Dynamics of a low‐density tiger population in Southeast Asia in the context of improved law enforcement

Recovering small populations of threatened species is an important global conservation strategy. Monitoring the anticipated recovery, however, often relies on uncertain abundance indices rather than on rigorous demographic estimates. To counter the severe threat from poaching of wild tigers (Panthera tigris), the Government of Thailand established an intensive patrolling system in 2005 to protect and recover its largest source population in Huai Kha Khaeng Wildlife Sanctuary. Concurrently, we assessed the dynamics of this tiger population over the next 8 years with rigorous photographic capture‐recapture methods. From 2006 to 2012, we sampled across 624–1026 km² with 137–200 camera traps. Cameras deployed for 21,359 trap days yielded photographic records of 90 distinct individuals. We used closed model Bayesian spatial capture‐recapture methods to estimate tiger abundances annually. Abundance estimates were integrated with likelihood‐based open model analyses to estimate rates of annual and overall rates of survival, recruitment, and changes in abundance. Estimates of demographic parameters fluctuated widely: annual density ranged from 1.25 to 2.01 tigers/100 km², abundance from 35 to 58 tigers, survival from 79.6% to 95.5%, and annual recruitment from 0 to 25 tigers. The number of distinct individuals photographed demonstrates the value of photographic capture–recapture methods for assessments of population dynamics in rare and elusive species that are identifiable from natural markings. Possibly because of poaching pressure, overall tiger densities at Huai Kha Khaeng were 82–90% lower than in ecologically comparable sites in India. However, intensified patrolling after 2006 appeared to reduce poaching and was correlated with marginal improvement in tiger survival and recruitment. Our results suggest that population recovery of low‐density tiger populations may be slower than anticipated by current global strategies aimed at doubling the number of wild tigers in a decade.     

Importance of Accounting for Detection Heterogeneity When Estimating Abundance: the Case of French Wolves

Abstract: Assessing conservation strategies requires reliable estimates of abundance. Because detecting all individuals is most often impossible in free‐ranging populations, estimation procedures have to account for a <1 detection probability. Capture–recapture methods allow biologists to cope with this issue of detectability. Nevertheless, capture–recapture models for open populations are built on the assumption that all individuals share the same detection probability, although detection heterogeneity among individuals has led to underestimating abundance of closed populations. We developed multievent capture–recapture models for an open population and proposed an associated estimator of population size that both account for individual detection heterogeneity (IDH). We considered a two‐class mixture model with weakly and highly detectable individuals to account for IDH. In a noninvasive capture–recapture study of wolves we based on genotypes identified in feces and hairs, we found a large underestimation of population size (27% on average) occurred when IDH was ignored.     

Pheromone Monitoring of Rare and Threatened Insects: Exploiting a Pheromone–Kairomone System to Estimate Prey and Predator Abundance

Abstract: Pheromone‐based monitoring is a promising new method for assessing the conservation status of many threatened insect species. We examined the versatility and usefulness of pheromone‐based monitoring by integrating a pheromone–kairomone trapping system and pitfall trapping system in the monitoring of two saproxylic beetles, the hermit beetle Osmoderma eremita (Coleoptera: Scarabaeidae) and its predator Elater ferrugineus (Coleoptera: Elateridae), which live inside hollow trees. We performed mark–recapture studies of both species with unbaited pitfall traps in oak hollows combined with pheromone‐baited funnel traps suspended from oak branches to intercept dispersing individuals. For O. eremita, the integrated trapping system showed that the population in the study sites may be considerably higher than estimates based on extrapolation from pitfall trapping alone (approximately 3400 vs. 1100 or 1800 individuals, respectively). Recaptures between odor‐baited funnel traps showed that males and females had similar dispersal rates, but estimating the number of dispersing individuals was problematic due to declining recapture probability between subsequent capture events. Our conservative estimate, assuming a linear decrease in capture probability, suggested that around 1900 individuals, or at least half of the O. eremita population, may perform flights from their natal host trees, representing higher dispersal rates than previous estimates. E. ferrugineus was rarely caught in pitfall traps. One hundred thirty‐nine individuals, likely almost exclusively females, were caught in odor‐baited funnel traps with approximately 4% recapture probability. If recapture probability over consecutive capture events follows that of O. eremita, this would correspond to a total population size of 2500–3000 individuals of the predator; similar to its supposed prey O. eremita. Our results demonstrate that pheromone‐based monitoring is a valuable tool in the study of species or life‐history stages that would otherwise be inaccessible.     

Optimization of capture–recapture monitoring of elusive species illustrated with a threatened grasshopper

Information on population sizes and trends of threatened species is essential for their conservation, but obtaining reliable estimates can be challenging. We devised a method to improve the precision of estimates of population size obtained from capture–recapture studies for species with low capture and recapture probabilities and short seasonal activity, illustrated with population data of an elusive grasshopper (Prionotropis rhodanica). We used data from 5 capture–recapture studies to identify methodological and environmental factors affecting capture and recapture probabilities and estimates of population size. In a simulation, we used the population size and capture and recapture probability estimates obtained from the field studies to identify the minimum number of sampling occasions needed to obtain unbiased and robust estimates of population size. Based on these results we optimized the capture–recapture design, implemented it in 2 additional studies, and compared their precision with those of the nonoptimized studies. Additionally, we simulated scenarios based on thresholds of population size in criteria C and D of the International Union for Conservation of Nature (IUCN) Red List to investigate whether estimates of population size for elusive species can reliably inform red-list assessments. Identifying parameters that affect capture and recapture probabilities (for the grasshopper time since emergence of first adults) and optimizing field protocols based on this information reduced study effort (−6% to −27% sampling occasions) and provided more precise estimates of population size (reduced coefficient of variation) compared with nonoptimized studies. Estimates of population size from the scenarios based on the IUCN thresholds were mostly unbiased and robust (only the combination of very small populations and little study effort produced unreliable estimates), suggesting capture–recapture can be considered reliable for informing red-list assessments. Although capture–recapture remains difficult and costly for elusive species, our optimization procedure can help determine efficient protocols to increase data quality and minimize monitoring effort.     

Minimum area requirements for an at‐risk butterfly based on movement and demography

Determining the minimum area required to sustain populations has a long history in theoretical and conservation biology. Correlative approaches are often used to estimate minimum area requirements (MARs) based on relationships between area and the population size required for persistence or between species’ traits and distribution patterns across landscapes. Mechanistic approaches to estimating MAR facilitate prediction across space and time but are few. We used a mechanistic MAR model to determine the critical minimum patch size (CMP) for the Baltimore checkerspot butterfly (Euphydryas phaeton), a locally abundant species in decline along its southern range, and sister to several federally listed species. Our CMP is based on principles of diffusion, where individuals in smaller patches encounter edges and leave with higher probability than those in larger patches, potentially before reproducing. We estimated a CMP for the Baltimore checkerspot of 0.7–1.5 ha, in accordance with trait‐based MAR estimates. The diffusion rate on which we based this CMP was broadly similar when estimated at the landscape scale (comparing flight path vs. capture‐mark‐recapture data), and the estimated population growth rate was consistent with observed site trends. Our mechanistic approach to estimating MAR is appropriate for species whose movement follows a correlated random walk and may be useful where landscape‐scale distributions are difficult to assess, but demographic and movement data are obtainable from a single site or the literature. Just as simple estimates of lambda are often used to assess population viability, the principles of diffusion and CMP could provide a starting place for estimating MAR for conservation.     

Use of Spatial Capture‐Recapture Modeling and DNA Data to Estimate Densities of Elusive Animals

Abstract: Assessment of abundance, survival, recruitment rates, and density (i.e., population assessment) is especially challenging for elusive species most in need of protection (e.g., rare carnivores). Individual identification methods, such as DNA sampling, provide ways of studying such species efficiently and noninvasively. Additionally, statistical methods that correct for undetected animals and account for locations where animals are captured are available to efficiently estimate density and other demographic parameters. We collected hair samples of European wildcat (Felis silvestris) from cheek‐rub lure sticks, extracted DNA from the samples, and identified each animals’ genotype. To estimate the density of wildcats, we used Bayesian inference in a spatial capture‐recapture model. We used WinBUGS to fit a model that accounted for differences in detection probability among individuals and seasons and between two lure arrays. We detected 21 individual wildcats (including possible hybrids) 47 times. Wildcat density was estimated at 0.29/km² (SE 0.06), and 95% of the activity of wildcats was estimated to occur within 1.83 km from their home‐range center. Lures located systematically were associated with a greater number of detections than lures placed in a cell on the basis of expert opinion. Detection probability of individual cats was greatest in late March. Our model is a generalized linear mixed model; hence, it can be easily extended, for instance, to incorporate trap‐ and individual‐level covariates. We believe that the combined use of noninvasive sampling techniques and spatial capture‐recapture models will improve population assessments, especially for rare and elusive animals.     

Estimates of sex- and age-class-specific survival probabilities for a southern Great Barrier Reef green sea turtle population

Sex- and age-class-specific survival probabilities of a southern Great Barrier Reef green sea turtle population were estimated using a capture–mark–recapture (CMR) study and a Cormack–Jolly–Seber (CJS) modelling approach. The CMR history profiles for 954 individual turtles tagged over a 9-year period (1984–1992) were classified into three age classes (adult, subadult, juvenile) based on somatic growth and reproductive traits. Reduced-parameter CJS models, accounting for constant survival and time-specific recapture, fitted best for all age classes. There were no significant sex-specific differences in either survival or recapture probabilities for any age class. Mean annual adult survival was estimated at 0.9482 (95% CI: 0.92–0.98) and was significantly higher than survival for either subadults or juveniles. Mean annual subadult survival was 0.8474 (95% CI: 0.79–0.91), which was not significantly different from mean annual juvenile survival estimated at 0.8804 (95% CI: 0.84–0.93). The time-specific adult recapture probabilities were a function of sampling effort but this was not the case for either juveniles or subadults. The sampling effort effect was accounted for explicitly in the estimation of adult survival and recapture probabilities. These are the first comprehensive sex- and age-class-specific survival and recapture probability estimates for a green sea turtle population derived from a long-term CMR program.Communicated by M.S. Johnson, Crawley     

Effects of Amphibian Chytrid Fungus on Individual Survival Probability in Wild Boreal Toads

Abstract: Chytridiomycosis is linked to the worldwide decline of amphibians, yet little is known about the demographic effects of the disease. We collected capture–recapture data on three populations of boreal toads (Bufo boreas [Bufo = Anaxyrus]) in the Rocky Mountains (U.S.A.). Two of the populations were infected with chytridiomycosis and one was not. We examined the effect of the presence of amphibian chytrid fungus (Batrachochytrium dendrobatidis [Bd]; the agent of chytridiomycosis) on survival probability and population growth rate. Toads that were infected with Bd had lower average annual survival probability than uninfected individuals at sites where Bd was detected, which suggests chytridiomycosis may reduce survival by 31–42% in wild boreal toads. Toads that were negative for Bd at infected sites had survival probabilities comparable to toads at the uninfected site. Evidence that environmental covariates (particularly cold temperatures during the breeding season) influenced toad survival was weak. The number of individuals in diseased populations declined by 5–7%/year over the 6 years of the study, whereas the uninfected population had comparatively stable population growth. Our data suggest that the presence of Bd in these toad populations is not causing rapid population declines. Rather, chytridiomycosis appears to be functioning as a low‐level, chronic disease whereby some infected individuals survive but the overall population effects are still negative. Our results show that some amphibian populations may be coexisting with Bd and highlight the importance of quantitative assessments of survival in diseased animal populations.     

A generalized estimating equations approach for capture–recapture closed population models

The estimation of population density animal population parameters, such as capture probability, population size, or population density, is an important issue in many ecological applications. Capture–recapture data may be considered as repeated observations that are often correlated over time. If these correlations are not taken into account then parameter estimates may be biased, possibly producing misleading results. We propose a generalized estimating equations (GEE) approach to account for correlation over time instead of assuming independence as in the traditional closed population capture–recapture studies. We also account for heterogeneity among observed individuals and over-dispersion, modelling capture probabilities as a function of covariates. The GEE versions of all closed population capture–recapture models and their corresponding estimating equations are proposed. We evaluate the effect of accounting for correlation structures on capture–recapture model selection based on the quasi-likelihood information criterion (QIC). An example is used for an illustrative application and for comparison to currently used methodology. A Horvitz–Thompson-like estimator is used to obtain estimates of population size based on conditional arguments. A simulation study is conducted to evaluate the performance of the GEE approach in capture-recapture studies. The GEE approach performs well for estimating population parameters, particularly when capture probabilities are high. The simulation results also reveal that estimated population size varies on the nature of the existing correlation among capture occasions.     

Determining Optimal Population Monitoring for Rare Butterflies

Abstract: Determining population viability of rare insects depends on precise, unbiased estimates of population size and other demographic parameters. We used data on the endangered St. Francis' satyr butterfly (Neonympha mitchellii francisci) to evaluate 2 approaches (mark–recapture and transect counts) for population analysis of rare butterflies. Mark–recapture analysis provided by far the greatest amount of demographic information, including estimates (and standard errors) of population size, detection, survival, and recruitment probabilities. Mark–recapture analysis can also be used to estimate dispersal and temporal variation in rates, although we did not do this here. Models of seasonal flight phenologies derived from transect counts (Insect Count Analyzer) provided an index of population size and estimates of survival and statistical uncertainty. Pollard–Yates population indices derived from transect counts did not provide estimates of demographic parameters. This index may be highly biased if detection and survival probabilities vary spatially and temporally. In terms of statistical performance, mark–recapture and Pollard–Yates indices were least variable. Mark–recapture estimates were less likely to fail than Insect Count Analyzer, but mark–recapture estimates became less precise as sampling intensity decreased. In general, count‐based approaches are less costly and less likely to cause harm to rare insects than mark–recapture. The optimal monitoring approach must reconcile these trade‐offs. Thus, mark–recapture should be favored when demographic estimates are needed, when financial resources enable frequent sampling, and when marking does not harm the insect populations. The optimal sampling strategy may use 2 sampling methods together in 1 overall sampling plan: limited mark–recapture sampling to estimate survival and detection probabilities and frequent but less expensive transect counts.     

Negative Effects of Habitat Loss on Survival of Migrant Warblers in a Forest Mosaic

Abstract: Habitat loss and fragmentation in forested landscapes often negatively affect animal abundance; however, whether these factors also affect fitness is not well known. We hypothesized that observed decreases in bird occurrence and abundance in landscapes with harvested forests are associated with reduced apparent survival of adults. We defined apparent survival as an estimate of survival that accounts for an imperfect resighting probability, but not permanent emigration (i.e., dispersal). We examined the association between spatially extensive habitat loss and apparent survival of males of 2 Neotropical migrant species, Blackburnian Warbler (Dendroica fusca) and Black‐Throated Green Warbler (D. virens), over 7 years in the Greater Fundy Ecosystem, New Brunswick, Canada. We estimated apparent survival among and within breeding seasons. We quantified amount of habitat in the context of individual species. In this landscape, boundaries between land‐cover types are gradual rather than clearly identifiable and abrupt. Estimated apparent within‐season survival of both species decreased as a function of amount of habitat within a 2000‐m radius; survival was approximately 12 times (95% CI 3.43–14) greater in landscapes with 85% habitat than in landscapes with 10% habitat. Apparent annual survival also decreased as a function of amount of habitat within a 100‐m radius. Over the range of habitat amount, apparent annual survival decreased 15% (95% CI 7–29%) as the amount of habitat decreased. Our results suggest that reduced species occurrence in landscapes with low proportions of habitat is due partly to lower apparent survival at these sites. This mechanism operates both directly (i.e., via effects on mortality or dispersal during breeding) and possibly through indirect effects during the nonbreeding season. Habitat loss was associated not only with a lower number of individuals, but also with lower survival of those individuals.     

Estimating abundance without recaptures of marked pallid sturgeon in the Mississippi River

Abundance estimates are essential for assessing the viability of populations and the risks posed by alternative management actions. An effort to estimate abundance via a repeated mark‐recapture experiment may fail to recapture marked individuals. We devised a method for obtaining lower bounds on abundance in the absence of recaptures for both panmictic and spatially structured populations. The method assumes few enough recaptures were expected to be missed by random chance. The upper Bayesian credible limit on expected recaptures allows probabilistic statements about the minimum number of individuals present in the population. We applied this method to data from a 12‐year survey of pallid sturgeon (Scaphirhynchus albus) in the lower and middle Mississippi River (U.S.A.). None of the 241 individuals marked was recaptured in the survey. After accounting for survival and movement, our model‐averaged estimate of the total abundance of pallid sturgeon ≥3 years old in the study area had a 1%, 5%, or 25% chance of being <4,600, 7,000, or 15,000, respectively. When we assumed fish were distributed in proportion to survey catch per unit effort, the farthest downstream reach in the survey hosted at least 4.5–15 fish per river kilometer (rkm), whereas the remainder of the reaches in the lower and middle Mississippi River hosted at least 2.6–8.5 fish/rkm for all model variations examined. The lower Mississippi River had an average density of pallid sturgeon ≥3 years old of at least 3.0–9.8 fish/rkm. The choice of Bayesian prior was the largest source of uncertainty we considered but did not alter the order of magnitude of lower bounds. Nil‐recapture estimates of abundance are highly uncertain and require careful communication but can deliver insights from experiments that might otherwise be considered a failure.     

Reexamining the Minimum Viable Population Concept for Long‐Lived Species

For decades conservation biologists have proposed general rules of thumb for minimum viable population size (MVP); typically, they range from hundreds to thousands of individuals. These rules have shifted conservation resources away from small and fragmented populations. We examined whether iteroparous, long‐lived species might constitute an exception to general MVP guidelines. On the basis of results from a 10‐year capture‐recapture study in eastern New York (U.S.A.), we developed a comprehensive demographic model for the globally threatened bog turtle (Glyptemys muhlenbergii), which is designated as endangered by the IUCN in 2011. We assessed population viability across a wide range of initial abundances and carrying capacities. Not accounting for inbreeding, our results suggest that bog turtle colonies with as few as 15 breeding females have >90% probability of persisting for >100 years, provided vital rates and environmental variance remain at currently estimated levels. On the basis of our results, we suggest that MVP thresholds may be 1–2 orders of magnitude too high for many long‐lived organisms. Consequently, protection of small and fragmented populations may constitute a viable conservation option for such species, especially in a regional or metapopulation context. Reexaminando el Concepto de Población Mínima Viable para Especies Longevas Resumen     

Toward accurate and precise estimates of lion density

Reliable estimates of animal density are fundamental to understanding ecological processes and population dynamics. Furthermore, their accuracy is vital to conservation because wildlife authorities rely on estimates to make decisions. However, it is notoriously difficult to accurately estimate density for wide‐ranging carnivores that occur at low densities. In recent years, significant progress has been made in density estimation of Asian carnivores, but the methods have not been widely adapted to African carnivores, such as lions (Panthera leo). Although abundance indices for lions may produce poor inferences, they continue to be used to estimate density and inform management and policy. We used sighting data from a 3‐month survey and adapted a Bayesian spatially explicit capture‐recapture (SECR) model to estimate spatial lion density in the Maasai Mara National Reserve and surrounding conservancies in Kenya. Our unstructured spatial capture‐recapture sampling design incorporated search effort to explicitly estimate detection probability and density on a fine spatial scale, making our approach robust in the context of varying detection probabilities. Overall posterior mean lion density was estimated to be 17.08 (posterior SD 1.310) lions >1 year old/100 km², and the sex ratio was estimated at 2.2 females to 1 male. Our modeling framework and narrow posterior SD demonstrate that SECR methods can produce statistically rigorous and precise estimates of population parameters, and we argue that they should be favored over less reliable abundance indices. Furthermore, our approach is flexible enough to incorporate different data types, which enables robust population estimates over relatively short survey periods in a variety of systems. Trend analyses are essential to guide conservation decisions but are frequently based on surveys of differing reliability. We therefore call for a unified framework to assess lion numbers in key populations to improve management and policy decisions.     

Accuracy of Short‐Term Demographic Data in Projecting Long‐Term Fate of Populations

Short‐term surveys are useful in conservation of species if they can be used to reliably predict the long‐term fate of populations. However, statistical evaluations of reliability are rare. We studied how well short‐term demographic data (1999–2002) of tartar catchfly (Silene tatarica), a perennial riparian plant, projected the fate and growth of 23 populations of this species up to the year 2010. Surveyed populations occurred along a river with natural flood dynamics and along a regulated river. Riparian plant populations are affected by flooding, which maintains unvegetated shores, while forest succession proceeds in areas with little flooding. Flooding is less severe along the regulated river, and vegetation overgrowth reduces abundance of tartar catchfly on unvegetated shores. We built matrix models to calculate population growth rates and estimated times to population extinction in natural and in regulated rivers, 13 and 10 populations, respectively. Models predicted population survival well (model predictions matched observed survival in 91% of populations) and accurately predicted abundance increases and decreases in 65% of populations. The observed and projected population growth rates differed significantly in all but 3 populations. In most cases, the model overestimated population growth. Model predictions did not improve when data from more years were used (1999–2006). In the regulated river, the poorest model predictions occurred in areas where cover of other plant species changed the fastest. Although vegetation cover increased in most populations, it decreased in 4 populations along the natural river. Our results highlight the need to combine disturbance and succession dynamics in demographic models and the importance of habitat management for species survival along regulated rivers. Precisión de Datos Demográficos de Corto Plazo en la Proyección del Destino de Poblaciones a Largo Plazo     

Associations of Forest Cover,Fragment Area,and Connectivity with Neotropical Understory Bird Species Richness and Abundance

Theoretical and empirical studies demonstrate that the total amount of forest and the size and connectivity of fragments have nonlinear effects on species survival. We tested how habitat amount and configuration affect understory bird species richness and abundance. We used mist nets (almost 34,000 net hours) to sample birds in 53 Atlantic Forest fragments in southeastern Brazil. Fragments were distributed among 3 10,800‐ha landscapes. The remaining forest in these landscapes was below (10% forest cover), similar to (30%), and above (50%) the theoretical fragmentation threshold (approximately 30%) below which the effects of fragmentation should be intensified. Species‐richness estimates were significantly higher (F= 3715, p = 0.00) where 50% of the forest remained, which suggests a species occurrence threshold of 30–50% forest, which is higher than usually occurs (<30%). Relations between forest cover and species richness differed depending on species sensitivity to forest conversion and fragmentation. For less sensitive species, species richness decreased as forest cover increased, whereas for highly sensitive species the opposite occurred. For sensitive species, species richness and the amount of forest cover were positively related, particularly when forest cover was 30–50%. Fragment size and connectivity were related to species richness and abundance in all landscapes, not just below the 30% threshold. Where 10% of the forest remained, fragment size was more related to species richness and abundance than connectivity. However, the relation between connectivity and species richness and abundance was stronger where 30% of the landscape was forested. Where 50% of the landscape was forested, fragment size and connectivity were both related to species richness and abundance. Our results demonstrated a rapid loss of species at relatively high levels of forest cover (30–50%). Highly sensitive species were 3‐4 times more common above the 30–50% threshold than below it; however, our results do not support a unique fragmentation threshold. Asociaciones de la Cobertura Forestal, Superficie del Fragmento y Conectividad con la Riqueza y Abundancia de Aves Neotropicales de Sotobosque     

Chytridiomycosis and Seasonal Mortality of Tropical Stream‐Associated Frogs 15 Years after Introduction of Batrachochytrium dendrobatidis

Assessing the effects of diseases on wildlife populations can be difficult in the absence of observed mortalities, but it is crucial for threat assessment and conservation. We performed an intensive capture‐mark‐recapture study across seasons and years to investigate the effect of chytridiomycosis on demographics in 2 populations of the threatened common mist frog (Litoria rheocola) in the lowland wet tropics of Queensland, Australia. Infection prevalence was the best predictor for apparent survival probability in adult males and varied widely with season (0–65%). Infection prevalence was highest in winter months when monthly survival probabilities were low (approximately 70%). Populations at both sites exhibited very low annual survival probabilities (12–15%) but high recruitment (71–91%), which resulted in population growth rates that fluctuated seasonally. Our results suggest that even in the absence of observed mortalities and continued declines, and despite host–pathogen co‐existence for multiple host generations over almost 2 decades, chytridiomycosis continues to have substantial seasonally fluctuating population‐level effects on amphibian survival, which necessitates increased recruitment for population persistence. Similarly infected populations may thus be under continued threat from chytridiomycosis which may render them vulnerable to other threatening processes, particularly those affecting recruitment success. Quitridiomicosis y Mortalidad Estacional de Ranas Asociadas a Arroyos Tropicales Quince Años Después de la Introducción de Batrachochytrium dendrobatidisvsp     

Relation between Occupancy and Abundance for a Territorial Species,the California Spotted Owl

Land and resource managers often use detection–nondetection surveys to monitor the populations of species that may be affected by factors such as habitat alteration, climate change, and biological invasions. Relative to mark‐recapture studies, using detection–nondetection surveys is more cost‐effective, and recent advances in statistical analyses allow the incorporation of detection probability, covariates, and multiple seasons. We examined the efficacy of using detection–nondetection data (relative to mark‐recapture data) for monitoring population trends of a territorial species, the California Spotted Owl (Strix occidentalis occidentalis). We estimated and compared the finite annual rates of population change (λ_t) and the resulting realized population change (Δ_t) from both occupancy and mark‐recapture data collected over 18 years (1993–2010). We used multiseason, robust‐design occupancy models to estimate that territory occupancy declined during our study (Δ_t = 0.702, 95% CI 0.552–0.852) due to increasing territory extinction rates ( = 0.019 [SE 0.012]; = 0.134 [SE 0.043]) and decreasing colonization rates ( = 0.323 [SE 0.124]; = 0.242 [SE 0.058]). We used Pradel's temporal‐symmetry model for mark‐recapture data to estimate that the population trajectory closely matched the trends in territory occupancy (Δ_t = 0.725, 95% CI 0.445–1.004). Individual survival was constant during our study ( = 0.816 [SE 0.020]; = 0.815 [SE 0.019]), whereas recruitment declined slightly ( = 0.195 [SE 0.032]; = 0.160 [SE 0.023]). Thus, we concluded that detection–nondetection data can provide reliable inferences on population trends, especially when funds preclude more intensive mark‐recapture studies. Relación entre Ocupación y Abundancia en una Especie Territorial, el Búho Moteado de California     

Problems with mitigation translocation of herpetofauna

Mitigation translocation of nuisance animals is a commonly used management practice aimed at resolution of human–animal conflict by removal and release of an individual animal. Long considered a reasonable undertaking, especially by the general public, it is now known that translocated subjects are negatively affected by the practice. Mitigation translocation is typically undertaken with individual adult organisms and has a much lower success rate than the more widely practiced conservation translocation of threatened and endangered species. Nonetheless, the public and many conservation practitioners believe that because population‐level conservation translocations have been successful that mitigation translocation can be satisfactorily applied to a wide variety of human‐wildlife conflict situations. We reviewed mitigation translocations of reptiles, including our own work with 3 long‐lived species (Gila monsters [Heloderma suspectum], Sonoran desert tortoises [Gopherus morafkai], and western diamond‐backed rattlesnakes [Crotalus atrox]). Overall, mitigation translocation had a low success rate when judged either by effects on individuals (in all studies reviewed they exhibited increased movement or increased mortality) or by the success of the resolution of the human–animal conflict (translocated individuals often returned to the capture site). Careful planning and identification of knowledge gaps are critical to increasing success rates in mitigation translocations in the face of increasing pressure to find solutions for species threatened by diverse anthropogenic factors, including climate change and exurban and energy development. Problemas con la Mitigación por Traslocación de Herpetofauna     

An EM algorithm for capture-recapture estimation

Analysis of capture—recapture data often involves maximizing a complex likelihood function with many unknown parameters. Statistical inference based on selection of a proper model depends on successful attainment of this maximum. An EM algorithm is developed for obtaining maximum likelihood estimates of capture and survival probabilities conditional on first capture from standard capture—recapture data. The algorithm does not require the use of numerical derivatives which may improve precision and stability relative to other estimation schemes. The asymptotic covariance matrix of the estimated parameters can be obtained using the supplemented EM algorithm. The EM algorithm is compared to a more traditional Newton-Raphson algorithm with both a simulated and a real dataset. The two algorithms result in the same parameter estimates, but Newton-Raphson variance estimates depend on a numerically estimated Hessian matrix that is sensitive to step size choice.