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Alfalfa ( L.) establishment is an effective strategy for grassland reconstruction in degraded ecosystems. However, the mechanisms underlying vegetation succession in reconstructed grasslands following alfalfa establishment remain elusive. In this study, we investigated vegetation community, soil quality and rhizosphere microbiota dynamics across a reconstructed grassland chronosequence in the loess region of Northwest China. A space-for-time substitution method was used to evaluate grassland vegetation coverage and alfalfa production performance in nine stands of different ages (1-50 years old). High-throughput sequencing was conducted to characterise rhizosphere microbial communities associated with alfalfa. The plant heights, yields and stem-to-leaf ratios of alfalfa all peaked in the 7-year-old stand and then decreased in older stands, with replacing alfalfa as the dominant species in the 50-year-old stand. Soil bulk density and major nutrient contents were highest in the artificial grassland (1-10 years). Soil enzyme activities (., urease and sucrase) were enhanced in the transitional grassland (10-30 years), accompanied by enrichment of potentially beneficial microbial taxa (., Actinobacteria and ) and functional fungi (., saprotrophs and symbiotrophs) in the rhizosphere. Soil water content, total porosity and rhizosphere microbial diversity reached their maximum levels in the natural grassland (>30 years). The results indicate that alfalfa establishment alters soil structure and nutrient status in the short term, creating an optimal rhizosphere micro-environment. The improved soil conditions and rhizosphere microbiota are favourable for subsequent establishment of native grass species, leading to the formation of a stable semi-natural grasslands.
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http://dx.doi.org/10.7717/peerj.18723 | DOI Listing |
PeerJ
December 2024
College of Forestry and Prataculture, Ningxia University, Yinchuan, China.
Alfalfa ( L.) establishment is an effective strategy for grassland reconstruction in degraded ecosystems. However, the mechanisms underlying vegetation succession in reconstructed grasslands following alfalfa establishment remain elusive.
View Article and Find Full Text PDFBiotechnol J
December 2024
Instituto de Biología Molecular y Celular de Plantas (IBMCP), Universitat Politècnica de Valencia-Consejo Superior de Investigaciones Científicas, Valencia, Spain.
Virus-induced gene silencing (VIGS) represents a particularly relevant tool in agricultural species for studying gene functionality. This study presents a novel approach for utilizing viruses belonging to the 30K family of movement proteins (MPs) as VIGS vectors. The method described here employs smaller inserts (54 bp or less) than those commonly used (100-500 bp).
View Article and Find Full Text PDFJ Environ Manage
December 2024
CSIC, Global Ecology Unit CREAF-CSIC-UAB, Bellaterra, Barcelona, Catalonia, Spain; CREAF, Cerdanyola del Vallès, Barcelona, Catalonia, Spain.
Adequate revegetation of abandoned farmland acts as a defence against desertification and soil loss, and can help remove carbon dioxide in the atmosphere, thereby playing an important role in regulating regional climate change. Legume, a nitrogen-fixation species, which could effectively improve vegetation coverage to control soil erosion, was widely used for revegetation. However, the dynamics of soil and plant development after legume introduction on abandoned farmland remain unclear.
View Article and Find Full Text PDFMicroorganisms
October 2024
College of Veterinary Medicine, Gansu Agricultural University, Lanzhou 730070, China.
Front Plant Sci
November 2024
College of Resources Environment and Life Sciences, Ningxia Normal University, Guyuan, China.
Leaf area index (LAI) of alfalfa is a crucial indicator of its growth status and a predictor of yield. The LAI of alfalfa is influenced by environmental factors, and the limitations of non-linear models in integrating these factors affect the accuracy of LAI predictions. This study explores the potential of classical non-linear models and deep learning for predicting alfalfa LAI.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!