Sampling tiger ungulate prey by the distance method: lessons learned in Bardia National Park, Nepal

Because tiger Panthera tigris numbers are regulated by their prey base, prey abundance needs to monitored and estimated reliably. Recently, distance sampling has been adopted as the most appropriate method and is now becoming the standard monitoring protocol in all tiger range countries in south Asia. However, the accuracy of the density estimates generated by this method has not been assessed. From total counts within habitat blocks, we obtained accurate density estimates of ungulates within three main habitats in Bardia National Park, Nepal. We then applied the distance sampling method in the same habitats and compared the results. Distance sampling on foot in dense habitats (riverine forest and tallgrass floodplain) violated method assumptions, and sampling from vehicle along roads gave biased estimates. Sampling from elephant back worked well in all habitat types, but owing to their behaviour, the density of barking deer Muntiacus muntjak was underestimated. The accuracy of the estimates varied with sampling effort; for the very abundant chital deer Axis axis , estimates varied markedly at <200 animal observations, but converged at larger sample sizes to a similar point estimate as intensive block counts when approaching 300 observations. For the less abundant species, with <20 observations along >100 km of transect lines, the confidence intervals were quite high, and, hence, of limited value for detecting short-term populations trends. It is therefore difficult to obtain accurate density estimates of rare species by the distance method. In areas consisting of dense habitats, we recommend that the food base of tiger be estimated by distance sampling from elephant back, not on foot, directed at the main and most abundant prey species. For rare species, encounter rates obtained simultaneously may then serve as indices of relative abundances.     

Robustness of close‐kin mark–recapture estimators to dispersal limitation and spatially varying sampling probabilities

1. Close‐kin mark–recapture (CKMR) is a method for estimating abundance and vital rates from kinship relationships observed in genetic samples. CKMR inference only requires animals to be sampled once (e.g., lethally), potentially widening the scope of population‐level inference relative to traditional monitoring programs.
2. One assumption of CKMR is that, conditional on individual covariates like age, all animals have an equal probability of being sampled. However, if genetic data are collected opportunistically (e.g., via hunters or fishers), there is potential for spatial variation in sampling probability that can bias CKMR estimators, particularly when genetically related individuals stay in close proximity.
3. We used individual‐based simulation to investigate consequences of dispersal limitation and spatially biased sampling on performance of naive (nonspatial) CKMR estimators of abundance, fecundity, and adult survival. Population dynamics approximated that of a long‐lived mammal species subject to lethal sampling.
4. Naive CKMR abundance estimators were relatively unbiased when dispersal was unconstrained (i.e., complete mixing) or when sampling was random or subject to moderate levels of spatial variation. When dispersal was limited, extreme variation in spatial sampling probabilities negatively biased abundance estimates. Reproductive schedules and survival were well estimated, except for survival when adults could emigrate out of the sampled area. Incomplete mixing was readily detected using Kolmogorov–Smirnov tests.
5. Although CKMR appears promising for estimating abundance and vital rates with opportunistically collected genetic data, care is needed when dispersal limitation is coupled with spatially biased sampling. Fortunately, incomplete mixing is easily detected with adequate sample sizes. In principle, it is possible to devise and fit spatially explicit CKMR models to avoid bias under dispersal limitation, but development of such models necessitates additional complexity (and possibly additional data). We suggest using simulation studies to examine potential bias and precision of proposed modeling approaches prior to implementing a CKMR program.

     

Estimability of migration survival rates from integrated breeding and winter capture–recapture data

Long‐distance migration is a common phenomenon across the animal kingdom but the scale of annual migratory movements has made it difficult for researchers to estimate survival rates during these periods of the annual cycle. Estimating migration survival is particularly challenging for small‐bodied species that cannot carry satellite tags, a group that includes the vast majority of migratory species. When capture–recapture data are available for linked breeding and non‐breeding populations, estimation of overall migration survival is possible but current methods do not allow separate estimation of spring and autumn survival rates. Recent development of a Bayesian integrated survival model has provided a method to separately estimate the latent spring and autumn survival rates using capture–recapture data, though the accuracy and precision of these estimates has not been formally tested. Here, I used simulated data to explore the estimability of migration survival rates using this model. Under a variety of biologically realistic scenarios, I demonstrate that spring and autumn migration survival can be estimated from the integrated survival model, though estimates are biased toward the overall migration survival probability. The direction and magnitude of this bias are influenced by the relative difference in spring and autumn survival rates as well as the degree of annual variation in these rates. The inclusion of covariates can improve the model's performance, especially when annual variation in migration survival rates is low. Migration survival rates can be estimated from relatively short time series (4–5 years), but bias and precision of estimates are improved when longer time series (10–12 years) are available. The ability to estimate seasonal survival rates of small, migratory organisms opens the door to advancing our understanding of the ecology and conservation of these species. Application of this method will enable researchers to better understand when mortality occurs across the annual cycle and how the migratory periods contribute to population dynamics. Integrating summer and winter capture data requires knowledge of the migratory connectivity of sampled populations and therefore efforts to simultaneously collect both survival and tracking data should be a high priority, especially for species of conservation concern.     

Mean life expectancy of Old World screwworm fly,Chrysomya bezziana,inferred from the reproductive age-structure of native females caught on swormlure-baited sticky traps

Abstract. The reproductive status of native (wild) screwworm fly, Chrysomya bezziana, caught on swormlure-baited sticky traps in Papua New Guinea is described. A total of 1122 females and 25 males were trapped. Of these females 595 were scored for insemination status and stage of ovarian development (on a scale of 2–10) of which 20% were in suitable condition for assignment to first, second and third ovarian cycles. Of the nulliparous females, only 17% were inseminated at stage 3 of ovarian development, 70% at stage 4, 93-97% at stages 5 and 6, and all of stages 7–10 (gravids). All parous females were inseminated. More than half of the captured females were parous (58%) and only 7% of the total were gravid. Proportions of females in ovarian cycles 1, 2 and 3 were 41%, 50% and 9% respectively. Survival of female Ch. bezziana in the laboratory was adequately described by lognormal and Gompertz survival functions, for both of which the mortality rate is an increasing function of reproductive age. Analysis of the reproductive age distribution of native females estimated their mean life-expectancy at 9 days under the prevailing mean field temperature of 26.5^oC. This equates to completion of 1.7 ovarian cycles and an estimated mean lifetime fecundity of 146 female progeny. The survival models, which also allowed responsiveness of females to swormlure-baited traps (female trappability) to vary according to their stage of ovarian development, indicated significant age-dependent trapping bias. These findings are compared with similar data for the New World screwworm fly, Cochliomyia hominivorax.     

The operational sex ratio influences choosiness in a pipefish

If more females than males are available for mating in the breedingpopulation (i.e., the operational sex ratio, OSR, is femalebiased), males can afford to be choosy. In the pipefish (Syngnathustyphle) females compete for males, who are choosy. In natureOSRs are typically female biased, but may occasionally be malebiased. In a series of experiments, males were allowed to choosebetween a large and a small female under a perceived excessof either males or females. Under female bias, males preferredthe large female: they spent more time close to her than tothe small female; they courted the large female sooner thanthe small; and they tended to copulate sooner and more oftenwith the large female. Under male bias all these differencesvanished and males mated at random with respect to female size.Males reproduced at a faster rate under male than under femalebias because they received more eggs in their brood pouches.Thus, males switched from maximizing mate quality (i.e., beingchoosy) to minimizing the risk of not reproducing (i.e., beingquick) as the OSR became male biased.     

Inferring speciation and extinction rates under different sampling schemes

The birth-death process is widely used in phylogenetics to model speciation and extinction. Recent studies have shown that the inferred rates are sensitive to assumptions about the sampling probability of lineages. Here, we examine the effect of the method used to sample lineages. Whereas previous studies have assumed random sampling (RS), we consider two extreme cases of biased sampling: "diversified sampling" (DS), where tips are selected to maximize diversity and "cluster sampling (CS)," where sample diversity is minimized. DS appears to be standard practice, for example, in analyses of higher taxa, whereas CS may occur under special circumstances, for example, in studies of geographically defined floras or faunas. Using both simulations and analyses of empirical data, we show that inferred rates may be heavily biased if the sampling strategy is not modeled correctly. In particular, when a diversified sample is treated as if it were a random or complete sample, the extinction rate is severely underestimated, often close to 0. Such dramatic errors may lead to serious consequences, for example, if estimated rates are used in assessing the vulnerability of threatened species to extinction. Using Bayesian model testing across 18 empirical data sets, we show that DS is commonly a better fit to the data than complete, random, or cluster sampling (CS). Inappropriate modeling of the sampling method may at least partly explain anomalous results that have previously been attributed to variation over time in birth and death rates.     

Performance tradeoffs in target‐group bias correction for species distribution models

Species distribution models (SDMs) are often calibrated using presence‐only datasets plagued with environmental sampling bias, which leads to a decrease of model accuracy. In order to compensate for this bias, it has been suggested that background data (or pseudoabsences) should represent the area that has been sampled. However, spatially‐explicit knowledge of sampling effort is rarely available. In multi‐species studies, sampling effort has been inferred following the target‐group (TG) approach, where aggregated occurrence of TG species informs the selection of background data. However, little is known about the species‐ specific response to this type of bias correction. The present study aims at evaluating the impacts of sampling bias and bias correction on SDM performance. To this end, we designed a realistic system of sampling bias and virtual species based on 92 terrestrial mammal species occurring in the Mediterranean basin. We manipulated presence and background data selection to calibrate four SDM types. Unbiased (unbiased presence data) and biased (biased presence data) SDMs were calibrated using randomly distributed background data. We used real and TG‐estimated sampling efforts in background selection to correct for sampling bias in presence data. Overall, environmental sampling bias had a deleterious effect on SDM performance. In addition, bias correction improved model accuracy, and especially when based on spatially‐explicit knowledge of sampling effort. However, our results highlight important species‐specific variations in susceptibility to sampling bias, which were largely explained by range size: widely‐distributed species were most vulnerable to sampling bias and bias correction was even detrimental for narrow‐ranging species. Furthermore, spatial discrepancies in SDM predictions suggest that bias correction effectively replaces an underestimation bias with an overestimation bias, particularly in areas of low sampling intensity. Thus, our results call for a better estimation of sampling effort in multispecies system, and cautions the uninformed and automatic application of TG bias correction.     

Effects of sample size on estimates of population growth rates calculated with matrix models

Background

Matrix models are widely used to study the dynamics and demography of populations. An important but overlooked issue is how the number of individuals sampled influences estimates of the population growth rate (λ) calculated with matrix models. Even unbiased estimates of vital rates do not ensure unbiased estimates of λ–Jensen''s Inequality implies that even when the estimates of the vital rates are accurate, small sample sizes lead to biased estimates of λ due to increased sampling variance. We investigated if sampling variability and the distribution of sampling effort among size classes lead to biases in estimates of λ.

Methodology/Principal Findings

Using data from a long-term field study of plant demography, we simulated the effects of sampling variance by drawing vital rates and calculating λ for increasingly larger populations drawn from a total population of 3842 plants. We then compared these estimates of λ with those based on the entire population and calculated the resulting bias. Finally, we conducted a review of the literature to determine the sample sizes typically used when parameterizing matrix models used to study plant demography.

Conclusions/Significance

We found significant bias at small sample sizes when survival was low (survival = 0.5), and that sampling with a more-realistic inverse J-shaped population structure exacerbated this bias. However our simulations also demonstrate that these biases rapidly become negligible with increasing sample sizes or as survival increases. For many of the sample sizes used in demographic studies, matrix models are probably robust to the biases resulting from sampling variance of vital rates. However, this conclusion may depend on the structure of populations or the distribution of sampling effort in ways that are unexplored. We suggest more intensive sampling of populations when individual survival is low and greater sampling of stages with high elasticities.     

Annual cycles of four flea species in the central Negev desert

Bionomics of fleas (Siphonaptera) parasitizing rodent hosts, mostly the gerbil Gerbillus dasyurus (Wagner) and the jird Meriones crassus Sundevall (Gerbillidae), were investigated in the central Negev desert of Israel. Populations were sampled weekly (by Sherman trapping of hosts) from August 2000 to July 2001. Among 1055 fleas of nine species captured, four species predominated (94%). Two species of Pulicidae, Xenopsylla dipodilli Smit and X. ramesis (Rothschild), reproduced perennially, whereas adults of Nosopsyllus iranus theodori Smit (Ceratophyllidae) and Stenoponia tripectinata medialis Jordan (Hystrichopsyllidae) occurred only in cool months (October-March). During their main activity season on the most infested host species (estimated from > 300 trap-nights/month), prevalence of these four flea species reached 40-70%, 20-30%, 100% and 50-70%, respectively, with infestation intensities of 2-2.7, 7-12, 2-3.5 and 2.5-7 fleas per infested rodent, respectively. Xenopsylla dipodilli oviposition peaked during autumn with parous rate > 80% by September-October. During December-April, the majority of X. dipodilli females were immature and/or nulliparous (defined as having mature ovaries but no follicular relics). In contrast, X. ramesis had two reproductive peaks, in mid-spring and autumn, evidenced by the influx of immature females in late spring and summer (30-40%) and in winter (20-30%) after maximal parous rates: 80-100% in March-April and 95-100% in October-November. Nosopsyllus iranus theodori and Stenoponia tripectinata medialis adults occurred only during cool months. At the beginning of activity, during October-November, the sex ratio of N. i. theodori was strongly biased to females (86%) that were immature and/or nulliparous. In winter, adult females were 52-65% parous and 10-32% immature. In March, as the adult population of N. i. theodori declined, 78% of females were parous and 12% immature. Seasonal activity of S. t. medialis (November-March) was shorter than for the other three species; females were predominantly nulliparous in November (80%), after which the proportion of parous females increased gradually to 84% in February. Two females of S. t. medialis collected in March were mature but nulliparous, suggesting that this species of flea might 'oversummer' (as pupae or teneral adults) in the cocooned stage.     

Maximum likelihood estimation of population growth rates based on the coalescent.

We describe a method for co-estimating 4Nemu (four times the product of effective population size and neutral mutation rate) and population growth rate from sequence samples using Metropolis-Hastings sampling. Population growth (or decline) is assumed to be exponential. The estimates of growth rate are biased upwards, especially when 4Nemu is low; there is also a slight upwards bias in the estimate of 4Nemu itself due to correlation between the parameters. This bias cannot be attributed solely to Metropolis-Hastings sampling but appears to be an inherent property of the estimator and is expected to appear in any approach which estimates growth rate from genealogy structure. Sampling additional unlinked loci is much more effective in reducing the bias than increasing the number or length of sequences from the same locus.     

Blood Feeding Status,Gonotrophic Cycle and Survivorship of <Emphasis Type="Italic">Aedes (Stegomyia) aegypti</Emphasis> (L.) (Diptera: Culicidae) Caught in Churches from Merida,Yucatan, Mexico

Blood-feeding status, gonotrophic cycle, and survival rates of Aedes (Stegmyia) aegypti (L.) was investigated in catholic churches from Merida, Yucatan. Female Ae. aegypti were caught using backpack aspirator during 25 consecutive days in rainy (2015) and dry season (2016). Blood-feeding status was determined by external examination of the abdomen and classified as unfed, fed, and gravid. Daily changes in the parous–nulliparous ratio were recorded, and the gonotrophic cycle length was estimated by a time series analysis. Also, was observed the vitellogenesis to monitoring egg maturity. In total, 408 females Ae. aegypti were caught, and there was a significant difference in the number of females collected per season (Z = ?6.729, P ≤ 0.05). A great number was caught in the rainy season (n = 329). In the dry season, 79 females were caught, which the fed females were twice greatest than the unfed. The length of gonotrophic cycle was estimated on the base of a high correlation coefficient value appearing every 4 days in rainy at 26.7 ± 1.22°C, and 3 days in dry season at 29.8 ± 1.47°C. The daily survival rate of the Ae. aegypti population was higher in both seasons, 0.94 and 0.93 for the rainy and dry season, respectively. The minimum time estimated for developing mature eggs after blood feeding was similar in both seasons (3.5 days in rainy versus 3.25 days in dry). The measurement of the vectorial capacity of Ae. aegypti in catholic churches could help to understand the dynamics of transmission of arboviruses in sites with high human aggregation.     

Demography and life history of a viviparous Central African caecilian amphibian

Many tropical ecosystems support exceptional levels of amphibian diversity, but in contrast to their temperate counterparts, many aspects of their biology are little studied and poorly understood. Demographic studies give valuable insights into the age structure and life histories of amphibian populations, thus they are of high importance in making accurate and precise conservation assessments in the light of current global amphibian declines. We analysed age structure and growth in a population of the viviparous caecilian Geotrypetes seraphini , a caecilian amphibian from Mount Cameroon, Central Africa, by using skeletochronology. We detected lines of arrested growth (LAG) in mid-body vertebrae and interpreted them as indicators of a seasonal growth pattern. We expect that LAG are materialized at a rate of one per year. In our sample male reach sexual maturity at an early age (age class 0+), whereas females mature later (age class 1+). Maximum longevity in our sample was estimated at 4+ years. Body size (total length) was significantly smaller in males than in females. Our study shows that skeletochronology is a highly suitable method to determine caecilian growth and age. Caecilian amphibians show a high diversity of reproductive modes including unusual brood care and parental investment strategies. In order to deepen our understanding of their ecology and evolution, many more demographic studies on other species and lineages are needed.     

A method for estimating population sex ratio for sage‐grouse using noninvasive genetic samples

Population sex ratio is an important metric for wildlife management and conservation, but estimates can be difficult to obtain, particularly for sexually monomorphic species or for species that differ in detection probability between the sexes. Noninvasive genetic sampling (NGS) using polymerase chain reaction (PCR) has become a common method for identifying sex from sources such as hair, feathers or faeces, and is a potential source for estimating sex ratio. If, however, PCR success is sex‐biased, naively using NGS could lead to a biased sex ratio estimator. We measured PCR success rates and error rates for amplifying the W and Z chromosomes from greater sage‐grouse (Centrocercus urophasianus) faecal samples, examined how success and error rates for sex identification changed in response to faecal sample exposure time, and used simulation models to evaluate precision and bias of three sex assignment criteria for estimating population sex ratio with variable sample sizes and levels of PCR replication. We found PCR success rates were higher for females than males and that choice of sex assignment criteria influenced the bias and precision of corresponding sex ratio estimates. Our simulations demonstrate the importance of considering the interplay between the sex bias of PCR success, number of genotyping replicates, sample size, true population sex ratio and accuracy of assignment rules for designing future studies. Our results suggest that using faecal DNA for estimating the sex ratio of sage‐grouse populations has great potential and, with minor adaptations and similar marker evaluations, should be applicable to numerous species.     

Comparative study on longevity of Anopheles sinensis in malarious and non-malarious areas in Korea

An outbreak of vivax malaria has been occurring in northern part of Kyonggi-do and north-western part of Kangwon-do, where are located near the demilitarized zone, since 1993. For understanding of epidemiological features of malaria, the probability of daily survival of Anopheles sinensis, the vector species of malaria was compared in malarious and non-malarious areas in July-August, 2000. Total 915 females collected at three locations in malarious areas were dissected for ovaries, and 64.6% of the parous rate was found. Total 758 females collected at three locations in non-malarious areas were dissected, and 57.8% of the parous rate was observed. It was estimated from the parous rates that the probability of daily survival of An. sinensis females was 0.864 in malarious areas and 0.850 in non-malarious areas, which was not significantly different.     

The feeding behaviour, activity and trappability of wild female Glossina pallidipe in relation to their pregnancy cycle

Female Glossina pallidipes Austen trapped with baited NG2B traps were subjected both to detailed ovarian dissection and to nutritional analysis. Using a calibration curve derived from dissected wild-caught, laboratory-held flies, the field females were assigned by discriminant analysis to each day of the pregnancy cycle. Field females were most available to NG2B traps while carrying the first instar larva. The nutritional characteristics of trapped field females over the pregnancy cycle lead to the following main conclusions. (i) Fat levels increase most rapidly during the egg in utero stage, while CRDW increases significantly only during the larval stages, culminating in a 4 mg increase during the last day of the third larval instar. (ii) The haematin content of the flies indicates that females feed at approximately 3-day intervals and may feed on any day of the pregnancy cycle. (iii) The estimated time of feeding during the day corresponds with the observed time of peak activity, both of which are earlier in the day later in the pregnancy cycle. (iv) The rate of fat usage reveals significantly greater flight activity on day 5 of the cycle than on other days, agreeing with the high trappability on this day, and overall females appear to use fat at twice the rate of males. Reproductive data provide a much more accurate picture of the relative sampling efficiency than do nutritional data, although the latter reveal the general trends correctly.     

Estimating incident population distribution from prevalent data

A prevalent sample consists of individuals who have experienced disease incidence but not failure event at the sampling time. We discuss methods for estimating the distribution function of a random vector defined at baseline for an incident disease population when data are collected by prevalent sampling. Prevalent sampling design is often more focused and economical than incident study design for studying the survival distribution of a diseased population, but prevalent samples are biased by design. Subjects with longer survival time are more likely to be included in a prevalent cohort, and other baseline variables of interests that are correlated with survival time are also subject to sampling bias induced by the prevalent sampling scheme. Without recognition of the bias, applying empirical distribution function to estimate the population distribution of baseline variables can lead to serious bias. In this article, nonparametric and semiparametric methods are developed for distribution estimation of baseline variables using prevalent data.     

Sex ratio,survival, and recapture rate in a Cuban population of the damselfly <Emphasis Type="BoldItalic">Hypolestes trinitatis</Emphasis> (Odonata: Megapodagrionidae)

Male-biased sex ratios in adult odonate populations have been the subject of vigorous discussion between the students of this order of insects. The debate has centered on whether the observed male bias in many populations is real, perhaps due to unequal survival rates, or whether it is an artifact caused by differences in recapture probabilities. A mark–recapture study to assess the relative contribution of survivorship and recapture rates on male-biased sex ratio was performed in a Cuban population of the damselfly Hypolestes trinitatis. Maximum likelihood theory and Akaike information criterion were used for parameter estimation and model selection, respectively. Females in the sample were outnumbered two to one by males. Estimated recapture and survival rates were 0.188 (females) and 0.638 (males), and 0.933 (females) and 0.944 (males), respectively. Recapture rates only partially explained the bias since the population sex ratio estimated after correcting for differences in this parameter was male biased (1.5). The observed higher survival probabilities in males could have generated the male-biased population sex ratio. Therefore, we concluded that the observed male-biased population sex ratio in H. trinitatis is real.     

Comparison of direct and indirect sampling methods for tarnished plant bug (Hemiptera: Miridae) in flowering cotton

A complex of hemipterans, especially the tarnished plant bug, Lygus lineolaris (Palisot de Beauvois) (Hemiptera: Miridae), has become a major target of insecticides in flowering cotton, Gossypium hirsutum L., in the mid-southern United States. Sampling protocols for this complex during this period of cotton development are poorly established, resulting in uncertainty about when infestations warrant treatment. Nine direct and indirect sampling methods were evaluated for bias, precision, and efficiency in cotton throughout the Mid-South during 2005 and 2006. The tarnished plant bug represented 94% of the bug complex in both years. Sweep-net and black drop-cloth methods were more efficient than other direct sampling methods, but they were biased toward adults and nymphs, respectively. Sampling dirty blooms was the most efficient indirect sampling method. The sweep-net, whole-plant, and dirty-bloom methods were more accurate than the other sampling methods evaluated based on correlations with other sampling methods. Variability attributed to the person collecting the sample was significant for all sampling methods, but least significant for the dirty-square method. Further research is needed to establish thresholds based on sweep-net, drop-cloth, dirty-square, and dirty-bloom sampling methods as these methods provide the best combinations of accuracy and efficiency for sampling tarnished plant bugs in cotton.     

Effects of parity on pelvic size and shape dimorphism in Mus

The pelvis is a sexually dimorphic structure and although the causes of that dimorphism have long been studied, relatively little is known regarding the effects of partuitive events on the magnitude of that dimorphism. Here, we use a sample of Mus musculus domesticus to contrast dimorphism in body length and os coxae size and shape between males and parous and nulliparous females. We also test for correlations between relative litter size (L/M) and relative offspring size (O/M) with body length and os coxae size and shape in parous females. Males had greater body length than nulliparous females but were not different from parous females. Females as a whole had the largest os coxae, with parous females having the largest and males the smallest. Os coxae shape was also significantly different between groups and was most divergent between parous females and males than between nulliparous females and males. Os coxae shape differences between females are associated with differences in body length between females and O/M is correlated with os coxae shape in parous females such that females with the largest offspring have the most divergent shapes along the relative warp one axis. Pelvic shape differences between males and females were consistent with previous findings in other taxa which identify the pubo‐ischial complex as the primary region of dimorphism. J. Morphol. 2009. © 2009 Wiley‐Liss, Inc.     

Using habitat suitability models to sample rare species in high-altitude ecosystems: a case study with Tibetan argali

Models of the distribution of rare and endangered species are important tools for their monitoring and management. Presence data used to build up distribution models can be based on simple random sampling, but this for patchy distributed species results in small number of presences and therefore low precision. Convenience sampling, either based on easily accessible units or a priori knowledge of the species habitat but with no known probability of sampling each unit, is likely to result in biased estimates. Stratified random sampling, with strata defined using habitat suitability models [estimated in the resource selection functions (RSFs) framework] is a promising approach for improving the precision of model parameters. We used this approach to sample the Tibetan argali (Ovis ammon hodgsoni) in Indian Transhimalaya in order to estimate their distribution and to test if it can lead to a significant reduction in survey effort compared to random sampling. We first used an initial sample of argali feeding sites in 2005 and 2006 based on a priori selected vantage points and survey transects. This initial sample was used to build up an initial distribution model. The spatial predictions based on estimated RSFs were then used to define three strata of the study area. The strata were randomly sampled in 2007. As expected, much more presences per hour were obtained in the high quality strata compared to the low quality strata—1.33 obs/h vs. 0.080/h. Furthermore the best models selected on the basis of the prospective sample differed from those using the first a priori sample, suggesting bias in the initial sampling effort. The method therefore has significant implications for decreasing sampling effort in terms of sampling time in the field, especially when dealing with rare species, and removing initial sampling bias.