While many paint the combined impact of climate change and global markets as something new, unpredictable, and unmanageable, they fail to grasp that most situations we are projected to see in the next few decades* have been experienced before in the form of previous extremes. Take, for example, the figure below:
This is a graph of the annual rainfall at one rain gauge in Ghana, near where I conducted the research that made up a big part of my book Delivering Development. The downward trend in rainfall is clear (and representative of the trend in this part of coastal West Africa that, according to my colleagues at IRI, continues to this day and is confirmed by satellite measurements). There are complex things happening inside these annual figures, including shifting timing of rainfall, but for the purposes of discussion here, it serves to make a point. While there is indeed a downward trend that continues to this day, there have already been several years where the total precipitation was much lower than the current average precipitation, or the likely annual precipitation for the next few decades.
This means is that the farmers in Dominase and Ponkrum, like so many around the world, have already seen the future – that is, they have already lived through at least one, if not several, seasons like those we expect to become the norm some decades in the future. These farmers survived those seasons, and learned from them, adjusting their expectations and strategies to account for the possibility of recurrence. These adjustments are likely over- or under-compensating for the likelihood of recurrence right now, as livelihoods strategies in these villages are largely reactive, reflecting last season’s events more than the average season. Further, the year-to-year hedging of farms against climate variability can be a costly practice – the likely “insurance premium” of lost production in a good year (due to planting in less-than-ideal, but precipitation-hedged situations like the tops and bottoms of hills – see my discussion in Chapter 4 of Delivering Development) probably eats up somewhere between 10% and 20% of total potential production. So these management strategies are not ideal. But they do reflect local capacities to adjust and account for extreme conditions, the extreme rainfall or drought events out along the tails of historical distributions whose unpredictable recurrences characterize a changing climate regime. Many of these farmers have little or no access to inputs, limited to no access to seasonal forecasts, and live in states without safety nets, yet they have repeatedly survived very difficult seasons. Clearly, their capacity for survival in an uncertain environment and economy is worthy of our respect.
This is not a phenomenon specific to Ghana. For example, the farmers in southern Mali with whom I (and many others) have been working to deliver better and more relevant climate services, such as seasonal and short-term forecasts. Most, if not all, of these farmers are using local indicators, such as the flowering of a particular tree or the emergence of a particular insect, as indicators that help them time various activities in their agricultural cycle. Many trust their local indicators more than the forecasts, perhaps with some reason – their indicators actually seem to work and the forecasts are not yet as accurate as anyone would like. But these indicators work under current climate regimes, and these regimes are changing. At some point, the tree will start to flower at a different, perhaps less appropriate time, or simply cease to flower. The insect will emerge at a different time, or perhaps be driven away by the emergence of new predators that can now move into the area. If the climate continues to change, local indicators will eventually fail.
I humbly suggest that instead of reengineering entire agroecological systems and their associated economies in the here and now (a fairly high risk enterprise), we should be building upon the capacities that already exist. For example, we can plan for the eventual failure of local indicators – we can study the indicators to understand under what conditions their behaviors will change, identify likely timeframes in which such changes are likely to occur, and create of new tools and sources of information that will be there for farmers when their current sources of information no longer work. We should be designing these tools and that information with the farmers, answering the questions they have (as opposed to the questions we want to ask). We should be building on local capacity, not succumbing to crisis narratives that suggest that these farmers have little capacity, either to manage their current environment or to change with the environment.
Farmers in the Global South have already fed the future. Perhaps they did not do it all that well, and all they managed was to stave off catastrophe. But given the absence of safety nets in most places in the Global South (see Theme 3, points 2 and 3), and the limited access so many farmers have to inputs and irrigation, avoiding catastrophe is an accomplishment that warrants study and serious consideration. We should build on that capacity, not blow it up.
The key principals and points:
1) A future under climate change is not a great unknown for farmers in the Global South. Most farmers have already managed several seasons as difficult, or more difficult, than what we project to be normal in the next few decades. Presuming these farmers are facing a catastrophe they cannot see coming fails to grasp the ways in which these past seasons inform contemporary planning.
2) Farmers have already developed strategies for addressing extreme seasons (i.e. drought or excessive precipitation). We should start with an understanding of what they already do, and why, before moving in with our interventions, lest we inadvertently undo otherwise functional safety nets.
3) Existing indigenous strategies for managing climate variability are not perfect. They tend to overestimate or underestimate actual risks of particular weather and climate states, tend to magnify the importance of the previous season (as opposed to historical averages, or current trends) when planning for the next season, and tend to be very costly in terms of lost potential agricultural productivity.
4) Current indigenous tools for making agricultural decisions, such as local indicators, are likely more robust than any climate product we can deliver right now. Just because this information comes in the form of a plant or animal behavior does not make it any less valid.
5) Current indigenous tools for making agricultural decisions will likely start to fail as climate regimes change. This fact presents an opportunity for development organizations to start working with farmers to identify useful information and ways of providing it such that this information is available when local indicators fail.
*Given the propagation of uncertainty in models of the global climate, global water availability, global land cover, the global economy, and global population (all of which, incidentally, impact one another), I don’t pay much attention to model results beyond about 2040, with 2030 being the really outer threshold of information that might usefully inform planning or our understanding of biophysical process. On the 100-year scale, we may as well be throwing darts at a wall as running models. I have no idea why we bother.