ALBERT

Description: Plankton community modeling is a critical tool for understanding the processes that shape marine ecosystems and their impacts on global biogeochemical cycles. These models can be of variable ecological, physiological, and physical complexity. Many published models are either not publicly available or implemented in static and inflexible code, thus hampering adoption, collaboration, and reproducibility of results. Here we present Phydra, an open-source library for plankton community modeling, and Xarray-simlab-ODE (XSO), a modular framework for efficient, flexible, and reproducible model development based on ordinary differential equations. Both tools are written in Python. Phydra provides pre-built models and model components that can be modified and assembled to develop plankton community models of various levels of ecological complexity. The components can be created, adapted, and modified using standard variable types provided by the XSO framework. XSO is embedded in the Python scientific ecosystem and is integrated with tools for data analysis and visualization. To demonstrate the range of applicability and how Phydra and XSO can be used to develop and execute models, we present three applications: (1) a highly simplified nutrient–phytoplankton (NP) model in a chemostat setting, (2) a nutrient–phytoplankton–zooplankton–detritus (NPZD) model in a zero-dimensional pelagic ocean setting, and (3) a size-structured plankton community model that resolves 50 phytoplankton and 50 zooplankton size classes with functional traits determined by allometric relationships. The applications presented here are available as interactive Jupyter notebooks and can be used by the scientific community to build, modify, and run plankton community models based on differential equations for a diverse range of scientific pursuits.

Description: Drainage divides separate Earth’s surface into individual river basins. Divide migration impacts the evolution of landforms, regional climate, ecosystems and biodiversity. In this Review, we assess the processes and dynamics of divide migration and offer insights into the impact on climate and biodiversity. Drainage divides are not static: they can move through the processes of gradual migration that is continuous in unsteady landscapes, or sudden through infrequent river capture events. Divides tend to move in the direction of slower erosion, faster uplift or with horizontal tectonic advection, with rates typically ranging between 0.001 and 10 mm year−1, and a global average of 0.6 mm year−1. Evidence of river capture, such as a sharp change in flow direction with an upstream waterfall, can constrain divide migration history. Topographic metrics, such as cross-divide steepness, can predict the migration of drainage divides towards directions with a lower topographic steepness. Divide migration influences the spatial distribution of regional precipitation, temperature and topographic connectivity between species, thereby affecting biodiversity. For example, freshwater fish can migrate into a new drainage basin through river capture, potentially increasing the species richness. Future research should couple advanced landscape evolution models and observations from field and remote sensing to better investigate divide migration dynamics.

Description: Biodiversity generally increases productivity in ecosystems; however, this is mediated by the specific functional traits that come with biodiversity loss or gain and how these traits interact with environmental conditions. Most biodiversity studies evaluate the effects of species richness alone, despite our increasing understanding that intraspecific diversity can have equally strong impacts. Here, we manipulate both species richness and intraspecific richness (i.e., number of distinct strains) in marine diatom communities to explicitly test the relative importance of species and strain richness for biomass and trait diversity in six distinct temperature/nutrient environments. We show that species and strain richness both have significant effects on biomass and growth rates, but more importantly, they interact with each other, indicating that cross-species diversity effects depend on within-species diversity and vice versa. This intertwined relationship thus calls for more integrative approaches quantifying the relative importance of distinct biodiversity components and environmental context on ecosystem functioning.