Abstract: Predation on livestock is a source of human-wildlife conflicts and can undermine the conservation of large carnivores. To design effective mitigation strategies, it is important to understand the determinants of predation across livestock species, which often differ in husbandry practices, vulnerability to predators and economic value. Moreover, attention should be given to both predation occurrence and intensity, because these can have different spatial patterns and predictors. We used spatial risk modelling to quantify factors affecting wolf predation on five livestock species in Portugal. Within the 1619 parishes encompassing the entire wolf range in the country, the national wolf compensation scheme recorded 17,670 predation events in 2009-2015, each involving one or more livestock species: sheep (31.7%), cattle (27.7%), goats (26.8%), horses (14.8%) and donkeys (3.2%). Models built with 2009-2013 data and validated with 2014-2015 data, showed a shared general pattern of predation probability on each species increasing with its own density and proximity to wolf packs. For some species there were positive relations with the density of other livestock species, and with habitat variables such as altitude, and land cover by shrubland and natural pastures. There was also a general pattern for predation intensity on each species increasing with its own density, while proximity to wolf packs had no significant effects. Predation intensity on goats, cattle and horses increased with the use of communal versus private pastures. Our results suggest that although predation may occur wherever wolves coexist with livestock species, high predation intensity is mainly restricted to particular areas where husbandry practices increase the vulnerability of animals, and this is where mitigation efforts should concentrate.

Abstract: Lipid-lowering fibrate drugs function as agonists for the nuclear receptor peroxisome proliferator-activated receptor alpha (PPARalpha). Sustained activation of PPARalpha leads to the development of liver tumors in rats and mice. However, humans appear to be resistant to the induction of peroxisome proliferation and the development of liver cancer by fibrate drugs. The molecular basis of this species difference is not known. To examine the mechanism determining species differences in peroxisome proliferator response between mice and humans, a PPARalpha-humanized mouse line was generated in which the human PPARalpha was expressed in liver under control of the tetracycline responsive regulatory system. The PPARalpha-humanized and wild-type mice responded to treatment with the potent PPARalpha ligand Wy-14643 as revealed by induction of genes encoding peroxisomal and mitochondrial fatty acid metabolizing enzymes and resultant decrease of serum triglycerides. However, surprisingly, only the wild-type mice and not the PPARalpha-humanized mice exhibited hepatocellular proliferation as revealed by elevation of cell cycle control genes, increased incorporation of 5-bromo-2'-deoxyuridine into hepatocyte nuclei, and hepatomegaly. These studies establish that following ligand activation, the PPARalpha-mediated pathways controlling lipid metabolism are independent from those controlling the cell proliferation pathways. These findings also suggest that structural differences between human and mouse PPARalpha are responsible for the differential susceptibility to the development of hepatocarcinomas observed after treatment with fibrates. The PPARalpha-humanized mice should serve as models for use in drug development and human risk assessment and to determine the mechanism of hepatocarcinogenesis of peroxisome proliferators.

Abstract: Altruism poses a problem for evolutionary biologists because natural selection is not expected to favor behaviors that are beneficial to recipients, but costly to actors. The theory of kin selection, first articulated by Hamilton (1964), provides a solution to the problem. Hamilton's well-known rule (br > c) provides a simple algorithm for the evolution of altruism via kin selection. Because kin recognition is a crucial requirement of kin selection, it is important to know whether and how primates can recognize their relatives. While conventional wisdom has been that primates can recognize maternal kin, but not paternal kin, this view is being challenged by new findings. The ability to recognize kin implies that kin selection may shape altruistic behavior in primate groups. I focus on two cases in which kin selection is tightly woven into the fabric of social life. For female baboons, macaques, and vervets maternal kinship is an important axis of social networks, coalitionary activity, and dominance relationships. Detailed studies of the patterning of altruistic interactions within these species illustrate the extent and limits of nepotism in their social lives. Carefully integrated analyses of behavior, demography, and genetics among red howlers provide an independent example of how kin selection shapes social organization and behavior. In red howlers, kin bonds shape the life histories and reproductive performance of both males and female. The two cases demonstrate that kin selection can be a powerful source of altruistic activity within primate groups. However, to fully assess the role of kin selection in primate groups, we need more information about the effects of kinship on the patterning of behavior across the Primates and accurate information about paternal kin relationships.

Abstract: Summary Reliable assessment of animal populations is a long-standing challenge in wildlife ecology. Technological advances have led to widespread adoption of camera traps (CTs) to survey wildlife distribution, abundance and behaviour. As for any wildlife survey method, camera trapping must contend with sources of sampling error such as imperfect detection. Early applications focused on density estimation of naturally marked species, but there is growing interest in broad-scale CT surveys of unmarked populations and communities. Nevertheless, inferences based on detection indices are controversial, and the suitability of alternatives such as occupancy estimation is debatable. We reviewed 266 CT studies published between 2008 and 2013. We recorded study objectives and methodologies, evaluating the consistency of CT protocols and sampling designs, the extent to which CT surveys considered sampling error, and the linkages between analytical assumptions and species ecology. Nearly two-thirds of studies surveyed more than one species, and a majority used response variables that ignored imperfect detection (e.g. presence?absence, relative abundance). Many studies used opportunistic sampling and did not explicitly report details of sampling design and camera deployment that could affect conclusions. Most studies estimating density used capture?recapture methods on marked species, with spatially explicit methods becoming more prominent. Few studies estimated density for unmarked species, focusing instead on occupancy modelling or measures of relative abundance. While occupancy studies estimated detectability, most did not explicitly define key components of the modelling framework (e.g. a site) or discuss potential violations of model assumptions (e.g. site closure). Studies using relative abundance relied on assumptions of equal detectability, and most did not explicitly define expected relationships between measured responses and underlying ecological processes (e.g. animal abundance and movement). Synthesis and applications. The rapid adoption of camera traps represents an exciting transition in wildlife survey methodology. We remain optimistic about the technology's promise, but call for more explicit consideration of underlying processes of animal abundance, movement and detection by cameras, including more thorough reporting of methodological details and assumptions. Such transparency will facilitate efforts to evaluate and improve the reliability of camera trap surveys, ultimately leading to stronger inferences and helping to meet modern needs for effective ecological inquiry and biodiversity monitoring.