DENSITY ESTIMATION OF SYMPATRIC GEOFFROY’S CATS AND PAMPAS CATS

CARUSO N.; MANFREDI C.; LUCHERINI M.; COSTILLA P.; CASANAVE E.

Mendoza

Congreso; 10th International Mammalogical Congress; 2009

The study of carnivore population abundances is particularly difficult, but is necessary to develop management and conservation programs. Little is known about sympatric cats ecology in the Pampas grasslands, which, in Argentina, have been strongly altered and fragmented by human intervention. The aim of this study was to learn more about the effect of human disruption on the abundante and distribution of this species. We conducted a camera survey (58 days) in a bushland-rich area (a private farm with cattle in southwestern Buenos Aires Province: 384200S-625700W). We placed 44 stations with 2 cameras positioned to photograph both flanks of the animals. The distance among cameras (800 m) was determined using data previously taken on radiotagged Geoffroy’s cats (Leopardus geoffroyi). Sixty six photos of Geoffroy’s cats and 13 of Pampas cats were taken; each photographed cat was identified by its unique spot pattern. We pooled daily data in blocks such that one encounter occasion consisted of a five-day time period. We used Capture software to estimate abundance. To calculate the effective survey area (39.5 km2) we created a convex polygon with camera locations and applied a buffer (using the MMDM) around it. The populations of both Pampas cat (L. colocolo, Z=-0.707, p=0.24) and Geoffroy’s cat (Z= 1.155, p=0.88) were closed. Geoffroy’s cats (20±7 individuals) were more abundant than Pampas cats (9±4.2 individuals) considering the H(0) model. The estimated density was 50.6 animals/100 km2 for Geoffroy’s cat and 22.8 animals/100 km2 for Pampas cat. Our abundance data suggest that the Geoffroy’s cat is more flexible to human impact than the Pampas cat. At present, natural grasslands are fragmented and bushland patches probably represent a good habitat for cats that may guarantee the survival of relatively large populations within a less favourable matrix.