Reingeniería de los procesos

Albert Einstein (1933)

Many current environmental issues, such as climate change, cannot be sufficiently addressed through a single disciplinary perspective but rather require an integrated view to address systems problems (Nicolson et al., 2002). Bridging perspectives and disciplines can effectively address systems problems and deal with complex processes over multiple temporal and spatial scales (Nicolson et al., 2002). Therefore, when dealing with complex social-ecological systems, an integrative approach to research is required and thus interdisciplinarity is valuable in that it is a means to solving problems and answering questions that cannot be sufficiently addressed through a single method or approach (Newing, 2011). As noted by Paterson et al. (2010: 782), “(i)ntegrative and transdisciplinary approaches are required to develop new attitudes, methods and solutions” to deal with increasingly complex environmental and social challenges that emulate at multiple scales. This thesis examines local social-ecological systems through an interdisciplinary perspective, which is underpinned by an over-arching research approach and design that bridges individual chapters to create an integrated picture of local systems under climate variability and change.

2.6.1. Approach

The over-arching approach for this thesis is associated with a pragmatist worldview that focuses on “the consequences of research, on the primary importance of the question asked rather than the methods, and on the use of multiple methods of data collection to inform the problems under study” (Creswell and Plano Clark, 2011: 41). Pragmatism is typically affiliated with mixed methods research as it is a well-developed and attractive philosophy for integrating approaches (Johnson et al., 2007). Ontology associated with a pragmatist worldview looks at both singular realities – which tests a hypothesis, and multiple realities – which provides perspectives; where researchers select the most appropriate data collection method to address questions through a practicality epistemology (Creswell and Plano Clark, 2011).

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Due to the nature of this study, the research strategy underpinning this project is based on inductive research. In contrast to deductive research where the researcher generates a specific hypothesis and designs data collection accordingly to test this specific theory, inductive research does not have a specific hypothesis (Newing, 2011). Rather, data collection is guided by a broad set of issues and these data are used to generate a theory or better understanding of the issues at hand. As there is limited understanding as well as knowledge gaps associated with how local climate is changing over time in the southern Cape and its possible impacts on natural resource users (such as farmers and fishers), an inductive approach is necessary to start with broad, open-ended research with the aim to build up detailed understanding of complex adaptive systems.

Local knowledge systems, together with natural and social sciences, can improve the understanding of how to care for social-ecological systems, as well as lead innovative or desirable pathways in the face of uncertainty (Tengö et al., 2014). Similar to the MEB approach described by Tengö et al. (2014) (refer to Figure 2.4), this thesis uses a parallel approach to bring together local climate knowledge from multiple sources, namely farmers, fishers and scientists. Drawing on existing work done by the SCIFR team, selected natural resource users are used as knowledgeable experts of their social- ecological systems alongside scientific data sources. This two-fold approach is interdisciplinary in nature in that it examines local knowledge systems in concert with regional climate data with the aim to build up a more comprehensive understanding of complex terrestrial and marine social-ecological systems of the southern Cape.

2.6.2. Design

A case study design, focusing on southern Cape farmers, fishers and local climate systems under the common theme of climate variability, is used to build a detailed description and understanding of this specific situation for the thesis. Case study design involves “detailed data collection about a single ‘case’ or situation” with the aim of contributing to its own understanding, as well as to add to broader theoretical understanding, to generate theories around underlying issues (Newing, 2011). The case study method in the context of this research is a way to better understand a real-life phenomenon, such as climate change, in depth – where this understanding encompasses pertinent contextual

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conditions, such as the realities of farmers and fishers operating in the southern Cape (Yin, 2009). Through linking different climate knowledge systems, drawing on knowledgeable resource users and local climatic data, the detailed case study undertaken for this thesis aims to better understand the southern Cape social-ecological system.

2.6.3. Methods

Research can be characterised based on various methods employed that are categorised through data collection and analyses. Examples of different research characteristics are determined through methods such as quantitative, semi-quantitative and qualitative tools (refer to Table 2.3), where different data collection and analyses tools are used that best suit the characteristics of what the research is examining. At a basic level, quantitative and qualitative research can take different positions when examining epistemological questions around the nature of knowledge (Newing, 2011): for example quantitative research can focus on statistical significance to validate scientific knowledge; whereas qualitative research can argue that reducing complex problems to numerical values can result in losing knowledge. Different forms of quantitative, semi-quantitative and qualitative research provide can useful perspectives when examining complex problems, as the limitations of one method can be offset by the strengths of the other to work towards solutions of complex problems, such as understanding climate variability.

Table 2.3: Quantitative, semi-quantitative and qualitative characteristics for research (adapted from Newing, 2011)

Quantitative Semi-quantitative Qualitative

Characteristics

Correlations

Cause-effect relationships Statistical significance Different factor prevalence

Models Decision makers Stakeholders Scenarios Overview Disentangle complexity In-depth understanding Social and cultural context

Data collection Numbers Indicators

Observations

Non-numerical (e.g. words)

Data analysis Statistical _{Synthesize knowledge} Narrative account

Critical analysis

Studies that make use of both quantitative and qualitative elements are referred to as mixed methods studies in that they can combine the best of both approaches to gain complementary insights into an over-arching topic (Newing, 2011). In the realm of

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interdisciplinary research, mixed methods are the typical methodology of choice (for example Ommer, 2007), as it allows for an integrated approach to problems in complex systems (Creswell and Plano Clark, 2011). “Research problems suited for mixed methods are those in which one data source may be insufficient, results need to be explained, exploratory findings need to generalized, a second method is needed to enhance a primary method, a theoretical stance needs to be employed, and an overall research objective can be best addressed with multiple phases” (Creswell and Plano Clark, 2011: 8).

Mixed methods designs include the convergent parallel design, explanatory sequential designs, embedded design, transformative design and multiphase design (for details see Creswell and Plano Clark, 2011: 96). For the purpose of this study, the convergent parallel design is applied within the mixed methods approach. This design is used by researchers who make use of concurrent timing to implement quantitative and qualitative strands during the same phase of the research process where methods are prioritised equally. Each strand is analysed separately and then results are mixed during the overall interpretation (Creswell and Plano Clark, 2011). The convergent design is a practical method to acquire a more comprehensive understanding of the topic at hand and identify possible mismatches between data sets or different knowledge systems, in line with objectives of this thesis.

As detailed in Figure 2.5, each empirical chapter (Chapters Three to Five) in this thesis focuses on a particular set of methods for data collection and analysis, which is then synthesised in the final chapters (Chapters Six and Seven) – drawing on the convergent parallel design. Through the framing of a pragmatist worldview, data collection and analysis of this thesis are directed through a mixed methods approach that is interdisciplinary by nature. Data collection for this project was guided by a set of broad issues with the aim to generate a theory once sufficient evidence has been collected. For this particular research strategy it is important to find a balance between “defining a precise focus for the research and keeping an open mind so that you don’t predetermine the results” (Newing, 2011: 6). This thesis therefore examines climate variability in local terrestrial and marine social-ecological systems through the perspective of local farming and fishing communities of the southern Cape.

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Figure 2.5: Thesis layout based on the convergent parallel design for mixed methods (adapted from Creswell and Plano Clark, 2011)

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CHAPTER 3