How do foragers decide when to leave a patch? A test of alternative models under natural and experimental conditions.

This is the peer reviewed version of the article which has been published in final form at DOI: http://dx.doi.org/10.1111/1365-2656.12089. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.© 2013 The Authors. Journal of Animal Ecology © 2013 British Ecological Society.A forager's optimal patch-departure time can be predicted by the prescient marginal value theorem (pMVT), which assumes they have perfect knowledge of the environment, or by approaches such as Bayesian updating and learning rules, which avoid this assumption by allowing foragers to use recent experiences to inform their decisions. In understanding and predicting broader scale ecological patterns, individual-level mechanisms, such as patch-departure decisions, need to be fully elucidated. Unfortunately, there are few empirical studies that compare the performance of patch-departure models that assume perfect knowledge with those that do not, resulting in a limited understanding of how foragers decide when to leave a patch. We tested the patch-departure rules predicted by fixed rule, pMVT, Bayesian updating and learning models against one another, using patch residency times (PRTs) recorded from 54 chacma baboons (Papio ursinus) across two groups in natural (n = 6175 patch visits) and field experimental (n = 8569) conditions. We found greater support in the experiment for the model based on Bayesian updating rules, but greater support for the model based on the pMVT in natural foraging conditions. This suggests that foragers may place more importance on recent experiences in predictable environments, like our experiment, where these experiences provide more reliable information about future opportunities. Furthermore, the effect of a single recent foraging experience on PRTs was uniformly weak across both conditions. This suggests that foragers' perception of their environment may incorporate many previous experiences, thus approximating the perfect knowledge assumed by the pMVT. Foragers may, therefore, optimize their patch-departure decisions in line with the pMVT through the adoption of rules similar to those predicted by Bayesian updating.Natural Environment Research Council (NERC)Fenner School of Environment and SocietyLeakey FoundationAnimal Behavior Society (USA)International Primatological SocietyExplorers Club Exploration Fun

Barriers to linking high-risk jail detainees to HIV pre-exposure prophylaxis

Individuals involved in the criminal justice (CJ) system continue to be at disproportionate risk for HIV infection, and often have a greater prevalence of substance use and sexual related risk behaviors relative to their non-CJ involved peers. Pre-exposure prophylaxis (PrEP), a once daily antiretroviral medicine, is an evidence-based approach for reducing the risk of contracting HIV but limited data exist regarding the use of PrEP among CJ populations, especially in the U.S. South. This study was conducted at the Pulaski County Regional Detention Facility (PCRDF) in Little Rock, Arkansas (AR), the largest county jail in the state. We explored knowledge about PrEP and HIV, perceptions about PrEP feasibility in both the jail and community settings and barriers to PrEP program implementation, through in-depth qualitative interviews with 21 jail detainees. We purposively sampled individuals based on specific self-reported risk behavior, including sexual risk (both heterosexual and same-sex) and drug related risk (e.g. IDU), among all eligible individuals. We identified five primary themes from the interviews: 1) accessing healthcare during community reentry was a low priority; 2) perception of risk and interaction with people with HIV was low; 3) there are many barriers to disclosing HIV risk behaviors in jail settings; 4) knowledge of PrEP is low but willingness to use is high; and 5) multiple barriers exist to PrEP uptake post-release. Our findings are contextually unique and therefore have important implications for future implementation of PrEP access either within jail settings or linkage to PrEP post release

The Peculiar Debris Disk of HD 111520 as Resolved by the Gemini Planet Imager

Using the Gemini Planet Imager (GPI), we have resolved the circumstellar debris disk around HD 111520 at a projected range of ~30-100 AU in both total and polarized $H$-band intensity. The disk is seen edge-on at a position angle of ~165$^{\circ}$ along the spine of emission. A slight inclination or asymmetric warping are covariant and alters the interpretation of the observed disk emission. We employ 3 point spread function (PSF) subtraction methods to reduce the stellar glare and instrumental artifacts to confirm that there is a roughly 2:1 brightness asymmetry between the NW and SE extension. This specific feature makes HD 111520 the most extreme examples of asymmetric debris disks observed in scattered light among similar highly inclined systems, such as HD 15115 and HD 106906. We further identify a tentative localized brightness enhancement and scale height enhancement associated with the disk at ~40 AU away from the star on the SE extension. We also find that the fractional polarization rises from 10 to 40% from 0.5" to 0.8" from the star. The combination of large brightness asymmetry and symmetric polarization fraction leads us to believe that an azimuthal dust density variation is causing the observed asymmetry.Comment: 9 pages, 8 Figures, 1 table, Accepted to Ap

The Global Risk Approach Should Be Better Applied in French Hypertensive Patients: A Comparison between Simulation and Observation Studies

The prediction of the public health impact of a preventive strategy provides valuable support for decision-making. International guidelines for hypertension management have introduced the level of absolute cardiovascular risk in the definition of the treatment target population. The public health impact of implementing such a recommendation has not been measured.We assessed the efficiency of three treatment scenarios according to historical and current versions of practice guidelines on a Realistic Virtual Population representative of the French population aged from 35 to 64 years: 1) BP≥160/95 mm Hg; 2) BP≥140/90 mm Hg and 3) BP≥140/90 mm Hg plus increased CVD risk. We compared the eligibility following the ESC guidelines with the recently observed proportion of treated amongst hypertensive individuals reported by the Etude Nationale Nutrition Santé survey. Lowering the threshold to define hypertension multiplied by 2.5 the number of eligible individuals. Applying the cardiovascular risk rule reduced this number significantly: less than 1/4 of hypertensive women under 55 years and less than 1/3 of hypertensive men below 45 years of age. This was the most efficient strategy. Compared to the simulated guidelines application, men of all ages were undertreated (between 32 and 60%), as were women over 55 years (70%). By contrast, younger women were over-treated (over 200%).The global CVD risk approach to decide for treatment is more efficient than the simple blood pressure level. However, lack of screening rather than guideline application seems to explain the low prescription rates among hypertensive individuals in France. Multidimensional analyses required to obtain these results are possible only through databases at the individual level: realistic virtual populations should become the gold standard for assessing the impact of public health policies at the national level

The role of quantitative cross-case analysis in understanding tropical smallholder farmers’ adaptive capacity to climate shocks

Climate shocks are predicted to increase in magnitude and frequency as the climate changes, notably impacting poor and vulnerable communities across the Tropics. The urgency to better understand and improve communities' resilience is reflected in international agreements such as the Paris Agreement and the multiplication of adaptation research and action programs. In turn, the need for collecting and communicating evidence on the climate resilience of communities has increasingly drawn questions concerning how to assess resilience. While empirical case studies are often used to delve into the context-specific nature of resilience, synthesizing results is essential to produce generalizable findings at the scale at which policies are designed. Yet datasets, methods and modalities that enable cross-case analyses that draw from individual local studies are still rare in climate resilience literature. We use empirical case studies on the impacts of El Niño on smallholder households from five countries to test the application of quantitative data aggregation for policy recommendation. We standardized data into an aggregated dataset to explore how key demographic factors affected the impact of climate shocks, modeled as crop loss. We find that while cross-study results partially align with the findings from the individual projects and with theory, several challenges associated with quantitative aggregation remain when examining complex, contextual and multi-dimensional concepts such as resilience. We conclude that future exercises synthesizing cross-site empirical evidence in climate resilience could accelerate research to policy impact by using mixed methods, focusing on specific landscapes or regional scales, and facilitating research through the use of shared frameworks and learning exercises