Comparing Uganda's indigenous soil classification system with World Reference Base and USDA Soil Taxonomy to predict soil productivity

Autor: Charles Kizza Luswata, Robert E. Mazur, Lance H. Goettsch, Stewart Kyebogola, Mwanjalolo J. G. Majaliwa, Moses M. Tenywa, Christopher Smith, Russell Yost, Onesimus Semalulu, C. Lee Burras, Prossy Kyomuhendo, Bradley A. Miller, Andrew W. Lenssen, Carol J. Pierce Colfer
Rok vydání: 2020
Předmět:
Zdroj: Geoderma Regional. 22:e00296
ISSN: 2352-0094
DOI: 10.1016/j.geodrs.2020.e00296
Popis: This study examines three soil classification systems - Buganda, World Reference Base, and US Soil Taxonomy - in order to evaluate their relative strengths and feasibility for making linkages between them. Nine field sites and 16 pedons were considered across the soil landscapes of the Buganda catena. Each identified field pedon diagnostic horizons and characteristics were described and their soils analyzed using standard pedological techniques and measurements. To document the indigenous use of the Buganda classification system, interviews and discussions were held with farmer groups and local extension specialists. Using this local expertise, five local soil units were identified. We also identified two landscape toposequences with pedons that classified into six WRB Reference Soil Groups and five US Soil Taxonomic Suborders. While four local soil classes each mismatched with international systems' groups, Liddugavu (black) soil corresponded to Phaeozem (WRB) and Udolls (US Soil Taxonomy) and is consistently viewed as the most productive soil due to faster weed growth, diversity of crops it supports and its stable landscape location. Statistical comparisons indicated that the Buganda classes were more homogeneous and effective at separating variability of different soil properties than those of either the WRB Reference Soil Groups or US Soil Taxonomy Suborders. Integrating soil texture, pH and bases information in indigenous system methods could locally complement international classifications and linking the best of both systems would be ideal for the generation of a hybrid system. Our findings show that using the toposequence framework assists in comparing these systems in a way that is useful for scientists and local farmers.
Databáze: OpenAIRE
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