An evaluation of multiple‐pass seining to monitor blackstripe topminnow Fundulus notatus (Rafinesque, 1820) in the Sydenham River (Ontario,Canada)

Multiple‐pass (i.e. removal) sampling and mark‐recapture experiments were undertaken in the Sydenham River (Ontario, Canada) to assess the effectiveness of seining to detect and estimate the local abundance of blackstripe topminnow, Fundulus notatus (Rafinesque, 1820) as well as to compare catch characteristics from closed and open (with and without block nets) sample units. Probability of species detection using three‐pass seining was estimated to be 0.58 in closed units, and 0.51 in open units. To be 95% confident of occupancy status, a minimum of five repeat surveys is required. A decline in catch occurred in only half of the sample units, population size estimates were often imprecise, and attempts to generate mark‐recapture population estimates were unsuccessful. Mean capture probabilities were 0.48 in closed units and 0.65 in open units, when depletion occurred. For blackstripe topminnow and other fishes encountered, there were no significant differences between closed and open units in the frequency of depletion or capture probability. Compared to single‐pass surveys, monitoring programs that employ three seine hauls are more likely to detect the presence of the blackstripe topminnow and any decline in local abundance.     

Trap‐shyness subsidence is a threshold function of mark–recapture interval in brown mudfish Neochanna apoda populations

The influence of capture interval on trap shyness, and temperature, rainfall and drought on capture probability (p) in 827 brown mudfish Neochanna apoda was quantified using mark–recapture models. In particular, it was hypothesized that the loss of trapping memory in marked N. apoda would lead to a capture‐interval threshold required to minimize trap shyness. Neochanna apoda trap shyness approximated a threshold response to capture interval, declining rapidly with increasing capture intervals up to 16·5 days, after which p remained constant. Tests for detecting trap‐dependent capture probability in Cormack–Jolly–Seber models failed to detect trap shyness in N. apoda capture histories with capture intervals averaging 16 days. This confirmed the applicability of the 16 day capture‐interval threshold for mark–recapture studies. Instead, N. apoda p was positively influenced by water temperature and rainfall during capture. These results imply that a threshold capture interval is required to minimize the trade‐off between the competing assumptions of population closure and p homogeneity between capture occasions in closed mark–recapture models. Moreover, environmental factors that influence behaviour could potentially confound abundance indices, and consequently abundance trends should be interpreted with caution in the face of long‐term climate change, such as with global warming.     

Using dynamic N‐mixture models to test cavity limitation on northern flying squirrel demographic parameters using experimental nest box supplementation

Dynamic N‐mixture models have been recently developed to estimate demographic parameters of unmarked individuals while accounting for imperfect detection. We propose an application of the Dail and Madsen ( 2011 : Biometrics, 67 , 577–587) dynamic N‐mixture model in a manipulative experiment using a before‐after control‐impact design (BACI). Specifically, we tested the hypothesis of cavity limitation of a cavity specialist species, the northern flying squirrel, using nest box supplementation on half of 56 trapping sites. Our main purpose was to evaluate the impact of an increase in cavity availability on flying squirrel population dynamics in deciduous stands in northwestern Québec with the dynamic N‐mixture model. We compared abundance estimates from this recent approach with those from classic capture–mark–recapture models and generalized linear models. We compared apparent survival estimates with those from Cormack–Jolly–Seber (CJS) models. Average recruitment rate was 6 individuals per site after 4 years. Nevertheless, we found no effect of cavity supplementation on apparent survival and recruitment rates of flying squirrels. Contrary to our expectations, initial abundance was not affected by conifer basal area (food availability) and was negatively affected by snag basal area (cavity availability). Northern flying squirrel population dynamics are not influenced by cavity availability at our deciduous sites. Consequently, we suggest that this species should not be considered an indicator of old forest attributes in our study area, especially in view of apparent wide population fluctuations across years. Abundance estimates from N‐mixture models were similar to those from capture–mark–recapture models, although the latter had greater precision. Generalized linear mixed models produced lower abundance estimates, but revealed the same relationship between abundance and snag basal area. Apparent survival estimates from N‐mixture models were higher and less precise than those from CJS models. However, N‐mixture models can be particularly useful to evaluate management effects on animal populations, especially for species that are difficult to detect in situations where individuals cannot be uniquely identified. They also allow investigating the effects of covariates at the site level, when low recapture rates would require restricting classic CMR analyses to a subset of sites with the most captures.     

Noninvasive Hair Sampling and Genetic Tagging of Co-Distributed Fishers and American Martens

ABSTRACT Estimation of abundance is important for assessing population responses to management actions. Accurate abundance estimates are particularly critical for monitoring temporal variation following reintroductions when the management goal is to attain population sizes capable of sustaining harvest. Numerous reintroductions have taken place in the Great Lakes region of North America, including efforts to restore extirpated fishers (Martes pennanti) and American martens (M. americana). We used a DNA-based noninvasive hair-snaring method based on one trap design and trapping -grid configuration, and evaluated capture—mark—recapture (CMR) analytical approaches to simultaneously estimate population size for co-distributed fishers and American martens in a 671-km² area of the Ottawa National Forest in the western Upper Peninsula of Michigan, USA. We included harvest as a final recapture period to increase probability of recapture and to evaluate potential violations of geographic closure assumptions. We used microsatellite markers to identify target species, eliminate congener species, and provide individual identity for estimation of abundance. Population estimates for fishers and martens on the study area ranged from 35 to 60 and 8 to 28, respectively. Estimators incorporating harvest data resulted in up to a 40% increase in abundance estimates relative to estimators without harvest. We considered population estimates not including harvest data the most appropriate for the study due to timing of sampling and environmental factors, but inclusion of harvested individuals was shown to be useful as a means to detect violations of the assumption of geographic closure. We suggest improvements on future CMR sampling designs for larger landscape scales of relevance to management through incorporation of habitat or historical harvest data. Noninvasive genetic methods that simultaneously estimate the numerical abundance of co-distributed species can greatly decrease assessment costs relative to traditional methods, and increase resulting demographic and ecological information.     

Assessing the effectiveness of long-term monitoring of the Broad-toothed Rat in the Barrington Tops National Park,Australia

Biodiversity monitoring is crucial for effective conservation efforts. Effective monitoring allows managers to determine the status and trends of biodiversity, as well as the success of conservation actions. The population of the Broad-toothed Rats (Mastacomys fuscus) in the Barrington Tops National Park New South Wales, Australia has been monitored since 1999 via scat and live-trapping surveys. We reviewed the methods used and analysed the data produced with the aim of describing patterns of population change over time using a range of outcome variables and identifying different climate correlates. A secondary aim was to explore the use of population statistics that account for imperfect detection by comparing naïve occupancy, with an index of relative abundance based on trap effort, the latency to find scats during scat surveys and an occupancy model based on trapping surveys. Neither of these three methods accounts for detectability variation. Naïve occupancy decreased slightly over time, while the relative abundance based on trap effort revealed no evidence of change. Additionally, naïve occupancy decreased with increasing temperature while temperature had no clear impact on relative abundance. Finally, precipitation had no impact on either naïve occupancy or relative abundance. We found no evidence of a relationship between the latency to find scats and the index of relative abundance, suggesting that one or neither is related to actual abundance. Finally, a multi-season occupancy model found occupancy probability to be 0.78 ± 0.23 (standard error); detection probability as 0.51 ± 0.06; seasonal colonisation rate as 0.36 ± 0.13 and seasonal extinction rate at 0.44 ± 0.13. We conclude that despite significant investment in monitoring, this historical data set does not allow managers to ascertain whether population change has occurred and to identify potential drivers of change. Careful consideration of future methods, in particular, whether there is imperfect detection in scat surveys, will help to inform future monitoring.     

Evaluation of Bear Rub Surveys to Monitor Grizzly Bear Population Trends

Abstract: Wildlife managers need reliable estimates of population size, trend, and distribution to make informed decisions about how to recover at-risk populations, yet obtaining these estimates is costly and often imprecise. The grizzly bear (Ursus arctos) population in northwestern Montana, USA, has been managed for recovery since being listed under the United States Endangered Species Act in 1975, yet no rigorous data were available to evaluate the program's success. We used encounter data from 379 grizzly bears identified through bear rub surveys to parameterize a series of Pradel model simulations in Program MARK to assess the ability of noninvasive genetic sampling to estimate population growth rates. We evaluated model performance in terms of 1) power to detect gender-specific and population-wide declines in population abundance, 2) precision and relative bias of growth rate estimates, and 3) sampling effort required to achieve 80% power to detect a decline within 10 years. Simulations indicated that ecosystem-wide, annual bear rub surveys would exceed 80% power to detect a 3% annual decline within 6 years. Robust-design models with 2 simulated surveys per year provided precise and unbiased annual estimates of trend, abundance, and apparent survival. Designs incorporating one survey per year require less sampling effort but only yield trend and apparent survival estimates. Our results suggest that systematic, annual bear rub surveys may provide a viable complement or alternative to telemetry-based methods for monitoring trends in grizzly bear populations.     

Towards meaningful monitoring: A case study of a threatened rodent

Detecting trends in species’ distribution and abundance are essential for conserving threatened species, and depend upon effective monitoring programmes. Despite this, monitoring programmes are often designed without explicit consideration of their ability to deliver the information required by managers, such as their power to detect population changes. Here, we demonstrate the use of existing data to support the design of monitoring programmes aimed at detecting declines in species occupancy. We used single‐season occupancy models and baseline data to gain information on variables affecting the occupancy and detectability of the threatened brush‐tailed rabbit‐rat Conilurus penicillatus (Gould 1842) on the Tiwi Islands, Australia. This information was then used to estimate the survey effort required to achieve sufficient power to detect changes in occupancy of different magnitudes. We found that occupancy varied spatially, driven primarily by habitat (canopy height and cover, distance to water) and fire history across the landscape. Detectability varied strongly among seasons, and was three times higher in the late dry season (July–September), compared to the early dry season (April–June). Evaluation of three monitoring scenarios showed that conducting surveys at times when detectability is highest can lead to a substantial improvement in our ability to detect declines, thus reducing the survey effort and costs. Our study highlights the need for careful consideration of survey design related to the ecology of a species, as it can lead to substantial cost savings and improved insight into species population change via monitoring.     

Abundance of rare and elusive species: Empirical investigation of closed versus spatially explicit capture–recapture models with lynx as a case study

Effective conservation and management require reliable monitoring methods and estimates of abundance to prioritize human and financial investments. Camera trapping is a non-invasive sampling method allowing the use of capture–recapture (CR) models to estimate abundance while accounting for the difficulty of detecting individuals in the wild. We investigated the relative performance of standard closed CR models and spatially explicit CR models (SECR) that incorporate spatial information in the data. Using simulations, we considered 4 scenarios comparing low versus high detection probability and small versus large populations and contrasted abundance estimates obtained from both approaches. Standard CR and SECR models both provided minimally biased abundance estimates, but precision was improved when using SECR models. The associated confidence intervals also provided better coverage than their non-spatial counterpart. We concluded SECR models exhibit better statistical performance than standard closed CR models and allow for sound management strategies based on density maps of activity centers. To illustrate the comparison, we considered the Eurasian lynx (Lynx lynx) as a case study that provided the first abundance estimates of a local population in France. © 2012 The Wildlife Society.     

Demography of the Heike firefly Luciola lateralis (Coleoptera: Lampyridae), a representative species of Japan’s traditional agricultural landscape

Populations of the Heike firefly, Luciola lateralis, a representative species of Japan’s traditional agricultural landscape (known as satoyama), have recently experienced rapid declines in many areas of Japan. Owing to the popularity of this firefly, many local communities have increased conservation efforts through the restoration of aquatic habitat complexes in satoyama. To provide fundamental parameters to predict population dynamics of the firefly, we conducted a mark–recapture study in restored paddy fields, and we estimated adult population parameters such as population size, survival, recruitment, sex ratio, and body size. We found that capture probability generally decreased as the season advanced, probably because of seasonal changes in detectability and/or firefly behavior. The daily survival rate of adults decreased over the season and may be related to a seasonal decline in adult body size. Adult population exhibited a highly male-biased sex ratio. Firefly abundance in the restored paddy fields doubled during the 4-year study period. Our analysis showed that adult detectability, recruitment, and survival rate are seasonally variable and could affect population size estimates obtained by a simple flash census. The mark–recapture technique can provide precise estimates of adult L. lateralis population characteristics and, thus, is a valuable method for predicting firefly populations and assessing the success of the restoration program.     

Estimating Abundance of an Unmarked,Low-Density Species using Cameras

Estimating abundance of wildlife populations can be challenging and costly, especially for species that are difficult to detect and that live at low densities, such as cougars (Puma concolor). Remote, motion-sensitive cameras are a relatively efficient monitoring tool, but most abundance estimation techniques using remote cameras rely on some or all of the population being uniquely identifiable. Recently developed methods estimate abundance from encounter rates with remote cameras and do not require identifiable individuals. We used 2 methods, the time-to-event and space-to-event models, to estimate the density of 2 cougar populations in Idaho, USA, over 3 winters from 2016–2019. We concurrently estimated cougar density using the random encounter model (REM), an existing camera-based method for unmarked populations, and genetic spatial capture recapture (SCR), an established method for monitoring cougar populations. In surveys for which we successfully estimated density using the SCR model, the time-to-event estimates were more precise and showed comparable variation between survey years. The space-to-event estimates were less precise than the SCR estimates and were more variable between survey years. Compared to REM, time-to-event was more precise and consistent, and space-to-event was less precise and consistent. Low sample sizes made the space-to-event and SCR models inconsistent from survey to survey, and non-random camera placement may have biased both of the camera-based estimators high. We show that camera-based estimators can perform comparably to existing methods for estimating abundance in unmarked species that live at low densities. With the time- and space-to-event models, managers could use remote cameras to monitor populations of multiple species at broader spatial and temporal scales than existing methods allow. © 2020 The Wildlife Society.     

High Turnover Rates in Remnant Populations of the Harlequin Frog Atelopus cruciger (Bufonidae): Low Risk of Extinction?

Atelopus is among the most threatened of all amphibian genera. Most species of harlequin frogs disappeared more than two decades ago and only a few still exist. From ten critically endangered Atelopus species endemic to Venezuela, Atelopus cruciger is the only one that can be located at present. To assess the status of remnant populations of A. cruciger and to provide the demographic data for designing in situ management programs, we estimated: (1) the population size; (2) the apparent survival; and (3) the recruitment rates of one remnant population using mark‐recapture data. The adult population size varied (69–117), and this variation was not related to that of abundance indices based on visual counts at the river margins. Thus, caution is recommended when using visual counts as an index of abundance in Atelopus, because capture rates differ significantly among months and between seasons. Despite the observed variations, this population appears to be stable. Previous reports suggest that species of Atelopus are long‐lived. For populations of long‐lived species to remain approximately constant, recruitment must be low. Our mark‐recapture study, however, showed that adults tend to remain in the population for approximately 15 mo, but an average of 165 new frogs are recruited every year. Although immigration and emigration are possibilities, the site fidelity and the absence of nearby streams suggests that movement in and out of the study area is less important than births and deaths. Under the proposed hypothesis of a short life expectancy/high recruitment, the risk of extinction must be lower than previously thought.     

Use of hair tubes to survey for shrews: new methods for identification and quantification of abundance

• 1 Accurate and sensitive survey and monitoring methods are needed for shrews. We present a new design of hair tube and a new, simple method of species identification from multivariate analysis of four parameters measured from shrew guard hairs using a binocular microscope with incident light.
• 2 Multivariate analysis of these parameters measured from hairs of known identity showed that they can be used to identify hair to the species level with 85% accuracy.
• 3 We compared our indices of abundance from hair tubes (the hair tube index) with those from live trapping in 40 field margins. Capture‐mark‐recapture methods showed that capture rate did not vary systematically across sites, so that number of individuals captured was used as an index of abundance.
• 4 The hair tube index showed a significant association with the number of individuals captured for Sorex araneus and Neomys fodiens. The lack of a significant association for Sorex minutus may be because hair tubes are more sensitive in detecting this species than live trapping.
• 5 Hair tubes have additional advantages over live trapping, since they do not require frequent checking, are much lighter and cheaper than live traps, and no licence is required for their use in the UK. We therefore recommend consideration of their use in future surveys and monitoring studies of shrews. We provide an equation so that other researchers can use our multivariate method.

     

multimark: an R package for analysis of capture–recapture data consisting of multiple “noninvasive” marks

I describe an open‐source R package, multimark , for estimation of survival and abundance from capture–mark–recapture data consisting of multiple “noninvasive” marks. Noninvasive marks include natural pelt or skin patterns, scars, and genetic markers that enable individual identification in lieu of physical capture. multimark provides a means for combining and jointly analyzing encounter histories from multiple noninvasive sources that otherwise cannot be reliably matched (e.g., left‐ and right‐sided photographs of bilaterally asymmetrical individuals). The package is currently capable of fitting open population Cormack–Jolly–Seber (CJS) and closed population abundance models with up to two mark types using Bayesian Markov chain Monte Carlo (MCMC) methods. multimark can also be used for Bayesian analyses of conventional capture–recapture data consisting of a single‐mark type. Some package features include (1) general model specification using formulas already familiar to most R users, (2) ability to include temporal, behavioral, age, cohort, and individual heterogeneity effects in detection and survival probabilities, (3) improved MCMC algorithm that is computationally faster and more efficient than previously proposed methods, (4) Bayesian multimodel inference using reversible jump MCMC, and (5) data simulation capabilities for power analyses and assessing model performance. I demonstrate use of multimark using left‐ and right‐sided encounter histories for bobcats (Lynx rufus) collected from remote single‐camera stations in southern California. In this example, there is evidence of a behavioral effect (i.e., trap “happy” response) that is otherwise indiscernible using conventional single‐sided analyses. The package will be most useful to ecologists seeking stronger inferences by combining different sources of mark–recapture data that are difficult (or impossible) to reliably reconcile, particularly with the sparse datasets typical of rare or elusive species for which noninvasive sampling techniques are most commonly employed. Addressing deficiencies in currently available software, multimark also provides a user‐friendly interface for performing Bayesian multimodel inference using capture–recapture data consisting of a single conventional mark or multiple noninvasive marks.     

Estimating multiple years,tributary-specific,and overall Atlantic salmon smolt abundance in a large Canadian catchment using capture–mark–recapture experiments

Population monitoring of Atlantic salmon (Salmo salar L.) abundance is an essential element to understand annual stock variability and inform fisheries management processes. Smolts are the life stage marking the transition from the freshwater to the marine phase of anadromous Atlantic salmon. Estimating smolt abundance allows for subsequent inferences on freshwater and marine survival rates. Annual abundances of out-migrating Atlantic salmon smolts were estimated using Bayesian models and an 18-year capture–mark–recapture time series from two to five trapping locations within the Restigouche River (Canada) catchment. Some of the trapping locations were at the outlet of large upstream tributaries, and these sampled a portion of the total out-migrating population of smolts for the watershed, whereas others were located just above the head of tide of the Restigouche River and sampled the entire run of salmon smolts. Due to logistic and environmental conditions, not all trapping locations were operational each year. Additionally, recapture rates were relatively low (<5%), and the absolute number of recaptures was relatively few (most often a few dozen), leading to incoherent and highly uncertain estimates of tributary-specific and whole catchment abundance estimates when the data were modeled independently among trapping locations and years. Several models of increasing complexity were tested using simulated data, and the best-performing model in terms of bias and precision incorporated a hierarchical structure among years on the catchability parameters and included an explicit spatial structure to account for the annual variations in the number of sampled locations within the watershed. When the best model was applied to the Restigouche River catchment dataset, the annual smolt abundance estimates varied from 250,000 to 1 million smolts, and the subbasin estimates of abundance were consistent with the spatial structure of the monitoring programme. Ultimately, increasing the probabilities of capture and the absolute number of recaptures at the different traps will be required to improve the precision and reduce the bias of the estimates of smolt abundance for the entire basin and within subbasins of the watershed. The model and approach provide a significant improvement in the models used to date based on independent estimates of abundance by trapping location and year. Total abundance and relative production in discrete spawning, nesting, or rearing areas provide critical information to appropriately understand and manage the threats to species that can occur at subpopulation spatial scales.     

Six‐year demographic study reveals threat of stochastic extinction for remnant populations of a threatened amphibian

Sustained demographic studies are essential for early detection of species decline in time for effective management response. A paucity of such background data hindered the potential for successful conservation during the global amphibian decline and remains problematic today. The current study analysed 6 years of mark‐recapture data to determine the vital demographic rates in three habitat precincts of the threatened frog, Litoria aurea (Hylidae) and to understand the underlying causes of variability in population size. Variability in population size of L. aurea was similar to many pond‐breeding species; however this level of fluctuation is rare among threatened amphibians. Highly variable populations are at greater risk of local extinction and the low level of connectivity between L. aurea populations means they are at a greater risk of further decline due to stochastic extinction events and incapacity to recolonize distant habitat. We recommend that management of this species should encourage recolonization through creation of habitat corridors and reintroduction of L. aurea to areas where stochastic extinction events are suspected.     

Decline in abundance and apparent survival rates of fin whales (Balaenoptera physalus) in the northern Gulf of St. Lawrence

Estimates of abundance and survivorship provide quantifiable measures to monitor populations and to define and understand their conservation status. This study investigated changes in abundance and survival rates of fin whales (Balaenoptera physalus) in the northern Gulf of St. Lawrence in the context of anthropogenic pressures and changing environmental conditions. A long‐term data set, consisting of 35 years of photo‐identification surveys and comprising more than 5,000 identifications of 507 individuals, formed the basis of this mark–recapture study. Based on model selection using corrected Akaike Information Criterion, the most parsimonious Cormack–Jolly–Seber model included a linear temporal trend in noncalf apparent survival rates with a sharp decline in the last 5 years of the study and a median survival rate of 0.946 (95% confidence interval (CI) 0.910–0.967). To account for capture heterogeneity due to divergent patterns of site fidelity, agglomerative hierarchical cluster analysis was employed to categorize individuals based on their annual and survey site fidelity indices. However, the negative trend in survivorship remained and was corroborated by a significant decline in the estimated super‐population size from 335 (95% CI 321–348) individuals in 2004–2010 to 291 (95% CI 270–312) individuals in 2010–2016. Concurrently, a negative trend was estimated in recruitment to the population, supported by a sharp decrease in the number of observed calves. Ship strikes and changes in prey availability are potential drivers of the observed decline in fin whale abundance. The combination of clustering methods with mark–recapture represents a flexible way to investigate the effects of site fidelity on demographic variables and is broadly applicable to other individual‐based studies.     

Estimating abundance and population trends when detection is low and highly variable: A comparison of three methods for the Hermann's tortoise

Assessing population trends is a basic prerequisite to carrying out adequate conservation strategies. Selecting an appropriate method to monitor animal populations can be challenging, particularly for low-detection species such as reptiles. This study compares 3 detection-corrected abundance methods (capture–recapture, distance sampling, and N-mixture) used to assess population size of the threatened Hermann's tortoise. We used a single dataset of 432 adult tortoise observations collected at 118 sampling sites in the Plaine des Maures, southeastern France. We also used a dataset of 520 tortoise observations based on radiotelemetry data collected from 10 adult females to estimate and model the availability (g0) needed for distance sampling. We evaluated bias for N-mixture and capture–recapture, by using simulations based on different values of detection probabilities. Finally, we conducted a power analysis to estimate the ability of the 3 methods to detect changes in Hermann's tortoise abundances. The abundance estimations we obtained using distance sampling and N-mixture models were respectively 1.75 and 2.19 times less than those obtained using the capture–recapture method. Our results indicated that g0 was influenced by temperature variations and can differ for the same temperature on different days. Simulations showed that the N-mixture models provide unstable estimations for species with detection probabilities <0.5, whereas capture–recapture estimations were unbiased. Power analysis showed that none of the 3 methods were precise enough to detect slow population changes. We recommend that great care should be taken when implementing monitoring designs for species with large variation in activity rates and low detection probabilities. Although N-mixture models are easy to implement, we would not recommend using them in situations where the detection probability is very low at the risk of providing biased estimates. Among the 3 methods allowing estimation of tortoise abundances, capture–recapture should be preferred to assess population trends. © 2013 The Wildlife Society.     

Long-term demographic surveys reveal a consistent relationship between average occupancy and abundance within local populations of a butterfly metapopulation

Species distribution models are the tool of choice for large-scale population monitoring, environmental association studies and predictions of range shifts under future environmental conditions. Available data and familiarity of the tools rather than the underlying population dynamics often dictate the choice of specific method – especially for the case of presence–absence data. Yet, for predictive purposes, the relationship between occupancy and abundance embodied in the models should reflect the actual population dynamics of the modelled species. To understand the relationship of occupancy and abundance in a heterogeneous landscape at the scale of local populations, we built a spatio-temporal regression model of populations of the Glanville fritillary butterfly Melitaea cinxia in a Baltic Sea archipelago. Our data comprised nineteen years of habitat surveys and snapshot data of land use in the region. We used variance partitioning to quantify relative contributions of land use, habitat quality and metapopulation covariates. The model revealed a consistent and positive, but noisy relationship between average occupancy and mean abundance in local populations. Patterns of abundance were highly variable across years, with large uncorrelated random variation and strong local population stochasticity. In contrast, the spatio-temporal random effect, habitat quality, population connectivity and patch size explained variation in occupancy, vindicating metapopulation theory as the basis for modelling occupancy patterns in fragmented landscapes. Previous abundance was an important predictor in the occupancy model, which points to a spillover of abundance into occupancy dynamics. While occupancy models can successfully model large-scale population structure and average occupancy, extinction probability estimates for local populations derived from occupancy-only models are overconfident, as extinction risk is dependent on actual, not average, abundance.     

Monitoring of the Flat-Tailed Horned Lizard With Methods Incorporating Detection Probability

Abstract: Difficulty in monitoring the flat-tailed horned lizard (Phrynosoma mcallii) has led to controversy over its conservation status. The difficulty in detecting this species has discouraged large-scale estimates of abundance and led to uncertainty over whether the species exists in population sizes of sufficient size for long-term persistence. We incorporated detection probability into monitoring of this species using closed mark—recapture and distance-sampling methods. Density estimation from mark—recapture abundance estimates was improved using an estimate of the proportion of time lizards were on the plot. We estimated the probability of detection on the line for distance sampling and adjusted density estimates accordingly. We estimated the populations of the Yuha Basin Management Area in 2002 and the East Mesa Management Area, Imperial County, California, USA, in 2003 to be 25,514 (95% CI 14,444-38,970) and 42,619 (95% CI 23,161-67,639), respectively. Two estimates of detection probability on the line in distance sampling by different methods were 0.45 and 0.65. Density estimates derived from distance analyses for 3 East Mesa Management Area plots and the Yuha Basin Management Area were 1.55 per ha (95% CI 0.64-3.76) and 0.41 per ha (95% CI 0.22-0.7), respectively. These are the first large-scale estimates of abundance and density for P. mcallii.     

Evaluating environmental,demographic and genetic effects on population‐level survival in an island endemic

The population dynamics of island species are considered particularly sensitive to variation in environmental, demographic and/or genetic processes. However, few studies have attempted to evaluate the relative importance of these processes for key vital rates in island endemics. We integrated the results of long‐term capture–mark–recapture analysis, prey surveys, habitat quality assessments and molecular analysis to determine the causes of variation in the survival rates of Komodo dragons Varanus komodoensis at 10 sites on four islands in Komodo National Park, Indonesia. Using open population capture–mark–recapture methods, we ranked competing models that considered environmental, ecological, genetic and demographic effects on site‐specific Komodo dragon survival rates. Site‐specific survival rates ranged from 0.49 (95% CI: 0.33–0.68) to 0.92 (0.79–0.97) in the 10 study sites. The three highest‐ranked models (i.e. ΔQAIC_c < 2) explained ～70% of variation in Komodo dragon survival rates and identified interactions between inbreeding coefficients, prey biomass density and habitat quality as important explanatory variables. There was evidence of additive effects from ecological and genetic (e.g. inbreeding) processes affecting Komodo dragon survival rates. Our results indicate that maintaining high ungulate prey biomass and habitat quality would enhance the persistence of Komodo dragon populations. Assisted gene flow may also increase the genetic and demographic viability of the smaller Komodo dragon populations.