Evaluation And Comparison Of Soil Organic Matter Models

Soil organic matter (SOM) represents a major pool of carbon within the biosphere, roughly twice than in atmospheric CO2. SOM models embody our best understanding of soil carbon dynamics and are needed to predict how global environmental change will influence soil carbon stocks. These models are also required for evaluating the likely effectiveness of different mitigation options. The first important step towards systematically evaluating the suitability of SOM models for these purposes is to test their simulations against real data. Since changes in SOM occur slowly, long-term datasets are required. This volume brings together leading SOM model developers and experimentalists to test SOM models using long-term datasets from diverse ecosystems, land uses and climatic zones within the temperate region.

Few topics cut across the soil science discipline wider than research on soil carbon. This book contains 48 chapters that focus on novel and exciting aspects of soil carbon research from all over the world. It includes review papers by global leaders in soil carbon research, and the book ends with a list and discussion of global soil carbon research priorities. Chapters are loosely grouped in four sections: § Soil carbon in space and time § Soil carbon properties and processes § Soil use and carbon management § Soil carbon and the environment A wide variety of topics is included: soil carbon modelling, measurement, monitoring, microbial dynamics, soil carbon management and 12 chapters focus on national or regional soil carbon stock assessments. The book provides up-to-date information for researchers interested in soil carbon in relation to climate change and to researchers that are interested in soil carbon for the maintenance of soil quality and fertility. Papers in this book were presented at the IUSS Global Soil C Conference that was held at the University of Wisconsin-Madison, USA.

The Soil Organic Carbon Mapping cookbook provides a step-by-step guidance for developing 1 km grids for soil carbon stocks. It includes the preparation of local soil data, the compilation and pre-processing of ancillary spatial data sets, upscaling methodologies, and uncertainty assessments. Guidance is mainly specific to soil carbon data, but also contains many generic sections on soil grid development, as it is relevant for other soil properties. This second edition of the cookbook provides generic methodologies and technical steps to produce SOC maps and has been updated with knowledge and practical experiences gained during the implementation process of GSOCmap V1.0 throughout 2017. Guidance is mainly specific to SOC data, but as this cookbook contains generic sections on soil grid development it can be applicable to map various soil properties.

This book presents the basic concepts of quantitative soil science and, within this framework, it seeks to construct a new body of knowledge. There is a growing need for quantitative approach in soil science, which arises from a general demand for improved economic production and environmental management. Pedometrics can be defined as the development and application of statistical and mathematical methods applicable to data analysis problems in soil science. This book shows how pedometrics can address key soil-related questions from a quantitative point of view. It addresses four main areas which are akin to the problems of conventional pedology: (i) Understanding the pattern of soil distribution in character space – soil classification, (ii) Understanding soil spatial and temporal variation, (iii) Evaluating the utility and quality of soil and ultimately, (iv) Understanding the genesis of soil. This is the first book that address these problems in a coherent quantitate approach.

Predictive Soil Mapping (PSM) is based on applying statistical and/or machine learning techniques to fit models for the purpose of producing spatial and/or spatiotemporal predictions of soil variables i.e. maps of soil properties and classes at different resolutions. It is a multidisciplinary field combining statistics, data science, soil science, physical geography, remote sensing, geoinformation science and a number of other sciences. Predictive Soil Mapping with R is about understanding the main concepts behind soil mapping, mastering R packages that can be used to produce high quality soil maps, and about optimizing all processes involved so that also the production costs can be reduced. The online version of the book is available at: https: //envirometrix.github.io/PredictiveSoilMapping/ Pull requests and general comments are welcome. These materials are based on technical tutorials initially developed by the ISRIC's Global Soil Information Facilities (GSIF) development team over the period 2014?2017

Tropical ecosystems - the regions between the tropics of Cancer and Capricorn - play an important role in global processes, economic issues, and political concerns. In their natural state, tropical ecosystems support a large quantity of above- and below-ground biomass, and constitute a major part of the terrestrial carbon pool. Conversion of the natural ecosystem to agriculture and forestry ecosystems disturbs this ecological balance. Global Climate Change and Tropical Ecosystems presents data on carbon pool fluxes from case studies in 12 countries in tropical regions. The chapters cover: Characteristics of tropical ecosystems Soil and biotic carbon pools Impacts of land use and soil management Slash-and-burn practices Crop residue and fertility management This volume adds to the understanding of pedospheric processes in tropical ecosystems and how to better use soils as a sink for carbon dioxide and other greenhouse gases. With Global Climate Change and Tropical Ecosystems you will understand the link between soil productivity, environmental quality and the global carbon cycle, not only in these ecologically sensitive regions but worldwide.