Towards unification of national vegetation classifications: A comparison of two methods for analysis of large data sets

Abstract. In European phytosociology, national classifications of corresponding vegetation types show considerable differences even between neighbouring countries. Therefore, the European Vegetation Survey project urgently needs numerical classification methods for large data sets that are able to produce compatible classifications using data sets from different countries. We tested the ability of two methods, TWINSPAN and COCKTAIL, to produce similar classifications of wet meadows (Calthion, incl. Filipendulenion) for Germany (7909 relevés) and the Czech Republic (1287 relevés) in this respect. In TWINSPAN, the indicator ordination option was used for classification of two national data sets, and the extracted assignment criteria (indicator species) were applied crosswise from one to the other national data set. Although the data sets presumably contained similar community types, TWINSPAN revealed almost no correspondence between the groups derived from the proper classification of the national data set and the groups defined by the assignment criteria taken from the other national data set. The reason is probably the difference in structure between the national data sets, which is a typical, but hardly avoidable, feature of any pair of phytosociological data sets. As a result, the first axis of the correspondence analysis, and consequently the first TWINSPAN division, are associated with different environmental gradients; the difference in the first division is transferred and multiplied further down the hierarchy. COCKTAIL is a method which produces relevé groups on the basis of statistically formed species groups. The user determines the starting points for the formation of species groups, and groups already found in one data set can be tested for existence in the other data set. The correspondence between the national classifications produced by COCKTAIL was fairly good. For some relevé groups, the lack of correspondence to groups in the other national data set could be explained by the absence of the corresponding vegetation types in one of the countries, rather than by methodological problems.     

A new measure of fidelity and its application to defining species groups

Abstract. The first objective of this paper is to define a new measure of fidelity of a species to a vegetation unit, called u. The value of u is derived from the approximation of the binomial or the hypergeometric distribution by the normal distribution. It is shown that the properties of u meet the requirements for a fidelity measure in vegetation science, i.e. (1) to reflect differences of a species’relative frequency inside a certain vegetation unit and its relative frequency in the remainder of the data set; (2) to increase with increasing size of the data set. Additionally (3), u has the property to be dependent on the proportion of the vegetation unit's size to the size of the whole data set. The second objective is to present a method of how to use the value of u for finding species groups in large data bases and for defining vegetation units. A species group is defined by possession of species that show the highest value of u among all species in the data set with regard to the vegetation unit defined by this species group. The vegetation unit is defined as comprising all relevés that include a minimum number of the species in the species group. This minimum number is derived statistically in such a way that fewer relevés always belong to a species group than would be expected if the differential species were distributed randomly among the relevés. An iterative algorithm is described for detecting species groups in data bases. Starting with an initial species group, species composition of this group and the vegetation unit defined by this group are mutually optimized. With this algorithm species groups are formed in a data set independently of each other. Subsequently, these species groups can be combined in such a way that they are suited to define commonly known syntaxa a posteriori.     

DMSO‐ and Serum‐Free Cryopreservation of Wharton's Jelly Tissue Isolated From Human Umbilical Cord

The facile nature of mesenchymal stem cell (MSC) acquisition in relatively large numbers has made Wharton's jelly (WJ) tissue an alternative source of MSCs for regenerative medicine. However, freezing of such tissue using dimethyl sulfoxide (DMSO) for future use impedes its clinical utility. In this study, we compared the effect of two different cryoprotectants (DMSO and cocktail solution) on post‐thaw cell behavior upon freezing of WJ tissue following two different freezing protocols (Conventional [?1°C/min] and programmed). The programmed method showed higher cell survival rate compared to conventional method of freezing. Further, cocktail solution showed better cryoprotection than DMSO. Post‐thaw growth characteristics and stem cell behavior of Wharton's jelly mesenchymal stem cells (WJMSCs) from WJ tissue cryopreserved with a cocktail solution in conjunction with programmed method (Prog‐Cock) were comparable with WJMSCs from fresh WJ tissue. They preserved their expression of surface markers, pluripotent factors, and successfully differentiated in vitro into osteocytes, adipocytes, chondrocytes, and hepatocytes. They also produced lesser annexin‐V‐positive cells compared to cells from WJ tissue stored using cocktail solution in conjunction with the conventional method (Conv‐Cock). Real‐time PCR and Western blot analysis of post‐thaw WJMSCs from Conv‐Cock group showed significantly increased expression of pro‐apoptotic factors (BAX, p53, and p21) and reduced expression of anti‐apoptotic factor (BCL2) compared to WJMSCs from the fresh and Prog‐Cock group. Therefore, we conclude that freezing of fresh WJ tissue using cocktail solution in conjunction with programmed freezing method allows for an efficient WJ tissue banking for future MSC‐based regenerative therapies. J. Cell. Biochem. 117: 2397–2412, 2016. © 2016 The Authors. Journal of Cellular Biochemistry published by Wiley Periodicals, Inc.

     

JUICE,software for vegetation classification

Abstract. The program JUICE was designed as a Microsoft® WINDOWS® application for editing, classification and analysis of large phytosociological tables and databases. This software, with a current maximum capacity of 30 000 relevés in one table, includes many functions for easy manipulation of table and header data. Various options include classification using COCKTAIL and TWINSPAN methods, calculation of interspecific associations, fidelity measures, average Ellenberg indicator values, preparation of synoptic tables, automatic sorting of relevé tables, and export of table data into other applications (word processors, spreadsheet programs or mapping packages). JUICE is optimized for use in association with TURBOVEG which is the most widespread database program for storing phytosociological data in Europe.     

Species groups can be transferred across different scales

Aim To test whether species groups (i.e. assemblages of species co‐occurring in nature) that are statistically derived at one scale (broad, medium, or fine scale) can be transferred to another scale, and to identify the driving forces that determine species groups at the various scales. Location Northern Bohemia (Czech Republic, central Europe) in the Je?tědský h?bet mountain range and its neighbourhood. Methods Three data sets were sampled: a floristic data set at the broad scale, another floristic data set at the intermediate scale, and a vegetation data set at the habitat scale. First, in each data set, species groups were produced by the COCKTAIL algorithm, which ensures maximized joint occurrence in the data set using a fidelity coefficient. Corresponding species groups were produced in the individual data sets by employing the same species for starting the algorithm. Second, the species groups formed in one data set, i.e. at a particular scale, were applied crosswise to the other data sets, i.e. to the other scales. Correspondence of a species group formed at a particular scale with a species group at another scale was determined. Third, to highlight the driving factors for the distribution of the plant species groups at each scale, canonical correspondence analysis was carried out. Results Twelve species groups were used to analyse the transferability of the groups across the three scales, but only six of them were found to be common to all scales. Correspondence of species groups derived from the finest scale with those derived at the broadest scale was, on average, higher than in the opposite direction. Forest (tree layer) cover, altitude and bedrock type explained most of the variability in canonical correspondence analysis across all scales. Main conclusions Transferability of species groups distinguished at a fine scale to broader scales is better than it is in the opposite direction. Therefore, a possible application of the results is to use species groups to predict the potential occurrence of missing species in broad‐scale floristic surveys from fine‐scale vegetation‐plot data.