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  • Perspective
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Integrating remote sensing with ecology and evolution to advance biodiversity conservation

Nature Ecology & Evolution volume 6, pages 506–519 (2022)Cite this article

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Abstract

Remote sensing has transformed the monitoring of life on Earth by revealing spatial and temporal dimensions of biological diversity through structural, compositional and functional measurements of ecosystems. Yet, many aspects of Earth’s biodiversity are not directly quantified by reflected or emitted photons. Inclusive integration of remote sensing with field-based ecology and evolution is needed to fully understand and preserve Earth’s biodiversity. In this Perspective, we argue that multiple data types are necessary for almost all draft targets set by the Convention on Biological Diversity. We examine five key topics in biodiversity science that can be advanced by integrating remote sensing with in situ data collection from field sampling, experiments and laboratory studies to benefit conservation. Lowering the barriers for bringing these approaches together will require global-scale collaboration.

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Fig. 1: The integration of remote sensing and in situ observations, experiments and models as tools to understand biodiversity in the Earth system.
Fig. 2: Remote sensing can contribute to uncovering the legacies of evolutionary history and human activity that influence the variation in composition and function of ecosystems across tropical floras (Neotropical, Afrotropical and Indo-Malay/Australasia).
Fig. 3: Field sampling and remote sensing are complementary approaches for capturing functional diversity across the globe.

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Acknowledgements

We are presenters at the World Biodiversity Symposia on Earth Observations and Biodiversity. The World Biodiversity Forum held 23–28 February 2020 in Davos (Switzerland) brought together biodiversity scientists and remote sensing experts to address these questions, through the National Aeronautics and Space Administration (NASA) symposium on Using Earth Observations to Understand Changes in Biodiversity and Ecosystem Function (NASA NNH19ZDA001N-TWSC) and the ESA-supported symposium Remote Sensing for Biodiversity Monitoring. Further support was provided by the NSF RCN project Cross-Scale Processes Impacting Biodiversity (DEB-1745562), NSF BII ASCEND (DBI-2021898), NSF DEB-1702379, NSF DEB-1638720, NASA Biodiversity (0048NNH20ZDA001N, 20-BIODIV20-0048, 20-ECOF20-0008), NASA BioSCape (80NSSC21K0086), NASA-CMS (80NSSC17K0710, 80NSSC21K1059), NASA-IDS (80NSSC17K0348) and the NASA Ecological Forecasting Team Applied Sciences Program (80NSSC19K0205). The research carried out at the Jet Propulsion Laboratory, California Institute of Technology, was under a contract with NASA (80NM0018D0004). Government sponsorship is acknowledged. The research conducted at the University of Zurich was supported by the University Research Priority Program in Global Change and Biodiversity. The GOSIF GPP product was obtained from http://globalecology.unh.edu. The artwork in Fig. 1 was drawn by D. Tschanz.

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Authors and Affiliations

  1. Department of Ecology, Evolution and Behavior, University of Minnesota, St Paul, MN, USA

    Jeannine Cavender-Bares

  2. Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA

    Fabian D. Schneider & David Schimel

  3. Department of Geography, University of Zurich, Zurich, Switzerland

    Maria João Santos

  4. Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA

    Amanda Armstrong & Lola Fatoyinbo

  5. Department of Biology, Ph.D. Program in Biology, City University of New York and The Graduate Center of CUNY, New York City, NY, USA

    Ana Carnaval

  6. Department of Geography, Environment, and Spatial Sciences, Michigan State University, East Lansing, MI, USA

    Kyla M. Dahlin

  7. Department of Geographical Sciences, University of Maryland, College Park, MD, USA

    George C. Hurtt

  8. Department of Forest and Wildlife Ecology, Univ. of Wisconsin-Madison, Madison, WI, USA

    Philip A. Townsend

  9. Department of Land, Air and Water Resources and the John Muir Institute of the Environment, University of California, Davis, CA, USA

    Susan L. Ustin

  10. Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou, China

    Zhihui Wang

  11. Department of Geography, University at Buffalo, Buffalo, NY, USA

    Adam M. Wilson

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Contributions

All authors contributed intellectually to the manuscript. J.C.-B., A.C., A.M.W., D.S., F.D.S., G.H., K.M.D., M.J.S. and S.L.U. conceived of and framed the manuscript. J.C.-B., A.C., A.M.W., D.S., F.D.S., K.M.D., M.J.S. and S.L.U. drafted the initial manuscript. J.C.-B., F.D.S., M.J.S., K.M.D., A.A., L.F., A.C., D.S. and A.M.W. revised the manuscript. All authors edited the manuscript. F.D.S., K.M.D., P.A.T. and Z.W. developed the figures with input from J.C.-B., M.J.S., S.L.U. and D.S.; Fig. 1 drawn by D. Tschanz and F.D.S. with J.C.-B. and M.J.S.; Fig. 2 created by F.D.S. with D.S.; and Fig. 3 created by K.M.D., P.A.T. and Z.W.

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Correspondence to Jeannine Cavender-Bares.

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Cavender-Bares, J., Schneider, F.D., Santos, M.J. et al. Integrating remote sensing with ecology and evolution to advance biodiversity conservation. Nat Ecol Evol 6, 506–519 (2022). https://doi.org/10.1038/s41559-022-01702-5

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