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Borana rangeland of southern Ethiopia: Estimating biomass production and carrying capacity using field and remote sensing data
Assessing rangeland productivity is critical to reduce ecological degradation and promote sustainable livestock management. Here, we estimated biomass productivity and carrying capacity dynamics in the Borana rangeland of southern Ethiopia by using field-based data and remote sensing data (i.e., nor...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Kunming Institute of Botany, Chinese Academy of Sciences
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9751217/ https://www.ncbi.nlm.nih.gov/pubmed/36540709 http://dx.doi.org/10.1016/j.pld.2022.03.003 |
Sumario: | Assessing rangeland productivity is critical to reduce ecological degradation and promote sustainable livestock management. Here, we estimated biomass productivity and carrying capacity dynamics in the Borana rangeland of southern Ethiopia by using field-based data and remote sensing data (i.e., normalized difference vegetation index (NDVI)). Data was collected from both rainy and dry seasons when biomass production was high and low respectively. Results of linear regression showed that both biomass production (R(2)(adj) = 0.672) and NDVI value (R(2)(adj) = 0.471) were significantly decreased from 1990 to 2019. Field data and NDVI values for mean annual biomass showed a significant linear relationship. The model accuracy in the annual relationship between the observed and predicted biomass values was strong (R(2)(adj) = 0.986) but with high standard error, indicating that the observed biomass production in the rangeland area was not in good condition as compared with the predicted one. This study suggests that, using NDVI data and field-based data in combined way has high potential to estimate rangeland biomass and carrying capacity dynamics at extensively grazed arid and semi-arid rangelands. And to use for estimating stoking rates and predicting future management techniques for decision making. |
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