Skip to main content
dryadopen

Data for: Biodiversity and elevation gradients across worldwide Mountains

<div> <em>Aim:</em> Identifying macroecological patterns and biases in species distribution is a challenging but essential task in biodiversity-oriented studies. Despite the extensive attempts to find consistent species richness elevation (SRE) patterns, the topic remains controversial owing to widespread conflicting, idiosyncratic, and non-generalizable underlying mechanisms. We compiled a database to perform a meta-analytical review to answer why patterns of species-richness in elevation gradients remain elusive, a long-standing, central but contentious macroecological and biogeographical question.</div> <div> <em>Location</em>: Global elevation gradients.</div> <div> <em>Taxon</em>: Major terrestrial taxa (invertebrates, vertebrates, and plants).</div> <div> <em>Methods</em>: We tested the effect of elevation on species richness using multilevel mixed-effects meta-analytical models. Data from 127 studies spawning almost one century of research were integrated to test the effect of elevation across distinct 1) SRE models, 2) quality of primary data (e.g., mountain sampling coverage), 3) biogeographic realms, 4) studied taxa, and 5) organism mobility.</div> <div> <em>Results</em>: The linear negative pattern showed the strongest model fit followed by the hump-shaped and the linear positive models. We observed that studies with higher sampling sizes showed a consistent decrease in the strength of SRE patterns. Further, the larger the mountain coverage and sampled range, the stronger the detection of some SRE patterns. Overall, the elevational effect on species richness was consistent across biogeographical realms, taxonomic groups, and organism mobility.</div> <div> <em>Main conclusions</em>: This study indicates a bias in the detection of SRE patterns, driven mostly by mountain comprehensiveness, namely the number of sampling units, sampled range, and mountain coverage. These results call attention to the evidence that undersampled elevation gradients may bias our understanding on the complex relationships between elevation and biodiversity, thus impairing a broad understanding on the ecology, evolution, biogeography, and conservation of mountain biota.</div>

ShareScore

32/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
12
Access
12
Reuse readiness
0
Engagement
4

Topics

Dataset details

Repository
dryad
Published
July 25, 2023
License
cc-zero
DOI
10.5061/dryad.fqz612jz0

Scored with release 0.9.0

ScienceDex for faculty

Your academic CV and NIH biosketch

Make your CV in your school's format and your NIH biosketch from it, then download both as Word files.