Abstract
Ecological Niche Modeling is a process by which spatiotemporal, climatic, and environmental data are analyzed to predict the distribution of an organism. Using this process, an ensemble ecological niche model for West Nile virus habitat prediction in the state of Florida was developed. This model was created through the weighted averaging of three separate machine learning models—boosted regression tree, random forest, and maximum entropy—developed for this study using sentinel chicken surveillance and remote sensing data. Variable importance differed among the models. The highest variable permutation value included mean dewpoint temperature for the boosted regression tree model, mean temperature for the random forest model, and wetlands focal statistics for the maximum entropy mode. Model validation resulted in area under the receiver curve predictive values ranging from good [0.8728 (95% CI 0.8422–0.8986)] for the maximum entropy model to excellent [0.9996 (95% CI 0.9988–1.0000)] for random forest model, with the ensemble model predictive value also in the excellent range [0.9939 (95% CI 0.9800–0.9979]. This model should allow mosquito control districts to optimize West Nile virus surveillance, improving detection and allowing for a faster, targeted response to reduce West Nile virus transmission potential.
Highlights
Ecological Niche Modeling (ENM), known as Environmental Niche Modeling, Species Distribution Modeling, or Habitat Suitability Modeling involves the use of computer algorithms to analyze features of a set of geographic locations that together represent a known niche of an organism of interest, with the goal of predicting its distribution across a defined geographic region
Pre-study modeling utilizing the complete presence dataset and all available land cover and environmental variables resulted in all models prioritizing land cover variables associated directly with human populations to the exclusion of others. This resulted in extreme overfitting with models selecting developed areas almost exclusively as high probability habitats for West Nile Virus (WNV)
Probability was characterized across the geographic range of the study as a continuous variable from 0 to 1
Summary
Ecological Niche Modeling (ENM), known as Environmental Niche Modeling, Species Distribution Modeling, or Habitat Suitability Modeling involves the use of computer algorithms to analyze features of a set of geographic locations that together represent a known niche of an organism of interest, with the goal of predicting its distribution across a defined geographic region. These algorithms make use of presence, presence and absence, or presence and pseudoabsence (PA) data of the organism of interest, along with spatial and temporal climatic and environmental data in the known niche to develop a model that describes a niche favorable for supporting the organism in question. This model is compared to other geospatial regions or even future climate models to predict their suitability as a potential habitat for the organism.
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