Temperature and Rainfall Are Separate Agents of Selection Shaping Population Differentiation in a Forest Tree

Silva, J Costa e; Potts, Brad M.; Harrison, Peter A.; Bailey, Tanya G.

doi:10.3390/f10121145

Cited by 21 publications

(26 citation statements)

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“…We chose the mean maximum temperature of the warmest month (BIO5) to test the effect of filtering on genotype-environment association (GEA) analyses. Temperature was selected as it is commonly used in GEA analyses and a key selective force given projected increases into the future; BIO5 represents the high temperature extremes, presumably a greater selective pressure than mean annual temperatures in Australia (Prober et al, 2016;Costa e Silva, Potts, Harrison, & Bailey, 2019). To assess the potential effect of multiple variables confounding GEA results, we also tested mean precipitation of the driest month (BIO14), representing a second key selective force of precipitation.…”

Section: Snp and Climate Datamentioning

confidence: 99%

Regarding theF-word: the effects of dataFilteringon inferred genotype-environment associations

Ahrens

Jordan

Bragg

et al. 2020

Preprint

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Genotype-environment association (GEA) methods have become part of the standard landscape genomics toolkit, yet, we know little about how to filter genotype-by-sequencing data to provide robust inferences for environmental adaptation. In many cases, default filtering thresholds for minor allele frequency and missing data are applied regardless of sample size, having unknown impacts on the results. These effects could be amplified in downstream predictions, including management strategies. Here, we investigate the effects of filtering on GEA results and the potential implications for adaptation to environment. Using empirical and simulated datasets derived from two widespread tree species to assess the effects of filtering on GEA outputs. Critically, we find that the level of filtering of missing data and minor allele frequency affect the identification of true positives. Even slight adjustments to these thresholds can change the rate of true positive detection. Using conservative thresholds for missing data and minor allele frequency substantially reduces the size of the dataset, lessening the power to detect adaptive variants (i.e. simulated true positives) with strong and weak strength of selections. Regardless, strength of selection was a good predictor for GEA detection, but even SNPs under strong selection went undetected. We further show that filtering can significantly impact the predictions of adaptive capacity of species in downstream analyses. We make several recommendations regarding filtering for GEA methods. Ultimately, there is no filtering panacea, but some choices are better than others, depending largely on the study system, availability of genomic resources, and desired objectives of the study.

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Section: Snp and Climate Datamentioning

confidence: 99%

Regarding theF-word: the effects of dataFilteringon inferred genotype-environment associations

Ahrens

Jordan

Bragg

et al. 2020

Preprint

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“…While it is undeniable that species evolve adaptations to local selective gradients such as climate (Costa e Silva et al . 2019), a mean shift in the selective gradient under global change will likely result in the decoupling of the local adaptations leading to an increased risk of maladaptation (Rehfeldt et al . 2002; Costa e Silva et al .…”

Section: Discussionmentioning

confidence: 99%

Climate change and the suitability of local and non‐local species for ecosystem restoration

Harrison¹

2021

Eco Management Restoration

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Summary Restoring damaged, degraded and destroyed forest ecosystems to a target state often follows a local‐is‐best approach. However, rapidly changing climates may result in the local species no longer being the best now or into the future. This raises questions about whether there is a need to consider emerging ecosystems that bring together local and non‐local species that have not historically co‐occurred to ensure climate‐resilience of restored forest ecosystems; or whether non‐regional species may be needed to support ecosystem functionality in some areas. In this study, I present an experimental framework to assist decision‐making by evaluating the suitability of local and non‐local native species for ecosystem restoration under current and predicted climates. I applied this framework using the Tasmanian Midlands, Australia, as a case study, focusing of the diverse eucalypt flora of the island. Three key findings emerged. Firstly, the climate of the Midlands has rapidly changed across this biodiversity hotspot over the last century, and current mean annual maximum temperatures are already tracking worse case climate change scenarios. Secondly, using a combination of climate envelope modelling and habitat suitability modelling, I identified the degree to which the Midlands region provides suitable climate habitat for a range of local and non‐local Eucalyptus species now and into the future. Thirdly, although the Midlands is predicted to support suitable climate habitat for 82% of the regionally local eucalypt species now and into the future, it is predicted that the local populations of these least vulnerable species may be at risk of climate maladaptation, particularly in the northern regions of the Midlands. Models suggests that mixing local seed with non‐local seed sources currently occupying habitat with a climate that is predicted for the Midlands will be required. The study provides a basis for managers to consider the suitability of regionally local species and identify potential areas where local seed may need to be supplemented with non‐local seed for ecosystem restoration in the face of climate change.

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“…Our findings of standing variation harbouring putative adaptations to climate associated with temperature and precipitation factors provides an evidence base for design and implementation of such strategies. In addition, phenotypic approaches on other eucalypt species have also highlighted the role of local climate in the development of adaptive traits (Costa e Silva et al, 2019;Ahrens et al, 2019b, Ahrens et al, 2021b. Expanding this work to a phenotypic approach in jarrah for identifying patterns of plasticity and adaptation associated with climate would contribute to further understanding the association of genomic and phenotypic diversity across environmental gradients.…”

Section: Management Perspectivesmentioning

confidence: 96%

Signatures of natural selection in a foundation tree along Mediterranean climatic gradients

Filipe

Rymer

Byrne³

et al. 2021

Preprint

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Temperature and precipitation regimes are rapidly changing, resulting in forest dieback and local extinction events, particularly in Mediterranean-type climates. Strategic forest management approaches that enhance forests’ resilience to future climates are urgently required, however adaptation to climates in heterogeneous landscapes with multiple selection pressures may be complex. For widespread trees in Mediterranean-type climates we hypothesized that patterns of local adaptation are associated with climate; precipitation is a stronger factor of adaptation than temperature; functionally related genes show similar signatures of adaptation; and adaptive variants are independently sorting across the landscape. To test our hypotheses, we sampled 28 populations across the geographic and climatic distribution of Eucalyptus marginata (jarrah), in south-west Western Australia, and obtained 13,534 independent single nucleotide polymorphic (SNP) markers across the genome. While overall levels of population differentiation were low (FST=0.04), environmental association analyses found a total of 2,336 unique SNPs potentially associated with five climate variables of temperature and precipitation. Allelic turnover was identified for SNPs associated with temperate seasonality and mean precipitation of the warmest quarter (39.2% and 36.9% deviance explained, respectively), suggesting that both temperature and precipitation are important factors in adaptation. SNPs within similarly function genes, according to gene ontology enrichment analysis, had analogous allelic turnover along climate gradients, while SNPs among temperature and precipitation variables had orthogonal patterns of adaptation. These contrasting patterns of adaptation provide evidence that there may be standing genomic variation adapted to changing climates, providing the substrate needed to promote adaptive management strategies to bolster forest resilience in the future.

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Temperature and Rainfall Are Separate Agents of Selection Shaping Population Differentiation in a Forest Tree

Cited by 21 publications

References 100 publications

Regarding theF-word: the effects of dataFilteringon inferred genotype-environment associations

Regarding theF-word: the effects of dataFilteringon inferred genotype-environment associations

Climate change and the suitability of local and non‐local species for ecosystem restoration

Signatures of natural selection in a foundation tree along Mediterranean climatic gradients

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