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Range Management and Agroforestry
Year : 2020, Volume : 41, Issue : 2
First page : ( 200) Last page : ( 208)
Print ISSN : 0971-2070. Online ISSN : 2249-5231.

Comportments of arid grazing land plant diversity: A temporal assessment with bottom-up and top-down factors

Manish Mathur*

ICAR-Central Arid Zone Research Institute, Jodhpur-342003, India

*Corresponding author eco5320@gmail.com

Online published on 18 February, 2021.


In the present study, behaviors of arid grazing lands richness (S), evenness (E), Shannon-Wiener diversity (H’) and SHE patterns were temporally assessed (pulse, inter-pulse and non-pulse) along with their intra and interrelationships with soil and habitat factors. Comportments of these diversity variables were also examined in the cumulative data set. Higher average species richness (9.0) and diversity (2.0) were recorded during pulse event while the lowest values for both these parameters (4.0 and 0.9, respectively) were recorded during non-pulse event. Statistically, temporal significant variability's in both these components were exhibited by student t test. Further, both species richness and diversity were positively related with each other during all the sampling period (r2 = 0.87, 0.64 and 0.73) and in cumulative data set (r2 = 0.89). A positive relationship (r2 = 0.77) between diversity and evenness were recorded only during interpulse(winter), however, cumulatively both diversity (r2 = -0.43) and richness (r2 = - 0.49) were negatively related with evenness. Log-normal SHE patterns were recorded during pulse and non-pulse periods, while log-series pattern was recorded during inter-pulse period. Partial Least Square (PLS) regression with individual diversity index revealed significant impacts of soil variables (electric conductivity, pH, soil moisture and nitrogen) and per cent bare surface size, while soil organic carbon, botanical composition of climax species along with bare surface size were controlling factors for SHE pattern. Model equations for all the diversity variables and for SHE pattern were prepared with selection of significant predictors with the help of variables importance for the projection (VIPs).



Arid region, Evenness, Grazing land, Richness, SHE analysis.


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