Category Archives: Land management

Cartography of Global Cropping Systems

In this era of big data, sophisticated computer models and near ubiquitous satellite remote sensing estimates, it’s amazing how limited we are in our ability to map cropping systems at a global scale. My colleagues at IFPRI and I investigated this issue in a recent study released in Global Ecology and Biogeography. Also see the IFPRI blog post for a short take on the issue and some additional info on IFPRI’s SPAM model.

The problem is that while developed countries have begun to map their crops, most developing countries simply don’t have the resources to do so. Data is often only available through national or sub-national statistics, which provide limited spatial information (none beyond the administrative boundaries associated with the statistic). This data constraint makes mapping crops in a spatially explicit manner difficult to say the least.

Our analysis looks at differences between the four major models used to map global cropping systems (M3, MIRCA, SPAM and GAEZ) as well as the implications of those differences for subsequent food security analyses. The differences between the models is significant for not only the crop-specific information, but even the extent of cropland delineated by each model. Below is a figure from the analysis showing the differences in the cropland extent:CroplandExtentComparison2

While it may seem unsurprising that these differences have implications for food security analyses, such as calculating the global yield gap, this has yet to be widely recognized. For example, having calculated the global yield gap using each of the four data sets, we found that the differences in the results were even larger than the estimated yield gap itself (i.e. the average from the four models).

Improving spatial understanding of crop production systems is a vital part of providing accurate analyses of global food security. Recognizing that the differences between models is significant is only the first step. Moving forward, we need to begin to reconcile these differences by evaluating external information against each of the four models to provide an indication of confidence in particular regions for each model, or more generally for each methodology.

How (and whether) to Disseminate Climate Forecasts

One topic that I’ve been interested in for a while now, but haven’t yet had the chance to explore in any depth is the way in which we disseminate drought forecasts. In this blog post I’d like to look a little further into how we disseminate, what we disseminate, and whether it makes a difference. The short version is this: we have thought quite a bit about what we provide, but surprisingly little about whether it is effective (cost or otherwise).

Numerous studies have explored the way in which we provide information (see here and edited collections here and here). They have made some real advances in shedding some light on how farmers’ make use of climate forecasts, as well as the estimated impact (i.e. whether farmers changed their responses in the context of a workshop participation).

As it turns out, farmers’ are quite capable of understanding and acting on probabilistic information. For forecasters, this is good news. One question that I would be interested in exploring further is whether the workshops required to train farmers to use forecasts is cost effective. This question relates both to the initial cost, and to the question of information retention. When testing principles in the context of daylong participatory workshops, we are unable to address issues such as usage retention (particularly following forecasts that do not match the eventual seasonal totals).

A related question, raised by a colleague of mine here at IFPRI, is whether we should really be providing the information to individual farmers or if it is more effective to provide the information to regional met agencies. Again, the question is not whether farmers are capable of using the forecasts, but rather whether providing them directly is cost effective in the long run.

The most pressing question, however, is in many ways the most obvious: do climate forecasts improve yields? A rigorous study (read randomized control) of the real-world implications of climate yields is badly needed as a means of addressing whether climate forecasts are effective. Although I understand the desire to provide a high quality product (accurate forecast) in a reliable manner, it is past time that we begin discussing the hard evidence of cost effectiveness.

Much time has been dedicated to studying climate forecasts, but surprisingly little has been invested in understanding what role climate forecasts are likely to play in improving livelihoods. We can’t afford to silo these questions any longer.

Workshop in Bhutan, building relationships

Workshop participants

Workshop participants in Thimphu, Bhutan

I’m recently returning from a workshop in Bhutan that colleagues here at IFPRI and I organized to address sustainable land management. The workshop was by most measures a tremendous success. It was well attended- including the Honorable Minister of Agriculture and Forests – the attendees were engaged in the discussion, and there was even local media coverage. It was refreshing to see real interest in scientific research coming from high-level members of parliament (something we don’t get much of in the US).

Yet the workshop also demonstrated the limitations of any single piece of research. The discussion among participants highlighted just how many different interests are at play in a project such as this. It’s impossible to provide a piece of research that addresses all of these needs simultaneously. In our study that manifested itself in our inability to include roads in our hydrologic model, which was a major discussion during the workshop. Although we do address the issue in the report, we could not incorporate it in a dynamic or quantified sense. This led to representatives from the Druk Green Power Corporation being honest in telling us that they would not be able to use portions of our research. This feedback is invaluable. It is only through this honest feedback that we are able to refine the methods and focus of our research.

These limitations made it immediately clear that ongoing collaborations are crucial for a project such as this. To build on existing relationships and extend past research is clearly a necessity when addressing complex issues, but it is not always the norm in international organizations. As we built on our relationships within Bhutan, we began to get a better understanding of the problem as well as some of the possible (and practical) solutions. Not only did we gain access to additional data of better quality over time, we also began to better understand the politics of the situation.

In research, exploring a problem in-depth can be a difficult sell to funding partners, which makes strategic project management important. Funding sources often (understandably) want to pursue novel ideas. This puts the onus on researchers to find ways of folding existing relationships and projects into new proposals as a means of continuing collaborations. Ephraim, here at IFPRI, for example, is using case-study countries as a means of maintaining (and funding) existing collaborations while simultaneously expanding his research into a new global scale. This is an example that I (and many researchers) would do well to follow.