Linking landscape structure and vegetation productivity with nut consumption by the Cantabrian brown bear during hyperphagia.

In bears, reproduction is dependent on the body reserves accumulated during hyperphagia. The Cantabrian brown bear mainly feeds on nuts during the hyperphagia period. Understanding how landscape heterogeneity and vegetation productivity in human-dominated landscapes influence the feeding habits of bears may therefore be important for disentangling species-habitat relationships of conservation interest. We determined the spatial patterns of nut consumption by brown bears during the hyperphagia period in relation to landscape structure, characteristics of fruit-producing patches and vegetation productivity. For this purpose, we constructed foraging models based on nut consumption data (obtained by scat analysis), by combining vegetation productivity data, topographical variables and landscape metrics to identify nut foraging patterns during this critical period for bears. The average wooded area of patches where scats were collected and where the nuts that the bears had consumed were produced was larger than that of the corresponding patches where nuts were not produced. For scats collected outside of nut-producing patches, the distance between the scats and the patches was greatest for chestnut-producing patches. Elevation, Gross Primary Production (GPP) and the Aggregation Index (AI) were good predictors of acorn consumption in the models. Good model fits were not obtained for data on chestnut consumption in bears. The findings confirm that brown bears feeding on nuts show a preference for relatively large, highly aggregated patches with a high degree of diversity in the landscape pattern, which may help the bears to remain undetected. The nut prediction model highlights areas of particular importance for brown bears during hyperphagia. The human presence associated with sweet chestnut forest stands or orchards may make bears feel more vulnerable when feeding.

The spatial level of analysis affects the patterns of forest ecosystem services supply and their relationships.

The implementation of the Ecosystem Services (ES) framework (including supply and demand) should be based on accurate spatial assessments to make it useful for land planning or environmental management. Despite the inherent dependence of ES assessments on the spatial resolution at which they are conducted, the studies analyzing these effects on ES supply and their relationships are still scarce. To study the influence of the spatial level of analysis on ES patterns and on the relationships among different ES, we selected seven indicators representing ES supply and three variables that describe forest cover and biodiversity for Catalonia (NE Iberian Peninsula). These indicators were estimated at three different scales: local, municipality and county. Our results showed differences in the ES patterns among the levels of analysis. The higher levels (municipality/county) removed part of the local heterogeneity of the patterns observed at the local scale, particularly for ES indicators characterized by a finely grained, scattered distribution. The relationships between ES indicators were generally similar at the three levels. However, some negative relationships (potential trade-offs) that were detected at the local level changed to positive (and significant) relationships at municipality and county. Spatial autocorrelation showed similarities between patterns at local and municipality levels, but differences with county level. We conclude that the use of high-resolution spatial data is preferable whenever available, in particular when identifying hotspots or trade-offs/synergies is of primary interest. When the main objective is describing broad patterns of ES, intermediate levels (e.g., municipality) are also adequate, as they conserve many of the properties of assessments conducted at finer scales, allowing the integration of data sources and, usually, being more directly relevant for policy-making. In conclusion, our results warn against the uncritical use of coarse (aggregated) spatial ES data and indicators in strategies for land use planning and forest conservation.

Spatiotemporal analysis of vehicle collisions involving wild boar and roe deer in NW Spain.

Ungulate-vehicle collisions pose a serious traffic safety hazard in the North of Spain. The understanding of underlying temporal and spatial structure of these non-random events is imperative to develop appropriate mitigation measures. This study analyses the temporal, spatial and spatiotemporal patterns of car crashes involving wild boar and roe deer in the province of Lugo (NW Spain) in the period 2006-2010 using geographic information systems (GIS) and spatial statistics. The temporal analysis--conducted at three scales: daily, weekly and seasonal--revealed that accidents are related to specific animal's life cycles and to interactions with human activities. The localization of collision points with GIS discovered the sections of the autonomic road network where accidents with the two studied species concentrate. Besides, the spatial arrangement of significant hotspots was mapped through kernel density estimation over two time scales (daily and seasonal), distinguishing among 41 sets, sequentially arranged to facilitate clustering comparison and determination of spatiotemporal risky areas. This work is of valuable help for road managers to design the appropriate mitigation measures that will improve traffic safety and animal welfare.