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USGS2020

How and why is the timing and occurrence of seasonal migrants in the Gulf of Maine changing due to climate?

Plants and animals undergo certain recurring life-cycle events, such as migrations between summer and winter habitats or the annual blooming of plants. Known as phenology, the timing of these events is very sensitive to changes in climate (and changes in one species’ phenology can impact entire food webs and ecosystems). Shifts in phenology have been described as a “fingerprint” of the temporal and spatial responses of wildlife to climate change impacts. Thus, phenology provides one of the strongest indicators of the adaptive capacity of organisms (or the ability of organisms to cope with future environmental conditions). In this study, researchers are exploring how the timing and occurrence of a number of highly migratory marine animals is changing due to a series of climatic and ecological shifts. First, using existing long-term historical data series, they will determine the direction and magnitude of how migration, abundance, or other phenological factors have changed for marine mammals, sea turtles, and fishes that migrate into the Gulf of Maine on a seasonal basis. Because marine animals are inherently difficult to detect, the team will apply dynamic occupancy models to evaluate seasonal migration patterns and habitat use across multiple habitats in the Gulf of Maine region. The project team will also synthesize regional information on a key, ecologically-important prey fish, sandlance, whose timing and abundance is a strong predictor of the occurrence and behavior of predator species targeted in this study as well as a range of other regional fish and wildlife of conservation and management concern. Results from this component of the project will identify coastal fish and wildlife species that are relatively more or less able to adapt and thus potentially vulnerable to climate change; determine the likely primary drivers of those changes; and identify data gaps and future monitoring needs. Ultimately, this information will be available and useful for regional coastal management and adaptation decisions that will allow managers to effectively plan for the future. In a second component of the project, researchers will focus specifically on changes in migration patterns of the endangered North Atlantic right whale. While shifts in the distribution and time of recurring life events are adaptive responses that may help species cope with climate impacts, they can also lead to changes in how species interact with humans. The North Atlantic right whale is one of the most endangered whale species on the planet. In the North Atlantic Ocean, ship strikes and entanglements with commercial fishing gear represent fatal threats to right whales. Recent reports suggest that North Atlantic right whale migration patterns have changed. Many researchers posit that shifts in migration are responsible for recent increases in the overlap between right whales and human activities, especially fishing. To help understand how changes in right whale movements and behaviors may overlap with ship traffic, and thus put the animals at risk of encountering vessels, we will combine right whale habitat models with ship traffic maps. The end result will be a set of maps identifying risk levels.

Gulf of Maine↗

USGS2023

A recruitment niche framework for improving seed-based restoration

As larger tracts of land experience degradation, seed-based restoration (SBR) will be a primary tool to reestablish vegetation and ecosystem function. SBR has advanced in terms of technical and technological approaches, yet plant recruitment remains a major barrier in some systems, notably drylands. There is an unmet opportunity to test science-based approaches to seed mix design and application, based not only on diversity or local provenance, but on the unique recruitment strategies of species. We lay out a framework that uses a quantitative representation of species' recruitment niches to match them to targeted goals (e.g. drought or invasion resistance) and methods (e.g. precision tools and technologies) in SBR. We first describe how to quantify the recruitment niche with seed and seedling traits tied to observed recruitment responses to environmental factors. We then show how a quantified recruitment niche framework can serve as the foundation to address three major restoration challenges: (1) designing forward-looking seed mixes that increase resilience to future climate and disturbance, (2) accounting for natural recovery in SBR planning, and (3) applying precision seeding practices to maximize restoration success. Finally, we demonstrate these ideas with existing data and discuss key challenges to adoption in SBR practice. While the ideas in this framework are based in ecological theory, they will require substantial testing and refinement by scientists engaged in SBR efforts. If this framework is integrated into research agendas, we believe it has the potential to unify and advance diverse elements of seed-based restoration ecology and improve restoration outcomes.

Restoration Ecology↗

USGS2021

Techniques to improve ecological interpretability of black box machine learning models

Statistical modeling of ecological data is often faced with a large number of variables as well as possible nonlinear relationships and higher-order interaction effects. Gradient boosted trees (GBT) have been successful in addressing these issues and have shown a good predictive performance in modeling nonlinear relationships, in particular in classification settings with a categorical response variable. They also tend to be robust against outliers. However, their black-box nature makes it difficult to interpret these models. We introduce several recently developed statistical tools to the environmental research community in order to advance interpretation of these black-box models. To analyze the properties of the tools, we applied gradient boosted trees to investigate biological health of streams within the contiguous USA, as measured by a benthic macroinvertebrate biotic index. Based on these data and a simulation study, we demonstrate the advantages and limitations of partial dependence plots (PDP), individual conditional expectation (ICE) curves and accumulated local effects (ALE) in their ability to identify covariate–response relationships. Additionally, interaction effects were quantified according to interaction strength (IAS) and Friedman’s H 2 "> H 2 statistic. Interpretable machine learning techniques are useful tools to open the black-box of gradient boosted trees in the environmental sciences. This finding is supported by our case study on the effect of impervious surface on the benthic condition, which agrees with previous results in the literature. Overall, the most important variables were ecoregion, bed stability, watershed area, riparian vegetation and catchment slope. These variables were also present in most identified interaction effects. In conclusion, graphical tools (PDP, ICE, ALE) enable visualization and easier interpretation of GBT but should be supported by analytical statistical measures. Future methodological research is needed to investigate the properties of interaction tests. Supplementary materials accompanying this paper appear on-line.

Journal of Agricultural, Biological, and Environme↗

USGS2019

Integrating anthropogenic factors into regional-scale species distribution models — A novel application in the imperiled sagebrush biome

Species distribution models (SDM) that rely on regional-scale environmental variables will play a key role in forecasting species occurrence in the face of climate change. However, in the Anthropocene, a number of local-scale anthropogenic variables, including wildfire history, land-use change, invasive species, and ecological restoration practices can override regional-scale variables to drive patterns of species distribution. Incorporating these human-induced factors into SDMs remains a major research challenge, in part because spatial variability in these factors occurs at fine scales, rendering prediction over regional extents problematic. Here, we used big sagebrush (Artemisia tridentata Nutt.) as a model species to explore whether including human-induced factors improves the fit of the SDM. We applied a Bayesian hurdle spatial approach using 21,753 data points of field-sampled vegetation obtained from the LANDFIRE program to model sagebrush occurrence and cover by incorporating fire history metrics and restoration treatments from 1980 to 2015 throughout the Great Basin of North America.

Global Change Biology↗

USGS2021

A science agenda to inform natural resource management decisions in an era of ecological transformation

Earth is experiencing widespread ecological transformation in terrestrial, freshwater, and marine ecosystems that is attributable to directional environmental changes, especially intensifying climate change. To better steward ecosystems facing unprecedented and lasting change, a new management paradigm is forming, supported by a decision-oriented framework that presents three distinct management choices: resist, accept, or direct the ecological trajectory. To make these choices strategically, managers seek to understand the nature of the transformation that could occur if change is accepted while identifying opportunities to intervene to resist or direct change. In this article, we seek to inspire a research agenda for transformation science that is focused on ecological and social science and based on five central questions that align with the resist–accept–direct (RAD) framework. Development of transformation science is needed to apply the RAD framework and support natural resource management and conservation on our rapidly changing planet.

BioScience↗

USGS1987

A model of the productivity of the mallard duck

This paper describes a stochastic computer model that simulates recruitment of the mallard ( Anas platyrhynchos ) under different habitat conditions and management scenarios. The model incorporates several environmental phenomena and biological relations that affect mallard recruitment. Major events include arrival of mallards in the spring, daily survival of hens, initiation of nests, selection of nest sites, survival of nests until hatching, and survival of broods until fledging. The model was originally developed as a tool for synthesizing the results of research. Subsequently, we applied the model to a variety of management situations. We also describe the sources of estimates used in the model, evaluate its sensitivity to input parameters, and review some practical applications.

Ecological Modelling↗

USGS1988

Assessment of the role of bottomland hardwoods in sediment and erosion control

Drainage and clearing of bottomland hardwoods have long been recognized by the U.S. Environmental Protection Agency (EPA) and the U.S. Fish and Wildlife Service (Service) as important impacts of Federal water projects in the lower Mississippi River Valley. More recently, the water quality impacts of such projects (e.g., increases in sediments, nutrients, and pesticides) have also become of concern. In 1984, in an effort to better define problems concerning wetland losses and water degradation, EPA initiated a cooperative project with the Western Energy and Land Use Team (now the National Ecology Research Center) of the Service. Three phases of the project were identified: 1. To collect existing literature and data; 2. To select, develop, and test the utility of methods to quantify the relationships between land use, cover types, soils, hydrology, and water quality (as represented by sediment); and 3. To apply selected methodologies to several sites within the Yazoo Basin of Mississippi to determine the, potential effectiveness of various management alternatives to reduce sediment yield, increase sediment deposition, and improve water quality. Methods development focused on linking a simulation of water and sediment movement to a computerized geographic information system. We had several objectives for the resulting model. We desired that it should: 1. Estimate the importance of bottomland and hardwoods as a cover type that performs the functions of erosion and sediment control, 2. Simulate effects of proportions of ' various cover types and their specific spatial configurations, 3. Be applicable to moderately large spatial areas with minimal site-specific calibration, 4. Simulate spatial patterns of sediment loss-gain over time, and 5. Represent both sediment detachment and transport. While it was recognized that impacts and management alternatives could be sorted roughly into landscape measures and channel measures, the decision was made to focus study efforts mainly on landscape measures. Landscape measures include altered drainage and flooding patterns, altered cover types (e.g., conversion of bottomland hardwoods to agricultural crops, reforestation of cropland to bottomland hardwoods, and creation of riparian buffer strips), altered cropping and tillage patterns, altered routing of water, and creation of buffer strips along wetlands and channel margins. Channel measures include vegetative bank stabilization, grade control structures, and regulation of channel water volume and velocity. During the first year of the study, EPA decided not to fund the third phase of the project. This required considerable rescoping of the project with the result that application of the sediment mobilization, routing, and deposition models to various management alternatives and portions of the Yazoo Basin was somewhat restricted. We believe, however, that this report will provide a good understanding of the various modes of sediment mobilization, transport, and deposition within the Yazoo Basin, as well as of the role of bottomland hardwoods. The model developed in this study could be applied to a variety of management or mitigation alternatives prior to implementation to determine their relative effectiveness. Policy, political, and socio-economic consequences of any proposed management/mitigation practice, however, must ultimately be taken into consideration by those charged with management of water resources within the Yazoo Basin before any practice is implemented. This study makes no effort to judge the feasibility of management alternatives in this regard.

Report↗

USGS2021

Bayesian change point quantile regression approach to enhance the understanding of shifting phytoplankton-dimethyl sulfide relationships in aquatic ecosystems

Dimethyl sulfide (DMS) serves as an anti-greenhouse gas, plays multiple roles 7 in aquatic ecosystems, and contributes to the global sulfur cycle. The chlorophyll 8 a (CHL, an indicator of phytoplankton biomass)-DMS relationship is critical for 9 estimating DMS emissions from aquatic ecosystems. Importantly, recent research has 10 identified that the CHL-DMS relationship has a breakpoint, where the relationship 11 is positive below a CHL threshold and negative at higher CHL concentrations. 12 Conventionally, mean regression methods are employed to characterize the CHL-DMS 13 relationship. However, these approaches focus on the response of mean conditions 14 and cannot illustrate responses of other parts of the DMS distribution, which could 15 be important in order to obtain a complete view of the CHL-DMS relationship. In 16 this study, for the first time, we proposed a novel Bayesian change point quantile 17 regression (BCPQR) model that integrates and inherits advantages of Bayesian change 18 point models and Bayesian quantile regression models. Our objective was to examine 19 whether or not the BCPQR approach could enhance the understanding of shifting 20 CHL-DMS relationships in aquatic ecosystems. We fitted BCPQR models at five 21 regression quantiles for freshwater lakes and for seas. We found that BCPQR models 22 could provide a relatively complete view on the CHL-DMS relationship. In particular, 23 it quantified the upper boundary of the relationship, representing the limiting effect of 24 CHL on DMS. Based on the results of paired parameter comparisons, we revealed the 25 inequality of regression slopes in BCPQR models for seas, indicating that applying 26 the mean regression method to develop the CHL-DMS relationship in seas might not 27 be appropriate. We also confirmed relationship differences between lakes and seas at 28 multiple regression quantiles. Further, by introducing the concept of DMS emission 29 potential, we found that pH was not likely a key factor leading to the change of the 30 CHL-DMS relationship in lakes. These findings cannot be revealed using piecewise 31 linear regression. We thereby concluded that the BCPQR model does indeed enhance 32 the understanding of shifting CHL-DMS relationships in aquatic ecosystems and is 33 expected to benefit efforts aimed at estimating DMS emissions. Considering that 34 shifting (threshold) relationships are not rare and that the BCPQR model can easily 35 be adapted to different systems, the BCPQR approach is expected to have great 36 potential for generalization in other environmental and ecological studies.

Water Research↗

USGS2016

Predictive mapping of seabirds, pinnipeds and cetaceans off the Pacific Coast of Washington

About this report This report supports Washington-led marine spatial planning and responsible stewardship of natural and cultural resources by the Olympic Coast National Marine Sanctuary. Washington state agencies and the sanctuary continually seek the best available science to improve management of marine uses and stewardship of resources (Etheridge et al., 2010; Washington Department of Fish and Wildlife, 2015a). This report and associated data provide new, state- and sanctuary-requested information on seabird, pinniped, and cetacean distributions. Through spatial planning, information on species distributions can help to identify high-value conservation areas, minimize adverse effects of ocean uses and mitigate impacts of coastal hazards. Correspondingly, the Washington Department of Fish and Wildlife has already begun to use the maps of predicted relative density presented in this report to identify ecologically important areas off the Pacific Coast of Washington and apply this information to plan for offshore renewable energy development. This is the culmination of three years of work to compile information on seabirds, pinnipeds, and cetaceans, and advance a modeling framework that can integrate data sets and develop accurate predictions of relative density for important species off the Pacific Coast of Washington. Previous reports, which evaluated existing datasets of at-sea observations (Menza et al., 2014; Kracker and Menza, 2015) and presented superseded versions of seabird models (Menza et al., 2015), provided base information for this report. In addition to the maps in this published report, all new seabird, pinniped and cetacean predictions will be made publicly available as digital geospatial data through the National Centers for Environmental Information. This research supports the National Oceanic and Atmospheric Administration (NOAA) Coastal Zone Management Program, a voluntary partnership between the federal government and U.S. coastal and Great Lakes states and territories authorized by the Coastal Zone Management Act (CZMA) of 1972 to address national coastal issues. The act provides the basis for protecting, restoring, and responsibly developing our nation’s diverse coastal communities and resources. To meet the goals of the CZMA, the national program takes a comprehensive approach to coastal resource management – balancing the often competing and occasionally conflicting demands of coastal resource use, economic development, and conservation. A wide range of issues are addressed through the program, including coastal development, water quality, public access, habitat protection, energy facility siting, ocean governance and planning, coastal hazards, and climate change. Accurate maps of seabird and marine mammal distributions are an important tool for making informed management decisions that affect all of these issues.

Washington↗

USGS2018

Iterative near-term ecological forecasting: Needs, opportunities, and challenges

Two foundational questions about sustainability are “How are ecosystems and the services they provide going to change in the future?” and “How do human decisions affect these trajectories?” Answering these questions requires an ability to forecast ecological processes. Unfortunately, most ecological forecasts focus on centennial-scale climate responses, therefore neither meeting the needs of near-term (daily to decadal) environmental decision-making nor allowing comparison of specific, quantitative predictions to new observational data, one of the strongest tests of scientific theory. Near-term forecasts provide the opportunity to iteratively cycle between performing analyses and updating predictions in light of new evidence. This iterative process of gaining feedback, building experience, and correcting models and methods is critical for improving forecasts. Iterative, near-term forecasting will accelerate ecological research, make it more relevant to society, and inform sustainable decision-making under high uncertainty and adaptive management. Here, we identify the immediate scientific and societal needs, opportunities, and challenges for iterative near-term ecological forecasting. Over the past decade, data volume, variety, and accessibility have greatly increased, but challenges remain in interoperability, latency, and uncertainty quantification. Similarly, ecologists have made considerable advances in applying computational, informatic, and statistical methods, but opportunities exist for improving forecast-specific theory, methods, and cyberinfrastructure. Effective forecasting will also require changes in scientific training, culture, and institutions. The need to start forecasting is now; the time for making ecology more predictive is here, and learning by doing is the fastest route to drive the science forward.

Proceedings of the National Academy of Sciences of↗

USGS2015

Sea-level rise modeling handbook: Resource guide for coastal land managers, engineers, and scientists

Global sea level is rising and may accelerate with continued fossil fuel consumption from industrial and population growth. In 2012, the U.S. Geological Survey conducted more than 30 training and feedback sessions with Federal, State, and nongovernmental organization (NGO) coastal managers and planners across the northern Gulf of Mexico coast to evaluate user needs, potential benefits, current scientific understanding, and utilization of resource aids and modeling tools focused on sea-level rise. In response to the findings from the sessions, this sea-level rise modeling handbook has been designed as a guide to the science and simulation models for understanding the dynamics and impacts of sea-level rise on coastal ecosystems. The review herein of decision-support tools and predictive models was compiled from the training sessions, from online research, and from publications. The purpose of this guide is to describe and categorize the suite of data, methods, and models and their design, structure, and application for hindcasting and forecasting the potential impacts of sea-level rise in coastal ecosystems. The data and models cover a broad spectrum of disciplines involving different designs and scales of spatial and temporal complexity for predicting environmental change and ecosystem response. These data and models have not heretofore been synthesized, nor have appraisals been made of their utility or limitations. Some models are demonstration tools for non-experts, whereas others require more expert capacity to apply for any given park, refuge, or regional application. A simplified tabular context has been developed to list and contrast a host of decision-support tools and models from the ecological, geological, and hydrological perspectives. Criteria were established to distinguish the source, scale, and quality of information input and geographic datasets; physical and biological constraints and relations; datum characteristics of water and land components; utility options for setting sea-level rise and climate change scenarios; and ease or difficulty of storing, displaying, or interpreting model output. Coastal land managers, engineers, and scientists can benefit from this synthesis of tools and models that have been developed for projecting causes and consequences of sea-level change on the landscape and seascape.

Professional Paper↗

USGS2010

Simulation of streamflow in the McTier Creek watershed, South Carolina

The McTier Creek watershed is located in the Sand Hills ecoregion of South Carolina and is a small catchment within the Edisto River Basin. Two watershed hydrology models were applied to the McTier Creek watershed as part of a larger scientific investigation to expand the understanding of relations among hydrologic, geochemical, and ecological processes that affect fish-tissue mercury concentrations within the Edisto River Basin. The two models are the topography-based hydrological model (TOPMODEL) and the grid-based mercury model (GBMM). TOPMODEL uses the variable-source area concept for simulating streamflow, and GBMM uses a spatially explicit modified curve-number approach for simulating streamflow. The hydrologic output from TOPMODEL can be used explicitly to simulate the transport of mercury in separate applications, whereas the hydrology output from GBMM is used implicitly in the simulation of mercury fate and transport in GBMM. The modeling efforts were a collaboration between the U.S. Geological Survey and the U.S. Environmental Protection Agency, National Exposure Research Laboratory. Calibrations of TOPMODEL and GBMM were done independently while using the same meteorological data and the same period of record of observed data. Two U.S. Geological Survey streamflow-gaging stations were available for comparison of observed daily mean flow with simulated daily mean flow-station 02172300, McTier Creek near Monetta, South Carolina, and station 02172305, McTier Creek near New Holland, South Carolina. The period of record at the Monetta gage covers a broad range of hydrologic conditions, including a drought and a significant wet period. Calibrating the models under these extreme conditions along with the normal flow conditions included in the record enhances the robustness of the two models. Several quantitative assessments of the goodness of fit between model simulations and the observed daily mean flows were done. These included the Nash-Sutcliffe coefficient of model-fit efficiency index, Pearson's correlation coefficient, the root mean square error, the bias, and the mean absolute error. In addition, a number of graphical tools were used to assess how well the models captured the characteristics of the observed data at the Monetta and New Holland streamflow-gaging stations. The graphical tools included temporal plots of simulated and observed daily mean flows, flow-duration curves, single-mass curves, and various residual plots. The results indicated that TOPMODEL and GBMM generally produced simulations that reasonably capture the quantity, variability, and timing of the observed streamflow. For the periods modeled, the total volume of simulated daily mean flows as compared to the total volume of the observed daily mean flow from TOPMODEL was within 1 to 5 percent, and the total volume from GBMM was within 1 to 10 percent. A noticeable characteristic of the simulated hydrographs from both models is the complexity of balancing groundwater recession and flow at the streamgage when flows peak and recede rapidly. However, GBMM results indicate that groundwater recession, which affects the receding limb of the hydrograph, was more difficult to estimate with the spatially explicit curve number approach. Although the purpose of this report is not to directly compare both models, given the characteristics of the McTier Creek watershed and the fact that GBMM uses the spatially explicit curve number approach as compared to the variable-source-area concept in TOPMODEL, GBMM was able to capture the flow characteristics reasonably well.

South Carolina↗

USGS2005

Decision making with environmental indices

Since Ott's seminal book on environmental indices (1978), the use of indices has expanded into several natural resource disciplines, including ecological studies, environmental policymaking, and agricultural economics. However, despite their increasing use in natural resource disciplines, researchers and public decision makers continue to express concern about validity of these instruments to capture and communicate multidimensional, and sometimes disparate, characteristics of research data and stakeholder interests. Our purpose is to demonstrate how useful indices can be for communicating environmental information to decision makers. We discuss how environmental indices have evolved over four stages: 1) simple; 2) compound multicriteria; 3) the impact matrix and 4) disparate stakeholder management. We provide examples of simple and compound indices that were used by policy decision makers. We then build a framework, called an Impact Matrix (IM), that comprehensively accounts for multiple indices but lets the user decide how to integrate them. The IM was shaped from the concept of a financial risk payoff matrix and applied to ecosystem risk. While the IM offers flexibility, it does not address stakeholder preferences about which index to use. Therefore, the last phase in our evolutionary ladder includes stakeholder indices to specifically address disparate stakeholder preferences. Finally, we assert that an environmental index has the potential to increase resource efficiency, since the number of decision making resources may be reduced, and hence improve upon resource productivity

Book chapter↗

USGS2011

The fecal bacteria

The Fecal Bacteria offers a balanced, integrated discussion of fecal bacteria and their presence and ecology in the intestinal tract of mammals, in the environment, and in the food supply. This new volume covers their use in examining and assessing water quality in order to offer protection from illnesses related to swimming in or ingesting contaminated water, in addition to discussing their use in engineering considerations of water quality, modeling, monitoring, and regulations. Fecal bacteria are additionally used as indicators of contamination of ready-to-eat foods and fresh produce. The intestinal environment, the microbial community structure of the gut microbiota, and the physiology and genomics of this broad group of microorganisms are explored in the book. With contributions from an internationally recognized group of experts, the book integrates medicine, public health, environmental, and microbiological topics in order to provide a unique, holistic understanding of fecal bacteria. Moreover, it shows how the latest basic science and applied research findings are helping to solve problems and develop effective management strategies. For example, readers will discover how the latest tools and molecular approaches have led to our current understanding of fecal bacteria and enabled us to improve human health and water quality. The Fecal Bacteria is recommended for microbiologists, clinicians, animal scientists, engineers, environmental scientists, food safety experts, water quality managers, and students. It will help them better understand fecal bacteria and use their knowledge to protect human and environmental health. They can also apply many of the techniques and molecular tools discussed in this book to the study of a broad range of microorganisms in a variety of habitats.

Book↗

USGS2024

Assessing the population consequences of disturbance and climate change for the Pacific walrus

Climate change and anthropogenic disturbance are increasingly affecting wildlife at a global scale. Predicting how varying types and degrees of disturbance may interact to influence population dynamics is a key management challenge. Population consequences of disturbance (PCoD) models provide a framework to link effects of anthropogenic disturbance on an individual’s behavior and physiology to population-level changes. In the present study, we develop a Pacific walrus ( Odobenus rosmarus divergens ) PCoD model to encompass the population-level effects of both anthropogenic disturbance and climate change. As the Arctic becomes increasingly ice-free, walruses spend more time at coastal (vs. ice-based) haulouts, from which they must expend more energy to reach foraging areas and where they have an elevated risk of mortality. Concurrently, sea ice loss is increasing the anthropogenic footprint in the Arctic (e.g. fisheries, shipping, energy exploration), which creates additional disturbance. We applied the PCoD model to 4 scenarios (ranging from optimistic to pessimistic) which incorporate different global sea ice model projections along with varying degrees of anthropogenic disturbance. All scenarios indicated a decline in Pacific walrus vital rates by the end of the 21st century, but our results demonstrated that the intensity of that decline could be mitigated by global efforts to reduce carbon emissions, along with local management and conservation efforts to protect important coastal haulouts and foraging grounds. In summary, we introduce a flexible PCoD modeling framework in a novel context which will prove useful to researchers studying species threatened by rapid environmental change.

Marine Ecology Progress Series↗

USGS2021

The application of metacommunity theory to the management of riverine ecosystems

River managers strive to use the best available science to sustain biodiversity and ecosystem function. To achieve this goal requires consideration of processes at different scales. Metacommunity theory describes how multiple species from different communities potentially interact with local-scale environmental drivers to influence population dynamics and community structure. However, this body of knowledge has only rarely been used to inform management practices for river ecosystems. In this article, we present a conceptual model outlining how the metacommunity processes of local niche sorting and dispersal can influence the outcomes of management interventions and provide a series of specific recommendations for applying these ideas as well as research needs. In all cases, we identify situations where traditional approaches to riverine management could be enhanced by incorporating an understanding of metacommunity dynamics. A common theme is developing guidelines for assessing the metacommunity context of a site or region, evaluating how that context may affect the desired outcome, and incorporating that understanding into the planning process and methods used. To maximize the effectiveness of management activities, scientists, and resource managers should update the toolbox of approaches to riverine management to reflect theoretical advances in metacommunity ecology.

WIREs Water↗

USGS2010

Spatial and stage-structured population model of the American crocodile for comparison of comprehensive Everglades Restoration Plan (CERP) alternatives

As part of the U.S. Geological Survey Priority Ecosystems Science (PES) initiative to provide the ecological science required during Everglades restoration, we have integrated current regional hydrologic models with American crocodile (Crocodylus acutus) research and monitoring data to create a model that assesses the potential impact of Comprehensive Everglades Restoration Plan (CERP) efforts on the American crocodile. A list of indicators was created by the Restoration Coordination and Verification (RECOVER) component of CERP to help determine the success of interim restoration goals. The American crocodile was established as an indicator of the ecological condition of mangrove estuaries due to its reliance upon estuarine environments characterized by low salinity and adequate freshwater inflow. To gain a better understanding of the potential impact of CERP restoration efforts on the American crocodile, a spatially explicit crocodile population model has been created that has the ability to simulate the response of crocodiles to various management strategies for the South Florida ecosystem. The crocodile model uses output from the Tides and Inflows in the Mangroves of the Everglades (TIME) model, an application of the Flow and Transport in a Linked Overland/Aquifer Density Dependent System (FTLOADDS) simulator. TIME has the capability to link to the South Florida Water Management Model (SFWMM), which is the primary regional tool used to assess CERP restoration scenarios. A crocodile habitat suitability index and spatial parameter maps that reflect salinity, water depth, habitat, and nesting locations are used as driving functions to construct crocodile finite rate of increase maps under different management scenarios. Local stage-structured models are integrated with a spatial landscape grid to display crocodile movement behavior in response to changing environmental conditions. Restoration efforts are expected to affect salinity levels throughout the habitat of the American crocodile. This modeling effort examines how CERP restoration alternatives will affect growth and survival rates of hatchling and juvenile crocodiles, hatchling dispersal to suitable nursery habitat, and relative abundance and distribution in response to changing salinity and water depth for all stage classes of crocodiles. The response of the American crocodile to restoration efforts will provide a quantifiable measure of restoration success. By applying the crocodile model to proposed restoration alternatives and predicting population responses, we can choose alternatives that approximate historical conditions, enhance habitat for multiple species, and identify future research needs.

Open-File Report↗

USGS2015

Final project memorandum: sea-level rise modeling handbook: resource guide for resource managers, engineers, and scientists

Coastal wetlands of the Southeastern United States are undergoing retreat and migration from increasing tidal inundation and saltwater intrusion attributed to climate variability and sea-level rise. Much of the literature describing potential sea-level rise projections and modeling predictions are found in peer-reviewed academic journals or government technical reports largely suited to reading by other Ph.D. scientists who are more familiar or engaged in the climate change debate. Various sea-level rise and coastal wetland models have been developed and applied of different designs and scales of spatial and temporal complexity for predicting habitat and environmental change that have not heretofore been synthesized to aid natural resource managers of their utility and limitations. Training sessions were conducted with Federal land managers with U.S. Fish and Wildlife Service, National Park Service, and NOAA National Estuarine Research Reserves as well as state partners and nongovernmental organizations across the northern Gulf Coast from Florida to Texas to educate and to evaluate user needs and understanding of concepts, data, and modeling tools for projecting sea-level rise and its impact on coastal habitats and wildlife. As a result, this handbook was constructed from these training and feedback sessions with coastal managers and biologists of published decision-support tools and simulation models for sea-level rise and climate change assessments. A simplified tabular context was developed listing the various kinds of decision-support tools and ecological models along with criteria to distinguish the source, scale, and quality of information input and geographic data sets, physical and biological constraints and relationships, datum characteristics of water and land elevation components, utility options for setting sea-level rise and climate change scenarios, and ease or difficulty of storing, displaying, or interpreting model output. The handbook is designed to be a primer to understanding sea-level rise and a practical synthesis of the current state of knowledge and modeling tools as a resource guide for DOl land management needs and facilitating Landscape Conservation Cooperative (LCC) research and conservation initiatives.

Conference Paper↗