By Joern Fischer
We’re working on both social and ecological issues here in Transylvania. One problem that we constantly face is the methodological trade-off between breadth and depth. To what extent should we investigate things in great detail? The advantage is that we specifically know how certain butterfly species respond to specific food plants; that we know exactly how different people in the village think about changes that are happening in the region; and that we know specifically which crop is grown in which field in a given year. Or should we go for less detail? If we want to make inferences about changes at a regional scale, we need to somehow cover a lot of villages, a lot of survey sites, and speak to many people. Doing this, however, means it’s impossible to cover things at the same level of depth.
The challenge then is obvious: how do we decide what’s the appropriate level of depth (or breadth)? The answer is twofold. On the one hand, it depends on the objective. If we want to inform policy at a regional level, it’s important that we cover things at a regional scale. Information that is too localized simply is not useful. On the other hand, we can try to achieve both objectives, at least at some level: through extensive surveys, we can cover large scales, and then at a subset of strategically chosen locations, we can try to address similar issues at greater depth. So for example, we might do a regional survey of butterfly occurrence; and combine it with more specific, and more intensive surveys at selected locations that link particular butterfly species to certain food plants. Or we might characterize villages in broad socioeconomic terms at a regional scale, but then do in-depth interview work at a small number of villages. This combination means we get the best of both worlds: both breadth (which is policy-relevant), but also depth, which is necessary to make sure we don’t oversimplify important issues when scaling up.
Issues of depth vs breadth are related to scale. Coarse scales require breadth; fine scales require depth. But they are also related to different disciplinary backgrounds and their specific epistemologies. What, for example, does it mean to know about butterflies? A landscape ecologist will be happy to have mapped the regional distribution of a whole suite of species, and probably is satisfied with basic presence/absence, or maybe abundance data. But a specialist will very likely consider this an over-simplified understanding of butterfly distribution – she or he might think about food plants, seasonal patterns in activity levels, year-to-year fluctuations in population sizes, and so on. The same is true in the social sciences. It is possible to find out something about villages through a basic questionnaire, and some socioeconomic data is often collected that way. But social scientists interested in local power structures or inequalities, or networks of people within a given village, are likely to find such questionnaires unappealing – or even just overly simplistic. The coarse scale approach, in their view, might mask critically important patterns.
When working on a social-ecological project, like ours, it is therefore important to move between different scales, different disciplines, and hence, different epistemologies. Collaborating in a group with different specialists, and generalists, only works smoothly if all team members can accept that there are many different ways of knowing, or of understanding the world. Such epistemological pluralism includes multiple scales, although it sometimes goes far deeper than just scales. The key is to have an open mind towards other ways of understanding the world – then there’s a good basis for interdisciplinary work.
Thanks to Ioan Fazey and Claudia Campeanu for interesting discussions on these issues in the last few days!