4.7 Article

How far does the tree affect the crop in agroforestry? New spatial analysis methods in a Faidherbia parkland

Journal

AGRICULTURE ECOSYSTEMS & ENVIRONMENT
Volume 296, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.agee.2020.106928

Keywords

Geostatistics; Unmanned Aerial Vehicle (UAV); Land Equivalent Ratio (LER); Spectral indices; Distance of influence

Funding

  1. CIRAD, UMR EcoSols
  2. LMI IESOL, ISRA
  3. CERAAS
  4. EU-LEAP-Agri RAMSES II
  5. USAID SIIL-SIMCO
  6. Agropolis
  7. Total Foundation DSCATT
  8. CGIAR GLDC
  9. EU-DESIRA CASSECS
  10. EC2CO ENCAS
  11. Bill and Melinda Gates Foundation through the Terra-SGT Project

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The trees in agroforestry plots create spatial heterogeneity of high interest for adaptation, mitigation, and the provision of ecosystem services. But to what distance, exactly, from the tree? We tested a novel approach, based upon geostatistics and Unmanned Aerial Vehicle (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 Land Equivalent Ratio (LERcp) at the whole-plot level. In an agro-silvo-pastoral parkland of semi-arid western Africa dominated by the multi-purpose tree Faidherbia 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. We 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)). Through geostatistical analysis of multi-spectral, centimetric-resolution images obtained from an UAV overflight of the entire plot, we determined that the 'Range' parameter of the semi-variogram (assumed to be the distance of influence of the trees on the Normalized difference vegetation index (NDVI)) was 17 m. We 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. The 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. The litter was estimated similarly at 1.05 tC ha(-1) yr(-1) and mapped. Using a geostatistical proxy for the sole crop, LERcp was estimated 1.16, despite the low tree density. This new method to handle heterogeneity in agroforestry systems is a first application. We also propose strategies for extension to the landscape level.

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