A bird distribution model for ring recovery data: where do the European robins go?

For the study of migratory connectivity, birds have been individually marked by metal rings for more than 100 years. The resulting ring recovery data have been compiled in numerous bird migration atlases. However, estimation of what proportion of a particular population is migrating to which region is confounded by spatial heterogeneity in ring recovery probability. We present a product multinomial model that enables quantifying the continent‐wide distribution of different bird populations during different seasons based on ring recovery data while accounting for spatial heterogeneity of ring recovery probability. We applied the model to an example data set of the European robin Erithacus rubecula. We assumed that ring recovery probability was equal between different groups of birds and that survival probability was constant. Simulated data indicate that violation of the assumption of constant survival did not affect our estimated bird distribution parameters but biased the estimates for recovery probability. Posterior predictive model checking indicated a good general model fit but also revealed lack of fit for a few groups of birds. This lack of fit may be due to between‐group differences in the spatial distribution on smaller scales within regions. We found that 48% of the Scandinavian robins, but only 31% of the central European robins, wintered in northern Africa. The remaining parts of both populations wintered in southern and central Europe. Therefore, a substantial part of the Scandinavian population appears to leap over individuals from the central European population during migration. The model is applied to summary tables of numbers of ringed and recovered birds. This allows us to handle very large data sets as, for example, those presented in bird migration atlases.     

Using soundscape recordings to estimate bird species abundance, richness, and composition

ABSTRACT Point counts are the most frequently used technique for sampling bird populations and communities, but have well‐known limitations such as inter‐ and intraobserver errors and limited availability of expert field observers. The use of acoustic recordings to survey birds offers solutions to these limitations. We designed a Soundscape Recording System (SRS) that combines a four‐channel, discrete microphone system with a quadraphonic playback system for surveying bird communities. We compared the effectiveness of SRS and point counts for estimating species abundance, richness, and composition of riparian breeding birds in California by comparing data collected simultaneously using both methods. We used the temporal‐removal method to estimate individual bird detection probabilities and species abundances using the program MARK. Akaike's Information Criterion provided strong evidence that detection probabilities differed between the two survey methods and among the 10 most common species. The probability of detecting birds was higher when listening to SRS recordings in the laboratory than during the field survey. Additionally, SRS data demonstrated a better fit to the temporal‐removal model assumptions and yielded more reliable estimates of detection probability and abundance than point‐count data. Our results demonstrate how the perceptual constraints of observers can affect temporal detection patterns during point counts and thus influence abundance estimates derived from time‐of‐detection approaches. We used a closed‐population capture–recapture approach to calculate jackknife estimates of species richness and average species detection probabilities for SRS and point counts using the program CAPTURE. SRS and point counts had similar species richness and detection probabilities. However, the methods differed in the composition of species detected based on Jaccard's similarity index. Most individuals (83%) detected during point counts vocalized at least once during the survey period and were available for detection using a purely acoustic technique, such as SRS. SRS provides an effective method for surveying bird communities, particularly when most species are detected by sound. SRS can eliminate or minimize observer biases, produce permanent records of surveys, and resolve problems associated with the limited availability of expert field observers.     

Separating Components of the Detection Process With Combined Methods: An Example With Northern Bobwhite

Abstract: There are various methods of estimating detection probabilities for avian point counts. Distance and multiple-observer methods require the sometimes unlikely assumption that all birds in the population are available (i.e., sing or are visible) during a count, but the time-of-detection method allows for the possibility that some birds are unavailable during the count. We combined the dependent double-observer method with the time-of-detection method and obtained field-based estimates of the components of detection probability for northern bobwhite (Colinus virginianus). Our approach was a special case of Pollock's robust capture-recapture design where the probability that a bird does not sing is analogous to the probability that an animal is a temporary emigrant. Top models indicated that observers' detection probabilities were similar (0.78–0.84) if bobwhite were available, but bobwhite only had an approximately 0.61 probability of being available during a 2.5-minute sampling interval. Additionally, observers' detection probabilities increased substantially after the initial encounter with an individual bobwhite (analogous to a trap-happy response on the part of the observer). A simulated data set revealed that the combined method was precise when availability and detection given availability were substantially lower. Combined methods approaches can provide critical information for researchers and land managers to make decisions regarding survey length and personnel requirements for point-count-based surveys.     

Spatial heterogeneity in mortality and its impact on the population dynamics of Eurasian woodcocks

Spatial heterogeneity, especially in mortality risk, is a major factor shaping population dynamics. Here we study the impacts of spatial heterogeneity in hunting pressure on the demography of Eurasian woodcock Scolopax rusticola, a relatively long-lived migratory game bird. We develop capture–recapture–recovery models in which both seasonality and spatial variation in hunting pressure are accounted for, and fit them to individual-based data collected across the French wintering range (>44000 banded individuals) as well as recoveries from spring stopovers and breeding grounds in Europe. Our results quantify spatial variation in survival probability in the wintering areas. They highlight the role of source-sink dynamics involving juvenile settlement decisions, as well as the importance of mortality outside the winter quarters. We also discuss the impact of spatial heterogeneity for demographic parameter estimation and data collection at the range scale.     

Comparison of Methods for Estimating Bird Abundance and Trends From Historical Count Data

Abstract: The use of bird counts as indices has come under increasing scrutiny because assumptions concerning detection probabilities may not be met, but there also seems to be some resistance to use of model-based approaches to estimating abundance. We used data from the United States Forest Service, Southern Region bird monitoring program to compare several common approaches for estimating annual abundance or indices and population trends from point-count data. We compared indices of abundance estimated as annual means of counts and from a mixed-Poisson model to abundance estimates from a count-removal model with 3 time intervals and a distance model with 3 distance bands. We compared trend estimates calculated from an autoregressive, exponential model fit to annual abundance estimates from the above methods and also by estimating trend directly by treating year as a continuous covariate in the mixed-Poisson model. We produced estimates for 6 forest songbirds based on an average of 621 and 459 points in 2 physiographic areas from 1997 to 2004. There was strong evidence that detection probabilities varied among species and years. Nevertheless, there was good overall agreement across trend estimates from the 5 methods for 9 of 12 comparisons. In 3 of 12 comparisons, however, patterns in detection probabilities potentially confounded interpretation of uncorrected counts. Estimates of detection probabilities differed greatly between removal and distance models, likely because the methods estimated different components of detection probability and the data collection was not optimally designed for either method. Given that detection probabilities often vary among species, years, and observers investigators should address detection probability in their surveys, whether it be by estimation of probability of detection and abundance, estimation of effects of key covariates when modeling count as an index of abundance, or through design-based methods to standardize these effects.     

Use of classical bird census transects as spatial replicates for hierarchical modeling of an avian community

New monitoring programs are often designed with some form of temporal replication to deal with imperfect detection by means of occupancy models. However, classical bird census data from earlier times often lack temporal replication, precluding detection‐corrected inferences about occupancy. Historical data have a key role in many ecological studies intended to document range shifts, and so need to be made comparable with present‐day data by accounting for detection probability. We analyze a classical bird census conducted in the region of Murcia (SE Spain) in 1991 and 1992 and propose a solution to estimating detection probability for such historical data when used in a community occupancy model: the spatial replication of subplots nested within larger plots allows estimation of detection probability. In our study, the basic sample units were 1‐km transects, which were considered spatial replicates in two aggregation schemes. We fit two Bayesian multispecies occupancy models, one for each aggregation scheme, and evaluated the linear and quadratic effect of forest cover and temperature, and a linear effect of precipitation on species occupancy probabilities. Using spatial rather than temporal replicates allowed us to obtain individual species occupancy probabilities and species richness accounting for imperfect detection. Species‐specific occupancy and community size decreased with increasing annual mean temperature. Both aggregation schemes yielded estimates of occupancy and detectability that were highly correlated for each species, so in the design of future surveys ecological reasons and cost‐effective sampling designs should be considered to select the most suitable aggregation scheme. In conclusion, the use of spatial replication may often allow historical survey data to be applied formally hierarchical occupancy models and be compared with modern‐day data of the species community to analyze global change process.     

Understanding implications of detection heterogeneity in wildlife abundance estimation

Negative bias in mark-recapture abundance estimators due to heterogeneity in detection (capture) probability is a well-known problem, but we believe most biologists do not understand why heterogeneity causes bias and how bias can be reduced. We demonstrate how heterogeneity creates dependence and bias in mark-recapture approaches to abundance estimation. In comparison, heterogeneity, and hence estimator bias, is not as problematic for distance sampling and mark-resight methods because both techniques estimate detection probabilities based on a known quantity. We show how the introduction of a known number of individuals planted into a study population prior to a mark-recapture survey can reduce bias from heterogeneity in detection probability. We provide examples with simulation and an analysis of motion-sensitive camera data from a study population of introduced eastern wild turkeys (Meleagris gallopavo silvestris) of known size with a subset of telemetered birds. In choosing a method for abundance estimation, careful consideration should be given to assumptions and how heterogeneity in detection probability can be accommodated for each application.     

Direct and indirect effects of area,energy and habitat heterogeneity on breeding bird communities

Aim To compare the ability of island biogeography theory, niche theory and species–energy theory to explain patterns of species richness and density for breeding bird communities across islands with contrasting characteristics. Location Thirty forested islands in two freshwater lakes in the boreal forest zone of northern Sweden (65°55′ N to 66°09′ N; 17°43′ E to 17°55′ E). Methods We performed bird censuses on 30 lake islands that have each previously been well characterized in terms of size, isolation, habitat heterogeneity (plant diversity and forest age), net primary productivity (NPP), and invertebrate prey abundance. To test the relative abilities of island biogeography theory, niche theory and species–energy theory to describe bird community patterns, we used both traditional statistical approaches (linear and multiple regressions) and structural equation modelling (SEM; in which both direct and indirect influences can be quantified). Results Using regression‐based approaches, area and bird abundance were the two most important predictors of bird species richness. However, when the data were analysed by SEM, area was not found to exert a direct effect on bird species richness. Instead, terrestrial prey abundance was the strongest predictor of bird abundance, and bird abundance in combination with NPP was the best predictor of bird species richness. Area was only of indirect importance through its positive effect on terrestrial prey abundance, but habitat heterogeneity and spatial subsidies (emerging aquatic insects) also showed important indirect influences. Thus, our results provided the strongest support for species–energy theory. Main conclusions Our results suggest that, by using statistical approaches that allow for analyses of both direct and indirect influences, a seemingly direct influence of area on species richness can be explained by greater energy availability on larger islands. As such, animal community patterns that seem to be in line with island biogeography theory may be primarily driven by energy availability. Our results also point to the need to consider several aspects of habitat quality (e.g. heterogeneity, NPP, prey availability and spatial subsidies) for successful management of breeding bird diversity at local spatial scales and in fragmented or insular habitats.     

Quantification of bird migration by radar – a detection probability problem

Besides the scientific interest in the quantification of bird migration, there is an increasing need to quantify bird movements for the assessment of bird collision risk with artificial structures. In many environmental impact studies, the radar method is used in an inappropriate manner. The processing of echoes consists often of counting blips within defined screen fields, and the surveyed volume is estimated without reference to the detection probabilities of different 'target sizes' (radar cross-sections). The aim of this paper is to present a procedure to quantify bird migration reliably using radar by stating the theoretical requirements of every single step of this procedure and presenting methodological solutions using our own radar data from extensive field studies. Our methodological solutions can be applied to various radar systems, including widely used ship radar. The procedure presented involves discriminating the echoes of birds and insects and estimating the different detection probabilities of differently 'sized' birds (radar cross-sections). By ignoring the different detection probabilities, density estimations may be wrong by as much as 400%. We fear that quantification of bird migration and predicted bird numbers affected by collisions with artificial structures are in many cases based on unreliable estimates.     

Should I Stay or Should I Go? A Habitat-Dependent Dispersal Kernel Improves Prediction of Movement

The analysis of animal movement within different landscapes may increase our understanding of how landscape features affect the perceptual range of animals. Perceptual range is linked to movement probability of an animal via a dispersal kernel, the latter being generally considered as spatially invariant but could be spatially affected. We hypothesize that spatial plasticity of an animal''s dispersal kernel could greatly modify its distribution in time and space. After radio tracking the movements of walking insects (Cosmopolites sordidus) in banana plantations, we considered the movements of individuals as states of a Markov chain whose transition probabilities depended on the habitat characteristics of current and target locations. Combining a likelihood procedure and pattern-oriented modelling, we tested the hypothesis that dispersal kernel depended on habitat features. Our results were consistent with the concept that animal dispersal kernel depends on habitat features. Recognizing the plasticity of animal movement probabilities will provide insight into landscape-level ecological processes.     

Dynamic occupancy models for analyzing species' range dynamics across large geographic scales

Large‐scale biodiversity data are needed to predict species' responses to global change and to address basic questions in macroecology. While such data are increasingly becoming available, their analysis is challenging because of the typically large heterogeneity in spatial sampling intensity and the need to account for observation processes. Two further challenges are accounting for spatial effects that are not explained by covariates, and drawing inference on dynamics at these large spatial scales. We developed dynamic occupancy models to analyze large‐scale atlas data. In addition to occupancy, these models estimate local colonization and persistence probabilities. We accounted for spatial autocorrelation using conditional autoregressive models and autologistic models. We fitted the models to detection/nondetection data collected on a quarter‐degree grid across southern Africa during two atlas projects, using the hadeda ibis (Bostrychia hagedash) as an example. The model accurately reproduced the range expansion between the first (SABAP1: 1987–1992) and second (SABAP2: 2007–2012) Southern African Bird Atlas Project into the drier parts of interior South Africa. Grid cells occupied during SABAP1 generally remained occupied, but colonization of unoccupied grid cells was strongly dependent on the number of occupied grid cells in the neighborhood. The detection probability strongly varied across space due to variation in effort, observer identity, seasonality, and unexplained spatial effects. We present a flexible hierarchical approach for analyzing grid‐based atlas data using dynamical occupancy models. Our model is similar to a species' distribution model obtained using generalized additive models but has a number of advantages. Our model accounts for the heterogeneous sampling process, spatial correlation, and perhaps most importantly, allows us to examine dynamic aspects of species ranges.     

Does the presence of an observer affect a bird's occurrence rate or singing rate during a point count?

The approach or presence of an observer may affect the behavior of nearby birds, rendering them either more or less detectable than when no observer is present due to a change in singing rates. To test whether there are systematic detection biases associated with the presence of an observer during point count bird surveys, we compared the occurrence and singing rates of birds during a 10-min period immediately preceding the time when an observer arrived to conduct a count and during the formal count itself by extracting song information from autonomous sound recorders. We obtained recordings of 36 species of birds detected at ≥5 locations in one of three vegetation types, including burned conifer forest, green conifer/riparian streamside forest, and riparian bottomland/marshland. We found that species richness and both the probability of occurrence and singing rate for any of the species recorded were unaffected by the presence of an observer. In addition, the probability of occurrence did not differ significantly among four 2.5-min recording sessions during 10-min counts when an observer was present. Thus, the presence of an observer did not appear to introduce any detectable systematic bias that would make bird lists or unadjusted occurrence rates inaccurate on that basis alone. In addition, rates of bird occurrence across 2.5-min temporal subsets of a 10-min count did not vary in a systematic way that would violate the assumption of equal occupancy across adjacent time periods as sometimes used to build detection histories in occupancy modeling.     

Spatial dynamics of an invasive bird species assessed using robust design occupancy analysis: the case of the Eurasian collared dove (Streptopelia decaocto) in France

Aim The study of the spatial dynamics of invasive species is a key issue in invasion ecology. While mathematical models are useful for predicting the extent of population expansions, they are not suitable for measuring and characterizing spatial patterns of invasion unless the probability of detection is homogeneous across the distribution range. Here, we apply recently developed statistical approaches incorporating detection uncertainty to characterize the spatial dynamics of an invasive bird species, the Eurasian collared dove (Streptopelia decaocto). Location France. Methods Data on presence/absence of doves were recorded from 1996 to 2004 over 1045 grid cells (28 × 20 km) covering the entire country. Each grid cell included five point counts spaced along a route, which was visited twice a year, allowing for an estimation of detection probability. Each route was assigned to one of six geographical regions. We used robust design occupancy analysis to assess spatial and temporal variation in parameters related to the spatial dynamics of the species. These parameters included occupancy rate, colonization and local extinction probabilities. Our inference approach was based on the selection of the most parsimonious model among competitive models parametrized with conditional probabilities. Results The probability of detecting the presence of doves on a given route was high. However, we found evidence to incorporate detection uncertainty in inference processes about spatial dynamics, since detection probability was neither perfect (i.e. it was < 1), nor constant over space and time. Results showed a clear positive trend in occupancy rate over the study period, increasing from 55% in 1996 to 76% in 2004. In addition, occupancy rate differed among regions (range: 37–79%) and further analysis showed that colonization probability by region was positively related to occupancy rate. Finally, local extinction probability was lower than colonization probability and showed a tendency to decrease over the study period. Main conclusions Our results emphasize the importance of estimating detection probabilities in order to draw proper inferences about the spatial and temporal dynamics of the invasion pattern of the collared dove. In contrast to the perceived spatial dynamics from national atlas surveys, we provide evidence that the range of this species is currently increasing in France. Other results, such as regional specificity in colonization probabilities and time variation in local extinction are consistent with expectations from invasion and metapopulation theory.     

Spatial variation in age-specific probabilities of first reproduction for Weddell seals

Spatial variation in vital rates can affect the dynamics and persistence of a population. We evaluated the prediction that age-specific probabilities of survival and first reproduction for Weddell seals would vary as a function of birth location in Erebus Bay, Antarctica. We used multi-state mark–resight models and 25 years of data to estimate demographic rates for female seals. We predicted that probabilities of survival and first reproduction would be higher for seals born at near-shore colonies or more southerly-located colonies with consistent ice conditions. Contrary to predictions, results revealed higher age-specific probabilities of first reproduction at offshore colonies relative to near-shore colonies and no spatial variation in survival rates. For 7-year old females (average age at 1st reproduction=7.6 years old) born at offshore colonies to mothers aged 10.8 years (average maternal age), probability of first reproduction was 0.43 (SE=0.07), whereas probability of first reproduction for females born at near-shore colonies was 0.30 (SE=0.05) based on estimates from our top-ranked model. Breeding probabilities following first reproduction were also higher at offshore colonies. Thus, our results (1) provide evidence of spatial variation in breeding probabilities, (2) reveal the importance of birth location on a female's vital rates, and (3) suggest that the effect persisted for many years. Birth-colony effects may be attributed to spatial variation in prey availability, or to heterogeneity in female quality in this population. If females who are superior competitors consistently chose offshore colonies for pupping, pups born at these locations may have inherited those superior qualities and displayed higher probabilities of first reproduction, relative to seals born at other colonies. Further research into physical or food-related differences among colonies may offer insight into spatial variation in breeding probabilities documented in this paper.     

Bayesian image restoration models for combining expert knowledge on recording activity with species distribution data

Biological atlases are, for many species, the only source of information on their distribution over large geographical areas, and are widely used to inform models of the environmental distribution of species. Such data are not collected using standardized survey techniques, however, and spatial variations in coverage (the relative extent or completeness of records) may lead to variations in the probability that the species will be recorded at locations where it is present (the “recording probability”). If spatial patterns in recording probabilities are correlated with key environmental variables, then biased estimates of the relationships between environmental variables and species distributions may be obtained. We outline a general statistical framework for modelling the environmental distribution of species using, known as Bayesian Image Restoration (BIR). BIR can be used in combination with any species distribution model, but in addition allows us to account for spatial heterogeneity in recording probabilities by utilizing expert knowledge on spatial patterns in coverage. We illustrate the methodology by applying it to maps of the recorded distribution of two plant species in Germany, taken from the German atlas of vascular plants. We find that estimated spatial patterns in recording probabilities for both species are correlated with key environmental variables. Consequently, different relationships between the probability of presence of a species and environmental variables were obtained when the species distribution models were parameterised within a BIR framework. Care must be taken in the application of BIR, since the resulting inferences can depend strongly upon the modelling assumptions that are adopted. Nevertheless, we conclude that BIR has the potential to make better use of uncertain information on species distributions than conventional methods, and can be used to formally investigate the robustness of inferences on the environmental distribution of species to assumptions concerning spatial patterns in recording probabilities.     

Mapping from heterogeneous biodiversity monitoring data sources

Field monitoring can vary from simple volunteer opportunistic observations to professional standardised monitoring surveys, leading to a trade-off between data quality and data collection costs. Such variability in data quality may result in biased predictions obtained from species distribution models (SDMs). We aimed to identify the limitations of different monitoring data sources for developing species distribution maps and to evaluate their potential for spatial data integration in a conservation context. Using Maxent, SDMs were generated from three different bird data sources in Catalonia, which differ in the degree of standardisation and available sample size. In addition, an alternative approach for modelling species distributions was applied, which combined the three data sources at a large spatial scale, but then downscaling to the required resolution. Finally, SDM predictions were used to identify species richness and high quality areas (hotspots) from different treatments. Models were evaluated by using high quality Atlas information. We show that both sample size and survey methodology used to collect the data are important in delivering robust information on species distributions. Models based on standardized monitoring provided higher accuracy with a lower sample size, especially when modelling common species. Accuracy of models from opportunistic observations substantially increased when modelling uncommon species, giving similar accuracy to a more standardized survey. Although downscaling data through a SDM approach appears to be a useful tool in cases of data shortage or low data quality and heterogeneity, it will tend to overestimate species distributions. In order to identify distributions of species, data with different quality may be appropriate. However, to identify biodiversity hotspots high quality information is needed.     

Do birds of a feather disperse plants together?

1. Dispersal of propagules by waterbirds is thought to be important for wetland plants because of the abundance of birds and their frequent movements among aquatic habitats. Differences in bird characteristics (size, movement, feeding ecology) were expected to lead to different outcomes for plant dispersal. 2. We investigated heterogeneity in plant dispersal by ducks (Anas superciliosa, Anas gracilis, Anas castanea). We calculated the probability of transport of viable seeds by germinating propagules retrieved from feathers and feet (epizoochory) and the contents of the oesophagus, gizzard and lower gut (endozoochory). 3. The abundance and richness of seeds carried internally and externally did not differ among sympatric bird species. We used estimates from the literature of movements of Anas species to approximate dispersal kernels for the transport of plant propagules. 4. Heterogeneity in the abundance and movement ecology of disperser species will result in differing patterns and degrees of connectivity for wetland plant metacommunities. Sedentary waterfowl are likely to have an important role in replenishing propagules and connecting aquatic metacommunities over small distances. Nomadic waterfowl may facilitate long‐distance dispersal. We discuss the implications of differences between duck species in movement patterns for connectivity of aquatic plant metacommunities across landscapes.     

101 Exploring the 3D spatial organization of the genome

Knowledge about the 3D organization of the genome will offer great insights into how cells retrieve and process the genetic information. Knowing the spatial probability distributions of individual genes will provide insights into gene regulatory and replication processes, and fill in the missing links between epigenomics, functional genomics, and structural biology. We will discuss an approach to determine 3D genome structures and structure–function maps of genomes by integrating divers types of data. To address the challenge of modeling highly variable genome structures, we discuss a population-based modeling approach, where we construct a large population of 3D genome structures that together are entirely consistent with all available experimental data including data from genome-wide chromosome conformation capture and imaging experiments. We interpret the result in terms of probabilities of a sample drawn from a population of heterogeneous structures. We will discuss results on the 3D spatial organization of genomes in human lymphoblastoid cells and budding yeast.     

Lek fidelity and movement among leks by male Greater Sage‐grouse Centrocercus urophasianus: a capture‐mark‐recapture approach

Males in lek mating systems tend to exhibit high fidelity to breeding leks despite substantial evidence of skewed mating success among males. Although movements between leks are often reported to be rare, such movements provide a mechanism for an individual to improve lifetime fitness in response to heterogeneity in reproductive conditions. Additionally, estimates of apparent movements among leks are potentially biased due to unaccounted variation in detection probability across time and space. We monitored breeding male Greater Sage‐grouse Centrocercus urophasianus on 13 leks in eastern Nevada over a 10‐year period, and estimated movement rates among leks using capture‐mark‐recapture methods. We expected that male movement rates among leks would be low, despite predictions of low breeding success for most males, and that detection rates would be highly variable among leks and years. We used a robust design multistate analysis in Program mark to estimate probability of movements among leks, while accounting for imperfect detection of males. Male Sage‐grouse were extremely faithful to their leks; the annual probability of a male moving away from its original lek of capture was approximately 3% (se = 0.01). Detection probabilities varied substantially among leks (range = 0.21–0.95), and among years (range = 0.30–0.76), but remained relatively constant within years at each lek. These results suggest that male Sage‐grouse dispersal is either rare, or consists primarily of dispersal of sub‐adults from their natal areas prior to the breeding season. The study highlights the benefits of robust design multistate models over standard ‘live‐encounter’ analyses, as they not only permit estimation of additional parameters, such as movement rates, but also allow for more precise parameter estimates that are less sensitive to heterogeneity in detection rates. Additionally, as these data were collected using capture‐mark‐recapture methods, our approach to estimating movement rates would be beneficial in systems where radiotagging is detrimental to the study organism.