Distance decay 2.0 – A global synthesis of taxonomic and functional turnover in ecological communities

Abstract

Aim Understanding the variation in community composition and species abundances (i.e., β‐diversity) is at the heart of community ecology. A common approach to examine β‐diversity is to evaluate directional variation in community composition by measuring the decay in the similarity among pairs of communities along spatial or environmental distance. We provide the first global synthesis of taxonomic and functional distance decay along spatial and environmental distance by analysing 148 datasets comprising different types of organisms and environments. Location Global. Time period 1990 to present. Major taxa studied From diatoms to mammals. Method We measured the strength of the decay using ranked Mantel tests (Mantel r) and the rate of distance decay as the slope of an exponential fit using generalized linear models. We used null models to test whether functional similarity decays faster or slower than expected given the taxonomic decay along the spatial and environmental distance. We also unveiled the factors driving the rate of decay across the datasets, including latitude, spatial extent, realm and organismal features. Results Taxonomic distance decay was stronger than functional distance decay along both spatial and environmental distance. Functional distance decay was random given the taxonomic distance decay. The rate of taxonomic and functional spatial distance decay was fastest in the datasets from mid‐latitudes. Overall, datasets covering larger spatial extents showed a lower rate of decay along spatial distance but a higher rate of decay along environmental distance. Marine ecosystems had the slowest rate of decay along environmental distances. Main conclusions In general, taxonomic distance decay is a useful tool for biogeographical research because it reflects dispersal‐related factors in addition to species responses to climatic and environmental variables. Moreover, functional distance decay might be a cost‐effective option for investigating community changes in heterogeneous environments.

Global patterns of vascular plant alpha diversity

“…Alternative explanations include rarity and priority effects related to high productivity 29 , more uniform environmental conditions and stronger dispersal limitation at fine scales 28 , or stronger mycorrhiza-mediated effects of interspecific competition and habitat adaptation 52 in the tropics compared to temperate regions. While the relative contribution of these processes remains a matter of speculation, our work points to the need for an improved understanding of the spatial variation of beta diversity in plant diversity analysis 53 . Beta diversity, rather than alpha diversity per se, appears to be the main driver of spatial differences in gamma diversity between temperate and tropical regions.…”

A protocol for reproducible functional diversity analyses

“…The correct reporting of methods and statistics, as well as sharing data and codes, provides the foundation for other scientists to build upon your work. A thorough description of sample sizes, statistics and model estimates ensures that others can incorporate your findings into meta‐analyses (Gerstner et al 2017), shared data can be integrated into larger databases for consensus analyses (Mouillot et al 2021, Graco‐Roza et al 2022), and available code can be reused by other researchers. Whether one sees this altruistically, as a collaborative effort to advance science as a whole, or opportunistically, as a way to increase one' own citations and credibility in the field, the long‐term benefits are undisputed.3) Be informed: find your way through the jungle of metrics.…”

“…Other methods, such as the trait probability density (TPD) framework, do not require initial matrix conformability because the T matrix is preprocessed before being combined with the information in the C matrix (see detailed explanation in Carmona et al 2016). Likewise, in the case of hypervolumes, functional trait spaces can be obtained via the union of individual‐level functional hypervolumes (see details in Mammola and Cardoso 2020, Graco‐Roza et al 2022).…”

“…Note that most approaches to study functional diversity can also integrate intraspecific variation in community‐level calculations, including functional dendrograms (Cianciaruso et al 2009, Cardoso et al 2015), weighted‐abundance sums of trait probability distributions across organisational levels (Carmona et al 2016, 2019) or the union of functional hypervolumes (Mammola and Cardoso 2020, Graco‐Roza et al 2022) (Step 4).…”

Arthropod beta-diversity is spatially and temporally structured by latitude

“…While previous assessments of beta-diversity have largely involved regional assessments 7 , which were then used to fuel meta-analyses 25 , this study represents a true global assessment of temporal-spatial dynamics in the most diverse lineage of terrestrial animals. The consistency in patterns among regions attest to a joint mechanistic pattern for a planetary pattern in biodiversity.…”