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INTRODUCTION The Anthropocene is marked by an accelerated loss of biodiversity, widespread population declines, and a global conservation crisis. Given limited resources for conservation intervention, an approach is needed to identify threatened species from among the thousands lacking adequate information for status assessments. Such prioritization for intervention could come from genome sequence data, as genomes contain information about demography, diversity, fitness, and adaptive potential. However, the relevance of genomic data for identifying at-risk species is uncertain, in part because genetic variation may reflect past events and life histories better than contemporary conservation status. RATIONALE The Zoonomia multispecies alignment presents an opportunity to systematically compare neutral and functional genomic diversity and their relationships to contemporary extinction risk across a large sample of diverse mammalian taxa. We surveyed 240 species spanning from the “Least Concern” to “Critically Endangered” categories, as published in the International Union for Conservation of Nature’s Red List of Threatened Species. Using a single genome for each species, we estimated historical effective population sizes ( N e ) and distributions of genome-wide heterozygosity. To estimate genetic load, we identified substitutions relative to reconstructed ancestral sequences, assuming that mutations at evolutionarily conserved sites and in protein-coding sequences, especially in genes essential for viability in mice, are predominantly deleterious. We examined relationships between the conservation status of species and metrics of heterozygosity, demography, and genetic load and used these data to train and test models to distinguish threatened from nonthreatened species. RESULTS Species with smaller historical N e are more likely to be categorized as at risk of extinction, suggesting that demography, even from periods more than 10,000 years in the past, may be informative of contemporary resilience. Species with smaller historical N e also carry proportionally higher burdens of weakly and moderately deleterious alleles, consistent with theoretical expectations of the long-term accumulation and fixation of genetic load under strong genetic drift. We found weak support for a causative link between fixed drift load and extinction risk; however, other types of genetic load not captured in our data, such as rare, highly deleterious alleles, may also play a role. Although ecological (e.g., physiological, life-history, and behavioral) variables were the best predictors of extinction risk, genomic variables nonrandomly distinguished threatened from nonthreatened species in regression and machine learning models. These results suggest that information encoded within even a single genome can provide a risk assessment in the absence of adequate ecological or population census data. CONCLUSION Our analysis highlights the potential for genomic data to rapidly and inexpensively gauge extinction risk by leveraging relationships between contemporary conservation status and genetic variation shaped by the long-term demographic history of species. As more resequencing data and additional reference genomes become available, estimates of genetic load, estimates of recent demographic history, and accuracy of predictive models will improve. We therefore echo calls for including genomic information in assessments of the conservation status of species. Genomic information can help predict extinction risk in diverse mammalian species. Across 240 mammals, species with smaller historical N e had lower genetic diversity, higher genetic load, and were more likely to be threatened with extinction. Genomic data were used to train models that predict whether a species is threatened, which can be valuable for assessing extinction risk in species lacking ecological or census data. [Animal silhouettes are from PhyloPic]
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Modeling Pre-Impact Baselines at Scale to Inform Species Recovery
This talk will describe the work of the CPN Pre-Impact Baselines Working Group to leverage the wealth of paleoecological and historical ecological data to facilitate estimation of pre-impact species distribution baselines. Species conservation has long focused on preventing human-driven extinctions, and over the past 50 years conservation success has been measured using changes in species’ extinction risk. However, recently calls have been made for a parallel focus on species recovery, and on developing metrics with which to assess its achievement. This call to action within the conservation community is fuelled in part by the recognition that baselines of species abundance and distribution have shifted dramatically across human generations with globally detectable human impacts on ecosystems beginning at least several thousand years ago. While assessment of extinction risk generally only considers species’ change over the past few decades, assessment of recovery requires considering change over centuries to millennia. This requires identifying the baseline status at the time when humans first became a major factor influencing the abundance and distribution of a species. Two new frameworks for considering conservation status relative to a species’ pre-impact baseline have been recently released: EPOCH (Evaluation of POpulation CHange), and the IUCN Green Status of Species. These frameworks have been lauded as moving conservation in a much-needed direction, but there is also concern about whether these methods will be applicable to any but a few well-known, charismatic species. Using a combination of modelling approaches, we are working to estimate species pre-impact distributions in a way that is accessible to conservation practitioners, helping to unshift the baseline and bring species recovery into the mainstream.
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- Award ID(s):
- 1922562
- PAR ID:
- 10634200
- Publisher / Repository:
- Bulletin of the Florida Museum of Natural History
- Date Published:
- Journal Name:
- Bulletin of the Florida Museum of Natural History
- Volume:
- 60
- Issue:
- 2
- ISSN:
- 2373-9991
- Page Range / eLocation ID:
- 83 to 83
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.58782/flmnh.wosu1828
