Spatial and phylogenetic structure of Alpine stonefly assemblages across seven habitats using DNA-species

Stream ecosystems are spatially heterogeneous, with many different habitat patches distributed within a small area. The influence of this heterogeneity on the biodiversity of benthic insect communities is well documented; however, studies of the role of habitat heterogeneity in species coexistence and assembly remain limited. Here, we investigated how habitat heterogeneity influences spatial structure (beta biodiversity) and phylogenetic structure (evolutionary processes) of benthic stonefly (Plecoptera, Insecta) communities. We sampled 20 sites along two Alpine rivers, including seven habitats in four different reaches (headwaters, meandering, bar-braided floodplain, and lowland spring-fed). We identified 21 morphological species and delineated 52 DNA-species based on sequences from mitochondrial cox1 and nuclear ITS markers. Using DNA-species, we first analysed the patterns of variation in richness, diversity, and assemblage composition by quantifing the contribution of each reach and habitat to the overall DNA-species diversity using an additive partition analysis and distance-based redundancy analysis. Using gene-tree phylogenies, we assessed whether environmental filtering could lead to the co-occurrence of DNA-species using a two-step analysis to detect a phylogenetic signal. All four reaches significantly contributed to DNA-species richness, with the meandering reach having the highest contribution. Habitats had an effect on DNA-species diversity, where glide, riffle and, pool influenced the spatial structure of stonefly assemblage possibly due to the high habitat heterogeneity. Among the habitats, the pool showed significant phylogenetic clustering, suggesting high levels of evolutionary adaptation and strong habitat filtering. This assemblage structure may be caused by long-term stability of the habitat and the similar requirements for co-occurring species. Our study shows the importance of different habitats for the spatial and phylogenetic structure of stonefly assemblage and sheds light on the habitat-specific diversity that may help improve conservation practices.

Linking quantitative genetics with community-level performance: Are there operational models for plant breeding?

Plant breeding is focused on the genotype and population levels while targeting effects at higher levels of biodiversity, from crop covers to agroecosystems. Making predictions across nested levels of biodiversity is therefore a major challenge for the development of intercropping practices. New prediction tools and concepts are required to design breeding strategies with desirable outcomes at the crop community level. We reviewed theoretical advances in the field of evolutionary ecology to identify potentially operational ways of predicting the effects of artificial selection on community-level performances. We identified three main types of approaches differing in the way they model interspecific indirect genetic effects (IIGEs) at the community level: (1) The community heritability approach estimates the variance for IIGE induced by a focal species at the community level; (2) the joint phenotype approach quantifies genetic constraints between direct genetic effects and IIGE for a set of interacting species; (3) the community-trait genetic gradient approach decomposes the IIGE for a focal species across a multivariate set of its functional traits. We discuss the potential operational capacities of these approaches and stress that each is a special case of a general multitrait and multispecies selection index. Choosing one therefore involves assumptions and goals regarding the breeding target and strategy. Obtaining reliable quantitative, community-level predictions at the genetic level is constrained by the size and complexity of the experimental designs usually required. Breeding strategies should instead be compared using theoretically informed qualitative predictions. The need to estimate genetic covariances between traits measured both within and among species (for IIGE) is another obstacle, as the two are not determined by the exact same biological processes. We suggest future research directions and strategies to overcome these limits. Our synthesis offers an integrative theoretical framework for breeders interested in the genetic improvement of crop communities but also for scientists interested in the genetic bases of plant community functioning.

The Indirect Genetic Effect Interaction Coefficient ψ: Theoretically Essential and Empirically Neglected

The interaction effect coefficient ψ has been a much-discussed, fundamental parameter of indirect genetic effect (IGE) models since its formal mathematical description in 1997. The coefficient simultaneously describes the form of changes in trait expression caused by genes in the social environment and predicts the evolutionary consequences of those IGEs. Here, we report a striking mismatch between theoretical emphasis on ψ and its usage in empirical studies. Surveying all IGE research, we find that the coefficient ψ has not been equivalently conceptualized across studies. Several issues related to its proper empirical measurement have recently been raised, and these may severely distort interpretations about the evolutionary consequences of IGEs. We provide practical advice on avoiding such pitfalls. The majority of empirical IGE studies use an alternative variance-partitioning approach rooted in well-established statistical quantitative genetics, but several hundred estimates of ψ (from 15 studies) have been published. A significant majority are positive. In addition, IGEs with feedback, that is, involving the same trait in both interacting partners, are far more likely to be positive and of greater magnitude. Although potentially challenging to measure without bias, ψ has critically-developed theoretical underpinnings that provide unique advantages for empirical work. We advocate for a shift in perspective for empirical work, from ψ as a description of IGEs, to ψ as a robust predictor of evolutionary change. Approaches that "run evolution forward" can take advantage of ψ to provide falsifiable predictions about specific trait interactions, providing much-needed insight into the evolutionary consequences of IGEs.

Nothing in Evolution Makes Sense Except in the Light of Biology

A key question in biology is the predictability of the evolutionary process. If we can correctly predict the outcome of evolution, we may be better equipped to anticipate and manage species' adaptation to climate change, habitat loss, invasive species, or emerging infectious diseases, as well as improve our basic understanding of the history of life on Earth. In the present article, we ask the questions when, why, and if the outcome of future evolution is predictable. We first define predictable and then discuss two conflicting views: that evolution is inherently unpredictable and that evolution is predictable given the ability to collect the right data. We identify factors that generate unpredictability, the data that might be required to make predictions at some level of precision or at a specific timescale, and the intellectual and translational value of understanding when prediction is or is not possible.

Order Through Disorder: The Characteristic Variability of Systems

Randomness characterizes many processes in nature, and therefore its importance cannot be overstated. In the present study, we investigate examples of randomness found in various fields, to underlie its fundamental processes. The fields we address include physics, chemistry, biology (biological systems from genes to whole organs), medicine, and environmental science. Through the chosen examples, we explore the seemingly paradoxical nature of life and demonstrate that randomness is preferred under specific conditions. Furthermore, under certain conditions, promoting or making use of variability-associated parameters may be necessary for improving the function of processes and systems.

Producing and scrounging can have stabilizing effects at multiple levels of organization

This study shows, for the first time, that the evolution of a simple behavior, scrounging, at the individual level can have effects on populations, food chains, and community structure. In particular, the addition of scrounging in consumer populations can allow multiple consumers to coexist while exploiting a single prey. Also, scrounging in the top predator of a tritrophic food chain can stabilize interactions between the top predator, its prey, and its prey's prey. This occurs because the payoffs to scrounging for food in a population are negative frequency dependent, allowing scroungers to invade a population and to coexist with producers at a frequency which is density-dependent. The presence of scroungers, who do not search for resources but simply use those found by others (producers) reduces the total amount of resource acquired by the group. As scrounging increases with group size, this leads to less resource acquired per individual as the group grows. Ultimately, this limits the size of the group, its impact on its prey, and its ability to outcompete other species. These effects can promote stability and thus increase species diversity. I will further suggest that prey may alter their spatial distribution such that scrounging will be profitable among their predators thus reducing predation rate on the prey.

Keystone Genes

The keystone species concept is used in ecology to describe individual species with disproportionately large effects on their communities. We extend this idea to the level of genes with disproportionately large effects on ecological processes. Such 'keystone genes' (KGs) would underlie traits involved in species interactions or causing critical biotic and/or abiotic changes that influence emergent community and ecosystem properties. We propose a general framework for how KGs could be identified, while keeping KGs under the umbrella of 'ecologically important genes' (EIGs) that also include categories such as 'foundation genes', 'ecosystem engineering genes', and more. Although likely rare, KGs and other EIGs could dominate certain ecological processes; thus, their discovery and study are relevant for understanding eco-evolutionary dynamics.

Effects of Intraspecific Genetic Variation and Prior Herbivory in an Old-Field Plant on the Abundance of the Specialist Aphid Uroleucon nigrotuberculatum (Hemiptera: Aphididae)

Intraspecific genetic variation in plants can contribute to the diversity and abundance of associated insects, though many questions remain about why some genotypes support more insects than others. Since plant secondary metabolites, which may be induced after insect attack, may potentially vary among genotypes, these compounds provide a possible explanation for insect abundance variation in plants with substantial genetic variation. In this study, we examined four genotypes of the old-field plant species Solidago altissima (L.; Asterales: Asteraceae) and asked if the abundance of the specialist aphid Uroleucon nigrotuberculatum (Olive; Hemiptera: Aphididae) was affected by genotype and previous foliage damage by a specialist beetle. We hypothesized that different genotypes and prior herbivory would result in different quantities of terpenes produced by S. altissima, and that terpenes would affect aphid abundance. We found evidence of foliar terpene induction in a greenhouse environment, and significant differences in terpene production among genotypes in a field setting, though prior damage had little effect on aphid abundance in the field. There were significant effects of genotypes on aphid abundance, as well as genotype effects on terpenes and foliar nutrients (leaf N and C:N). Noteworthy was a change in the allocation of particular terpenes among genotypes that related to aphid abundance. Our analyses demonstrated that phytochemicals, and especially terpenes, related to aphid abundance. This study adds to a previous finding that variation in leaf terpenes in S. altissima provides a partial explanation for variable abundance among genotypes of a specialist aphid, and suggests that differences in the allocation of compounds is important.

Human drivers of ecological and evolutionary dynamics in emerging and disappearing infectious disease systems

Humans have contributed to the increased frequency and severity of emerging infectious diseases, which pose a significant threat to wild and domestic species, as well as human health. This review examines major pathways by which humans influence parasitism by altering (co)evolutionary interactions between hosts and parasites on ecological timescales. There is still much to learn about these interactions, but a few well-studied cases show that humans influence disease emergence every step of the way. Human actions significantly increase dispersal of host, parasite and vector species, enabling greater frequency of infection in naive host populations and host switches. Very dense host populations resulting from urbanization and agriculture can drive the evolution of more virulent parasites and, in some cases, more resistant host populations. Human activities that reduce host genetic diversity or impose abiotic stress can impair the ability of hosts to adapt to disease threats. Further, evolutionary responses of hosts and parasites can thwart disease management and biocontrol efforts. Finally, in rare cases, humans influence evolution by eradicating an infectious disease. If we hope to fully understand the factors driving disease emergence and potentially control these epidemics we must consider the widespread influence of humans on host and parasite evolutionary trajectories.This article is part of the themed issue 'Human influences on evolution, and the ecological and societal consequences'.

Differential phenotypic and genetic expression of defence compounds in a plant-herbivore interaction along elevation

Elevation gradients impose large differences in abiotic and biotic conditions over short distances, in turn, likely driving differences in gene expression more than would genetic variation per se, as natural selection and drift are less likely to fix alleles at such a narrow spatial scale. As elevation increases, the pressure exerted on plants by herbivores and on arthropod herbivores by predators decreases, and organisms spanning the elevation gradient are thus expected to show lower levels of defence at high elevation. The alternative hypothesis, based on the optimal defence theory, is that defence allocation should be higher in low-resource habitats such as those at high elevation, due to higher costs associated with tissue replacement. In this study, we analyse variation with elevation in (i) defence compound content in the plant Lotus corniculatus and (ii) gene expression associated with defence against predators in the specific phytophagous moth, Zygaena filipendulae. Both species produce cyanogenic glycosides (CNglcs) such as lotaustralin and linamarin as defence mechanisms, with the moth, in addition, being able to sequester CNglcs from its host plant. Specifically, we tested the assumption that the defence-associated phenotype in plants and the gene expression in the insect herbivore should covary between low- and high-elevation environments. We found that L. corniculatus accumulated more CNglcs at high elevation, a result in agreement with the optimal defence theory. By contrast, we found that the levels of expression in the defence genes of Z. filipendulae larvae were not related to the CNglc content of their host plant. Overall, expression levels were not correlated with elevation either, with the exception of the UGT33A1 gene, which showed a marginally significant trend towards higher expression at high elevation when using a simple statistical framework. These results suggest that the defence phenotype of plants against herbivores, and subsequent herbivore sequestration machineries and de novo production, are based on a complex network of interactions.

The Genetics Underlying Natural Variation in the Biotic Interactions of Arabidopsis thaliana: The Challenges of Linking Evolutionary Genetics and Community Ecology

In the context of global change, predicting the responses of plant communities in an ever-changing biotic environment calls for a multipronged approach at the interface of evolutionary genetics and community ecology. However, our understanding of the genetic basis of natural variation involved in mediating biotic interactions, and associated adaptive dynamics of focal plants in their natural communities, is still in its infancy. Here, we review the genetic and molecular bases of natural variation in the response to biotic interactions (viruses, bacteria, fungi, oomycetes, herbivores, and plants) in the model plant Arabidopsis thaliana as well as the adaptive value of these bases. Among the 60 identified genes are a number that encode nucleotide-binding site leucine-rich repeat (NBS-LRR)-type proteins, consistent with early examples of plant defense genes. However, recent studies have revealed an extensive diversity in the molecular mechanisms of defense. Many types of genetic variants associate with phenotypic variation in biotic interactions, even among the genes of large effect that tend to be identified. In general, we found that (i) balancing selection rather than directional selection explains the observed patterns of genetic diversity within A. thaliana and (ii) the cost/benefit tradeoffs of adaptive alleles can be strongly dependent on both genomic and environmental contexts. Finally, because A. thaliana rarely interacts with only one biotic partner in nature, we highlight the benefit of exploring diffuse biotic interactions rather than tightly associated host-enemy pairs. This challenge would help to improve our understanding of coevolutionary quantitative genetics within the context of realistic community complexity.

Human-aided admixture may fuel ecosystem transformation during biological invasions: theoretical and experimental evidence

Biological invasions can transform our understanding of how the interplay of historical isolation and contemporary (human-aided) dispersal affects the structure of intraspecific diversity in functional traits, and in turn, how changes in functional traits affect other scales of biological organization such as communities and ecosystems. Because biological invasions frequently involve the admixture of previously isolated lineages as a result of human-aided dispersal, studies of invasive populations can reveal how admixture results in novel genotypes and shifts in functional trait variation within populations. Further, because invasive species can be ecosystem engineers within invaded ecosystems, admixture-induced shifts in the functional traits of invaders can affect the composition of native biodiversity and alter the flow of resources through the system. Thus, invasions represent promising yet under-investigated examples of how the effects of short-term evolutionary changes can cascade across biological scales of diversity. Here, we propose a conceptual framework that admixture between divergent source populations during biological invasions can reorganize the genetic variation underlying key functional traits, leading to shifts in the mean and variance of functional traits within invasive populations. Changes in the mean or variance of key traits can initiate new ecological feedback mechanisms that result in a critical transition from a native ecosystem to a novel invasive ecosystem. We illustrate the application of this framework with reference to a well-studied plant model system in invasion biology and show how a combination of quantitative genetic experiments, functional trait studies, whole ecosystem field studies and modeling can be used to explore the dynamics predicted to trigger these critical transitions.

Genetic sorting of subordinate species in grassland modulated by intraspecific variation in dominant species

Genetic variation in a single species can have predictable and heritable effects on associated communities and ecosystem processes, however little is known about how genetic variation of a dominant species affects plant community assembly. We characterized the genetic structure of a dominant grass (Sorghastrum nutans) and two subordinate species (Chamaecrista fasciculata, Silphium integrifolium), during the third growing season in grassland communities established with genetically distinct (cultivated varieties or local ecotypes) seed sources of the dominant grasses. There were genetic differences between subordinate species growing in the cultivar versus local ecotype communities, indicating that intraspecific genetic variation in the dominant grasses affected the genetic composition of subordinate species during community assembly. A positive association between genetic diversity of S. nutans, C. fasciculata, and S. integrifolium and species diversity established the role of an intraspecific biotic filter during community assembly. Our results show that intraspecific variation in dominant species can significantly modulate the genetic composition of subordinate species.

Global climate change and the evolutionary ecology of ecosystem functioning

Environmental warming due to global climate change is an important stressor that stands to alter organismal physiology and, ultimately, carbon cycling in ecosystems. Yet the theoretical framework for predicting warming effects on whole-ecosystem carbon balance by way of changes in organismal physiology remains rudimentary. This is because ecosystem science has yet to embrace principles of evolutionary ecology that offer the means to explain how environmental stress on organisms mediates ecosystem carbon dynamics. Here, using selected case studies and a theoretical model, I sketch out one framework that shows how increases in animal metabolic rates in response to thermal stress lead to phenotypically plastic shifts in animal elemental demand, from nitrogen-rich proteins that support production to carbon-rich soluble carbohydrates that support elevated energy demands. I further show how such a switch in resource selection alters the fate of carbon between atmospheric versus animal, plant, and soil pools. The framework shows that animals, despite having relatively low biomass representation in ecosystems, can nonetheless have disproportionately larger effects on carbon cycling in ecosystems whose effects are exacerbated by environmental stressors like climate warming.

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.