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Coral reefs are both exceptionally biodiverse and threatened by climate change and other human activities. Here, we review population genomic processes in coral reef taxa and their importance for understanding responses to global change. Many taxa on coral reefs are characterized by weak genetic drift, extensive gene flow, and strong selection from complex biotic and abiotic environments, which together present a fascinating test of microevolutionary theory. Selection, gene flow, and hybridization have played and will continue to play an important role in the adaptation or extinction of coral reef taxa in the face of rapid environmental change, but research remains exceptionally limited compared to the urgent needs. Critical areas for future investigation include understanding evolutionary potential and the mechanisms of local adaptation, developing historical baselines, and building greater research capacity in the countries where most reef diversity is concentrated. 

Populations can adapt to novel selection pressures through dramatic frequency changes in a few genes of large effect or subtle shifts in many genes of small effect. The latter (polygenic adaptation) is expected to be the primary mode of evolution for many life-history traits but tends to be more difficult to detect than changes in genes of large effect. Atlantic cod (Gadus morhua) were subjected to intense fishing pressure over the twentieth century, leading to abundance crashes and a phenotypic shift toward earlier maturation across many populations. Here, we use spatially replicated temporal genomic data to test for a shared polygenic adaptive response to fishing using methods previously applied to evolve-and-resequence experiments. Cod populations on either side of the Atlantic show covariance in allele frequency change across the genome that are characteristic of recent polygenic adaptation. Using simulations, we demonstrate that the degree of covariance in allele frequency change observed in cod is unlikely to be explained by neutral processes or background selection. As human pressures on wild populations continue to increase, understanding and attributing modes of adaptation using methods similar to those demonstrated here will be important in identifying the capacity for adaptive responses and evolutionary rescue. This article is part of the theme issue ‘Detecting and attributing the causes of biodiversity change: needs, gaps and solutions’. 

Recent research has revealed the diversity and biomass of life across ecosystems, but how that biomass is distributed across body sizes of all living things remains unclear. We compile the present-day global body size-biomass spectra for the terrestrial, marine, and subterranean realms. To achieve this compilation, we pair existing and updated biomass estimates with previously uncatalogued body size ranges across all free-living biological groups. These data show that many biological groups share similar ranges of body sizes, and no single group dominates size ranges where cumulative biomass is highest. We then propagate biomass and size uncertainties and provide statistical descriptions of body size-biomass spectra across and within major habitat realms. Power laws show exponentially decreasing abundance (exponent -0.9±0.02 S.D.,R²= 0.97) and nearly equal biomass (exponent 0.09±0.01,R²= 0.56) across log size bins, which resemble previous aquatic size spectra results but with greater organismal inclusivity and global coverage. In contrast, a bimodal Gaussian mixture model describes the biomass pattern better (R²= 0.86) and suggests small (~10⁻¹⁵g) and large (~10⁷g) organisms outweigh other sizes by one order magnitude (15 and 65 Gt versus ~1 Gt per log size). The results suggest that the global body size-biomass relationships is bimodal, but substantial one-to-two orders-of-magnitude uncertainty mean that additional data will be needed to clarify whether global-scale universal constraints or local forces shape these patterns. 

Abstract The demographic history of a population is important for conservation and evolution, but this history is unknown for many populations. Methods that use genomic data have been developed to infer demography, but they can be challenging to implement and interpret, particularly for large populations. Thus, understanding if and when genetic estimates of demography correspond to true population history is important for assessing the performance of these genetic methods. Here, we used double‐digest restriction‐site associated DNA (ddRAD) sequencing data from archived collections of larval summer flounder (Paralichthys dentatus,n = 279) from three cohorts (1994–1995, 1997–1998 and 2008–2009) along the U.S. East coast to examine how contemporary effective population size and genetic diversity responded to changes in abundance in a natural population. Despite little to no detectable change in genetic diversity, coalescent‐based demographic modelling from site frequency spectra revealed that summer flounder effective population size declined dramatically in the early 1980s. The timing and direction of change corresponded well with the observed decline in spawning stock census abundance in the late 1980s from independent fish surveys. Census abundance subsequently recovered and achieved the prebottleneck size. Effective population size also grew following the bottleneck. Our results for summer flounder demonstrate that genetic sampling and site frequency spectra can be useful for detecting population dynamics, even in species with large effective sizes. 

Synopsis Understanding recent population trends is critical to quantifying species vulnerability and implementing effective management strategies. To evaluate the accuracy of genomic methods for quantifying recent declines (beginning <120 generations ago), we simulated genomic data using forward-time methods (SLiM) coupled with coalescent simulations (msprime) under a number of demographic scenarios. We evaluated both site frequency spectrum (SFS)-based methods (momi2, Stairway Plot) and methods that employ linkage disequilibrium information (NeEstimator, GONE) with a range of sampling schemes (contemporary-only samples, sampling two time points, and serial sampling) and data types (RAD-like data and whole-genome sequencing). GONE and momi2 performed best overall, with >80% power to detect severe declines with large sample sizes. Two-sample and serial sampling schemes could accurately reconstruct changes in population size, and serial sampling was particularly valuable for making accurate inferences when genotyping errors or minor allele frequency cutoffs distort the SFS or under model mis-specification. However, sampling only contemporary individuals provided reliable inferences about contemporary size and size change using either site frequency or linkage-based methods, especially when large sample sizes or whole genomes from contemporary populations were available. These findings provide a guide for researchers designing genomics studies to evaluate recent demographic declines. 

The year 2021 marked the highest temperature and likely the lowest oxygen content for the oceans since human records began ( 1 , 2 ). These changes have put marine species on the front lines of climate change. For example, marine species’ geographical ranges are shifting faster and experiencing more contractions than those of terrestrial species ( 3 , 4 ). However, whether climate change poses an existential threat to ocean life has been less clear. Marine species are often considered to be more resilient to extinction than terrestrial ones, and human-caused global extinctions of marine species have been relatively rare ( 5 ). On page 524 of this issue, Penn and Deutsch ( 6 ) present extensive modeling to reveal that runaway climate change would put ocean life on track for a mass extinction rivaling the worst in Earth’s history. Furthermore, they reveal how keeping global warming below an increase of 2°C compared with preindustrial levels could largely prevent these outcomes.