Keywords 16Organic matter, microbial phosphorus, mineralisation, phosphate, soil phosphorus pools 17 18 19 1 2 to enable accurate predictions of the required external P inputs to achieve optimum growth of 46 subsequent crops. While our understanding of soil inorganic phosphate (Pi) pools is relatively 47 comprehensive, the value of P returned to the soil in crop residues has not been fully resolved. 48 Agronomically significant amounts of P can be present in crop residues and the microbial biomass 49 associated with their decomposition, and the potential contribution of this pool to the P nutrition of 50 cropping systems is significant (eg. Chauhan et al., 1979;Dalal, 1979;White and Ayoub, 1983; Thibaud 51 et al., 1988;Umrit and Friesen, 1994;Kwabiah et al., 2003a;Nachimuthu et al., 2009). The main factors 52 influencing the amount of crop residue P, its rate of mineralisation and subsequent availability to crops 53 have been identified (Stockdale and Brookes, 2006;Guppy and McLaughlin, 2009;; 54 but their interactions remain poorly elucidated and largely unquantified. By reviewing the published 55 literature in which quantitative measurements of P transformations from plant residues applied to soil 56 have been reported, we will evaluate the contribution of crop residue-derived P to the P nutrition of 57 subsequent crops, assess the key factors involved and summarise the knowledge as an empirical model. 58
59The dynamics of organically-derived nitrogen (N) and carbon (C) in agricultural soils has been extensively 60 described, and a wide range of predictive tools have been developed. These have proved a valuable 61 asset for landholders, agronomists and policy makers by providing good estimates of the impacts of 62 agronomic management options on the dynamics of both C (eg. Parton et al., 1988; Coleman and 63 Jenkinson, 1999;Grace et al., 2006) and N (see Herridge et al., 2008) in agricultural soils. Considering 64 our extensive knowledge of the N cycle in agricultural systems, and the benefits (economic, social and 65 environmental) that have been obtained by our ability to predict and manipulate it, similar knowledge 66 of the organic P cycle could also yield significant benefits. Yet, although the principal driving factors of 67 organic P cycling have long been recognised and modelled (Cole et al., 1977), models have not proven 68 to be universally applicable (Gijsman et al., 1996;Schnepf et al., 2011). Several models have 69 demonstrated a capacity to incorporate P release from crop residues and manures into projected crop 70 growth and yield, notably The Agricultural Production Systems Simulation (APSIM) (Keating et al., 2003), 71 3 Century (Parton et al., 1988) and CERES-Wheat (Ritchie et al., 1988;Godwin et al., 1989; Singh et al., 72 1991;Daroub et al., 2003) modelling frameworks. However, these models require detailed climate and 73 site information that may not be available, and are specialised tools that cannot be operated by the 74 layperson. The contribution of crop residue P to the nutriti...