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Abstract Teak (Tectona grandis) is a valuable tropical tree species that is widely planted in more than 65 countries, including extensive plantations on Java Island, Indonesia. Java plays a critical role in global teak production. However, few studies have assessed the genetic diversity and local adaptation of this species using genome-wide sequencing data across its natural distribution and Indonesian landraces. Analysis of genetic structure and local adaptation can provide information on the genetic origin and indicate the genetic adaptation capacity. Such information can inform the planning of more resilient planting strategies against the projected future climate change, which can contribute to sustainable forest management. Climate change is expected to alter suitable habitats for teaks, thus negatively impact teak production on Java. Thus, this study aimed to elucidate climatic adaptations. We analyzed genomic data for eight natural origin teak populations (India, Thailand, Laos, and Myanmar) and nine Indonesian landraces, using approximately 9000 SNPs from dd-RAD seq analysis, to investigate genomic environmental adaptation to inform future teak planting in Java. Malabar, India, exhibited local allele frequency changes along climatic gradients. Additionally, this population exhibited a small genetic offset between the present and future projected climatic conditions compared with other regions. Thus, they may adapt to the local environment and have some resilience to projected future climatic conditions. Similarly, Indonesian landraces on Java also displayed a relatively small genetic offset, suggesting they may be less vulnerable to climate change when planted on Java.

We studied the genetic differentiation in budburst timing among Fagus crenata populations along spatial gradients in late frost timing in the Hakkoda Mountains, northern Japan, by focusing on last fatal frost day and topography. For budburst timing, we analyzed interpopulation variations in habitats, genetic variations in a nursery, and the relationships between these variations and environmental conditions in the habitats. Analyses of interpopulation variation showed that the day and the temperature sum of budburst positively correlated with the last fatal frost day in the habitats. Analyses of genetic variation showed significant genetic variations among provenances and families for both traits. For all provenances, the heritability for these traits were 0.7–0.8. The genetic variations were significantly associated with variations in the last fatal frost day among the provenances, suggesting that natural selection due to late fatal frost causes genetic differentiation in the traits along the spatial gradient in late frost timing. These results demonstrate that late frost is a key factor driving genetic differentiation of leaf-out phenology within a regional tree population.

Loci responsible for local adaptation are likely to have more genetic differentiation among populations than neutral loci. However, neutral loci can vary widely in their amount of genetic differentiation, even over the same geographic range. Unfortunately, the distribution of differentiation—as measured by an index such as FST—depends on the details of the demographic history of the populations in question, even without spatially heterogeneous selection. Many methods designed to detect FST outliers assume a specific model of demographic history, which can result in extremely high false positive rates for detecting loci under selection. We develop a new method that infers the distribution of FST for loci unlikely to be strongly affected by spatially diversifying selection, using data on a large set of loci with unknown selective properties. Compared to previous methods, this approach, called OutFLANK, has much lower false positive rates and comparable power, as shown by simulation.

The fall armyworm (FAW) Spodoptera frugiperda is a long-distance migratory insect pest, and the invaded range of its recent expansion includes regions colder than the tropical and subtropical regions in East Asia. In order to understand the potential distribution of S. frugiperd in temperate and colder regions, we quantified the effects of temperature and exposure duration on the degree of indirect chilling injury caused to S. frugiperd under laboratory conditions. The adults were more tolerant to moderately low temperatures (3 to 15 °C) than the larvae and pupae. Survival decreased significantly when adult S. frugiperd were exposed to temperatures of 9 °C or lower. A time–temperature model suggested that indirect chilling injury began occurring at 15 °C. Survival was improved by short-term daily exposure to higher temperatures, indicating the existence of a repair mechanism for indirect chilling injury in S. frugiperd. The degree of repair depended on the temperature, but the relationship was not a simple direct proportion. These findings on indirect chilling injury and repair will improve the estimation of the potential distribution of S. frugiperd in temperate and colder regions.

Uncovering the genetic and evolutionary basis of local adaptation is a major focus of evolutionary biology. The recent development of cost-effective methods for obtaining high-quality genome-scale data makes it possible to identify some of the loci responsible for adaptive differences among populations. Two basic approaches for identifying putatively locally adaptive loci have been developed and are broadly used: one that identifies loci with unusually high genetic differentiation among populations (differentiation outlier methods) and one that searches for correlations between local population allele frequencies and local environments (genetic-environment association methods). Here, we review the promises and challenges of these genome scan methods, including correcting for the confounding influence of a species’ demographic history, biases caused by missing aspects of the genome, matching scales of environmental data with population structure, and other statistical considerations. In each case, we make suggestions for best practices for maximizing the accuracy and efficiency of genome scans to detect the underlying genetic basis of local adaptation. With attention to their current limitations, genome scan methods can be an important tool in finding the genetic basis of adaptive evolutionary change.

Ecological rules such as Bergmann’s rule and the temperature–size rule state that body-size decline is a universal response to warm temperatures in both homeotherms and poikilotherms. In the present study, we investigated the biological responses of Nannophya koreana, an endangered dragonfly species in Korea, by comparing body size in two habitats with large differences in water temperature, Mungyong-si (MG, terraced paddy fields) and Muui-do (MU, a mountainous wetland). To conserve the dragonfly populations, the collected larvae were photographed and released, and their head widths and body lengths were measured. There was no difference in the annual mean air temperature and precipitation between the two sites; however, the annual mean water temperature was substantially lower in MU than in MG. There was little difference in larval head width between the two sites; however, body length in the MU population was smaller than that in the MG population. Larval growth rate per 100-degree-days was 0.75 mm for MG and 1.16 for MU. The relationship between temperature and body size of N. koreana larvae showed opposite trends to Bergmann’s rule and the temperature–size rule. Since the larval growth period during a year in MU was shorter than that in MG, the MU population potentially exhibits a higher growth rate as a mechanism of compensating for the low water temperature. Our study established the relationship between temperature and body size of N. koreana in two wetlands that had an obvious difference in water temperature despite being geographically close. The results highlight the importance of considering detailed factors such as habitat type when studying the temperature–size responses of organisms.

R package pcadapt is a user-friendly R package for performing genome scans for local adaptation. Here, we present version 4 of pcadapt which substantially improves computational efficiency while providing similar results. This improvement is made possible by using a different format for storing genotypes and a different algorithm for computing principal components of the genotype matrix, which is the most computationally demanding step in method pcadapt. These changes are seamlessly integrated into the existing pcadapt package, and users will experience a large reduction in computation time (by a factor of 20–60 in our analyses) as compared with previous versions.

An urgent challenge facing biologists is predicting the regional-scale population dynamics of species facing environmental change. Biologists suggest that we must move beyond predictions based on phenomenological models and instead base predictions on underlying processes. For example, population biologists, evolutionary biologists, community ecologists and ecophysiologists all argue that the respective processes they study are essential. Must our models include processes from all of these fields? We argue that answering this critical question is ultimately an empirical exercise requiring a substantial amount of data that have not been integrated for any system to date. To motivate and facilitate the necessary data collection and integration, we first review the potential importance of each mechanism for skilful prediction. We then develop a conceptual framework based on reaction norms, and propose a hierarchical Bayesian statistical framework to integrate processes affecting reaction norms at different scales. The ambitious research programme we advocate is rapidly becoming feasible due to novel collaborations, datasets and analytical tools.

Five provenance tests with twenty-six European silver fir autochthonous populations were used in order to assess the response of populations to climate change. Height growth and diameter at breast height of trees at age 31 years were considered as response variables and eight climate variables as predictors. Climatic variables for the trial sites and for origin location of provenances were calculated from 1961 to 2010. The experiments revealed a large genetic variability within species level and a plastic response to climate change, which certainly has a genetic basis. The transfer to warmer climate has resulted in an increase of the provenances growth, in the trial sites situated on the lower vegetation layer. But growth is significantly influenced by mean annual temperature and annual precipitation of planting site and also by the differences in mean annual temperature, annual precipitation, monthly mean temperature in July and July precipitation between provenance site and test site. These are the climatic factors which should be associated with risk in case of the transfer of forest reproductive materials. The provenance origin should be especially considered if the species will be planted outside of its current climate optimum. The best provenances in terms of total height and diameter at 1.30 m came from origin climate close to site climate, small transfer distances. Based on growth response functions and RCP4.5 scenario, we could project the shifts in species distribution for 2050s and 2100s and identify vulnerable populations.

Theory suggests that evolutionary changes in phenotypic plasticity could either hinder or facilitate evolutionary rescue in a changing climate. Nevertheless, the actual role of evolving plasticity in the responses of natural populations to climate change remains unresolved. Direct observations of evolutionary change in nature are rare, making it difficult to assess the relative contributions of changes in trait means versus changes in plasticity to climate change responses. To address this gap, this review explores several proxies that can be used to understand evolving plasticity in the context of climate change, including space for time substitutions, experimental evolution and tests for genomic divergence at environmentally responsive loci. Comparisons among populations indicate a prominent role for divergence in environmentally responsive traits in local adaptation to climatic gradients. Moreover, genomic comparisons among such populations have identified pervasive divergence in the regulatory regions of environmentally responsive loci. Taken together, these lines of evidence suggest that divergence in plasticity plays a prominent role in adaptation to climatic gradients over space, indicating that evolving plasticity is also likely to play a key role in adaptive responses to climate change through time. This suggests that genetic variation in plastic responses to the environment (G × E) might be an important predictor of species' vulnerabilities to climate-driven decline or extinction. This article is part of the theme issue ‘The role of plasticity in phenotypic adaptation to rapid environmental change’.