Inferring Controls on Dissolved Oxygen Criterion Attainment in the Chesapeake Bay
Inferring Controls on Dissolved Oxygen Criterion Attainment in the Chesapeake Bay
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DOI：
10.1021/acsestwater.0c00307
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发表时间：
2021-08
期刊：
影响因子：
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通讯作者：
R. Langendorf;V. Lyubchich;J. Testa;Qian Zhang
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作者：
R. Langendorf;V. Lyubchich;J. Testa;Qian Zhang
环境监测方案生成用于评估生态系统健康的多变量时间序列。因果推理的最新发展提供了将这些观测数据转化为能够解释指标变量轨迹中的得失的网络的方法。在这里，我们提供了一个使用切萨皮克湾地表水溶解氧(DO)达标的方法的案例研究。我们试图了解DO对外部流域输入(淡水、营养物质、沉积物)和内部水性质(水温、叶绿素a、营养物质浓度)的长期波动。我们发现切萨皮克湾不同地区的控制措施截然不同。夏季淡水和泥沙输入减少了地表水在陆上地区的达标情况，但在开阔的主干水域却增加了达标情况。在地表水中，藻类生物量通常与AD呈正相关，而在深水中，藻类被普遍理解为氧气水平较低。利用对净影响的估计，我们还发现，冬春季节流入许多主干部分的沉积物对氧气水平产生了净负面影响。这些领域尚未恶化，这掩盖了这一风险。这项工作证明了长期监测方案对更好地了解和管理复杂生态系统的作用。
Environmental monitoring programs generate multivariate time series for the assessment of ecosystem health. Recent developments in causal inference offer ways to translate these observational data into networks able to explain gains and losses in the trajectories of indicator variables. Here, we present a case study of this approach using surface water dissolved oxygen (DO) criteria attainment across the Chesapeake Bay. We sought to understand the long-term fluctuations of DO in response to external watershed inputs (freshwater, nutrients, sediments) and internal water properties (water temperature, chlorophyll-a, nutrient concentrations). We found contrasting controls across different regions of the Chesapeake Bay. Summer freshwater and sediment inputs reduced surface water DO criteria attainment in landward regions but elevated attainment in open, mainstem waters. Algal biomass was often positively associated with AD in surface waters, in contrast to deep waters where algae are well-understood to lower oxygen levels. Using estimates of net effects, we also discovered that sediment flowing into many of the mainstem segments during the winter-spring season has had a net negative effect on oxygen levels. These segments have yet to deteriorate, which has masked this risk. This work demonstrates the utility of long-term monitoring programs to better understand and manage complex ecosystems.