Data from: Ecological and evolutionary factors shape the extra-tropical latitudinal species diversity peak in Procellariiform seabirds
Data files
Jun 23, 2026 version files 135.71 KB
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README.md
5.50 KB
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Scripts.zip
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Abstract
Aim: Latitudinal diversity gradients are common across broad taxonomic groups, with most exhibiting peak species richness in the tropics. These have often been explained by greater primary productivity and diversification rates in the tropics. However, some taxa show peak species richness outside the tropics, providing valuable contrasts for improving our understanding of the factors driving latitudinal diversity gradients. In this study, we tested ecological and evolutionary predictors of latitudinal diversity in Procellariiform seabirds, which exhibit peak species richness at temperate Southern Hemisphere latitudes.
Location: Global
Time period: Paleogene to present
Major taxa studied: Order Procellariformes (Seabirds)
Methods: We assessed latitudinal diversity gradient for Procellariiformes in the context of ecological factors including ocean productivity, ocean area, wind speed, and number of coastlines for breeding. We simultaneously tested evolutionary factors comprising lineage ages and transition and diversification rates among latitudes.
Results: While most ecological factors were retained in a Generalized Additive Model, wind appeared positively and most closely related to latitudinal breeding species richness. There was no evidence that unequal evolutionary transitions or diversification explained the latitudinal diversity gradient. However, an approximately two-fold earlier origin in the Southern Temperate zone likely provided more time for species accumulation there.
Main conclusion: Wind and time since evolutionary origin best explain the extratropical peak in breeding species richness of Procellariiform seabirds, emphasizing the importance of integrating ecological and evolutionary perspectives when investigating latitudinal diversity gradients. Additionally, our study also illustrates how quantification of species distributions and the choice of phylogeny when testing evolutionary predictors can influence interpretations of latitudinal diversity gradients.
https://doi.org/10.5061/dryad.69p8cz9fd
This "README.txt" file was generated on 4th May 2025
DATA & FILE OVERVIEW
This dataset includes the code and data that support the findings as described in the paper "Ng et al. (2025) Ecological and evolutionary factors shape the extra-tropical latitudinal species diversity peak in seabirds" published in Journal of Biogeography. The detailed methods are in the main text of the associated article. Scripts and documentation are provided in 'Scripts.zip' within different folders based on their primary functionalities in the analyses. All R scripts were run in R 4.3.1. Below is a brief description of the data structure in each folder.
All codes work off the default directory and will need to be set to the directory where the input files are stored.
- Folder named "Cerezer" contains:
- 'Cerezer map code.R' script to calculate Procellariiform species richness according to Cerezer et al. (2022).
- 'Cerezer species present.xlsx' lists the relevant species as included within Cerezer et al. (2019)
- Folder named "Chla" contains script (chla.R) to calculate per latitude chlorophyll a. Cholorphyll raster obtained from: https://oceancolor.gsfc.nasa.gov/l3/. All annual Aqua-Modis files from 2002 to 2024 for chlorophyll concentration at 4km resolution was downloaded and calculated for the mean as described in chla.R
- Folder named "Coastline" contains script (Coastline.R) to calculate per latitude coastline. No input file required.
- Folder named "GAM" contains script (GAM_models_final.R) that was used to conduct GAM. Input file 'all factors and species richness.xlsx' included within, which compiles the information generated from all other folders included here and described as:
- y: latititude band (in degrees latitude)
- unique_species: number of species at each latitudinal band
- ocean_area_m2: ocean area (m2)
- coast_sum: Count of coastal edges as calculated using Coastline.R script in folder "Coastline"
- chla_mean_per_lat: mean annual chlorophyll a (mg m-3)
- NPP_mean_per_lat: mean annual NPP (mg C m⁻² d⁻¹) as calculated in folder NPP using raster obtained from Silsbe et al. (2016).
- mean_wind_per_lat: mean annual wind speed (m/s) as calculated in the folder Wind using raster from Wentz et al (2015)
- SST_mean_revised: mean annual SST (°C) as calculated in folder SST
- meanTipDR_ES: mean tip diversification rate calculated for each species (no units)
- Folder named "NPP" contains script (NPP.R) to calculate per latitude net primary productivity. NPP raster obtained from Silsbe et al. (2016), for file: "1998_2022_NPP_SILSBE_CAFE_25KM_8D.nc" and calculated for annual mean.
- Folder named "Ocean Area" contains custom clipping script (Ocean Area_PR.ipynb) to generate latitudinal bands in ArcGIS. No additional input file required.
- Folder named "Phylogeny" contains script (Character_state_evolution.R) used to conduct Mk models and reconstruct ancestral states using 'seabird_consensus.trees' as the input phylogeny that is included within. Included species are specified in Procellariformes.csv, with the latitudinal category provided.
- Folder named "Species richness" contains script (Species richness.R) used to calculate number of species present at each latitude and specifying the included species using 'Species present.xlsx'. Shape file for all studied species included within and retrieved from IUCN redlist as data_0.shp and associated files data_0.cpg, data_0.dbf, data_0.prj, data_0.sbn, data_0.ai.
- Folder named "SSE2" contains script and phylogeny used to conduct Several examined and concealed state-dependent speciation and extinction (SecSSE) using SecSSE.R script and generated seabird_consensus_pruned.trees and the provided latitudinal category (Procellariformes_states.csv).()
- Folder named "SST" contains script (SST.R) used to calculate sea surface temperature at each latitude. Raster file retrieved from: https://www.ncei.noaa.gov/access/world-ocean-atlas-2023/bin/woa23.pl and download in netCDF format, 1/4 degree grid, with statistical mean field, averaged across decades, for annual SST. NA values were removed, and grouped by latitude to calculate latitudinal mean.
- Folder named "Wind speed" contains script (Wind.R) used to calculate wind speed at each latitude, raster was retrieved from Wentz et al (2015) as file "CCMP_Wind_Analysis_Climatology_1995_2014_V03.1_L4.0_RSS.nc", using the 'w' - mean 10m wind speed to calculate the mean at each latitude
Cerezer, F. O., A. Machac, T. F. Rangel, and C. S. Dambros. 2022. “Exceptions to the Rule: Relative Roles of Time, Diversification Rates and Regional Energy in Shaping the Inverse Latitudinal Diversity Gradient.” Global Ecology and Biogeography 31: 1794–1809.
Silsbe, G. M., M. J. Behrenfeld, K. H. Halsey, A. J. Milligan, and T. K. Westberry. 2016. “The CAFE Model: A Net Production Model for Global Ocean Phytoplankton.” Global Biogeochemical Cycles 30: 1756–1777.
Wentz, F. J., J. Scott, R. Hoffman, M. Leidner, R. Atlas, and J. Ardizzone. 2015. Remote Sensing Systems Cross- Calibrated Multi-Platform (CCMP) 6-Hourly Ocean Vector Wind Analysis Product on 0.25 Deg Grid, Version 2.0. Remote Sensing Systems.