Process-explicit models reveal the structure and dynamics of biodiversity patterns

Abstract

With ever-growing data availability and computational power at our disposal, we now have the capacity to use process-explicit models more widely to reveal the ecological and evolutionary mechanisms responsible for spatiotemporal patterns of biodiversity. Most research questions focused on the distribution of diversity cannot be answered experimentally, because many important environmental drivers and biological constraints operate at large spatiotemporal scales. However, we can encode proposed mechanisms into models, observe the patterns they produce in virtual environments, and validate these patterns against real-world data or theoretical expectations. This approach can advance understanding of generalizable mechanisms responsible for the distributions of organisms, communities, and ecosystems in space and time, advancing basic and applied science. We review recent developments in process-explicit models and how they have improved knowledge of the distribution and dynamics of life on Earth, enabling biodiversity to be better understood and managed through a deeper recognition of the processes that shape genetic, species, and ecosystem diversity.

Fig. 1.. Modeling the mechanisms that govern the structure and dynamics of biodiversity.

Process-explicit models can simulate changes in species distributions, population abundance, phylogenies, and genomes based on evolutionary and ecological processes (movement, extinction, ecological interaction, adaptation, and speciation) and drivers of environmental change (invasive species, land-use change, human exploitation, climate change, volcanism, and plate tectonics). Processes and drivers are ordered clockwise according to the temporal scale at which they operate. The timeline shows breakthrough developments in process-explicit models of biodiversity up to 2001. Image of finches adapted from Charles Darwin.

Fig. 2.. Moving from empirical observations to process-explicit models.

The relationship between biodiversity and ecosystem functioning can be observed experimentally in mesocosms. Statistical analysis of experimental data can lead to proposed mechanisms of biodiversity functioning, such as niche complementarity (55). This mechanism can be integrated into process-explicit models to simulate interactions between community structure and function. Image credits: photograph (top panel), Matthew Pintar; plant icons (middle panel), Andy Wilson.

Fig. 3.. Processes and levels of biological organization.

Bars show the number of studies using process-explicit models published before 2006 and in the 5-year periods from 2006 to 2016 and from 2016 to 2021, color-coded to indicate the unit of biological organization simulated. Pie charts show the biotic processes (speciation, ecological interaction, adaptation, movement, and extinction) modeled as fractions of the total number of processes modeled across all studies for each time bin.

Fig. 4.. Model structure and assessment.

(A) shows model structure (parameterization) and (B) shows model assessment (verification and validation) for five levels of biological organization (left to right): gene, individual, population, community, and ecosystem. Model structure categories (A) include (top to bottom) multiple biotic processes and dynamic environment (env.), single biotic process and dynamic environment, single biotic process and static environment, either a biotic process or environmental data, and no empirical data. Model assessment categories (B) include (top to bottom): multivariate validation (Multivar. valid.), univariate (Univar.) validation, nonstatistical (Non-stat.) validation, verification (verif.) using theory, and no verification or validation. For additional detail, see the “Relationship to data and theory” section and Supplementary Methods. Size of circles indicates the relative number of studies reviewed (total = 225).

Fig. 5.. Models for predicting continental species richness.

Community-level biogeographical models (46), driven by interactions between climate and biological processes, can incorporate all five biological processes that govern biodiversity: movement, extinction, ecological interaction, adaptation, and speciation. Model outputs can simulate maps of current-day and future species richness and endemism (rarity-weighted species richness). Top plot shows temperature across thousands of years (ka). Image of finches adapted from Charles Darwin.