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

Variabilidade genética da raça Brahman no Brasil detectada por meio de análise de pedigree

O objetivo deste trabalho foi analisar a variabilidade genética da raça Brahman no Brasil, por meio da análise de 15.851 pedigrees. O arquivo de dados foi dividido em dois períodos: 1998-2001 e 2002-2005. A variabilidade genética foi avaliada por parâmetros baseados na probabilidade de origem do gene: número efetivo de ancestrais, número efetivo de fundadores, número efetivo de genomas remanescentes e coeficientes de parentesco e de endogamia. Os valores encontrados quanto ao número de fundadores mostraram que a população está em expansão, embora o número efetivo de fundadores tenha diminuído de um período para outro. Os resultados foram diferentes em relação ao número de ancestrais e genomas remanescentes, que apresentaram crescimento de 23% nos períodos avaliados. O coeficiente de endogamia diminuiu nos períodos estudados, porém o coeficiente de parentesco "inter se" cresceu. Poucos ancestrais apresentaram grande contribuição genética para a população, o que evidencia a utilização de poucos indivíduos na reprodução. A raça Brahman, no Brasil, encontra-se em expansão, caracterizada pela diminuição do coeficiente de endogamia e aumento nos números efetivos de fundadores e de genótipos remanescentes. Entretanto, a variabilidade genética da raça mostra aumento do parentesco "inter se" e grande concentração do patrimônio genético de poucos indivíduos na população

Population structure of Brazilian Gyr dairy cattle

The objective of the present study was to evaluate the genetic structure of Gyr cattle selected for milk production. Files of pedigree and production were composed of 27,610 animals. The ENDOG program was used for the calculation of individual inbreeding coefficient (F) and coefficient of average relatedness (AR), effective number of animals(Ne), effective number of founders (f e) and ancestors (f a), and generation interval (GI). Individual inbreeding coefficients and average relatedness in the population were 2.82% and 2.10%, respectively. It was observed a reduction in the effective number of animals, especially after publication of the results of the first progeny test. The estimated effective number of founders was 146 and 75 for the ancestrals. Out of those, only 28 ancestors accounted for the origin of 50% of the population genes. The average generation interval was 8.41 years and it was longer for males than for females. For maintaining genetic variability in future generations, it should be invested mating strategies that reduce inbreeding and which do not use massively only some high breeding value sires.O objetivo neste trabalho foi avaliar a estrutura genética da raça Gir selecionada para produção de leite. Os arquivos de pedigree e de produção eram compostos de 27.610 animais. Utilizou-se o programa ENDOG para cálculo dos coeficientes individuais de endogamia (F) e coeficiente de relação médio (AR), número efetivo de animais (Ne), de fundadores (fe) e de ancestrais (fa) e do intervalo de gerações (GI). Os coeficientes individuais de endogamia e de relação médios da população foram 2,82 e 2,10%, respectivamente. Foi observada redução do número efetivo de animais, especialmente após a publicação dos resultados do primeiro teste de progênie. O número efetivo de fundadores estimado foi de 146 e o de ancestrais, 75. Desses, apenas 28 ancestrais foram responsáveis pela origem de 50% dos genes da população. O intervalo médio de gerações foi 8,41 anos e foi maior para machos que para fêmeas. Para manutenção da variabilidade genética em futuras gerações, deve-se investir em estratégias de acasalamento que reduzam a endogamia e que não façam uso maciço de apenas alguns reprodutores de alto valor genético

A note on ENDOG: a computer program for analysing pedigree information

The aim of this note is to describe the program endog (v.3.0). The program handles pedigree information to conduct several demographic and genetic analyses including: (a) the individual inbreeding and average relatedness coefficients; (b) effective population size; (c) parameters characterizing the concentration of both gene and individuals origin such as the effective number of founders and ancestors, the effective number of founder herds; (d) F statistics and paired genetic distances for each subpopulation under study; (e) descriptors of the genetic importance of the herds in a population and (f) generation intervals. The program will help breeders and researchers to monitor the changes in genetic variability and population structure with limited costs of preparing datasets. The program, user’s guide and example file can be downloaded free of charge from the World Wide Web at http://www.ucm.es/ info/prodanim/Endog30.zip