Distribution of the Hantavirus reservoir Oligoryzomys nigripes in Argentina: Choosing spatial models for the actual and potential distribution of the black-footed colilargo.

ANIBAL EDUARDO CARBAJO; PABLO TETA

MAMMALIA

DeGruyter's

Lugar: Paris-Berlin; Año: 2009 vol. 73 p. 313 - 321

0025-1461

<!-- /* Style Definitions */ p.MsoNormal, li.MsoNormal, div.MsoNormal {mso-style-parent:""; margin-top:0cm; margin-right:2.25pt; margin-bottom:0cm; margin-left:0cm; margin-bottom:.0001pt; text-indent:9.0pt; line-height:200%; mso-pagination:widow-orphan; font-size:12.0pt; font-family:"Times New Roman"; mso-fareast-font-family:"Times New Roman"; mso-ansi-language:EN;} @page Section1 {size:612.0pt 792.0pt; margin:70.85pt 3.0cm 70.85pt 3.0cm; mso-header-margin:36.0pt; mso-footer-margin:36.0pt; mso-paper-source:0;} div.Section1 {page:Section1;} --> A first step in understanding the ecology of rodents as reservoirs and their relation with the disease they transmit is to determine their geographical distribution. This distribution can be modelled as a function of environmental variables. We georeferenced an extensive database of hantavirus reservoir Oligoryzomys nigripes (Muridae: Sigmodontinae) records in Argentina and used generalized linear models (GLM) and GARP to model the presence probability of this rodent as a function of multiple environmental variables. The GLM model correctly classified 86% of the sites and gave a good prediction area. The GLM model with a spatial term resulted in a probable presence area that matched the rodent occurrences too tightly, and thus was not useful to speculate the potential distribution. The GARP model resulted in a broader probable presence area for the black-footed colilargo than regression models. We suggest that the GLM model without spatial term reflects the actual distribution and should be considered for hantavirus most urgent control plans, while the GARP model may be regarded as the most widespread potential distribution and thus considered in long term plans.