Tag Archives: ILRI

Research collaboration for global challenges: why it’s really hard

I spent much of last week at London zoo. It was the final conference of a project I have been involved in over the past four years on zoonoses, ecosystems and wellbeing in Africa. The conference highlighted the idea of ‘One Health’, a movement aimed at linking human, livestock and ecosystem health. The focus was on how to make this happen in the ‘real world’, so that both emerging and endemic zoonotic diseases can be tackled effectively.

Over the last few years, influenza, Ebola and now Zika have struck in different parts of the world, often with devastating consequences. The argument of those at the conference – and indeed of our project, the Dynamic Drivers or Disease in Africa Consortium (DDDAC) – was that better integration, and more interdisciplinary collaboration will make a big difference to the effectiveness of responses to disease, and a focus on ecosystems, poverty and wellbeing needs to be central.

There was certainly a great buzz at the conference, and beyond (#OneHealth2016 was one of the top trending topics on Twitter in the UK on the opening day!). We had some very high level speakers, from the head of the Wellcome Trust, Jeremy Farrar, to the Chief Scientist at the UK’s Department for International Development, Charlotte Watts, as well as excellent participation from a range of stellar researchers and students working on One Health issues.

One of the recurrent themes was that making a ‘One Health’ approach, rooted in interdisciplinary science, is really tough. And perhaps even more so, when we move to a transdisciplinary approach, working with practitioners and policy makers to ‘co-construct’ knowledge and action.

There is a lot of talk of inter- and transdisciplinary research these days. Everyone wants cutting edge research that makes a difference. So whether it’s the Gates Foundation, the Wellcome Trust, the European Commission’s Horizon 2020 programme, or the new UK research council strategy, or umbrella programmes such as Future Earth, all want such problem focused research to tackle the big global issues of our time. And the themes of our conference, and our project, linking environmental change with disease with policy impacts certainly fit into this category.

Our project was supported by the UK Ecosystem Services and Poverty Alleviation Programme, funded by DFID, the UK Natural Environmental Research Council and the Economic and Social Research Council, and was hosted by the ESRC STEPS Centre based at Sussex University. It involved five countries in Africa (Zimbabwe, Zambia, Kenya, Sierra Leone and Ghana), four diseases (trypanosomiasis, Rift Valley Fever, Lassa Fever and Henipah). Each country study was focused on a puzzle, focusing on how diseases emerge, get transmitted, and who they affect different groups of people. The overall Consortium involved 19 institutions, ranging from diverse research groups in multiple universities in Africa, Europe and the US to veterinary, public health and wildlife departments in Africa. At last count there were more than 50 researchers involved in various ways. It was massively ambitious, and premised on a commitment to transdisciplinary working,

 Unpacking the process of transdisciplinary research

 Here I want to focus on the challenges and opportunities of the research process, rather than the results (more on those soon on this blog). The work has aimed to seek answers to on-the-ground problems, aiming at producing top-level research and generating an impact. But this is easier said (or written glibly into a proposal) than done. Building the ways of working in a transdisciplinary team is not easy. Much of it is about building trust, creating relationships, and finding new languages for interacting. These do not come easily. We had four all-team workshops during the project. Their tenor followed almost exactly the phases of group formation proposed by the psychologist, Bruce Tuckman.

The first was about ‘forming’ – finding out what the Consortium was about – which we held at ILRI in Nairobi. We didn’t know each other then. There was a nervousness, and not a little scepticism. The next workshop at Sussex focused on setting up the research and methodology. This was the ‘storming’ phase. Here we had to negotiate our roles, and define our stance – in a potentially threatening and confusing setting. There were a few arguments, and some misunderstandings – and some storming. We got through this, and got on with the work, but it took us a while to reach the ‘norming’ phase. This was already three years into the project at a workshop in Naivasha, Kenya. We had found a way of working, but we were only just beginning to build the relationships that really deliver transdisciplinary work. This really only happened in the final period, and at our last workshop – last week at London zoo – we could really say that we were ‘performing’. This final stage, where groups genuinely work together, came too late. We already had a nine-month no-cost extension ending next month, and the money had run out.

What lessons have we learned from this journey?

Central is the importance of time. It takes a while for any group to go through these stages. With a large, complex, international group, it takes longer. There are no real short-cuts.

Time is also important when studying dynamic complex systems, as there will be events that cannot be planned for that reframe the way we think, and the way we work. Ebola was the big one in our project, coming in 2014, right in the middle of the Sierra Leone fieldwork, which was in the epicentre of the outbreak. This made us rethink and restructure the work. But, despite the horrors, the experience helped us focus on new issues, and appreciate the value of cross-disciplinary working; something that of course proved to be vital to the Ebola response more generally.

Time is also important as the last pieces of the puzzle may be difficult to find. The whole story of the Zimbabwe work looking at trypanosomiasis only fell into place last week, when we were able to sit together and discuss the results of the livestock blood sampling. Mapped onto our GIS information from the geographers, and combined with the participatory analysis done in the field in Hurungwe the story became much clearer (more on this on this blog soon).

Linking different disciplinary approaches is not easy. There are different languages (from complex mathematics to complex words), and different styles of collecting, analysing and writing up data. Fieldwork means different things to different disciplines; as does paper writing, policy engagement, and so on. All these have to be negotiated. To work together we have to learn both new languages and cultures, and be patient and respectful.

But we also need frameworks that help make the connections that create the new insights. The DDDAC project had a simple framework that helped our earlier ‘forming’ and ‘norming’ stages, but we really got to ‘performing’ when we were able to link analytical approaches. This particularly focused on connecting different types of ‘modelling’. Everyone models the world – it’s just a framework for understanding expressed in different ways – but what the assumptions, frames and data requirements are will depend on who is modelling, and posing the questions.

We had various modelling efforts looking at diseases, emergence, spread and impact, from mechanistic Process based models, to statistical, macro ecological Pattern models to a diversity of Participatory modelling approaches, rooted in field analysis. Our 3P approach allowed conversations to happen and new results to begin to emerge, in this final period.

In other cross-disciplinary experiences – whether around the sustainable livelihoods framework or the STEPS pathways approach – my experience has been that, for all their limitations (there are many, for sure), these frameworks (‘models’) allow new conversations to happen, and new insights to emerge. So it has been in our integrative modelling, although only just touching the surface, due to our curtailed ‘performing’ phase. Four years in, new insights on disease emergence, transmission and effect were just beginning to emerge.

But it’s not just the frameworks that are important, it’s the people who are able to make the links – creating the basis for joint work. There are many different people with different roles in a successful team, as group psychologists, such as Meredith Belbin, have long known. We had very high-powered people in our team, many top researchers in their disciplines. But getting researchers and other project participants to work together required some unusual and new skills.

Research brokers, facilitators and leaders are rarely recognised, but are essential for cross-disciplinary work. We had a number of such people luckily, but I don’t think we knew enough about their importance at the beginning to give them well thought through roles, or even identify such skills in advance. Leadership in transdisciplinary working is a very special skill and a vital, usually unrecognised, and poorly rewarded, role.

Challenges faced

Our four team workshops moved the approach to working together forward incrementally. But between our four workshops, the team dispersed, fragmented, and often went back to silo working. Sustaining a continuous process of interaction is difficult, and expensive in an international project. Students can be key, as they are not subject to the same institutional strictures, and set professional behaviours and practices. Yet in our project, studentships were not encouraged, and we had only selective engagements, often from outside the project. This undermined coherence and continuity, and constrained genuine opportunities for transdisciplinary working.

As so many large projects, the temptation is to break things down into ‘work packages’; manageable units, associated with certain deliverables, with devolved leadership roles. This makes sense from an ease of management point of view, and indeed was encouraged in our project by the funding going to four separate Principal Investigators in four institutions. But integration then becomes incredibly difficult, as making links between activities, and making use of budgets to make this happen is impossible, as they are held multiply in protected silos.

Breaking out of existing institutional cultures, structured around disciplines and sectors, is incredibly difficult. And any project must know its limits. People have to be rewarded in their own systems, as well as gaining benefits from new collaborations. It’s not an easy balancing act. Ultimately people get promoted in their own institutions/disciplines, not in a project. And different people in such a project have very different reward systems, styles of publishing, forms of authorship and so on. Developing ways of working that take these into account, but move people to work in new ways is important, but not easy.

As so many projects formulated in a highly competitive funding environment, the earth was promised. But inevitably it could not be delivered in three  years. It would be absurd to expect it to have been despite the generous budget. The pressure was on from the beginning – high end, international science delivering impact. Anyone involved in research projects these days will know the routine. Impact, engagement, communications are central. This is all good, but forcing it may not make sense. Impacts emerge over time through relationships, and based on results that may not emerge easily. These are complex, difficult, challenging puzzles.

So the formulaic model of impact may not be appropriate, and we perhaps should be more sanguine about what is possible. Of course in our ‘pathways to impact’ assessments we over-promise (sometimes even lie), so the audit culture of project management kicks in to assess why we haven’t met the targets. And changing course, being flexible and reinventing projects to fit the moment is regarded with horror by research managers.

There is a dangerous culture of control in much research funding. Yes, linked to accountability, and assuring ‘value for money’, but pushing an inflexible audit approach can too often undermine creative, innovative research. There were moments in this project where overbearing centralised funder management constrained operations, and undermined partnerships.

Ways forward?

At the end of our project last week, we felt we’d only just started. We had done some good work, we had struck up excellent new transdisciplinary relationships, but we had only just started ‘performing’ when the money had run out.

All large group based projects (a common feature of funding modalities these days) go through the four group formation phases. So why not fund and manage in relation to this? Fund the forming, norming and storming, and performing separately in a phased approach.

There can be an expectation that some projects never get past forming, some never generate norms, and some fall apart during the storming (I have been in projects of all these types over the last 30 years!). But if you get to performing, often after quite a while, then you need proper funding for really generating the value from the funding. In our case much of the investment is sunk in a set of relationships that sadly will not be fully utilised as the funds have finished.

One route to this is through such a phased ‘challenge’ approach (Gates follows something similar, in the language of proof of concept to final project, although the argument is a bit different here). Another is to establish long-term, well-funded Centres around successful groups that have begun ‘performing’. This is the approach of UK research councils, Wellcome Trust and others. Centres with 10-20 years of funding can really make a difference. They can provide the home (real and virtual) for the type of interactions that are required to create real transdisciplinary work.

Only as part of Centres can the ‘constructive conflict’ between disciplines be generated and the type of frameworks that allow integrative, joint working encouraged. And only in such settings can the new norms and cultures that transdisciplinary work requires be fostered – and across generations of researchers and practitioners, this is a long-haul job.

Such efforts are of course not cheap, but the investment can be very worthwhile (and great value for money), as the sunk costs can genuinely be capitalised upon for really change-making work. Too often the money is pulled just as things get going, and exciting. The costs need to be focused on the relation-building that generate impact, rather than formulaic approaches, and invested in leadership, brokerage and facilitation that allow creative partnerships to be nurtured and allowed to work. This is difficult to programme and plan, and even more difficult to fit into the audit systems that dominate funding agencies’ obsessions.

Interdisciplinary and transdisciplinary collaboration is really hard, and involves a long slog that can be conflictual and challenging. But in the big issues that confront us today – whether climate change, sustainable development, zoonotic disease emergence, or indeed any area where multiple perspectives on a complex, dynamic problem are required – such approaches are imperative, and in my view a good investment. In our DDDAC project we made a creditable start, but are only at the beginning.

This post was written by Ian Scoones and appeared on Zimbabweland.  The blog will be back on 28 March, after a short Easter break

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Are livestock destroying the planet?

Livestock are essential to rural economies and livelihoods across Africa. On Zimbabweland there have been many blogs on this theme focusing on Zimbabwe’s livestock and marketing systems. But are these animals contributing to planetary destruction through greenhouse gas emissions?

A special issue of the Proceedings of the National Academy of Sciences on livestock and global change late last year offered some new data, and generated a minor storm of controversy thanks in large part to the Economist weighing into the debate. The Economists’ summary of a paper by Mario Herrero from CSIRO in Australia and colleagues from IIASA and ILRI suggested that the solution to the high climate change impacts of traditional livestock rearing was to abandon free range pastoralism and shift to a form of intensive factory farming. The answer The Economist believes is “intensive livestock farming, which is more efficient and environmentally friendlier than small-scale, traditional pastoralism of the sort beloved by many greens”. Why is this position adopted? The Economist explains:

… More acres are given over to feeding animals than to any other single use. Meat accounts for a sixth of humanity’s calorific intake but uses roughly a third of its crop land, water and grain. Producing a kilogram of grain takes 1,500 litres of water; a kilo of beef takes 15,000 litres. A fifth of the world’s pasture has been spoilt by overgrazing….livestock farming produces 8-18% of greenhouse-gas emissions. It is the main contributor to the build-up of nitrogen and phosphorus in the world’s soils, producing too much ammonia (which is caustic), nitrous oxide (a greenhouse gas) and dead zones in oceans (the result of excess phosphorus). A fifth of the world’s pasture has been spoilt by overgrazing….

Extensive livestock production it seems is bad news. This was in part the argument of the FAO’s controversial book from 2006, Livestock’s Long Shadow. And it has been picked up by many since, including another FAO publication published recently that provided a rather more rounded perspective than its predecessor. So should Zimbabwe and other countries in Africa be abandoning livestock production to save the planet? Are intensive systems of ‘factory farming’ the answer?

The debate is actually hopelessly confused, and confusing. The data in the PNAS article is clear. Inefficient feed systems result in more greenhouse gases being produced during production than more intensive systems (essentially more belching and farting). And white meat (pigs and poultry) are better than red meat and milk in this regard.

But the assessment does not account for the costs of the other inputs of industrial farming, including fossil fuels used in feed production, housing, transport and so on. Traditional livestock systems are often very ‘low input’, with little fossil fuel dependency, and linked into markets not reliant on massively long supply chains.

Such systems make efficient use of marginal land and resources; as Tara Garnett puts it a ‘livestock on leftovers’ approach focused on adapting existing systems rather than the simple focus on efficiencies. The trouble with studies such as the PNAS one is that the results and conclusions depend crucially on what ‘the system’ is, and what is being compared with what. These choices are crucial and can inject fatal biases, or encourage wayward misinterpretations.

Simon Fairlie produced a brilliant book a few years back, Meat: a Benign Extravagance. It even got George Monbiot to change his views on meat eating. The book argues – with masses of data and careful argument – that meat production if done in an ecologically sensitive and humane manner is fine on a whole range of counts, and should not be discounted as a form of production and source of livelihood. It just depends on who produces it and how. The same applies in the great climate and environmental impact debate, a theme that is picked up in the book, and in a recent paper that questions many of the data assumptions used in FAO’s livestock climate assessments.

In the exchange of comments following the Economist article Mario Herrero distances himself from the claims made by the Economist, arguing that they never claimed that “we should get rid of pastoralism” (they didn’t!). Instead he argues that small-scale intensive systems are the best way forward, as part of a diversity of approaches.

This is all well and good, but how then can the extensive savannah grasslands of Africa be best used? This is not where intensive small-scale systems are likely to emerge. Should they be turned over for carbon sequestration as some argue, or wildlife, with people and their environmentally destructive animals forced off the range? What then happens to the many livelihoods of often very poor people who are dependent on livestock? And if livestock are not consuming the grass, fires or termites might result in less production and perhaps even larger emissions.

The problem with studies of this sort – and perhaps especially the media and policy commentary that follows – is the way that complex systems are simplified. First is the way the accounting is done, with often limited data and missing out key aspects. What is included in the model and how it is bounded makes a huge difference. In this case focusing only on food conversion efficiency gives a distorted picture of climate impacts of different livestock based production-marketing systems.

Second is the interpretation that focuses on the accounted for measure – in this case greenhouse gases – and excludes the complexity of the wider system. Any assessment of costs and benefits must look at the whole picture, including the array of opportunity costs and trade-offs, and so crucially must involve the people concerned who know these best.

Third is the way uncertainties are dealt with, often put to one side (or in very long appendices of supplementary data). In the case of aggregate global pictures across all livestock systems, uncertainties can be massive. Inadequate data plagues agricultural policymaking, and particularly for extensive livestock. Add to that the uncertainties associated with climate change predictions and the data problems are compounded.

And fourth is the way alternatives are defined as part of policy narratives that are developed through such modelling efforts. By defining (narrowly) a problem, a solution (again narrow) is defined. Too often dramatic alternatives to the status quo are recommended, without thinking about the consequences.

Pastoralism is a way of life adapted to dry non-equiibrium rangelands, and is a massive contributor to livelihoods and economies, as well as providing a route to land management. Our book, Pastoralism and Development in Africa, highlighted through many case studies the way pastoralism contributes to development in the Greater Horn of Africa. A similar case could be made for the livestock dependent areas of Zimbabwe, as I and many others have long argued.

Surely the most appropriate response is to seek out more climate-compatible forms of livestock development, based on existing systems, and working with people and their animals, rather than seeking a dramatic transformation that would result in increased poverty and growing inequality in already poor areas of the world. The models may help think through the options, but they are no replacement for engaging with the realities on the ground.

This post was written by Ian Scoones and originally appeared on Zimbabweland

 

 

 

 

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