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1. Population genomic structure of a widespread, urban‐dwelling mammal: The eastern grey squirrel ( Sciurus carolinensis )

   https://doi.org/10.1111/mec.17230  

   Fusco, Nicole A.; Cosentino, Bradley J.; Gibbs, James P.; Allen, Maximilian L.; Blumenfeld, Alexander J.; Boettner, George H.; Carlen, Elizabeth J.; Collins, Merri; Dennison, Catherine; DiGiacopo, Devin; et al (December 2023, Molecular Ecology)

   Abstract Urbanization is a persistent and widespread driver of global environmental change, potentially shaping evolutionary processes due to genetic drift and reduced gene flow in cities induced by habitat fragmentation and small population sizes. We tested this prediction for the eastern grey squirrel (Sciurus carolinensis), a common and conspicuous forest‐dwelling rodent, by obtaining 44K SNPs using reduced representation sequencing (ddRAD) for 403 individuals sampled across the species' native range in eastern North America. We observed moderate levels of genetic diversity, low levels of inbreeding, and only a modest signal of isolation‐by‐distance. Clustering and migration analyses show that estimated levels of migration and genetic connectivity were higher than expected across cities and forested areas, specifically within the eastern portion of the species' range dominated by urbanization, and genetic connectivity was less than expected within the western range where the landscape is fragmented by agriculture. Landscape genetic methods revealed greater gene flow among individual squirrels in forested regions, which likely provide abundant food and shelter for squirrels. Although gene flow appears to be higher in areas with more tree cover, only slight discontinuities in gene flow suggest eastern grey squirrels have maintained connected populations across urban areas in all but the most heavily fragmented agricultural landscapes. Our results suggest urbanization shapes biological evolution in wildlife species depending strongly on the composition and habitability of the landscape matrix surrounding urban areas. 

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2. A Synthesis of Game Theory and Quantitative Genetic Models of Social Evolution

   https://doi.org/10.1093/jhered/esab064  

   McGlothlin, Joel W.; Akçay, Erol; Brodie, III, Edmund D.; Moore, Allen J.; Van Cleve, Jeremy; Hughes, ed., Kimberly (February 2022, Journal of Heredity)

   Abstract Two popular approaches for modeling social evolution, evolutionary game theory and quantitative genetics, ask complementary questions but are rarely integrated. Game theory focuses on evolutionary outcomes, with models solving for evolutionarily stable equilibria, whereas quantitative genetics provides insight into evolutionary processes, with models predicting short-term responses to selection. Here we draw parallels between evolutionary game theory and interacting phenotypes theory, which is a quantitative genetic framework for understanding social evolution. First, we show how any evolutionary game may be translated into two quantitative genetic selection gradients, nonsocial and social selection, which may be used to predict evolutionary change from a single round of the game. We show that synergistic fitness effects may alter predicted selection gradients, causing changes in magnitude and sign as the population mean evolves. Second, we show how evolutionary games involving plastic behavioral responses to partners can be modeled using indirect genetic effects, which describe how trait expression changes in response to genes in the social environment. We demonstrate that repeated social interactions in models of reciprocity generate indirect effects and conversely, that estimates of parameters from indirect genetic effect models may be used to predict the evolution of reciprocity. We argue that a pluralistic view incorporating both theoretical approaches will benefit empiricists and theorists studying social evolution. We advocate the measurement of social selection and indirect genetic effects in natural populations to test the predictions from game theory and, in turn, the use of game theory models to aid in the interpretation of quantitative genetic estimates. 

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3. Genetic structure and landscape effects on gene flow in the Neotropical lizard Norops brasiliensis (Squamata: Dactyloidae)

   https://doi.org/10.1038/s41437-024-00682-5  

   Fonseca, Emanuel_M; Pope, Nathaniel_S; Peterman, William_E; Werneck, Fernanda_P; Colli, Guarino_R; Carstens, Bryan_C (April 2024, Heredity)

   Abstract One key research goal of evolutionary biology is to understand the origin and maintenance of genetic variation. In the Cerrado, the South American savanna located primarily in the Central Brazilian Plateau, many hypotheses have been proposed to explain how landscape features (e.g., geographic distance, river barriers, topographic compartmentalization, and historical climatic fluctuations) have promoted genetic structure by mediating gene flow. Here, we asked whether these landscape features have influenced the genetic structure and differentiation in the lizard speciesNorops brasiliensis(Squamata: Dactyloidae). To achieve our goal, we used a genetic clustering analysis and estimate an effective migration surface to assess genetic structure in the focal species. Optimized isolation-by-resistance models and a simulation-based approach combined with machine learning (convolutional neural network; CNN) were then used to infer current and historical effects on population genetic structure through 12 unique landscape models. We recovered five geographically distributed populations that are separated by regions of lower-than-expected gene flow. The results of the CNN showed that geographic distance is the sole predictor of genetic variation inN. brasiliensis, and that slope, rivers, and historical climate had no discernible influence on gene flow. Our novel CNN approach was accurate (89.5%) in differentiating each landscape model. CNN and other machine learning approaches are still largely unexplored in landscape genetics studies, representing promising avenues for future research with increasingly accessible genomic datasets. 

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4. Mapping the connectivity–conflict interface to inform conservation

   https://doi.org/10.1073/pnas.2211482119  

   Vasudev, Divya; Fletcher, Robert J.; Srinivas, Nishanth; Marx, Andrew J.; Goswami, Varun R. (January 2023, Proceedings of the National Academy of Sciences)

   Balancing the competing, and often conflicting, needs of people and wildlife in shared landscapes is a major challenge for conservation science and policy worldwide. Connectivity is critical for wildlife persistence, but dispersing animals may come into conflict with people, leading to severe costs for humans and animals and impeding connectivity. Thus, conflict mitigation and connectivity present an apparent dilemma for conservation. We present a framework to address this dilemma and disentangle the effects of barriers to animal movement and conflict-induced mortality of dispersers on connectivity. We extend random-walk theory to map the connectivity–conflict interface, or areas where frequent animal movement may lead to conflict and conflict in turn impedes connectivity. We illustrate this framework with the endangered Asian elephantElephas maximus, a species that frequently disperses out of protected areas and comes into conflict with humans. We mapped expected movement across a human-dominated landscape over the short- and long-term, accounting for conflict mortality. Natural and conflict-induced mortality together reduced expected movement and connectivity among populations. Based on model validation, our conflict predictions that explicitly captured animal movement better explained observed conflict than a model that considered distribution alone. Our work highlights the interaction between connectivity and conflict and enables identification of location-specific conflict mitigation strategies that minimize losses to people, while ensuring critical wildlife movement between habitats. By predicting where animal movement and humans collide, we provide a basis to plan for broad-scale conservation and the mutual well-being of wildlife and people in shared landscapes. 

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5. Sulfur cycling connects microbiomes and biogeochemistry in deep-sea hydrothermal plumes

   https://doi.org/10.1038/s41396-023-01421-0  

   Zhou, Zhichao; Tran, Patricia Q.; Adams, Alyssa M.; Kieft, Kristopher; Breier, John A.; Fortunato, Caroline S.; Sheik, Cody S.; Huber, Julie A.; Li, Meng; Dick, Gregory J.; et al (January 2023, The ISME Journal)

   Abstract In globally distributed deep-sea hydrothermal vent plumes, microbiomes are shaped by the redox energy landscapes created by reduced hydrothermal vent fluids mixing with oxidized seawater. Plumes can disperse over thousands of kilometers and their characteristics are determined by geochemical sources from vents, e.g., hydrothermal inputs, nutrients, and trace metals. However, the impacts of plume biogeochemistry on the oceans are poorly constrained due to a lack of integrated understanding of microbiomes, population genetics, and geochemistry. Here, we use microbial genomes to understand links between biogeography, evolution, and metabolic connectivity, and elucidate their impacts on biogeochemical cycling in the deep sea. Using data from 36 diverse plume samples from seven ocean basins, we show that sulfur metabolism defines the core microbiome of plumes and drives metabolic connectivity in the microbial community. Sulfur-dominated geochemistry influences energy landscapes and promotes microbial growth, while other energy sources influence local energy landscapes. We further demonstrated the consistency of links among geochemistry, function, and taxonomy. Amongst all microbial metabolisms, sulfur transformations had the highest MW-score, a measure of metabolic connectivity in microbial communities. Additionally, plume microbial populations have low diversity, short migration history, and gene-specific sweep patterns after migrating from background seawater. Selected functions include nutrient uptake, aerobic oxidation, sulfur oxidation for higher energy yields, and stress responses for adaptation. Our findings provide the ecological and evolutionary bases of change in sulfur-driven microbial communities and their population genetics in adaptation to changing geochemical gradients in the oceans. 

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