Tag: UKADR

Having very recently attended the March UKADR conference, organised by the Cabot Institute here in Bristol, I did so with some hope and anticipation. Hope and anticipation for displays and discussions that conscientiously touched upon this volta, this need for change in how we study the dynamics of natural hazards. The conference itself was very agreeable, it had great sandwiches, with much stimulating discussion taking place and many displays of great skill and ingenuity having been demonstrated. Yet, despite a few instances where this need for change was indirectly touched upon by a handful of speakers and displays, I managed to go the entirety of the conference without getting what I really wanted, an explicit discussion, mention, susurration of the role of emergence in natural disaster and resilience.

My interest in this kind of science is essentially motivated by merit of my Ph.D. research, here at the School of Geographical Sciences in Bristol, broadly concentrating on modelling social influence on, and response to, natural perturbations in the physical environment, i.e. urban flooding scenarios. From the moment I began the preliminary work for this project, it has steadily transformed into a much more complex mise-en-abyme of human inter-social dynamics, of understanding how these dynamics determine the systems within which we exist, both social and physical, and then the broader dynamics of these systems when change is enacted from within and upon them externally. A discipline known broadly as Complex Physical and Adaptive Systems, of which a very close theoretical by-product is the concept of emergence.

An enormous preoccupation throughout my research to this point has been in developing ways to communicate the links between these outlying concepts and those that are ad unicum subsidium. Emergence itself is considered a rather left-field concept, essentially because you can’t physically observe it happening around you. Defined, broadly, as a descriptive term whereby “the whole is greater than the sum of the parts”, it can be used to describe a system which is characterised by traits beyond those of the individual parts that comprise that system, some examples include a market economy, termite mounds, a rainforest ecosystem, a city and the internet. Applying this concept to human systems affected by natural disasters, to interpret the dynamics therein, is quite simple but due to the vast inter-disciplinary nature of doing so is seen as being a bit of an academic taboo.

So then, I remind myself that I shouldn’t feel downhearted, I saw clear evidence that we, the academic community, are certainly asking the right questions now and more often than ever before;

• “How do we translate new methods for vulnerability and risk assessment into practice?”
• “Are huge bunches of data, fed through rigid equations and tried and tested methods, really all we need to reduce the impacts of vulnerability and exposure, or do we need to be more dynamic in our methods?”
• “Are the methods employed in our research producing an output with which the affected communities in vulnerable areas can engage with? If not, then why not and how can this be improved?”

Upon reflection, this pleased me. These questions are an acknowledgement of the complex hazard systems which exist and indicate that we are clearly thinking about the links between ourselves, our personal environment and the natural environment at large. Furthermore, it is clear, from the themes within these questions, that academia is crawling its way towards accepted and mainstream interdisciplinary method and practice. I am pleased, though not satiated, as I witnessed a discussion in the penultimate conference session where “more data and community training” was suggested as a solution to ever-increasing annual losses attributable to natural disasters globally. I am inherently pessimistic, but I am as unconvinced by the idea of Huxleyesque, neo-Pavlovian disaster training for the global masses as I am unmotivated by the value of my research being placed in the amount of data it produces to inform such exercises!