Probabilistic Modelling of Cattle Farm Distribution in Australia

A probabilistic Bayesian method called weights of evidence (WofE) was used to develop a synthetic dataset of cattle farm locations at a national scale across Australia. The synthetic dataset was required for the modelling of livestock movements with a view to assessing biosecurity implications. The WofE method is based on the analysis of spatial relationships between evidential patterns with respect to an event, such as the actual location of a farm. The evidential patterns of cattle farms were derived from maps of land use, land tenure, drainage systems, roads, settlements and long-term averaged rainfall. These evidential patterns were used for delineating and ranking land areas suitable for cattle farming. For each evidential pattern statistics such as a positive weight, a negative weight and a contrast were calculated for estimating the degree of correlation between the evidential patterns and known farm locations. The integrated evidential patterns of known farms were then used for estimating posterior probabilities and splitting land into five different classes according to its suitability for farming.

Assessing the environmental performance of English arable and livestock holdings using data from the Farm Accountancy Data Network (FADN)

Agri-environment schemes (AESs) have been implemented across EU member states in an attempt to reconcile agricultural production methods with protection of the environment and maintenance of the countryside. To determine the extent to which such policy objectives are being fulfilled, participating countries are obliged to monitor and evaluate the environmental, agricultural and socio-economic impacts of their AESs. However, few evaluations measure precise environmental outcomes and critically, there are no agreed methodologies to evaluate the benefits of particular agri-environmental measures, or to track the environmental consequences of changing agricultural practices. In response to these issues, the Agri-Environmental Footprint project developed a common methodology for assessing the environmental impact of European AES. The Agri-Environmental Footprint Index (AFI) is a farm-level, adaptable methodology that aggregates measurements of agri-environmental indicators based on Multi-Criteria Analysis (MCA) techniques. The method was developed specifically to allow assessment of differences in the environmental performance of farms according to participation in agri-environment schemes. The AFI methodology is constructed so that high values represent good environmental performance. This paper explores the use of the AFI methodology in combination with Farm Business Survey data collected in England for the Farm Accountancy Data Network (FADN), to test whether its use could be extended for the routine surveillance of environmental performance of farming systems using established data sources. Overall, the aim was to measure the environmental impact of three different types of agriculture (arable, lowland livestock and upland livestock) in England and to identify differences in AFI due to participation in agri-environment schemes. However, because farm size, farmer age, level of education and region are also likely to influence the environmental performance of a holding, these factors were also considered. Application of the methodology revealed that only arable holdings participating in agri-environment schemes had a greater environmental performance, although responses differed between regions. Of the other explanatory variables explored, the key factors determining the environmental performance for lowland livestock holdings were farm size, farmer age and level of education. In contrast, the AFI value of upland livestock holdings differed only between regions. The paper demonstrates that the AFI methodology can be used readily with English FADN data and therefore has the potential to be applied more widely to similar data sources routinely collected across the EU-27 in a standardised manner.     

Agricultural Pesticide Residues in Farm Ditches of the Lower Fraser Valley,British Columbia,Canada

Transient and permanent farm ditches flowing to the Lower Fraser River tributary fish streams of British Columbia, Canada, were sampled at several locations in 2003–2004 to determine the occurrence and concentration of residues of selected pesticides, their transformation products, and soluble/extractable Cu⁺⁺ ions. Of the 43 compounds analyzed, 28 and 22 pesticides were detected in transient farm ditch water and sediments, respectively. About 34% fewer pesticides, however, were found in both matrices of permanent farm ditches. Average concentrations (μ g L^?1) of those most frequently detected in permanent farm ditch water were atrazine (0.20), α -chlordane (0.06), desethylatrazine (0.13), diazinon (0.55), dieldrin (0.28), endosulfan sulfate (0.16), glyphosate (6), metalaxyl (0.27); and soluble Cu⁺⁺ ions (25). Those most often found in ditch sediments (μ g kg^?1) were aminomethylphosphonic acid (AMPA) (2,300), 1,1,1-trichloro-2,2-bis-(4-chlorophenyl)ethane (DDT) (250), endosulfan sulfate (500), glyphosate (1,225); and extractable Cu⁺⁺ ions (58,000). The risk potential of these pesticide residues to non-target aquatic organisms inhabiting Fraser River tributary fish streams contiguous to permanent farm ditches is evaluated and discussed.     

Exploring diversity in soil fertility management of smallholder farms in western Kenya: I. Heterogeneity at region and farm scale

The processes of nutrient depletion and soil degradation that limit productivity of smallholder African farms are spatially heterogeneous. Causes of variability in soil fertility management at different scales of analysis are both biophysical and socio-economic. Such heterogeneity is categorised in this study, which quantifies its impact on nutrient flows and soil fertility status at region and farm scales, as a first step in identifying spatial and temporal niches for targeting of soil fertility management strategies and technologies. Transects for soil profile observation, participatory rural appraisal techniques and classical soil sampling and chemical analysis were sampled across 60 farms in three sub-locations (Emuhaia, Shinyalu, Aludeka), which together represent much of the variability found in the highlands of western Kenya. Five representative farm types were identified using socio-economic information and considering production activities, household objectives and the main constraints faced by farmers. Soil fertility management and nutrient resource flows were studied for each farm type and related to differences in soil fertility status at farm scale. Farm types 1 and 2 were the wealthiest; the former relied on off-farm income and farmed small pieces of land (0.6–1.1 ha) while the latter farmed relatively large land areas (1.6–3.8 ha) mainly with cash crops. The poorest farm type 5 also farmed small pieces of land (0.4–1.0 ha) but relied on low wages derived from working for wealthier farmers. Both farm types 1 and 5 relied on off-farm earnings and sold the least amounts of farm produce to the market, though the magnitude of their cash, labour and nutrient flows was contrasting. Farms of types 3 and 4 were intermediate in size and wealth, and represented different crop production strategies for self-consumption and the market. Average grain yields fluctuated around 1 t ha⁻¹ year⁻¹ for all farm types and sub-locations. Grain production by farms of types 4 and 5 was much below annual family requirements, estimated at 170 kg person⁻¹ year⁻¹. Household wealth and production orientation affected the pattern of resource flow at farm scale. In the land-constrained farms of type 1, mineral fertilisers were often used more intensively (ca. 50 kg ha⁻¹), though with varying application rates (14–92 kg ha⁻¹). The use of animal manure in such small farms (e.g. 2.2 t year⁻¹) represented intensities of use of up to 8 t ha⁻¹, and a net accumulation of C and macronutrients brought into the farm by livestock. In farms of type 5, intensities of use of mineral and organic fertilisers ranged between 0–12 kg ha⁻¹ and 0–0.5 t ha⁻¹, respectively. A consistent trend of decreasing input use from farm types 1–5 was generally observed, but nutrient resources and land management practices (e.g. fallow) differed enormously between sub-locations. Inputs of nutrients were almost nil in Aludeka farms. Both inherent soil properties and management explained the variability found in soil fertility status. Texture explained the variation observed in soil C and related total N between sub-locations, whereas P availability varied mainly between farm types as affected by input use.     

Community and farm forestry climate mitigation projects: case studies from Uttaranchal,India

The methodologies for forest mitigation projects still present challenges to project developers for fulfillment of criteria within the Clean Development Mechanism (CDM) or other such mechanisms for the purpose of earning carbon credits. This paper systematically approaches the process of establishing carbon (C) stocks for baseline (BSL) and mitigation scenario (MSL) for two case studies i.e., community and farm forestry projects in Uttaranchal, India. The analysis of various interventions shows that both projects present high carbon mitigation potential. However, the C reversibility risk is lower in long-rotation pine and mixed species plantation on community lands. The project is financially viable though not highly lucrative but the carbon mitigation potential in this ‘restoration of degraded lands’ type of project is immense provided challenges in the initial phase are adequately overcome. C revenue is an essential driver for investors in community projects. The short-rotation timber species such as Eucalyptus (Eucalyptus), Poplar (Populus) have high internal rates of return (IRR) and high carbon benefit reversibility potential due to fluctuations in market prices of commodities produced. The land holdings are small and bundling is desired for projects to achieve economies of scale. The methodological concerns such as sampling intensities, monitoring methodologies, sharing of benefits with communities and bundling arrangements for projects need further research to make these projects viable.     

丹东市主要农产品生产基地环境质量调查与评价

通过对丹东市主要农产品生产基地作物生长期的主要环境质量要素及周围污染源分布情况进行同步调查监测，并采用国家现行环境质量评价标准对其环境质量水平给予全面评价，得出结论是被调查区域土壤、灌溉用水和环境空气质量均达到《国家有机食品基地考核管理规定》中对基地环境质量的要求。     

GOAL-ORIENTED AGRICULTURAL WATER QUALITY LEGISLATION1

ABSTRACT: While significant nonpoint source (NIPS) pollution control progress has been made since passage of Section 319 in the 1987 Water Quality Act, existing federal legislation does not provide for the most timely and cost-effective NIPS pollution reduction. In this paper, we use findings from the Rural Clean Water Program and other nationwide agricultural NIPS pollution control programs, building on legislative history to recommend a coordinated and efficient direction for agricultural water quality legislation. A collaborative framework should be established to accomplish the goals of the Clean Water Act (CWA), Coastal Zone Management Act (CZMA), and the Conservation Title of the Farm Bill. Valuable elements of the 1990 CZMA amendments that created a coastal NIPS program should be subsumed into the CWA. The CWA should reemphasize use of receiving water quality criteria and standards and should allow states flexibility to tailor basin-scale NPS program implementation to local needs. Implementation should involve targeting of NIPS pollution control efforts to critical land treatment areas and use of systems of best management practices to address these targeted water quality problems. The 1995 Farm Bill should reorient production incentives toward water quality to support the collaborative framework, implementing ecologically sound source reduction principles. The Farm Bill and the CWA should contain interrelated provisions for voluntary, incentive-assisted producer participation and fallback regulatory measures. Such coordinated national water quality and Farm Bill legislation that recognizes the need for flexibility in state implementation is supported as the most rational and cost-effective means of attaining water quality goals.     

Modelling farm structural change for integrated ex-ante assessment: review of methods and determinants

This paper provides a literature review of methods and determinants relevant for modelling farm structural change within an integrated modelling chain. Environmental and economic impacts at farm level and individual farm responses to agricultural and agri-environmental policies strongly depend on characteristics like farm size, specialisation, and production intensity. Consequently, up-scaling results of corresponding farm type models in ex-ante assessment exercises requires comprehensive and valid predictions of the farm types’ future relevance under different scenarios. The paper reviews methods relevant to forecasting farm numbers in classes defined by farm typologies with the objective to identify (1) a preferable modelling approach and (2) empirically relevant determinants. Despite the literature's considerable size, even recent studies are rather limited in scope and typically restricted to a subset of farm types and one or very few regions. With regard to data availability, computational complexity and statistical validation procedures, Markov chain models are identified as the only generally suitable method for a broadly scoped modelling approach across European regions and a differentiated farm typology. However, other research on determinants of farm growth, the number of farm holders, farm succession as well as new multi-agent based simulation approaches hint at relevant explanatory variables previously not considered in Markov chain analyses. Their impact seems testable in more ambitious cross-regional and cross-farm type setups.     

重庆市农产品质量安全现状与发展对策

重庆市农产品质量安全总体上不容乐观,全面提升农产品质量刻不容缓。市场粮食质量安全令人担忧;茶叶质量安全不容乐观;蔬菜质量安全得到一定程度的控制,无公害蔬菜基地建设取得可喜成绩;水果质量安全总体较好。针对重庆市农产品质量安全现状与原因,提出了全面提升农产品质量安全的八大对策。