Abstract
<p>Climate conditions in which tree species are able to grow are determined by their ecophysiological traits. The genus Pinus spp. is widespread across Eurasia, so that the different Pinus species have evolved to live within diverse climate envelops, from the boreal Scots pine (Pinus sylvestris L.) to the Mediterranean Aleppo pine (Pinus halepensis Mill.). Therefore, the different pine species are expected to present contrasting responses to environmental stressors, depending on the ones that populations had faced in the past.</p><p>Here we analyze the impact of climate on stand carbon fluxes in two contrasting stands -i.e. a boreal Finnish Scots pine stand and a Mediterranean Israeli Aleppo pine stand. We use a machine learning approach -i.e. Random Forest algorithm- to evaluate seasonal changes in the most limiting environmental driver (MLED) for forest productivity. Then, we use data from controlled experiments with Aleppo and Scots pine saplings, in which we evaluated their response to drought and heat stresses, in order to assess if differences in their ecophysiological traits may explain their ability to grow in such contrasting climate conditions.</p><p>Our results suggest that the MLED of forest productivity during all year in the boreal stand are low temperatures. Conversely but not surprisingly, the MLED in the Mediterranean stand is soil water availability, especially during summer. Therefore, we expect P. halepensis to be better adapted to heat and drought stresses, whereas we expect P. sylvestris to present higher photosynthetic rates at lower temperatures. Controlled experiments confirm these expectations, with a remarkable isohydric behavior of P. halepensis during drought, and different species responses of photosynthesis thermal optimum to heat and drought stress. Our results highlight the need to understand how traits determine tree species’ responses to different environmental stressors, in order to anticipate their performance in a warmer world.</p>
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