Speaker
Description
Investigating climate niche properties of plant species is, in face of climate change, of great interest, especially to predict their future distribution or their response to future conditions. The fitting of climate niche requires both reliable climatic variables and distribution data. Most of the studies use distribution data from the well-known open access Global Biodiversity Information Facility (GBIF). However, the data coverage in this database is uneven between countries, with a good coverage in Western Europe and often a lack of data in Central and Eastern European countries. This bias in distribution data may lead to truncated modeled climate niche or inaccurate niche properties.
In this study we aim to quantify the potential impact of this bias on the accuracy of fitted climate niches of a large number a grassland species that all occur in Central Europe but exhibit different distribution patterns. For this, we compare climate niches, fitted for each of these species based on three different datasets, i) raw GBIF data, ii) digitalized expert range maps covering the whole distribution of the species, and iii) GBIF data enriched with data from digitalized national atlases of several Central European countries. We expect for the latter dataset values of niche size and optimum position intermediate between those based on the raw GBIF data and expert range maps. Moreover, we expect the change in niche properties between the raw GBIF dataset and the enriched one to be stronger for rather continental species than for rather oceanic or widely distributed ones.
With this study, we call for a careful use of GBIF data in climate niche modeling. The targeted integration of other data sources helps tackling the geographical bias in data availability and leads to more accurate modeled niche properties.
| Status Group | Doctoral Researcher |
|---|---|
| Poster Presentation Option | No, I prefer to present only as a talk. |
