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A species distribution may be determined by its responses to patterns of human disturbance as well as by its habitat preferences. Here we investigate the distribution of the Upland Goose Chloephaga picta, which has been historically persecuted by farmers and ranchers in Patagonia because it feeds on crops and pastures and is assumed to compete with sheep for forage. We assess whether its current breeding distribution is shaped by persecution by ranchers or whether it can be better explained by differences in habitat primary productivity and preference for wetlands, or by other anthropogenic disturbances not associated with ranching. We built species distribution models to examine the relative effect of environmental and anthropogenic predictors on the regional distribution of Upland Goose. We performed vehicle surveys in the province of Santa Cruz, Argentina, in two years, surveying 8000 km of roads and recording 6492 Geese. Generalized additive models were used to model the presence/absence of Geese in 1-km cells. The models suggested that Upland Goose distribution is not currently affected by rancher control, as the species is more abundant in areas with high sheep stocking levels, but it is positively influenced by primary productivity and negatively influenced by urban areas. Anthropogenic disturbance caused by urban areas and oil extraction camps had a greater impact in limiting the species distribution than sheep ranching. [ABSTRACT FROM AUTHOR]

In this paper we show how new technologies can be incorporated from the gathering of field data on wildlife distribution to the final stage of producing distribution maps. We describe an integrated framework for conducting wildlife censuses to obtain data to build predictive models of species distribution that when integrated in a GIS will produce a distribution map. Field data can be obtained with greater accuracy and at lower costs using a combination of Global Positioning System, Personal Digital Assistant, and specific wildlife recording software. Sampling design benefits from previous knowledge of environmental variability that can be obtained from free remote sensing data. Environmental predictors derived from this remote sensing information alone, combined with automatic procedures for predictor selection and model fitting, can render cost-effective predictive distribution models for wildlife. We show an example with guanaco distribution in the Patagonian steppes of Santa Cruz province, Argentina. [ABSTRACT FROM AUTHOR]

The knowledge of environmental variables associated with the species occurrence allows the recognition of sites which fulfil ecological requirements eventually used for conservation of species. The coastal dunes of Argentina are inhabited by sand lizards. Anthropic activities have severely degraded this ecosystem, affecting the habitat structure at a large scale. In this context, the effects of landscape characteristics on the sand lizard's ( Liolaemus wiegmannii, Liolaemidae) presence were analysed to build habitat suitability maps along the coastal dunes of Argentina. A thematic map of study area was obtained from supervised classification of satellite images to identify landscape characteristics. Surveys were conducted during the lizard activity season, and landscape variables were measured in two spatial units. All information collected was compiled into a Geographic Information System. The relationship between the presence of lizards and landscape variables was evaluated by Generalized Linear Models. The predictions of these models were transferred by using Geographic Information System to habitat suitability maps. Almost all individuals (80%) were observed in semi-fixed dunes. The analysis of landscape metrics in the two spatial extents showed complementary results. The habitat suitability models suggest that: (i) heterogeneous landscapes composed by disaggregated patches of semi-fixed dunes and low or null percentages of active dunes distant from the coastline are the preferred environments, and (ii) human modifications such as urbanizations and forestation of dunes, have a negative impact on species occurrence. Suitable habitats were almost absent in those sectors of coastal dunes with highest level of urbanization, whereas they were distributed almost continuously in those areas without human disturbances. [ABSTRACT FROM AUTHOR]