Volume 18, Issue 1 (7-2024)
مرتع 2024, 18(1): 132-151 |
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Heidari Ghahfarrokhi Z, Tahmasebi P, Naghipour A A. Relationship Between Plant Diversity and Functional Diversity Indices with Landscape Function Analysis (LFA) Functionalities. مرتع 2024; 18 (1) :132-151
URL: http://rangelandsrm.ir/article-1-1239-en.html
URL: http://rangelandsrm.ir/article-1-1239-en.html
Department of Nature engineering, Faculty of Natural Resources and Earth Sciences, Shahrekord University, Shahrekord
Abstract: (470 Views)
Background and objectives: Rangeland condition assessment is crucial for effective management. While qualitative methods like Landscape Function Analysis (LFA) provide valuable information on ecosystem functions, their application can be time-consuming and require expertise. This study aimed to identify relationships between quantitative plant diversity and functional diversity indices with the qualitative functional characteristics assessed by LFA in Tang e Sayad protected area, Chaharmahal va Bakhtiari Province, Iran.
Methodology: Three rangeland sites experiencing different long-term grazing pressures were selected along a grazing intensity gradient. Within each site, two representative areas were chosen, and three 30 x 30 m macroplots were established. Plant canopy cover and functional characteristics were sampled in May 2021, corresponding to peak plant growth. Functional diversity was assessed using plant performance characteristics like specific leaf area index, leaf length, leaf nitrogen, leaf phosphorus, and growth form. Species diversity indices (species richness, Shannon-Evenness, and Shannon diversity) and functional diversity indices (Quadratic Entropy Rao, Functional Richness, Functional Evenness, and Functional Dispersion) were calculated using vegan and FD packages in R software (version 4.3.0). LFA software was used to analyze data from 162 patches and the space between patches (interpatch) to obtain three functional characteristics: stability, infiltration, and nutrient cycling. Correlations and univariate regressions were performed using ggcorrplot, ggpubr, and ggpmisc packages in R to establish relationships between diversity indices, functional diversity indices, and LFA functionalities.
Results: A positive and significant relationship was found between the nutrients index, Functional Evenness, and community-weighted mean leaf length (R² = 0.3). Landscape infiltration showed a stronger positive and significant association (P < 0.05) with Functional Evenness, Functional Dispersion, Quadratic Entropy Rao, and community-weighted mean leaf nitrogen (R² = 0.4) compared to Shannon diversity, Functional Richness, and community-weighted mean leaf length (R² = 0.3). The landscape stability index exhibited a positive and significant relationship (P < 0.05) with biodiversity indices (species richness and Shannon diversity), functional diversity indices based on multiple characteristics (Functional Richness, Functional Evenness, Functional Dispersion, and Quadratic Entropy Rao), and functional diversity indices based on single characteristics (community-weighted mean of leaf phosphorus, specific leaf area, and perennial grass), while displaying a negative and significant relationship (R² = 0.5) with the community-weighted mean of perennial forbs.
Conclusion: The positive correlations observed between plant diversity and functional diversity metrics with LFA functional characteristics suggest their potential application in rangeland condition assessment. The complex interactions between these indices highlight the need for further research on integrating them into a robust assessment protocol applicable across different climatic regions. This study opens doors for developing a practical method for evaluating rangeland health using quantitative biodiversity and functional diversity indicators.
Methodology: Three rangeland sites experiencing different long-term grazing pressures were selected along a grazing intensity gradient. Within each site, two representative areas were chosen, and three 30 x 30 m macroplots were established. Plant canopy cover and functional characteristics were sampled in May 2021, corresponding to peak plant growth. Functional diversity was assessed using plant performance characteristics like specific leaf area index, leaf length, leaf nitrogen, leaf phosphorus, and growth form. Species diversity indices (species richness, Shannon-Evenness, and Shannon diversity) and functional diversity indices (Quadratic Entropy Rao, Functional Richness, Functional Evenness, and Functional Dispersion) were calculated using vegan and FD packages in R software (version 4.3.0). LFA software was used to analyze data from 162 patches and the space between patches (interpatch) to obtain three functional characteristics: stability, infiltration, and nutrient cycling. Correlations and univariate regressions were performed using ggcorrplot, ggpubr, and ggpmisc packages in R to establish relationships between diversity indices, functional diversity indices, and LFA functionalities.
Results: A positive and significant relationship was found between the nutrients index, Functional Evenness, and community-weighted mean leaf length (R² = 0.3). Landscape infiltration showed a stronger positive and significant association (P < 0.05) with Functional Evenness, Functional Dispersion, Quadratic Entropy Rao, and community-weighted mean leaf nitrogen (R² = 0.4) compared to Shannon diversity, Functional Richness, and community-weighted mean leaf length (R² = 0.3). The landscape stability index exhibited a positive and significant relationship (P < 0.05) with biodiversity indices (species richness and Shannon diversity), functional diversity indices based on multiple characteristics (Functional Richness, Functional Evenness, Functional Dispersion, and Quadratic Entropy Rao), and functional diversity indices based on single characteristics (community-weighted mean of leaf phosphorus, specific leaf area, and perennial grass), while displaying a negative and significant relationship (R² = 0.5) with the community-weighted mean of perennial forbs.
Conclusion: The positive correlations observed between plant diversity and functional diversity metrics with LFA functional characteristics suggest their potential application in rangeland condition assessment. The complex interactions between these indices highlight the need for further research on integrating them into a robust assessment protocol applicable across different climatic regions. This study opens doors for developing a practical method for evaluating rangeland health using quantitative biodiversity and functional diversity indicators.
Keywords: Biodiversity indices, Range condition, Landscape Function Analysis, Tang e Sayad protected area
Type of Study: Research |
Subject:
Special
Received: 2024/01/1 | Accepted: 2024/04/22 | Published: 2024/07/31
Received: 2024/01/1 | Accepted: 2024/04/22 | Published: 2024/07/31
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