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Quantifying spatial and temporal relationships between diatoms and nutrients in streams strengthens evidence of nutrient effects from monitoring data.量化溪流中硅藻与养分之间的时空关系,能增强监测数据中养分效应的证据。
Freshw Sci. 2022 Mar;41(1):100-112. doi: 10.1086/718631.
2
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Inferences based on diatom compositions improve estimates of nutrient concentrations in streams.基于硅藻组成的推断可改进对溪流中营养物浓度的估计。
Sci Total Environ. 2024 Nov 20;952:176032. doi: 10.1016/j.scitotenv.2024.176032. Epub 2024 Sep 3.
2
Using DNA metabarcoding to characterize national scale diatom-environment relationships and to develop indicators in streams and rivers of the United States.利用 DNA 代谢组学来描述国家尺度的硅藻-环境关系,并在美国的溪流和河流中开发指示物种。
Sci Total Environ. 2024 Aug 20;939:173502. doi: 10.1016/j.scitotenv.2024.173502. Epub 2024 May 28.
3
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Heliyon. 2023 Dec 19;10(1):e23603. doi: 10.1016/j.heliyon.2023.e23603. eCollection 2024 Jan 15.
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Understanding the effects of phosphorus on diatom richness in rivers and streams using taxon-environment relationships.利用分类单元与环境的关系理解磷对河流和溪流中硅藻丰富度的影响。
Freshw Biol. 2023 Mar 1;68(3):473-486. doi: 10.1111/fwb.14040.
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Evaluation of Nitrogen and Carbon Stable Isotopes in Filter Feeding Bivalves and Surficial Sediment for Assessing Aquatic Condition in Lakes and Estuaries.利用滤食性双壳贝类和表层沉积物中的氮和碳稳定同位素评估湖泊和河口的水生环境
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6
Characterizing temporal variability in streams supports nutrient indicator development using diatom and bacterial DNA metabarcoding.描述溪流时间变异特征有助于利用硅藻和细菌 DNA 宏条形码开发营养物指标。
Sci Total Environ. 2022 Jul 20;831:154960. doi: 10.1016/j.scitotenv.2022.154960. Epub 2022 Apr 1.

本文引用的文献

1
Taxonomic harmonization may reveal a stronger association between diatom assemblages and total phosphorus in large datasets.分类协调可能会揭示大型数据集中硅藻组合与总磷之间更强的关联。
Ecol Indic. 2019 Jul 1;102:166-174. doi: 10.1016/j.ecolind.2019.01.061.
2
DNA metabarcoding effectively quantifies diatom responses to nutrients in streams.DNA metabarcoding 有效地量化了硅藻对溪流中营养物质的响应。
Ecol Appl. 2020 Dec;30(8):e02205. doi: 10.1002/eap.2205. Epub 2020 Aug 18.
3
Evaluation and sensitivity analysis of diatom DNA metabarcoding for WFD bioassessment of Mediterranean rivers.基于硅藻 DNA metabarcoding 对地中海河流 WFD 生物评估的评价与敏感性分析。
Sci Total Environ. 2020 Jul 20;727:138445. doi: 10.1016/j.scitotenv.2020.138445. Epub 2020 Apr 4.
4
Excess of nitrogen reduces temporal variability of stream diatom assemblages.氮过量会降低溪流硅藻组合的时间变异性。
Sci Total Environ. 2020 Apr 15;713:136630. doi: 10.1016/j.scitotenv.2020.136630. Epub 2020 Jan 10.
5
Determining suspended solids and total phosphorus from turbidity: comparison of high-frequency sampling with conventional monitoring methods.从浊度中测定悬浮物和总磷:高频采样与常规监测方法的比较。
Environ Monit Assess. 2019 Sep 4;191(10):605. doi: 10.1007/s10661-019-7775-7.
6
The impact of OTU sequence similarity threshold on diatom-based bioassessment: A case study of the rivers of Mayotte (France, Indian Ocean).OTU序列相似性阈值对基于硅藻的生物评估的影响:以马约特岛(法国,印度洋)河流为例的研究
Ecol Evol. 2018 Dec 18;9(1):166-179. doi: 10.1002/ece3.4701. eCollection 2019 Jan.
7
Ammonium recycling supports toxic Planktothrix blooms in Sandusky Bay, Lake Erie: Evidence from stable isotope and metatranscriptome data.铵的再循环支持伊利湖桑达斯基湾有毒束丝藻水华的形成:稳定同位素和宏转录组数据的证据。
Harmful Algae. 2019 Jan;81:42-52. doi: 10.1016/j.hal.2018.11.011. Epub 2018 Dec 1.
8
Ranking stressor impacts on periphyton structure and function with mesocosm experiments and environmental-change forecasts.利用中观实验和环境变化预测对底栖生物结构和功能的压力源影响进行排序。
PLoS One. 2018 Sep 24;13(9):e0204510. doi: 10.1371/journal.pone.0204510. eCollection 2018.
9
Identifying congruence in stream assemblage thresholds in response to nutrient and sediment gradients for limit setting.为了确定限制因素,识别在养分和沉积物梯度下河流综合阈值响应中的一致性。
Ecol Appl. 2017 Mar;27(2):469-484. doi: 10.1002/eap.1457. Epub 2017 Feb 17.
10
Entrapped Sediments as a Source of Phosphorus in Epilithic Cyanobacterial Proliferations in Low Nutrient Rivers.低营养河流中附着性蓝藻增殖过程中作为磷源的截留沉积物
PLoS One. 2015 Oct 19;10(10):e0141063. doi: 10.1371/journal.pone.0141063. eCollection 2015.

量化溪流中硅藻与养分之间的时空关系,能增强监测数据中养分效应的证据。

Quantifying spatial and temporal relationships between diatoms and nutrients in streams strengthens evidence of nutrient effects from monitoring data.

作者信息

Yuan Lester L, Smucker Nathan J, Nietch Christopher T, Pilgrim Erik M

机构信息

United States Environmental Protection Agency, Office of Water 4304T, 1200 Pennsylvania Avenue NW, Washington, DC 20460 USA.

United States Environmental Protection Agency, Office of Research and Development, Mail Stop 587, 26 West Martin Luther King Drive, Cincinnati, Ohio 45268 USA.

出版信息

Freshw Sci. 2022 Mar;41(1):100-112. doi: 10.1086/718631.

DOI:10.1086/718631
PMID:35646474
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9132200/
Abstract

Observational data are frequently used to better understand the effects of changes in P and N on stream biota, but nutrient gradients in streams are usually associated with gradients in other environmental factors, a phenomenon that complicates efforts to accurately estimate the effects of nutrients. Here, we propose a new approach for analyzing observational data in which we compare the effects of changes in nutrient concentrations in time within individual sites and in space among many sites. Covarying relationships between other, potentially confounding environmental factors and nutrient concentrations are unlikely to be the same in both time and space, and, therefore, estimated effects of nutrients that are similar in time and space are more likely to be accurate. We applied this approach to diatom metabarcoding data collected from streams in the East Fork of the Little Miami River watershed, Ohio, USA. Changes in diatom assemblage composition were consistently associated with changes in the concentration of total reactive P in both time and space. In contrast, despite being associated with spatial differences in ammonia and urea concentrations, diatom assemblage composition was not associated with temporal changes in these nitrogen species. We suggest that the results of this analysis provide evidence of a causal effect of increased P on diatom assemblage composition. We further analyzed the effects of temporal variability in measurements of total reactive P and found that averaging periods greater than ~1 wk prior to sampling best represented the effects of P on the diatom assemblage. Comparisons of biological responses in space and time can sharpen insights beyond those that are based on analyses conducted on only 1 of the 2 dimensions.

摘要

观测数据经常被用于更好地理解磷(P)和氮(N)的变化对河流生物群的影响,但是河流中的养分梯度通常与其他环境因素的梯度相关,这一现象使得准确估计养分的影响变得复杂。在这里,我们提出一种分析观测数据的新方法,即比较单个站点内养分浓度随时间的变化以及多个站点间养分浓度在空间上的变化所产生的影响。其他潜在的混杂环境因素与养分浓度之间的协变关系在时间和空间上不太可能相同,因此,在时间和空间上相似的养分估计影响更可能是准确的。我们将这种方法应用于从美国俄亥俄州小迈阿密河流域东叉的溪流中收集的硅藻代谢条形码数据。硅藻组合组成的变化在时间和空间上都与总活性磷浓度的变化一致相关。相比之下,尽管硅藻组合组成与氨和尿素浓度的空间差异有关,但与这些氮形态的时间变化无关。我们认为该分析结果提供了磷增加对硅藻组合组成有因果效应的证据。我们进一步分析了总活性磷测量中时间变异性的影响,发现采样前大于约1周的平均周期最能代表磷对硅藻组合的影响。在空间和时间上对生物响应进行比较,可以深化基于仅在二维中的一个维度上进行的分析所获得的见解。