Family‐level variation in early life‐cycle traits of kelp

Temperate kelp forests (Laminarians) are threatened by temperature stress due to ocean warming and photoinhibition due to increased light associated with canopy loss. However, the potential for evolutionary adaptation in kelp to rapid climate change is not well known. This study examined family‐level variation in physiological and photosynthetic traits in the early life‐cycle stages of the ecologically important Australasian kelp Ecklonia radiata and the response of E. radiata families to different temperature and light environments using a family × environment design. There was strong family‐level variation in traits relating to morphology (surface area measures, branch length, branch count) and photosynthetic performance (F_v/F_m) in both haploid (gametophyte) and diploid (sporophyte) stages of the life‐cycle. Additionally, the presence of family × environment interactions showed that offspring from different families respond differently to temperature and light in the branch length of male gametophytes and oogonia surface area of female gametophytes. Negative responses to high temperatures were stronger for females vs. males. Our findings suggest E. radiata may be able to respond adaptively to climate change but studies partitioning the narrow vs. broad sense components of heritable variation are needed to establish the evolutionary potential of E. radiata to adapt under climate change.     

Why does the magnitude of genotype‐by‐environment interaction vary?

Genotype‐by‐environment interaction (G × E), that is, genetic variation in phenotypic plasticity, is a central concept in ecology and evolutionary biology. G×E has wide‐ranging implications for trait development and for understanding how organisms will respond to environmental change. Although G × E has been extensively documented, its presence and magnitude vary dramatically across populations and traits. Despite this, we still know little about why G × E is so evident in some traits and populations, but minimal or absent in others. To encourage synthetic research in this area, we review diverse hypotheses for the underlying biological causes of variation in G × E. We extract common themes from these hypotheses to develop a more synthetic understanding of variation in G × E and suggest some important next steps.     

Prediction of near-term climate change impacts on UK wheat quality and the potential for adaptation through plant breeding

Wheat is a major crop worldwide, mainly cultivated for human consumption and animal feed. Grain quality is paramount in determining its value and downstream use. While we know that climate change threatens global crop yields, a better understanding of impacts on wheat end-use quality is also critical. Combining quantitative genetics with climate model outputs, we investigated UK-wide trends in genotypic adaptation for wheat quality traits. In our approach, we augmented genomic prediction models with environmental characterisation of field trials to predict trait values and climate effects in historical field trial data between 2001 and 2020. Addition of environmental covariates, such as temperature and rainfall, successfully enabled prediction of genotype by environment interactions (G × E), and increased prediction accuracy of most traits for new genotypes in new year cross validation. We then extended predictions from these models to much larger numbers of simulated environments using climate scenarios projected under Representative Concentration Pathways 8.5 for 2050–2069. We found geographically varying climate change impacts on wheat quality due to contrasting associations between specific weather covariables and quality traits across the UK. Notably, negative impacts on quality traits were predicted in the East of the UK due to increased summer temperatures while the climate in the North and South-west may become more favourable with increased summer temperatures. Furthermore, by projecting 167,040 simulated future genotype–environment combinations, we found only limited potential for breeding to exploit predictable G × E to mitigate year-to-year environmental variability for most traits except Hagberg falling number. This suggests low adaptability of current UK wheat germplasm across future UK climates. More generally, approaches demonstrated here will be critical to enable adaptation of global crops to near-term climate change.     

Heritability of male attractiveness persists despite evidence for unreliable sexual signals in Drosophila simulans

Sexual signals can be used to attract mates, but to be honest indicators of signaller quality they need to convey information reliably. However, environmental variation and genotype‐by‐environment (G × E) interactions have the potential to compromise the reliability of sexual signals. Here, we test the reliability of cuticular hydrocarbons (CHCs) as signals of heritable aspects of male attractiveness in Drosophila simulans. We examined the heritability of male attractiveness and a measure of the difference between fathers' and sons' CHC profiles across dietary and temperature environments. Our results show that environmental heterogeneity disrupts the similarity of some components of father and son CHC profile. However, overall male attractiveness is heritable within and across environments, so that sire attractiveness is a good predictor of son attractiveness even with environmental heterogeneity. This suggests that although some male CHC signals are unreliable, attractive genotypes retain their attractiveness across environments on average.     

Modelling shifts in agroclimate and crop cultivar response under climate change

This paper aims: (i) to identify at national scale areas where crop yield formation is currently most prone to climate‐induced stresses, (ii) to evaluate how the severity of these stresses is likely to develop in time and space, and (iii) to appraise and quantify the performance of two strategies for adapting crop cultivation to a wide range of (uncertain) climate change projections. To this end we made use of extensive climate, crop, and soil data, and of two modelling tools: N‐AgriCLIM and the WOFOST crop simulation model. N‐AgriCLIM was developed for the automatic generation of indicators describing basic agroclimatic conditions and was applied over the whole of Finland. WOFOST was used to simulate detailed crop responses at four representative locations. N‐AgriCLIM calculations have been performed nationally for 3829 grid boxes at a 10 × 10 km resolution and for 32 climate scenarios. Ranges of projected shifts in indicator values for heat, drought and other crop‐relevant stresses across the scenarios vary widely – so do the spatial patterns of change. Overall, under reference climate the most risk‐prone areas for spring cereals are found in south‐west Finland, shifting to south‐east Finland towards the end of this century. Conditions for grass are likely to improve. WOFOST simulation results suggest that CO₂ fertilization and adjusted sowing combined can lead to small yield increases of current barley cultivars under most climate scenarios on favourable soils, but not under extreme climate scenarios and poor soils. This information can be valuable for appraising alternative adaptation strategies. It facilitates the identification of regions in which climatic changes might be rapid or otherwise notable for crop production, requiring a more detailed evaluation of adaptation measures. The results also suggest that utilizing the diversity of cultivar responses seems beneficial given the high uncertainty in climate change projections.     

Genotype‐by‐genotype interactions between an insect and its pathogen

Genotype‐by‐genotype (G×G) interactions are an essential requirement for the coevolution of hosts and parasites, but have only been documented in a small number of animal model systems. G×G effects arise from interactions between host and pathogen genotypes, such that some pathogen strains are more infectious in certain hosts and some hosts are more susceptible to certain pathogen strains. We tested for G×G interactions in the gypsy moth (Lymantria dispar) and its baculovirus. We infected 21 full‐sib families of gypsy moths with each of 16 isolates of baculovirus and measured the between‐isolate correlations of infection rate across host families for all pairwise combinations of isolates. Mean infectiousness varied among isolates and disease susceptibility varied among host families. Between‐isolate correlations of infection rate were generally less than one, indicating nonadditive effects of host and pathogen type consistent with G×G interactions. Our results support the presence of G×G effects in the gypsy moth–baculovirus interaction and provide empirical evidence that correlations in infection rates between field‐collected isolates are consistent with values that mathematical models have previously shown to increase the likelihood of pathogen polymorphism.     

Genotype‐by‐environment interactions for cuticular hydrocarbon expression in Drosophila simulans

Genotype‐by‐environment interactions (G × Es) describe genetic variation for phenotypic plasticity. Recent interest in the role of these interactions in sexual selection has identified G × Es across a diverse range of species and sexual traits. Additionally, theoretical work predicts that G × Es in sexual traits could help to maintain genetic variation, but could also disrupt the reliability of these traits as signals of mate quality. However, empirical tests of these theoretical predictions are scarce. We reared iso‐female lines of Drosophila simulans across two axes of environmental variation (diet and temperature) in a fully factorial design and tested for G × Es in the expression of cuticular hydrocarbons (CHCs), a multivariate sexual trait in this species. We find sex‐specific environmental, genetic and G × E effects on CHC expression, with G × Es for diet in both male and female CHC profile and a G × E for temperature in females. We also find some evidence for ecological crossover in these G × Es, and by quantifying variance components, genetic correlations and heritabilities, we show the potential for these G × Es to help maintain genetic variation and cause sexual signal unreliability in D. simulans CHC profiles.     

Crop connectivity under climate change: future environmental and geographic risks of potato late blight in Scotland

The impact of climate change on dispersal processes is largely ignored in risk assessments for crop diseases, as inoculum is generally assumed to be ubiquitous and nonlimiting. We suggest that consideration of the impact of climate change on the connectivity of crops for inoculum transmission may provide additional explanatory and predictive power in disease risk assessments, leading to improved recommendations for agricultural adaptation to climate change. In this study, a crop‐growth model was combined with aerobiological models and a newly developed infection risk model to provide a framework for quantifying the impact of future climates on the risk of disease occurrence and spread. The integrated model uses standard meteorological variables and can be easily adapted to various crop pathosystems characterized by airborne inoculum. In a case study, the framework was used with data defining the spatial distribution of potato crops in Scotland and spatially coherent, probabilistic climate change data to project the future connectivity of crop distributions for Phytophthora infestans (causal agent of potato late blight) inoculum and the subsequent risk of infection. Projections and control recommendations are provided for multiple combinations of potato cultivar and CO₂ emissions scenario, and temporal and spatial averaging schemes. Overall, we found that relative to current climatic conditions, the risk of late blight will increase in Scotland during the first half of the potato growing season and decrease during the second half. To guide adaptation strategies, we also investigated the potential impact of climate change‐driven shifts in the cropping season. Advancing the start of the potato growing season by 1 month proved to be an effective strategy from both an agronomic and late blight management perspective.     

Phenotypic integration plasticity in Daphnia magna: an integral facet of G × E interactions

Phenotypic integration can be defined as the network of multivariate relationships among behavioural, physiological and morphological traits that describe the organism. Phenotypic integration plasticity refers to the change in patterns of phenotypic integration across environments or ontogeny. Because studies of phenotypic plasticity have predominantly focussed on single traits, a G × E interaction is typically perceived as differences in the magnitude of trait expression across two or more environments. However, many plastic responses involve coordinated responses in multiple traits, raising the possibility that relative differences in trait expression in different environments are an important, but often overlooked, source of G × E interaction. Here, we use phenotypic change vectors to statistically compare the multivariate life‐history plasticity of six Daphnia magna clones collected from four disparate European populations. Differences in the magnitude of plastic responses were statistically distinguishable for two of the six clones studied. However, differences in phenotypic integration plasticity were statistically distinguishable for all six of the clones studied, suggesting that phenotypic integration plasticity is an important component of G × E interactions that may be missed unless appropriate multivariate analyses are used.     

Genetic by environment interactions affect plant–soil linkages

The role of plant intraspecific variation in plant–soil linkages is poorly understood, especially in the context of natural environmental variation, but has important implications in evolutionary ecology. We utilized three 18‐ to 21‐year‐old common gardens across an elevational gradient, planted with replicates of five Populus angustifolia genotypes each, to address the hypothesis that tree genotype (G), environment (E), and G × E interactions would affect soil carbon and nitrogen dynamics beneath individual trees. We found that soil nitrogen and carbon varied by over 50% and 62%, respectively, across all common garden environments. We found that plant leaf litter (but not root) traits vary by genotype and environment while soil nutrient pools demonstrated genotype, environment, and sometimes G × E interactions, while process rates (net N mineralization and net nitrification) demonstrated G × E interactions. Plasticity in tree growth and litter chemistry was significantly related to the variation in soil nutrient pools and processes across environments, reflecting tight plant–soil linkages. These data overall suggest that plant genetic variation can have differential affects on carbon storage and nitrogen cycling, with implications for understanding the role of genetic variation in plant–soil feedback as well as management plans for conservation and restoration of forest habitats with a changing climate.     

Quantitative trait loci and candidate genes underlying genotype by environment interaction in the response of Arabidopsis thaliana to drought

Drought stress was imposed on two sets of Arabidopsis thaliana genotypes grown in sand under short‐day conditions and analysed for several shoot and root growth traits. The response to drought was assessed for quantitative trait locus (QTL) mapping in a genetically diverse set of Arabidopsis accessions using genome‐wide association (GWA) mapping, and conventional linkage analysis of a recombinant inbred line (RIL) population. Results showed significant genotype by environment interaction (G×E) for all traits in response to different watering regimes. For the RIL population, the observed G×E was reflected in 17 QTL by environment interactions (Q×E), while 17 additional QTLs were mapped not showing Q×E. GWA mapping identified 58 single nucleotide polymorphism (SNPs) associated with loci displaying Q×E and an additional 16 SNPs associated with loci not showing Q×E. Many candidate genes potentially underlying these loci were suggested. The genes for RPS3C and YLS7 were found to contain conserved amino acid differences when comparing Arabidopsis accessions with strongly contrasting drought response phenotypes, further supporting their candidacy. One of these candidate genes co‐located with a QTL mapped in the RIL population.     

Plastic responses in the metabolome and functional traits of maize plants to temperature variations

Environmentally inducible phenotypic plasticity is a major player in plant responses to climate change. However, metabolic responses and their role in determining the phenotypic plasticity of plants that are subjected to temperature variations remain poorly understood. The metabolomic profiles and metabolite levels in the leaves of three maize inbred lines grown in different temperature conditions were examined with a nuclear magnetic resonance metabolomic technique. The relationship of functional traits to metabolome profiles and the metabolic mechanism underlying temperature variations were then explored. A comparative analysis showed that during heat and cold stress, maize plants shared common plastic responses in biomass accumulation, carbon, nitrogen, sugars, some amino acids and compatible solutes. We also found that the plastic response of maize plants to heat stress was different from that under cold stress, mainly involving biomass allocation, shikimate and its aromatic amino acid derivatives, and other non‐polar metabolites. The plastic responsiveness of functional traits of maize lines to temperature variations was low, while the metabolic responsiveness in plasticity was high, indicating that functional and metabolic plasticity may play different roles in maize plant adaptation to temperature variations. A linear regression analysis revealed that the maize lines could adapt to growth temperature variations through the interrelation of plastic responses in the metabolomes and functional traits, such as biomass allocation and the status of carbon and nitrogen. We provide valuable insight into the plastic response strategy of maize plants to temperature variations that will permit the optimisation of crop cultivation in an increasingly variable environment.     

High night temperatures during grain number determination reduce wheat and barley grain yield: a field study

Warm nights are a widespread predicted feature of climate change. This study investigated the impact of high night temperatures during the critical period for grain yield determination in wheat and barley crops under field conditions, assessing the effects on development, growth and partitioning crop‐level processes driving grain number per unit area (GN). Experiments combined: (i) two contrasting radiation and temperature environments: late sowing in 2011 and early sowing in 2013, (ii) two well‐adapted crops with similar phenology: bread wheat and two‐row malting barley and (iii) two temperature regimes: ambient and high night temperatures. The night temperature increase (ca. 3.9 °C in both crops and growing seasons) was achieved using purpose‐built heating chambers placed on the crop at 19:000 hours and removed at 7:00 hours every day from the third detectable stem node to 10 days post‐flowering. Across growing seasons and crops, the average minimum temperature during the critical period ranged from 11.2 to 17.2 °C. Wheat and barley grain yield were similarly reduced under warm nights (ca. 7% °C^?1), due to GN reductions (ca. 6% °C^?1) linked to a lower number of spikes per m². An accelerated development under high night temperatures led to a shorter critical period duration, reducing solar radiation capture with negative consequences for biomass production, GN and therefore, grain yield. The information generated could be used as a starting point to design management and/or breeding strategies to improve crop adaptation facing climate change.     

Crop production structure and stability under climate change in South America

Southern South America is expected to play an increasingly important role in global food production, but climate change could seriously threaten it. Here we have analysed long‐term historical data for major crops (rice, oats, barley, sunflower, soybean, sorghum, wheat, maize) at subnational scale to (a) look for common features among crop yield dynamics, evaluating their structure and implications for the persistence of that crop; (b) address complex crop responses to changes in environmental growing conditions; and (c) identify climate impact hotspots that are crucial for adaptation and mitigation. We have proposed a novel methodological approach based on dynamics systems in order to understand the processes behind annual crop yield fluctuations. We report the results of general patterns in the internal process (biophysical adjustments by rapid negative feedbacks) regulating crop production and analyse how it influences crop persistence and yield ceilings. The structure of a crop yield dynamic system defines its behaviour, but climate variations could displace it from yield equilibrium and affect its stability. Our findings suggest that weather conditions have a stronger impact on yield growth at high rather than at low yield levels (non‐additive impacts). This allows agriculture management to be refined and applied more efficiently, weakening the relationship between crop productivity and climate change and predicting the response of crop production to yield‐improvement strategies. We have identified those crops and regions which are most vulnerable to the current climate change trends in southern South American agroecosystems. Our results allow us to point to new ways to enhance self‐regulatory success, maximising the efficiency of crop production and reducing climate impacts. We have discussed important implications for crop management and climate change mitigation in an area where agriculture plays a key role in its socioeconomic and ecologic dimensions.     

Agriculture under Climate Change in China: Mitigate the Risks by Grasping the Emerging Opportunities

ABSTRACT

There have been increasing concerns on risks and uncertainty posed by climate change to China's future crop production. The existing assessments using popular process-based and site-specific crop growing models highlight the significant extent of climate-induced yield reduction, and thus suggest a scary downward risk for China's future food production. Surprisingly, much less attention has been paid to exploring the potential gains that may also be brought by climate change. To address this imbalance, we develop an integrated agro-climatic and ecological assessment tool that is capable of detecting the shifts of multicropping opportunities under different climate change scenarios. The application of this tool to the context of China reveals significant extension of multicropping opportunities brought in by climate change. We argue for an active adaptation to such emerging opportunities through both market and policy incentives, because the aggregate gain of such adaptation is sufficient to outweigh the loss as revealed by the existing assessments.     

Coherent synthesis of genomic associations with phenotypes and home environments

Local adaptation is often studied via (i) multiple common garden experiments comparing performance of genotypes in different environments and (ii) sequencing genotypes from multiple locations and characterizing geographic patterns in allele frequency. Both approaches aim to characterize the same pattern (local adaptation), yet the complementary information from each has not yet been coherently integrated. Here, we develop a genome‐wide association model of genotype interactions with continuous environmental gradients (G × E), that is reaction norms. We present an approach to impute relative fitness, allowing us to coherently synthesize evidence from common garden and genome–environment associations. Our approach identifies loci exhibiting environmental clines where alleles are associated with higher fitness in home environments. Simulations show our approach can increase power to detect loci causing local adaptation. In a case study on Arabidopsis thaliana, most identified SNPs exhibited home allele advantage and fitness trade‐offs along climate gradients, suggesting selective gradients can maintain allelic clines. SNPs exhibiting G × E associations with fitness were enriched in genic regions, putative partial selective sweeps and associations with an adaptive phenotype (flowering time plasticity). We discuss extensions for situations where only adaptive phenotypes other than fitness are available. Many types of data may point towards the loci underlying G × E and local adaptation; coherent models of diverse data provide a principled basis for synthesis.     

Will changes in phenology track climate change? A study of growth initiation timing in coast Douglas‐fir

Under climate change, the reduction of frost risk, onset of warm temperatures and depletion of soil moisture are all likely to occur earlier in the year in many temperate regions. The resilience of tree species will depend on their ability to track these changes in climate with shifts in phenology that lead to earlier growth initiation in the spring. Exposure to warm temperatures (‘forcing’) typically triggers growth initiation, but many trees also require exposure to cool temperatures (‘chilling’) while dormant to readily initiate growth in the spring. If warming increases forcing and decreases chilling, climate change could maintain, advance or delay growth initiation phenology relative to the onset of favorable conditions. We modeled the timing of height‐ and diameter‐growth initiation in coast Douglas‐fir (an ecologically and economically vital tree in western North America) to determine whether changes in phenology are likely to track changes in climate using data from field‐based and controlled‐environment studies, which included conditions warmer than those currently experienced in the tree's range. For high latitude and elevation portions of the tree's range, our models predicted that warming will lead to earlier growth initiation and allow trees to track changes in the onset of the warm but still moist conditions that favor growth, generally without substantially greater exposure to frost. In contrast, toward lower latitude and elevation range limits, the models predicted that warming will lead to delayed growth initiation relative to changes in climate due to reduced chilling, with trees failing to capture favorable conditions in the earlier parts of the spring. This maladaptive response to climate change was more prevalent for diameter‐growth initiation than height‐growth initiation. The decoupling of growth initiation with the onset of favorable climatic conditions could reduce the resilience of coast Douglas‐fir to climate change at the warm edges of its distribution.     

Genotype by environment interaction for index traits that combine growth and wood density in loblolly pine

 Genotype×environment interactions of individual traits have been assessed in numerous experiments with forest trees. However, since breeding programs rarely aim at the improvement of a single trait, the impact of G×E on index or composite traits must also be assessed. In a study with 12-year-old loblolly pine families in the southeastern U.S., G×E variance was of relatively little importance compared to genetic variance for wood density but was of greater significance for several growth traits. An index that combined stem volume and wood density to improve dry weight but maintain wood density constant (restricted selection index) resulted in substantially greater G×E variance compared to either of the component traits. The interaction variance of an index trait is shown to be a function of the index coefficients and the G×E variances and covariances for its constituent traits. As a result, for some conditions it surpasses the magnitude of G×E variance for each component trait. Received: 5 September 1996 / Accepted: 25 October 1996     

Predicting how adaptation to climate change could affect ecological conservation: secondary impacts of shifting agricultural suitability

Aim:  Ecosystems face numerous well‐documented threats from climate change. The well‐being of people also is threatened by climate change, most prominently by reduced food security. Human adaptation to food scarcity, including shifting agricultural zones, will create new threats for natural ecosystems. We investigated how shifts in crop suitability because of climate change may overlap currently protected areas (PAs) and priority sites for PA expansion in South Africa. Predicting the locations of suitable climate conditions for crop growth will assist conservationists and decision‐makers in planning for climate change. Location:  South Africa. Methods:  We modelled climatic suitability in 2055 for maize and wheat cultivation, two extensively planted, staple crops, and overlaid projected changes with PAs and PA expansion priorities. Results:  Changes in winter climate could make an additional 2 million ha of land suitable for wheat cultivation, while changes in summer climate could expand maize suitability by up to 3.5 million ha. Conversely, 3 million ha of lands currently suitable for wheat production are predicted to become climatically unsuitable, along with 13 million ha for maize. At least 328 of 834 (39%) PAs are projected to be affected by altered wheat or maize suitability in their buffer zones. Main conclusions:  Reduced crop suitability and food scarcity in subsistence areas may lead to the exploitation of PAs for food and fuel. However, if reduced crop suitability leads to agricultural abandonment, this may afford opportunities for ecological restoration. Expanded crop suitability in PA buffer zones could lead to additional isolation of PAs if portions of newly suitable land are converted to agriculture. These results suggest that altered crop suitability will be widespread throughout South Africa, including within and around lands identified as conservation priorities. Assessing how climate change will affect crop suitability near PAs is a first step towards proactively identifying potential conflicts between human adaptation and conservation planning.