Control remoto mediante la aplicación Sm@rtClient

McCune & Grace (2002) present an Indicator species analysis (ISA) in the multivariate software PC- ORD which determines and describes the value of individual species to a particular group and its associated environmental conditions, by combining information on the concentration of species abundance in a particular group and the faithfulness of occurrence of a species in a particular group.

68 Indicator values for each species are tested for statistical significance by a Monte Carlo permutation test with 999 runs.

PC-ORD 6.19 was used to conduct this analysis. All species with Indicator Values (IV) of 20% and higher and with Monte Carlo significance levels of higher than 95% (p < 0.05) have been listed as characteristic of groups. In cases where the cut-off level of 20% was not obtained, values between 10 and 20% were also reported, as long as the significance levels of p < 0.05 were met (Dufrêne & Legendre 1997). In some cases, there were no indicator species for a group. According to Sieben (2014), these communities can be regarded as “rump” communities, which are mostly characterized by the absence of certain indicator species.

The wetland types were assessed individually in order to obtain the species indicative of each separate type and its respective zones, regardless of whether this species may occur or be dominant in one of the other wetland types as well.

4.3.4 Weighted Averaging

For each relevé a community index was calculated using the approach of Scott et al. (1989). The following formula calculates the mean of the species’ index value, by weighting each species’ index by the relative importance of that species in the plot:









S

W

W

Where WA is the weighted average, Wi is the weight or importance of species i in the relevé, Si is the

index value of species i, and n is the number of species in the relevé. In this study, the weight (Wi) of

the species was determined using the species cover abundance values. These Braun-Blanquet values were transformed as follows (Table 4.2):

Table 4.2. The weight (Wi) value assigned to each species according to their Braun-Blanquet cover

values. Braun- Blanquet cover

values

Description of the cover values Assigned corresponding weight (Wi)

5 76 - 100% of the plot area 5

4 51 - 75% of the plot area 4

3 25 - 50% of the plot area 3

2 5 - 25% of the plot area 2

1 1-5% of the plot area 1

+ less than 1% of the plot area 0.5

r usually a single individual with negligible

69 All species with an ‘r’ Braun-Blanquet cover abundance value were removed prior to analysis due to the negligibility of the weight of the species.

The index value (Si) was determined using the ‘Annotated checklist of the wetland flora of southern

Africa’ (Glen unpublished). This checklist assigns a wetland indicator status based on the probability of occurrence in a wetland. Table 4.3 is an adaptation of Table 3.3, indicating the index value which was assigned to each wetland indicator status and used in the analysis.

Table 4.3. The criteria on which the wetland indicator status is based (adapted from Glen (undated)).

Wetland Indicator Status % Probability of occurring in a wetland Index Value

Obligate wetland plant > 99% 1

Facultative wetland plant+ 65–98% 2

Facultative wetland plant 50–64% 3

Facultative wetland plant– 25–49% 4

Upland plant 1–24% 5

The use of the term ‘Opportunistic plant’ in category 5 was replaced with ‘upland plant’. Glen (Unpublished) did not list all the plants which do not occur in wetlands, and therefore category 5 contains those general or pioneer species which do not have a place in any of the other categories. For the purpose of this study, however, the category had to be changed to be similar to that of Reed (1988) in order to be able to apply the weighted averaging scale indicated in Table 4.3.

According to Scott et al. (1989), it is accepted for the data collector to assign a species to a different category based on literature, and/or personal experience. Based on experience of the study area as well as consultation with the author of the Annotated checklist of the wetland flora of southern Africa (R. Glen pers. comm. 2015) the following species were moved between categories (Table 4.4): Table 4.4. The species that were assigned to a different Wetland Indicator category.

Species Wetland Indicator Status as per Glen

(Undated) New Indicator Status

Centella asiatica Facultative Facultative +

Cyperus natalensis Obligate wetland plant Facultative

Dactyloctenium

aegyptium Opportunist plant Facultative

Hibiscus cannabinus Opportunist plant Facultative

Hibiscus trionum Opportunist plant Facultative

Marsilea species Unlisted Obligate wetland

plant

Unknown species were removed from analysis. Species which could only be identified up to genus level was also removed. For a full species list with assigned values, refer to Addendum D.

70 The Weighted Averaging function in the multivariate software PC-ORD (McCune & Mefford 2011) was used to obtain a graphical representation of the WA scores of all the relevés along an axis. The software SPSS version 22 (IBM Corporation 2013) was used for other statistical analysis and graphical representations. Index values results are interpreted in the following manner, according to the method of (Tiner 1999) (Table 4.5):

Table 4.5. Criteria on the interpretation of the WA scores (Tiner 1999).

WA score Criteria

< 2 Site is a wetland

2 – 2.5 Site has a good probability of being a wetland, but soil and hydrology should confirm 2.5 – 3.5 Inconclusive regarding its prevalence to wetlands or uplands (other criteria must be

taken into account)

3.5 – 4 Site has a good probability of being an upland site, but soil and hydrology should confirm

71