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If we are writing about life in the deep ocean in today’s issue of Water Matters, we couldn’t miss mentioning another report on the negative impact of ocean heating and human extractive activities on biodiversity. We also write about a paper addressing the issue of using satellite imagery to assess the impact of the occurrence of “red bloom” snow on North American glaciers on accelerating their melting. There will also be quite a bit about statistical tools for assessing water status and developing an early warning system for undesirable changes in water quality, as well as the effects of eutrophication and humification on the depth of lake stratification and phytoplankton communities.
1. experimental mining plumes and ocean warming trigger stress in a deep pelagic jellyfish
Stenvers V.I., Hauss H., Bayer T. et al. (2023). Experimental mining plumes and ocean warming trigger stress in a deep pelagic jellyfish. Nat Commun 14, 7352.
The main threat to the pelagic fauna of the oceans is the global increase in water temperature, caused by greenhouse gas emissions. Batiatic and abisopelagial organisms evolved under relatively stable thermal conditions, making their physiological tolerance to thermal changes very low. An international team of scientists studied the effects of simulated ocean warming and mining-induced sediment disturbance on the helmet jellyfish Periphylla periphylla (Péron & Lesueur, 1810). It is a cosmopolitan, widely distributed species that lives at a depth of 4,000 meters, making it a good model organism for testing the effects of warming and mining on deep-sea ocean fauna. Studies have included physiological effects, gene expression and changes in the associated microbiota. Warming the waters by 4°C increased metabolic rates P. periphylla, increased expression of genes related to innate immunity, and reduced respiration. In contrast, the introduction of an inorganic slurry (simulated sediment resuspension) triggered a very energetically costly reaction by increasing mucus secretion. It also stimulated genes related to oxygen respiration and the wound healing process. In contrast, none of the stressors tested had an effect on the symbiotic microbial complex. The paper presents the first results on the physiological, molecular and microbiological response of deep-sea jellyfish to environmental stressors, a key step toward assessing the impact of pressures on the health of deep-sea pelagic ocean zones. If these responses are representative of other deep-sea fauna, the effects of seafloor resource exploitation could have adverse effects on pelagic deep-sea biodiversity and the functioning of the entire ecosystem.
2. satellite mapping of red snow on North American glaciers
Engstrom C. B., Quarmby L. M. (2023). Satellite mapping of red snow on North American glaciers. Sci. Adv. 9, eadi3268.
The phenomenon of “red snow,” a bloom caused by freshwater microorganisms, known as “red snow. snow algae, causes – in addition to the deposition of soot and mineral dust – the darkening of the surface of summer snow fields, accelerating their melting. We wrote about the phenomenon of these algae blooms in one of the first issues of Water Matters. It turns out that modern techniques for measuring the environment make it possible to quantify its scale. Two Canadian researchers at Simon Fraser University in Burnaby have mapped and analyzed the distribution of snow algae blooms from 2019 to 2022 on glaciers in northwestern North America. They used more than 6,000 for this. satellite images acquired from Sentinel-2 and the Random Forest classifier algorithm. Their analysis confirmed the occurrence of blooms at 5 percent. of the total glaciation area, which had a significantly negative impact on the snow cover of the study area. In the case of individual glaciers, up to 65 percent. area in a given year was covered by a bloom, which scientists estimate caused a snowmelt of 3.1 ± 1.2 cm snowmelt warter equivalent, which equates to a layer of snow about 5.5 cm thick. Glaciers with less than 10 km2 had the highest proportion of algae-covered area. In large ice fields and glaciers, the percentage of coverage was smaller, but the absolute areas of bloom – very large. For example, on the Black Rapids glacier in eastern Alaska in 2020. The bloom covered an area of 235 square kilometers (20% of the total area). Snow melt, as expected by the researchers, was directly proportional to the area of the bloom and dependent on its duration and intensity. These results show the importance of the albedo of “red snow” for the disappearance of glaciers in areas of North America, but also demonstrate the possibility of using remote information to quantify this phenomenon.
3. lake browning counteracts cyanobacteria responses to nutrients: Evidence from phytoplankton dynamics in large enclosure experiments and comprehensive observational data
Lyche Solheim A., Gundersen H., Mischke U. et al. (2023). Lake browning counteracts cyanobacteria responses to nutrients: Evidence from phytoplankton dynamics in large enclosure experiments and comprehensive observational data. Global Change Biology, 00, e17013.
Aquatic ecosystems around the world are under pressure from a number of stressors. While we are all aware of the effects of excessive nutrient supply (eutrophication), the phenomenon of water browning (humification) as a result of humic runoff and its consequences for the thermal stratification of lake waters is not sufficiently recognized, especially in the context of climate change. The problem of the interaction of eutrophication, humification and disruption of thermal stratification of waters on phytoplankton assemblages in the lakes of northern and central Europe was looked at by a team of scientists from several European centers. They analyzed survey results from three sources of information: (a) experiments set up on the clear-water Lake Stechlin in northeastern Germany, where gradients in water trophy (nutrient supply) and color (by adding the highly colored substance HumiFeed) were tested in conjunction with deep mixing for effects on the biomass and composition of the phytoplankton community; (b) A 25-year time series from Lake Vansjø-Vanemfjorden (southeastern Norway) accounting for nutrient and browning dynamics; (c) a large dataset from nearly 600 lakes across Northern Europe, including nutrient and water color data.
The results of the experiments showed that water browning reduced the stimulating effect of nutrients on phytoplankton (antagonistic effect) and caused a change in its taxonomic composition from the dominance of phototrophic cyanobacteria and green algae to myxotrophic cryptophytes. The change was most likely due to a reduction in light due to a change in the color of the water. Analysis of the time series data confirmed the experimental results, indicating that browning reduced the biomass of both cyanobacteria and the entire phytoplankton community. Both experimental and archival results showed lower threshold values of total phosphorus for the development of cyanobacterial blooms in clear lakes (10-20 μg P L-1) than in humic lakes (20-30 μg P L-1). The discovery is applicable to the management of lakes with an increased supply of nutrients and humic substances, mainly as a result of increasingly frequent extreme weather events.
4. Setting nutrient boundaries to protect aquatic communities: the importance of comparing observed and predicted classifications using measures derived from a confusion matrix
Phillips G., Teixeira H., Kelly M. et al. (2024). Setting nutrient boundaries to protect aquatic communities: The importance of comparing observed and predicted classifications using measures derived from a confusion matrix. Science Of The Total Environment, 168872.
A prerequisite for the protection and maintenance of aquatic biodiversity and resilience to pressure is the establishment of such limits for nutrients (and other water quality parameters) that will protect and support the ecological integrity of ecosystems. However, it turns out that this task is not straightforward, and many EU countries that are implementing the Water Framework Directive regulations need clear methodological guidance to approach this issue. Developing such guidelines is the task of working groups at the EC, and the publication that has just appeared in STOTEN presents the results of a team of scientists from just such a group, of which I have had the pleasure of being a member for several years. The team used artificially generated as well as real data on nutrient concentrations (exemplified by total phosphorus) and values of ecological quality indicators (exemplified by phytoplankton) from European lakes to test a wide range of statistical measures of classification accuracy and precision based on the so-called “confusion matrix. “confusion matrix“). This matrix analyzes the proportion of conformity of classification on the basis of the environmental variable (phosphorus) and the dependent variable (phytoplankton) in a 2×2 arrangement (here, the state of at least good and worse than good). One of the key challenges in this approach is the objective selection of the probability on the basis of which the limit value for an environmental parameter is set. This value is also significantly influenced by the shape of the response of the dependent variable to the stressor.
The analyses carried out made it possible to identify the statistics most suitable for determining threshold values in various scenarios. Applying the recommended approach on real data for an example type of lakes (very shallow lowland lakes on calcareous substrate) allowed us to indicate the most likely range of total phosphorus concentrations supporting good phytoplankton condition and being between 60 and 83 µg l-1, or with a more restrictive approach – a value of 48 µg l-1. Nevertheless, the authors emphasize that any criteria for assessing water status, regardless of the statistical approach adopted, will always require critical evaluation before deciding to implement them. The proposed approach deserves the attention of the authorities responsible for water management in our country.
This work is another in a series of publications by this research team on methodological approaches to setting environmental standards for water. It is very methodical in nature and is based essentially solely on statistical quibbles, but it illustrates well the complexity and nuance of the problem of establishing reliable criteria for assessing the status of surface waters in the context of ensuring their good ecological status. To anyone who thinks it was a simple task, I heartily recommend reading.
5. Rapid assessment of surface water quality using statistical multivariate analysis approach: Oder River system case study
Balcerowska-Czerniak G., Gorczyca B. (2024). Rapid assessment of surface water quality using statistical multivariate analysis approach: Oder River system case study. Science Of The Total Environment, 912, 168754.
And while we’re on the subject of tools for monitoring and assessing waters influenced by human impacts, it’s worth presenting an indigenous paper by two female scientists that addresses the development of a water quality exceedance alert system in the context of last year’s Oder River disaster. In it, the authors use the results of monitoring the water quality of the Oder River during and after the Oder disaster to develop a universal methodology for interpreting multiple measurement parameters simultaneously and for early detection of outlier samples. The approach uses a multivariate statistical quality control chart based on a principal component analysis (PCA) model with two well-known measures of deviation: the T2 Hoteling statistic and the Q statistic. The proposed TQ_PCA allows for online assessment of water sample quality, without the need for specific knowledge and assumptions about control limits for monitored parameters. The indicator showed very good performance in analyzing a set of physicochemical water quality data from Polish stations and the German station in Frankfurt/Oder. As the authors declare, the proposed approach can be easily extended to any study involving a large set of monitoring data from any industrial chemical process. Whether the proposed method will find wider application, the future will tell, but it certainly represents an important voice in the discussion of the need to implement early warning systems in water quality management. The paper was published in the journal STOTEN, which lately seems to have been a grateful platform for Oder topics.
