AIMC Topic: Climate

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Climate and traits drive bark decomposition patterns at global scale.

Nature communications
Tree bark represents a large global carbon stock, comprising 2-20 % of woody biomass, and plays a distinct role in carbon and nutrient cycling. It is poorly understood how different abiotic and biotic drivers contribute to bark decomposition globally...

Assessing climatic and non-climatic habitat suitability of Haloxylon salicornicum (Moq.) Bunge ex Boiss using ensemble species distribution modelling coupled with analytic hierarchy process.

Environmental monitoring and assessment
Haloxylon salicornicum is a keystone shrub of the Indian arid zone, valued for dune stabilization, fodder, and ecosystem restoration, yet its climatic resilience remains poorly understood. This study assessed the ecological thresholds, current habita...

Climate stability and low population pressure predict peaceful interactions over 10,000 years of Central Andean history.

Science advances
As anthropogenic climate change threatens to destabilize global societies and ecosystems, anticipating likely human responses becomes ever more urgent. A key global initiative is the promotion of peaceful relations. Nonetheless, studies that systemat...

Uncovering the Influence of Land Cover and Climate Extremes on Wildfire Smoke PM in the United States Using Explainable Artificial Intelligence.

Environmental science & technology
Fine particulate matter (PM) from wildfire smoke has emerged as a significant environmental health threat in the United States (U.S.), yet the combined roles of climate extremes and land cover in shaping wildfire smoke PM exposure remain poorly under...

Predicting coastal erosion susceptibility in Bangladesh under climate scenario via machine learning techniques.

PloS one
Using advanced machine learning methods along with geospatial data and climate estimates, this study found areas in Bangladesh that are likely to experience coastal erosion. Twenty important factors were looked at, such as meteorological, geographica...

An interpretable machine learning approach based on SHAP, Sobol and LIME values for precise estimation of daily soybean crop coefficients.

Scientific reports
Increasing water scarcity and climate variability have intensified the need for precise agricultural irrigation management. Accurate estimation of crop coefficients (Kc) is critical for determining crop water requirements, especially in arid and semi...

Variables for habitat and vertebrate hosts of Ixodes scapularis are the best ecological predictors of the spatial spread of Lyme disease in the United States (2010-2019).

Parasites & vectors
BACKGROUND: Lyme disease (LD) is a major public health concern in North America. The incidence of LD has increased in part due to the rapid expansion of Ixodes scapularis infected with Borrelia burgdorferi sensu lato (Bb), the causative agent of LD. ...

Machine learning framework for forecasting air pollution: Evaluating seasonal and climatic influences in Istanbul, Turkey.

PloS one
Air pollution, driven by seasonal and meteorological variations, poses a significant threat to public health and urban sustainability. Despite numerous forecasting approaches, the influence of seasonal patterns on air pollutant levels remains underex...

Genetic regulations of citrus flowering: insights towards climatic factors and modern biotechnological approaches.

Planta
The review highlights the intricate relationship between genetic and molecular mechanisms that regulate floral development and responses in citrus under diverse climatic conditions. Citrus, the world's top traded and third most produced fruit crop, h...

Human activities and climate override local catchment characteristics in explaining long-term phytoplankton trends in prairie lakes.

The Science of the total environment
Lakes across the globe are experiencing growing ecological pressure from climate change and human activities. In prairie regions, these pressures often result in shifts in phytoplankton abundance, a key indicator of water quality. Yet identifying the...