Opinion: Is gene mapping in wild populations useful for understanding and predicting adaptation to global change?

How Can Genomics Help or Hinder Wildlife Conservation?

Genomic data are becoming increasingly affordable and easy to collect, and new tools for their analysis are appearing rapidly. Conservation biologists are interested in using this information to assist in management and planning but are typically limited financially and by the lack of genomic resources available for non-model taxa. It is therefore important to be aware of the pitfalls as well as the benefits of applying genomic approaches. Here, we highlight recent methods aimed at standardizing population assessments of genetic variation, inbreeding, and forms of genetic load and methods that help identify past and ongoing patterns of genetic interchange between populations, including those subjected to recent disturbance. We emphasize challenges in applying some of these methods and the need for adequate bioinformatic support. We also consider the promises and challenges of applying genomic approaches to understand adaptive changes in natural populations to predict their future adaptive capacity.

Moving beyond heritability in the search for coral adaptive potential

Global environmental change is happening at unprecedented rates. Coral reefs are among the ecosystems most threatened by global change. For wild populations to persist, they must adapt. Knowledge shortfalls about corals' complex ecological and evolutionary dynamics, however, stymie predictions about potential adaptation to future conditions. Here, we review adaptation through the lens of quantitative genetics. We argue that coral adaptation studies can benefit greatly from "wild" quantitative genetic methods, where traits are studied in wild populations undergoing natural selection, genomic relationship matrices can replace breeding experiments, and analyses can be extended to examine genetic constraints among traits. In addition, individuals with advantageous genotypes for anticipated future conditions can be identified. Finally, genomic genotyping supports simultaneous consideration of how genetic diversity is arrayed across geographic and environmental distances, providing greater context for predictions of phenotypic evolution at a metapopulation scale.

Climate differently influences the genomic patterns of two sympatric marine fish species

Climate influences population genetic variation in marine species. Capturing these impacts remains challenging for marine fishes which disperse over large geographical scales spanning steep environmental gradients. It requires the extensive spatial sampling of individuals or populations, representative of seascape heterogeneity, combined with a set of highly informative molecular markers capable of revealing climatic-associated genetic variations. We explored how space, dispersal and environment shape the genomic patterns of two sympatric fish species in the Mediterranean Sea, which ranks among the oceanic basins most affected by climate change and human pressure. We hypothesized that the population structure and climate-associated genomic signatures of selection would be stronger in the less mobile species, as restricted gene flow tends to facilitate the fixation of locally adapted alleles. To test our hypothesis, we genotyped two species with contrasting dispersal abilities: the white seabream Diplodus sargus and the striped red mullet Mullus surmuletus. We collected 823 individuals and used genotyping by sequencing (GBS) to detect 8,206 single nucleotide polymorphisms (SNPs) for the seabream and 2,794 for the mullet. For each species, we identified highly differentiated genomic regions (i.e. outliers) and disentangled the relative contribution of space, dispersal and environmental variables (climate, marine primary productivity) on the outliers' genetic structure to test the prevalence of gene flow and local adaptation. We observed contrasting patterns of gene flow and adaptive genetic variation between the two species. The seabream showed a distinct Alboran sea population and panmixia across the Mediterranean Sea. The mullet revealed additional differentiation within the Mediterranean Sea that was significantly correlated to summer and winter temperatures, as well as marine primary productivity. Functional annotation of the climate-associated outlier SNPs then identified candidate genes involved in heat tolerance that could be examined to further predict species' responses to climate change. Our results illustrate the key steps of a comparative seascape genomics study aiming to unravel the evolutionary processes at play in marine species, to better anticipate their response to climate change. Defining population adaptation capacities and environmental niches can then serve to incorporate evolutionary processes into species conservation planning.

Divergent patterns between phenotypic and genetic variation in Scots pine

In boreal forests, autumn frost tolerance in seedlings is a critical fitness component because it determines survival rates during regeneration. To understand the forces that drive local adaptation in this trait, we conducted freezing tests in a common garden setting for 54 Pinus sylvestris (Scots pine) populations (>5000 seedlings) collected across Scandinavia into western Russia, and genotyped 24 of these populations (>900 seedlings) at >10 000 SNPs. Variation in cold hardiness among populations, as measured by Q_ST , was above 80% and followed a distinct cline along latitude and longitude, demonstrating significant adaptation to climate at origin. In contrast, the genetic differentiation was very weak (mean F_ST 0.37%). Despite even allele frequency distribution in the vast majority of SNPs among all populations, a few rare alleles appeared at very high or at fixation in marginal populations restricted to northwestern Fennoscandia. Genotype-environment associations showed that climate variables explained 2.9% of the genetic differentiation, while genotype-phenotype associations revealed a high marker-estimated heritability of frost hardiness of 0.56, but identified no major loci. Very extensive gene flow, strong local adaptation, and signals of complex demographic history across markers are interesting topics of forthcoming studies on this species to better clarify signatures of selection and demography.

Research challenges and opportunities for using big data in global change biology

Global change biology has been entering a big data era due to the vast increase in availability of both environmental and biological data. Big data refers to large data volume, complex data sets, and multiple data sources. The recent use of such big data is improving our understanding of interactions between biological systems and global environmental changes. In this review, we first explore how big data has been analyzed to identify the general patterns of biological responses to global changes at scales from gene to ecosystem. After that, we investigate how observational networks and space-based big data have facilitated the discovery of emergent mechanisms and phenomena on the regional and global scales. Then, we evaluate the predictions of terrestrial biosphere under global changes by big modeling data. Finally, we introduce some methods to extract knowledge from big data, such as meta-analysis, machine learning, traceability analysis, and data assimilation. The big data has opened new research opportunities, especially for developing new data-driven theories for improving biological predictions in Earth system models, tracing global change impacts across different organismic levels, and constructing cyberinfrastructure tools to accelerate the pace of model-data integrations. These efforts will uncork the bottleneck of using big data to understand biological responses and adaptations to future global changes.