Keywords
Biomod2, ensemble model, habitat suitability, nonnative species, species distribution model, virtual species
Abstract
Species distribution models (SDMs) can be important tools for proactive conservation management if they are realistic. Unfortunately, achieving and assessing SDM realism is challenging given the general limitations of scientific models and empirical species data. We addressed the issue of achieving realism with high model quality and reproducibility by reviewing 200 SDMs and cataloguing methods for data availability, response and predictor variables, model fitting, and model performance. We addressed the issue of assessing SDM realism by comparing known and predicted distributions of habitat suitability with simulated data for various model fitting choices. Finally, we applied and compared subsequent lessons to empirical, ensemble SDMs for the exotic ball python (Python regius) and invasive Argentine black and white tegu (Salvator merianae) as case studies for Florida mitigation management practices. Fundamental SDM standards were addressed inconsistently in the literature and lacked transparency and replicability. This decreases SDM quality and increases method confusion. We provided a new checklist with well-supported guidelines to aid in greater method consistency (thus quality and reproducibility) and realism. Model realism varied based on algorithm choice but was consistent across sample sizes and species types. No algorithm was perfectly realistic, but eight consistently produced high rates of realism and performance (and the two were not strongly correlated). Ensemble strategies were consistently more robust than individual algorithms, so we recommended a new ensemble based on those eight high-performing algorithms. We applied this ensemble strategy to our empirical SDMs along with other ensemble groupings (including the most popular individual algorithm) from the literature to inform novel SDMs. Ensemble SDMs consistently performed well with the empirical data and outperformed the individual algorithm. Results here help inform general SDM method guidance for a variety of native and nonnative species (with both simulated and empirical demonstrations) to improve SDM realism and applications in the future.
Completion Date
2024
Semester
Summer
Committee Chair
David Jenkins
Degree
Doctor of Philosophy (Ph.D.)
College
College of Sciences
Department
Biology
Degree Program
Integrative Consrv Biology
Format
application/pdf
Identifier
DP0028883
URL
https://stars.library.ucf.edu/cgi/viewcontent.cgi?article=1455&context=etd2023
Language
English
Rights
In copyright
Release Date
2-15-2025
Length of Campus-only Access
None
Access Status
Doctoral Dissertation (Open Access)
Campus Location
Orlando (Main) Campus
STARS Citation
Bevan, Hannah R., "Is this the real life, or is this just fantasy? Assessing species distribution model realism and applicability with virtual and empirical species" (2024). Graduate Thesis and Dissertation 2023-2024. 479.
https://stars.library.ucf.edu/etd2023/479
Accessibility Status
Meets minimum standards for ETDs/HUTs
