Farmer perception and utilization of leaf functional traits in managing agroecosystems

Isaac Marney E., Cerda Rolando, Rapidel Bruno, Martin Adam R., Dickinson Adam K., Sibelet Nicole. 2018. Farmer perception and utilization of leaf functional traits in managing agroecosystems. Journal of Applied Ecology, 55 (1) : pp. 69-80.

Journal article ; Article de recherche ; Article de revue à facteur d'impact
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Quartile : Q1, Sujet : ECOLOGY / Quartile : Outlier, Sujet : BIODIVERSITY CONSERVATION

Liste HCERES des revues (en SHS) : oui

Thème(s) HCERES des revues (en SHS) : Economie-gestion

Abstract : Using knowledge of leaf functional traits, such as those forming the leaf economics spectrum (LES), to understand plant responses to environmental change is well-established and now being more widely applied to agroecosystems. Yet, little is known about how farm managers invoke leaf functional traits to inform management decisions. The objectives of this research were to (1) evaluate whether farmers use knowledge of intraspecific trait variation (ITV) in LES traits (or trait proxies) of target crops as response indicators of management conditions; (2) determine whether LES trait values are ranked consistently among multiple farmers along a “Farmer Leaf Economics Spectrum” (FES); (3) evaluate how a FES corresponds to the LES; and (4) identify the farmer and farm attributes that best predict the agreement between the FES and the LES. We collaborated with coffee (Coffea arabica) farmers in the Turrialba Valley, Costa Rica. We used a visual elicitation tool of fresh leaves along an intraspecific spectrum of leaf size, leaf thickness and leaf colour (as a proxy for leaf nutrients); respondents were asked to rank leaves in response to shade and nutrient scenarios as well as yield potential. On-farm biophysical data, management practices and socio-economic attributes were also collected. The majority of farmers demonstrated a developed system of utilizing coffee leaf and whole-plant ITV as indicators of management practices. Farmers managing smaller farms tended to more commonly acknowledge ITV in LES chemical–morphological traits, as compared to those managing large farms. The agreement between a respondent-identified ranking of leaf thickness ITV as a function of light environment and an empirically defined thickness-to-light ranking was partially explained by farmers' physical engagement with plants. Synthesis and applications. In scientific literature, analyses of crop intraspecific trait variation have provided important insights into the mechanistic bases of multiple key agroecological processes. We demonstrate that farmers use crop leaf trait variation as an indicator to both evaluate management prescriptions and to initiate management actions including shade-tree species selection and abundance, crop- and shade-tree pruning regimes and fertilization treatments. These findings signify that functional traits represent a key nexus between scientific and local knowledge. (Résumé d'auteur)

Mots-clés Agrovoc : Agroforesterie, agroécologie, Coffea arabica, Agriculteur, Pratique culturale, Feuille, Adaptation, Morphologie végétale, Agroécosystème, Gestion, Écologie, Arbre d'ombrage, Indicateur biologique

Mots-clés géographiques Agrovoc : Costa Rica

Mots-clés libres : Agroecology, Agroforestry, Coffee, Functional traits, Intraspecific trait variation, Leaf economics, Spectrum, Local ecological knowledge, Shade trees, Trait-based ecology, Visual elicitation tool

Classification Agris : F08 - Cropping patterns and systems
U30 - Research methods
E50 - Rural sociology
F60 - Plant physiology and biochemistry

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

Auteurs et affiliations

  • Isaac Marney E., University of Toronto (CAN) - auteur correspondant
  • Rapidel Bruno, CIRAD-DG-Saurs (FRA) ORCID: 0000-0003-0288-5650
  • Martin Adam R., Université de Toronto (CAN)
  • Dickinson Adam K., Université de Toronto (CAN)
  • Sibelet Nicole, CIRAD-ES-UMR INNOVATION (CRI) ORCID: 0000-0002-2107-6376

Source : Cirad-Agritrop (

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