A cryptic syngameon within Betula shrubs revealed: Implications for conservation in changing subarctic environments.

Arctic and subarctic ecosystems are rapidly transforming due to global warming, emphasizing the need to understand the genetic diversity and adaptive strategies of northern plant species for effective conservation. This study focuses on Betula glandulosa, a native North American tundra shrub known as dwarf birch, which demonstrates an apparent capacity to adapt to changing climate conditions. To address the taxonomic challenges associated with shrub birches and logistical complexities of sampling in the northernmost areas where species' ranges overlap, we adopted a multicriteria approach. Incorporating molecular data, ploidy level assessment and leaf morphology, we aimed to distinguish B. glandulosa individuals from other shrub birch species sampled. Our results revealed three distinct species and their hybrids within the 537 collected samples, suggesting the existence of a shrub birch syngameon, a reproductive network of interconnected species. Additionally, we identified two discrete genetic clusters within the core species, B. glandulosa, that likely correspond to two different glacial lineages. A comparison between the nuclear and chloroplast SNP data emphasizes a long history of gene exchange between different birch species and genetic clusters. Furthermore, our results highlight the significance of incorporating interfertile congeneric species in conservation strategies and underscores the need for a holistic approach to conservation in the context of climate change, considering the complex dynamics of species interactions. While further research will be needed to describe this shrub birches syngameon and its constituents, this study is a first step in recognizing its existence and disseminating awareness among ecologists and conservation practitioners. This biological phenomenon, which offers evolutionary flexibility and resilience beyond what its constituent species can achieve individually, may have significant ecological implications.

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

Methods using genomic information to forecast potential population maladaptation to climate change or new environments 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 2- 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.

Contrasting physiological strategies explain heterogeneous responses to severe drought conditions within local populations of a widespread conifer.

Understanding how trees prioritize carbon gain at the cost of drought vulnerability under severe drought conditions is crucial for predicting which genetic groups and individuals will be resilient to future climate conditions. In this study, we investigated variations in growth, tree-ring anatomy as well as carbon and oxygen isotope ratios to assess the sensitivity and the xylem formation process in response to an episode of severe drought in 29 mature white spruce (Picea glauca [Moench] Voss) families grown in a common garden trial. During the drought episode, the majority of families displayed decreased growth and exhibited either sustained or increased intrinsic water-use efficiency (iWUE), which was largely influenced by reduced stomatal conductance as revealed by the dual carbon­oxygen isotope approach. Different water-use strategies were detected within white spruce populations in response to drought conditions. Our results revealed intraspecific variation in the prevailing physiological mechanisms underlying drought response within and among populations of Picea glauca. The presence of different genetic groups reflecting diverse water-use strategies within this largely-distributed conifer is likely to lessen the negative effects of drought and decrease the overall forest ecosystems' sensitivity to it.

Spruce giga-genomes: structurally similar yet distinctive with differentially expanding gene families and rapidly evolving genes.

Spruces (Picea spp.) are coniferous trees widespread in boreal and mountainous forests of the northern hemisphere, with large economic significance and enormous contributions to global carbon sequestration. Spruces harbor very large genomes with high repetitiveness, hampering their comparative analysis. Here, we present and compare the genomes of four different North American spruces: the genome assemblies for Engelmann spruce (Picea engelmannii) and Sitka spruce (Picea sitchensis) together with improved and more contiguous genome assemblies for white spruce (Picea glauca) and for a naturally occurring introgress of these three species known as interior spruce (P. engelmannii × glauca × sitchensis). The genomes were structurally similar, and a large part of scaffolds could be anchored to a genetic map. The composition of the interior spruce genome indicated asymmetric contributions from the three ancestral genomes. Phylogenetic analysis of the nuclear and organelle genomes revealed a topology indicative of ancient reticulation. Different patterns of expansion of gene families among genomes were observed and related with presumed diversifying ecological adaptations. We identified rapidly evolving genes that harbored high rates of non-synonymous polymorphisms relative to synonymous ones, indicative of positive selection and its hitchhiking effects. These gene sets were mostly distinct between the genomes of ecologically contrasted species, and signatures of convergent balancing selection were detected. Stress and stimulus response was identified as the most frequent function assigned to expanding gene families and rapidly evolving genes. These two aspects of genomic evolution were complementary in their contribution to divergent evolution of presumed adaptive nature. These more contiguous spruce giga-genome sequences should strengthen our understanding of conifer genome structure and evolution, as their comparison offers clues into the genetic basis of adaptation and ecology of conifers at the genomic level. They will also provide tools to better monitor natural genetic diversity and improve the management of conifer forests. The genomes of four closely related North American spruces indicate that their high similarity at the morphological level is paralleled by the high conservation of their physical genome structure. Yet, the evidence of divergent evolution is apparent in their rapidly evolving genomes, supported by differential expansion of key gene families and large sets of genes under positive selection, largely in relation to stimulus and environmental stress response.

Breeding for adaptation to climate change: genomic selection for drought response in a white spruce multi-site polycross test.

With climate change, increasingly intense and frequent drought episodes will be affecting water availability for boreal tree species, prompting tree breeders and forest managers to consider adaptation to drought stress as a priority in their reforestation efforts. We used a 19-year-old polycross progeny test of the model conifer white spruce (Picea glauca) replicated on two sites affected by distinct drought episodes at different ages to estimate the genetic control and the potential for improvement of drought response in addition to conventional cumulative growth and wood quality traits. Drought response components were measured from dendrochronological signatures matching drought episodes in wood ring increment cores. We found that trees with more vigorous growth during their lifespan resisted better during the current year of a drought episode when the drought had more severe effects. Phenotypic data were also analyzed using genomic prediction (GBLUP) relying on the genomic relationship matrix of multi-locus gene SNP marker information, and conventional analysis (ABLUP) based on validated pedigree information. The accuracy of predicted breeding values for drought response components was marginally lower than that for conventional traits and comparable between GBLUP and ABLUP. Genetic correlations were generally low and nonsignificant between drought response components and conventional traits, except for resistance which was positively correlated to tree height. Heritability estimates for the components of drought response were slightly lower than for conventional traits, but similar single-trait genetic gains could be obtained. Multi-trait genomic selection simulations indicated that it was possible to improve simultaneously for all traits on both sites while sacrificing little on gain in tree height. In a context of rapid climate change, our results suggest that with careful phenotypic assessment, drought response may be considered in multi-trait improvement of white spruce, with accelerated screening of large numbers of candidates and selection at young age with genomic selection.

Finding common ground: Toward comparable indicators of adaptive capacity of tree species to a changing climate.

Adaptive capacity, one of the three determinants of vulnerability to climate change, is defined as the capacity of species to persist in their current location by coping with novel environmental conditions through acclimation and/or evolution. Although studies have identified indicators of adaptive capacity, few have assessed this capacity in a quantitative way that is comparable across tree species. Yet, such multispecies assessments are needed by forest management and conservation programs to refine vulnerability assessments and to guide the choice of adaptation measures. In this paper, we propose a framework to quantitatively evaluate five key components of tree adaptive capacity to climate change: individual adaptation through phenotypic plasticity, population phenotypic diversity as influenced by genetic diversity, genetic exchange within populations, genetic exchange between populations, and genetic exchange between species. For each component, we define the main mechanisms that underlie adaptive capacity and present associated metrics that can be used as indices. To illustrate the use of this framework, we evaluate the relative adaptive capacity of 26 northeastern North American tree species using values reported in the literature. Our results show adaptive capacity to be highly variable among species and between components of adaptive capacity, such that no one species ranks consistently across all components. On average, the conifer Picea glauca and the broadleaves Acer rubrum and A. saccharinum show the greatest adaptive capacity among the 26 species we documented, whereas the conifers Picea rubens and Thuja occidentalis, and the broadleaf Ostrya virginiana possess the lowest. We discuss limitations that arise when comparing adaptive capacity among species, including poor data availability and comparability issues in metrics derived from different methods or studies. The breadth of data required for such an assessment exemplifies the multidisciplinary nature of adaptive capacity and the necessity of continued cross-collaboration to better anticipate the impacts of a changing climate.

Combining QTL Mapping and Transcriptomics to Decipher the Genetic Architecture of Phenolic Compounds Metabolism in the Conifer White Spruce.

Conifer forests worldwide are becoming increasingly vulnerable to the effects of climate change. Although the production of phenolic compounds (PCs) has been shown to be modulated by biotic and abiotic stresses, the genetic basis underlying the variation in their constitutive production level remains poorly documented in conifers. We used QTL mapping and RNA-Seq to explore the complex polygenic network underlying the constitutive production of PCs in a white spruce (Picea glauca) full-sib family for 2 years. QTL detection was performed for nine PCs and differentially expressed genes (DEGs) were identified between individuals with high and low PC contents for five PCs exhibiting stable QTLs across time. A total of 17 QTLs were detected for eight metabolites, including one major QTL explaining up to 91.3% of the neolignan-2 variance. The RNA-Seq analysis highlighted 50 DEGs associated with phenylpropanoid biosynthesis, several key transcription factors, and a subset of 137 genes showing opposite expression patterns in individuals with high levels of the flavonoids gallocatechin and taxifolin glucoside. A total of 19 DEGs co-localized with QTLs. Our findings represent a significant step toward resolving the genomic architecture of PC production in spruce and facilitate the functional characterization of genes and transcriptional networks responsible for differences in constitutive production of PCs in conifers.

Connecting tree-ring phenotypes, genetic associations and transcriptomics to decipher the genomic architecture of drought adaptation in a widespread conifer.

As boreal forests face significant threats from climate change, understanding evolutionary trajectories of coniferous species has become fundamental to adapting management and conservation to a drying climate. We examined the genomic architecture underlying adaptive variation related to drought tolerance in 43 populations of a widespread boreal conifer, white spruce (Picea glauca [Moench] Voss), by combining genotype-environment associations, genotype-phenotype associations, and transcriptomics. Adaptive genetic variation was identified by correlating allele frequencies for 6,153 single nucleotide polymorphisms from 2,606 candidate genes with temperature, precipitation and aridity gradients, and testing for significant associations between genotypes and 11 dendrometric and drought-related traits (i.e., anatomical, growth response and climate-sensitivity traits) using a polygenic model. We identified a set of 285 genes significantly associated with a climatic factor or a phenotypic trait, including 110 that were differentially expressed in response to drought under greenhouse-controlled conditions. The interlinked phenotype-genotype-environment network revealed eight high-confidence genes involved in white spruce adaptation to drought, of which four were drought-responsive in the expression analysis. Our findings represent a significant step toward the characterization of the genomic basis of drought tolerance and adaptation to climate in conifers, which is essential to enable the establishment of resilient forests in view of new climate conditions.

Annual aboveground carbon uptake enhancements from assisted gene flow in boreal black spruce forests are not long-lasting.

Assisted gene flow between populations has been proposed as an adaptive forest management strategy that could contribute to the sequestration of carbon. Here we provide an assessment of the mitigation potential of assisted gene flow in 46 populations of the widespread boreal conifer Picea mariana, grown in two 42-year-old common garden experiments and established in contrasting Canadian boreal regions. We use a dendroecological approach taking into account phylogeographic structure to retrospectively analyse population phenotypic variability in annual aboveground net primary productivity (NPP). We compare population NPP phenotypes to detect signals of adaptive variation and/or the presence of phenotypic clines across tree lifespans, and assess genotype-by-environment interactions by evaluating climate and NPP relationships. Our results show a positive effect of assisted gene flow for a period of approximately 15 years following planting, after which there was little to no effect. Although not long lasting, well-informed assisted gene flow could accelerate the transition from carbon source to carbon sink after disturbance.

Plant Genotype Influences Physicochemical Properties of Substrate as Well as Bacterial and Fungal Assemblages in the Rhizosphere of Balsam Poplar.

Abandoned unrestored mines are an important environmental concern as they typically remain unvegetated for decades, exposing vast amounts of mine waste to erosion. Several factors limit the revegetation of these sites, including extreme abiotic and unfavorable biotic conditions. However, some pioneer tree species having high levels of genetic diversity, such as balsam poplar (Populus balsamifera), can naturally colonize these sites and initiate plant succession. This suggests that some tree genotypes are likely more suited for acclimation to the conditions of mine wastes. In this study, we selected two contrasting mine waste storage facilities (waste rock from a gold mine and tailings from a molybdenum mine) from the Abitibi region of Quebec (Canada), on which poplars were found to have grown naturally. First, we assessed in situ the impact of vegetation presence on each mine waste type. The presence of balsam poplars improved soil health locally by modifying the physicochemical properties (e.g., higher nutrient content and pH) of the mine wastes and causing an important shift in their bacterial and fungal community compositions, going from lithotrophic communities that dominate mine waste environments to heterotrophic communities involved in nutrient cycling. Next, in a greenhouse experiment we assessed the impact of plant genotype when grown in these mine wastes. Ten genotypes of P. balsamifera were collected locally, found growing either at the mine sites or in the surrounding natural forest. Tree growth was monitored over two growing seasons, after which the effects of genotype-by-environment interactions were assessed by measuring the physicochemical properties of the substrates and the changes in microbial community assembly. Although substrate type was identified as the main driver of rhizosphere microbiome diversity and community structure, a significant effect due to tree genotype was also detected, particularly for bacterial communities. Plant genotype also influenced aboveground tree growth and the physicochemical properties of the substrates. These results highlight the influence of balsam poplar genotype on the soil environment and the potential importance of tree genotype selection in the context of mine waste revegetation.

Strong overestimation of water-use efficiency responses to rising CO2 in tree-ring studies.

The carbon isotope ratio (δ13 C) in tree rings is commonly used to derive estimates of the assimilation-to-stomatal conductance rate of trees, that is, intrinsic water-use efficiency (iWUE). Recent studies have observed increased iWUE in response to rising atmospheric CO2 concentrations (Ca ), in many different species, genera and biomes. However, increasing rates of iWUE vary widely from one study to another, likely because numerous covarying factors are involved. Here, we quantified changes in iWUE of two widely distributed boreal conifers using tree samples from a forest inventory network that were collected across a wide range of growing conditions (assessed using the site index, SI), developmental stages and stand histories. Using tree-ring isotopes analysis, we assessed the magnitude of increase in iWUE after accounting for the effects of tree size, stand age, nitrogen deposition, climate and SI. We also estimated how growth conditions have modulated tree physiological responses to rising Ca . We found that increases in tree size and stand age greatly influenced iWUE. The effect of Ca on iWUE was strongly reduced after accounting for these two variables. iWUE increased in response to Ca , mostly in trees growing on fertile stands, whereas iWUE remained almost unchanged on poor sites. Our results suggest that past studies could have overestimated the CO2 effect on iWUE, potentially leading to biased inferences about the future net carbon balance of the boreal forest. We also observed that this CO2 effect is weakening, which could affect the future capacity of trees to resist and recover from drought episodes.

High-throughput drone-based remote sensing reliably tracks phenology in thousands of conifer seedlings.

Phenology is an important indicator of environmental variation and climate change impacts on tree responses. In conifers, monitoring phenology of photosynthesis through remote sensing has been unreliable, because needle foliage varies little throughout the year. This is challenging for modelling ecosystem carbon uptake and monitoring phenology for enhanced breeding (genomic selection) and forest health. Here, we demonstrate that drone-based carotenoid-sensitive spectral indices, such as the Chl/carotenoid index (CCI), can be used to track phenology in conifers by taking advantage of the close relationship between seasonally changing carotenoid levels and the variation of photosynthetic activity. Physiological ground measurements, including photosynthetic pigments and maximum quantum yield of Chl fluorescence, indicated that CCI tracked the variation of photosynthetic activity better than other vegetation indices for 30 white spruce seedlings measured over 1 yr. A machine-learning approach, using CCI derived from drone-based multispectral imagery, was used to model phenology of photosynthesis for the entire pedigree population (6000 seedlings). This high-throughput drone-based phenotyping approach is suitable for studying climate change impacts and environmental variation on the physiological status of thousands of field-grown conifers at unprecedented speed and scale.

Adaptive genetic variation to drought in a widely distributed conifer suggests a potential for increasing forest resilience in a drying climate.

Drought intensity and frequency are increasing under global warming, with soil water availability now being a major factor limiting tree growth in circumboreal forests. Still, the adaptive capacity of trees in the face of future climatic regimes remains poorly documented. Using 1481 annually resolved tree-ring series from 29-yr-old trees, we evaluated the drought sensitivity of 43 white spruce (Picea glauca (Moench) Voss) populations established in a common garden experiment. We show that genetic variation among populations in response to drought plays a significant role in growth resilience. Local genetic adaptation allowed populations from drier geographical origins to grow better, as indicated by higher resilience to extreme drought events, compared with populations from more humid geographical origins. The substantial genetic variation found for growth resilience highlights the possibility of selecting for drought resilience in boreal conifers. As a major research outcome, we showed that adaptive genetic variation in response to changing local conditions can shape drought vulnerability at the intraspecific level. Our findings have wide implications for forest ecosystem management and conservation.

Chemotyping and identification of protected Dalbergiatimber using gas chromatography quadrupole time of flight mass spectrometry.

The international trade in illegally logged and environmentally endangered timber has spurred enforcement agencies to seek additional technical procedures for the identification of wood species. All Dalbergia species are listed under the Convention on International Trade in Endangered Species (CITES) which is the reason this genus was chosen for study. Multiple sources of the heartwood from different Dalbergia species were extracted and chromatographic profiles collected by gas chromatography with high resolution quadrupole Time of Flight mass spectrometry (GC/QToF). The collected data was mined to select peaks and mass ions representative of the investigated Dalbergia species, and used to develop a Microsoft Excel® template offering immediate graphical representation of the results. Using wood specimens sourced from different xylaria, this graphical fingerprint proved adept at definitive identification of Dalbergia species. The CITES Appendix I species, D. nigra, was easily distinguished from D. melanoxylon and look-alike species of other genera. Similarly, a number of other Dalbergia species were differentiated using this current approach. Kernel discrimination analysis (KDA) was applied to increase the confidence of the species identification. The mislabeling of specimens appears to be common, and the emerging technique of GC/QToF in combination with other techniques, offers improved confidence in identification. GC/QToF further provides automation, the dimension of chromatography to avoid interferences, and production of reproducible electron impact positive (EI+) spectra. The prospect of building an EI+ spectral database for future wood identification is an important feature considering the limited accessibility of authenticated wood species specimens.

Genomic prediction for hastening and improving efficiency of forward selection in conifer polycross mating designs: an example from white spruce.

Genomic selection (GS) has a large potential for improving the prediction accuracy of breeding values and significantly reducing the length of breeding cycles. In this context, the choice of mating designs becomes critical to improve the efficiency of breeding operations and to obtain the largest genetic gains per time unit. Polycross mating designs have been traditionally used in tree and plant breeding to perform backward selection of the female parents. The possibility to use genetic markers for paternity identification and for building genomic prediction models should allow for a broader use of polycross tests in forward selection schemes. We compared the accuracies of genomic predictions of offspring's breeding values from a polycross and a full-sib (partial diallel) mating design with similar genetic background in white spruce (Picea glauca). Trees were phenotyped for growth and wood quality traits, and genotyped for 4092 SNPs representing as many gene loci distributed across the 12 spruce chromosomes. For the polycross progeny test, heritability estimates were smaller, but more precise using the genomic BLUP (GBLUP) model as compared with pedigree-based models accounting for the maternal pedigree or for the reconstructed full pedigree. Cross-validations showed that GBLUP predictions were 22-52% more accurate than predictions based on the maternal pedigree, and 5-7% more accurate than predictions using the reconstructed full pedigree. The accuracies of GBLUP predictions were high and in the same range for most traits between the polycross (0.61-0.70) and full-sib progeny tests (0.61-0.74). However, higher genetic gains per time unit were expected from the polycross mating design given the shorter time needed to conduct crosses. Considering the operational advantages of the polycross design in terms of easier handling of crosses and lower associated costs for test establishment, we believe that this mating scheme offers great opportunities for the development and operational application of forward GS.

Forest genomics: Advancing climate adaptation, forest health, productivity, and conservation.

Forest ecosystems provide important ecological services and resources, from habitat for biodiversity to the production of environmentally friendly products, and play a key role in the global carbon cycle. Humanity is counting on forests to sequester and store a substantial portion of the anthropogenic carbon dioxide produced globally. However, the unprecedented rate of climate change, deforestation, and accidental importation of invasive insects and diseases are threatening the health and productivity of forests, and their capacity to provide these services. Knowledge of genetic diversity, local adaptation, and genetic control of key traits is required to predict the adaptive capacity of tree populations, inform forest management and conservation decisions, and improve breeding for productive trees that will withstand the challenges of the 21st century. Genomic approaches have well accelerated the generation of knowledge of the genetic and evolutionary underpinnings of nonmodel tree species, and advanced their applications to address these challenges. This special issue of Evolutionary Applications features 14 papers that demonstrate the value of a wide range of genomic approaches that can be used to better understand the biology of forest trees, including species that are widespread and managed for timber production, and others that are threatened or endangered, or serve important ecological roles. We highlight some of the major advances, ranging from understanding the evolution of genomes since the period when gymnosperms separated from angiosperms 300 million years ago to using genomic selection to accelerate breeding for tree health and productivity. We also discuss some of the challenges and future directions for applying genomic tools to address long-standing questions about forest trees.

Multi-trait genomic selection for weevil resistance, growth, and wood quality in Norway spruce.

Plantation-grown trees have to cope with an increasing pressure of pest and disease in the context of climate change, and breeding approaches using genomics may offer efficient and flexible tools to face this pressure. In the present study, we targeted genetic improvement of resistance of an introduced conifer species in Canada, Norway spruce (Picea abies (L.) Karst.), to the native white pine weevil (Pissodes strobi Peck). We developed single- and multi-trait genomic selection (GS) models and selection indices considering the relationships between weevil resistance, intrinsic wood quality, and growth traits. Weevil resistance, acoustic velocity as a proxy for mechanical wood stiffness, and average wood density showed moderate-to-high heritability and low genotype-by-environment interactions. Weevil resistance was genetically positively correlated with tree height, height-to-diameter at breast height (DBH) ratio, and acoustic velocity. The accuracy of the different GS models tested (GBLUP, threshold GBLUP, Bayesian ridge regression, BayesCπ) was high and did not differ among each other. Multi-trait models performed similarly as single-trait models when all trees were phenotyped. However, when weevil attack data were not available for all trees, weevil resistance was more accurately predicted by integrating genetically correlated growth traits into multi-trait GS models. A GS index that corresponded to the breeders' priorities achieved near maximum gains for weevil resistance, acoustic velocity, and height growth, but a small decrease for DBH. The results of this study indicate that it is possible to breed for high-quality, weevil-resistant Norway spruce reforestation stock with high accuracy achieved from single-trait or multi-trait GS.

Going with the flow: Intraspecific variation may act as a natural ally to counterbalance the impacts of global change for the riparian species Populus deltoides.

The speed and magnitude of global change will have major impacts on riparian ecosystems, thereby leading to greater forest vulnerability. Assessing species' adaptive capacities to provide relevant information for vulnerability assessments remains challenging, especially for nonmodel species like the North American Populus deltoides W. Bartram ex Marshall. The objective of this study was to understand how genomic diversity of this foundation species was shaped by its environment (climate, soil, and biotic interactions) to gauge its adaptive capacity. We used two complementary approaches to get a full portrait of P. deltoides genetic diversity at both the species and whole-genome ranges. First, we used a set of 93 nuclear and three chloroplastic SNP markers in 946 individuals covering most of the species' natural distribution. Then, to measure the degree of intraspecific divergence at the whole-genome level and to support the outlier and genomic-environment association analyses, we used a sequence capture approach on DNA pools. Three distinct lineages for P. deltoides were detected, and their current distribution was associated with abiotic and biotic variations. The comparison between both cpDNA and ncDNA patterns showed that gene flow between the lineages is unbalanced. The southern and northeastern populations may benefit from the input, through river flow, of novel alleles located upstream to their local gene pools. These alleles could migrate from populations that are already adapted to conditions that fit the predicted climates in the receiving local populations, hotter at the northeastern limit and drier in the Central United States. These "preadapted" incoming alleles may help to cope with maladaptation in populations facing changing conditions.

Measuring Rapid A-Ci Curves in Boreal Conifers: Black Spruce and Balsam Fir.

Climate change is steering tree breeding programs towards the development of families and genotypes that will be adapted and more resilient to changing environments. Making genotype-phenotype-environment connections is central to these predictions and it requires the evaluation of functional traits such as photosynthetic rates that can be linked to environmental variables. However, the ability to rapidly measure photosynthetic parameters has always been limiting. The estimation of V c,max and J max using CO2 response curves has traditionally been time consuming, taking anywhere from 30 min to more than an hour, thereby drastically limiting the number of trees that can be assessed per day. Technological advancements have led to the development of a new generation of portable photosynthesis measurement systems offering greater chamber environmental control and automated sampling and, as a result, the proposal of a new, faster, method (RACiR) for measuring V c,max and J max . This method was developed using poplar trees and involves measuring photosynthetic responses to CO2 over a range of CO2 concentrations changing at a constant rate. The goal of the present study was to adapt the RACiR method for use on conifers whose measurement usually requires much larger leaf chambers. We demonstrate that the RACiR method can be used to estimate V c,max and J max in conifers and provide recommendations to enhance the method. The use our method in conifers will substantially reduce measurement time, thus greatly improving genotype evaluation and selection capabilities based on photosynthetic traits. This study led to the developpement of an R package (RapidACi, https://github.com/ManuelLamothe/RapidACi) that facilitates the correction of multiple RACiR files and the post-measurement correction of leaf areas.