scholarly journals Population dynamics of harmful algal blooms in Lake Champlain: A tale of two phases

2013 ◽  
Author(s):  
Edmund Hart ◽  
Nicholas Gotelli ◽  
Rebecca Gorney ◽  
Mary Watzin
Keyword(s):  
Population Growth ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Time Series Data ◽  
Growth Parameters ◽  
Series Data ◽  
Nutrient Concentrations ◽  
Nutrient Inputs ◽  
Lake Champlain ◽  
Two Phases

Understanding the dynamics of harmful algal blooms (HABs) in lakes can inform management strategies to reduce their economic and health impacts. Previous studies have analyzed spatially replicated samples from a single time or have fit phenomenological models to time series data. We fit mechanistic population models to test the effects of critical nutrient concentrations and the density of potential algal competitors on population growth parameters in HABs in Lake Champlain, U.S.A. We fit models to five years (2003-2006, 2008) of weekly cyanobacteria counts. Plankton dynamics exhibited two phases of population growth: an initial “bloom phase” of rapid population growth and a subsequent “post-bloom phase” of stochastic decline. Population growth rates in the bloom phase were strongly density dependent and increased with increasing TN:TP ratios. The post-bloom phase was largely stochastic and was not obviously related to nutrient concentrations. Because TN:TP was important only in the initial phase of population growth, correlative analyses of the relationship between cyanobacteria blooms and nutrient concentrations may be especially sensitive to when snapshot data are collected. Limiting nutrient inputs early in the season could be an effective management strategy for suppressing or reducing the bloom phase of cyanobacteria population growth.

scholarly journals Population dynamics of harmful algal blooms in Lake Champlain: A tale of two phases

2013 ◽  
Author(s):  
Edmund Hart ◽  
Nicholas Gotelli ◽  
Rebecca Gorney ◽  
Mary Watzin
Keyword(s):  
Population Growth ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Time Series Data ◽  
Growth Parameters ◽  
Series Data ◽  
Nutrient Concentrations ◽  
Nutrient Inputs ◽  
Lake Champlain ◽  
Two Phases

Understanding the dynamics of harmful algal blooms (HABs) in lakes can inform management strategies to reduce their economic and health impacts. Previous studies have analyzed spatially replicated samples from a single time or have fit phenomenological models to time series data. We fit mechanistic population models to test the effects of critical nutrient concentrations and the density of potential algal competitors on population growth parameters in HABs in Lake Champlain, U.S.A. We fit models to five years (2003-2006, 2008) of weekly cyanobacteria counts. Plankton dynamics exhibited two phases of population growth: an initial “bloom phase” of rapid population growth and a subsequent “post-bloom phase” of stochastic decline. Population growth rates in the bloom phase were strongly density dependent and increased with increasing TN:TP ratios. The post-bloom phase was largely stochastic and was not obviously related to nutrient concentrations. Because TN:TP was important only in the initial phase of population growth, correlative analyses of the relationship between cyanobacteria blooms and nutrient concentrations may be especially sensitive to when snapshot data are collected. Limiting nutrient inputs early in the season could be an effective management strategy for suppressing or reducing the bloom phase of cyanobacteria population growth.

scholarly journals Population dynamics of harmful algal blooms in Lake Champlain: A tale of two phases

2013 ◽  
Author(s):  
Edmund Hart ◽  
Nicholas Gotelli ◽  
Rebecca Gorney ◽  
Mary Watzin
Keyword(s):  
Population Growth ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Time Series Data ◽  
Growth Parameters ◽  
Series Data ◽  
Nutrient Concentrations ◽  
Nutrient Inputs ◽  
Lake Champlain ◽  
Two Phases

Understanding the dynamics of harmful algal blooms (HABs) in lakes can inform management strategies to reduce their economic and health impacts. Previous studies have analyzed spatially replicated samples from a single time or have fit phenomenological models to time series data. We fit mechanistic population models to test the effects of critical nutrient concentrations and the density of potential algal competitors on population growth parameters in HABs in Lake Champlain, U.S.A. We fit models to five years (2003-2006, 2008) of weekly cyanobacteria counts. Plankton dynamics exhibited two phases of population growth: an initial “bloom phase” of rapid population growth and a subsequent “post-bloom phase” of stochastic decline. Population growth rates in the bloom phase were strongly density dependent and increased with increasing TN:TP ratios. The post-bloom phase was largely stochastic and was not obviously related to nutrient concentrations. Because TN:TP was important only in the initial phase of population growth, correlative analyses of the relationship between cyanobacteria blooms and nutrient concentrations may be especially sensitive to when snapshot data are collected. Limiting nutrient inputs early in the season could be an effective management strategy for suppressing or reducing the bloom phase of cyanobacteria population growth.

scholarly journals LSTM Networks to Improve the Prediction of Harmful Algal Blooms in the West Coast of Sabah

2021 ◽  
Vol 18 (14) ◽  
pp. 7650
Author(s):  
Fatin Nadiah Yussof ◽  
Normah Maan ◽  
Mohd Nadzri Md Reba
Keyword(s):  
West Coast ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Time Series Data ◽  
Short Term Memory ◽  
Harmful Algal Bloom ◽  
Series Data ◽  
Severe Illness ◽  
The West ◽  
Chl A

Harmful algal bloom (HAB) events have alarmed authorities of human health that have caused severe illness and fatalities, death of marine organisms, and massive fish killings. This work aimed to perform the long short-term memory (LSTM) method and convolution neural network (CNN) method to predict the HAB events in the West Coast of Sabah. The results showed that this method could be used to predict satellite time series data in which previous studies only used vector data. This paper also could identify and predict whether there is HAB occurrence in the region. A chlorophyll a concentration (Chl-a; mg/L) variable was used as an HAB indicator, where the data were obtained from MODIS and GEBCO bathymetry. The eight-day dataset interval was from January 2003 to December 2018. The results obtained showed that the LSTM model outperformed the CNN model in terms of accuracy using RMSE and the correlation coefficient r as the statistical criteria.

scholarly journals Dynamic Mapping of Rice Growth Parameters Using HJ-1 CCD Time Series Data

2016 ◽  
Vol 8 (11) ◽  
pp. 931 ◽  
Author(s):  
Jing Wang ◽  
Jingfeng Huang ◽  
Ping Gao ◽  
Chuanwen Wei ◽  
Lamin Mansaray
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Growth Parameters ◽  
Series Data ◽  
Rice Growth ◽  
Dynamic Mapping

scholarly journals An Econometric Validation of Malthusian Theory: Evidence in Nigeria

2018 ◽  
Vol 7 (1) ◽  
pp. 77-90
Author(s):  
Musa Abdullahi Sakanko ◽  
Joseph David
Keyword(s):  
Population Growth ◽  
Food Production ◽  
Time Series Data ◽  
Control Measure ◽  
Series Data ◽  
Long Run ◽  
Short Run ◽  
The Government ◽  
Bound Test ◽  
Malthusian Theory

Rising population is an asset, provided, the skills of the workforce are used to the maximum extent. If not appropriately channelized, it can be a liability for a nation. A skilled and hardworking population can emerge as a foundation for a country’s development. This study examines the validity of Malthusian Theory in Nigeria using time series data from 1960 to 2016, employs the ARDL bound test techniques. The result shows that in the long-run, population growth and food production move proportionately, while population growth poses a depleting effect on food production in the short-run, thus validating the incidence of Malthusian impact in Nigerian economy in the short-run. The researcher recommended the government should strategize plans, which will further intensify family planning and birth control measure, compulsory western education and revitalization of the agricultural sector.DOI: 10.150408/sjie.v7i1.6461

scholarly journals Tracing the sources of nutrients fueling dinoflagellate red tides occurring along the coast of Korea using radium isotopes

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Hyeong Kyu Kwon ◽  
Guebuem Kim ◽  
Yongjin Han ◽  
Junhyeong Seo ◽  
Weol Ae Lim ◽  
...  
Keyword(s):  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Red Tide ◽  
Subsurface Layer ◽  
Vertical Mixing ◽  
Eastern Coast ◽  
Nutrient Concentrations ◽  
Red Tides ◽  
Radium Isotopes ◽  
Nutrient Sources

Abstract It is a well held concept that the magnitude of red-tide occurrence is dependent on the amount of nutrient supply if the conditions are same for temperature, salinity, light, interspecific competition, etc. However, nutrient sources fueling dinoflagellate red-tides are difficult to identify since red tides usually occur under very low inorganic-nutrient conditions. In this study, we used short-lived Ra isotopes (223Ra and 224Ra) to trace the nutrient sources fueling initiation and spread of Cochlodinium polykrikoides blooms along the coast of Korea during the summers of 2014, 2016, and 2017. Horizontal and vertical distributions of nutrient concentrations correlated well with 224Ra activities in nutrient-source waters. The offshore red-tide areas showed high 224Ra activities and low-inorganic and high-organic nutrient concentrations, which are favorable for blooming C. polykrikoides in competition with diatoms. Based on Ra isotopes, the nutrients fueling red-tide initiation (southern coast of Korea) are found to be transported horizontally from inner-shore waters. However, the nutrients in the spread region (eastern coast of Korea), approximately 200 km from the initiation region, are supplied continuously from the subsurface layer by vertical mixing or upwelling. Our study highlights that short-lived Ra isotopes are excellent tracers of nutrients fueling harmful algal blooms in coastal waters.

A new hydrology: effects on ecosystem form and functioning

2012 ◽  
Vol 69 (8) ◽  
pp. 1377-1379 ◽  
Author(s):  
Daniel L. Roelke ◽  
Sofie Spatharis ◽  
Simon M. Mitrovic
Keyword(s):  
Climate Change ◽  
Population Growth ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Human Population ◽  
Vertical Mixing ◽  
System Level ◽  
Hydrologic Processes ◽  
Human Population Growth ◽  
Altered Hydrology

Water cycles are changing because of human population growth and climate change. Such changes will affect fundamental system-level characteristics that in turn will greatly influence ecosystem form and functioning. Here, a collection of papers is offered that furthers our understanding of cause and effect relationships between altered hydrology and various ecosystem properties. Combined, these papers address issues related to inflows, connectivity, and circulation and vertical mixing. In regards to altered inflows, this collection of papers addresses how seagrass bed communities, incidence of some haptophyte harmful algal blooms, and biodiversity of intermittently flowing streams might respond. These papers also address factors that influence connectivity in wetlands, and in the case of a lake and its neighboring wetland, how connectivity between systems can profoundly affect ecosystem form and functioning. Finally, the effects of altered circulation and vertical mixing are addressed as they relate to the spread of some cyanobacteria blooms to higher latitudes. The reader of this collection of papers gains a better appreciation of how ecosystem form and functioning is influenced by hydrologic processes and can conclude that there is a need for continued research in this area to better understand the impacts of human population growth and climate change.

scholarly journals Status of Sewage Water Generation in Karnataka, India

2019 ◽  
pp. 1-5
Author(s):  
V. S. Radhika ◽  
G. N. Kulkarni
Keyword(s):  
Population Growth ◽  
Time Series Data ◽  
Critical Factor ◽  
High Water ◽  
Sewage Water ◽  
Series Data ◽  
Twin Cities ◽  
Economic Activities ◽  
Living Organisms ◽  
Future Population

Water is vital to the existence of all living organisms, but this valuable resource is increasingly being threatened with increasing population growth and demand for high water quality for both domestic purposes and economic activities. A critical factor in the estimation of waste water generation is the population growth. The population of the Hubli-Dharwad twin cities is the second-largest in Karnataka, after Bangalore. The present study was based on secondary (time series) data. The population and sewage water flow in twin cities was found to have increased almost nearly about twelve times with the growth rate of 1.07 percent per annum. The projected future population and sewage water generation from twin cities for three decadal points of time showed an increasing trend. This poses a challenging task in future with respect to management. The farmers consider the resource as a boon which provides water for irrigation throughout the year and serves as a source of income and employment.

scholarly journals Pengaruh Pertumbuhan Ekonomi, Tingkat Inflasi, dan Pertumbuhan Penduduk terhadap Tingkat Pengangguran Terbuka di Indonesia

2019 ◽  
Vol 18 (1) ◽  
pp. 52
Author(s):  
Irma Yuni Astuti ◽  
Nanik Istiyani ◽  
Lilis Yuliati
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Regression Analysis ◽  
Linear Regression ◽  
Population Growth ◽  
Multiple Linear Regression ◽  
Time Series Data ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Series Data

This study aims to determine the effect of economic growth, inflation and population growth in open unemployment rate in Indonesia. The type of data used in this study is secondary data in the form of time series data and variable data used are annual data in the period 1986-2017 with the object of research in the country o Indonesia. The data sources used in this study were obtained from the Central Statistics Agency (BPS) Indonesia and World Bank. The analytical method used in this study is multiple linear regression analysis with the Ordinary Least Square (OLS) technique. The estimation of time series data with multiple linear regression analysis shows that the economics growth variable has a positive and not significant effect on the level of open unemployment, the inflation variable has a positive and not significant effect on the level of open unemployment, and the population growth variable has a negative and significant effect on the level of open unemployment in Indonesia. Keywords: Open Unemployment, Economic Growth, Inflation, Population Growth

Sign in / Sign up

Export Citation Format

Share Document