Recognition of the importance of intraspecific variation in ecological processes has been growing, but empirical studies and models of global change have only begun to address this issue in detail. This review discusses sources and patterns of intraspecific trait variation and their consequences for understanding how ecological processes and patterns will respond to global change. We examine how current ecological models and theories incorporate intraspecific variation, review existing data sources that could help parameterize models that account for intraspecific variation in global change predictions, and discuss new data that may be needed. We provide guidelines on when it is most important to consider intraspecific variation, such as when trait variation is heritable or when nonlinear relationships are involved. We also highlight benefits and limitations of different model types and argue that many common modeling approaches such as matrix population models or global dynamic vegetation models can allow a stronger consideration of intraspecific trait variation if the necessary data are available. We recommend that existing data need to be made more accessible, though in some cases, new experiments are needed to disentangle causes of variation.

High biodiversity of forests is not predicted by traditional models, and evidence for trade‐offs those models require is limited. High‐dimensional regulation (e.g., N factors to regulate N species) has long been recognized as a possible alternative explanation, but it has not be been seriously pursued, because only a few limiting resources are evident for trees, and analysis of multiple interactions is challenging. We develop a hierarchical model that allows us to synthesize data from long‐term, experimental, data sets with processes that control growth, maturation, fecundity, and survival. We allow for uncertainty at all stages and variation among 26 000 individuals and over time, including 268 000 tree years, for dozens of tree species. We estimate population‐level parameters that apply at the species level and the interactions among latent states, i.e., the demographic rates for each individual, every year. The former show that the traditional trade‐offs used to explain diversity are not present. Demographic rates overlap among species, and they do not show trends consistent with maintenance of diversity by simple mechanisms (negative correlations and limiting similarity). However, estimates of latent states at the level of individuals and years demonstrate that species partition environmental variation. Correlations between responses to variation in time are high for individuals of the same species, but not for individuals of different species. We demonstrate that these relationships are pervasive, providing strong evidence that high‐dimensional regulation is critical for biodiversity regulation.

Biologists have recently devoted increasing attention to the role of rapid evolution in species' responses to environmental change. However, it is still unclear what evolutionary responses should be expected, at what rates, and whether evolution will save populations at risk of extinction. The potential of biological invasions to provide useful insights has barely been realised, despite the close analogies to species responding to global change, particularly climate change; in both cases, populations encounter novel climatic and biotic selection pressures, with expected evolutionary responses occurring over similar timescales. However, the analogy is not perfect, and invasive species are perhaps best used as an upper bound on expected change. In this article, we review what invasive species can and cannot teach us about likely evolutionary responses to global change and the constraints on those responses. We also discuss the limitations of invasive species as a model and outline directions for future research.

As ecological data are usually analysed at a scale different from the one at which the process of interest operates, interpretations can be confusing and controversial. For example, hypothesised differences between species do not operate at the species level, but concern individuals responding to environmental variation, including competition with neighbours. Aggregated data from many individuals subject to spatio-temporal variation are used to produce species-level averages, which marginalise away the relevant (process-level) scale. Paradoxically, the higher the dimensionality, the more ways there are to differ, yet the more species appear the same. The aggregate becomes increasingly irrelevant and misleading. Standard analyses can make species look the same, reverse species rankings along niche axes, make the surprising prediction that a species decreases in abundance when a competitor is removed from a model, or simply preclude parameter estimation. Aggregation explains why niche differences hidden at the species level become apparent upon disaggregation to the individual level, why models suggest that individual-level variation has a minor impact on diversity when disaggregation shows it to be important, and why literature-based synthesis can be unfruitful. We show how to identify when aggregation is the problem, where it has caused controversy, and propose three ways to address it.

Contents 1034I.1034II.1035III.1037IV.1038V.1042VI.1043VII.1045References1045 Summary As temperatures warm and precipitation patterns shift as a result of climate change, interest in the identification of tree genotypes that will thrive under more arid conditions has grown. In this review, we discuss the multiple definitions of ‘drought tolerance’ and the biological processes involved in drought responses. We describe the three major approaches taken in the study of genetic variation in drought responses, the advantages and shortcomings of each, and what each of these approaches has revealed about the genetic basis of adaptation to drought in conifers. Finally, we discuss how a greater knowledge of the genetics of drought tolerance may aid forest management, and provide recommendations for how future studies may overcome the limitations of past approaches. In particular, we urge a more direct focus on survival, growth and the traits that directly predict them (rather than on proxies, such as water use efficiency), combining research approaches with complementary strengths and weaknesses, and the inclusion of a wider range of taxa and life stages.