High‐resolution mapping of soil phosphorus concentration in agricultural landscapes with readily available or detailed survey data

Abstract

Summary High‐resolution mapping of soil phosphorus (P) concentration is necessary to identify critical source areas reliably where a large risk of transport coincides with a large potential source of P in agricultural landscapes. However, dense soil P data are not usually available to produce such maps and to obtain them is expensive. In this study, we modelled and mapped soil extractable P (ExtP) and total P (TP) concentrations in an intensively farmed 12‐km2 catchment in Brittany (NW France) with two different datasets to test the suitability of readily available regional or national databases for high‐resolution mapping. We used a machine learning tool (Cubist) to develop rule‐based predictive models from a calibration dataset. Covariates included pedological, geological, agricultural, terrain and geophysical‐related attributes obtained specifically in the study area (SURVEY) or derived from readily available regional or national databases (DATABASE). Even though better predictions were obtained with the SURVEY data (RMSE = 0.018 g kg−1 for ExtP and RMSE = 0.219 g kg−1 for TP), the DATABASE data produced acceptable predictions (RMSE = 0.024 g kg−1 for ExtP and RMSE = 0.253 g kg−1 for TP). The machine learning tool helped to identify key covariates that would improve the prediction of soil P when detailed data are not available. Readily available data about crop rotations could increase the accuracy of existing ExtP maps. These maps, combined with additional soil analysis for extractable Al, would improve the mapping of TP and the identification of areas with a large potential source of P. Highlights Modelling and mapping of soil phosphorus with the machine learning algorithm Cubist. Comparison of regional or national databases and detailed survey data for prediction. Models with regional and national data performed well, but some areas with large concentrations of P were not identified. Information about crop rotation and soil extractable Al improved model performance.

Recent trends in soil fertility across the farms of East Gippsland

“…Records were not sufficiently complete or accurate to elucidate trends in Olsen P in terms of inputs and outputs of P for each paddock as has been done in other studies, e.g. Lewis et al (1987a) and Matos-Moreira et al (2017). An alternative approach is possible.…”

Map of total phosphorus content in native soils of Brazil

“…Knowledge of the spatial variation and distribution of total P content in native soils may help increase agricultural productivity potential, environmental quality, and biodiversity conservation (Rossel andBui, 2016, Delmas et al, 2015;Matos-Moreira et al, 2017). Maps of total P in native soils can foster regional and/ global biogeochemistry models by providing initial estimates of the soil P that can be potentially mobilized for plant uptake and by microbes (Yang et al, 2013).…”

“…For instance, Yang et al (2014) presented a global map of naturally occurring soil total P at 0.5-degree spatial resolution. More recently, detailed maps of soil total P for managed land have been refined for many countries, namely Australia (Rossel and Bui, 2016), France (Delmas et al, 2015;Matos-Moreira et al, 2017), and the United States (Jarvie et al, 2015). Brazil currently does not have a map of national soil total P. Thus, we mapped the spatial distribution of soil total P in the topsoil (0-30 cm) of uncultivated (native) areas of Brazil for a better understanding of patterns of past agricultural expansion, for quantifying rates of soil P build-up associated to intensive farming systems, and for optimizing soil-crop specific strategies for sustainable land management with minimal environmental impact.…”

Combining Laser-Induced Breakdown Spectroscopy (LIBS) and Visible Near-Infrared Spectroscopy (Vis-NIRS) for Soil Phosphorus Determination

“…This provides a driver for quantifying the pool of potentially mobile soil P as part of effective mitigation [ 12 ]. Thus, numerous soil tests are routinely employed for quantifying the size of the agronomically or environmentally relevant soil P pools [ 13 , 14 , 15 ], while inventorying the total soil P resource is important for sustainable P management [ 16 , 17 ]. Characteristic of all these P determinations is that they are labor-intensive wet chemical analyses that often involve the use of harmful chemicals [ 18 ].…”