Survey
Survey about Plot-based Vegetation Classification Methods (December, 2012)
Why a survey about classification methods?
Vegetation classification is an exercise of abstraction from observed vegetation patterns to vegetation units. This kind of exercise is artificial in the sense that there is not a unique (or natural) way of classifying plant communities. The purpose of this survey is to determine what are the most usual aims and approaches followed in plot-based vegetation classification exercises around the world.
Who was gathering this information?
This questionnaire has been designed by Miquel De Cáceres (Centre Tecnològic Forestal de Catalunya, Spain) and Milan Chytrý (Masaryk University, Czech Republic) on behalf of the Vegetation Classification Committee of the International Association for Vegetation Science (http://www.iavs.org).
Summary of responses
Number of respondants: 236
Geographical origin of respondants
Country
Continent
Experience with plot-based classification of vegetation
Number of studies where you have used numerical classification techniques (approximate)
Scale of the study area in your classification exercises
People could select more than one checkbox, so percentages may add up to more than 100%.
Continent(s) where you have done this research
People could select more than one checkbox, so percentages may add up to more than 100%.
Purpose and general criteria for vegetation classification
What are the main purposes of vegetation classification based on plot records?
People could select more than one checkbox, so percentages may add up to more than 100%.
What are the most important levels of abstraction that can be derived from plot data?
People could select more than one checkbox, so percentages may add up to more than 100%.
What are the most elemental 'objects' in vegetation classification?
People could select more than one checkbox, so percentages may add up to more than 100%.
Sampling design and/or selection of plots from vegetation databases
If you work in the field, what strategy of plot selection do you use in field sampling?
People could select more than one checkbox, so percentages may add up to more than 100%.
If you work in the field, please describe briefly the most rellevant details of your approach to select sampling locations.
This was a free text question where people could indicate more than one method, so percentages do not add up to 100%.
If you work with vegetation-plot databases, what strategy of plot selection from the database do you use?
People could select more than one checkbox, so percentages may add up to more than 100%.
If you work with vegetation-plot databases, do you use some kind of stratified resampling before data analysis?
People could select more than one checkbox, so percentages may add up to more than 100%.
Homogenization of plots of mixed provenance
When merging vegetation plot data coming from different authors/surveys/databases, do you check...
People could select more than one checkbox, so percentages may add up to more than 100%.
If you marked (1) or (2) in the first question, please explain briefly how do you normally deal with taxonomic issues
1. Problems with taxonomic nomenclature (among 193 answers to the previous question)
This was a free text question where people could indicate more than one method, so percentages do not add up to 100%.
2. Problems with taxonomic resolution (among 152 answers to the previous question)
This was a free text question where people could indicate more than one method, so percentages do not add up to 100%.
If you marked (3), (4) or (5) in the first question, please explain briefly how do you normally deal with problems of heterogeneity in field methods.
3. Differences in plot sizes (among 150 answers to the previous question)
This was a free text question where people could indicate more than one method, so percentages do not add up to 100%.
4. Differences in measurement scales/units (among 147 answers to the previous question)
This was a free text question where people could indicate more than one method, so percentages do not add up to 100%.
5. Differences in the definition of vegetation strata (among 87 answers to the previous question)
This was a free text question where people could indicate more than one method, so percentages do not add up to 100%.
Defining ressemblance between stands (or strata within stands)
What are the vegetation attributes that you normally use for vegetation classification?
People could select more than one checkbox, so percentages may add up to more than 100%.
What kind of scale(s) of measurement do you normally use for these attributes?
Measurements for plant abundance
This was a free text question where people could indicate more than one method, so percentages do not add up to 100%.
What kind of data-transformation and/or resemblance measure do you normally use?
Data transformations
This was a free text question where people could indicate more than one method, so percentages do not add up to 100%.
Ressemblance measures (some include implicit transformations)
This was a free text question where people could indicate more than one method, so percentages do not add up to 100%.
Unsupervised classification methods
Indicate your preferred hierarchical or non-hierarchical classification method(s)
This was a free text question where people could indicate more than one method, so percentages do not add up to 100%.
How do you deal with vegetation units previously-defined in your study area?
This was a free text question where people could indicate more than one method, so percentages do not add up to 100%.
What are the most important criteria to validate the resulting vegetation units ?
People could select more than one checkbox, so percentages may add up to more than 100%.
Indicate what kind of statistical techniques you prefer to validate vegetation units
What aspects are the most important to characterize vegetation units before publication?
People could select more than one checkbox, so percentages may add up to more than 100%.
Supervised classification methods
Indicate your preferred supervised classification method(s) (e.g., neural networks).
Indicate your experience with on-line expert systems for vegetation classification
