Optimal management of cattle grazing in a seasonally dry tropical forest ecosystem under rainfall fluctuations

 

Programa: 
meteorologia
Primeiro Autor: 
Rodolfo Souza
Ano de Publicação: 
2020
Nome da Revista/Jornal: 
Journal of Hydrology
Tipo de publicação: 
Artigo publicado em Revista
localidade: 
Publicação Internacional
TítuloOptimal management of cattle grazing in a seasonally dry tropical forest ecosystem under rainfall fluctuations
Tipo da publicaçãoJournal Article
Ano de Publicação2020
AutoresSouza R, Hartzell S, Feng X, Dantas Antonino AC, de Souza ES, Cezar Menezes RS, Porporato A
JournalJournal of Hydrology
Volume588
Issue1
Paginação125102 a 125112
Data de Publicação09/2020
ISSN0022-1694
Resumo

Climate change will likely trigger shifts in rainfall regimes that may intensify water scarcity in semi-arid regions. In the semi-arid region of Brazil, the seasonally dry ecosystem is the primary source of forage for livestock. Because the correct stocking rate of livestock (animals per area) is not well understood, overgrazing tends to advance rangeland degradation in this ecosystem. This implies that the region may become even more vulnerable under changing rainfall regimes, which in turn may exacerbate livestock and food insecurity. We developed a coupled soil water balance, vegetation, and cattle biomass model to illustrate the impacts of rainfall seasonality on the dynamics of vegetation and animal growth. The outcomes were simulated by considering different stocking rates and the timing of animal placement and removal from the rangeland. A more pronounced reduction in vegetation biomass was found in grazed vs. non-grazed paddocks. Under strongly seasonal rainfall patterns, the maximum animal weight gain decreases with average rainfall inter-arrival time and increases with total annual rainfall. Thus, a forecast of dry spells could benefit farmers in planning grazing management strategies. Our model can be used to test different management scenarios and give feedback for local herders, and to guide future experiments to reduce the time and cost of acquiring data

URLhttps://www.sciencedirect.com/science/article/abs/pii/S002216942030562X?via%3Dihub
DOI10.1016/j.jhydrol.2020.125102
Short TitleJournal of Hydrology