Bias is inherent to any kind of data. And so is biodiversity data. There are many biases in the distribution of species records, as well as spatial biases in the location of points, and in the environmental variables used for modelling. So it comes as no surprise that accouting for such bias is one of the key problems that need to be solved when modelling biodiversity trends. In a paper in npj Biodiversity, a large group of experts in different types of biodiversity modelling led by Duccio Rocchini discuss different ways of accouting for several sources of bias to improve the reliability and accuracy of any kind of biodiversity model.
About The Author
I am a biogeographer with broad interests in macroecology, community ecology, island biogeography, insect ecology, evolution, and biodiversity research. My main research aim is to determine why biodiversity – and in particular community structure – is geographically distributed the way it is, and to identify the processes that domain the spatial and temporal dynamics of ecological assemblages. I work as Scientific Researcher at the Department of Biogeography and Global Change of the Natural History Museum in Madrid (MNCN), a research institute of the Spanish Scientific Council (CSIC). I am also External Professor at the Departamento de Ecologia of the Federal University of Goiás (UFG) in Brazil, and Associate Researcher of the Centre for Ecology, Evolution and Environmental Changes (cE3c) of the Faculty of Sciences of the University of Lisbon in Portugal.
I am a biogeographer and community ecologist, working as scientific researcher at the Department of Biogeography and Global Change of the Museo Nacional de Ciencias Naturales (CSIC).
I am also scientific collaborator at the Postgraduate Course on Ecology and Evolution of the Universidade Federal de Goiás and the Centre for Ecology, Evolution and Environmental Changes (cE3c) of the Universidade de Lisboa, and member of eBryo – Research Group on Experimental Bryology.