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Dryad

Data for: Biodiversity and elevation gradients across worldwide Mountains

Cite this dataset

Costa, Fernanda (2023). Data for: Biodiversity and elevation gradients across worldwide Mountains [Dataset]. Dryad. https://doi.org/10.5061/dryad.fqz612jz0

Abstract

Aim: 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.
Location: Global elevation gradients.
Taxon: Major terrestrial taxa (invertebrates, vertebrates, and plants).
Methods: 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.
Results: 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.
Main conclusions: 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.

Methods

To perform a systematic quantitative review on SRE patterns we used different approaches, following the synthesis guidelines in Haddaway et al. (2020). First, we conducted literature searches in the Web of Science and Scopus searching engines, using the following keyword combination: (“altitud* gradient*” OR “elevation* gradient*” OR “mountain* gradient*” OR altitud* OR elevation* OR mountain*) AND (“species richness” OR richness OR diversity OR “species diversity" OR biodiversity). Initial searches were conducted between July 2020 and March 2021 and covered the timespan of the bibliographic databases (1945-2021). To complement our database, we also included studies provided in the reference list of elevational gradients reviews (e.g., Rahbek, 1995; Sanders & Rahbek, 2012; see Figure S1 and Table S1). A total of 644 published studies were fully screened for eligibility. 

From these, we selected all studies that reported data on SRE relationships. This search comprised global data across all biogeographical realms, all continents, except Antarctica, and insular regions. We focused on the dominant components of terrestrial ecosystems by reviewing SRE models reported for microorganisms, invertebrates, vertebrates, and plants. Studies were included when meeting the following criteria: 1) raw data on species richness (neither rarefied nor transformed) provided for each elevational gradient; 2) any statistical parameter stated for species richness along an elevation gradient (e.g., r, F, Spearman-rho, t or R2); and 3) reported sample sizes. In less than 5% of the database, we contacted the authors to obtain original raw data and calculated the correlation coefficients whenever missing from the original publication. Studies that treated elevation as a categoric or qualitative variable were excluded. This selection criteria resulted in 143 studies and 479 gradients that were screened for quantitative data. 

As a conservative approach, we further excluded the gradients reporting sample size lower than five elevational quotas sampled over a single mountain (n=2), undefined SRE models (i.e., no clear pattern reported in published figures or results, n=15 gradients, 3.13% of total cases), infrequent SRE models (e.g., polynomial models, n=14, 2.92% of total cases), and studies focusing exclusively on microorganisms (n=12, 2.5%), due to an insufficient number of records. Further, we excluded gradients with inconsistent sampling throughout the mountain and/or those with inflated sample sizes, likely due to pseudoreplication (n=63, 13% of records). Thus, the final database comprised 373 gradients from 127 studies comprising the three most frequent SRE models reported in the literature: linear negative, hump-shaped, and linear positive.