 that we are following and proposing also then to apply to other parts of the world. That sets the stage then for the subsequent presentations that go into more detail. David is the Strategic Planning and Impact Assessment Specialist at URI. Okay, thank you Akim for that introduction. This is just a very brief introduction actually to the following three presentations. But the three presentations you're going to hear, they're actually part of the same study. So this provides an overview of the architecture and the rationale that links them together. Now, this study is overall a priority assessment or a priority setting study. So the objective is really to use structured information concerning impact potential to inform our resource allocation across different research opportunities. At URI, this actually hasn't really been systematically undertaken since the early to mid-1990s. We've had a lot of strategic planning exercises since then. We've thought about the impact of different projects and components of the portfolio, but a comprehensive exercise to compare all the options that URI could pursue hasn't taken place in the last 15 years. So a renewed effort is long overdue. So what we intend with this analysis is basically to have an evidence-based approach for orienting the Asian component of risk towards the portfolio that maximizes impact potential. And that is not only through the product and findings, but it's also through the process and the educational role that it plays. So we intended this study is a participatory study with the scientists across the Institute of URI as well as certain partners, and the idea is really to engage those scientists in the process without overburdening them and in the process that we get more of a consensus about how impact can be achieved, what these concepts mean, what our assumptions are, and how we can move forward. In the end, the product that we're looking for will be evidence for strategic decisions about future directions, but we don't want to fall into the trap of becoming overly mechanistic. We also hope to lead to increased clarity about our research products, the resources required to produce them, and the assumptions that underpin our expectations of impact. That also is feeding into a reorganization of the research structure for URI that is also accompanying risk. Now the structure of this analysis, the key overall intended findings are estimates of the economic poverty and environmental benefits in Asia resulting from specific investments in different potential URI research areas. And this is being conducted in parallel to the exercise by Africa Rice that you just heard about, but we have different data and resources so we're pursuing slightly different methods but oriented towards the same ultimate questions. Our analysis has been organized into what you could call a series of steps. We start with background analyses, then we have working groups who look at problem prevalence and then scientific solutions to those problems. Then we do calculations of impact potential from that information that's generated and that will ultimately feed into decision making later. It's overseen by an interdisciplinary strategic assessment task force that represents senior scientists in different disciplines across URI. So the first stage in that flow chart that I just showed would be the background analyses. This started with some background intelligence collection, particularly putting together some data on documented adoption to date, what is known about adoption to date for different areas of research and information on what other actors and partners are doing, and where they're investing their research efforts. Now this is kind of soft background information that's fed into the process later rather than a specific output. Then we went into actually preparing the background for the second stage, the working group activities of looking at problem prevalence and scientific solutions. So a big part of that was first to define the unit of analysis. The unit of analysis we're doing that we decided on a new set of agroecologies and set of agroecologies that integrate cropping systems elements with the traditional rain fed irrigated and seasonal considerations. That will be presented along with the next analysis that I'll mention in the next presentation. We then also decided that because many URI technologies are oriented towards closing yield gaps, the gap between actual on-farm yields and what you can consider attainable yields, that we really needed to get a handle on how those yield gaps are likely to evolve over time. And that is a good cross-check on what we think individual research solutions can deliver to close those gaps. So that's what you will also hear about in the next presentation, the way we've done that through a spatial approach. So we're following this yield gap framework, just to explain what I previously mentioned, where a large share of URI's portfolio is really oriented towards closing the gap between actual on-farm yield and what is attainable, given water and other unchangeable limitations at the farm level. So those are technologies that are oriented towards reducing losses from abiotic stresses, reducing losses from biotic syndromes, and for increasing the efficiency of input use so as to raise actual on-farm yields. All of those have to operate between the attainable yield and the actual yield, so that's the envelope for those improvements. So that's why we put a fair amount of effort into trying to look at that envelope. After the background analyses, then we've had these working groups of scientists. These working groups have been broken into six core problem opportunity categories. The first would be biotic yield reducers. The second would be abiotic stresses or yield limiters. The third would be efficiency gaps. The fourth would be quality and nutritional content. The fifth would be freestanding policy problems that aren't reflected in the other groups, and then the sixth is really an opportunity category, and that's yield potential. So each of these six groups has a core set of scientists who've been heavily engaged in putting together information and leading the later scientist elicitation process. Their first task was really to define the problem prevalence, the magnitude and distribution of the problem or opportunity that those that fall within that working group's mandate. So for each of those key problems or opportunities that try to characterize as best they can, the distribution, magnitude and frequency of the problem by subregion, by ecology under this new framework of agroecologies that we've developed. And they've also tried to think about how that is likely to change over time. And then for each of those problems, they've defined solutions. So intersections of what we've called under the GRISP are products or in the older CGIR terminology outputs, how those intersect specifically with the different constraints in a very concrete and discernible way. And so we've termed those things as solutions. They're in a finer level than the products that you would find in the GRISP document. For each of those solutions, the scientists have worked together to think about really what's required on the scientific side in order to get to an effective solution that could be delivered. So they've looked at the investment required, the number of years required before the solution would actually be available. They've looked at the probability of success and assumptions affecting success and reaching a solution that functions well. Alternative suppliers and when they would be likely to deliver the solution if international effort isn't devoted to that particular solution. For each of those, then, they've also gone through and they've tried to look at the effects expected in the field in terms of likely adoption profiles and different points of time, expected on-farm costs and benefits changes to input-output use as a result of adoption, as well as environmental externalities that would be associated with the changes in practice and vision and what kind of delivery and extension requirements are necessary in order to actually achieve the levels of adoption that they forecast. This is a process that we're mostly through, but it's still ongoing. It's been a long iterative process of scientists coming together, making estimates, then us more collectively reviewing those estimates and then going back and giving feedback to the scientists who originated the estimates, making revisions and slowly adjusting things until we get to a set of estimates that we all feel we have good confidence in to the degree that's possible. We will then, as I mentioned previously, we'll also do some more triangulation by looking at what we expect in terms of gains compared with the evolution of yield gaps. Once we go back and get those estimates more finalized, then we'll start to use them with our survey data to look at what they really mean in terms of input-output effects and effects on the unit cost of production. That would be used in the trade model to look at the price effects of the changes in the unit cost of production. With that price response and the on-farm data, then we can start to look at what the actual farm level changes in revenue and benefits are. We will then do distributional analysis to try and identify how they also particularly work out for poor consumers and producers. We will also have a supplementary exercise to look at environmental and health impacts. Using both the environmental effects from the on-farm adoption as well as more indirect effects through land use change. Just to give you a flavor of the kinds of findings we intend to have at the end of the process without revealing the second presentation, there was a somewhat similar exercise undertaken a few years ago by the International Potato Center. It revealed some quite interesting kinds of findings. It showed, for example, that there was a great difference between the cost efficiency in terms of raising one person out of poverty between research to raise productivity and value-adding market chain research. It showed that there was a relative disparity between the share of poverty impact expected across their two commodities relative to their actual allocation of the research portfolio. It also showed great differences in terms of what was expected across different regions.