Data strategy for environmental assessment of agricultural regions via LCA: case study of a French catchment

Purpose

Various approaches have been carried out to extrapolate environmental assessments of farms to the regional level, some of them oversimplified and thus leading to high uncertainty. Key challenges include selection of a representative sample, construction of a farm/land use typology, the extrapolation strategy and dealing with data limitations. This work proposes a method for addressing these issues by means of statistically supported approaches.

Methods

We applied a novel approach combining a sampling strategy, estimation of farm-level environmental impacts via life cycle assessment (LCA), a farm typology based on principal component analysis, a statistical method for extending the farm sample given data constraints and finally linear extrapolation based on regional production and land use, taking into account the regional import–export balance. The approach was applied to a French case study, the Lieue de Grève catchment in the dairy-intensive Brittany region. A decision flowchart was developed to generalise the approach for similar applications dealing with farm and LCA data constraints. Additionally, innovative farm practices were modelled and their impacts propagated to the regional level.

Results and discussion

The typology developed identified “dairy”, “beef”, “dairy + beef” and “swine” farms as the dominant farm types in the region. While swine farms had the highest mean impacts per hectare, dairy and dairy + beef farms had impacts two to five times as high as those of beef and swine farms, when extrapolated to the entire catchment. Multiple linear regressions based on an extended farm and LCA dataset were used to predict environmental impacts of dairy farms lacking LCA results, thus increasing their sample size before extrapolation. The inclusion of farm and LCA data from a neighbouring region did not contribute to the accuracy of predicted impacts, as determined by comparing them to those of the farm closest to the dairy cluster’s centre, but rather produced significantly larger coefficients of variation. Results of tests of including two extra-regional farm and LCA datasets helped determine decision rules for the decision flowchart. Modelling of innovative agricultural practices yielded regional impacts consistent with previous estimates.

Conclusions

This approach provides a generalisable approach for farm typologies, data handling and regional extrapolation of farm-level LCAs, applicable to estimate environmental impacts of any agricultural area if requirements of a representative farm sample are met. We demonstrate the utility of the method for estimating effects of innovative agricultural practices on a region’s impacts by modelling practices on virtual farms and extrapolating their results.

     

Mixed crop-livestock systems: an economic and environmental-friendly way of farming?

Intensification and specialisation of agriculture in developed countries enabled productivity to be improved but had detrimental impacts on the environment and threatened the economic viability of a huge number of farms. The combination of livestock and crops, which was very common in the past, is assumed to be a viable alternative to specialised livestock or cropping systems. Mixed crop-livestock systems can improve nutrient cycling while reducing chemical inputs and generate economies of scope at farm level. Most assumptions underlying these views are based on theoretical and experimental evidence. Very few assessments of their environmental and economic advantages have nevertheless been undertaken in real-world farming conditions. In this paper, we present a comparative assessment of the environmental and economic performances of mixed crop-livestock farms v. specialised farms among the farm population of the French ‘Coteaux de Gascogne’. In this hilly region, half of the farms currently use a mixed crop-livestock system including beef cattle and cash crops, the remaining farms being specialised in either crops or cattle. Data were collected through an exhaustive survey of farms located in our study area. The economic performances of farming systems were assessed on 48 farms on the basis of (i) overall gross margin, (ii) production costs and (iii) analysis of the sensitivity of gross margins to fluctuations in the price of inputs and outputs. The environmental dimension was analysed through (i) characterisation of farmers’ crop management practices, (ii) analysis of farm land use diversity and (iii) nitrogen farm-gate balance. Local mixed crop-livestock farms did not have significantly higher overall gross margins than specialised farms but were less sensitive than dairy and crop farms to fluctuations in the price of inputs and outputs considered. Mixed crop-livestock farms had lower costs than crop farms, while beef farms had the lowest costs as they are grass-based systems. Concerning crop management practices, our results revealed an intensification gradient from low to high input farming systems. Beyond some general trends, a wide range of management practices and levels of intensification were observed among farms with a similar production system. Mixed crop-livestock farms were very heterogeneous with respect to the use of inputs. Nevertheless, our study revealed a lower potential for nitrogen pollution in mixed crop-livestock and beef production systems than in dairy and crop farming systems. Even if a wide variability exists within system, mixed crop-livestock systems appear to be a way for an environmental and economical sustainable agriculture.     

Implications of feed concentrate reduction in organic grassland-based dairy systems: a long-term on-farm study

In response to increasing efforts for reducing concentrate inputs to organic dairy production in grassland-rich areas of Europe, a long-term study was conducted, which assessed the impacts of concentrate reductions on cows’ performance, health, fertility and average herd age. In total, 42 Swiss commercial organic dairy cattle farms were monitored over 6 years (‘Y0’, 2008/09 until ‘Y5’, 2013/14). In comparison with overall data of Swiss herdbooks (including conventional and organic farms), the herds involved in the project had lower milk yields, similar milk solids, shorter calving intervals and higher average lactation numbers. During the first 3 project years farmers reduced the concentrate proportion (i.e. cereals, oilseeds and grain legumes) in the dairy cows’ diets to varying degrees. In Y0, farms fed between 0% and 6% (dietary dry matter proportion per year) of concentrates. During the course of the study they changed the quantity of concentrates to voluntarily chosen degrees. Retrospectively, farms were clustered into five farm groups: Group ‘0-conc’ (n=6 farms) already fed zero concentrates in Y0 and stayed at this level. Group ‘Dec-to0’ (n=11) reduced concentrates to 0 during the project period. Groups ‘Dec-strong’ (n=8) and ‘Dec-slight’ (n=12) decreased concentrate amounts by >50% and <50%, respectively. Group ‘Const-conc’ (n=5 farms) remained at the initial level of concentrates during the project. Milk recording data were summarised and analysed per farm and project year. Lactation number and calving intervals were obtained from the databases of the Swiss breeders’ associations. Dietary concentrate amounts and records of veterinary treatments were obtained from the obligatory farm documentations. Data were analysed with GLMs. Daily milk yields differed significantly between farm groups already in Y0, being lowest in groups 0-conc (16.0 kg) and Dec-to0 (16.7 kg), and highest in groups Dec-slight (19.6 kg) and Const-conc (19.2 kg). Milk yield decreases across the years within groups were not significant, but urea contents in milk decreased significantly during the course of the project. Milk protein, somatic cell score, fat–protein ratio, average lactation number, calving interval and frequency of veterinary treatments did not differ by group and year. In conclusion, 5 years of concentrate reduction in low-input Swiss organic dairy farms, affected neither milk composition, nor fertility and veterinary treatments. Milk yields tended to decline, but at a low rate per saved kilogram of concentrate.     

Graph-based impact analysis as a framework for incorporating practitioner knowledge in dairy herd health management

Production diseases in dairy cows are multifactorial, which means they emerge from complex interactions between many different farm variables. Variables with a large impact on production diseases can be identified for groups of farms using statistical models, but these methods cannot be used to identify highly influential variables in individual farms. This, however, is necessary for herd health planning, because farm conditions and associated health problems vary largely between farms. The aim of this study was to rank variables according to their anticipated effect on production diseases on the farm level by applying a graph-based impact analysis on 192 European organic dairy farms. Direct impacts between 13 pre-defined variables were estimated for each farm during a round-table discussion attended by practitioners, that is farmer, veterinarian and herd advisor. Indirect impacts were elaborated through graph analysis taking into account impact strengths. Across farms, factors supposedly exerting the most influence on production diseases were ‘feeding’, ‘hygiene’ and ‘treatment’ (direct impacts), as well as ‘knowledge and skills’ and ‘herd health monitoring’ (indirect impacts). Factors strongly influenced by production diseases were ‘milk performance’, ‘financial resources’ and ‘labour capacity’ (directly and indirectly). Ranking of variables on the farm level revealed considerable differences between farms in terms of their most influential and most influenced farm factors. Consequently, very different strategies may be required to reduce production diseases in these farms. The method is based on perceptions and estimations and thus prone to errors. From our point of view, however, this weakness is clearly outweighed by the ability to assess and to analyse farm-specific relationships and thus to complement general knowledge with contextual knowledge. Therefore, we conclude that graph-based impact analysis represents a promising decision support tool for herd health planning. The next steps include testing the method using more specific and problem-oriented variables as well as evaluating its effectiveness.     

An appraisal of carbon footprint of milk from commercial grass-based dairy farms in Ireland according to a certified life cycle assessment methodology

Purpose

Life cycle assessment (LCA) studies of carbon footprint (CF) of milk from grass-based farms are usually limited to small numbers of farms (<30) and rarely certified to international standards, e.g. British Standards Institute publicly available specification 2050 (PAS 2050). The goals of this study were to quantify CF of milk from a large sample of grass-based farms using an accredited PAS 2050 method and to assess the relationships between farm characteristics and CF of milk.

Materials and methods

Data was collected annually using on-farm surveys, milk processor records and national livestock databases for 171 grass-based Irish dairy farms with information successfully obtained electronically from 124 farms and fed into a cradle to farm-gate LCA model. Greenhouse gas (GHG) emissions were estimated with the LCA model in CO₂ equivalents (CO₂-eq) and allocated economically between dairy farm products, except exported crops. Carbon footprint of milk was estimated by expressing GHG emissions attributed to milk per kilogram of fat and protein-corrected milk (FPCM). The Carbon Trust tested the LCA model for non-conformities with PAS 2050. PAS 2050 certification was achieved when non-conformities were fixed or where the effect of all unresolved non-conformities on CF of milk was?<?±5 %.

Results and discussion

The combined effect of LCA model non-conformities with PAS 2050 on CF of milk was <1 %. Consequently, PAS 2050 accreditation was granted. The mean certified CF of milk from grass-based farms was 1.11 kg of CO₂-eq/kg of FPCM, but varied from 0.87 to 1.72 kg of CO₂-eq/kg of FPCM. Although some farm attributes had stronger relationships with CF of milk than the others, no attribute accounted for the majority of variation between farms. However, CF of milk could be reasonably predicted using N efficiency, the length of the grazing season, milk yield/cow and annual replacement rate (R ²?=?0.75). Management changes can be applied simultaneously to improve each of these traits. Thus, grass-based farmers can potentially significantly reduce CF of milk.

Conclusions

The certification of an LCA model to PAS 2050 standards for grass-based dairy farms provides a verifiable approach to quantify CF of milk at a farm or national level. The application of the certified model highlighted a wide range between the CF of milk of commercial farms. However, differences between farms’ CF of milk were explained by variation in various aspects of farm performance. This implies that improving farm efficiency can mitigate CF of milk.     

Life cycle assessment framework in agriculture on the farm level

Life Cycle Assessment (LCA) is a method that can be used to assess the environmental impact of agriculture, but impact categories and the functional unit of classical LCA’s must be adapted to the specific agricultural production process. Serving as an example, the framework of a LCA of 18 grassland dairy farms covering three farming intensity levels and carried out in the Allgäu region in southern Germany is presented. By focussing on the chosen impact categories and the respective, suitable functional units, the specific needs and backgrounds of conducting an agricultural LCA are discussed in general.     

Quantitative Ecological Risk Analysis by Evaluating China's Eco-Efficiency and Its Determinants

Industrial production can produce large amounts of harmful by-products, causing serious pollution and ecological risk. In addition, if government regulations are subjected into the industries, huge cost risk will be faced. This article adopts a two-stage slack-based undesirable-output data envelope analysis (DEA) model to measure the eco-efficiency of China. In the first stage, we analyze the eco-efficiency of each province of China, and in the second stage, we employed a truncated bootstrap method to understand the determinants of eco-efficiency. The results indicate that whereas the eco-efficiency of the eastern region was the highest, that of the western region was the lowest. The western region's economy lagged behind that of other regions, and its environment suffered from heavy pollution. It was found that the level of industrialization did not contribute to eco-efficiency. However, promotion of the service industry, investment for the environment, and regional innovation have positive effects on eco-efficiency.     

On the link between economic and environmental performance of Swiss dairy farms of the alpine area

Purpose

Promoting the economic and environmental performance of Swiss farms is a major objective of Swiss agricultural policy. In the present paper, we investigate the relationship between the economic and global environmental performance of the Swiss dairy farms in the alpine area.

Methods

The analysis relies on a sample of 56 dairy farms from the Farm Accountancy Data Network, for which highly precise and comprehensive Life Cycle Assessments have been carried out. The work income per family work unit is used as indicator of the economic performance of a farm. The so-called global environmental performance of a farm is, for its part, measured by means of an eco-efficiency indicator for each environmental impact considered (demand for non-renewable energy resources, eutrophication potential, aquatic ecotoxicity potential, human toxicity potential and land use) and of an aggregate eco-efficiency indicator assessed using a Data Envelopment Analysis-based approach. The relationship between economic and global environmental performance is assessed by means of non-parametric Spearman??s rank correlation analysis.

Results

The results of the analysis reveal the existence of a positive relationship between economic and global environmental performance. This positive relationship exists for all environmental issues considered and thus also for the aggregate eco-efficiency indicator. Its strength, however, substantially varies from one issue to another.

Conclusions

This study provides the evidence that there is no trade-off between economic and global environmental farm performance. When they improve their economic performance, farms also tend to improve their global environmental performance and vice versa. This finding is of central relevance for policy-makers as it should contribute to improving the acceptance among farmers of the environmental objectives of Swiss agricultural policy in terms of an increase in environmental resource use productivity. In this sense this work provides valuable insights into the sustainable performance of the Swiss dairy sector in the alpine area.     

Farm-level emission intensities of smallholder cattle (Bos indicus; B. indicus–B. taurus crosses) production systems in highlands and semi-arid regions

Ruminants are central to the economic and nutritional life of much of sub-Saharan Africa, but cattle are now blamed for having a disproportionately large negative environmental impact through emissions of greenhouse gas (GHG). However, the mechanism underlying excessive emissions occurring only on some farms is imperfectly understood. Reliable estimates of emissions themselves are frequently lacking due to a paucity of reliable data. Employing individual animal records obtained at regular farm visits, this study quantified farm-level emission intensities (EIs) of greenhouse gases of smallholder farms in three counties in Western Kenya. CP was chosen as the functional unit to capture the outputs of both milk and meat. The results showed that milk is responsible for 80–85% of total CP output. Farm EI ranged widely from 20 to >1 000 kg CO₂-eq/kg CP. Median EIs were 60 (Nandi), 71 (Bomet), and 90 (Nyando) kg CO₂-eq/kg. Although median EIs referenced to milk alone (2.3 kg CO₂-eq/kg milk) were almost twice that reported for Europe, up to 50% of farms had EIs comparable to the mean Pan-European EIs. Enteric methane (CH₄) contributed >95% of emissions and manure ～4%, with negligible emissions attributed to inputs to the production system. Collecting data from individual animals on smallholder farms enabled the demonstration of extremely heterogeneous EI status among similar geographical spaces and provides clear indicators on how low EI status may be achieved in these environments. Contrary to common belief, our data show that industrial-style intensification is not required to achieve low EI. Enteric CH₄ production overwhelmingly drives farm emissions in these systems and as this is strongly collinear with nutrition and intake, an effort will be required to achieve an “efficient frontier” between feed intake, productivity, and GHG emissions.     

The relation between input-output transformation and gastrointestinal nematode infections on dairy farms

Efficiency analysis is used for assessing links between technical efficiency (TE) of livestock farms and animal diseases. However, previous studies often do not make the link with the allocation of inputs and mainly present average effects that ignore the often huge differences among farms. In this paper, we studied the relationship between exposure to gastrointestinal (GI) nematode infections, the TE and the input allocation on dairy farms. Although the traditional cost allocative efficiency (CAE) indicator adequately measures how a given input allocation differs from the cost-minimising input allocation, they do not represent the unique input allocation of farms. Similar CAE scores may be obtained for farms with different input allocations. Therefore, we propose an adjusted allocative efficiency index (AAEI) to measure the unique input allocation of farms. Combining this AAEI with the TE score allows determining the unique input-output position of each farm. The method is illustrated by estimating efficiency scores using data envelopment analysis (DEA) on a sample of 152 dairy farms in Flanders for which both accountancy and parasitic monitoring data were available. Three groups of farms with a different input-output position can be distinguished based on cluster analysis: (1) technically inefficient farms, with a relatively low use of concentrates per 100 l milk and a high exposure to infection, (2) farms with an intermediate TE, relatively high use of concentrates per 100 l milk and a low exposure to infection, (3) farms with the highest TE, relatively low roughage use per 100 l milk and a relatively high exposure to infection. Correlation analysis indicates for each group how the level of exposure to GI nematodes is associated or not with improved economic performance. The results suggest that improving both the economic performance and exposure to infection seems only of interest for highly TE farms. The findings indicate that current farm recommendations regarding GI nematode infections could be improved by also accounting for the allocation of inputs on the farm.     

Rearing performances and environmental assessment of sea cage farming in Tunisia using life cycle assessment (LCA) combined with PCA and HCPC

Purpose

The present study aims to understand the influence of rearing practices and the contributions of production phases of fish farming to their environmental impacts and determine which practices and technical characteristics can best improve the farms’ environmental performance. Another objective is to identify the influence of variability in farming practices on the environmental performances of sea cage aquaculture farms of sea bass and sea bream in Tunisia by using principal component analysis (PCA) and hierarchical clustering on principal components (HCPC) methods and then combining the classification with life cycle assessment (LCA).

Methods

The approach consisted of three major steps: (i) of the 24 aquaculture farms in Tunisia, 18 were selected which follow intensive rearing practices in sea cages of European sea bass (Dicentrarchus labrax) and gilthead sea bream (Sparus aurata) and then a typology was developed to classify the studied farms into rearing practice groups using HCPC; (ii) LCA was performed on each aquaculture farm and (iii) mean impacts and contributions of production phases were calculated for each group of farms. Impact categories included acidification, eutrophication, global warming, land occupation, total cumulative energy demand and net primary production use.

Results and discussion

Results revealed high correlation between rearing practices and impacts. The feed-conversion ratio (FCR), water column depth under the cages and cage size had the greatest influence on impact intensity. Rearing practices and fish feed were the greatest contributors to the impacts studied due to the production of fish meal and oil and the low efficiency of feed use, which generated large amounts of nitrogen and phosphorus emissions. It is necessary to optimise the diet formulation and to follow better feeding strategies to lower the FCR and improve farm performance. Water column depth greatly influenced the farms’ environmental performance due to the increase in waste dispersion at deeper depths, while shallow depths resulted in accumulation of organic matter and degradation of water quality. Cage size influences environmental performances of aquaculture farms. Thus, from an environmental viewpoint, decision makers should grant licences for farms in deeper water with larger cages and encourage them to improve their FCRs.

Conclusions

This study is the first attempt to combine the HCPC method and the LCA framework to study the environmental performance of aquacultural activity. The typology developed captures the variability among farms because it considers several farm characteristics in the classification. The LCA demonstrated that technical parameters in need of improvement are related to the technical expertise of farm managers and workers and to the location of the farm.

     

基于高通量测序技术分析四川两个奶牛场乳汁的菌群差异

【目的】本试验测定了两个奶牛场健康乳汁和乳房炎乳汁中微生物菌群的变化,以揭示不同奶牛场之乳汁菌群的异同,评估其对乳汁代谢的影响是否相同。【方法】采用16S rRNA高通量测序技术,分别测定两个奶牛场6头健康奶牛和6头乳房炎奶牛乳汁中微生物16S rRNA V4区序列,并对菌群群落结构和多样性进行比较,分析场内及场间的乳汁菌群差异。【结果】四组乳汁样本共获得4013234条原始序列,经过滤后获得2887024条优化序列。Alpha多样性Chao指数、Ace指数、Shannon指数、Simpson指数差异均不显著(P0.05);Beta多样性四组样本均分别聚类;在场1和场2中,引起奶牛乳房炎的优势菌属分别是克雷伯氏菌属和埃希氏菌属;在2个奶牛场的健康乳汁中,场2的埃希氏菌属、葡萄球菌属的丰度显著高于场1;在2个奶牛场的乳房炎乳汁中,场2的埃希氏菌属、乳球菌属的丰度显著高于场1;2个奶牛场健康乳汁中的嗜冷菌总丰度分别为31.87%和38.72%;关联分析及功能预测分析表明,2个奶牛场健康乳汁与乳房炎乳汁优势物种之间的关系差异较大;场1无论是Level 1还是Level 2水平,均发现显著性差异的代谢通路,而场2均未发现显著性差异的代谢通路。【结论】本试验研究了两个奶牛场健康乳汁和乳房炎乳汁微生物菌群之间的异同,为两个奶牛场在乳房炎的预防工作以及原料奶在冷链运输过程中质量控制提供理论依据。     

Feeding behavior improves prediction of dairy cow voluntary feed intake but cannot serve as the sole indicator

Low-cost feeding-behavior sensors will soon be available for commercial use in dairy farms. The aim of this study was to develop a feed intake model for the individual dairy cow that includes feeding behavior. In a research farm, the individual cows’ voluntary feed intake and feeding behavior were monitored at every meal. A feed intake model was developed based on data that exist in commercial modern farms: ‘BW,’ ‘milk yield’ and ‘days in milking’ parameters were applied in this study. At the individual cow level, eating velocity seemed to be correlated with feed intake (R²=0.93 to 0.94). The eating velocity coefficient varied among individuals, ranging from 150 to 230 g/min per cow. The contribution of feeding behavior (0.28) to the dry matter intake (DMI) model was higher than the contribution of BW (0.20), similar to the contribution of fat-corrected milk (FCM)/BW (0.29) and not as large as the contribution of FCM (0.49). Incorporating feeding behavior into the DMI model improved its accuracy by 1.3 (38%) kg/cow per day. The model is ready to be implemented in commercial farms as soon as companies introduce low-cost feeding-behavior sensors on commercial level.     

Involvement of small-scale dairy farms in an industrial supply chain: when production standards meet farm diversity

In certain contexts, dairy firms are supplied by small-scale family farms. Firms provide a set of technical and economic recommendations meant to help farmers meet their requirements in terms of the quantity and quality of milk collected. This study analyzes how such recommendations may be adopted by studying six farms in Brazil. All farms are beneficiaries of the country's agrarian reforms, but they differ in terms of how they developed their activities, their resources and their milk collection objectives. First, we built a technical and economic benchmark farm based on recommendations from a dairy firm and farmer advisory institutions. Our analysis of the farms' practices and technical and economic results show that none of the farms in the sample apply all of the benchmark recommendations; however, all farms specialized in dairy production observe the main underlying principles with regard to feeding systems and breeding. The decisive factors in whether the benchmark is adopted and successfully implemented are (i) access to the supply chain when a farmer establishes his activity, (ii) a grasp of reproduction and forage production techniques and (iii) an understanding of dairy cattle feed dietary rationing principles. The technical problems observed in some cases impact the farms' dairy performance and cash position; this can lead to a process of disinvestment. This dynamic of farms facing production standards suggests that the diversity of specialized livestock farmers should be taken into account more effectively through advisory approaches that combine basic zootechnical training with assistance in planning farm activities over the short and medium term.     

Relative emissions intensity of dairy production systems: employing different functional units in life-cycle assessment

This study aimed to assess the merit and suitability of individual functional units (FU) in expressing greenhouse gas emissions intensity in different dairy production systems. An FU provides a clearly defined and measurable reference to which input and output data are normalised. This enables the results from life-cycle assessment (LCA) of different systems to be treated as functionally equivalent. Although the methodological framework of LCA has been standardised, selection of an appropriate FU remains ultimately at the discretion of the individual study. The aim of the present analysis was to examine the effect of different FU on the emissions intensities of different dairy production systems. Analysis was based on 7 years of data (2004 to 2010) from four Holstein-Friesian dairy systems at Scotland’s Rural College’s long-term genetic and management systems project, the Langhill herd. Implementation of LCA accounted for the environmental impacts of the whole-farm systems and their production of milk from ‘cradle to farm gate’. Emissions intensity was determined as kilograms of carbon dioxide equivalents referenced to six FU: UK livestock units, energy-corrected milk yield, total combined milk solids yield, on-farm land used for production, total combined on- and off-farm land used for production, and the proposed new FU–energy-corrected milk yield per hectare of total land used. Energy-corrected milk was the FU most effective for reflecting differences between the systems. Functional unit that incorporated a land-related aspect did not find difference between systems which were managed under the same forage regime, despite their comprising different genetic lines. Employing on-farm land as the FU favoured grazing systems. The proposed dual FU combining both productivity and land use did not differentiate between emissions intensity of systems as effectively as the productivity-based units. However, this dual unit displayed potential to quantify in a simple way the positive or negative outcome of trade-offs between land and production efficiencies, in which improvement in emissions intensity using one FU may be accompanied by deterioration using another FU. The perceived environmental efficiencies of different dairy production systems in terms of their emissions intensities were susceptible to change based upon the FU employed, and hence the FU used in any study needs to be taken into account in the interpretation of results.     

中国农业生态效率评价方法与实证——基于非期望产出的SBM模型分析

生态效率是衡量经济与资源环境协调发展的重要指标.基于将农业面源污染作为非期望产出的考量,在对传统DEA模型进行修正的基础上,采用非径向、非角度的SBM模型对中国30个省份的农业生态效率进行了测算,并给出了农业生态效率的改善途径.研究结果表明:1998-2009年中国农业生态效率虽然呈现缓慢上升态势,但整体仍处于较低水平,除北京、上海、海南、重庆外,其余省市都需要改变投入和产出来优化农业生态效率;资源的过度消耗和环境污染物的过量排放是农业生态效率损失的主要原因.提高资源利用效率、降低资源消耗量和环境污染物的排放量是农业生态效率改善的重要途径.     

Evaluation of the effect of accounting method,IPCC v. LCA,on grass-based and confinement dairy systems’ greenhouse gas emissions

Life cycle assessment (LCA) and the Intergovernmental Panel on Climate Change (IPCC) guideline methodology, which are the principal greenhouse gas (GHG) quantification methods, were evaluated in this study using a dairy farm GHG model. The model was applied to estimate GHG emissions from two contrasting dairy systems: a seasonal calving pasture-based dairy farm and a total confinement dairy system. Data used to quantify emissions from these systems originated from a research study carried out over a 1-year period in Ireland. The genetic merit of cows modelled was similar for both systems. Total mixed ration was fed in the Confinement system, whereas grazed grass was mainly fed in the grass-based system. GHG emissions from these systems were quantified per unit of product and area. The results of both methods showed that the dairy system that emitted the lowest GHG emissions per unit area did not necessarily emit the lowest GHG emissions possible for a given level of product. Consequently, a recommendation from this study is that GHG emissions be evaluated per unit of product given the growing affluent human population and increasing demand for dairy products. The IPCC and LCA methods ranked dairy systems’ GHG emissions differently. For instance, the IPCC method quantified that the Confinement system reduced GHG emissions per unit of product by 8% compared with the grass-based system, but the LCA approach calculated that the Confinement system increased emissions by 16% when off-farm emissions associated with primary dairy production were included. Thus, GHG emissions should be quantified using approaches that quantify the total GHG emissions associated with the production system, so as to determine whether the dairy system was causing emissions displacement. The IPCC and LCA methods were also used in this study to simulate, through a dairy farm GHG model, what effect management changes within both production systems have on GHG emissions. The findings suggest that single changes have a small mitigating effect on GHG emissions (<5%), except for strategies used to control emissions from manure storage in the Confinement system (14% to 24%). However, when several management strategies were combined, GHG emissions per unit of product could be reduced significantly (15% to 30%). The LCA method was identified as the preferred approach to assess the effect of management changes on GHG emissions, but the analysis indicated that further standardisation of the approach is needed given the sensitivity of the approach to allocation decisions regarding milk and meat.     

Variation in the faecal shedding of Salmonella and E. coli O157:H7 in lactating dairy cattle and examination of Salmonella genotypes using pulsed-field gel electrophoresis

AIMS: To examine the variability in faecal shedding of Salmonella and Escherichia coli O157:H7 in healthy lactating dairy cattle and to evaluate the genetic relatedness of Salmonella isolates. METHODS: Faecal samples were obtained from lactating Holstein dairy cattle on four commercial farms in the southwestern US. All farms were within an 8-km radius and were sampled in August 2001, January 2002 and August 2002 (60 cows per farm per sampling; n = 720 total samples). Samples were cultured for E. coli O157:H7 and Salmonella and a portion of the recovered Salmonella isolates were examined for genetic relatedness using pulsed-field gel electrophoresis (PFGE). RESULTS: Faecal shedding of E. coli O157:H7 and Salmonella varied considerably between farms and at the different sampling times. Large fluctuations in the percentage of positive animals were observed from summer to summer for both of these pathogens. Similarly, Salmonella serotype and serotype prevalence varied from farm to farm and within farm from one sampling time to another. Multiple Salmonella genotypes were detected for a number of serotypes and identical genotypes were found on different farms with one genotype of Salmonella Senftenberg identified on three of the four farms. Significance and Impact of the STUDY: This study demonstrated the wide variability in pathogen shedding within and among dairy farms all located in a small geographical region and highlights the complexity of pathogen control at the farm level.     

Climate mitigation by dairy intensification depends on intensive use of spared grassland

Milk and beef production cause 9% of global greenhouse gas (GHG) emissions. Previous life cycle assessment (LCA) studies have shown that dairy intensification reduces the carbon footprint of milk by increasing animal productivity and feed conversion efficiency. None of these studies simultaneously evaluated indirect GHG effects incurred via teleconnections with expansion of feed crop production and replacement suckler‐beef production. We applied consequential LCA to incorporate these effects into GHG mitigation calculations for intensification scenarios among grazing‐based dairy farms in an industrialized country (UK), in which milk production shifts from average to intensive farm typologies, involving higher milk yields per cow and more maize and concentrate feed in cattle diets. Attributional LCA indicated a reduction of up to 0.10 kg CO₂e kg^?1 milk following intensification, reflecting improved feed conversion efficiency. However, consequential LCA indicated that land use change associated with increased demand for maize and concentrate feed, plus additional suckler‐beef production to replace reduced dairy‐beef output, significantly increased GHG emissions following intensification. International displacement of replacement suckler‐beef production to the “global beef frontier” in Brazil resulted in small GHG savings for the UK GHG inventory, but contributed to a net increase in international GHG emissions equivalent to 0.63 kg CO₂e kg^?1 milk. Use of spared dairy grassland for intensive beef production can lead to net GHG mitigation by replacing extensive beef production, enabling afforestation on larger areas of lower quality grassland, or by avoiding expansion of international (Brazilian) beef production. We recommend that LCA boundaries are expanded when evaluating livestock intensification pathways, to avoid potentially misleading conclusions being drawn from “snapshot” carbon footprints. We conclude that dairy intensification in industrialized countries can lead to significant international carbon leakage, and only achieves GHG mitigation when spared dairy grassland is used to intensify beef production, freeing up larger areas for afforestation.     

Paddock trees, parrots and agricultural production: An urgent need for large-scale, long-term restoration in south-eastern Australia

Summary Scattered trees, or ‘paddock trees’, are keystone structures, which provide multiple ecological values. However, they are in decline in many places. This has serious implications for species that use them, such as the vulnerable Superb Parrot (Polytelis swainsonii) of south‐eastern Australia. We outline three key aspects of the ecology, biology and distribution of the species that illustrate the implications of scattered tree decline. These are that (i) it depends on trees; (ii) it lives across agricultural landscapes; and (iii) it uses scattered tree landscapes dynamically in response to climate variation. We outline the dual challenge of maintaining populations of both scattered trees and the Superb Parrot over large scales and over the long term. Without urgent restoration action, a narrow bottleneck (where there are few mature trees) will make the long‐term future of the Superb Parrot precarious in these landscapes. We outline a vision for future landscapes that addresses this challenge, including the development of a form of Australian ‘wood‐pasture’. We suggest some ways that might be implemented at two scales. At the farm scale, we suggest (i) protecting what remnant vegetation we currently have; (ii) recruiting future large, old trees; (iii) sequentially setting aside land to ensure whole‐of‐farm tree regeneration; (iv) use of incentives to encourage restoration actions; and (v) using a revolving land fund to purchase and reorganize farms into economically and ecologically sustainable units. At the landscape scale, we suggest (i) the need for coordination of long‐term landscape restoration plans; (ii) the possible collaborative management of adjacent farms to ensure economic and ecological sustainability. We conclude that addressing the large‐scale and long‐term challenges of restoring scattered trees in landscapes occupied by the Superb Parrot could restore lost or diminished ecological services. This challenge illustrates the need for action at both the farm and the landscape scale that is planned over the short, medium and long term.