SDMtoolbox: a python‐based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses

By Jason L. Brown. 2014

1,162 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Genetics

View Paper: https://www.semanticscholar.org/paper/fcc1b8378bae7d59334139dde5624b2381a24f81

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecological Modeling

1. Jane Elith
2. Antoine Guisan
3. Wilfried Thuiller
4. A. Townsend Peterson
5. Miguel B. Araújo
6. Janet Franklin
7. N. E. Zimmermann
8. Jorge M. Lobo

In Ecology

1. Jane Elith
2. Antoine Guisan
3. Wilfried Thuiller
4. A. Townsend Peterson
5. Miguel B. Araújo
6. Janet Franklin
7. N. E. Zimmermann
8. Jorge Soberón

In Genetics

1. Jane Elith
2. Wilfried Thuiller
3. A. Townsend Peterson
4. Bharat B. Shrestha
5. Uttam Babu Shrestha
6. Antoine Guisan
7. N. E. Zimmermann
8. S. Dudov

Citations in the corpus

• Species-Distribution Modeling: Advantages and Limitations of Its Application. 2. MaxEnt (2021, methodology): “To eliminate the influence of projection error, previously calculated coefficients can be used (Brown, 2014).”
• A standard protocol for reporting species distribution models (2020, methodology): “…data (Jetz et al. 2012, Franklin et al. 2017, Wüest et al. 2020) and easy-to-use software packages (Phillips et al. 2006, Thuiller et al. 2009, Brown 2014, Naimi and Araújo 2016, Golding et al. 2018, Kass et al. 2018) accompanied by detailed guides, manuals and textbooks (Elith et al. 2008,…”
• Global climate suitability of citrus huanglongbing and its vector, the Asian citrus psyllid, using two correlative species distribution modeling approaches, with emphasis on the USA (2016, methodology): “To avoid model overfitting of spatially clustered presence points and not being able to predict spatially independent data, the presence data were spatially rarified using SDMtoolbox (Brown 2014).”
• Climate change amplifies plant invasion hotspots in Nepal (2019, methodology): “Each dot represents geographic coordinates of the species using sdmtoolbox 2.3 (Brown, 2014).”
• Predicting the Potential Distribution of Paeonia veitchii (Paeoniaceae) in China by Incorporating Climate Change into a Maxent Model (2019, methodology): “The SDM toolbox (e.g., current and future SDMs) was applied to calculate the distributional changes of these two binary SDMs [34], and the primary shifts in the distribution of P. veitchii were analyzed.”
• SDMtoolbox 2.0: the next generation Python-based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses (2017, methodology): “Since SDMtoolbox’s first release (Brown 2014), in April 57 2014, the program has been download over 20,000 times by users in 160 countries (from every sub58 continent) and cited over 147 times.”