Standardising terminology and notation for the analysis of demographic processes in marked populations

The development of statistical methods for the analysis of demographic processes in marked animal populations has brought with it the challenges of communication between the disciplines of statistics, ecology, evolutionary biology and computer science. In order to aid communication and comprehension, we sought to root out a number of cases of ambiguity, redundancy and inaccuracy in notation and terminology that have developed in the literature. We invited all working in this field to submit topics for resolution and to express their own views. In the ensuing discussion forum it was then possible to establish a series of general principles which were, almost without exception, unanimously accepted. Here we set out the background to the areas of confusion, how these were debated and the conclusions which were reached in each case. We hope that the resulting guidelines will be widely adopted as standard terminology in publications and in software for the analysis of demographic processes in marked animal populationspostprin

Incorporating ‘recruitment’ in matrix projection models : estimation, parameters, and the influence of model structure

Author Posting. © The Author(s), 2010. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Journal of Ornithology 152, Suppl.2 (2012):585-595, doi:10.1007/s10336-010-0573-1.Advances in the estimation of population parameters using encounter data from marked individuals have made it possible to include estimates of the probability of recruitment in population projection models. However, the projected growth rate of the population, and the sensitivity of projected growth to changes in recruitment, can vary significantly depending upon both the structural form of the model and how recruitment is parameterized. We show that the common practices of (1) collapsing some age classes into a single, terminal ‘aggregated’ age-class, and (2) parameterizing recruitment using the proportion of recruited individuals (breeders) in a given age-class may confound analysis of age-based (Leslie) matrix projection models in some instances, relative to state-based projection models where recruited and pre-recruited individuals are treated as separate states. Failing to account for these differences can lead to misinterpretation of the relative role of recruitment in the dynamics of an age-structured population.We show that such problems can be avoided, either by structural changes to the terminal aggregated age-class in age-based models, or by using using a state-based model instead. Since all the metrics of general interest from a classical age-based matrix models are readily derived from a state-based model equivalent, this suggests there may be little reason to use the classical age-based approach in situations where recruitment is a parameter of interest

Inference of the infection status of individuals using longitudinal testing data from cryptic populations: Towards a probabilistic approach to diagnosis

Effective control of many diseases requires the accurate detection of infected individuals. Confidently ascertaining whether an individual is infected can be challenging when diagnostic tests are imperfect and when some individuals go for long periods of time without being observed or sampled. Here, we use a multi-event capture-recapture approach to model imperfect observations of true epidemiological states. We describe a method for interpreting potentially disparate results from individuals sampled multiple times over an extended period, using empirical data from a wild badger population naturally infected with Mycobacterium bovis as an example. We examine the effect of sex, capture history and current and historical diagnostic test results on the probability of being truly infected, given any combination of diagnostic test results. In doing so, we move diagnosis away from the traditional binary classification of apparently infected versus uninfected to a probability-based interpretation which is updated each time an individual is re-sampled. Our findings identified temporal variation in infection status and suggest that capture probability is influenced by year, season and infection status. This novel approach to combining ecological and epidemiological data may aid disease management decision-making by providing a framework for the integration of multiple diagnostic test data with other information

Variance in Centrality within Rock Hyrax Social Networks Predicts Adult Longevity

BACKGROUND: In communal mammals the levels of social interaction among group members vary considerably. In recent years, biologists have realized that within-group interactions may affect survival of the group members. Several recent studies have demonstrated that the social integration of adult females is positively associated with infant survival, and female longevity is affected by the strength and stability of the individual social bonds. Our aim was to determine the social factors that influence adult longevity in social mammals. METHODOLOGY/PRINCIPAL FINDINGS: As a model system, we studied the social rock hyrax (Procavia capensis), a plural breeder with low reproductive skew, whose groups are mainly composed of females. We applied network theory using 11 years of behavioral data to quantify the centrality of individuals within groups, and found adult longevity to be inversely correlated to the variance in centrality. In other words, animals in groups with more equal associations lived longer. Individual centrality was not correlated with longevity, implying that social tension may affect all group members and not only the weakest or less connected ones. CONCLUSIONS/SIGNIFICANCE: Our novel findings support previous studies emphasizing the adaptive value of social associations and the consequences of inequality among adults within social groups. However, contrary to previous studies, we suggest that it is not the number or strength of associations that an adult individual has (i.e. centrality) that is important, but the overall configuration of social relationships within the group (i.e. centrality SD) that is a key factor in influencing longevity

Impacts of Parasites in Early Life: Contrasting Effects on Juvenile Growth for Different Family Members

Parasitism experienced early in ontogeny can have a major impact on host growth, development and future fitness, but whether siblings are affected equally by parasitism is poorly understood. In birds, hatching asynchrony induced by hormonal or behavioural mechanisms largely under parental control might predispose young to respond to infection in different ways. Here we show that parasites can have different consequences for offspring depending on their position in the family hierarchy. We experimentally treated European Shag (Phalacrocorax aristoteli) nestlings with the broad-spectrum anti-parasite drug ivermectin and compared their growth rates with nestlings from control broods. Average growth rates measured over the period of linear growth (10 days to 30 days of age) and survival did not differ for nestlings from treated and control broods. However, when considering individuals within broods, parasite treatment reversed the patterns of growth for individual family members: last-hatched nestlings grew significantly slower than their siblings in control nests but grew faster in treated nests. This was at the expense of their earlier-hatched brood-mates, who showed an overall growth rate reduction relative to last-hatched nestlings in treated nests. These results highlight the importance of exploring individual variation in the costs of infection and suggest that parasites could be a key factor modulating within-family dynamics, sibling competition and developmental trajectories from an early age

Food supplements increase adult tarsus length, but not growth rate, in an island population of house sparrows (Passer domesticus)

<p>Abstract</p> <p>Background</p> <p>Variation in food supply during early development can influence growth rate and body size in many species. However, whilst the detrimental effects of food restriction have often been studied in natural populations, how young individuals respond to an artificial increase in food supply is rarely investigated. Here, we investigated both the short-term and long-term effects of providing house sparrow chicks with food supplements during a key period of growth and development and assessed whether providing food supplements had any persistent effect upon adult size (measured here as tarsus length).</p> <p>Results</p> <p>Male nestlings tended to reach higher mass asymptotes than females. Furthermore, brood size was negatively associated with a chick's asymptotic mass. However, providing food supplements had no influence upon the growth rate or the asymptotic mass of chicks. Adults that received food supplements as chicks were larger, in terms of their tarsus length, than adults that did not receive extra food as chicks. In addition, the variation in tarsus length amongst adult males that were given food supplements as chicks was significantly less than the variance observed amongst males that did not receive food supplements.</p> <p>Conclusions</p> <p>Our results demonstrate that the food supply chicks experience during a critical developmental period can have a permanent effect upon their adult phenotype. Furthermore, providing extra food to chicks resulted in sex-biased variance in a size-related trait amongst adults, which shows that the degree of sexual size dimorphism can be affected by the environment experienced during growth.</p

Deploying System Dynamics Models for Disease Surveillance in the Philippines

Disease surveillance is vital for monitoring outbreaks and designing timely public health interventions. However, especially in developing contexts, disease surveillance efforts are constrained by challenges of data scarcity. In this work, we discuss the deployment of system dynamics simulation models to aid in local disease surveillance programs in the Philippines. More specifically, we propose that (a) available time series records of disease incidence can be used to initialize simulation models with high accuracy and interpretability, and (b) virtual experiments can be used to test various what-if scenarios in designing potential interventions. Experiments with three years of data on dengue fever in the Western Visayas region illustrate our proposed framework as deployed on the FASSSTER platform. We conclude by outlining challenges and potential directions for future work