Spatiotemporal variability of plant phenology in drylands: A case study from the northern Chihuahuan Desert

With global change, which includes climate change, there is a sense of urgency to understand how shifts in climate will affect ecosystems. Although several studies have improved understanding of how and why some ecosystems respond, most studies have not explored simultaneous responses of different land cover types throughout a given region. Dryland ecosystems, such as the Chihuahuan Desert, appear to respond to climate variability and currently make up about 40% of global land surface area. It is expected that drylands will expand to cover 60% of land surface area on earth by mid-century making this ecosystem more critical to global land-atmosphere interactions than previously thought. The goal of the proposed study is to determine how plant phenology in multiple desert land cover types responds to seasonal and inter annual climate variability over five years. Phenology is the timing of major growth stages in plants and animals which has been shown to provide important insights into the environmental state heavily influenced by climate change. Dryland plant phenology is relatively understudied. Time series imagery acquired by static digital cameras in five land cover types on the USDA Jornada Experimental Range in Southern New Mexico between 2010 and 2015 were analyzed with alternative remote sensing techniques at the landscape level phenology. At each site, both the phenology of the landscape and replicates of key species were analyzed using custom phenology analysis software developed within the Systems Ecology Lab at the University of Texas at El Paso. This study is expected to expand the current knowledge of the effects of climate variability and change in dryland ecosystems by understanding which land cover types and species are more/less sensitive to change. The study is also novel in that it will explore image processing methods that have yet to be fully explored by ecosystem scientists. Grasses displayed greater seasonal fluctuation in greening thought to be tied closely to rainfall events, where shrubs displayed a more consistent inter-annual growth pattern. This is hypothesized to be attributed to accessibility to deeper water storage attainable by the more extensive root systems commonly found in shrubs. Exploration into the use of alternate spectral signatures from images to capture timing of key growth stages proved to be useful in the patchy land cover. More extensive research needs to be done, but this study has hinted to advantages for using alternate color models for processing images within these extreme and complex ecosystems. These results may provide strong implications to predicting future ecosystem states of the northern Chihuahuan Desert region including ecosystem properties and processes such as biodiversity and land-atmosphere carbon fluxes