Leaf area index as an indicator of ecosystem services and management practices: An application for coffee agroforestry

Taugourdeau Simon, Le Maire Guerric, Avelino Jacques, Jones Jeffrey R., Ramirez Luis G., Jara Quesada Manuel, Charbonnier Fabien, Gómez-Delgado Federico, Harmand Jean-Michel, Rapidel Bruno, Vaast Philippe, Roupsard Olivier. 2014. Leaf area index as an indicator of ecosystem services and management practices: An application for coffee agroforestry. Agriculture, Ecosystems and Environment, 192 : pp. 19-37.

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Quartile : Outlier, Sujet : AGRICULTURE, MULTIDISCIPLINARY / Quartile : Q1, Sujet : ENVIRONMENTAL SCIENCES / Quartile : Q1, Sujet : ECOLOGY

Abstract : Scalable indicators are promising to assess ecosystem services. In a large (660 ha) coffee agroforestry farm,we calibrated the relationship between the Normalized Difference Vegetation Index (NDVI), calculatedon a High Resolution (HR) satellite image and ground-truth LAI, providing a 2-layer (shade trees andcoffee) LAI calibration with LAI 2000 and a new technique based on the cumulative distribution of LAIalong transects. The effective and apparent clumping of coffee leaves were computed (0.76 and 0.89,respectively). We also calibrated the relationship between the derived HR-LAI farm map and NDVI fromthe Moderate Resolution Imaging Spectroradiometer (MODIS) in order to re-construct LAI time-series(2001-2011).Coffee LAI, as derived from MODIS after substracting the contribution of shade tree LAI varied seasonallybetween 2.4 and 4.4 m2m?2, with a maximum by the end of wet season (peak of harvest), steep declineduring the drier-cooler season, minimum after annual coffee pruning, recovery during the next rainyseason and pause during the grain filling period. MODIS also detected significant inter-annual variationsin LAI originating from annual pruning, or plot renovation followed by a progressive LAI recovery duringup to 4 years.We related the coffee-LAI time-series with farm registries to examine the impacts of management onLAI and on selected ecosystem services, namely yield and hydrological services. Nitrogen fertilizationwas adjusted annually by the farmer and appeared as the best yield predictor (R2= 0.53). CombiningN-fertilization with LAI from 6 significant months of the year, the prediction was improved (R2= 0.74),confirming LAI as an important co-predictor of yield. We ended up with a yield prediction model includingalso the percentage of pruned resprouts (R2= 0.79), with potential uses for regional yield mapping orreconstruction of historical yield time-series. (Résumé d'auteur)

Mots-clés Agrovoc : Indice de surface foliaire, service, Agroforesterie, Technique de culture, Coffea, Mesure, Rendement des cultures, Télédétection, Modèle

Mots-clés géographiques Agrovoc : Costa Rica

Mots-clés complémentaires : Service environnemental

Classification Agris : P01 - Nature conservation and land resources
F08 - Cropping patterns and systems
K10 - Forestry production
U10 - Computer science, mathematics and statistics
U30 - Research methods

Champ stratégique Cirad : Axe 1 (2014-2018) - Agriculture écologiquement intensive

Auteurs et affiliations

  • Taugourdeau Simon, Université de Lorraine (FRA) ORCID: 0000-0001-6561-3228
  • Le Maire Guerric, CIRAD-PERSYST-UMR Eco&Sols (FRA) ORCID: 0000-0002-5227-958X
  • Avelino Jacques, CIRAD-BIOS-UPR Bioagresseurs (CRI) ORCID: 0000-0003-1983-9431
  • Jones Jeffrey R., CATIE (CRI)
  • Ramirez Luis G., Cafetalera Aquiares (CRI)
  • Jara Quesada Manuel, Cafetalera Aquiares (CRI)
  • Charbonnier Fabien, Université de Lorraine (FRA)
  • Gómez-Delgado Federico, ICE (CRI)
  • Harmand Jean-Michel, CIRAD-PERSYST-UMR Eco&Sols (FRA) ORCID: 0000-0002-8065-106X
  • Rapidel Bruno, CIRAD-PERSYST-UMR SYSTEM (CRI) ORCID: 0000-0003-0288-5650
  • Vaast Philippe, CIRAD-PERSYST-UMR Eco&Sols (KEN)
  • Roupsard Olivier, CIRAD-PERSYST-UMR Eco&Sols (CRI)

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