Mapping suitability of pasture species using fine-scale soils and rainfall data
R. W. Smith
A E , M. Webb B C , D. Kidd B and D. B. Hannaway D
+ Author Affiliations
- Author Affiliations
A Tasmanian Institute of Agriculture, Launceston, Tas. 7250, Australia.
B Natural Values Conservation Branch, Department of Primary Industries, Parks, Water and Environment (DPIPWE), Prospect, Tas. 7250, Australia.
C School of Life and Environmental Sciences and Sydney Institute of Agriculture, The University of Sydney, Sydney, NSW 2006, Australia.
D Crop and Soil Science Department, Oregon State University, Corvallis, OR 97331, USA.
E Corresponding author. Email: Rowan.Smith@utas.edu.au
Crop and Pasture Science 70(12) 1175-1183 https://doi.org/10.1071/CP18573
Submitted: 14 December 2018 Accepted: 29 October 2019 Published: 13 December 2019
Abstract
Species composition is limiting production in >65% of pastures in Tasmania, Australia—a situation not unique to Tasmania. There are many reasons for degradation and poor persistence of improved pastures, with species selection crucial. Selection currently relies on producers making an assessment based on experience, external advice from agronomists and seed merchants, and experimental trial data. This project sought to assess the benefit of using fine-scale soils data and long-term rainfall data to determine the suitability of pasture species at a farm level across >3 Mha of agricultural land in Tasmania. Suitability rules were developed for perennial ryegrass (Lolium perenne L.) and lucerne (Medicago sativa L.) involving growth responses to soil characteristics (pH, soil depth, electrical conductivity, drainage, and coarse fragments) and average annual rainfall. Suitability classes were defined as well suited, suitable, moderately suitable, and unsuitable, with additional subclasses to account for soil limitations that could be mitigated through management. Soil grids were generated using digital soil mapping techniques from ~6500 new and existing site data sources spread across Tasmania. Rainfall data from 539 Bureau of Meteorology rainfall-recording sites were modelled using regression kriging interpolation. Soil pH was found to be a major constraint on lucerne, with 61.3% of the land area having a pH <5.7. Ameliorating the soil with lime could reduce this constraint to 33.5% of the land area. Drainage was another major constraint on lucerne suitability, with 37.8% of land constrained by imperfectly or poorly drained soils. Improving drainage by installing surface or underground drains could reduce the affected area to 22.1%. The mapping showed that perennial ryegrass was constrained by soil pH, with 38.2% of land having a pH <5.5. However, liming could reduce this constraint to just 9.6%. Accurate identification of the likely constraints on pasture production and persistence before sowing and choice of appropriate species and management intervention will result in fewer failed sowings and greater productivity. The feasibility of expanding this approach is being assessed for a larger area of south-eastern Australia and across a wider range of pasture species.
Additional keywords: alfalfa, temperate pastures.
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