Deutsches Zentrum für integrative Biodiversitätsforschung (iDiv)

Research areas

We are developing overarching conceptual and theoretical principles, as well as new analytical tools for understanding the patterns of biodiversity and its heterogeneous distribution across multiple scales, and the underlying ecological drivers that influence those patterns.

Metacommunity Ecology

Representation of a metacommunity (Leibold and Chase, 2017, Metacommunity Ecology. Princeton University Press).

We aim at disentangling the different processes underlying community assembly and metacommunity dynamics. To this end, we are currently moving beyond classical approaches by integrating crucial dimensions such as spatial scale and time, as well as using and/or developing state-of-the-art analytical tools that allow us to infer assembly processes from measured biodiversity patterns.

Measures of Biodiversity

(Chase et al., 2018, bioarXiv)

Our aim is to use biodiversity metrics that, unlike traditional measures of biodiversity (richness and Shannon diversity), are unbiased by sample size and thus allow us to disentangle factors that determine biodiversity at any given place, time and scale. We use metrics derived from the individual rarefaction curve that capture the components of biodiversity we are most interested in, namely:

1. The Species Abundance Distribution (SAD)

2. Number of individuals (density effects)

3. Aggregation (clumping) of conspecific individuals

The metrics we use are: N - Number of individuals, S - Observed species richness, Sn - Rarefied species richness, PIE - Probability of Interspecific Encounter (Hurlbert 1971), SPIE - Effective Number of Species conversion of the PIE (Jost 2007).

Biodiversity Change

We are interested in quantifying biodiversity change across space and through time. In addition to our work quantifying classical macro- and biogeographical patterns, we are also involved in analyses of global databases of time-series (e.g., BioTIME). We make unbiased measures of all components of biodiversity in a scale-sensitive manner to provide robust estimates of how and where biodiversity is changing across the globe.

Macroecology and Biodiversity Patterns

Species richness of trees, mapped globally at two spatial scales (Petr Keil).

We study broad-scale variation of biodiversity on Earth, focusing on multiple taxa such as trees, ants, coral reef fishes, birds, or mammals. We document and explain patterns that include the latitudinal gradient of diversity, species-area relationships, species-energy relationships, or imprints of historical processes in the geographic distribution of biodiversity.

Community Assembly and Ecosystem Functioning (CAFE)

The Community assembly and the functioning of ecosystems (CAFE) concept. The relationship between ecosystem function and species richness is composed of three key interrelated components: (a) The general increasing trend of ecosystem function with increasing number of species. (b) The species composition of each community and each species’ (represented by a letter) contribution to total ecosystem function for that community. (c) The community assembly processes that lead to changes in community composition, structure and species richness along the red arrows in panel a). (Bannar-Martin et al., 2017, Integrating community assembly and biodiversity to better understand ecosystem function: the Community Assembly and the Functioning of Ecosystems (CAFE) approach)

We explicitly investigate the entire set of community assembly processes that might affect the functioning of ecosystems. This includes the classical relationship with biodiversity (Biodiversity-Ecosystem-Function (BEF) relationship), but also uniquely focuses on the identity and composition of species as well as the processes that determine which species compose a community. We build on recent analytical advances and tools, including Structural Equation Modelling (SEM) and prioritization, to investigate how changes in species richness and composition driven by environmental change affect ecosystem function, to help develop the next generation of ecosystem-biodiversity interaction studies.

Synthesis, Meta-Analyses, Data Integration

Relative influence of dataset features (size of the environmental gradient, kingdom, i.e. animal vs. producers, dataset size, number of species, realm, i.e. terrestrial vs. aquatic, and hemeroby level) on the amount of significant Trait-Environment relationships obtained from 4th-Corner analyses (after Leibold & Chase, 2017, Metacommunity Ecology. Princeton University Press).

We develop syntheses on biodiversity, from species distributions to community patterns and biodiversity metrics, across taxonomic, functional and phylogenetic levels. Ultimately, we aim to unify ecological theories and better understand the processes underlying species diversity and coexistence across different trophic levels, ecosystems, realms, and spatial scales. For that purpose, we build large-scale databases and develop conceptual and analytical frameworks to integrate across multiple sources of data and test general ecological hypotheses.

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