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The Bioclim registry

CliMond: The Bioclim registryBioclim 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.

Download Bioclim data

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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Detailed information on the Bioclim variables

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).

Frequently asked questions

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

Register of Bioclim variable definitions

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).