Bioclim variables have become a core component of the species distribution modelling tool kit. This Bioclim registry represents an agreement with ANUCLIM, the previous de facto record of variables (Hutchinson et al. 2009), to have a single online reference point for the Bioclim variables. Referring to each variable by its Bio number has proven popular in the literature, and if the number of Bio variables is to increase, a suitable repository is needed to record and describe these variables.

Bioclim variables include the core set of 19 variables (temperature and precipitation), an extended set of 16 additional variables (solar radiation and soil moisture), and a growing list of new Bioclim variables at a global extent. We encourage researchers to identify additional Bioclimatic covariates to extend the suite further. We suggest that good candidate variables are 1) global in nature, and 2) will be useful to a broad range of modellers. A protocol for the proposal of new variables is outlined in the FAQ below.

Bioclim variables for Bio01 to Bio40, based on the CliMond climate data, are available in ASCII or ESRI grid format. Most ecological modelling and GIS software that utilises the Bioclim variables can import at least one of these two formats.


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The first 19 Bioclim variables (Bio01 to Bio19) are the "core variables" because they require only temperature and precipitation data for their calculation.

The next 16 Bioclim variables require data on solar radiation (Bio20-27), and soil moisture (Bio28-35; Hutchinson et al. 2009). Data on solar radiation and atmospheric moisture content (relative humidity or vapour pressure) are frequently unavailable in many climatologies, and the data processing required to calculate the soil moisture variables is significantly more involved than the calculation of the core Bioclim variables.

Bio36 to Bio40 represent the first five principal components of the first 35 Bioclim variables in the CliMond 1975H dataset (Kriticos et al. 2014). These capture more than 90% of the variance in the full dataset. They are best suited to studies describing the current distribution of a species or other taxon, particularly when little is known about the species that could inform the selection of suitable modelling covariates. These variables are unsuited to work involving climate change analyses. They are also scale invariant, meaning that if you run the analysis on a subset of the climate data, the results for the subset area will differ from the result derived using the whole dataset.

A description of the Bioclim variables and the climate variables used in their calculation is detailed below (Table 1).

How do I propose and prepare a new Bioclim variable and add it to the registry?
The process is as follows:
1. Firstly consider whether it is really suitable. Is it global in extent, and is it likely to be useful to a wide range of modellers?
2. Contact us and suggest the variable. We will discuss the criteria above with you, and if we all agree that it is a suitable candidate, a provisional Bioclim variable number will be assigned.
3. You publish a paper in a peer-reviewed journal demonstrating an application of the new variables and describing their derivation.
4. When accepted for publication, we add the variable to the register, formalise their Bioclim number assignment and cite your publication.

How do I cite a Bioclim variable downloaded from the CliMond registry?
We suggest you consider the content of the following wording for inspiration: Bioclim variables were downloaded from the CliMond Archive (VX.X; Kriticos et al. 2012) and the following variables were chosen: BioA, BioB, BioC (Hutchinson et al. 2009, Kriticos et al. 2014).

• Hutchinson M., Xu T., Houlder D., Nix H. & McMahon J. (2009). ANUCLIM 6.0 User’s Guide. Australian National University, Fenner School of Environment and Society.

• Kriticos D.J., Webber B.L., Leriche A., Ota N., Macadam I., Bathols J. & Scott J.K. (2012) CliMond: global high resolution historical and future scenario climate surfaces for bioclimatic modelling. Methods in Ecology and Evolution, 3: 53-64.

• Kriticos D.J., Jarošik V. and Ota N. (2014) Extending the suite of Bioclim variables: a proposed registry system and case study using principal components analysis. Methods in Ecology and Evolution, Online Early, DOI: 10.1111/2041-210X.12244

This list can be expanded. Please contact us to suggest new and useful variables to be added to the list.

Table 1 | Description of Bioclim variables and the contributing variables used in their calculation.

Variable Number	Variable	Minimum temp (°C)	Maximum temp (°C)	Rainfall (mm month-1)	Radiation (W m-2d-1)	Pan evaporation (mm d-1)	Ref.
Bio01	Annual mean temperature (°C)	×	×				1
Bio02	Mean diurnal temperature range (mean(period max-min)) (°C)	×	×				1
Bio03	Isothermality (Bio02 ÷ Bio07)	×	×				1
Bio04	Temperature seasonality (C of V)	×	×				1
Bio05	Max temperature of warmest week (°C)		×				1
Bio06	Min temperature of coldest week (°C)	×					1
Bio07	Temperature annual range (Bio05-Bio06) (°C)	×	×				1
Bio08	Mean temperature of wettest quarter (°C)	×	×	×			1
Bio09	Mean temperature of driest quarter (°C)	×	×	×			1
Bio10	Mean temperature of warmest quarter (°C)	×	×				1
Bio11	Mean temperature of coldest quarter (°C)	×	×				1
Bio12	Annual precipitation (mm)			×			1
Bio13	Precipitation of wettest week (mm)			×			1
Bio14	Precipitation of driest week (mm)			×			1
Bio15	Precipitation seasonality (C of V)			×			1
Bio16	Precipitation of wettest quarter (mm)			×			1
Bio17	Precipitation of driest quarter (mm)			×			1
Bio18	Precipitation of warmest quarter (mm)	×	×	×			1
Bio19	Precipitation of coldest quarter (mm)	×	×	×			1
Bio20	Annual mean radiation (W m-2)				×		1
Bio21	Highest weekly radiation (W m-2)				×		1
Bio22	Lowest weekly radiation (W m-2				×		1
Bio23	Radiation seasonality (C of V)				×		1
Bio24	Radiation of wettest quarter (W m-2)			×	×		1
Bio25	Radiation of driest quarter (W m-2)			×	×		1
Bio26	Radiation of warmest quarter (W m-2)	×	×		×		1
Bio27	Radiation of coldest quarter (W m-2)	×	×		×		1
Bio28	Annual mean moisture index			×		×	1
Bio29	Highest weekly moisture index			×		×	1
Bio30	Lowest weekly moisture index			×		×	1
Bio31	Moisture index seasonality (C of V)			×		×	1
Bio32	Mean moisture index of wettest quarter			×		×	1
Bio33	Mean moisture index of driest quarter			×		×	1
Bio34	Mean moisture index of warmest quarter	×	×	×		×	1
Bio35	Mean moisture index of coldest quarter	×	×	×		×	1
Bio36	First principal component of the first 35 Bioclim variables	×	×	×	×	×	2
Bio37	Second principal component of the first 35 Bioclim variables	×	×	×	×	×	2
Bio38	Third principal component of the first 35 Bioclim variables	×	×	×	×	×	2
Bio39	Fourth principal component of the first 35 Bioclim variables	×	×	×	×	×	2
Bio40	Fifth principal component of the first 35 Bioclim variables	×	×	×	×	×	2

N.B. Variables without units are dimensionless indices. Source: 1: Hutchinson et al. (2009); 2: Kriticos et al. (2014).