Applied scaling theory

长期的研究目标是开发可靠的、理论上合理的方法，从现场测量和实验(通常是在小的空间和时间尺度上)扩展到人类对环境的影响问题，这通常发生在更大的尺度上。整个应用生态学需要在大空间尺度上进行可靠的计算，包括基于生境的保护生物学研究，估计生物多样性的变化率，以及预测气候变化的影响，渔业管理，和基于科学的点源和区域环境影响评估。他说，这项建议的主要目标是表明，应用生态学的科学基础可以通过发展研究和测试基于广义尺度关系的空间尺度函数来改善(Schneider 2001)。尺度函数将与两名博士生合作开发(渔业兼捕、海洋污染物)。为了解决渔业兼捕问题，研究假设将是，在干预减少捕捞的渔业中，渔获量与努力的尺度指数将下降。由此得到的指数变化的知识将改善对总副渔获量的估计。对于污染物问题，研究假设将是风险与污染物身体负担呈指数级增长，而污染物身体负担又与身体大小呈异速增长。因此，由此产生的知识将提高监测活动的效率。此外，该建议的第三个目标是发现导致鳗草栖息地空间结构的机制，众所周知，它控制着新招募的鳕鱼的密度和饲养成功。基于过程的尺度函数比经验函数更可靠，从而改善了应用生态学的科学基础。这项研究将使学生接触到一种预测性方法，即基于过程的尺度函数被制定出来，然后根据数据进行测试。

The long-term research objective is to develop reliable,  theoretically sound means for scaling from field measurements and experiments (typically at a small spatial and temporal scales) to questions of human impact on the environment, which typically occurs at far larger scales.  Reliable calculations at large spatial scales are required throughout applied ecology, including habitat-based research in conservation biology, estimating rates of change in biodiversity,  anticipating the impacts of climate change, management of fisheries, and science-based assessment of point-source and regional environmental impacts.       The primary objective of this proposal is to show that the science base for applied ecology can be improved by developing  and testing spatial scaling functions based on a generalised scaling relation (Schneider 2001).  Scaling functions will be developed in collaboration with two doctoral students (fishery bycatch, marine contaminants).    For the problem of fishery bycatch, the research hypothesis will be that the exponent that scales catch to effort will decrease in fisheries where intervention reduces catch. The resulting knowledge of variation in exponent will improve estimates of total bycatch.  For the problem of contaminants, the research hypothesis will be that risk scales exponentially with contaminant body burden, which in turn scales allometrically with body size.  The resulting knowledge will improve the efficiency of monitoring activities.     A third objective of this proposal is to discover the mechanisms responsible for spatial structure of eelgrass habitat, which is known to govern the density and feeding success of newly recruited cod.     Process based scaling functions are more reliable than empirical function and thus improve the science base of applied ecology.  The research will expose students to a predictive approach, where process-based scaling functions are formulated and then tested against data.