Division of labor among H3K4 methyltransferases defines distinct facets of homeostatic plasticity. [PDF]
Tsukahara T +8 more
europepmc +1 more source
Opportunities for targeted, small‐scale law reform in marine and coastal restoration
Across the globe, law reform is being considered as a mechanism to support, guide, and encourage the upscaling of ecological restoration. While high‐profile examples like the European Nature Restoration Law show the value of large‐scale law reform, this scale of law reform will not be feasible or politically tractable everywhere.
Justine Bell‐James +3 more
wiley +1 more source
Downscaling local distribution of cattle over Guadeloupe archipelago: An adapted method for disaggregating census data. [PDF]
Dufleit V +4 more
europepmc +1 more source
Monthly 0.05° winter months snow depth dataset for the Northern Hemisphere from 21 CMIP6 models. [PDF]
Lin S +5 more
europepmc +1 more source
Replicable Fine-Spatio-Temporal Climate Data for Long-Term Ecology in the Western Mediterranean. [PDF]
Romera-Romera D +3 more
europepmc +1 more source
Update of the Köppen-Geiger climate classification for EFSA PLH risk assessment. [PDF]
European Food Safety Authority (EFSA) +3 more
europepmc +1 more source
A High-Resolution Gridded Dataset for China's Monthly Sectoral Water Use. [PDF]
Zhang Y, Yin Y, Yin M, Zhang X.
europepmc +1 more source
Quantum Simulation Study of Ultrascaled Label-Free DNA Sensors Based on Sub-10 nm Dielectric-Modulated TMD FETs: Sensitivity Enhancement Through Downscaling. [PDF]
Tamersit K +3 more
europepmc +1 more source
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AbstractDownscaling is a fundamental procedure in the assessment of the future climate change impact at regional and watershed scales. Hence, it is important to investigate the spatial variability of the climate conditions that are constructed by various downscaling methods to assess whether each method can properly model the climate conditions at ...
S. Jang, M. L. Kavvas
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Empirical-Statistical Downscaling: Nonlinear Statistical Downscaling
2021Empirical-statistical downscaling (ESD) models use statistical relationships to infer local climate information from large-scale climate information produced by global climate models (GCMs), as an alternative to the dynamical downscaling provided by regional climate models (RCMs).
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