Measuring Habitat Restoration using the Darwin and "Event" Cores: Australian examples powered by BioCollect

Peter Brenton, Peggy Eby, Robert Stevenson, Elizabeth R. Ellwood
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Abstract

Habitat decline and fragmentation are major factors in biodiversity loss across the globe and can be difficult to measure, particularly at landscape scale (Brooks et al. 2002, Fahrig 2003, Ritchie and Roser 2019). In Australia, rural, coastal and urban communities have been undertaking habitat restoration activities since the mid-1980s to protect and restore ecological balance on private land and in local shared and natural spaces. Much of the restoration effort has centered around hands-on activities as a mechanism for building community with environmental benefits. Over such a time span, thousands of locations throughout the country have been transformed from degraded and highly disturbed landscapes into resemblances of more-or-less natural areas. However, collecting and analysing data for these activities was given little attention until quite recently, as governments, philanthropists and other investors have become increasingly interested in measuring the value and outcomes from investment. To measure the effectiveness of the restoration effort, it is essential to to benchmark the environmental state and species composition before the restoration begins, but surprisingly or unsurprisingly, this is rarely done (Hale et al. 2019). Responding to this call for better documentation of restoration outcomes, over 30 groups have been using the Atlas of Living Australia’s BioCollect platform to capture complex information about current and past restoration work. The BioCollect platform enables each type of monitoring, establishment, and follow-up activity to have its own data collection schema and associated metadata structured around using a hierarchy of sampling events based on the Event class in the Darwin Core standard, which allows relationships between types of event records to be specified. When event records are created through use of an activity-based template, each occurrence of a species is also parsed and configured as a Darwin Core occurrence record. Standard templates have been created for a range of activities, such as benchmarking assessments, site establishment, follow-up interventions and monitoring over time, which are being used by many different groups over large areas of the landscape. This allows each group to operate independently, yet collect standardised data that can be easily aggregated at larger temporal and spatial scales, quantifying change over time. The relationships between occurrences and the event context in which they were collected is also preserved and navigable. Here we present how Darwin Core and Event Core have been implemented in the BioCollect platform to enable this important data to be collected and stored in its full richness and resolution.
使用达尔文和“事件”核心测量栖息地恢复:由BioCollect提供动力的澳大利亚例子
栖息地减少和破碎化是全球生物多样性丧失的主要因素,很难测量,特别是在景观尺度上(Brooks et al. 2002, Fahrig 2003, Ritchie and Roser 2019)。在澳大利亚,自20世纪80年代中期以来,农村、沿海和城市社区一直在开展栖息地恢复活动,以保护和恢复私人土地和当地共享和自然空间的生态平衡。大部分的修复工作都集中在实践活动上,作为一种建立具有环境效益的社区的机制。在这段时间里,全国成千上万的地方已经从退化和高度受干扰的景观变成了或多或少与自然地区相似的地方。然而,收集和分析这些活动的数据直到最近才受到重视,因为政府、慈善家和其他投资者对衡量投资的价值和结果越来越感兴趣。为了衡量恢复工作的有效性,必须在恢复开始之前对环境状态和物种组成进行基准测试,但令人惊讶或不出所料的是,很少这样做(Hale et al. 2019)。为了更好地记录修复结果,30多个小组一直在使用澳大利亚生活地图集的BioCollect平台来捕捉有关当前和过去修复工作的复杂信息。BioCollect平台允许每种类型的监测、建立和后续活动都有自己的数据收集模式和相关的元数据,这些模式和元数据使用基于Darwin Core标准中的Event类的采样事件层次结构,这允许指定事件记录类型之间的关系。当通过使用基于活动的模板创建事件记录时,物种的每次出现也被解析并配置为Darwin Core发生记录。已经为一系列活动创建了标准模板,例如基准评估、场地建立、后续干预和长期监测,这些模板正在被许多不同群体在大片景观中使用。这使得每个小组可以独立运作,但可以收集标准化的数据,这些数据可以很容易地在更大的时间和空间尺度上进行汇总,量化随时间的变化。事件与收集事件的事件上下文之间的关系也得到了保存和可导航。在这里,我们介绍了如何在BioCollect平台上实现达尔文核心和事件核心,以使这些重要的数据能够以其完整的丰富性和分辨率被收集和存储。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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