Ecosystem service-support tools are commonly used to guide natural resource management. Often, empirically based models are preferred due to low data requirements, simplicity and clarity. Yet, uncertainty produced by local context or parameter estimation remains poorly quantified and documented. ...
Enlace original:
https://cgspace.cgiar.org/handle/10568/78565
Estrada Carmona, C.
,
Harper, E.B.
,
DeClerck, Fabrice A.J.
,
Fremier, Alexander K.
,
[Quantifying model uncertainty to improve watershed-level ecosystem service quantification: a global sensitivity analysis of the RUSLE]
,
Quantifying model uncertainty to improve watershed-level ecosystem service quantification: a global sensitivity analysis of the RUSLE
