Applied scaling theory

长期研究目标是开发可靠的、理论上合理的方法，从实地测量和实验（通常在小的空间和时间尺度上）到人类对环境的影响问题，这通常发生在更大的尺度上。 在整个应用生态学中，包括基于生境的保护生物学研究、估计生物多样性变化率、预测气候变化的影响、渔业管理以及基于科学的点源和区域环境影响评估，都需要在大空间尺度上进行可靠的计算。 该建议的主要目的是表明，应用生态学的科学基础可以通过开发和测试基于广义尺度关系的空间尺度函数来改进（Schneider 2001）。 将与两名博士生（渔业副渔获物、海洋污染物）合作开发比例函数。 对于渔业兼捕问题，研究假设是，在干预减少渔获量的渔业中，渔获量与努力量的比例指数将下降。由此产生的指数变化的知识将改善总兼捕量的估计。 对于污染物的问题，研究假设是，风险与污染物的身体负担呈指数关系，而污染物的身体负担又与身体大小呈异速生长关系。 由此产生的知识将提高监测活动的效率。 本建议的第三个目标是发现的机制负责的空间结构的鳗草栖息地，这是已知的管理密度和喂养成功的新招募的鳕鱼。 基于过程的尺度函数比经验函数更可靠，从而增强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方法，在这种方法中，基于过程的缩放函数被制定出来，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.