Community trait overdispersion due to trophic interactions: concerns for assembly process inference

The expected link between competitive exclusion and community trait overdispersion has been used to infer competition in local communities, and trait clustering has been interpreted as habitat filtering. Such community assembly process inference has received criticism for ignoring trophic interactions, as competition and trophic interactions might create similar trait patterns. While other theoretical studies have generally demonstrated the importance of predation for coexistence, ours provides the first quantitative demonstration of such effects on assembly process inference, using a trait-based ecological model to simulate the assembly of a competitive primary consumer community with and without the influence of trophic interactions. We quantified and contrasted trait dispersion/clustering of the competitive communities with the absence and presence of secondary consumers. Trophic interactions most often decreased trait clustering (i.e. increased dispersion) in the competitive communities due to evenly distributed invasions of secondary consumers and subsequent competitor extinctions over trait space. Furthermore, effects of trophic interactions were somewhat dependent on model parameters and clustering metric. These effects create considerable problems for process inference from trait distributions; one potential solution is to use more process-based and inclusive models in inference

Inferring processes of community assembly from macroscopic patterns: the case for inclusive and mechanistic approaches

Statistical techniques exist for inferring community assembly processes from community patterns. Habitat filtering, competition, and biogeographical effects have, for example, been inferred from signals in phenotypic and phylogenetic data. The usefulness of current inference techniques is, however, debated as the causal link between process and pattern is often lacking and processes known to be important are ignored. Here, we revisit current knowledge on community assembly across scales and, in line with several reviews that have outlined the features and challenges associated with current inference techniques, we identify a discrepancy between features of real communities and current inference techniques. We argue, that mechanistic eco-evolutionary models in combination with novel model fitting and model evaluation techniques can provide avenues for more accurate, reliable and inclusive inference. To exemplify, we implement a trait-based and spatially explicit dynamic eco-evolutionary model and discuss steps of model modification, fitting, and evaluation as an iterative approach enabling inference from diverse data sources. This suggested approach can be computationally intensive, and model fitting and parameter estimation can be challenging. We discuss optimization of model implementation, data requirements and availability, and Approximate Bayesian Computation (ABC) as potential solutions to challenges that may arise in our quest for better inference techniques

The interactive effects of environmental gradient and dispersal shape spatial phylogenetic patterns

IntroductionThe emergence and maintenance of biodiversity include interacting environmental conditions, organismal adaptation to such conditions, and dispersal. To understand and quantify such ecological, evolutionary, and spatial processes, observation and interpretation of phylogenetic relatedness across space (e.g., phylogenetic beta diversity) is arguably a way forward as such patterns contain signals from all the processes listed above. However, it remains challenging to extract information about complex eco-evolutionary and spatial processes from phylogenetic patterns.MethodsWe link environmental gradients and organismal dispersal with phylogenetic beta diversity using a trait-based and eco-evolutionary model of diversification along environmental gradients. The combined effect of the environment and dispersal leads to distinct phylogenetic patterns between subsets of species and across geographical distances.Results and discussionSteep environmental gradients combined with low dispersal lead to asymmetric phylogenies, a high phylogenetic beta diversity, and the phylogenetic diversity between communities increases linearly along the environmental gradient. High dispersal combined with a less steep environmental gradient leads to symmetric phylogenies, low phylogenetic beta diversity, and the phylogenetic diversity between communities along the gradient increases in a sigmoidal form. By disentangling the eco-evolutionary mechanisms that link such interacting environment and dispersal effects and community phylogenetic patterns, our results improve understanding of biodiversity in general and help interpretation of observed phylogenetic beta diversity

Models of natural pest control : Towards predictions across agricultural landscapes

Natural control of invertebrate crop pests has the potential to complement or replace conventional insecticide based practices, but its mainstream application is hampered by predictive unreliability across agroecosystems. Inconsistent responses of natural pest control to changes in landscape characteristics have been attributed to ecological complexity and system-specific conditions. Here, we review agroecological models and their potential to provide predictions of natural pest control across agricultural landscapes. Existing models have used a multitude of techniques to represent specific crop-pest-enemy systems at various spatiotemporal scales, but less wealthy regions of the world are underrepresented. A realistic representation of natural pest control across systems appears to be hindered by a practical trade-off between generality and realism. Nonetheless, observations of context-sensitive, trait-mediated responses of natural pest control to land-use gradients indicate the potential of ecological models that explicitly represent the underlying mechanisms. We conclude that modelling natural pest control across agroecosystems should exploit existing mechanistic techniques towards a framework of contextually bound generalizations. Observed similarities in causal relationships can inform the functional grouping of diverse agroecosystems worldwide and the development of the respective models based on general, but context-sensitive, ecological mechanisms. The combined use of qualitative and quantitative techniques should allow the flexible integration of empirical evidence and ecological theory for robust predictions of natural pest control across a wide range of agroecological contexts and levels of knowledge availability. We highlight challenges and promising directions towards developing such a general modelling framework.Peer reviewe

The Latitudinal Diversity Gradient: Novel Understanding through Mechanistic Eco-evolutionary Models

The latitudinal diversity gradient (LDG) is one of the most widely studied patterns in ecology, yet no consensus has been reached about its underlying causes. We argue that the reasons for this are the verbal nature of existing hypotheses, the failure to mechanistically link interacting ecological and evolutionary processes to the LDG, and the fact that empirical patterns are often consistent with multiple explanations. To address this issue, we synthesize current LDG hypotheses, uncovering their eco-evolutionary mechanisms, hidden assumptions, and commonalities. Furthermore, we propose mechanistic eco-evolutionary modeling and an inferential approach that makes use of geographic, phylogenetic, and trait-based patterns to assess the relative importance of different processes for generating the LDG.Additional co-authors: David Storch, Thorsten Wiegand, Allen H Hurlber

The ecological forecast horizon, and examples of its uses and determinants

Forecasts of ecological dynamics in changing environments are increasingly important, and are available for a plethora of variables, such as species abundance and distribution, community structure and ecosystem processes. There is, however, a general absence of knowledge about how far into the future, or other dimensions (space, temperature, phylogenetic distance), useful ecological forecasts can be made, and about how features of ecological systems relate to these distances. The ecological forecast horizon is the dimensional distance for which useful forecasts can be made. Five case studies illustrate the influence of various sources of uncertainty (e.g. parameter uncertainty, environmental variation, demographic stochasticity and evolution), level of ecological organisation (e.g. population or community), and organismal properties (e.g. body size or number of trophic links) on temporal, spatial and phylogenetic forecast horizons. Insights from these case studies demonstrate that the ecological forecast horizon is a flexible and powerful tool for researching and communicating ecological predictability. It also has potential for motivating and guiding agenda setting for ecological forecasting research and development

Phylogenetic Analysis Suggests That Habitat Filtering Is Structuring Marine Bacterial Communities Across the Globe

The phylogenetic structure and community composition were analysed in an existing data set of marine bacterioplankton communities to elucidate the evolutionary and ecological processes dictating the assembly. The communities were sampled from coastal waters at nine locations distributed worldwide and were examined through the use of comprehensive clone libraries of 16S ribosomal RNA genes. The analyses show that the local communities are phylogenetically different from each other and that a majority of them are phylogenetically clustered, i.e. the species (operational taxonomic units) were more related to each other than expected by chance. Accordingly, the local communities were assembled non-randomly from the global pool of available bacterioplankton. Further, the phylogenetic structures of the communities were related to the water temperature at the locations. In agreement with similar studies, including both macroorganisms and bacteria, these results suggest that marine bacterial communities are structured by “habitat filtering”, i.e. through non-random colonization and invasion determined by environmental characteristics. Different bacterial types seem to have different ecological niches that dictate their survival in different habitats. Other eco-evolutionary processes that may contribute to the observed phylogenetic patterns are discussed. The results also imply a mapping between phenotype and phylogenetic relatedness which facilitates the use of community phylogenetic structure analysis to infer ecological and evolutionary assembly processes

Biodiversity increases and decreases ecosystem stability

International audienc

Ecological and evolutionary assembly processes and metacommunity structure

This thesis aims to elucidate the link between abiotic and biotic effects and biogeographical contingencies, eco-evolutionary assembly processes, and community structure in a spatially explicit metacommunity framework. To this end, we used structure analysis of naturally sampled and experimentally manipulated marine bacterial communities and mathematical eco-evolutionary modeling and simulations of metacommunity assembly. We showed that marine bacterial communities are dictated by abiotically driven assembly processes ("habitat filtering") (Paper I) and that the community composition can be highly affected by environmental stress (Papers II and III). Intriguingly, community composition in marine bacterial communities does however not seem to affect community function. In addition, we provided the first "proof" of a direct link between abiotic environmental stress and community phylogenetic clustering (Paper IV). Consequently, we tested and support the "habitat filtering" hypothesis. Further, we concluded that alternative methods need to be developed for a more thorough investigation of the effect of both ecological and evolutionary processes and biogeography. The theoretical studies showed that environmental differences among, e.g., islands, lakes or forest fragments (regional complexity) and the number of available niches within each habitat (habitat complexity) dictate ecological and evolutionary processes such as colonization into novel habitats, invasion between established communities and local evolutionary branching. When habitats are different, species will be adapted to one or few habitats only. Consequently, although dispersal may be facilitated, colonization into novel habitats will be low. When habitat complexity is high, there will initially be many niches available locally. These niches will be filled by local sympatric speciation. Consequently, high habitat complexity leads to fast local branching. Invasion into already established communities will be contingent on both regional and habitat complexity. For the same reasons as for colonization, invasion is facilitated by low regional complexity. However, niches must also be available for species to invade. Consequently, invasion is highest when habitat complexity is high and regional complexity is low. The relative rate between these processes will ultimately result in different types of speciation modes (Paper VI) and community structure (Paper V). This thesis provide a synthetic view of how communities and metacommunities are structured by ecological and evolutionary assembly processes on different spatial scales. It provides a framework for process inference from community structure analysis. Further, this thesis contains methodological approaches that can provide further knowledge about several interesting topics within the scope of metacommunity assembly and structure

Ecological opportunity and upward prey-predator radiation cascades

A general goal in community ecology and evolutionary biology is to understand how diversity has arisen. In our attempts to reach such goals we become increasingly aware of interacting ecological and evolutionary processes shaping biodiversity. Ecological opportunity and adaptive radiations can, for example, drive diversification in competitive communities but little is known about how such processes propagate through trophic levels in adaptive radiation cascades. I use an eco-evolutionary model of trait-based ecological interactions and micro-evolutionary processes to investigate the macro-evolutionary aspects of predator diversification in such cascades. Prey diversification facilitates predator radiation through predator feeding opportunity and disruptive selection. Predator radiation, however, often disconnects from the prey radiation as the diversification progresses. Only when predators have an intermediate niche width, high predatory efficiency, and high evolutionary potential can radiation cascades be maintained over macro-evolutionary time scales. These results provide expectations for predator response to prey divergence and insight into eco-evolutionary feedbacks between trophic levels. Such expectations are crucial for future studies that aim for a better understanding of how diversity is generated and maintained in complex communities