Detecting ecological thresholds and tipping points in the natural capital assets of a protected coastal ecosystem

Detecting ecological thresholds and tipping points in the natural capital assets of a protected coastal ecosystem
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检测受保护的沿海生态系统的自然资本资产的生态阈值和临界点

DOI:
10.1016/j.ecss.2018.10.006
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发表时间:
2018
期刊:
Estuarine, Coastal and Shelf Science
影响因子:
--
通讯作者:
Watson S
Watson S
中科院分区:
--
文献类型:
--
作者:
Watson S

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人们越来越关注突发性和潜在不可逆转的生态系统阈值和临界点,因为它们可能对自然资本和人类福祉产生重大影响。尽管这些现象在理论上得到了很好的确立,但很少有实证研究为沿海和河口生态系统中的这些现象提供证据,尽管它们在提供生态系统服务方面具有很高的价值。为了确定此类事件的可能性,我们测试了两种统计方法;港口生态系统的顺序t检验分析(STARS)和广义加性模型(GAMs)。这些方法应用于长达25年的时间序列数据,并分析了驱动因素与自然资本资产流动之间的关系。STARS分析的结果确定了普尔港三种自然资本资产的非线性阈值;泥滩面积,马尼拉蛤种群和涉禽/野禽数量,以及影响港口的几个驱动因素的增加。最显著的阈值记录在港口的马尼拉蛤渔业中,2006年至2008年期间,港口两个地点的种群数量下降了73-78%。我们认为,港口马尼拉蛤蜊种群的历史性下降部分可归因于非法捕捞压力,尽管疾病和租赁床持有人转向其他物种等其他因素也可能起作用。最近(2015年起),由于地方当局改善了管理措施,港口的野生蛤蜊种群有所增加。广义加性模型还确定了大型藻垫、沉积物浅滩和河流流量对泥滩地区、盐沼地区和涉禽/野禽数量的历史变化的贡献。我们的结论是,通过关注可能导致沿海生态系统突变的驱动因素之间的相互作用和正反馈,使用这些方法获得的阈值和临界点信息在管理背景下可能具有潜在的价值。
Concern about abrupt and potentially irreversible ecosystem thresholds and tipping points is increasing, as they may have significant implications for natural capital and human wellbeing. Although well established in theory, there are few empirical studies that provide evidence for these phenomena in coastal and estuarine ecosystems, despite their high value for provision of ecosystem services. To determine the likelihood of such events, we tested two statistical methods; sequential T-test analysis (STARS) and generalised additive models (GAMs) in a harbour ecosystem. These methods were applied to time series data spanning up to 25 years coupled with analysis of the relationships between drivers and natural capital asset flows. Results of the STARS analysis identified nonlinear thresholds in three of the natural capital assets of Poole harbour; mudflat area, Manila clam stocks and wader/wildfowl numbers, as well as an increase in several drivers affecting the harbour. The most prominent threshold was recorded in the Manila clam fisheries of the harbour, with stocks in two locations of the harbour declining by 73–78% between 2006 and 2008. We suggest that the historic decline in the Manila clam stocks of the harbour were partly attributable to illegal fishing pressure although other factors such as disease and lease bed holders switching to other species were also likely to have contributed. More recently (2015-onwards) wild clam stocks of the harbour have increased thanks to improved management measures by local authorities. Generalised additive models also identified the contribution of macroalgal mats, sediment shoaling and river flows to historic changes in mudflat area, saltmarsh area and wader/wildfowl numbers. We conclude that information on thresholds and tipping points obtained using these approaches can potentially be of value in a management context, by focusing attention on the interactions and positive feedbacks between drivers that may cause abrupt change in coastal ecosystems.
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