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Climate change is shifting the phenology of migratory animals earlier; yet an understanding of how climate change leads to variable shifts across populations, species and communities remains hampered by limited spatial and taxonomic sampling. In this study, we used a hierarchical Bayesian model to analyse 88,965 site-specific arrival dates from 222 bird species over 21 years to investigate the role of temperature, snowpack, precipitation, the El-Niño/Southern Oscillation and the North Atlantic Oscillation on the spring arrival timing of Nearctic birds. Interannual variation in bird arrival on breeding grounds was most strongly explained by temperature and snowpack, and less strongly by precipitation and climate oscillations. Sensitivity of arrival timing to climatic variation exhibited spatial nonstationarity, being highly variable within and across species. A high degree of heterogeneity in phenological sensitivity suggests diverging responses to ongoing climatic changes at the population, species and community scale, with potentially negative demographic and ecological consequences.
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http://dx.doi.org/10.1111/ele.14526 | DOI Listing |
Sci Total Environ
September 2025
Center for Environmental Studies and Research, Sultan Qaboos University, Muscat, Oman. Electronic address:
Droughts rank among the most devastating natural disasters, particularly in arid regions such as Oman. However, traditional drought assessment based on stationarity may not be applicable under climate change. Moreover, most previous studies have been point-based, relying on station observations without capturing the spatial variability of drought.
View Article and Find Full Text PDFBrain Sci
August 2025
College of Computer Science and Technology, Changchun University, Changchun 130022, China.
Background: Brain-computer interfaces (BCIs) based on motor imagery (MI) offer promising solutions for motor rehabilitation and communication. However, electroencephalography (EEG) signals are often characterized by low signal-to-noise ratios, strong non-stationarity, and significant inter-subject variability, which pose significant challenges for accurate decoding. Existing methods often struggle to simultaneously model the spatial interactions between EEG channels, the local fine-grained features within signals, and global semantic patterns.
View Article and Find Full Text PDFFront Public Health
August 2025
Research Centre of Light Alloy Net Forming, Shanghai Jiao Tong University, Shanghai, China.
This study examines COVID-19 transmission across 3,142 U.S. counties using a truncated dataset from March to September 2020.
View Article and Find Full Text PDFSci Rep
August 2025
College of Landscape and Horticulture, Heilongjiang Bayi Agricultural University, Da Qing, 163319, China.
Heilongjiang Province, a key ecological barrier in Northeast China, is crucial for regional ecosystem stability. Previous vegetation index research in this region primarily focused on annual or growing-season scales, without comprehensive comparisons of seasonal and interannual variations. This study addresses this gap by analyzing spatiotemporal vegetation dynamics and their driving forces in Heilongjiang Province using MODIS data (2000-2021).
View Article and Find Full Text PDFSci Data
August 2025
Programa de Investigación en Cambio Climático, Universidad Nacional Autónoma de México, Av. Universidad 3004, Copilco Universidad, Coyoacán, 04510, Ciudad de México, CDMX, Mexico.
In this paper we present GeoMIP-pattern, the first global geoengineering pattern scaling dataset. This dataset is useful to generate custom solar radiation modification scenarios and to emulate the GeoMIP model output with low data volume. Temperature, precipitation, and relative humidity patterns are derived from ScenarioMIP SSP5-8.
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