Using dogs to find cats: detection dogs as a survey method for wide-ranging cheetah

Rapid global large carnivore declines make evaluations of remaining populations critical. Yet landscape-scale evaluations of presence, abundance and distribution are difficult, as many species are wide-ranging, occur only at low densities and are elusive. Insufficient information-gathering tools for many large carnivore species compounds these challenges. Specially trained detection dogs have demonstrated effectiveness for carnivore surveys, but are untested on extremely sparse, wide-ranging species, such as cheetah Acinonyx jubatus. In this study, we conducted the first rigorous cheetah survey using detection dogs in a key transboundary area in the remote Liuwa–Mussuma Transfrontier Conservation Area (TFCA) in Western Zambia. We proposed to (1) evaluate the effectiveness of detection dog versus spoor surveys in detecting cheetah presence; (2) extract and analyze DNA from scat samples to estimate minimum population size and genetic effective population size; (3) determine the extent of cheetah occurrence in the unprotected transboundary corridor. Two detection dog teams surveyed 2432 km2 containing 74 randomly located transects in the transfrontier area. Twenty-seven cheetah scats were detected and confirmed by genetic analysis, while no cheetah spoor was detected, clearly demonstrating the superiority of detection dogs in detecting cheetah presence. Combining scat samples with opportunistically collected samples, we estimated 17–19 cheetahs, an effective population size of 8–14 and a density of 5.9–6.6 per 1000 km2. Cheetah utilized key transfrontier areas outside of the national park; however, because utilization appears low, improved connectivity and protection for these areas are critical. Approximately one third of Africa's estimated cheetah resides in protected areas, with 87% in transboundary areas. Our study demonstrates the efficacy of detection dog survey methods in providing information on cheetah across large landscapes. It will have particular value in areas where other survey means may be impossible, such as TFCAs, where size, remoteness and lack of accessibility often make traditional survey methods difficult or cost prohibitive

Predicting Bison Migration out of Yellowstone National Park Using Bayesian Models

Long distance migrations by ungulate species often surpass the boundaries of preservation areas where conflicts with various publics lead to management actions that can threaten populations. We chose the partially migratory bison (Bison bison) population in Yellowstone National Park as an example of integrating science into management policies to better conserve migratory ungulates. Approximately 60% of these bison have been exposed to bovine brucellosis and thousands of migrants exiting the park boundary have been culled during the past two decades to reduce the risk of disease transmission to cattle. Data were assimilated using models representing competing hypotheses of bison migration during 1990–2009 in a hierarchal Bayesian framework. Migration differed at the scale of herds, but a single unifying logistic model was useful for predicting migrations by both herds. Migration beyond the northern park boundary was affected by herd size, accumulated snow water equivalent, and aboveground dried biomass. Migration beyond the western park boundary was less influenced by these predictors and process model performance suggested an important control on recent migrations was excluded. Simulations of migrations over the next decade suggest that allowing increased numbers of bison beyond park boundaries during severe climate conditions may be the only means of avoiding episodic, large-scale reductions to the Yellowstone bison population in the foreseeable future. This research is an example of how long distance migration dynamics can be incorporated into improved management policies

Integrated Modelling for river basin management planning

Complex spatio-temporal environmental problems call for an integrated assessment of environmental systems due to their interdisciplinary nature. Within this context, the approach of Integrated Water Resource Management (IWRM) at the catchment scale, which is at the heart of advanced European environmental policy such as the Water Framework Directive (WFD), argues for integrated modelling tools and approaches. This paper examines recent technological developments that facilitate integrated modelling and focuses on a novel approach, the Open Modelling Interface (OpenMI), which allows models built by different developers to communicate at runtime. The individual models, when made compliant with the OpenMI standard, can be considered as “components” of an integrated model and seamlessly exchange data. Two OpenMI-enabled integrated modelling case studies are presented and their results critically discussed. The paper concludes with opportunities and challenges towards the design of flexible, component-based models supporting integrated environmental policy in general and the WFD implementation in particular

Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies

Background Uncertainties persist about the magnitude of associations of diabetes mellitus and fasting glucose concentration with risk of coronary heart disease and major stroke subtypes. We aimed to quantify these associations for a wide range of circumstances. Methods We undertook a meta-analysis of individual records of diabetes, fasting blood glucose concentration, and other risk factors in people without initial vascular disease from studies in the Emerging Risk Factors Collaboration. We combined within-study regressions that were adjusted for age, sex, smoking, systolic blood pressure, and body-mass index to calculate hazard ratios (HRs) for vascular disease. Findings Analyses included data for 698 782 people (52765 non-fatal or fatal vascular outcomes; 8.49 million person-years at risk) from 102 prospective studies. Adjusted HRs with diabetes were: 2.00 (95% CI 1.83-2.19) for coronary heart disease; 2.27 (1.95-2.65) for ischaemic stroke; 1.56 (1.19-2.05) for haemorrhagic stroke; 1.84 (1.59-2.13) for unclassified stroke; and 1.73 (1.51-1.98) for the aggregate of other vascular deaths. HRs did not change appreciably after further adjustment for lipid, inflammatory, or renal markers. HRs for coronary heart disease were higher in women than in men, at 40-59 years than at 70 years and older, and with fatal than with non-fatal disease. At an adult population-wide prevalence of 10%, diabetes was estimated to account for 11% (10-12%) of vascular deaths. Fasting blood glucose concentration was non-linearly related to vascular risk, with no significant associations between 3.90 mmol/L and 5.59 mmol/L. Compared with fasting blood glucose concentrations of 3.90-5.59 mmol/L, HRs for coronary heart disease were: 1.07 (0.97-1.18) for lower than 3.90 mmol/L; 1.11 (1.04-1.18) for 5.60-6-09 mmol/L; and 1.17 (1.08-1.26) for 6.10-6.99 mmol/L. In people without a history of diabetes, information about fasting blood glucose concentration or impaired fasting glucose status did not significantly improve metrics of vascular disease prediction when added to information about several conventional risk factors. Interpretation Diabetes confers about a two-fold excess risk for a wide range of vascular diseases, independently from other conventional risk factors. In people without diabetes, fasting blood glucose concentration is modestly and nonlinearly associated with risk of vascular disease.Pathophysiology, epidemiology and therapy of agein