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Drought is one of the most important selection pressures for forest trees in the con-text of climate change. Yet, the different evolutionary mechanisms, and their envi-ronmental drivers, by which certain populations become more drought tolerant than others is still little understood. We studied adaptation to drought in 16 silver fir (Abies alba Mill.) populations from the French Mediterranean Alps by combining observa-tions on seedlings from a greenhouse experiment (N = 8,199) and on adult tress in situ (N = 315). In the greenhouse, we followed half-sib families for four growing seasons for growth and phenology traits, and tested their water stress response in a "drought until death" experiment. Adult trees in the field were assessed for δ13C, a proxy for water use efficiency, and genotyped at 357 SNP loci. SNP data was used to gen-erate a null expectation for seedling trait divergence between populations in order to detect the signature of selection, and 31 environmental variables were used to identify the selective environment. We found that seedlings originating from popula-tions with low soil water capacity grew more slowly, attained a smaller stature, and resisted water stress for a longer period of time in the greenhouse. Additionally, adult trees of these populations exhibited a higher water use efficiency as evidenced by their δ13C. These results suggest a correlated evolution of the growth-drought toler-ance trait complex. Population divergence in bud break phenology was adaptive only in the second growing season, and evolved independently from the growth-drought tolerance trait complex. Adaptive divergence in bud break phenology was principally driven by the inter- and intra-annual variation in temperature at the geographic origin of the population. Our results illustrate the different evolutionary strategies used by populations to cope with drought stress at the range limits across a highly heteroge-neous landscape, and can be used to inform assisted migration programs. ISSN:1752-4571 ISSN:1752-4563

Damage due to wind storms and droughts are increasing in many temperate forest, yet little is known about the long-term roles of these key climatic factors in forest dynamics and in the carbon budget. The objective of this study was to estimate individual and coupled effects of droughts and wind-storms on adult tree mortality across a 31-year period in 115 managed, mixed-coniferous forest stands from the Western Alps and the Jura mountains. For each stand, yearly mortality was inferred from management records, yearly drought from interpolated fields of monthly temperature, precipitation and soil water holding capacity, and wind-storms from interpolated fields of daily maximum wind-speed. We performed a thorough model selection based on a leave-one-out cross-validation of the time series. We compared different critical wind-speeds (CWSs) for damage, wind-storm and stand variables and statistical models. We found that a model including stand characteristics, drought and storm strength using a CWS of 25 ms−1 performed the best across most stands. Using this best model, we found that drought increased damage risk only in the most southerly forests, and its effect is generally maintained for up to two years. Storm strength increased damage risk in all forests in a relatively uniform way. In some stands, we found positive interaction between drought and storm strength most likely because drought weakens trees, and they became more prone to stem breakage under wind-loading. In other stands, we found negative interaction between drought and storm strength, where excessive rain likely leads to soil water saturation making trees more susceptible to overturning in a wind-storm. Our results stress that temporal data is essential to make valid inferences about ecological impacts of disturbance events, and that making inferences about disturbance agents separately can be of limited validity. Under projected future climatic conditions, the direction and strength of these ecological interactions could also change. This article is protected by copyright. All rights reserved.

Understanding local adaptation in forest trees is currently a key research and societal priority. Geographically and ecologically marginal populations provide ideal case studies, because environmental stress along with reduced gene flow can facilitate the establishment of locally adapted populations. We sampled European silver fir (Abies alba Mill.) trees in the French Mediterranean Alps, along the margin of its distribution range, from pairs of high- and low-elevation plots on four different mountains situated along a 170-km east-west transect. The analysis of 267 SNP loci from 175 candidate genes suggested a neutral pattern of east-west isolation by distance among mountain sites. F(ST) outlier tests revealed 16 SNPs that showed patterns of divergent selection. Plot climate was characterized using both in situ measurements and gridded data that revealed marked differences between and within mountains with different trends depending on the season. Association between allelic frequencies and bioclimatic variables revealed eight genes that contained candidate SNPs, of which two were also detected using F(ST) outlier methods. All SNPs were associated with winter drought, and one of them showed strong evidence of selection with respect to elevation. Q(ST)-F(ST) tests for fitness-related traits measured in a common garden suggested adaptive divergence for the date of bud flush and for growth rate. Overall, our results suggest a complex adaptive picture for A. alba in the southern French Alps where, during the east-to-west Holocene recolonization, locally advantageous genetic variants established at both the landscape and local scales.

Tree mortality is a complex process that exhibits great spatio-temporal variability. Long term mortality data is needed to understand this demographic parameter and how it is related to biotic, climatic, and anthropogenic disturbances. Here, we propose a Bayesian state-space model to estimate tree mortality time series in managed forests, where tree mortality is expressed as the annual proportion of the dead volume over the growing stock volume in a forest stand (subsequently, volume mortality rate). We argue that the volume mortality rate is an informative measure of tree mortality; and our simulations and field data suggests that the volume mortality rate is a good proxy of the demographic sense annual mortality rate (i.e. based on the number of trees), though the quality of the approximation depends on the particular management scheme. The proposed Bayesian state-space model combines two types of data: annual dead volumes from harvest reports and total growing stock volumes from periodic inventories. We illustrate the performance of the Bayesian state-space model using data simulated with an individual based and spatially explicit forest dynamic model (Samsara2). Then, we apply the Bayesian state-space model to field data from four forests in the French Alps and recover, unprecedented, century long, time series of annual volume mortality rate at the scale of a forest stand (10 ha) within each forest. We advocate the use of forest management data for future research, since temperate forests are managed in many countries since decades, thus many other unexploited data sets must exist.