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Roots are the interface between the plant and the soil and play a central role in multiple ecosystem processes. With intensification of agricultural practices, rhizosphere processes are being disrupted and are causing degradation of the physical, chemical and biotic properties of soil. However, cover crops, a group of plants that provide ecosystem services, can be utilised during fallow periods or used as an intercrop to restore soil health. The effectiveness of ecosystem services provided by cover crops varies widely as very little breeding has occurred in these species. Improvement of ecosystem service performance is rarely considered as a breeding trait due to the complexities and challenges of belowground evaluation. Advancements in root phenotyping and genetic tools are critical in accelerating ecosystem service improvement in cover crops. In this study, we provide an overview of the range of belowground ecosystem services provided by cover crop roots: (1) soil structural remediation, (2) capture of soil resources and (3) maintenance of the rhizosphere and building of organic matter content. Based on the ecosystem services described, we outline current and promising phenotyping technologies and breeding strategies in cover crops that can enhance agricultural sustainability through improvement of root traits.
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http://dx.doi.org/10.1111/pce.14247 | DOI Listing |
Glob Chang Biol
September 2025
Chair of Silviculture, Faculty of Environment and Natural Resources, Institute of Forest Sciences, University of Freiburg, Freiburg, Germany.
Mixed-species forests are proposed to enhance tree resistance and resilience to drought. However, growing evidence shows that tree species richness does not consistently improve tree growth responses to drought. The underlying mechanisms remain uncertain, especially under unprecedented multiyear droughts.
View Article and Find Full Text PDFEnviron Monit Assess
September 2025
School of Civil Engineering, Putian University, Putian City, 351100, China.
Land degradation (LD) is a critical environmental challenge caused by human activities and climate change. Reversing degraded land requires effective LD monitoring. The UN Sustainable Development Goal (SDG) indicator 15.
View Article and Find Full Text PDFNat Microbiol
September 2025
Division of Computational Pathology, Brigham and Women's Hospital, Boston, MA, USA.
Although dynamical systems models are a powerful tool for analysing microbial ecosystems, challenges in learning these models from complex microbiome datasets and interpreting their outputs limit use. We introduce the Microbial Dynamical Systems Inference Engine 2 (MDSINE2), a Bayesian method that learns compact and interpretable ecosystems-scale dynamical systems models from microbiome timeseries data. Microbial dynamics are modelled as stochastic processes driven by interaction modules, or groups of microbes with similar interaction structure and responses to perturbations, and additionally, noise characteristics of data are modelled.
View Article and Find Full Text PDFJ Acoust Soc Am
September 2025
Applied Physics Laboratory, University of Washington, Seattle, Washington 98105, USA.
Echolocating bats provide vital ecosystem services and can be monitored effectively using passive acoustic monitoring (PAM) techniques. Duty-cycle subsampling is widely used to collect PAM data at regular ON/OFF cycles to circumvent battery and storage capacity constraints for long-term monitoring. However, the impact of duty-cycle subsampling and potential detector errors on estimating bat activity has not been systematically investigated for bats.
View Article and Find Full Text PDFNurs Health Sci
September 2025
School of Nursing and Midwifery, Centre for Quality and Patient Safety, Institute for Health Transformation, Deakin University, Geelong, Victoria, Australia.
Caesarean section (CS) rates are increasing globally. We aimed to understand stakeholders' perspectives on factors driving CS in pregnancy care to inform areas for intervention. Stakeholders from five health services participated in three Group Model Building workshops to identify the drivers of CS and intervention opportunities.
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