Results 111 to 120 of about 64,103 (258)
Ecography, EarlyView.Predator–prey interactions are vital to ecosystem functioning but may be disrupted by climate change. We investigated a food‐web network involving three owl species over 24 years in a semi‐arid ecosystem at Bosque Fray Jorge National Park, Chile.
Jazmin M. Quiroz‐Calizaya +12 more
wiley +1 more source
Topography constrains the climatic response of treeline migration in Taiwan's subalpine forests
Ecography, EarlyView.Treelines are moving upslope, but the rates and drivers differ among different regions, globally. Many studies have examined the relationship between treeline movement and climate change, particularly rising temperature, while the role of topographical factors has received much less attention, despite the longstanding recognition of its importance.
Kuan‐Yu Chen +3 more
wiley +1 more source
Ecography, EarlyView.Ecosystem dynamics are shaped by interacting top‐down and bottom‐up processes, yet their relative importance may vary through time following disturbances such as disease outbreaks and changes in apex predator communities. Using a 52‐year time series in south‐central Sweden, we examined how disease, apex predators, and prey availability jointly impact a
Camilla Wikenros +4 more
wiley +1 more source
Impact of Severe Winter Weather on Operations of a Radiation Oncology Department. [PDF]
Adv Radiat OncolFekrmandi F +4 more
europepmc +1 more source
Forecasting heart failure: Seasonal alignment of heart failure outcomes in New York
ESC Heart Failure, Volume 12, Issue 2, Page 819-831, April 2025.Abstract Background Seasonal variations have been observed in heart failure (HF) hospitalization. Numerous explanatory mechanisms have been proposed, but no prior studies have examined potential contributors directly. Our objective was to identify specific factors that could contribute to seasonal variability using a large longitudinal dataset of HF ...
Prerna Gupta +5 more
wiley +1 more source
Energy Science &Engineering, EarlyView.This graphical abstract illustrates a reproducible pipeline that combines gradient‐boosting‐based feature selection with a CNN–BiLSTM–Transformer model to forecast solar irradiance across multi‐site satellite and ground datasets, delivering robust, high‐accuracy predictions that support sustainable grid planning and reliable PV integration.
Muhammad Farhan Hanif +5 more
wiley +1 more source
Graph Neural Network‐Based Prediction of Building Energy Consumption
Energy Science &Engineering, EarlyView.A graph neural network that encodes a multi‐zone building as a graph accurately predicts hourly cooling and heating loads across three distinct climates, outperforming Random Forest and XGBoost baselines and serving as a fast surrogate to EnergyPlus simulations for scalable building energy management.
Ali Maboudi Reveshti +4 more
wiley +1 more source
Energy Science &Engineering, EarlyView.This study integrates climatic simulations with machine learning to predict solar and wind energy across Iraq. Results show Random Forest excels for solar (R2 = 0.98) and neural networks for wind (R2 = 0.97), enabling a practical web tool for renewable energy planning. ABSTRACT Driven by the global shift away from fossil fuels, solar and wind resources
Bassam Musheer Kareem +3 more
wiley +1 more source