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Open AccessJournal ArticleDOI

Heterogeneous global crop yield response to biochar: a meta-regression analysis

TLDR
In this article, the authors employ meta-analytical, missing data, and semiparametric statistical methods to explain heterogeneity in crop yield responses across different soils, biochars, and agricultural management factors, and then estimate potential changes in yield across different soil environments globally.
Abstract
Biochar may contribute to climate change mitigation at negative cost by sequestering photosynthetically fixed carbon in soil while increasing crop yields. The magnitude of biochar's potential in this regard will depend on crop yield benefits, which have not been well-characterized across different soils and biochars. Using data from 84 studies, we employ meta-analytical, missing data, and semiparametric statistical methods to explain heterogeneity in crop yield responses across different soils, biochars, and agricultural management factors, and then estimate potential changes in yield across different soil environments globally. We find that soil cation exchange capacity and organic carbon were strong predictors of yield response, with low cation exchange and low carbon associated with positive response. We also find that yield response increases over time since initial application, compared to non-biochar controls. High reported soil clay content and low soil pH were weaker predictors of higher yield response. No biochar parameters in our dataset—biochar pH, percentage carbon content, or temperature of pyrolysis—were significant predictors of yield impacts. Projecting our fitted model onto a global soil database, we find the largest potential increases in areas with highly weathered soils, such as those characterizing much of the humid tropics. Richer soils characterizing much of the world's important agricultural areas appear to be less likely to benefit from biochar.

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Citations
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Journal ArticleDOI

Comprehensive evaluation of environmental footprints of regional crop production: A case study of Chizhou City, China

TL;DR: Wang et al. as mentioned in this paper examined the agricultural development of a prefecture city, Chizhou Municipality, in lower reach of Yangtze River valley, China, over the period 2004-2015.
Journal ArticleDOI

Biochar for intensification of plant-related industries to meet productivity, sustainability and economic goals: A review

TL;DR: In this article , a review of biochar as a vehicle to assist plant-related industries meet productivity, sustainability and economic goals is presented, focusing industry, research and policy makers towards strategic opportunities that will maximise biochar benefits and profitability across industry sectors.
Journal ArticleDOI

A financial analysis and life-cycle carbon emissions assessment of oil palm waste biochar exports from Indonesia for use in Australian broad-acre agriculture

TL;DR: In this paper, a cost-benefit analysis and carbon foot-principle analysis of palm waste from South Sumatra is presented for beneficial agronomic use in Australian broad-acre farming systems.
Journal ArticleDOI

Poultry Litter, Biochar, and Fertilizer Effect on Corn Yield, Nutrient Uptake, N2O and CO2 Emissions

TL;DR: In this paper, the authors used hardwood biochar to assess its impact on corn (Zea mays) grain, biomass yields and greenhouse gas emission in central Kentucky, USA, and concluded that this biochar did not significantly increase dry matter, grain yield, and N-P-K uptake.
Journal ArticleDOI

Nitrogen dynamics affected by biochar and irrigation level in an onion field.

TL;DR: There was no significant biochar effect on total N gas emissions or soil NO3- accumulation, but significant irrigation effect and interaction with biochar were determined on soil NO2- accumulation and high leaching was associated withBiochar amendment and higher irrigation level.
References
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Book

Statistical Analysis with Missing Data

TL;DR: This work states that maximum Likelihood for General Patterns of Missing Data: Introduction and Theory with Ignorable Nonresponse and large-Sample Inference Based on Maximum Likelihood Estimates is likely to be high.
Journal ArticleDOI

Generalized Additive Models.

Book

Data Analysis Using Regression and Multilevel/Hierarchical Models

TL;DR: Data Analysis Using Regression and Multilevel/Hierarchical Models is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models.
Book

Generalized Additive Models: An Introduction with R, Second Edition

Simon N Wood
TL;DR: In this article, a simple linear model is proposed to describe the geometry of linear models, and a general linear model specification in R is presented. But the theory of linear model theory is not discussed.
Journal ArticleDOI

Multiple imputation using chained equations: Issues and guidance for practice

TL;DR: The principles of the method and how to impute categorical and quantitative variables, including skewed variables, are described and shown and the practical analysis of multiply imputed data is described, including model building and model checking.
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