Local spatial structure of forest biomass and its consequences for remote sensing of carbon stocks

Rejou-Mechain Maxime, Muller-Landau Hélène C., Detto M., Thomas Sean C., Le Toan Thuy, Saatchi Sassan, Barreto-Silva J.S., Bourg N.A., Bunyavejchewin Sarayudh, Butt Nathalie, Brockelman W.Y., Cao M., Cardenas D., Chiang J.M., Chuyong George B., Clay K., Condit Richard, Dattaraja Handanakere Shivaramai, Davies Stuart J., Duque Alvaro, Esufali S., Ewango Corneille, Fernando R.H.S., Fletcher Christine D., Gunatilleke I.A.U.N., Hao Z., Harms K.E., Hart T.B., Hérault Bruno, Howe Robert, Hubbell Stephen P., Johnson D.J., Kenfack David, Larson A.J., Lin L., Lin Y., Lutz James A., Makana Jean-Rémy, Malhi Yadvinder, Marthews T. R., McEwan R. W., McMahon S.M., McShea William, Muscarella R., Nathalang A., Noor N.S.M., Nytch C.J., Oliveira A.A., Phillips R.P., Pongpattananurak N., Punchi-Manage R., Salim R., Schurman J., Sukumar Raman, Suresh Hebbalalu S., Suwanvecho U., Thomas D.W., Thompson J., Uriarte Maria, Valencia Renato, Vicentini Alberto, Wolf A.T., Yap S., Yuan Zuoqiang, Zartman Charles Eugene, Zimmerman Jess K., Chave Jérôme. 2014. Local spatial structure of forest biomass and its consequences for remote sensing of carbon stocks. Biogeosciences, 11 : 6827-6840.

Matériel d'accompagnement : 1 fichier complémentaire "Online material" (20 p.)

Quartile : Q1, Sujet : GEOSCIENCES, MULTIDISCIPLINARY / Quartile : Q1, Sujet : ECOLOGY

Résumé : Advances in forest carbon mapping have the potential to greatly reduce uncertainties in the global carbon budget and to facilitate effective emissions mitigation strategies such as REDD+. Though broad scale mapping is based primarily on remote sensing data, the accuracy of resulting forest carbon stock estimates depends critically on the quality of field measurements and calibration procedures. The mismatch in spatial scales between field inventory plots and larger pixels of current and planned remote sensing products for forest biomass mapping is of particular concern, as it has the potential to introduce errors, especially if forest biomass shows strong local spatial variation. Here, we used 30 large (8-50 ha) globally distributed permanent forest plots to quantify the spatial variability in aboveground biomass (AGB) at spatial grains ranging from 5 to 250 m (0.025-6.25 ha), and we evaluate the implications of this variability for calibrating remote sensing products using simulated remote sensing footprints. We found that the spatial sampling error in AGB is large for standard plot sizes, averaging 46.3% for 0.1 ha subplots and 16.6% for 1 ha subplots. Topographically heterogeneous sites showed positive spatial autocorrelation in AGB at scales of 100 m and above; at smaller scales, most study sites showed negative or nonexistent spatial autocorrelation in AGB. We further show that when field calibration plots are smaller than the remote sensing pixels, the high local spatial variability in AGB leads to a substantial "dilution" bias in calibration parameters, a bias that cannot be removed with current statistical methods. Overall, our results suggest that topography should be explicitly accounted for in future sampling strategies and that much care must be taken in designing calibration schemes if remote sensing of forest carbon is to achieve its promise.

Mots-clés Agrovoc : forêt, forêt tropicale, biomasse, carbone, évaluation des stocks, télédétection, cartographie, modèle mathématique, modélisation environnementale, méthodologie, échantillonnage, topographie, changement climatique, atténuation des effets du changement climatique, séquestration du carbone

Classification Agris : U30 - Méthodes de recherche
K01 - Foresterie - Considérations générales
P01 - Conservation de la nature et ressources foncières
P40 - Météorologie et climatologie

Champ stratégique Cirad : Axe 6 (2014-2018) - Sociétés, natures et territoires

Auteurs et affiliations

• Rejou-Mechain Maxime, CIRAD-BIOS-UMR AMAP (FRA)
• Muller-Landau Hélène C., Smithsonian Tropical Research Institute (PAN)
• Detto M., Smithsonian Tropical Research Institute (PAN)
• Thomas Sean C., Université de Toronto (CAN)
• Le Toan Thuy, CESBIO (FRA)
• Saatchi Sassan, California Institute of Technology (USA)
• Barreto-Silva J.S., Instituto Amazonico de Investigaciones Cientificas SINCHI (COL)
• Bourg N.A., Smithsonian Conservation Biology Institute (USA)
• Bunyavejchewin Sarayudh, National Parks-Wildlife and plant Conservation Department (THA)
• Butt Nathalie, OUCE (GBR)
• Brockelman W.Y., Ecology Lab (THA)
• Cao M., CAS (CHN)
• Cardenas D., Instituto Amazonico de Investigaciones Cientificas SINCHI (COL)
• Chiang J.M., Tunghai University (TWN)
• Chuyong George B., Université de Buéa (CMR)
• Clay K., Indiana University (USA)
• Condit Richard, Smithsonian Tropical Research Institute (PAN)
• Dattaraja Handanakere Shivaramai, IISC (IND)
• Davies Stuart J., STRI (USA)
• Duque Alvaro, Universidad Nacional de Colombia (COL)
• Esufali S., University of Peradeniya (LKA)
• Ewango Corneille, CEFRECOF (COG)
• Fernando R.H.S., Royal Botanical Garden (LKA)
• Fletcher Christine D., FRIM [Forest Research Institute Malaysia] (MYS)
• Gunatilleke I.A.U.N., University of Peradeniya (LKA)
• Hao Z., CAS (CHN)
• Harms K.E., Louisiana State University (USA)
• Hart T.B., Project TL2 (COG)
• Hérault Bruno, CIRAD-ES-UMR Ecofog (GUF) ORCID: 0000-0002-6950-7286
• Howe Robert, University of Wisconsin (USA)
• Hubbell Stephen P., UC (USA)
• Johnson D.J., Indiana University (USA)
• Kenfack David, Harvard University (USA)
• Larson A.J., University of Montana (USA)
• Lin L., CAS (CHN)
• Lin Y., Tunghai University (TWN)
• Lutz James A., Utah State University (USA)
• Makana Jean-Rémy, Wildlife Conservation Society (COD)
• Malhi Yadvinder, University of Oxford (GBR)
• Marthews T. R., University of Oxford (GBR)
• McEwan R. W., Université de Dayton (USA)
• McMahon S.M., Université de Dayton (USA)
• McShea William, Smithsonian Conservation Biology Institute (USA)
• Muscarella R., Columbia University (USA)
• Nathalang A., Ecology Lab (THA)
• Noor N.S.M., FRIM [Forest Research Institute Malaysia] (MYS)
• Nytch C.J., Universidad de Puerto Rico (PRI)
• Oliveira A.A., USP (BRA)
• Phillips R.P., Indiana University (USA)
• Pongpattananurak N., Kasetsart University (THA)
• Punchi-Manage R., Georg-August University of Göttingen (DEU)
• Salim R., FRIM [Forest Research Institute Malaysia] (MYS)
• Schurman J., Université de Toronto (CAN)
• Sukumar Raman, IISC (IND)
• Suresh Hebbalalu S., IISC (IND)
• Suwanvecho U., Ecology Lab (THA)
• Thomas D.W., Oregon State University (USA)
• Thompson J., Columbia University (USA)
• Uriarte Maria, Columbia University (USA)
• Valencia Renato, Pontificia Universidad Catolica del Ecuador (ECU)
• Vicentini Alberto, INPA (BRA)
• Wolf A.T., University of Wisconsin (USA)
• Yap S., UPLB (PHL)
• Yuan Zuoqiang, CAS (CHN)
• Zartman Charles Eugene, INPA (BRA)
• Zimmerman Jess K., Universidad de Puerto Rico (PRI)
• Chave Jérôme, CNRS (FRA)

Source : Cirad - Agritrop (https://agritrop.cirad.fr/574428/)

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