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Climate more important than soils for predicting forest biomass at the continental scale

Cite this dataset

Bennett, Alison et al. (2020). Climate more important than soils for predicting forest biomass at the continental scale [Dataset]. Dryad.


Above-ground biomass in forests is critical to the global carbon cycle as it stores and sequesters carbon from the atmosphere. Climate change will disrupt the carbon cycle hence understanding how climate and other abiotic variables determine forest biomass at broad spatial scales is important for validating and constraining Earth System models and predicting the impacts of climate change on forest carbon stores. We examined the importance of climate and soil variables to explaining above-ground biomass distribution across the Australian continent using publicly available biomass data from 3130 mature forest sites, in 6 broad ecoregions, encompassing tropical, subtropical, and temperate biomes. We used the Random Forest algorithm to test the explanatory power of 14 abiotic variables (8 climate, 6 soil) and to identify the best-performing models based on climate-only, soil-only, and climate plus soil. The best performing models explained ~50% of the variation (climate-only: R2 = 0.47 ± 0.04, and climate plus soils: R2 = 0.49 ± 0.04). Mean temperature of the driest quarter was the most important climate variable, and bulk density was the most important soil variable. Climate variables were consistently more important than soil variables in combined models, and model predictive performance was not substantively improved by the inclusion of soil variables. This result was also achieved when the analysis was repeated at the ecoregion scale. Predicted forest above-ground biomass ranged from 18 to 1066 Mg ha-1, often under-predicting measured above-ground biomass, which ranged from 7 to 1500 Mg ha-1. This suggested that other non-climate, non-edaphic variables impose a substantial influence on forest above-ground biomass, particularly in the high biomass range. We conclude that climate is a strong predictor of above-ground biomass at broad spatial scales and across large environmental gradients, yet to predict forest above-ground biomass distribution under future climates, other non-climatic factors must also be identified.


These data are a compilation of Australia-wide forest above ground biomass records retrieved from the Biomass Plot Library (TERN AusCover, 2017), soil data retrived from the Australian Soil and Landscape Grid (Viscarra Rossel, R., et al. 2014), climate data retrieved from WorldClim 2.0 (Fick, S. E. and Hijmans, R. J. 2017), forest-type data retrieved from Australia's State of the Forest report (ABARES 2013), biome data from Australia's ecoregion map (Department of Agriculture Water and the Environment 2020), and ecoregion data from the Global ecological zones map (Food and Agricultural Organisation of the United Nations 2001).

Data sets were first processed in ArcGIS 10.4.1 to spatially join raster data to above-ground biomass point data, and then processed in R to remove measurements that were suspected to be errors, duplicated site measurements, non-forest, or highly disturbed.  A full description of this process is provided in the published manuscript and in the supplementary material.

Usage notes

Data fields are described as follows:

Field Description Original Source
ID Row index Used in processing
FID_ Unique identifier Biomass Plot Library
agb_drymass_ha Tree AGB /ha Biomass Plot Library
State Australian State Biomass Plot Library
Long Longitude Biomass Plot Library
Lat Latitude Biomass Plot Library
E Easting Added during processing
N Northing Added during processing
HEIGHT Forest height code Forest extent 2013 (v2)
COVER Forest cover code Forest extent 2013 (v2)
FOR_CAT Forest category Forest extent 2013 (v2)
FOR_TYPE Forest type Forest extent 2013 (v2)
bio_1 Mean annual temperature WorldClim 2.0
bio_3 Isothermality WorldClim 2.0
bio_7 Temperature annual range WorldClim 2.0
bio_9 Mean temperature of driest quarter WorldClim 2.0
bio_12 Annual precipitation WorldClim 2.0
bio_15 Precipitation seasonality WorldClim 2.0
bio_17 Precipitation of driest quarter WorldClim 2.0
bio_19 Precipitation of coldest quarter WorldClim 2.0
awc_0_5 Available water capacity (%) Soil and Landscape Grid
bdw_0_5 Bulk density (g cm-3) Soil and Landscape Grid
cly_0_5 Clay (%) Soil and Landscape Grid
ece_0_5 Effective cation exchange capacity (me 100 g-1) Soil and Landscape Grid
phc_0_5 pH Soil and Landscape Grid
pto_0_5 Total phosphorus (%) Soil and Landscape Grid
Biome Global biome classification Global ecological zones map
Ecoregion World ecoregion classification Australia's ecoregion map

References for data sources are as follows:

ABARES 2013. Australia national forest inventory - Forest extent (2013) v2.0, electronic dataset. - ABARES., Accessed [25 October 2017].

Department of Agriculture Water and the Environment 2020. Australia's ecoregions map. -, Accessed [20 March 2020].

Fick, S. E. and Hijmans, R. J. 2017. Worldclim 2: New 1-km spatial resolution climate surfaces for global land areas. - Int. J. Climatol. 37: 4302-4315.

Food and Agricultural Organisation of the United Nations 2001. Global ecological zones map. - GeoNetwork. Accessed [8th October 2018].

TERN AusCover 2017. Biomass Plot Library - National collation of tree and shrub inventory data, allometric model predictions of above and below-ground biomass, Australia. - Dataset., Accessed [17 September 2017].

Viscarra Rossel, R., et al. 2014. Soil and landscape grid national soil attribute maps (3" resolution): Bulk density - whole earth (v1.4); Organic carbon (v1.1); Clay (v1.1); Soil depth (v1.2); Effective cation exchange capacity (v1.3); pH - CaCl2 (v1.3); Available water capactiy (v1.3); Sand (v1.4); Total nitrogen (v1.4); Total phosphorus (v1.4); and Silt (v1.4). - CSIRO Data Collection., Accessed [9th October 2017].


Feed the Future Sustainable Intensification Innovation Lab (SIIL), Award: AID-OOA-L-14-00006