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Water is a key driver of ecosystem processes in aridland ecosystems. Thus, changes in climate could have significant impacts on ecosystem structure and function. In the southwestern US, interactions among regional climate drivers (e.g., El Ni�o Southern Oscillation) and topographically controlled convective storms create a spatially and temporally variable precipitation regime that governs the rate and magnitude of ecosystem processes. We quantified the spatial and temporal distribution of reduced grassland greenness in response to seasonal and annual variation in precipitation at two scales at the Sevilleta Long Term Ecological Research site in central New Mexico, using Normalized Difference Vegetation Index (NDVI)...
Mapping salt-affected soils in remote rangelands is challenging. We used Landsat 7 ETM data to facilitate digital mapping of gypsic and natric soil areas in the upper Colorado River drainage. Optimum index factor band combinations were used to explore the scene. Normalized difference ratio models and threshold values were developed by comparing spectral signatures with gypsic and natric soil areas verifi ed in the fi eld. Gypsic soil areas were mapped using the normalized difference ratio of Bands 5 and 7 with a threshold >0.11, probably related to the spectral refl ectance of gypsum within a few centimeters of the surface. All sites predicted to be gypsic soil areas were determined to be gypsic by fi eld assessment,...
To assess the North American high-latitude vegetation response to the rising temperature, we derived NDVI trend for 91.2% of the non-water, non-snow land area of Canada and Alaska using the peak-summer Landsat surface reflectance data of 1984–2012. Our analysis indicated that 29.4% and 2.9% of the land area of Canada and Alaska showed statistically significant positive (greening) and negative (browning) trends respectively, at significance level p < 0.01, after burned forest areas were masked out. The area with greening trend dominated over that with browning trend for all land cover types. The greening occurred primarily in the tundra of western Alaska, along the north coast of Canada and in northeastern Canada;...
To assess the North American high-latitude vegetation response to the rising temperature, we derived NDVI trend for 91.2% of the non-water, non-snow land area of Canada and Alaska using the peak-summer Landsat surface reflectance data of 1984–2012. Our analysis indicated that 29.4% and 2.9% of the land area of Canada and Alaska showed statistically significant positive (greening) and negative (browning) trends respectively, at significance level p < 0.01, after burned forest areas were masked out. The area with greening trend dominated over that with browning trend for all land cover types. The greening occurred primarily in the tundra of western Alaska, along the north coast of Canada and in northeastern Canada;...
In this study we present a technique to discriminate between climate or human-induced dryland degradation, based on evaluations of AVHRR NDVI data and rainfall data. Since dryland areas typically have high inter-annual rainfall variations and rainfall has a dominant role in determining vegetation growth, minor biomass trends imposed by human influences are difficult to verify. By performing many linear regression calculations between different periods of accumulated precipitation and the annual NDVImax, we identify the rainfall period that is best related to the NDVImax and by this the proportion of biomass triggered by rainfall. Positive or negative deviations in biomass from this relationship, expressed in the...
Groundwater dependent ecosystems (GDEs) rely on near-surface groundwater. These systems are receiving more attention with rising air temperature, prolonged drought, and where groundwater pumping captures natural groundwater discharge for anthropogenic use. Phreatophyte shrublands, meadows, and riparian areas are GDEs that provide critical habitat for many sensitive species, especially in arid and semi-arid environments. While GDEs are vital for ecosystem services and function, their long-term (i.e. ~ 30 years) spatial and temporal variability is poorly understood with respect to local and regional scale climate, groundwater, and rangeland management. In this work, we compute time series of NDVI derived from sensors...