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Local adaptation to climate is common in plant species and has been studied in a range of contexts, from improving crop yields to predicting population maladaptation to future conditions. The genomic era has brought new tools to study this process, which was historically explored through common garden experiments.

In this study, we combine genomic methods and common gardens to investigate local adaptation in red spruce and identify environmental gradients and loci involved in climate adaptation. We first use climate transfer functions to estimate the impact of climate change on seedling performance in three common gardens. We then explore the use of multivariate gene–environment association methods to identify genes underlying climate adaptation, with particular attention to the implications of conducting genome scans with and without correction for neutral population structure.

This integrative approach uncovered phenotypic evidence of local adaptation to climate and identified a set of putatively adaptive genes, some of which are involved in three main adaptive pathways found in other temperate and boreal coniferous species: drought tolerance, cold hardiness, and phenology. These putatively adaptive genes segregated into two ‘modules’ associated with different environmental gradients.

This study nicely exemplifies the multivariate dimension of adaptation to climate in trees.

 

Gradient Forest (GF) is a machine learning algorithm designed to analyze spatial patterns of biodiversity as a function of environmental gradients. An offset measure between the GF‐predicted environmental association of adapted alleles and a new environment (GF Offset) is increasingly being used to predict the loss of environmentally adapted alleles under rapid environmental change, but remains mostly untested for this purpose. Here, we explore the robustness of GF Offset to assumption violations, and its relationship to measures of fitness, using SLiM simulations with explicit genome architecture and a spatial metapopulation. We evaluate measures of GF Offset in: (1) a neutral model with no environmental adaptation; (2) a monogenic “population genetic” model with a single environmentally adapted locus; and (3) a polygenic “quantitative genetic” model with two adaptive traits, each adapting to a different environment. We found GF Offset to be broadly correlated with fitness offsets under both single locus and polygenic architectures. However, neutral demography, genomic architecture, and the nature of the adaptive environment can all confound relationships between GF Offset and fitness. GF Offset is a promising tool, but it is important to understand its limitations and underlying assumptions, especially when used in the context of predicting maladaptation.

 

Shifting range limits are predicted for many species as the climate warms. However, the rapid pace of climate change will challenge the natural dispersal capacity of long-lived, sessile organisms such as forest trees. Adaptive responses of populations will, therefore, depend on levels of genetic variation and plasticity for climate-responsive traits, which likely vary across the range due to expansion history and current patterns of selection. Here, we study levels of genetic and plastic variation for phenology and growth traits in populations of red spruce ( Picea rubens ), from the range core to the highly fragmented trailing edge. We measured more than 5000 offspring sampled from three genetically distinct regions (core, margin and edge) grown in three common gardens replicated along a latitudinal gradient. Genetic variation in phenology and growth showed low to moderate heritability and differentiation among regions, suggesting some potential to respond to selection. Phenology traits were highly plastic, but this plasticity was generally neutral or maladaptive in the effect on growth, revealing a potential liability under warmer climates. These results suggest future climate adaptation will depend on the regional availability of genetic variation in red spruce and provide a resource for the design and management of assisted gene flow. This article is part of the theme issue ‘Species’ ranges in the face of changing environments (Part II)’. 

Red spruce (Picea rubens Sarg.) is a coniferous tree with a highly fragmented range in eastern North American montane forests. It serves as a foundational species for many locally rare and threatened taxa and has therefore been the focus of large-scale reforestation efforts aimed at restoring these montane ecosystems, yet genetic input guiding these efforts has been lacking. To tackle this issue, we took advantage of a common garden experiment and a whole exome sequencing dataset to investigate the impact of different population genetic parameters on early-life seedling fitness in red spruce. The level of inbreeding, genetic diversity and genetic load were assessed for 340 mother trees sampled from 65 localities across the spe- cies range and compared to different fitness traits measured on 5100 of their seedlings grown in a controlled environment. We identified an overall positive influence of genetic diversity and negative impact of genetic load and population-level inbreeding on early-life fitness. Those associations were most apparent for the highly fragmented populations in the Central and Southern Appalachians, where lower genetic diversity and higher inbreeding were associated with lower germination rate, shorter height and reduced early-life fitness of the seedlings. These results provide unprecedented information that could be used by field managers aiming to restore red spruce forests and to maximize the success of future plantations. 

Signals of local adaptation have been found in many plants and animals, highlighting the heterogeneity in the distribution of adaptive genetic variation throughout species ranges. In the coming decades, global climate change is expected to induce shifts in the selective pressures that shape this adaptive variation. These changes in selective pressures will likely result in varying degrees of local climate maladaptation and spatial reshuffling of the underlying distributions of adaptive alleles. There is a growing interest in using population genomic data to help predict future disruptions to locally adaptive gene-environment associations. One motivation behind such work is to better understand how the effects of changing climate on populations’ short-term fitness could vary spatially across species ranges. Here we review the current use of genomic data to predict the disruption of local adaptation across current and future climates. After assessing goals and motivations underlying the approach, we review the main steps and associated statistical methods currently in use and explore our current understanding of the limits and future potential of using genomics to predict climate change (mal)adaptation. Expected final online publication date for the Annual Review of Ecology, Evolution, and Systematics, Volume 51 is November 2, 2020. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates. 

Understanding the factors influencing the current distribution of genetic diversity across a species range is one of the main questions of evolutionary biology, especially given the increasing threat to biodiversity posed by climate change. Historical demographic processes such as population expansion or bottlenecks and decline are known to exert a predominant influence on past and current levels of genetic diversity, and revealing this demo‐genetic history can have immediate conservation implications. We used a whole‐exome capture sequencing approach to analyze polymorphism across the gene space of red spruce (Picea rubens Sarg.), an endemic and emblematic tree species of eastern North America high‐elevation forests that are facing the combined threat of global warming and increasing human activities. We sampled a total of 340 individuals, including populations from the current core of the range in northeastern USA and southeastern Canada and from the southern portions of its range along the Appalachian Mountains, where populations occur as highly fragmented mountaintop “sky islands.” Exome capture baits were designed from the closely relative white spruce (P. glauca Voss) transcriptome, and sequencing successfully captured most regions on or near our target genes, resulting in the generation of a new and expansive genomic resource for studying standing genetic variation in red spruce applicable to its conservation. Our results, based on over 2 million exome‐derived variants, indicate that red spruce is structured into three distinct ancestry groups that occupy different geographic regions of its highly fragmented range. Moreover, these groups show small Ne , with a temporal history of sustained population decline that has been ongoing for thousands (or even hundreds of thousands) of years. These results demonstrate the broad potential of genomic studies for revealing details of the demographic history that can inform management and conservation efforts of nonmodel species with active restoration programs, such as red spruce. 

Red spruce (Picea rubens) is a long-lived tree species that thrives in cool, moist environs. Its ability to adapt to rapidly changing climate is uncertain. In the southern Appalachian Mountains, red spruce reaches its greatest abundance at high elevations, but can also occur across a range of mid and lower elevations, suggesting the possibility of a correlation between genetic variation and habitat. To assess clinal phenotypic variation in functional traits related to climate adaptation, we collected seed from 82 maternal sib families located along replicated elevational gradients in the Great Smoky Mountains National Park, TN (GSMNP) and Mount Mitchell State Park, NC (MMSP). The percentage of filled seeds and seed mass increased with elevation, indicating that successful pollination and seed development was greatest at the highest elevations. Seedlings sourced from GSMNP displayed a strong relationship between elevation and bud set when grown under common garden conditions. High elevation families set bud as many as 10 days earlier than low elevation families, indicating adaptation to local climate. Across parks, no effect of elevation was noted for bud flush. Our results demonstrate that red spruce in the southern Appalachian Mountains displays clinal variation in bud set that may reflect local adaptation to climate, although this varied between the two parks sampled. We suggest that genetic adaption of red spruce to different climate regimes, at both local and broad spatial scales, is in need of more intensive study, and should be carefully considered when selecting seed sources for restoration. 

Flotation of seeds in solvents is a common means of separating unfilled and filled seeds. While a few protocols for processing red spruce (Picea rubens) seeds recommend ethanol flotation, delayed and reduced germination have been reported. We conducted an ethanol bioassay on seeds previously stored at -20°C to quantify the concentration required to separate red spruce seeds and the effects on germination. We used seeds from Canada (CAN) that had been exposed to ethanol during processing, and seeds from the United States (USA) that had not been exposed to ethanol during processing. Seeds were exposed to 10 ethanol concentrations (10-100%) and deionised water was used as a control. The effective concentration of ethanol for 50% (EC50) of the seeds to sink ranged by source from 70.9 to 90.7%, with all seeds sinking in 100% ethanol. The use of less than 100% ethanol is not adequate for seed separation, as some filled seeds could float and be mistakenly categorised as unfilled. The mean EC50 of ethanol that inhibits germination was significantly higher for USA sources (52.7%), than for CAN sources (40.8%; P < 0.05). Ethanol concentrations that inhibited germination coincided with delays in germination. The mechanism of phytotoxity was not determined; however, damage during extraction, desiccation and storage at -20°C are potential sources. We recommend separating red spruce seeds by physical means rather than ethanol flotation to avoid potential negative impacts on germination.