{"title":"基于逻辑生长模型的典型高原湖泊蓝藻水华生物量模拟与控制兴云湖案例研究","authors":"Chenhui Wu, Cuiling Jiang, Maosen Ju, Zhengguo Pan, Zeshun Li, Lei Sun, Hui Geng","doi":"10.1016/j.ecoinf.2024.102779","DOIUrl":null,"url":null,"abstract":"The simulation and early warning of cyanobacterial blooms in lakes are of great significance. Controlling the growth of cyanobacteria in plateau lakes is challenging due to the unique geographical environment, climatic conditions, and impact of anthropogenic activities. Therefore, conducting simulations and early warning is crucial to effectively control cyanobacterial blooms in plateau lakes. This study aimed to investigate Xingyun Lake, a representative plateau lake in China, using the logistic growth model to analyze cyanobacterial growth patterns and assess the effects of control projects, along with the influence of meteorological and environmental factors. Moreover, the study proposed a method for establishing control curves and ranges for managing cyanobacterial blooms. The results demonstrated that the chlorophyll-a concentration in the effluent decreased by an average of 97.74% compared with that in the influent after implementing the integrated “deep-well pressure algal control” and “ecological purification for algae-water separation” processes in Xingyun Lake. The total annual decrease in chlorophyll-a was approximately 3.40 times the lake's total chlorophyll-a content. The growth of cyanobacteria in Xingyun Lake followed a logistic pattern during the blooming period, before and after implementing control projects (from 2018 to 2022), with the overall growth trend from 2010 to 2022 aligning with the logistic growth model. The study identified lower temperatures and precipitation, reduced nitrogen and phosphorus loads, and a higher nitrogen-to‑phosphorus ratio as the main environmental factors inhibiting cyanobacterial growth. Establishing logistic control curves for cyanobacterial blooms and sustaining the algal control project before the transition point effectively reduced the maximum chlorophyll-a concentration and attenuated cyanobacterial growth rate throughout the year. This study offered novel perspectives for preventing and controlling cyanobacterial blooms, offering practical guidance for lake management, especially in plateau regions.","PeriodicalId":51024,"journal":{"name":"Ecological Informatics","volume":"10 1","pages":""},"PeriodicalIF":5.8000,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Simulation and control of the cyanobacterial bloom biomass in a typical plateau lake based on the logistic growth model: A case study of Xingyun Lake\",\"authors\":\"Chenhui Wu, Cuiling Jiang, Maosen Ju, Zhengguo Pan, Zeshun Li, Lei Sun, Hui Geng\",\"doi\":\"10.1016/j.ecoinf.2024.102779\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The simulation and early warning of cyanobacterial blooms in lakes are of great significance. Controlling the growth of cyanobacteria in plateau lakes is challenging due to the unique geographical environment, climatic conditions, and impact of anthropogenic activities. Therefore, conducting simulations and early warning is crucial to effectively control cyanobacterial blooms in plateau lakes. This study aimed to investigate Xingyun Lake, a representative plateau lake in China, using the logistic growth model to analyze cyanobacterial growth patterns and assess the effects of control projects, along with the influence of meteorological and environmental factors. Moreover, the study proposed a method for establishing control curves and ranges for managing cyanobacterial blooms. The results demonstrated that the chlorophyll-a concentration in the effluent decreased by an average of 97.74% compared with that in the influent after implementing the integrated “deep-well pressure algal control” and “ecological purification for algae-water separation” processes in Xingyun Lake. The total annual decrease in chlorophyll-a was approximately 3.40 times the lake's total chlorophyll-a content. The growth of cyanobacteria in Xingyun Lake followed a logistic pattern during the blooming period, before and after implementing control projects (from 2018 to 2022), with the overall growth trend from 2010 to 2022 aligning with the logistic growth model. The study identified lower temperatures and precipitation, reduced nitrogen and phosphorus loads, and a higher nitrogen-to‑phosphorus ratio as the main environmental factors inhibiting cyanobacterial growth. Establishing logistic control curves for cyanobacterial blooms and sustaining the algal control project before the transition point effectively reduced the maximum chlorophyll-a concentration and attenuated cyanobacterial growth rate throughout the year. This study offered novel perspectives for preventing and controlling cyanobacterial blooms, offering practical guidance for lake management, especially in plateau regions.\",\"PeriodicalId\":51024,\"journal\":{\"name\":\"Ecological Informatics\",\"volume\":\"10 1\",\"pages\":\"\"},\"PeriodicalIF\":5.8000,\"publicationDate\":\"2024-08-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ecological Informatics\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://doi.org/10.1016/j.ecoinf.2024.102779\",\"RegionNum\":2,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecological Informatics","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1016/j.ecoinf.2024.102779","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECOLOGY","Score":null,"Total":0}
Simulation and control of the cyanobacterial bloom biomass in a typical plateau lake based on the logistic growth model: A case study of Xingyun Lake
The simulation and early warning of cyanobacterial blooms in lakes are of great significance. Controlling the growth of cyanobacteria in plateau lakes is challenging due to the unique geographical environment, climatic conditions, and impact of anthropogenic activities. Therefore, conducting simulations and early warning is crucial to effectively control cyanobacterial blooms in plateau lakes. This study aimed to investigate Xingyun Lake, a representative plateau lake in China, using the logistic growth model to analyze cyanobacterial growth patterns and assess the effects of control projects, along with the influence of meteorological and environmental factors. Moreover, the study proposed a method for establishing control curves and ranges for managing cyanobacterial blooms. The results demonstrated that the chlorophyll-a concentration in the effluent decreased by an average of 97.74% compared with that in the influent after implementing the integrated “deep-well pressure algal control” and “ecological purification for algae-water separation” processes in Xingyun Lake. The total annual decrease in chlorophyll-a was approximately 3.40 times the lake's total chlorophyll-a content. The growth of cyanobacteria in Xingyun Lake followed a logistic pattern during the blooming period, before and after implementing control projects (from 2018 to 2022), with the overall growth trend from 2010 to 2022 aligning with the logistic growth model. The study identified lower temperatures and precipitation, reduced nitrogen and phosphorus loads, and a higher nitrogen-to‑phosphorus ratio as the main environmental factors inhibiting cyanobacterial growth. Establishing logistic control curves for cyanobacterial blooms and sustaining the algal control project before the transition point effectively reduced the maximum chlorophyll-a concentration and attenuated cyanobacterial growth rate throughout the year. This study offered novel perspectives for preventing and controlling cyanobacterial blooms, offering practical guidance for lake management, especially in plateau regions.
期刊介绍:
The journal Ecological Informatics is devoted to the publication of high quality, peer-reviewed articles on all aspects of computational ecology, data science and biogeography. The scope of the journal takes into account the data-intensive nature of ecology, the growing capacity of information technology to access, harness and leverage complex data as well as the critical need for informing sustainable management in view of global environmental and climate change.
The nature of the journal is interdisciplinary at the crossover between ecology and informatics. It focuses on novel concepts and techniques for image- and genome-based monitoring and interpretation, sensor- and multimedia-based data acquisition, internet-based data archiving and sharing, data assimilation, modelling and prediction of ecological data.