Abstract

Iranian natural ecosystems have aesthetic, conservation and genetics values and provide many functions and services, but have become vulnerable. This investigation aimed to (1) survey flora of an arid-steppe montain ecosystem, (2) analyze the ecological characteristics of the vegetation in relation to altitude and soil properties and (3) elaborate on ecophysiological processes. Samples of soil and plants were collected randomly in three altitudes at about 36^° latitude in Parvar Protected Area (PPA), Iran. Plant species were identified, ecologic and floristic data were collected and statistical analyses were performed using Excel and SPSS. Physiognomy of the region is steppe. The type of soil is sandy-loam, and it becomes loamy with increasing altitude. Majority (45.5%) of species are cryptophytes and belong to Irano-Turani region followed by chameophytes (36.4%) and therophyte (18.1%). Artemisia aucheri, Eremopyrum elengutum and Stachys aucheri dominated at the upper (2338 m), middle (2009m) and lower (1783 m) elevations above sea level, respectively. Onobrychis cornuta and Astragalus ochrochlorous were also common to all stations. Ecological indices showed reducing trend with hike in altitude except dominance index which increased. Artemisia aucheri was the overall dominant plant and in need of ecological management. Ecophysiological interaction of plant species with environmental parameters at local level undoubtedly determines their community structure, scale and pattern of distribution. Since plant species in semi-arid regions have developed specific adaptation strategies to cope with environmental changes, it is useful to link local adaptation strategies (for example, avoidance, tolerance, resistance) and physiological processes to global changes. In this way, knowledge on morphology, physiology, life-history, phenology and behavior gained from ecological studies based on individuals, communities and ecosystems can be analyzed in ecological and evolutionary context and thus, afford the tool of predicting responses and simulating ecosystem models to environmental changes in future.

This work is licensed under a Creative Commons Attribution 4.0 License.