4.8 Article

Increasing the spatial and temporal impact of ecological research: A roadmap for integrating a novel terrestrial process into an Earth system model

Journal

GLOBAL CHANGE BIOLOGY
Volume 28, Issue 2, Pages 665-684

Publisher

WILEY
DOI: 10.1111/gcb.15894

Keywords

collaborative bridging; data-model integration; Earth system models; global ecology; history of models; interdisciplinary workflow; modeling across scales

Funding

  1. USDA National Institute of Food and Agriculture [2015-35615-22747, 2015-67003-23485]
  2. National Center for Atmospheric Research (NCAR) - National Science Foundation [1852977]
  3. NSF Graduate Research Fellowship [DGE-1450271]
  4. NSF [DEB-1637686, DEB-2045968]
  5. Texas Tech University
  6. New Hampshire Agricultural Experiment Station

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Terrestrial ecosystems play a crucial role in regulating Earth's climate, yet they have been historically underrepresented in Earth system models. Integrating ecology and Earth system modeling is essential for a comprehensive understanding of ecological systems' impact on global environmental change.
Terrestrial ecosystems regulate Earth's climate through water, energy, and biogeochemical transformations. Despite a key role in regulating the Earth system, terrestrial ecology has historically been underrepresented in the Earth system models (ESMs) that are used to understand and project global environmental change. Ecology and Earth system modeling must be integrated for scientists to fully comprehend the role of ecological systems in driving and responding to global change. Ecological insights can improve ESM realism and reduce process uncertainty, while ESMs offer ecologists an opportunity to broadly test ecological theory and increase the impact of their work by scaling concepts through time and space. Despite this mutualism, meaningfully integrating the two remains a persistent challenge, in part because of logistical obstacles in translating processes into mathematical formulas and identifying ways to integrate new theories and code into large, complex model structures. To help overcome this interdisciplinary challenge, we present a framework consisting of a series of interconnected stages for integrating a new ecological process or insight into an ESM. First, we highlight the multiple ways that ecological observations and modeling iteratively strengthen one another, dispelling the illusion that the ecologist's role ends with initial provision of data. Second, we show that many valuable insights, products, and theoretical developments are produced through sustained interdisciplinary collaborations between empiricists and modelers, regardless of eventual inclusion of a process in an ESM. Finally, we provide concrete actions and resources to facilitate learning and collaboration at every stage of data-model integration. This framework will create synergies that will transform our understanding of ecology within the Earth system, ultimately improving our understanding of global environmental change, and broadening the impact of ecological research.

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