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Dryad

Taking stock of climate-driven risks to mountain biodiversity

Cite this dataset

Chen, Yi-Hsiu; Lenoir, Jonathan; Chen, I-Ching (2024). Taking stock of climate-driven risks to mountain biodiversity [Dataset]. Dryad. https://doi.org/10.5061/dryad.83bk3jb1m

Abstract

Mountain biodiversity is rapidly reorganizing as species migrate upslope to track climate warming. Despite the potential threats of mountaintop extirpation, range shift gaps, and lowland biodiversity attrition, empirical evidence of these risks remains scarce. We analyzed 8,800 records of historical and modern elevational range limits for 440 animals and 1,629 plant species and found that the risk of mountaintop extirpation did not exceed random expectations. Upper limits expanded for species with narrow ranges or lowland affinities, but lower limits showed little contraction, implying scant risk to date of these threats, even in the tropics. Yet the predominance of upslope expansion combined with delayed mountaintop extirpations points to a biotic homogenization, which may profoundly alter biotic interactions in mountain ecosystems with increasing warming.

README: Taking stock of Climate-Driven Risks to Mountain Biodiversity

https://doi.org/10.5061/dryad.83bk3jb1m

To assess range shifts of global mountain species under warming climate, we compiled 2,200 quadruplets of historic (1849-1998) and modern (2003-2017) elevational range limits, both the upper and lower limit, for a total 2069 terrestrial plant and animal species, extracted from 21 peer-reviewed studies conducted across 23 montane regions. To test the three above-listed predictions of climate-driven risks, we analyzed the four metrics by pairs of response variables: lower and upper limit shifts combined (Model 1) as well as range extent change and midpoint shift combined (Model 2). We fitted two separate Bayesian multivariate response models (Model 1 and Model 2), applying a multivariate mixed-effects modelling approach (MMMs), to estimate correlations between pairs of response variables. Model significance for the three predictions of climate-driven risks was obtained against null models.

Description of the data and file structure

Data.csv: This CSV file contains species range shift records 2,200 quadruplets of historic (1849-1998) and modern (2003-2017) elevational range limits for a total 2069 terrestrial plant and animal species, extracted from 21 peer-reviewed studies.

Metadata.xlsx: This XLSX file contains metadata for Data.xlsx.

Publication_list.xlsx: This XLSX file lists the scientific reports included in the dataset.

1_MMMs.R: This script contains the code used to conduct multivariate mixed-effects model analysis.

2_Null_model_example.R: This script contains the code used to construct a null model by randomizing the boundary shifts with replacement among species historically at different elevational positions.

Funding

Forestry and Nature Conservation Agency, Taiwan, Award: 113-09.1-EP-03

National Science and Technology Council, Award: 112-2628-B-006 -005

National Science and Technology Council, Award: 111-2628-B-006 -016