Zhang-Zheng H., Deng X., Aguirre-Gutiérrez J., Stocker B.D., Thomson E., Ding R., Adu-Bredu S., Duah-Gyamfi A., Gvozdevaite A., Moore S., Oliveras Menor Imma, Prentice I. C., Malhi Y. (2024). Why models underestimate West African tropical forest primary productivity. Nature Communications, 15 (1), 9574 [12 p.]. ISSN 2041-1723.
Titre du document
Why models underestimate West African tropical forest primary productivity
Année de publication
2024
Auteurs
Zhang-Zheng H., Deng X., Aguirre-Gutiérrez J., Stocker B.D., Thomson E., Ding R., Adu-Bredu S., Duah-Gyamfi A., Gvozdevaite A., Moore S., Oliveras Menor Imma, Prentice I. C., Malhi Y.
Source
Nature Communications, 2024,
15 (1), 9574 [12 p.] ISSN 2041-1723
Tropical forests dominate terrestrial photosynthesis, yet there are major contradictions in our understanding due to a lack of field studies, especially outside the tropical Americas. A recent field study indicated that West African forests have among the highest forests gross primary productivity (GPP) yet observed, contradicting models that rank them lower than Amazonian forests. Here, we show possible reasons for this data-model mismatch. We found that biometric GPP measurements are on average 56.3% higher than multiple global GPP products at the study sites. The underestimation of GPP largely disappears when a standard photosynthesis model is informed by local field-measured values of (a) fractional absorbed photosynthetic radiation (fAPAR), and (b) photosynthetic traits. Remote sensing products systematically underestimate fAPAR (33.9% on average at study sites) due to cloud contamination issues. The study highlights the potential widespread underestimation of tropical forests GPP and carbon cycling and hints at the ways forward for model and input data improvement.
Plan de classement
Environnement, écologie générale [021ENVECO]
;
Météorologie / Climatologie [126TELAPP06]
;
Végétation / Forêt [126TELAPP08]
Localisation
Fonds IRD [F B010092541]
Identifiant IRD
fdi:010092541
