Taxonomic and structural diversity indices predict soil carbon storage better than functional diversity indices along a dieback intensity gradient in semi-arid oak forests

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Английский. The use of structural diversity indices can be efficient tools to increase understanding of changes in soil carbon storage as a key ecosystem function along the oak dieback intensity Taxonomic and structural diversity indices predict soil carbon storage better than functional diversity indices along a dieback intensity gradient in semi-arid oak forests.Investigating the relationships between diversity indices and ecosystem functions within the26 mass‐ratio and niche complementary hypotheses is still a challenging issue in terrestrial27 ecology. These relationships have not been studied along a dieback gradient of disturbance in28 semiarid forest ecosystems. To fill this gap, we investigated the relationships between a main29 ecosystem function -soil carbon storage- and various diversity indices along a dieback intensity30gradient (no, low, moderate or high dieback intensity) in protected or intensively managed31 mixed oak forests in western Iran. We used different diversity approaches and calculated the32 functional divergence index (FDvar), community weighted mean trait values; CWM, taxonomic33 diversity indices (richness, Shannon–Wiener diversity and evenness) and structural diversity34 indices (MI: mingling index, HD: height differentiation, DD: diameter differentiation). Soil35carbon storage was significantly influenced by the type of management, the intensity of dieback36 and their interactions and was higher in the protected areas (95.90 ± 4.62 ton ha- 1) than in the37 intensively managed areas (76.52 ± 2.04 ton ha-1). It showed a humped-shaped pattern along38 the dieback intensity gradient in the protected areas, as it peaked at the low dieback intensity39 (122.47 ± 10.12 ton ha-1), indicating that soil function was maximized at a low disturbance40level. Soil carbon storage was positively and significantly correlated with all structural and41 taxonomic diversity indices, except for evenness, but negatively with most functional42 composition indices (CWM of LNC: leaf nitrogen concentration, H: mean of woody species43 height and LDMC: leaf dry-matter content). It was best predicted by a structural index44 (Mingling index: R2=0.214) followed by a taxonomic index (species richness, R2=0.173) and a45CWM index (CWM LDMC, R2=0.158). Our results emphasize the role played by the diversity46 indices to predict ecosystem functions in contrasted management conditions and along a47 dieback gradient. They also provide evidence to support both the mass‐ratio and niche48 complementary hypotheses.