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USGS2016

An evaluation of inorganic toxicity reference values for use in assessing hazards to American robins ( Turdus migratorius )

When performing screening-level and baseline risk assessments, assessors usually compare estimated exposures of wildlife receptor species with toxicity reference values (TRVs). We modeled the exposure of American robins ( Turdus migratorius ) to 10 elements (As, Cd, Cr, Cu, Hg, Mn, Pb, Se, Zn, and V) in spring and early summer, a time when earthworms are the preferred prey. We calculated soil benchmarks associated with possible toxic effects to these robins from 6 sets of published TRVs. Several of the resulting soil screening-level benchmarks were inconsistent with each other and less than soil background concentrations. Accordingly, we examined the derivations of the TRVs as a possible source of error. In the case of V, a particularly toxic chemical compound (ammonium vanadate) containing V, not normally present in soil, had been used to estimate a TRV. In the cases of Zn and Cu, use of uncertainty values of 10 in estimating TRVs led to implausibly low soil screening values. In the case of Pb, a TRV was calculated from studies demonstrating reductions in egg production in Japanese quail ( Coturnix coturnix japonica ) exposed to Pb concentrations well below than those causing toxic effects in other species of birds. The results on quail, which were replicated in additional trials, are probably not applicable to other, unrelated species, although we acknowledge that only a small fraction of all species of birds has been tested. These examples underscore the importance of understanding the derivation and relevance of TRVs before selecting them for use in screening or in ecological risk assessment.

Integrated Environmental Assessment and Management↗

USGS2016

Panarchy use in environmental science for risk and resilience planning

Environmental sciences have an important role in informing sustainable management of built environments by providing insights about the drivers and potentially negative impacts of global environmental change. Here, we discuss panarchy theory, a multi-scale hierarchical concept that accounts for the dynamism of complex socio-ecological systems, especially for those systems with strong cross-scale feedbacks. The idea of panarchy underlies much of system resilience, focusing on how systems respond to known and unknown threats. Panarchy theory can provide a framework for qualitative and quantitative research and application in the environmental sciences, which can in turn inform the ongoing efforts in socio-technical resilience thinking and adaptive and transformative approaches to management.

Environment Systems and Decisions↗

USGS2017

International Watershed Technology: Improving Water Quality and Quantity at the Local, Basin, and Regional Scales

This article introduces the five papers in the “International Watershed Technology” collection. These papers were selected from 60 technical presentations at the fifth biennial ASABE 21st Century Watershed Technology Conference and Workshop: Improving the Quality of Water Resources at Local, Basin, and Regional Scales, held in Quito, Ecuador, on 3-9 December 2016. The conference focused on solving spatial and temporal water quality and quantity problems and addressed topics such as watershed management in developing countries, aquatic ecology and ecohydrology, ecosystem services, climate change mitigation strategies, flood forecasting, remote sensing, and water resource policy and management. While diverse, the presentation topics reflected the continuing evolution of the “data mining” and “big data” themes of past conferences related to geospatial data applications, with increasing emphasis on practical solutions. The papers selected for this collection represent applications of spatial data analyses toward practical ends with a theme of “tools and techniques for sustainability.” The papers address a range of topics, including the matching of crops with water availability, and assessing the environmental impacts of agricultural production. The papers identify some of the latest tools and techniques for improving sustainability in watershed resource management that are relevant to both developing and developed countries.

Transactions of the ASABE↗

USGS2013

Spatial capture-recapture models for jointly estimating population density and landscape connectivity

Population size and landscape connectivity are key determinants of population viability, yet no methods exist for simultaneously estimating density and connectivity parameters. Recently developed spatial capture–recapture (SCR) models provide a framework for estimating density of animal populations but thus far have not been used to study connectivity. Rather, all applications of SCR models have used encounter probability models based on the Euclidean distance between traps and animal activity centers, which implies that home ranges are stationary, symmetric, and unaffected by landscape structure. In this paper we devise encounter probability models based on “ecological distance,” i.e., the least-cost path between traps and activity centers, which is a function of both Euclidean distance and animal movement behavior in resistant landscapes. We integrate least-cost path models into a likelihood-based estimation scheme for spatial capture–recapture models in order to estimate population density and parameters of the least-cost encounter probability model. Therefore, it is possible to make explicit inferences about animal density, distribution, and landscape connectivity as it relates to animal movement from standard capture–recapture data. Furthermore, a simulation study demonstrated that ignoring landscape connectivity can result in negatively biased density estimators under the naive SCR model.

Ecology↗

USGS2002

Flood pulsing in wetlands: Restoring the natural hydrological balance

The latest cutting-edge research on flood pulsing and wetland restoration in North America. Presenting the latest research from leaders in the field of restoration ecology, Flood Pulsing in Wetlands reflects the current movement to incorporate flood pulsing into wetland restoration efforts. Emphasizing how integral flood pulsing is to successful wetland restoration, the book's contributors provide descriptions of restoration projects across North America in which flood pulsing has been primarily used to restore beneficial hydrodynamic conditions to floodplain areas, and improve or save vegetation, wildlife, and terrain. Detailing the importance and applicability of recreating flood-pulsed conditions on floodplains for successful restoration, the first chapter introduces the concept of flood pulse and its unique role in wetland restoration. The following chapters detail the strategies and results of individual projects and the impact flood pulsing had on the projects' overall goals. Case studies detail the history of each region, such as the Southwest, including the Sonoran Desert communities and the Middle Rio Grande; the Missouri River in Montana; the Illinois River Valley; and the Southeast, including Brushy Lake, Arkansas. Also documented is the most famous case of flood pulsing used in the restoration of an entire landscape, the Kissimmee River project. Approaches used to restore specific plant and animal populations, the unique ecological concerns of each region, and the future outlook for each area are fully described. Extensive bibliographies for each chapter make Flood Pulsing in Wetlands: Restoring the Natural Hydrological Balance the essential reference for restoration ecologists, consultants in wetland restoration, government and restoration agency employees, land managers, ecologists, foresters, and geologists.

Book↗

USGS2026

Applying automated avalanche terrain mapping to wildlife ecology: A case study of Dall's sheep in southcentral Alaska

Avalanche hazard has been studied extensively in the context of human risk, but its role in alpine wildlife ecology remains poorly understood. Long-term telemetry studies have revealed that avalanches are an important source of mortality for some mountain ungulates. Investigating the processes underlying these events is challenging because avalanche activity and snowpack conditions are rarely monitored across the spatial and temporal extent of wildlife studies. Recent advances in automated avalanche terrain mapping provide a new opportunity to address this knowledge gap by quantifying wildlife exposure to modeled avalanche terrain across large landscapes. We demonstrate this application using Dall's sheep (Ovis dalli dalli) in southcentral Alaska, where a 12-year study identified avalanches as the leading known cause of adult mortality. We used GPS locations from 134 adult Dall's sheep (385 sheep-years) collected between 2012 and 2024 across Chugach State Park and the Talkeetna Mountains, Alaska, USA. We characterized seasonal patterns of terrain exposure using the Automated Avalanche Terrain Exposure Scale and complementary metrics representing potential release areas, runout terrain, slope, and aspect. Guided by previous studies of Dall's sheep habitat selection, we developed a priori ecological expectations for seasonal exposure and used descriptive summaries of GPS locations to examine patterns of sheep use. Sheep locations occurred almost exclusively within avalanche terrain throughout the year, with Complex terrain accounting for 61–67% of locations across seasons. Winter and spring locations occurred on slightly steeper slopes while simultaneously having lower potential release area values and lower-value runout terrain than summer and autumn locations. Use of south-facing terrain increased from 64% of locations in summer to 70% in autumn and winter and 83% in spring—coinciding with the highest seasonal concentration of avalanche mortality. These descriptive patterns illustrate how complementary avalanche-terrain metrics can reveal patterns of wildlife exposure that would not be apparent from slope angle and aspect alone. Integrating automated avalanche terrain mapping with wildlife telemetry provides a new approach for identifying patterns of terrain exposure to guide further investigation into factors influencing wildlife avalanche risk.

Alaska↗

USGS2014

Impacts of drought and crayfish invasion on stream ecosystem structure and function

Drought and seasonal drying can be important disturbance events in many small streams, leading to intermittent or isolated habitats. Many small streams contain crayfish populations that are often keystone or dominant species in these systems. I conducted an experiment in stream mesocosms to examine the effects of drought and potential ecological redundancy of a native and invasive crayfish species. I examined the effects of drought (drought or control) and crayfish presence (none, native crayfish Orconectes eupunctus or invasive crayfish Orconectes neglectus ) on stream mesocosm structure and function (leaf breakdown, community metabolism, periphyton, sediment and chironomid densities) in a fully factorial design. Each mesocosm contained a deep and shallow section, and drought treatments had surface water present (5-cm depth) in deep sections where tiles and leaf packs were placed. Drought and crayfish presence did not interact for any response variable. Drought significantly reduced leaf breakdown, and crayfish presence significantly increased leaf breakdown. However, the native and invasive crayfish species did not differ significantly in their effects on leaf breakdown. Drought significantly reduced primary production and community respiration overall, whereas crayfish presence did not significantly affect primary production and community respiration. Neither drought nor crayfish presence significantly affected periphyton overall. However, drought significantly reduced autotrophic index (AI), and crayfish presence increased AI. Inorganic sediment and chironomid density were not affected by drought, but both were significantly reduced by crayfish presence. O. eupunctus reduced AI and sediment more than O. neglectus did. Neither drought nor crayfish species significantly affected crayfish growth or survival. Drought can have strong effects on ecosystem function, but weaker effects on benthic structure. Crayfish can have strong effects on ecosystem structure and function regardless of drought. In stream mesocosms, native and invasive crayfish species appeared largely ecologically redundant, although subtle differences in crayfish effects could cascade throughout the food web, and further research is needed to address this question.

River Research and Applications↗

USGS2014

A suggestion for computing objective function in model calibration

A parameter-optimization process (model calibration) is usually required for numerical model applications, which involves the use of an objective function to determine the model cost (model-data errors). The sum of square errors (SSR) has been widely adopted as the objective function in various optimization procedures. However, ‘square error’ calculation was found to be more sensitive to extreme or high values. Thus, we proposed that the sum of absolute errors (SAR) may be a better option than SSR for model calibration. To test this hypothesis, we used two case studies—a hydrological model calibration and a biogeochemical model calibration—to investigate the behavior of a group of potential objective functions: SSR, SAR, sum of squared relative deviation (SSRD), and sum of absolute relative deviation (SARD). Mathematical evaluation of model performance demonstrates that ‘absolute error’ (SAR and SARD) are superior to ‘square error’ (SSR and SSRD) in calculating objective function for model calibration, and SAR behaved the best (with the least error and highest efficiency). This study suggests that SSR might be overly used in real applications, and SAR may be a reasonable choice in common optimization implementations without emphasizing either high or low values (e.g., modeling for supporting resources management).

Ecological Informatics↗

USGS2021

Integrating tracking and resight data enables unbiased inferences about migratory connectivity and winter range survival from archival tags

Archival geolocators have transformed the study of small, migratory organisms but analysis of data from these devices requires bias correction because tags are only recovered from individuals that survive and are re-captured at their tagging location. We show that integrating geolocator recovery data and mark–resight data enables unbiased estimates of both migratory connectivity between breeding and nonbreeding populations and region-specific survival probabilities for wintering locations. Using simulations, we first demonstrate that an integrated Bayesian model returns unbiased estimates of transition probabilities between seasonal ranges. We also used simulations to determine how different sampling designs influence the estimability of transition probabilities. We then parameterized the model with tracking data and mark–resight data from declining Painted Bunting ( Passerina ciris ) populations breeding in the eastern United States, hypothesized to be threatened by the illegal pet trade in parts of their Caribbean, nonbreeding range. Consistent with this hypothesis, we found that male buntings wintering in Cuba were 20% less likely to return to the breeding grounds than birds wintering elsewhere in their range. Improving inferences from archival tags through proper data collection and further development of integrated models will advance our understanding of the full annual cycle ecology of migratory species.

Ornithological Applications↗

USGS2021

Patterns of conifer invasion following prescribed fire in grasslands and oak woodlands of Redwood National Park, California

The invasion, or “encroachment”, of native conifers commonly occurs in the absence of frequent fire in deciduous woodlands and grasslands of the Pacific Northwest, USA. To effectively target restoration activities, managers require a better understanding of the outcomes of prescribed fire and the spatial patterns of conifer invasions. We examined the duration of prescribed fire effectiveness for controlling conifer invasions, as well as multiple site characteristics (including distance to potential seed trees, prescribed fire history, and topographic variables) that influenced conifer invasions following fire in grassland and oak woodland communities in the Bald Hills of Redwood National Park, California. Prescribed fire substantially reduced counts of small conifers (< 0.91 m in height), but reinvasion was rapid for sites ≤75 m from the forest edge, returning to pre‐fire levels by 2 years post‐fire. Following prescribed fires the presence of conifers was largely determined by proximity of overstory trees, with more than 95% of conifer seedlings (stems <1.37 m in height) found within 44 m of an overstory conifer. Number of fires and years since the most recent fire were not strongly related to counts of conifer seedlings and density of conifer saplings (stems from 0.1 to 10 cm diameter at breast height, 1.37 m). Our results suggest that in the Bald Hills vulnerability to conifer invasion is principally a function of proximity to seed sources, and the frequent application of prescribed fire or surrogate treatments are needed to prevent conifer seedlings from attaining fire‐resistant sizes.

California↗

USGS2022

Golden eagle occupancy surveys and monitoring strategy in coastal southern California, United States

Golden eagles ( Aquila chrysaetos ) are of increasing conservation concern in western North America. Effective conservation measures for this wide-ranging, federally protected raptor species require monitoring frameworks that accommodate strong inference on the status of breeding populations across vast landscapes. We used a broad-scale sampling design to identify relationships between landscape conditions, detection rates, and site occupancy by territorial pairs of golden eagles in coastal southern California, United States. In 2016 and 2017, we surveyed 175 territory-sized sample sites (13.9-km 2 randomly selected grid cells) up to four times each year and detected a pair of eagles at least once in 22 (12.6%) sites. The probability of detecting pairs of eagles varied substantially between years and declined with increasing amounts of forest cover at survey sites, which obscured observations of eagles during ground-based surveys. After accounting for variable detection, the mean estimate of expected site occupancy by eagle pairs was 0.156 (SE = 0.081). Site-level estimates of occupancy were greatest (>0.30) at sample sites with more rugged terrain conditions, <20% human development, and lower amounts of scrubland vegetation cover. The proportion of a sample site with open grassland or forest cover was not strongly correlated with occupancy. We estimated that approximately 16% of the 5,338-km 2 sampling frame was used by resident pairs of golden eagles, corresponding to a sparsely distributed population of about 60 pairs (95% CI = 19 – 151 pairs). Our study provided baseline data for future surveys of golden eagles along with a widely applicable monitoring framework for identifying spatial conservation priorities in urbanizing landscapes.

California↗

USGS2023

Long-term monitoring in transition: Resolving spatial mismatch and integrating multistate occupancy data

The success of long-term wildlife monitoring programs can be influenced by many factors and study designs often represent compromises between spatial scales and costs. Adaptive monitoring programs can iteratively manage this tension by adopting new cost-efficient technologies, which can provide projects the opportunity to reallocate costs to address new hypotheses, adapt to changing ecological conditions, or adjust sampling scale or resolution. If there is interest in longer time series of monitoring data, methodological transitions may necessitate integrated models to link newer data with historical data. However, data integration can be difficult if spatial or temporal scales are mismatched. Here, we develop an integrated multistate site-occupancy model and resolve sample unit spatial mismatch to link datasets from two northern spotted owl ( Strix occidentalis caurina ) monitoring schemes that broadly overlapped during a methodological transition. The first dataset was obtained from a decades-long spotted owl monitoring program using call-playback and mark-resight surveys on historical territories of varying size and shape. This monitoring program has recently transitioned to passive acoustic monitoring of randomly selected 5-km 2 hexagons over larger spatial extents. Both monitoring datasets overlapped with areas in which barred owl ( Strix varia ), an invasive competitor that has played an important role in northern spotted owl declines, were being removed experimentally. Reconciling spatial mismatch substantially increased the representation of the call-playback dataset and integrating the two datasets increased precision of spotted owl use and paired occupancy estimates relative to single dataset estimates. Estimates of spotted owl pair occupancy across the study area were lower than previous territory-based estimates based on call-playback surveys. Our integrated model further showed that a concurrent barred owl removal experiment increased landscape use and site occupancy by pairs of spotted owls. Our empirical application of an integrated modelling approach demonstrates a useful analytical framework for long-term monitoring efforts undergoing methodological transitions (e.g. mark-recapture to non-invasive population monitoring). This framework allows monitoring programs to maintain continuity of monitoring objectives across methodological transitions, rigorously incorporate previous findings, and adaptively respond to changing ecological conditions.

Oregon↗

USGS2024

Estimating traffic volume and road age in Wyoming to inform resource management planning: An application with wildlife-vehicle collisions

Road networks and their associated vehicular traffic disturb many terrestrial systems, but inventories of roads used to assess these effects often focus on the ‘where’ (e.g., local road type and density) and neglect the ‘when’ (e.g., temporal disturbance) or ‘how much’ (e.g., traffic volume disturbance). We developed annual estimates of the ‘when’ (road age) and ‘how much’ (vehicular traffic volume) across 148,172 km of highways, arterials, collectors, local, and gravel/graded roads within the state of Wyoming for the years 1986 to 2020 to provide a comprehensive dataset for future ecological investigations. We leveraged a suite of ancillary data on surface disturbances (e.g., oil & gas drilling operations, wind turbines, and open pit mines) with known establishment dates and combined them using graph theory and centrality metrics to estimate the age of each road. We then predicted traffic volume obtained from the Wyoming Department of Transportation for each year across Wyoming using a machine learning method, XGBoost, and a separate set of spatial covariates hypothesized to explain traffic patterns across large regions. We found that 132,476 km of these roads likely existed before 1986, but that 16,693 km (10.7 %) of roads have been built since 1986. Overall, our estimates of road age were 89 % accurate when assessed on a subset of 1,330 roads with high-resolution aerial imagery. Mean absolute error for predicting traffic volume ranged from 35.2 to 77.9 annual average daily traffic (aadt) for trucks and 269.2 to 516.7 aadt for all-vehicles across the 35 years. We found that mean traffic volume across the state increased by 23 % for both truck-only traffic and all vehicular traffic from 1986 to 2020. However, changes in traffic volume have varied substantially across the state (e.g., 100 % increases in volume in some areas, while other areas experienced declines of up to 1,786 %). We also illustrate a novel application of these data by predicting rates of reported wildlife-vehicle collisions (WVCs) along a subset of roads. We found evidence of a non-linear relationship that supported a threshold hypothesis for WVCs, wherein increases in traffic volume equate to increases in WVCs up to a threshold, above which increases in traffic volume result in declines in WVCs. The data provided here will enable better-informed studies of road ecology to address how roads may affect wildlife populations and key ecosystems across Wyoming.

Wyoming↗

USGS2023

Mapping landslide susceptibility over large regions with limited data

Landslide susceptibility maps indicate the spatial distribution of landslide likelihood. Modeling susceptibility over large or diverse terrains remains a challenge due to the sparsity of landslide data (mapped extent of known landslides) and the variability in triggering conditions. Several different data sampling strategies of landslide locations used to train a susceptibility model are used to mitigate this challenge. However, to our knowledge, no study has systematically evaluated how different sampling strategies alter a model's predictor effects (i.e., how a predictor value influences the susceptibility output) critical to explaining differences in model outputs. Here, we introduce a statistical framework that examines the variation in predictor effects and the model accuracy (measured using receiver operator characteristics) to highlight why certain sampling strategies are more effective than others. Specifically, we apply our framework to an array of logistic regression models trained on landslide inventories collected at sub-regional scales over four terrains across the United States. Results show significant variations in predictor effects depending on the inventory used to train the models. The inconsistent predictor effects cause low accuracies when testing models on inventories outside the domain of the training data. Grouping test and training sets according to physiographic and ecological characteristics, which are thought to share similar triggering mechanisms, does not improve model accuracy. We also show that using limited landslide data distributed uniformly over the entire modeling domain is better than using dense but spatially isolated data to train a model for applications over large regions.

California, Kentucky, North Carolina, West Virgini↗

USGS2019

Bioclimatic envelopes for individual demographic events driven by extremes: Plant mortality from drought and warming

The occurrence of plant species across the globe is largely constrained by climate. Ecologists use plant-climate relationships such as bioclimatic envelopes and related niche models to determine potential environmental conditions promoting probable species occurrence. Traditionally bioclimatic envelopes either exclude disturbance explicitly, or only include disturbance as infrequent and smaller scale processes, assuming that the net effect of climate parameters on key demographic processes predict longer-term equilibrial responses of biota. Due to increasing frequency and extent of extreme events associated with climate change, ecologists may need to increase focus on individual demographic events driven by environmental extremes such as widespread coral bleaching or large-scale tree die-off. An expanded focus on how extreme events catalyze individual demographic events would complement existing tools that predict long-term equilibrial biogeographic responses associated with long-term trends in climate. In many cases, extreme conditions (e.g. drought) are a necessary precursor for an abrupt demographic event (e.g. large-scale tree die-off) and the effects of extremes can be exacerbated by climatic trends (e.g. higher temperatures in combination with drought). Here, we highlight application of bioclimatic models for predicting individual demographic events. Defining the environmental conditions that precipitate demographic events such as widespread tree mortality is a necessary precursor for applying predictions to geographic space, and may require challenging biota with experiments that impose a combination of ecologically extreme conditions in one parameter and a shifting distribution in another (e.g. drought under higher temperatures). Currently data on conditions that drive individual demographic events associated with extremes are usually rare, aggregated across time, and/or correlative. We highlight this approach with a case study of drought-induced mortality in adult Pinus edulis trees that predicts a more than five-fold increase in frequency of die-off events under a global change scenario of high emissions. This general approach complements both traditional bioclimatic envelopes and more detailed physiological approaches currently being refined to address climate change challenges. Notably, this proposed approach could be developed for any climate condition or plant life stage, offering promise for improving predictions of individual demographic events that are rapidly altering ecosystems globally.

International Journal of Plant Sciences↗

USGS2022

Assessing vegetation recovery from energy development using a dynamic reference approach

Ecologically relevant references are useful for evaluating ecosystem recovery, but references that are temporally static may be less useful when environmental conditions and disturbances are spatially and temporally heterogeneous. This challenge is particularly acute for ecosystems dominated by sagebrush ( Artemisia spp.), where communities may require decades to recover from disturbance. We demonstrated application of a dynamic reference approach to studying sagebrush recovery using three decades of sagebrush cover estimates from remote sensing (1985–2018). We modelled recovery on former oil and gas well pads ( n = 1200) across southwestern Wyoming, USA, relative to paired references identified by the Disturbance Automated Reference Toolset. We also used quantile regression to account for unmodelled heterogeneity in recovery, and projected recovery from similar disturbance across the landscape. Responses to weather and site-level factors often differed among quantiles, and sagebrush recovery on former well pads increased more when paired reference sites had greater sagebrush cover. Little (<5%) of the landscape was projected to recover within 100 years for low to mid quantiles, and recovery often occurred at higher elevations with cool and moist annual conditions. Conversely, 48%–78% of the landscape recovered quickly (within 25 years) for high quantiles of sagebrush cover. Our study demonstrates advantages of using dynamic reference sites when studying vegetation recovery, as well as how additional inferences obtained from quantile regression can inform management.

Wyoming↗

USGS2018

Inferring species interactions through joint mark–recapture analysis

Introduced species are frequently implicated in declines of native species. In many cases, however, evidence linking introduced species to native declines is weak. Failure to make strong inferences regarding the role of introduced species can hamper attempts to predict population viability and delay effective management responses. For many species, mark–recapture analysis is the more rigorous form of demographic analysis. However, to our knowledge, there are no mark–recapture models that allow for joint modeling of interacting species. Here, we introduce a two‐species mark–recapture population model in which the vital rates (and capture probabilities) of one species are allowed to vary in response to the abundance of the other species. We use a simulation study to explore bias and choose an approach to model selection. We then use the model to investigate species interactions between endangered humpback chub ( Gila cypha ) and introduced rainbow trout ( Oncorhynchus mykiss ) in the Colorado River between 2009 and 2016. In particular, we test hypotheses about how two environmental factors (turbidity and temperature), intraspecific density dependence, and rainbow trout abundance are related to survival, growth, and capture of juvenile humpback chub. We also project the long‐term effects of different rainbow trout abundances on adult humpback chub abundances. Our simulation study suggests this approach has minimal bias under potentially challenging circumstances (i.e., low capture probabilities) that characterized our application and that model selection using indicator variables could reliably identify the true generating model even when process error was high. When the model was applied to rainbow trout and humpback chub, we identified negative relationships between rainbow trout abundance and the survival, growth, and capture probability of juvenile humpback chub. Effects on interspecific interactions on survival and capture probability were strongly supported, whereas support for the growth effect was weaker. Environmental factors were also identified to be important and in many cases stronger than interspecific interactions, and there was still substantial unexplained variation in growth and survival rates. The general approach presented here for combining mark–recapture data for two species is applicable in many other systems and could be modified to model abundance of the invader via other modeling approaches.

Ecology↗

USGS2014

Book review: Spatial capture-recapture

Understanding how animals use space is a vital aspect of conservation planning and wildlife management. Technological developments (e.g., increased computer power and desktop geographic information system [GIS] applications) are bringing the ability to analyze spatial data sets to the individual biologist. Therefore, it is not surprising that methodologies have been developed to incorporate space into capture-recapture models, which are some of the most fundamental models in the field of wildlife ecology. Spatial Capture-Recapture (hereafter SCR) is a timely and informative contribution that summarizes the history and motivation behind SCR models, in addition to providing details of the methodological framework that allows the reader to develop and customize SCR models to address their own ecological questions. Review info: Spatial Capture-Recapture. By J. Andrew Royle, Richard B. Chandler, Rahel Sollmann, and Beth Gardner, 2014. ISBN: 978-0124059399, 577 pp.

Journal of Wildlife Management↗