Due to the activity of methane-oxidizing bacteria, forest soils are usually net sinks for the greenhouse gas methane (CH4). Despite several hints that CH4 balances might be influenced by vegetation, there are only few investigations dealing with this connection. Therefore, we studied this soil-plant-microbe interaction by using mesocosm experiments with forest soil and Larix decidua, a common coniferous tree species within the Alps. Gas measurements showed that the presence of L. decidua significantly reduced CH4 oxidation of the forest soil by ∼10% (-0.95 µmol m-2 h-1 for soil vs -0.85 µmol m-2 h-1 for soil plus L. decidua) leading to an increased net CH4 balance. Increased light intensity was used to intensify the influence of the plant on the soil's CH4 balance. The increase in light intensity strengthened the effect of the plant and led to a greater reduction of CH4 oxidation. Besides, we examined the impact of L. decidua and light on the abundance of methanogens and methanotrophs in the rhizosphere as compared with bulk soil. The abundance of both methane-oxidizing bacteria and methanogenic archaea was significantly increased in the rhizosphere compared with bulk soil but no significant response of methanogens and methanotrophs upon light exposure was established.
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http://dx.doi.org/10.1093/femsle/fnz259 | DOI Listing |
BMC Plant Biol
January 2025
Hebei Agricultural University, Baoding, China.
Background: Nitrogen (N) deposition has become a major driving factor affecting the balance of terrestrial ecosystems, changing the soil environment, element balance and species coexistence relationships, driving changes in biodiversity and ecosystem structure and function. Human-induced nitrogen input leads to a high NH/ NO ratio in soil. However, relatively few studies have investigated the effects of different nitrogen sources on forest plant-microbial symbionts.
View Article and Find Full Text PDFJ Hazard Mater
December 2024
The Key Lab of Pollution Control and Ecosystem Restoration in Industry Clusters, Ministry of Education, School of Environment and Energy, South China University of Technology, Guangzhou, Guangdong 510006, PR China.
Microbe-mediated remediation becomes a desire method for removal of persistent organic pollutants (POPs) due to its eco-friendly and sustainable nature. The improvement of practical feasibility requires constructing comprehensive species pool, while it is still limited by the rapid recognition of potential bacterial resources from environment. Here, based on the relative abundances of bacterial OTUs and pollutant concentrations, we established indexes to assess their tolerance to organochlorine pesticides (OCPs) and flame retardants (FRs) that are atmospheric transported and naturally accumulated in forest soil via forest filter effect.
View Article and Find Full Text PDFBMC Plant Biol
January 2025
Guangxi Key Laboratory of Theory and Technology for Environmental Pollution Control, Guilin University of Technology, Guilin, 541004, China.
Background: Nutrient limitation is a universal phenomenon in terrestrial ecosystems. Root and mycorrhizal are critical to plant nutrient absorption in nutrient-limited ecosystems. However, how they are modified by N and P limitations with advancing vegetation successions in karst forests remains poorly understood.
View Article and Find Full Text PDFSci Rep
January 2025
College of Jilin Emergency Management, Changchun Institute of Technology, Changchun, 130012, China.
Globally, heavy metal (HM) soil pollution is becoming an increasingly serious concern. Heavy metals in soils pose significant environmental and health risks due to their persistence, toxicity, and potential for bioaccumulation. These metals often originate from anthropogenic activities such as industrial emissions, agricultural practices, and improper waste disposal.
View Article and Find Full Text PDFSci Rep
January 2025
ICFRE-Institute of Forest Genetics and Tree Breeding, Coimbatore, Tamil Nadu, India.
Evaluating high-throughput soil profile information is essential in safflower precision agriculture, as it facilitates efficient resource management and design of an experiment that promotes sustainable production. We collected soil from representative target environments (TE) of safflower cultivation and evaluated 14 soil physio-chemical features for constructing fine-resolution maps. The robustness, versatility, and predictive ability of two statistical learning models in correctly classifying the soil profile to clusters were tested.
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