The Visual Evaluation of Soil Structure (VESS) is a straightforward and logistically simple method for characterising and scoring soil structural and physical quality, ideally suited to evaluate and monitor soil degradation in remote and undeveloped areas. The research presented here tested for the first time the feasibility of using VESS in the Amazon basin, under the specialised land uses and soils (Yellow Oxisol and "Terra Preta de Índio") of the region, and its relation with quantitative soil indicators. The evaluated areas, which had never been subjected to mechanisation, fertilisation nor tillage, were "Terra Preta de Índio"/ Anthropogenic Dark Earth; Regenerating Forest; Slash and Burn; Pasture; and Pristine Forest. The results showed that the quantitative indicators were less sensitive at revealing signs of degradation than VESS and that VESS brought to light evidence of historic land use change and limitations to crop productivity. VESS was significantly correlated with soil resistance to penetration. However, VESS had difficulty capturing possible low water-holding capacity and surface sealing, but the hands on approach to VESS allowed the user to identify these problems, despite not being listed in the reference chart. Overall, VESS was a more integrated soil quality indicator, exposing more aspects of soil functionality than the quantitative indicators, it was also logistically easier to perform making it ideal for tracking soil degradation and structural quality in similarly challenging situations. However, more research is required to fully enable VESS to capture structural quality in 'sandified' soils, caused by the slash and burn method widely used in the Amazon region.
- Soil quality
- Soil structure
- Visual soil evaluation
Guimaraes, RML., Neves Jr, AF., Silva, WG., Rogers, CD., Ball, BC., Montes, CR., & Pereira, BF. (2016). The merits of the Visual Evaluation of Soil Structure method (VESS) for assessing soil physical quality in the remote, undeveloped regions of the Amazon basin. Soil and Tillage Research, 173, 75 - 82. https://doi.org/10.1016/j.still.2016.10.014