Published December 19, 2020 | Version v1
Dataset Open

Steep topography buffers threatened gymnosperm species against anthropogenic pressures in China

  • 1. Aarhus University
  • 2. Institute of Botany

Description

China is one of the most species-rich countries in the world, harbouring many rare gymnosperms. Following recent human-led loss of forests, China is now experiencing increases in forest cover resulting from efforts of reforestation-schemes. As anthropogenic activities have previously been found to interact with topography in shaping forest cover in China and considering the large human population and the ongoing population increase of the country, it is important to understand the role of anthropogenic pressures relative to environmental drivers for shaping species distributions here. Based on the well-established relationship between human population density and topography, we propose a hypothesis for explaining species distributions in a country dominated by human activities, predicting that species are more likely to occur in areas of steep topography under medium human population densities compared to low- and high human population densities. Using species occurrence data from the Chinese Vascular Plant Distribution Database along with a common SDM method (Maximum Entropy Modelling) we tested this hypothesis. Our results show that steep topography has the highest importance for predicting Chinese gymnosperm species occurrences in general, and threatened species specifically, in areas of medium human population densities. Consequently, these species are more often found in areas of steep terrain, supporting the proposed hypothesis. Results from this study highlight the need to include topographically heterogeneous habitats when planning new protected areas for species conservation.

Notes

The excell sheet contains presence data for all gymnosperm species in China. Ones in the dataset indicate a species presence. Zeros in the dataset do not indicate true presences. Presences are recorded for all chinese counties, and each of these counties is represented by a county code ('CNTY_CODE'). Each county is likewise associated by the point location of the county centroid in WGS84 latitude and longitude coordinates (columns 'Lon' and 'Lat'). 

Funding provided by: Det Frie Forskningsråd
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100004836
Award Number: 6108-00078B

Funding provided by: Villum Fonden
Crossref Funder Registry ID: http://dx.doi.org/10.13039/100008398
Award Number: 16549

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