Testing trophic-functional relationships for modelling farmland diversity and functional dynamics

人们普遍担心，英国生物多样性的持续下降将因进一步的农业集约化而加剧，例如采用转基因技术。Defra资助的农场规模评估是为了解决这些关切，并成功地表明，与GMHT作物种植相关的管理变化对耕地多样性产生了影响。然而，鉴于可耕种生物多样性已经处于下降状态，我们没有客观标准来比较新管理做法的效果。此外，与所有经验研究一样，很难预测结果可能会随着不同的作物或管理系统，或在不同的空间和时间尺度上而变化。因此，需要建立模型来解决这些问题，并提供一种手段，根据客观定义的生物多样性标准预测新技术的可能风险。在这个建议中，我们的目的是测试假设，即Hawes等人的模型规范。(2003)和Bohan等人。(提交的a、b)将导致可预测生态系统动态和不同管理做法对生态系统功能的影响的通用功能模型。我们使用官能团的概念将杂草和无脊椎动物物种合并为易于处理的类别以进行建模。这些功能组模型将从监管框架中获取数据，以预测与科学家、公众和政策制定者相关的若干复杂程度上的管理对功能多样性的影响，以便就新农业技术的风险做出客观决策。

There is widespread concern that the ongoing decline in UK biodiversity will be exacerbated by further agricultural intensification, such as the adoption of GM technologies. The Defra-funded Farm-scale Evaluations were instigated to address these concerns, and successfully demonstrated that the change in management associated with GMHT crop cultivation had an impact on arable diversity. However, given that arable biodiversity is already in a state of decline, we do not have objective criteria with which to compare the effects of new management practices. Also, as with all empirical studies, it is difficult to predict how the results may vary with different crops, or management systems, or at different spatial and temporal scales. Modelling is therefore required to address these problems, and provide a means of predicting the likely risk of new technology against objectively defined biodiversity criteria. In this proposal we aim to test the hypothesis that the model specification of Hawes et al. (2003) and Bohan et al. (submitted a, b) would lead to generalised functional models that could predict ecosystem dynamics and the impacts of diverse management practice on ecosystem functioning. We use the concept of functional groups to amalgamate weed and invertebrate species into tractable groupings for modelling. These functional group models will take data from the regulatory framework to predict the effects of management on functional diversity at a number of levels of complexity relevant to scientists, the public and policymakers to allow objective decision making on the risks of new farming technologies.