AIMC Topic: Climate Change

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Flash droughts threaten global managed forests.

Nature communications
Flash droughts, characterized by rapid onset and increasing frequency, pose significant threats to ecosystem stability and function. However, there remains no global consensus regarding forest responses to flash droughts. Here, using a reconstructed ...

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...

Anaerobic microbial degradation of persistent organic pollutants in aquatic sediments: implications of climate change.

Archives of microbiology
Persistent organic pollutants (POPs) are harmful chemicals that resist degradation and remain in the environment for a long time. These pollutants originate from various sources, such as industrial, agricultural, and waste disposal. They contaminate ...

An Integrated Machine Learning and Remote Sensing Method for Predicting Cyanobacterial Blooms: A Case Study in China's lakes along a large-scale water diversion project.

Environmental management
Cyanobacterial blooms in lakes are a complex and challenging environmental issue worldwide. However, many existing studies on cyanobacterial bloom prediction were constrained by limited data availability, which poses significant challenges to the dev...

Four decades of satellite observations reveal climate-driven shifts and spatial heterogeneity in shallow lake Chlorophyll-a dynamics.

Water research
Shallow lakes worldwide face escalating pressures from eutrophication and climate change, yet comprehensive monitoring of Chlorophyll-a (Chl-a) spatiotemporal dynamics remains challenging due to the high costs and logistical constraints of traditiona...

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...

Decoding climate-induced phytoplankton dynamics in a tropical macrotidal estuary using explainable machine learning.

The Science of the total environment
Phytoplankton communities in tropical macrotidal estuaries are highly sensitive to hydroclimatic variability, particularly during extreme El Niño-Southern Oscillation (ENSO) events. This study assessed ENSO effects on phytoplankton dynamics in the Sã...

Integrating climate scenarios and advanced modeling to predict freshwater fish invasions: insights from Carassius species in Iran.

Scientific reports
Freshwater ecosystems are increasingly imperiled by the dual pressures of biological invasions and climate change, necessitating robust predictive frameworks for effective management. This study integrates advanced ensemble machine learning (EML) wit...

Machine learning applied to global scale species distribution models.

Scientific reports
Species Distribution Models (SDMs) are widely used in ecology to analyze historical and future patterns of marine species distributions. Given the growing impact of climate change, predicting potential shifts in species ranges has become a key challe...