Validation of phytosociological classifications based on a fuzzy set approach

Questions How can existing vegetation classifications be updated when new plot data are obtained? Can we use the properties of plots classed as outliers to identify gaps in our understanding of vegetation patterns and so direct future enquiry? Location New Zealand. Methods We updated a pre‐existing classification of New Zealand's forests and shrublands based on a nationally representative data set (1177 plots) by using 12 374 additional plot records from New Zealand's National Vegetation Survey Databank (NVS). We resampled the NVS plot records to remove uneven representation along floristic and geographic gradients. To update the classification at the alliance level, we first cast the original classification into the fuzzy classification framework of Noise Clustering and then discarded original types with low plot numbers and high compositional variation. We then used the plot records that could not be assigned to any original alliance to define new alliances, while retaining the original alliances as fixed elements. We also defined vegetation associations to create a classification at a lower level of abstraction and related it to the classification at the alliance level. Finally, we determined whether known rare types were represented among the new vegetation types and characterized plot records classed as outliers. Results After casting the 24 original alliances in the NC framework, we discarded seven. We extended the 17 remaining alliances with 12 new ones and defined 79 associations. All 12 new alliances had extents <120 986 ha, which is smaller than the original alliances, and included rare types that were known to exist but could not be defined using the objectively sampled data set underpinning the original classification. Plot records classed as outliers tended to occur at lower altitudes or in successional shrublands. Further sampling is required to adequately define vegetation types in such situations, although composition may be inherently erratic in successional shrublands. Conclusions Our analysis illustrates the application of a fuzzy classification framework at a national scale and provides a model for others wishing to extend and update vegetation classifications. Our approach allows rare community types to be defined and identifies portions of compositional and geographic gradients that are poorly documented.

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“…Feoli et al. ). In general, the validation of vegetation classifications is an area that deserves further research.…”

Section: Discussionmentioning

confidence: 99%

“…Feoli et al. ). A second set of challenges arises when one intends to update the existing classification using a large number of plot records, such as those available in large phytosociological databases (Dengler et al.…”

Section: Introductionmentioning

confidence: 99%

Updating vegetation classifications: an example with New Zealand's woody vegetation

Wiser

Cáceres

2012

J Vegetation Science

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“…The availability of phytosociological data is increasing all around the European continent (see Feoli & Orloci 1991;Feoli et al 2006;Schaminé et al 2009) and the possibility to use such data to study the relationships between biodiversity and other relevant parameters of plant communities with the aim to assess management conservation plans becomes more feasible. The advantage to use phytosociological data for discovering relationships among environmental parameters, functional and structural features (plant traits) of plant communities (Redžić 2007;Diekmann et al 2008;Ewald 2008;Zelnik & Č arni 2008) was already clearly shown by Feoli (1984) with a simple approach based on matrix multiplication.…”

Section: Introductionmentioning

confidence: 99%

Correlations among biodiversity, biomass and other plant community parameters using the phytosociological approach: A case study from the south-eastern Alps

Poldini

Sburlino

Buffa

et al. 2011

Plant Biosystems - An International Journal Dealing with all As

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“…This method incorporates fuzzy set theory for classification purposes, and thus helps to avoid the assumption that relevés are unequivocal representatives of a type without admixture of any other types (Dale ; Feoli et al. ). FCM has the disadvantage of being sensitive to outliers.…”

Section: Discussionmentioning

confidence: 99%

“…Among unsupervised methods, fuzzy C-means (FCM) has been proposed for the clustering of species community data (De C aceres et al 2010). This method incorporates fuzzy set theory for classification purposes, and thus helps to avoid the assumption that relev es are unequivocal representatives of a type without admixture of any other types (Dale 1995;Feoli et al 2006). FCM has the disadvantage of being sensitive to outliers.…”

Section: Evaluation Of the Methods Used: Advantages And Disadvantagesmentioning

confidence: 99%

Floodplain forests of the Iberian Peninsula: Vegetation classification and climatic features

Biurrun

Campos

García‐Mijangos

et al. 2016

Applied Vegetation Science

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Aims To produce a formalized classification of floodplain forests in the Iberian Peninsula and to assess their main bioclimatic gradients. Location Iberian Peninsula. Methods A data set with more than 3000 vegetation plots of floodplain forests was compiled from vegetation‐plot databases, while climatic data were derived from a digital climatic atlas. After filtering of plots according to their area and geographic stratification, 1892 plots were used to build a typology from association to order level using multivariate classification methods (Fuzzy C‐means, agglomerative hierarchical clustering). The phi fidelity index was used to determine the diagnostic species of the syntaxa in the proposed classification. Main climatic gradients were explored using non‐metric multidimensional gradient analysis, and ANOVA was carried out in order to define the bioclimatic features of Iberian floodplain forests. Results A total of 41 floodplain forest associations were distinguished for the Iberian Peninsula, grouped in nine suballiances, four alliances and two orders. Mediterraneity (summer aridity) was the main climatic driver, as it separates the temperate floodplain forests of the order Alno‐Fraxinetalia from the Mediterranean forests of the Populetalia albae. Continentality and precipitation were mainly relevant at alliance level, as they separated both the temperate alliances Alnion and Hyperico‐Alnion, the latter more oceanic, and the Mediterranean alliances Populion and Osmundo‐Alnion, the latter from more rainy areas. Temperature was an important driver at association level, as the associations included in the same suballiance or alliance differed regarding their thermicity index. Conclusions Our study develops the first formalized classification of Iberian floodplain forests and provides their bioclimatic diagnosis. One new alliance, Hyperico‐Alnion, is proposed for floodplain forests of the Cantabrian watershed. Mediterraneity, continentality and precipitation drive floodplain forest diversity at broad scale, while temperature is the main bioclimatic driver at fine scale. The proposed classification provides the scientific basis for the conservation of this habitat type, with high conservation priority, in southern Europe.

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Validation of phytosociological classifications based on a fuzzy set approach

Cited by 15 publications

References 39 publications

Updating vegetation classifications: an example with New Zealand's woody vegetation

Updating vegetation classifications: an example with New Zealand's woody vegetation

Correlations among biodiversity, biomass and other plant community parameters using the phytosociological approach: A case study from the south-eastern Alps

Floodplain forests of the Iberian Peninsula: Vegetation classification and climatic features

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