Mike Grundy

The Australian three-dimensional soil grid: Australia’s contribution to the GlobalSoilMap project

Information on the geographic variation in soil has traditionally been presented in polygon (choropleth) maps at coarse scales. Now scientists, planners, managers and politicians want quantitative information on the variation and functioning of soil at finer resolutions; they want it to plan better land use for agriculture, water supply and the mitigation of climate change land degradation and desertification. The GlobalSoilMap project aims to produce a grid of soil attributes at a fine spatial resolution (approximately 100 m), and at six depths, for the purpose. This paper describes the three-dimensional spatial modelling used to produce the Australian soil grid, which consists of Australia-wide soil attribute maps. The modelling combines historical soil data plus estimates derived from visible and infrared soil spectra. Together they provide a good coverage of data across Australia. The soil attributes so far include sand, silt and clay contents, bulk density, available water capacity, organic carbon, pH, effective cation exchange capacity, total phosphorus and total nitrogen. The data on these attributes were harmonised to six depth layers, namely 0–0.05 m, 0.05–0.15 m, 0.15–0.30 m, 0.30–0.60 m, 0.60–1.00 m and 1.00–2.00 m, and the resulting values were incorporated simultaneously in the models. The modelling itself combined the bootstrap, a decision tree with piecewise regression on environmental variables and geostatistical modelling of residuals. At each layer, values of the soil attributes were predicted at the nodes of a 3 arcsecond (approximately 90 m) grid and mapped together with their uncertainties. The assessment statistics for each attribute mapped show that the models explained between 30% and 70% of their total variation. The outcomes are illustrated with maps of sand, silt and clay contents and their uncertainties. The Australian three-dimensional soil maps fill a significant gap in the availability of quantitative soil information in Australia.

Australia is ‘free to choose’ economic growth and falling environmental pressures

Over two centuries of economic growth have put undeniable pressure on the ecological systems that underpin human well-being. While it is agreed that these pressures are increasing, views divide on how they may be alleviated. Some suggest technological advances will automatically keep us from transgressing key environmental thresholds; others that policy reform can reconcile economic and ecological goals; while a third school argues that only a fundamental shift in societal values can keep human demands within the Earth’s ecological limits. Here we use novel integrated analysis of the energy–water–food nexus, rural land use (including biodiversity), material flows and climate change to explore whether mounting ecological pressures in Australia can be reversed, while the population grows and living standards improve. We show that, in the right circumstances, economic and environmental outcomes can be decoupled. Although economic growth is strong across all scenarios, environmental performance varies widely: pressures are projected to more than double, stabilize or fall markedly by 2050. However, we find no evidence that decoupling will occur automatically. Nor do we find that a shift in societal values is required. Rather, extensions of current policies that mobilize technology and incentivize reduced pressure account for the majority of differences in environmental performance. Our results show that Australia can make great progress towards sustainable prosperity, if it chooses to do so.

Soil and Landscape Grid of Australia

The Soil and Landscape Grid of Australia (SLGA) is the first continental version of the GlobalSoilMap concept and the first nationally consistent, fine spatial resolution set of continuous soil attributes with Australia-wide coverage. The SLGA relies on digital soil mapping methods and integrates historical soil data, new measurement with spectroscopic sensors, novel spatial modelling and a web-service delivery architecture. The SLGA provides soil, regolith and landscape estimates at the centre point of 3 arcsecond grid cells (~90 × 90 m) across Australia. At each point, there are estimates of 11 soil attributes and confidence intervals for each estimate to a depth of 2 m or less, depth of regolith and a set of terrain descriptors. The information system also includes a library of mid-infrared spectra, an inference engine that allows estimation of additional soil parameters and an information model that enables users to access the system via web services. The explicit mapping of depth, bulk density and coarse fragments allows estimation of material stores and fluxes on a volumetric basis. The SLGA therefore has immediate applications in carbon, nitrogen and water process modelling. The map of regolith depth will find immediate application to studies of vadose zone processes, including solute transport, groundwater and nutrient fluxes beyond the root zone. Landscape attributes at 1 and 3 arcseconds are useful for a wide spectrum of ecological, hydrological and broader environmental applications. The SLGA can be accessed at no cost from www.csiro.au/soil-and-landscape-grid. It is managed and delivered as part of the Australian Soil Resource Information System (ASRIS).

Modelling Australian land use competition and ecosystem services with food price feedbacks at high spatial resolution

In a globalised world, land use change outlooks are influenced by both locally heterogeneous land attributes and world markets. We demonstrate the importance of high resolution land heterogeneity representation in understanding local impacts of future global scenarios with carbon markets and land competition influencing food prices. A methodologically unique Australian continental model is presented with bottom-up parcel scale granularity in land use change, food, carbon, water, and biodiversity ecosystem service supply determination, and partial equilibrium food price impacts of land competition. We show that food price feedbacks produce modest aggregate national land use and ecosystem service supply changes. However, high resolution results show amplified land use change and ecosystem service impact in some places and muted impacts in other areas relative to national averages. We conclude that fine granularity modelling of geographic diversity produces local land use change and ecosystem service impact insights not discernible with other approaches. We modeled Australian land use change and ecosystem service responses to global scenarios.The model features a novel approach to very high resolution land heterogeneity representation.To demonstrate, we model how food price feedbacks of land competition differ spatially.Modest land use change and ecosystem service impacts are observed in aggregate for Australia.High resolution impacts vary from large to minuscule depending on local land heterogeneity.

How does grinding affect the mid-infrared spectra of soil and their multivariate calibrations to texture and organic carbon?

Mid-infrared (mid-IR) diffuse reflectance spectroscopy can be used to effectively analyse soil, but the preparation of soil samples by grinding is time consuming. Soil samples are usually finely ground to a particle size of less than 0.250 mm because the spectrometer’s beam aperture is approximately 1–2 mm in diameter. Larger particles can generate specular reflections and spectra that do not adequately represent the soil sample. Grinding soil to small particle sizes enables the diffuse reflectance of light and more representative sample measurements. Here, we report on research that investigates the effect that grinding to different particle sizes have on soil mid-IR spectra. Our aims were to compare the effect of grinding soil to different particle sizes (2.000 mm, 1.000 mm, 0.500 mm, 0.250 mm and 0.106 mm) on the frequencies of mid-IR spectra, and compare the effect of these particle sizes on the accuracy of spectroscopic calibrations to predict organic carbon, sand, silt and clay contents. Using the Commonwealth Scientific and Industrial Research Organisation’s (CSIRO) National visible–near infrared database, we selected 227 soil samples from the National Soil Archive for our experiments, and designed an experiment whereby each soil sample was ground in triplicate to the different particle sizes. These ground samples were measured using an FT-IR spectrometer with a spectral range of 4000–600 cm–1. Grinding to particle sizes that are ≤2.000 mm reduces subsample variability. Smaller particle sizes produce finer and sharper absorption features, which are related to organic carbon, and clay and sand mineralogies. Generally, better predictions for clay, sand and soil organic carbon contents were achieved using soil that is more finely ground, but there were no statistically significant differences between predictions that use soil ground to 1 mm, 0.5 mm, 0.25 mm. Grinding did not affect predictions of silt content. Recommendations on how much grinding is required for mid-IR analysis should also consider the time, cost and effort needed to prepare the soil samples as well as the purpose of the analysis.

The need for better links between pedology and soil carbon research in Australia

Considerable soil carbon research has occurred in Australia in recent years. A review of published literature suggests there are gaps in both the collection of associated data and the long-term storage of soil carbon data, thus limiting the potential use of these data beyond the original purpose. A more co-operative approach between researchers and pedologists is essential to ensure maximum value is obtained from research investment. Further capacity needs to develop to capture data from all sources and especially non-government scientists. ASRIS can be the national focal point; it is recommended that it be more effectively utilised as a data management tool for Australian soil carbon data.

Soil legacy data rescue via GlobalSoilMap and other international and national initiatives

Legacy soil data have been produced over 70 years in nearly all countries of the world. Unfortunately, data, information and knowledge are still currently fragmented and at risk of getting lost if they remain in a paper format. To process this legacy data into consistent, spatially explicit and continuous global soil information, data are being rescued and compiled into databases. Thousands of soil survey reports and maps have been scanned and made available online. The soil profile data reported by these data sources have been captured and compiled into databases. The total number of soil profiles rescued in the selected countries is about 800,000. Currently, data for 117, 000 profiles are compiled and harmonized according to GlobalSoilMap specifications in a world level database (WoSIS). The results presented at the country level are likely to be an underestimate. The majority of soil data is still not rescued and this effort should be pursued. The data have been used to produce soil property maps. We discuss the pro and cons of top-down and bottom-up approaches to produce such maps and we stress their complementarity. We give examples of success stories. The first global soil property maps using rescued data were produced by a top-down approach and were released at a limited resolution of 1km in 2014, followed by an update at a resolution of 250m in 2017. By the end of 2020, we aim to deliver the first worldwide product that fully meets the GlobalSoilMap specifications.

Using Proximal Soil Sensors for Digital Soil Mapping

There is a great need for soil data to be used in natural resource assessment and management, e.g. for environmental modelling and digital soil mapping (DSM) to better understand soil processes and reduce risks in decision making. Conventional soil survey cannot efficiently provide these data because the techniques are time consuming and expensive. Proximal soil sensing (PSS) can be used to acquire spatial and temporal data cheaply and with less effort. This paper reviews some the technologies that may be used for PSS and proposes a framework for their use with DSM.

GlobalSoilMap and Global Carbon Predictions

The GlobalSoilMap project is representative of a global consortium of scientific institutions involved in soil survey and soil science. The GlobalSoilMap group was formed as an outgrowth of the International Union of Soil Sciences Working Group for Digital Soil Mapping with the purpose of providing consistently produced soil property information at 100 m resolution across the world. This information will aid in solving some of the key environment and societal issues of the day, including food security, global climate change land degradation and carbon sequestration. Data would be produced using mostly the storehouse of existing legacy soils data along with geographic information and a range of covariates. A range of modeling techniques is used dependant on the complexity of the background soil survey information. The key soil properties that would be most useful to the modeling community and other users are: organic carbon (g/kg), texture (sand %, silt %, clay % and coarse fragments %), pH, depth to bedrock or restrictive layer. Predictions are made at specified depths with uncertainty values assigned to each prediction. An innovative splining technique will be employed to provide a continuous prediction of soil property values throughout the depth of each profile. Maps have been produced at the country level in the Australia, Canada, Denmark, Nigeria, South Korea and the US and work is on-going in many other parts of the world.