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Diversity
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Bayesian Survival Trajectory Analysis in Wildlife
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Bayesian Survival Trajectory Analysis in Wildlife

A special issue of Diversity (ISSN 1424-2818). This special issue belongs to the section "Animal Diversity".

Deadline for manuscript submissions: closed (31 October 2019) | Viewed by 9926

Special Issue Editor

Dr. Fernando Colchero

E-Mail Website
Guest Editor
Syddansk Universitet, Department of Mathematics and Computer Science, Odense, Denmark

Special Issue Information

Dear Colleagues,

Today, we know that there is a large diversity of age-specific trajectories of mortality and fecundity in wild populations (Jones et al. 2014) and that ignoring these trajectories can have serious implications on the estimation of population dynamics (Colchero et al. 2019). These age-specific trajectories of mortality are commonly estimated from sampling efforts in the wild, such as capture–mark–recapture or capture–mark–recovery. However, due to the difficulty in sampling individuals from birth or in estimating the age of individuals first captured as adults, researchers are forced to make simplifying assumptions, such as constant adult mortality. Bayesian survival trajectory analysis (BaSTA) was developed as a modeling tool that allows researchers to estimate age-specific mortality when times of birth are scarce or even entirely missing from the dataset (Colchero and Clark 2012). The method can be implemented by means of a freely available R package (BaSTA; Colchero et al. 2012), while it has become an important tool for researchers interested in senescence, population dynamics, and conservation, among many other disciplines. This Special Issue aims at providing a forum for researchers using Bayesian survival trajectory analysis, while highlighting the breadth and scope of research using the method.

Dr. Fernando Colchero
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diversity is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Bayesian survival trajectory analysis
  • Survival
  • Mortality
  • Bayesian inference
  • Senescence
  • Population dynamics

Published Papers (3 papers)

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Research

12 pages, 1380 KiB  
Article
Assessing the Diversity of the Form of Age-Specific Changes in Adult Mortality from Captive Mammalian Populations
by Victor Ronget, Jean-François Lemaître, Morgane Tidière and Jean-Michel Gaillard
Diversity 2020, 12(9), 354; https://doi.org/10.3390/d12090354 - 15 Sep 2020
Cited by 6 | Viewed by 2472
Abstract
Actuarial senescence (i.e., the age-specific increase in mortality rate) is pervasive across mammalian species, but our current understanding of the diversity of forms that actuarial senescence displays across species remains limited. Although several mathematical models have been proposed to model actuarial senescence, there [...] Read more.
Actuarial senescence (i.e., the age-specific increase in mortality rate) is pervasive across mammalian species, but our current understanding of the diversity of forms that actuarial senescence displays across species remains limited. Although several mathematical models have been proposed to model actuarial senescence, there is still no consensus on which model to use, especially when comparing mortality patterns among species. To fill this knowledge gap, we fitted and compared different forms of increase using models commonly used in senescence studies (i.e., Gompertz, Weibull, and logistic) across 61 species of mammalian captive populations using the Bayesian Survival Trajectory Analysis (BaSTA) approach. For as much as 79% of the species, a Gompertz increase of mortality with age was the most parsimonious model that satisfactorily described the shape of age-specific mortality changes in adults. This highlights that the form of the increase in mortality is mostly consistent across mammalian species and follows the Gompertz rule with some rare exceptions. The implications of that result are twofold. First, the Gompertz rate of mortality increase should be used in cross-species comparative analyses of mammals, as already done in some studies. Second, although the Gompertz model accurately describes actuarial senescence in most mammals, there are notable exceptions, and the factors causing this deviation from an exponential mortality increase during the adult stage warrant further investigation. Full article
(This article belongs to the Special Issue Bayesian Survival Trajectory Analysis in Wildlife)
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14 pages, 5602 KiB  
Article
Age-Independent Adult Mortality in a Long-Lived Herb
by Stina Edelfeldt, Torbjörn Lindell and Johan P. Dahlgren
Diversity 2019, 11(10), 187; https://doi.org/10.3390/d11100187 - 1 Oct 2019
Cited by 6 | Viewed by 3102
Abstract
Relative to mammals and birds, little is known about the mortality trajectories of perennial plants, as there are few long-term demographic studies following multiple yearly cohorts from birth to death. This is particularly important because if reproductively mature individuals show actuarial senescence, current [...] Read more.
Relative to mammals and birds, little is known about the mortality trajectories of perennial plants, as there are few long-term demographic studies following multiple yearly cohorts from birth to death. This is particularly important because if reproductively mature individuals show actuarial senescence, current estimations of life spans assuming constant survival would be incorrect. There is also a lack of studies documenting how life history trade-offs and disturbance influence the mortality trajectories of plants. We conducted Bayesian survival trajectory analyses (BaSTA) of a 33-year individual-based dataset of Pulsatilla vulgaris ssp. gotlandica. Mortality trajectories corresponded to “Type III” survivorship patterns, with rapidly decreasing annual mortality rates for young plants, but with constant mortality for reproductively mature individuals. We found trade-off effects resulting in a cost of growth for non-reproductive plants but no apparent cost of reproduction. Contrarily to our expectation, young plants that had previously shrunk in size had a lower mortality. However, accounting for trade-offs and disturbance only had minor effects on the mortality trajectories. We conclude that BaSTA is a useful tool for assessing mortality patterns in plants if only partial age information is available. Furthermore, if constant mortality is a general pattern in polycarpic plants, long-term studies may not be necessary to assess their age-dependent demography. Full article
(This article belongs to the Special Issue Bayesian Survival Trajectory Analysis in Wildlife)
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16 pages, 1353 KiB  
Article
Analysis of Lifetime Mortality Trajectories in Wildlife Disease Research: BaSTA and Beyond
by Dave W. Hudson, Richard Delahay, Robbie A. McDonald, Trevelyan J. McKinley and Dave J. Hodgson
Diversity 2019, 11(10), 182; https://doi.org/10.3390/d11100182 - 1 Oct 2019
Cited by 3 | Viewed by 3920
Abstract
Wildlife hosts are important reservoirs of a wide range of human and livestock infections worldwide, and in some instances, wildlife populations are threatened by disease. Yet wildlife diseases are difficult to monitor, and we often lack an understanding of basic epidemiological parameters that [...] Read more.
Wildlife hosts are important reservoirs of a wide range of human and livestock infections worldwide, and in some instances, wildlife populations are threatened by disease. Yet wildlife diseases are difficult to monitor, and we often lack an understanding of basic epidemiological parameters that might inform disease management and the design of targeted interventions. The impacts of disease on host survival are generally associated with age, yet traditional epidemiological models tend to use simplistic categories of host age. Mortality trajectory analysis provides the opportunity to understand age-specific impacts of disease and uncover epidemiological patterns across complete life histories. Here, we use Bayesian survival trajectory analysis (BaSTA) software to analyse capture-mark-recapture data from a population of wild badgers Meles meles naturally infected with Mycobacterium bovis, the causative agent of tuberculosis in badgers and cattle. We reveal non-constant mortality trajectories, and show that infection exaggerates an age-dependent increase in late-life mortality. This study provides evidence for actuarial senescence in badgers, a species previously believed to display constant mortality throughout life. Our case study demonstrates the application of mortality trajectory analysis in wildlife disease research, but also highlights important limitations. We recommend BaSTA for mortality trajectory analysis in epidemiological research, but also suggest combining approaches that can include diagnostic uncertainty and the movement of hosts between disease states as they age. We recommend future combinations of multi-state and multi-event modelling frameworks for complex systems incorporating age-varying disease states. Full article
(This article belongs to the Special Issue Bayesian Survival Trajectory Analysis in Wildlife)
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