Genomic Diversity as a Key Conservation Criterion: Proof-of-Concept From Mammalian Whole-Genome Resequencing Data.

Many international, national, state, and local organizations prioritize the ranking of threatened and endangered species to help direct conservation efforts. For example, the International Union for Conservation of Nature (IUCN) assesses the Green Status of species and publishes the influential Red List of threatened species. Unfortunately, such conservation yardsticks do not explicitly consider genetic or genomic diversity (GD), even though GD is positively associated with contemporary evolutionary fitness, individual viability, and with future evolutionary potential. To test whether populations of genome sequences could help improve conservation assessments, we estimated GD metrics from 82 publicly available mammalian datasets and examined their statistical association with attributes related to conservation. We also considered intrinsic biological factors, including trophic level and body mass, that could impact GD and quantified their relative influences. Our results identify key population GD metrics that are both reflective and predictive of IUCN conservation categories. Specifically, our analyses revealed that Watterson's theta (the population mutation rate) and autozygosity (a product of inbreeding) are associated with the current Red List categorization, likely because demographic declines that lead to "listing" decisions also reduce levels of standing genetic variation. We argue that by virtue of this relationship, conservation organizations like IUCN could leverage emerging genome sequence data to help categorize Red List threat rankings (especially in otherwise data-deficient species) and/or enhance Green Status assessments to establish a baseline for future population monitoring. Thus, our paper (1) outlines the theoretical and empirical justification for a new GD-based assessment criterion, (2) provides a bioinformatic pipeline for estimating GD from population genomic data, and (3) suggests an analytical framework that can be used to measure baseline GD while providing quantitative GD context for consideration by conservation authorities.

Habitat remediation followed by managed connectivity reduces unwanted changes in evolutionary trajectory of high extirpation risk populations.

As we continue to convert green spaces into roadways and buildings, connectivity between populations and biodiversity will continue to decline. In threatened and endangered species, this trend is particularly concerning because the cessation of immigration can cause increased inbreeding and loss of genetic diversity, leading to lower adaptability and higher extirpation probabilities in these populations. Unfortunately, monitoring changes in genetic diversity from management actions such as assisted migration and predicting the extent of introduced genetic variation that is needed to prevent extirpation is difficult and costly in situ. Therefore, we designed an agent-based model to link population-wide genetic variability and the influx of unique alleles via immigration to population stability and extirpation outcomes. These models showed that management of connectivity can be critical in restoring at-risk populations and reducing the effects of inbreeding depression. However, the rescued populations were more similar to the migrant source population (average FST range 0.05-0.10) compared to the historical recipient population (average FST range 0.23-0.37). This means that these management actions not only recovered the populations from the effects of inbreeding depression, but they did so in a way that changed the evolutionary trajectory that was predicted and expected for these populations prior to the population crash. This change was most extreme in populations with the smallest population sizes, which are representative of critically endangered species that could reasonably be considered candidates for restored connectivity or translocation strategies. Understanding how these at-risk populations change in response to varying management interventions has broad implications for the long-term adaptability of these populations and can improve future efforts for protecting locally adapted allele complexes when connectivity is restored.

Effects of developmental exposure to neurotoxic algal metabolites on predator-prey interactions in larval Pimephales promelas.

Harmful algal blooms are a growing environmental concern in aquatic systems. Although it is known that some of the secondary metabolites produced by cyanobacteria can alter predator-prey dynamics in aquatic communities by reducing foraging and/or predator evasion success, the mechanisms underpinning such responses are largely unknown. In this study, we examined the effects of a potent algal neurotoxin, ß-N-methylamino-L-alanine (BMAA), on the development and behavior of larval Fathead Minnows, Pimephales promelas, during predator-prey interactions. We exposed eggs and larvae to environmentally relevant concentrations of BMAA for 21 days, then tested subjects in prey-capture and predator-evasion assays designed to isolate the effects of exposure at sequential points of the stimulus-response pathway. Exposure was associated with changes in the ability of larvae to detect and respond to environmental stimuli (i.e., a live prey item and a simulated vibrational predator), as well as changes in behavior and locomotor performance during the response. Our findings suggest that chronic exposure to neurodegenerative cyanotoxins could alter the outcomes of predator-prey interactions in natural systems by impairing an animal's ability to perceive, process, and respond to relevant biotic stimuli.