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Tropical forest leaves may darken in response to climate change

Nature Ecology & Evolution volume 2, pages 1918–1924 (2018)Cite this article

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Abstract

Tropical forest leaf albedo (reflectance) greatly impacts how much energy the planet absorbs; however; little is known about how it might be impacted by climate change. Here, we measure leaf traits and leaf albedo at ten 1-ha plots along a 3,200-m elevation gradient in Peru. Leaf mass per area (LMA) decreased with warmer temperatures along the elevation gradient; the distribution of LMA was positively skewed at all sites indicating a shift in LMA towards a warmer climate and future reduced tropical LMA. Reduced LMA was significantly (P < 0.0001) correlated with reduced leaf near-infrared (NIR) albedo; community-weighted mean NIR albedo significantly (P < 0.01) decreased as temperature increased. A potential future 2 °C increase in tropical temperatures could reduce lowland tropical leaf LMA by 6–7 g m−2 (5–6%) and reduce leaf NIR albedo by 0.0015–0.002 units. Reduced NIR albedo means that leaves are darker and absorb more of the Sun’s energy. Climate simulations indicate this increased absorbed energy will warm tropical forests more at high CO2 conditions with proportionately more energy going towards heating and less towards evapotranspiration and cloud formation.

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Fig. 1: Individual leaf albedo versus LMA.
Fig. 2: Basal area-weighted plot averaged albedo.
Fig. 3: Four simulations averaging the last 50 years of a 100-year simulation.
Fig. 4: Climate simulations with reduced tropical leaf NIR albedo.

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Data availability

All the data in this paper can be found in a data repository at the following website: https://ora.ox.ac.uk/objects/uuid:4101e249-3cf5-443f-9c29-9204604c667b.

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Acknowledgements

This work is a product of the GEM network (gem.tropicalforests.ox.ac.uk), ABERG (andesresearch.org), the Amazon Forest Inventory Network (www.rainfor.org) and the Carnegie Spectranomics Project (spectranomics.carnegiescience.edu) research consortia. The field campaign was funded by a grant to Y.M. from the UK Natural Environment Research Council (NERC) (grant no. NE/J023418/1), with additional support from European Research Council advanced investigator grants GEM-TRAITS (no. 321131) and T-FORCES (no. 291585), and a John D. and Catherine T. MacArthur Foundation grant to G.P.A. We thank the Servicio Nacional de Áreas Naturales Protegidas por el Estado and the personnel of the Manu and Tambopata National Parks for logistical assistance and permission to work in the protected areas. We also thank the Explorers’ Inn and the Pontifical Catholic University of Peru, as well as Asociación para la Conservación de la Cuenca Amazónica. We thankE. Cosio (Pontifical Catholic University of Peru) for his assistance with research permissions and sample analysis and storage. Taxonomic work at the Carnegie Institution was helped by R. Tupayachi, F. Sinca and N. Jaramillo. B.B. was supported by a United States National Science Foundation (NSF) graduate research fellowship and doctoral dissertation improvement grant (no. DEB-1209287), as well as an NERC independent research fellowship (grant no. NE/M019160/1). G.P.A. and the Spectranomics team were supported by the endowment of the Carnegie Institution for Science and a grant from the NSF (no. DEB-1146206). S.D. was partially supported by a Visiting Professorship grant from the Leverhulme Trust, UK. Y.M. was also supported by the Jackson Foundation. G.R.G. was supported by funding from the European Community’s Seventh Framework Program (FP7/2007–2013) under grant agreement no. 290605 (COFUND: PSI-FELLOW). C.E.D. received funding from the John Fell Fund, Google and a NASA grant (no. 80NSSC17K0749). Climate simulations were run on Monsoon, Northern Arizona University’s supercomputer.

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Authors and Affiliations

  1. School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ, USA

    Christopher E. Doughty

  2. Universidad Nacional San Antonio Abad del Cusco, Cusco, Peru

    Paul Efren Santos-Andrade & Norma Salinas

  3. Environmental Change Institute, School of Geography and the Environment, University of Oxford, Oxford, UK

    Alexander Shenkin, Benjamin Blonder & Yadvinder Malhi

  4. Schmid College of Science and Technology, Chapman University, Orange, CA, USA

    Gregory R. Goldsmith

  5. Department of Biology, Sonoma State University, Rohnert Park, CA, USA

    Lisa P. Bentley

  6. Instituto Multidisciplinario de Biología Vegetal, CONICET and Universidad Nacional de Córdoba, Córdoba, Argentina

    Sandra Díaz

  7. Seccion Quimica, Pontificia Universidad Catolica del Peru, Lima, Peru

    Norma Salinas

  8. Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, USA

    Brian J. Enquist

  9. Department of Global Ecology, Carnegie Institution for Science, Stanford, CA, USA

    Roberta E. Martin & Gregory P. Asner

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Contributions

C.E.D. wrote the paper with contributions from G.P.A., B.B., G.R.G. and R.E.M. P.E.S.-A. and C.E.D. collected the spectral data. P.E.S.-A., A.S., L.P.B., G.R.G., B.B., N.S., B.J.E., R.E.M., G.P.A., S.D. and Y.M. provided data or support. C.E.D. analysed the data and ran the climate and leaf reflectance simulations.

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Correspondence to Christopher E. Doughty.

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Doughty, C.E., Santos-Andrade, P.E., Shenkin, A. et al. Tropical forest leaves may darken in response to climate change. Nat Ecol Evol 2, 1918–1924 (2018). https://doi.org/10.1038/s41559-018-0716-y

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