A stochastic model for estimating sustainable limits to wildlife mortality in a changing world

Human-caused mortality of wildlife is a pervasive threat to biodiversity. Assessing the population-level impact of fisheries bycatch and other human-caused mortality of wildlife has typically relied upon deterministic methods. However, population declines are often accelerated by stochastic factors that are not accounted for in such conventional methods. Building on the widely applied potential biological removal (PBR) equation, we devised a new population modeling approach for estimating sustainable limits to human-caused mortality and applied it in a case study of bottlenose dolphins affected by capture in an Australian demersal otter trawl fishery. Our approach, termed sustainable anthropogenic mortality in stochastic environments (SAMSE), incorporates environmental and demographic stochasticity, including the dependency of offspring on their mothers. The SAMSE limit is the maximum number of individuals that can be removed without causing negative stochastic population growth. We calculated a PBR of 16.2 dolphins per year based on the best abundance estimate available. In contrast, the SAMSE model indicated that only 2.3–8.0 dolphins could be removed annually without causing a population decline in a stochastic environment. These results suggest that reported bycatch rates are unsustainable in the long term, unless reproductive rates are consistently higher than average. The difference between the deterministic PBR calculation and the SAMSE limits showed that deterministic approaches may underestimate the true impact of human-caused mortality of wildlife. This highlights the importance of integrating stochasticity when evaluating the impact of bycatch or other human-caused mortality on wildlife, such as hunting, lethal control measures, and wind turbine collisions. Although population viability analysis (PVA) has been used to evaluate the impact of human-caused mortality, SAMSE represents a novel PVA framework that incorporates stochasticity for estimating acceptable levels of human-caused mortality. It offers a broadly applicable, stochastic addition to the demographic toolbox to evaluate the impact of human-caused mortality on wildlife

Observing Supermassive Black Holes across cosmic time: from phenomenology to physics

In the last decade, a combination of high sensitivity, high spatial resolution observations and of coordinated multi-wavelength surveys has revolutionized our view of extra-galactic black hole (BH) astrophysics. We now know that supermassive black holes reside in the nuclei of almost every galaxy, grow over cosmological times by accreting matter, interact and merge with each other, and in the process liberate enormous amounts of energy that influence dramatically the evolution of the surrounding gas and stars, providing a powerful self-regulatory mechanism for galaxy formation. The different energetic phenomena associated to growing black holes and Active Galactic Nuclei (AGN), their cosmological evolution and the observational techniques used to unveil them, are the subject of this chapter. In particular, I will focus my attention on the connection between the theory of high-energy astrophysical processes giving rise to the observed emission in AGN, the observable imprints they leave at different wavelengths, and the methods used to uncover them in a statistically robust way. I will show how such a combined effort of theorists and observers have led us to unveil most of the SMBH growth over a large fraction of the age of the Universe, but that nagging uncertainties remain, preventing us from fully understating the exact role of black holes in the complex process of galaxy and large-scale structure formation, assembly and evolution.Comment: 46 pages, 21 figures. This review article appears as a chapter in the book: "Astrophysical Black Holes", Haardt, F., Gorini, V., Moschella, U and Treves A. (Eds), 2015, Springer International Publishing AG, Cha

Predators and genetic fitness: key threatening factors for the conservation of a bettong species

Globally, many wildlife species are declining and an increasing number are threatened by extinction or are extinct. Active management is generally required to mitigate these trends and population viability analysis (PVA) enables different scenarios to be evaluated and informs management decisions. Based on population parameters obtained from a threatened bettong, the woylie (Bettongia penicillata ogilbyi), we developed and validated a PVA model. We identified the demographic and genetic responses to different threatening factors and developed a general framework that would facilitate similar work in other bettong species. The two main threatening processes are predation by introduced animals and its interaction with reduced fitness (e.g. due to inbreeding depression or a disease). Although predation alone can drive a decline in certain circumstances (e.g. when predation success is independent from prey population density), synergistically, predation and reduced fitness can be particularly relevant, especially for small populations. The minimum viable population size was estimated at 1000–2000 individuals. In addition, the models identified that research into age-specific mortality rates and predation rates by introduced animals should be the focus of future work. The PVA model created here provides a basis to investigate threatening processes and management strategies in woylie populations and other extant bettong species, given the ecological and physiological similarities among these threatened species