PRIMER 6 for Windows
PRIMER 6 is suitable for most versions of the Microsoft Windows operating system including Windows 98/Me/2000/NT4/XP/Vista
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PRIMER 6 (Plymouth Routines In Multivariate Ecological Research) consists of a wide range of univariate, graphical and multivariate routines for analysing the species/samples abundance (or biomass) matrices that arise in biological monitoring of environmental impact and more fundamental studies in community ecology, together with associated physico-chemical data.The methods make few, if any, assumptions about the form of the data ('non-metric' ordination and permutation tests are fundamental to the approach) and concentrate on approaches that are straightforward to understand and explain. V6 has been rewritten for the new .Net environment. Most analyses now run 5 times faster. It features a new workspace explorer making it easy to keep track of the worksflow. Many additional options to the analyses and new ones like LINKTREE which can link biotic patterns to environmental vari ables. See Changes... for details. | |
| This robustness makes them widely applicable, leading to greater confidence in interpretation of community patterns, and the transparency perhaps explains why they have been adopted worldwide, particularly in marine science but increasingly in terrestrial, freshwater, palaeontology etc contexts. The statistical methods underlying the software are explained in non-mathematical terms in an extensive 'methods manual', which also shows outcomes from many literature studies, e.g. of environmental effects of oil spills, drilling mud disposal, sewage pollution etc on soft-sediment benthic assemblages, disturbance or climatic effects on coral reef composition or fish communities, more fundamental biodiversity and community ecology patterns, mesocosm studies with multi-species outcomes etc. Many of these full data sets are included with the package so that the user can replicate the analyses given in the manual for himself/herself. |  |
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The basic routines of the package cover: hierarchical clustering into sample (or species) groups (CLUSTER); ordination by non-metric multidimensional scaling (MDS) and principal components (PCA) to summarise patterns in species composition and environmental variables; permutation-based hypothesis testing (ANOSIM), an analogue of univariate ANOVA which tests for differences between groups of (multivariate) samples from different times, locations, experimental treatments etc; identifying the species primarily providing the discrimination between two observed sample clusters (SIMPER); the linking of multivariate biotic patterns to suites of environmental variables (BEST); comparative (Mantel-type) tests on similarity matrices (RELATE); standard diversity indices; dominance plots; species abundance distributions; aggregation of arrays to allow data analysis at higher taxonomic levels, etc. | |
| The full integration within a standard Windows environment allows: easy manipulation of data and results, e.g. in input/output from Excel spreadsheets or other sources; the ability to view and manipulate data and some derived files/plots on screen, in multiple windows; standard Windows printing and export to Windows .emf or .bmp files (graphics) and .rtf files (text); flexibility in specifying analyses, particularly for subsets of data and in defining group structures for tests and displays; ability to handle relatively large data sets (subject to available Windows memory and, primarily, time constraints - as with all non-parametric and permutation-based methods, computation time can be heavy). |  |
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Finally, a further unique feature of PRIMER 6 is the ability to calculate biodiversity indices based on the taxonomic distinctness or relatedness of the species making up a quantitative sample or species list, indices whose statistical properties are robust to variations in sampling effort. These routines allow formal hypothesis tests for change in biodiversity structure at a location (as measured by average and variation in taxonomic 'breadth' of the species list), from that 'expected' from a larger, regional species pool. It provides a possible way of comparing biodiversity patterns over wide space and time scales, when sampling effort is not controlled (and is based on recent K R Clarke and R M Warwick research papers, some of which are still in press) | |
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