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. https://doi.org/10.5061/dryad.dr7sqv9w9
Abstract
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.
Methods
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. http://data.daff.gov.au/data/warehouse/9aaf/foa/2013_v2/foa13g9abfs20160212egialb132.zip, Accessed [25 October 2017].
Department of Agriculture Water and the Environment 2020. Australia's ecoregions map. - http://www.environment.gov.au/land/nrs/science/ibra/australias-ecoregions, 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. http://www.fao.org/geonetwork/srv/en/resources.get?id=1255&fname=eco_zone.zip&access=private. 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. http://www.auscover.org.au/purl/biomass-plot-library, 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. http://www.clw.csiro.au/aclep/soilandlandscapegrid/GetData-DAP.html, Accessed [9th October 2017].
Funding
Feed the Future Sustainable Intensification Innovation Lab (SIIL), Award: AID-OOA-L-14-00006