Institutional Repository of Yantai Institute of Coastal Zone Research, CAS
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Coastline Monitoring and Prediction Based on Long-Term Remote Sensing Data-A Case Study of the Eastern Coast of Laizhou Bay, China
No full textMonitoring shoreline movements is essential for understanding the impact of anthropogenic activities and climate change on the coastal zone dynamics. The use of remote sensing allows for large-scale spatial and temporal studies to better comprehend current trends. This study used Landsat 5 (TM), Landsat 8 (OLI), and Sentinel-2 (MSI) remote sensing images, together with the Otsu algorithm, marching squares algorithm, and tidal correction algorithm, to extract and correct the coastline positions of the east coast of Laizhou Bay in China from 1984 to 2022. The results indicate that 89.63% of the extracted shoreline segments have an error less than 30 m compared to the manually drawn coastline. The total length of the coastline increased from 166.90 km to 364.20 km, throughout the observation period, with a length change intensity (LCI) of 3.11% due to the development of coastal protection and engineering structures for human activities. The anthropization led to a decrease in the natural coastline from 83.33% to 13.89% and a continuous increase in the diversity and human use of the coastline. In particular, the index of coastline diversity (ICTD) and the index of coastline utilization degree (ICUD) increased from 0.39 to 0.79, and from 153.30 to 390.37, respectively. Over 70% of the sandy beaches experienced erosional processes. The shoreline erosion calculated using the end point rate (EPR) and the linear regression rate (LRR) is 79.54% and 85.58%, respectively. The fractal dimension of the coastline shows an increasing trend and is positively correlated with human activities. Coastline changes are primarily attributed to interventions such as land reclamation, aquaculture development, and port construction resulting in the creation of 10,000.20 hectares of new coastal areas. Finally, the use of Kalman filtering for the first time made it possible to predict that approximately 84.58% of the sandy coastline will be eroded to varying degrees by 2032. The research results can provide valuable reference for the scientific planning and rational utilization of resources on the eastern coast of Laizhou Bay
How can Phycobilisome, the unique light harvesting system in certain algae working highly efficiently: The connection in between structures and functions
No full textAlgae, which are ubiquitous in ecosystems, have evolved a variety of light-harvesting complexes to better adapt to diverse habitats. Phycobilisomes/phycobiliproteins, unique to cyanobacteria, red algae, and certain cryptomonads, compensate for the lack of chlorophyll absorption, allowing algae to capture and efficiently transfer light energy in aquatic environments. With the advancement of microscopy and spectroscopy, the structure and energy transfer processes of increasingly complex phycobilisomes have been elucidated, providing us with a vivid portrait of the dynamic adaptation of their structures to the light environment in which algae thrive: 1) Cyanobacteria living on the surface of the water use short, small phycobilisomes to absorb red-orange light and reduce the damage from blue-violet light via multiple methods; 2) Large red algae inhabiting the depths of the ocean have evolved long and dense phycobilisomes containing phycoerythrin to capture the feeble blue-green light; 3) In far-red light environments such as caves, algae use special allophycocyanin cores to optimally utilize the far-red light; 4) When the environment shifts, algae can adjust the length, composition and density of their rods to better adapt; 5) By carefully designing the position of the pigments, phycobilisomes can transfer light energy to the reaction center with nearly 100% efficiency via three energy transfer processes
Research on Automatic Microalgae Detection System Based on Deep Learning
No full textObjective The scale of microalgae farming industry is huge. During farming, it is easy for microalgae to be affected by miscellaneous bacteria and other contaminants. Because of that, periodic test is necessary to ensure the growth of microalgae. Present microscopy imaging and spectral analysis methods have higher requirements for experiment personnel, equipment and sites, for which it is unable to achieve real-time portable detection. For the purpose of real-time portable microalgae detection, a real-time microalgae detection system of low detection requirement and fast detection speed is needed. Methods This study has developed a microalgae detection system based on deep learning. A microscopy imaging device based on bright field was constructed. With imaged captured from the device, a neural network based on YOLOv3 was trained and deployed on microcomputer, thus realizing real-time portable microalgae detection. This study has also improved the feature extraction network by introducing cross-region residual connection and attention mechanism and replacing optimizer with Adam optimizer using multistage and multimethod strategy. Results With cross-region residual connection, the mAP value reached 0.92. Compared with manual result, the detection error was 2.47%. Conclusion The system could achieve real-time portable microalgae detection and provide relatively accurate detection result, so it can be applied to periodic test in microalgae farming
Spatiotemporal variation of land surface temperature and its driving factors in Xinjiang, China
No full textLand surface temperature (LST) directly affects the energy balance of terrestrial surface systems and impacts regional resources, ecosystem evolution, and ecosystem structures. Xinjiang Uygur Autonomous Region is located at the arid Northwest China and is extremely sensitive to climate change. There is an urgent need to understand the distribution patterns of LST in this area and quantitatively measure the nature and intensity of the impacts of the major driving factors from a spatial perspective, as well as elucidate the formation mechanisms. In this study, we used the MOD11C3 LST product developed on the basis of Moderate Resolution Imaging Spectroradiometer (MODIS) to conduct regression analysis and determine the spatiotemporal variation and differentiation pattern of LST in Xinjiang from 2000 to 2020. We analyzed the driving mechanisms of spatial heterogeneity of LST in Xinjiang and the six geomorphic zones (the Altay Mountains, Junggar Basin, Tianshan Mountains, Tarim Basin, Turpan-Hami (Tuha) Basin, and Pakakuna Mountain Group) using geographical detector (Geodetector) and geographically weighted regression (GWR) models. The warming rate of LST in Xinjiang during the study period was 0.24 degrees C/10a, and the spatial distribution pattern of LST had obvious topographic imprints, with 87.20% of the warming zone located in the Gobi desert and areas with frequent human activities, and the cooling zone mainly located in the mountainous areas. The seasonal LST in Xinjiang was at a cooling rate of 0.09 degrees C/10a in autumn, and showed a warming trend in other seasons. Digital elevation model (DEM), latitude, wind speed, precipitation, normalized difference vegetation index (NDVI), and sunshine duration in the single-factor and interactive detections were the key factors driving the LST changes. The direction and intensity of each major driving factor on the spatial variations of LST in the study area were heterogeneous. The negative feedback effect of DEM on the spatial differentiation of LST was the strongest. Lower latitudes, lower vegetation coverage, lower levels of precipitation, and longer sunshine duration increased LST. Unused land was the main heat source landscape, water body was the most important heat sink landscape, grassland and forest land were the land use and land cover (LULC) types with the most prominent heat sink effect, and there were significant differences in different geomorphic zones due to the influences of their vegetation types, climatic conditions, soil types, and human activities. The findings will help to facilitate sustainable climate change management, analyze local climate and environmental patterns, and improve land management strategies in Xinjiang and other arid areas
Functional analyses of TRAF6 gene in Argopecten scallops
No full textThe tumor necrosis factor (TNF) receptor-associated factor (TRAF) family has been reported to be involved in many immune pathways. In a previous study, we identified 5 TRAF genes, including TRAF2, 3, 4, 6, and 7, in the bay scallop (Argopecten irradians, Air) and the Peruvian scallop (Argopecten purpuratus, Apu). Since TRAF6 is a key molecular link in the TNF superfamily, we conducted a series of studies targeting the TRAF6 gene in the Air and Apu scallops as well as their hybrid progeny, Aip (Air 9 x Apu d) and Api (Apu 9 x Air d). Subcellular localization assay showed that the Air-, Aip-, and Api-TRAF6 were widely distributed in the cytoplasm of the human embryonic kidney cell line (HEK293T). Additionally, dual-luciferase reporter assay revealed that among TRAF3, TRAF4, and TRAF6, only the overexpression of TRAF6 significantly activated NF-kappa B activity in the HEK293T cells in a dose-dependent manner. These results suggest a crucial role of TRAF6 in the immune response in Argopecten scallops. To investigate the specific immune mechanism of TRAF6 in Argopecten scallops, we conducted TRAF6 knockdown using RNA interference. Transcriptomic analyses of the TRAF6 RNAi and control groups identified 1194, 2403, and 1099 differentially expressed genes (DEGs) in the Air, Aip, and Api scallops, respectively. KEGG enrichment analyses revealed that these DEGs were primarily enriched in transport and catabolism, amino acid metabolism, peroxisome, lysosome, and phagosome pathways. Expression profiles of 28 key DEGs were confirmed by qRT-PCR assays. The results of this study may provide insights into the immune mechanisms of TRAF in Argopecten scallops and ultimately benefit scallop breeding
Atmospheric deposition and river runoff stimulate the utilization of dissolved organic phosphorus in coastal seas
No full textIn coastal seas, the role of atmospheric deposition and river runoff in dissolved organic phosphorus (DOP) utilization is not well understood. Here, we address this knowledge gap by combining microcosm experiments with a global approach considering the relationship between the activity of alkaline phosphatases and changes in phytoplankton biomass in relation to the concentration of dissolved inorganic phosphorus (DIP). Our results suggest that the addition of aerosols and riverine water stimulate the biological utilization of DOP in coastal seas primarily by depleting DIP due to increasing nitrogen concentrations, which enhances phytoplankton growth. This "Anthropogenic Nitrogen Pump" was therefore identified to make DOP an important source of phosphorus for phytoplankton in coastal seas but only when the ratio of chlorophyll a to DIP [Log10 (Chl a / DIP)] is larger than 1.20. Our study therefore suggests that anthropogenic nitrogen input might contribute to the phosphorus cycle in coastal seas
New insights into estimation of bioavailable inorganic phosphorus in natural coastal seawater
No full textConsidering the impact of the high salinity and high turbidity of coastal seawater on phosphorus forms, a new method was proposed to determine bioavailable inorganic phosphorus (BIP). The phosphorus most relevant to eutrophication is BIP, and traditional analysis methods may underestimate the degree of eutrophication. In this study, a microelectrode of multigold (Au mu E) was fabricated for direct voltammetric determination of BIP without filtration, and BIP environmental characteristics including distribution and correlation relationships with environmental factors in typical coastal seawater of Northern China were analyzed. The proposed Au mu E showed a low detection limit of 0.03 mu M. The surface and bottom BIP concentrations ranged from 1.00 to 2.13 and from 0.88 to 2.05 mu M, respectively. BIP dominated the total P (TP) accounting for 48.5-67.5 % in the surface layer samples, and 32.6-92.7 % in the bottom layer samples, respectively. The concentrations of BIP were obviously higher than those of DIP, indicating that DIP may underestimate the probability of eutrophication occurring. And BIP was positively correlated with dissolved oxygen (DO) (P < 0.05). BIP may be a promising indicator of eutrophication potential in coastal areas with high salinity and high turbidity. The proposed reliable voltammetry method provides a new indicator for environmental assessment and represents a significant step in the comprehensive analysis of P species
Source identification and risk assessment of trace metals in surface sediment of China Sea by combining APCA-MLR receptor model and lead isotope analysis
No full textThis study aimed to investigate the distribution, pollution, risk and sources of trace metals in sediments along China Sea. Clear spatial variations were found for Cr, Mn, Co, Ni, Cu, Zn, Se, Mo, Ag, Cd, and Pb, whereas As did not show spatial variation. East China Sea (ECS) contained the highest concentrations of Mn, Co, Ni, Cu, Zn, South China Sea (SCS) shallow sea contained the highest concentrations of Zn, Se, Mo, Ag, Cd, and Pb, whereas coral reefs contained the lowest concentrations of trace metals. Spatial variations could be explained by economic development characteristics along China Sea. As, Se and Cd exhibited low to moderate pollution in China Sea sediment, yet pollution for Cu, Zn, Ni, and Ag appeared in some regions. Sediment in ECS had moderate ecological risks and other regions at low ecological risks. The absolute principle component score-multiple linear regression (APCS-MLR) and Pb stable isotope indicated that 43-74% of trace metals (Ni, Cu, Zn, As, Se, Cd, and Pb) were derived from anthropogenic sources like traffic emission, agricultural activities, industrial source. No pollution and ecological risk were observed in coral reefs, yet 39-71% (Pb) was derived from anthropogenic activities such as motor vessels
Genome-wide characterization and expression analysis of MADS-box transcription factor gene family in <i>Perilla frutescens</i>
No full textMADS-box transcription factors are widely involved in the regulation of plant growth, developmental processes, and response to abiotic stresses. Perilla frutescens, a versatile plant, is not only used for food and medicine but also serves as an economical oil crop. However, the MADS-box transcription factor family in P. frutescens is still largely unexplored. In this study, a total of 93 PfMADS genes were identified in P. frutescens genome. These genes, including 37 Type I and 56 Type II members, were randomly distributed across 20 chromosomes and 2 scaffold regions. Type II PfMADS proteins were found to contain a greater number of motifs, indicating more complex structures and diverse functions. Expression analysis revealed that most PfMADS genes (more than 76 members) exhibited widely expression model in almost all tissues. The further analysis indicated that there was strong correlation between some MIKC (c)-type PfMADS genes and key genes involved in lipid synthesis and flavonoid metabolism, which implied that these PfMADS genes might play important regulatory role in the above two pathways. It was further verified that PfMADS47 can effectively mediate the regulation of lipid synthesis in Chlamydomonas reinhardtii transformants. Using cis-acting element analysis and qRT-PCR technology, the potential functions of six MIKC (c)-type PfMADS genes in response to abiotic stresses, especially cold and drought, were studied. Altogether, this study is the first genome-wide analysis of PfMADS. This result further supports functional and evolutionary studies of PfMADS gene family and serves as a benchmark for related P. frutescens breeding studies
Synthesis of 12-Connected Three-Dimensional Covalent Organic Framework with lnj Topology
No full textThe structural exploration of three-dimensional covalent organic frameworks (3D COFs) is of great significance to the development of COF materials. Different from structurally diverse MOFs, which have a variety of connectivity (3-24), now the valency of 3D COFs is limited to only 4, 6, and 8. Therefore, the exploration of organic building blocks with higher connectivity is a necessary path to broaden the scope of 3D COF structures. Herein, for the first time, we have designed and synthesized a 12-connected triptycene-based precursor (triptycene-12-CHO) with 12 symmetrical distributions of aldehyde groups, which is also the highest valency reported until now. Based on this unique 12-connected structure, we have successfully prepared a novel 3D COF with lnj topology (termed 3D-lnj-COF). The as-synthesized 3D COF exhibits honeycomb main pores and permanent porosity with a Brunauer-Emmett-Teller surface area of 1159.6 m(2) g(-1). This work not only provides a strategy for synthesizing precursors with a high connectivity but also provides inspiration for enriching the variety of 3D COFs