Forest conservation mediating soil quality relationship with diversity of various plant layers in the biosphere of Arasabran, Iran

• Published in: The Science of the total environment 2024-06, Vol.928, p.172475-172475, Article 172475
• Main Authors: Sasanifar, Samira, Alijanpour, Ahmad, Banj Shafiei, Abbas, Eshaghi Rad, Javad, Molaei, Morteza
• Format: Article
• Language: English
• Subjects: Biodiversity; biodiversity conservation; biosphere; clay; conservation areas; Conservation of Natural Resources - methods; data collection; ecological function; ecosystems; Efficiency index; Environmental Monitoring - methods; forest conservation; forest litter; Forests; gravel; Iran; Overall sensitivity index; Plants; sand; Sensitivity index; silt; Soil - chemistry; soil quality; Soil quality index; species; Trees; vegetation index
• ISSN: 0048-9697; 1879-1026
• DOI: 10.1016/j.scitotenv.2024.172475

The link between biodiversity and ecosystem multi-functionality is an ongoing concern in ecological studies. Ecologists have focused on soil quality (SQ) as an ecosystem function and its relationship to biodiversity. Developing an appropriate and sensitive soil quality index (SQI) is critical, but it is severely restricted particularly in the forests. This study determined the most appropriate SQI for both protected and unprotected areas of Arasbaran biosphere reserve forests (Northwest Iran), as well as its relationship to the diversity of three layers of forest plant species (tree, tree regeneration, and forest floor plant cover), NDVI index, and litter amount. Three approaches were utilized to establish SQI for two types of soil data sets, including total data set (TDS) (pH, EC, SP. OC, caco3, clay, silt, sand, N, P, K, BD, gravel, C·N) and the minimum data sets (MDS) (SP. OC, clay, silt, N, K, BD, C·N): (1) SQI-1 (simple additive), (2) SQI-2 (Nemero quality index), and (3) SQI-3 (weighted additive modeled). Three SQI strategies were assessed using three different methods: Overall Sensitivity Index, Efficiency Index and Sensitivity Index. The findings revealed that the SQI-3 is the best SQI for employing only a limited number of soil properties (MDS). The findings revealed that the SQI-3 has a positive and significant relationship with the Evenness-tree and Taxa-Regeneration in the protected region (P-Value: 0.02). In contrast, the SQI-3 has a negative correlation with the NDVI (Normalized Difference vegetation Index) (P-Value: 0.02) but a positive significant relationship with the litter and Taxa-Grass indicators in the unprotected region (P-Value: 0.00). The study's findings demonstrated that forest preservation affected the link between the SQI and the studied parameters. As a result, it is concluded that biodiversity-ecosystem function is impacted by management changes and cannot be maintained constant under varied management conditions. This shift in the links between plant and SQ emphasizes the fact that plants biodiversity loss and SQ can have particularly severe consequences in non-protective conditions, necessitating biodiversity conservation measures to mitigate the effects of conservation. [Display omitted] •This study shows that the weighted additive SQI model is suitable for evaluating the SQ of temperate deciduous forests.•There is a significant positive relationship between the SQI and the Taxa-regeneration and Evenness-tree indices in th