Mapping tropical forest functional variation at satellite remote sensing resolutions depends on key traits

Elsa M. Ordway; Gregory P. Asner; David F.R.P. Burslem; Simon L. Lewis; Reuben Nilus; Roberta E. Martin; Michael J. O’Brien; Oliver L. Phillips; Lan Qie; Nicholas R. Vaughn; Paul R. Moorcroft

doi:10.1038/s43247-022-00564-w

Mapping tropical forest functional variation at satellite remote sensing resolutions depends on key traits

Elsa M. Ordway^* (Corresponding Author), Gregory P. Asner, David F.R.P. Burslem, Simon L. Lewis, Reuben Nilus, Roberta E. Martin, Michael J. O’Brien, Oliver L. Phillips, Lan Qie, Nicholas R. Vaughn, Paul R. Moorcroft

^*Corresponding author for this work

Aberdeen Centre For Environmental Sustainability

Research output: Contribution to journal › Article › peer-review

3 Citations (Scopus)

Abstract

Although tropical forests differ substantially in form and function, they are often represented as a single biome in global change models, hindering understanding of how different tropical forests will respond to environmental change. The response of the tropical forest biome to environmental change is strongly influenced by forest type. Forest types differ based on functional traits and forest structure, which are readily derived from high resolution airborne remotely sensed data. Whether the spatial resolution of emerging satellite-derived hyperspectral data is sufficient to identify different tropical forest types is unclear. Here, we resample airborne remotely sensed forest data at spatial resolutions relevant to satellite remote sensing (30 m) across two sites in Malaysian Borneo. Using principal component and cluster analysis, we derive and map seven forest types. We find ecologically relevant variations in forest type that correspond to substantial differences in carbon stock, growth, and mortality rate. We find leaf mass per area and canopy phosphorus are critical traits for distinguishing forest type. Our findings highlight the importance of these parameters for accurately mapping tropical forest types using space borne observations.

Original language	English
Article number	247
Number of pages	11
Journal	Communications Earth and Environment
Volume	3
Early online date	20 Oct 2022
DOIs	https://doi.org/10.1038/s43247-022-00564-w
Publication status	Published - 20 Oct 2022

Bibliographical note

Funding Information:
E.O. was supported by the Harvard University Center for the Environment Postdoctoral Fellowship program (PM, mentor). The airborne science was completed with funding from the United Nations Development Programme and donations to GA from the Avatar Alliance Foundation, Margaret A. Cargill Foundation, David and Lucile Packard Foundation, Gordon and Betty Moore Foundation, Grantham Foundation for the Protection of the Environment, W. M. Keck Foundation, John D. and Catherine T. MacArthur Foundation, Andrew Mellon Foundation, Mary Anne Nyburg Baker and G. Leonard Baker Jr., and William R. Hearst III, and Arizona State University. Plots at Sepilok were funded by the British Ecological Society, with the re-census in 2013 carried out by RN and LQ funded by an ERC Advanced Grant to OLP (291585, T-FORCES). The Danum plot is a core project of the Southeast Asia Rain Forest Research Partnership (SEARRP). We thank SEARRP partners, especially Yayasan Sabah for their support, and HSBC Malaysia and the University of Zurich for funding. We are grateful to the research assistants who are conducting the census, in particular the team leader Alex Karolus, and to Mike Bernados and Bill McDonald for species identifications. We thank Stuart Davies and Shameema Esufali for advice and training. This contribution is an output of ForestPlots.net approved research project no. 46, entitled, Unraveling the role of prior disturbance histories in heterogeneous tropical forest responses to climate change.

Data Availability Statement

The data associated with this paper are published on Zenodo via the Global Airborne Observatory account and can be found via the searchable DOIs cited below. Trait Maps: Global Airborne Observatory foliar trait maps for Sepilok Forest Reserve and the Danum Valley ForestGEO 50-ha plot with a 1 km buffer in Sabah, Malaysia derived from imaging spectroscopy data collected 31 March to 30 April 2016: Foliar N, Foliar P, Leaf Mass per Area (LMA) rasters. https://doi.org/10.5281/zenodo.7051897; https://zenodo.org/record/7051897#.YxZ_m3bMJPZ. LiDAR: Global Airborne Observatory LiDAR data for Sepilok Forest Reserve and the Danum Valley ForestGEO 50 ha plot with a 1 km buffer in Sabah, Malaysia collected 31 March to 30 April 2016: Top-of-canopy height (TCH), P:H, Leaf Area Density (LAD), rasters. https://doi.org/10.5281/zenodo.7051897; https://zenodo.org/record/7051897#.YxZ_m3bMJPZ.

Code availability
Code to organize, resample, and merge data for application of PCA and k-means clustering. Also includes code to estimate Vcmax, and calculate Leaf Area Index (LAI) from Leaf Area Density (LAD), Peak height of LAI (PeakLAI), and Cover20. https://doi.org/10.5281/zenodo.7052347; https://zenodo.org/record/7052347#.YxbQnHbMJPY.

Supplementary information: The online version contains supplementary material
available at https://doi.org/10.1038/s43247-022-00564-w.

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Cite this

Ordway, E. M., Asner, G. P., Burslem, D. F. R. P., Lewis, S. L., Nilus, R., Martin, R. E., O’Brien, M. J., Phillips, O. L., Qie, L., Vaughn, N. R., & Moorcroft, P. R. (2022). Mapping tropical forest functional variation at satellite remote sensing resolutions depends on key traits. Communications Earth and Environment, 3, Article 247. https://doi.org/10.1038/s43247-022-00564-w

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abstract = "Although tropical forests differ substantially in form and function, they are often represented as a single biome in global change models, hindering understanding of how different tropical forests will respond to environmental change. The response of the tropical forest biome to environmental change is strongly influenced by forest type. Forest types differ based on functional traits and forest structure, which are readily derived from high resolution airborne remotely sensed data. Whether the spatial resolution of emerging satellite-derived hyperspectral data is sufficient to identify different tropical forest types is unclear. Here, we resample airborne remotely sensed forest data at spatial resolutions relevant to satellite remote sensing (30 m) across two sites in Malaysian Borneo. Using principal component and cluster analysis, we derive and map seven forest types. We find ecologically relevant variations in forest type that correspond to substantial differences in carbon stock, growth, and mortality rate. We find leaf mass per area and canopy phosphorus are critical traits for distinguishing forest type. Our findings highlight the importance of these parameters for accurately mapping tropical forest types using space borne observations.",

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AU - O’Brien, Michael J.

AU - Phillips, Oliver L.

AU - Qie, Lan

AU - Vaughn, Nicholas R.

AU - Moorcroft, Paul R.

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Mapping tropical forest functional variation at satellite remote sensing resolutions depends on key traits

Abstract

Bibliographical note

Data Availability Statement

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