**2.3.1 Final set elaboration**

A consolidated list of indicators was generated with all proposed elements from all the workshops and PRA sessions. This list was used as a basis for comparison, so that the presence of an element in both consolidated and stakeholder list was coded as "1" whereas the absence of element analogy was coded as "0" (Tab. 1).

The final C&I set should have both expert and local population acceptance, and be applicable to all forest use types. Regarding the single forest use type, only elements accepted by more than 50 % of the workshops and villages were accepted. The same

Setting Up Locally Appropriate Ecological Criteria and Indicators to

**Agglomerative**

finer groupings.

Evaluate Sustainable Forest Management in Dinh Hoa District (Northern Vietnam) 209

Given these similarity measures for all possible pairs of stakeholders, the data was organized into useful / meaningful groups, so that those within each group (cluster) were more closely related to one another than subjects in different clusters. Hierarchical clustering can either follow *agglomerative* or *divisive* methods (Janssen and Laatz, 2010; Manning et al., 2008). The output can be illustrated by a so called dendrogram (Fig. 4).

a, b, c, d, e

a, b c, d, e

d, e

**Divisive**

d e

Fig. 4. Example of a dendrogram with fictive data. The agglomerative method makes series of fusions of the n objects into groups whereas the divisive method separates n objects into

a b c

As a result of various ways of calculating the distance between the clusters (Janssen and Laatz, 2010; Manning et al., 2008), different fusion procedures exist for the agglomerative method. In *single linkage*, the distance between two clusters is given by the value of the shortest link between two objects of the two clusters. In *complete linkage*, the distance between two clusters is given by the value of the longest link between two objects of the two clusters. In *group average linkage,* the distance between two clusters is defined as the average of distances between all pairs of objects, where each pair is made up of one object from each cluster (Fig. 5). This type of linkage appears to be the most useful for this study, because it

Fig. 5. Examples of three linkage calculation methods (adapted from Manning et al., 2008). The average linkage method is used in this study for its use of all possible pairs of elements.

takes into account all the possible pairs of distances between the C&I sets.


counted for new elements proposed by villages which got incorporated if they were proposed by more than 50 % of villages under each forest use type (Fig. 3a and 3b).

Table 1. Binary representation of the stakeholders' perceptions (note: This table is made up and does not contain data of the study).

Fig. 3. Decisional Framework for the final set elaboration of indicators. To be accepted in the final list, an indicator had to be accepted by minimum 50 % of the expert workshops and 50 % of the villages for each forest use type.
