Document Type
Article
Abstract
1. The estimation of extinction dates from limited and incomplete sighting records
is a key challenge in conservation (when experts are uncertain whether a species has
gone extinct) and historical ecology (when the date and mechanism of extinction is
controversial).
2. We introduce a spatially-explicit method of interpolating extinction date estima8 tors, allowing users to estimate spatiotemporal surfaces of population persistence 9 from georeferenced sighting data of variable quality.
3. We present the R package spatExtinct, which produces spatially-explicit extinction date surfaces from geolocated sightings, including options for custom randomization schemes to improve accuracy with limited datasets. We use simulations to illustrate the sensitivity of the method to parameterization, and apply the method to identify potential areas where Bachman’s warbler (Vermivora bachmanii) might be rediscovered.
4. Our method, and the spatExtinct package, has the potential to help describe and differentiate different drivers of extinction for historical datasets, and could be used to identify possible regions of population persistence for species with an uncertain extinction status, improving on non-spatial or imprecise methods that are currently in use.
2. We introduce a spatially-explicit method of interpolating extinction date estima8 tors, allowing users to estimate spatiotemporal surfaces of population persistence 9 from georeferenced sighting data of variable quality.
Digital Object Identifier (DOI)
Publication Info
Preprint version bioRxiv The Preprint Server for Biology, 2018.
Rights
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
APA Citation
Carlson, C. J., Burgio, K. R., Dallas, T. A., & Bond, A. L. (2018). Spatial Extinction Date Estimation: A Novel Method for Reconstructing Spatiotemporal Patterns of Extinction and Identifying Potential Zones of Rediscovery. https://doi.org/10.1101/279679