronically elevated levels of petroleum hydrocarbons in coastal wetlands are a concern because they may lead to decadal-long impacts on biota (Culbertson et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2008a\u003c/span\u003e; Culbertson et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Culbertson et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2008b\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe responses to oiling in DWH-impacted salt marshes have been studied in a diverse array of biota over varying periods of time (Beyer et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Rabalais and Turner \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Roth and Baltz \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Zengel et al. \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2016a\u003c/span\u003e; Zengel et al. 2022b), and results indicate a wide variation in recovery trajectories. For example, macrophytes in oiled marshes experienced a chronic, multiyear decline in above- and belowground biomass that is predicted to last longer than a decade (Zengel et al. 2022b), potentially degrading critical foundation species functions (e.g., protection against erosion, moderation of light levels reaching the sediment surface). One factor that influenced this long-term effect was variation in the recovery rates of the two regionally dominant macrophyte species as \u003cem\u003eSpartina alterniflora\u003c/em\u003e began to regrow after near complete mortality in heavily oiled sites by 18\u0026ndash;24 mo post spill while revegetation by \u003cem\u003eJuncus roemerianus\u003c/em\u003e was minimal after almost nine years (Lin et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Zengel et al. 2022b). Similarly, densities of meiofauna, including juvenile bivalves, amphipods, ostracods, juvenile gastropods, the polychaete \u003cem\u003eManayunkia aestuarina\u003c/em\u003e and the kinorhynch \u003cem\u003eEchinoderes coulli\u003c/em\u003e, remained depressed 42 months after the spill in heavily oiled compared with reference marshes, although many other taxa (e.g., nematodes and benthic copepods) recovered relatively rapidly (~\u0026thinsp;2\u0026ndash;3 years) (Fleeger et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Fleeger et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Recovery of macroinvertebrates also varied, e.g., the greenhead horsefly, \u003cem\u003eTabanus nigrovittatus\u003c/em\u003e recovered by five years (Husseneder et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), and fiddler crabs were affected up to four years (Zengel et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2016b\u003c/span\u003e). On the contrary, periwinkle snail, \u003cem\u003eLittoraria irrorata\u003c/em\u003e, density and size structure had not recovered completely at oiled sites almost nine years post-spill (Deis et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and amphipods in heavily oiled marshes increased greatly in densities from near zero values but were not considered recovered because densities in heavily oiled marshes far exceeded regional and companion reference means 7 years post-spill (Fleeger et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). These chronic impacts on macrophytes and invertebrates as well as impacts on benthic microalgal biomass (Fleeger et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), decomposers (Cagle et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Formel et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), the macrophyte microbiome (Lumibao et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), and the reduced trophic niche width observed in seaside sparrows at oiled sites (Moyo et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) suggest significant alterations of ecological function in oiled marshes.\u003c/p\u003e \u003cp\u003eMacroinfauna, such as polychaetes and amphipods, are important consumers among the saltmarsh benthos. They facilitate nutrient cycling and decomposition (Kristensen et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), graze benthic microalgae and particulate organic matter and are prey for higher trophic level shrimp and fishes (Beseres and Feller \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Fry et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Nelson et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Macroinfauna affects the composition of microbial communities (Lacoste et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), and because some microbes enhance plant growth (Bledsoe and Boopathy \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), they may indirectly affect plant communities. Given these important roles and a broad range in sensitivity to environmental perturbations, macroinfauna frequently serve as indicators of marsh health, productivity, and resiliency following disturbance. Macroinfauna community analyses have long been used to assess the impacts and resiliency from hydrocarbon contamination (e.g., Reuscher et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Sanders et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e1980\u003c/span\u003e). In addition, various indices derived from macrofauna (e.g., the relative densities of the total number of polychaetes and amphipods, Dauvin et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), are frequently used as an indicator of ecological quality in soft sediment ecosystems contaminated by crude or refined oils. Among the adult macroinfauna in DWH-impacted salt marshes, no species-level analyses have been conducted and only total amphipod and total macroinfaunal responses have been documented for more than 6 years post-spill (Fleeger et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Fleeger et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe factors that drive change in benthic populations and communities after oil spills are complex and varied (Barron et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Fleeger et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Not only can oiling induce profound change in the environment (for example, if foundation species are disproportionately affected by oiling), but physiological tolerance to hydrocarbons varies greatly among species even in the same environment (Monteiro et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Furthermore, macroinfaunal species traits such as mobility, vertical position in the sediment (i.e., surface vs subsurface dwellers), and life history/mode of reproduction may influence the ability to avoid contamination, control initial exposure to oil, or influence the rate of repopulation after an oil-induced population bottleneck. The DWH spill created a variable landscape of exposure to oil residues (Michel et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) as designations immediately after the spill ranged from no visible oil to heavily oiled (in which surface oil residues covered 50\u0026ndash;100% of the sediment with thicknesses of ~\u0026thinsp;1 cm, Zengel et al. \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Plant mortality was very high in areas that experienced the heaviest oiling, and many environmental factors were immediately altered in the absence of foundation species (Cagle et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Fleeger et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Over time and as recovery progressed, heavily oiled marshes revegetated, and environmental factors continued to change. Marshes categorized as moderately oiled experienced injuries to plants without significant mortality and oiling-induced environmental changes occurred but were less striking. Here we examine longer term recovery and resiliency of the community of macroinfauna within these changing environments by comparing recovery in moderately oiled marshes with recovery in areas that were heavily oiled. We hypothesized that macroinfaunal communities at these oiled marshes would not differ from reference marshes after 8.5 years post-spill.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eAn oiling effects and recovery assessment following the DHW was conducted at various sites in the microtidal intertidal zone within 3 m of the open shoreline in northern Barataria Bay, Louisiana, USA. Such marsh edge environments are known to be biologically diverse (Baltz et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1993\u003c/span\u003e) and to modify surrounding environmental conditions (Kawaida et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). We established sites with the explicit objective of determining effects and recovery of biota exposed to different oiling intensities. Sites were located over an area 8 km x 5 km, between coordinates N 29.44060\u0026deg;\u0026ndash;29.47459\u0026deg;, W 89.88492\u0026deg;\u0026ndash;89.94647\u0026deg; and were assigned to three oiling categories (Lin et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). These sites were partially interspersed and randomly stratified, where seven showed no visible oiling and were designated \u0026ldquo;companion reference\u0026rdquo; (RF), seven were \u0026ldquo;moderately oiled\u0026rdquo; (MD) and seven were \u0026ldquo;heavily oiled\u0026rdquo; (HV). Because oil was primarily transported into the bay by south and southeastern winds, heavily oiled sites generally occurred on south- and southeast-facing shorelines, while moderately oiled sites generally occurred on adjacent tangential shorelines (Cagle et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Companion reference sites were located along north- and south-facing shorelines\u0026thinsp;~\u0026thinsp;0.5\u0026ndash;4 km from oiled stations. Barataria Bay typically experiences high rates of shoreline retreat due to wind and wave action (Deis et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), and oiling has been shown to increase erosion of the marsh surface (Lin et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Zengel et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2022a\u003c/span\u003e). Three heavily oiled sites experienced severe shoreline retreat by 6-y after the spill and were relocated to immediately adjacent areas with the same oiling zone (subsequent total petroleum hydrocarbon measurements revealed similar values at these sites compared to heavily oiled sites that were not eroded away). Maps showing the sampling site locations are available in several publications, e.g., Cagle et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The macroinfaunal community was sampled at approximately 6-mo intervals on 16 occasions from 1.5 (18 mo) to 8.5 y (102 mo) after the spill.\u003c/p\u003e \u003cp\u003eMacroinfauna were sampled with a hand-held corer (inner diameter\u0026thinsp;=\u0026thinsp;3.5 cm). Two cores were taken to a depth of 2 cm at haphazardly selected locations at each site, and both cores were combined into a single sample cup and fixed in 4% formalin. Sample cups were shaken to break up soil clumps and to ensure complete mixing of sample and formalin. Formalin was replaced and a solution of Rose Bengal was added after ~\u0026thinsp;24 h. Prior to sorting, samples were rinsed through a 0.5-mm sieve. A stereo-dissecting microscope was used to identify and enumerate fauna to the lowest possible taxon. Density was standardized to the number of individuals m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e based on the corer diameter.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eSamples from our biannual collections were merged across different time periods for data exploration and statistical analysis. Samples from all collections within each calendar year (from 2011\u0026ndash;2018 with 21\u0026ndash;63 core samples per year) were combined to create plots of the number of taxa, the densities of total macroinfauna and most abundant individual species, as well as the densities of the sum total of polychaetes and amphipods over time. Based on these plots (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) and on a previous analysis of the abundance of total macroinfauna and amphipods (Fleeger et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), statistical analyses of the macroinfaunal community were conducted to quantify recovery trajectories by categorizing samples into three time periods. The early recovery period was designated from 18\u0026ndash;30 mo (2011\u0026ndash;2012, 62 core samples) post-spill during which time the diversity and abundance increased steadily, a middle period was designated from 36\u0026ndash;85 mo (2013\u0026ndash;2017, 210 core samples) when diversity reached consistently high levels while density was highly variable with highest abundances at HV, and a late period was designated from 90\u0026ndash;102 mo (2017\u0026ndash;2018, 63 core samples) when diversity declined and densities in oiled sites were lower and more consistently similar to RF.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eA total of 40 sediment-dwelling taxa was defined as the macroinfaunal community. Non-metric Multidimensional Scaling (nMDS) was conducted to compare communities at 18\u0026ndash;30, 36\u0026ndash;85 and 90\u0026ndash;102 mo post-spill and among oiling categories using Package Vegan (version 2.6\u0026ndash;6.1, Oksanen et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) in statistical software R (version 4.4.0; R Core Team \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The nMDS was based on a distance matrix calculated using Bray-Curtis dissimilarity index on community data that were first standardized using Hellinger transformation. For clarity, we show only the centroids for each recovery period-oil level group. A similar analysis was conducted on samples from the final collection date, 102 mo post-spill, to compare macrofaunal communities across the oiling categories. For these samples, we used log transformation because this transformation resulted in the lowest stress value. Analysis of Similarity (ANOSIM) was used in a 2-way crossed design with replication to test for community differences among the three recovery periods and oiling categories using PRIMER software (Clarke \u0026amp; Gorley \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). A separate one-way ANOSIM was conducted on the last collection date to compare faunal similarity among the oiling categories.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eAnnelids and crustaceans were the most abundant and diverse taxa. Overall, 12 species of polychaetes (and oligochaetes as a single taxon) and 11 crustacean taxa were identified (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The polychaetes \u003cem\u003eManayunkia aestuarina\u003c/em\u003e (which comprised 18.1% of the total macroinfauna across all samples), \u003cem\u003eAlitta succinea\u003c/em\u003e (7.9%), \u003cem\u003ePolydora cornuta (\u003c/em\u003e5.2%\u003cem\u003e), Boccardia hamata\u003c/em\u003e (3.8%), Capitellidae sp. (2.1%), and \u003cem\u003eStreblospio gynobrachiata\u003c/em\u003e (2.0%), and Oligochaeta (14.8%) were the most common and abundant annelids. The amphipod \u003cem\u003eApocorophium louisianum\u003c/em\u003e (28.5%) was the most abundant crustacean overall followed by the tanaid, \u003cem\u003eLeptochelia rapax\u003c/em\u003e (11.3%).\u003c/p\u003e \u003cp\u003eThe diversity and abundance of total macroinfauna were at near zero values in HV marshes in 2011 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) and were at their lowest values across time in MD and RF marshes. Only one species, \u003cem\u003eM. aestuarina\u003c/em\u003e, was found with one specimen in 3 of the 7 HV samples in 2011. Among oiling categories, macroinfauna richness (expressed as the number of taxa per core) increased from means of \u0026lt;\u0026thinsp;1\u0026ndash;4 in 2011 to 7\u0026ndash;8 in 2015\u0026ndash;2017. The mean abundance of total macroinfauna in 2011 was 7874 (\u0026plusmn;\u0026thinsp;2251 standard error) at RF, 2773 (\u0026plusmn;\u0026thinsp;667) m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e at MD and 222 m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e (\u0026plusmn;\u0026thinsp;105) at HV. Abundances in all oiling categories then steadily increased and peaked in 2015 at MD and 2016 at RF and HV. Compared to densities in 2011, peak densities at RF and MD were 10\u0026ndash;25 x higher and 2 orders of magnitude higher at HV.\u003c/p\u003e \u003cp\u003eThe pattern of temporal changes in the densities of the sum total of polychaetes and amphipods was similar in our companion reference marshes as well as oiled sites (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Amphipod density in all oiling categories, including RF, remained very low, below about 1000 m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e, in the early recovery period but increased to peaks between 10,000\u0026ndash;60,000 m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e in 2015\u0026ndash;2016. Polychaete density increased earlier (beginning in about 2013) than amphipods and steadily from their lowest values in 2011 in all oiling categories with peak densities of about 25,000 m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e at MD and RF in 2015\u0026ndash;2016. Polychaete density at HV averaged from 15,000\u0026ndash;20,000 m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e between 2013\u0026ndash;2018 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The relative abundance of polychaetes and amphipods varied over time primarily because of the large increases in amphipods that took place in 2016\u0026ndash;2017.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePercentage of each taxon (%), mean (x̅, number m\u003csup\u003e\u0026minus;2\u003c/sup\u003e) and standard error (st) of the most abundant species within each oiling level and across time after the DWH spill. The percentage for each taxon of all macroinfauna for each oiling level and time period is given as % of fauna.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" 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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e18\u0026ndash;30 mo post-spill\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eM. aestuarina\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eS. gynobrachiata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eA. succinea\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCapitellidae sp.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eOligochaeta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eA. louisianum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eL. rapax\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e% of fauna\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eHV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e27.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e69.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ex̅\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e371.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e569.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e173.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e173.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1188.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e297.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e198.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e548.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1979.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e474.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e342.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2106.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1146.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e687.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eMD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e17.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e25.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e80.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ex̅\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e910.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e572.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1118.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e676.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1092.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2028.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2938.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1839.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1261.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2005.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1054.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1563.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6159.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8075.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eRF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e13.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e90.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ex̅\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2203.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e173.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e594.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e965.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1188.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e371.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e965.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3136.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e342.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1189.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1398.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1595.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e660.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1605.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e36\u0026ndash;85 mo post-spill\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eM. aestuarina\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP. cornuta\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eA. succinea\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOligochaeta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eA. louisianum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eL. rapax\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eHV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e39.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e91.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ex̅\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3885.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3298.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5749.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7896.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19492.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4531.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16440.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6796.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5849.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11387.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e55818.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8928.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eMD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e83.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ex̅\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7406.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e564.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1500.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3476.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4798.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2518.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18168.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1841.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2109.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5128.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18344.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5660.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eRF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e14.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e85.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ex̅\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11900.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1381.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e609.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5296.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6886.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5162.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19391.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4147.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e885.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6950.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22559.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7221.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e90\u0026ndash;102 mo post-spill\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eM. aestuarina\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP. cornuta\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eB. hamata\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eA. succinea\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eOligochaeta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eA. louisianum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eL. rapax\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eHV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e35.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e11.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e93.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ex̅\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e421.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2971.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3937.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6215.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5472.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e14683.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4704.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e690.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4256.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5780.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5676.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10004.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e26166.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6736.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eMD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e28.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e84.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ex̅\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1931.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e817.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1535.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2575.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1560.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5101.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1584.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6881.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1705.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2628.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2239.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1619.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10285.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2299.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eRF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e29.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e90.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ex̅\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3689.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2302.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4061.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1114.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4655.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9186.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3021.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7956.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6952.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9932.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1368.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7109.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23155.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4033.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThere was substantial variation in the recovery trajectories of individual taxa among oiling categories. Four taxa, \u003cem\u003eA. louisianum\u003c/em\u003e, \u003cem\u003eA. succinea\u003c/em\u003e, \u003cem\u003eL. rapax\u003c/em\u003e and oligochaetes primarily contributed to post-spill increases at HV with highest densities in 2016 and 2017, ranging from 3\u0026ndash;5 times greater than RF at the same period (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Densities for these taxa in MD did not display strong peaks over time and values were more similar to those in RF. However, three taxa, \u003cem\u003eM. aestuarina\u003c/em\u003e, \u003cem\u003eS. gynobrachiata\u003c/em\u003e, Capitellidae sp., at HV remained at very low abundances over time at HV (50\u0026ndash;75% lower than RF; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Densities of these species at MD more closely tracked variations at RF.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe nMDS centroid plot shows that samples from all three oiling categories during the early recovery period were loosely clustered along with RF samples from the middle period (left side, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). RF during the late period did not cluster with any other oiling category or time period (lower middle, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Samples from MD and HV for the middle and late periods were loosely clustered (right side, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Two-way crossed ANOSIM revealed that there were significant differences in similarities among all oiling categories and across the three recovery periods (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, p values\u0026thinsp;\u0026le;\u0026thinsp;0.005).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of 2-way crossed ANOSIM conducted on the three recovery periods and oiling categories.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComparison\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR Statistic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHV, MD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHV, RF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMD, RF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u0026ndash;30, 36\u0026ndash;85 mo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u0026ndash;30, 90\u0026ndash;102 mo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.293\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e36\u0026ndash;85, 90\u0026ndash;102, mo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.005\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\u003eThe nMDS plot for samples taken on the final collection date, 102 mo after the spill, placed HV samples mostly on one side (left side, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e), and RF samples were mostly on another side (lower and right side, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Samples from MD tended to be intermediate between both RF and HV samples. Corresponding ANOSIM indicated that similarities between HV and MD (p\u0026thinsp;=\u0026thinsp;0.473) and similarities between MD and RF (p\u0026thinsp;=\u0026thinsp;0.170) did not differ. However, HV and RF similarities significantly differed (p\u0026thinsp;=\u0026thinsp;0.003).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eEcological resilience is defined as the capacity of a community to absorb and recover from disturbance without affecting the function and stability of the community or broader ecosystem (McCloy et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Our results show that resiliency of the macroinfaunal community following the DWH was dependent on both oiling intensity and time. The community in heavily oiled marshes differed from our companion reference sites throughout the study period when grouped into early, middle, and late recovery periods (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Furthermore, the community in heavily oiled marshes remained significantly different than our reference marshes on our last collection date, 8.5 years post-spill. The finding that macroinfauna at these heavily oiled sites will likely take longer than a decade to recover is comparable to findings from the same study sites for macrophyte and microbial communities as well as the periwinkle snail population (Cagle et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Deis et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Zengel et al. 2022b). The community in the moderately oiled marshes, with more modest but measurable oiling effects on macrophytes (Lin et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), also differed from reference marshes in each of the three recovery periods but did not differ from reference marshes 8.5 years post-spill suggesting that resiliency was achieved after about 8 years. A similar distinction between the microbial communities at heavily and moderately oiled marshes from the same study sites and time frame was shown by Cagle et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) as microbial indicator species known to respond to chronic oil contamination were significantly more common at heavily than moderately oiled sites.\u003c/p\u003e \u003cp\u003eThe recovery trajectories of individual species also strongly depended on oiling intensity. Although species composition in 2011 was similar in all three oiling categories (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), the community in heavily oiled marshes diverged from moderately oiled and reference marshes during the middle recovery period when \u003cem\u003eA. louisianum\u003c/em\u003e, \u003cem\u003eA. succinea\u003c/em\u003e, \u003cem\u003eL. rapax\u003c/em\u003e and oligochaetes dramatically increased in abundance (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), while at the same time, abundance increases of \u003cem\u003eM. aestuarina\u003c/em\u003e, \u003cem\u003eS. gynobrachiata\u003c/em\u003e, and Capitellidae sp. in heavily oiled marshes lagged behind increasing trends in moderately oiled and reference marshes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Not only did peak densities in heavily oiled marshes (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) exceed those at our companion reference sites, densities were also much higher than would be expected based on regional averages. Baumann et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and Fleeger et al. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) conducted meta-analyses of the densities of total macroinfauna and amphipods in the Gulf of Mexico marsh edge environment and estimated mean densities of 28,000 (\u0026plusmn;\u0026thinsp;5838) m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e for total macroinfauna and 1300 (\u0026plusmn;\u0026thinsp;180) m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e for amphipods respectively; peak values in heavily oiled marshes for macroinfauna were 100,000 (\u0026plusmn;\u0026thinsp;33,000) m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e and 60,000 (\u0026plusmn;\u0026thinsp;2900) m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e for amphipods. At moderately oiled sites, most taxa, including all polychaetes and amphipods (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) and the species that failed to recover in heavily oiled marshes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), tended to change over time in concert with variation in reference marshes. Also, abundance peaks at moderately oiled sites for individual species were much lower than at heavily oiled marshes and more similar to patterns at reference sites. These observations suggest that ecosystem function or processes differed greatly with oiling intensity especially during the middle recovery period.\u003c/p\u003e \u003cp\u003eThe extreme oiling impacts on macrophytes in heavily oiled marshes likely contributed to a severely altered ecosystem function. The marsh edge along heavily oiled shores experienced the greatest reductions in total plant cover, total aboveground biomass, and belowground biomass and are predicted to take longer than a decade to fully recover (Zengel et al. 2022b). Our heavily oiled sites were essentially unvegetated during the early recovery period but progressively regained plant cover during the middle recovery period (Lin et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The absence of vegetation (or low levels of plant biomass) at our heavily oiled sites would alter the soil environment in many ways compared to the vegetated moderately oiled and reference sites that would indirectly affect macroinfauna, e.g., by influencing dissolved organic matter, gas exchange, bulk density, and the microbial community (Kawaida et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). One important factor that may have contributed to high densities in heavily oiled marshes was food supply. Many macroinfaunal species consume benthic microalgae (Galv\u0026aacute;n et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), and light reaching the sediment would be increased in the absence of vegetation (or before aboveground biomass fully recovered). Reductions in shading stimulate benthic microalgae in the vegetated marsh (DeLaune et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1984\u003c/span\u003e; Whipple et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e1981\u003c/span\u003e; Whitcraft and Levin \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), and benthic microalgal biomass in 2016 averaged about 4 times higher in heavily oiled compared to moderately oiled marshes during the middle recovery period (Fleeger et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). At the same time, the abundances of some meiofauna (Fleeger et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and adult amphipods (Fleeger et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) were positivity correlated with microalgal biomass.\u003c/p\u003e \u003cp\u003eAnother factor potentially important to ecosystem function associated with macrophyte responses to oiling is variation in tidal currents and wave action (generated by winds and boat wakes along the microtidal shoreline). Flow velocities over unvegetated mudflats are well known to be much higher than in adjacent vegetated marshes because plant structure baffles flow (Bouma et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Furthermore, heavily oiled marshes, with the loss of belowground roots and rhizomes, experienced reduced shear strength and were subject to shoreline retreat (Zengel et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2022a\u003c/span\u003e), which may have further exposed our heavily oiled sites on the marsh edge to stronger waves, higher flow velocities and more frequent disturbance of the soil surface. In addition, fetch distances across Barataria Bay were longest at our heavily oiled sites compared to our moderately oiled and reference sites (Deis et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) which would also increase wave intensity. It is therefore likely that the highest flow velocities occurred in heavily oiled marshes during the middle recovery period coinciding with exceptionally high abundances. Macroinfauna are generally very sensitive to sediment dynamics such as burial or surface disturbances (often experimentally mimicked by raking, Whomersley et al. \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) associated with high flow velocities. Zhou et al. (\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) found that disturbance by raking is erosive of surface sediments in mudflats and influences the mobility traits of macroinfauna such that species with fewer mobile traits are negatively impacted at high levels of erosion/disturbance while species with high mobility exhibit a greater abundance. Differences in mobility may have contributed to the lack of resiliency at our heavily oiled sites of the polychaetes \u003cem\u003eM. aestuarina\u003c/em\u003e and \u003cem\u003eS\u003c/em\u003e. \u003cem\u003egynobrachiata\u003c/em\u003e as both are tube dwellers with relatively low mobility. Furthermore, an experimental study in a related species, \u003cem\u003eManayunkia speciosa\u003c/em\u003e, experienced high rates of dislodgement from sediment under high flow conditions (above critical erosion velocity, Malakauskas et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Alternatively, tube dwelling macroinfauna in salt marshes has been positively correlated with below-ground plant biomass (da Cunha Lana and Guiss \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1992\u003c/span\u003e), and the slow recovery of roots and rhizomes in DWH heavily oiled marshes was implicated as a factor that contributed to the slow recovery of juvenile \u003cem\u003eM. aestuarina\u003c/em\u003e (Fleeger at al. 2019). In contrast, amphipods in the Family Corophiidae, including \u003cem\u003eA. louisianum\u003c/em\u003e, that achieved very high densities are highly mobile as adults and juveniles, and are attracted to areas with high benthic algal biomass (Sakamaki and Richardson \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Weerman et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). In addition, another high-density species abundant in heavily oiled marshes, \u003cem\u003eA. succinea\u003c/em\u003e, is capable of pelagic dispersal as adults (Santos and Simon \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e1980\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur companion reference sites were selected due to the absence of visible oiling and because total petroleum hydrocarbon concentrations were significantly lower than at moderately and heavily oil sites in 2011 (Lin et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). However, it is unreasonable to assume that these sites were not impacted by hydrocarbon contamination from the DWH spill. Offshore oil residues from the DWH spill were driven by winds and tides through tidal passes and surged into Barataria Bay in the summer of 2010. Turner et al. (\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) reported dissolved aromatic hydrocarbon concentrations in the nearshore and bay in the late summer of 2010 that were 100 x that found in May. In addition, Turner et al. concluded that the distinction between oiled and unoiled sites became blurred over time as oil residues were redistributed with tides and storm events. Thus, oil residues, including dissolved aromatics, spread over an area much wider than was initially visibly oiled. Even relatively brief exposures to the water-soluble fraction of aromatics derived from crude oil are known to cause mortality to many infaunal groups (Indiketi et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Monteiro et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Our faunal data also support the hypothesis that oil spill-related effects occurred at our companion reference sites. We observed uncharacteristically low values of diversity and density in 2011 in reference marshes as the density of total macroinfauna was ~\u0026thinsp;80% lower than expected regional values (Fleeger et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Amphipods especially are well known to be intolerant (Monteiro et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Scarlett et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; van Eenennaam et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Widbom and Oviatt \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e1994\u003c/span\u003e) and were at near zero values at heavily oiled sites and very low at moderately oiled and reference sites in 2011. The relative abundance of polychaetes and amphipods are also suggestive of initial mortality in 2011 followed by recovery of the community as polychaetes (the more tolerant taxon), increased in abundance before amphipods (the less tolerant taxon) (Dauvin et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The density of \u003cem\u003eM. aestuarina\u003c/em\u003e, a surface-deposit feeding, tube-dwelling polychaete (Galv\u0026aacute;n et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), that would be readily exposed to dissolved aromatic hydrocarbons from the water column was about 2000 m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e in 2011 in reference marshes while densities from a broad range of locations at the marsh edge are typically five times higher (Bell \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1982\u003c/span\u003e; Johnson et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Finally, the density of total macroinfauna at our reference sites increased to regional averages after about 3 y post-spill, a similar recovery trajectory of macroinfauna after the \u003cem\u003ePrestige\u003c/em\u003e oil spill (Junoy et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Although our companion reference sites were likely impacted, the lower levels of exposure to sediment-associated hydrocarbons compared to moderately and heavily oiled sites and the relatively rapid return to regional means suggests our reference sites can serve as standards for resiliency in the changing environment due to oiling (e.g., in an increasing erosive environment caused by oiling).\u003c/p\u003e \u003cp\u003eThe long recovery time for macroinfauna in heavily oiled marshes should not be unexpected given the profound environmental changes associated with foundational plant mortality and the slow pace of plant recovery. However, a similar slow recovery from other saltmarsh oil spills has been reported (Mendelssohn et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) and novel interactions (Murawski et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Powers et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Wiens et al. \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) and unexpected indirect ecological effects are commonly reported after oil spills (Fleeger et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Henkel et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Lewis et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Peterson \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) that could further impede resiliency. Although the residence time of hydrocarbons buried in saltmarsh soils is measurable in decades, along with continuing effects on saltmarsh fauna (Culbertson et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), our results suggest that it is unlikely that macroinfaunal resiliency will be directly related to hydrocarbon concentrations. Although heavily oiled marshes experienced elevated concentrations of total petroleum hydrocarbon concentrations throughout study period (and an altered microbial community with indicator species associated with hydrocarbon contamination, Cagle et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), hydrocarbon concentration did not significantly explain meiobenthic community variation (that included juvenile macroinfauna) during the middle recovery period (Fleeger et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur results show that the macroinfauna in moderately oiled marshes exhibited resiliency about 8 years post-spill while the community in heavily oiled marshes remained altered relative to companion reference sites. Abundance trends and functional species traits in heavily oiled marshes both differed from reference and moderately oiled sites over time. Our results from heavily oiled marshes reflect a dynamic response by macroinfauna with large variations in densities and diversity that would have been difficult to predict given scant knowledge of the macroinfauna along the saltmarsh edge (only one study before the DWH of macroinfauna in Louisiana marshes was conducted along the marsh edge, McFarlin et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The recovery of macrophytes, the microbial community and periwinkle snails in heavily oiled marshes will also likely take more than a decade (Cagle et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Deis et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Zengel et al. 2022b), suggesting that ecosystem function was broadly altered for years after the spill. Furthermore, heavily oiled sites along the marsh edge that experienced severe oil-induced erosion will be unable to recover to the pre-spill community because these shorelines were permanently lost to open water. In fact, three of our seven fixed sites on the marsh edge were subject to loss due to oil-induced erosion. Zengel et al. (\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2022a\u003c/span\u003e) reviewed studies of erosion induced by oiling from DWS and concluded that erosion (including linear shoreline retreat) in oiled marshes was increased by ~\u0026thinsp;100\u0026ndash;200% over 2\u0026ndash;3 years post-spill suggesting that the DHW contributed to an abrupt, and in some locations, permanent regional declines in the abundance of diversity of saltmarsh macroinfauna.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLouisiana State University requires approval for research with vertebrate animals, as per policies from its IACUC committee. \u0026nbsp;No vertebrates were used in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analyzed during the current study are available in the GRIIDC repository, https://www.griidc.org/\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was made possible by grants from The Gulf of Mexico Research Initiative.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMP sorted samples, identified invertebrates, conducted statistical analyses and contributed prose and editorial comments. JF drafted the manuscript and oversaw most of the sample collection, sorting and data archiving. DJ supervised sample, sorting and identification of invertebrates for two years of the project. RR collected samples in the field, sorted samples and compiled data for much of the project. AH was a participant in all funding applications, experimental design and an active participant in data interpretation and editing of the manuscript. DD was a participant in all funding applications, experimental design and an active participant in data interpretation and editing of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eBaltz, D.M., C. Rakocinski, and J.W. Fleeger. 1993. Microhabitat use by marsh-edge fishes in a Louisiana estuary. \u003cem\u003eEnvironmental Biology of Fishes\u003c/em\u003e 36: 109-126.\u003c/li\u003e\n \u003cli\u003eBam, W., L.M. Hooper-Bui, R.M. Strecker, P.L. Adhikari, and E.B. Overton. 2018. Coupled effects of oil spill and hurricane on saltmarsh terrestrial arthropods. \u003cem\u003ePlos one\u003c/em\u003e 13: e0194941.\u003c/li\u003e\n \u003cli\u003eBarron, M.G., D.N. Vivian, R.A. Heintz, and U.H. Yim. 2020. Long-Term Ecological Impacts from Oil Spills: Comparison of \u0026lt;i\u0026gt;Exxon Valdez\u0026lt;/i\u0026gt;, \u0026lt;i\u0026gt;Hebei Spirit\u0026lt;/i\u0026gt;, and Deepwater Horizon. \u003cem\u003eEnvironmental Science \u0026amp; Technology\u003c/em\u003e 54: 6456-6467.\u003c/li\u003e\n \u003cli\u003eBaumann, M.S., G.F. Fricano, K. Fedeli, C.E. Schlemme, M.C. Christman, and M.V. Carle. 2020. Recovery of salt marsh invertebrates following habitat restoration: Implications for marsh restoration in the northern Gulf of Mexico. \u003cem\u003eEstuaries and Coasts\u003c/em\u003e 43: 711-1721.\u003c/li\u003e\n \u003cli\u003eBell, S.S. 1982. On the population biology and meiofaunal characteristics of \u003cem\u003eManayunkia aestuarina\u003c/em\u003e (Polychaeta: Sabellidae: Fabricinae) from a South Carolina salt marsh. \u003cem\u003eEstuarine, Coastal and Shelf Science\u003c/em\u003e 14: 215-221.\u003c/li\u003e\n \u003cli\u003eBergen, A., C. Alderson, R. Bergfors, C. Aquila, and M. Matsil. 2000. Restoration of a Spartina alterniflora salt marsh following a fuel oil spill, New York City, NY. \u003cem\u003eWetlands Ecology and Management\u003c/em\u003e 8: 185-195.\u003c/li\u003e\n \u003cli\u003eBeseres, J.J., and R.J. Feller. 2007. Importance of predation by white shrimp \u003cem\u003eLitopenaeus setiferus\u003c/em\u003e on estuarine subtidal macrobenthos. \u003cem\u003eJournal of Experimental Marine Biology and Ecology\u003c/em\u003e 344: 193-205.\u003c/li\u003e\n \u003cli\u003eBeyer, J., H.C. Trannum, T. Bakke, P.V. Hodson, and T.K. Collier. 2016. Environmental effects of the Deepwater Horizon oil spill: A review. \u003cem\u003eMarine Pollution Bulletin\u003c/em\u003e 110: 28-51.\u003c/li\u003e\n \u003cli\u003eBledsoe, R., and R. Boopathy. 2016. Bioaugmentation of microbes to restore coastal wetland plants to protect land from coastal erosion. \u003cem\u003eInternational Biodeterioration \u0026amp; Biodegradation\u003c/em\u003e 113: 155-160.\u003c/li\u003e\n \u003cli\u003eBouma, T.J., M.B. De Vries, E. Low, L. Kusters, P.M.J. Herman, I.C. T\u0026aacute;nczos, S. Temmerman, A. Hesselink, P. Meire, and S. van Regenmortel. 2005. Flow hydrodynamics on a mudflat and in salt marsh vegetation:: identifying general relationships for habitat characterisations. \u003cem\u003eHydrobiologia\u003c/em\u003e 540: 259-274.\u003c/li\u003e\n \u003cli\u003eCagle, G., Q. Lin, S.A. Graham, I. Mendelssohn, J.W. Fleeger, D. Deis, D.S. Johnson, J. Zhou, and A. Hou. 2020. Planting Spartina alterniflora in a salt marsh denuded of vegetation by an oil spill induces a rapid response in the soil microbial community. \u003cem\u003eEcological Engineering\u003c/em\u003e 151: 105815.\u003c/li\u003e\n \u003cli\u003eCagle, G.A., H. Chen, J.W. Fleeger, D. Deis, Q. Lin, and A. Hou. 2024. Spatial heterogeneity and oil pollution structured the soil microbial community in salt marshes in Barataria Bay, Louisiana, USA, eight years after the Deepwater Horizon oil spill. \u003cem\u003eEcological Indicators\u003c/em\u003e 160: 111884.\u003c/li\u003e\n \u003cli\u003eClarke K, Gorley R (2006) Primer v6: user manual/tutorial. \u0026nbsp;Primer-E, Plymouth\u003c/li\u003e\n \u003cli\u003eCulbertson, J.B., I. Valiela, Y.S. Olsen, and C.M. Reddy. 2008a. Effect of field exposure to 38-year-old residual petroleum hydrocarbons on growth, condition index, and filtration rate of the ribbed mussel, Geukensia demissa. \u003cem\u003eEnvironmental Pollution\u003c/em\u003e 154: 312-319.\u003c/li\u003e\n \u003cli\u003eCulbertson, J.B., I. Valiela, E.E. Peacock, C.M. Reddy, A. Carter, and R. VanderKruik. 2007. Long-term biological effects of petroleum residues on fiddler crabs in salt marshes. \u003cem\u003eMarine Pollution Bulletin\u003c/em\u003e 54: 955-962.\u003c/li\u003e\n \u003cli\u003eCulbertson, J.B., I. Valiela, M. Pickart, E.E. Peacock, and C.M. Reddy. 2008b. Long-term consequences of residual petroleum on salt marsh grass. \u003cem\u003eJournal of Applied Ecology\u003c/em\u003e 45: 1284-1292.\u003c/li\u003e\n \u003cli\u003eda Cunha Lana, P., and C. Guiss. 1992. Macrofauna\u0026ndash;plant-biomass interactions in a euhaline salt marsh in Paranagu\u0026aacute; Bay (SE Brazil). Mar Ecol Prog Ser 80: 57-64.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eDauvin, J.C., H. Andrade, J. de-la-Ossa-Carretero, Y. Del-Pilar-Ruso, and R. Riera. 2016. Polychaete/amphipod ratios: An approach to validating simple benthic indicators. \u003cem\u003eEcological Indicators\u003c/em\u003e 63: 89-99.\u003c/li\u003e\n \u003cli\u003eDeis, D.R., J.W. Fleeger, D.S. Johnson, I.A. Mendelssohn, Q. Lin, S.A. Graham, S. Zengel, and A. Hou. 2020. Recovery of the salt marsh periwinkle (\u003cem\u003eLittoraria irrorata\u003c/em\u003e) 9 years after the \u003cem\u003eDeepwater Horizon\u003c/em\u003e oil spill: Size matters. \u003cem\u003eMarine Pollution Bulletin\u003c/em\u003e 160: 111581.\u003c/li\u003e\n \u003cli\u003eDeis, D.R., I.A. Mendelssohn, J.W. Fleeger, S.M. Bourgoin, and Q. Lin. 2019. Legacy effects of Hurricane Katrina influenced marsh shoreline erosion following the Deepwater Horizon oil spill. \u003cem\u003eScience of The Total Environment\u003c/em\u003e 672: 456-467.\u003c/li\u003e\n \u003cli\u003eDeLaune, R.D., C.J. Smith, W.H.J. Patrick, J.W. Fleeger, and M.D. Tolley. 1984. Effect of oil on salt marsh biota: Methods for restoration. \u003cem\u003eEnviron. Pollut\u003c/em\u003e 36: 207-227.\u003c/li\u003e\n \u003cli\u003eDong, Y., Y. Liu, C. Hu, I.R. MacDonald, and Y. Lu. 2022. Chronic oiling in global oceans. \u003cem\u003eScience\u003c/em\u003e 376: 1300-1304.\u003c/li\u003e\n \u003cli\u003eEngle, V.D. 2011. Estimating the Provision of Ecosystem Services by Gulf of Mexico Coastal Wetlands. \u003cem\u003eWetlands\u003c/em\u003e 31: 179-193.\u003c/li\u003e\n \u003cli\u003eFleeger, J.W., K.R. Carman, M.R. Riggio, I.A. Mendelssohn, Q.X. Lin, A. Hou, D.R. Deis, and S. Zengel. 2015. Recovery of salt marsh benthic microalgae and meiofauna following the \u003cem\u003eDeepwater Horizon\u003c/em\u003e oil spill linked to recovery of \u003cem\u003eSpartina alterniflora\u003c/em\u003e. \u003cem\u003eMarine Ecology Progress Series\u003c/em\u003e 536: 39-54.\u003c/li\u003e\n \u003cli\u003eFleeger, J.W., D.S. Johnson, S. Zengel, I.A. Mendelssohn, D.R. Deis, S.A. Graham, Q. Lin, M.C. Christman, M.R. Riggio, and M. Pant. 2020. Macroinfauna responses and recovery trajectories after an oil spill differ from those following saltmarsh restoration. \u003cem\u003eMarine Environmental Research\u003c/em\u003e 155.\u003c/li\u003e\n \u003cli\u003eFleeger, J.W., D.S. Johnson, S.A. Zengel, I.A. Mendelssohn, D.R. Deis, and S.A. Graham. 2022. A Macroinfaunal Ecosystem Engineer May Facilitate Recovery of Benthic Invertebrates and Accompanying Ecosystem Services After an Oil Spill. \u003cem\u003eEstuaries and Coasts\u003c/em\u003e 45: 582-591.\u003c/li\u003e\n \u003cli\u003eFleeger, J.W., M.R. Riggio, I.A. Mendelssohn, Q. Lin, D.R. Deis, D.S. Johnson, K.R. Carman, S.A. Graham, S. Zengel, and A. Hou. 2019. What promotes the recovery of salt marsh infauna after oil spills? \u003cem\u003eEstuaries and Coasts\u003c/em\u003e 42: 204-217.\u003c/li\u003e\n \u003cli\u003eFleeger, J.W., M.R. Riggio, I.A. Mendelssohn, Q. Lin, A. Hou, and D.R. Deis. 2018. Recovery of saltmarsh meiofauna six years after the Deepwater Horizon oil spill. \u003cem\u003eJournal of Experimental Marine Biology and Ecology\u003c/em\u003e 502: 182-190.\u003c/li\u003e\n \u003cli\u003eFormel, S.K., K.L. Mighell, D. Kandalepas, E. Jarrell, B.M. Bernik, V. Elango, J.H. Pardue, M.J. Blum, and S.A. Van Bael. 2022. Spatial and temporal comparisons of salt marsh soil fungal communities following the deepwater horizon spill. \u003cem\u003eWetlands Ecology and Management\u003c/em\u003e 30: 239-256.\u003c/li\u003e\n \u003cli\u003eFry, B., D.M. Baltz, M.C. Benfield, J.W. Fleeger, A. Grace, H.L. Haas, and Z.J. Qui\u0026ntilde;ones-Rivera. 2003. Chemical indicators of movement and residency for brown shrimp (\u003cem\u003eFarfantepenaeus aztecus\u003c/em\u003e) in coastal Louisiana marshscapes. \u003cem\u003eEstuaries\u003c/em\u003e 26: 82-97.\u003c/li\u003e\n \u003cli\u003eGalv\u0026aacute;n, K.A., J.W. Fleeger, and B. Fry. 2008. Stable isotope addition reveals dietary importance of phytoplankton and benthic microalgae to saltmarsh infauna. \u003cem\u003eMarine Ecology Progress Series\u003c/em\u003e 359: 37-49.\u003c/li\u003e\n \u003cli\u003eGalv\u0026aacute;n, K.A., J.W. Fleeger, B.J. Peterson, D.C. Drake, L.A. Deegan, and D.S. Johnson. 2011. Natural abundance stable isotopes and dual isotope tracer additions help to resolve resources supporting a saltmarsh food web. \u003cem\u003eJournal of Experimental Marine Biology and Ecology\u003c/em\u003e 410: 1-11.\u003c/li\u003e\n \u003cli\u003eHenkel, J.R., B.J. Sigel, and C.M. Taylor. 2012. Large-Scale Impacts of the \u0026lt;i\u0026gt;Deepwater Horizon\u0026lt;/i\u0026gt; Oil Spill: Can Local Disturbance Affect Distant Ecosystems through Migratory Shorebirds? \u003cem\u003eBioscience\u003c/em\u003e 62: 676-685.\u003c/li\u003e\n \u003cli\u003eHusseneder, C., J.-S. Park, and L.D. Foil. 2018. Recovery of horse fly populations in Louisiana marshes following the Deepwater Horizon oil spill. \u003cem\u003eScientific Reports\u003c/em\u003e 8: 13777.\u003c/li\u003e\n \u003cli\u003eIndiketi, N., M.C. Grenon, P. Groleau, \u0026Eacute;. Veilleux, G. Triffault-Bouchet, and P. Couture. 2022. The effects of dissolved petroleum hydrocarbons on benthic organisms: Chironomids and amphipods. \u003cem\u003eEcotoxicology and Environmental Safety\u003c/em\u003e 237.\u003c/li\u003e\n \u003cli\u003eJohnson, D.S., J.W. Fleeger, K.A. Galv\u0026aacute;n, and E.B. Moser. 2007. Worm holes and their space-time continuum: \u0026nbsp;Spatial and temporal variability of macroinfaunal annelids in a northern New England salt marsh. \u003cem\u003eEstuaries and Coasts\u003c/em\u003e 30: 226-237.\u003c/li\u003e\n \u003cli\u003eJunoy, J., C. Castellanos, R. Bernardo-Madrid, R. Riera, and J.M. Vi\u0026eacute;itez. 2014. Macroinfaunal recovery on the beach most severely affected by the \u0026apos;Prestige\u0026apos; oil spill (O Rostro, Galicia, north-west Spain). \u003cem\u003eJournal of the Marine Biological Association of the United Kingdom\u003c/em\u003e 94: 17-24.\u003c/li\u003e\n \u003cli\u003eKawaida, S., M. Horinouchi, K. Kurata, and K. Toda. 2024. Differences in benthic assemblage structures between vegetated and unvegetated habitats in a salt marsh in Lake Shinji, western Japan. \u003cem\u003eFisheries Science,\u0026nbsp;\u003c/em\u003e2024, 1-14.\u003c/li\u003e\n \u003cli\u003eKristensen, E., M. Delefosse, C.O. Quintana, M.R. Flindt, and T. Valdemarsen. 2014. Influence of benthic macrofauna community shifts on ecosystem functioning in shallow estuaries. \u003cem\u003eFrontiers in Marine Science, 2014, 1-14.\u003c/em\u003e\u003c/li\u003e\n \u003cli\u003eLacoste, \u0026Eacute;., A. Piot, P. Archambault, C.W. McKindsey, and C. Nozais. 2018. Bioturbation activity of three macrofaunal species and the presence of meiofauna affect the abundance and composition of benthic bacterial communities. \u003cem\u003eMarine environmental research\u003c/em\u003e 136: 62-70.\u003c/li\u003e\n \u003cli\u003eLewis, J.P., J.H. Tarnecki, S.B. Garner, D.D. Chagaris, and W.F. Patterson. 2020. Changes in Reef Fish Community Structure Following the Deepwater Horizon Oil Spill. \u003cem\u003eScientific Reports\u003c/em\u003e 10.\u003c/li\u003e\n \u003cli\u003eLin, Q., I.A. Mendelssohn, S. Graham, A. Hou, J.W. Fleeger, and D.R. Deis. 2016. Response of salt marshes to oiling from the \u003cem\u003eDeepwater Horizon\u003c/em\u003e Spill: Implications for plant growth, soil surface-erosion, and shoreline stability. \u003cem\u003eScience of the Total Environment\u003c/em\u003e 557-558: 369-377.\u003c/li\u003e\n \u003cli\u003eLumibao, C.Y., S. Formel, V. Elango, J.H. Pardue, M. Blum, and S.A. Van Bael. 2018. Persisting responses of salt marsh fungal communities to the Deepwater Horizon oil spill. \u003cem\u003eScience of The Total Environment\u003c/em\u003e 642: 904-913.\u003c/li\u003e\n \u003cli\u003eMalakauskas, D.M., S.J. Willson, M.A. Wilzbach, and N.A. Som. 2013. Flow variation and substrate type affect dislodgement of the freshwater polychaete, \u0026lt;i\u0026gt;Manayunkia speciosa\u0026lt;/i\u0026gt;. \u003cem\u003eFreshwater Science\u003c/em\u003e 32: 862-873.\u003c/li\u003e\n \u003cli\u003eMcCloy, M.W., R.K. Andringa, and J.K. Grace. 2022. Resilience of avian communities to urbanization and climate change: An Integrative Review. \u003cem\u003eFrontiers in Conservation Science\u003c/em\u003e 3: 918873.\u003c/li\u003e\n \u003cli\u003eMcFarlin, C.R., T.D. Bishop, M.W. Hester, and M. Alber. 2015. Context-dependent effects of the loss of \u003cem\u003eSpartina alterniflora\u003c/em\u003e on salt marsh invertebrate communities. \u003cem\u003eEstuarine, Coastal and Shelf Science\u003c/em\u003e 163: 218-230.\u003c/li\u003e\n \u003cli\u003eMendelssohn, I.A., G.L. Andersen, D.M. Baltz, R.H. Caffey, K.R. Carman, J.W. Fleeger, S.B. Joye, Q. Lin, E. Maltby, and E.B. Overton. 2012. Oil impacts on coastal wetlands: implications for the Mississippi River Delta ecosystem after the Deepwater Horizon oil spill. \u003cem\u003eBioScience\u003c/em\u003e 62: 562-574.\u003c/li\u003e\n \u003cli\u003eMichel, J., E.H. Owens, S. Zengel, A. Graham, Z. Nixon, T. Allard, W. Holton, P. Reimer, A. Lamarche, M. White, N. Rutherford, C. Childs, G. Mauseth, G. Challenger, and E. Taylor. 2013. Extent and Degree of Shoreline Oiling: Deepwater Horizon Oil Spill, Gulf of Mexico, USA. \u003cem\u003ePlos One\u003c/em\u003e 8.\u003c/li\u003e\n \u003cli\u003eMonteiro, L., W. Traunspurger, F. Lynen, and T. Moens. 2019. Effects of the water-soluble fraction of a crude oil on estuarine meiofauna: A microcosm approach. \u003cem\u003eMarine Environmental Research\u003c/em\u003e 147: 113-125.\u003c/li\u003e\n \u003cli\u003eMoyo, S., H. Bennadji, D. Laguaite, A.A. P\u0026eacute;rez-Umphrey, A.M. Snider, A. Bonisoli-Alquati, J.A. Olin, P.C. Stouffer, S.S. Taylor, and P.C. L\u0026oacute;pez-Duarte. 2021. Stable isotope analyses identify trophic niche partitioning between sympatric terrestrial vertebrates in coastal saltmarshes with differing oiling histories. \u003cem\u003ePeerJ\u003c/em\u003e 9: e11392.\u003c/li\u003e\n \u003cli\u003eMurawski, S.A., P.T. Schwing, W.F. Patterson, T.T. Sutton, P.A. Montagna, R.J. Milligan, S.B. Joye, L. Thomas, J.P. Kilborn, C.B. Paris, R. Faillettaz, D.S. Portnoy, and S. Gilbert. 2023. Vulnerability and resilience of living marine resources to the \u0026lt;i\u0026gt;Deepwater Horizon\u0026lt;/i\u0026gt; oil spill: an overview. \u003cem\u003eFrontiers in Marine Science\u003c/em\u003e 10.\u003c/li\u003e\n \u003cli\u003eNelson, J.A., D.S. Johnson, L.A. Deegan, A.C. Spivak, and N.R. Sommer. 2019. Feedbacks between nutrient enrichment and geomorphology alter bottom-up control on food webs. \u003cem\u003eEcosystems\u003c/em\u003e 22: 229-242.\u003c/li\u003e\n \u003cli\u003eNixon, Z., S. Zengel, M. Baker, M. Steinhoff, G. Fricano, S. Rouhani, and J. Michel. 2016. Shoreline oiling from the Deepwater Horizon oil spill. \u003cem\u003eMarine Pollution Bulletin\u003c/em\u003e 107: 170-178.\u003c/li\u003e\n \u003cli\u003eOksanen J, Simpson G, Blanchet F, Kindt R, Legendre P, Minchin P, O\u0026apos;Hara R, Solymos P, Stevens M, Szoecs E, Wagner H, Barbour M, Bedward M, Bolker B, Borcard D, Carvalho G, Chirico M, De Caceres M, Durand S, Evangelista H, FitzJohn R, Friendly M, Furneaux B, Hannigan G, Hill M, Lahti L, McGlinn D, Ouellette M, Ribeiro Cunha E, Smith T, Stier A, Ter Braak C, Weedon J (2024). _vegan: Community Ecology Package_. R package version 2.6-6.1, https://CRAN.R-project.org/package=vegan\u003c/li\u003e\n \u003cli\u003ePeterson, C.H. 2001. The \u0026quot;Exxon Valdez\u0026quot; oil spill in Alaska: Acute, indirect and chronic effects on the ecosystem. \u003cem\u003eAdv. Mar. Biol\u003c/em\u003e 39: 1-103.\u003c/li\u003e\n \u003cli\u003ePowers, S.P., F.J. Hernandez, R.H. Condon, J.M. Drymon, and C.M. Free. 2013. Novel Pathways for Injury from Offshore Oil Spills: Direct, Sublethal and Indirect Effects of the \u0026lt;i\u0026gt;Deepwater Horizon\u0026lt;/i\u0026gt; Oil Spill on Pelagic \u0026lt;i\u0026gt;Sargassum\u0026lt;/i\u0026gt; Communities. \u003cem\u003ePlos One\u003c/em\u003e 8.\u003c/li\u003e\n \u003cli\u003eRabalais, N.N., and R.E. Turner. 2016. Effects of the Deepwater Horizon Oil Spill on Coastal Marshes and Associated Organisms. \u003cem\u003eOceanography\u003c/em\u003e 29: 150-159.\u003c/li\u003e\n \u003cli\u003eReddy, C.M., T.I. Eglinton, A. Hounshell, H.K. White, L. Xu, R.B. Gaines, and G.S. Frysinger. 2002. The west falmouth oil spill after thirty years: The persistence of petroleum hydrocarbons in marsh Sediments. \u003cem\u003eEnvironmental Science \u0026amp; Technology\u003c/em\u003e 36: 4754-4760.\u003c/li\u003e\n \u003cli\u003eReuscher, M.G., J.G. Baguley, N. Conrad-Forrest, C. Cooksey, J.L. Hyland, C. Lewis, P.A. Montagna, R.W. Ricker, M. Rohal, and T. Washburn. 2017. Temporal patterns of Deepwater Horizon impacts on the benthic infauna of the northern Gulf of Mexico continental slope. \u003cem\u003ePlos One\u003c/em\u003e 12.\u003c/li\u003e\n \u003cli\u003eR Core Team (2024). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. \u0026lt;https://www.R-project.org/\u0026gt;\u003c/li\u003e\n \u003cli\u003eRoth, A.M.F., and D.M. Baltz. 2009. Short-Term Effects of an Oil Spill on Marsh-Edge Fishes and Decapod Crustaceans. \u003cem\u003eEstuaries and Coasts\u003c/em\u003e 32: 565-572.\u003c/li\u003e\n \u003cli\u003eSakamaki, T., and J.S. Richardson. 2009. Dietary responses of tidal flat macrobenthos to reduction of benthic microalgae: a test for potential use of allochthonous organic matter. \u003cem\u003eMarine Ecology-Progress Series\u003c/em\u003e 386: 107-113.\u003c/li\u003e\n \u003cli\u003eSanders, H.L., J.F. Grassle, G.R. Hampson, L.S. Morse, S. Garner-Price, and C.C. Jones. 1980. Anatomy of an oil spill: long-term effects from the grounding of the barge Florida off West Falmouth, Massachusetts. \u003cem\u003eJ. Mar. Res\u003c/em\u003e 38: 265-380.\u003c/li\u003e\n \u003cli\u003eSantos, S.L., and J.L. Simon. 1980. Response of soft-bottom benthos to annual catastrophic disturbance in a South Florida estuary. \u003cem\u003eMar. Ecol. Prog. Ser\u003c/em\u003e 3: 347-355.\u003c/li\u003e\n \u003cli\u003eScarlett, A., S.J. Rowland, M. Canty, E.L. Smith, and T.S. Galloway. 2007. Method for assessing the chronic toxicity of marine and estuarine sediment-associated contaminants using the amphipod \u0026lt;i\u0026gt;Corophium volutator\u0026lt;/i\u0026gt;. \u003cem\u003eMarine Environmental Research\u003c/em\u003e 63: 457-470.\u003c/li\u003e\n \u003cli\u003eTurner, R.E., N.N. Rabalais, E.B. Overton, B.M. Meyer, G. McClenachan, E.M. Swenson, M. Besonen, M.L. Parsons, and J. Zingre. 2019. Oiling of the continental shelf and coastal marshes over eight years after the 2010 Deepwater Horizon oil spill. \u003cem\u003eEnvironmental Pollution\u003c/em\u003e 252: 1367-1376.\u003c/li\u003e\n \u003cli\u003evan Eenennaam, J.S., S. Rahsepar, J.R. Radovic, T.B.P. Oldenburg, J. Wonink, A.A.M. Langenhoff, A.J. Murk, and E.M. Foekema. 2018. Marine snow increases the adverse effects of oil on benthic invertebrates. \u003cem\u003eMarine Pollution Bulletin\u003c/em\u003e 126: 339-348.\u003c/li\u003e\n \u003cli\u003eUnited States v. BP Exploration \u0026amp; Prod., Inc. (In re Oil Spill by the Oil Rig \u0026ldquo;Deepwater Horizon\u0026rdquo;), 21 F. Supp. 3d 657 (E.D. La. 2014)\u003c/li\u003e\n \u003cli\u003eWeerman, E.J., P.M.J. Herman, and J. van de Koppel. 2011. Macrobenthos abundance and distribution on a spatially patterned intertidal flat. \u003cem\u003eMarine Ecology Progress Series\u003c/em\u003e 440: 95-103.\u003c/li\u003e\n \u003cli\u003eWhipple, S.A., J.W. Fleeger, and L.L. Cook. 1981. The influence of tidal flushing, light exposure and natant macrofauna on edaphic chlorophyll\u003cem\u003e\u0026nbsp;a\u0026nbsp;\u003c/em\u003ein a Louisiana salt marsh. \u003cem\u003eEstuarine, Coastal and Shelf Science\u003c/em\u003e 13: 637-643.\u003c/li\u003e\n \u003cli\u003eWhitcraft, C.R., and L.A. Levin. 2007. Regulation of benthic algal and animal communities by salt marsh plants: Impact of shading. \u003cem\u003eEcology\u003c/em\u003e 88: 904-917.\u003c/li\u003e\n \u003cli\u003eWhomersley, P., M. Huxham, S. Bolam, M. Schratzberger, J. Augley, and D. Ridland. 2010. Response of intertidal macrofauna to multiple disturbance types and intensities - An experimental approach. \u003cem\u003eMarine Environmental Research\u003c/em\u003e 69: 297-308.\u003c/li\u003e\n \u003cli\u003eWidbom, B., and C.A. Oviatt. 1994. THE WORLD-PRODIGY OIL-SPILL IN NARRAGANSETT BAY, RHODE-ISLAND - ACUTE EFFECTS ON MACROBENTHIC CRUSTACEAN POPULATIONS. \u003cem\u003eHydrobiologia\u003c/em\u003e 291: 115-124.\u003c/li\u003e\n \u003cli\u003eWiens, J.A., T.O. Crist, R.H. Day, S.M. Murphy, and G.D. Hayward. 2001. A canonical correspondence analysis of the effects of the \u0026lt;i\u0026gt;Exxon Valdez\u0026lt;/i\u0026gt; oil spill on marine birds. \u003cem\u003eEcological Applications\u003c/em\u003e 11: 828-839.\u003c/li\u003e\n \u003cli\u003eZengel, S., B.M. Bernik, N. Rutherford, Z. Nixon, and J. Michel. 2015. Heavily oiled salt marsh following the \u003cem\u003eDeepwater Horizon\u003c/em\u003e oil spill, Ecological comparisons of shoreline cleanup treatments and recovery. \u003cem\u003ePlos One\u003c/em\u003e 10.\u003c/li\u003e\n \u003cli\u003eZengel, S., C.L. Montague, S.C. Pennings, S.P. Powers, M. Steinhoff, G. Fricano, C. Schlemme, M.N. Zhang, J. Oehrig, Z. Nixon, S. Rouhani, and J. Michel. 2016a. Impacts of the \u003cem\u003eDeepwater Horizon\u003c/em\u003e oil spill on salt marsh periwinkles (\u003cem\u003eLittoraria irrorata\u003c/em\u003e). \u003cem\u003eEnvironmental Science \u0026amp; Technology\u003c/em\u003e 50: 643-652.\u003c/li\u003e\n \u003cli\u003eZengel, S., Z. Nixon, J. Weaver, N. Rutherford, B.M. Bernik, and J. Michel. 2022a. Accelerated marsh erosion following the Deepwater Horizon oil spill confirmed, ameliorated by planting. \u003cem\u003eScientific Reports\u003c/em\u003e 12: 13802.\u003c/li\u003e\n \u003cli\u003eZengel, S., S.C. Pennings, B. Silliman, C. Montague, J. Weaver, D.R. Deis, M.O. Krasnec, N. Rutherford, and Z. Nixon. 2016b. \u003cem\u003eDeepwater Horizon\u003c/em\u003e oil spill impacts on salt marsh fiddler crabs (\u003cem\u003eUca\u003c/em\u003e spp.). \u003cem\u003eEstuaries and Coasts\u003c/em\u003e 39: 1154-1163.\u003c/li\u003e\n \u003cli\u003eZengel, S., J. Weaver, I.A. Mendelssohn, S.A. Graham, Q. Lin, M.W. Hester, J.M. Willis, B.R. Silliman, J.W. Fleeger, G. McClenachan, N.N. Rabalais, R.E. Turner, A.R. Hughes, J. Cebrian, D.R. Deis, N. Rutherford, and B.J. Roberts. 2022b. Meta-analysis of salt marsh vegetation impacts and recovery: a synthesis following the Deepwater Horizon oil spill. \u003cem\u003eEcological Applications\u003c/em\u003e 32: e02489.\u003c/li\u003e\n \u003cli\u003eZhou, Z., T.J. Grandjean, J. de Smit, J. van Belzen, G.S. Fivash, B. Walles, O. Beauchard, J. van Dalen, D.B. Blok, and L. van IJzerloo. 2024. Sediment dynamics shape macrofauna mobility traits and abundance on tidal flats. \u003cem\u003eLimnology and Oceanography\u003c/em\u003e.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"estuaries-and-coasts","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"esco","sideBox":"Learn more about [Estuaries and Coasts](https://www.springer.com/journal/12237)","snPcode":"12237","submissionUrl":"https://www.editorialmanager.com/esco/","title":"Estuaries and Coasts","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"macroinfauna, resiliency, Deepwater Horizon oil spill, salt marsh","lastPublishedDoi":"10.21203/rs.3.rs-5582083/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5582083/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTo examine invertebrate resiliency after the 2010 \u003cem\u003eDeepwater Horizon\u003c/em\u003e oil spill, we monitored the recovery of macroinfauna in replicated reference, moderately and heavily oiled salt marshes in Barataria Bay Louisiana for 8.5 y after the spill. Plants suffered near 100% mortality in heavily oiled marshes, profoundly altering the sedimentary environment. Plants in moderately oiled marshes did not suffer extensive mortality but experienced reduced above- and belowground plant biomass. A community analysis based on 40 macroinfaunal taxa was conducted during early, 2011\u0026ndash;2012, middle, 2013\u0026ndash;2017 and late, 2017\u0026ndash;2018, stages of recovery. The early stage was marked by very low taxonomic diversity and low total macroinfaunal abundance in all marshes, while the middle stage was denoted by relatively high diversity and very high abundances in heavily oiled marshes where densities far exceeded reference and regional means. The community in the heavily oiled marshes diverged from reference and moderately oiled marshes during the middle recovery period when the crustaceans \u003cem\u003eApocorophium louisianum\u003c/em\u003e and \u003cem\u003eLeptochelia rapax\u003c/em\u003e, the polychaete \u003cem\u003eAlitta succinea\u003c/em\u003e, and oligochaetes dramatically increased in abundance, while at the same time, abundance increases of the polychaetes \u003cem\u003eManayunkia aestuarina, Streblospio gynobrachiata\u003c/em\u003e, and Capitellidae sp. lagged behind increasing trends at reference and moderately oiled sites. Macroinfaunal community similarity in moderately oiled marshes differed from reference and heavily oiled marshes in all three recovery stages but did not differ from reference sites on the last collection date. Heavily oiled community similarity not only differed from moderately oiled and reference marshes in all three recovery stages but remained different from reference sites on the last collection date. These observations indicate that moderately oiled marshes recovered by about 8 years, but that heavily oiled marshes require more than a decade to achieve resiliency.\u003c/p\u003e","manuscriptTitle":"Recovery of saltmarsh macroinfauna after the Deepwater Horizon Oil Spill","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-09 12:26:18","doi":"10.21203/rs.3.rs-5582083/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2024-12-09T13:01:29+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-12-06T19:00:31+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Estuaries and Coasts","date":"2024-12-05T17:52:56+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-12-05T04:00:36+00:00","index":"","fulltext":""},{"type":"submitted","content":"Estuaries and Coasts","date":"2024-12-04T14:08:40+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"estuaries-and-coasts","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"esco","sideBox":"Learn more about [Estuaries and Coasts](https://www.springer.com/journal/12237)","snPcode":"12237","submissionUrl":"https://www.editorialmanager.com/esco/","title":"Estuaries and Coasts","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"68a61bf5-de44-4153-b478-f52fafd2a448","owner":[],"postedDate":"December 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-03-31T16:03:33+00:00","versionOfRecord":{"articleIdentity":"rs-5582083","link":"https://doi.org/10.1007/s12237-025-01520-5","journal":{"identity":"estuaries-and-coasts","isVorOnly":false,"title":"Estuaries and Coasts"},"publishedOn":"2025-03-24 15:57:10","publishedOnDateReadable":"March 24th, 2025"},"versionCreatedAt":"2024-12-09 12:26:18","video":"","vorDoi":"10.1007/s12237-025-01520-5","vorDoiUrl":"https://doi.org/10.1007/s12237-025-01520-5","workflowStages":[]},"version":"v1","identity":"rs-5582083","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5582083","identity":"rs-5582083","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}