Data and source code for "Climate change drives rapid and asymmetric niche divergence in high-altitude freshwater fishes: insights from niche3D"
Description
This dataset contains the data and source code supporting the study “[MANUSCRIPT TITLE]” (submitted to Global Ecology and Conservation), which quantifies climate-driven niche divergence between two sympatric alpine fish species (H. microcephalus and P. kaznakovi) on the Tibetan Plateau using an ensemble SDM framework (biomod2) and the niche3D (3D Environment Risk Detection) workflow. Contents include: (1) Occurrence data (spatially thinned) and metadata for both species; (2) CPUE (Catch Per Unit Effort) data used for independent model validation (Pearson r and MSE); (3) Modeling scripts/workflows for biomod2 ensemble SDMs (10 algorithms), including pseudo-absence generation, model filtering (AUC ≥ 0.7), and ensemble forecasting (EMmean and EMca); (4) niche3D scripts for niche similarity divergence, barycenter shift analyses, and 3D environmental niche dynamics; (5) Output products (tables/figures and derived metrics) used to generate results in the manuscript. Environmental predictors follow the manuscript Methods (7 predictors: flow accumulation, flow direction, Strahler stream order, and Bio2/Bio11/Bio13/Bio14). Future projections use CMIP6 downscaled bioclimatic layers for the 2050s (2041–2060) and 2070s (2061–2080) under SSP1-2.6/SSP2-4.5/SSP3-7.0/SSP5-8.5, using an ensemble mean of BCC-CSM2-MR, CanESM5, and MIROC6. To reproduce analyses, follow the README (software versions and step-by-step commands). No sensitive personal information is included.