New Paper in Methods in Ecology and Evolution: Integrated SDM Database
Veronica Frans
Do you struggle with translating your species distribution model (SDM) results into a simple, accessible format for conservation managers & practitioners? Try our Integrated SDM Database!
The iSDMdb informs on SDM predictions, uncertainty, human impacts, habitat restoration, novel preferences/adaptations, & management priorities--All in one place!
We exemplify our work with the complex case of the endangered New Zealand sea lions, which are recolonising the mainland as a sign of hope for this precious species. 😊 To ensure the iSDMdb serves managers best, we need to communicate and engage with them.
The iSDMdb can be converted into multiple formats: GIS layers, printed maps, tables, & an interactive map using tmap. We demonstrate how to do this in R using Maxent. You can access the interactive map we created here: https://bit.ly/nzslmap (takes a moment to load, so please be patient).
We also summarize the work in a Methods Blog (https://bit.ly/nzslBLG).
You can learn more about the conservation story of the New Zealand sea lion in the New York Times (https://bit.ly/nzslNYT) and Washington Post (https://bit.ly/nzslWP).
We provide R code in the supplementary materials of the paper, but also in Zenodo (https://zenodo.org/record/5502316) and GitHub (https://github.com/vffrans/iSDMdb).
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Here's the abstract:
1. Species' ranges are changing at accelerating rates. Species distribution models (SDMs) are powerful tools that help rangers and decision-makers prepare for reintroductions, range shifts, reductions and/or expansions by predicting habitat suitability across landscapes. Yet, range-expanding or -shifting species in particular face other challenges that traditional SDM procedures cannot quantify, due to large differences between a species' currently occupied range and potential future range. The realism of SDMs is thus lost and not as useful for conservation management in practice. Here, we address these challenges with an extended assessment of habitat suitability through an integrated SDM database (iSDMdb).
2. The iSDMdb is a spatial database of predicted sites in a species' prediction range, derived from SDM results, and is a single spatial feature that contains additional, user-friendly data fields that synthesise and summarise SDM predictions and uncertainty, human impacts, restoration features, novel preferences in novel spaces and management priorities. To illustrate its utility, we used the endangered New Zealand sea lion Phocarctos hookeri. We consulted with wildlife rangers, decision-makers and sea lion experts to supplement SDM predictions with additional, more realistic and applicable information for management.
3. Almost half the data fields included in this database resulted from engaging with these end-users during our study. The SDM found 395 predicted sites. However, the iSDMdb's additional assessments showed that the actual suitability of most sites (90%) was questionable due to human impacts. >50% of sites contained unnatural barriers (fences, grazing grasslands), and 75% of sites had roads located within the species' range of inland movement. Just 5% of the predicted sites were mostly (>80%) protected.
4. Integrating SDM results with supplemental assessments provides a way to address SDM limitations, especially for range-expanding or -shifting species. SDM products for conservation applications have been critiqued for lacking transparency and interpretation support, and ineffectively communicating uncertainty. The iSDMdb addresses these issues and enhances the practical relevance and utility of SDMs for stakeholders, rangers and decision-makers. We exemplify how to build an iSDMdb using open-source tools, and how to make diverse, complex assessments more accessible for end-users.
If you have any questions or feedback about the work, I look forward to hearing from you!
Cheers,
Veronica Frans, MSc., Michigan State University, USA
