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Species‐abundance distributions (SADs) describe the spectrum of commonness and rarity in a community. Beyond the universal observation that most species are rare and only a few common, more‐precise description of SAD shape is controversial. Furthermore, the mechanisms behind SADs and how they vary along environmental gradients remain unresolved. We lack a general, non‐neutral theory of SADs. Here, we develop a trait‐based framework, focusing on a local community coupled to the region by dispersal. The balance of immigration and exclusion determines abundances, which vary over orders‐of‐magnitude. The local trait‐abundance distribution (TAD) reflects a transformation of the regional TAD. The left‐tail of the SAD depends on scaling exponents of the exclusion function and the regional species pool. More‐complex local dynamics can lead to multimodal TADs and SADs. Connecting SADs with trait‐based ecological theory provides a way to generate more‐testable hypotheses on the controls over commonness and rarity in communities.

 

The worldwide proliferation of harmful algal blooms (HABs) both in freshwater and marine ecosystems make understanding and predicting their occurrence urgent. Trait‐based approaches, where the focus is on functional traits, have been successful in explaining community structure and dynamics in diverse ecosystems but have not been applied extensively to HABs. The existing trait compilations suggest that HAB taxa differ from non HAB taxa in key traits that determine their responses to major environmental drivers. Multi‐trait comparisons between HAB‐forming and other phytoplankton taxa, as well as within the HAB groups to characterize interspecific and intraspecific differences will help better define ecological niches of different HAB taxa, develop trait‐based mechanistic models, and better identify environmental conditions that would likely lead to HABs. Building databases of HAB traits and using them in diverse statistical and mechanistic models will increase our ability to predict the HAB occurrence, composition, and severity under changing conditions, including the anthropogenic global change.

 

Recent work has shown that evaluating functional trait distinctiveness, the average trait distance of a species to other species in a community offers promising insights into biodiversity dynamics and ecosystem functioning. However, the ecological mechanisms underlying the emergence and persistence of functionally distinct species are poorly understood. Here, we address the issue by considering a heterogeneous fitness landscape whereby functional dimensions encompass peaks representing trait combinations yielding positive population growth rates in a community. We identify four ecological cases contributing to the emergence and persistence of functionally distinct species. First, environmental heterogeneity or alternative phenotypic designs can drive positive population growth of functionally distinct species. Second, sink populations with negative population growth can deviate from local fitness peaks and be functionally distinct. Third, species found at the margin of the fitness landscape can persist but be functionally distinct. Fourth, biotic interactions (positive or negative) can dynamically alter the fitness landscape. We offer examples of these four cases and guidelines to distinguish between them. In addition to these deterministic processes, we explore how stochastic dispersal limitation can yield functional distinctiveness. Our framework offers a novel perspective on the relationship between fitness landscape heterogeneity and the functional composition of ecological assemblages.

 

Climate warming is altering life cycles of ectotherms by advancing phenology and decreasing generation times. Theoretical models provide powerful tools to investigate these effects of climate warming on consumer–resource population dynamics. Yet, existing theory primarily considers organisms with simplified life histories in constant temperature environments, making it difficult to predict how warming will affect organisms with complex life cycles in seasonal environments. We develop a size-structured consumer–resource model with seasonal temperature dependence, parameterized for a freshwater insect consuming zooplankton. We simulate how climate warming in a seasonal environment could alter a key life-history trait of the consumer, number of generations per year, mediating responses of consumer–resource population sizes and consumer persistence. We find that, with warming, consumer population sizes increase through multiple mechanisms. First, warming decreases generation times by increasing rates of resource ingestion and growth and/or lengthening the growing season. Second, these life-history changes shorten the juvenile stage, increasing the number of emerging adults and population-level reproduction. Unstructured models with similar assumptions found that warming destabilized consumer–resource dynamics. By contrast, our size-structured model predicts stability and consumer persistence. Our study suggests that, in seasonal environments experiencing climate warming, life-history changes that lead to shorter generation times could delay population extinctions.

 

How is trait diversity in a community apportioned between and within coevolving species? Disruptive selection may result in either a few species with large intraspecific trait variation (ITV) or many species with different mean traits but little ITV. Similar questions arise in spatially structured communities: heterogeneous environments could result in either a few species that exhibit local adaptation or many species with different mean traits but little local adaptation. To date, theory has been well-equipped to either include ITV or to dynamically determine the number of coexisting species, but not both. Here, we devise a theoretical framework that combines these facets and apply it to the above questions of how trait variation is apportioned within and between species in unstructured and structured populations, using two simple models of Lotka-Volterra competition. For unstructured communities, we find that as the breadth of the resource spectrum increases, ITV goes from being unimportant to crucial for characterizing the community. For spatially structured communities on two patches, we find no local adaptation, symmetric local adaptation, or asymmetric local adaptation, depending on how much the patches differ. Our framework provides a general approach to incorporate ITV in models of eco-evolutionary community assembly. 

Competition is a pervasive interaction known to structure ecological communities. The Lotka-Volterra (LV) model has been foundational for our understanding of competition, and trait-based LV models have been used to model community assembly and eco-evolutionary phenomena like diversification. The intrinsic growth rate function is determined by the underlying resource distribution and is a key deter- minant of the resulting diversity, traits and abundances of species. In these models, the width of the resource distribution relative to the width of the competition kernel has been identified as a key param- eter that leads to diversification. However, studies have only investigated the impact of width at just a few discrete values, while also often assuming the intrinsic growth rate function to be unimodal. Thus, the impact of the underlying resource distribution’s width and shape together remains incompletely explored, particularly for large, diverse communities. In this study, we vary its width continuously for two shapes (unimodal and bimodal) to explore its impact on community structure. When the resource distribution is very narrow in both the unimodal bimodal cases, competition is strong, leading to exclu- sion of all but the best-adapted species. Wider resource distributions allow stable coexistence, where the traits of the species depend on the shape of the resource distribution. Extremely wide resource distribu- tions support a diverse community, where the strength of competition ultimately determines the diver- sity and traits of coexisting species, but their abundances reflect the underlying resource distribution. Further, competition acts to maximize the use of available resources among the competing species. For large communities, the shape of resource distribution becomes immaterial and the width determines the diversity. These results affirm and extend our understanding of limiting similarity. 

Environments change, for both natural and anthropogenic reasons, which can threaten species persistence. Evolutionary adaptation is a potentially powerful mechanism to allow species to persist in these changing environments. To determine the conditions under which adaptation will prevent extinction (evolutionary rescue), classic quantitative genetics models have assumed a constantly changing environment. They predict that species traits will track a moving environmental optimum with a lag that approaches a constant. If fitness is negative at this lag, the species will go extinct. There have been many elaborations of these models incorporating increased genetic realism. Here, we review and explore the consequences of four ecological complications: non-quadratic fitness functions, interacting density- and trait-dependence, species interactions and fundamental limits to adaptation. We show that non-quadratic fitness functions can result in evolutionary tipping points and existential crises, as can the interaction between density- and trait-dependent mortality. We then review the literature on how interspecific interactions affect adaptation and persistence. Finally, we suggest an alternative theoretical framework that considers bounded environmental change and fundamental limits to adaptation. A research programme that combines theory and experiments and integrates across organizational scales will be needed to predict whether adaptation will prevent species extinction in changing environments. This article is part of the theme issue ‘Integrative research perspectives on marine conservation’.