The increased recognition of the importance of soil is reflected in the UN Post‐2015 Development Agenda with sustainable development goals that directly and indirectly relate to soil quality and protection. Despite a lack of legally binding legislation for soil protection, the European Commission remains committed to the objective of soil protection. However, the achievement of a legally binding framework for soil protection relies on the implementation of a soil monitoring network (SMN) that can detect changes to soil quality over time. As beneficiaries do not pay for the provision of soil information, the options for soil monitoring are limited. The use of existing data sets should be considered first. Using Ireland as an example, this research explored the opportunities for a SMN for Ireland considering three existing national data sets. The options for a SMN are considered in terms of their spatial and stratified distribution, the parameters to be measured and an economic analysis of the options proposed. This research finds that for Ireland, either a 10 or a 16 km2 grid interval stratified by land use and drainage class offers the best potential in relation to the spatial distribution of existing data sets to reflect local data at a national level. With existing data, the stratified SIS data using the 16 km2 grid offers the best value for money, with baseline costs for analysis, excluding field costs, of between €706 481 and €2.8 million. Acknowledging the impossibility of measuring all parameters with ideal frequency, this study proposes a two‐tier system for optimized monitoring frequency. Parameters must anticipate future policy requirements. Finally, the implementation of a SMN must be accompanied by standardized methods, defined thresholds and action mandates to maintain soil quality within allowable limits. 相似文献
Genetic factors are undoubtedly involved in inter-individual variability of the behaviours that may be important for livestock production, as shown by pedigree studies, comparison of genetic stocks raised in the same environment, and selection experiments. The knowledge of gene polymorphisms responsible for genetic variability would increase the efficiency of selection, as shown for instance by the identification of the ryanodine receptor gene that harbours the mutations responsible for the porcine stress syndrome, that allows the eradication of the susceptibility allele. One strategy is to screen systematically the genes that are known to be involved in regulation of behaviour (functional candidate genes). This strategy is however very difficult for most behavioural traits, since behaviour is an emerging function from the whole brain/body and the molecular pathways involved in genetic variability are very poorly understood. Another strategy is to investigate linkage between trait variation and genetic markers in a segregating population (usually an intercross or backcross between two strains or breeds contrasting for the trait under study). It allows the detection of genomic regions influencing that trait (quantitative trait loci or QTL), and further investigation aims at the identification of the gene(s) located in each of these regions and the molecular polymorphisms involved in phenotypic variation. Although many QTL have been published for behavioural traits in experimental animals, very few examples are available where strong candidate genes have been identified. Further progress will be very much dependent upon the careful definition of behavioural traits to be studied (including their importance for animal production), on the reliability of their measurement in a large number of animals and on the efficient mastering of environmental factors of variability. The fast increase in the knowledge of genome sequence in several species will undoubtedly facilitate the application to farm animal species of the knowledge obtained in model organisms, as well as the use of model organisms to explore candidate genes detected by QTL studies in farm animals. 相似文献
1. The aim of this study was to investigate if male-to-female aggression of common pheasants in the course of the breeding season was related to the concentration of plasma testosterone and/or other biochemical plasma indicators in male pheasants housed in breeding cages. The influence of season on the concentration of testosterone and biochemical indicators was also investigated.
2. Males were divided into non-aggressive and aggressive groups during the breeding season based on ethological evaluation. At the beginning, in the middle and at the end of the breeding season, a blood sample was taken from all males on the same day and the concentration of selected biochemical indicators and the total circulating testosterone in the plasma were determined.
3. Male-to-female aggression during the breeding season of pheasants was not influenced by the total plasma testosterone of males.
4. The concentration of total plasma testosterone in males decreased gradually during the breeding season.
5. Male-to-female aggression of pheasants did not have a significant effect on any of the assessed biochemical indicators.
6. The influence of the breeding season affected the activities of alanine aminotransferase and aspartate aminotransferase as well as the concentrations of glucose, magnesium, potassium and chloride in the blood plasma of cage-housed male pheasants. 相似文献
The impact of extreme events (such as prolonged droughts, heat waves, cold shocks and frost) is poorly represented by most of the existing yield forecasting systems. Two new model-based approaches that account for the impact of extreme weather events on crop production are presented as a way to improve yield forecasts, both based on the Crop Growth Monitoring System (CGMS) of the European Commission. A first approach includes simple relations – consistent with the degree of complexity of the most generic crop simulators – to explicitly model the impact of these events on leaf development and yield formation. A second approach is a hybrid system which adds selected agro-climatic indicators (accounting for drought and cold/heat stress) to the previous one. The new proposed methods, together with the CGMS-standard approach and a system exclusively based on selected agro-climatic indicators, were evaluated in a comparative fashion for their forecasting reliability. The four systems were assessed for the main micro- and macro-thermal cereal crops grown in highly productive European countries. The workflow included the statistical post-processing of model outputs aggregated at national level with historical series (1995–2013) of official yields, followed by a cross-validation for forecasting events triggered at flowering, maturity and at an intermediate stage. With the system based on agro-climatic indicators, satisfactory performances were limited to microthermal crops grown in Mediterranean environments (i.e. crop production systems mainly driven by rainfall distribution). Compared to CGMS-standard system, the newly proposed approaches increased the forecasting reliability in 94% of the combinations crop × country × forecasting moment. In particular, the explicit simulation of the impact of extreme events explained a large part of the inter-annual variability (up to +44% for spring barley in Poland), while the addition of agro-climatic indicators to the workflow mostly added accuracy to an already satisfactory forecasting system. 相似文献