Earth Systems

Showcasing advances and building community in modeling for sustainability (Intro to SPECIAL FEATURE: Modeling Dynamic Systems for Sustainable Development)

Abstract: We organized this Special Feature on “Modeling Dynamic Systems for Sustainable Development” to showcase the field’s recent advances. Much recent research in sustainability science has mobilized data and theory to better understand systems that include interacting people, technologies, institutions, ecosystems, and both social and environmental processes. A recent National Academies workshop and an Annual Review paper identified several challenges and open questions for the field, stressing the importance of developing and testing new theories to advance knowledge and guide action. However, there has been less attention in sustainability science towards integrating modeling with theory and data-focused approaches. Modeling is necessary for making projections about the dynamical implications of our present understanding of nature-society systems – which is essential to determining whether long term trends in nature-society interactions are consistent with sustainable development goals, and to analyze whether particular interventions (e.g. technologies, policies, behavior) are likely to change those interactions in ways that promote such goals.

The papers in this Special Feature highlight advances in simulating coupled nature-society systems. We believe that these techniques, if they were more widely adopted, could significantly improve the capacity of sustainability science researchers to test
theory, mobilize data, and inform action. Each contribution to the Special Feature addresses a specific area in which novel modeling approaches have demonstrated the capacity to advance theory and insight more broadly. The contributions were selected to be illustrative rather than comprehensive, and to facilitate connections across the communities they represent.

 

SPECIAL FEATURE: Modeling Dynamic Systems for Sustainable Development

Abstract: The Modeling Dynamic Systems for Sustainable Development Special Feature showcases recent advances in modeling that, if more widely adopted, could significantly improve the capacity of sustainability science researchers to test theory, mobilize data, and evaluate interventions. The contributors show how new methods and approaches for analyzing complex interactions in nature–society systems can help to link knowledge with action in society’s efforts to address the core challenges of sustainable development.

Summary: This project aims to build an integrated modeling framework that links highly resolved sectoral models for agriculture and water with the MIT Integrated Global System Model (IGSM), which represents global economic and climate systems. This novel global framework will capture (a) global, inter-regional and inter-sectoral dynamics, (b) highly-resolved local and sectoral dynamics of water and agricultural systems, and (c) multiple channels of climate impacts on the economy.

Food security in Africa under a changing climate – Navigating the energy and agricultural transition to net zero
Phytoplankton thermal trait parameterization alters community structure and biogeochemical processes in a modeled ocean

Abstract: Phytoplankton exhibit diverse physiological responses to temperature which influence their fitness in the environment and consequently alter their community structure. Here, we explored the sensitivity of phytoplankton community structure to thermal response parameterization in a modelled marine phytoplankton community. Using published empirical data, we evaluated the maximum thermal growth rates (μmax) and temperature coefficients (Q10; the rate at which growth scales with temperature) of six key Phytoplankton Functional Types (PFTs): coccolithophores, cyanobacteria, diatoms, diazotrophs, dinoflagellates, and green algae. Following three well-documented methods, PFTs were either assumed to have (1) the same μmax and the same Q10 (as in to Eppley, 1972), (2) a unique μmax but the same Q10 (similar to Kremer et al., 2017), or (3) a unique μmax and a unique Q10 (following Anderson et al., 2021). These trait values were then implemented within the Massachusetts Institute of Technology biogeochemistry and ecosystem model (called Darwin) for each PFT under a control and climate change scenario.

Our results suggest that applying a μmax and Q10 universally across PFTs (as in Eppley, 1972) leads to unrealistic phytoplankton communities, which lack diatoms globally. Additionally, we find that accounting for differences in the Q10 between PFTs can significantly impact each PFT's competitive ability, especially at high latitudes, leading to altered modeled phytoplankton community structures in our control and climate change simulations. This then impacts estimates of biogeochemical processes, with, for example, estimates of export production varying by ~10% in the Southern Ocean depending on the parameterization.

Our results indicate that the diversity of thermal response traits in phytoplankton not only shape community composition in the historical and future, warmer ocean, but that these traits have significant feedbacks on global biogeochemical cycles.

Multiple biotic interactions establish phytoplankton community structure across environmental gradients

Abstract: The combination of taxa and size classes of phytoplankton that coexist at any location affects the structure of the marine food web and the magnitude of carbon fluxes to the deep ocean. But what controls the patterns of this community structure across environmental gradients remains unclear.

Here, we focus on the North East Pacific Transition Zone, a ~ 10° region of latitude straddling warm, nutrient-poor subtropical and cold, nutrient-rich subpolar gyres. Data from three cruises to the region revealed intricate patterns of phytoplankton community structure: poleward increases in the number of cell size classes; increasing biomass of picoeukaryotes and diatoms; decreases in diazotrophs and Prochlorococcus; and both increases and decreases in Synechococcus. These patterns can only be partially explained by existing theories.

Using data, theory, and numerical simulations, we show that the patterns of plankton distributions across the transition zone are the result of gradients in nutrient supply rates, which control a range of complex biotic interactions. We examine how interactions such as size-specific grazing, multiple trophic strategies, shared grazing between several phytoplankton size classes and heterotrophic bacteria, and competition for multiple resources can individually explain aspects of the observed community structure. However, it is the combination of all these interactions together that is needed to explain the bulk compositional patterns in phytoplankton across the North East Pacific Transition Zone. The synthesis of multiple mechanisms is essential for us to begin to understand the shaping of community structure over large environmental gradients.

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