Measuring the demographic parameters of exploited populations is central to predicting their vulnerability and extinction risk. However, current rates of population decline and species loss greatly outpace our ability to empirically monitor all populations that are potentially threatened. The scale of this problem cannot be addressed through additional data collection alone, and therefore it is a common practice to conduct population assessments based on surrogate data collected from similar species. However, this approach introduces biases and imprecisions that are difficult to quantify. Recent developments in hierarchical modelling have enabled missing values to be reconstructed based on the correlations between available life‐history data, linking similar species based on phylogeny and environmental conditions. However, these methods cannot resolve life‐history variability among populations or species that are closely placed spatially or taxonomically. Here, theoretically motivated constraints that align with life‐history theory offer a new avenue for addressing this problem. We describe a Bayesian hierarchical approach that combines fragmented, multispecies and multi‐population data with established life‐history theory, in order to objectively determine similarity between populations based on trait correlations (life‐history trade‐offs) obtained from model fitting. We reconstruct 59 unobserved life‐history parameters for 23 populations of tuna that sustain some of the world's most valuable fisheries. Testing by cross‐validation across different scenarios indicated that life‐histories were accurately reconstructed when information was available for other populations of the same species. The reconstruction of several traits was also accurate for species represented by a single population, although credible intervals increased dramatically.
This content will become publicly available on May 1, 2024
The unsustainable harvest of species for the global wildlife trade is a major cause of vertebrate extinction. Through the anthropogenic Allee effect (AAE), overexploitation to extinction can occur when a species' rarity drives up its market price, enabling profitable harvest of all remaining individuals. Even in the absence of rarity value, however, the harvest of other species can subsidize the overexploitation of a rare species to the point of extinction, a phenomenon termed opportunistic exploitation. These two pathways to extinction have been considered independently, but many traded species experience them simultaneously. In this study, we develop a simple model that incorporates these mechanisms simultaneously and demonstrate that including multiple harvest strategies with market‐based feedbacks fundamentally alters rare species extinction risk and the rate at which overexploitation occurs. As a pertinent case study, we consider the harvest of ground pangolins Our results show that pangolin extinction was generally associated with high rarity value, the use of multiple harvest strategies and the simultaneous harvest of a common species that has a fast life history. Pangolin population depletion and short‐term extinction risk were greatest when harvesters used a combination of pursuit and opportunistic (i.e. multi‐species) harvest strategies.
- Award ID(s):
- 2052616
- NSF-PAR ID:
- 10494990
- Publisher / Repository:
- John Wiley & Sons Ltd
- Date Published:
- Journal Name:
- Journal of Applied Ecology
- Volume:
- 60
- Issue:
- 5
- ISSN:
- 0021-8901
- Page Range / eLocation ID:
- 754 to 763
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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