Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

Despite the known collective contribution of above- (plants) and below-ground (soil fungi) biodiversity on multiple soil functions, how the associations among plant and fungal communities regulate soil multifunctionality (SMF) differentially remains unknown. Here, plant communities were investigated at 81 plots across a typical arid inland river basin, within which associated soil fungal communities and seven soil functions (nutrients storage and biological activity) were measured in surface (0-15 cm) and subsurface soil (15-30 cm). We evaluated the relative importance of species richness and biotic associations (reflected by network complexity) on SMF. Our results demonstrated that plant species richness and plant-fungus network complexity promoted SMF in surface and subsurface soil. SMF in two soil layers was mainly determined by plant-fungus network complexity, mean groundwater depth and soil variables, among which plant-fungus network complexity played a crucial role. Plant-fungus network complexity had stronger effects on SMF in surface soil than in subsurface soil. We present evidence that plant-fungus network complexity surpassed plant-fungal species richness in determining SMF in surface and subsurface soil. Moreover, plant-fungal species richness could not directly affect SMF. Greater plant-fungal species richness indirectly promoted SMF since they ensured greater plant-fungal associations. Collectively, we concluded that interkingdom networks between plants and fungi drive SMF even in different soil layers. Our findings enhanced our knowledge of the underlying mechanisms that above- and below-ground associations promote SMF in arid inland river basins. Future study should place more emphasis on the associations among plant and microbial communities in protecting soil functions under global changes.

Download full-text PDF

Source
http://dx.doi.org/10.1111/mec.17184DOI Listing

Publication Analysis

Top Keywords

network complexity
24
species richness
20
plant-fungus network
20
subsurface soil
16
soil
15
arid inland
12
inland river
12
soil functions
12
smf surface
12
plant-fungal species
12

Similar Publications

Semantic composition allows us to construct complex meanings (e.g., "dog house", "house dog") from simpler constituents ("dog", "house").

View Article and Find Full Text PDF

This review article, developed by the EASD Global Council, addresses the growing global challenges in diabetes research and care, highlighting the rising prevalence of diabetes, the increasing complexity of its management and the need for a coordinated international response. With regard to research, disparities in funding and infrastructure between high-income countries and low- and middle-income countries (LMICs) are discussed. The under-representation of LMIC populations in clinical trials, challenges in conducting large-scale research projects, and the ethical and legal complexities of artificial intelligence integration are also considered as specific issues.

View Article and Find Full Text PDF

What are the key targets to improve quality of life among MSM living with HIV on antiretroviral therapy? A network analysis.

Qual Life Res

September 2025

Department of Epidemiology, School of Public Health, Cheeloo College of Medicine, Shandong University, 44 West Wenhua Road, Jinan, 250012, Shandong, China.

Purpose: The study aimed to assess the interconnection of quality of life (QoL) variables and identify key areas for which interventions could improve QoL among men who have sex with men (MSM) living with HIV on antiretroviral therapy (ART).

Methods: A cross-sectional study was conducted in Jinan of Shandong Province, between October to December 2020. Undirected network analyses were conducted to examine and visualize the interconnections between QoL variables among MSM living with HIV.

View Article and Find Full Text PDF

Background And Objectives: Older adults living with dementia are a heterogeneous group, which can make studying optimal medication management challenging. Unsupervised machine learning is a group of computing methods that rely on unlabeled data-that is, where the algorithm itself is discovering patterns without the need for researchers to label the data with a known outcome. These methods may help us to better understand complex prescribing patterns in this population.

View Article and Find Full Text PDF

Background: Ear canker in domestic rabbits is caused by infestations of non-burrowing parasitic mites, Psoroptes spp., but the specific species responsible for these infestations remains unclear. This study reports the clinical signs and performs the molecular characterization and phylogenetic analysis of Psoroptes ovis isolated from the ear canal of a domestic rabbit in South India.

View Article and Find Full Text PDF