Software

SDMvspecies: virtual species for SDM (R package) [CRAN] [paper]

SDMvspecies creates virtual species for species distribution modelling with ease and simplicity. It is an R package built on the raster package, so it accepts every raster format raster supports and runs on any platform with R (developed and tested on Linux). Free and open source under GPL v2; the package, manual and sample data are on CRAN. Persistent identifier: doi:10.32614/CRAN.package.sdmvspecies.

How to cite: Duan, R.-Y., Kong, X.-Q., Huang, M.-Y., Wu, G.-L. and Wang, Z.-G. (2015), SDMvspecies: a software for creating virtual species for species distribution modelling. Ecography, 38: 108–110. doi:10.1111/ecog.01080

SDMdata: collecting GBIF occurrence records (web tool) [online service] [source] [paper]

High-quality species occurrence data is the first requirement for predicting species distributions. SDMdata is a web-based tool, written in Python, that collects occurrence records from the Global Biodiversity Information Facility (GBIF), checks species names against the GBIF backbone taxonomy and cross-checks the accuracy of coordinates against country borders, then exports clean presence data for SDM software. Open source under the GNU Affero General Public License.

The public service formerly at sdmdata.sdmserialsoftware.org was rebuilt in 2026 and runs at sdmdata.xiaoquankong.ai (same workflow, current GBIF API and GADM 4.1 borders). The 2015 source code remains on GitHub.

SDMengine: SDM modelling for many species at once

SDMengine is an SDM modelling tool designed for large numbers of species and environmental layers, built around the dismo R package with a PostgreSQL-backed job pipeline. It was used internally for the group's studies and was never released as a package.

SDManalysis: post-modelling analysis

Analysis and plotting routines (climate-change scenarios, model comparison) on top of SDMengine output. Work in progress when the project ended; not released.

Publications

The Niche Limitation Method (NicheLim), a new algorithm for generating virtual species to study biogeography
Min-Yi Huang*, Xiaoquan Kong*, Sara Varela, Renyan Duan • Ecological Modelling, 320: 30–40, 2016 • [doi]
SDMdata: A Web-Based Software Tool for Collecting Species Occurrence Records
Xiaoquan Kong, Minyi Huang, Renyan Duan • PLoS ONE, 10(6): e0128295, 2015 • [doi] [software]
SDMvspecies: a software for creating virtual species for species distribution modelling
Ren-Yan Duan*, Xiaoquan Kong*, Min-Yi Huang, Gui-Lin Wu, Zhi-Gao Wang • Ecography, 38: 108–110, 2015 • [doi] [software]
The Predictive Performance and Stability of Six Species Distribution Models
Ren-Yan Duan*, Xiaoquan Kong*, Min-Yi Huang, Wei-Yi Fan, Zhi-Gao Wang • PLoS ONE, 9(11): e112764, 2014 • [doi]

* These authors contributed equally to this work.

People

Xiaoquan Kong — developer

Numerical ecology researcher with professional training in software engineering (Linux, Python, R). Led the design and development of every tool in the family. Now an AI engineer and researcher: www.xiaoquankong.ai.

Renyan Duan — supervisor

PhD in Ecology (Shaanxi Normal University); research associate professor of Ecology at Anqing Normal University and postdoctoral researcher at Nanjing Normal University. Research on species diversity and climate change, funded by the National Natural Science Foundation of China and provincial programmes in Jiangsu and Anhui.

Minyi Huang — supervisor

PhD in Ecology (Nanjing Normal University); associate professor at Anqing Normal University. Interests in biogeography, global change biology and animal conservation.

Sara Varela — collaborator

Co-author of the NicheLim virtual-species algorithm.

Contact

Questions about the software or the papers: Xiaoquan Kong, u1mail2me@gmail.com. Bug reports for SDMdata go to its GitHub issues.