Dryad
Published January 26, 2019 | Version v1
Dataset Open

Data from: GlobTherm, a global database on thermal tolerances for aquatic and terrestrial organisms

Authors/Creators

  • 1. German Center for Integrative Biodiversity Research
  • 2. Université du Québec à Rimouski
  • 3. Stellenbosch University
  • 4. King Juan Carlos University
  • 5. University of British Columbia
  • 6. University of Nottingham
  • 7. Spanish National Research Council
  • 8. University of California, Irvine
  • 9. Natural History Museum
  • 10. Swedish Species Information Centre
  • 11. Universidade Federal de Goiás
  • 12. Harvard University

Description

How climate affects species distributions is a longstanding question receiving renewed interest owing to the need to predict the impacts of global warming on biodiversity. Is climate change forcing species to live near their critical thermal limits? Are these limits likely to change through natural selection? These and other important questions can be addressed with models relating geographical distributions of species with climate data, but inferences made with these models are highly contingent on non-climatic factors such as biotic interactions. Improved understanding of climate change effects on species will require extensive analysis of thermal physiological traits, but such data are scarce and scattered. To overcome current limitations, we created the GlobTherm database. The database contains experimentally derived species' thermal tolerance data currently comprising over 2,000 species of terrestrial, freshwater, intertidal and marine multicellular algae, pl ants, fungi, and animals. The GlobTherm database will be maintained and curated by iDiv with the aim of expanding it, and enable further investigations on the effects of climate on the distribution of life on Earth.

Notes

GlobTherm, a global database on thermal tolerances for aquatic and terrestrial organisms, Excel format
This database includes thermal tolerance metrics for 2,133 species of multicellular algae, plants, fungi, and animals in 43 classes, 203 orders and 525 families from both aquatic, and terrestrial realms, extracted from published studies. Abbreviated citations are included in the 'REF_min' and 'REF_max' variable in the data file. For full citations, please see the attached workbook, "References_1_09_2017.xlsx". The data are available in both Excel and CSV formats in the Dryad Digital Repository (doi:10.5061/dryad.1cv08). Updates to the data and metadata will be curated through the iDiv data portal (https://idata.idiv.de/). For example, in the future we plan to include interspecific variation in the dataset, to provide multiple estimates of thermal tolerance limits for a given species where estimates determined using the best possible methods will be more highly ranked.
GlobalTherm_upload_10_11_17.xlsx
References_1_09_2017.xlsx
GlobTherm, a global database on thermal tolerances for aquatic and terrestrial organisms, CSV format
This database includes thermal tolerance metrics for 2,133 species of multicellular algae, plants, fungi, and animals in 43 classes, 203 orders and 525 families from both aquatic, and terrestrial realms, extracted from published studies. Abbreviated citations are included in the 'REF_min' and 'REF_max' variable in the data file. For full citations, please see the attached workbook, "References_1_09_2017.xlsx". The data are available in both Excel and CSV formats in the Dryad Digital Repository (doi:10.5061/dryad.1cv08). Updates to the data and metadata will be curated through the iDiv data portal (https://idata.idiv.de/). For example, in the future we plan to include interspecific variation in the dataset, to provide multiple estimates of thermal tolerance limits for a given species where estimates determined using the best possible methods will be more highly ranked.
GlobalTherm_upload_02_11_17.csv
References_1_09_2017.xlsx

Files

GlobalTherm_upload_02_11_17.csv

Files (748.2 kB)

Name Size Download all
md5:2f0bef14f8b121a8ca7cba8c7b5d4cf8
354.0 kB Preview Download
md5:ccc946ae0da34b63b76973805dc7d571
258.2 kB Download
md5:da586441762d1bf3b8cca5a7dacfbfad
136.0 kB Download

Additional details

Related works

Is cited by
10.1038/sdata.2018.22 (DOI)