Division for Marine and Environmental Research, Rudjer Bošković Institute, Zagreb, Croatia.
PLoS One. 2018 Jun 13;13(6):e0197932. doi: 10.1371/journal.pone.0197932. eCollection 2018.
Managing the disturbance of visitors due to crowding is an important management task in protected areas with high use levels. To achieve this, managers need to know how the use level affects the perceived disturbance due to crowding. Here we present a method to predict the level of disturbance as a function of use level measured by number of visitors. In contrast to the visual approach where subjects are asked to evaluate acceptability of use levels from manipulated images of scenery, our approach uses data gathered from actual experiences: actual (measured) use levels and concurrent on-site data on levels of disturbance experienced by visitors. Using the example of Nature Park Telašćica, we show how these data can be acquired with limited resources (a smart-phone and short, time-stamped questionnaires), and demonstrate the subsequent analysis and model fitting. The resulting model estimates the probability that a visitor experiencing a given use level will report certain level of disturbance. We suggest a way of using the probability density functions to define an inherent limit of acceptable disturbance (LAD) due to crowding; the LAD can also be set to a desired value by management. Regardless of the definition, LAD can be used to determine the maximum acceptable use level as dictated by crowding considerations. The method gives predictions consistent with previous literature and can be used even when data are collected at low use levels.
管理因拥挤而导致的访客干扰是高使用水平保护区的一项重要管理任务。为此,管理人员需要了解使用水平如何影响因拥挤而产生的感知干扰。在这里,我们提出了一种方法,可以根据访客数量衡量的使用水平来预测干扰水平。与视觉方法不同,后者要求参与者从风景的人为图像中评估使用水平的可接受性,我们的方法使用从实际经验中收集的数据:实际(测量)使用水平以及访客实际经历的干扰水平的现场同期数据。以特拉斯奇察自然公园为例,我们展示了如何在有限的资源(智能手机和简短的、带时间戳的问卷)下获取这些数据,并演示了随后的分析和模型拟合。由此产生的模型估计了在给定使用水平下,访客报告特定干扰水平的概率。我们建议使用概率密度函数来定义由于拥挤而产生的可接受干扰的固有极限(LAD)的方法;管理层也可以将 LAD 设置为所需的值。无论如何定义,LAD 都可以用于根据拥挤情况确定最大可接受的使用水平。该方法的预测结果与先前的文献一致,即使在低使用水平下收集数据也可以使用。