Summary: 1. Many recent statistical applications involve inference under complex models, where it is computationally prohibitive to calculate likelihoods but possible to simulate data. Approximate Bayesian computation (ABC) is devoted to these complex models because it bypasses the evaluation of the likelihood function by comparing observed and simulated data.2. We introduce the R package ‘abc’ that implements several ABC algorithms for performing parameter estimation and model selection. In particular, the recently developed nonlinear heteroscedastic regression methods for ABC are implemented. The ‘abc’ package also includes a cross‐validation tool for measuring the accuracy of ABC estimates and to calculate the misclassification probabilities when performing model selection. The main functions are accompanied by appropriate summary and plotting tools.3. R is already widely used in bioinformatics and several fields of biology. The R package ‘abc’ will make the ABC algorithms available to a large number of R users. ‘abc’ is a freely available R package under the GPL license, and it can be downloaded at http://cran.r‐project.org/web/packages/abc/index.html.

Silver fir (Abies alba Mill.) is a keystone conifer of European montane forest ecosystems that has experienced large fluctuations in population size during during the Quaternary and, more recently, due to land-use change. To forecast the species9 future distribution and survival, it is important to investigate the genetic basis of adaptation to environmental change, notably to extreme events. For this purpose, we here provide a first draft genome assembly and annotation of the silver fir genome, established through a community-based initiative. DNA obtained from haploid megagametophyte and diploid needle tissue was used to construct and sequence Illumina paired-end and mate-pair libraries, respectively, to high depth. The assembled A. alba genome sequence accounted for over 37 million scaffolds corresponding to 18.16 Gb, with a scaffold N50 of 14,051 bp. Despite the fragmented nature of the assembly, a total of 50,757 full-length genes were functionally annotated in the nuclear genome. The chloroplast genome was also assembled into a single scaffold (120,908 bp) that shows a high collinearity with both the A. koreana and A. sibirica complete chloroplast genomes. This first genome assembly of silver fir is an important genomic resource that is now publicly available in support of a new generation of research. By genome-enabling this important conifer, this resource will open the gate for new research and more precise genetic monitoring of European silver fir forests.

Drought is one of the most important selection pressures for forest trees in the context of climate change. Yet, the different evolutionary mechanisms, and their environmental 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 observations 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 generate 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 populations 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 tolerance 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 heterogeneous landscape, and can be used to inform assisted migration programs.