41 research outputs found

    On the use and misuse of climate change projections in international development

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    Climate resilience is increasingly prioritized by international development agencies and national governments. However, current approaches to informing communities of future climate risk are problematic. The predominant focus on end-of-century projections neglects more pressing development concerns, which relate to the management of shorter-term risks and climate variability, and constitutes a substantial opportunity cost for the limited financial and human resources available to tackle development challenges. When a long-term view genuinely is relevant to decisionmaking, much of the information available is not fit for purpose. Climate model projections are able to capture many aspects of the climate system and so can be relied upon to guide mitigation plans and broad adaptation strategies, but the use of these models to guide local, practical adaptation actions is unwarranted. Climate models are unable to represent future conditions at the degree of spatial, temporal, and probabilistic precision with which projections are often provided, which gives a false impression of confidence to users of climate change information. In this article, we outline these issues, review their history, and provide a set of practical steps for both the development and climate scientist communities to consider. Solutions to mobilize the best available science include a focus on decision-relevant timescales, an increased role for model evaluation and expert judgment and the integration of climate variability into climate change service

    A farm-level evaluation of nitrogen and phosphorus fertilizer use and planting density for pearl millet production in Niger

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    Mineral fertilizer use is increasing in West Africa though little information is available on yield response in farmers' fields. Farmers in this region plant at low density (average 5,000 pockets ha−1, 3 plants pocket−1), which can affect fertilizer use efficiency. A study was conducted with 20 farmers in Niger to assess the response of pearl millet [Pennisetum glaucum (L.) R. Br.] to phosphorus and nitrogen fertilizers under farm conditions. In each field, treatments included control, single superphosphate (SSP) only, SSP plus N (point placed near plant), and either SSP or partially acidulated phosphate rock (PAPR) plus N broadcast. N and P were applied at 30 kg N ha−1 and 30 kg P2O5 ha−1. Farmers were allowed to plant, weed, etc., as they wished and they planted at densities ranging from 2,000 to 12,000 pockets ha−1. In the absence of fertilizer, increasing density from 2,000 to 7,000 pockets ha−1 increased yield by 400%. A strong interaction was found between fertilizer use and density. Farmers planting at densities less than 3,500 pockets ha−1 had average yields of 317 kg grain ha−1 while those planting at densities higher than 6,500 pockets ha−1 showed average yields of 977 grain ha−1. Though phosphate alone increased yields significantly at all densities, little response to fertilizer N was found at densities below 6,000 pockets ha−1. Significant residual responses in 1987 and 1988 were found to P applied in high-density plots in 1986. Depending on fertilizer and grain prices, analysis showed that fertilizer use must be be combined with high plant density (10,000 pockets ha−1) or no economic benefit from fertilizer use will be realize

    A framework for priority-setting in climate smart agriculture research

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    Climate-smart agriculture (CSA) is widely promoted as an approach for reorienting agricultural development under the realities of climate change. Prioritising research-for-development activities is crucial, given the need to utilise scarce resources as effectively as possible. However, no framework exists for assessing and comparing different CSA research investments. Several aspects make it challenging to prioritise CSA research, including its multi-dimensional nature (productivity, adaptation and mitigation), the uncertainty surrounding many climate impacts, and the scale and temporal dependencies that may affect the benefits and costs of CSA adoption. Here we propose a framework for prioritising agricultural research investments across scales and review different approaches to setting priorities among agricultural research projects. Many priority-setting case studies address the short- to medium-term and at relatively local scales. We suggest that a mix of actions that span spatial and temporal time scales is needed to be adaptive to a changing climate, address immediate problems and create enabling conditions for enduring change
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