A United Kingdom Lake Ecological Observatory Network

英国湖泊生态观测站网络

• 批准号: NE/I007318/1
• 负责人: Keith Beven
• 金额: $ 19.19万
• 依托单位: Lancaster University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2011
• 资助国家: 英国
• 起止时间: 2011 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FI007318%2F1
• 关键词: United; Kingdom; Lake; Ecological; Observatory

Lake systems play a fundamental role in storing and providing freshwater and food, in supporting recreation and in protecting species diversity. However, the stability of these ecosystem services can be undermined by the increased demands society makes upon these systems and changes in atmospheric composition and lake water balance that arise through a societal-mediated changing climate. To safeguard against such loss of functioning there is in place legally-binding national and European directives that set stringent targets for water quality and biodiversity. Meeting these targets requires a detailed understanding of lake processes that in turn requires measurements at an appropriate temporal scale. Traditional monitoring, of at best weekly-fortnightly intervals, is sufficient to record seasonal change but cannot resolve the processes driving many aspects of lake function. To resolve these processes we need to 'hear every note in the full symphony of lake functioning', with such resolution only viable through semi-continuous measurement of parameters that are key reflectors of lake functioning. We are fortunate that deployed in eleven lakes across the UK, of different size, altitude, latitude and nutrient status, are basic systems automated to make such measurements, Automatic Water Quality Monitoring Stations (AWQMS). However at present, most buoys are restricted to a meteorological station and temperature measurements. A few have other probes to measure water quality, but these are subject to biofouling which could compromise the data. At present, the data are mainly downloaded by telemetry to the host-site via a range of procedures. Thus we are not utilising advances in data-logger-, computer- and sensor-technology to measure automatically at high frequency and 'hear the full symphony'. We propose to change this by installing stable, state-of-the-art sensor technology, with mechanical devices to minimise biofouling. Further, we will maximise the value of generating this high frequency data by linking together the lakes in a sensor network to deliver quality-controlled data onto the internet for analysis by project partners, the wider scientific community and the general public. Such infrastructure investment needs to reflect the need for high quality measurement from science-driven agendas. We will demonstrate such a network supports these agendas through the following projects: DST1: Real-time forecasting of lake behaviour: We will incorporate the real-time data available from the sensor network into a forecast system for lake phytoplankton behaviour and, in particular, to provide warning for the onset of phytoplankton blooms. DST2: The effect of meteorology on the fate of carbon within lakes: We will track pool and flux variability of dissolved carbon dioxide over daily to seasonal time scales. By relating these measurements to meteorological and within-lake physico-chemical measurements within and between sites we are better equipped to define critical controls on the lake carbon cycle. DST3: The level of regional coherence in sub-seasonal timescales: Lakes can show a regionally coherent response e.g. strong links exist between air and surface water temperature; large-scale weather patterns such as the position of north wall of the Gulf Stream have also been shown to influence directly the regional coherence of lakes. Use of high resolution data to examine coherence in lake temperatures has just begun but as yet no-one has investigated coherence of biological, chemical or wider physical variables on these short time-scales, an approach which is viable through this network. In summary, this sensor network of AWQMSs, offering detail of observation through high resolution data generation and the new instrumentation will demonstrate not only the value of observing the environment remotely and in detail, but the benefit from integration systems to offer real advances in environmental science.

湖泊系统在储存和提供淡水和食物、支持娱乐和保护物种多样性方面发挥着根本性作用。然而，这些生态系统服务的稳定性可能会受到社会对这些系统的需求增加以及社会介导的气候变化引起的大气成分和湖泊水平衡变化的破坏。为了防止这种功能的丧失，制定了具有法律约束力的国家和欧洲指令，为水质和生物多样性设定了严格的目标。实现这些目标需要对湖泊过程有详细的了解，而这又需要在适当的时间尺度上进行测量。传统的监测，最多每两周一次的间隔，足以记录季节变化，但不能解决驱动湖泊功能的许多方面的过程。为了解决这些过程，我们需要“听到湖泊功能完整交响乐中的每一个音符”，只有通过半连续测量湖泊功能的关键反射器参数，才能实现这种分辨率。幸运的是，在英国各地不同大小、海拔、纬度和营养状况的11个湖泊中部署了自动进行此类测量的基本系统，即自动水质监测站（AWQMS）。然而，目前大多数浮标仅限于气象站和温度测量。少数有其他探头来测量水质，但这些探头会受到生物污染的影响，这可能会损害数据。目前，数据主要是通过遥测技术通过一系列程序下载到主站点。因此，我们没有利用先进的数据记录器，计算机和传感器技术来自动测量高频和“听到完整的交响乐”。我们建议通过安装稳定的、最先进的传感器技术来改变这种情况，并使用机械装置来最大限度地减少生物污染。此外，我们将通过将传感器网络中的湖泊连接在一起，将质量受控的数据传输到互联网上，供项目合作伙伴、更广泛的科学界和公众分析，从而最大限度地发挥产生这种高频数据的价值。这种基础设施投资需要反映科学驱动的议程对高质量衡量的需要。我们将通过以下项目证明这样的网络支持这些议程：DST 1：湖泊行为的实时预测：我们将把传感器网络提供的实时数据纳入湖泊浮游植物行为的预测系统，特别是为浮游植物水华的爆发提供预警。DST 2：气象学对湖泊内碳命运的影响：我们将跟踪溶解二氧化碳在每日至季节时间尺度上的池和通量变化。通过将这些测量与站点内和站点之间的气象和湖内物理化学测量相关联，我们能够更好地定义对湖泊碳循环的关键控制。DST 3：次季节时间尺度的区域一致性水平：湖泊可以显示出区域一致性反应，例如空气和地表水温度之间存在密切联系;大规模的天气模式，如墨西哥湾流北壁的位置也被证明直接影响湖泊的区域一致性。使用高分辨率数据来检查湖泊温度的一致性才刚刚开始，但到目前为止，还没有人研究过这些短时间尺度上的生物，化学或更广泛的物理变量的一致性，这是一种通过这个网络可行的方法。总之，AWQMS传感器网络通过高分辨率数据生成和新仪器提供详细的观察，不仅将展示远程和详细观察环境的价值，而且还将展示集成系统的好处，以提供环境科学的真实的进步。

项目成果

Constraining uncertainty and process-representation in an algal community lake model using high frequency in-lake observations

使用高频湖内观测限制藻类群落湖泊模型中的不确定性和过程表示

• DOI: 10.1016/j.ecolmodel.2017.04.011
• 发表时间: 2017
• 期刊: Ecological Modelling
• 影响因子: 3.1
• 作者: Page T

Adaptive forecasting of phytoplankton communities.

• DOI: 10.1016/j.watres.2018.01.046
• 发表时间: 2018-05
• 期刊: Water research
• 影响因子: 12.8
• 作者: T. Page;Paul Smith;Paul Smith;K. Beven;I. D. Jones;J. Elliott;S. Maberly;E. Mackay;M. D. Ville;H. Feuchtmayr