A method for early warning of algal bloom based on cell activity potential

Abstract

The present application relates to a kind of algal bloom early warning method based on cell activity potential, comprising: data collection;Basic judgment;Calculate algal cell activity;Draw algal cell activity curve;Early warning to algal bloom.The present application selects the most basic element of algal cell synthesis, phycocyanin as an index, and no longer monitors algal bloom influencing factors, because all influencing factors ultimately reflect in phycocyanin concentration.By monitoring the synthesis rate of algal cell protein in different time periods, the life activity of algal cell is analyzed, and an algal bloom early warning method based on the characteristics of algal cell life cycle is constructed.

Description

Technical Field

[0001] This invention relates to an early warning method for algal blooms based on cell activity potential, a method for monitoring and analyzing aquatic ecological environment, and a method for monitoring and analyzing the impact of algae on the environment. Background Technology

[0002] With the increasing interaction between human activities and nature, the aquatic ecological environment is constantly changing, and algal blooms have become a significant problem affecting the aquatic ecosystem. Current early warning methods for algal blooms primarily rely on constructing relationships between nutrients or environmental factors and algal biomass to estimate algal density and predict blooms. However, because algal cells are living organisms with cellular life cycles, and their proliferation rate is not limited by a single influencing factor, this method of predicting blooms based on nutrient or environmental factors and algal biomass is not only inaccurate but also suffers from a significant lag in the response of algal biomass to influencing factors due to the algal cell growth process. Consequently, when using existing methods to predict algal blooms, the algae in the water are often already about to bloom or have already bloomed, leaving very little time for implementing measures to suppress the bloom, thus failing to provide effective early warning. Therefore, how to prepare accurate forecasts and provide early warnings for algal blooms is a problem that needs to be solved. Summary of the Invention

[0003] To overcome the problems of existing technologies, this invention proposes an early warning method for algal blooms based on cell activity potential. The method selects phycocyanin, the most basic element synthesized by algal cells, as an indicator. By monitoring the synthesis rate of algal cell proteins at different time periods, analyzing algal cell activity, and calculating the average value of phycocyanin over two consecutive time periods, an early warning method for algal blooms based on the characteristics of the algal cell life cycle is constructed.

[0004] The objective of this invention is achieved as follows: a method for early warning of algal blooms based on cellular viability potential, characterized by the following steps:

[0005] Step 1, Data Collection: Collect phycocyanin density data of the studied area online in steps of half a day to several days, arrange them in chronological order, and form a phycocyanin density data sequence group;

[0006] Step 2, Basic Judgment: Based on the current season and the general trend of previous algal blooms, determine the likelihood of an algal bloom;

[0007] Step 3, calculate algal cell activity: Select two monitoring time periods, i.e., N values. Based on the N values, select phycocyanin density data and input them into the calculation formula to calculate two sets of algal cell activity data sequences. The calculation formula is as follows:

[0008]

[0009] Where: t is the data sequence. ; or This is the predicted value of phycocyanin at the (t+1)th digit. This represents the actual value of phycocyanin t during online monitoring. The monitoring period for phycocyanin is twice;

[0010] Step 4: Plot the algal cell activity curve: Establish a rectangular coordinate system with the predicted phycocyanin value as the ordinate and time as the abscissa, and input the two sets of predicted phycocyanin values. Two algal cell activity curves, one for short-term and one for long-term, were plotted. A phycocyanin outbreak warning value was preset and marked on the algal cell activity curve graph.

[0011] Step 5, Early warning of algal bloom: During the detection, recording, and plotting of algal cell activity curves, if a short-period curve crosses above a long-period curve, triggering an algal bloom risk warning signal, it means that algal cell biomass will increase rapidly in the near future, and measures should be taken as soon as possible to prevent an algal bloom. As time goes on, continue to detect, record, and plot algal cell activity curves. When the short-period curve crosses below the long-period curve again, the risk of an algal bloom is relieved, meaning that the algal bloom has ended or will not occur in the near future.

[0012] Step 6, Algal Bloom Alarm: During the detection, recording, and plotting of algal cell activity curves, if a short period of upward movement crosses the artificially set phycocyanin threshold, an algal bloom alarm is triggered. As time progresses, the detection, recording, and plotting of algal cell activity curves continue. When a short period of downward movement crosses the artificially set phycocyanin threshold, the algal bloom alarm is lifted.

[0013] Furthermore, the phycocyanin threshold is... .

[0014] The advantages and beneficial effects of this invention are as follows: This invention selects phycocyanin, the most basic element synthesized by algal cells, as the indicator, and no longer monitors algal bloom influencing factors, because all influencing factors are ultimately reflected in phycocyanin concentration. By monitoring the synthesis rate of algal cell proteins at different time periods, the life activity of algal cells is analyzed, and an algal bloom early warning method based on the characteristics of the algal cell life cycle is constructed. Furthermore, by monitoring the synthesis rate of algal cell proteins at different time periods and manually setting thresholds, the difference between "early warning" and "alarm" of algal bloom outbreaks is distinguished, avoiding the defect of traditional prediction methods that treat algal bloom outbreak thresholds as forecast signals. Attached Figure Description

[0015] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0016] Figure 1This is a flowchart of the method described in Embodiment 1 of the present invention;

[0017] Figure 2 This is a graph showing the algal cell activity curve of the method described in Embodiment 1 of the present invention;

[0018] Figure 3 This is a schematic diagram of the warning points in the algal cell activity curve of the method described in Embodiment 1 of the present invention;

[0019] Figure 4 This is a schematic diagram of the warning point being lifted in the algal cell activity curve of the method described in Embodiment 1 of the present invention. Detailed Implementation

[0020] Example 1:

[0021] This embodiment is a method for early warning of algal blooms based on cell viability potential. The steps of the method are as follows, and the process is as follows: Figure 1 As shown:

[0022] Step 1, Data Collection: Collect phycocyanin density data of the studied area in steps ranging from half a day (12 hours) to several days, and arrange them in chronological order to form a phycocyanin density data sequence group;

[0023] Phycocyanin density data were collected by detecting and recording data once every half day or once a day, and data sequence groups were formed in units of 30 days per month.

[0024] Phycocyanin density is defined as the number of cells per gram in one milliliter of water, expressed as 1g cells / ml.

[0025] The distribution of cyanobacteria in the study area is uneven, so the entire study area can be divided into multiple smaller areas, and then further subdivided into multiple measuring points within each smaller area, and the average value can be calculated.

[0026] To reduce the consumption of excessive storage resources, the raw data that has already been calculated and recorded can be discarded, thereby speeding up on-site calculations.

[0027] Step 2, Basic Judgment: Based on the current season and the general trend of previous algal blooms, determine the likelihood of an algal bloom;

[0028] Phycocyanin synthesis rates in any time series data contain three components: seasonality or periodicity, trend, and random fluctuation. This step is mainly used to determine seasonality or periodicity: summer is the most likely time for outbreaks, while some lower latitude regions may also experience outbreaks in spring or autumn. Therefore, relatively close observation is needed during these seasons to nip problems in the bud. The trend and random fluctuation of cyanobacterial outbreaks are mainly determined by the steps outlined in this embodiment.

[0029] Step 3, calculate algal cell activity: Select two monitoring time periods, i.e., N values. Based on the N values, select phycocyanin density data and input them into the calculation formula to calculate two sets of algal cell activity data sequences. The calculation formula is as follows:

[0030]

[0031] Where: t is the data sequence. ; or This is the predicted value of phycocyanin at the (t+1)th digit. This represents the true value of phycocyanin at the t-th chromatin level. The time interval (window size) for two monitoring sessions of phycocyanin. Phycocyanin predicted value. or It can also be extended to other indicators that characterize algal blooms.

[0032] N determines the model's sensitivity and smoothness. A smaller N value makes the model more responsive to changes in data and captures trend changes more quickly; a larger N value provides excellent smoothing and displays long-term trends more clearly, but it also exhibits greater lag and is very slow to react to data changes. When a trend reverses, a large N value takes a long time to catch up.

[0033] Specific calculation example: Select 30 phycocyanin data points from a certain month, i.e., measure once a day, for 30 days a month, and measure at least 4 consecutively. Select a short period of 1 month, i.e., N=1; select a long period of 4 months, i.e., N=4.

[0034] Predicted values ​​of phycocyanin calculated over a one-month period:

[0035]

[0036]

[0037]

[0038] Predicted values ​​of phycocyanin over a 4-month period (4 months are calculated as 120 days for simplicity):

[0039]

[0040]

[0041]

[0042] This yielded two sets of predicted phycocyanin values. .

[0043] Step 4: Plot the algal cell activity curve: Establish a rectangular coordinate system with the predicted phycocyanin value as the ordinate and time as the abscissa, and input the two sets of predicted phycocyanin values. Two algal cell activity curves, one for short-term and one for long-term cycles, were plotted. A pre-set warning value for phycocyanin outbreaks was established and marked on the algal cell activity curve graph, as shown below. Figure 2 As shown in the graph, the phycocyanin outbreak warning value is represented by a horizontal straight line.

[0044] Based on the above calculation example, the vertical axis of the curve represents the predicted value of phycocyanin. The x-axis is set at one-month intervals to form a rectangular coordinate system. The two curves were generated during the process of simultaneous detection, recording, and plotting. The cyanobacteria bloom warning value was set at... Location, Figure 2 The middle part is represented by a thick dashed line.

[0045] Step 5, Early warning of algal bloom: During the detection, recording, and plotting of algal cell activity curves, if a short-period curve crosses above a long-period curve, triggering an algal bloom risk warning signal, it means that algal cell biomass will increase rapidly in the near future, and measures should be taken as soon as possible to prevent an algal bloom. As time goes on, continue to detect, record, and plot algal cell activity curves. When the short-period curve crosses below the long-period curve again, the risk of an algal bloom is relieved, meaning that the algal bloom has ended or will not occur in the near future.

[0046] The method described in this embodiment is based on a fundamental assumption—that the future is a continuation of the most recent past. In other words, the phycocyanin concentration value in the next period is most likely to be close to the average level of recent periods, rather than the value of earlier periods.

[0047] The method described in this embodiment represents algal cell activity by calculating the average value of phycocyanin over two different time periods. It fully utilizes the sensitivity of short-term moving averages and the lag of long-term moving averages to predict the evolution trend of phycocyanin density and other related indicators over different time series.

[0048] Typically, short-term phycocyanin predictions show more dramatic changes and steeper curves, while long-term phycocyanin predictions show relatively smaller changes and gentler curves. In practice, the two curves usually intersect at least two points, such as... Figure 2 As shown, typically, the first crossover point occurs when the long-term curve is still progressing smoothly, while the short-term curve rises sharply and crosses the long-term curve, as... Figure 3 As shown, this can be used to determine that this is a warning point for algal blooms. Conversely, when the long-term curve remains at a certain value, the short-term curve drops sharply, crosses the long-term curve again, and then declines, as shown in the image. Figure 4As shown, it can be concluded that the algal bloom has passed, or at least this bloom has ended, and the warning for the algal bloom can be lifted.

[0049] Step 6, Algal Bloom Alarm: During the detection, recording, and plotting of algal cell activity curves, if a short period of upward movement crosses the artificially set phycocyanin threshold, an algal bloom alarm is triggered. As time progresses, the detection, recording, and plotting of algal cell activity curves continue. When a short period of downward movement crosses the artificially set phycocyanin threshold, the algal bloom alarm is lifted.

[0050] The predicted value of phycocyanin in the short period crosses the phycocyanin threshold line (horizontal line) upwards, and the point of crossing is the critical point of phycocyanin bloom. When the activity curve of phycocyanin drops after the phycocyanin bloom, that is, when it crosses the phycocyanin threshold line downwards again, it indicates that the phycocyanin bloom has passed or will remain at a low level in the near future.

[0051] Example 2:

[0052] This embodiment is an improvement upon Embodiment 1, refining the threshold value. The threshold value described in this embodiment is 5-10 μg / L.

[0053] Currently, there is no universally accepted standard for determining algal blooms. Different studies use different criteria for judging algal blooms, and the damage caused by algal blooms varies in different regions. Generally, the concentration of phycocyanin > When the threshold for algal bloom is reached, the concentration of phycocyanin in this embodiment is considered to be [value missing]. Set as the threshold for algal blooms, but this value can be adjusted according to the actual situation and severity of the damage in different water bodies. between.

[0054] Finally, it should be noted that the above is only used to illustrate the technical solution of the present invention and not to limit it. Although the present invention has been described in detail with reference to the preferred arrangement, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solution of the present invention (such as the detection method of phycocyanin, the application of various formulas, the order of steps, etc.) without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A method for early warning of a bloom based on the potential of cell activity, characterized in that, The steps of the method are as follows: Step 1, Data Collection: Collect phycocyanin density data of the studied area in steps of half a day to several days, arrange them in chronological order, and form a phycocyanin density data sequence group; Step 2, Basic Judgment: Based on the current season and the general trend of previous algal blooms, determine the likelihood of an algal bloom; Step 3, calculate algal cell activity: Select two monitoring time periods, i.e., N values. Based on the N values, select phycocyanin density data and input them into the calculation formula to calculate two sets of algal cell activity data sequences. The calculation formula is as follows: Where: t is the data sequence. ; or This is the predicted value of phycocyanin at the (t+1)th digit. This represents the true value of phycocyanin at the t-th chromatin level. The monitoring period for phycocyanin is twice; Step 4: Plot the algal cell activity curve: Establish a rectangular coordinate system with the predicted phycocyanin value as the ordinate and time as the abscissa, and input the two sets of predicted phycocyanin values. Two algal cell activity curves, one for short cycles and one for long cycles, were plotted. Step 5, Early warning of algal bloom: During the detection, recording, and plotting of algal cell activity curves, if a short-period curve crosses above a long-period curve, triggering an algal bloom risk warning signal, it means that algal cell biomass will increase rapidly in the near future, and measures should be taken as soon as possible to prevent an algal bloom. As time goes on, continue to detect, record, and plot algal cell activity curves. When the short-period curve crosses below the long-period curve again, the risk of an algal bloom is relieved, meaning that the algal bloom has ended or will not occur in the near future. Step 6, Algal Bloom Alarm: During the detection, recording, and plotting of algal cell activity curves, if a short period of upward movement crosses the artificially set phycocyanin threshold, an algal bloom alarm is triggered. As time progresses, the detection, recording, and plotting of algal cell activity curves continue. When a short period of downward movement crosses the artificially set phycocyanin threshold, the algal bloom alarm is lifted.

2. The method of claim 1, wherein, The phycocyanin threshold value is .

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