Abstract
Acid phosphatase produced by plants and microbes plays a fundamental role in the recycling of soil phosphorus (P). A quantification of the spatial variation in potential acid phosphatase activity (AP) on large spatial scales and its drivers can help to reduce the uncertainty in our understanding of bio-availability of soil P. We applied two machine-learning methods (Random forests and back-propagation artificial networks) to simulate the spatial patterns of AP across Europe by scaling up 126 site observations of potential AP activity from field samples measured in the laboratory, using 12 environmental drivers as predictors. The back-propagation artificial network (BPN) method explained 58% of AP variability, more than the regression tree model (49%). In addition, BPN was able to identify the gradients in AP along three transects in Europe. Partial correlation analysis revealed that soil nutrients (total nitrogen, total P, and labile organic P) and climatic controls (annual precipitation, mean annual temperature, and temperature amplitude) were the dominant factors influencing AP variations in space. Higher AP occurred in regions with higher mean annual temperature, precipitation and higher soil total nitrogen. Soil TP and Po were non-monotonically correlated with modeled AP for Europe, indicating diffident strategies of P utilization by biomes in arid and humid area. This study helps to separate the influences of each factor on AP production and to reduce the uncertainty in estimating soil P availability. The BPN model trained with European data, however, could not produce a robust global map of AP due to the lack of representative measurements of AP for tropical regions. Filling this data gap will help us to understand the physiological basis of P-use strategies in natural soils.
Highlights
Phosphorus (P) is an essential nutrient for all living organisms (White and Hammond, 2008)
We assessed the performance of the back-propagation artificial network (BPN) and Regression Trees (RT) models for each of the 126 European sites (Data set A) by LOO cross-validation
Excluding nine outliers with absolute bias >20 μmol g−1 h−1 and relative bias >50% (Supporting Information Appendix S4, Figures S4, S5), the BPN models explained 58% of Acid phosphatases (AP) variability across all sites, with an RMSE of 6.83 μmol g−1 h−1 (Figure 3, Table S2)
Summary
Phosphorus (P) is an essential nutrient for all living organisms (White and Hammond, 2008). As weathering of minerals and the deposition of atmospheric dust are minor sources of P (Walker and Syers, 1976; Vitousek et al, 2010; Wang et al, 2015), the recycling of organic P from litter and soil organic matter is of utter importance for plant growth and microbial activity in terrestrial ecosystems. The rate at which ecosystems can recycle P from litter and soil organic matter is poorly quantified by observation (Gill and Finzi, 2016). Soil phosphatases secreted by fungi, bacteria, and plant roots play an important but poorly quantified role in transforming complex and unavailable forms of organic P into assimilable phosphate (Caldwell, 2005). Potential phosphatase activity in soils, which can be measured in the lab from soil samples, is an indicator of the capacity of enzyme communities to cleave organic molecules containing P (Krämer and Green, 2000), and serves as a surrogate for the lacking measurements of P mineralization in the soil
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