DOI: 10.5061/dryad.z08kprrd4
title: Exceptions to the rule: Relative roles of time, diversification rates and regional energy in shaping the inverse latitudinal diversity gradient

description: Aim: Inverse latitudinal diversity gradients (i-LDG), whereby regional
 richness peaks outside the tropics, have rarely been investigated and
 their causes remain unclear. Here, we investigate three prominent
 explanations, postulating that species-rich regions have had (1) longer
 time to accumulate species, (2) faster diversification, and (3) more
 energy to support more diverse communities. These mechanisms have been
 shown to explain the tropical megadiversity, and we examine whether they
 can also explain i-LDG. Location: Global Time period: Contemporary Major
 taxa studied: Amphibians, birds, mammals  Methods: We estimated
 the time for species accumulation, regional diversification rates, and
 regional energy for six tetrapod taxa (≈ 800 species). Then, we quantified
 the relative effects and interactions among these three classes of
 variables, using variance partitioning, and confirmed the results across
 alternative metrics for time (community phylometrics and BioGeoBEARS),
 diversification rates (BAMM and DR), and regional energy (past and current
 temperature, productivity). Results: While regional richness across each
 of the six taxa peaked in the temperate region, it varied markedly across
 hemispheres and continents. The effects of time, diversification rates,
 and regional energy varied greatly from one taxon to another, but high
 diversification rates generally emerged as the best predictor of high
 regional richness. The effects of time and regional energy were limited,
 with the exception of salamanders and cetaceans.  Main
 conclusions: Together, our results indicate that the causes of i-LDG are
 highly taxon-specific. Consequently, large-scale richness gradients might
 not have a universal explanation and different causal pathways might
 converge on similar gradients. Moreover, regional diversification rates
 might vary dramatically between similar environments and, depending on the
 taxon, regional richness might or might not depend on the time for species
 accumulation. Together, these results underscore the complexity behind the
 formation of richness gradients, which might involve a symphony of
 variations on the interplay of time, diversification rates, and regional
 energy.
description: This release includes the code and data that support the findings
 as described in the paper "Cerezer et al. (2022) Exceptions to the
 rule: Relative roles of time, diversification rates, and regional energy
 in shaping the inverse latitudinal diversity gradient" published in
 <em>Global Ecology and Biogeography</em>. The detailed methods
 are in the main text of the associated article.
description: Scripts and documentation are provided in different folders based
 on their primary functionalities in the analyses. Below is a brief
 description of the data structure in each folder (in italics). Please
 refer to README file.  
 <strong>Presence-absence matrix based on species range maps
 ("Pres_Abs_RawData"; section 2.1 of the main
 text): </strong><br> 
  <em>Spatial_Distribution.R</em> = This R script
 computes the presence-absence on each 2 x 2 degree grid-cells from species
 range maps.  <em>Shapefiles</em> = These
 are some species range maps used as an illustrative proposal.
  <em>WorldShape</em> = Shapefile with the World
 Administrative boundaries.
  <em>RawDataExtracted</em> = Presence-absence matrix
 calculated for each of the six taxa. 
 <strong>Phylogenetic hypotheses
 considered in the analyses ("Phylogenies"; section 2.2 of the
 main text):</strong> These are
 the phylogenies obtained for the six taxa and used in all downstream
 analyses (see section 2.2 of the main text for more details).
 
 <strong>Time for species accumulation
 ("Evolutionary_time"; section 2.3 of the main
 text):</strong> <em>MPD</em> = The
 R script "<em>MPD_Codes.R</em>" quantifies the mean
 pairwise distance (MPD) between species co-occurring in a
 community. <em>MBL</em> = The R script
 "<em>MBL_Codes.R</em>" calculates the maximum branch
 length (MBL) among species co-occurring in a community. 
 <em>Species_tip_age</em> = The R script
 "<em>Species_tip_age_codes.R</em>" calculates the
 species tip age through the age of its closest internal node.
 <em>Geographic_Reconstructions</em> = The R script
 "<em>Geographic.R</em>" measures an index of
 geographic tropicality by verifying the percentage in which the
 species' distribution is within the Tropics of Cancer and Capricorn
 (23.436°N and 23.436°S). The phylogenetic signal on geographic tropicality
 is also calculated. 
 <em>Climatic_Reconstructions</em> = The R script
 "<em>Climatic.R</em>" calculates the mean
 temperature across the species' distribution and checks the
 phylogenetic signal of climatic preferences. 
 <strong>Estimates of
 diversification rates ("Diversification_rates"; section 2.4 of
 the main text):</strong> 
 <em>BAMM</em> = This folder contains the Bayesian analysis of
 macroevolutionary mixtures (BAMM -
 "<em>Outputs.zip</em>") outputs, which include
 estimates of diversification rates for 100 tree samples in each
 taxon. <em>DR</em> = The R script
 "<em>DR.codes.R</em>" computes the DR statistic
 (Jetz et al., 2012) across 100 tree samples for each taxon.
 
 <strong>Regional energy ("Regional_energy"; section 2.5 of
 the main text):</strong> 
 <em>Regional_energy.R</em> = This R script extracts a
 multitude of proxies associated with regional energy for terrestrial and
 marine environments. 
 <em>AtlasBiosphere</em> = This folder provides actual
 evapotranspiration (AET) and net primary productivity (NPP) data taken
 from the Atlas of the Biosphere. 
 <em>RawDataExtracted</em> = These are the regional energy
 measurements extracted for the six taxa. 
 <strong>Statistical
 and sensitivity analyses ("Analyses"; sections 2.6 and 2.7 of
 the main text):</strong> 
 <em>Analyses_codes.R </em>= The R script
 "<em>Analysis_codes.R</em>" is used to test the
 influence of evolutionary time, diversification rates, and regional energy
 on species richness (e.g. variance partitioning and gam analyses). This
 script also compares the main findings against a series of sensitivity
 analyses.  <em>All_Merged_Data</em> =
 This folder presents the combined data used to perform the main analyses
 and figures of the manuscript.