Data Analysis in Community and Landscape Ecology
Анализ данных в экологии сообществ и ландшафтов
1995-03-02
SCID: 54.1/h34bb93b
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canonical correspondence analysiscommunity ecologykriginglandscape ecologylogic regression
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Abstract (AI)
Ecological data has several special properties: the presence or absence of species on a semi-quantitative abundance scale; non-linear relationships between species and environmental factors; and high inter-correlations among species and among environmental variables. The analysis of such data is important to the interpretation of relationships within plant and animal communities and with their environments. In this corrected version of Data Analysis in Community and Landscape Ecology, without using complex mathematics, the contributors demonstrate the methods that have proven most useful, with examples, exercises and case-studies. Chapters explain in an elementary way powerful data analysis techniques such as logic regression, canonical correspondence analysis, and kriging.
Key Findings
1
Analyzing these distinctive data properties is essential for interpreting relationships within plant and animal communities and between communities and their environments.
2
Ecological datasets commonly involve species presence–absence, semi-quantitative abundances, nonlinear species–environment relationships, and strong inter-correlations.
3
It explains powerful techniques including logic regression, canonical correspondence analysis, and kriging in an elementary manner.
4
The work presents practical ecological data-analysis methods using accessible mathematics, examples, exercises, and case studies.
Research Object
Ecological community and landscape datasets of species occurrences/abundances and environmental variables
Research Subject
Relationships within communities and between species and environmental factors, including nonlinear associations and inter-correlations
Publication Details
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1995-03-02
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