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Holman, I. P., Brown, C., Carter, T. R., Harrison, P. A., & Rounsevell, M. (2019). Improving the representation of adaptation in climate change impact models. Reg. Environ. Change, 19(3), 711–721.
Abstract: Climate change adaptation is a complex human process, framed by uncertainties and constraints, which is difficult to capture in existing assessment models. Attempts to improve model representations are hampered by a shortage of systematic descriptions of adaptation processes and their relevance to models. This paper reviews the scientific literature to investigate conceptualisations and models of climate change adaptation, and the ways in which representation of adaptation in models can be improved. The review shows that real-world adaptive responses can be differentiated along a number of dimensions including intent or purpose, timescale, spatial scale, beneficiaries and providers, type of action, and sector. However, models of climate change consequences for land use and water management currently provide poor coverage of these dimensions, instead modelling adaptation in an artificial and subjective manner. While different modelling approaches do capture distinct aspects of the adaptive process, they have done so in relative isolation, without producing improved unified representations. Furthermore, adaptation is often assumed to be objective, effective and consistent through time, with only a minority of models taking account of the human decisions underpinning the choice of adaptation measures (14%), the triggers that motivate actions (38%) or the time-lags and constraints that may limit their uptake and effectiveness (14%). No models included adaptation to take advantage of beneficial opportunities of climate change. Based on these insights, transferable recommendations are made on directions for future model development that may enhance realism within models, while also advancing our understanding of the processes and effectiveness of adaptation to a changing climate.
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Sandhu, H., Wratten, S., Costanza, R., Pretty, J., Porter, J. R., & Reganold, J. (2015). Significance and value of non-traded ecosystem services on farmland. PeerJ, 3, e762.
Abstract: Background. Ecosystem services (ES) generated within agricultural landscapes, including field boundaries, are vital for the sustainable supply of food and fibre. However, the value of ES in agriculture has not been quantified experimentally and then extrapolated globally. Methods. We quantified the economic value of two key but contrasting ES (biological control of pests and nitrogen mineralisation) provided by non-traded non-crop species in ten organic and ten conventional arable fields in New Zealand using field experiments. The arable crops grown, same for each organic and conventional pair, were peas (Pisum sativum), beans (Phaseolus vulgaris), barley (Hordeum vulgare), and wheat (Triticum aestivum). Organic systems were chosen as comparators not because they are the only forms of sustainable agriculture, but because they are subject to easily understood standards. Results. We found that organic farming systems depended on fewer external inputs and produced outputs of energy and crop dry matter generally less than but sometimes similar to those of their conventional counterparts. The economic values of the two selected ES were greater for the organic systems in all four crops, ranging from US$ 68-200 ha(-1) yr(-1) for biological control of pests and from US$ 110-425 ha(-1)yr(-1) for N mineralisation in the organic systems versus US$ 0 ha(-1)yr(-1) for biological control of pests and from US$ 60-244 ha(-1)yr(-1) for N mineralisation in the conventional systems. The total economic value (including market and non-market components) was significantly greater in organic systems, ranging from US$ 1750-4536 ha(-1)yr(-1), with US$ 1585-2560 ha(-1)yr(-1) in the conventional systems. The non-market component of the economic value in organic fields was also significantly higher than those in conventional fields. Discussion. To illustrate the potential magnitude of these two ES to temperate farming systems and agricultural landscapes elsewhere, we then extrapolate these experimentally derived figures to the global temperate cropping area of the same arable crops. We found that the extrapolated net value of the these two services provided by non-traded species could exceed the combined current global costs of pesticide and fertiliser inputs, even if utilised on only 10% of the global arable area. This approach strengthens the case for ES-rich agricultural systems, provided by non-traded species to global agriculture.
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Coles, G. D., Wratten, S. D., & Porter, J. R. (2016). Food and nutritional security requires adequate protein as well as energy, delivered from whole-year crop production. PeerJ, 4, 17.
Abstract: Human food security requires the production of sufficient quantities of both high-quality protein and dietary energy. In a series of case-studies from New Zealand, we show that while production of food ingredients from crops on arable land can meet human dietary energy requirements effectively, requirements for high-quality protein are met more efficiently by animal production from such land. We present a model that can be used to assess dietary energy and quality-corrected protein production from various crop and crop/animal production systems, and demonstrate its utility. We extend our analysis with an accompanying economic analysis of commercially available pre-prepared or simply-cooked foods that can be produced from our case-study crop and animal products. We calculate the per-person, per-day cost of both quality-corrected protein and dietary energy as provided in the processed foods. We conclude that mixed dairy/cropping systems provide the greatest quantity of high quality protein per unit price to the consumer, have the highest food energy production and can support the dietary requirements of the highest number of people, when assessed as all-year-round production systems. Global food and nutritional security will largely be an outcome of national or regional agroeconomies addressing their town food needs. We hope that lour model will be used for similar analyses of food production systems in other countries, agroecological zones and economies.
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Paas, W., Kanellopoulos, A., van de Ven, G., & Reidsma, P. (2016). Integrated impact assessment of climate and socio-economic change on dairy farms in a watershed in the Netherlands. NJAS – Wageningen Journal of Life Sciences, .
Abstract: Climate and socio-economic change will affect the land use and the economic viability of Dutch dairy farms. Explorations of future scenarios, which include different drivers and impacts, are needed to perform ex-ante policy assessment. This study uses a bio-economic farm model to assess impacts of climate and socio-economic change on dairy farms in a sandy area in the Netherlands. Farm data from the Farm Accountancy Data Network provided information on the current production levels and available farm resources. First, the farm plans of individual farms were optimized in the current situation to benchmark farms and assess the current scope for improvement. Secondly, simulations for two scenarios were included: a Global Economy with 2 °C global temperature rise (GE/W+) and a Regional Community with 1 °C global temperature rise (RC/G). The impacts of climate change, extreme events, juridical change (including abolishment of milk quota), technological change and price changes were evaluated in separate model runs within the predefined scenarios. We found that farms can increase profit both by intensification and land expansion; the latter especially for medium sized farms (less than 70 cows). Climate change including the effect of increased occurrence of extreme events may negatively affect farm gross margin in the GE/W+ scenario. Lower gross margins are compensated for by the effects of technology and price changes. In contrast with the GE/W+ scenario, climate change has positive impacts on farm profit in RC/G, but less favourable farm input-output price ratios have a negative effect. Technological change is needed to compensate for revenue losses due to higher input prices. In both GE/W+ and RC/G scenarios, dairy farms increase production and the use of artificial fertilizer. Medium sized farms have more options to increase profit than the large farms: they benefit more from the abolishment of the milk quota and better adapt to negative and positive impacts of climate change. While the exact impact of different drivers will always remain uncertain, this study showed that changes in prices, technology and markets have a relatively larger impact than climate change, even when extreme events are taken into account. By using whole farm plans as activities that can be selected, the model is grounded in observations, and it was shown that half of the farms are gross margin maximizers as assumed in the model. The model therefore indicates ‘what could happen if’, and gives insights in drivers and impacts of dairy farming in the region.
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Asseng, S., Ewert, F., Martre, P., Rötter, R. P., Lobell, D. B., Cammarano, D., et al. (2014). Rising temperatures reduce global wheat production. Nat. Clim. Change, 5(2), 143–147.
Abstract: Crop models are essential tools for assessing the threat of climate change to local and global food production1. Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature2. Here we systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 °C to 32 °C, including experiments with artificial heating. Many models simulated yields well, but were less accurate at higher temperatures. The model ensemble median was consistently more accurate in simulating the crop temperature response than any single model, regardless of the input information used. Extrapolating the model ensemble temperature response indicates that warming is already slowing yield gains at a majority of wheat-growing locations. Global wheat production is estimated to fall by 6% for each °C of further temperature increase and become more variable over space and time.
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