Smallholder Agriculture: a Smart Investment for the Poor and the Planet When you add up all the worrying statistics on the ecosystems, biodiversity, and water that sustain agriculture, and then add the extra threat of climate change, you come up with a global problem that we cannot ignore. While large scale agriculture is a major driver, smallholder farming is also both a perpetrator and victim of environmental degradation. Business as usual is not a viable option. How can competing demands on these scarce resources be reconciled? What has been the experience in establishing sustainable approaches to smallholder production and marketing – and can these be scaled up more rapidly? The global climate and environment challenge seems enormous, but there is a growing body of evidence of the success of sustainable approaches to agricultural production and planning.
Good impact measurement is needed to justify the use of scarce funding, to demonstrate value for money, to learn about what works, and – in the case of ASAP – to build a strong case that investing in the climate resilience of smallholder farming makes sense. Climate change is becoming a more prominent driver of both public and private resource flows, and adaptation to climate change will inevitably be a big part of that – including through the new Green Climate Fund [http://gcfund.net/home.html].
Challenge 1: unpredictability. Knowledge is amassing quickly on what climate change will mean across the world, and climate models are getting more fine-grained, thereby appearing to give more accurate and localized projections. Yet, the uncertainty range of modelled climate impacts remains pretty high, depending on the underlying General Circulation Models (GCMs) and socio-economic assumptions that feed into the modelling. For example, when calculating average changes in rainfall for the Greater Mekong sub-region, some climate models show average increases in rainfall, while others show average losses. This makes estimates of the threat level to people and systems right now more a probabilistic rather than exact science ( http://weadapt.org/knowledge-base/using-climate-information/climate-model-uncertainty ) . Challenge 2: heterodoxy. Unlike measuring greenhouse gas emissions (which is difficult enough but nevertheless a well-understood quantitative process), climate resilience can and should involve any number of things. For some smallholder farmers it can mean access to a road that doesn’t get washed away during the monsoon season, or access to drought-resistant seeds and better seasonal forecasts, or better representation in water user groups, or access to public health services that reduce the effects of water-borne diseases. Measurement systems should not discourage this diversity since resilient systems – be it societies, communities or ecosystems - are generally more diverse ones [see link to Fig.1 on p.14 in http://community.eldis.org/.59e0d267/resilience-renaissance.pdf ]. A problem with the original Green Revolution in agriculture was that it often encouraged a standardized approach rather than tailoring production systems it to the vastly different circumstances at the local level [http://www.ifad.org/pub/op/3.pdf]. The breadth of responses required makes aggregating impacts a bit like adding apples to oranges. At some point, practitioners may converge on a standard ‘metric’ that ranks all aspects of resilience and cranks out an overall rating, but it would be a long, long list if it is to be relevant across very different communities. IFAD’s Result Framework for ASAP tries to accommodate this diversity by having a range of quantitative indicators to describe the aggregate impact of the overall programme, while capturing more diverse and qualitative information at the individual project-level. ASAP will also pilot experimental designs in the form of randomized control trials, which can focus on the take up of specific approaches. Challenge 3: interconnectivity. Individual climate resilience depends on the overall stock of risks in the wider social, economic and ecological fabric of the society in which we live. So measuring our resilience means understanding the underlying drivers of our vulnerability, rather than just focusing on only one discrete aspect of one discrete problem. For example, if superstorm Sandy is hitting several thousand households unprepared, what has made them vulnerable? Is it lack of accurate or timely forecasting information? Lack of transport to get to the grocery store and buy emergency stockpiles? A weak energy transmission system without sufficient backup? Or a house with only a flimsy roof that dates back to job loss during the financial crisis? In the developing world, one thing farmers are re-learning is the interconnectivity within and across landscapes – it really matters to downstream smallholder farmers that logging has taken place upstream since this means more floods. The financial crisis has galvanized more attention and attempts to measure systemic financial risk – the same is happening for climate risk. Ways to measure this are holistic metrics that rate people’s stock of assets and risks, capturing both the biophysical dimension (such as the natural capital available in a particular landscape), but also socio-economic characteristics (such as access to information, institutional representation, or networks of mutual supportl). Satellite-based mapping systems are developing rapidly, and can at low cost measure quite a few of the biophysical aspects of climate resilience for smallholder farmers – for example, they can measure the level of diversification of cropping systems, or the level of trees present in cropping areas, both of which have an important role to play in withstanding floods or droughts. If this is combined with well-designed household surveys, which help us understand why exactly these landscapes look like they do, we can come a long way in understanding the key drivers of risk. Challenge 4: timing. Over time, climate change will accentuate and magnify both ‘intensive risks’ (which may materialize in infrequent but highly destructive hazards, such as ‘super-storm’ Sandy in the USA)) as well as ‘extensive risks’ (low-intensity and high frequency events, such as seasonal floods and dry spells which cause less damage in macroeconomic terms, but affect low-income households with destructive regularity) The problem is that we can only really know if people are becoming more resilient if we have a long-enough trend line of comparable events. If events occur infrequently, e.g. every 10 or 20 years, this does not yield the kind of steady and incremental numbers that most measurement systems (and cost-benefit analysis) are designed for. And if we are planning for, say, 4 degrees increases in average global temperature, we will only really know if the adaptation measures are successful when we reach such temperatures. Ways to respond to this are to measure some of the intermediate stepping stones on the pathway to climate change resilience – for example, if households are better able to absorb the vagaries of the weather. The assumption is that if seasonal disaster risks can be reduced, the magnifying effects of climate change will also be reduced. Monitoring systems also tend to measure inputs built – such as the number of people receiving information from a new weather information system – as a proxy for being unable to (yet) measure whether this is actually protecting them from storms.
Results: analysis - overall, SRI, IPM; emulation - conservation agriculture, agroforestry For example, agroforestry is now practised on between 12.5-25% of total agricultural land worldwide. Brazil currently practices minimum-tillage for about 60% of its cultivatable area. Conservation agriculture is used in about 100 million hectares worldwide (about 8 per cent of arable land). Current trade in organic food, drinks and cotton amounts to about US$ 60 billion a year. India, Indonesia, and Philippines have removed insecticide subsidies and reduced insecticide use nationally by 50 -75 percent, while rice production continued to increase annually. From IFAD’s newly launched Rural Poverty Report (p.159) The broadest assessment of sustainable agricultural approaches in developing countries to date is based on a study of 286 initiatives in 57 poor countries, covering 12.6 million farms on 37 million hectares. According to this study, virtually all these initiatives have increased productivity, while improving the supply of critical environmental services. Out of 198 sampled yield comparisons, the mean yield increase over four years was 79 per cent; all crops showed water-use efficiency gains; the practices sequestered carbon; and most of those projects with data substantially reduced pesticide use while increasing yields. They typically maintain healthy and diverse landscapes with maintained groundcover, diverse production systems and healthy soil that can retain moisture. They are already being successfully scaled up. For example, Brazil currently practices zero-till for about 40% of its cultivatable area, and has almost eliminated the use of inorganic nitrogen fertilizer in its soy production [FAO doc]. Agroforestry is used in greater than 10 million square kilometres worldwide (about 10 per cent of total arable land). Conservation agriculture is used in about 1 million square kilometres worldwide (about 8 per cent of arable land). Current trade in organic food, drinks and cotton amounts to about US$ 60 billion a year. From IFAD’s newly launched Rural Poverty Report (p.159) Pretty (2006): 286 initiatives, 57 countries – 79% yield increase; water-use efficiency gains; emissions; pesticides The broadest assessment of sustainable agricultural approaches in developing countries to date is based on a study of 286 initiatives in 57 poor countries, covering 12.6 million farms on 37 million hectares. According to this study, virtually all these initiatives have increased productivity, while improving the supply of critical environmental services. Out of 198 sampled yield comparisons, the mean yield increase over four years was 79 per cent; all crops showed water-use efficiency gains; the practices sequestered carbon; and most of those projects with data substantially reduced pesticide use while increasing yields. See http://www.unep.ch/etb/publications/Organic%20Agriculture/OA%20Synthesis%20v2.pdf See p.144 Rural Poverty Report Chapter 5 http://www.ifad.org/rpr2011/report/e/rpr2011.pdf Pretty, J., A. D. Noble, D. Bossio, J. Dixon, R.E. Hine, F.W.T. Penning de Vries, and J.I.L. Morison. 2006. Resource-conserving agriculture increases yields in developing countries. Environment Science and Technology 40(4):1114-1119. India 1994-2002 food grain incr 20% while volume pesticide decree 35%]. The International Assessment of Agricultural Knowledge, Science and Technology for Development (IAASTD) Although some varieties respond better than others to SRI methods, it is claimed that increased yield is achieved with 80 to 90 per cent reductions in seed requirements and 25 to 50 per cent less irrigation water. Supporters of SRI report other benefits – resistance to pests and diseases, resistance to drought and storm damage, less pollution of soil and water resources, and reduced methane emissions. The benefits of SRI have now been documented in more than 40 countries in Asia, Africa and Latin America. In Cambodia, more than 80,000 families now use SRI practices, which are reported as leading to a doubling of rice yields, substantial reductions in the use of fertilizers and agrochemicals, and increases in farm profits of 300 per cent. Governments in the largest rice producing countries (China, India and Indonesia) are now supporting SRI extension and committed to significant expansion of SRI rice.
Challenge 5: data. Many aspects of resilience are not easily quantifiable. How to put a value on the responsiveness on emergency services in New Jersey? How to measure the benefits delivered by natural systems that act as buffers to storms and floods? How to quantify the number of lives saved because IFAD has helped to establish more effective drought Early Warning systems in the Sahel? It is possible to measure various general qualities of ‘good governance’, and to measure things like the level of insurance coverage in communities or the amount of formal social protection. One approach is to use personal valuations, asking people to rate their vulnerability. But because of the often unpredictable impacts of climate change, which manifest in greater uncertainty and variability of the weather rather than a clean and long-term trend, farmers themselves are sometimes unaware of how their exposure to risks is increasing. Statisticians have been ingenious in finding a way to put most things in numbers, and the same will apply to climate resilience. Where we reach the limits of this, there must be space to capture qualitative lessons too on what creates climate resilience.
A Results Framework for Smallholder Adaptation - the ASAP initiative
Adaptation for Smallholder Agriculture Programme – “ASAP”ASAP GoalIncreased resilience of poor smallholderfarmers to climate changeASAP Development ObjectiveMultiple-benefit adaptation approacheswith smallholders are scaled up and shared
A Results Framework - Why?• accountability for results• national/local policymaking• project/policy design and implementation• global policymaking• knowledge-sharing
A Results Frame-work - What?• Heterodoxy• Systemic• Additionality• Institutional change• Timeframes• Valuation of risk reduction
Biophysical Climate lens Primary MultipleFeature Impact Benefits: Long-runMaximum use of scenarios analysis Maintained •Yieldsnatural processes and planning and enhanced •Profit+ ecosystems groundcover •Local Risk analysis and pollutionLess external tools Healthy soil And adds to..inorganic inputs +waste that can retain •Resilience Landscape/ nutrients & •EmissionsDiversity + systems-level moisture reductionsproportionality of emphasisproduction Enhanced biodiversityMixture oftraditional & newtechnologies
A Results Framework - How?• Aggregate Results Framework – 10 key indicators• Build on government (often PPCR-related) systems• Geo-informatics• Randomized field trials – causality• RIMs update to strengthen biophysical indicators• Qualitative assessments