ANÁLISIS DE LA LONGITUD TELOMÉRICA POR TERMINAL RESTRICTION FRAGMENTS-SOUTHERN BLOT (TRF SOUTHERN

Part of the inductive approach previously described in the methodological approach of this document (Chapter 3.2), refers to the investigation of how humans interpret, or attach meaning to, situations (Pathirage et al., 2008). Using informal interviews, or open-ended interviews, data can be extracted from which interpretations are made to inform research (Ellen, 1988). Thematic analysis of comments extracted during informal interviews searches for themes and patterns derived from, inter alia, feelings, vocabulary, conversation topics, ideas, and experiences (Ellen, 1988; Aronson, 1994).

Informal interviews were carried out with visitors who stopped to look at the main viewing point and who were close enough to be amicably and amiably approached at the time. Care was taken to maintain uniformity in the initial approach to the visitor(s). This consisted of the question and statement; ‘Are you interested in the cattle? I am part of the research team from the University of Salford looking at the effects of the cattle grazing.’ Or ‘Are you interested in the cattle, I am studying the effects of the cattle on the salt marsh.’ Given that the interview maintained an informal approach (no clipboard or luminous tabard), the conversation was allowed to flow as the visitor either engaged in conversation or not. For visitors who showed an interest, it was explained that the cattle were being used as a natural conservation instrument that improve the ecology of the salt marsh as they engineered a habitat that would be favourable to avifauna and flora. Care was taken to use lay terms such as ‘nature’ instead of ‘ecology’ or ‘biodiversity’ and ‘a mixed environment with lots of variety’ instead of ‘heterogeneity’. Of those with whom informal interviews took place, salient comments regarding their opinions, viewpoints, and any relevant information were transcribed for later content and thematic analysis.

Content analysis of texts and documents using a content cloud (aka. a tag cloud) has been used to visualise and summarise text within documents (Cidell, 2010; White, 2013). Content clouds have been in practical use since a ‘mental map’ of Paris was created by Stanley Milgram, a social scientist, who used the frequency of words used by interviewees’ responses to geographical questions related to that city in the early 20th century (Crown, 2013b). Based on the

122 frequency of words used, content clouds allow visualisation of text, to create an overview which hierarchically displays common words (White, 2013). Words within documents with a higher occurrence are presented in a larger font

through a series of algorithms so that interpretation of the text is carried out in a participatory visualisation technique (Viegas et al., 2009). Content clouds are used intensively in social internet media to indicate main themes of discussion in social media interfaces (Mishra and Mishra, 2012).

Transcribed comments made by visitors were entered into a document and a tag cloud was created using the Wordle™ software (Wordle.net, 2011). Wordle™ is freely accessible on the internet and has recently been used as a tool to generate a consensus of the understanding of ‘sustainability’ (White, 2013). Other well-known use of tag clouds for content analysis has been carried out on United States presidential speeches (White, 2013).

Comments were first manually ‘stemmed’ to disengage any letters which could alter the frequency count by the Wordle™ program (Wordle.net, 2011; White, 2013), especially with possessives and plurals for example. Examples of this include ‘river’s’ to ‘river’ and ‘chemicals’ to ‘chemical’. Colloquialism was also taken into account and words removed which may skew results; the word ‘like’ is often used by locals as a suffix to a sentence to add weight to the statement, an example would be;

‘Any problems with the cattle? What with it being down here and all like’.

The ‘like’ replacement occurred on six occasions. Plural form was replaced in ‘chemical’ to ‘chemicals’ and from ‘cow’ to ‘cows’ on two occasions each.

An initial overview of content clouds showed ‘used’ and ‘to’ as separate high incidence words, this overview revealed these to be part of comments pertaining to the history of the personal experiences and observations around research area, for example;

‘There used to be Lapwing when the cattle were here, maybe

123 The words ‘used’ and ‘to’ were joined using the tilde symbol, ‘~’, to show this phrase as one element within the comments. This occurred on twenty occasions.

For clarity and ease of visualising, the Wordle™ program automatically removes common English words including all pronouns and articles. This creates an issue where comments have naturally included pronouns to replace the cattle or another facet, examples of this were;

‘Have you seen the size of the horns on them?’

In this example the visitor is using the pronoun ‘them’ to refer to the cattle. Or another example;

‘There’s a few dinners in there. They’ve been here all week.’ (Referring to the geese).

In this case the visitor is referring to a flock of Canada Geese, in ‘They’ve’, on the salt marsh.

The comments were individually analysed and pronouns describing nouns were replaced where necessary. In the above two examples, ‘them’ was

replaced by ‘cattle’ and in the second example, ‘They’ve’ was replaced by ‘geese’ (Table 28).

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Table 28: Pronouns replaced from informal interview comments with number of times this occurred.

Word Number of pronouns replaced

cattle 55 people 5 council 3 farmer 2 geese 2 drugs 2 kids 2 birds 1 merlin 1 redshank 1 widgeon 1 corncrake 1 lapwing 1

The number of words to be displayed in the content cloud was set at 33, this figure was derived by compiling a frequency table and observing where natural breaks took place (Figure 41).This was found to be more or equal to seven occasions. This process also aided in engaging further with the text to extract themes for later thematic analysis.

Thematic analysis of interviews follows a funnelled approach to discerning themes (Blaxter et al., 2010). This begins with an overall view of the text to begin understanding themes and ideas which may be flowing from them, an initial start is made on coding text, based on the texts’ common aspects, these are refined as the process goes on to a point where the results can be strongly backed up with examples from the text (Blaxter et al., 2010).

125 0 5 10 15 20 used to come back good people grass now seen to see see year go much wildlife geese look area birds get nature always around day days grazing lapwing like lot old saw think years chemicals cows last many nice time walking better canal idea kids lad

Frequency of occasions word appeared.

Wor d s i n t e xt.

Figure 4134: Frequency of appearance of words in informal interviews. The word ‘cattle’ has been removed for clarity. The frequency of ‘cattle

n = 101. Red line indicates the cut-off for words included in the wordle image.

126 Informal interviews were carried out during the grazing period of 2011 and 2012. During the grazing period of 2011 these coincided with the unobtrusive observation surveys described in Section 8.2.1. During 2012, informal

interviews were carried out in a similar opportunistic manner although the categorical observations had ceased for this period as these data had

generated sufficient results for the case study. The timing of the observations was determined by a random number table generated in Excel selected (using the =RAND (between) function in Microsoft ® Office Excel ® 2007). In addition to the 70.5 hours of opportunistic interviews carried out in 2011, a further 32.0 hours were completed in 2012.

The survey schedule for the 2012 grazing period was severely altered by precipitation. The Met Office reports that the summer of 2012 showed the highest level of rainfall for the UK for 100 years. For June, July and August of 2012 the total rainfall was 371mm of rain equating to 154% of the average for 1981-2010 (Crown, 2013b). For the months between April and September for the two years, the mean precipitation for the periods was 76.79mm (s.d.+/- = 29.96) and 123.58mm (s.d.+/- = 40.53) respectively; these data are displayed in tabular form in Table 29.

Table 29: Precipitation data for the summer period (to include September) for North Western England and Wales, supplied by the Met Office Hadley Centre, shown in millimetres. (Crown, 2013b).

Year April May June July August Sept Total Mean s.d

2011 (mm) 28.0 79.9 72.7 77.7 97.1 105.3 460.7 76.78 26.96

2012 (mm) 98.8 59.5 174.4 131.9 124.3 152.6 741.5 123.58 40.53

Comments recorded following informal interview were examined to discern recurring ideas and themes (Aronson, 1994; Kim and Kaplan, 2004). These comments and interviews supplemented the observations and allowed the examination of any possible motives and feelings that visitors to the

conservation area experience. Kim and Kaplan (2004) used interviews to augment observations in a similar fashion. Comments were grouped and analysed to derive main themes (Aronson, 1994). These themes were then matched with ecosystem goods related to the final ecosystem service of Environmental Settings.

127 As the process of thematic analysis was refined, comments were viewed using four basic questions:

1. What, if any, are the obvious underlying themes of the comment? 2. What are visitors deriving from the visit?

3. What constituent perception (benefit or detriment) is the intention from what is said?

4. What ecosystem service aspect of environmental settings is being engendered or highlighted?

The comments were viewed through these questions both from a hierarchical level (1 to 4) but also holistically so as not to limit or constrict the interpretation.

Patterns and themes were viewed from an emic perspective, that which

seeks to understand how people understand things at the ground level, in case studies for example, as opposed to an etic perspective which seeks to link results to studies conducted in other environments (Angrosino et al., 2007). The

emic perspective of the analysis was entered into with no pre-conceived ideas

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6.3 Results