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Peatlands are wetland ecosystems with great significance as natural habitats and as major global carbon stores. They have been subject to widespread exploitation and degradation with resulting losses in characteristic biota and ecosystem functions such as climate regulation. More recently, large-scale programmes have been established to restore peatland ecosystems and the various services they provide to society. Despite significant progress in peatland science and restoration practice, we lack a process-based understanding of how soil microbiota influence peatland functioning and mediate the resilience and recovery of ecosystem services, to perturbations associated with land use and climate change. We argue that there is a need to: in the short-term, characterise peatland microbial communities across a range of spatial and temporal scales and develop an improved understanding of the links between peatland habitat, ecological functions and microbial processes; in the medium term, define what a successfully restored 'target' peatland microbiome looks like for key carbon cycle related ecosystem services and develop microbial-based monitoring tools for assessing restoration needs; and in the longer term, to use this knowledge to influence restoration practices and assess progress on the trajectory towards 'intact' peatland status. Rapid advances in genetic characterisation of the structure and functions of microbial communities offer the potential for transformative progress in these areas, but the scale and speed of methodological and conceptual advances in studying ecosystem functions is a challenge for peatland scientists. Advances in this area require multidisciplinary collaborations between peatland scientists, data scientists and microbiologists and ultimately, collaboration with the modelling community. Developing a process-based understanding of the resilience and recovery of peatlands to perturbations, such as climate extremes, fires, and drainage, will be key to meeting climate targets and delivering ecosystem services cost effectively.
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http://dx.doi.org/10.1016/j.scitotenv.2020.143467 | DOI Listing |
Glob Chang Biol
September 2025
Department of Agronomy, Purdue University, West Lafayette, Indiana, USA.
Understanding how interactive management practices and climatic behavior influence soybean [Glycine max (L.) Merr.] productivity is imperative to inform future production systems under changing climate.
View Article and Find Full Text PDFAdv Child Dev Behav
September 2025
University of California, Davis, CA, USA.
Here, we will review the developmental literature on how infants and young children learn about emotions. We take a process-based perspective, highlighting how the protracted trajectory of emotional development unfolds concurrently with changes in children's cognitive abilities, and how variability based on context, culture, and experience shape this trajectory over time. We will also emphasize the role of input into this development, a factor that has often been ignored.
View Article and Find Full Text PDFSci Data
September 2025
School of the Environment, the University of Queensland, Brisbane, 4072, Australia.
Value, technology, and policy are three interactive societal factors affecting the willingness, capacity, and formal rules of human interactions with water. Existing human-water models generally neglect the dynamic and accumulated processes of these factors, failing to explain the societal causes of changes in water practices. Here we developed nine process-based quantitative datasets of Value-Technology-Policy regarding water.
View Article and Find Full Text PDFSci Total Environ
August 2025
Department of Earth Sciences (DST), University of Florence (UNIFI), Via G. La Pira 4, Florence 50121, Italy.
We investigate the spatial patterns of major geo-hydrological disasters across Italy (for which national-level emergencies were issued), using an innovative target variable (Months in Emergency State - MES), which captures both the recurrence of disasters and the persistence of their impacts. A total of 62 potential predisposing factors were considered, covering four different fields: environmental, territorial planning, soil sealing, and socio-economic. A three-step feature selection process based on Pearson correlation, multicollinearity analysis, and ReliefF algorithm, was applied to reduce redundancy and identify the most relevant predictors (18), which were used in a CatBoost regression model.
View Article and Find Full Text PDFChildren (Basel)
August 2025
Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA.
Exposure-based cognitive behavioral therapy (Ex-CBT) is widely seen as the gold-standard treatment for anxiety and obsessive-compulsive disorder (OCD). Yet, minoritized youth are underrepresented in efficacy studies, raising questions about the applicability of Ex-CBT to minoritized youth. Effectiveness data suggest systematic adaptation of Ex-CBT to address youth culture and context is likely needed, and many clinicians make adaptations and augmentations in practice.
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