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      When does no-till yield more? A global meta-analysis

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          An introduction to recursive partitioning: rationale, application, and characteristics of classification and regression trees, bagging, and random forests.

          Recursive partitioning methods have become popular and widely used tools for nonparametric regression and classification in many scientific fields. Especially random forests, which can deal with large numbers of predictor variables even in the presence of complex interactions, have been applied successfully in genetics, clinical medicine, and bioinformatics within the past few years. High-dimensional problems are common not only in genetics, but also in some areas of psychological research, where only a few subjects can be measured because of time or cost constraints, yet a large amount of data is generated for each subject. Random forests have been shown to achieve a high prediction accuracy in such applications and to provide descriptive variable importance measures reflecting the impact of each variable in both main effects and interactions. The aim of this work is to introduce the principles of the standard recursive partitioning methods as well as recent methodological improvements, to illustrate their usage for low and high-dimensional data exploration, but also to point out limitations of the methods and potential pitfalls in their practical application. Application of the methods is illustrated with freely available implementations in the R system for statistical computing. (c) 2009 APA, all rights reserved.
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            Productivity limits and potentials of the principles of conservation agriculture.

            One of the primary challenges of our time is to feed a growing and more demanding world population with reduced external inputs and minimal environmental impacts, all under more variable and extreme climate conditions in the future. Conservation agriculture represents a set of three crop management principles that has received strong international support to help address this challenge, with recent conservation agriculture efforts focusing on smallholder farming systems in sub-Saharan Africa and South Asia. However, conservation agriculture is highly debated, with respect to both its effects on crop yields and its applicability in different farming contexts. Here we conduct a global meta-analysis using 5,463 paired yield observations from 610 studies to compare no-till, the original and central concept of conservation agriculture, with conventional tillage practices across 48 crops and 63 countries. Overall, our results show that no-till reduces yields, yet this response is variable and under certain conditions no-till can produce equivalent or greater yields than conventional tillage. Importantly, when no-till is combined with the other two conservation agriculture principles of residue retention and crop rotation, its negative impacts are minimized. Moreover, no-till in combination with the other two principles significantly increases rainfed crop productivity in dry climates, suggesting that it may become an important climate-change adaptation strategy for ever-drier regions of the world. However, any expansion of conservation agriculture should be done with caution in these areas, as implementation of the other two principles is often challenging in resource-poor and vulnerable smallholder farming systems, thereby increasing the likelihood of yield losses rather than gains. Although farming systems are multifunctional, and environmental and socio-economic factors need to be considered, our analysis indicates that the potential contribution of no-till to the sustainable intensification of agriculture is more limited than often assumed.
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              Conservation agriculture and smallholder farming in Africa: The heretics’ view

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                Author and article information

                Journal
                Field Crops Research
                Field Crops Research
                Elsevier BV
                03784290
                November 2015
                November 2015
                : 183
                :
                : 156-168
                Article
                10.1016/j.fcr.2015.07.020
                b2b1f2a3-b8ee-4e14-a11a-1892959f8d91
                © 2015
                History

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