The distribution of soil phosphorus for global biogeochemical modeling

Abstract

Phosphorus (P) is a major element required for biological activity in terrestrial ecosystems. Although the total P content in most soils can be large, only a small fraction is available or in an organic form for biological utilization because it is bound either in incompletely weathered mineral particles, adsorbed on mineral surfaces, or, over the time of soil formation, made unavailable by secondary mineral formation (occluded). In order to adequately represent phosphorus availability in global biogeochemistry-climate models, a representation of the amount and form of P in soils globally is required. We develop an approach that builds on existing knowledge of soil P processes and databases of parent material and soil P measurements to provide spatially explicit estimates of different forms of soil P on the global scale. We assembled data on the various forms of phosphorus in soils globally, chronosequence information, and several global spatial databases to develop a map of total soil P and the distribution among mineral bound, labile, organic, occluded, and secondary P forms in soils globally. The amount of P, to 50 cm soil depth, in soil labile, organic, occluded, and secondary pools is 3.5 ± 3, 8.7 ± 6, 13.2 ± 9, and 3.3 ± 2 Pg P respectively. The amount in soil mineral particles to the same depth is estimated at 12.5 ± 9 Pg P for a global soil total of 41.2 ± 20 Pg P. The large uncertainty in our estimates reflects our limited understanding of the processes controlling soil P transformations during pedogenesis and lack of measurements of soil P. In spite of the large uncertainty, the estimated global spatial variation and distribution of different soil P forms presented in this study will be useful for global biogeochemistry models that include P as a limiting element in biological production by providing initial estimates of the available soil P for plant uptake and microbial utilization

Improved identification of primary biological aerosol particles using single-particle mass spectrometry

“…This misidentification effect is repeated for the mineral dust emission rate and misidentification fraction. For simplicity, we considered the mineral dust fraction to be desert soils, termed Aridisols and Entisols, which are predominantly present in dust-productive regions, such as the Sahara or the dust bowl (Yang et al, 2013). According to Yang and Post (2011), the organic phosphate content of those soils is 5-15 %, but this is a second-order effect when compared to misclassification.…”

“…Spodosols (moist forest soils) have the highest fraction of organic phosphorus (∼ 45 %), and Aridisols (sandy desert soils) have the lowest (∼ 5 %) (Yang and Post, 2011). Yang et al (2013) compiled a global map of soil phosphorus distribution and its forms and found that 20 %, on average, of total phosphorus is organic. Wang et al (2010) arrive at 34 % of soil phosphorus as organic globally.…”

Seasonal changes in soil organic matter after a decade of nutrient addition in a lowland tropical forest

“…In temperate rain forest soils on the west coast of the South Island of New Zealand, microbial biomass also accounted for a considerable fraction of the soil organic P, and for approximately two thirds of the total biomass P in the ecosystem (i.e., plant plus microbial) (Turner and Condron 2013). Given the significance of soil organic P in the nutrition of tropical forests, and the need to accurately portray biologically available soil P pools in biogeochemical models (Yang et al 2013), a priority must be to quantify the extent to which live microbial cells contribute to soil organic P in tropical forests.…”

Use of a coupled soil-root-leaf model to optimise phosphate fertiliser use efficiency in barley

“…Over-fertilising soils due to inaccurate estimation of requirement, or mis-interpretation of soil P supply through inappropriate tests leads not only to waste of finite reserves of phosphate-rock but also increased risk of P loss to water causing eutrophication (Hooda et al 2001). By using knowledge about the distribution of P within the soil and by modelling its implications, it should be possible to save on fertiliser costs by implementing better optimised treatments through targeting P use (Yang et al 2013;Withers et al 2014). Furthermore, since crop and fertiliser management have long-term effects on topsoil and subsoil P availability (Bolland and Baker 1998), it will be important to validate the model over several years if it is to improve on current simpler approaches to decision making.…”