Toward accurate and precise estimates of lion density

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

环境中的药物——LC-MS/MS分析地表水和地下水

成百上千的活性物质正被用于人药和兽药处方中.由于药物的广泛应用,它们的残留物可通过多种途径进入环境.虽然主要通过尿和粪便的排泄,但是药品生产中的排放也应被考虑.当抗生素用于水产业,就会产生更直接的影响.污水处理设备不能完全除去药物,因此药物会出现在地表和地下水样品中.近年来,人们对环境中药物的兴趣正在增加,需要建立一种快速、灵敏、有选择性的方法来分析水样.     

Living with Wildlife and Mitigating Conflicts Around Three Indian Protected Areas

Crop and livestock losses to wildlife are a concern for people neighboring many protected areas (PAs) and can generate opposition to conservation. Examining patterns of conflict and associated tolerance is important to devise policies to reduce conflict impacts on people and wildlife. We surveyed 398 households from 178 villages within 10 km of Ranthambore, Kanha, and Nagarahole parks in India. We compared different attitudes toward wildlife, and presented hypothetical response scenarios, including killing the problem animal(s). Eighty percent of households reported crop losses to wildlife and 13 % livestock losses. Higher crop loss was associated with more cropping months per year, greater crop variety, and more harvest seasons per year but did not vary with proximity to the PA, suggesting that PAs are not necessarily “sources” for crop raiders. By contrast, complaints of “depredating carnivores” were associated with people-grazing animals and collecting resources from PAs. Many households (83 %) engaged in mitigation efforts. We found that only fencing and guard animals reduce crop losses, and no efforts to lower livestock losses. Contrary to our expectations, carnivores were not viewed with more hostility than crop-raiding wildlife. Households reported greater inclination to kill herbivores destroying crops or carnivores harming people, but not carnivores preying on livestock. Our model estimated crop loss was 82 % across surveyed households (highest in Kanha), while the livestock loss experienced was 27 % (highest in Ranthambore). Our comparative study provides insights into factors associated with conflict loss and tolerance, and aids in improving ongoing conservation and compensation efforts.     

Density estimation in tiger populations: combining information for strong inference

A productive way forward in studies of animal populations is to efficiently make use of all the information available, either as raw data or as published sources, on critical parameters of interest. In this study, we demonstrate two approaches to the use of multiple sources of information on a parameter of fundamental interest to ecologists: animal density. The first approach produces estimates simultaneously from two different sources of data. The second approach was developed for situations in which initial data collection and analysis are followed up by subsequent data collection and prior knowledge is updated with new data using a stepwise process. Both approaches are used to estimate density of a rare and elusive predator, the tiger, by combining photographic and fecal DNA spatial capture-recapture data. The model, which combined information, provided the most precise estimate of density (8.5 +/- 1.95 tigers/100 km2 [posterior mean +/- SD]) relative to a model that utilized only one data source (photographic, 12.02 +/- 3.02 tigers/100 km2 and fecal DNA, 6.65 +/- 2.37 tigers/100 km2). Our study demonstrates that, by accounting for multiple sources of available information, estimates of animal density can be significantly improved.     

Cross-sectional biomonitoring study of pesticide exposures in Queensland,Australia, using pooled urine samples

A range of pesticides are available in Australia for use in agricultural and domestic settings to control pests, including organophosphate and pyrethroid insecticides, herbicides, and insect repellents, such as N,N-diethyl-meta-toluamide (DEET). The aim of this study was to provide a cost-effective preliminary assessment of background exposure to a range of pesticides among a convenience sample of Australian residents. De-identified urine specimens stratified by age and sex were obtained from a community-based pathology laboratory and pooled (n = 24 pools of 100 specimens). Concentrations of urinary pesticide biomarkers were quantified using solid-phase extraction coupled with isotope dilution high-performance liquid chromatography–tandem mass spectrometry. Geometric mean biomarker concentrations ranged from <0.1 to 36.8 ng/mL for organophosphate insecticides, <0.1 to 5.5 ng/mL for pyrethroid insecticides, and <0.1 to 8.51 ng/mL for all other biomarkers with the exception of the DEET metabolite 3-diethylcarbamoyl benzoic acid (4.23 to 850 ng/mL). We observed no association between age and concentration for most biomarkers measured but noted a “U-shaped” trend for five organophosphate metabolites, with the highest concentrations observed in the youngest and oldest age strata, perhaps related to age-specific differences in behavior or physiology. The fact that concentrations of specific and non-specific metabolites of the organophosphate insecticide chlorpyrifos were higher than reported in USA and Canada may relate to differences in registered applications among countries. Additional biomonitoring programs of the general population and focusing on vulnerable populations would improve the exposure assessment and the monitoring of temporal exposure trends as usage patterns of pesticide products in Australia change over time.