Evaluating genomic data for management of local adaptation in a changing climate: A lodgepole pine case study

Abstract

The need for tools to cost-effectively identify adaptive variation within ecologically and 13 economically important plant species is mounting as the detrimental effects of climate change 14 become increasingly apparent. For crop and wild populations alike, mismatches between adaptive 15 variation and climatic optima will reduce health, growth, survival, reproduction, and continued 16 establishment. The ease with which land managers can quantify the relative importance of different 17climate factors or the spatial scale of local adaptation to climate will have direct implications for 18 the potential of mitigating or resolving such risks. Using seed collected from 281 provenances of 19 lodgepole pine (Pinus contorta) from across western Canada, we compare genomic data to 20 phenotypic and climatic data to assess their effectiveness in characterizing the climatic drivers and 21 spatial scale of local adaptation in this species. We find that genomic and climate data are nearly 22 equivalent for describing local adaptation in seedling traits. We also find strong agreement between 23 the climate variables associated with genomic variation and with 20-year heights from a long-term 24 provenance trial, suggesting that genomic data may be a viable option for identifying climatic 25 drivers of local adaptation where phenotypic data are unavailable. Genetic clines associated with 26 cold injury occur at broad spatial scales, suggesting that standing variation of adaptive alleles for 27 this and similar species does not require management at scales finer than are indicated by 28 phenotypic data. This study demonstrates that genomic data are most useful when paired with 29 phenotypic data, but can also fill some of the traditional roles of phenotypic data in management 30of species for which phenotypic trials are not feasible.

Can long‐lived species keep pace with climate change? Evidence of local persistence potential in a widespread conifer

“…This finding, combined with outcomes from the Illingworth provenance trials in British Columbia (e.g., Rehfeldt et al., 1999, 2001; Ying & Liang, 1994), supports the notion that P. contorta populations are locally adapted to somewhat narrower ranges of climatic conditions than are present across its entire range. Cold‐tolerance, for example, may have affected survival in our study, a characteristic observed to strongly affect P. contorta survival and growth (Liepe et al., 2016; Mahony et al., 2020; Rehfeldt et al., 1999, 2001; Wang et al., 2010). In our experiment, murrayana and contorta populations had strikingly low survival in the cooler latifolia garden (Figure 3c), suggesting maladaptation to the extreme winter temperatures of this intermountain climate.…”

“…Local declines are likely in portions of the species’ distribution where, despite predicted increases in precipitation (Mahony et al., 2017), concurrent temperature increases will change the timing and type of precipitation (e.g., from snow‐ to rain‐dominated precipitation; Buma et al., 2019) and thus growing‐season water availability. Given that drought is expected to become increasingly common across its range (Coops & Waring, 2011; Mahony et al., 2020), drought adaptation may be key to local P. contorta population persistence.…”

“…Louden) is one of the most widely distributed tree species in North America, and its occurrence across a topographically and climatically heterogeneous landscape makes it a consummate species for quantifying the influence of landscape complexity on genetic and phenotypic variation. For this reason, P. contorta is one of the most well-studied conifers in biogeographical (e.g., Strong, 2010;Wheeler & Critchfield, 1985;Wheeler & Guries, 1982a, 1982b, forest productivity (e.g., Chuine et al, 2006;McLane et al, 2011;Rehfeldt et al, 1999;Wang et al, 2010) and evolutionary (e.g., Fazekas & Yeh, 2006;Godbout et al, 2008;Liepe et al, 2016;Mahony et al, 2020;Yang & Yeh, 1995) research on forest tree species. However, little is known about the influence of climatically and topographically heterogeneous landscapes on range-wide population genetic structure and population response to novel landscape conditions in this and other widely distributed tree species-information critical to evaluating local population persistence under future conditions.…”

Combining genotype, phenotype, and environmental data to delineate site‐adjusted provenance strategies for ecological restoration

“…By using the combined candidate loci detected in GEA and GPA, using both univariate and multivariate methods, we improved the detection of single‐locus and multilocus adaptive signals. (Mahony et al., 2019; Talbot et al., 2016; Vangestel et al, 2018)⁠. Interestingly, more intersections between GEA and GPA were found when using RDA than when using LFMM (Figure 3), indicating that most adaptations to local environmental conditions expressing differential phenotypes are polygenic (Forester et al., 2018)⁠.…”

“…While the assessment of phenotype through common garden and reciprocal transplant experiments to identify local adaptations has a long history (Aitken & Bemmels, 2016)⁠, no study has yet combined genotype‐environment associations (GEA) with genotype‐phenotype associations (GPA) to delineate seed sourcing areas. This approach could improve the inference of potential candidate genes and provide important insights into genes underlying fitness‐related traits (Mahony et al., 2019; Talbot et al., 2016; Vangestel, Eckert, Wegrzyn, St. Clair, & Neale, 2018)⁠.…”