An open spatial capture–recapture model for estimating density,movement, and population dynamics from line‐transect surveys

The purpose of many wildlife population studies is to estimate density, movement, or demographic parameters. Linking these parameters to covariates, such as habitat features, provides additional ecological insight and can be used to make predictions for management purposes. Line‐transect surveys, combined with distance sampling methods, are often used to estimate density at discrete points in time, whereas capture–recapture methods are used to estimate movement and other demographic parameters. Recently, open population spatial capture–recapture models have been developed, which simultaneously estimate density and demographic parameters, but have been made available only for data collected from a fixed array of detectors and have not incorporated the effects of habitat covariates. We developed a spatial capture–recapture model that can be applied to line‐transect survey data by modeling detection probability in a manner analogous to distance sampling. We extend this model to a) estimate demographic parameters using an open population framework and b) model variation in density and space use as a function of habitat covariates. The model is illustrated using simulated data and aerial line‐transect survey data for North Atlantic right whales in the southeastern United States, which also demonstrates the ability to integrate data from multiple survey platforms and accommodate differences between strata or demographic groups. When individuals detected from line‐transect surveys can be uniquely identified, our model can be used to simultaneously make inference on factors that influence spatial and temporal variation in density, movement, and population dynamics.     

Spatial capture–recapture with random thinning for unidentified encounters

1. Spatial capture–recapture (SCR) models have increasingly been used as a basis for combining capture–recapture data types with variable levels of individual identity information to estimate population density and other demographic parameters. Recent examples are the unmarked SCR (or spatial count model), where no individual identities are available and spatial mark–resight (SMR) where individual identities are available for only a marked subset of the population. Currently lacking, though, is a model that allows unidentified samples to be combined with identified samples when there are no separate classes of “marked” and “unmarked” individuals and when the two sample types cannot be considered as arising from two independent observation models. This is a common scenario when using noninvasive sampling methods, for example, when analyzing data on identified and unidentified photographs or scats from the same sites.
2. Here we describe a “random thinning” SCR model that utilizes encounters of both known and unknown identity samples using a natural mechanistic dependence between samples arising from a single observation model. Our model was fitted in a Bayesian framework using NIMBLE.
3. We investigate the improvement in parameter estimates by including the unknown identity samples, which was notable (up to 79% more precise) in low‐density populations with a low rate of identified encounters. We then applied the random thinning SCR model to a noninvasive genetic sampling study of brown bear (Ursus arctos) density in Oriental Cantabrian Mountains (North Spain).
4. Our model can improve density estimation for noninvasive sampling studies for low‐density populations with low rates of individual identification, by making use of available data that might otherwise be discarded.

     

Survival and abundance of polar bears in Alaska’s Beaufort Sea, 2001–2016

The Arctic Ocean is undergoing rapid transformation toward a seasonally ice‐free ecosystem. As ice‐adapted apex predators, polar bears (Ursus maritimus) are challenged to cope with ongoing habitat degradation and changes in their prey base driven by food‐web response to climate warming. Knowledge of polar bear response to environmental change is necessary to understand ecosystem dynamics and inform conservation decisions. In the southern Beaufort Sea (SBS) of Alaska and western Canada, sea ice extent has declined since satellite observations began in 1979 and available evidence suggests that the carrying capacity of the SBS for polar bears has trended lower for nearly two decades. In this study, we investigated the population dynamics of polar bears in Alaska''s SBS from 2001 to 2016 using a multistate Cormack–Jolly–Seber mark–recapture model. States were defined as geographic regions, and we used location data from mark–recapture observations and satellite‐telemetered bears to model transitions between states and thereby explain heterogeneity in recapture probabilities. Our results corroborate prior findings that the SBS subpopulation experienced low survival from 2003 to 2006. Survival improved modestly from 2006 to 2008 and afterward rebounded to comparatively high levels for the remainder of the study, except in 2012. Abundance moved in concert with survival throughout the study period, declining substantially from 2003 and 2006 and afterward fluctuating with lower variation around an average of 565 bears (95% Bayesian credible interval [340, 920]) through 2015. Even though abundance was comparatively stable and without sustained trend from 2006 to 2015, polar bears in the Alaska SBS were less abundant over that period than at any time since passage of the U.S. Marine Mammal Protection Act. The potential for recovery is likely limited by the degree of habitat degradation the subpopulation has experienced, and future reductions in carrying capacity are expected given current projections for continued climate warming.     

Factors associated with black bear density and implications for management

Wildlife density estimates are important to accurately formulate population management objectives and understand the relationship between habitat characteristics and a species’ abundance. Despite advances in density and abundance estimation methods, management of common game species continues to be challenged by a lack of reliable population estimates. In Washington, USA, statewide American black bear (Ursus americanus) abundance estimates are predicated on density estimates derived from research in the 1970s and are hypothesized to be a function of precipitation and vegetation, with higher densities in western Washington. To evaluate current black bear density and landscape relationships in Washington, we conducted a 4-year capture-recapture study in 2 areas of the North Cascade Mountains using 2 detection methods, non-invasive DNA collection and physical capture and deployment of global positioning system (GPS) collars. We integrated GPS telemetry from collared bears with spatial capture-recapture (SCR) data and created a SCR-resource selection model to estimate density as a function of spatial covariates and test the hypothesis that density is higher in areas with greater vegetative food resources. We captured and collared 118 bears 132 times and collected 7,863 hair samples at hair traps where we identified 537 bears from 1,237 detections via DNA. The most-supported model in the western North Cascades depicted a negative relationship between black bear density and an index of human development. We estimated bear density at 20.1 bears/100 km², but density varied from 13.5/100 km² to 27.8 bears/100 km² depending on degree of human development. The model best supported by the data in the eastern North Cascades estimated an average density of 19.2 bears/100 km², which was positively correlated with primary productivity, with resulting density estimates ranging from 7.1/100 km² to 33.6 bears/100 km². The hypothesis that greater precipitation and associated vegetative production in western Washington supports greater bear density compared to eastern Washington was not supported by our data. In western Washington, empirically derived average density estimates (including cubs) were nearly 50% lower than managers expected prior to our research. In eastern Washington average black bear density was predominantly as expected, but localized areas of high primary productivity supported greater than anticipated bear densities. Our findings underscore the importance that black bear density is not likely uniform and management risk may be increased if an average density is applied at too large a scale. Disparities between expected and empirically derived bear density illustrate the need for more rigorous monitoring to understand processes that affect population numbers throughout the jurisdiction, and suggest that management plans may need to be reevaluated to determine if current harvest strategies are achieving population objectives. © 2019 The Wildlife Society.     

Estimating preharvest density,adult sex ratio,and fecundity of white‐tailed deer using noninvasive sampling techniques

Adult sex ratio and fecundity (juveniles per female) are key population parameters in sustainable wildlife management, but inferring these requires abundance estimates of at least three age/sex classes of the population (male and female adults and juveniles). Prior to harvest, we used an array of 36 wildlife camera traps during 2 and 3 weeks in the early autumn of 2016 and 2017, respectively. We recorded white‐tailed deer adult males, adult females, and fawns from the pictures. Simultaneously, we collected fecal DNA (fDNA) from 92 20 m × 20 m plots placed in 23 clusters of four plots between the camera traps. We identified individuals from fDNA samples with microsatellite markers and estimated the total sex ratio and population density using spatial capture–recapture (SCR). The fDNA‐SCR analysis concluded equal sex ratio in the first year and female bias in the second year, and no difference in space use between sexes (fawns and adults combined). Camera information was analyzed in a spatial capture (SC) framework assuming an informative prior for animals’ space use, either (a) as estimated by fDNA‐SCR (same for all age/sex classes), (b) as assumed from the literature (space use of adult males larger than adult females and fawns), or (c) by inferring adult male space use from individually identified males from the camera pictures. These various SC approaches produced plausible inferences on fecundity, but also inferred total density to be lower than the estimate provided by fDNA‐SCR in one of the study years. SC approaches where adult male and female were allowed to differ in their space use suggested the population had a female‐biased adult sex ratio. In conclusion, SC approaches allowed estimating the preharvest population parameters of interest and provided conservative density estimates.     

Integrating sign surveys and telemetry data for estimating brown bear (Ursus arctos) density in the Romanian Carpathians

Accurate population size estimates are important information for sustainable wildlife management. The Romanian Carpathians harbor the largest brown bear (Ursus arctos) population in Europe, yet current management relies on estimates of density that lack statistical oversight and ignore uncertainty deriving from track surveys. In this study, we investigate an alternative approach to estimate brown bear density using sign surveys along transects within a novel integration of occupancy models and home range methods. We performed repeated surveys along 2‐km segments of forest roads during three distinct seasons: spring 2011, fall‐winter 2011, and spring 2012, within three game management units and a Natura 2000 site. We estimated bears abundances along transects using the number of unique tracks observed per survey occasion via N‐mixture hierarchical models, which account for imperfect detection. To obtain brown bear densities, we combined these abundances with the effective sampling area of the transects, that is, estimated as a function of the median (± bootstrapped SE) of the core home range (5.58 ± 1.08 km²) based on telemetry data from 17 bears tracked for 1‐month periods overlapping our surveys windows. Our analyses yielded average brown bear densities (and 95% confidence intervals) for the three seasons of: 11.5 (7.8–15.3), 11.3 (7.4–15.2), and 12.4 (8.6–16.3) individuals/100 km². Across game management units, mean densities ranged between 7.5 and 14.8 individuals/100 km². Our method incorporates multiple sources of uncertainty (e.g., effective sampling area, imperfect detection) to estimate brown bear density, but the inference fundamentally relies on unmarked individuals only. While useful as a temporary approach to monitor brown bears, we urge implementing DNA capture–recapture methods regionally to inform brown bear management and recommend increasing resources for GPS collars to improve estimates of effective sampling area.     

Habitat selection by vulnerable golden bandicoots in the arid zone

In 2010, vulnerable golden bandicoots (Isoodon auratus) were translocated from Barrow Island, Western Australia, to a mainland predator‐free enclosure on the Matuwa Indigenous Protected Area. Golden bandicoots were once widespread throughout a variety of arid and semiarid habitats of central and northern Australia. Like many small‐to‐medium‐sized marsupials, the species has severely declined since colonization and has been reduced to only four remnant natural populations. Between 2010 and 2020, the reintroduced population of golden bandicoots on Matuwa was monitored via capture–mark–recapture data collection, which was used in spatially explicit capture–recapture analysis to monitor their abundance over time. In 2014, we used VHF transmitters to examine the home range and habitat selection of 20 golden bandicoots in the enclosure over a six‐week period. We used compositional analysis to compare the use of four habitat types. Golden bandicoot abundance in the enclosure slowly increased between 2010 and 2014 and has since plateaued at approximately one quarter of the density observed in the founding population on Barrow Island. The population may have plateaued because some bandicoots escape through the fence. Golden bandicoots used habitats dominated by scattered shrubland with spinifex grass more than expected given the habitat''s availability. Nocturnal foraging range was influenced by sex and trapping location, whereas diurnal refuge habitat, which was typically under a spinifex hummock with minimal overstory vegetation, was consistent across sex and trapping location. Our work suggests that diurnal refuge habitat may be an important factor for the success of proposed translocations of golden bandicoots.     

Incorporating capture heterogeneity in the estimation of autoregressive coefficients of animal population dynamics using capture–recapture data

Population dynamic models combine density dependence and environmental effects. Ignoring sampling uncertainty might lead to biased estimation of the strength of density dependence. This is typically addressed using state‐space model approaches, which integrate sampling error and population process estimates. Such models seldom include an explicit link between the sampling procedures and the true abundance, which is common in capture–recapture settings. However, many of the models proposed to estimate abundance in the presence of capture heterogeneity lead to incomplete likelihood functions and cannot be straightforwardly included in state‐space models. We assessed the importance of estimating sampling error explicitly by taking an intermediate approach between ignoring uncertainty in abundance estimates and fully specified state‐space models for density‐dependence estimation based on autoregressive processes. First, we estimated individual capture probabilities based on a heterogeneity model for a closed population, using a conditional multinomial likelihood, followed by a Horvitz–Thompson estimate for abundance. Second, we estimated coefficients of autoregressive models for the log abundance. Inference was performed using the methodology of integrated nested Laplace approximation (INLA). We performed an extensive simulation study to compare our approach with estimates disregarding capture history information, and using R‐package VGAM, for different parameter specifications. The methods were then applied to a real data set of gray‐sided voles Myodes rufocanus from Northern Norway. We found that density‐dependence estimation was improved when explicitly modeling sampling error in scenarios with low process variances, in which differences in coverage reached up to 8% in estimating the coefficients of the autoregressive processes. In this case, the bias also increased assuming a Poisson distribution in the observational model. For high process variances, the differences between methods were small and it appeared less important to model heterogeneity.     

Integrating high‐speed videos in capture‐mark‐recapture studies of insects

Capture–mark–recapture (CMR) studies have been used extensively in ecology and evolution. While it is feasible to apply CMR in some animals, it is considerably more challenging in small fast‐moving species such as insects. In these groups, low recapture rates can bias estimates of demographic parameters, thereby handicapping effective analysis and management of wild populations. Here, we use high‐speed videos (HSV) to capture two large dragonfly species, Anax junius and Rhionaeschna multicolor, that rarely land and, thus, are particularly challenging for CMR studies. We test whether HSV, compared to conventional “eye” observations, increases the “resighting” rates and, consequently, improves estimates of both survival rates and the effects of demographic covariates on survival. We show that the use of HSV increases the number of resights by 64% in A. junius and 48% in R. multicolor. HSV improved our estimates of resighting and survival probability which were either under‐ or overestimated with the conventional observations. Including HSV improved credible intervals for resighting rate and survival probability by 190% and 130% in A. junius and R. multicolor, respectively. Hence, it has the potential to open the door to a wide range of research possibilities on species that are traditionally difficult to monitor with distance sampling, including within insects and birds.     

Evaluating otter reintroduction outcomes using genetic spatial capture–recapture modified for dendritic networks

Monitoring the demographics and genetics of reintroduced populations is critical to evaluating reintroduction success, but species ecology and the landscapes that they inhabit often present challenges for accurate assessments. If suitable habitats are restricted to hierarchical dendritic networks, such as river systems, animal movements are typically constrained and may violate assumptions of methods commonly used to estimate demographic parameters. Using genetic detection data collected via fecal sampling at latrines, we demonstrate applicability of the spatial capture–recapture (SCR) network distance function for estimating the size and density of a recently reintroduced North American river otter (Lontra canadensis) population in the Upper Rio Grande River dendritic network in the southwestern United States, and we also evaluated the genetic outcomes of using a small founder group (n = 33 otters) for reintroduction. Estimated population density was 0.23–0.28 otter/km, or 1 otter/3.57–4.35 km, with weak evidence of density increasing with northerly latitude (β = 0.33). Estimated population size was 83–104 total otters in 359 km of riverine dendritic network, which corresponded to average annual exponential population growth of 1.12–1.15/year since reintroduction. Growth was ≥40% lower than most reintroduced river otter populations and strong evidence of a founder effect existed 8–10 years post‐reintroduction, including 13–21% genetic diversity loss, 84%–87% genetic effective population size decline, and rapid divergence from the source population (F _ST accumulation = 0.06/generation). Consequently, genetic restoration via translocation of additional otters from other populations may be necessary to mitigate deleterious genetic effects in this small, isolated population. Combined with non‐invasive genetic sampling, the SCR network distance approach is likely widely applicable to demogenetic assessments of both reintroduced and established populations of multiple mustelid species that inhabit aquatic dendritic networks, many of which are regionally or globally imperiled and may warrant reintroduction or augmentation efforts.     

Estimating abundance with sparse data: tigers in northern Myanmar

As part of a national strategy for recovering tiger populations, the Myanmar Government recently proposed its first and the world’s largest tiger reserve in the Hukaung Valley, Kachin State. During November 2002–June 2004, camera-traps were used to record tigers, identify individuals, and, using capture–recapture approaches, estimate density in the reserve. Despite extensive (203 trap locations, 275–558 km² sample plots) and intensive (>4,500 trap nights, 9 months of sampling) survey efforts, only 12 independent detections of six individual tigers were made across three study sites. Due to the sparse data, estimates of tiger abundance generated by Program CAPTURE could not be made for all survey sites. Other approaches to estimating density, based on numbers of tigers caught, or derived from borrowed estimates of detection probability, offer an alternative to capture–recapture analysis. Tiger densities fall in the range of 0.2–2.2 tigers/100 km², with 7–71 tigers inside a 3,250 km² area of prime tiger habitat, where efforts to protect tigers are currently focused. Tiger numbers might be stabilized if strict measures are taken to protect tigers and their prey from seasonal hunting and to suppress illegal trade in wildlife. Efforts to monitor abundance trends in the tiger population will be expensive given the difficulty with which tiger data can be obtained and the lack of available surrogate indices of tiger density. Monitoring occupancy patterns, the subject of a separate ongoing study, may be more efficient.     

Evaluating the potential biases in carnivore capture–recapture studies associated with the use of lure and varying density estimation techniques using photographic-sampling data of the Malagasy civet

Estimating density of elusive carnivores with capture–recapture analyses is increasingly common. However, providing unbiased and precise estimates is still a challenge due to uncertainties arising from the use of (1) bait or lure to attract animals to the detection device and (2) ad hoc boundary-strip methods to compensate for edge effects in area estimation. We used photographic-sampling data of the Malagasy civet Fossa fossana collected with and without lure to assess the effects of lure and to compare the use of four density estimators which varied in methods of area estimation. The use of lure did not affect permanent immigration or emigration, abundance and density estimation, maximum movement distances, or temporal activity patterns of Malagasy civets, but did provide more precise population estimates by increasing the number of recaptures. The spatially-explicit capture–recapture (SECR) model density estimates ±SE were the least precise as they incorporate spatial variation, but consistent with each other (Maximum likelihood-SECR = 1.38 ± 0.18, Bayesian-SECR = 1.24 ± 0.17 civets/km²), whereas estimates relying on boundary-strip methods to estimate effective trapping area did not incorporate spatial variation, varied greatly and were generally larger than SECR model estimates. Estimating carnivore density with ad hoc boundary-strip methods can lead to overestimation and/or increased uncertainty as they do not incorporate spatial variation. This may lead to inaction or poor management decisions which may jeopardize at-risk populations. In contrast, SECR models free researchers from making subjective decisions associated with boundary-strip methods and they estimate density directly, providing more comparable and valuable population estimates.     

Killer whale (Orcinus orca) population dynamics in response to a period of rapid ecosystem change in the eastern North Atlantic

This study investigates survival and abundance of killer whales (Orcinus orca) in Norway in 1988–2019 using capture–recapture models of photo‐identification data. We merged two datasets collected in a restricted fjord system in 1988–2008 (Period 1) with a third, collected after their preferred herring prey shifted its wintering grounds to more exposed coastal waters in 2012–2019 (Period 2), and investigated any differences between these two periods. The resulting dataset, spanning 32 years, comprised 3284 captures of 1236 whales, including 148 individuals seen in both periods. The best‐supported models of survival included the effects of sex and time period, and the presence of transients (whales seen only once). Period 2 had a much larger percentage of transients compared to Period 1 (mean = 30% vs. 5%) and the identification of two groups of whales with different residency patterns revealed heterogeneity in recapture probabilities. This caused estimates of survival rates to be biased downward (females: 0.955 ± 0.027 SE, males: 0.864 ± 0.038 SE) compared to Period 1 (females: 0.998 ± 0.002 SE, males: 0.985 ± 0.009 SE). Accounting for this heterogeneity resulted in estimates of apparent survival close to unity for regularly seen whales in Period 2. A robust design model for Period 2 further supported random temporary emigration at an estimated annual probability of 0.148 (± 0.095 SE). This same model estimated a peak in annual abundance in 2015 at 1061 individuals (95% CI 999–1127), compared to a maximum of 731 (95% CI 505–1059) previously estimated in Period 1, and dropped to 513 (95% CI 488–540) in 2018. Our results indicate variations in the proportion of killer whales present of an undefined population (or populations) in a larger geographical region. Killer whales have adjusted their distribution to shifts in key prey resources, indicating potential to adapt to rapidly changing marine ecosystems.     

Trap Array Configuration Influences Estimates and Precision of Black Bear Density and Abundance

Spatial capture-recapture (SCR) models have advanced our ability to estimate population density for wide ranging animals by explicitly incorporating individual movement. Though these models are more robust to various spatial sampling designs, few studies have empirically tested different large-scale trap configurations using SCR models. We investigated how extent of trap coverage and trap spacing affects precision and accuracy of SCR parameters, implementing models using the R package secr. We tested two trapping scenarios, one spatially extensive and one intensive, using black bear (Ursus americanus) DNA data from hair snare arrays in south-central Missouri, USA. We also examined the influence that adding a second, lower barbed-wire strand to snares had on quantity and spatial distribution of detections. We simulated trapping data to test bias in density estimates of each configuration under a range of density and detection parameter values. Field data showed that using multiple arrays with intensive snare coverage produced more detections of more individuals than extensive coverage. Consequently, density and detection parameters were more precise for the intensive design. Density was estimated as 1.7 bears per 100 km² and was 5.5 times greater than that under extensive sampling. Abundance was 279 (95% CI = 193–406) bears in the 16,812 km² study area. Excluding detections from the lower strand resulted in the loss of 35 detections, 14 unique bears, and the largest recorded movement between snares. All simulations showed low bias for density under both configurations. Results demonstrated that in low density populations with non-uniform distribution of population density, optimizing the tradeoff among snare spacing, coverage, and sample size is of critical importance to estimating parameters with high precision and accuracy. With limited resources, allocating available traps to multiple arrays with intensive trap spacing increased the amount of information needed to inform parameters with high precision.     

Modeling the demography of species providing extended parental care: A capture–recapture multievent model with a case study on polar bears (Ursus maritimus)

1. In species providing extended parental care, one or both parents care for altricial young over a period including more than one breeding season. We expect large parental investment and long‐term dependency within family units to cause high variability in life trajectories among individuals with complex consequences at the population level. So far, models for estimating demographic parameters in free‐ranging animal populations mostly ignore extended parental care, thereby limiting our understanding of its consequences on parents and offspring life histories.
2. We designed a capture–recapture multievent model for studying the demography of species providing extended parental care. It handles statistical multiple‐year dependency among individual demographic parameters grouped within family units, variable litter size, and uncertainty on the timing at offspring independence. It allows for the evaluation of trade‐offs among demographic parameters, the influence of past reproductive history on the caring parent''s survival status, breeding probability, and litter size probability, while accounting for imperfect detection of family units. We assess the model performance using simulated data and illustrate its use with a long‐term dataset collected on the Svalbard polar bears (Ursus maritimus).
3. Our model performed well in terms of bias and mean square error and in estimating demographic parameters in all simulated scenarios, both when offspring departure probability from the family unit occurred at a constant rate or varied during the field season depending on the date of capture. For the polar bear case study, we provide estimates of adult and dependent offspring survival rates, breeding probability, and litter size probability. Results showed that the outcome of the previous reproduction influenced breeding probability.
4. Overall, our results show the importance of accounting for i) the multiple‐year statistical dependency within family units, ii) uncertainty on the timing at offspring independence, and iii) past reproductive history of the caring parent. If ignored, estimates obtained for breeding probability, litter size, and survival can be biased. This is of interest in terms of conservation because species providing extended parental care are often long‐living mammals vulnerable or threatened with extinction.

     

Spatial variation in density of American black bears in northern Yellowstone National Park

The quality and availability of resources are known to influence spatial patterns of animal density. In Yellowstone National Park, relationships between the availability of resources and the distribution of grizzly bears (Ursus arctos) have been explored but have yet to be examined in American black bears (Ursus americanus). We conducted non-invasive genetic sampling during 2017–2018 (mid-May to mid-July) and applied spatially explicit capture-recapture models to estimate density of black bears and examine associations with landscape features. In both years, density estimates were higher in forested vegetation communities, which provide food resources and thermal and security cover preferred by black bears, compared with non-forested areas. In 2017, density also varied by sex, with female densities being higher than males. Based on our estimates, the northern range of Yellowstone National Park supports one of the highest densities of black bears (20 black bears/100 km²) in the northern Rocky Mountains (6–12 black bears/100 km² in other regions). Given these high densities, black bears could influence other wildlife populations more than previously thought, such as through displacement of sympatric predators from kills. Our study provides the first spatially explicit estimates of density for black bears within an ecosystem that contains the majority of North America's large mammal species. Our density estimates provide a baseline that can be used for future research and management decisions of black bears, including efforts to reduce human–bear conflicts.     

Abundance and Survival Rates of the Hawai’i Island Associated Spinner Dolphin (Stenella longirostris) Stock

Reliable population estimates are critical to implement effective management strategies. The Hawai’i Island spinner dolphin (Stenella longirostris) is a genetically distinct stock that displays a rigid daily behavioural pattern, foraging offshore at night and resting in sheltered bays during the day. Consequently, they are exposed to frequent human interactions and disturbance. We estimated population parameters of this spinner dolphin stock using a systematic sampling design and capture–recapture models. From September 2010 to August 2011, boat-based photo-identification surveys were undertaken monthly over 132 days (>1,150 hours of effort; >100,000 dorsal fin images) in the four main resting bays along the Kona Coast, Hawai’i Island. All images were graded according to photographic quality and distinctiveness. Over 32,000 images were included in the analyses, from which 607 distinctive individuals were catalogued and 214 were highly distinctive. Two independent estimates of the proportion of highly distinctive individuals in the population were not significantly different (p = 0.68). Individual heterogeneity and time variation in capture probabilities were strongly indicated for these data; therefore capture–recapture models allowing for these variations were used. The estimated annual apparent survival rate (product of true survival and permanent emigration) was 0.97 SE±0.05. Open and closed capture–recapture models for the highly distinctive individuals photographed at least once each month produced similar abundance estimates. An estimate of 221±4.3 SE highly distinctive spinner dolphins, resulted in a total abundance of 631±60.1 SE, (95% CI 524–761) spinner dolphins in the Hawai’i Island stock, which is lower than previous estimates. When this abundance estimate is considered alongside the rigid daily behavioural pattern, genetic distinctiveness, and the ease of human access to spinner dolphins in their preferred resting habitats, this Hawai’i Island stock is likely more vulnerable to negative impacts from human disturbance than previously believed.     

Increased growth rates of stream salamanders following forest harvesting

Timber harvesting can influence headwater streams by altering stream productivity, with cascading effects on the food web and predators within, including stream salamanders. Although studies have examined shifts in salamander occupancy or abundance following timber harvest, few examine sublethal effects such as changes in growth and demography. To examine the effect of upland harvesting on growth of the stream‐associated Ouachita dusky salamander (Desmognathus brimleyorum), we used capture–mark–recapture over three years at three headwater streams embedded in intensely managed pine forests in west‐central Arkansas. The pine stands surrounding two of the streams were harvested, with retention of a 14‐ and 21‐m‐wide forested stream buffer on each side of the stream, whereas the third stream was an unharvested control. At the two treatment sites, measurements of newly metamorphosed salamanders were on average 4.0 and 5.7 mm larger post‐harvest compared with pre‐harvest. We next assessed the influence of timber harvest on growth of post‐metamorphic salamanders with a hierarchical von Bertalanffy growth model that included an effect of harvest on growth rate. Using measurements from 839 individual D. brimleyorum recaptured between 1 and 6 times (total captures, n = 1229), we found growth rates to be 40% higher post‐harvest. Our study is among the first to examine responses of individual stream salamanders to timber harvesting, and we discuss mechanisms that may be responsible for observed shifts in growth. Our results suggest timber harvest that includes retention of a riparian buffer (i.e., streamside management zone) may have short‐term positive effects on juvenile stream salamander growth, potentially offsetting negative sublethal effects associated with harvest.     

Multiple coping strategies maintain stability of a small mammal population in a resource‐restricted environment

In semi‐arid environments, aperiodic rainfall pulses determine plant production and resource availability for higher trophic levels, creating strong bottom‐up regulation. The influence of climatic factors on population vital rates often shapes the dynamics of small mammal populations in such resource‐restricted environments. Using a 21‐year biannual capture–recapture dataset (1993 to 2014), we examined the impacts of climatic factors on the population dynamics of the brush mouse (Peromyscus boylii) in semi‐arid oak woodland of coastal‐central California. We applied Pradel''s temporal symmetry model to estimate capture probability (p), apparent survival (φ), recruitment (f), and realized population growth rate (λ) of the brush mouse and examined the effects of temperature, rainfall, and El Niño on these demographic parameters. The population was stable during the study period with a monthly realized population growth rate of 0.993 ± SE 0.032, but growth varied over time from 0.680 ± 0.054 to 1.450 ± 0.083. Monthly survival estimates averaged 0.789 ± 0.005 and monthly recruitment estimates averaged 0.175 ± 0.038. Survival probability and realized population growth rate were positively correlated with rainfall and negatively correlated with temperature. In contrast, recruitment was negatively correlated with rainfall and positively correlated with temperature. Brush mice maintained their population through multiple coping strategies, with high recruitment during warmer and drier periods and higher survival during cooler and wetter conditions. Although climatic change in coastal‐central California will likely favor recruitment over survival, varying strategies may serve as a mechanism by which brush mice maintain resilience in the face of climate change. Our results indicate that rainfall and temperature are both important drivers of brush mouse population dynamics and will play a significant role in predicting the future viability of brush mice under a changing climate.     

Genetic mark–recapture population estimation in black bears and issues of scale

Abundance estimates for black bears (Ursus americanus) are important for effective management. Recently, DNA technology has resulted in widespread use of noninvasive, genetic capture–mark–recapture (CMR) approaches to estimate populations. Few studies have compared the genetic CMR methods to other estimation methods. We used genetic CMR to estimate the bear population at 2 study sites in northern New Hampshire (Pittsburg and Milan) in 2 consecutive years. We compared these estimates to those derived from traditional methods used by the New Hampshire Fish and Game Department (NHFG) using hunter harvest and mortality data. Density estimates produced with genetic CMR methods were similar both years and were comparable to those derived from traditional methods. In 2006, the estimated number of bears in Pittsburg was 79 (95% CI = 60–98) corresponding to a density of 15–24 (95% CI) bears/100 km²; the 2007 estimate was 83 (95% CI = 67–99; density = 16–24 bears/100 km²). In 2006, the estimated number of bears in Milan was 95 (95% CI = 74–117; density = 16–25 bears/100 km²); the 2007 estimate was 96 (95% CI = 77–114; density = 17–25 bears/100 km²). We found that genetic CMR methods were able to identify demographic variation at a local scale, including a strongly skewed sex ratio (2 M:1 F) in the Milan population. Genetic CMR is a useful tool for wildlife managers to monitor populations of local concern, where abundance or demographic characteristics may deviate from regional estimates. Future monitoring of the Milan population with genetic CMR is recommended to determine if the sex ratio bias continues, possibly warranting a change in local harvest regimes. © 2011 The Wildlife Society.