NATECOLEVOL-25093093
收藏DataCite Commons2026-04-17 更新2026-04-25 收录
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https://springernature.figshare.com/articles/dataset/NATECOLEVOL-25093093/30061603
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资源简介:
This repository contains the analysis code, processed datasets, and statistical model outputs associated with the study "Long-term warming reduces fish biomass, but heatwaves shift it."
This study quantifies the individual and combined effects of long-term ocean warming, interannual temperature variability, and marine heatwaves (MHWs) on fish biomass. The analysis covers 33,990 fish populations (1,566 species) across the Northern Hemisphere (Northeast Pacific, North Atlantic, and Mediterranean) from 1993 to 2021.
Repository Contents:
The materials provided here allow for the reproduction of the statistical analyses and figures presented in the main text and supplementary materials.
Code:
R scripts used for:
Data processing and integration of biological (trawl surveys) and climatic (GLORY reanalysis) data.
Statistical modeling using Generalized Linear Mixed-effect Models (GLMMs) via the glmmTMB package.
Detection and quantification of MHWs using the heatwaveR package.
Generation of figures and marginal effects visualization.
Processed Data:
- Population-level fish biomass time series (log-transformed year-over-year changes).
- Thermal position indices for populations (warm-edge vs. cold-edge).
- Climatic indices, including decadal seabed warming trends, interannual temperature differences, and MHW cumulative intensities.
Model Outputs:
Summary statistics and coefficients from the GLMMs assessing biomass responses to thermal stressors.
Data Sources:
Raw input data used to generate these processed files are publicly available from their respective repositories:
- Fish Biomass: FISHGLOB database and EU Mediterranean and Black Sea Fisheries Independent Survey Data.
- Climatic Data: Copernicus Marine Service Global Ocean Physics Reanalysis (GLORY).
- Taxonomy & Occurrences: Global Biodiversity Information Facility (GBIF).
Usage Notes:
The code was developed in R. Key dependencies include glmmTMB, heatwaveR, DHARMa, ggeffects, and bdc. Please refer to the manuscript for detailed methodological descriptions regarding the detrending of temperature baselines and the calculation of biomass log ratios.
提供机构:
figshare
创建时间:
2025-09-05



