AIMC Topic: Climate Change

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Association of precipitation extremes and crops production and projecting future extremes using machine learning approaches with CMIP6 data.

Environmental science and pollution research international Sep 2, 2024
Precipitation extremes have surged in frequency and duration in recent decades, significantly impacting various sectors, including agriculture, water resources, energy, and public health worldwide. Pakistan, being highly susceptible to climate change...
Machine Learning Agriculture Crops, Agricultural Rain Crop Production Pakistan Climate Change
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From data to harvest: Leveraging ensemble machine learning for enhanced crop yield predictions across Canada amidst climate change.

The Science of the total environment Aug 23, 2024
Accurate crop yield predictions are crucial for farmers and policymakers. Despite the widespread use of ensemble machine learning (ML) models in computer science, their application in crop yield prediction remains relatively underexplored. This study...
Agriculture Climate Change Crops, Agricultural Machine Learning Canada
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Assessing spirlin Alburnoides bipunctatus (Bloch, 1782) as an early indicator of climate change and anthropogenic stressors using ecological modeling and machine learning.

The Science of the total environment Aug 22, 2024
Combining single-species ecological modeling with advanced machine learning to investigate the long-term population dynamics of the rheophilic fish spirlin offers a powerful approach to understanding environmental changes and climate shifts in aquati...
Cyprinidae Population Dynamics Climate Change Animals Ecosystem Machine Learning Environmental Monitoring
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Reevaluating the Drivers of Fertilizer-Induced NO Emission: Insights from Interpretable Machine Learning.

Environmental science & technology Aug 20, 2024
Direct nitrous oxide (NO) emissions from fertilizer application are the largest anthropogenic source of global NO, but the factors influencing these emissions remain debated. Here, we compile 1134 observations of fertilizer-induced NO emission factor...
Soil Climate Change Nitrous Oxide Fertilizers Machine Learning
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Exploring the response and prediction of phytoplankton to environmental factors in eutrophic marine areas using interpretable machine learning methods.

The Science of the total environment Aug 17, 2024
Coastal marine areas are frequently affected by human activities and face ecological and environmental threats, such as algal blooms and climate change. The community structure of phytoplankton-primary producers in marine ecosystems-is highly sensiti...
Machine Learning Climate Change Salinity Eutrophication Temperature Environmental Monitoring Ecosystem Phytoplankton
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Examining optimized machine learning models for accurate multi-month drought forecasting: A representative case study in the USA.

Environmental science and pollution research international Aug 13, 2024
The Colorado River has experienced a significant streamflow reduction in recent decades due to climate change, resulting in pronounced hydrological droughts that pose challenges to the environment and human activities. However, current models struggl...
Climate Change Droughts Models, Theoretical Rivers Forecasting Machine Learning United States
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Long-term trend forecast of chlorophyll-a concentration over eutrophic lakes based on time series decomposition and deep learning algorithm.

The Science of the total environment Aug 10, 2024
Long-term trend forecast of chlorophyll-a concentration (Chla) holds significant implications for eutrophication management and pollution control planning on lakes, especially under the background of climate change. However, it is a challenging task ...
Climate Change Chlorophyll Chlorophyll A Environmental Monitoring Seasons Forecasting Eutrophication Deep Learning China Lakes
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Investigating the impact of climate variables on the organic honey yield in Turkey using XGBoost machine learning.

Journal of the science of food and agriculture Aug 9, 2024
BACKGROUND: The Turkish organic honey industry, a major player in the global market, faces challenges due to climate fluctuations. Understanding the influence of climate factors on honey production is vital for sustainable farming and economic stabil...
Machine Learning Organic Agriculture Wind Animals Beekeeping Temperature Climate Change Turkey Honey Humidity Bees
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An integrated deep learning approach for modeling dissolved oxygen concentration at coastal inlets based on hydro-climatic parameters.

Journal of environmental management Aug 7, 2024
Climate change has a significant impact on dissolved oxygen (DO) concentrations, particularly in coastal inlets where numerous human activities occur. Due to the various water quality (WQ), hydrological, and climatic parameters that influence this ph...
Climate Change Oxygen Water Quality Deep Learning Neural Networks, Computer Environmental Monitoring
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Monitoring the Spatial Distribution of Cover Crops and Tillage Practices Using Machine Learning and Environmental Drivers across Eastern South Dakota.

Environmental management Jul 29, 2024
The adoption of conservation agriculture methods, such as conservation tillage and cover cropping, is a viable alternative to conventional farming practices for improving soil health and reducing soil carbon losses. Despite their significance in miti...
Climate Change Crops, Agricultural Glycine max South Dakota Conservation of Natural Resources Environmental Monitoring Machine Learning Zea mays Agriculture
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