A model for first‐estimates of species‐specific, age‐specific mortality from centralized band‐recovery databases

Abstract

Citation: Baylis, S. M., P. Sunnucks, and R. Clarke. 2018. A model for first-estimates of species-specific, age-specific mortality from centralized band-recovery databases. Ecosphere 9(4):e02136. 10.1002/ecs2.2136Abstract. Population mortality curves, otherwise known as lifetime distribution functions, can be indispensable in many areas of ecology and environmental management including population viability and stock management analyses, disaster-recovery monitoring, and fundamental evolutionary biology. Yet available modeling tools are often unable to estimate population mortality curves from commonly available datasets because these datasets fail to meet stringent experimental-design requirements. Here, we present a new method for estimating population mortality curves from records of marked individuals found dead. Such data are increasingly accessible in some of the largest biological datasets, such as continent-or nation-wide marking-and-recovery schemes for birds and other animals. The method accounts for known biases in availability by age class, variable monitoring effort through time, and mark loss. We show that our modeling approach generates accurate estimates of population mortality structure across a range of populations differing in marking histories, true mortality curves, monitoring regimes, and mark loss rates. Our approach can be applied to multiple species or groups at a time and can provide estimates of interannual adult, immature, and first-year survival rates, required by predictive modeling applications such as population viability analyses. Our approach is also capable of estimating apparent senescence rates for each population and facilitates evolutionary analyses of life-history traits. For example, our method is potentially useful for exploring the evolution of senescence or for inter-group comparisons of mortality rates where groups that differ by environment may be identified within mark-recovery records. To demonstrate the efficacy of this method, we present fitted population mortality curves for a suite of seabird species represented in a national mark-recapture database.

Age estimation in a long‐lived seabird (Ardenna tenuirostris) using DNA methylation‐based biomarkers

“…The oldest individual, at 21 years old, represents a little over half of the maximum reported lifespan for this species of 39 years. However, research on age‐dependent survival on Fisher Island birds shows few animals living beyond 25 years post‐first breeding, which would place our oldest individual at closer to 70% of the expected lifespan of approximately 30 years (Baylis, Sunnucks, & Clarke, ; Bradley et al, ). The relationship we have observed with age should be investigated further for older individuals; however, previous studies in mammals have primarily shown linear correlations with age (Maegawa et al, ; Polanowski et al, ; Spiers et al, ).…”

Estimates of wear rates in metal bird bands, with applications for survival and movement models of marked individuals

“…In particular, we collected these data because the national‐scale ABBBS mark–recapture dataset has been made open‐access, and estimates of band wear across a wide phylogenetic range are useful in analyses of national‐scale mark–recapture (Baylis et al. ). We hope that our set of estimates will be useful to researchers performing further analyses of the ABBBS dataset and other open‐access mark–recapture datasets.…”

“…Similarly, some population‐structure estimates perform a correction for expected band loss inferred from observed band wear (e.g., Ludwig , Baylis et al. ). The lack of wear‐rate estimates for many taxa limits the ability of researchers to make inferences about population structure for these taxa.…”

“…For many taxa, there is little empirical support for the idea that bands outlast the birds that are banded, potentially limiting the ability of investigators to make informed statements about whether the bands used are fit-forpurpose for those taxa. Similarly, some population-structure estimates perform a correction for expected band loss inferred from observed band wear (e.g., Ludwig 1981, Baylis et al 2018. The lack of wear-rate estimates for many taxa limits the ability of researchers to make inferences about population structure for these taxa.…”

“…More generally, worn bands may become illegible or be lost, and illegible or lost bands present a critical challenge to many mark-recapture models. We have not estimated band loss here, but Ludwig (1981) and Baylis et al (2018) provided examples of how band wear rates may be used to parameterize models estimating rates of band loss through time. Mark loss may also be estimated by marking animals with a permanent mark and a mark subject to loss, especially in studies where highly visible marks allow animals to be resighted without requiring capture, but highly visible marks are also at an increased risk of loss (e.g., Samuel et al 2001).…”