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At least 37 records · Page 2Linked to original sources
USGS2024

Predicting the response of a long-distance migrant to changing environmental conditions in winter

Access to high-quality food is critical for long-distance migrants to provide energy for migration and arrival at breeding grounds in good condition. We studied effects of changing abundance and availability of a marine food, common eelgrass ( Zostera marina L.), on an arctic-breeding, migratory goose, black brant ( Brant bernicla nigricans Lawrence 1846), at a key non-breeding site, Bahía San Quintín, Mexico. Eelgrass, the primary food of brant, is consumed when exposed by the tide or within reach from the water's surface. Using an individual-based model, we predicted effects of observed changes (1991–2013) in parameters influencing food abundance and availability: eelgrass biomass (abundance), eelgrass shoot length (availability, as longer shoots more within reach), brant population size (availability, as competition greater with more birds), and sea level (availability, as less food within reach when sea level higher). The model predicted that the ability to gain enough energy to migrate was most strongly influenced by eelgrass biomass (threshold January biomass for migration = 60 g m −2 dry mass). Conversely, annual variation in population size (except for 1998), was relatively low, and variation in eelgrass shoot length and sea level were not strongly related to ability to migrate. We used observed data on brant body mass at Bahía San Quintín and annual survival to test for effects of eelgrass biomass in the real system. The lowest observed values of body mass and survival were in years when biomass was below 60 g m −2 , although in some years of low biomass body mass and/or survival was higher. This suggests that the real birds may have some capacity to compensate to meet their energy demands when eelgrass biomass is low. We discuss consequences for brant population trends and conservation.

Baja California↗
USGS2026

Survey protocols drive heterogeneity in occupancy estimates that cannot be standardized using post hoc analyses

Site occupancy models are widely used to estimate species distributions from presence–nondetection data, yet for mobile animals, the true proportion of sites occupied varies in time. Thus, true occupancy and estimates generated from different protocols are affected by temporal characteristics of survey design. Here we tested whether we could standardize occupancy estimates across different sampling protocols with a post hoc statistical test. Using an individual-based movement model of Wood Thrush ( Hylocichla mustelina ), we simulated point count surveys across 3000 populations under 90 spatially and temporally variable sampling protocols. For each simulation, we fit a standard occupancy model, then used minute-level detections to truncate surveys and generate occupancy estimates across increasing survey lengths. We fit asymptotic models to these series to estimate intercepts (instantaneous occupancy) and asymptotes (longer-term occupancy) and evaluated how well they approximated true instantaneous, daily and seasonal occupancy. We were unable to recover instantaneous or seasonal occupancy from any approach. Both standard occupancy models and asymptotic regression (the top-performing asymptotic model) most closely approximated daily occupancy; although asymptotic regression produced slightly less biased estimates, it showed substantially greater variability, resulting in greater overall error. Our results show that post hoc analytical approaches cannot, at present, reliably standardize occupancy estimates across heterogeneous survey designs. Instead, ensuring biologically informative and comparable estimates will depend on standardized survey protocols. Practical implication : Monitoring programs using presence–nondetection data should prioritize consistent survey protocols when estimating occupancy for mobile species, with a focus on daily occupancy as the most attainable and useful metric. Although the highest accuracy and precision were achieved under the most intensive survey protocols, for point counts of Wood Thrush and similar species, four consecutive 15–20 min surveys provide near-optimal precision and can be completed in a single visit, making them well suited for estimating relative occupancy under logistical constraints. Three 20-min surveys spaced ~24 h apart closely approximate daily occupancy while maintaining reasonable precision. Developing similar protocols for other species and survey methods will be critical to ensuring comparable occupancy estimates across space and time.

Ecological Solutions and Evidence↗
USGS2022

Predation thresholds for reintroduction of native avifauna following suppression of invasive brown treesnakes on Guam

The brown treesnake (BTS) ( Boiga irregularis ) invasion on Guåhan (in English, Guam) led to the extirpation of nearly all native forest birds. In recent years, methods have been developed to reduce BTS abundance on a landscape scale. To help assess the prospects for the successful reintroduction of native birds to Guåhan following BTS suppression, we modeled bird population persistence based on their life history characteristics and relative sensitivity to BTS predation. We constructed individual-based models and simulated BTS predation in hypothetical founding populations for each of seven candidate bird species. We represented BTS predation risk in two steps: risk of being encountered and risk of mortality if encountered. We link encounter risk from the bird's perspective to snake contact rates at camera traps with live animal lures, the most direct practical means of estimating BTS predation risk. Our simulations support the well-documented fact that Guåhan's birds cannot persist with an uncontrolled population of BTS but do indicate that bird persistence in Guåhan's forests is possible with suppression short of total eradication. We estimate threshold BTS contact rates would need to be below 0.0002–0.0006 snake contacts per bird per night for these birds to persist on the landscape, which translates to an annual encounter probability of 0.07–0.20. We simulated the effects of snake-proof nest boxes for Sihek ( Todiramphus cinnamominus ) and Såli ( Aplonis opaca ), but the benefits were small relative to the overall variation in contact rate thresholds among species. This variation among focal bird species in sustainable predation levels can be used to prioritize species for reintroduction in a BTS-suppressed landscape, but variation among these species is narrow relative to the required reduction from current BTS levels, which may be four orders of magnitude higher (>0.18). Our modeling indicates that the required predation thresholds may need to be lower than have yet been demonstrated with current BTS management. Our predation threshold metric provides an important management tool to help estimate target BTS suppression levels that can be used to determine when bird reintroduction campaigns might begin and serves as a model for other systems to match predator control with reintroduction efforts.

Ecological Applications↗
USGS2022

Evaluating risks associated with capture and handling of mule deer for individual-based, long-term research

Capture and handling techniques for individual-based, long-term research that tracks the life history of animals by recapturing the same individuals for several years has vastly improved study inferences and our understanding of animal ecology. Yet there are corresponding risks to study animals associated with physical trauma or capture myopathy that can occur during or following capture events. Rarely has empirical evidence existed to guide decisions associated with understanding the magnitude of capture-related risks, how to reduce these risks when possible, and implications for mortality censoring and survival estimates. We used data collected from 2,399 capture events of mule deer ( Odocoileus hemionus ) via helicopter net-gunning to compare daily survival probabilities within a 10-week period centered on a capture event and evaluated how animal age, nutritional condition (body fat), and various handling methods influenced survival before, during, and following a capture event. Direct mortality resulting from capture efforts was 1.59%. Mean daily survival was 0.9993 ± 0.0001 (SE) during the 5-week pre-capture window, was depressed the day of capture at 0.9841 ± 0.0004, and rebounded to 0.9990 ± 0.0008 during the 5-week post-capture window. Neither capture nor handling had a detectable effect on post-capture survival, including handling time ( x̄ = 13.30 ± 1.87 min), capture time of year (i.e., Dec or Mar), tooth extraction, and the number of times an animal had been recaptured (2–17 times). Although mortality rate was slightly elevated during capture (resulting from physical trauma associated with capture), age and nutritional condition did not influence the probability of mortality during a capture event. Following a capture event, nutritional condition influenced survival; however, that relationship was consistent with expected effects of nutritional condition on winter survival and independent of capture and handling. Overall survival rates 5 weeks before capture and 5 weeks after capture were not different. A specified window of time with depressed survival following capture and handling was not evident, which contradicts the implementation of a predetermined window often used by researchers and managers for censoring mortalities that occur after capture. Previous notions that censorship of all mortality data in the 2 weeks following capture is unwarranted and risks removal of meaningful data. With previous evidence guiding our protocols for capture (e.g., reduced chase time) and handling (e.g., temperature mitigation), low direct mortality and almost undetectable indirect mortality post capture reinforces the efficacy of helicopter net-gunning for capture and recapture of mule deer in long-term, individual-based studies.

Wyoming↗
USGS2022

Spatial models can improve the experimental design of field-based transplant gardens by preventing bias due to neighborhood crowding

Field-based transplant gardens, including common and reciprocal garden experiments, are a powerful tool for studying genetic variation and gene-by-environment interactions. These experiments assume that individuals within the garden represent independent replicates growing in a homogenous environment. Plant neighborhood interactions are pervasive across plant populations and could violate assumptions of transplant garden experiments. We demonstrate how spatially explicit models for plant–plant interactions can provide novel insights on genotypes' performance in field-transplant garden designs. We used individual-based models, based on data from a sagebrush ( Artemisia spp.) common garden, to simulate the impact of spatial plant–plant interactions on between-group differences in plant growth. We found that planting densities within the range of those used in many common gardens can bias experimental outcomes. Our results demonstrate that higher planting densities can lead to inflated group differences and may confound genotypes' competitive ability and genetically underpinned variation. Synthesis. We propose that spatially explicit models can help avoid biased results by informing the design and analysis of field-based transplant garden experiments. Alternately, including neighborhood effects in post hoc analyses of transplant garden experiments is likely to provide novel insights into the roles of biotic factors and density dependence in genetic differentiation.

Ecology and Evolution↗
USGS2017

Altitudinal migration and the future of an iconic Hawaiian honeycreeper in response to climate change and management

Altitudinal movement by tropical birds to track seasonally variable resources can move them from protected areas to areas of increased vulnerability. In Hawaiʻi, historical reports suggest that many Hawaiian honeycreepers such as the ‘I‘iwi ( Drepanis coccinea ) once undertook seasonal migrations, but the existence of such movements today is unclear. Because Hawaiian honeycreepers are highly susceptible to avian malaria, currently minimal in high-elevation forests, understanding the degree to which honeycreepers visit lower elevation forests may be critical to predict the current impact of malaria on population dynamics and how susceptible bird populations may respond to climate change and mitigation scenarios. Using radio telemetry data, we demonstrate for the first time that a large fraction of breeding adult and juvenile ‘I‘iwi originating from an upper-elevation (1,920 m) population at Hakalau Forest National Wildlife Refuge exhibit post-breeding movements well below the upper elevational limit for mosquitoes. Bloom data suggest seasonal variation in floral resources is the primary driver of seasonal movement for ‘I‘iwi. To understand the demographic implications of such movement, we developed a spatial individual-based model calibrated using previously published and original data. ʻI‘iwi dynamics were simulated backward in time, to estimate population levels in the absence of avian malaria, and forward in time, to assess the impact of climate warming as well as two potential mitigation actions. Even in disease-free ‘refuge’ populations, we found that breeding densities failed to reach the estimated carrying capacity, suggesting the existence of a seasonal “migration load” as a result of travel to disease-prevalent areas. We predict that ‘I‘iwi may be on the verge of extinction in 2100, with the total number of pairs reaching only ~ 0.2–12.3% of the estimated pre-malaria density, based on an optimistic climate change scenario. The probability of extinction of ‘I‘iwi populations, as measured by population estimates for 2100, is strongly related to their estimated migration propensity. Long-term conservation strategies likely will require a multi-pronged response including a reduction of malaria threats, habitat restoration and continued landscape-level access to seasonally variable nectar resources.

Ecological Monographs↗
USGS2024

Sources of bias in applying close-kin mark–recapture to terrestrial game species with different life histories

Close-kin mark–recapture (CKMR) is a method analogous to traditional mark–recapture but without requiring recapture of individuals. Instead, multilocus genotypes (genetic marks) are used to identify related individuals in one or more sampling occasions, which enables the opportunistic use of samples from harvested wildlife. To apply the method accurately, it is important to build appropriate CKMR models that do not violate assumptions linked to the species’ and population's biology and sampling methods. In this study, we evaluated the implications of fitting overly simplistic CKMR models to populations with complex reproductive success dynamics or selective sampling. We used forward-in-time, individual-based simulations to evaluate the accuracy and precision of CKMR abundance and survival estimates in species with different longevities, mating systems, and sampling strategies. Simulated populations approximated a range of life histories among game species of North America with lethal sampling to evaluate the potential of using harvested samples to estimate population size. Our simulations show that CKMR can yield nontrivial biases in both survival and abundance estimates, unless influential life history traits and selective sampling are explicitly accounted for in the modeling framework. The number of kin pairs observed in the sample, in combination with the type of kinship used in the model (parent–offspring pairs and/or half-sibling pairs), can affect the precision and/or accuracy of the estimates. CKMR is a promising method that will likely see an increasing number of applications in the field as costs of genetic analysis continue to decline. Our work highlights the importance of applying population-specific CKMR models that consider relevant demographic parameters, individual covariates, and the protocol through which individuals were sampled.

Ecology↗
USGS2021

Stock composition of the historical New York Bight Atlantic sturgeon (Acipenser oxyrinchus oxyrinchus) intercept fishery revealed through microsatellite analysis of archived spines

A targeted commercial fishery for Atlantic Sturgeon Acipenser oxyrinchus oxyrinchus once operated in the New York Bight, where it was assumed that most harvested Atlantic Sturgeon were natal to the Hudson River population. However, more recent evidence suggests that the fishery may have been targeting a mixed-stock aggregation, in which case harvested Atlantic Sturgeon could have been comprised of individuals from multiple populations throughout the species’ range. Although there is now a moratorium on Atlantic Sturgeon harvest in the New York Bight, modern molecular approaches provide an opportunity to use archived tissues to perform a retrospective mixed-stock analysis on the fishery. Genomic DNA extracted from archived fin spines from 80 Atlantic Sturgeon collected nearly 30 years ago suggests that the fishery primarily harvested individuals from the Hudson River population. However, based on individual-based assignment tests, our results indicate that the fishery also harvested individuals from at least eight other populations located throughout the species’ range. This study highlights how archival hard parts that were previously used for age and growth analyses can be employed for retrospective genetic analyses. Further, because the New York Bight harbors relatively high concentrations of Atlantic Sturgeon, the study shows how localized management decisions can influence Atlantic Sturgeon conservation at rangewide scales. When integrated with more recent knowledge of species ecology, these analyses can be used to evaluate the efficacy of previous management strategies and understand the effects of historical processes on contemporary demography.

New York↗
USGS2017

Using dynamic population simulations to extend resource selection analyses and prioritize habitats for conservation

Prioritizing habitats for conservation is a challenging task, particularly for species with fluctuating populations and seasonally dynamic habitat needs. Although the use of resource selection models to identify and prioritize habitat for conservation is increasingly common, their ability to characterize important long-term habitats for dynamic populations are variable. To examine how habitats might be prioritized differently if resource selection was directly and dynamically linked with population fluctuations and movement limitations among seasonal habitats, we constructed a spatially explicit individual-based model for a dramatically fluctuating population requiring temporally varying resources. Using greater sage-grouse ( Centrocercus urophasianus) in Wyoming as a case study, we used resource selection function maps to guide seasonal movement and habitat selection, but emergent population dynamics and simulated movement limitations modified long-term habitat occupancy. We compared priority habitats in RSF maps to long-term simulated habitat use. We examined the circumstances under which the explicit consideration of movement limitations, in combination with population fluctuations and trends, are likely to alter predictions of important habitats. In doing so, we assessed the future occupancy of protected areas under alternative population and habitat conditions. Habitat prioritizations based on resource selection models alone predicted high use in isolated parcels of habitat and in areas with low connectivity among seasonal habitats. In contrast, results based on more biologically-informed simulations emphasized central and connected areas near high-density populations, sometimes predicted to be low selection value. Dynamic models of habitat use can provide additional biological realism that can extend, and in some cases, contradict habitat use predictions generated from short-term or static resource selection analyses. The explicit inclusion of population dynamics and movement propensities via spatial simulation modeling frameworks may provide an informative means of predicting long-term habitat use, particularly for fluctuating populations with complex seasonal habitat needs. Importantly, our results indicate the possible need to consider habitat selection models as a starting point rather than the common end point for refining and prioritizing habitats for protection for cyclic and highly variable populations.

Wyoming↗
USGS2018

The confluences of ideas leading to, and the flow of ideas emerging from, individual-based modeling of riverine fishes

In this review article, we trace the history of events leading to the development of individual-based models (IBMs) to represent aquatic organisms in rivers and streams. As a metaphor, we present this history as a series of confluences between individual scientists (tributaries) sharing ideas. We describe contributions of these models to science and management. One iconic feature of river IBMs is the linkage between flow and the physical habitat experienced by individual animals, and the first model that focused on this linkage is briefly described. We continue by reviewing the contributions of riverine IBMs to eight broad areas of scientific inquiry. The first four areas include research to understand 1) the effects of flow regimes on fish populations, 2) species interactions (e.g., size-mediated competition and predation), 3) fish movement and habitat selection, and 4) contaminant and water quality impacts on populations. Next, we review research using IBMs 5) to guide conservation biology of imperiled taxa through population viability analysis, including research 6) to understand river fragmentation by dams and reconnection, 7) to understand genetic outcomes for riverine metapopulations, and 8) to anticipate the future effects of temperature and climate change. This rich body of literature has contributed to both theoretical insights (e.g., about animal behavior and life history) and applied insights (e.g., population-level effects of flow regimes, temperature, and the effects of hydropower and other industries that share rivers with aquatic biota). We finish by exploring promising branches that lie ahead in the braided, downstream channel that represents future river modeling research.

Ecological Modelling↗
USGS2020

The economics of territory selection

Territorial behavior is a fundamental and conspicuous behavior within numerous species, but the mechanisms driving territory selection remain uncertain. Theory and empirical precedent indicate that many animals select territories economically to satisfy resource requirements for survival and reproduction, based on benefits of food resources and costs of competition and travel. Costs of competition may vary by competitive ability, and costs of predation risk may also drive territory selection. Habitat structure, resource requirements, conspecific density, and predator distribution and abundance are likely to further influence territorial behavior. We developed a mechanistic, spatially-explicit, individual-based model to better understand how and why animals select particular territories. The model was based on optimal selection of individual patches for inclusion in a territory according to their net value, i.e., benefits (food resources) minus costs (travel, competition, predation risk). Simulations produced predictions for what may be observed empirically if such optimization drives placement and characteristics of territories. Simulations consisted of sequential, iterative selection of territories by simulated animals that interacted to defend and maintain territories. Results explain why certain patterns in space use are commonly observed, and when and why these patterns will differ from the norm. For example, more clumped or abundant food resources are predicted to result, on average, in smaller territories with more overlap. Strongly different resource requirements for individuals or groups in a population will directly affect space use and are predicted to cause different responses under identical conditions. Territories are predicted to decrease in size with increasing population density, which can enable a population’s density of territories to change at faster rates than their spatial distribution. Due to competition, less competitive territory-holders are generally predicted to have larger territories in order to accumulate sufficient resources, which could produce an ideal despotic distribution of territories. Interestingly, territory size and overlap are predicted to show a parabolic response to increases in predator densities, and territories are predicted to be larger where predators are more clumped in distribution. Our model’s predictions are consistent with many empirical observations, providing support for optimal patch selection as a mechanism for the economical territories of animals commonly observed in nature.

Ecological Modelling↗
USGS2021

Modeling structural mechanics of oyster reef self-organization including environmental constraints and community interactions

Self-organization is a process of establishing and reinforcing local structures through feedbacks between internal population dynamics and external factors. In reef-building systems, substrate is collectively engineered by individuals that also occupy it and compete for space. Reefs are constrained spatially by the physical environment, and by mortality, which reduces production but exposes substrate for recruits. Reef self-organization therefore depends on efficient balancing of production and occupancy of substrate. To examine this, we develop a three-dimensional individual-based model (IBM) of oyster reef mechanics. Shell substrate is grown by individuals as valves, accumulates at the reef level, and degrades following mortality. Single restoration events and subsequent dynamics are simulated for a case study in South Carolina (USA). Variability in model processes is included on recruitment, spatial environmental constraints, and predation, over multiple independent runs and five predator community scenarios. The main goal for this study is to summarize trends in dynamics that are robust across this uncertainty, and from these generate new hypotheses and predictions for future studies. Simulation results demonstrate three phases following restoration: initial transient dynamics with considerable shell loss, followed by growth and saturation of the live population, and then saturation of settlement habitat several years later. Over half of simulations recoup initial shell losses as populations grow, while others continue in decline. The balance between population density, substrate supporting the reef, and exposed surfaces for settlement is mediated by overall population size and size structure, presence of predators, and relative amounts of live individuals and intact dead shells. The efficiency of settlement substrate production improves through time as population size structure becomes more complex, and the population of dead valves accumulates.

Ecological Modelling↗
USGS2024

Visualizing wading bird optimal foraging decisions with aggregation behaviors using individual-based modeling

Foragers on patchy landscapes must efficiently balance time between searching for and consuming resources to meet their daily energetic requirements. Spatial aggregation foraging behaviors may improve foraging efficiency by sharing information on locations of resource hotspots. Wading birds are an example of patch foragers that form colonial aggregations during the breeding season to obtain sufficient prey energy to sustain themselves and their offspring each day. Here, we describe a spatially-explicit simulation model of wading bird optimal foraging that represents information sharing through visual cues. The overall purpose of the model is to describe how wading bird daily foraging and reproductive success may change with alternative water control management practices that determine spatial availability of prey for wading birds on the landscape, throughout their breeding seasons. Wading birds are simulated as individuals that operate independently, sampling and selecting among patches based on a prey density tolerance threshold, but also use information from other birds to inform their selection decisions. Foraging success is evaluated against the fundamental objectives of (a) fulfilling daily energetic demands and (b) minimizing predation exposure, by tracking individual daily energetic intake and time spent foraging. In this way, the model approximates population level dynamics of wading bird aggregations that emerge through collective decision making of birds simulated at the lower individual level. Key results of this study suggest that aggregation behaviors may improve population-level foraging success rates, and the optimal settling threshold may modulate when resources become more scarce or difficult to find. Thus, the model addresses ecological theory on the advantages of foraging in groups versus independently. This technique is appropriate for evaluating wading bird populations that forage on patchy landscapes, such as seasonally-pulsed wetlands, wherever sufficient information is available to describe (1) foraging behavior (e.g., feeding rate, flight speeds, patch selection decisions), (2) key landscape characteristics, (3) spatial distributions of prey densities among foraging patches, and (4) changes in prey densities through time. The model was designed to predict qualitative, testable spatial patterns of wading bird foraging movements which can be compared with empirical observations and empirically-derived habitat suitability models. These techniques can also be applied to other bird species, such as shorebirds, or more generally to any species that transits between discrete foraging patches.

Ecological Modelling↗
USGS2025

Foraging of wading birds on a patchy landscape: Simulating effects of social information, interference competition, and patch selection on prey intake and individual distribution

Foragers on patchy landscapes must acquire sufficient resources despite uncertainty in the location and amount of the resources. Optimal Foraging Theory posits that foragers deal with this uncertainty by using strategies that optimize resource intake within foraging periods. For species such as wading birds, this optimization is closely linked to their survival and reproductive success. Understanding the influence of patch selection on individual resource intake and foraging distribution is therefore crucial. In this study, we simulated how resource distribution, interference competition, and social cues—such as aggregation behaviors—influence resource intake and foraging spatial distribution. We employed an individual-based model simulating wading bird foraging behaviors, with 900 individuals simultaneously foraging across a landscape with unknown resource distribution. Birds employed one of three patch-finding strategies: random, cue-searching, or hybrid, which uses both searching strategies. Each bird decided whether to remain in a patch based on a prey density threshold. We compared the daily resource intake and foraging distribution of birds across different modeled patch-finding strategies, resource distribution patterns, and the presence or absence of interference competition. Wading birds exhibiting aggregation behavior displayed increased intake rates when resources were concentrated and interference minimal. Aggregation behavior led to a closer match with the ideal free distribution when the prey density threshold was optimal. These findings provide theoretical support that aggregation behavior is effective in scenarios where resources are concentrated in a few patches, social cues are used by relatively few individuals, and interference competition is limited.

Ecological Modelling↗
USGS2022

The occupancy-abundance relationship and sampling designs using occupancy to monitor populations of Asian bears

Designing a population monitoring program for Asian bears presents challenges associated with their low densities and detectability, generally large home ranges, and logistical or resource constraints. The use of an occupancy-based method to monitor bear populations can be appropriate under certain conditions given the mechanistic relationship between occupancy and abundance. The form of the occupancy–abundance relationship is dependent on species-specific characteristics such as home range size and population density, as well as study area size. To assess the statistical power of tests to detect population change of Asian bears, we conducted a study using a range of scenarios by simulating spatially explicit individual-based capture-recapture data from a demographically open model. Simulations assessed the power to detect changes in population density via changes in site-level occupancy or abundance through time, estimated using a standard occupancy model or a Royle-Nichols model, both with point detectors (representing camera traps). We used IUCN Red List criteria as a guide in selection of two population decline scenarios (20% and 50%), but we chose a shorter time horizon (10 years = 1 bear generation), meaning that declines were steeper than used for IUCN criteria (3 generations). Our simulations detected population declines of 50% with high power (>0.80) and low false positive rates (FPR: incorrectly detecting a decline) (<0.10) when detectors were spaced at > 0.67 times the home range diameter (home-range spacing ratio: HRSR, a measure of spatial correlation), such that bears would tend to overlap no more than two detectors. There was high (0.85) correlation between realized occupancy and N in these scenarios. The FPR increased as the HRSR decreased because of spatial correlation in the occupancy process induced when individual home ranges overlap multiple detectors. The mean statistical power to detect more gradual population declines (20% in 10 years) with HRSR > 0.67 was low for occupancy models 0.22 (maximum power 0.67) and Royle-Nichols models (0.24; maximum power 0.67), suggesting that declines of this magnitude may not be described reliably with 10 years of monitoring. Our results demonstrated that under many realistic scenarios that we explored, false positive rates were unacceptably high. We highlight that when designing occupancy studies, the spacing between point detectors be at least 0.67 times the diameter of the home range size of the larger sex (e.g., males) when the assumptions of the spatial capture-recapture model used for simulation are met.

Global Ecology and Conservation↗
USGS2017

Basis function models for animal movement

Advances in satellite-based data collection techniques have served as a catalyst for new statistical methodology to analyze these data. In wildlife ecological studies, satellite-based data and methodology have provided a wealth of information about animal space use and the investigation of individual-based animal–environment relationships. With the technology for data collection improving dramatically over time, we are left with massive archives of historical animal telemetry data of varying quality. While many contemporary statistical approaches for inferring movement behavior are specified in discrete time, we develop a flexible continuous-time stochastic integral equation framework that is amenable to reduced-rank second-order covariance parameterizations. We demonstrate how the associated first-order basis functions can be constructed to mimic behavioral characteristics in realistic trajectory processes using telemetry data from mule deer and mountain lion individuals in western North America. Our approach is parallelizable and provides inference for heterogenous trajectories using nonstationary spatial modeling techniques that are feasible for large telemetry datasets. Supplementary materials for this article are available online.

Journal of the American Statistical Association↗
USGS2024

Thinking beyond the closure assumption: Designing surveys for estimating biological truth with occupancy models

Occupancy models estimate distributions of imperfectly detected species, but violations of the closure assumption can bias results. However, researchers working with mobile animals may find it impossible to eliminate such violations. Here, we tested the hypothesis that occupancy models fit to realistic sampling data can generate unbiased occupancy estimates for an itinerant Wood Thrush ( Hylocichla mustelina ) population. In 2013 and 2014, we tracked movements of 41 breeding Wood Thrush males. We modelled territory shift probabilities using logistic exposure models and within-territory movements using continuous-time stochastic process models. We then constructed an individual-based model, simulated (1000 iterations) spatiotemporal locations for individuals and simulated sampling these populations using 162 different point count protocols with variable spatial (sampling radius and point placement method), and temporal (survey length, between-survey intervals and number of surveys) characteristics. We compared occupancy estimates with true values of instantaneous, daily and seasonal occupancy from the simulations. We parameterized continuous time stochastic process models based on movements within 34 unique territories and estimated a daily territory shift probability of 0.0099 (95% CI: 0.0060, 0.0152). Simulated data indicated that estimates of occupancy ranged from 0.18 (0.06, 1.00) to 0.80 (0.71, 0.89) depending on protocol characteristics. Occupancy estimates increased with increasing survey radius, survey length and between-survey interval. Protocols using shorter surveys and between-survey intervals were good estimators for instantaneous occupancy (low bias and mean-squared error) but poor estimators for daily and seasonal occupancy; longer surveys and intervals generated unbiased estimators of daily occupancy but underestimated seasonal occupancy. Logistic regression models that ignored imperfect detection outperformed occupancy models for estimating instantaneous occupancy but not daily or seasonal occupancy. For mobile animals, occupancy of sampling sites changes in space and time. Consequently, the spatial and temporal aspects of a sampling protocol have strong, but predictable, effects on occupancy model parameter estimates. Our results demonstrate that how these factors interact is critical for designing surveys that produce occupancy estimates representative of the biological process of interest to a researcher.

Methods in Ecology and Evolution↗
USGS2017

Growth potential and habitat requirements of endangered age-0 pallid sturgeon (Scaphirhynchus albus) in the Missouri River, USA, determined using a individual-based model framework

An individual-based model framework was used to evaluate growth potential of the federally endangered pallid sturgeon ( Scaphirhynchus albus ) in the Missouri River. The model, developed for age-0 sturgeon, combines information on functional feeding response, bioenergetics and swimming ability to regulate consumption and growth within a virtual foraging arena. Empirical data on water temperature, water velocity and prey density were obtained from three sites in the Missouri River and used as inputs in the model to evaluate hypotheses concerning factors affecting pallid sturgeon growth. The model was also used to evaluate the impacts of environmental heterogeneity and water velocity on individual growth variability, foraging success and dispersal ability. Growth was simulated for a period of 100 days using 100 individuals (first feeding; 19 mm and 0.035 g) per scenario. Higher growth was shown to occur at sites where high densities of Ephemeroptera and Chironomidae larvae occurred throughout the growing season. Highly heterogeneous habitats (i.e., wide range of environmental conditions) and moderate water velocities (0.3 m/s) were also found to positively affect growth rates. The model developed here provides an important management and conservation tool for evaluating growth hypotheses and(or) identifying habitats in the Missouri River that are favourable to age-0 pallid sturgeon growth.

Ecology of Freshwater Fish↗