@article{fdi:010078974,
  title = {{H}ow far does the tree affect the crop in agroforestry ? {N}ew spatial analysis methods in a {F}aidherbia parkland},
  author = {{R}oupsard, {O}. and {A}udebert, {A}. and {N}dour, {A}. {P}. and {C}lermont {D}auphin, {C}athy and {A}gbohessou, {Y}. and {S}anou, {J}. and {K}oala, {J}. and {F}aye, {E}. and {S}ambakhe, {D}. and {J}ourdan, {C}. and le {M}aire, {G}. and {T}all, {L}. and {S}anogo, {D}. and {S}eghieri, {J}osiane and {C}ournac, {L}aurent and {L}eroux, {L}.},
  editor = {},
  language = {{ENG}},
  abstract = {{T}he trees in agroforestry plots create spatial heterogeneity of high interest for adaptation, mitigation, and the provision of ecosystem services. {B}ut to what distance, exactly, from the tree? {W}e tested a novel approach, based upon geostatistics and {U}nmanned {A}erial {V}ehicle ({UAV}) sensing, to infer the distance at which a single agroforestry tree affects the surrounding under-crop, to map yield, litter (i.e. stover) and compute crop-partial {L}and {E}quivalent {R}atio ({LER}cp) at the whole-plot level. {I}n an agro-silvo-pastoral parkland of semi-arid western {A}frica dominated by the multi-purpose tree {F}aidherbia albida, we harvested the pearl-millet under-crop at the whole-plot scale (ca. 1 ha) and also in subplot transects, at three distances from the trunks. {W}e observed that the yield was three times higher below the tree crown (135.6 g m(-2)) than at a distance of five tree-crown radii from the trunk (47.7 g m(-2)). {T}hrough geostatistical analysis of multi-spectral, centimetric-resolution images obtained from an {UAV} overflight of the entire plot, we determined that the '{R}ange' parameter of the semi-variogram (assumed to be the distance of influence of the trees on the {N}ormalized difference vegetation index ({NDVI})) was 17 m. {W}e correlated the yield (r(2) = 0.41; {RRMSE} = 48 %) and litter production (r(2) = 0.46; {RRMSE} = 35 %) in subplots with {NDVI}, and generated yield and litter maps at the whole-plot scale. {T}he measured whole-plot yield (0.73 t ha(-1)) differed from the one estimated via the {UAV} mapping by only 20 %, thereby validating the overall approach. {T}he litter was estimated similarly at 1.05 t{C} ha(-1) yr(-1) and mapped. {U}sing a geostatistical proxy for the sole crop, {LER}cp was estimated 1.16, despite the low tree density. {T}his new method to handle heterogeneity in agroforestry systems is a first application. {W}e also propose strategies for extension to the landscape level.},
  keywords = {{G}eostatistics ; {U}nmanned {A}erial {V}ehicle ({UAV}) ; {L}and {E}quivalent {R}atio ({LER}) ; {S}pectral indices ; {D}istance of influence ; {SENEGAL} ; {NIAKHAR} ; {ZONE} {SEMIARIDE}. {ZONE} {SOUDANOSAHELIENNE}},
  booktitle = {},
  journal = {{A}griculture {E}cosystems and {E}nvironment},
  volume = {296},
  numero = {},
  pages = {art. 106928 [14 p.]},
  ISSN = {0167-8809},
  year = {2020},
  DOI = {10.1016/j.agee.2020.106928},
  URL = {https://www.documentation.ird.fr/hor/fdi:010078974},
}