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Tackling uncertainties of future projections from species distribution models with package mopa

Revista: The R Journal
Año: 2018   Volumen: 10
Página inicial: 122   Última página: 139
Estado: Publicado
En este estado desde: 3 Ago 2018
Enlace al PDF: https://journal.r-project.org/archive/2018/RJ-2018-019/index.html

In light of current global change, Species Distribution Models (SDMs) constitute an important tool to assist decision-making in environmental conservation and planning. Nevertheless, a wide range of uncertainties around the SDM projections directly affect their potential value and limitations, remaining their quantification as an ongoing challenge. The new package mopa provides tools for SDM generation and for the straightforward design of relatively complex experiments with multiple factors affecting SDM uncertainty (pseudo-absence generation, climate projections, statistical technique...), allowing users to quantify the contribution of different factors to the final SDM spread, for optimal ensemble generation. In addition, mopa is seamlessly integrated with other SDM-oriented packages as well as already standard geospatial data classes in R. It is also part of the climate4R bundle for an easy retrieval and post-processing of climate data, thus providing maximum flexibility and inter-operability with a wide range of SDM-related tools.