Advanced Statistical Analysis for Soil Scientists

by Tancredo Souza

Overview

In the evolving field of soil science, advanced statistical analysis has become essential for understanding complex soil processes. Handbook of Advanced Statistical Analysis Applied offers a comprehensive guide to modern statistical methods such as PERMANOVA, ANOSIM, PCA, NMDS, RDA, and SEM, tailored specifically for soil science research.Through practical examples and case studies, the book demonstrates how these techniques can be applied to analyze complex datasets, identify patterns, and model interactions within soil ecosystems. It provides step-by-step guidance on data preparation, analysis, and interpretation, making it a valuable resource for students, early-career researchers, and professionals in soil science.

By combining theoretical foundations with practical applications, Handbook of Advanced Statistical Analysis Applied presentes analytical tools needed to conduct rigorous research, contribute to scientific knowledge, and address challenges in sustainable land management. This book serves as a critical resource for mastering advanced statistical approaches in soil science.

Product Details

ISBN-13:	9783031881602
Publisher:	Springer Nature Switzerland
Publication date:	06/25/2025
Pages:	150
Product dimensions:	6.10(w) x 9.25(h) x (d)

About the Author

Tancredo Souza is a Visiting Professor at the Department of Agriculture, Federal University of Paraiba, Brazil. His research focuses on the effects of land use on the diversity of soil organisms in tropical and subtropical ecosystems. He is particularly interested in plant-soil interactions, the ecology of mycorrhizal fungi, and biogeochemistry. Additionally, he has expertise in multivariate statistical analysis, applying techniques such as PCA, CCA, RDA, NMDS, and SEM to interpret complex soil data. He holds a Bachelor's degree in Agronomy, a Master's degree in Soil and Water Management and Conservation, and a Ph.D. in Soil Sciences from the Federal University of Paraíba, Brazil, and the University of Coimbra, Portugal.

Affiliation: Federal University of Paraiba, Department of Agriculture, Campus III, Bananeiras, Paraiba, Brazil

Table of Contents

PERMANOVA.- Analysis of Similarities (ANOSIM).- Multiple Regression.- Principal component analysis (PCA).- Redundancy analysis (RDA).- Non-metric muldimensional scaling (NMDS).- Canonical correspondence analysis (CCA).- Structural equation modelling (SEM).