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USGS1989

Use of experimental ecosystems in regulatory decision making

Tiered testing for the effects of chemicals on aquatic ecosystems has begun to include tests at the ecosystem level as a component in pesticide regristration. Because such tests are expensive, regulators and industry need to know what additional information they can gain from such tests relative to the costs of the simpler single-species toxicity bioassays. Requirements for ecosystem-level testing have developed because resource managers have not fully understood the implications of potential damage to resources without having evaluations of the predicted impacts under field conditions. We review approaches taken in the use of experimental ecosystems, discuss benefits and limitations of small- and large-scale ecosystem tests, and point to correlative approaches between laboratory and field toxicity testing. Laboratory experimental ecosystems (microcosms) have been successfully used to measure contaminant bioavailability, to determine routes of uptake in moderately complex aquatic systems, and to isolate factors modifying contaminant uptake into the biota. Such factors cannot be as readily studied in outdoor experimental ecosystems because direct cause-and-effect relations are often confounded and difficult to isolate. However, laboratory tests can be designed to quantify the relations among three variables: known concentrations of Stressors; specific sublethal behavioral, biochemical, and physiological effects displayed by organisms; and responses that have been observed in ecosystem-level analyses. For regulatory purposes, the specificity of test results determines how widely they can be applied. Ecotoxicological research should be directed at attempts to identify instances where single-species testing would be the appropriate level of analysis for identifying critical ecological endpoints and for clarifying relationships between ecosystem structure and function, and where it would be inadequate for a given level of analysis.

Environmental Management↗

USGS2015

Literature review of giant gartersnake ( Thamnophis gigas ) biology and conservation

This report reviews the available literature on giant gartersnakes ( Thamnophis gigas ) to compile existing information on this species and identify knowledge gaps that, if addressed, would help to inform conservation efforts for giant gartersnakes. Giant gartersnakes comprise a species of semi-aquatic snake precinctive to wetlands in the Central Valley of California. The diversion of surface water and conversion of wetlands to agricultural and other land uses resulted in the loss of more than 90 percent of natural giant gartersnake habitats. Because of this habitat loss, giant gartersnakes are now listed by the United States and California Endangered Species Acts as Threatened. Most extant populations occur in the rice-growing regions of the Sacramento Valley, which comprises the northern portion of the giant gartersnake’s former range. The huge demand for water in California for agriculture, industry, recreation, and other human consumption, combined with periodic severe drought, places remaining giant gartersnake habitats at increased risk of degradation and loss. This literature review summarizes the available information on giant gartersnake distribution, habitat relations, behavior, demography, and other aspects of its biology relevant to conservation. This information is then compiled into a graphical conceptual model that indicates the importance of different aspects of giant gartersnake biology for maintaining positive population growth, and identifies those areas for which important information relevant for conservation is lacking. Directing research efforts toward these aspects of giant gartersnake ecology will likely result in improvements to conserving this unique species while meeting the high demands for water in California.

Open-File Report↗

USGS1990

Comparisons of patch-use models for wintering American tree sparrows

Optimal foraging theory has stimulated numerous theoretical and empirical studies of foraging behavior for >20 years. These models provide a valuable tool for studying the foraging behavior of an organism. As with any other tool, the models are most effective when properly used. For example, to obtain a robust test of a foraging model, Stephens and Krebs (1986) recommend experimental designs in which four questions are answered in the affirmative. First, do the foragers play the same "game" as the model? Sec- ond, are the assumptions of the model met? Third, does the test rule out alternative possibilities? Finally, are the appropriate variables measured? Negative an- swers to any of these questions could invalidate the model and lead to confusion over the usefulness of foraging theory in conducting ecological studies. Gaines (1989) attempted to determine whether American Tree Sparrows ( Spizella arborea ) foraged by a time (Krebs 1973) or number expectation rule (Gibb 1962), or in a manner consistent with the predictions of Charnov's (1976) marginal value theorem (MVT). Gaines (1989: 118) noted appropriately that field tests of foraging models frequently involve uncontrollable circumstances; thus, it is often difficult to meet the assumptions of the models. Gaines also states (1989: 118) that "violations of the assumptions are also in- formative but do not constitute robust tests of predicted hypotheses," and that "the problem can be avoided by experimental analyses which concurrently test mutually exclusive hypotheses so that alter- native predictions will be eliminated if falsified." There is a problem with this approach because, when major assumptions of models are not satisfied, it is not justifiable to compare a predator's foraging behavior with the model's predictions. I submit that failing to follow the advice offered by Stephens and Krebs (1986) can invalidate tests of foraging models.

The Auk↗

USGS2018

Development of on-shore behavior among polar bears (Ursus maritimus) in the southern Beaufort Sea: Inherited or learned?

Polar bears ( Ursus maritimus ) are experiencing rapid and substantial changes to their environment due to global climate change. Polar bears of the southern Beaufort Sea (SB) have historically spent most of the year on the sea ice. However, recent reports from Alaska indicate that the proportion of the SB subpopulation observed on-shore during late summer and early fall has increased. Our objective was to investigate whether this on-shore behavior has developed through genetic inheritance, asocial learning, or through social learning. From 2010 to 2013, genetic data were collected from SB polar bears in the fall via hair snags and remote biopsy darting on-shore and in the spring from captures and remote biopsy darting on the sea ice. Bears were categorized as either on-shore or off-shore individuals based on their presence on-shore during the fall. Levels of genetic relatedness, first-order relatives, mother–offspring pairs, and father–offspring pairs were determined and compared within and between the two categories: on-shore versus off-shore. Results suggested transmission of on-shore behavior through either genetic inheritance or social learning as there was a higher than expected number of first-order relatives exhibiting on-shore behavior. Genetic relatedness and parentage data analyses were in concurrence with this finding, but further revealed mother–offspring social learning as the primary mechanism responsible for the development of on-shore behavior. Recognizing that on-shore behavior among polar bears was predominantly transmitted via social learning from mothers to their offspring has implications for future management and conservation as sea ice continues to decline.

Alaska↗

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↗

USGS1996

Use of behavioral avoidance testing in natural resource damage assessment

Natural Resource Damage Assessment (NRDA) provisions established under federal and state statutes enable natural resource trustees to recover compensation from responsible parties to restore injured natural resources. Behavioral avoidance testing with fish has been used in NRDAs to determine injuries to natural resources and to establish restoration thresholds. In this manuscript we evaluate the use of avoidance testing to NRDA. Specifically, we discuss potential “acceptance criteria” to evaluate the applicability and relevance of avoidance testing. These acceptance criteria include: (1) regulatory relevance, (2) reproducibility of testing, (3) ecological significance, (4) quality assurance/quality control, and (5) relevance to restoration. We discuss each of these criteria with respect to avoidance testing. Overall, we conclude that avoidance testing can be an appropriate, defensible, and desirable aspect of an NRDA.

ASTM Symposium on Environmental Toxicology and Ris↗

USGS2023

Linear and landscape disturbances alter Mojave desert tortoise movement behavior

Introduction: Animal movements are influenced by landscape features; disturbances to the landscape can alter movements, dispersal, and ultimately connectivity among populations. Faster or longer movements adjacent to a localized disturbance or within disturbed areas could indicate reduced habitat quality whereas slower or shorter movements and reduced movements may indicate greater availability of resources. The Mojave desert tortoise ( Gopherus agassizii ) is a threatened species that is challenged by anthropogenic disturbances. Methods: We studied tortoise movements using Global Positioning System (GPS) loggers at multiple sites in the Mojave Desert of Nevada and California. Tortoises at our sites encountered localized, linear human infrastructure, including paved roads, dirt roads, and fences, as well as landscape-scale disturbances [wildfire, off highway vehicle use (OHV), livestock grazing area]. We fit two-state (moving and encamped) Hidden Markov models to GPS logger data to infer how tortoise movement behavior relates to anthropogenic and natural features. Results: We found that temporal covariates, individual-level random effects (intercepts), and sex best explained state transition probability in all sites. We compared relationships between tortoise movement and linear disturbances, which varied depending on site and context. Tortoises made longer movements within the OHV recreation area, near most dirt roads, and near a low-traffic paved road, indicating that tortoises avoid these habitat disturbances. Conversely, tortoises made shorter movements in areas of higher slope and near highways, suggesting that these features may restrict movement or provide resources that result in prolonged use (e.g., forage or drinking locations). Tortoises that encountered fences around utility-scale solar installations were more active and made longer movements near fences, indicative of pacing behavior. Discussion: These results provide insight into how different disturbances alter tortoise movement behavior and modify tortoise habitat use, providing information that can be used to manage tortoise habitat.

California, Nevada↗

USGS2020

Resilience management for conservation of inland recreational fisheries

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

Frontiers in Ecology and Evolution↗

USGS2024

Individual-based ecological particle tracking model (ECO-PTM) for simulating juvenile chinook salmon migration and survival through the Sacramento – San Joaquin Delta

Recovery of endangered salmon species in the Central Valley of California amidst prolonged drought and climate change necessitates innovative water management actions that balance species recovery and California's water demands. We describe an individual-based ecological particle tracking model (ECO-PTM) that can be used to assess the efficacy of proposed actions. Based on a random walk theory, the model tracks individual particles’ travel time, routing and survival in a flow field simulated by the Delta Simulation Model 2 hydrodynamic module (DSM2 HYDRO). The random walk particles are parameterized to have fish-like swimming behaviors, including upstream/downstream swimming, probabilistic holding behaviors, and stochastic swimming velocities. Particle routing at key junctions is based on well-established statistical models, and route-specific survival is calculated using the XT mean free-path length model. Behavioral parameters were estimated by fitting several competing models to a multiyear dataset of travel times from acoustic tagged juvenile salmon. The model’s baseline simulations under historical flow conditions from 1991 to 2016 successfully replicated essential relationships between salmon outmigration survival and hydrodynamic conditions, consistent with previous studies and the STARS (Survival Travel Time and Routing Simulation) statistical simulation model. Simulation results for management scenarios revealed multifaceted influences on fish survival, including Delta flow, flow at key junctions, route alterations, seasons, and water year characteristics. Importantly, these results highlight ECO-PTM’s potential to predict fish survival outcomes of proposed actions, serving as a foundation for informed future research, decision-making, and effective management strategies to enhance the survival prospects of out-migrating salmonids within the Sacramento-San Joaquin Delta ecosystem.

California↗

USGS2013

American badgers selectively excavate burrows in areas used by black-footed ferrets: implications for predator avoidance

We evaluated how American badgers ( Taxidea taxus ) might exert selective pressure on black-footed ferrets ( Mustela nigripes ) to develop antipredator defenses. In a colony of black-tailed prairie dogs ( Cynomys ludovicianus ) in South Dakota, badgers concentrated their activities where burrow openings and prairie dogs were abundant, a selective behavior that was exhibited by ferrets in the same colony. Badgers excavated burrows more often when in areas recently used by a ferret, suggesting that badgers hunt ferrets or steal prey from ferrets, or both. We also conducted an analysis of survival studies for ferrets and Siberian polecats ( M. eversmanii ) released onto prairie dog colonies. This polecat is the ferret's ecological equivalent but evolved without a digging predator. Badgers accounted for 30.0% of predation on polecats and 5.5% of predation on ferrets. In contrast, both polecats and ferrets have evolutionary experience with canids, providing a plausible explanation for the similar relative impact of coyotes ( Canis latrans ) on them (65.0% and 67.1% of predation, respectively). We hypothesize that ferrets and badgers coexist because ferrets are superior at exploitation competition and are efficient at avoiding badgers, and badgers are superior at interference competition.

South Dakota↗

USGS2017

Southern sea otter range expansion and habitat use in the Santa Barbara Channel, California

The re-colonization of the Santa Barbara channel by sea otters brings these ESA-listed marine mammals closer to active oil and gas production facilities, shipping lanes and naturally occurring oil and gas seeps. However, the degree to which sea otters may actually be affected by human-caused oil spills or exposure to natural oil seeps is currently unknown. Between 2012 and 2014, the U.S. Geological Survey and collaborating agencies conducted a telemetry-based study of sea otters in Santa Barbara channel, in order to provide critical information for resource managers (specifically the Bureau of Ocean Energy Management, henceforth BOEM, and the U.S. Fish and Wildlife Service, henceforth USFWS) about the spatial ecology, population status, and potential population threats to sea otters in Santa Barbara Channel, with particular reference to exposure to manmade structures and sources of oil and natural gas. Analysis of spatial monitoring data using a Bayesian-based synoptic model allowed for description of sea otter home ranges, identification of hot-spots of use, and insights into habitat selection behavior by male and female sea otters. Important findings included the deeper modal depth preferred by males versus females, strong preferences by both sexes for areas with persistent kelp canopy, and greater use of soft-sediment areas by males. The synoptic model also provided the ability to predict population-level density distribution for each sex in new habitats: by calculating the value of these probability density distributions at the known locations of natural seeps, we were able to identify those seeps with higher potential for sea otter encounters. The relative probability of occurrence at locations near to some seeps was sufficiently high (about 1% likelihood of occurrence for some of our study animals) that one would anticipate occasional encounters. Data on male and female survival, reproductive success, activity budgets, and body condition all indicated that sea otters in Santa Barbara Channel are not resource limited, and thus we would expect to see continued strong population growth in this area. However, the principal cause of death for study animals was lethal bites by white sharks, suggesting that shark bite mortality represents the single biggest threat to continued population growth in the Santa Barbara Channel.

California↗

USGS2003

The use of traditional Hawaiian knowledge in the contemporary management of marine resources

It is traditional for Hawaiians to "consult nature" so that fishing is practiced at times and places, and with gear that causes minimum disruption of natural biological and ecological processes. The Ho'olehua Hawaiian Homestead continues this tradition in and around Mo'omomi Bay on the northwest coast of the island of Moloka'i. This community relies heavily on inshore marine resources for subsistence and consequently, has an intimate knowledge of these resources. The shared knowledge, beliefs, and values of the community are culturally channeled to promote proper fishing behavior. This informal system brings more knowledge, experience, and moral commitment to fishery conservation than more centralized government management. Community-based management in the Mo'omomi area involves observational processes and problem-solving strategies for the purpose of conservation. The system is not articulated in the manner of Western science, but relies instead on mental models. These models foster a practical understanding of local inshore resource dynamics by the fishing community and, thus, lend credibility to unwritten standards for fishing conduct. The "code of conduct" is concerned with how people fish rather than how much they catch.

Hawai'i↗

USGS2023

Supervised versus unsupervised approaches to classification of accelerometry data

Sophisticated animal-borne sensor systems are increasingly providing novel insight into how animals behave and move. Despite their widespread use in ecology, the diversity and expanding quality and quantity of data they produce have created a need for robust analytical methods for biological interpretation. Machine learning tools are often used to meet this need. However, their relative effectiveness is not well known and, in the case of unsupervised tools, given that they do not use validation data, their accuracy can be difficult to assess. We evaluated the effectiveness of supervised ( n = 6), semi-supervised ( n = 1), and unsupervised ( n = 2) approaches to analyzing accelerometry data collected from critically endangered California condors ( Gymnogyps californianus ). Unsupervised K-means and EM (expectation–maximization) clustering approaches performed poorly, with adequate classification accuracies of <0.8 but very low values for kappa statistics (range: −0.02 to 0.06). The semi-supervised nearest mean classifier was moderately effective at classification, with an overall classification accuracy of 0.61 but effective classification only of two of the four behavioral classes. Supervised random forest (RF) and k-nearest neighbor (kNN) machine learning models were most effective at classification across all behavior types, with overall accuracies >0.81. Kappa statistics were also highest for RF and kNN, in most cases substantially greater than for other modeling approaches. Unsupervised modeling, which is commonly used for the classification of a priori-defined behaviors in telemetry data, can provide useful information but likely is instead better suited to post hoc definition of generalized behavioral states. This work also shows the potential for substantial variation in classification accuracy among different machine learning approaches and among different metrics of accuracy. As such, when analyzing biotelemetry data, best practices appear to call for the evaluation of several machine learning techniques and several measures of accuracy for each dataset under consideration.

Ecology and Evolution↗

USGS2012

Hybridization among Arctic white-headed gulls (Larus spp.) obscures the genetic legacy of the Pleistocene

We studied the influence of glacial oscillations on the genetic structure of seven species of white-headed gull that breed at high latitudes ( Larus argentatus, L. canus, L. glaucescens, L. glaucoides, L. hyperboreus, L. schistisagus, and L. thayeri ). We evaluated localities hypothesized as ice-free areas or glacial refugia in other Arctic vertebrates using molecular data from 11 microsatellite loci, mitochondrial DNA (mtDNA) control region, and six nuclear introns for 32 populations across the Holarctic. Moderate levels of genetic structure were observed for microsatellites ( F ST = 0.129), introns ( Φ ST = 0.185), and mtDNA control region ( Φ ST = 0.461), with among-group variation maximized when populations were grouped based on subspecific classification. Two haplotype and at least two allele groups were observed across all loci. However, no haplotype/allele group was composed solely of individuals of a single species, a pattern consistent with recent divergence. Furthermore, northernmost populations were not well differentiated and among-group variation was maximized when L. argentatus and L. hyberboreus populations were grouped by locality rather than species, indicating recent hybridization. Four populations are located in putative Pleistocene glacial refugia and had larger t estimates than the other 28 populations. However, we were unable to substantiate these putative refugia using coalescent theory, as all populations had genetic signatures of stability based on mtDNA. The extent of haplotype and allele sharing among Arctic white-headed gull species is noteworthy. Studies of other Arctic taxa have generally revealed species-specific clusters as well as genetic structure within species, usually correlated with geography. Aspects of white-headed gull behavioral biology, such as colonization ability and propensity to hybridize, as well as their recent evolutionary history, have likely played a large role in the limited genetic structure observed.

Ecology and Evolution↗

USGS2021

Identifying resting locations of a small elusive forest carnivore using a two-stage model accounting for GPS measurement error and hidden behavioral states

Studies of animal movement using location data are often faced with two challenges. First, time series of animal locations are likely to arise from multiple behavioral states (e.g., directed movement, resting) that cannot be observed directly. Second, location data can be affected by measurement error, including failed location fixes. Simultaneously addressing both problems in a single statistical model is analytically and computationally challenging. To both separate behavioral states and account for measurement error, we used a two-stage modeling approach to identify resting locations of fishers ( Pekania pennanti ) based on GPS and accelerometer data.

California, Oregon↗

USGS2011

Biogeochemistry of a temperate forest nitrogen gradient

Wide natural gradients of soil nitrogen (N) can be used to examine fundamental relationships between plant–soil–microbial N cycling and hydrologic N loss, and to test N-saturation theory as a general framework for understanding ecosystem N dynamics. We characterized plant production, N uptake and return in litterfall, soil gross and net N mineralization rates, and hydrologic N losses of nine Douglas-fir ( Pseudotsuga menziesii ) forests across a wide soil N gradient in the Oregon Coast Range (USA). Surface mineral soil N (0–10 cm) ranged nearly three-fold from 0.29% to 0.78% N, and in contrast to predictions of N-saturation theory, was linearly related to 10-fold variation in net N mineralization, from 8 to 82 kg N·ha −1 ·yr −1 . Net N mineralization was unrelated to soil C:N, soil texture, precipitation, and temperature differences among sites. Net nitrification was negatively related to soil pH, and accounted for <20% of net N mineralization at low-N sites, increasing to 85–100% of net N mineralization at intermediate- and high-N sites. The ratio of net : gross N mineralization and nitrification increased along the gradient, indicating progressive saturation of microbial N demands at high soil N. Aboveground N uptake by plants increased asymptotically with net N mineralization to a peak of 35 kg N·ha −1 ·yr −1 . Aboveground net primary production per unit net N mineralization varied inversely with soil N, suggesting progressive saturation of plant N demands at high soil N. Hydrologic N losses were dominated by dissolved organic N at low-N sites, with increased nitrate loss causing a shift to dominance by nitrate at high-N sites, particularly where net nitrification exceeded plant N demands. With the exception of N mineralization patterns, our results broadly support the application of the N-saturation model developed from studies of anthropogenic N deposition to understand N cycling and saturation of plant and microbial sinks along natural soil N gradients. This convergence of behavior in unpolluted and polluted forest N cycles suggests that where future reductions in deposition to polluted sites do occur, symptoms of N saturation are most likely to persist where soil N content remains elevated.

Oregon↗

USGS2016

Movement reveals scale dependence in habitat selection of a large ungulate

Ecological processes operate across temporal and spatial scales. Anthropogenic disturbances impact these processes, but examinations of scale dependence in impacts are infrequent. Such examinations can provide important insight to wildlife–human interactions and guide management efforts to reduce impacts. We assessed spatiotemporal scale dependence in habitat selection of mule deer ( Odocoileus hemionus ) in the Piceance Basin of Colorado, USA, an area of ongoing natural gas development. We employed a newly developed animal movement method to assess habitat selection across scales defined using animal-centric spatiotemporal definitions ranging from the local (defined from five hour movements) to the broad (defined from weekly movements). We extended our analysis to examine variation in scale dependence between night and day and assess functional responses in habitat selection patterns relative to the density of anthropogenic features. Mule deer displayed scale invariance in the direction of their response to energy development features, avoiding well pads and the areas closest to roads at all scales, though with increasing strength of avoidance at coarser scales. Deer displayed scale-dependent responses to most other habitat features, including land cover type and habitat edges. Selection differed between night and day at the finest scales, but homogenized as scale increased. Deer displayed functional responses to development, with deer inhabiting the least developed ranges more strongly avoiding development relative to those with more development in their ranges. Energy development was a primary driver of habitat selection patterns in mule deer, structuring their behaviors across all scales examined. Stronger avoidance at coarser scales suggests that deer behaviorally mediated their interaction with development, but only to a degree. At higher development densities than seen in this area, such mediation may not be possible and thus maintenance of sufficient habitat with lower development densities will be a critical best management practice as development expands globally.

Colorado↗

USGS2024

Behavioral trade-offs and multitasking by elk in relation to predation risk from Mexican gray wolves

Predator non-consumptive effects (NCE) can alter prey foraging time and habitat use, potentially reducing fitness. Prey can mitigate NCEs by increasing vigilance, chewing-vigilance synchronization, and spatiotemporal avoidance of predators. We quantified the relationship between Mexican wolf ( Canis lupus baileyi ) predation risk and elk ( Cervus canadensis ) behavior. We conducted behavioral observations on adult female elk and developed predation risk indices using GPS collar data from Mexican wolves, locations of elk killed by wolves, and landscape covariates. We compared a priori models to determine the best predictors of adult female behavior and multitasking. Metrics that quantified both spatial and temporal predation risk were the most predictive. Vigilance was positively associated with increased predation risk. The effect of predation risk on foraging and resting differed across diurnal periods. During midday when wolf activity was lower, the probability of foraging increased while resting decreased in high-risk areas. During crepuscular periods when elk and wolves were most active, increased predation risk was associated with increased vigilance and slight decreases in foraging. Our results suggest elk are temporally avoiding predation risk from Mexican wolves by trading resting for foraging, a trade-off often not evaluated in behavioral studies. Probability of multitasking depended on canopy openness and an interaction between maternal period and predation risk; multitasking decreased prior to parturition and increased post parturition in high-risk areas. Openness was inversely related to multitasking. These results suggest adult female elk are altering the type of vigilance used depending on resource availability/quality, current energetic needs, and predation risk. Our results highlight potentially important, but often-excluded behaviors and trade-offs prey species may use to reduce the indirect effects of predation and contribute additional context to our understanding of predator–prey dynamics.

Ecology and Evolution↗