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At least 703 records · Page 39Linked to original sources
USGS2023

Advances in wildlife abundance estimation using pedigree reconstruction

The conservation and management of wildlife populations, particularly for threatened and endangered species are greatly aided with abundance, growth rate, and density measures. Traditional methods of estimating abundance and related metrics represent trade-offs in effort and precision of estimates. Pedigree reconstruction is an emerging, attractive alternate approach because its use of one-time, noninvasive sampling of individuals to infer the existence of unsampled individuals. However, advances in pedigree reconstruction could improve its utility, including forming a measure of precision for the method, establishing required spatial sampling effort for accurate estimates, ascertaining the spatial extent of abundance estimates derived from pedigree reconstruction, and assessing how population density affects the estimator's performance. Using established relationships for a stochastic, spatially explicit simulated moose ( Alces americanus ) population, pedigree reconstruction provided accurate estimates of the adult moose population size and trend. Novel bootstrapped confidence intervals performed as expected with intensive sampling but underperformed with moderate sampling efforts that could produce abundance estimates with low bias. Adult population estimates more closely reflected the total number of adults in the extant population, rather than number of adults inhabiting the area where sampling occurred. Increasing sampling effort, measured as the proportion of individuals sampled and as the proportion of a hypothetical study area, yielded similar asymptotic patterns over time. Simulations indicated a positive relationship between animal density and sampling effort required for unbiased estimates. These results indicate that pedigree reconstruction can produce accurate abundance estimates and may be particularly valuable for surveying smaller areas and low-density populations.

Ecology and Evolution↗
USGS2019

Flooding regimes increase avian predation on wildlife prey in tidal marsh ecosystems

Within isolated and fragmented populations, species interactions such as predation can cause shifts in community structure and demographics in tidal marsh ecosystems. It is critical to incorporate species interactions into our understanding when evaluating the effects of sea‐level rise and storm surges on tidal marshes. In this study, we hypothesize that avian predators will increase their presence and hunting activities during high tides when increased inundation makes their prey more vulnerable. We present evidence that there is a relationship between tidal inundation depth and time of day on the presence, abundance, and behavior of avian predators. We introduce predation pressure as a combined probability of predator presence related to water level. Focal surveys were conducted at four tidal marshes in the San Francisco Bay, California where tidal inundation patterns were monitored across 6 months of the winter. Sixteen avian predator species were observed. During high tide at Tolay Slough marsh, ardeids had a 29‐fold increase in capture attempts and 4 times greater apparent success rate compared with low tide. Significantly fewer raptors and ardeids were found on low tides than on high tides across all sites. There were more raptors in December and January and more ardeids in January than in other months. Ardeids were more prevalent in the morning, while raptors did not exhibit a significant response to time of day. Modeling results showed that raptors had a unimodal response to water level with a peak at 0.5 m over the marsh platform, while ardeids had an increasing response with water level. We found that predation pressure is related to flooding of the marsh surface, and short‐term increases in sea levels from high astronomical tides, sea‐level rise, and storm surges increase vulnerability of tidal marsh wildlife.

California↗
USGS2019

Temporally adaptive acoustic sampling to maximize detection across a suite of focal wildlife species

Acoustic recordings of the environment can produce species presence–absence data for characterizing populations of sound-producing wildlife over multiple spatial scales. If a species is present at a site but does not vocalize during a scheduled audio recording survey, researchers may incorrectly conclude that the species is absent (“false negative”). The risk of false negatives is compounded when audio devices have sampling constraints, do not record continuously, and must be manually scheduled to operate at pre-selected times of day, particularly when research programs target multiple species with acoustic availability that varies across temporal conditions. We developed a temporally adaptive acoustic sampling algorithm to maximize detection probabilities for a suite of focal species amid sampling constraints. The algorithm combines user-supplied species vocalization models with site-specific weather forecasts to set an optimized sampling schedule for the following day. To test our algorithm, we simulated hourly vocalization probabilities for a suite of focal species in a hypothetical monitoring area for the year 2016. We conducted a factorial experiment that sampled from the 2016 acoustic environment to compare the probability of acoustic detection by a fixed (stationary) schedule versus a temporally adaptive optimized schedule under several sampling efforts and monitoring durations. We found that over the course of a study season, the probability of acoustically capturing a focal species (given presence) at least once via automated acoustic monitoring was greater (and acoustic capture occurred earlier in the season) when using the temporally adaptive optimized schedule as compared to a fixed schedule. The advantages of a temporally adaptive optimized acoustic sampling schedule are magnified when a study duration is short, sampling effort is low, and/or species acoustic availability is minimal. This methodology presents the opportunity to maximize acoustic monitoring sampling efforts amid constraints.

Colorado↗
USGS2020

Evaluating wildlife translocations using genomics: A bighorn sheep case study

Wildlife restoration often involves translocation efforts to reintroduce species and supplement small, fragmented populations. We examined the genomic consequences of bighorn sheep ( Ovis canadensis ) translocations and population isolation to enhance understanding of evolutionary processes that affect population genetics and inform future restoration strategies. We conducted a population genomic analysis of 511 bighorn sheep from 17 areas, including native and reintroduced populations that received 0–10 translocations. Using the Illumina High Density Ovine array, we generated datasets of 6,155 to 33,289 single nucleotide polymorphisms and completed clustering, population tree, and kinship analyses. Our analyses determined that natural gene flow did not occur between most populations, including two pairs of native herds that had past connectivity. We synthesized genomic evidence across analyses to evaluate 24 different translocation events and detected eight successful reintroductions (i.e., lack of signal for recolonization from nearby populations) and five successful augmentations (i.e., reproductive success of translocated individuals) based on genetic similarity with the source populations. A single native population founded six of the reintroduced herds, suggesting that environmental conditions did not need to match for populations to persist following reintroduction. Augmentations consisting of 18–57 animals including males and females succeeded, whereas augmentations of two males did not result in a detectable genetic signature. Our results provide insight on genomic distinctiveness of native and reintroduced herds, information on the relative success of reintroduction and augmentation efforts and their associated attributes, and guidance to enhance genetic contribution of augmentations and reintroductions to aid in bighorn sheep restoration.

Montana, Idaho, Wyoming↗
USGS2016

To cross or not to cross: modeling wildlife road crossings as a binary response variable with contextual predictors

Roads are significant barriers to landscape-scale movements of individuals or populations of many wildlife taxa. The decision by an animal near a road to either cross or not cross may be influenced by characteristics of the road, environmental conditions, traits of the individual animal, and other aspects of the context within which the decision is made. We considered such factors in a mixed-effects logistic regression model describing the nightly road crossing probabilities of invasive nocturnal Brown Treesnakes ( Boiga irregularis ) through short-term radiotracking of 691 snakes within close proximity to 50 road segments across the island of Guam. All measures of road magnitude (traffic volume, gap width, surface type, etc.) were significantly negatively correlated with crossing probabilities. Snake body size was the only intrinsic factor associated with crossing rates, with larger snakes crossing roads more frequently. Humidity was the only environmental variable affecting crossing rate. The distance of the snake from the road at the start of nightly movement trials was the most significant predictor of crossings. The presence of snake traps with live mouse lures during a portion of the trials indicated that localized prey cues reduced the probability of a snake crossing the road away from the traps, suggesting that a snake's decision to cross roads is influenced by local foraging opportunities. Per capita road crossing rates of Brown Treesnakes were very low, and comparisons to historical records suggest that crossing rates have declined in the 60+ yr since introduction to Guam. We report a simplified model that will allow managers to predict road crossing rates based on snake, road, and contextual characteristics. Road crossing simulations based on actual snake size distributions demonstrate that populations with size distributions skewed toward larger snakes will result in a higher number of road crossings. Our method of modeling per capita road crossing probabilities as a binary response variable, influenced by contextual factors, may be useful for describing or predicting road crossings by individuals of other taxa provided that appropriate spatial and temporal resolution can be achieved and that potentially influential covariate data can be obtained.

Ecosphere↗
USGS2019

Designing multi-scale hierarchical monitoring frameworks for wildlife to support management: A sage-grouse case study

Population monitoring is integral to the conservation and management of wildlife; yet, analyses of population demographic data rarely consider processes occurring across spatial scales, potentially limiting the effectiveness of adaptive management. Therefore, we developed a method to identify hierarchical levels of organization (i.e., populations) to define multiple spatial scales, specifically intended to help guide appropriate conservation and management actions. This approach can support mobile species with high site fidelity where surveys occur on birthing/breeding grounds or migratory stopovers. Our approach used a graphbased clustering algorithm (Spatial K’luster Analysis by Tree Edge Removal) that explicitly included habitat selection information at multiple scales and further refined with constraint-based rules. We applied these concepts to greater sage-grouse leks (breeding grounds), a species of conservation concern, in two different ecological contexts (Nevada and Wyoming, USA). The constraint-based rules accounted for inter-lek movement distances based on literature and field studies in Nevada from 2012 to 2016, included methods to support a spatially balanced monitoring design, and identified barriers to movements among leks based on resistance surfaces. We evaluated the performance of our hierarchical clusters in Nevada using independent data from radio-marked sage-grouse, and we found the finest-scaled cluster level captured ~90% of sagegrouse movements and mid-level scales captured ~97–99% of movements. We expected comparable performance for Wyoming, where we lacked radio-marked sage-grouse for an evaluation, because genetic studies estimate similar dispersal distances to our ~15 km inter-lek movement distance in Nevada. For sage-grouse and other mobile species with high site fidelity, our approach to defining these frameworks could prove valuable for conservation and management applications, such as improving estimation of scale-dependent population trends and guiding the prescription of management actions at spatial scales that align with identified threats. Specific to sage-grouse, our analysis sets the stage for designing a monitoring framework that relies on comparison of short- and long-term population trends across our defined spatial scales and identifies and disentangles factors driving local (e.g., habitat quality) and regional (e.g., climate) population changes, thereby supporting scale-dependent management and research needs for adaptive management practices.

Nevada, Wyoming↗
USGS2020

Expanding the feasibility of fish and wildlife assessments with close-kin mark–recapture

Close-kin mark–recapture (CKMR) is a powerful new method for the assessment of fish and wildlife population dynamics. Unlike traditional mark–recapture techniques, the use of kinship as an identifying mark is robust to many forms of capture heterogeneity including variation in gear efficiency and tagging-based effects such as loss and differential mortality. In addition, close-kin methods can be applied to a wider range of sampling designs than traditional methods (e.g., single-occasion surveys and lethal capture), can provide retrospective historical abundance estimates, and can produce survival estimates from as few as two sampling occasions. We evaluated the ability of CKMR to provide estimates of abundance and adult survival and then compared results to those from traditional mark–recapture. This analysis incorporated data from a three-year study of lake resident brook trout ( Salvelinus fontinalis ) where individuals were both physically (PIT) tagged and genotyped for 44 de novo developed microsatellites with high throughput sequencing. Traditional mark–recapture estimates were derived using Pollock’s Robust Design, relying upon three primary open sampling occasions and four secondary closed occasions. We found that close-kin methods produced contemporary estimates of adult abundance and survival that were similar to those produced by traditional mark–recapture in both magnitude and precision. Furthermore, CKMR provided abundance estimates for multiple years prior to sampling and, when restricted to data from a single year, still produced reliable abundance estimates for at least one and as many as three years. Retrospective abundance estimates corresponded with those from a separate historical two-sample mark–recapture dataset. This study provides support for the use of CKMR as a robust and sampling-efficient alternative to traditional mark–recapture methods of assessing population parameters.

New York↗
USGS2023

Bayesian spatio-temporal survival analysis for all types of censoring with application to a wildlife disease study

In this article, we consider modeling arbitrarily censored survival data with spatio-temporal covariates. We demonstrate that under the piecewise constant hazard function, the likelihood for uncensored or right-censored subjects is proportional to the likelihood of multiple conditionally independent Poisson random variables. To address left- or interval-censored subjects, we propose to impute the exact event times and convert them into uncensored subjects, enabling the application of the integrated nested Laplace approximation to update model parameters using the imputed data. We introduce an iterative algorithm that alternates between imputing event times for left- and interval-censored subjects and re-estimating model parameters. The proposed method is assessed through a simulation study and applied to analyze a spatio-temporal survival dataset in a wildlife disease study investigating bovine tuberculosis in white-tailed deer in Michigan.

Environmetrics↗
USGS1989

Use of mixed-function oxygenases to monitor contaminant exposure in wildlife

This overview examines the utility of mixed-function oxygenase (MFO) enzymes as a bioeffects monitor for wildlife (amphibians, reptiles, birds and mammals) in view of their widespread use as indicators of contaminant exposure in aquatic invertebrates and fish. Phylogenetic trends in MFO activity, toxicological implications of induction and the relationship between contaminant exposure and MFO activity are discussed. Field studies using avian embryos and hatchlings suggest that MFO induction has utility for documenting contaminant exposure; however, findings in adult birds and mammals are equivocal. Age, sex and season are sources of variation that require consideration when undertaking field trials. Further understanding of MFO inducibility among species and application of recently developed analytical techniques including quantification of specific cytochrome P-450 isozymes are warranted.

Environmental Toxicology and Chemistry↗
USGS2018

Looking beyond wildlife: Using remote cameras to evaluate accuracy of gridded snow data

The use of remote cameras is widespread in wildlife ecology, yet few examples exist of their utility for collecting environmental data. We used a novel camera trap method to evaluate the accuracy of gridded snow data in a mountainous region of the northeastern US. We were specifically interested in assessing (1) how snow depth observations from remote cameras compare with gridded climate data, (2) the sources of error associated with the gridded data and (3) the influence of spatial sampling on bias. We compared daily observations recorded by remote cameras with Snow Data Assimilation System (SNODAS ) gridded predictions using data from three winters (2014–2016). Snow depth observations were correlated with SNODAS predictions for sites ( R 2 = 0.20) and regions ( R 2 = 0.16), yet we detected factors associated with SNODAS bias at both scales. Specifically, SNODAS underpredicted depths at high elevations, at sites with higher solar radiation, and within conifer‐dominated forest. Depths were most underpredicted at highest elevations, up to 44 and 26 cm on average at the site and region scales, respectively. Bias was greatest when predictions were lowest, occasionally predicting snow absence when depths were >100 cm at camera sites. We also detected breakdowns in accuracy when certain environmental conditions varied within the 1 km 2 SNODAS grid cells. For example, underprediction was greatest when the solar radiation values of camera stations increased relative to the mean of the SNODAS grid cells. This relationship was most prominent in mountainous regions, suggesting that factors which influence solar radiation (e.g. topographic complexity) contribute to SNODAS inaccuracy. We caution using gridded snow data for ecological studies when bias is unknown. We suggest increased sampling to adjust for errors associated with gridded data products that arise from factors, such as forest cover and topographic variability. Increasing resolution and accuracy of climate data will improve predictions of species’ responses to climate change.

New Hampshire, Vermont↗
USGS2017

Anticoagulant rodenticides and wildlife: Introduction

Rodents have interacted with people since the beginning of systematic food storage by humans in the early Neolithic era. Such interactions have had adverse outcomes such as threats to human health, spoiling and consumption of food sources, damage to human infrastructure and detrimental effects on indigenous island wildlife (through inadvertent anthropogenic assisted introductions). These socio/economic and environmental impacts illustrate the clear need to control populations of commensal rodents. Different methods have been applied historically but the main means of control in the last decades is through the application of rodenticides, mainly anticoagulant rodenticides (ARs) that inhibit blood clotting. The so-called First Generation Anticoagulant Rodenticides (FGARs) proved highly effective but rodents increasingly developed resistance. This led to a demand for more effective alternative compounds and paved the way to the development of Second Generation Anticoagulant Rodenticides (SGARs). These were more acutely toxic and persistent, making them more effective but also increasing the risks of exposure of non-target species and secondary poisoning of predatory species. SGARs often fail the environmental thresholds of different regulatory frameworks because of these negative side-effects, but their use is still permitted because of the overwhelming societal needs for rodent control and the lack of effective alternatives. This book provides a state-of-the-art overview of the scientific advancements in assessment of environmental exposure, effects and risks of currently used ARs. This is discussed in relation to the societal needs for rodent control, including risk mitigation and development of alternatives.

Book chapter↗
USGS1995

U.S. Fish and Wildlife Service 1979 wetland classification: A review

In 1979 the US Fish and Wildlife Service published and adopted a classification of wetlands and deepwater habitats of the United States. The system was designed for use in a national inventory of wetlands. It was intended to be ecologically based, to furnish the mapping units needed for the inventory, and to provide national consistency in terminology and definition. We review the performance of the classification after 13 years of use. The definition of wetland is based on national lists of hydric soils and plants that occur in wetlands. Our experience suggests that wetland classifications must facilitate mapping and inventory because these data gathering functions are essential to management and preservation of the wetland resource, but the definitions and taxa must have ecological basis. The most serious problem faced in construction of the classification was lack of data for many of the diverse wetland types. Review of the performance of the classification suggests that, for the most part, it was successful in accomplishing its objectives, but that problem areas should be corrected and modification could strengthen its utility. The classification, at least in concept, could be applied outside the United States. Experience gained in use of the classification can furnish guidance as to pitfalls to be avoided in the wetland classification process.

Vegetatio↗
USGS1994

Ambient air concentrations of PCDDs, PCDFs, coplanar PCBs, and PAHs at the Mississippi Sandhill Crane National Wildlife Refuge, Jackson County, Mississippi

Our objective was to determine the levels of selected airborne contaminants in ambient air at the Mississippi Sandhill Crane National Wildlife Refuge, Mississippi, that might be affecting the health of endangered cranes living there. Two high-volume air samplers were operated at separate locations on the Refuge during May–September 1991. The sampling media were micro-quartz filters in combination with polyurethane foam plugs. Composite bimonthly samples from each station were analyzed for polychlorinated dibenzo- p -dioxins (PCDDs), dibenzofurans (PCDFs), coplanar polychlorinated biphenyls (PCBs), and polycyclic aromatic hydrocarbons (PAHs). Overall, residue concentrations were low. The toxic PCDD isomer 2,3,7,8-tetra-CDD was not detected, nor was penta-CDD. There was no difference ( P >0.05) in residue concentrations between stations or over time and meteorological parameters were not correlated with residue concentrations. Because contaminant levels and patterns may differ seasonally, we recommend that air samples collected during winter months also be analyzed for these same chemical groups.

Environmental Monitoring and Assessment↗
USGS1989

Selenium accumulation by raccoons exposed to irrigation drainwater at Kesterson National Wildlife Refuge, California, 1986

In February–March 1986, eight raccoons ( Procyon lotor ) were collected at Kesterson Reservoir (Merced Co., California), which had received selenium-contaminated irrigation drainwater, and four raccoons were collected at the nearby Volta Wildlife Area, which had not. Selenium concentrations in Kesterson raccoons averaged 19.9 ppm (μg/g dry wt) in liver, 28.3 ppm (dry wt) in hair, 21.6 ppm (dry wt) in feces, and 2.61 ppm (wet wt) in blood and exceeded Volta concentrations by 12, 30, 21, and 10 times, respectively. Selenium concentrations in livers of Kesterson raccoons were less than those in five of nine other mammal species sampled in 1984. Selenium concentrations in hair provided the strongest statistical separation between study areas. Hemoglobin levels in two Kesterson raccoons equalled levels reported in rats with selenium-induced anemia, but the raccoons showed no illness. Amyloidosis in one Kesterson raccoon may have been selenium-induced. Our data indicate that raccoon births peaked about 2 months later than was previously reported. Based on our sample of 12 raccoons, we found no evidence that contamination by irrigation drainwater had negative effects on raccoons inhabiting Kesterson.

California↗
USGS2004

Avian mortality events in the United States caused by anticholinesterase pesticides: A retrospective summary of National Wildlife Health Center records from 1980 to 2000

We reviewed the U.S. Geological Survey National Wildlife Health Center (NWHC) mortality database from 1980 to 2000 to identify cases of poisoning caused by organophosphorus and carbamate pesticides. From the 35,022 cases from which one or more avian carcasses were submitted to the NWHC for necropsy, we identified 335 mortality events attributed to anticholinesterase poisoning, 119 of which have been included in earlier reports. Poisoning events were classified as confirmed (n = 205) when supported by findings of ≥50% inhibition of cholinesterase (ChE) activity in brain tissue and the detection of a specific pesticide in the gastrointestinal contents of one or more carcasses. Suspected poisonings (n = 130) were defined as cases where brain ChE activity was ≥50% inhibited or a specific pesticide was identified in gastrointestinal contents. The 335 avian mortality events occurred in 42 states. Washington, Virginia, and Ohio had the highest frequency of events, with 24 (7.2%), 21 (6.3%), and 20 (6.0%) events, respectively. A total of 8877 carcasses of 103 avian species in 12 orders was recovered. Because carcass counts underestimate total mortality, this represents the minimum actual mortality. Of 24 different pesticides identified, the most frequent were famphur (n = 59; 18%), carbofuran (n = 52; 15%), diazinon (n = 40; 12%), and fenthion (n = 17; 5.1%). Falconiformes were reported killed most frequently (49% of all die-offs) but Anseriformes were found dead in the greatest numbers (64% of 8877 found dead). The majority of birds reported killed by famphur were Passeriformes and Falconiformes, with the latter found dead in 90% of famphur-related poisoning events. Carbofuran and famphur were involved in mortality of the greatest variety of species (45 and 33, respectively). Most of the mortality events caused by diazinon involved waterfowl.

Ohio, Virginia, Washington↗
USGS2007

Selenium and metal concentrations in waterbird eggs and chicks at Agassiz National Wildlife Refuge, Minnesota

Exceptionally high cadmium (Cd) and chromium (Cr) concentrations were reported in eggs, feathers, or livers of selected waterbird species nesting at Agassiz National Wildlife Refuge (Agassiz) in 1994. Ten- to 15-day-old Franklin's gull (Larus pipixcan), black-crowned night-heron (Nycticorax nycticorax), and eared grebe (Podiceps nigricollis) chicks were collected in 1998, 1999, and 2001 at Agassiz and analyzed for selenium (Se) and metals including Cd and Cr. Freshly laid eggs were collected in 2001 from Franklin's gull, black-crowned night-heron, eared grebe, and pied-billed grebe (Podilymbus podiceps) nests at Agassiz. Based on a multivariate analysis, the pattern of Se and metal concentrations differed among species for eggs, chick feathers, and chick livers. Low Cd and Cr concentrations were measured in eggs, chick livers, and chick feathers of all four species. Mercury concentrations in black-crowned night-heron and eared grebe eggs collected from Agassiz in 2001 were lower than concentrations reported in 1994. Se and metal concentrations, including Cd and Cr, in waterbird eggs and chicks collected at Agassiz in 1998, 1999, and 2001 were not at toxic levels. ?? 2007 Springer Science+Business Media, LLC.

Archives of Environmental Contamination and Toxico↗
USGS2000

Wintering greater scaup as biomonitors of metal contamination in federal wildlife refuges in the Long Island Region

Tissues of greater scaup (Aythya marila mariloides) and components of their habitat (sediment, plankton, macroalgae, and invertebrates) were collected for heavy metal analysis in the winter of 1996-97 from US Department of the Interior wildlife refuges in the Long Island region. Geographic and temporal relationships between the concentration of nine metals in tissue and in habitat components were examined. In greater scaup tissues and habitat components, concentrations of As and Se were highest in Branford, Connecticut; Pb values were greatest in Oyster Bay, New York; and Hg concentrations were largest in Sandy Hook, New Jersey. Over the course of the winter, the concentration of Hg in liver increased, and concentrations of Cd, Cr, Cu, Hg, Pb, Se, and Zn in kidney decreased. Based on several criteria derived from geographic and temporal trends, metals were ranked using the apparent biomonitoring efficacy of greater scaup (As = Cr > Cu = Pb = Zn = Hg > Se = Cd > Ni). Although the seasonal migration and daily mobility of greater scaup are drawbacks to using this species as a sentinel for metal pollution, it was possible to demonstrate a relationship between geographic and temporal patterns of metals in habitat and greater scaup tissue. However, most metal concentrations in tissue were below thresholds known to adversely affect health of waterfowl.

Archives of Environmental Contamination and Toxico↗
USGS2012

Wildlife contact analysis: Emerging methods, questions, and challenges

Recent technological advances, such as proximity loggers, allow researchers to collect complete interaction histories, day and night, among sampled individuals over several months to years. Social network analyses are an obvious approach to analyzing interaction data because of their flexibility for fitting many different social structures as well as the ability to assess both direct contacts and indirect associations via intermediaries. For many network properties, however, it is not clear whether estimates based upon a sample of the network are reflective of the entire network. In wildlife applications, networks may be poorly sampled and boundary effects will be common. We present an alternative approach that utilizes a hierarchical modeling framework to assess the individual, dyadic, and environmental factors contributing to variation in the interaction rates and allows us to estimate the underlying process variation in each. In a disease control context, this approach will allow managers to focus efforts on those types of individuals and environments that contribute the most toward super-spreading events. We account for the sampling distribution of proximity loggers and the non-independence of contacts among groups by only using contact data within a group during days when the group membership of proximity loggers was known. This allows us to separate the two mechanisms responsible for a pair not contacting one another: they were not in the same group or they were in the same group but did not come within the specified contact distance. We illustrate our approach with an example dataset of female elk from northwestern Wyoming and conclude with a number of important future research directions.

Behavioral Ecology and Sociobiology↗