Physiological Stress Mediates the Honesty of Social Signals

Peer reviewedPublisher PD

Meta-analysis of the effects of predation on animal prey abundance: evidence from UK vertebrates

Background: Controlling vertebrate predators is one of the most widespread forms of wildlife management and it continues to cause conflict between stakeholders worldwide. It is important for managers and policy-makers to make decisions on this issue that are based on the best available scientific evidence. Therefore, it is first important to understand if there is indeed an impact of vertebrate predators on prey, and then to quantify this impact. Methodology/Principal Findings: Using the UK as a case study, we use a meta-analytical approach to review the available evidence to assess the effect of vertebrate predation on animal prey abundance. We find a significant effect of predators on prey abundance across our studies. On average, there is a 1.6 fold increase in prey abundance in the absence of predation. However, we show significant heterogeneity in effect sizes, and discuss how the method of predator control, whether the predator is native or non-native, and aspects of study design, may be potential causes. Conclusions/Significance: Our results allow some cautious policy recommendations to be made regarding the management of predator and prey populations. Meta-analysis is an important tool for understanding general patterns in the effect of predators on prey abundance across studies. Such an approach is especially valuable where management decisions need to be made in the absence of site-specific information

Coping with Natural Hazards in a Conservation Context: Resource-Use Decisions of Maasai Households During Recent and Historical Droughts

Analyzing people’s decisions can reveal key variables that affect their behaviors. Despite the demonstrated utility of this approach, it has not been applied to livelihood decisions in the context of conservation initiatives. We used ethnographic decision modeling in combination with qualitative comparative analysis (QCA) to examine the herding decisions of Maasai households living near Tarangire National Park (TNP) during recent and historical droughts. The effects of the establishment of TNP on herding practices during drought were different than anticipated based on the size and reliability of several prominent resource areas that are now within the park. We found little evidence of people relying on these swamps and rivers for watering cattle during historical droughts; rather, these sites were more commonly used as grazing areas for small stock and wet-season grazing areas for cattle to avoid disease carried by calving wildebeest. Yet during the 2009 drought, many herders moved their livestock – especially cattle from outside of the study area – toward TNP in search of grazing. Our analysis of herding decisions demonstrates that resource-use decisions are complex and incorporate a variety of information beyond the size or reliability of a given resource area, including contextual factors (e.g., disease, conflict, grazing) and household factors (e.g., social capital, labor, herd size). More broadly, this research illustrates that pairing decision modeling with QCA is a structured approach to identifying these factors and understanding how opportunities, constraints, and perceptions influence how people respond to changes in resource access

Behavioural variation in Eurasian perch populations with respect to relative catchability

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Radiation Hormesis: Historical Perspective and Implications for Low-Dose Cancer Risk Assessment

Current guidelines for limiting exposure of humans to ionizing radiation are based on the linear-no-threshold (LNT) hypothesis for radiation carcinogenesis under which cancer risk increases linearly as the radiation dose increases. With the LNT model even a very small dose could cause cancer and the model is used in establishing guidelines for limiting radiation exposure of humans. A slope change at low doses and dose rates is implemented using an empirical dose and dose rate effectiveness factor (DDREF). This imposes usually unacknowledged nonlinearity but not a threshold in the dose-response curve for cancer induction. In contrast, with the hormetic model, low doses of radiation reduce the cancer incidence while it is elevated after high doses. Based on a review of epidemiological and other data for exposure to low radiation doses and dose rates, it was found that the LNT model fails badly. Cancer risk after ordinarily encountered radiation exposure (medical X-rays, natural background radiation, etc.) is much lower than projections based on the LNT model and is often less than the risk for spontaneous cancer (a hormetic response). Understanding the mechanistic basis for hormetic responses will provide new insights about both risks and benefits from low-dose radiation exposure