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At least 181 records · Page 10Linked to original sources
USGS2019

A temporally stratified extension of space‐for‐time Cormack–Jolly–Seber for migratory animals

Understanding drivers of temporal variation in demographic parameters is a central goal of mark‐recapture analysis. To estimate the survival of migrating animal populations in migration corridors, space‐for‐time mark–recapture models employ discrete sampling locations in space to monitor marked populations as they move past monitoring sites, rather than the standard practice of using fixed sampling points in time. Because these models focus on estimating survival over discrete spatial segments, model parameters are implicitly integrated over the temporal dimension. Furthermore, modeling the effect of time‐varying covariates on model parameters is complicated by unknown passage times for individuals that are not detected at monitoring sites. To overcome these limitations, we extended the Cormack–Jolly–Seber (CJS) framework to estimate temporally stratified survival and capture probabilities by including a discretized arrival time process in a Bayesian framework. We allow for flexibility in the model form by including temporally stratified covariates and hierarchical structures. In addition, we provide tools for assessing model fit and comparing among alternative structural models for the parameters. We demonstrate our framework by fitting three competing models to estimate daily survival, capture, and arrival probabilities at four hydroelectric dams for over 200 000 individually tagged migratory juvenile salmon released into the Snake River, USA.

Biometrics↗
USGS2016

A systematic survey of the integration of animal behavior into conservation

The role of behavioral ecology in improving wildlife conservation and management has been the subject of much recent debate. We aim to answer two foundational questions about the current use of behavioral knowledge in conservation: 1. To what extent is behavioral knowledge used in wildlife conservation and management? 2. How does the use of behavior differ among conservation fields in both frequency and types of use? To answer these questions, we searched the literature for intersections between key fields of animal behavior and conservation biology and created a systematic ‘heat’ map to visualize relative efforts. Our analysis challenges previous suggestions that there is little association between the fields of behavioral ecology and conservation and reveals tremendous variation in the use of different behaviors in conservation. For instance, some behaviors, such as foraging and dispersal, are commonly considered, but other behaviors such as learning, social or anti-predatory behaviors are hardly considered. Our analysis suggests that in many cases awareness of the importance of behavior does not translate into applicable management tools. We recommend that researchers should focus on developing research in underutilized intersections of behavior and conservation themes for which preliminary work show a potential for improving conservation and management, on translating behavioral theory into applicable and testable predictions, and on creating systematic reviews to summarize the behavioral evidence within the behavior-conservation intersections for which many studies exist.

Conservation Biology↗
USGS2019

Reserve design to optimize functional connectivity and animal density

Ecological distance-based spatial capture–recapture models (SCR) are a promising approach for simultaneously estimating animal density and connectivity, both of which affect spatial population processes and ultimately species persistence. We explored how SCR models can be integrated into reserve-design frameworks that explicitly acknowledge both the spatial distribution of individuals and their space use resulting from landscape structure. We formulated the design of wildlife reserves as a budget-constrained optimization problem and conducted a simulation to explore 3 different SCR-informed optimization objectives that prioritized different conservation goals by maximizing the number of protected individuals, reserve connectivity, and density-weighted connectivity. We also studied the effect on our 3 objectives of enforcing that the space-use requirements of individuals be met by the reserve for individuals to be considered conserved (referred to as home-range constraints). Maximizing local population density resulted in fragmented reserves that would likely not aid long-term population persistence, and maximizing the connectivity objective yielded reserves that protected the fewest individuals. However, maximizing density-weighted connectivity or preemptively imposing home-range constraints on reserve design yielded reserves of largely spatially compact sets of parcels covering high-density areas in the landscape with high functional connectivity between them. Our results quantify the extent to which reserve design is constrained by individual home-range requirements and highlight that accounting for individual space use in the objective and constraints can help in the design of reserves that balance abundance and connectivity in a biologically relevant manner.

Conservation Biology↗
USGS2018

The importance of early life experience and animal cultures in reintroductions

Even within a single population, individuals can display striking differences in behavior, with consequences for their survival and fitness. In reintroduced populations, managers often attempt to promote adaptive behaviors by controlling the early life experiences of individuals, but it remains largely unknown whether this early life training has lasting effects on behavior. We investigated the behavior of reintroduced whooping cranes ( Grus americana ) trained to migrate using two different methods to see whether their migration behavior remained different or converged over time. We found that the behavior of the two groups converged relatively rapidly, indicating that early life training may not produce lasting effects, especially in species that display lifelong learning and behavioral adaptation. In some cases, managers may consider continual behavioral interventions after release if desired behaviors are not present. Understanding the roles early life experience and animal cultures play in determining behavior is crucial for successful reintroduction programs.

Conservation Letters↗
USGS2018

Running on empty: Recharge dynamics from animal movement data

Vital rates such as survival and recruitment have always been important in the study of population and community ecology. At the individual level, physiological processes such as energetics are critical in understanding biomechanics and movement ecology and also scale up to influence food webs and trophic cascades. Although vital rates and population-level characteristics are tied with individual-level animal movement, most statistical models for telemetry data are not equipped to provide inference about these relationships because they lack the explicit, mechanistic connection to physiological dynamics. We present a framework for modelling telemetry data that explicitly includes an aggregated physiological process associated with decision making and movement in heterogeneous environments. Our framework accommodates a wide range of movement and physiological process specifications. We illustrate a specific model formulation in continuous-time to provide direct inference about gains and losses associated with physiological processes based on movement. Our approach can also be extended to accommodate auxiliary data when available. We demonstrate our model to infer mountain lion ( Puma concolor ; in Colorado, USA) and African buffalo ( Syncerus caffer ; in Kruger National Park, South Africa) recharge dynamics.

Ecology Letters↗
USGS2022

Geomorphology shapes relationships between animal communities and ecosystem function in large rivers

Understanding how the Earth's surface (i.e. ‘nature's stage') influences connections between biodiversity and ecosystem function (BEF) is a central objective in ecology. Despite recent calls to examine these connections at multiple trophic levels and at more complex and realistic scales, little is known about how landscape structure shapes BEF relationships among animal communities in nature. We coupled high-resolution habitat mapping with extensive field sampling to quantify connections among the geophysical habitat templet, invertebrate assemblages and secondary production in two large North American riverscapes. Patterns of sediment size governed invertebrate assemblage structure, with particularly strong effects on composition, richness and taxonomic and functional diversity. These relationships propagated to drive positive relationships between biodiversity and secondary production that were modified by scale, context-dependencies and anthropogenic modification. Finally, leveraging spatially-explicit descriptions of geophysical and biological properties, we uncovered distinct and nested spatial scales of biodiversity and secondary production, and suggest that multiple geophysical processes simultaneously influence these patterns at different scales. Together, our findings advance our understanding of relationships between the physical templet and patterns of BEF, and help to predict how perturbations to the Earth's surface may propagate to influence biodiversity and energy flux through food webs.

Oikos↗
USGS1970

Apollo 11: Exposure of lower animals to lunar material

Lunar material returned from the first manned landing on the moon was assayed for the presence of replicating agents possibly harmful to life on earth. Ten species of lower animals were exposed to lunar material for 28 days. No pathological effects attributable to contact with lunar material were detected.

Science↗
USGS1998

Estimation of temporal variability of survival in animal populations

Temporal variation of demographic characteristics for animal populations is of interest to both ecologists and biological modelers. The standard deviation of a series of estimated parameter values (e.g., estimated population size) or some function thereof (e.g., log of the estimated parameters) is commonly used as a measure of temporal variability. These measures of temporal variation overestimate the true temporal variation by not accounting for sampling variability inherent to the estimation of unknown population parameters. Using a variance-components approach to partitioning the total variability of an estimated parameter, we demonstrate the ease with which sampling variation can be removed from the observed total variation of parameter estimates. Estimates of temporal variability of survival are given after removal of sampling variation for three bird species: the federally listed Roseate Tern ( Sterna dougallii ), Black-capped Chickadees ( Parus atricapillus ), and Mallard ducks ( Anas platyrhynchos ). Sampling variation accounted for the majority of the total variation in the survival estimates for nearly all of the populations studied. Substantial differences in observed significance levels were observed when testing for demographic differences in temporal variation using temporal variance estimates adjusted and unadjusted for sampling variance.

Ecology↗
USGS2013

Inferential consequences of modeling rather than measuring snow accumulation in studies of animal ecology

Abstract. It is increasingly common for studies of animal ecology to use model-based predictions of environmental variables as explanatory or predictor variables, even though model prediction uncertainty is typically unknown. To demonstrate the potential for misleading inferences when model predictions with error are used in place of direct measurements, we compared snow water equivalent (SWE) and snow depth as predicted by the Snow Data Assimilation System (SNODAS) to field measurements of SWE and snow depth. We examined locations on elk (Cervus canadensis) winter ranges in western Wyoming, because modeled data such as SNODAS output are often used for inferences on elk ecology. Overall, SNODAS predictions tended to overestimate field measurements, prediction uncertainty was high, and the difference between SNODAS predictions and field measurements was greater in snow shadows for both snow variables compared to non-snow shadow areas. We used a simple simulation of snow effects on the probability of an elk being killed by a predator to show that, if SNODAS prediction uncertainty was ignored, we might have mistakenly concluded that SWE was not an important factor in where elk were killed in predatory attacks during the winter. In this simulation, we were interested in the effects of snow at finer scales (<1 km 2 ) than the resolution of SNODAS. If bias were to decrease when SNODAS predictions are averaged over coarser scales, SNODAS would be applicable to population-level ecology studies. In our study, however, averaging predictions over moderate to broad spatial scales (9–2200 km 2 ) did not reduce the differences between SNODAS predictions and field measurements. This study highlights the need to carefully evaluate two issues when using model output as an explanatory variable in subsequent analysis: (1) the model’s resolution relative to the scale of the ecological question of interest and (2) the implications of prediction uncertainty on inferences when using model predictions as explanatory or predictor variables.

Wyoming↗
USGS2014

A multi-scale assessment of animal aggregation patterns to understand increasing pathogen seroprevalence

Understanding how animal density is related to pathogen transmission is important to develop effective disease control strategies, but requires measuring density at a scale relevant to transmission. However, this is not straightforward or well-studied among large mammals with group sizes that range several orders of magnitude or aggregation patterns that vary across space and time. To address this issue, we examined spatial variation in elk ( Cervus canadensis ) aggregation patterns and brucellosis across 10 regions in the Greater Yellowstone Area where previous studies suggest the disease may be increasing. We hypothesized that rates of increasing brucellosis would be better related to the frequency of large groups than mean group size or population density, but we examined whether other measures of density would also explain rising seroprevalence. To do this, we measured wintering elk density and group size across multiple spatial and temporal scales from monthly aerial surveys. We used Bayesian hierarchical models and 20 years of serologic data to estimate rates of increase in brucellosis within the 10 regions, and to examine the linear relationships between these estimated rates of increase and multiple measures of aggregation. Brucellosis seroprevalence increased over time in eight regions (one region showed an estimated increase from 0.015 in 1991 to 0.26 in 2011), and these rates of increase were positively related to all measures of aggregation. The relationships were weaker when the analysis was restricted to areas where brucellosis was present for at least two years, potentially because aggregation was related to disease-establishment within a population. Our findings suggest that (1) group size did not explain brucellosis increases any better than population density and (2) some elk populations may have high densities with small groups or lower densities with large groups, but brucellosis is likely to increase in either scenario. In this case, any one control method such as reducing population density or group size may not be sufficient to reduce transmission. This study highlights the importance of examining the density-transmission relationship at multiple scales and across populations before broadly applying disease control strategies.

Wyoming↗
USGS2015

A method for estimating abundance of mobile populations using telemetry and counts of unmarked animals

While numerous methods exist for estimating abundance when detection is imperfect, these methods may not be appropriate due to logistical difficulties or unrealistic assumptions. In particular, if highly mobile taxa are frequently absent from survey locations, methods that estimate a probability of detection conditional on presence will generate biased abundance estimates. Here, we propose a new estimator for estimating abundance of mobile populations using telemetry and counts of unmarked animals. The estimator assumes that the target population conforms to a fission-fusion grouping pattern, in which the population is divided into groups that frequently change in size and composition. If assumptions are met, it is not necessary to locate all groups in the population to estimate abundance. We derive an estimator, perform a simulation study, conduct a power analysis, and apply the method to field data. The simulation study confirmed that our estimator is asymptotically unbiased with low bias, narrow confidence intervals, and good coverage, given a modest survey effort. The power analysis provided initial guidance on survey effort. When applied to small data sets obtained by radio-tracking Indiana bats, abundance estimates were reasonable, although imprecise. The proposed method has the potential to improve abundance estimates for mobile species that have a fission-fusion social structure, such as Indiana bats, because it does not condition detection on presence at survey locations and because it avoids certain restrictive assumptions.

Ecosphere↗
USGS1975

Optimal exploitation strategies for an animal population in a Markovian environment: A theory and an example

Optimal exploitation strategies were studied for an animal population in a Markovian (stochastic, serially correlated) environment. This is a general case and encompasses a number of important special cases as simplifications. Extensive empirical data on the Mallard (Anas platyrhynchos) were used as an example of general theory. The number of small ponds on the central breeding grounds was used as an index to the state of the environment. A general mathematical model was formulated to provide a synthesis of the existing literature, estimates of parameters developed from an analysis of data, and hypotheses regarding the specific effect of exploitation on total survival. The literature and analysis of data were inconclusive concerning the effect of exploitation on survival. Therefore, two hypotheses were explored: (1) exploitation mortality represents a largely additive form of mortality, and (2) exploitation mortality is compensatory with other forms of mortality, at least to some threshold level. Models incorporating these two hypotheses were formulated as stochastic dynamic programming models and optimal exploitation strategies were derived numerically on a digital computer. Optimal exploitation strategies were found to exist under the rather general conditions. Direct feedback control was an integral component in the optimal decision—making process. Optimal exploitation was found to be substantially different depending upon the hypothesis regarding the effect of exploitation on the population. If we assume that exploitation is largely an additive force of mortality in Mallards, then optimal exploitation decisions are a convex function of the size of the breeding population and a linear or slight concave function of the environmental conditions. Under the hypothesis of compensatory mortality forces, optimal exploitation decisions are approximately linearly related to the size of the Mallard breeding population. Dynamic programming is suggested as a very general formulation for realistic solutions to the general optimal exploitation problem. The concepts of state vectors and stage transformations are completely general. Populations can be modeled stochastically and the objective function can include extra—biological factors. The optimal level of exploitation in year t must be based on the observed size of the population and the state of the environment in year t unless the dynamics of the population, the state of the environment, and the result of the exploitation decisions are completely deterministic. Exploitation based on an average harvest, or harvest rate, or designed to maintain a constant breeding population size is inefficient.

Ecology↗
USGS1971

A device for monitoring radio-marked animals

A simple, portable, and economical recording system consisting of a receiver, signal conditioner, recorder, and power source is described. The system was designed to monitor the signal strength from a radio-marked animal at a particular location. Information is stored on recorder chart paper. Radio-marked ducks have been successfully monitored at nest sites, potholes, and other locations.

Journal of Wildlife Management↗
USGS1991

Satellite telemetry: performance of animal-tracking systems

t: We used 10 Telonics ST-3 platform transmitter terminals (PTT's) configured for wolves and ungulates to examine the performance of the Argos satellite telemetry system. Under near-optimal conditions, 68 percentile errors for location qualities (NQ) 1, 2, and 3 were 1,188, 903, and 361 m, respectively. Errors (rE) exceeded expected values for NQ = 2 and 3, varied greatly among PTT's, increased as the difference (HE) between the estimated and actual PTT elevations increased, and were correlated nonlinearly with maximum satellite pass height (P,). We present a model of the relationships among rE, HE, and PH. Errors were bimodally distributed along the east-west axis and tended to occur away from the satellite when HE was positive. A southeasterly bias increased with HE, probably due to the particular distribution of satellite passes and effects of HE on rE. Under near-optimal conditions, 21 sensor message was received for up to 64% of available (PH, 50) satellite passes, and a location (NQ 2 1) was calculated for up to 63% of such passes. Sampling frequencies of sensor and location data declined 13 and 70%, respectively, for PTT's in a valley bottom and 65 and 86%, respectively, for PTT's on animals that were in valley bottoms. Sampling frequencies were greater for ungulate than for wolf collars.

Journal of Wildlife Management↗