Biodiversity and productivity in eastern US forests.

Despite experimental and observational studies demonstrating that biodiversity enhances primary productivity, the best metric for predicting productivity at broad geographic extents-functional trait diversity, phylogenetic diversity, or species richness-remains unknown. Using >1.8 million tree measurements from across eastern US forests, we quantified relationships among functional trait diversity, phylogenetic diversity, species richness, and productivity. Surprisingly, functional trait and phylogenetic diversity explained little variation in productivity that could not be explained by tree species richness. This result was consistent across the entire eastern United States, within ecoprovinces, and within data subsets that controlled for biomass or stand age. Metrics of functional trait and phylogenetic diversity that were independent of species richness were negatively correlated with productivity. This last result suggests that processes that determine species sorting and packing are likely important for the relationships between productivity and biodiversity. This result also demonstrates the potential confusion that can arise when interdependencies among different diversity metrics are ignored. Our findings show the value of species richness as a predictive tool and highlight gaps in knowledge about linkages between functional diversity and ecosystem functioning.

Habitat Choice and Temporal Variation Alter the Balance between Adaptation by Genetic Differentiation, a Jack-of-All-Trades Strategy, and Phenotypic Plasticity.

Confronted with variable environments, species adapt in several ways, including genetic differentiation, a jack-of-all-trades strategy, or phenotypic plasticity. Adaptive habitat choice favors genetic differentiation and local adaptation over a generalist, jack-of-all-trades strategy. Models predict that, absent plasticity costs, variable environments generally favor phenotypic plasticity over genetic differentiation and being a jack-of-all-trades generalist. It is unknown how habitat choice might affect the evolution of plasticity. Using an individual-based simulation model, I explored the interaction of choice and plasticity. With only spatial variation, habitat choice promotes genetic differentiation over a jack-of-all-trades strategy or phenotypic plasticity. In the absence of plasticity, temporal variation favors a jack-of-all-trades strategy over choice-mediated genetic differentiation; when plasticity is an option, it is favored. This occurs because habitat choice creates a feedback between genetic differentiation and dispersal rates. As demes become better adapted to their local environments, the effective dispersal rate decreases, because more individuals have very high fitness and so choose not to disperse, reinforcing local stabilizing selection and negating selection for plasticity. Temporal variation breaks that feedback. These results point to a potential data paradox: systems with habitat choice may have the lowest actual movement rates. The potential for adaptive habitat choice may be very common, but its existence may reduce observed dispersal rates enough that we do not recognize systems where it may be present, warranting further exploration of likely systems.

The Genetics of Phenotypic Plasticity. XIV. Coevolution.

Plastic changes in organisms' phenotypes can result from either abiotic or biotic effectors. Biotic effectors create the potential for a coevolutionary dynamic. Through the use of individual-based simulations, we examined the coevolutionary dynamic of two species that are phenotypically plastic. We explored two modes of biotic and abiotic interactions: ecological interactions that determine the form of natural selection and developmental interactions that determine phenotypes. Overall, coevolution had a larger effect on the evolution of phenotypic plasticity than plasticity had on the outcome of coevolution. Effects on the evolution of plasticity were greater when the fitness-maximizing coevolutionary outcomes were antagonistic between the species pair (predator-prey interactions) than when those outcomes were augmenting (competitive or mutualistic). Overall, evolution in the context of biotic interactions reduced selection for plasticity even when trait development was responding to just the abiotic environment. Thus, the evolution of phenotypic plasticity must always be interpreted in the full context of a species' ecology. Our results show how the merging of two theory domains--coevolution and phenotypic plasticity--can deepen our understanding of both and point to new empirical research.

The genetics of phenotypic plasticity. XVIII. Developmental limits restrict adaptive plasticity.

After environmental change, the trait evolution needed to rescue a population depends on the functional form of the plastic change (reaction norm) of that trait. Nearly all previous models of plasticity evolution for continuous traits have assumed that the functional form is linear, i.e., no limits on the range of plasticity. This paper examines the effect of developmental limits, modeled as a sigmoidal reaction norm, on evolutionary rescue after an abrupt environmental change and the subsequent evolution of plasticity, including genetic assimilation. We examined four different scenarios: (1) developmental limits only, (2) developmental limits plus a cost of plasticity, (3) developmental limits with developmental noise, and (4) developmental limits plus environmental variation. The probability of evolutionary rescue increased with an increase in phenotypic variation allowed by plastic development. With a smaller limit to the range of the plastic phenotype, the evolution of adaptive plasticity was limited, meaning the evolution of non-plastic genes was necessary. The addition of developmental constraints to the model did not speed up genetic assimilation, suggesting new theory is needed to understand empirical observations. The modeling framework presented here could be extended to different ecological and evolutionary conditions, alternative reaction norm shapes, the evolution of additional reaction norm parameters such as the range or the location of the inflection point on the environmental axis, or other function-valued traits.

The factors that favor adaptive habitat construction versus non-adaptive environmental conditioning.

Adaptive habitat construction is a process by which individuals alter their environment so as to increase their (inclusive) fitness. Such alterations are a subset of the myriad ways that individuals condition their environment. We present an individual-based model of habitat construction to explore what factors might favor selection when the benefits of environmental alterations are shared by individuals of the same species. Our results confirm the predictions of inclusive fitness and group selection theory and expectations based on previous models that construction will be more favored when its benefits are more likely to be directed to self or near kin. We found that temporal variation had no effect on the evolution of construction. For spatial heterogeneity, construction was disfavored when the spatial pattern of movement did not match the spatial pattern of environmental heterogeneity, especially when there was spatial heterogeneity in the optimal amount of construction. Under those conditions, very strong selection was necessary to favor genetic differentiation of construction propensity among demes. We put forth a constitutive theory for the evolution of adaptive habitat construction that unifies our model with previous verbal and quantitative models into a formal conceptual framework.

Do I build or do I move? Adaptation by habitat construction versus habitat choice.

Trait adaptation to a heterogeneous environment can occur through six modes: genetic differentiation of those traits, a jack-of-all-trades phenotypic uniformity, diversified bet-hedging, phenotypic plasticity, habitat choice, and habitat construction. A key question is what circumstances favor one mode over another, and how they might interact if a system can express more than one mode at a time. We examined the joint evolution of habitat choice and habitat construction using individual-based simulations. We manipulated when during the life cycle construction occurred and the fitness value of construction. We found that for our model habitat construction was nearly always favored over habitat choice, especially if construction happened after dispersal. Because of the ways that the various modes of adaptation interact with each other, there is no simple answer as to which will be favored; it depends on details of the biology and ecology of a given system.

The evolution of habitat construction with and without phenotypic plasticity.

Habitat construction and phenotypic plasticity are alternative responses to variable environments. We explored evolution along an environmental gradient of habitat construction alone and in combination with phenotypic plasticity using individual-based simulations that manipulated the fitness benefit of construction and whether construction maintained or eliminated that gradient. Construction was favored when its benefits were more likely to flow to the immediate offspring of the constructing individuals. Habitat construction and phenotypic plasticity traded off against each other or plasticity was selected against, depending on how the optimum environment varied and with the fitness value of construction. When selection favored differences in the amount of construction along the environmental gradient, genetic differentiation for habitat construction increased as the fitness value of construction increased. The degree to which each adaptive response was likely to evolve also depended on the precise ordering of life history events. Adaptive habitat construction does not always occur and may be selected against.

Severe limitations of the FEve metric of functional evenness and some alternative metrics.

The metric of functional evenness FEve is an example of how approaches to conceptualizing and measuring functional variability may go astray. This index has several critical conceptual and practical drawbacks: Different values of the FEve index for the same community can be obtained if the species have unequal species abundances; this result is highly likely if most of the traits are categorical.Very minor differences in even one pairwise distance can result in very different values of FEve.FEve uses only a fraction of the information contained in the matrix of species distances. Counterintuitively, this can cause very similar FEve scores for communities with substantially different patterns of species dispersal in trait space.FEve is a valid metric only if all species have exactly the same abundances. However, the meaning of FEve in such an instance is unclear as the purpose of the metric is to measure the variability of abundances in trait space. We recommend not using the FEve metric in studies of functional variability. Given the wide usage of FEve index over the last decade, the validity of the conclusions based on those estimates is in question. Instead, we suggest three alternative metrics that combine variability in species distances in trait space with abundance in various ways. More broadly, we recommend that researchers think about which community properties (e.g., trait distances of a focus species to the nearest neighbor or all other species, variability of pairwise interactions between species) they want to measure and pick from among the appropriate metrics.

The genetics of phenotypic plasticity. XVII. Response to climate change.

The world is changing at a rapid rate, threatening extinction for a large part of the world's biota. One potential response to those altered conditions is to evolve so as to be able to persist in place. Such evolution includes not just traits themselves, but also the phenotypic plasticity of those traits. We used individual-based simulations to explore the potential of an evolving phenotypic plasticity to increase the probability of persistence in the response to either a step change or continual, directional change in the environment accompanied by within-generation random environmental fluctuations. Populations could evolve by altering both their nonplastic and plastic genetic components. We found that phenotypic plasticity enhanced survival and adaptation if that plasticity was not costly. If plasticity was costly, for it to be beneficial the phenotypic magnitude of plasticity had to be great enough in the initial generations to overcome those costs. These results were not sensitive to either the magnitude of the within-generation correlation between the environment of development and the environment of selection or the magnitude of the environmental fluctuations, except for very small phenotypic magnitudes of plasticity. So, phenotypic plasticity has the potential to enhance survival; however, more data are needed on the ubiquity of trait plasticity, the extent of costs of plasticity, and the rate of mutational input of genetic variation for plasticity.

Nestedness of remnant sonoran desert plant communities in metropolitan Phoenix, Arizona.

Urbanization can have profound effects on the plant communities persisting in remnant habitats. That process can be explored by examining patterns of nestedness. Species composition for a set of communities exhibits a nested pattern if species present in progressively richer assemblages form a series of subsets. Nestedness can form as a result of the dynamic processes of extinction or colonization. It can also reflect a nested distribution of habitats among the sites or the differential abundance properties of species through passive sampling. This study investigated whether Sonoran Desert woody vegetation in remnant islands within metropolitan Phoenix is nested and explored which mechanisms are responsible for the pattern. It also examined whether vegetation is nested in similar habitat types across islands, and how species abundance relates to the nested pattern and hypothesized mechanisms. All data sets were significantly nested, indicating a nested pattern at the island and habitat levels. Community-level analyses did not indicate a primary mechanism leading to the nested pattern. Among species with abundances correlated with the nested rank-order of sites, abundance properties were significantly related to different variables. This suggests that individual taxa respond to divergent ecological mechanisms, leading to nestedness. Thus, nestedness in plant communities can result from a complex set of contributors and may not be attributable to a single factor.

The genetics of phenotypic plasticity. XVI. Interactions among traits and the flow of information.

Although the environment varies, adaptive trait plasticity is uncommon, which can be due to either costs or limitations. Currently there is little evidence for costs of plasticity; limitations are a more promising explanation, including information reliability. A possible cause for a decrease in information reliability is the channeling of environmental information through one trait that then affects the phenotype of a second trait, the information path. Using an individual-based simulation model, I explored the ways in which configurations of trait interactions and patterns of environmental variation in space and time affect the evolution of phenotypic plasticity. I found that genotypes and phenotypes evolved to shorten and simplify the information path from the environment to fitness. A shortened path was characterized by a decrease in the amount of plasticity for traits that had a less direct connection between the environment of development and fitness. A simplified path was characterized by a decrease in the amount of plasticity for traits that had multiple paths between the environment and their phenotype. These results suggest that an eighth proposition be added to the theory of the evolution of phenotypic plasticity: Trait plasticity will evolve to minimize the information path between the environment and fitness.

Plastic trait integration across a CO2 gradient in Arabidopsis thaliana.

Shifts across environments in patterns of trait integration may govern or alter adaptive responses. Changes in resource supply rates may be an especially important cause of plasticity of trait integration because they can lead to shifts in colimitation and coregulation of traits. Traditional evolutionary genetic characterization of trait integration relies on covariance analyses. Structural equation modeling (SEM) can complement such analyses. The SEM provides insights into causal structure not possible with a covariance analysis, thereby providing mechanistic understanding of shifts in integration and suggesting likely foci of selection in changing environments. We tested for changes in trait integration by growing 35 genotypes of Arabidopsis thaliana (Brassicaceae; mouse-eared cress) from throughout the species' range in four atmospheric CO2 concentrations: 250 (past), 355 (approximately recent CO2), 530, and 710 (future) microM M(-1). SEM revealed significant shifts in the integration of N, C, and H2O use and their effects on reproductive dry mass across the CO2 gradient. The low CO2 stress of 250 microM M(-1) had the most divergent integration structures. Standardized total effects of C assimilation, water loss, and early N mass changed in sign across the C supply gradient, and the total effect of quantum yield decreased from significant to nonsignificant values across the gradient. Transpiration exhibited significant genetic variation and is thus a candidate target for selection and adaptation under novel growth CO2 concentrations. The strength of the correlation between C assimilation and transpiration declined by 19% from 250 to 710 microM M(-1), indicating a partial decoupling of their current mutual evolutionary constraint in the atmosphere of the future. Structural equation analysis of functional integration provides unique insights into the mechanisms through which changes in limiting resources can alter the nature of trait integration.

Phylogenetic Insight into Zika and Emerging Viruses for a Perspective on Potential Hosts.

Global viral diversity is substantial, but viruses that contribute little to the public health burden or to agricultural damage receive minimal attention until a seemingly unimportant virus becomes a threat. The Zika virus (ZIKV) illustrated this, as there was limited information and awareness of the virus when it was identified as a public health emergency in February 2016. Predicting which virus may pose a future threat is difficult. This is in part because significant knowledge gaps in the basic biology and ecology of an emerging virus can impede policy development, delay decision making, and hinder public health action. We suggest using a phylogenetic framework of pathogens and their infected host species for insight into which animals may serve as reservoirs. For example, examining flaviviruses closely related to ZIKV, the phylogenetic framework indicates New World monkeys are the most likely candidates to be potential reservoirs for ZIKV. Secondarily, mammals that are in close proximity to humans should be considered because of the increased opportunity for pathogen exchange. The increase in human-mediated environmental change is accelerating the probability of another previously overlooked virus becoming a significant concern. By investing in basic science research and organizing our knowledge into an evolutionary framework, we will be better prepared to respond to the next emerging infectious disease.

Correction to: Phylogenetic Insight into Zika and Emerging Viruses for a Perspective on Potential Hosts.

The article Phylogenetic Insight into Zika and Emerging Viruses for a Perspective on Potential Hosts, written by Diana S. Weber, Karen A. Alroy, and Samuel M. Scheiner, was originally published Online First without open access.

The genetics of phenotypic plasticity. XV. Genetic assimilation, the Baldwin effect, and evolutionary rescue.

We used an individual-based simulation model to examine the role of phenotypic plasticity on persistence and adaptation to two patterns of environmental variation, a single, abrupt step change and continual, linear change. Our model tested the assumptions and predictions of the theory of genetic assimilation, explored the evolutionary dynamics of the Baldwin effect, and provided expectations for the evolutionary response to climate change. We found that genetic assimilation as originally postulated is not likely to occur because the replacement of plasticity by fixed genetic effects takes much longer than the environment is likely to remain stable. On the other hand, trait plasticity as an enhancement to continual evolutionary change may be an important evolutionary mechanism as long as plasticity has little or no costs. Whether or not plasticity helps or hinders evolutionary rescue following a step change in the environment depends on whether plasticity is costly. For linear environmental change, noncostly plasticity always decreases extinction rates, while costly plasticity can create a fitness drag and increase the chance of extinction. Thus, with changing climates plasticity can enhance adaptation and prevent extinction under some conditions, but not others.

The components of biodiversity, with a particular focus on phylogenetic information.

We present a framework for biodiversity metrics that organizes the growing panoply of metrics. Our framework distinguishes metrics based on the type of information-abundance, phylogeny, function-and two common properties-magnitude and variability. Our new metrics of phylogenetic diversity are based on a partition of the total branch lengths of a cladogram into the proportional share of each species, including: a measure of divergence which standardizes the amount of evolutionary divergence by species richness and time depth of the cladogram; a measure of regularity which is maximal when the tree is perfectly symmetrical so that all species have the same proportional branch lengths; a measure that combines information on the magnitude and variability of abundance with phylogenetic variability, and a measure of phylogenetically weighted effective mean abundance; and indicate how those metrics can be decomposed into α and ß components. We illustrate the utility of these new metrics using empirical data on the bat fauna of Manu, Peru. Divergence was greatest in lowland rainforest and at the transition between cloud and elfin forests, and least in upper elfin forests and in cloud forests. In contrast, regularity was greatest in lowland rainforest, dipping to its smallest values in mid-elevation cloud forests, and then increasing in high elevation elfin forests. These patterns indicate that the first species to drop out with increasing elevation are ones that are closely related to other species in the metacommunity. Measures of the effective number of phylogenetically independent or distinct species decreased very rapidly with elevation, and ß-diversity was larger. In contrast, a comparison of feeding guilds shows a different effect of phylogenetic patterning. Along the elevational gradient, each guild generally loses some species from each clade-rather than entire clades-explaining the maintenance of functional diversity as phylogenetic diversity decreases.

Developing unified theories in ecology as exemplified with diversity gradients.

A scientific field matures as its theoretical underpinnings consolidate around unified theories: conceptual structures consisting of a few general propositions that encompass a wide domain of phenomena and from which can be derived an array of models. We demonstrate this process with a synthetic theory of ecological gradients and species richness. Our unified theory rests on four propositions. First, variation in some environmental factor effects variation in the number of individuals creating a gradient. Second, in a uniform environment of fixed area, more individuals lead to more species. Third, the variance of an environmental factor increases with its mean for sites of equal area. Fourth, all nonmonotonic relationships (i.e., hump shaped or U shaped) require a trade-off in organismal performance or in population characteristics with respect to the environmental gradient. We identify 17 models that link environmental gradients with diversity, show their relationship to our framework, and describe issues surrounding their empirical testing. We illustrate how a general theory can be used to build new models such as that for the U-shaped productivity-diversity relationship. Finally, we discuss how our theory could be unified further with other theories of diversity and indicate other areas of ecology that are ripe for unification. By providing an example of the process of theory unification, we hope to encourage such efforts throughout ecology.

Reducing environmental bias when measuring natural selection.

Crucial to understanding the process of natural selection is characterizing phenotypic selection. Measures of phenotypic selection can be biased by environmental variation among individuals that causes a spurious correlation between a trait and fitness. One solution is analyzing genotypic data, rather than phenotypic data. Genotypic data, however, are difficult to gather, can be gathered from few species, and typically have low statistical power. Environmental correlations may act through traits other than through fitness itself. A path analytic framework, which includes measures of such traits, may reduce environmental bias in estimates of selection coefficients. We tested the efficacy of path analysis to reduce bias by re-analyzing three experiments where both phenotypic and genotypic data were available. All three consisted of plant species (Impatiens capensis, Arabidopsis thaliana, and Raphanus sativus) grown in experimental plots or the greenhouse. We found that selection coefficients estimated by path analysis using phenotypic data were highly correlated with those based on genotypic data with little systematic bias in estimating the strength of selection. Although not a panacea, using path analysis can substantially reduce environmental biases in estimates of selection coefficients. Such confidence in phenotypic selection estimates is critical for progress in the study of natural selection.