| Title |
The Use of Climatic Niches in Screening Procedures for Introduced Species to Evaluate Risk of Spread: A Case with the American Eastern Grey Squirrel
|
|---|---|
| Published in |
PLOS ONE, July 2013
|
| DOI | 10.1371/journal.pone.0066559 |
| Pubmed ID | |
| Authors |
Mirko Di Febbraro, Peter W. W. Lurz, Piero Genovesi, Luigi Maiorano, Marco Girardello, Sandro Bertolino |
| Abstract |
Species introduction represents one of the most serious threats for biodiversity. The realized climatic niche of an invasive species can be used to predict its potential distribution in new areas, providing a basis for screening procedures in the compilation of black and white lists to prevent new introductions. We tested this assertion by modeling the realized climatic niche of the Eastern grey squirrel Sciurus carolinensis. Maxent was used to develop three models: one considering only records from the native range (NRM), a second including records from native and invasive range (NIRM), a third calibrated with invasive occurrences and projected in the native range (RCM). Niche conservatism was tested considering both a niche equivalency and a niche similarity test. NRM failed to predict suitable parts of the currently invaded range in Europe, while RCM underestimated the suitability in the native range. NIRM accurately predicted both the native and invasive range. The niche equivalency hypothesis was rejected due to a significant difference between the grey squirrel's niche in native and invasive ranges. The niche similarity test yielded no significant results. Our analyses support the hypothesis of a shift in the species' climatic niche in the area of introductions. Species Distribution Models (SDMs) appear to be a useful tool in the compilation of black lists, allowing identifying areas vulnerable to invasions. We advise caution in the use of SDMs based only on the native range of a species for the compilation of white lists for other geographic areas, due to the significant risk of underestimating its potential invasive range. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Colombia | 2 | 50% |
| United Kingdom | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 75% |
| Science communicators (journalists, bloggers, editors) | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 148 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Denmark | 2 | 1% |
| United States | 2 | 1% |
| Italy | 2 | 1% |
| Brazil | 1 | <1% |
| South Africa | 1 | <1% |
| Colombia | 1 | <1% |
| Argentina | 1 | <1% |
| Germany | 1 | <1% |
| Spain | 1 | <1% |
| Other | 1 | <1% |
| Unknown | 135 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 39 | 26% |
| Student > Ph. D. Student | 25 | 17% |
| Student > Master | 17 | 11% |
| Student > Bachelor | 15 | 10% |
| Professor | 8 | 5% |
| Other | 27 | 18% |
| Unknown | 17 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 66 | 45% |
| Environmental Science | 50 | 34% |
| Earth and Planetary Sciences | 2 | 1% |
| Engineering | 2 | 1% |
| Immunology and Microbiology | 1 | <1% |
| Other | 3 | 2% |
| Unknown | 24 | 16% |