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Dono, G.; Cortignani, R.; Dell’Unto, D.; Deligios, P.; Doro, L.; Lacetera, N.; Mula, L.; Pasqui, M.; Quaresima, S.; Vitali, A.; Roggero, P.P. |
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Winners and losers from climate change in agriculture: Insights from a case study in the Mediterranean basin |
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Journal Article |
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Year |
2016 |
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Agricultural Systems |
Abbreviated Journal |
Agricultural Systems |
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147 |
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65-75 |
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Adaptation of farms to CC; Mediterranean region; Discrete Stochastic Programming; Regional Atmospheric Modelling System; Crop models; Livestock models |
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The Mediterranean region has always shown a marked inter-annual variability in seasonal weather, creating uncertainty in decisional processes of cultivation and livestock breeding that should not be neglected when modeling farmers’ adaptive responses. This is especially relevant when assessing the impact of climate change (CC), which modifies the atmospheric variability and generates new uncertainty conditions, and the possibility of adaptation of agriculture. Our analysis examines this aspect reconstructing the effects of inter-annual climate variability in a diversified farming district that well represents a wide range of rainfed and irrigated agricultural systems in the Mediterranean area. We used a Regional Atmospheric Modelling System and a weather generator to generate 150 stochastic years of the present and near future climate. Then, we implemented calibrated crop and livestock models to estimate the corresponding productive responses in the form of probability distribution functions (PDFs) under the two climatic conditions. We assumed these PDFs able to represent the expectations of farmers in a discrete stochastic programming (DSP) model that reproduced their economic behaviour under uncertainty conditions. The comparison of the results in the two scenarios provided an assessment of the impact of CC, also taking into account the possibility of adjustment allowed by present technologies and price regimes. The DSP model is built in blocks that represent the farm typologies operating in the study area, each one with its own resource endowment, decisional constraints and economic response. Under this latter aspect, major differences emerged among farm typologies and sub-zones of the study area. A crucial element of differentiation was water availability, since only irrigated C3 crops took full advantage from the fertilization effect of increasing atmospheric CO2 concentration. Rainfed crop production was depressed by the expected reduction of spring rainfall associated to the higher temperatures. So, a dualism emerges between the smaller impact on crop production in the irrigated plain sub-zone, equipped with collective water networks and abundant irrigation resources, and the major negative impact in the hilly area, where these facilities and resources are absent. However intensive dairy farming was also negatively affected in terms of milk production and quality, and cattle mortality because of the increasing summer temperatures. This provides explicit guidance for addressing strategic adaptation policies and for framing farmers’ perception of CC, in order to help them to develop an awareness of the phenomena that are already in progress, which is a prerequisite for effective adaptation responses. |
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0308521x |
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CropM, LiveM, TradeM, ft_macsur |
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MA @ admin @ |
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4756 |
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Lacetera, N.; Vitali, A.; Bernabucci, U.; Nardone, A. |
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Title |
Relationships between temperature humidity index, mortality, milk yield and composition in Italian dairy cows |
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Report |
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Year |
2014 |
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FACCE MACSUR Reports |
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3 |
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Sp3-3 |
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The aim of this presentation is to illustrate the activities performed by the LiveM-Task L1.2. group based at the University of Tuscia, Viterbo, Italy. Three different pluriannual databases were built to perform retrospective studies aimed at establishing the relationships between temperature humidity index (THI) and parameters of interest for dairy cow farms. The THI combines temperature and humidity in a single value and has been widely used to quantify heat stress in farm animals. The first database was built to assess the relationships between THI and mortality over a 6 yr period (2002-2007); the second one was a 7 yr database (2001-2007) which was built to establish the relationships between THI and milk yield; the last database included THI, milk somatic cell counts, total bacterial counts, fat and protein percentages data collected over a 7 yr period (2003-2009). The analysis of the three databases provided several equations which demonstrated and quantified an increase of mortality, reduction of milk yield and a worsening of milk quality in hot environment. Results of these analyzes authorized speculations about risks for dairy cows and their productivity in a warming planet. Furthermore, the same results are being utilized by economists also working within MACSUR at the University of Tuscia for an integrated study aimed at establishing the economic impact of climate change in the dairy sector. Combining this information with climate change regional scenarios might permit prediction of the impact of global warming and identification of adaptation measures that are appropriate for specific contexts. No Label |
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MA @ admin @ |
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2220 |
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Lacetera, N.; Vitali, A.; Bernabucci, U.; Nardone, A. |
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Report on relationships between THI and dairy cow performance |
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2015 |
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FACCE MACSUR Reports |
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4 |
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D-L1.2.3 |
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The work carried out under LiveM, L1.2 and described herein was based on construction and query of large databases which included multiannual productive and health field data. Productive data referred to dairy cows and included milk yield and composition, whereas health data were relative both to dairy cows and pigs. The analysis established the THI values above which a significant decline in the performance and health of dairy cows or pigs is to be expected. These results may help to adopt management environmental strategies which may permit to limit THI increase under farming conditions and/or to provide animals with interventions which may reduce heat load and/or increase dissipation of heat. No Label |
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MA @ admin @ |
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2217 |
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Lacetera, N.; Vitali, A.; Bernabucci, U.; Nardone, A. |
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Report on the analysis of interannual and seasonal variations in productive, reproductive and health data |
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2015 |
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FACCE MACSUR Reports |
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4 |
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D-L1.2.2 |
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The work carried out under LiveM, L1.2 and described herein was based on construction and query of large databases which included multiannual productive and health field data. Productive data referred to dairy cows, whereas health data were relative both to dairy cows and pigs. The analysis pointed out significant seasonal variations of parameters under study. In synthesis, summer/hot season was associated with significant worsening of dairy cows milk composition and with significant higher risk of death in pigs. These results may help to predict consequences of climate change in economically important sectors of the livestock industry and also to identify and target adaptation options that are appropriate for specific contexts, and that can contribute to environmental sustainability as well as to economic development. No Label |
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MA @ admin @ |
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2216 |
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Vitali, A.; Lana, E.; Amadori, M.; Bernabucci, U.; Nardone, A.; Lacetera, N. |
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Analysis of factors associated with mortality of heavy slaughter pigs during transport and lairage |
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2014 |
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Journal of Animal Science |
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J. Anim. Sci. |
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92 |
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11 |
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5134-5141 |
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Abattoirs/*statistics & numerical data; Animals; *Data Interpretation, Statistical; Humidity/adverse effects; Light/adverse effects; *Mortality; Retrospective Studies; Seasons; Swine/*physiology; Temperature; Time Factors; Transportation/*statistics & numerical data; lairage; mortality; pigs; temperature-humidity index; transport |
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The study was based on data collected during 5 yr (2003-2007) and was aimed at assessing the effects of the month, slaughter house of destination (differing for stocking density, openings, brightness, and cooling device types), length of the journey, and temperature-humidity index (THI) on mortality of heavy slaughter pigs (approximately 160 kg live weight) during transport and lairage. Data were obtained from 24,098 journeys and 3,676,153 pigs transported from 1,618 farms to 3 slaughter houses. Individual shipments were the unit of observation. The terms dead on arrival (DOA) and dead in pen (DIP) refer to pigs that died during transport and in lairage at the abattoir before slaughtering, respectively. These 2 variables were assessed as the dependent counts in separate univariate Poisson regressions. The independent variables assessed univariately in each set of regressions were month of shipment, slaughter house of destination, time traveled, and each combination of the month with the time traveled. Two separate piecewise regressions were done. One used DOA counts within THI levels over pigs transported as a dependent ratio and the second used DIP counts within THI levels over pigs from a transport kept in lairage as a dependent ratio. The THI was the sole independent variable in each case. The month with the greatest frequency of deaths was July with a risk ratio of 1.22 (confidence interval: 1.06-1.36; P < 0.05) and 1.27 (confidence interval: 1.06-1.51; P < 0.05) for DOA and DIP, respectively. The lower mortality risk ratios for DOA and DIP were recorded for January and March (P < 0.05). The aggregated data of the summer (June, July, and August) versus non-summer (January, March, September, and November) months showed a greater risk of pigs dying during the hot season when considering both transport and lairage (P < 0.05). The mortality risk ratio of DIP was lower at the slaughter house with the lowest stocking density (0.64 m(2)/100 kg live weight), large open windows on the roof and sidewalls, low brightness (40 lx) lights, and high-pressure sprinklers as cooling devices. The mortality risk ratio of DOA increased significantly for journeys longer than 2 h, whereas no relationship was found between length of transport and DIP. The piecewise analysis pointed out that 78.5 and 73.6 THI were the thresholds above which the mortality rate increased significantly for DOA and DIP, respectively. These results may help the pig industry to improve the welfare of heavy slaughter pigs during transport and lairage. |
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1525-3163 (Electronic) 0021-8812 (Linking) |
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LiveM, ft_macsur |
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MA @ admin @ |
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4641 |
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