Assessment of plotless plant density methods of Astragalus albispinus Sirj & Bornm in various plant density intensities and distribution patterns

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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:

Quantitative methods to the evaluation of vegetation are the basis for describing and analyzing the plant communities and density as one of the main characteristics plays an important role in evaluating the performance (short and long effects) of rangeland ecosystems and management decisions. Therefore, the efficiency of plotless plant density methods in different density intensities and distribution patterns have been examined using a simulated population based on the real density of Astragalus albispinus (control method) in a semi-arid region of Marjan, Boroujen. Simulation schemes in the three density intensities and three distribution patterns within eight 40×100 m sampling units were designed. The predictive precision and accuracy of seven distance-based methods in various density intensities and distribution patterns were investigated comparing with the control method and the ideal point error index. Overall, angel order method in regular distribution pattern and point centered quarter method in random distribution pattern were the best plotless density methods of plant populations in low density. Third closest individual method was the most accurate and precise method of density among the studied methods in other different density intensities and distribution patterns. Therefore, in selecting the most appropriate distance method for estimating the density, the type of distribution pattern and in some cases the intensity of plant species density should be considered to achieve an unbiased estimation of plant populationʼs density, accordingly, the different habitats of this plant species can be monitored and evaluated in terms of management and utilization.

Language:
Persian
Published:
Journal of Plant Ecosystem Conservation, Volume:9 Issue: 1, 2021
Pages:
69 to 92
https://magiran.com/p2326876  
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