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Author |
Mandryk, M.; Reidsma, P.; van Ittersum, M.K. |
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Title |
Scenarios of long-term farm structural change for application in climate change impact assessment |
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Journal Article |
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Year |
2012 |
Publication |
Landscape Ecology |
Abbreviated Journal |
Landscape Ecol. |
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Volume |
27 |
Issue |
4 |
Pages |
509-527 |
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Keywords |
agriculture; adaptation; climate change; farm structural change; flevoland; agricultural land-use; future; policy; adaptation; diversification; vulnerability; productivity; consequences; variability; performance |
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Abstract |
Towards 2050, climate change is one of the possible drivers that will change the farming landscape, but market, policy and technological development may be at least equally important. In the last decade, many studies assessed impacts of climate change and specific adaptation strategies. However, adaptation to climate change must be considered in the context of other driving forces that will cause farms of the future to look differently from today’s farms. In this paper we use a historical analysis of the influence of different drivers on farm structure, complemented with literature and stakeholder consultations, to assess future structural change of farms in a region under different plausible futures. As climate change is one of the drivers considered, this study thus puts climate change impact and adaptation into the context of other drivers. The province of Flevoland in the north of The Netherlands was used as case study, with arable farming as the main activity. To account for the heterogeneity of farms and to indicate possible directions of farm structural change, a farm typology was developed. Trends in past developments in farm types were analyzed with data from the Dutch agricultural census. The historical analysis allowed to detect the relative importance of driving forces that contributed to farm structural changes. Simultaneously, scenario assumptions about changes in these driving forces elaborated at global and European levels, were downscaled for Flevoland, to regional and farm type level in order to project impacts of drivers on farm structural change towards 2050. Input from stakeholders was also used to detail the downscaled scenarios and to derive historical and future relationships between drivers and farm structural change. These downscaled scenarios and future driver-farm structural change relationships were used to derive quantitative estimations of farm structural change at regional and farm type level in Flevoland. In addition, stakeholder input was used to also derive images of future farms in Flevoland. The estimated farm structural changes differed substantially between the two scenarios. Our estimations of farm structural change provide a proper context for assessing impacts of and adaptation to climate change in 2050 at crop and farm level. |
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0921-2973 1572-9761 |
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CropM |
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MA @ admin @ |
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4477 |
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Kros, J.; Bakker, M.M.; Reidsma, P.; Kanellopoulos, A.; Jamal Alam, S.; de Vries, W. |
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Title |
Impacts of agricultural changes in response to climate and socioeconomic change on nitrogen deposition in nature reserves |
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Journal Article |
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Year |
2015 |
Publication |
Landscape Ecology |
Abbreviated Journal |
Landscape Ecol. |
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30 |
Issue |
5 |
Pages |
871-885 |
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Keywords |
Agricultural adaptation; Climate change; Land use change; Environmental; impact; Farming system; Nitrogen losses; netherlands; diversity; scenario |
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This paper describes the environmental consequences of agricultural adaptation on eutrophication of the nearby ecological network for a study area in the Netherlands. More specifically, we explored (i) likely responses of farmers to changes in climate, technology, policy, and markets; (ii) subsequent changes in nitrogen (N) emissions in responses to farmer adaptations; and (iii) to what extent the emitted N was deposited in nearby nature reserves, in view of the potential impacts on plant species diversity and desired nature targets. For this purpose, a spatially-explicit study at landscape level was performed by integrating the environmental model INITIATOR, the farm model FSSIM, and the land-use model RULEX. We evaluated two alternative scenarios of change in climate, technology, policy, and markets for 2050: one in line with a ‘global economy’ (GE) storyline and the other in line with a ‘regional communities’ (RC) storyline. Results show that the GE storyline resulted in a relatively strong increase in agricultural production compared to the RC storyline. Despite the projected conversions of agricultural land to nature (as part of the implementation of the National Ecological Network), we project an increase in N losses and N deposition due to N emissions in the study area of about 20 %. Even in the RC storyline, with a relatively modest increase in agricultural production and a larger expansion of the nature reserve, the N losses and deposition remain at the current level, whereas a reduction is required. We conclude that more ambitious green policies are needed in view of nature protection. |
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0921-2973 1572-9761 |
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MA @ admin @ |
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4565 |
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Abdelrahman, H.M.; Olk, D.C.; Dinnes, D.; Ventrella, D.; Miano, T.; Cocozza, C. |
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Title |
Occurrence and abundance of carbohydrates and amino compounds in sequentially extracted labile soil organic matter fractions |
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Journal Article |
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2016 |
Publication |
Journal of Soils and Sediments |
Abbreviated Journal |
Journal of Soils and Sediments |
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16 |
Issue |
10 |
Pages |
2375-2384 |
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Light fraction; Mobile humic acid; Organic farming; Particulate organic matter; SOM sequential extraction |
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Purpose The study aimed to describe the carbohydrates and amino compounds content in soil, the light fraction (LF), the >53 μm particulate organic matter (POM), and the mobile humic acid (MHA) fraction and to find out whether the carbohydrates and amino compounds can be used to explain the origin of SOM fractions. Materials and methods Soil samples were collected from two agricultural fields managed under organic farming in southern Italy. The LF, the POM, and the MHA were sequentially extracted from each soil sample then characterized. Seven neutral sugars and 19 amino compounds (amino acids and amino sugars) were determined in each soil sample and its correspondent fractions. Results and discussion The MHA contained less carbohydrate than the LF or the POM but its carbohydrates, although dominated by arabinose, were relatively with larger microbial contribution as revealed by the mannose/xylose ratio. The amino compounds were generally less in the LF or the POM than in the MHA, while the fungal (aspartic and serine) and bacterial (alanine and glycine) amino acids were larger in the MHA than in the LF or the POM, underlining the microbial contribution to the MHA. Results from both sites indicated that total carbohydrates content decreased moving from the LF (younger fraction) to the MHA (older fraction), which seems to follow a decomposition continuum of organic matter in the soil-plant system. Conclusions The study showed that the MHA is a labile humified fraction of soil C due to its content of carbohydrates and concluded that the content of carbohydrates and amino compounds in the LF, the POM and the MHA can depict the nature of these fractions and their cycling pattern and response to land management. |
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1439-0108 |
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CropM, ftnotmacsur |
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MA @ admin @ |
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4992 |
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Bellocchi, G.; Rivington, M.; Matthews, K.; Acutis, M. |
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Title |
Deliberative processes for comprehensive evaluation of agroecological models. A review |
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Journal Article |
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2015 |
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Agronomy for Sustainable Development |
Abbreviated Journal |
Agron. Sust. Developm. |
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35 |
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2 |
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589-605 |
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Keywords |
component-oriented programing; deliberative approach; modeling; model evaluation; multiple metrics; stakeholders; decision-support-systems; environmental-models; performance evaluation; groundwater models; farming systems; climate-change; irene-dll; simulation; validation; integration |
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The use of biophysical models in agroecology has increased in the last few decades for two main reasons: the need to formalize empirical knowledge and the need to disseminate model-based decision support for decision makers (such as farmers, advisors, and policy makers). The first has encouraged the development and use of mathematical models to enhance the efficiency of field research through extrapolation beyond the limits of site, season, and management. The second reflects the increasing need (by scientists, managers, and the public) for simulation experimentation to explore options and consequences, for example, future resource use efficiency (i.e., management in sustainable intensification), impacts of and adaptation to climate change, understanding market and policy responses to shocks initiated at a biophysical level under increasing demand, and limited supply capacity. Production concerns thus dominate most model applications, but there is a notable growing emphasis on environmental, economic, and policy dimensions. Identifying effective methods of assessing model quality and performance has become a challenging but vital imperative, considering the variety of factors influencing model outputs. Understanding the requirements of stakeholders, in respect of model use, logically implies the need for their inclusion in model evaluation methods. We reviewed the use of metrics of model evaluation, with a particular emphasis on the involvement of stakeholders to expand horizons beyond conventional structured, numeric analyses. Two major topics are discussed: (1) the importance of deliberative processes for model evaluation, and (2) the role computer-aided techniques may play to integrate deliberative processes into the evaluation of agroecological models. We point out that (i) the evaluation of agroecological models can be improved through stakeholder follow-up, which is a key for the acceptability of model realizations in practice, (ii) model credibility depends not only on the outcomes of well-structured, numerically based evaluation, but also on less tangible factors that may need to be addressed using complementary deliberative processes, (iii) comprehensive evaluation of simulation models can be achieved by integrating the expectations of stakeholders via a weighting system of preferences and perception, (iv) questionnaire-based surveys can help understand the challenges posed by the deliberative process, and (v) a benefit can be obtained if model evaluation is conceived in a decisional perspective and evaluation techniques are developed at the same pace with which the models themselves are created and improved. Scientific knowledge hubs are also recognized as critical pillars to advance good modeling practice in relation to model evaluation (including access to dedicated software tools), an activity which is frequently neglected in the context of time-limited framework programs. |
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1774-0746 1773-0155 |
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Review |
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CropM, LiveM, ft_macsur |
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MA @ admin @ |
Serial |
4551 |
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Özkan Gülzari, Ş.; Vosough Ahmadi, B.; Stott, A.W. |
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Title |
Impact of subclinical mastitis on greenhouse gas emissions intensity and profitability of dairy cows in Norway |
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Journal Article |
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2018 |
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Preventive Veterinary Medicine |
Abbreviated Journal |
Preventive Veterinary Medicine |
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150 |
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19-29 |
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Dairy cow; Dynamic programming; Greenhouse gas emissions intensity; Profitability; Subclinical mastitis; Whole farm modelling |
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Impaired animal health causes both productivity and profitability losses on dairy farms, resulting in inefficient use of inputs and increase in greenhouse gas (GHG) emissions produced per unit of product (i.e. emissions intensity). Here, we used subclinical mastitis as an exemplar to benchmark alternative scenarios against an economic optimum and adjusted herd structure to estimate the GHG emissions intensity associated with varying levels of disease. Five levels of somatic cell count (SCC) classes were considered namely 50,000 (i.e. SCC50), 200,000, 400,000, 600,000 and 800,000 cells/mL (milliliter) of milk. The effects of varying levels of SCC on milk yield reduction and consequential milk price penalties were used in a dynamic programming (DP) model that maximizes the profit per cow, represented as expected net present value, by choosing optimal animal replacement rates. The GHG emissions intensities associated with different levels of SCC were then computed using a farm-scale model (HolosNor). The total culling rates of both primiparous (PP) and multiparous (MP) cows for the five levels of SCC scenarios estimated by the model varied from a minimum of 30.9% to a maximum of 43.7%. The expected profit was the highest for cows with SCC200 due to declining margin over feed, which influenced the DP model to cull and replace more animals and generate higher profit under this scenario compared to SCC50. The GHG emission intensities for the PP and MP cows with SCC50 were 1.01 kg (kilogram) and 0.95 kg carbon dioxide equivalents (CO2e) per kg fat and protein corrected milk (FPCM), respectively, with the lowest emissions being achieved in SCC50. Our results show that there is a potential to reduce the farm GHG emissions intensity by 3.7% if the milk production was improved through reducing the level of SCC to 50,000 cells/mL in relation to SCC level 800,000 cells/mL. It was concluded that preventing and/or controlling subclinical mastitis consequently reduces the GHG emissions per unit of product on farm that results in improved profits for the farmers through reductions in milk losses, optimum culling rate and reduced feed and other variable costs. We suggest that further studies exploring the impact of a combination of diseases on emissions intensity are warranted. |
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0167-5877 |
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LiveM, ft_macsur |
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MA @ admin @ |
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5181 |
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