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USGS2017

Predicting landscape effects of Mississippi River diversions on soil organic carbon sequestration

Large Mississippi River (MR) diversions (peak water flow >1416 m 3 /s and sediment loads >165 kg/s) have been proposed as part of a suite of coastal restoration projects and are expected to rehabilitate and rebuild wetlands to alleviate the significant historic wetland loss in coastal Louisiana. These coastal wetlands are undergoing increasing eustatic sea‐level rise, land subsidence, climate change, and anthropogenic disturbances. However, the effect of MR diversions on wetland soil organic carbon (SOC) sequestration in receiving basins remains unknown. The rate of SOC sequestration or carbon burial in wetlands is one of the variables used to assess the role of wetland soils in carbon cycling and also to construct wetland carbon budgets. In this study, we examined the effects of MR water and sediment diversions on landscape‐scale SOC sequestration rates that were estimated from vertical accretion for the next 50 yr (2010–2060) under two environmental (moderate and less optimistic) scenarios. Our analyses were based on model simulations taken from the Wetland Morphology model developed for Louisiana's 2012 Coastal Master Plan. The master plan modeled a “future‐without‐action” scenario as well as eight individual MR diversion projects in two of the hydrologic basins (Barataria and Breton Sound). We examined the effects that discharge rates (peak flow) and locations of these individual diversion projects had on SOC sequestration rates. Modeling results indicate that large river diversions are capable of improving basin‐wide SOC sequestration capacity (162–222 g C·m −2 ·yr −1 ) by up to 14% (30 g C·m −2 ·yr −1 ) in Louisiana deltaic wetlands compared to the future‐without‐action scenario, especially under the less optimistic scenario. When large river diversions are placed in the upper receiving basin, SOC sequestration rates are 3.7–10.5% higher (6–24 g C·m −2 ·yr −1 ) than when these structures are placed in the lower receiving basin. Modeling results also indicate that both diversion discharge and location have large effects on SOC sequestration in low‐salinity (freshwater and intermediate marshes) as compared to high‐salinity marshes (brackish and saline marshes).

Louisiana↗

USGS2014

Uncertainty, robustness, and the value of information in managing an expanding Arctic goose population

We explored the application of dynamic-optimization methods to the problem of pink-footed goose (Anser brachyrhynchus) management in western Europe. We were especially concerned with the extent to which uncertainty in population dynamics influenced an optimal management strategy, the gain in management performance that could be expected if uncertainty could be eliminated or reduced, and whether an adaptive or robust management strategy might be most appropriate in the face of uncertainty. We combined three alternative survival models with three alternative reproductive models to form a set of nine annual-cycle models for pink-footed geese. These models represent a wide range of possibilities concerning the extent to which demographic rates are density dependent or independent, and the extent to which they are influenced by spring temperatures. We calculated state-dependent harvest strategies for these models using stochastic dynamic programming and an objective function that maximized sustainable harvest, subject to a constraint on desired population size. As expected, attaining the largest mean objective value (i.e., the relative measure of management performance) depended on the ability to match a model-dependent optimal strategy with its generating model of population dynamics. The nine models suggested widely varying objective values regardless of the harvest strategy, with the density-independent models generally producing higher objective values than models with density-dependent survival. In the face of uncertainty as to which of the nine models is most appropriate, the optimal strategy assuming that both survival and reproduction were a function of goose abundance and spring temperatures maximized the expected minimum objective value (i.e., maxi–min). In contrast, the optimal strategy assuming equal model weights minimized the expected maximum loss in objective value. The expected value of eliminating model uncertainty was an increase in objective value of only 3.0%. This value represents the difference between the best that could be expected if the most appropriate model were known and the best that could be expected in the face of model uncertainty. The value of eliminating uncertainty about the survival process was substantially higher than that associated with the reproductive process, which is consistent with evidence that variation in survival is more important than variation in reproduction in relatively long-lived avian species. Comparing the expected objective value if the most appropriate model were known with that of the maxi–min robust strategy, we found the value of eliminating uncertainty to be an expected increase of 6.2% in objective value. This result underscores the conservatism of the maxi–min rule and suggests that risk-neutral managers would prefer the optimal strategy that maximizes expected value, which is also the strategy that is expected to minimize the maximum loss (i.e., a strategy based on equal model weights). The low value of information calculated for pink-footed geese suggests that a robust strategy (i.e., one in which no learning is anticipated) could be as nearly effective as an adaptive one (i.e., a strategy in which the relative credibility of models is assessed through time). Of course, an alternative explanation for the low value of information is that the set of population models we considered was too narrow to represent key uncertainties in population dynamics. Yet we know that questions about the presence of density dependence must be central to the development of a sustainable harvest strategy. And while there are potentially many environmental covariates that could help explain variation in survival or reproduction, our admission of models in which vital rates are drawn randomly from reasonable distributions represents a worst-case scenario for management. We suspect that much of the value of the various harvest strategies we calculated is derived from the fact that they are state dependent, such that appropriate harvest rates depend on population abundance and weather conditions, as well as our focus on an infinite time horizon for sustainability.

Ecological Modelling↗

USGS2003

Characterization and statistical modeling of bacterial (Escherichia coli) outflows from watersheds that discharge into Southern Lake Michigan

Two watersheds in northwestern Indiana were selected for detailed monitoring of bacterially contaminated discharges (Escherichia coli) into Lake Michigan. A large watershed that drains an urbanized area with treatment plants that release raw sewage during storms discharges into Lake Michigan at the outlet of Burns Ditch. A small watershed drains part of the Great Marsh, a wetland complex that has been disrupted by ditching and limited residential development, at the outlet of Derby Ditch. Monitoring at the outlet of Burns Ditch in 1999 and 2000 indicated that E. coli concentrations vary over two orders of magnitude during storms. During one storm, sewage overflows caused concentrations to increase to more than 10,000 cfu/100 mL for several hours. Monitoring at Derby Ditch from 1997 to 2000 also indicated that E. coli concentrations increase during storms with the highest concentrations generally occurring during rising streamflow. Multiple regression analysis indicated that 60% of the variability in measured outflows of E. coli from Derby Ditch (n = 88) could be accounted for by a model that utilizes continuously measured rainfall, stream discharge, soil temperature and depth to water table in the Great Marsh. A similar analysis indicated that 90% of the variability in measured E. coli concentrations at the outlet of Burns Ditch (n = 43) during storms could be accounted for by a combination of continuously measured water-quality variables including nitrate and ammonium. These models, which utilize data that can be collected on a real-time basis, could form part of an Early Warning System for predicting beach closures.

Environmental Monitoring and Assessment↗

USGS2022

A review of supervised learning methods for classifying animal behavioural states from environmental features

Accurately predicting behavioural modes of animals in response to environmental features is important for ecology and conservation. Supervised learning (SL) methods are increasingly common in animal movement ecology for classifying behavioural modes. However, few examples exist of applying SL to classify polytomous animal behaviour from environmental features especially in the context of millions of animal observations. We review SL methods (weighted k -nearest neighbours; neural nets; random forests; and boosted classification trees with XGBoost) for classifying polytomous animal behaviour from environmental predictors. We also describe tuning parameter selection and assessment strategies, approaches for visualizing relationships between predictors and class outputs, and computational considerations. We demonstrate these methods by predicting three categories of risk to bald eagles from colliding with wind turbines using, as predictors, 12 environmental state features associated with 1.7 million GPS telemetry data points from 57 eagles. Of the SL methods we considered, XGBoost yielded the most accurate model with 86.2% classification accuracy and pairwise-averaged area under the ROC curve of 90.6. Computational time of XGBoost scaled better to large data than any other SL method. We also show how SHAP values integrated in the R package ( xgboost ) facilitate investigation of variable relationships and importance. For big data applications, XGBoost appears to provide superior classification accuracy and computational efficiency. Our results suggest XGBoost should be considered as an early modelling option in situations where the intent is to classify millions of animal behaviour observations from environmental predictors and to understand relationships between those predictors and movement behaviours. We also offer a tutorial to assist researchers in implementing this method.

Methods in Ecology and Evolution↗

USGS2012

Evaluating changes in matrix based, recovery-adjusted concentrations in paired data for pesticides in groundwater

Pesticide concentration data for waters from selected carbonate-rock aquifers in agricultural areas of Pennsylvania were collected in 1993–2009 for occurrence and distribution assessments. A set of 30 wells was visited once in 1993–1995 and again in 2008–2009 to assess concentration changes. The data include censored matched pairs (nondetections of a compound in one or both samples of a pair). A potentially improved approach for assessing concentration changes is presented where (i) concentrations are adjusted with models of matrix-spike recovery and (ii) area-wide temporal change is tested by use of the paired Prentice-Wilcoxon (PPW) statistical test. The PPW results for atrazine, simazine, metolachlor, prometon, and an atrazine degradate, deethylatrazine (DEA), are compared using recovery-adjusted and unadjusted concentrations. Results for adjusted compared with unadjusted concentrations in 2008–2009 compared with 1993–1995 were similar for atrazine and simazine (significant decrease; 95% confidence level) and metolachlor (no change) but differed for DEA (adjusted, decrease; unadjusted, increase) and prometon (adjusted, decrease; unadjusted, no change). The PPW results were different on recovery-adjusted compared with unadjusted concentrations. Not accounting for variability in recovery can mask a true change, misidentify a change when no true change exists, or assign a direction opposite of the true change in concentration that resulted from matrix influences on extraction and laboratory method performance. However, matrix-based models of recovery derived from a laboratory performance dataset from multiple studies for national assessment, as used herein, rather than time- and study-specific recoveries may introduce uncertainty in recovery adjustments for individual samples that should be considered in assessing change.

Pennsylvania↗

USGS2022

Understory structure and heterospecifics influence the occupancy of a ground-nesting species of conservation concern, the Canada Warbler

Forest structure and composition in eastern U.S. forests are changing because of forest regeneration after farmland abandonment, less frequent occurrence of severe disturbances, and climate change. Some of these changes may disproportionally affect birds that rely on gap dynamics or other forest canopy disturbances to create understory habitat. The Canada Warbler ( Cardellina canadensis ) is one such understory specialist that has undergone consistent declines. We assessed environmental and interspecific factors associated with Canada Warbler space use in its southern breeding distribution to understand potential causes of population declines and inform conservation efforts. We evaluated Canada Warbler occupancy from 840 point count surveys conducted in 2017 and 2018 at 470 unique locations (79% of locations surveyed in both years) throughout Monongahela National Forest, West Virginia, USA. We modeled Canada Warbler occupancy probability as a function of environmental variables and included Black-throated Blue Warbler ( Setophaga caerulescens ) and Hermit Thrush ( Catharus guttatus ) as interacting species because all three species exhibit similar habitat preferences. Canada Warblers were most likely to occur in areas with rhododendron ( Rhododendron maximum ) density > 0.27 stems/m² and within 3 m of riparian areas (streams and wetlands). They were also more likely to occur in mid-elevation (highest occupancy at 930 m) northern hardwood forests when Black-throated Blue Warblers were also present. Black-throated Blue Warblers were most likely to occupy mid-elevation sites with high shrub density, whereas Hermit Thrushes were more likely to occupy high-elevation, old-age forests. Potential management actions could focus on conserving riparian areas in northern hardwood forests, especially those with dense rhododendron thickets. Such potential actions could also be beneficial across the entire elevation range we explored within the region (500–1300 m). Canada Warblers may be benefiting from the recent spread of rhododendron habitats and northern hardwood forest types within West Virginia.

West Virginia↗

USGS2012

Application of empirical predictive modeling using conventional and alternative fecal indicator bacteria in eastern North Carolina waters

Coastal and estuarine waters are the site of intense anthropogenic influence with concomitant use for recreation and seafood harvesting. Therefore, coastal and estuarine water quality has a direct impact on human health. In eastern North Carolina (NC) there are over 240 recreational and 1025 shellfish harvesting water quality monitoring sites that are regularly assessed. Because of the large number of sites, sampling frequency is often only on a weekly basis. This frequency, along with an 18–24 h incubation time for fecal indicator bacteria (FIB) enumeration via culture-based methods, reduces the efficiency of the public notification process. In states like NC where beach monitoring resources are limited but historical data are plentiful, predictive models may offer an improvement for monitoring and notification by providing real-time FIB estimates. In this study, water samples were collected during 12 dry (n = 88) and 13 wet (n = 66) weather events at up to 10 sites. Statistical predictive models for Escherichiacoli (EC), enterococci (ENT), and members of the Bacteroidales group were created and subsequently validated. Our results showed that models for EC and ENT (adjusted R2 were 0.61 and 0.64, respectively) incorporated a range of antecedent rainfall, climate, and environmental variables. The most important variables for EC and ENT models were 5-day antecedent rainfall, dissolved oxygen, and salinity. These models successfully predicted FIB levels over a wide range of conditions with a 3% (EC model) and 9% (ENT model) overall error rate for recreational threshold values and a 0% (EC model) overall error rate for shellfish threshold values. Though modeling of members of the Bacteroidales group had less predictive ability (adjusted R 2 were 0.56 and 0.53 for fecal Bacteroides spp. and human Bacteroides spp., respectively), the modeling approach and testing provided information on Bacteroidales ecology. This is the first example of a set of successful statistical predictive models appropriate for assessment of both recreational and shellfish harvesting water quality in estuarine waters.

North Carolina↗

USGS2011

Implications of community concordance for assessing stream integrity at three nested spatial scales in Minnesota, U.S.A.

1. Fish and invertebrate assemblage data collected from 670 stream sites in Minnesota (U.S.A.) were used to calculate concordance across three nested spatial scales (statewide, ecoregion and catchment). Predictive taxa richness models, calibrated using the same data, were used to evaluate whether concordant communities exhibited similar trends in human‐induced taxa loss across all three scales. Finally, we evaluated the strength of the relationship between selected environmental variables and the composition of both assemblages at all three spatial scales. 2. Significant concordance between fish and invertebrate communities occurred at the statewide scale as well as in six of seven ecoregions and 17 of the 21 major catchments. However, concordance was not consistently indicative of significant relationships between rates of fish and invertebrate taxa loss at those same scales. 3. Fish and invertebrate communities were largely associated with different environmental variables, although the composition of both communities was strongly correlated with stream size across all three scales. 4. Predictive taxa‐loss models for fish assemblages were less sensitive and precise than models for invertebrate assemblages, likely because of the relatively low number of common fish taxa in our data set. Both models, however, distinguished reference from non‐reference sites. 5. The importance of concordance, geographic context and scale are discussed in relation to the design and interpretation of stream integrity indicators. In particular, our findings suggest that community concordance should not be viewed as a substitute for an evaluation of how assemblages respond to environmental stressors.

Minnesota↗

USGS2024

Identifying indicators of polar bear population status

Monitoring trends in large mammal populations is a fundamental component of wildlife management and conservation. However, direct estimates of population size and vital rates of large mammals can be logistically challenging and expensive. Indicators that reflect trends in abundance, therefore, can be valuable tools for supporting population monitoring. Polar bears have a relatively simple life history such that a few key variables may be effective indicators for tracking changes in body condition and recruitment that affect abundance. Direct estimates of polar bear abundance are difficult to obtain due to their large home ranges in remote Arctic habitats. Changes in abundance associated with environmental conditions appear to affect polar bears largely via effects on female body condition which influence reproduction and cub survival (i.e., recruitment). Loss of sea ice habitat is further limiting researcher access for population monitoring creating a need for alternative approaches. Here we used relationships established from eight years (2008–2017) of data collected on 439 polar bears in the Chukchi Sea, to transform previously published individual-based relationships with annually available sea ice, atmospheric circulation, and prey body condition variables to predict annual mean body condition and recruitment during 2018–2022. Although annual sample sizes were limited for verifying predicted body condition and recruitment via techniques such as cross-validation, in most cases predicted annual means were closely correlated with observed means for 2008–2017. Summer sea ice and prey body condition remained within or increased relative to levels observed during 2008–2017 and predicted polar bear body condition and recruitment during 2018–2022 were largely within or above observed annual means during 2008–2017. A lack of trend in environmental and ecological variables or polar bear body condition and recruitment metrics during 2008–2022 is suggestive that the Chukchi Sea polar bear population was likely stable during this time. Our results provide support for developing models that predict important population parameters of large mammals based on environmental and ecological indicators. Given that trend information is lacking for 10 of the 19 recognized polar bear populations and is outdated for others, the use of environmental and ecological indicators may be particularly useful for augmenting direct estimates of polar bear vital rates in between periods of data collection. Although demographic assessments for polar bears have primarily focused on correlations with sea ice availability, our study and others highlight that prey health is also an important indicator of polar bear population status.

Ecological Indicators↗

USGS2021

Clutch may predict growth of hatchling Burmese pythons better than food availability or sex

Identifying which environmental and genetic factors affect growth pattern phenotypes can help biologists predict how organisms distribute finite energy resources in response to varying environmental conditions and physiological states. This information may be useful for monitoring and managing populations of cryptic, endangered, and invasive species. Consequently, we assessed the effects of food availability, clutch, and sex on the growth of invasive Burmese pythons ( Python bivittatus Kuhl) from the Greater Everglades Ecosystem in Florida, USA. Though little is known from the wild, Burmese pythons have been physiological model organisms for decades, with most experimental research sourcing individuals from the pet trade. Here, we used 60 hatchlings collected as eggs from the nests of two wild pythons, assigned them to High or Low feeding treatments, and monitored growth and meal consumption for 12 weeks, a period when pythons are thought to grow very rapidly. None of the 30 hatchlings that were offered food prior to their fourth week post-hatching consumed it, presumably because they were relying on internal yolk stores. Although only two clutches were used in the experiment, we found that nearly all phenotypic variation was explained by clutch rather than feeding treatment or sex. Hatchlings from clutch 1 (C1) grew faster and were longer, heavier, in better body condition, ate more frequently, and were bolder than hatchlings from clutch 2 (C2), regardless of food availability. On average, C1 and C2 hatchling snout-vent length (SVL) and weight grew 0.15 cm d −1 and 0.10 cm d −1 , and 0.20 g d −1 and 0.03 g d −1 , respectively. Additional research may be warranted to determine whether these effects remain with larger clutch sample sizes and to identify the underlying mechanisms and fitness implications of this variation to help inform risk assessments and management.

Biology Open↗

USGS2001

All equal-area map projections are created equal, but some are more equal than others

High-resolution regional and global raster databases are currently being generated for a variety of environmental and scientific modeling applications. The projection of these data from geographic coordinates to a plane coordinate system is subject to significant areal error. Sources of error include users selecting an inappropriate projection or incorrect parameters for a given projection, algorithmic errors in commercial geographic information system (GIS) software, and errors resulting from the projection of data in the raster format. To assess the latter type of errors, the accuracy of raster projection was analyzed by two methods. First, a set of 12 one-degree by one-degree quadrilaterals placed at various latitudes was projected at several raster resolutions and compared to the projection of a vector representation of the same quadrilaterals. Second, several different raster resolutions of land cover data for Asia were projected and the total areas of 21 land cover categories were tabulated and compared. While equal-area projections are designed to specifically preserve area, the comparison of the results of the one-degree by one-degree quadrilaterals with the common equal area projections (e.g., the Mollweide) indicates a considerable variance in the one-degree area after projection. Similarly, the empirical comparison of land cover areas for Asia among various projections shows that total areas of land cover vary with projection type, raster resolution, and latitude. No single projection is best for all resolutions and all latitudes. While any of the equal-area projections tested are reasonably accurate for most applications with resolutions of eight-kilometer pixels or smaller, significant variances in accuracies appear at larger pixel sizes.

Cartography and Geographic Information Science↗

USGS2006

Modeling black-footed ferret energetics: Are southern release sites better?

Several models have been developed to estimate prey requirements and to assess habitat suitability of release sites for the black-footed ferret (Mustela nigripes) (e.g., Stromberg and others, 1983; Powell and others, 1985; Biggins and others, 1993). None of these models, however, addressed possible differences in energetic requirements between sites due to climatic differences within the ferret’s historical range. We used a simplified energetics model to examine the effect of variation in environmental conditions on ferret energetic requirements. The aim of the study was to determine whether the ferret might be more successful in one area than another.

Conference Paper↗

USGS2024

Assessing the sustainability of Pacific walrus harvest in a changing environment

Harvest sustainability is a primary goal of wildlife management and conservation, and in a changing world, it is increasingly important to consider environmental drivers of population dynamics alongside harvest in cohesive management plans. This is particularly pertinent for harvested species that acutely experience effects of climate change. The Pacific walrus ( Odobenus rosmarus divergens ), a crucial subsistence resource for Indigenous communities, is simultaneously subject to rapid habitat loss associated with diminishing sea ice and an increasing anthropogenic footprint in the Arctic. We developed a theta-logistic population modeling-management framework to evaluate various harvest scenarios combined with 4 potential climate and disturbance scenarios (ranging from optimistic to pessimistic, based largely on sea ice projections from general circulation models) to simulate Pacific walrus population dynamics to the end of the twenty-first century, focusing on the independent-aged female subset of the population. We considered 2 types of harvest strategies: 1) state-dependent harvest scenarios wherein we calculated harvest as a percentage of the population and updated annual harvests at set intervals as the population was reassessed, and 2) annually consistent harvest scenarios wherein annual harvest levels remain consistent into the future. All climate and disturbance scenarios indicated declines of varying severity in Pacific walrus abundance to the end of the twenty-first century, even in the absence of harvest. However, we found that a state-dependent annual harvest of 1.23% of the independent-aged female subset of the population (e.g., 1,280 independent-aged females harvested in 2020, similar to contemporary harvest levels) met our criterion for sustainability under all climate and disturbance scenarios, considering a medium risk tolerance level of 25%. This indicates that the present rate of Pacific walrus harvest is sustainable and will continue to be—provided the population is assessed at regular intervals and harvest is adapted to match changes in population dynamics. Our simulations indicate that a sustainable annually-consistent harvest is also possible but only at low levels if the population declines as expected. Applying a constant annual harvest of 1,280 independent-aged females failed to meet our criterion for sustainability under 3 of the 4 climate and disturbance scenarios we evaluated and had a higher probability of quasi-extinction than an equivalent state-dependent harvest scenario (1.23%). We highlight the importance of state-dependent management strategies and suggest our modeling framework is useful for managing harvest sustainability in a changing climate.

Journal of Wildlife Management↗

USGS2006

Assessment of factors limiting Klamath River fall Chinook salmon production potential using historical flows and temperatures

We parameterized and applied a deterministic salmon production model to infer the degree to which river flows and temperatures may limit freshwater production potential of the Klamath River in California. Specific parameter requirements, data sources, and significant assumptions are discussed in detail. Model simulations covered a wide variety of historical hydrologic and meteorologic conditions for 40+ years of environmental data. The model was calibrated only qualitatively, appearing to perform well in predicted outmigrant timing, but overestimating growth. Egg-to-outmigrant survival was near that reported for other rivers north of the Klamath River. Predicted production potential appeared to be determined by multiple causes involving both regularly occurring habitat-related constraints and irregularly occurring exposure to high water temperatures. Simulated production was greatest in years of intermediate water availability and was constrained in both dry and wet years, but for different reasons. Reducing mortality associated with limitations to juvenile habitat, if possible, would be expected to have the highest payoff in increasing production. Water temperature was important in determining predicted production in some years but overall was not predicted to be as important as physical microhabitat. No single mortality cause acted as a true “bottleneck” on production. Model uncertainty is addressed through a sensitivity analysis. Predicted habitat area may be a large source of model uncertainty and sensitivity, but collectively, model parameters associated with timing of events (for example spawning, fry emergence, and emigration) or related triggers control much of the model sensitivity. Though model uncertainty remains, one can begin to explore potential alternatives to reduce production limitations. Specific recommendations are made regarding future study and reducing uncertainty.

California, Oregon↗

USGS2018

Contaminants in tropical island streams and their biota

Environmental contamination is problematic for tropical islands due to their typically dense human populations and competing land and water uses. The Caribbean island of Puerto Rico (USA) has a long history of anthropogenic chemical use, and its human population density is among the highest globally, providing a model environment to study contaminant impacts on tropical island stream ecosystems. Polycyclic Aromatic Hydrocarbons, historic-use chlorinated pesticides, current-use pesticides, Polychlorinated Biphenyls (PCBs), and metals (mercury, cadmium, copper, lead, nickel, zinc, and selenium) were quantified in the habitat and biota of Puerto Rico streams and assessed in relation to land-use patterns and toxicological thresholds. Water, sediment, and native fish and shrimp species were sampled in 13 rivers spanning broad watershed land-use characteristics during 2009–2010. Contrary to expectations, freshwater stream ecosystems in Puerto Rico were not severely polluted, likely due to frequent flushing flows and reduced deposition associated with recurring flood events. Notable exceptions of contamination were nickel in sediment within three agricultural watersheds (range 123–336 ppm dry weight) and organic contaminants (PCBs, organochlorine pesticides) and mercury in urban landscapes. At an urban site, PCBs i n several fish species (Mountain Mullet Agonostomus monticola [range 0.019–0.030 ppm wet weight] and American Eel Anguilla rostrata [0.019–0.031 ppm wet weight]) may pose human health hazards, with concentrations exceeding the U.S. Environmental Protection Agency (EPA) consumption limit for 1 meal/month. American Eel at the urban site also contained dieldrin (range < detection-0.024 ppm wet weight) that exceeded the EPA maximum allowable consumption limit. The Bigmouth Sleeper Gobiomorous dormitor , an important piscivorus sport fish, accumulated low levels of organic contaminants in edible muscle tissue (due to its low lipid c ontent) and may be most suitable for human consumption island-wide; only mercury at one site (an urban location) exceeded EPA's consumption limit of 3 meals/month for this species. These results comprise the first comprehensive island-wide contaminant assessment of Puerto Rico streams and biota and provide natural resource and public health agencies here and in similar tropical islands elsewhere with information needed to guide ecosystem and fisheries conservation and management and human health risk assessment.

Environmental Research↗

USGS2015

Resilience and risk: a demographic model to inform conservation planning for polar bears

Climate change is having widespread ecological effects, including loss of Arctic sea ice. This has led to listing of the polar bear ( Ursus maritimus ) and other ice-dependent marine mammals under the U.S. Endangered Species Act (ESA). Methods are needed to evaluate the effects of climate change on population persistence to inform recovery planning for listed species. For polar bears, this includes understanding interactions between climate and secondary factors, such as subsistence harvest, which provide economic, nutritional, or cultural value to humans. We developed a matrix-based demographic model for polar bears that can be used for population viability analysis and to evaluate the effects of human-caused removals. This model includes density-dependence (the potential for a declining environmental carrying capacity), density-independent limitation, and sex- and age-specific harvest vulnerabilities. We estimated values of adult female survival (0.93–0.96), recruitment (number of yearling cubs per adult female; 0.1–0.3), and carrying capacity (>250 animals) that must be maintained for a hypothetical population to achieve a 90-percent probability of persistence over 100 years. We also developed a state-dependent management framework, based on harvest theory and the potential biological removal method, by linking the demographic model to simulated population assessments. This framework can be used to estimate the maximum sustainable rate of human-caused removals, including subsistence harvest, which maintains a population at its maximum net productivity level. The framework also can be used to calculate a recommended sustainable harvest rate, which generally is lower than the maximum sustainable rate and depends on management objectives, the precision and frequency of population data, and risk tolerance. The historical standard 4.5-percent harvest rate for polar bears, at a 2:1 male-to-female ratio, is reasonable under many biological and management conditions, although lower or higher rates may be appropriate in some cases. Our modeling results suggest that harvest of polar bears is unlikely to accelerate population declines that result from declining carrying capacity caused by sea-ice loss, provided that several conditions are met: (1) the sustainable harvest rate reflects the population’s intrinsic growth rate, and the corresponding harvest level is obtained by applying this rate to an estimate of population size; (2) the sustainable harvest rate reflects the quality of population data (e.g., lower harvest when data are poor); and (3) the level of human-caused removals can be adjusted. Finally, our results suggest that stopgap measures (e.g., further reduction or cessation of harvest when the population size is less than a critical threshold) may be necessary to minimize the incremental risk associated with harvest, if environmental conditions are deteriorating rapidly. We suggest that the demographic model and approaches presented here can serve as a template for conservation planning for polar bears and other species facing similar challenges.

Open-File Report↗

USGS2021

Juvenile moose stress and nutrition dynamics related to winter ticks, landscape characteristics, climate-mediated factors and survival

Moose populations in the northeastern United States have declined over the past 15 years, primarily due to the impacts of winter ticks. Research efforts have focused on the effects of winter tick infestation on moose survival and reproduction, but stress and nutritional responses to ticks and other stressors remain understudied. We examined the influence of several environmental factors on moose calf stress hormone metabolite concentrations and nutritional restriction in Vermont, USA. We collected 407 fecal and 461 snow urine samples from 84 radio-collared moose calves in the winters of 2017–2019 (January–April) to measure fecal glucocorticoid metabolites (fGCM) concentrations and urea nitrogen:creatinine (UN:C) ratios. We used generalized mixed-effects models to evaluate the influence of individual condition, winter ticks, habitat, climate and human development on stress and nutrition in calf moose. We then used these physiological data to build generalized linear models to predict calf winter survival. Calf fGCM concentrations increased with nutritional restriction and snow depth during adult winter tick engorgement. Calf UN:C ratios increased in calves with lighter weights and higher tick loads in early winter. Calf UN:C ratios also increased in individuals with home ranges composed of little deciduous forests during adult winter tick engorgement. Our predictive models estimated that winter survival was negatively related to UN:C ratios and positively related to fGCM concentrations, particularly in early winter. By late March, as winter ticks are having their greatest toll and endogenous resources become depleted, we estimated a curvilinear relationship between fGCM concentrations and survival. Our results provide novel evidence linking moose calf stress and nutrition, a problematic parasite and challenging environment and winter survival. Our findings provide a baseline to support the development of non-invasive physiological monitoring for assessing environmental impacts on moose populations.

Vermont↗

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↗