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. 2011 Mar 25;6(3):e17731.
doi: 10.1371/journal.pone.0017731.

Tracking a medically important spider: climate change, ecological niche modeling, and the brown recluse (Loxosceles reclusa)

Erin E Saupe  1 , Monica Papes, Paul A Selden, Richard S Vetter
Affiliations

Tracking a medically important spider: climate change, ecological niche modeling, and the brown recluse (Loxosceles reclusa)

Erin E Saupe et al. PLoS One. .

Abstract

Most spiders use venom to paralyze their prey and are commonly feared for their potential to cause injury to humans. In North America, one species in particular, Loxosceles reclusa (brown recluse spider, Sicariidae), causes the majority of necrotic wounds induced by the Araneae. However, its distributional limitations are poorly understood and, as a result, medical professionals routinely misdiagnose brown recluse bites outside endemic areas, confusing putative spider bites for other serious conditions. To address the issue of brown recluse distribution, we employ ecological niche modeling to investigate the present and future distributional potential of this species. We delineate range boundaries and demonstrate that under future climate change scenarios, the spider's distribution may expand northward, invading previously unaffected regions of the USA. At present, the spider's range is centered in the USA, from Kansas east to Kentucky and from southern Iowa south to Louisiana. Newly influenced areas may include parts of Nebraska, Minnesota, Wisconsin, Michigan, South Dakota, Ohio, and Pennsylvania. These results illustrate a potential negative consequence of climate change on humans and will aid medical professionals in proper bite identification/treatment, potentially reducing bite misdiagnoses.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Brown recluse specimen.
Collected in Lawrence, KS, USA. Scale: 5 mm.
Figure 2
Figure 2. Present-day niche modeling results in comparison to previously identified distribution.
A) Distribution of the brown recluse based on field studies and literature surveys from . Note the general congruence between the niche model results and the distribution recognized by arachnologists. B) GARP models are depicted on the left, with the training region above and projection below. Maxent models are depicted on the right, with the training region above and projection below. Occurrence points are mapped onto these models, with lime green points = training data and salmon points = testing data. A threshold has been applied, allowing for a maximum of five percent omission error based on presence data. Results are depicted in USA Contiguous Albers Equal Area Conic map projection.
Figure 3
Figure 3. Future niche modeling results for three time slices: 2020, 2050, and 2080.
GARP models are depicted on the left, with Maxent models on the right. Two climate change scenarios were utilized: a2a (liberal) and b2a (conservative). The lime green dotted polygon indicates the distribution of L. reclusa according to arachnologists, as was depicted in Fig. 2B. Suitable habitat for the brown recluse shifts northward with time. A threshold has been applied, allowing for a maximum of five percent omission error based on presence data. Results are depicted in USA Contiguous Albers Equal Area Conic map projection.
Figure 4
Figure 4. Model agreement between climate change scenarios per time slice.
GARP results are depicted above, with Maxent models below. The two climate change scenarios (a2a and b2a) are compared, with area of overlap indicated in maroon, for the three time slices: 2020, 2050, and 2080. A threshold has been applied, allowing for a maximum of five percent omission error based on presence data. Results are depicted in USA Contiguous Albers Equal Area Conic map projection.
Figure 5
Figure 5. GARP-Maxent model agreement for each time slice and scenario.
Maroon signals agreement; thus, blue areas are where Maxent predicted suitable habitat, but not GARP, or vice versa. A threshold has been applied, allowing for a maximum of five percent omission error based on presence data. Results are depicted in USA Contiguous Albers Equal Area Conic map projection.
Figure 6
Figure 6. Niche overlap between extant and future models.
GARP results are depicted on the left, with Maxent models on the right. Three time slices: 2020, 2050, and 2080 are illustrated for two climate change scenarios: a2a (liberal) and b2a (conservative). Area of overlap between the extant and future models is portrayed in maroon. A threshold has been applied, allowing for a maximum of five percent omission error based on presence data. Results are depicted in USA Contiguous Albers Equal Area Conic map projection.
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