We present the MARAS (Environmental Monitoring of Arid and Semiarid Regions) dataset, which stores vegetation and soil data of 426 rangeland monitoring plots installed throughout Patagonia, a 624.500 km2 area of southern Argentina and Chile. Data for each monitoring plot includes basic climatic and landscape features, photographs, 500 point intercepts for vegetation cover, plant species list and biodiversity indexes, 50-m line-intercept transect for vegetation spatial pattern analysis, land function indexes drawn from 11 measures of soil surface characteristics and laboratory soil analysis (pH, conductivity, organic matter, N and texture). Monitoring plots were installed between 2007 and 2019, and are being reassessed at 5-year intervals (247 have been surveyed twice). The MARAS dataset provides a baseline from which to evaluate the impacts of climate change and changes in land use intensity in Patagonian ecosystems, which collectively constitute one of the world´s largest rangeland areas. This dataset will be of interest to scientists exploring key ecological questions such as biodiversity-ecosystem functioning relationships, plant-soil interactions and climatic controls on ecosystem structure and functioning.

Trend-cycles of vegetation dynamics as a tool for land degradation assessment and monitoring Easdale, M. H.

No abstract

Distinguishing the contributions of different vegetation cover such as shrubs and grasses components into the primary production in arid and semi-arid rangelands is a key step to understanding changes at a landscape scale. The aim was to assess the contribution of shrubs, grasses and bare soil components into a total biophysical variable at a patch level, and the relationship between that biophysical variable and remote sensing vegetation index, in a grass–shrub steppe from North-West Patagonia, Argentina. We conducted a field survey in the period 2015–2017 to analyzing the relationship between monthly values of Normalized Difference Vegetation Index (NDVI) of two grasses, two shrub species and bare soil, weighted by their cover area at a patch level, and the concomitant patch NDVI records, respectively. The contribution of the patch components to the total NDVI value at a patch level was additive. The relationship between the weighted NDVI of patch components and the concomitant NDVI value at a patch level along time was linear for perennial grasses and deciduous shrub–grass patches, but linearity was not significant for most perennial shrub–grass patches. Differences among patch compositions and their surface reflectance suggest the need to move forward in a more precise distinction of the floristic composition of patches, to better understanding their contribution to NDVI temporal dynamics at a landscape scale.