Estimating the population and related dynamics of the cave-dwelling Edible-nest Swiftlet in the Andaman Islands, India

International trade of swiftlet nests has affected wild populations of edible-nest swiftlets throughout their range. The white-nest swiftlet Aerodramus fuciphagus of the Andaman and Nicobar Islands lost 80% of its population in the 1990s. Conservation efforts for the species were initiated in 2000, with the active involvement of former nest collectors. To measure the efficacy of protection measures we collected data on the swiftlet, using the nest count method. We monitored annual breeding populations in 28 protected caves on Chalis-ek and one on Interview Island during 2000–2008, and in 168 unprotected caves on Baratang and Interview Islands during February–April 2008. The swiftlet population in protected caves increased by 39%, whereas it declined by 74% in unprotected caves. Nearly 61% of the 152 caves on Baratang Island were abandoned by the swiftlet during 1997–2008. This study highlights the importance of extending protection to the unprotected caves on the Andaman and Nicobar Islands.

The status and conservation of the Edible-nest Swiftlet ( Collocalia fuciphaga) in the Andaman and Nicobar Islands

We estimated the annual population size, survival rates and capture probabilities for two populations of the Levantine Frog, Pelophylax bedriagae, using a Capture-Mark-Recapture (CMR) non-invasive digital photographic identification technique in Karagöl Lake and Soğan-harımı Pond in the western Aegean Region of Turkey, and used POLLOCK’s methodology to assess population parameters. Time specific capture probability, time specific survival rate and no temporary emigration were found to be the best appropriate models for our data. Population sizes were estimated as 245 adults in 2006, 301 in 2007, 67 in 2008 and 54 in 2009. Annual capture probabilities were estimated on average as 0.161, and annual survival rates across years were on average 0.301. Soğanharımı Pond was destroyed for recreational purposes after the first year of our study. To determine the size of the population, which was depleted during the construction of the recreational facilities, we used a closed population model, and concluded that in total 54 adults disappeared. In addition, we determined the possible negative factors that affect the population size and survival rates of the Levantine Frog including habitat destruction and the introduction of Siluris glanis and Astacus leptodactylus into the freshwater body.

Population estimates are a fundamental requirement of ecology and conservation. While capture–recapture models are an established method for producing such estimates, their assumption of homogeneous capture probabilities is problematic given that heterogeneity in individual capture probability is inherent to most species. Such variation must be accounted for by abundance models; otherwise, biased estimates are risked.Here, we investigate the performance of four types of heterogeneity models for estimating abundance of male cheetah Acinonyx jubatus, a species with two distinct spatial tactics of territorial and nonterritorial (floater) males. The differences in spatial movements of territory holders and floaters are expected to result in intrasexual heterogeneous capture probabilities. Four heterogeneity models were used to model male abundance at five territories in central Namibia; (a) a spatial tactic model, (b) a finite mixture model, both run in program MARK, (c) a floater‐only model, and (d) a heterogeneity Mh model, both run in the program CAPTURE. Camera trap data of cheetah, taken at frequently visited marking trees, were used to derive true abundance. Model results were compared to the true abundance to assess the accuracy of estimates.Only models (a), (b), and (c) were able to consistently produce accurate results. Mixture models do not require prior knowledge regarding spatial tactic of males, which might not always be available. Therefore, we recommend such models as the preferred model type for cheetahs.Results highlight the potential for mixture models in overcoming the challenges of capture probability heterogeneity and in particular their use with species where intrasexual behavioral differences exist.

Three subterranean termite species [eastern subterranean termite, Reticulitermes flavipes (Kollar); R. virginicus (Banks); and R. hageni (Banks)] were included in 67 mark–release–recapture experiments conducted with 57 different colonies in Georgia over 3 yr (1992, 1993, and 1995). Data were collected in 1992–1993 under a triple-mark–release protocol and analyzed using 2 mathematical models–the Lincoln index and a weighted mean model. During 1995, data were collected using a single release of marked termites followed by 3 collections and analyzed using the Lincoln index. In addition, 71 different termite infested logs were returned to the laboratory where termites were extracted and counted. Termite foraging population estimates ranged from 106 to 1,453,021 for the weighted mean model and 127 to 384,617 for the Lincoln index in 1992–1993. The 1995 Lincoln index estimates ranged from 1,463 to 3,547,152 termites per colony. The numbers of termites extracted from infested logs ranged from 1,033 to 344,457 termites per log. Both mathematical models applied to the 1992–1993 data provided similar population estimates. The 1995 Lincoln index data provided population estimates which were higher than the 1992–1993 data, median 98,202 and 28,473 termites per colony, respectively. Results of these mark–release–recapture experiments, when examined by capture cycle, suggest that the biology of subterranean termites may violate some of the assumptions of these mathematical models for estimating population size.

Foraging habits and habitats of exclusive aerial insectivores, the Edible-nest Swiftlet (Aerodramus fuciphagus inexpectatus) and Glossy Swiftlet (Collocalia esculenta affinis), were studied in Andaman Islands, India. Observations were made during January to June 2004 between 0500 and 1800 hrs at four locations in the forest and on open paddy land. Edible-nest and Glossy swiftlets, respectively, spent (x¯ ± SD) 17.2 ± 11.4% and 25.8 ± 15.6% of their time foraging with significant temporal variations. Glossy Swiftlets had spatial variations in twist, flutter, and tail-wing-open foraging maneuvers. This species also had diurnal variations in flock size, which were positively correlated with feeding attempts. Both swiftlets shared all microhabitats except Inside Forest Canopy and Inside Stream Bank Canopy. Microhabitat use did not vary significantly in Below Stream Bank Canopy, >10 m Above Forest Canopy, >30 m Above Ground, and Above Forest Canopy for Edible-nest Swiftlets. Inside Forest Canopy and Inside Stream Bank Canopy categories for Glossy Swiftlets were relatively important in descending order. Deforestation near and distant from caves used by swiftlets for breeding in the islands can severely affect the wild population of both species.

Population estimates of hispid cotton rats (Sigmodon hispidus) in 2 southern Florida sugarcane fields were obtained from capture-recapture data. A model for population estimation that assumes an open population of individuals with equal probabilities of capture (Jolly-Seber) and a sequence of models (program CAPTURE) that assumes a closed population of individuals with varying capture probabilities yielded similar estimates, despite considerable heterogeneity of capture probabilities over 8-day trapping periods. The trends of the open and closed model estimates and 2 population indices, minimum number known to be alive and captures per 100 trap-nights, were similar: population size in both fields was reduced following harvest, remained low during spring and early summer, and increased in late summer and throughout the fall. Minimum number known to be alive appeared to be a more sensitive index to population fluctuation than captures per 100 trap-nights. J. WILDL. MANAGE. 46(1):156-163 Despite considerable literature on statistical methods of population estimation based on capture-recapture data, many researchers prefer to use indices of abundance or simple estimators such as the Lincoln Index. Indices such as minimum number of animals known to be alive, number of individuals trapped, and captures per 100-trap nights are commonly used. A gap exists between the practical use of various models for population estimation, each with their restrictive assumptions, and an understanding of how capture-recapture data for a given species meet or fail to meet the models' assumptions. Otis et al. (1978), drawing from recent work by Pollock (1974) and Burnham and Overton (1978), developed a number of models that allow unequal capture probabilities in capture-recapture studies, and formulated computer program CAPTURE to test the fit of these models to capture-recapture data, select the most appropriate model for a given data set, and compute the estimate of population size under that model. Such an approach gives the biologist an objective means of learning which assumption(s) the data violate most seriously when using specific models and which model(s), if any, fit the data. Otis et al.'s (1978) models assume a closed population, that is, recruitment, immigration, emigration, and mortality are not allowed, and this may limit their usefulness for many studies. However, when trapping periods are short in relation to the opportunity for the occurrence of such factors, and when the area trapped is sufficiently large, this assumption can be approximately met. Smallmammal studies conducted in a fairly w ll-defined area for a period of a week, for example, may often meet the closure criterion adequately. In contrast to the above closed models, the Jolly-Seber (J-S) model (Jolly 1965; Seber 1965, 1973) is a so-called open population model, allowing the occurrence of immigration, emigration, recruitment, and mortality during the trapping period. The model assumes, however, that capture probabilities vary only by trapping occasion, and thus individual heterogeneity among animals or behavioral response to capture are not permitted. Both the J-S model and the models of Otis et al. (1978) assume geographic 156 J. Wildl. Manage. 46(1):1982 This content downloaded from 207.46.13.103 on Thu, 20 Oct 2016 04:32:10 UTC All use subject to http://about.jstor.org/terms ESTIMATING SIZE OF COTTON RAT POPULATIONS* Lefebvre et al. 157 closure; that is, the concept of a population, occupying a defined geographical area and made up of an absolute number of individuals, is implicit in both types of models. Our study investigates use of program CAPTURE on cotton rat capture-recapture data, and compares estimates obtained with J-S estimates and with the population indices minimum number of animals known to be alive (MNA) and captures per 100 trap-nights. D. Decker, U.S. Fish and Wildlife Service, conducted much of the rat handling and assisted in data preparation. C. Ingram assisted in developing trapping design, N. Shafer assisted in obtaining Jolly-Seber estimates, and W. Braley, T. O'Brien, D. Buecker, P. Gall, W. Maddox, M. Sandsberry, K. Simpson, D. Steffen, and S. Williams assisted in setting traps and data recording. K. Burnham and D. Anderson reviewed an earlier version and made several helpful suggestions.

The understanding of the dynamics of animal populations and of related ecological and evolutionary issues frequently depends on a direct analysis of life history parameters. For instance, examination of trade—offs between reproduction and survival usually rely on individually marked animals, for which the exact time of death is most often unknown, because marked individuals cannot be followed closely through time. Thus, the quantitative analysis of survival studies and experiments must be based on capture—recapture (or resighting) models which consider, besides the parameters of primary interest, recapture or resighting rates that are nuisance parameters. Capture—recapture models oriented to estimation of survival rates are the result of a recent change in emphasis from earlier approaches in which population size was the most important parameter, survival rates having been first introduced as nuisance parameters. This emphasis on survival rates in capture—recapture models developed rapidly in the 1980s and used as a basic structure the Cormack—Jolly—Seber survival model applied to an homogeneous group of animals, with various kinds of constraints on the model parameters. These approaches are conditional on first captures; hence they do not attempt to model the initial capture of unmarked animals as functions of population abundance in addition to survival and capture probabilities. This paper synthesizes, using a common framework, these recent developments together with new ones, with an emphasis on flexibility in modeling, model selection, and the analysis of multiple data sets. The effects on survival and capture rates of time, age, and categorical variables characterizing the individuals (e.g., sex) can be considered, as well as interactions between such effects. This "analysis of variance" philosophy emphasizes the structure of the survival and capture process rather than the technical characteristics of any particular model. The flexible array of models encompassed in this synthesis uses a common notation. As a result of the great level of flexibility and relevance achieved, the focus is changed from fitting a particular model to model building and model selection. The following procedure is recommended: (1) start from a global model compatible with the biology of the species studied and with the design of the study, and assess its fit; (2) select a more parsimonious model using Akaike's Information Criterion to limit the number of formal tests; (3) test for the most important biological questions by comparing this model with neighboring ones using likelihood ratio tests; and (4) obtain maximum likelihood estimates of model parameters with estimates of precision. Computer software is critical, as few of the models now available have parameter estimators that are in closed form. A comprehensive table of existing computer software is provided. We used RELEASE for data summary and goodness—of—fit tests and SURGE for iterative model fitting and the computation of likelihood ratio tests. Five increasingly complex examples are given to illustrate the theory. The first, using two data sets on the European Dipper (Cinclus cinclus), tests for sex—specific parameters, explores a model with time—dependent survival rates, and finally uses a priori information to model survival allowing for an environmental variable. The second uses data on two colonies of the Swift (Apus apus), and shows how interaction terms can be modeled and assessed and how survival and recapture rates sometimes partly counterbalance each other. The third shows complex variation in survival rates across sexes and age classes in the roe deer (Capreolus capreolus), with a test of density dependence in annual survival rates. The fourth is an example of experimental density manipulation using the common lizard (Lacerta vivipara). The last example attempts to examine a large and complex data set on the Greater Flamingo (Phoenicopterus ruber), where parameters are age specific, survival is a function of an environmental variable, and an age × year interaction term is important. Heterogeneity seems present in this example and cannot be adequately modeled with existing theory. The discussion presents a summary of the paradigm we recommend and details issues in model selection and design, and foreseeable future developments.

We collected data from 10 caves (3 sites) in the North and Middle Andaman Islands to determine the spatiotemporal changes in the roosting pattern of the Andaman populations of Edible-nest Swiftlet (Aerodramus fuciphagus inexpectatus). This echolocating diurnal aerial forager showed temporal variation in its round-the-clock entry and exit patterns. With spatiotemporal variations (site-wise, cave-wise, hourly, and monthly), more than 98% of birds returned daily to the roosting caves between 1700 h and 2000 h. However, their daily departure time (between 0400 h and 0700 h) did not vary spatially (site-wise and cave-wise). The movements of birds at the cave openings were higher during the nestling period in April and May. The daily roosting period inside the caves (mean 525.20 min; SD 82.98) also showed spatiotemporal variation. Day length affected movement of the birds before and after sunset and sunrise. We conclude that roosting movement of the Andaman Edible-nest Swiftlet varied spatiotemporally in the Andaman Islands. This first detailed description of such variation in the roosting patterns of the species will stimulate further exploration of the various biological and environmental factors affecting movements of this cave-dwelling endemic.

Estimating population trends provides valuable information for conservation biologists. Although there are many methods for estimating demographic rates, capture-mark-recapture (CMR) methods are known to be the most realistic method that can provide detailed data on individuals and populations, including the achievement of conservation goals. This study focused on determining the population trend of Pelophylax bedriagae caralitanus, Beyşehir frog using the CMR method in a protected area during the 2011 - 2019 breeding seasons. Our CMR data led to the selection of a model-considering constant survival rates, capture/recapture probabilities, and year-specific immigration/emigration patterns [Φ(··) y'(t) y''(t) p(··) = c(··) N(t)]-as the most fitting biological hypothesis among 22 constructed models. According to the best fitted model, 6% of all individuals of Gölcük population can be captured during each sampling occasions. The annual survival rates how low variation between years, and the mean survival rate was estimated as 0.85. that means 85% of the individuals of Pelophylax bedriagae caralitanusin the Gölcük population were able to live on to subsequent breeding seasons. The average population size of Gölcük population for nine consecutive years was estimated as 5094 (range 4834 - 5382) individuals that shows minor and acceptable level of population size fluctuations, and slightly increasing over the years. These findings can guide future research, aiding in assessing population size changes in both protected and non-protected areas while understanding population decline trends.

Objective The Michigan Department of Natural Resources uses standardized electrofishing and capture–recapture methods to estimate the population of salmonids in small coldwater streams. These methods require 2 d of effort per site, which limits the number of sites that can be sampled per year. In this paper, I explore how estimates of capture probability from sites with full capture–recapture data can be used to allow for population estimates at sites with only a single pass. Methods I used simulation modeling to evaluate the performance of four different approaches using Chapman estimates of population size from capture–recapture sampling to calibrate catches at single-pass sites. These approaches include computing the mean capture probability across all calibration sites, two regression approaches, and a ratio estimator approach. I also compared results from calibrated single-pass estimates to Chapman estimates in 26 streams. Results Performance of these methods depends on the population size, the capture probability, and the process variation in capture probability among sites. Each of these approaches has unique attributes such that no single method is generally preferable. In situations where capture probability is low (i.e., 0.2), single-pass estimates perform better than independent estimates using a Chapman estimator. At population sizes and process variation typical of data from Michigan coldwater streams, the Chapman estimator performs better than single-pass estimates but comes at double the cost of sampling effort. Conclusions Estimates from a single pass generally parallel trends from the Chapman estimator, indicating that single-pass sampling may be used to evaluate population trends in most cases at a substantially reduced cost.

A fundamental challenge to estimating population size with mark-recapture methods is heterogeneous capture probabilities and subsequent bias of population estimates. Confronting this problem usually requires substantial sampling effort that can be difficult to achieve for some species, such as carnivores. We developed a methodology that uses two data sources to deal with heterogeneity and applied this to DNA mark-recapture data from grizzly bears (Ursus arctos). We improved population estimates by incorporating additional DNA "captures" of grizzly bears obtained by collecting hair from unbaited bear rub trees concurrently with baited, grid-based, hair snag sampling. We consider a Lincoln-Petersen estimator with hair snag captures as the initial session and rub tree captures as the recapture session and develop an estimator in program MARK that treats hair snag and rub tree samples as successive sessions. Using empirical data from a large-scale project in the greater Glacier National Park, Montana, USA, area and simulation modeling we evaluate these methods and compare the results to hair-snag-only estimates. Empirical results indicate that, compared with hair-snag-only data, the joint hair-snag-rub-tree methods produce similar but more precise estimates if capture and recapture rates are reasonably high for both methods. Simulation results suggest that estimators are potentially affected by correlation of capture probabilities between sample types in the presence of heterogeneity. Overall, closed population Huggins-Pledger estimators showed the highest precision and were most robust to sparse data, heterogeneity, and capture probability correlation among sampling types. Results also indicate that these estimators can be used when a segment of the population has zero capture probability for one of the methods. We propose that this general methodology may be useful for other species in which mark-recapture data are available from multiple sources.

We applied capture-mark-recapture (CMR) methods to estimate the population size of the Tavas frog Rana tavasensis in its terra typica. For this purpose, we used Pollock?s robust design in program MARK in the 2011-2015 breeding seasons in its terra typica. Based on the selected model, equal catchability of each individual and absence of temporary migration were found to be the most likely biological hypotheses. Population sizes were estimated as 398, 348, 275, and 117 individuals during the four study years, respectively. Annual capture probabilities were estimated to average 0.07, and annual survival rates across years averaged 0.19. The year-specific estimations showed a remarkable decline in population size and survival rates. Anthropogenic factors, such as off-road activities, recreational activities, and animal grazing, might have played a role in this decline. This trend provides us with useful knowledge for conservation and management activities.

ABSTRACTReliable estimates of great ape abundance are needed to assess distribution, monitor population status, evaluate conservation tactics, and identify priority populations for conservation. Rather than using direct counts, surveyors often count ape nests. The standing crop nest count (SCNC) method converts the standing stock of nests into animal densities using a set of parameters, including nest decay rate. Nest decay rates vary greatly over space and time, and it takes months to calculate a site‐specific value. The marked nest count (MNC) method circumvents this issue and only counts new nests produced during a defined period. We compared orangutan densities calculated by the two methods using data from studies in Sumatra and Kalimantan, Indonesia. We show how animal densities calculated using nest counts should be cautiously interpreted when used to make decisions about management or budget allocation. Even with site‐specific decay rates, short studies using the SCNC method may not accurately reflect the current population unless conducted at a scale sufficient to include wide‐ranging orangutan movement. Density estimates from short studies using the MNC method were affected by small sample sizes and by orangutan movement. To produce reliable results, the MNC method may require a similar amount of effort as the SCNC method. We suggest a reduced reliance on the traditional line transect surveys in favor of feasible alternative methods when absolute abundance numbers are not necessary or when site‐specific nest decay rates are not known. Given funding constraints, aerial surveys, reconnaissance walks, and interview techniques may be more cost‐effective means of accomplishing some survey goals.

I review the use of auxiliary variables in capture-recapture models for estimation of demographic parameters (e.g. capture probability, population size, survival probability, and recruitment, emigration and immigration numbers). I focus on what has been done in current research and what still needs to be done. Typically in the literature, covariate modelling has made capture and survival probabilities functions of covariates, but there are good reasons also to make other parameters functions of covariates as well. The types of covariates considered include environmental covariates that may vary by occasion but are constant over animals, and individual animal covariates that are usually assumed constant over time. I also discuss the difficulties of using time-dependent individual animal covariates and some possible solutions. Covariates are usually assumed to be measured without error, and that may not be realistic. For closed populations, one approach to modelling heterogeneity in capture probabilities uses observable individual covariates and is thus related to the primary purpose of this paper. The now standard Huggins-Alho approach conditions on the captured animals and then uses a generalized Horvitz-Thompson estimator to estimate population size. This approach has the advantage of simplicity in that one does not have to specify a distribution for the covariates, and the disadvantage is that it does not use the full likelihood to estimate population size. Alternately one could specify a distribution for the covariates and implement a full likelihood approach to inference to estimate the capture function, the covariate probability distribution, and the population size. The general Jolly-Seber open model enables one to estimate capture probability, population sizes, survival rates, and birth numbers. Much of the focus on modelling covariates in program MARK has been for survival and capture probability in the Cormack-Jolly-Seber model and its generalizations (including tag-return models). These models condition on the number of animals marked and released. A related, but distinct, topic is radio telemetry survival modelling that typically uses a modified Kaplan-Meier method and Cox proportional hazards model for auxiliary variables. Recently there has been an emphasis on integration of recruitment in the likelihood, and research on how to implement covariate modelling for recruitment and perhaps population size is needed. The combined open and closed 'robust' design model can also benefit from covariate modelling and some important options have already been implemented into MARK. Many models are usually fitted to one data set. This has necessitated development of model selection criteria based on the AIC (Akaike Information Criteria) and the alternative of averaging over reasonable models. The special problems of estimating over-dispersion when covariates are included in the model and then adjusting for over-dispersion in model selection could benefit from further research.