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Biology subjects

Candido-Ribeiro, R.

Publications and source records attributed to Candido-Ribeiro, R..

2 recordsLinked to original sources

Weak local adaptation to drought in seedlings of a widespread conifer

There is an urgent need for better understanding how populations of trees will respond to predictable changes in climate and the intensification of extreme weather events such as droughts. The distribution of adaptive traits in seedlings is a crucial component of population adaptive potential and its characterization is important for development of management approaches mitigating the effects of climate change on forests. In this study, we used a large-scale common garden drought experiment to characterize the variation in drought tolerance, growth, and plastic responses to extreme summer drought in seedlings of 73 natural provenances of the two main varieties of Douglas-fir (Pseudotsuga menziesii var. menziesii and var. glauca), sampled across most of their extensive natural ranges. We detected large differences between the two Douglas-fir varieties for all traits assessed, with var. glauca showing higher tolerance to drought but slower height growth and less plasticity than var. menziesii. Surprisingly, signals of local adaptation to drought within varieties were weak within var. glauca and nearly absent within var. menziesii. Temperature-related variables were identified as the main climatic drivers of clinal variation in drought tolerance and height growth species-wide, and in height growth within var. menziesii. Furthermore, our data indicate that higher plasticity under extreme droughts could be maladaptive in var. menziesii. Overall, our study suggests that genetic variation for drought tolerance in seedlings is maintained primarily within rather than among provenances within varieties and does not compromise growth at early stages of plant development. Given these results, assisted gene flow is unlikely to help facilitate adaptation to drought within Douglas-fir varieties, but selective breeding within provenances could accelerate adaptation.

evolutionary biology↗

How useful is genomic data for predicting maladaptation to future climate?

Methods using genomic information to forecast potential population maladaptation to climate change are becoming increasingly common, yet the lack of model validation poses serious hurdles toward their incorporation into management and policy. Here, we compare the validation of maladaptation estimates derived from two methods - Gradient Forests (GFoffset) and the Risk Of Non-Adaptedness (RONA) - using exome capture pool-seq data from 35 to 39 populations across three conifer taxa: two Douglas-fir varieties and jack pine. We evaluate sensitivity of these algorithms to the source of input loci (markers selected from genotype-environment associations [GEA] or those selected at random). We validate these methods against two-year and 52-year growth and mortality measured in independent transplant experiments. Overall, we find that both methods often better predict transplant performance than climatic or geographic distances. We also find that GFoffset and RONA models are surprisingly not improved using GEA candidates. Even with promising validation results, variation in model projections to future climates makes it difficult to identify the most maladapted populations using either method. Our work advances understanding of the sensitivity and applicability of these approaches, and we discuss recommendations for their future use.

evolutionary biology↗