AIM: To investigate a possible interaction between lolitrem B and ergovaline by comparing the incidence and severity of ryegrass staggers in sheep grazing ryegrass (Lolium perenne) containing lolitrem B or ryegrass containing both lolitrem B and ergovaline.
METHODS: Ninety lambs, aged approximately 6 months, were grazed on plots of perennial ryegrass infected with either AR98 endophyte (containing lolitrem B), standard endophyte (containing lolitrem B and ergovaline) or no endophyte, for up to 42 days from 2 February 2010. Ten lambs were grazed on three replicate plots per cultivar. Herbage samples were collected for alkaloid analysis and lambs were scored for ryegrass staggers (scores from 0–5) weekly during the study. Any animal which was scored ≥4 was removed from the study.
RESULTS: Concentrations of lolitrem B did not differ between AR98 and standard endophyte-infected pastures during the study period (p=0.26), and ergovaline was present only in standard endophyte pastures. Ryegrass staggers was observed in sheep grazing both the AR98 and standard endophyte plots, with median scores increasing in the third week of the study. Prior to the end of the 42-day grazing period, 22 and 17 animals were removed from the standard endophyte and AR98 plots, respectively, because their staggers scores were ≥4. The cumulative probability of lambs having scores ≥4 did not differ between animals grazing the two pasture types (p=0.41).
CONCLUSIONS AND CLINICAL RELEVANCE: There was no evidence for ergovaline increasing the severity of ryegrass staggers induced by lolitrem B. In situations where the severity of ryegrass staggers appears to be greater than that predicted on the basis of concentrations of lolitrem B, the presence of other tremorgenic alkaloids should be investigated. 相似文献
Based on the results of the atmospheric deposition classification of the year 1989, a methodical approach should be introduced,
which—based on the modelled total deposition rates—enables us to characterise the input situation of forest monitoring plots
and to delimit load areas in Germany. In 1989, the deposition situation in nearly 1,800 forest monitoring sites (BZE/extensive
Soil Condition Inventory) in Germany could be explained by four factors (or three, excluding sea salt impact) with the help
of a factor analysis. The factor values were grouped into six deposition types with typical compounds and regional patterns.
The classified input rates of the soil inventory plots adequately represent the stress situation and deposition changes in
Germany. The application of the statistical approach on the level of Brandenburg clarifies the special local input situation.
Due to the special combination of deposed elements, the sources of emissions can be characterised as well. When the soil inventory
is repeated, a project planned for 2006, this approach can be used in order to determine homogenous areas for stratified data
evaluation. 相似文献
In the 1970s unexpected forest damages, called “new type of forest damage” or “forest decline”, were observed in Germany and
other European countries. The Federal Republic of Germany and the German Federal States implemented a forest monitoring system
in the early 1980s, in order to monitor and assess the forest condition. Due to the growing public awareness of possible adverse
effects of air pollution on forests, in 1985 the ICP Forests was launched under the convention on long-range transboundary
air pollution (CLRTAP) of the United Nations Economic Commission for Europe (UN-ECE). The German experience in forest monitoring
was a base for the implementation of the European monitoring system. In 2001 the interdisciplinary case study “concept and
feasibility study for the integrated evaluation of environmental monitoring data in forests”, funded by the German Federal
Ministry of Education and Research, concentrated on in-depths evaluations of the German data of forest monitoring. The objectives
of the study were: (a) a reliable assessment of the vitality and functioning of forest ecosystems, (b) the identification
and quantification of factors influencing forest vitality, and (c) the clarification of cause-effect-relationships leading
to leaf/needle loss. For these purposes additional data from external sources were acquired: climate and deposition, for selected
level I plots tree growth data, as well as data on groundwater quality. The results show that in particular time series analysis
(crown condition, tree growth, and tree ring analysis), in combination with climate and deposition are valuable and informative,
as well as integrated evaluation of soil, tree nutrition and crown condition data. Methods to combine information from the
extensive and the intensive monitoring, and to transfer process information to the large scale should be elaborated in future.