2019 Vol. 41, No. 4
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2019, 41(4): .
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2019, 41(4): .
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2019, 41(4): 1-14.
doi: 10.3969/j.issn.0253-4193.2019.04.001
Abstract:
Global warming "hiatus" has attracted much attention since it was put forward, which is a hot issue in the field of global climate change. It is mainly manifested by the lower warming rate of the global mean air surface temperature than before during 1998-2012. Besides, the atmospheric circulation and ocean circulation have also changed significantly. In the attribution analysis of global warming "hiatus", many scientists believe that the Pacific Decadal Oscillation plays an important role. Other possible factors may include changes of the Atlantic meridional overturning circulation and Antarctic Bottom Water. However, there are biases in temporal consistence and spatial coverage of observation data, which increase the uncertainty of global warming "hiatus". Nevertheless, it is the consensus of many scientists that the internal variability of the climate system changed and then led to the increased absorption of heat in the deep ocean. If the uncertainty of the global warming hiatus is hoped to be resolved, the enrichment and improvement of observation data is a tough requirement.
Global warming "hiatus" has attracted much attention since it was put forward, which is a hot issue in the field of global climate change. It is mainly manifested by the lower warming rate of the global mean air surface temperature than before during 1998-2012. Besides, the atmospheric circulation and ocean circulation have also changed significantly. In the attribution analysis of global warming "hiatus", many scientists believe that the Pacific Decadal Oscillation plays an important role. Other possible factors may include changes of the Atlantic meridional overturning circulation and Antarctic Bottom Water. However, there are biases in temporal consistence and spatial coverage of observation data, which increase the uncertainty of global warming "hiatus". Nevertheless, it is the consensus of many scientists that the internal variability of the climate system changed and then led to the increased absorption of heat in the deep ocean. If the uncertainty of the global warming hiatus is hoped to be resolved, the enrichment and improvement of observation data is a tough requirement.
2019, 41(4): 15-26.
doi: 10.3969/j.issn.0253-4193.2019.04.002
Abstract:
The biogeochemical processes of carbon in estuaries are an important part of global carbon cycle. Dissolved inorganic carbon (DIC), stable carbon isotopic abundance of (δ13CDIC), dissolved organic carbon (DOC), chromophoric dissolved organic matter (CDOM), particle organic carbon (POC), stable carbon isotopic abundance of POC (δ13CPOC), atomic element ratios (N/C) and other related parameters were analyzed in order to study the distribution, sources and mixing behavior of different carbon species along a salinity gradient in the Changjiang Estuary in July 2014. The concentrations of DIC, DOC and POC range from 1 583.2 to 1 739.6 μmol/L, 128.4 to 369.4 μmol/L, 51.2 to 530.8 μmol/L, respectively. Similar with CDOM, these carbon species increase first and then decrease from the inner estuary to outer estuary, showing non-conservative mixing behaviors with salinity. The addition behavior of these carbon species mostly occurs in the turbidity maximum zone. In contrast, the values of δ13CDIC and δ13CPOC first decrease and then increase from the inner estuary to outer estuary, with the minimum values are found in the river mouth (-9.7‰ and -26.7‰, respectively). The increasing of carbon concentrations and decreasing of δ13CDIC, δ13CPOC values near the river mouth could be attributed to sediment re-suspension and/or microbial processes. The results of a three end-member mixing model based on Monte-Carlo Simulation indicate that the sources of POC vary greatly from the inner estuary to outer estuary. Terrestrial organic carbon is the main source of POC in the inner estuary, with the average value of 62.3%, whereas contribution of marine organic carbon gradually increase in the outer estuary. The results of CDOM related parameters show that the CDOM is mainly derived from terrestrial input, however, marine sources and human activities may also have impacts in the Changjiang Estuary.
The biogeochemical processes of carbon in estuaries are an important part of global carbon cycle. Dissolved inorganic carbon (DIC), stable carbon isotopic abundance of (δ13CDIC), dissolved organic carbon (DOC), chromophoric dissolved organic matter (CDOM), particle organic carbon (POC), stable carbon isotopic abundance of POC (δ13CPOC), atomic element ratios (N/C) and other related parameters were analyzed in order to study the distribution, sources and mixing behavior of different carbon species along a salinity gradient in the Changjiang Estuary in July 2014. The concentrations of DIC, DOC and POC range from 1 583.2 to 1 739.6 μmol/L, 128.4 to 369.4 μmol/L, 51.2 to 530.8 μmol/L, respectively. Similar with CDOM, these carbon species increase first and then decrease from the inner estuary to outer estuary, showing non-conservative mixing behaviors with salinity. The addition behavior of these carbon species mostly occurs in the turbidity maximum zone. In contrast, the values of δ13CDIC and δ13CPOC first decrease and then increase from the inner estuary to outer estuary, with the minimum values are found in the river mouth (-9.7‰ and -26.7‰, respectively). The increasing of carbon concentrations and decreasing of δ13CDIC, δ13CPOC values near the river mouth could be attributed to sediment re-suspension and/or microbial processes. The results of a three end-member mixing model based on Monte-Carlo Simulation indicate that the sources of POC vary greatly from the inner estuary to outer estuary. Terrestrial organic carbon is the main source of POC in the inner estuary, with the average value of 62.3%, whereas contribution of marine organic carbon gradually increase in the outer estuary. The results of CDOM related parameters show that the CDOM is mainly derived from terrestrial input, however, marine sources and human activities may also have impacts in the Changjiang Estuary.
2019, 41(4): 27-41.
doi: 10.3969/j.issn.0253-4193.2019.04.003
Abstract:
Radium isotopes are one of the useful tracers to study the submarine groundwater discharge (SGD) processes. It is indispensable to estimate the desorption flux of the river sediment when estimate SGD flux. Thus, it is necessary to study the desorption behavior of the radium isotopes in river sediment/suspended particles, especially for the smaller size range of sediment. In the present work, the effects of grain sizes of sediments and salinities of sea water from the Qinzhou Bay on the desorption of radium isotopes were investigated by laboratory experiments. The results show that, within the grain size range of 0.9-136.0 μm, the desorption amounts of radium isotopes from the sediment to seawater (salinity 33.9) decrease with the grain size increase, and the desorption amounts keep almost constant when the grain size is larger than 43.7 μm. Within the salinity range of 4.9-33.9, the desorption amounts of radium isotopes from sediments gradually increase with the salinity increasing until the salinity reaches 24.9. By establishing creatively the radium desorption model using the sediment surface fractal structure theory, the maximum exchangeable activities of 224Ra, 226Ra and 228Ra from the river sediment of Qinzhou Bay are estimated to be 1.13 dpm/g, 0.17 dpm/g and 0.85 dpm/g, respectively; and the concerned maximum desorption ratios are 30%, 7% and 18%. Compared to those from other estuarine/coastal regions, the maximum exchangeable activities of 224Ra and 226Ra from the river sediments in Qinzhou Bay are in the middle or low ranges, while the maximum desorption ratios are in the higher or lower levels, respectively. The results of this study is expected to be useful to better understand the desorption behavior of radium isotopes and estimate accurately SGD flux.
Radium isotopes are one of the useful tracers to study the submarine groundwater discharge (SGD) processes. It is indispensable to estimate the desorption flux of the river sediment when estimate SGD flux. Thus, it is necessary to study the desorption behavior of the radium isotopes in river sediment/suspended particles, especially for the smaller size range of sediment. In the present work, the effects of grain sizes of sediments and salinities of sea water from the Qinzhou Bay on the desorption of radium isotopes were investigated by laboratory experiments. The results show that, within the grain size range of 0.9-136.0 μm, the desorption amounts of radium isotopes from the sediment to seawater (salinity 33.9) decrease with the grain size increase, and the desorption amounts keep almost constant when the grain size is larger than 43.7 μm. Within the salinity range of 4.9-33.9, the desorption amounts of radium isotopes from sediments gradually increase with the salinity increasing until the salinity reaches 24.9. By establishing creatively the radium desorption model using the sediment surface fractal structure theory, the maximum exchangeable activities of 224Ra, 226Ra and 228Ra from the river sediment of Qinzhou Bay are estimated to be 1.13 dpm/g, 0.17 dpm/g and 0.85 dpm/g, respectively; and the concerned maximum desorption ratios are 30%, 7% and 18%. Compared to those from other estuarine/coastal regions, the maximum exchangeable activities of 224Ra and 226Ra from the river sediments in Qinzhou Bay are in the middle or low ranges, while the maximum desorption ratios are in the higher or lower levels, respectively. The results of this study is expected to be useful to better understand the desorption behavior of radium isotopes and estimate accurately SGD flux.
2019, 41(4): 42-52.
doi: 10.3969/j.issn.0253-4193.2019.04.004
Abstract:
Submarine sand waves have great activity and may cause potential threatens to underwater facilities, thus the assessment of submarine sand waves always attracts wide attentions. At present, most researchers still use plane and profile contrast to analyze the characteristics of sand wave migration which however cannot produce 2D migration vectors of sand waves efficiently. Basing on high-resolution multi-beam bathymetric data in 2007 and 2009, this study describes the method of using spatial cross correlation to analyze the migration of submarine sand waves in southeastern Beibu Gulf in detail. By contrasting the measured data, the migration characteristics of sand waves in the study area are obtained. And the effects of various crucial parameters on the results in the spatial cross correlation algorithm are also discussed. Results show that spatial cross correlation method is feasible and reliable to produce the 2D migration vector of sand waves. The results are accordant to the previous results of the migration of sand waves in the study area. Nevertheless, when using the spatial cross correlation method, the appropriate parameters and vector acquisition method according to different geometry of sand waves and various data quality are required. This study has practiced a new method to determine the migrations of submarine sand waves, which will improve the efficiency and accuracy of obtaining the migration of marine landforms, as well as the refined dynamics of marine topography.
Submarine sand waves have great activity and may cause potential threatens to underwater facilities, thus the assessment of submarine sand waves always attracts wide attentions. At present, most researchers still use plane and profile contrast to analyze the characteristics of sand wave migration which however cannot produce 2D migration vectors of sand waves efficiently. Basing on high-resolution multi-beam bathymetric data in 2007 and 2009, this study describes the method of using spatial cross correlation to analyze the migration of submarine sand waves in southeastern Beibu Gulf in detail. By contrasting the measured data, the migration characteristics of sand waves in the study area are obtained. And the effects of various crucial parameters on the results in the spatial cross correlation algorithm are also discussed. Results show that spatial cross correlation method is feasible and reliable to produce the 2D migration vector of sand waves. The results are accordant to the previous results of the migration of sand waves in the study area. Nevertheless, when using the spatial cross correlation method, the appropriate parameters and vector acquisition method according to different geometry of sand waves and various data quality are required. This study has practiced a new method to determine the migrations of submarine sand waves, which will improve the efficiency and accuracy of obtaining the migration of marine landforms, as well as the refined dynamics of marine topography.
2019, 41(4): 53-63.
doi: 10.3969/j.issn.0253-4193.2019.04.005
Abstract:
Marine mud sediment contains huge quantities of information concerning with catchment change, climate change and environment evolution. Therefore, analyzing the fine grain sized fraction of sediment is a crucial method to extract environment evolution information. The surficial sediments collected from north-central of the North Yellow Sea (NYS) were sieved and the fine fraction (<63 μm) were tested for rare earth elements (REE). The test results indicate that, as bounded by Changshan Islands, the discrepancies of REE concentration and distribution patterns between the east and west sediments of the mud deposition of the eastern Liaodong Peninsula (MDELP) was observed. The sediments in east of Changshan Islands, dominated by Yalu River, are defective in Eu and rich in REE, especially in light rare earth elements (LREE). However, the REE contents are low in the west side of Changshan Island and their distribution patterns are flat. Meanwhile, attributing to the wildly use of contrast agent (Gd-DTPA) in the Magnetic Resonance Imaging (MRI), the Gd in the sediment of the study area is obviously enriched. Furthermore, new recognition concerning with the sediment transport and origin is acquired: previous study believed the sediment source of MDELP is mainly derived from the Yalu River. However, our research reveals that, due to the transport of shelf circulation, there exists sediment exchange between the MDELP and the mud deposition of the west NYS: the sediment source in east of MDELP is controlled by the Yalu River, and that in the west of MDELP is mainly dominated by the Yellow River; in addition, Yalu River-derived sediment is supplied to the mud deposition of the west NYS.
Marine mud sediment contains huge quantities of information concerning with catchment change, climate change and environment evolution. Therefore, analyzing the fine grain sized fraction of sediment is a crucial method to extract environment evolution information. The surficial sediments collected from north-central of the North Yellow Sea (NYS) were sieved and the fine fraction (<63 μm) were tested for rare earth elements (REE). The test results indicate that, as bounded by Changshan Islands, the discrepancies of REE concentration and distribution patterns between the east and west sediments of the mud deposition of the eastern Liaodong Peninsula (MDELP) was observed. The sediments in east of Changshan Islands, dominated by Yalu River, are defective in Eu and rich in REE, especially in light rare earth elements (LREE). However, the REE contents are low in the west side of Changshan Island and their distribution patterns are flat. Meanwhile, attributing to the wildly use of contrast agent (Gd-DTPA) in the Magnetic Resonance Imaging (MRI), the Gd in the sediment of the study area is obviously enriched. Furthermore, new recognition concerning with the sediment transport and origin is acquired: previous study believed the sediment source of MDELP is mainly derived from the Yalu River. However, our research reveals that, due to the transport of shelf circulation, there exists sediment exchange between the MDELP and the mud deposition of the west NYS: the sediment source in east of MDELP is controlled by the Yalu River, and that in the west of MDELP is mainly dominated by the Yellow River; in addition, Yalu River-derived sediment is supplied to the mud deposition of the west NYS.
2019, 41(4): 64-73.
doi: 10.3969/j.issn.0253-4193.2019.04.006
Abstract:
Illex argentinus is the main fishing target in the southwest Atlantic. The accurate prediction of resource abundance can guide enterprises to arrange fishery production rationally. In this study, based on the fishing data of Illex argentinus in southwest Atlantic from 2001-2016, we computed the grey absolute correlation degree between the logarithmic CPUE sequence in the following year and SST sequence in the spawning ground from June to August . And we selected the points which the grey absolute correlation index was greater than 0.90 as the forecasting factors, and then a CPUE forecast of Illex argentinus in southwest Atlantic was established, and used the actual CPUE in 2016 to verify the model. The grey correlation analysis shows that there are a large number of points have strong grey correlation index between SST and CPUE sequence from June to August in the region 30°~40°S,45°~60°W. Results suggest that GM (0, 4) model, which includes average SST from June to August, has the best model effect. The relative error is 7%,which can be used in the prediction of resources abundance of Illex argentinus in the southwest Atlantic. In contrast, the GM (0, 3) does not include the spawning area's mean SST in June and in July, which relative errors are 128% and 289% respectively. This suggests June and July are the main spawning months for Illex argentinus in Southwest Atlantic Ocean.
Illex argentinus is the main fishing target in the southwest Atlantic. The accurate prediction of resource abundance can guide enterprises to arrange fishery production rationally. In this study, based on the fishing data of Illex argentinus in southwest Atlantic from 2001-2016, we computed the grey absolute correlation degree between the logarithmic CPUE sequence in the following year and SST sequence in the spawning ground from June to August . And we selected the points which the grey absolute correlation index was greater than 0.90 as the forecasting factors, and then a CPUE forecast of Illex argentinus in southwest Atlantic was established, and used the actual CPUE in 2016 to verify the model. The grey correlation analysis shows that there are a large number of points have strong grey correlation index between SST and CPUE sequence from June to August in the region 30°~40°S,45°~60°W. Results suggest that GM (0, 4) model, which includes average SST from June to August, has the best model effect. The relative error is 7%,which can be used in the prediction of resources abundance of Illex argentinus in the southwest Atlantic. In contrast, the GM (0, 3) does not include the spawning area's mean SST in June and in July, which relative errors are 128% and 289% respectively. This suggests June and July are the main spawning months for Illex argentinus in Southwest Atlantic Ocean.
2019, 41(4): 74-82.
doi: 10.3969/j.issn.0253-4193.2019.04.007
Abstract:
The technique of stable isotope analysis has been widely applied for the field of food web studies in recent years. However, few researches concerned about the impacts of different tissues used for analysis on the food web building. With the purpose of accuracy and comparability in the food web studies, the sampling tissues should be standardized. In this study, 10 macrobenthic species from the intertidal zone of the Yellow River Delta and Yantai were chosen as the target object to test the isotopic characteristic variations of δ13C and δ15N at different body parts (whole bodies, muscles and gills). Our results show that δ13C and δ15N values vary in different sampling tissues for most species, which indicates the different tissues used for analysis impact the food web building. To achieve a more accuracy and comparability result, suitable tissue should be primarily chosen for their food sources and trophic levels analysis. Namely, when the organism as predator, their muscles should first be chosen, for examples, adductor and foot muscles of mollusks, leg muscles of crabs and back muscles of fishes; when the organism as prey, most of their tissues, except for indigestible part (for polychaetes, the digestive tract contents should be removed) should be chosen for analysis on food sources and trophic levels of the secondary consumer, for example, whole soft parts of mollusks, the mixture of muscles and gills of crabs.
The technique of stable isotope analysis has been widely applied for the field of food web studies in recent years. However, few researches concerned about the impacts of different tissues used for analysis on the food web building. With the purpose of accuracy and comparability in the food web studies, the sampling tissues should be standardized. In this study, 10 macrobenthic species from the intertidal zone of the Yellow River Delta and Yantai were chosen as the target object to test the isotopic characteristic variations of δ13C and δ15N at different body parts (whole bodies, muscles and gills). Our results show that δ13C and δ15N values vary in different sampling tissues for most species, which indicates the different tissues used for analysis impact the food web building. To achieve a more accuracy and comparability result, suitable tissue should be primarily chosen for their food sources and trophic levels analysis. Namely, when the organism as predator, their muscles should first be chosen, for examples, adductor and foot muscles of mollusks, leg muscles of crabs and back muscles of fishes; when the organism as prey, most of their tissues, except for indigestible part (for polychaetes, the digestive tract contents should be removed) should be chosen for analysis on food sources and trophic levels of the secondary consumer, for example, whole soft parts of mollusks, the mixture of muscles and gills of crabs.
2019, 41(4): 83-93.
doi: 10.3969/j.issn.0253-4193.2019.04.008
Abstract:
The present study is based on the data of crustaceans obtained from 80 sample sites of the nearshore waters of Zhoushan through a fishery resources survey during November in 2015 and May in 2016. The total of 80 sample sites were divided into 10 statistic areas, which were prepared for stratified random sampling, and 20 sites were selected for analysis at last. The methods including niche breadth, canonical correspondence analysis (CCA), variance ratio (VR), x2-test, association coefficient (AC), percentage of co-occurrence (PC), and point correlation coefficients (Ф) were used. The results show that there are 19 species of crustaceans, in which 3 are dominant species and 6 are important species. Based on the niche breadth cluster analysis, the major crustaceans can be divided into three groups. They are wide niche breadth species, moderate niche breath species and narrow niche breath species. The niche overlap values of them ranged from 0 to 0.96, indicating that these species are of great similarity in resource utilization, and there is a certain degree of competition between them. The result of CCA reveals that the influence of salinity, temperature and chlorophyll a are significant to crustaceans in this region. The values of VR and W indicate that there is significantly positive correlation between the communities of major crustaceans. The x2-test suggests that there is significantly interspecific association for 61 species pair (x2≥3.841),The results of AC,PC and Ф reveal that the association of interspecific is strong and tend to be positive correlation.
The present study is based on the data of crustaceans obtained from 80 sample sites of the nearshore waters of Zhoushan through a fishery resources survey during November in 2015 and May in 2016. The total of 80 sample sites were divided into 10 statistic areas, which were prepared for stratified random sampling, and 20 sites were selected for analysis at last. The methods including niche breadth, canonical correspondence analysis (CCA), variance ratio (VR), x2-test, association coefficient (AC), percentage of co-occurrence (PC), and point correlation coefficients (Ф) were used. The results show that there are 19 species of crustaceans, in which 3 are dominant species and 6 are important species. Based on the niche breadth cluster analysis, the major crustaceans can be divided into three groups. They are wide niche breadth species, moderate niche breath species and narrow niche breath species. The niche overlap values of them ranged from 0 to 0.96, indicating that these species are of great similarity in resource utilization, and there is a certain degree of competition between them. The result of CCA reveals that the influence of salinity, temperature and chlorophyll a are significant to crustaceans in this region. The values of VR and W indicate that there is significantly positive correlation between the communities of major crustaceans. The x2-test suggests that there is significantly interspecific association for 61 species pair (x2≥3.841),The results of AC,PC and Ф reveal that the association of interspecific is strong and tend to be positive correlation.
2019, 41(4): 94-108.
doi: 10.3969/j.issn.0253-4193.2019.04.009
Abstract:
From September 2016 to August 2017, the spatial and temporal distributions of heterotrophic bacteria were studied based on monthly cruise in the northern Beibu Gulf, to reveal their correlation with major environmental factors. The heterotrophic bacteria abundances range in (2.75~56.86)×105 cell/mL, with an average of (11.01±6.31)×105 cell/mL. Generally, they are higher in the summer and spring, while lower in the autumn and winter. Heterotrophic bacteria are densely distributed in the coastal water, and gradually reduce in the southwest offshore. The vertical distribution of heterotrophic bacteria is evenly distributed in the coastal areas, and the seasonal stratification that the surface bacteria abundance is higher and bottom bacteria abundance is lower occurred in sea areas below 20 m. The principal components analysis reveals that the distribution of heterotrophic bacteria is influenced by temperature. The correlations between temperature and heterotrophic bacteria are significantly negative in autumn and winter, while significantly positive in spring and summer. The heterotrophic bacteria abundance correlates negatively with salinity, and positively with chlorophyll a and dissolved oxygen. It suggests that salinity and primary production of phytoplankton affect the spatial and temporal distribution of heterotrophic bacteria. Excluding summer, inorganic nutrients negatively correlate with the heterotrophic bacteria, which is indirectly affected by phytoplankton biomass. Spatial-temporal distributions of heterotrophic bacteria are mainly influenced by temperature, salinity, chlorophyll a and dissolved oxygen.
From September 2016 to August 2017, the spatial and temporal distributions of heterotrophic bacteria were studied based on monthly cruise in the northern Beibu Gulf, to reveal their correlation with major environmental factors. The heterotrophic bacteria abundances range in (2.75~56.86)×105 cell/mL, with an average of (11.01±6.31)×105 cell/mL. Generally, they are higher in the summer and spring, while lower in the autumn and winter. Heterotrophic bacteria are densely distributed in the coastal water, and gradually reduce in the southwest offshore. The vertical distribution of heterotrophic bacteria is evenly distributed in the coastal areas, and the seasonal stratification that the surface bacteria abundance is higher and bottom bacteria abundance is lower occurred in sea areas below 20 m. The principal components analysis reveals that the distribution of heterotrophic bacteria is influenced by temperature. The correlations between temperature and heterotrophic bacteria are significantly negative in autumn and winter, while significantly positive in spring and summer. The heterotrophic bacteria abundance correlates negatively with salinity, and positively with chlorophyll a and dissolved oxygen. It suggests that salinity and primary production of phytoplankton affect the spatial and temporal distribution of heterotrophic bacteria. Excluding summer, inorganic nutrients negatively correlate with the heterotrophic bacteria, which is indirectly affected by phytoplankton biomass. Spatial-temporal distributions of heterotrophic bacteria are mainly influenced by temperature, salinity, chlorophyll a and dissolved oxygen.
2019, 41(4): 109-118.
doi: 10.3969/j.issn.0253-4193.2019.04.010
Abstract:
In order to determine the parameters related to the growth of Sesuvium portulacastrum, hydroponic experiments are performed on the S. portulacastrum to continuously monitor the growth of S. portulacastrum and the status of ecological factors. Considering nutrient cycling, the model of S. portulacastrum is constructed based on first order attenuation pattern. The global qualitative sensitivity analysis using Morris method based on the simplex experimental design shows that the parameters sensitive to all state variables are ammonia nitrogen nitrification rate and mineralization constant of organic nitrogen, indicating that the model is mainly dominated by the nitrogen circulation system. The optimum illumination is the most sensitive parameter for the growth of S. portulacastrum, and light is the most important ecological factor that affects the growth of the S. portulacastrum. Based on the minimum mean squared error, the simulated annealing algorithm is used to optimize and determine the parameters of the model, and multiple indicators are selected to evaluate the model. The results show that the simulated values can be well fitted with the measured values, and the maximum mean absolute percentage error is 5.023%. It is found that the absorption of the S. portulacastrum to NO3-N has a certain bias to the parameter analysis, and it has high tolerance to phosphorus. The growth rate of S. portulacastrum is fast, and it has a certain development prospect.
In order to determine the parameters related to the growth of Sesuvium portulacastrum, hydroponic experiments are performed on the S. portulacastrum to continuously monitor the growth of S. portulacastrum and the status of ecological factors. Considering nutrient cycling, the model of S. portulacastrum is constructed based on first order attenuation pattern. The global qualitative sensitivity analysis using Morris method based on the simplex experimental design shows that the parameters sensitive to all state variables are ammonia nitrogen nitrification rate and mineralization constant of organic nitrogen, indicating that the model is mainly dominated by the nitrogen circulation system. The optimum illumination is the most sensitive parameter for the growth of S. portulacastrum, and light is the most important ecological factor that affects the growth of the S. portulacastrum. Based on the minimum mean squared error, the simulated annealing algorithm is used to optimize and determine the parameters of the model, and multiple indicators are selected to evaluate the model. The results show that the simulated values can be well fitted with the measured values, and the maximum mean absolute percentage error is 5.023%. It is found that the absorption of the S. portulacastrum to NO3-N has a certain bias to the parameter analysis, and it has high tolerance to phosphorus. The growth rate of S. portulacastrum is fast, and it has a certain development prospect.
2019, 41(4): 119-130.
doi: 10.3969/j.issn.0253-4193.2019.04.011
Abstract:
Sanduao is an important sea-breeding bay in China and holds a high economic status in aquaculture. Quickly and accurately obtaining information such as the distribution area, quantity, and aquaculture area is important for breeding area planning, production value estimation, ecological survey, and storm surge prevention. However, as the aquaculture area expands, the seawater background becomes increasingly complex and spectral characteristics differ dramatically, making it difficult to determine the aquaculture area. In this study, we used a high-resolution remote-sensing satellite GF-2 image to introduce a deep-learning Richer Convolutional Features network model to extract the raft aquaculture area in the bay. The results demonstrate that this method does not require land and water separation of the area in advance, and good extraction can be achieved in areas with more sediment and waves, with an extraction accuracy >93%, which is suitable for large-scale raft aquaculture area extraction.
Sanduao is an important sea-breeding bay in China and holds a high economic status in aquaculture. Quickly and accurately obtaining information such as the distribution area, quantity, and aquaculture area is important for breeding area planning, production value estimation, ecological survey, and storm surge prevention. However, as the aquaculture area expands, the seawater background becomes increasingly complex and spectral characteristics differ dramatically, making it difficult to determine the aquaculture area. In this study, we used a high-resolution remote-sensing satellite GF-2 image to introduce a deep-learning Richer Convolutional Features network model to extract the raft aquaculture area in the bay. The results demonstrate that this method does not require land and water separation of the area in advance, and good extraction can be achieved in areas with more sediment and waves, with an extraction accuracy >93%, which is suitable for large-scale raft aquaculture area extraction.
2019, 41(4): 131-144.
doi: 10.3969/j.issn.0253-4193.2019.04.012
Abstract:
Due to the influence of clouds, the visible light images that can be used effectively for green tide detection are limited, especially when the cloud coverage is serious, which can not be used to detect green tide. Even if the image data is acquired under thin cloud, mist, and cloudless coverage, it is still difficult to use the same threshold for green tide detection because of the large difference in spectral reflectance values. Based on this, in order to improve the utilization of visible light image and realize green tide high-precision automatic detection of the adaptive threshold under different cloud coverage conditions, GF-1 images are selected as data source, firstly, K-means clustering and C4.5 decision tree methods are used to automatically identify cloud coverage type; secondly, a large number of sub-image samples with different cloud coverage are selected (each sub-image sample contains two types of green tide and sea water), and the linear relationship between the classification threshold y and the image spectral difference x (x = bandnir-bandred) is analyzed under different cloud coverage, here, the classification threshold y is the value that can distinguish green tide and sea; then, green tide partition adaptive threshold automatic detection method for GF-1 image is proposed by using the linear relationship analyzed. Finally, in order to verify the effectiveness of the proposed method, NDVI、EVI methods and the adaptive threshold automatic detection method proposed in this paper are used to carry out the green tide extraction experiment. The experimental results show that for the GF-1 satellite remote sensing data, the green tide adaptive threshold partition automatic detection method is better than traditional NDVI and EVI methods, which not only improves the monitoring accuracy of green tide, but also realizes the full automation of green tide extraction.
Due to the influence of clouds, the visible light images that can be used effectively for green tide detection are limited, especially when the cloud coverage is serious, which can not be used to detect green tide. Even if the image data is acquired under thin cloud, mist, and cloudless coverage, it is still difficult to use the same threshold for green tide detection because of the large difference in spectral reflectance values. Based on this, in order to improve the utilization of visible light image and realize green tide high-precision automatic detection of the adaptive threshold under different cloud coverage conditions, GF-1 images are selected as data source, firstly, K-means clustering and C4.5 decision tree methods are used to automatically identify cloud coverage type; secondly, a large number of sub-image samples with different cloud coverage are selected (each sub-image sample contains two types of green tide and sea water), and the linear relationship between the classification threshold y and the image spectral difference x (x = bandnir-bandred) is analyzed under different cloud coverage, here, the classification threshold y is the value that can distinguish green tide and sea; then, green tide partition adaptive threshold automatic detection method for GF-1 image is proposed by using the linear relationship analyzed. Finally, in order to verify the effectiveness of the proposed method, NDVI、EVI methods and the adaptive threshold automatic detection method proposed in this paper are used to carry out the green tide extraction experiment. The experimental results show that for the GF-1 satellite remote sensing data, the green tide adaptive threshold partition automatic detection method is better than traditional NDVI and EVI methods, which not only improves the monitoring accuracy of green tide, but also realizes the full automation of green tide extraction.
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