@article{fdi:010092541,
  title = {{W}hy models underestimate {W}est {A}frican tropical forest primary productivity},
  author = {{Z}hang-{Z}heng, {H}. and {D}eng, {X}. and {A}guirre-{G}uti{\'e}rrez, {J}. and {S}tocker, {B}.{D}. and {T}homson, {E}. and {D}ing, {R}. and {A}du-{B}redu, {S}. and {D}uah-{G}yamfi, {A}. and {G}vozdevaite, {A}. and {M}oore, {S}. and {O}liveras {M}enor, {I}mma and {P}rentice, {I}. {C}. and {M}alhi, {Y}.},
  editor = {},
  language = {{ENG}},
  abstract = {{T}ropical forests dominate terrestrial photosynthesis, yet there are major contradictions in our understanding due to a lack of field studies, especially outside the tropical {A}mericas. {A} recent field study indicated that {W}est {A}frican forests have among the highest forests gross primary productivity ({GPP}) yet observed, contradicting models that rank them lower than {A}mazonian forests. {H}ere, we show possible reasons for this data-model mismatch. {W}e found that biometric {GPP} measurements are on average 56.3% higher than multiple global {GPP} products at the study sites. {T}he underestimation of {GPP} largely disappears when a standard photosynthesis model is informed by local field-measured values of (a) fractional absorbed photosynthetic radiation (f{APAR}), and (b) photosynthetic traits. {R}emote sensing products systematically underestimate f{APAR} (33.9% on average at study sites) due to cloud contamination issues. {T}he 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.},
  keywords = {{ZONE} {TROPICALE} ; {AFRIQUE} {DE} {L}'{OUEST} ; {GHANA}},
  booktitle = {},
  journal = {{N}ature {C}ommunications},
  volume = {15},
  numero = {1},
  pages = {9574 [12 ]},
  ISSN = {2041-1723},
  year = {2024},
  DOI = {10.1038/s41467-024-53949-0},
  URL = {https://www.documentation.ird.fr/hor/fdi:010092541},
}