Microorganisms play an important role in soil phosphorus (P) cycling and regulation of P availability in agroecosystems. However, the responses of the functional and ecological traits of P-transformation microorganisms to long-term nutrient inputs are largely unknown. This study used metagenomics to investigate changes in the relative abundance of microbial P-transformation genes at four long-term experimental sites that received various inputs of N and P nutrients (up to 39 years). Long-term P input increased microbial P immobilization by decreasing the relative abundance of the P-starvation response gene (phoR) and increasing that of the low-affinity inorganic phosphate transporter gene (pit). This contrasts with previous findings that low-P conditions facilitate P immobilization in culturable microorganisms in short-term studies. In comparison, long-term nitrogen (N) input significantly decreased soil pH, and consequently decreased the relative abundances of total microbial P-solubilizing genes and the abundances of Actinobacteria, Gammaproteobacteria, and Alphaproteobacteria containing genes coding for alkaline phosphatase, and weakened the connection of relevant key genes. This challenges the concept that microbial P-solubilization capacity is mainly regulated by N:P stoichiometry. It is concluded that long-term N inputs decreased microbial P-solubilizing and mineralizing capacity while P inputs favored microbial immobilization via altering the microbial functional profiles, providing a novel insight into the regulation of P cycling in sustainable agroecosystems from a microbial perspective.

Phosphorus (P) limitation of aboveground plant production is usually assumed to occur in tropical regions but rarely elsewhere. Here we report that such P limitation is more widespread and much stronger than previously estimated. In our global meta-analysis, almost half (46.2%) of 652 P-addition field experiments reveal a significant P limitation on aboveground plant production. Globally, P additions increase aboveground plant production by 34.9% in natural terrestrial ecosystems, which is 7.0–15.9% higher than previously suggested. In croplands, by contrast, P additions increase aboveground plant production by only 13.9%, probably because of historical fertilizations. The magnitude of P limitation also differs among climate zones and regions, and is driven by climate, ecosystem properties, and fertilization regimes. In addition to confirming that P limitation is widespread in tropical regions, our study demonstrates that P limitation often occurs in other regions. This suggests that previous studies have underestimated the importance of altered P supply on aboveground plant production in natural terrestrial ecosystems.

Climate is predicted to change over the 21st century. However, little is known about how climate change can affect soil phosphorus (P) cycle and availability in global terrestrial ecosystems, where P is a key limiting nutrient. With a global database of Hedley P fractions and key‐associated physiochemical properties of 760 (seminatural) natural soils compiled from 96 published studies, this study evaluated how climate pattern affected soil P cycle and availability in global terrestrial ecosystems. Overall, soil available P, indexed by Hedley labile inorganic P fraction, significantly decreased with increasing mean annual temperature (MAT) and precipitation (MAP). Hypothesis‐oriented path model analysis suggests that MAT negatively affected soil available P mainly by decreasing soil organic P and primary mineral P and increasing soil sand content. MAP negatively affected soil available P both directly and indirectly through decreasing soil primary mineral P; however, these negative effects were offset by the positive effects of MAP on soil organic P and fine soil particles, resulting in a relatively minor total MAP effect on soil available P. As aridity degree was mainly determined by MAP, aridity also had a relatively minor total effect on soil available P. These global patterns generally hold true irrespective of soil depth (≤10 cm or >10 cm) or site aridity index (≤1.0 or >1.0), and were also true for the low‐sand (≤50%) soils. In contrast, available P of the high‐sand (>50%) soils was positively affected by MAT and aridity and negatively affected by MAP. Our results suggest that temperature and precipitation have contrasting effects on soil P availability and can interact with soil particle size to control soil P availability.

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.