/pdf/roots-contribute-more-to-refractory-soil-organic-matter-than-4fmd0x8xzo.pdf

Roots contribute more to refractory soil organic matter than above-ground crop residues, as revealed by a long-term field experiment

We developed a comprehensive, gridded Global Soil Dataset for use in Earth System Models (GSDE) and other applications. The GSDE provides soil information, such as soil particle-size distribution, organic carbon, and nutrients, and quality control information in terms of confidence level at 30″ × 30″ horizontal resolution and for eight vertical layers to a depth of 2.3 m. The GSDE is based on the Soil Map of the World and various regional and national soil databases, including soil attribute data and soil maps. We used a standardized data structure and data processing procedures to harmonize the data collected from various sources. We then used a soil type linkage method (i.e., taxotransfer rules) and a polygon linkage method to derive the spatial distribution of the soil properties. To aggregate the attributes of different compositions of a mapping unit, we used three mapping approaches: the area-weighting method, the dominant soil type method, and the dominant binned soil attribute method. The data set can also be aggregated to a lower resolution. In this paper, we only show the vertical and horizontal variations of sand, silt and clay contents, bulk density, and soil organic carbon as examples of the GSDE. The GSDE estimates of global soil organic carbon stock to the depths of 2.3, 1, and 0.3 m are 1922.7, 1455.4, and 720.1 Gt, respectively. This newly developed data set provides more accurate soil information and represents a step forward to advance earth system modeling.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2013MS000293

A global soil data set for earth system modeling

This paper is an extensive review of the research that has been undertaken on near-infrared (NIR) and mid-infrared (MIR) spectroscopy applied to soil particularly for determining carbon (C) content. The objective is to determine which acquisition method (NIR, MIR, in the field or in the laboratory) might be recommended for the purpose of C stock measurement with a particular interest in carbon credit trading. For this purpose, an optimal method has to satisfy the dual constraints of low-cost and high throughput analysis. The various methods proposed in the literature are compared. In order to make comparisons as reliable as possible, special attention has been paid to the conditions of data acquisition (sample preparation), and to calibration and validation procedures. In particular, whether the validation has been carried out on fully independent samples or on samples similar to the ones of the calibration set greatly influences the results. Also, for C stock measurement, it is absolutely necessary to measure the bias of the prediction in order to be conclusive about the feasibility of the method. However, only few researchers provide this parameter and we recommend including it as a matter of course in future reports. Finally, although MIR on dried and ground samples is the most accurate method, on-the-go and in-field sensors provide predictions accurate enough to show promise in being a valuable component of technologies that would be used for C-credit purposes. But in order to meet the cost/accuracy trade-off, the main issue using such field sensors is to be able to simultaneously measure the bulk density or, better, to directly measure the volumetric concentration of C in soil. This circumvents the costs of field extraction and laboratory analysis. This is the next great challenge to be met by soil scientists.

Near-infrared (NIR) and mid-infrared (MIR) spectroscopic techniques for assessing the amount of carbon stock in soils – Critical review and research perspectives

Long-term elevated nitrogen (N) input from anthropogenic sources may cause soil acidification and decrease crop yield, yet the response of the belowground microbial community to long-term N input alone or in combination with phosphorus (P) and potassium (K) is poorly understood. We explored the effect of long-term N and NPK fertilization on soil bacterial diversity and community composition using meta-analysis of a global dataset. Nitrogen fertilization decreased soil pH, and increased soil organic carbon (C) and available N contents. Bacterial taxonomic diversity was decreased by N fertilization alone, but was increased by NPK fertilization. The effect of N fertilization on bacterial diversity varied with soil texture and water management, but was independent of crop type or N application rate. Changes in bacterial diversity were positively related to both soil pH and organic C content under N fertilization alone, but only to soil organic C under NPK fertilization. Microbial biomass C decreased with decreasing bacterial diversity under long-term N fertilization. Nitrogen fertilization increased the relative abundance of Proteobacteria and Actinobacteria, but reduced the abundance of Acidobacteria, consistent with the general life history strategy theory for bacteria. The positive correlation between N application rate and the relative abundance of Actinobacteria indicates that increased N availability favored the growth of Actinobacteria. This first global analysis of long-term N and NPK fertilization that differentially affects bacterial diversity and community composition provides a reference for nutrient management strategies for maintaining belowground microbial diversity in agro-ecosystems worldwide.

Long-term nitrogen fertilization decreases bacterial diversity and favors the growth of Actinobacteria and Proteobacteria in agro-ecosystems across the globe

. Resilient, productive soils are necessary to sustainably intensify
agriculture to increase yields while minimizing environmental harm. To
conserve and regenerate productive soils, the need to maintain and build soil
organic matter (SOM) has received considerable attention. Although SOM is
considered key to soil health, its relationship with yield is contested
because of local-scale differences in soils, climate, and farming systems.
There is a need to quantify this relationship to set a general framework for
how soil management could potentially contribute to the goals of sustainable
intensification. We developed a quantitative model exploring how SOM relates
to crop yield potential of maize and wheat in light of co-varying factors of
management, soil type, and climate. We found that yields of these two crops
are on average greater with higher concentrations
of SOC (soil organic carbon). However, yield
increases level off at ∼2  % SOC. Nevertheless, approximately
two-thirds of the world's cultivated maize and wheat lands currently have SOC
contents of less than 2 %. Using this regression relationship developed
from published empirical data, we then estimated how an increase in SOC
concentrations up to regionally specific targets could potentially help
reduce reliance on nitrogen (N) fertilizer and help close global yield gaps.
Potential N fertilizer reductions associated with increasing SOC amount to
7 % and 5 % of global N fertilizer inputs across maize and wheat
fields, respectively. Potential yield increases of 10±11  %
(mean  ±  SD) for maize and 23±37  % for wheat amount to 32 %
of the projected yield gap for maize and 60 % of that for wheat. Our
analysis provides a global-level prediction for relating SOC to crop yields.
Further work employing similar approaches to regional and local data, coupled
with experimental work to disentangle causative effects of SOC on yield and
vice versa, is needed to provide practical prescriptions to incentivize soil
management for sustainable intensification.

/pdf/global-meta-analysis-of-the-relationship-between-soil-41n3fur6kt.pdf

Douglas W. Pribyl

Papers

A critical review of the conventional SOC to SOM conversion factor