Inferring plant functional diversity from space : the potential of Sentinel-2
Plant functional diversity (FD) is an important component of biodiversity that characterizes the variability of functional traits within a community, landscape, or even large spatial scales. It can influence ecosystem processes and stability. Hence, it is important to understand how and why FD varies within and between ecosystems, along resources availability gradients and climate gradients, and across vegetation successional stages. Usually, FD is assessed through labor-intensive field measurements, while assessing FD from space may provide a way to monitor global FD changes in a consistent, time and resource efficient way. The potential of operational satellites for inferring FD, however, remains to be demonstrated. Here we studied the relationships between FD and spectral reflectance measurements taken by ESA's Sentinel-2 satellite over 117 field plots located in 6 European countries, with 46 plots having in-situ sampled leaf traits and the other 71 using traits from the TRY database. These field plots represent major European forest types, from boreal forests in Finland to Mediterranean mixed forests in Spain. Based on in-situ data collected in 2013 we computed functional dispersion (FDis), a measure of FD, using foliar and whole-plant traits of known ecological significance. These included five foliar traits: leaf nitrogen concentration (N%), leaf carbon concentration (%C), specific leaf area (SLA), leaf dry matter content (LDMC), leaf area (LA). In addition they included three whole-plant traits: tree height (H), crown cross-sectional area (CCSA), and diameter-at-breast-height (DBH). We applied partial least squares regression using Sentinel-2 surface reflectance measured in 2015 as predictive variables to model in-situ FDis measurements. We predicted, in cross-validation, 55% of the variation in the observed FDis. We also showed that the red-edge, near infrared and shortwave infrared regions of Sentinel-2 are more important than the visible region for predicting FDis. An initial 30-m resolution mapping of FDis revealed large local FDis variation within each forest type. The novelty of this study is the effective integration of spaceborne and in-situ measurements at a continental scale, and hence represents a key step towards achieving rapid global biodiversity monitoring schemes.
Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , |
---|---|
Format: | Article/Letter to editor biblioteca |
Language: | English |
Subjects: | Forest, FunDivEUROPE, Plant traits, Remote sensing, |
Online Access: | https://research.wur.nl/en/publications/inferring-plant-functional-diversity-from-space-the-potential-of- |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
dig-wur-nl-wurpubs-618069 |
---|---|
record_format |
koha |
spelling |
dig-wur-nl-wurpubs-6180692024-03-07 Ma, Xuanlong Mahecha, Miguel D. Migliavacca, Mirco van der Plas, Fons Benavides, Raquel Ratcliffe, Sophia Kattge, Jens Richter, Ronny Musavi, Talie Baeten, Lander Barnoaiea, Ionut Bohn, Friedrich J. Bouriaud, Olivier Bussotti, Filippo Coppi, Andrea Domisch, Timo Huth, Andreas Jaroszewicz, Bogdan Joswig, Julia Pabon-Moreno, Daniel E. Papale, Dario Selvi, Federico Laurin, Gaia Vaglio Valladares, Fernando Reichstein, Markus Wirth, Christian Article/Letter to editor Remote Sensing of Environment 233 (2019) ISSN: 0034-4257 Inferring plant functional diversity from space : the potential of Sentinel-2 2019 Plant functional diversity (FD) is an important component of biodiversity that characterizes the variability of functional traits within a community, landscape, or even large spatial scales. It can influence ecosystem processes and stability. Hence, it is important to understand how and why FD varies within and between ecosystems, along resources availability gradients and climate gradients, and across vegetation successional stages. Usually, FD is assessed through labor-intensive field measurements, while assessing FD from space may provide a way to monitor global FD changes in a consistent, time and resource efficient way. The potential of operational satellites for inferring FD, however, remains to be demonstrated. Here we studied the relationships between FD and spectral reflectance measurements taken by ESA's Sentinel-2 satellite over 117 field plots located in 6 European countries, with 46 plots having in-situ sampled leaf traits and the other 71 using traits from the TRY database. These field plots represent major European forest types, from boreal forests in Finland to Mediterranean mixed forests in Spain. Based on in-situ data collected in 2013 we computed functional dispersion (FDis), a measure of FD, using foliar and whole-plant traits of known ecological significance. These included five foliar traits: leaf nitrogen concentration (N%), leaf carbon concentration (%C), specific leaf area (SLA), leaf dry matter content (LDMC), leaf area (LA). In addition they included three whole-plant traits: tree height (H), crown cross-sectional area (CCSA), and diameter-at-breast-height (DBH). We applied partial least squares regression using Sentinel-2 surface reflectance measured in 2015 as predictive variables to model in-situ FDis measurements. We predicted, in cross-validation, 55% of the variation in the observed FDis. We also showed that the red-edge, near infrared and shortwave infrared regions of Sentinel-2 are more important than the visible region for predicting FDis. An initial 30-m resolution mapping of FDis revealed large local FDis variation within each forest type. The novelty of this study is the effective integration of spaceborne and in-situ measurements at a continental scale, and hence represents a key step towards achieving rapid global biodiversity monitoring schemes. en text/html https://research.wur.nl/en/publications/inferring-plant-functional-diversity-from-space-the-potential-of- 10.1016/j.rse.2019.111368 https://edepot.wur.nl/636951 Forest FunDivEUROPE Plant traits Remote sensing https://creativecommons.org/licenses/by/4.0/ Wageningen University & Research |
institution |
WUR NL |
collection |
DSpace |
country |
Países bajos |
countrycode |
NL |
component |
Bibliográfico |
access |
En linea |
databasecode |
dig-wur-nl |
tag |
biblioteca |
region |
Europa del Oeste |
libraryname |
WUR Library Netherlands |
language |
English |
topic |
Forest FunDivEUROPE Plant traits Remote sensing Forest FunDivEUROPE Plant traits Remote sensing |
spellingShingle |
Forest FunDivEUROPE Plant traits Remote sensing Forest FunDivEUROPE Plant traits Remote sensing Ma, Xuanlong Mahecha, Miguel D. Migliavacca, Mirco van der Plas, Fons Benavides, Raquel Ratcliffe, Sophia Kattge, Jens Richter, Ronny Musavi, Talie Baeten, Lander Barnoaiea, Ionut Bohn, Friedrich J. Bouriaud, Olivier Bussotti, Filippo Coppi, Andrea Domisch, Timo Huth, Andreas Jaroszewicz, Bogdan Joswig, Julia Pabon-Moreno, Daniel E. Papale, Dario Selvi, Federico Laurin, Gaia Vaglio Valladares, Fernando Reichstein, Markus Wirth, Christian Inferring plant functional diversity from space : the potential of Sentinel-2 |
description |
Plant functional diversity (FD) is an important component of biodiversity that characterizes the variability of functional traits within a community, landscape, or even large spatial scales. It can influence ecosystem processes and stability. Hence, it is important to understand how and why FD varies within and between ecosystems, along resources availability gradients and climate gradients, and across vegetation successional stages. Usually, FD is assessed through labor-intensive field measurements, while assessing FD from space may provide a way to monitor global FD changes in a consistent, time and resource efficient way. The potential of operational satellites for inferring FD, however, remains to be demonstrated. Here we studied the relationships between FD and spectral reflectance measurements taken by ESA's Sentinel-2 satellite over 117 field plots located in 6 European countries, with 46 plots having in-situ sampled leaf traits and the other 71 using traits from the TRY database. These field plots represent major European forest types, from boreal forests in Finland to Mediterranean mixed forests in Spain. Based on in-situ data collected in 2013 we computed functional dispersion (FDis), a measure of FD, using foliar and whole-plant traits of known ecological significance. These included five foliar traits: leaf nitrogen concentration (N%), leaf carbon concentration (%C), specific leaf area (SLA), leaf dry matter content (LDMC), leaf area (LA). In addition they included three whole-plant traits: tree height (H), crown cross-sectional area (CCSA), and diameter-at-breast-height (DBH). We applied partial least squares regression using Sentinel-2 surface reflectance measured in 2015 as predictive variables to model in-situ FDis measurements. We predicted, in cross-validation, 55% of the variation in the observed FDis. We also showed that the red-edge, near infrared and shortwave infrared regions of Sentinel-2 are more important than the visible region for predicting FDis. An initial 30-m resolution mapping of FDis revealed large local FDis variation within each forest type. The novelty of this study is the effective integration of spaceborne and in-situ measurements at a continental scale, and hence represents a key step towards achieving rapid global biodiversity monitoring schemes. |
format |
Article/Letter to editor |
topic_facet |
Forest FunDivEUROPE Plant traits Remote sensing |
author |
Ma, Xuanlong Mahecha, Miguel D. Migliavacca, Mirco van der Plas, Fons Benavides, Raquel Ratcliffe, Sophia Kattge, Jens Richter, Ronny Musavi, Talie Baeten, Lander Barnoaiea, Ionut Bohn, Friedrich J. Bouriaud, Olivier Bussotti, Filippo Coppi, Andrea Domisch, Timo Huth, Andreas Jaroszewicz, Bogdan Joswig, Julia Pabon-Moreno, Daniel E. Papale, Dario Selvi, Federico Laurin, Gaia Vaglio Valladares, Fernando Reichstein, Markus Wirth, Christian |
author_facet |
Ma, Xuanlong Mahecha, Miguel D. Migliavacca, Mirco van der Plas, Fons Benavides, Raquel Ratcliffe, Sophia Kattge, Jens Richter, Ronny Musavi, Talie Baeten, Lander Barnoaiea, Ionut Bohn, Friedrich J. Bouriaud, Olivier Bussotti, Filippo Coppi, Andrea Domisch, Timo Huth, Andreas Jaroszewicz, Bogdan Joswig, Julia Pabon-Moreno, Daniel E. Papale, Dario Selvi, Federico Laurin, Gaia Vaglio Valladares, Fernando Reichstein, Markus Wirth, Christian |
author_sort |
Ma, Xuanlong |
title |
Inferring plant functional diversity from space : the potential of Sentinel-2 |
title_short |
Inferring plant functional diversity from space : the potential of Sentinel-2 |
title_full |
Inferring plant functional diversity from space : the potential of Sentinel-2 |
title_fullStr |
Inferring plant functional diversity from space : the potential of Sentinel-2 |
title_full_unstemmed |
Inferring plant functional diversity from space : the potential of Sentinel-2 |
title_sort |
inferring plant functional diversity from space : the potential of sentinel-2 |
url |
https://research.wur.nl/en/publications/inferring-plant-functional-diversity-from-space-the-potential-of- |
work_keys_str_mv |
AT maxuanlong inferringplantfunctionaldiversityfromspacethepotentialofsentinel2 AT mahechamigueld inferringplantfunctionaldiversityfromspacethepotentialofsentinel2 AT migliavaccamirco inferringplantfunctionaldiversityfromspacethepotentialofsentinel2 AT vanderplasfons inferringplantfunctionaldiversityfromspacethepotentialofsentinel2 AT benavidesraquel inferringplantfunctionaldiversityfromspacethepotentialofsentinel2 AT ratcliffesophia inferringplantfunctionaldiversityfromspacethepotentialofsentinel2 AT kattgejens inferringplantfunctionaldiversityfromspacethepotentialofsentinel2 AT richterronny inferringplantfunctionaldiversityfromspacethepotentialofsentinel2 AT musavitalie inferringplantfunctionaldiversityfromspacethepotentialofsentinel2 AT baetenlander inferringplantfunctionaldiversityfromspacethepotentialofsentinel2 AT barnoaieaionut inferringplantfunctionaldiversityfromspacethepotentialofsentinel2 AT bohnfriedrichj inferringplantfunctionaldiversityfromspacethepotentialofsentinel2 AT bouriaudolivier inferringplantfunctionaldiversityfromspacethepotentialofsentinel2 AT bussottifilippo inferringplantfunctionaldiversityfromspacethepotentialofsentinel2 AT coppiandrea inferringplantfunctionaldiversityfromspacethepotentialofsentinel2 AT domischtimo inferringplantfunctionaldiversityfromspacethepotentialofsentinel2 AT huthandreas inferringplantfunctionaldiversityfromspacethepotentialofsentinel2 AT jaroszewiczbogdan inferringplantfunctionaldiversityfromspacethepotentialofsentinel2 AT joswigjulia inferringplantfunctionaldiversityfromspacethepotentialofsentinel2 AT pabonmorenodaniele inferringplantfunctionaldiversityfromspacethepotentialofsentinel2 AT papaledario inferringplantfunctionaldiversityfromspacethepotentialofsentinel2 AT selvifederico inferringplantfunctionaldiversityfromspacethepotentialofsentinel2 AT lauringaiavaglio inferringplantfunctionaldiversityfromspacethepotentialofsentinel2 AT valladaresfernando inferringplantfunctionaldiversityfromspacethepotentialofsentinel2 AT reichsteinmarkus inferringplantfunctionaldiversityfromspacethepotentialofsentinel2 AT wirthchristian inferringplantfunctionaldiversityfromspacethepotentialofsentinel2 |
_version_ |
1813196939842289664 |