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This title focuses on the design and analysis of ecological experiments, concentrating on statistical approaches. Each chapter presents a particular statistical technique or set of techniques in the context of resolving an ecological issue.

Ecology --- Environmental Sciences and Forestry. Ecology -- Ecology (General) --- Experimental design. --- Statistical methods. --- ALLW. --- Experimental design --- 574 --- 574 General ecology. Biocoenology. Hydrobiology. Biogeography --- General ecology. Biocoenology. Hydrobiology. Biogeography --- Design of experiments --- Statistical design --- Mathematical optimization --- Research --- Science --- Statistical decision --- Statistics --- Analysis of means --- Analysis of variance --- Statistical methods --- Experiments --- Methodology --- Ecología --- Diseño experimental

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Plant ecology. Plant sociology --- Plant ecology. --- 581.5 --- Plant ecology --- Botany --- Plants --- Ecology --- Habits of plants. Plant behaviour. Plant ecology. Plant ethology. The plant and its environment. Bionomics of plants --- ECO Ecology --- ecology --- plant ecology --- 581.5 Habits of plants. Plant behaviour. Plant ecology. Plant ethology. The plant and its environment. Bionomics of plants --- Phytoecology --- Vegetation ecology --- Floristic ecology

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Meta-analysis is a powerful statistical methodology for synthesizing research evidence across independent studies. This is the first comprehensive handbook of meta-analysis written specifically for ecologists and evolutionary biologists, and it provides an invaluable introduction for beginners as well as an up-to-date guide for experienced meta-analysts. The chapters, written by renowned experts, walk readers through every step of meta-analysis, from problem formulation to the presentation of the results. The handbook identifies both the advantages of using meta-analysis for research synthesis and the potential pitfalls and limitations of meta-analysis (including when it should not be used). Different approaches to carrying out a meta-analysis are described, and include moment and least-square, maximum likelihood, and Bayesian approaches, all illustrated using worked examples based on real biological datasets. This one-of-a-kind resource is uniquely tailored to the biological sciences, and will provide an invaluable text for practitioners from graduate students and senior scientists to policymakers in conservation and environmental management. Walks you through every step of carrying out a meta-analysis in ecology and evolutionary biology, from problem formulation to result presentation Brings together experts from a broad range of fields Shows how to avoid, minimize, or resolve pitfalls such as missing data, publication bias, varying data quality, nonindependence of observations, and phylogenetic dependencies among species Helps you choose the right software Draws on numerous examples based on real biological datasets

Meta-analysis. --- Evolution --- Ecology --- Philosophy --- Creation --- Emergence (Philosophy) --- Teleology --- Medicine --- Psychometrics --- Social sciences --- Mathematical models. --- Statistical methods. --- Research --- Evaluation --- Statistical methods --- Bayesian analysis. --- Bayesian approach. --- Lepidoptera mating. --- allometric scaling. --- average trends. --- biodiversity. --- collaborative research. --- computer software. --- conceptual tool. --- conservation. --- conventional wisdom. --- data analysis. --- data appraisal. --- data collection. --- data extraction. --- data gathering. --- data quality. --- ecology. --- effect size. --- effect sizes. --- evolution. --- evolutionary biology. --- exemplar studies. --- forest plots. --- imputation methods. --- insufficient data. --- interaction effects. --- invasive plants. --- knowledge gaps. --- large-scale monitoring. --- least-squares method. --- literature search. --- management intervention. --- maximum likelihood estimation. --- medicine. --- meta-analysis database. --- meta-analysis. --- meta-analytic process. --- meta-regression plots. --- missing data. --- moment-based approach. --- non-independence. --- parameter estimation. --- partial information. --- phylogenetic nonindependence. --- phylogenetic relationships. --- plant abundance. --- primary data. --- problem formulation. --- publication bias. --- published studies. --- quantitative research synthesis. --- research evidence. --- research pooling. --- research practice. --- research synthesis. --- sample error. --- sampling. --- scatter plots. --- scientific literature. --- scientific publications. --- scoping search. --- sex ratio theory. --- sexual selection. --- small-scale surveys. --- social sciences. --- statistical analysis. --- statistical inference. --- statistical methodology. --- statistical models. --- statistical power. --- statistical software. --- statistical tool. --- study quality. --- study replication. --- study selection. --- subjectivity. --- systematic research synthesis. --- systematic review. --- systematic reviews. --- systematic search. --- temporal change. --- temporal trends. --- visualization.