[Talk] Using SVMs to model ranges of congeneric sloth species
Incorporating biotic information to guide range estimates of three species of *Bradypus*.
By Cecina Babich Morrow in species distribution modeling Bradypus machine learning
March 15, 2019
Date
March 15, 2019
Time
2:30 PM
Location
New York, NY
Event
Species distribution modeling (SDM) techniques are a common tool for estimating species ranges. These models typically rely only only on abiotic variables without accounting for biotic interactions, despite the fact that these interactions may impose important constraints on ranges. Distribution patterns in which closely-related parapatric species replace each other across geographic space are common in ecology. We sought to address whether incorporating biotic information into range estimates for three species of sloth (genus Bradypus) would improve distribution models for species demonstrating this parapatric pattern of distribution. We used support vector machines (SVMs) as masks to delineate the predicted boundaries between these three species’ ranges. We created two different kinds of SVMs: 1) spatial SVMs using only occurrence data, and 2) sp+env SVMs using occurrence data in conjunction with predicted habitat suitability from SDMs. We found that the sp+env SVM resulted in the most ecologically realistic distribution model, accounting for contact zones between species and the effects of climate.
Slides
- Posted on:
- March 15, 2019
- Length:
- 1 minute read, 159 words
- Categories:
- species distribution modeling Bradypus machine learning
- See Also:
- Operationalizing expert knowledge in species’ range estimates using diverse data types
- [Talk] Delineating parapatric ranges using species distribution models and support vector machines: An example with three-toed sloths (Bradypus)
- [Poster] Improving species range estimates for an arboreal species group with a parapatric distribution