Predicting the distribution potential of an invasive frog using remotely sensed data in Hawaii
Article first published online: 26 NOV 2011
© 2011 Blackwell Publishing Ltd
Diversity and Distributions
Volume 18, Issue 7, pages 648–660, July 2012
How to Cite
Bisrat, S. A., White, M. A., Beard, K. H. and Richard Cutler, D. (2012), Predicting the distribution potential of an invasive frog using remotely sensed data in Hawaii. Diversity and Distributions, 18: 648–660. doi: 10.1111/j.1472-4642.2011.00867.x
- Issue published online: 7 JUN 2012
- Article first published online: 26 NOV 2011
- classification trees;
- Eleutherodactylus coqui;
- model comparison;
- random forests;
- species distribution models;
- support vector machines
Aim Eleutherodactylus coqui (commonly known as the coqui) is a frog species native to Puerto Rico and non-native in Hawaii. Despite its ecological and economic impacts, its potential range in Hawaii is unknown, making control and management efforts difficult. Here, we predicted the distribution potential of the coqui on the island of Hawaii.
Location Puerto Rico and Hawaii.
Methods We predicted its potential distribution in Hawaii using five biophysical variables derived from Moderate Resolution Imaging Spectroradiometer (MODIS) as predictors, presence/absence data collected from Puerto Rico and Hawaii and three classification methods – Classification Trees (CT), Random Forests (RF) and Support Vector Machines (SVM).
Results Models developed separately using data from the native range and the invaded range predicted potential coqui habitats in Hawaii with high performance. Across the three classification methods, mean area under the ROC curve (AUC) was 0.75 for models trained using the native range data and 0.88 for models trained using the invaded range data. We achieved the highest AUC value of 0.90 using RF for models trained with invaded range data.
Main conclusions Our results showed that the potential distribution of coquis on the island of Hawaii is much larger than its current distribution, with RF predicting up to 49% of the island as suitable coqui habitat. Predictions also show that most areas with an elevation between 0 and 2000 m are suitable coqui habitats, whereas the cool and dry high elevation areas beyond 2000 m elevation are unsuitable. Results show that MODIS-derived biophysical variables are capable of characterizing coqui habitats in Hawaii.