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Spatiotemporal variations of albedo in managed agricultural landscapes: inferences to global warming impacts (GWI)

Landscape Ecology volume 35, pages 1385–1402 (2020)Cite this article

Abstract

Context

Albedo can be used to quantify ecosystem and landscape contributions to local and global climate. Such contributions are conventionally expressed as radiative forcing (RF) and global warming impact (GWI). We contextualize our results within landscape carbon production and storage to highlight the importance of changes in albedo for landscape GWI from multiple causes, including net ecosystem production (NEP) and greenhouse gas (GHG) emissions.

Objective

To examine the spatiotemporal changes in albedo (Δα) in contrasting managed landscapes through calculations of albedo-induced RF (RFΔα) and GWI (GWIΔα) under different climatic conditions.

Methods

We selected five contrasting landscapes within the Kalamazoo River watershed in southern Michigan USA as proof of concept. The daily MCD43A3 MODIS (V006) product was used to analyze the inter- and intra-annual variations of growing season albedo. In addition, the variations of RFΔα and GWIΔα were computed based on landscape composition and climate.

Results

The RFΔα (− 5.6 W m−2) and GWIΔα (− 1.3 CO2eq ha−1 year−1) were high in forest-dominated landscapes, indicating cooling effects and CO2eq mitigation impacts similar to crops. The CO2eq mitigation of cropland-dominated landscapes was on average 52% stronger than forest-dominated landscapes. In the landscape with the highest proportion of forest, under dry and wet conditions CO2eq mitigation was reduced by up to 24% and ~ 30%, respectively; in one cropland-dominated landscape wet conditions reduced CO2eq mitigation by 23%.

Conclusions

Findings demonstrate that quantifying spatiotemporal changes in albedo in managed landscapes and under different climatic conditions is essential to understand how landscape modification affects RFΔα and GWIΔα and thereby contributes to ecosystem-level GWI.

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Acknowledgements

This study was supported, in part, by the NASA Carbon Cycle & Ecosystems program (NNX17AE16G), the Great Lakes Bioenergy Research Center funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research under Award Numbers DE-SC0018409 and DE-FC02-07ER64494 and the Natural Science Foundation Long-term Ecological Research Program (DEB 1637653) at the Kellogg Biological Station, the NASA Science of Terra and Aqua program (NNX14AJ32G). We wish to thank Dr. Geoffrey Henebry for helpful suggestions and comments during the post-review process. We also thank the two anonymous reviewers who helped improving the quality of our manuscript.

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Authors and Affiliations

  1. Department of Geography, Environment & Spatial Sciences, Michigan State University, East Lansing, MI, 48823, USA

    Pietro Sciusco, Jiquan Chen, Cheyenne Lei & Gabriela Shirkey

  2. Center for Global Change and Earth Observations, Michigan State University, East Lansing, MI, 48823, USA

    Pietro Sciusco, Jiquan Chen, Michael Abraha, Cheyenne Lei, Raffaele Lafortezza & Gabriela Shirkey

  3. Great Lakes Bioenergy Research Center, Michigan State University, East Lansing, MI, 48824, USA

    Michael Abraha & G. Philip Robertson

  4. W.K. Kellogg Biological Station, Michigan State University, Hickory Corners, MI, 49060, USA

    Michael Abraha & G. Philip Robertson

  5. Department of Agricultural and Environmental Sciences, University of Bari “A. Moro”, 70126, Bari, Italy

    Raffaele Lafortezza

  6. Department of Geography, The University of Hong Kong, Centennial Campus, Pokfulam Road, Hong Kong, China

    Raffaele Lafortezza

  7. Department of Earth System Science, Stanford University, Stanford, CA, 94305, USA

    Zutao Ouyang

  8. Zhejiang Tiantong Forest Ecosystem National Observation and Research Station, School of Ecological and Environmental Sciences, East China Normal University, Shanghai, 200241, China

    Rong Zhang

  9. Center for Global Change and Ecological Forecasting, East China Normal University, Shanghai, 200062, China

    Rong Zhang

  10. Department of Biology, University of South Dakota, Vermillion, SD, 57069, USA

    Ranjeet John

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  1. Pietro Sciusco
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Correspondence to Pietro Sciusco.

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Sciusco, P., Chen, J., Abraha, M. et al. Spatiotemporal variations of albedo in managed agricultural landscapes: inferences to global warming impacts (GWI). Landscape Ecol 35, 1385–1402 (2020). https://doi.org/10.1007/s10980-020-01022-8

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