Variability and Controls of Plant Phenology in Drylands: A Novel Case Study from the Northern Chihuahuan Desert

Abstract:

By mid century, arid ecosystems will likely comprise the largest terrestrial biome on the planet largely as a result of anthropogenic disturbance and climate change. The size, extent, increased prevalence of shrubs, and large pool of soil carbon are just some of the underlying reasons why it is important to advance our understanding of biogeochemical cycling and energy balance in these landscapes and how change may alter feedbacks with other components of the Earth System. Although substantial progress has been made over the past decade, few studies have simultaneously examined how plant stress can constrain larger scale phenomenon (e.g. plant and landscape phenology), and how large scale phenomenon (e.g. climatic extremes and variability) can impact relatively small scale processes such as plant photosynthetic stress. This study, conducted in a creosote shrubland on the USDA Jornada Experimental Range (JER) in southern New Mexico during 2012-2015, documents seasonal changes in plant and landscape phenology (NPN protocols and phenocams) across four different land cover types (LCTs). The selected LCTs includes grassland, grassland-tobosa playa, shrubland-sandy ridge, and shrubland where each vegetative growth is captured with Windscape “PlantCams” between 11:00 am and 2:00 pm MST. An image processing program (Phenology Analyzer Software), developed in-house has been used to process and analyze imagery. Regions of interest (ROIs) were chosen at the plant and landscape scale to enable inter-comparison of plant phenological trends within and between LCTs using a well-acceted greenness index (Richardson et al. 2007). Timing of green-up was similar between sites but peak greenness varied between LCTs. Shrubland greenness was substantially greater than values from other LCTs. Ongoing analysis is also exploring the utility of alternate color spaces (HSV and L*a*b*) for describing plant phenology using custom phenocams maintained on the JER by UTEP Systems Ecology Lab. This study is expected to expand current knowledge of the effects of climate variability and change in dryland ecosystems by understanding which LCTs 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.