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At least 757 records · Page 42Linked to original sources
USGS2023

Movement beyond the mean: decoupling sources of individual variation in brook trout movement across seasons

Movement is an important eco-evolutionary process that can shape population and ecosystem structure and function. Accordingly, a firm understanding of species movement ecology is often foundational to effective management and conservation. However, despite movement being an inherently individual-level behavior, there remains a tendency to describe dispersal and migration patterns using simple population-level processes and effects. Overlooking within- and among-individual variation in movement risks incomplete understanding of the intrinsic and extrinsic factors that govern dispersal dynamics and could potentially result in inadequate management of critical behavioral phenotypes. In this study, we monitored movement of over 100 brook trout ( Salvelinus fontinalis ) and quantified the effect of individual-level traits, season, and their interactions to better understand factors that influence vagility. Our results suggest that movement was higher in fall than in summer, particularly for fish in poor condition. But we found no significant main effects for sex, providing no evidence for sex-biased dispersal. To better understand sources of individual variation, we also allowed for sex- and season-specific residual standard deviations. In doing so, we found that, on average, movement was more variable in fall compared to summer, and that females were more variable than males in vagility. Taken together, these results demonstrate how intrinsic, individual-level traits can interact with abiotic environmental conditions to determine movement. They also highlight the potential for simple explanations of movement ecology to overlook important traits that may help predict individual-level behaviors.

Pennsylvania↗
USGS2019

Genetic tagging in the Anthropocene: Scaling ecology from alleles to ecosystems

The Anthropocene is an era of marked human impact on the world. Quantifying these impacts 51 has become central to understanding the dynamics of coupled human-natural systems, resource52 dependent livelihoods, and biodiversity conservation. Ecologists are facing growing pressure to 53 quantify the size, distribution, and trajectory of wild populations in a cost-effective and socially54 acceptable manner. Genetic tagging, combined with modern computational and genetic analyses, 55 is an under-utilized tool to meet this demand, especially for wide-ranging, elusive, sensitive, and 56 low-density species. Genetic tagging studies are now revealing unprecedented insight into the 57 mechanisms that control the density, trajectory, connectivity and human-wildlife conflict for 58 populations over vast spatial scales. Here we outline the application of, and ecological inferences 59 from, new analytical techniques applied to genetically-tagged individuals, contrast this approach 60 with conventional methods, and describe how genetic tagging can be better applied to address 61 outstanding questions in ecology. We provide example analyses using a long-term genetic 62 tagging dataset of grizzly bears in the Canadian Rockies. The genetic tagging toolbox is a 63 powerful and overlooked ensemble that ecologists and conservation biologists can leverage to 64 generate evidence and meet the challenges of the Anthropocene.

Ecological Applications↗
USGS2024

Genetic analysis of harvest samples reveals population structure in a highly mobile generalist carnivore

Delineating wildlife population boundaries is important for effective population monitoring and management. The bobcat ( Lynx rufus ) is a highly mobile generalist carnivore that is ecologically and economically important. We sampled 1225 bobcats harvested in South Dakota, USA (2014–2019), of which 878 were retained to assess genetic diversity and infer population genetic structure using 17 microsatellite loci. We assigned individuals to genetic clusters ( K ) using spatial and nonspatial Bayesian clustering algorithms and quantified differentiation ( F ST and GST″ ) among clusters. We found support for population genetic structure at K = 2 and K = 4, with pairwise F ST and GST″ values indicating weak to moderate differentiation, respectively, among clusters. For K = 2, eastern and western clusters aligned closely with historical bobcat management units and were consistent with a longitudinal suture zone for bobcats previously identified in the Great Plains. We did not observe patterns of population genetic structure aligning with major rivers or highways. Genetic divergence observed at K = 4 aligned roughly with ecoregion breaks and may be associated with environmental gradients, but additional sampling with more precise locational data may be necessary to validate these patterns. Our findings reveal that cryptic population structure may occur in highly mobile and broadly distributed generalist carnivores, highlighting the importance of considering population structure when establishing population monitoring programs or harvest regulations. Our study further demonstrates that for elusive furbearers, harvest can provide an efficient, broad-scale sampling approach for genetic population assessments.

South Dakota↗
USGS2022

Modeling spatiotemporal abundance and movement dynamics using an integrated spatial capture–recapture movement model

Animal movement is a fundamental ecological process affecting the survival and reproduction of individuals, the structure of populations, and the dynamics of communities. Methods to quantify animal movement and spatiotemporal abundances, however, are generally separate and therefore omit linkages between individual-level and population-level processes. We describe an integrated spatial capture–recapture (SCR) movement model to jointly estimate (1) the number and distribution of individuals in a defined spatial region and (2) movement of those individuals through time. We applied our model to a study of polar bears ( Ursus maritimus ) in a 28,125 km 2 survey area of the eastern Chukchi Sea, USA in 2015 that incorporated capture–recapture and telemetry data. In simulation studies, the model provided unbiased estimates of movement, abundance, and detection parameters using a bivariate normal random walk and correlated random walk movement process. Our case study provided detailed evidence of directional movement persistence for both male and female bears, where individuals regularly traversed areas larger than the survey area during the 36-day study period. Scaling from individual- to population-level inferences, we found that densities varied from <0.75 bears/625 km 2 grid cell/day in nearshore cells to 1.6–2.5 bears/grid cell/day for cells surrounded by sea ice. Daily abundance estimates ranged from 53 to 69 bears, with no trend across days. The cumulative number of unique bears that used the survey area increased through time due to movements into and out of the area, resulting in an estimated 171 individuals using the survey area during the study (95% credible interval 124–250). Abundance estimates were similar to a previous multiyear integrated population model using capture–recapture and telemetry data (2008–2016; Regehr et al., Scientific Reports 8:16780, 2018). Overall, the SCR–movement model successfully quantified both individual- and population-level space use, including the effects of landscape characteristics on movement, abundance, and detection, while linking the movement and abundance processes to directly estimate density within a prescribed spatial region and temporal period. Integrated SCR–movement models provide a generalizable approach to incorporate greater movement realism into population dynamics and link movement to emergent properties including spatiotemporal densities and abundances.

eastern Chukchi Sea↗
USGS2024

Identifying new invasive plants in the face of climate change: A focus on sleeper species

Sleeper populations are established populations of introduced species whose population growth is limited by one or more abiotic or biotic conditions. Sleeper populations pose an invasion risk if a change in those limiting conditions, such as climate change, enables population growth and invasion. With thousands of established introduced species, it is critical that we identify and prioritize potential sleepers. Here, we identified introduced plants established in the northeastern United States with high impacts and the potential to expand with climate change. Of 1795 introduced plants established in one or more northeastern states, we focused on 118 taxa regulated by one or more states outside the Northeast plus 61 taxa recorded as invasive globally and under consideration for regulation in the Northeast. We used the environmental impact classification for alien taxa framework to quantify negative ecological and socioeconomic impacts reported in the scientific literature for these 169 taxa. We compared mean minimum winter temperature and annual precipitation where the species were abundant with current and future climate in the Northeast to evaluate whether climate change could increase risk. We identified 49 plants with ecological impacts linked to loss of native diversity and 94 plants with socioeconomic impacts. 81 species showed an increase in climatic suitability for abundant populations with climate change. Using ecological impact, increased climate suitability, and presence in fewer than 20 Northeastern counties, we highlight 18 species as high priorities for potential management in the Northeast. This approach can inform climate-smart, proactive management of sleeper populations before they become invasive.

Biological Invasions↗
USGS2017

A method to assess the population-level consequences of wind energy facilities on bird and bat species

For this study, a methodology was developed for assessing impacts of wind energy generation on populations of birds and bats at regional to national scales. The approach combines existing methods in applied ecology for prioritizing species in terms of their potential risk from wind energy facilities and estimating impacts of fatalities on population status and trend caused by collisions with wind energy infrastructure. Methods include a qualitative prioritization approach, demographic models, and potential biological removal. The approach can be used to prioritize species in need of more thorough study as well as to identify species with minimal risk. However, the components of this methodology require simplifying assumptions and the data required may be unavailable or of poor quality for some species. These issues should be carefully considered before using the methodology. The approach will increase in value as more data become available and will broaden the understanding of anthropogenic sources of mortality on bird and bat populations.

Book chapter↗
USGS2018

California mallards: a review

Mallards (Anas platyrhynchos) are the most abundant breeding waterfowl species in California and are important to waterfowl hunters in the state. California is unique among major North American wintering waterfowl areas, in that most mallards harvested in California are also produced in California, meaning that California must provide both high quality wintering and breeding habitats for mallard populations to remain stable. California’s breeding and wintering mallard population estimates have generally declined since the mid-1990s. Herein, we synthesized existing information on the ecology of breeding mallards in California and summarize key demographic rates. In general, demographic estimates differed substantially from other mallard populations in North America, highlighting the importance of separate management of western mallard populations. We suggest long-term research and monitoring activities to help improve management.

California Fish and Game↗
USGS2016

Estimating abundance: Chapter 27

This chapter provides a non-technical overview of ‘closed population capture–recapture’ models, a class of well-established models that are widely applied in ecology, such as removal sampling, covariate models, and distance sampling. These methods are regularly adopted for studies of reptiles, in order to estimate abundance from counts of marked individuals while accounting for imperfect detection. Thus, the chapter describes some classic closed population models for estimating abundance, with considerations for some recent extensions that provide a spatial context for the estimation of abundance, and therefore density. Finally, the chapter suggests some software for use in data analysis, such as the Windows-based program MARK, and provides an example of estimating abundance and density of reptiles using an artificial cover object survey of Slow Worms ( Anguis fragilis ).

Book chapter↗
USGS2022

Natural and anthropogenic landscape factors shape functional connectivity of an ecological specialist in urban Southern California

Identifying how natural (i.e., unaltered by human activity) and anthropogenic landscape variables influence contemporary functional connectivity in terrestrial organisms can elucidate the genetic consequences of environmental change. We examine population genetic structure and functional connectivity among populations of a declining species, the Blainville's horned lizard ( Phrynosoma blainvillii ), in the urbanized landscape of the Greater Los Angeles Area in Southern California, USA. Using single nucleotide polymorphism data, we assessed genetic structure among populations occurring at the interface of two abutting evolutionary lineages, and at a fine scale among habitat fragments within the heavily urbanized area. Based on the ecology of P. blainvillii , we predicted which environmental variables influence population structure and gene flow and used gravity models to distinguish among hypotheses to best explain population connectivity. Our results show evidence of admixture between two evolutionary lineages and strong population genetic structure across small habitat fragments. We also show that topography, microclimate, and soil and vegetation types are important predictors of functional connectivity, and that anthropogenic disturbance, including recent fire history and urban development, are key factors impacting contemporary population dynamics. Examining how natural and anthropogenic sources of landscape variation affect contemporary population genetics is critical to understanding how to best manage sensitive species in a rapidly changing landscape.

California↗
USGS2021

From satellites to frogs: Quantifying ecohydrological change, drought mitigation, and population demography in desert meadows

Increasing frequency and severity of droughts have motivated natural resource managers to mitigate harmful ecological and hydrological effects of drought, but drought mitigation is an emerging science and evaluating its effectiveness is difficult. We examined ecohydrological responses of drought mitigation actions aimed at conserving populations of the Columbia spotted frog ( Rana luteiventris ) in a semi-arid valley in Nevada, USA. Abundance of this rare frog had declined precipitously after multiple droughts. Mitigation included excavating ponds to increase available surface water and installing earthen dams to raise water tables. We assessed responses of riparian vegetation to mitigation using a 30-year time series of satellite-derived Normalized Difference Vegetation Index (NDVI) and gridded weather data. We then analyzed a 23-year mark-recapture dataset to evaluate the effects of drought mitigation and NDVI on the probability of frog survival and rates of recruitment. After accounting for interannual precipitation variability, we found that NDVI increased significantly from before to after drought mitigation, suggesting that mitigation influenced the hydrology and vegetation of the meadows. Frog survival increased with NDVI, but mitigation had a stronger effect than NDVI suggesting that excavated mitigation ponds were particularly important for frog survival during drought. In contrast, frog recruitment was associated with NDVI more than mitigation, but only in meadows where NDVI was dependent on precipitation. At meadows with available groundwater, recruitment was associated with mitigation ponds. These findings suggest that mitigation ponds are critical for juvenile frogs to recruit into the adult population, but recruitment can also be increased by raising water tables in meadows lacking groundwater sources. Lagged recruitment (i.e., effects on larvae and juveniles) was negatively associated with NDVI. This study illustrates the ecohydrological complexity of drought mitigation and demonstrates novel ways to assess the effectiveness of drought mitigation using time series of readily available satellite imagery and organismal data.

Nevada↗
USGS2012

Assessing the vulnerability of human and biological communities to changing ecosystem services using a GIS-based multi-criteria decision support tool

In this paper we describe an application of a GIS-based multi-criteria decision support web tool that models and evaluates relative changes in ecosystem services to policy and land management decisions. The Santa Cruz Watershed Ecosystem Portfolio (SCWEPM) was designed to provide credible forecasts of responses to ecosystem drivers and stressors and to illustrate the role of land use decisions on spatial and temporal distributions of ecosystem services within a binational (U.S. and Mexico) watershed. We present two SCWEPM sub-models that when analyzed together address bidirectional relationships between social and ecological vulnerability and ecosystem services. The first model employs the Modified Socio-Environmental Vulnerability Index (M-SEVI), which assesses community vulnerability using information from U.S. and Mexico censuses on education, access to resources, migratory status, housing situation, and number of dependents. The second, relating land cover change to biodiversity (provisioning services), models changes in the distribution of terrestrial vertebrate habitat based on multitemporal vegetation and land cover maps, wildlife habitat relationships, and changes in land use/land cover patterns. When assessed concurrently, the models exposed some unexpected relationships between vulnerable communities and ecosystem services provisioning. For instance, the most species-rich habitat type in the watershed, Desert Riparian Forest, increased over time in areas occupied by the most vulnerable populations and declined in areas with less vulnerable populations. This type of information can be used to identify ecological conservation and restoration targets that enhance the livelihoods of people in vulnerable communities and promote biodiversity and ecosystem health.

Santa Cruz watershed↗
USGS2009

Population and habitat restoration - Preamble to section 5

Diadromous fish populations are particularly difficult to understand, model and manage because they traverse multiple habitats that present not only environmental, ecological, reproductive, and physiological challenges, but also frequently convey them across multiple management jurisdictions. Our knowledge of population-level effects is also dependent on the quality and extent of biological, population, and demographic data. For some species, such as Pacific salmon, populations are routinely monitored, life cycles are fairly well understood, and population trends are, in general, well documented. However, for other species such as anguillid eels, our understanding of life history is incomplete, population-level data are meager, and the trends in abundance are less clear.

Book chapter↗
USGS2026

Optimizing camera-trap survey designs for multi-species density estimation using spatial capture–recapture models

Conservation efforts are increasingly required to move beyond single-species perspectives and towards community-level inferences. Obtaining reliable multispecies population size estimates poses practical challenges as analytical tools and design recommendations are primarily focused on single species. Density estimation using spatial capture–recapture methods requires deploying detectors (e.g. camera-traps) with spacing proportional to the space use of the focal species. Given that the design itself is species-specific, sampling can be inefficient for species with larger ranges than the focal species due to restricted spatial coverage and insufficient for species with smaller ranges because fewer recaptures are generated. To address this practical issue, we developed a two-stage optimization approach to generate camera-trap survey designs that are appropriate for estimating density of a suite of individually identifiable species that vary in home range sizes. Our approach applies an algorithm to first optimize placement of a subset of detectors for large and vagile species based on maximizing spatial coverage, followed by a second optimization for the remaining cameras based on maximizing spatial recaptures for smaller and less mobile species. We empirically tested our approach using six individually identifiable carnivore species with varying home range sizes in the Munywana Conservancy, South Africa. Our design included 60 camera locations optimized for leopards ( Panthera pardus ) and 40 cameras optimized for small-bodied, less-mobile carnivores. Our design optimization procedure generated designs characterized by a distribution of inter-trap distances, based on ecological parameters, and resulted in plausible density estimates for all species. The two-stage approach resulted in moderate precision gains for larger ranging species and, importantly, substantial gains for smaller ranging species. Simulations demonstrated improved precision of spatially explicit capture–recapture (SCR) parameter estimates for all species compared to standard grid-based designs, driven not solely by increased sampling but also by the optimized spatial configuration. Synthesis and applications . We developed and tested a new camera-trap survey design method for estimating population densities for multiple co-occurring species with differing spatial ecologies. By streamlining multispecies population monitoring, our approach reduces costs associated with species-specific programmes and broadens opportunities for community ecology and conservation research based on explicit demographic parameters.

Munyawana Conservancy↗
USGS2012

Serologic and molecular evidence for testudinid herpesvirus 2 infection in wild Agassiz’s desert tortoise, Gopherus agassizii

Following field observations of wild Agassiz’s desert tortoises ( Gopherus agassizii ) with oral lesions similar to those seen in captive tortoises with herpesvirus infection, we measured the prevalence of antibodies to Testudinid herpesvirus (TeHV) 3 in wild populations of desert tortoises in California. The survey revealed 30.9% antibody prevalence. In 2009 and 2010, two wild adult male desert tortoises, with gross lesions consistent with trauma and puncture wounds, respectively, were necropsied. Tortoise 1 was from the central Mojave Desert and tortoise 2 was from the northeastern Mojave Desert. We extracted DNA from the tongue of tortoise 1 and from the tongue and nasal mucosa of tortoise 2. Sequencing of polymerase chain reaction products of the herpesviral DNA-dependent DNA polymerase gene and the UL39 gene respectively showed 100% nucleotide identity with TeHV2, which was previously detected in an ill captive desert tortoise in California. Although several cases of herpesvirus infection have been described in captive desert tortoises, our findings represent the first conclusive molecular evidence of TeHV2 infection in wild desert tortoises. The serologic findings support cross-reactivity between TeHV2 and TeHV3. Further studies to determine the ecology, prevalence, and clinical significance of this virus in tortoise populations are needed.

California;Nevada↗
USGS2014

Nesting ecology and nest survival of lesser prairie-chickens on the Southern High Plains of Texas

The decline in population and range of lesser prairie-chickens ( Tympanuchus pallidicinctus ) throughout the central and southern Great Plains has raised concerns considering their candidate status under the United States Endangered Species Act. Baseline ecological data for lesser prairie-chickens are limited, especially for the shinnery oak-grassland communities of Texas. This information is imperative because lesser prairie-chickens in shinnery oak grasslands occur at the extreme southwestern edge of their distribution. This geographic region is characterized by hot, arid climates, less fragmentation, and less anthropogenic development than within the remaining core distribution of the species. Thus, large expanses of open rangeland with less anthropogenic development and a climate that is classified as extreme for ground nesting birds may subsequently influence nest ecology, nest survival, and nest site selection differently compared to the rest of the distribution of the species. We investigated the nesting ecology of 50 radio-tagged lesser prairie-chicken hens from 2008 to 2011 in the shinnery oak-grassland communities in west Texas and found a substantial amount of inter-annual variation in incubation start date and percent of females incubating nests. Prairie-chickens were less likely to nest near unimproved roads and utility poles and in areas with more bare ground and litter. In contrast, hens selected areas dominated by grasses and shrubs and close to stock tanks to nest. Candidate models including visual obstruction best explained daily nest survival; a 5% increase in visual obstruction improved nest survival probability by 10%. The model-averaged probability of a nest surviving the incubation period was 0.43 (SE = 0.006; 95% CI: 0.23, 0.56). Our findings indicate that lesser prairie-chicken reproduction during our study period was dynamic and was correlated with seasonal weather patterns that ultimately promoted greater grass growth earlier in the nesting season that provided visual obstruction from predators.

Texas↗
USGS2017

Integrating count and detection–nondetection data to model population dynamics

There is increasing need for methods that integrate multiple data types into a single analytical framework as the spatial and temporal scale of ecological research expands. Current work on this topic primarily focuses on combining capture–recapture data from marked individuals with other data types into integrated population models. Yet, studies of species distributions and trends often rely on data from unmarked individuals across broad scales where local abundance and environmental variables may vary. We present a modeling framework for integrating detection–nondetection and count data into a single analysis to estimate population dynamics, abundance, and individual detection probabilities during sampling. Our dynamic population model assumes that site-specific abundance can change over time according to survival of individuals and gains through reproduction and immigration. The observation process for each data type is modeled by assuming that every individual present at a site has an equal probability of being detected during sampling processes. We examine our modeling approach through a series of simulations illustrating the relative value of count vs. detection–nondetection data under a variety of parameter values and survey configurations. We also provide an empirical example of the model by combining long-term detection–nondetection data (1995–2014) with newly collected count data (2015–2016) from a growing population of Barred Owl ( Strix varia ) in the Pacific Northwest to examine the factors influencing population abundance over time. Our model provides a foundation for incorporating unmarked data within a single framework, even in cases where sampling processes yield different detection probabilities. This approach will be useful for survey design and to researchers interested in incorporating historical or citizen science data into analyses focused on understanding how demographic rates drive population abundance.

Ecology↗
USGS1995

Population modeling and its role in toxicological studies

A model could be defined as any abstraction from reality that is used to provide some insight into the real system. In this discussion, we will use a more specific definition that a model is a set of rules or assumptions, expressed as mathematical equations, that describe how animals survive and reproduce, including the external factors that affect these characteristics. A model simplifies a system, retaining essential components while eliminating parts that are not of interest. ecology has a rich history of using models to gain insight into populations, often borrowing both model structures and analysis methods from demographers and engineers. Much of the development of the models has been a consequence of mathematicians and physicists seeing simple analogies between their models and patterns in natural systems. Consequently, one major application of ecological modeling has been to emphasize the analysis of dynamics of often complex models to provide insight into theoretical aspects of ecology. 1

Book chapter↗
USGS2025

A system dynamics model to understand the integrated ecological and human dimension aspects of wildlife health and disease management

Chronic wasting disease (CWD) presents an ongoing challenge for the management of deer populations and sustaining harvest opportunities across North America. Existing disease models often fail to fully capture the complex interplay between disease dynamics, host ecology, and socio-economic factors. We developed a comprehensive system dynamics (SD) model that integrates demographic, epidemiological, ecological, and socio-economic processes within a single model to more fully characterize the complex network of causal feedbacks throughout the system. The model was calibrated using a Bayesian approach that incorporates prior knowledge to generate biologically interpretable outcomes, even with sparse data. For estimating the joint posterior distribution of model parameters, we leveraged time series of deer abundance, harvest composition, genetic profiles, CWD surveillance, and hunter demographics and behavior. Model outputs reproduced key system behaviors, including observed CWD prevalence trends, deer population dynamics, and hunter license purchasing patterns. Model predictions were most sensitive to parameters governing initial deer population size and recruitment. While model predictions generally aligned with observed data, discrepancies in early CWD detection and overestimation of the reactivation of long-inactive hunters reflect data limitations and modeling challenges. Key results suggest that indirect transmission is necessary to explain observed prevalence, that transmission is moderately density-dependent, and that observed population-level genetic shifts driven by CWD may play a role in transmission and progression. The SD modelling approach enabled estimation of difficult-to-measure parameters and identified potential leverage points for management—such as prioritizing increasing participation in antlerless harvest of existing hunters over the recruitment of new hunters. This integrated modeling approach offers a flexible foundation for adaptive wildlife disease management and emphasizes the value of unifying biological and human dimension processes to better inform effective, evidence-based policy.

BioRxiv↗