Similar a Towards a systematic framework for analysis of tools and approaches to integrate disciplines and other knowledge systems for biodiversity conservation
Similar a Towards a systematic framework for analysis of tools and approaches to integrate disciplines and other knowledge systems for biodiversity conservation (20)
Towards a systematic framework for analysis of tools and approaches to integrate disciplines and other knowledge systems for biodiversity conservation
1. Towards a systematic framework for analysis of tools and approaches to integrate disciplines and other knowledge systems for biodiversity conservation Dr Rosemary Hill Prof Iain Gordon Dr Leanne Cullen-Unsworth Dr Kristen Williams Dr Allan Dale Acknowledgements: ICEF organisers CSIRO Biodiversity Theme Co-researchers, partners Traditional Owners. July 2011
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4. Integrative science challenge: provide underpinning knowledge and tools for biodiversity conservation in this context of competing values, visions, knowledge, use
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9. Systemization issue 1: Different types of engagement between disciplines and other knowledge generation systems Tress, G., B. Tress, and G. Fry. 2005. Clarifying integrative research concepts in landscape ecology. Landscape Ecology 20 (4):479-493
10. Systemization issue 2: differences in philosophy, theory, research strategy (methodology), method Cf. Khagram, S., Nicholas, K.A., Bever, D.M., Warren, J., Richards, E.H., Oleson, K., Kitzes, J., Katz, R., Hwany, R., Goldman, R., Funk, J., and Brauman, K.A., 2010: Thinking about knowing: conceptual foundations for interdisciplinary environmental research: Environmental Conservation , 37, 388-397; Crotty, M. 1998. The Foundations of Social Research . Sydney: Allen & Unwin.
11. Systemization issue 3: nesting of philosophy/ theory/ strategy can leads to significant perceptual gaps
13. Perceptual gap Status and trends of wet tropics environment Indigenous cultural indicators of wet tropics environment
14. Systemization approach 1: matching tools Common data collection tools: Field based protocols and tools, citizen-based data collection, adaptive management experiments Methods Common platform tools: Simulation and integrative models that can combine multiple data sources, radar plots, Bayesian Belief Networks, Mind-mapping software applications Research strategy (methodology) Topic-focused dialogic tools: Scenario-generation, dynamic systems conceptual models, common vision tools (e.g. collaborative planning for habitat) Theory Deep dialogic tools: Place-based learning communities; principles of Indigenous governance, cooperative frameworks Philosophy Relevant integrative tool Nested hierarchy
15. Systemization approach 2: prioritizing tools Common platform tool: Computer models that can integrate data, radar plots, score-card. Status and trends of wet tropics biodiversity soils, landscapes Low Research strategy Focused dialogic tool: dynamic systems conceptual modelling Why biodiversity declines when protected areas increase Medium Theory Inter- disciplinary Focused dialogic tool: Participatory scenario generation, participatory modelling Habitat Network Action Plan High: Theory Deep dialogic tools: Indigenous governance, relationship-building cooperative framework Indigenous cultural indicators Very high Philosophy Trans- disciplinary Priority tool selected Our example Perception diversity (Issue 3) Highest level (Issue 2) Type (Issue 1)
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17. Thank you Ecosystem Sciences Division Social and Economic Sciences Program Human Geography and Planning Group Dr Rosemary Hill Senior Research Scientist Phone: 0740595013 Email: ro.hill@csiro.au Web: www.csiro.au Contact Us Phone: 1300 363 400 or +61 3 9545 2176 Email: enquiries@csiro.au Web: www.csiro.au
Notas del editor
Thanks very much. I just like to start by acknowledging my co-authors, and also conference organisers and thanking them for the opportunity to present today. I’d also like to acknowledge CSIRO who supported my conference attendance, our co-researchers, partners and in particular the many Aboriginal Traditional Owners who have contributed to this work.
In this presentation, I’m going to firstly describe the context of our research in Australia’s globally significant tropical forests. I will then present the three key issues we have identified as critical in developing a systematic framework for analysis of interdisciplinary approaches. I will describe the two steps in our systemization framework and finish with some concluding remarks about future directions.
This framework for systemisation draws on research experiences within a particular context: ongoing efforts to achieve conservation of Australia’s humid tropical forests. These forests stretch in a narrow band between about 500 km Townsville and Cooktown on Australia’s north-east coast. They are recognised as a living record of the evolutionary processes that shaped Australian flora and fauna. Some 900,000 ha are listed as a world heritage site for their natural values. However, many important areas of habitat remain outside the protected area estate with multiple and contested values, for example to Indigenous peoples, agriculture, tourism, for lifestyle. There is ongoing forest lost from land use change to accommodate some of these values. In addition, two severe tropical cyclones have crossed the coast in the last five years, highlighting the vulnerability of the habitat and the need for enhanced protection
The interdisciplinary science challenges we report are contextualised in the overall goal to provide the underpinning knowledge and tools for biodiversity conservation in this context of competing values, visions, knowledge and uses of the landscape. We acknowledge there is a value-basis and normative dimension here. We define interdisciplinarity broadly as work that achieves a signification transformation of knowledge through the integration of ideas or tools typically used by different disciplines or knowledge-generation systems (drawing on Khagram et al).
Interdisciplinary experiences have been numerous – here are a few examples we have been closely involved with. We used participatory scenario generation, bringing together biophysical, social and institutional data within action co-research approaches to build integrated understanding and an agreed local Habitat Network Action Plan. We developed a cooperative research approach with Indigenous peoples to generate linked cultural-biophysical indicators, which relied on principles of Indigenous govenance, common problem framing, relationship-management and scale sensitivity. We used radar plots and score-cards to integrate biodiversity, landscape and soils data for a prototype indicator framework of the status and trends of the wet tropics environment. Other applications have included the use of dynamics system modelling to understand how links between governance, public discourse, extinction debt and increased public access to biodiversity in protected areas influences biodiversity change. These experiences, together with the existing literature on interdisciplinary research, provide the basis from which we are developing this systematic framework. It should be regarded as a work in progress and we would appreciate feedback and input from today’s session.
The first systemisation issue we identify is that of clarifying how the engagement between disciplines and other knowledge-generation systems is conceptualised. We think broadly about interdisciplinarity here, based on our definition given earlier that is essentially about transformation of knowledge through integration. This diagram from Tress et al. is very helpful to clarifying the nature of the engagement between disciplines. We have encountered using the generic term “interdisciplinary research” to what can be recognised as three different types of engagement between disciplines – multi-disciplinary, transdisciplinary and interdisciplinarity. Systemisation is aided by discriminating between the three, particularly in relation to the integrative approach. Multi- disciplinary research with separate goals, requires integrating the knowledge after it has been delivered by the disciplines. Interdisciplinary research crosses disciplinary boundaries to deliver knowledge to a common goal, requiring integration along the way – but subsequent integration with society. Transdisplinary research brings disciplines together with non-academic participants and builds the integrated knowledge between science and society throughout the research endeavour.
The second systemisation issue we identify regards differences in theory, research strategy and philosophy that occur within academic disciplines. and also within other knowledge-generation systems, such as local and Indigenous knowledge systems, that might be encountered in the conduct of transdisciplinary research. We conceptualise these as linked in a nested hierarchy, drawing parallels with the work of Michael Crotty, and also drawing on Khagram et al’s recent paper. Philosophy addresses issues of epistemology and ontology, eg. positivist, interprevist contructivist, and to which we have added Indigenous holism of our Indigenous cultural indicators research. theory addresses what is understood to be theory (for example predictive or explanatory theory) as well as the key concepts underpinning the research, e.g. linked social-ecological systems, in the example of the Indigenous cultural indicators. Methodology (or research strategy) refers to overall plan that underpins the specific methods deployed e.g. qualitative social research. Understanding the differences at each level in this hierarchy is critical to integration across disciplines
The third systemisation issue arises because philosophy, theory, methodology and methods are clearly linked in most research endeavours. We use the metaphor of a lens to illustrate how inquiry into the external reality through linked philosophy-theory-methodology illuminates certain aspects of the external reality. In this example, the lens generated for the Indigenous cultural indicators research illuminates aspects including Indigenous rights and interests, heritage and spiritual values, and participation in management. This illumination process can also be seen as an interpretation or construction – a result of the linkage between the external reality and the nested set of research practices. The key point is that very different lens can inquire into the same external reality (or research question) and illuminate entirely different entities.
For example (next slide), the assessment of status and trends of the wet tropics environment to produce the prototype indicator framework, used a positivist paradigm, drawing on theory about ecosystem services, biodiversity and natural landscapes, the pressure-state-response methodology to engage multiple data sets and produce a common platform based on radar plots and score-cards.
The status and trends focused attention on native extent and condition, number of species while the Indigenous cultural indicators highlight some very different aspects of the same research environment. The size of such perceptual gap that may exist influences what we need to do to achieve integration of knowledge.
We now turn to our systematic framework, which involves two systemization steps. The first step involves recognition that different tools are more effective for integration for different parts of the nested hierarchy of research practices. Differences in philosophy require tools that enable deep discussions of underlying differences in ontology and epistemology – for example, when working with Indigenous communities, attention to Indigenous governance and cooperative frameworks that establish principles for research. Place-based learning communities that enable interaction between researchers and practitioners over many years are gaining recognition as key to achieving integration across philosophies. At the level of theory, tools that enable the different theories being used to be discussed and applied are highly relevant – for example, scenarios, conceptual dynamic system models, and real-world collaborative planning exercises. Integration at the level of methodology involves bringing together out puts from various research applications for example bringing weed distribution models together with remote sensed vegetation – simulation and integrative models, radar plots, BBN networks and mind-mapping software is useful here. Finally integrating at the level of methods can be supported by common data collection protocols, and the design of adaptive management experiments.
Interdisciplinary research projects would no doubt benefit from the application of such tools at all levels throughout the research project. However, as in all endeavours, resources are not limitless, so prioritizing the right tool to the research challenge is important. Our second systemization approach involves consideration ot the three issues in systemisation. The first challenge is to clarify the nature of engagement between disciplines. Transdisciplinary projects that engage non-academic participants are more likely to benefit from dialogic tools, without too much technical complexity. After that, consideration should be given to the highest level in the nested framework where differences are likely to be encountered, and then to size of the perceptual gap.
In conclusion, we have identified the key challenge in interdisciplinary research as how to bring together multiple disciplines and integrate their findings. We have identified three issues that need to be addressed in systemization of approaches, and developed an initial two-step framework for such systemization. Finally, we see that the sustainability challenges in the wet tropics highlights the need for integrated knowledge between science and society – rather than the old approach of integrating knowledge in the academy and then trying to hand it to society. We see this as the key area for future development of interdisciplinary science.