Evaluating the effects of urbanisation on salamander abundances using a before‐after control‐impact design

1. Urbanisation represents a significant threat to semi‐aquatic amphibian populations, especially stream‐dwelling salamanders. Although studies of urbanisation effects on amphibians have been conducted, there is an urgent need to follow populations over longer time periods, account for imperfect detection and determine the response time to urbanisation. Consequently, we used a before‐after control‐impact (BACI) study design to estimate changes in abundances of larval and adult salamanders in streams affected by urbanisation. 2. From 2005 to 2009, we used standard sampling techniques to obtain a count of salamanders in 13 first‐order streams that underwent urbanisation of their catchments after the first year of sampling. Simultaneously, we counted salamanders in 17 streams that experienced no disturbance within stream catchments. Additionally, we measured environmental variables at each stream. 3. We used Royle’s binomial mixture model to estimate annual mean abundances and individual detection probabilities, and Bayesian inference was used to estimate population parameters for each stage and species. 4. Although mean abundance estimates varied among years in control and urbanised streams, we found that urbanisation had a negative effect on larval and adult salamander abundances. Larval salamander abundances at sites 1 year after urbanisation were significantly lower than abundances from control sites. Abundances of adult two‐lined salamanders (Eurycea cirrigera) at urbanised sites were lower than abundances at control sites 2 years post‐urbanisation, and adult dusky salamander (Desmognathus fuscus) abundances at urbanised sites were lower than abundances at control sites 3 years post‐urbanisation. Maximum conductivity, sedimentation level and maximum stream channel width differed between urban and non‐urban streams. 5. Our results suggest that stream‐dwelling salamanders exhibit little resistance to urbanisation. Our study also highlights the use of the BACI design to study how urbanisation affects populations in semi‐aquatic habitats. We emphasise that inferences regarding urbanisation effects on population response may be compromised unless urban populations are compared to populations in control sites, especially for species in which populations fluctuate.     

Improving Aquatic Warbler Population Assessments by Accounting for Imperfect Detection

Monitoring programs designed to assess changes in population size over time need to account for imperfect detection and provide estimates of precision around annual abundance estimates. Especially for species dependent on conservation management, robust monitoring is essential to evaluate the effectiveness of management. Many bird species of temperate grasslands depend on specific conservation management to maintain suitable breeding habitat. One such species is the Aquatic Warbler (Acrocephalus paludicola), which breeds in open fen mires in Central Europe. Aquatic Warbler populations have so far been assessed using a complete survey that aims to enumerate all singing males over a large area. Because this approach provides no estimate of precision and does not account for observation error, detecting moderate population changes is challenging. From 2011 to 2013 we trialled a new line transect sampling monitoring design in the Biebrza valley, Poland, to estimate abundance of singing male Aquatic Warblers. We surveyed Aquatic Warblers repeatedly along 50 randomly placed 1-km transects, and used binomial mixture models to estimate abundances per transect. The repeated line transect sampling required 150 observer days, and thus less effort than the traditional ‘full count’ approach (175 observer days). Aquatic Warbler abundance was highest at intermediate water levels, and detection probability varied between years and was influenced by vegetation height. A power analysis indicated that our line transect sampling design had a power of 68% to detect a 20% population change over 10 years, whereas raw count data had a 9% power to detect the same trend. Thus, by accounting for imperfect detection we increased the power to detect population changes. We recommend to adopt the repeated line transect sampling approach for monitoring Aquatic Warblers in Poland and in other important breeding areas to monitor changes in population size and the effects of habitat management.     

Combining band recovery data and Pollock's robust design to model temporary and permanent emigration

Capture-recapture models are widely used to estimate demographic parameters of marked populations. Recently, this statistical theory has been extended to modeling dispersal of open populations. Multistate models can be used to estimate movement probabilities among subdivided populations if multiple sites are sampled. Frequently, however, sampling is limited to a single site. Models described by Burnham (1993, in Marked Individuals in the Study of Bird Populations, 199-213), which combined open population capture-recapture and band-recovery models, can be used to estimate permanent emigration when sampling is limited to a single population. Similarly, Kendall, Nichols, and Hines (1997, Ecology 51, 563-578) developed models to estimate temporary emigration under Pollock's (1982, Journal of Wildlife Management 46, 757-760) robust design. We describe a likelihood-based approach to simultaneously estimate temporary and permanent emigration when sampling is limited to a single population. We use a sampling design that combines the robust design and recoveries of individuals obtained immediately following each sampling period. We present a general form for our model where temporary emigration is a first-order Markov process, and we discuss more restrictive models. We illustrate these models with analysis of data on marked Canvasback ducks. Our analysis indicates that probability of permanent emigration for adult female Canvasbacks was 0.193 (SE = 0.082) and that birds that were present at the study area in year i - 1 had a higher probability of presence in year i than birds that were not present in year i - 1.     

Use of the Robust Design to Estimate Seasonal Abundance and Demographic Parameters of a Coastal Bottlenose Dolphin (Tursiops aduncus) Population

As delphinid populations become increasingly exposed to human activities we rely on our capacity to produce accurate abundance estimates upon which to base management decisions. This study applied mark–recapture methods following the Robust Design to estimate abundance, demographic parameters, and temporary emigration rates of an Indo-Pacific bottlenose dolphin (Tursiops aduncus) population off Bunbury, Western Australia. Boat-based photo-identification surveys were conducted year-round over three consecutive years along pre-determined transect lines to create a consistent sampling effort throughout the study period and area. The best fitting capture–recapture model showed a population with a seasonal Markovian temporary emigration with time varying survival and capture probabilities. Abundance estimates were seasonally dependent with consistently lower numbers obtained during winter and higher during summer and autumn across the three-year study period. Specifically, abundance estimates for all adults and juveniles (combined) varied from a low of 63 (95% CI 59 to 73) in winter of 2007 to a high of 139 (95% CI 134 to148) in autumn of 2009. Temporary emigration rates (γ'') for animals absent in the previous period ranged from 0.34 to 0.97 (mean  =  0.54; ±SE 0.11) with a peak during spring. Temporary emigration rates for animals present during the previous period (γ'''') were lower, ranging from 0.00 to 0.29, with a mean of 0.16 (± SE 0.04). This model yielded a mean apparent survival estimate for juveniles and adults (combined) of 0.95 (± SE 0.02) and a capture probability from 0.07 to 0.51 with a mean of 0.30 (± SE 0.04). This study demonstrates the importance of incorporating temporary emigration to accurately estimate abundance of coastal delphinids. Temporary emigration rates were high in this study, despite the large area surveyed, indicating the challenges of sampling highly mobile animals which range over large spatial areas.     

Use of hidden Markov capture–recapture models to estimate abundance in the presence of uncertainty: Application to the estimation of prevalence of hybrids in animal populations

Estimating the relative abundance (prevalence) of different population segments is a key step in addressing fundamental research questions in ecology, evolution, and conservation. The raw percentage of individuals in the sample (naive prevalence) is generally used for this purpose, but it is likely to be subject to two main sources of bias. First, the detectability of individuals is ignored; second, classification errors may occur due to some inherent limits of the diagnostic methods. We developed a hidden Markov (also known as multievent) capture–recapture model to estimate prevalence in free‐ranging populations accounting for imperfect detectability and uncertainty in individual's classification. We carried out a simulation study to compare naive and model‐based estimates of prevalence and assess the performance of our model under different sampling scenarios. We then illustrate our method with a real‐world case study of estimating the prevalence of wolf (Canis lupus) and dog (Canis lupus familiaris) hybrids in a wolf population in northern Italy. We showed that the prevalence of hybrids could be estimated while accounting for both detectability and classification uncertainty. Model‐based prevalence consistently had better performance than naive prevalence in the presence of differential detectability and assignment probability and was unbiased for sampling scenarios with high detectability. We also showed that ignoring detectability and uncertainty in the wolf case study would lead to underestimating the prevalence of hybrids. Our results underline the importance of a model‐based approach to obtain unbiased estimates of prevalence of different population segments. Our model can be adapted to any taxa, and it can be used to estimate absolute abundance and prevalence in a variety of cases involving imperfect detection and uncertainty in classification of individuals (e.g., sex ratio, proportion of breeders, and prevalence of infected individuals).     

Are Private Reserves Effective for Jaguar Conservation?

We present the first study of density and apparent survival for a jaguar (Panthera onca) population in northern Mexico using 13 years of camera trap data from 2000 to 2012. We used the Barker robust design model which combines data from closed sampling periods and resight data between these periods to estimate apparent survival and abundance. We identified 467 jaguar pictures that corresponded to 48 jaguar individuals. We included camera type and field technician as covariates for detection probabilities. We used three covariates to evaluate the effect of reserve on jaguar apparent survival: i) private reserve creation ii) later reserve expansions, and iii) cattle ranches’ conservation activities. We found that the use of digital cameras in addition to film cameras increased detection probability by a factor of 6x compared with the use of only film cameras (p = 0.34 ± 0.05 and p = 0.05 ± 0.02 respectively) in the closed period and more than three times in the open period (R = 0.91 ± 0.08 and R = 0.30 ± 0.13 mixed and film cameras respectively). Our availability estimates showed no temporary emigration and a fidelity probability of 1. Despite an increase of apparent survival probability from 0.47 ± 0.15 to 0.56 ± 0.11 after 2007, no single covariate explained the change in these point estimates. Mean jaguar density was 1.87 ± 0.47 jaguars/100 km². We found that 13 years of jaguar population monitoring with our sampling size were not enough for detecting changes in survival or density. Our results provide a baseline for studies evaluating the effectiveness of protected areas and the inclusion of ranch owners in jaguar conservation programs and long-term population viability.     

Improving species occupancy estimation when sampling violates the closure assumption

Site occupancy models that account for imperfect detection of species are increasingly utilized in ecological research and wildlife monitoring. Occupancy models require replicate surveys to estimate detection probability over a time period where the occupancy status at sampled sites is assumed closed. Unlike mark–recapture models, few studies have examined how violations of closure can bias occupancy estimates. Our study design allowed us to differentiate among two processes that violate the closure assumption during a sampling season: 1) repeated destructive sampling events that result in either short‐ or long‐term site avoidance by the target species and 2) sampling occurring over a time period during which non‐random movements of the target species result in variable occupancy status. We used dynamic occupancy models to quantify the potential bias in occupancy estimation associated with these processes for a terrestrial salamander system. Our results provide strong evidence of a systematic decrease in salamander occupancy within a field season. Chronic disturbance due to repeated searches of natural cover objects accelerated natural declines in species occurrence on the forest surface as summer progressed. We also observed a strong but temporary disturbance effect on salamander detection probability associated with repeated sampling within a 24‐h. period. We generalized our findings by conducting a simulation to evaluate how violations of closure can bias occupancy estimates when local extinction occurs within a sampling season. Our simulation study revealed general sensitivity of estimates from single‐season occupancy models to violations of closure, with the strength and direction of bias varying between scenarios. Bias was minimal when extinction proba bility or the number of sample occasions was relatively low. Our research highlights the importance of addressing closure in occupancy studies and we provide multiple solutions, using both design‐ and model‐based frameworks, for minimizing bias associated with non‐random changes in occupancy and repeated sampling disturbances.     

Using time‐of‐detection to evaluate detectability assumptions in temporally replicated aural count indices: an example with Ring‐necked Pheasants

ABSTRACT The validity of treating counts as indices to abundance is based on the assumption that the expected detection probability, E(p), is constant over time or comparison groups or, more realistically, that variation in p is small relative to variation in population size that investigators seek to detect. Unfortunately, reliable estimates of E(p) and var(p) are lacking for most index methods. As a case study, we applied the time‐of‐detection method to temporally replicated (within season) aural counts of crowing male Ring‐necked Pheasants (Phasianus colchicus) at 18 sites in southern Minnesota in 2007 to evaluate the detectability assumptions. More specifically, we used the time‐of‐detection method to estimate E(p) and var(p), and then used these estimates in a Monte Carlo simulation to evaluate bias‐variance tradeoffs associated with adjusting count indices for imperfect detection. The estimated mean detection probability in our case study was 0.533 (SE = 0.030) and estimated spatial variation in E(p) was 0.081 (95% CI: 0.057–0.126). On average, both adjusted (for) and unadjusted counts of crowing males qualitatively described the simulated relationship between pheasant abundance and grassland abundance, but the bias‐variance tradeoff was smaller for adjusted counts (MSE = 0.003 vs. 0.045, respectively). Our case study supports the general recommendation to use, whenever feasible, formal population‐estimation procedures (e.g., mark‐recapture, distance sampling, double sampling) to account for imperfect detection. However, we caution that interpreting estimates of absolute abundance can be complicated, even if formal estimation methods are used. For example, the time‐of‐detection method was useful for evaluating detectability assumptions in our case study and the method could be used to adjust aural count indices for imperfect detection. Conversely, using the time‐of‐detection method to estimate absolute abundances in our case study was problematic because the biological populations and sampling coverage could not be clearly delineated. These estimation and inference challenges may also be important in other avian surveys that involve mobile species (whose home ranges may overlap several sampling sites), temporally replicated counts, and inexact sampling coverage.     

Ecological and methodological factors affecting detectability and population estimation in elusive species

Although mark-recapture methods are among the most powerful tools for monitoring wildlife populations, the secretive nature of some species requires a comprehensive understanding of the factors that affect capture probability to maximize accuracy and precision of population parameter estimates (e.g., population size and survivorship). Here, we used aquatic snakes as a case study in applying rigorous mark-recapture methods to estimate population parameters for secretive species. Specifically, we used intensive field sampling and robust design mark-recapture analyses in Program MARK to test specific hypotheses about ecological and methodological factors influencing detectability of two species of secretive aquatic snakes, the banded watersnake (Nerodia fasciata), and the black swamp snake (Seminatrix pygaea). We constructed a candidate set of a priori mark-recapture models incorporating various combinations of time- and sex-varying capture and recapture probabilities, behavioral responses to traps (i.e., trap-happiness or trap-shyness), and temporary emigration, and we ranked models for each species using Akaike's Information Criterion. For both banded watersnakes and black swamp snakes we found strong support for time-varying capture and recapture probabilities and strong trap-happy responses, factors that can bias population estimation if not accommodated in the models. We also found evidence of sex-dependent temporary emigration in black swamp snakes. Our study is among the first comprehensive assessments of factors affecting detectability in snakes and provides a framework for studies aimed at monitoring populations of other secretive species. © 2010 The Wildlife Society.     

Estimating survival of a streamside salamander: importance of temporary emigration,capture response,and location

Estimating survival for highly secretive aquatic animals, such as stream salamanders, presents numerous challenges. Salamanders often spend a considerable time in refugia where they are difficult to capture. Few studies have calculated vital rates for stream salamanders, yet the need is substantial as they are threatened by a wide range of land-use stressors, especially urban development. In this study, we used 34 months of continuous field samples collected at an urban and undisturbed stream and robust design mark-recapture analysis to evaluate the importance of temporary emigration, capture response, and location on survival estimates of the salamander Desmognathus fuscus. We constructed a set of candidate models incorporating combinations of time- and location-varying capture and recapture probabilities, capture responses, temporary emigration, and survival estimates and ranked models using Akaike’s Information Criterion. We found strong support for month-specific capture probabilities, recapture probabilities, temporary emigration and a negative behavioral response to capture in the majority of months. We found no support for variation in capture probabilities, recapture probabilities, and temporary emigration between locations. However, we found that location strongly influenced survival estimates. Specifically, survival estimates were significantly higher at the undisturbed site than at the urban site. Our results emphasize the importance of estimating capture probabilities, recapture probabilities, capture response, and temporary emigration when evaluating survival in highly secretive aquatic animals. Failure to account for these population parameters will likely yield biased estimates of survival in freshwater animal populations.     

Population Dynamics of the Critically Endangered Golden Lancehead Pitviper,Bothrops insularis: Stability or Decline?

Little is known about vital rates of snakes generally because of the difficulty in collecting data. Here we used a robust design mark-recapture model to estimate survival, behavioral effects on capture probability, temporary emigration, abundance and test the hypothesis of population decline in the golden lancehead pitviper, Bothrops insularis, an endemic and critically endangered species from southeastern Brazil. We collected data at irregular intervals over ten occasions from 2002 to 2010. Survival was slightly higher in the wet season than in the dry season. Temporal emigration was high, indicating the importance of accounting for this parameter both in the sampling design and modeling. No behavioral effects were detected on capture probability. We detected an average annual population decrease ( = 0.93, CI = 0.47–1.38) during the study period, but estimates included high uncertainty, and caution in interpretation is needed. We discuss the potential effects of the illegal removal of individuals and the implications of the vital rates obtained for the future persistence and conservation of this endemic, endangered species.     

Evaluating Multi-Level Models to Test Occupancy State Responses of Plethodontid Salamanders

Plethodontid salamanders are diverse and widely distributed taxa and play critical roles in ecosystem processes. Due to salamander use of structurally complex habitats, and because only a portion of a population is available for sampling, evaluation of sampling designs and estimators is critical to provide strong inference about Plethodontid ecology and responses to conservation and management activities. We conducted a simulation study to evaluate the effectiveness of multi-scale and hierarchical single-scale occupancy models in the context of a Before-After Control-Impact (BACI) experimental design with multiple levels of sampling. Also, we fit the hierarchical single-scale model to empirical data collected for Oregon slender and Ensatina salamanders across two years on 66 forest stands in the Cascade Range, Oregon, USA. All models were fit within a Bayesian framework. Estimator precision in both models improved with increasing numbers of primary and secondary sampling units, underscoring the potential gains accrued when adding secondary sampling units. Both models showed evidence of estimator bias at low detection probabilities and low sample sizes; this problem was particularly acute for the multi-scale model. Our results suggested that sufficient sample sizes at both the primary and secondary sampling levels could ameliorate this issue. Empirical data indicated Oregon slender salamander occupancy was associated strongly with the amount of coarse woody debris (posterior mean = 0.74; SD = 0.24); Ensatina occupancy was not associated with amount of coarse woody debris (posterior mean = -0.01; SD = 0.29). Our simulation results indicate that either model is suitable for use in an experimental study of Plethodontid salamanders provided that sample sizes are sufficiently large. However, hierarchical single-scale and multi-scale models describe different processes and estimate different parameters. As a result, we recommend careful consideration of study questions and objectives prior to sampling data and fitting models.     

Evaluation of three methods to estimate density and detectability from roadside point counts

Roadside point counts are often used to estimate trends of bird populations. The use of aural counts of birds without adjustment for detection probability, however, can lead to incorrect population trend estimates. We compared precision of estimates of density and detectability of whistling northern bobwhites (Colinus virginianus) using distance sampling, independent double-observer, and removal methods from roadside surveys. Two observers independently recorded each whistling bird heard, distance from the observer, and time of first detection at 362 call-count stops in Ohio. We examined models that included covariates for year and observer effects for each method and distance from observer effects for the double-observer and removal methods using Akaike's Information Criterion (AIC). The best model of detectability from distance sampling included observer and year effects. The best models from the removal and double-observer techniques included observer and distance effects. All 3 methods provided precise estimates of detection probability (CV = 2.4–4.4%) with a range of detectability of 0.44–0.95 for a 6-min survey. Density estimates from double-observer surveys had the lowest coefficient of variation (2005 = 3.2%, 2006 = 1.7%), but the removal method also provided precise estimates of density (2005 CV = 3.4%, 2006 CV = 4.8%), and density estimates from distance sampling were less precise (2005 CV = 9.6%, 2006 CV = 7.9%). Assumptions of distance sampling were violated in our study because probability of detecting bobwhites near the observer was <1 or the roadside survey points were not randomly distributed with respect to the birds. Distances also were not consistently recorded by individual members of observer pairs. Although double-observer surveys provided more precise estimates, we recommend using the removal method to estimate detectability and abundance of bobwhites. The removal method provided precise estimates of density and detection probability and requires half the personnel time as double-observer surveys. Furthermore, the likelihood of meeting model assumptions is higher for the removal survey than with independent double-observers. © 2011 The Wildlife Society.     

Site occupancy models with heterogeneous detection probabilities

Models for estimating the probability of occurrence of a species in the presence of imperfect detection are important in many ecological disciplines. In these "site occupancy" models, the possibility of heterogeneity in detection probabilities among sites must be considered because variation in abundance (and other factors) among sampled sites induces variation in detection probability (p). In this article, I develop occurrence probability models that allow for heterogeneous detection probabilities by considering several common classes of mixture distributions for p. For any mixing distribution, the likelihood has the general form of a zero-inflated binomial mixture for which inference based upon integrated likelihood is straightforward. A recent paper by Link demonstrates that in closed population models used for estimating population size, different classes of mixture distributions are indistinguishable from data, yet can produce very different inferences about population size. I demonstrate that this problem can also arise in models for estimating site occupancy in the presence of heterogeneous detection probabilities. The implications of this are discussed in the context of an application to avian survey data and the development of animal monitoring programs.     

Spatial variation in water loss predicts terrestrial salamander distribution and population dynamics

Many patterns observed in ecology, such as species richness, life history variation, habitat use, and distribution, have physiological underpinnings. For many ectothermic organisms, temperature relationships shape these patterns, but for terrestrial amphibians, water balance may supersede temperature as the most critical physiologically limiting factor. Many amphibian species have little resistance to water loss, which restricts them to moist microhabitats, and may significantly affect foraging, dispersal, and courtship. Using plaster models as surrogates for terrestrial plethodontid salamanders (Plethodon albagula), we measured water loss under ecologically relevant field conditions to estimate the duration of surface activity time across the landscape. Surface activity time was significantly affected by topography, solar exposure, canopy cover, maximum air temperature, and time since rain. Spatially, surface activity times were highest in ravine habitats and lowest on ridges. Surface activity time was a significant predictor of salamander abundance, as well as a predictor of successful recruitment; the probability of a juvenile salamander occupying an area with high surface activity time was two times greater than an area with limited predicted surface activity. Our results suggest that survival, recruitment, or both are demographic processes that are affected by water loss and the ability of salamanders to be surface-active. Results from our study extend our understanding of plethodontid salamander ecology, emphasize the limitations imposed by their unique physiology, and highlight the importance of water loss to spatial population dynamics. These findings are timely for understanding the effects that fluctuating temperature and moisture conditions predicted for future climates will have on plethodontid salamanders.     

Estimating Survival for Elusive Juvenile Pond-Breeding Salamanders

Juvenile vital rates have important effects on population dynamics for many species, but this demographic is often difficult to locate and track. As such, we frequently lack reliable estimates of juvenile survival, which are necessary for accurately assessing population stability and potential management approaches to conserve biodiversity. We estimated survival rates for elusive juveniles of 3 species, the ringed salamander (Ambystoma annulatum), spotted salamander (A. maculatum), and small-mouthed salamander (A. texanum), using 2 approaches. First, we conducted an 11-month (2016–2017) mark-recapture study within semi-natural enclosures and used Bayesian Cormack-Jolly-Seber models to estimate survival and recapture probabilities. Second, we inferred the expected annual juvenile survival rate given published vital rates for pre-metamorphic and adult ambystomatids assuming stable population growth. For all 3 species, juvenile survival probabilities were constant across recapture occasions, whereas recapture probability estimates were time-dependent. Further, survival and recapture probabilities among study species were similar. Post-study sampling revealed that the initial study period median estimate of annual survival probability (0.39) underestimated the number of salamanders known alive at 11 months. We therefore appended approximately 1 year of opportunistic data, which produced a median annual survival probability of 0.50, encompassing salamanders that we knew to have been alive. Calculation from literature values suggested a mean annual terrestrial juvenile ambystomatid survival probability of 0.49. Similar results among our approaches indicated that juvenile survival estimates for the study species were robust and likely comparable to rates in nature. These estimates can now be confidently applied to research, monitoring, and management efforts for the study species and ecologically similar taxa. Our findings indicated that similarly robust vital rate estimates for subsets of ecologically and phylogenetically similar species can provide reasonable surrogate demographic information that can be used to reveal key factors influencing population viability for data-deficient species. © 2020 The Wildlife Society.     

Occupancy models including local and landscape variables are useful to assess the distribution of a salamander species at risk

Numerous amphibian species are at risk of extinction worldwide. Therefore, reliable estimations of the distribution and abundance of these species are necessary for their conservation. Generally, amphibians are difficult to detect in the wild, which compromises the accuracy of long-term population monitoring and management. Occupancy models are useful tools to assess how environmental variables, at a local and at a landscape scale, affect the distribution and abundance of organisms taking into account species imperfect detectability. In this study, we evaluated with an environmental multiscale approach the seasonal variation of the occupation area of the threatened salamander, Ambystoma ordinarium along its distribution range. We obtained readings in 60 streams of physicochemical variables associated with habitat quality and landscape features. We found that detection and occupation probability of A. ordinarium are seasonally associated with different environmental variables. During the dry season, detectability was positively associated with temperature and stream depth, whereas occupancy was positively associated with the proportion of crops in the landscape and stream elevation. In the rainy season, the detection probability was not explained by any variable considered, and occupancy was negatively associated with stream's electrical conductivity and dissolved oxygen. Based on the estimation of occupied sites, we showed that A. ordinarium presents a more restricted distribution range than previously projected. Therefore, our results reveal the importance of evaluating the accuracy of distribution estimates for the conservation of threatened species as A. ordinarium.     

Accounting for imperfect detection of groups and individuals when estimating abundance

If animals are independently detected during surveys, many methods exist for estimating animal abundance despite detection probabilities <1. Common estimators include double‐observer models, distance sampling models and combined double‐observer and distance sampling models (known as mark‐recapture‐distance‐sampling models; MRDS). When animals reside in groups, however, the assumption of independent detection is violated. In this case, the standard approach is to account for imperfect detection of groups, while assuming that individuals within groups are detected perfectly. However, this assumption is often unsupported. We introduce an abundance estimator for grouped animals when detection of groups is imperfect and group size may be under‐counted, but not over‐counted. The estimator combines an MRDS model with an N‐mixture model to account for imperfect detection of individuals. The new MRDS‐Nmix model requires the same data as an MRDS model (independent detection histories, an estimate of distance to transect, and an estimate of group size), plus a second estimate of group size provided by the second observer. We extend the model to situations in which detection of individuals within groups declines with distance. We simulated 12 data sets and used Bayesian methods to compare the performance of the new MRDS‐Nmix model to an MRDS model. Abundance estimates generated by the MRDS‐Nmix model exhibited minimal bias and nominal coverage levels. In contrast, MRDS abundance estimates were biased low and exhibited poor coverage. Many species of conservation interest reside in groups and could benefit from an estimator that better accounts for imperfect detection. Furthermore, the ability to relax the assumption of perfect detection of individuals within detected groups may allow surveyors to re‐allocate resources toward detection of new groups instead of extensive surveys of known groups. We believe the proposed estimator is feasible because the only additional field data required are a second estimate of group size.     

Capture–recapture models with heterogeneity to study survival senescence in the wild

Detecting senescence in wild populations and estimating its strength raise three challenges. First, in the presence of individual heterogeneity in survival probability, the proportion of high‐survival individuals increases with age. This increase can mask a senescence‐related decrease in survival probability when the probability is estimated at the population level. To accommodate individual heterogeneity we use a mixture model structure (discrete classes of individuals). Second, the study individuals can elude the observers in the field, and their detection rate can be heterogeneous. To account for detectability issues we use capture–mark–recapture (CMR) methodology, mixture models and data that provide information on individuals’ detectability. Last, emigration to non‐monitored sites can bias survival estimates, because it can occur at the end of the individuals’ histories and mimic earlier death. To model emigration we use Markovian transitions to and from an unobservable state. These different model structures are merged together using hidden Markov chain CMR models, or multievent models. Simulation studies illustrate that reliable evidence for survival senescence can be obtained using highly heterogeneous data from non site‐faithful individuals. We then design a tailored application for a dataset from a colony of black‐headed gull Chroicocephalus ridibundus. Survival probabilities do not appear individually variable, but evidence for survival senescence becomes significant only when accounting for other sources of heterogeneity. This result suggests that not accounting for heterogeneity leads to flawed inference and/or that emigration heterogeneity mimics survival heterogeneity and biases senescence estimates.