Abstract:In Southern Patagonia, a long-term monitoring network has been established to assess bio-indicators as an early warning of environmental changes due to climate change and human activities. Soil organic carbon (SOC) content in rangelands provides a range of important ecosystem services and supports the capacity of the land to sustain plant and animal productivity. The objectives in this study were to model SOC (30 cm) stocks at a regional scale using climatic, topographic and vegetation variables, and to establish a baseline that can be used as an indicator of rangeland condition. For modelling, we used a stepwise multiple regression to identify variables that explain SOC variation at the landscape scale. With the SOC model, we obtained a SOC map for the entire Santa Cruz province, where the variables derived from the multiple linear regression models were integrated into a geographic information system (GIS). SOC stock to 30 cm ranged from 1.38 to 32.63 kg C m −2 . The fitted model explained 76.4% of SOC variation using as independent variables isothermality, precipitation seasonality and vegetation cover expressed as a normalized difference vegetation index. The SOC map discriminated in three categories (low, medium, high) determined patterns among environmental and land use variables. For example, SOC decreased with desertification due to erosion processes. The understanding and mapping of SOC in Patagonia contributes as a bridge across main issues such as climate change, desertification and biodiversity conservation.

Soil total nitrogen (N) stock in rangelands, shrublands, and forests support key ecological functions such as the capacity of the land to sustain plant and animal productivity and ecosystem services. The objective of this study was to model soil total N stocks and soil C/N ratio from 0–30 cm depth across the region using freely accessible information on topography, climate, and vegetation with a view to establishing a baseline against which sustainable land management practices can be evaluated in Southern Patagonia. We used stepwise multiple regression to determine which independent variables best explained soil total N variation across the landscape in Southern Patagonia. We then used multiple regression models to upscale and produce maps of soil total N and C/N across the Santa Cruz province. Soil total N stock to 30 cm ranged from 0.13 to 2.21 kg N m−2, and soil C/N ratios ranged from 4.5 to 26.8. The model for variation of soil total N stock explained 88% of the variance on the data and the most powerful predictor variables were: isothermality, elevation, and vegetation cover (normalized difference vegetation index (NDVI)). Soil total N and soil C/N ratios were allocated to three categories (low, medium, high) and these three levels were used to map the variation of soil total N and soil C/N ratios across Southern Patagonia. The results demonstrate that soil total N decreases as desertification increases, probably due to erosional processes, and that soil C/N is lower at low temperatures and increased with increasing precipitation. Soil total N and soil C/N ratios are critical variables that determine system capacity for productivity, especially the provisioning ecosystem services, and can serve as baselines against which efforts to adopt more sustainable land management practices in Patagonia can be assessed.

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