A fine-tuned global distribution dataset of marine forests

Jorge Assis,David Abecasis,Duarte Frade,João Neiva,Ester A Serrão,Eliza Fragkopoulou,Sylvain Faugeron,André Oliveira

doi:10.1038/s41597-020-0459-x

Abstract

Species distribution records are a prerequisite to follow climate-induced range shifts across space and time. However, synthesizing information from various sources such as peer-reviewed literature, herbaria, digital repositories and citizen science initiatives is not only costly and time consuming, but also challenging, as data may contain thematic and taxonomic errors and generally lack standardized formats. We address this gap for important marine ecosystem-structuring species of large brown algae and seagrasses. We gathered distribution records from various sources and provide a fine-tuned dataset with ~2.8 million dereplicated records, taxonomically standardized for 682 species, and considering important physiological and biogeographical traits. Specifically, a flagging system was implemented to signal potentially incorrect records reported on land, in regions with limiting light conditions for photosynthesis, and outside the known distribution of species, as inferred from the most recent published literature. We document the procedure and provide a dataset in tabular format based on Darwin Core Standard (DwC), alongside with a set of functions in R language for data management and visualization.

Highlights

Bioclimatic modelling[1,2], macroecology[3] and evolution[4] are fields that have recently seen a boost in broad scale analyses owing to increased accessibility of large scale biodiversity data
These can be obtained from digital online databases (e.g., GBIF, the Global Biodiversity Information Facility, www.gbif.org and OBIS, the Ocean Biogeographic Information System, www.obis.org), herbarium (e.g., Macroalgal Herbarium Portal, www.macroalgae.org), museum collections, as well as citizen science initiatives[5,6,7], they can be very incomplete and contain geographical and taxonomic errors
Studies focused on the impacts of global climate changes[8,9], or locating evolutionary biodiversity hotspots[10,11], require complete and extremely accurate baselines on the distribution of species across space and time[12]

Summary

Background & Summary

Bioclimatic modelling[1,2], macroecology[3] and evolution[4] are fields that have recently seen a boost in broad scale analyses owing to increased accessibility of large scale biodiversity data These can be obtained from digital online databases (e.g., GBIF, the Global Biodiversity Information Facility, www.gbif.org and OBIS, the Ocean Biogeographic Information System, www.obis.org), herbarium (e.g., Macroalgal Herbarium Portal, www.macroalgae.org), museum collections, as well as citizen science initiatives[5,6,7], they can be very incomplete and contain geographical and taxonomic errors. “Marine forests” is a common name used here to designate large brown algae (kelp and fucoids) and seagrasses These blue-green infrastructures rank among the most productive and biodiversity-rich ecosystems[21], supporting diverse food webs[22,23], critical habitats and nursery grounds for numerous associated species[24,25]. Because climate change is shifting their distribution and abundance worldwide[1,8,30,31], a comprehensive dataset providing essential baselines is needed to better report and understand marine forests’ variability across space and time[14]

Methods

Findings

Code availability