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At least 145 records · Page 8Linked to original sources
USGS2007

Proceedings of the Fourth Glacier Bay Science Symposium

Foreword Glacier Bay was established as a National Monument in 1925, in part to protect its unique character and natural beauty, but also to create a natural laboratory to examine evolution of the glacial landscape. Today, Glacier Bay National Park and Preserve is still a place of profound natural beauty and dynamic landscapes. It also remains a focal point for scientific research and includes continuing observations begun decades ago of glacial processes and terrestrial ecosystems. In recent years, research has focused on glacial-marine interactions and ecosystem processes that occur below the surface of the bay. In October 2004, Glacier Bay National Park convened the fourth in a series of science symposiums to provide an opportunity for researchers, managers, interpreters, educators, students and the general public to share knowledge about Glacier Bay. The Fourth Glacier Bay Science Symposium was held in Juneau, Alaska, rather than at the Park, reflecting a desire to maximize attendance and communication among a growing and diverse number of stakeholders interested in science in the park. More than 400 people attended the symposium. Participants provided 46 oral presentations and 41 posters covering a wide array of disciplines including geology, glaciology, oceanography, wildlife and fisheries biology, terrestrial and marine ecology, socio-cultural research and management issues. A panel discussion focused on the importance of connectivity in Glacier Bay research, and keynote speakers (Gary Davis and Terry Chapin) spoke of long-term monitoring and ecological processes. These proceedings include 56 papers from the symposium. A summary of the Glacier Bay Science Plan-itself a subject of a meeting during the symposium and the result of ongoing discussions between scientists and resource managers-also is provided. We hope these proceedings illustrate the diversity of completed and ongoing scientific studies, conducted within the Park. To this end, we invited all presenters to submit brief technical summaries of their work, to capture the gist of their study and its main findings without an overload of details and methodology. We also asked authors to include a few words on the management implications of their work to help bridge the gap between scientists and managers in understanding how specific research questions may translate to management practice. Papers in this volume are laid out by subject matter, from terrestrial and freshwater subjects to glacial-marine geology, to the ecology of marine animals and ending with risk assessment, human impacts and science-management considerations. In summary, we hope the proceedings will serve as a useful reference to completed and ongoing studies in Glacier Bay National Park, and thereby provide park enthusiasts, scientists, and managers with a road map of scientific progress.

Scientific Investigations Report↗
USGS2020

Resilience management for conservation of inland recreational fisheries

Resilience thinking has generated much interest among scientific communities, yet most resilience concepts have not materialized into management applications. We believe that using resilience concepts to characterize systems and the social and ecological processes affecting them is a way to integrate resilience into better management decisions. This situation is exemplified by inland recreational fisheries, which represent complex socioecological systems that face unpredictable and unavoidable change. Making management decisions in the context of resilience is increasingly important given mounting environmental and anthropogenic perturbations to inland systems. Herein, we propose a framework that allows resilience concepts to be better incorporated into management by (i) recognizing how current constraints and management objectives focus on desired or undesired systems (specific fish and anglers), (ii) evaluating the state of a system in terms of how both social and ecological forces enforce or erode the desired or undesired system, (iii) identifying the resilience-stage cycles a system state may undergo, and (iv) determining the broad management strategies that may be viable given the system state and resilience stage. We use examples from inland recreational fisheries to illustrate different system state and resilience stages and synthesize several key results. Across all combinations of socioecological forces, five common types of viable management strategies emerge: (i) adopt a different management preference or focus, (ii) change stakeholder attitudes or behaviors via stakeholder outreach, (iii) engage in (sometimes extreme) biological intervention, (iv) engage in fishery intervention, and (v) adopt landscape-level management approaches focusing on achieving different systems in different waters. We then discuss the challenges and weaknesses of our approach, including specifically the cases in which there are multiple strong social forces (i.e., stakeholders holding competing objectives or values) and situations where waters are not readily divisible, such as rivers or great lakes, and in which spatial separation of competing objectives will be difficult. We end with our vision of how we believe these types of operationalized resilience approaches could improve or transform inland recreational fisheries management.

Frontiers in Ecology and Evolution↗
USGS2016

Tamarisk beetle ( Diorhabda spp.) in the Colorado River basin: Synthesis of an expert panel forum

Executive Summary In 2001, the U.S. Department of Agriculture approved the release of a biological control agent, the tamarisk beetle ( Diorhabda spp.), to naturally control tamarisk populations and provide a less costly, and potentially more effective, means of removal compared with mechanical and chemical methods. The invasive plant tamarisk ( Tamarix spp.; saltcedar) occupies hundreds of thousands of acres of river floodplains and terraces across the western half of the North American continent. Its abundance varies, but can include dense monocultures, and can alter some physical and ecological processes associated with riparian ecosystems. The tamarisk beetle now occupies hundreds of miles of rivers throughout the Upper Colorado River Basin (UCRB) and is spreading into the Lower Basin. The efficacy of the beetle is evident, with many areas repeatedly experiencing tamarisk defoliation. While many welcome the beetle as a management tool, others are concerned by the ecosystem implications of widespread defoliation of a dominant woody species. As an example, defoliation may possibly affect the nesting success of the endangered southwestern willow flycatcher ( Empidonax traillii extimus ). In January 2015, the Tamarisk Coalition convened a panel of experts to discuss and present information on probable ecological trajectories in the face of widespread beetle presence and to consider opportunities for restoration and management of riparian systems in the Colorado River Basin (CRB). An in-depth description of the panel discussion follows.

Arizona, California, Chihuahua, Colorado, Idaho, K↗
USGS2019

Phylogeny and foraging mode correspond with thiaminase activity in freshwater fishes: Potential links to environmental factors

Knowledge of the dietary components of fish species is important for understanding their growth, survival, and recruitment. Deficiency in thiamine (vitamin B1) leading to reproductive failure and physiological illness among freshwater fishes has been attributed to thiaminase activity in fish in the Great Lakes and the New York Finger Lakes, but the causes of variation in thiaminase activity among freshwater fishes is unclear. We characterized thiaminase activity in 29 species of freshwater fishes across 7 ray-finned and 1 jawless family. All fish were further categorized by phylogeny, trophic category (trophic level and feeding mode), and native or non-native status to evaluate how ecological processes correspond with thiaminase activity. Thiaminase activity varied significantly across species, families, trophic factors, phylogenetic groups, and sites. Teleosts that were more recently derived had higher thiaminase activity than more basal species. Thiaminase activity was also higher among herbivores than omnivores or carnivores. This trend was clearest in the Cyprinidae family, which had the greatest range in thiaminase activity and a wide range in trophic-level position and trophic categories (herbivores, omnivores, and carnivores). Variation in average thiaminase activity of Spotfin Shiners (Cyprinella spiloptera) among sites within a watershed was correlated with anthropogenic and natural components of land cover. Our study contributes much-needed quantitative ecological information related to thiaminase activity in a suite of fish species that vary in evolutionary history, trophic level, and foraging modes. However, more studies are needed to identify interacting causes of thiaminase variation and examine the implications of these findings on the overall health of aquatic populations and freshwater ecosystems.

Freshwater Science↗
USGS2022

Modeling functional flows in California rivers

Environmental flows are critical to the recovery and conservation of freshwater ecosystems worldwide. However, estimating desired ranges of environmental flows across large, diverse landscapes is challenging. To advance protections of environmental flows for streams in California, USA, we developed a statewide modeling approach focused on functional components of the natural flow regime. Functional flow components in California streams—fall pulse flows, wet season peak flows and base flows, the spring flow recession, and dry season baseflows—support essential physical and ecological processes in riverine ecosystems. These functional flow components can be represented by functional flow metrics (FFMs) and quantified by their magnitude, timing, frequency, duration, and rate-of-change from daily streamflow records. After quantifying FFMs at reference-quality streamflow gages in California, we used machine-learning methods to estimate their natural range of values for all stream reaches in the state based on physical watershed characteristics and climatic factors. We found that the models performed well in predicting FFMs in streams across a diversity of landscape and climate contexts, according to several model performance criteria. Using the predicted FFM values, we established initial estimates of ecological flows that are expected to support critical functions and are broadly protective of ecosystem health. Modeling functional flows statewide offers a pathway for increasing the pace and scale of environmental flow protections in California and beyond.

California↗
USGS2018

Using partial aggregation in spatial capture recapture

Spatial capture–recapture (SCR) models are commonly used for analysing data collected using noninvasive genetic sampling (NGS). Opportunistic NGS often leads to detections that do not occur at discrete detector locations. Therefore, spatial aggregation of individual detections into fixed detectors (e.g., centre of grid cells) is an option to increase computing speed of SCR analyses. However, it may reduce precision and accuracy of parameter estimations. Using simulations, we explored the impact that spatial aggregation of detections has on a trade‐off between computing time and parameter precision and bias, under a range of biological conditions. We used three different observation models: the commonly used Poisson and Bernoulli models, as well as a novel way to partially aggregate detections (Partially Aggregated Binary model [PAB]) to reduce the loss of information after aggregating binary detections. The PAB model divides detectors into K subdetectors and models the frequency of subdetectors with more than one detection as a binomial response with a sample size of K. Finally, we demonstrate the consequences of aggregation and the use of the PAB model using NGS data from the monitoring of wolverine ( Gulo gulo ) in Norway. Spatial aggregation of detections, while reducing computation time, does indeed incur costs in terms of reduced precision and accuracy, especially for the parameters of the detection function. SCR models estimated abundance with a low bias (<10%) even at high degree of aggregation, but only for the Poisson and PAB models. Overall, the cost of aggregation is mitigated when using the Poisson and PAB models. At the same level of aggregation, the PAB observation model out‐performs the Bernoulli model in terms of accuracy of estimates, while offering the benefits of a binary observation model (less assumptions about the underlying ecological process) over the count‐based model. We recommend that detector spacing after aggregation does not exceed 1.5 times the scale‐parameter of the detection function in order to limit bias. We recommend the use of the PAB observation model when performing spatial aggregation of binary data as it can mitigate the cost of aggregation, compared to the Bernoulli model.

Methods in Ecology and Evolution↗
USGS2021

Structured decision making and optimal bird monitoring in the northern Gulf of Mexico

The avian conservation community struggles to design and implement large scale, long-term coordinated bird monitoring programs within the northern Gulf of Mexico due to the complexity of the conservation enterprise in the region; this complexity arises from the diverse stakeholders, multiple jurisdictions, complex ecological processes, myriad habitats, and over 500 species of birds using the region for at least some part of their annual cycle. In addition, long-term monitoring over large spatial scales is difficult because of the need for monitoring data to both (1) evaluate management and restoration outcomes, and (2) provide reliable information about the status and trends of bird populations over time. To address these challenges, the Gulf of Mexico Avian Monitoring Network developed a problem statement: “How can a cost-effective monitoring strategy for the Gulf Coast bird community and ecosystem be developed that evaluates ongoing conservation activities and chronic and acute threats; maximizes learning; and is flexible and holistic enough to detect novel ecological threats and evaluate new and emerging conservation activities?” A structured decision-making framework was then used to articulate and quantify stakeholder values related to the problem statement. One use of the stakeholder values was to develop a regional, strategic plan for bird monitoring, which is presented elsewhere. A formal and complete decision support tool for conservation investments in monitoring and research guided by the stakeholder values is presented in this report. The technical aspects of the stakeholder value model and a portfolio analysis that could be used to guide decision making when allocating resources for monitoring activities is described. Whereas the decision analysis presented here could be useful to any decision maker faced with difficult choices about resource allocation, it is designed for decision makers who request monitoring study proposals and then determine which combination of proposals to fund. The portfolio decision support tool is designed to help funding agencies and organizations identify resource allocation strategies to maximize stated objectives. To begin the decision analysis, an objectives hierarchy and quantitative performance metrics from the values of the Gulf of Mexico bird conservation community were created by a panel of regional stakeholders. Each fundamental objective and sub-objective in the hierarchy is composed of several performance metrics. To test the decision support tool, the authors evaluated a combination of monitoring study proposals written for the region and simulated proposals. Each proposal was scored against the performance metrics and used multi-attribute utility theory to combine the multiple objectives into a measure of total monitoring benefit. The total monitoring benefit and costs of each proposal were then used in a constrained optimization routine to identify optimal monitoring portfolios, that is, a combination of activities that maximizes monitoring benefits while meeting cost and other constraints of interest to stakeholders. A graphical solution based on the concept of Pareto efficiency, which is useful in situations when cost constraints and exact budgets are not known, is also provided. Finally, an evaluation of the sensitivity of the decision-making framework to the weights assigned to objectives by stakeholders is included. This decision support tool allows decision makers to identify an optimal suite of monitoring proposals with a transparent portfolio analysis that includes user-defined constraints (such as costs).

Alabama, Florida, Louisiana, Mississippi, Texas↗
USGS2010

Assessing transportation infrastructure impacts on rangelands: test of a standard rangeland assessment protocol

Linear disturbances associated with on- and off-road vehicle use on rangelands has increased dramatically throughout the world in recent decades. This increase is due to a variety of factors including increased availability of all-terrain vehicles, infrastructure development (oil, gas, renewable energy, and ex-urban), and recreational activities. In addition to the direct impacts of road development, the presence and use of roads may alter resilience of adjoining areas through indirect effects such as altered site hydrologic and eolian processes, invasive seed dispersal, and sediment transport. There are few standardized methods for assessing impacts of transportation-related land-use activities on soils and vegetation in arid and semi-arid rangelands. Interpreting Indicators of Rangeland Health (IIRH) is an internationally accepted qualitative assessment that is applied widely to rangelands. We tested the sensitivity of IIRH to impacts of roads, trails, and pipelines on adjacent lands by surveying plots at three distances from these linear disturbances. We performed tests at 16 randomly selected sites in each of three ecosystems (Northern High Plains, Colorado Plateau, and Chihuahuan Desert) for a total of 208 evaluation plots. We also evaluated the repeatability of IIRH when applied to road-related disturbance gradients. Finally, we tested extent of correlations between IIRH plot attribute departure classes and trends in a suite of quantitative indicators. Results indicated that the IIRH technique is sensitive to direct and indirect impacts of transportation activities with greater departure from reference condition near disturbances than far from disturbances. Trends in degradation of ecological processes detected with qualitative assessments were highly correlated with quantitative data. Qualitative and quantitative assessments employed in this study can be used to assess impacts of transportation features at the plot scale. Through integration with remote sensing technologies, these methods could also potentially be used to assess cumulative impacts of transportation networks at the landscape scale.

Rangeland Ecology and Management↗
USGS2016

Climate change is advancing spring onset across the U.S. national park system

Many U.S. national parks are already at the extreme warm end of their historical temperature distributions. With rapidly warming conditions, park resource management will be enhanced by information on seasonality of climate that supports adjustments in the timing of activities such as treating invasive species, operating visitor facilities, and scheduling climate-related events (e.g., flower festivals and fall leaf-viewing). Seasonal changes in vegetation, such as pollen, seed, and fruit production, are important drivers of ecological processes in parks, and phenology has thus been identified as a key indicator for park monitoring. Phenology is also one of the most proximate biological responses to climate change. Here, we use estimates of start of spring based on climatically modeled dates of first leaf and first bloom derived from indicator plant species to evaluate the recent timing of spring onset (past 10–30 yr) in each U.S. natural resource park relative to its historical range of variability across the past 112 yr (1901–2012). Of the 276 high latitude to subtropical parks examined, spring is advancing in approximately three-quarters of parks (76%), and 53% of parks are experiencing “extreme” early springs that exceed 95% of historical conditions. Our results demonstrate how changes in climate seasonality are important for understanding ecological responses to climate change, and further how spatial variability in effects of climate change necessitates different approaches to management. We discuss how our results inform climate change adaptation challenges and opportunities facing parks, with implications for other protected areas, by exploring consequences for resource management and planning.

Ecosphere↗
USGS2018

Estimating the societal benefits of carbon dioxide sequestration through peatland restoration

The Great Dismal Swamp National Wildlife Refuge (GDS) is a forested peatland that provides a number of ecosystem services including carbon (C) sequestration. We modeled and analyzed the potential capacity of the GDS to sequester C under four management scenarios: no management, no management with catastrophic fire, current management, and increased management. The analysis uses the Land Use and Carbon Scenario Simulator developed for the GDS to estimate net ecosystem C balance. The model simulates net C gains and losses on an annual time-step from 2013 through 2062 which is converted to carbon dioxide equivalent (CO2-eq) and monetized using the Interagency Working Group's Social Cost of Carbon. Our analysis incorporates compounded uncertainty including variation in ecological processes, temporal and spatial heterogeneity, and uncertainty in the discount rate. The no management scenario results in 2.4 million tons of CO2 emissions with a Net Present Value (NPV) under a 3% discount rate of −\$67 million. No management with catastrophic fires emits 6.5 million tons of CO2 with an NPV of −\$232 million. Current management avoids 9.9 million tons of emissions (via sequestration) with an NPV of \$326 million. Increased management avoids 16.5 million tons of emissions with an NPV of \$524 million.

North Carolina, Virginia↗
USGS2014

Connecting the dots: a collaborative USGS-NPS effort to expand the utility of monitoring data

The Natural Resource Challenge (National Park Service 1999) was a call to action. It constituted a mandate for monitoring based on the twin premises that (1) natural resources in national parks require active management and stewardship if we are to protect them from gradual degradation, and (2) we cannot protect what we do not understand. The intent of the challenge was embodied in its original description: We must expand existing inventory programs and develop efficient ways to monitor the vital signs of natural systems. We must enlist others in the scientific community to help, and also facilitate their inquiry. Managers must have and apply this information to preserve our natural resources. In this article, we report on ongoing collaborative work between the National Park Service (NPS) and the US Geological Survey (USGS) that seeks to add to our scientific understanding of the ecological processes operating behind vital signs monitoring data. The ultimate goal of this work is to provide insights that can facilitate an understanding of the systems and identify potential opportunities for active stewardship by NPS managers (Bennetts et al. 2007; Mitchell et al. 2014). The bulk of the work thus far has involved Acadia and Rocky Mountain national parks, but there are plans for extending the work to additional parks. Our story stats with work designed to consider ways of assessing the status and condition of natural resources and the potential for historical or ongoing influences of human activities. In the 1990s, the concept of "biotic integrity" began to take hold as an aspiration for developing quantitative indices describing how closely the conditions at a site resemble those found at pristine, unimpacted sites. Quantitative methods for developing indices of biotic integrity (IBIs) and elaborations of that idea (e.g., ecological integrity) have received considerable attention and application of these methods to natural resources has become widespread (Karr 1991; Barbour et al. 1999; Stoddard et al. 2008). Despite widespread use, many questions remain about how metrics are combined to form effective indices and about how to interpret both. Scientists and natural resource specialists within NPS and USGS have joined forces to critique the current analysis methods, with the collaboration involving the Rocky Mountain and Northeast Temperate NPS Inventory and Monitoring (I & M) networks, along with others, and USGS scientists from the National Wetlands Research Center and Patuxent Wildlife Research Center. Funding that initiated the project was from a joint-partnership fund managed by the USGS Ecosystems Program for National Park Monitoring research and the work was focused at Acadia National Park and Rocky Mountain National Park. Here we present synopses of two major issues addressed by the group.

The George Wright Forum↗
USGS2014

Seasonal drift and feeding periodicity during summer of the amphipod, Gammarus psuedolimnaeus

Downstream drift of aquatic invertebrates is an important ecological process that varies temporally. Seasonal patterns of diel drift and diel feeding periodicity during summer of the amphipod Gammarus pseudolimnaeus were examined in a small stream in central New York. Seasonal trends in drift were similar with peak drift occurring from 2000 to 0400 h. Very little drift occurred during the day. Feeding intensity of G. pseudolimnaeus was greatest from 2000 to 0400 h and was significantly greater than at 0400 to 0800 h and 0800 to 1200 h. Previous research on feeding periodicity of this species found no evidence of periods of increased food consumption. Conflicting results between this study and earlier studies may be due to sampling drifting versus non-drifting amphipods.

New York↗
USGS2023

Virtual snow stakes: a new method for snow depth measurement at remote camera stations

Remote cameras are used to study demographics, ecological processes, and behavior of wildlife populations. Cameras have also been used to measure snow depth with physical snow stakes. However, concerns that physical instruments at camera sites may influence animal behavior limit installation of instruments to facilitate collecting such data. Given that snow depth data are inherently contained within images, potential insights that could be made using these data are lost. To facilitate camera-based snow depth observations without additional equipment installation, we developed a method implemented in an R package called edger to superimpose virtual measurement devices onto images. The virtual snow stakes can be used to derive snow depth measurements. We validated the method for snow depth estimation using camera data from Latah County, Idaho, USA in winter 2020–2021. Mean bias error between the virtual snow stake and a physical snow stake was 5.8 cm; the mean absolute bias error was 8.8 cm. The mean Nash Sutcliffe Efficiency score comparing the fit of the 2 sets of measurements within each camera was 0.748, indicating good agreement. The edger package provides researchers with a means to take critical measurements for ecological studies without the use of physical objects that could alter animal behavior, and snow data at finer scales can complement other snow data sources that have coarser spatial and temporal resolution.

Idaho↗
USGS2018

A guide to Bayesian model checking for ecologists

Checking that models adequately represent data is an essential component of applied statistical inference. Ecologists increasingly use hierarchical Bayesian statistical models in their research. The appeal of this modeling paradigm is undeniable, as researchers can build and fit models that embody complex ecological processes while simultaneously accounting for observation error. However, ecologists tend to be less focused on checking model assumptions and assessing potential lack of fit when applying Bayesian methods than when applying more traditional modes of inference such as maximum likelihood. There are also multiple ways of assessing the fit of Bayesian models, each of which has strengths and weaknesses. For instance, Bayesian P values are relatively easy to compute, but are well known to be conservative, producing P values biased toward 0.5. Alternatively, lesser known approaches to model checking, such as prior predictive checks, cross‐validation probability integral transforms, and pivot discrepancy measures may produce more accurate characterizations of goodness‐of‐fit but are not as well known to ecologists. In addition, a suite of visual and targeted diagnostics can be used to examine violations of different model assumptions and lack of fit at different levels of the modeling hierarchy, and to check for residual temporal or spatial autocorrelation. In this review, we synthesize existing literature to guide ecologists through the many available options for Bayesian model checking. We illustrate methods and procedures with several ecological case studies including (1) analysis of simulated spatiotemporal count data, (2) N‐mixture models for estimating abundance of sea otters from an aircraft, and (3) hidden Markov modeling to describe attendance patterns of California sea lion mothers on a rookery. We find that commonly used procedures based on posterior predictive P values detect extreme model inadequacy, but often do not detect more subtle cases of lack of fit. Tests based on cross‐validation and pivot discrepancy measures (including the “sampled predictive P value”) appear to be better suited to model checking and to have better overall statistical performance. We conclude that model checking is necessary to ensure that scientific inference is well founded. As an essential component of scientific discovery, it should accompany most Bayesian analyses presented in the literature.

Ecological Monographs↗
USGS2002

Scaling roads and wildlife: The Cinderella principle

It is clear that a reduction in both direct and indirect effects of roads and road networks must be the goal of management agencies. However, increased permeability of roaded landscapes can only be achieved by up-front planning and subsequent mitigative actions. The key is to understand that roads must be made permeable to the movement of animals. More profoundly, ecosystem services, i.e., clean water, clean air, uncontaminated soil, natural landscapes, recreation opportunities, abundant wildlife, and life sustaining ecological processes must not be seriously impacted. In other words, quality of life as measured by ecosystem services should be a major component of the planning process when roads are constructed or improved. Mitigative structures exist to increase permeability of roads. Wildlife overpasses and underpasses, often referred to as ecoducts or green bridges, with associated structures to enable larger animals to exit the road right of way, e.g., earthen escape ramps (BISSONETTE and HAMMER, 2001), various culvert designs for smaller animals including badger pipes and amphibian and reptile tunnels, and fish ladders are but a small sampling of the structures already in place around the world. What is needed is attention to the big picture. Landscapes need to be reconnected and made more permeable. Responsible agencies and organizations need to be aggressive about promoting mitigations and a conservation ethic into road planning. Only with a broad based effort between a concerned public, a database to work from, and a willingness of responsible agencies, will the now very large virtual footprint of roads and road networks be reduced to more closely approximate the physical footprint. By embracing the Cinderella Principle of making the virtual shoe fit more closely the actual physical footprint of roads, we will be able to achieve a closer connection with ecological harmony with its resultant effect of abundant wildlife.

Conference Paper↗
USGS2016

The statistical power to detect cross-scale interactions at macroscales

Macroscale studies of ecological phenomena are increasingly common because stressors such as climate and land-use change operate at large spatial and temporal scales. Cross-scale interactions (CSIs), where ecological processes operating at one spatial or temporal scale interact with processes operating at another scale, have been documented in a variety of ecosystems and contribute to complex system dynamics. However, studies investigating CSIs are often dependent on compiling multiple data sets from different sources to create multithematic, multiscaled data sets, which results in structurally complex, and sometimes incomplete data sets. The statistical power to detect CSIs needs to be evaluated because of their importance and the challenge of quantifying CSIs using data sets with complex structures and missing observations. We studied this problem using a spatially hierarchical model that measures CSIs between regional agriculture and its effects on the relationship between lake nutrients and lake productivity. We used an existing large multithematic, multiscaled database, LAke multiscaled GeOSpatial, and temporal database (LAGOS), to parameterize the power analysis simulations. We found that the power to detect CSIs was more strongly related to the number of regions in the study rather than the number of lakes nested within each region. CSI power analyses will not only help ecologists design large-scale studies aimed at detecting CSIs, but will also focus attention on CSI effect sizes and the degree to which they are ecologically relevant and detectable with large data sets.

Ecosphere↗
USGS2017

A hierarchical model for estimating the spatial distribution and abundance of animals detected by continuous-time recorders

Motivation Several spatial capture-recapture (SCR) models have been developed to estimate animal abundance by analyzing the detections of individuals in a spatial array of traps. Most of these models do not use the actual dates and times of detection, even though this information is readily available when using continuous-time recorders, such as microphones or motion-activated cameras. Instead most SCR models either partition the period of trap operation into a set of subjectively chosen discrete intervals and ignore multiple detections of the same individual within each interval, or they simply use the frequency of detections during the period of trap operation and ignore the observed times of detection. Both practices make inefficient use of potentially important information in the data. Model and data analysis We developed a hierarchical SCR model to estimate the spatial distribution and abundance of animals detected with continuous-time recorders. Our model includes two kinds of point processes: a spatial process to specify the distribution of latent activity centers of individuals within the region of sampling and a temporal process to specify temporal patterns in the detections of individuals. We illustrated this SCR model by analyzing spatial and temporal patterns evident in the camera-trap detections of tigers living in and around the Nagarahole Tiger Reserve in India. We also conducted a simulation study to examine the performance of our model when analyzing data sets of greater complexity than the tiger data. Benefits Our approach provides three important benefits: First, it exploits all of the information in SCR data obtained using continuous-time recorders. Second, it is sufficiently versatile to allow the effects of both space use and behavior of animals to be specified as functions of covariates that vary over space and time. Third, it allows both the spatial distribution and abundance of individuals to be estimated, effectively providing a species distribution model, even in cases where spatial covariates of abundance are unknown or unavailable. We illustrated these benefits in the analysis of our data, which allowed us to quantify differences between nocturnal and diurnal activities of tigers and to estimate their spatial distribution and abundance across the study area. Our continuous-time SCR model allows an analyst to specify many of the ecological processes thought to be involved in the distribution, movement, and behavior of animals detected in a spatial trapping array of continuous-time recorders. We plan to extend this model to estimate the population dynamics of animals detected during multiple years of SCR surveys.

Western Ghats, Nagarahole Tiger Reserve↗
USGS2026

Mississippi’s resiliency and changing environmental conditions

Mississippi is experiencing shifts in environmental conditions, many of which are expected to intensify in the coming decades, and will have important implications for ecosystems, species, and natural resource management across the state. Historical climate analyses and downscaled projections summarized for the state’s Environmental Protection Agency (EPA) level III Ecoregions show that Mississippi will likely face increases in extremely hot days, more intense heatwaves, greater evapotranspiration, and reductions in cold-season extremes. Temperature trends indicate that while Mississippi has warmed relatively little over the last century, recent years have been among the warmest on record. Projections suggest substantial increases in the number of days with maximum temperatures at or above 95°F across all Ecoregions, particularly under higher warming scenarios. Correspondingly, the number of freezing nights is expected to decline, with statewide decreases of 7–21 days depending on the global warming level and timeframe. These combined patterns are likely to reshape habitat conditions, influence species’ thermal stress, and alter ecological processes such as soil moisture retention and stream temperature regimes. Mississippi’s hydrological systems are also expected to be significantly affected. Extreme rainfall events, particularly the most intense 1% of precipitation days, are projected to increase across the state, raising risks of flooding, erosion, and altered stream flow. Coastal Mississippi faces additional stress from sea‑level rise, which is already contributing to more frequent high‑tide flooding; projections show continued increases in inundation risk throughout the century. These flooding patterns, combined with stronger hurricane rainfall rates and the potential for landfalling storms to stall, pose ongoing threats to coastal ecosystems and communities. The state is also vulnerable to extreme weather hazards such as tornadoes. Recent research shows a geographic shift in tornado activity toward the Southeast, with Mississippi experiencing some of the nation’s greatest increases in favorable tornado days and nighttime tornado frequency—hazards that have direct implications for wildlife, habitat stability, and human safety. Drought conditions may intensify as well: higher temperatures and increased evapotranspiration during dry spells could worsen water stress regardless of uncertainty in average annual precipitation. These changing environmental conditions have important consequences for Mississippi’s Species of Greatest Conservation Need (SGCN). Vulnerability assessments and ecological niche models indicate that several fish, mussel, crayfish, plant, amphibian, bird, and mammal species may face heightened stress due to warming temperatures, shifting hydrology, habitat loss, and increases in extreme events. For example, many cold‑water and moisture‑dependent species in the state’s rivers and wetlands are already near their thermal limits, and further warming could reduce suitable habitat. Birds breeding in bottomland hardwood forests, such as the Prothonotary Warbler, are increasingly susceptible to nest loss from flooding. Similarly, species like the Louisiana Black Bear may encounter higher risks from habitat inundation and shifting food availability. The “A Closer Look” section underscores the vulnerability of the Mississippi Alluvial Plain—one of the state’s most ecologically rich yet heavily altered Ecoregions. Its bottomland hardwood forests, wetlands, and floodplain habitats support diverse wildlife but are increasingly threatened by rising temperatures, hydrological changes, development pressures, and compounded disturbances. These habitats provide critical ecosystem services such as water filtration, flood attenuation, and biodiversity support, making their conservation particularly urgent under future conditions. Collectively, these findings indicate that Mississippi’s ongoing and projected environmental changes present both challenges and opportunities for natural resource management. Incorporating adaptation strategies into the State Wildlife Action Plan will be essential for sustaining habitats, mitigating risks, and supporting the long‑term resilience of Mississippi’s wildlife and ecosystems.

Mississippi↗