Characterization of the water bodies of Extremadura (SW Spain).

Extremadura is the region that stores the greatest amount of fresh water in Spain. Such water is mainly used for power generation, irrigation in agriculture, biodiversity conservation, tourism, recreation, and human and livestock consumption. Nevertheless, crucial information on the total number of water bodies and their geometrical characteristics and spatial distribution patterns are still missing. Thus, our main goal was to characterize the Extremenian water bodies geometrically and spatially through different statistical techniques such as kernel density, Moran's index, the Getis-Ord Gi*, and principal component analysis (PCA). Firstly, all existing hydrological information was gathered, and using aerial aircraft imagery and satellite images, each water body (WB) was then carefully collected, checked, and corrected. We have inventoried 100,614 WBs (mean density: 2.45 WB km2), irregularly distributed on the territory. WBs with an area < 0.01 km2 (100 ha) represent 64.5% of the total. A multivariate statistical study was conducted, showing that livestock, aridity of the climate, and topography are the main factors controlling the density of water bodies (WBs) in this area. It can be concluded that monitoring of small bodies is crucial to understand their spatial distribution, since they are spread over areas in which extensive farming and commercial crops such as tobacco strongly influence the way of living of many families.

Exploring the economic, social and environmental prospects for commercial natural annual grasslands by performing a sensitivity analysis on a multidisciplinary integrated model.

This paper presents an integrated modelling study aimed at exploring the possible effects of drivers of change in commercial natural annual grasslands. We consider drivers as factors that affect the rangeland but are not affected by it. Thus, the stocking rate is not treated as a driver, but as an endogenous factor ultimately determined by drivers. This approach, which call for integrated multidisciplinary studies, is rare in the rangeland literature. We try to alleviate this lack by presenting and utilizing a novel multidisciplinary integrated system-dynamics model (108 equations) which represents an area of privately owned extensive farms, its farmers (their numbers and decisions), herds or flocks, herbage production, soil erosion and the linked local markets. By means of a global sensitivity analysis of this model we evaluated the sensitivities of key endogenous factors to the same percentage variation in 70 factors, including economic and climate drivers. The analysis considered the behaviours of 288,000 variants of the modelled system, each under a different 300-year driver scenario. We found that the environmental component of the model was almost exclusively sensitive to biophysical factors, whereas the socio-economic component was almost exclusively sensitive to socio-economic factors, despite the model takes account of key feedbacks connecting both components. Our results suggest that cautiously-managed commercial natural grasslands could socially and economically cope with climate change, especially in a scenario of rising prices of animal products, and also that, even though stocking rates would increase due to an increase in the demand for livestock products, the main threat to the provision of ecosystem services in the studied system would be climate change.