Scanning of the scientific literature has revealed a range of methodologies employed by researchers citing use of GBIF-mediated data. Some of the most prominent are given below, and resources supporting these methodologies are shown on the right. We are always interested to hear of novel ways in which the biodiversity data published through GBIF are being used, so please contact us if you think other methodologies should be included.
Species distribution modelling is among the most common techniques employed by researchers citing GBIF-mediated data. Studies of ecology, evolution, conservation and other fields make use of a variety of models that predict the potential distribution of species by combining known occurrence records with digital layers of environmental variables. This method is used to help understand species distributions based on a given number of verified occurrences, as well as modelling the ecological/geographical niche occupied by a species, to estimate the probably of occurrence in the past, present and future.
SDM has been widely used for applications such as predicting the distribution of invasive alien species, protected areas planning and assessing the impacts of climate change on species distributions, and potential species declines.
The elucidation of new taxa and phylogenetic relationships is a major use of GBIF-mediated data. Reference to species data, in particular in museums is core to fundamental study in basic taxonomy. The GBIF portal contains occurrence data for more than one million species, and their use as a taxonomy thesaurus is therefore an important contribution arising from the data publication efforts of the GBIF community. The publication of floras and faunas, and the development of comprehensive checklists, are also examples of this methodology.
The availability of large volumes of information on the geographical and temporal distribution of a given species or phylogenic groups enables the mapping of different taxonomic concepts, in particular over geographical regions. In combination with traits and other information, this method is used to develop a variety of taxonomy clustering, and bio and geo-representations.
The study of phylogenies, or evolutionary trees, is enhanced by the use of primary species occurrence data. For example, data of the kind accessible through GBIF can assist in research inferring the ancestral geographical area for a given family. Typically, family-level analysis into consistent clusters, combined with the observation of their geographical distributions, is used to improve the understanding of the historical development of biological diversity.