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USGS2017

Shale Gas Development and Brook Trout: Scaling Best Management Practices to Anticipate Cumulative Effects

Shale gas development may involve trade-offs between energy development and benefits provided by natural ecosystems. However, current best management practices (BMPs) focus on mitigating localized ecological degradation. We review evidence for cumulative effects of natural gas development on brook trout (Salvelinus fontinalis) and conclude that BMPs should account for potential watershed-scale effects in addition to localized influences. The challenge is to develop BMPs in the face of uncertainty in the predicted response of brook trout to landscape-scale disturbance caused by gas extraction. We propose a decision-analysis approach to formulating BMPs in the specific case of relatively undisturbed watersheds where there is consensus to maintain brook trout populations during gas development. The decision analysis was informed by existing empirical models that describe brook trout occupancy responses to landscape disturbance and set bounds on the uncertainty in the predicted responses to shale gas development. The decision analysis showed that a high efficiency of gas development (e.g., 1 well pad per square mile and 7 acres per pad) was critical to achieving a win-win solution characterized by maintaining brook trout and maximizing extraction of available gas. This finding was invariant to uncertainty in predicted response of brook trout to watershed-level disturbance. However, as the efficiency of gas development decreased, the optimal BMP depended on the predicted response, and there was considerable potential value in discriminating among predictive models through adaptive management or research. The proposed decision-analysis framework provides an opportunity to anticipate the cumulative effects of shale gas development, account for uncertainty, and inform management decisions at the appropriate spatial scales.

Environmental Practice↗

USGS2022

The hydroclimate niche: A tool for predicting and managing riparian plant community responses to streamflow seasonality

Habitat suitability is a consequence of interacting environmental factors. In riparian ecosystems, suitable plant habitat is influenced by interactions between stream hydrology and climate, hereafter referred to as “hydroclimate”. We tested the hypothesis that hydroclimate variables would improve the fit of ecological niche models for a suite of riparian species using occurrence data from the western United States. We focus on the climate conditions (temperature, precipitation and vapor pressure deficit) during the months of lowest and highest streamflow as integrative hydroclimate metrics of resource and stress levels. We found that the inclusion of hydroclimate variables improved model fit for all species in the western USA dataset. We then tested the utility of the improved habitat suitability models by projecting them onto a regulated segment of the Colorado River to assess potential impacts of streamflow seasonality on vegetation metrics of management concern. Species frequency derived from independent survey data in the Colorado River segment was significantly higher for species with predicted suitable habitat than for species without predicted suitable habitat. Under different simulated hydrographs for the Colorado River, overall species richness was predicted to be greatest with peak streamflows during summer, and native-to-non-native species ratios were predicted to be greatest with lowest streamflows in winter. Summer high flows were particularly associated with higher predicted habitat suitability for species that have increased in cover over recent decades (e.g., Pluchea sericea, Baccharis species). We conclude that hydroclimate covariates can be useful tools for predicting how riparian vegetation communities respond to changes in the seasonal timing of low and high streamflows.

River Research and Applications↗

USGS2015

Investigating the temporal effects of metal-based coagulants to remove mercury from solution in the presence of dissolved organic matter

The presence of mercury (Hg), particularly methylmercury (MeHg), is a concern for both human and ecological health as MeHg is a neurotoxin and can bioaccumulate to lethal levels in upper trophic level organisms. Recent research has demonstrated that coagulation with metal-based salts can effectively remove both inorganic mercury (IHg) and MeHg from solution through association with dissolved organic matter (DOM) and subsequent flocculation and precipitation. In this study, we sought to further examine interactions between Hg and DOM and the resulting organo-metallic precipitate (floc) to assess if (1) newly added IHg could be removed to the same extent as ambient IHg or whether the association between IHg and DOM requires time, and (2) once formed, if the floc has the capacity to remove additional Hg from solution. Agricultural drainage water samples containing ambient concentrations of both DOM and IHg were spiked with a traceable amount of isotopically enriched IHg and dosed with ferric sulfate after 0, 1, 5, and 30 days. Both ambient and newly added IHg were removed within hours, with 69–79 % removed. To a separate sample set, isotopically enriched IHg was added to solution after floc had formed. Under those conditions, 81–95 % of newly added Hg was removed even at Hg concentrations 1000-fold higher than ambient levels. Results of this study indicate coagulation with ferric sulfate effectively removes both ambient and newly added IHg entering a system and suggests rapid association between IHg and DOM. This work also provides new information regarding the ability of floc to remove additional Hg from solution even after it has formed.

Environmental Management↗

USGS2023

Using public litigation records to identify priority science needs for managing public lands

Relevant science is essential for effective natural resource decision making, including on public lands managed by the United States Department of the Interior (DOI) Bureau of Land Management (BLM), that cover 1/10th of the United States. Most of the BLM’s management decisions require analyses under the National Environmental Policy Act, and the use of science in these decisions is often challenged. Using coproduction, we assembled an interagency team of scientists and resource managers to develop a method for using public litigation to identify priority science needs for the BLM. We searched publicly available case documents finalized from 2015–2019 in Wyoming, Colorado, Utah, and New Mexico within federal courts and the DOI Office of Hearings and Appeals, and identified 108 case documents that involved challenges to the BLM’s use of science. We retained 48 case documents that contained at least one challenge about the BLM’s use of science for a specific resource. We categorized all challenges in each case document according to the proposed action, affected resource, type of science challenged (data about resources, science relevant to potential impacts, methods for analyzing potential impacts, and mitigation actions), and specific nature of the challenge (e.g., challenging direct effects analysis). We identified priority science needs based on the frequency of challenges, the number of states where similar challenges occurred, whether the BLM lost the challenge, and whether the case was remanded. Top needs related to oil and gas development actions and included science about effects on air quality and climate, water, and socioeconomics; data for air quality and climate; and methods for analyzing potential impacts to cultural resources and air quality and climate. The BLM can use this information to prioritize actions (e.g., funding new research or science syntheses) to strengthen its science foundation for decision-making.

Colorado, New Mexico, Utah, Wyoming↗

USGS2023

Hawksbill and green turtle niche overlap in a marine protected area, US Virgin Islands

Studying how species interact with their environment and other co-occurring species are 2 main aspects of ecology. For marine turtles, ocean currents drive migratory routes and may determine the location of surrounding foraging grounds. As a result, circumglobal species like the hawksbill turtle Eretmochelys imbricata and green turtle Chelonia mydas adapt to diverse foraging habitats and employ varied feeding strategies. Dietary specializations may reduce competition for available food and space resources between co-occurring hawksbill and green turtles in US Virgin Island shallow reef habitats. This study analyzed isotopic data from immature hawksbill (n = 49; range: 18.7-49.8 cm straight carapace length [SCL]) and green turtles (n = 225; range: 24.1-69.4 cm SCL) to examine foraging niche. We used nitrogen stable isotope (δ 15 N) values as an indicator of trophic positioning and carbon stable isotope (δ 13 C) values as a habitat variable. Turtles were hand-captured across an 8 yr period (2012-2019), which facilitated the distinction of isotopic patterns in both the environment and among individual turtles. Understanding variations in habitat, community dynamics, and dietary consumption allowed us to utilize a 5 point framework to translate isotopic space to foraging niche. We found that the site’s relatively stable environmental conditions allow for isotopic overlap between hawksbill and green turtles despite the specialized feeding strategies each species employs. We also underscore the need to evaluate species-specific tissue turnover estimates as evidenced by the influence of tropical storms on recaptured turtle isotopic signatures. These findings inform our understanding of resource use for these imperiled species at our study site and are useful for future global isotopic comparisons.

U.S. Virgin Islands↗

USGS2025

Grass carp (Ctenopharyngodon idella) movement states and backwater use can inform removal efforts

Expansion of grass carp ( Ctenopharyngodon idella ) within the Laurentian Great Lakes poses significant ecological and economic risks. Suppression efforts to remove grass carp have increased to curtail population growth, but capture efficiency remains low. One management challenge is the lack of understanding how this invasive species is using its novel habitats in the Great Lakes. This study aimed to identify spatiotemporal patterns in grass carp behavior and backwater use that could be exploited by management efforts, including removal. We used acoustic telemetry to examine when grass carp occurred in areas vulnerable to removal by boat electrofishing in the Sandusky River, Ohio, USA. Hidden Markov models were used to categorize behavioral states and evaluate their relationships with environmental factors. Best performing 2-state and 3-state hidden Markov models included proximity to backwater as a factor in state-dependent step length and transition probability between states, with a higher probability of being in less mobile states during the middle of the day and in backwaters. For the 2-state model, this less mobile state was also more common during warmer temperatures. Distinct diel patterns and backwater use identified in this study provide critical insights for improving management. Model results suggest that current removal efforts, focused primarily on the mainstem of the river, may benefit from adjustments in both timing and removal gear. The findings raise further questions about unobserved behaviors contributing to state assignment and sufficiently flexible adaptive management strategies to account for individual variation in grass carp behavior.

Ohio↗

USGS2013

MODIS phenology image service ArcMap toolbox

Seasonal change is important to consider when managing conservation areas at landscape scales. The study of such patterns throughout the year is referred to as phenology. Recurring life-cycle events that are initiated and driven by environmental factors include animal migration and plant flowering. Phenological events capture public attention, such as fall color change in deciduous forests, the first flowering in spring, and for those with allergies, the start of the pollen season. These events can affect our daily lives, provide clues to help understand and manage ecosystems, and provide evidence of how climate variability can affect the natural cycle of plants and animals. Phenological observations can be gathered at a range of scales, from plots smaller than an acre to landscapes of hundreds to thousands of acres. Linking these observations to diverse disciplines such as evolutionary biology or climate sciences can help further research in species and ecosystem responses to climate change scenarios at appropriate scales. A cooperative study between the National Park Service (NPS), the U.S. Geological Survey (USGS), and the National Aeronautics and Space Administration (NASA) has been exploring how satellite information can be used to summarize phenological patterns observed at the park or landscape scale and how those summaries can be presented to both park managers and visitors. This study specifically addressed seasonal changes in plants, including the onset of growth, photosynthesis in the spring, and the senescence of deciduous vegetation in the fall. The primary objective of the work is to demonstrate that seasonality even in protected areas changes considerably across years. A major challenge is to decouple natural variability from possible trends—directional change that can lead to a permanent and radically different ecosystem state. Trends can be either a gradual degradation of the landscape (often from external influences) or steady improvement (by implementing long-term conservation plans). In either case, it is important to first grasp the magnitude of natural variation so that it is not confused with actual trends. This work used existing and freely available remote sensing data, specifically the NASA-funded 250-meter (m) spatial resolution land-surface phenology product for North America. This product is calculated from an annual record of vegetation health observed by NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. The land-surface phenology product is, in essence, a method to summarize all the observations throughout a year into a few key, ecologically relevant “metrics”.

Open-File Report↗

USGS2011

The role of the Everglades Mangrove Ecotone Region (EMER) in regulating nutrient cycling and wetland productivity in South Florida

The authors summarize the main findings of the Florida Coastal Everglades Long-Term Ecological Research (FCE-LTER) program in the EMER, within the context of the Comprehensive Everglades Restoration Plan (CERP), to understand how regional processes, mediated by water flow, control population and ecosystem dynamics across the EMER landscape. Tree canopies with maximum height <3 m cover 49% of the EMER, particularly in the SE region. These scrub/dwarf mangroves are the result of a combination of low soil phosphorus (P < 59 μg P g dw −1 ) in the calcareous marl substrate and long hydroperiod. Phosphorus limits the EMER and its freshwater watersheds due to the lack of terrigenous sediment input and the phosphorus-limited nature of the freshwater Everglades. Reduced freshwater delivery over the past 50 years, combined with Everglades compartmentalization and a 10 cm rise in coastal sea level, has led to the landward transgression (∼1.5 km in 54 years) of the mangrove ecotone. Seasonal variation in freshwater input strongly controls the temporal variation of nitrogen and P exports (99%) from the Everglades to Florida Bay. Rapid changes in nutrient availability and vegetation distribution during the last 50 years show that future ecosystem restoration actions and land use decisions can exert a major influence, similar to sea level rise over the short term, on nutrient cycling and wetland productivity in the EMER.

Florida↗

USGS2015

Performance of species occurrence estimators when basic assumptions are not met: a test using field data where true occupancy status is known

Populations are rarely censused. Instead, observations are subject to incomplete detection, misclassification and detection heterogeneity that result from human and environmental constraints. Though numerous methods have been developed to deal with observational uncertainty, validation under field conditions is rare because truth is rarely known in these cases. We present the most comprehensive test of occupancy estimation methods to date, using more than 33 000 auditory call observations collected under standard field conditions and where the true occupancy status of sites was known. Basic occupancy estimation approaches were biased when two key assumptions were not met: that no false positives occur and that no unexplained heterogeneity in detection parameters occurs. The greatest bias occurred for dynamic parameters (i.e. local colonization and extinction), and in many cases, the degree of inaccuracy would render results largely useless. We examined three approaches to increase adherence or relax these assumptions: modifying the sampling design, employing estimators that account for false-positive detections and using covariates to account for site-level heterogeneity in both false-negative and false-positive detection probabilities. We demonstrate that bias can be substantially reduced by modifications to sampling methods and by using estimators that simultaneously account for false-positive detections and site-level covariates to explain heterogeneity. Our results demonstrate that even small probabilities of misidentification and among-site detection heterogeneity can have severe effects on estimator reliability if ignored. We challenge researchers to place greater attention on both heterogeneity and false positives when designing and analysing occupancy studies. We provide 9 specific recommendations for the design, implementation and analysis of occupancy studies to better meet this challenge.

Methods in Ecology and Evolution↗

USGS2021

Fire, land cover, and temperature drivers of bat activity in winter

Background Understanding the effects of disturbance events, land cover, and weather on wildlife activity is fundamental to wildlife management. Currently, in North America, bats are of high conservation concern due to white-nose syndrome and wind-energy development impact, but the role of fire as a potential additional stressor has received less focus. Although limited, the vast majority of research on bats and fire in the southeastern United States has been conducted during the growing season, thereby creating data gaps for bats in the region relative to overwintering conditions, particularly for non-hibernating species. The longleaf pine ( Pinus palustris Mill.) ecosystem is an archetypal fire-mediated ecosystem that has been the focus of landscape-level restoration in the Southeast. Although historically fires predominately occurred during the growing season in these systems, dormant-season fire is more widely utilized for easier application and control as a means of habitat management in the region. To assess the impacts of fire and environmental factors on bat activity on Camp Blanding Joint Training Center (CB) in northern Florida, USA, we deployed 34 acoustic detectors across CB and recorded data from 26 February to 3 April 2019, and from 10 December 2019 to 14 January 2020. Results We identified eight bat species native to the region as present at CB. Bat activity was related to the proximity of mesic habitats as well as the presence of pine or deciduous forest types, depending on species morphology ( i.e., body size, wing-loading, and echolocation call frequency). Activity for all bat species was influenced positively by either time since fire or mean fire return interval. Conclusion Overall, our results suggested that fire use provides a diverse landscape pattern at CB that maintains mesic, deciduous habitat within the larger pine forest matrix, thereby supporting the diverse bat community at CB during the dormant season and early spring.

Florida↗

USGS2015

When do we need more data? A primer on calculating the value of information for applied ecologists

Applied ecologists continually advocate further research, under the assumption that obtaining more information will lead to better decisions. Value of information (VoI) analysis can be used to quantify how additional information may improve management outcomes: despite its potential, this method is still underused in environmental decision-making. We provide a primer on how to calculate the VoI and assess whether reducing uncertainty will change a decision. Our aim is to facilitate the application of VoI by managers who are not familiar with decision-analytic principles and notation, by increasing the technical accessibility of the tool. Calculating the VoI requires explicit formulation of management objectives and actions. Uncertainty must be clearly structured and its effects on management outcomes evaluated. We present two measures of the VoI. The expected value of perfect information is a calculation of the expected improvement in management outcomes that would result from access to perfect knowledge. The expected value of sample information calculates the improvement in outcomes expected by collecting a given sample of new data. We guide readers through the calculation of VoI using two case studies: (i) testing for disease when managing a frog species and (ii) learning about demographic rates for the reintroduction of an endangered turtle. We illustrate the use of Bayesian updating to incorporate new information. The VoI depends on our current knowledge, the quality of the information collected and the expected outcomes of the available management actions. Collecting information can require significant investments of resources; VoI analysis assists managers in deciding whether these investments are justified.

Methods in Ecology and Evolution↗

USGS2011

Effects of wetland vs. landscape variables on parasite communities of Rana pipiens: Links to anthropogenic factors

The emergence of several diseases affecting amphibian populations worldwide has prompted investigations into determinants of the occurrence and abundance of parasites in frogs. To understand the spatial scales and identify specific environmental factors that determine risks of parasitism in frogs, helminth communities in metamorphic frogs of the northern leopard frog ( Rana pipiens ) were examined in relation to wetland and landscape factors at local (1 km) and regional (10 km) spatial extents in an agricultural region of Minnesota (USA) using regression analyses, ordination, and variance partitioning techniques. Greater amounts of forested and woody wetland habitats, shorter distances between woody wetlands, and smaller-sized open water patches in surrounding landscapes were the most consistently positive correlates with the abundances, richness, and diversity of helminths found in the frogs. Wetland and local landscape variables were suggested as most important for larval trematode abundances, whereas local and regional landscape variables appeared most important for adult helminths. As previously reported, the sum concentration of atrazine and its metabolite desethylatrazine, was the strongest predictor of larval trematode communities. In this report, we highlight the additional influences of landscape factors. In particular, our data suggest that anthropogenic activities that have resulted in the loss of the availability and connectivity of suitable habitats in the surrounding landscapes of wetlands are associated with declines in helminth richness and abundance, but that alteration of wetland water quality through eutrophication or pesticide contamination may facilitate the transmission of certain parasite taxa when they are present at wetlands. Although additional research is needed to quantify the negative effects of parasitism on frog populations, efforts to reduce inputs of agrochemicals into wetlands to limit larval trematode infections may be warranted, given the current high rates of amphibian declines and extinction events.

Minnesota↗

USGS2020

Permafrost mapping with electrical resistivity tomography in two wetland systems north of the Tanana River, Interior Alaska

Surface-based 2D electrical resistivity tomography (ERT) surveys were used to characterize permafrost distribution at wetland sites on the alluvial plain north of the Tanana River, 20 km southwest of Fairbanks, Alaska, in June and September 2014. The sites were part of an ecologically-sensitive research area characterizing biogeochemical response of this region to warming and permafrost thaw, and the site contained landscape features characteristic of interior Alaska, including thermokarst bog, forested permafrost plateau, and a rich fen. The results show how vegetation reflects shallow (0–10 m depth) permafrost distribution. Additionally, we saw shallow (0–3 m depth) low resistivity areas in forested permafrost plateau potentially indicating the presence of increased unfrozen water content as a precursor to ground instability and thaw. Time-lapse study from June to September suggested a depth of seasonal influence extending several meters below the active layer, potentially as a result of changes in unfrozen water content. A comparison of several electrode geometries (dipole-dipole, extended dipole-dipole, Wenner-Schlumberger) showed that for depths of interest to our study (0–10 m) results were similar, but data acquisition time with dipole-dipole was the shortest, making it our preferred geometry. The results show the utility of ERT surveys to characterize permafrost distribution at these sites, and how vegetation reflects shallow permafrost distribution. These results are valuable information for ecologically sensitive areas where ground-truthing can cause excessive disturbance. ERT data can be used to characterize the exact subsurface geometry of permafrost such that over time an understanding of changing permafrost conditions can be made in great detail. Characterizing the depth of thaw and thermal influence from the surface in these areas also provides important information as an indication of the depth to which carbon storage and microbially-mediated carbon processing may be affected.

Alaska↗

USGS2024

Comparison of seven DNA metabarcoding sampling methods to assess diet in a large avian predator

DNA metabarcoding is a rapidly advancing tool for diet assessment in wildlife ecology. Studies have used a variety of field collection methods to evaluate diet; however, there is a pressing need to understand the differences among sampling methods and the downstream inferential consequences they may have on our ability to document diet accurately and efficiently. We evaluated seven DNA metabarcoding sampling methods to assess the diet of a large avian predator: Buteo lagopus (rough-legged hawk). We collected beak swabs, talon swabs, cheek (buccal) swabs, cloacal swabs, and cloacal loops from captured birds, and collected fecal samples from both captured and uncaptured birds. We described and compared variation in prey recovery within and among the seven sampling methods and identified appropriate analytical methods to compare diet among individuals sampled via different methods. Beak and talon swabs produced the highest prey detection rates, yielded the greatest prey richness per sample, and contributed the most to an individual's total prey richness per sampling occasion compared to other sampling methods. Within individuals sampled using five methods during a single capture occasion, cloacal swabs and cheek swabs positively predicted prey richness and average prey mass, respectively, from fecal samples. While all methods identified similar dominant prey taxa that were consistent with prior diet studies, beak and talon swabs detected greater prey richness at both the individual and population levels. We propose a food residue duration hypothesis whereby methods which sample areas containing food DNA consumed from longer and more continuous pre-sampling time intervals explain variation among sampling methods in observed prey richness. Choice of sampling method can influence predator diet characterization and is particularly important if researchers wish to quantify uncommon diet items or compare diet metrics using samples collected via different methods.

Environmental DNA↗

USGS2018

An analytical framework for estimating aquatic species density from environmental DNA

Environmental DNA (eDNA) analysis of water samples is on the brink of becoming a standard monitoring method for aquatic species. This method has improved detection rates over conventional survey methods and thus has demonstrated effectiveness for estimation of site occupancy and species distribution. The frontier of eDNA applications, however, is to infer species density. Building upon previous studies, we present and assess a modeling approach that aims at inferring animal density from eDNA. The modeling combines eDNA and animal count data from a subset of sites to estimate species density (and associated uncertainties) at other sites where only eDNA data are available. As a proof of concept, we first perform a cross-validation study using experimental data on carp in mesocosms. In these data, fish densities are known without error, which allows us to test the performance of the method with known data. We then evaluate the model using field data from a study on a stream salamander species to assess the potential of this method to work in natural settings, where density can never be known with absolute certainty. Two alternative distributions (Normal and Negative Binomial) to model variability in eDNA concentration data are assessed. Assessment based on the proof of concept data (carp) revealed that the Negative Binomial model provided much more accurate estimates than the model based on a Normal distribution, likely because eDNA data tend to be overdispersed. Greater imprecision was found when we applied the method to the field data, but the Negative Binomial model still provided useful density estimates. We call for further model development in this direction, as well as further research targeted at sampling design optimization. It will be important to assess these approaches on a broad range of study systems.

Ecology and Evolution↗

USGS2020

Shared functional traits explain synchronous changes in long‐term count trends of migratory raptors

Aim Assessing long‐term shifts in faunal assemblages is important to understand the consequences of ongoing global environmental change. One approach to assess drivers of assemblage changes is to identify the traits associated with synchronous shifts in count trends among species. Our research identified traits influencing trends in 73 years of count data on migrating raptors recorded in the north‐eastern USA. Location Pennsylvania, USA. Time period 1946–2018. Major taxa studied Birds of prey/raptors. Methods Migrating raptors were counted during autumn, following a standardized protocol. We used a hierarchical breakpoint model to identify when count trends shifted and to assess the role of traits in driving these trends before and after the breakpoint. Specifically, we quantified the probability of the direction (PD) of an effect of body mass, habitat or dietary specialization, migratory behaviour and susceptibility to dichlorodiphenyltrichloroethane (DDT) on count trends. Results We documented an assemblage‐wide mean shift in count trends of migrating raptors in 1974. In general, species that exhibited negative count trends before the breakpoint exhibited positive count trends afterwards. We found that traits associated with resource use (diet and habitat specialization) had high probabilities of affecting count trends, pre‐ and post‐breakpoint (> 90%). Moreover, the direction of their effects differed during both periods. Unexpectedly, other traits we evaluated, including DDT susceptibility, had relatively weaker associations with count trends. Main conclusions Trait‐based frameworks have promise for testing generalized assumptions about drivers of population trajectories. Historically, DDT was considered a key driver of changes in raptor population trends. However, our analysis suggests that other factors were also relevant. Moreover, the positive association between count trends and generalist behaviour depended on the temporal context. This result has implications for other settings where demographic trends can be linked to traits and help to identify drivers of biodiversity change.

Pennsylvania↗

USGS2021

Oyster model inventory: Identifying critical data and modeling approaches to support restoration of oyster reefs in coastal U.S. Gulf of Mexico waters

Executive Summary Along the coast of the U.S. Gulf of Mexico, the eastern oyster ( Crassostrea virginica ) plays important ecological and economic roles. Commercial landings from this region account for more than 50 percent of all U.S. landings; these oyster reefs also provide varied ecosystem services, including nursery habitat for many fish and macroinvertebrate species, shoreline protection, and water-quality maintenance. Declining trends in both total oyster production and functional reef area across this region have spurred investment in restoration of oyster resources, with specific calls for restoration projects to develop a network of reefs and identify broodstock and sanctuary reef restoration sites. Decision making related to restoration and establishment of a network of oyster reefs in the Gulf of Mexico requires information on both the environment and the effects of the environment on the oyster life cycle (including larval movement, survival, oyster recruitment, reproduction, growth, and mortality). Here, we examined the current state of data and model development in this region with the goal of providing an overview of oyster modeling approaches and an inventory of available data and existing oyster models. This report is meant to provide an overview to managers for understanding existing efforts and identify a path forward to most efficiently inform oyster resource management and restoration planning in moving from a single reef management approach to a reef network management approach. Numerous models related to some aspect of the oyster life cycle have been built, calibrated, and validated for various Gulf of Mexico estuaries over the last few decades (over 30 models identified). These models, which could inform site restoration, can be classified into four approaches: (1) oyster Habitat Suitability Index (HSI) models; (2) larval transport models; (3) on-reef oyster models that may include oyster growth, mortality and reproduction, and substrate persistence; and (4) coupled larval transport on-reef metapopulation models that simulate the entire oyster life cycle. The data requirements, model complexity and assumptions, and transferability vary by approach. Specifically, some approaches may offer greater accessibility, flexibility, and transferability spatially or temporally, with minimal data input, but only provide broad information to support site selection. In contrast, other approaches may require significant site-specific data for their construction and validation but may provide more accurate and location-specific data to support site selection for broodstock reefs. Regardless of modeling approach used, data on environmental drivers, such as salinity, water temperature, or water flow impacting oyster metabolism and movement, are required at appropriate spatial and temporal scales. While numerous data collection platforms, environmental models, and research products exist within Gulf of Mexico estuaries to provide important environmental data to use as drivers in the oyster models, significant variability in temporal and spatial coverage of the data, and variation in the availability of future condition models, exists across estuaries. This variation influences the spatial and temporal scales at which oyster models may be developed and impacts the calibration and validation of the oyster models within a given estuary, affecting its potential ability to address specific management or restoration questions. While multiple modeling approaches exist for informing site selection of broodstock or sanctuary oyster reefs, the development, calibration, and validation of a single modeling platform presents the most efficient, transferable, and useful tool for managers across the Gulf of Mexico. The development of a single modeling platform would involve using standardized input variables, governing equations, and assumptions for the modeled oyster processes and outputs, and for standardized calibration and validation procedures that could be applied within each estuary. The differences among estuary applications would require substituting only estuary-specific environmental data, and calibrating and validating the modeling approach with local oyster data. Two modeling approaches likely to be useful include (1) development of a general geospatial HSI modeling framework that could be applied consistently across estuaries and (2) a mechanistic coupled larval transport on-reef metapopulation model requiring only estuarine specific calibration and hydrodynamic models. Both approaches benefit from existing work across multiple Gulf of Mexico estuaries and could provide valuable support for oyster restoration, but may differ in their ability to address specific questions related to oyster restoration. HSI models specifically guide restoration practitioners in determining suitable habitat based on available data. The HSI approach, while currently more widely used and accessible, requires more development of larval suitability and larval input and output components in order to inform reef connectivity. A metapopulation approach considering the full oyster life cycle that simulates both on-reef oyster growth, mortality, reproduction, substrate persistence, and larval transport (ideally with larval growth and mortality) would provide the greatest detail and level of understanding but requires significant up-front investment. The larval oyster model and on-reef oyster model are usually developed independently for systems, although the two approaches can be coupled to represent the entire oyster life cycle in order to characterize and assess a reef metapopulation. This approach may be less accessible and much more data-intensive, however, and it requires some expertise to run and apply to inform oyster resource management. Ultimately, the development of single modeling platforms for each of these approaches would provide flexible tools applicable across all Gulf of Mexico oyster supporting estuaries. By using a single platform for model development, testing, calibrating and validating, and evaluation of modeled future scenarios, oyster restoration scientists and managers would not only be able to examine different scenario outcomes within a single estuary, but could also have comparable modeled results to evaluate potential outcomes, across estuaries and regions, that are not confounded by varying modeled data inputs, governing equations, assumptions, or user judgement.

Alabama, Florida, Louisiana, Mississippi, Texas↗

USGS2011

Multi-scale temporal and spatial variation in genotypic composition of Cladophora-borne Escherichia coli populations in Lake Michigan

High concentrations of Escherichia coli in mats of Cladophora in the Great Lakes have raised concern over the continued use of this bacterium as an indicator of microbial water quality. Determining the impacts of these environmentally abundant E. coli, however, necessitates a better understanding of their ecology. In this study, the population structure of 4285 Cladophora-borne E. coli isolates, obtained over multiple three day periods from Lake Michigan Cladophora mats in 2007-2009, was examined by using DNA fingerprint analyses. In contrast to previous studies that have been done using isolates from attached Cladophora obtained over large time scales and distances, the extensive sampling done here on free-floating mats over successive days at multiple sites provided a large dataset that allowed for a detailed examination of changes in population structure over a wide range of spatial and temporal scales. While Cladophora-borne E. coli populations were highly diverse and consisted of many unique isolates, multiple clonal groups were also present and accounted for approximately 33% of all isolates examined. Patterns in population structure were also evident. At the broadest scales, E. coli populations showed some temporal clustering when examined by year, but did not show good spatial distinction among sites. E. coli population structure also showed significant patterns at much finer temporal scales. Populations were distinct on an individual mat basis at a given site, and on individual days within a single mat. Results of these studies indicate that Cladophora-borne E. coli populations consist of a mixture of stable, and possibly naturalized, strains that persist during the life of the mat, and more unique, transient strains that can change over rapid time scales. It is clear that further study of microbial processes at fine spatial and temporal scales is needed, and that caution must be taken when interpolating short term microbial dynamics from results obtained from weekly or monthly samples.

Water Research↗