Continuous Dynamic Monitoring Research Articles

Gap expansion is the dominant driver of canopy openings in a temperate mountain forest landscape

Abstract Natural disturbances are important drivers of forest dynamics, and canopy gaps are their fingerprints in forest ecosystems. Gaps form and persist because of the interplay of tree mortality and regeneration. They can have long‐lasting impacts on ecosystems, yet the temporal dynamics of gap formation and closure remains poorly quantified. We analysed 11,331 canopy gaps and their changes through time across 3999 ha of unmanaged temperate mountain forests at Berchtesgaden National Park (Germany). We assessed gap formation and closure using three repeat lidar acquisitions between 2009 and 2021, analysing canopy height changes at 1 m horizontal resolution. Our objective was to determine the dominant mode of gap formation, distinguishing the creation of new gaps from the expansion of existing ones. Additionally, we studied the rate of gap closure, considering closure from tree regeneration and lateral crown expansion. Gap formation was primarily driven by gap expansion rather than the initiation of new gaps. Gap expansion accounted for 81.3% of gap formation, although new gaps were on average twice as large as gap expansions. Only 1.4% of gaps did not expand over the 12‐year study period, and Norway spruce forests had the highest rate of gap expansion. Overall, gap closure rate (0.74 ha 100 ha−1 year−1) was higher than gap formation (0.58 ha 100 ha−1 year−1) in our study system. Ingrowth of the regenerating tree cohort was the primary mode of gap closure, with lateral crown expansion accounting for 20% of all gap area closed. Mixed‐species stands had the highest rate of gap closure, and gaps <0.1 ha closed faster than larger gaps. Synthesis. While canopy openings are generally small in the European Alps, we show that they keep growing over multiple years, underlining that gap expansion is an important driver of temperate forest dynamics. Canopy gaps closed faster than they were created, highlighting the resilience of European mountain forests to natural disturbances. However, as disturbances are projected to increase under climate change, this resilience might be challenged in the future, requiring a continuous monitoring of gap dynamics as an important early warning indicator of forest change.

Measurement report: The Palau Atmospheric Observatory and its ozonesonde record – continuous monitoring of tropospheric composition and dynamics in the tropical western Pacific

Abstract. The tropical western Pacific is recognized as an important region for stratosphere–troposphere exchange but lies in a data-sparse location that had a measurement gap in the global ozone sounding network. The Palau Atmospheric Observatory (PAO, approx. 7.3∘ N, 134.5∘ E) was established to study the atmospheric composition above the remote tropical western Pacific with a comprehensive instrumental setup. Since 2016, two laboratory containers in Palau host a Fourier transform infrared spectrometer; a lidar (micro-lidar until 2016, cloud and aerosol lidar from 2018); a Pandora 2S photometer; and laboratory space for weather balloon soundings with ozone, water vapor, aerosol, and radiosondes. In this analysis, we focus on the continuous, fortnightly ozone sounding program with electrochemical concentration cell (ECC) ozonesondes. The aim of this study is to introduce the PAO and its research potential, present the first observation of the typical seasonal cycle of tropospheric ozone in the tropical western Pacific based on a multiannual record of in situ observations, and investigate major drivers of variability and seasonal variation from January 2016 until December 2021​​​​​​​ related to the large-scale atmospheric circulation. We present the PAO ozone (O3) volume mixing ratios (VMR) and relative humidity (RH) time series complemented by other observations. The site is exposed to year-round high convective activity reflected in dominating low O3 VMR and high RH. In 2016, the impact of the strong El Niño is evident as a particularly dry, ozone-rich episode. The main modulator of annual tropospheric O3 variability is identified as the movement of the Intertropical Convergence Zone (ITCZ), with the lowest O3 VMR in the free troposphere during the ITCZ position north of Palau. An analysis of the relation of O3 and RH for the PAO and selected sites from the Southern Hemispheric Additional Ozonesondes (SHADOZ) network reveals three different regimes. Palau's O3 / RH distribution resembles the one in Fiji, Java and American Samoa but is unique in its seasonality and its comparably narrow Gaussian distribution around low O3 VMR and the evenly distributed RH. A previously found bimodal distribution of O3 VMR and RH could not be seen for the full Palau record but only during specific seasons and years. Due to its unique remote location, Palau is an ideal atmospheric background site to detect changes in air dynamics imprinted on the chemical composition of the tropospheric column. The efforts to establish, run and maintain the PAO have succeeded to fill an observational gap in the remote tropical western Pacific and give good prospects for ongoing operations. The ECC sonde record will be integrated into the SHADOZ database in the near future.

Dynamic changes in cardiac biomarkers in radiotherapy for oesophageal cancer and their correlations with cardiac radiation dosimetry

Background and purposeTo investigate the dynamic changes in cardiac enzymes, high-sensitivity troponin T (hs-TnT), pro-brain natriuretic peptide (pro-BNP) and left ventricular ejection fraction (LVEF) during radiotherapy (RT) and 6 months after RT for oesophageal squamous cell carcinoma (ESCC) in the middle and lower locations and to analyse the correlations between these indicators and cardiac radiation dosimetry parameters. MethodsFor 35 patients with ESCC in the middle and lower locations receiving radical concurrent chemoradiotherapy (cCRT), intensity-modulated RT was performed at 1.8 Gy or 2.0 Gy per day, and the totle dose was 50.4 Gy or 60 Gy. Serum creatine kinase (CK), creatine kinase isoenzyme (CK-MB), lactate dehydrogenase (LDH), alpha-hydroxybutyrate dehydrogenase (α-HBDH), hs-TnT, pro-BNP and LVEF were measured before, during, and at the end of RT and 1, 3 and 6 months after RT, and correlations of these indicators with mean heart dose (MHD) and heart V5-V50 were analysed. Resultshs-TnT during, at the end and 6 months after RT for oesophageal cancer showed increasing trends, however, LVEF showed a downward trend. pro-BNP showed an increasing trend during RT and gradually returned to normal after RT. CK and CK-MB showed decreasing trends during RT and continued until one month after RT and then gradually returned to normal. Compared with the low-dose group (MHD < 2000 cGy), the high-dose group (MHD ≥ 2000 cGy) had larger increases in hs-TnT and pro-BNP, a more significant decrease in LVEF, and a longer recovery time for these indicators. MHD and V35 were positively correlated with dynamic changes in hs-TnT. ConclusionsCardiac injury caused by cCRT for ESCC in the middle and lower locations led to increased hs-TnT and pro-BNP levels and a decrease in LVEF in the early stage of treatment, effects that were more pronounced in the high-dose group. MHD and V35 may be potential indicators to predict the degree of cardiac damage. hs-TnT and pro-BNP are sensitive indicators reflecting cardiac injury in RT for oesophageal cancer. Continuous dynamic monitoring of these markers can provide a reference for cardiac protection in clinical RT.

Microfluidic Device-Based In Vivo Detection of PD-L1-Positive Small Extracellular Vesicles and Its Application for Tumor Monitoring.

Liquid biopsy is of great significance in tumor early diagnosis and treatment stratification. PD-L1-positive small extracellular vesicles (PD-L1+ sEVs) are closely related to tumor growth and immunotherapy response, which are considered valuable liquid biopsy biomarkers. In contrast to conventional in vitro detection, in vivo detection has the ability to improve the detection efficiency and enable continuous or real-time dynamic monitoring. However, in vivo detection of PD-L1+ sEVs has multiple difficulties, such as high cell background, complex blood environments, and lack of a specific and stable detection method. Herein, the in vivo detection of PD-L1+ sEVs method was constructed, which efficiently separated sEVs based on the microfluidic device and quantitatively analyzed PD-L1+ sEVs by aptamer recognition and hybridization chain reaction. The concentration of PD-L1+ sEVs was continuously monitored, and significant differences at different stages of tumor as well as a correlation with tumor volume were found. Diseased and healthy individuals could also be effectively distinguished based on the concentration of PD-L1+ sEVs. The method with good stability, biocompatibility, and detection performance provided a powerful means for in vivo detection of PD-L1+ sEVs, contributing to the clinical diagnosis and treatment of tumor.

The Impact of Climate Change on Glacier Retreat

Purpose: The main objective of this study was to explore the impact of climate change on glacier retreat.&#x0D; Methodology: The study adopted a desktop research methodology. Desk research refers to secondary data or that which can be collected without fieldwork. Desk research is basically involved in collecting data from existing resources hence it is often considered a low cost technique as compared to field research, as the main cost is involved in executive’s time, telephone charges and directories. Thus, the study relied on already published studies, reports and statistics. This secondary data was easily accessed through the online journals and library.&#x0D; Findings: The findings revealed that there exists a contextual and methodological gap relating to the impact of climate change on glacier retreat. Preliminary empirical review revealed that glacier retreat, driven by rising global temperatures and greenhouse gas emissions, poses significant threats to our environment, water resources, ecosystems, and communities. The studies emphasize glaciers' role as sensitive indicators of climate change and the urgent need for further research to understand regional variations and develop adaptation strategies. To address these challenges, international collaboration and sustainable solutions are essential to slow glacier retreat, mitigate impacts, and preserve these vital natural resources for the future.&#x0D; Unique Contribution to Theory, Practice and Policy: The Theory of Anthropogenic Climate Change, Theory of Glacier Response to Temperature Change and Theory of Glacial Mass Balance may be used to anchor future studies on glacier retreat. The study recommends a three-fold approach to address the impact of climate change on glacier retreat: first, urgent global efforts to reduce greenhouse gas emissions and mitigate climate change; second, the development of adaptive strategies for vulnerable communities, focusing on water resource diversification and sustainable agricultural practices; and third, the continuous monitoring and research of glacier dynamics to enhance our understanding and inform localized strategies for glacier-dependent regions.

The Association of Serum Calprotectin with Fitness Indicators and Biochemical Markers in High-Level Athletes: A Continuous Dynamic Monitoring during One Competitive Season.

Twenty professional male water polo players (median age: 28 (22-42)) were included in this study. Serum creatine kinase activity was determined by the automated photometric UV method. The concentrations of calprotectin, C-reactive protein, and myoglobin were measured using an automated immunoturbidimetric method, while an automated immunochemistry method was employed for interleukin-6, troponin I, and cortisol determination. Tests of repeated strength, maximal strength, and static strength were used to evaluate physical activity. Serum calprotectin concentrations expressed in median and IQR were significantly different: T1: 2.92 g/mL (2.47; 3.86); T2: 2.35 g/mL (1.26; 2.87); T3: 2.27 g/mL (1.60; 3.27); and T4: 1.47 g/mL (1.04; 2.85) (p = 0.004). Cortisol concentration and CK activity showed significant changes among phases (p = 0.049 and p = 0.014, respectively). Each physical activity examined showed a significant seasonal decrease (all p values were 0.001). Calprotectin serum concentration and indicators of muscular injury, inflammation, and physical activity were found to be correlated during particular stages of the seasonal examination. Calprotectin values determined throughout one competitive season decreased as training intensity among water polo players increased. Serum calprotectin concentrations and indicators were related to biochemical markers of inflammation and muscle damage.

Application of Remote Wireless Intelligent Layered Water Injection Technology in Dagang Oilfield

A remote wireless intelligent layered water injection technolo-gy is proposed to address the problems of traditional layered water in-jection well testing in oil fields, such as the inability to achieve continu-ous dynamic monitoring of injection parameters, high failure rate, and low success rate of testing and commissioning. The technology consists of a host computer client, a server, a surface controller, and an under-ground intelligent water distributor. The underground intelligent water distributor takes the injected water as the carrier, and uses the fluctua-tion of the water injection pressure in the tubing for signal transmission to realize two-way communication between the ground controller and the downhole intelligent water distributor. The underground intelligent water distributor integrates high-precision pressure gauges, controllable water nozzles, and calculation and control modules to form an intelli-gent control system, realizing the reception of ground down transmitted commands or data, the calculation and control of water injection flow rate of water nozzles, and the storage and upload of underground data. Remote wireless intelligent layered water injection technology has been applied in 43 wells, with a success rate of 100%. The maximum depth is 3897m, and the maximum wellbore inclination is 56.07°. This tech-nology realizes remote control of water injection wells, intelligent au-tomatic measurement and adjustment, real-time data monitoring, and automatic early warning functions, laying a foundation for the con-struction of “Digital Intelligence” oilfield.

An Automated Procedure for Continuous Dynamic Monitoring of Structures: Theory and Validation

IntroductionStability diagrams are a helpful tool for operational modal analysis to obtain the physical modes of a structure. These modes can be defined by visualizing stable columns formed by consistently identified modes over a range of model orders. Extracting these modes manually becomes an obstacle if continuous identification of modal parameters is required.Materials and methodsIn this paper, a procedure is configured to automatically interpret the stability diagrams constructed with the identification results of the SSI-COV/ref algorithm. This procedure is based on some methodologies found in the literature, which follow three stages. First, a stability diagram cleaning stage is defined where modal validation criteria and partitioning clustering algorithms are used to detect spurious modes. Second, a mode grouping stage based on a hierarchical clustering algorithm is implemented to form sets of modes that share similar modal information. Finally, a selection stage is applied to define representative modal parameters from the set of physical modes.ResultsThe proposed procedure is validated by simulating a beam-type structural model with ten degrees of freedom affected by ambient temperature functions. Natural frequencies computed for the DT140 and DT220 datasets collection with the frequency-domain decomposition method agree with the computed ones with the proposed procedure, presenting MAC coefficients higher than 0.97. A total of 192 datasets are simulated, and the acceleration responses are polluted with two noise levels, SRN = 40 [dB] and SNR = 20 [dB].ConclusionsFor the analyzed beam, the modal tracking results showed that the procedure could perform continuous identification automatically. The variations in the natural frequencies are correlated to the variations in the ambient temperature functions.

Time-varying overdispersion of SARS-CoV-2 transmission during the periods when different variants of concern were circulating in Japan

Japan has implemented a cluster-based approach for coronavirus disease 2019 (COVID-19) from the pandemic’s beginning based on the transmission heterogeneity (overdispersion) of severe acute respiratory coronavirus 2 (SARS-CoV-2). However, studies analyzing overdispersion of transmission among new variants of concerns (VOCs), especially for Omicron, were limited. Thus, we aimed to clarify how the transmission heterogeneity has changed with the emergence of VOCs (Alpha, Delta, and Omicron) using detailed contact tracing data in Yamagata Prefecture, Japan. We estimated the time-varying dispersion parameter ({k}_{t}) by fitting a negative binomial distribution for each transmission generation. Our results showed that even after the emergence of VOCs, there was transmission heterogeneity of SARS-CoV-2, with changes in {k}_{t} during each wave. Continuous monitoring of transmission dynamics is vital for implementing appropriate measures. However, a feasible and sustainable epidemiological analysis system should be established to make this possible.

Natural Protected Areas effect on the cover change rate of mangrove forests in the Yucatan Peninsula, Mexico

Mangrove forests provide important ecosystem services that support the maintenance of coastal socio-ecological systems. Strategies such as the establishment of Natural Protected Areas (NPAs) have been encouraged worldwide to promote their conservation. However, mangroves are still being lost as a consequence of anthropogenic disturbance and environmental variation. In here, we determine the change rate in mangrove cover, between 2005–2015, in eight coastal NPAs and the corresponding four km adjacent transition area in the Yucatan Peninsula (YP), and assess the relationship with location (inside or outside the protected area), their time since establishment and distance to roads. In general, we observed higher positive rates of change in mangrove cover inside the protected areas than in the adjacent transition zones (p < 0.05). Change was related to both the distance to roads and the time since establishment of the NPAs (p < 0.05). Higher (positive and negative) mangrove rates of change were observed in areas closer to roads, and more stable areas were detected as the distance to the roads increased. The positive rate of change also increased with the age of the protected area. These patterns were more evident inside the NPAs. The continuous monitoring of mangrove change dynamics in protected areas in this important region and their drivers, is necessary to establish effective management strategies considering the spatial and temporal variability of environmental and anthropogenic disturbances.

Diabetes mellitus in the Russian Federation: dynamics of epidemiological indicators according to the Federal Register of Diabetes Mellitus for the period 2010–2022

BACKGROUND. The clinical and epidemiological characteristics of diabetes mellitus (DM) and the quality of its therapy are the key prognostic dominant that determines the organizational aspects of the diabetic service. The continuous dynamic monitoring of DM has been carried out in the Russian Federation (RF) since 1996 through the activities of the Federal Register of Diabetes Mellitus (FDR).AIMS. The aim of our study was to analyze the epidemiological characteristics of DM in the RF (prevalence, morbidity, mortality), the prevalence diabetic of complications, the state of carbohydrate metabolism (level of HbA1c) and the dynamics of the structure of glucose-lowering therapy (GLT) according to the FDR.MATERIALS AND METHODS. The database of FRD (https://www.diaregistry.ru/), 85 regions of the RF. The data are presented as of 01.01.2023 and in dynamics for the period 2010–2022.RESULTS. The total number of DM patients in the RF as of 01.01.2023 was 4 962 762 (3.31% of the population), including: Type 1 (T1) — 5.58% (277.1 ths), T2 — 92.33% (4.58 million), other DM types —2.08% (103 ths). The dynamics of prevalence over the 13-year period (2010→2022) was 146.0→191.0/100 ths people with T1, and 2036.2→3158.8/100 ths people with T2; morbidity in T1 12.3→8.2/100 ths population, in T2 260.1→191.4/100 ths population; мortality: T1 2.1→2.4/100 ths population, T2 41.2→86.1/100 ths of the population. The main cause of death was cardiovascular: in T1 38.6% cases, in T2 — 50.9%. Life expectancy (average age of death of patients): T1 was 52.7 years, the dynamics in males 50.9 → 50.7 years, females 62.1→56.0 years; in T2 — 74.2 years, males 69.5→70.4 years, females 74.2→76.1 years. The dynamic of DM duration from onset to the death: in T1 15.4→19.9 years; in T2 11→11.4 10.2→11.8 years. The proportion of patients with laboratory-measured HbA1c &lt;7% in the dynamics of 2010–2022: with DM1 24.4%→29%, with DM2 41.5%→42.2%, with HbA1c ≥9.0%: with DM1 29, 4% → 20.4%, with DM2 13.8 → 9.0%.The incidence of diabetic complications as of 01.01.2023 in T1 and T2 patients: neuropathy 41.3% and 23.7%, nephropathy (CKD) 22.8% and 19.1%, retinopathy 28.9% and 12.3%, respectively. The structure GLT in T2 patients as of 01.01.2023: monotherapy — 41.6%; combination of 2 GLM — 30.0%, 3 GLM — 5.8%, insulin therapy in 18.3%.CONCLUSIONS. The information-analytical system FDR is a key tool for systematizing the most important epidemiological and clinical characteristics of DM based on data from real clinical practice, which allows optimizing the algorithm of patient management and improving the quality of care for diabetes.

Deformation Analysis of Guobu Slope based on SBAS-InSAR

The Laxiwa hydropower station reservoir in the upper reaches of the Yellow River basin is located in a canyon zone. Due to its complex terrain and difficult transportation, traditional monitoring methods are difficult to implement in this area, especially during the critical deformation stage when personnel may face danger or encounter difficulty reaching the site. To achieve long-term continuous dynamic monitoring of the upstream active slope of the Laxiwa hydropower station, namely the Guobu slope, SBAS-InSAR technology has been adopted as a replacement for traditional measurement methods to monitor landslide movements. Based on the deformation information of the monitoring targets, safety analysis, and disaster warnings are conducted to ensure the safe operation of the power station and the safety of downstream communities and residents' lives and property.

Unsupervised data normalization for continuous dynamic monitoring by an innovative hybrid feature weighting-selection algorithm and natural nearest neighbor searching

Continuous dynamic monitoring brings an important opportunity to evaluate the health and integrity of civil structures in a long-term manner. However, high dimensionality and sparsity of data caused by long-term monitoring and negative influences of environmental and/or operational variability are major challenges in this process. To address these important issues, this article proposes an innovative unsupervised data normalization method based on a novel hybrid feature weighting-selection algorithm and the idea of natural nearest neighbor (NN) searching emanated from the theory of mutual friendships in human societies. The proposed hybrid algorithm is a combination of global feature weighting with a new weighting measure and local feature selection. For this algorithm, this article leverages the natural NN searching that seeks to find adequate NNs automatically. The main objective of the proposed method is to remove the environmental and/or operational effects and provide normalized weighted features for reliable continuous dynamic monitoring. Using such features, an anomaly detector based on the Mahalanobis-squared distance is developed to assess and detect structural damage. The key innovations of this paper contain proposing a fully nonparametric unsupervised learning technique in two parts of data normalization and anomaly detection and developing a novel hybrid algorithm for removing the environmental and/or operational variations. Long-term dynamic features (modal frequencies) of a three-span box-girder concrete bridge (Z24 Bridge) and a long-span concrete arch bridge (Infante Dom Henrique Bridge) are considered to verify the proposed technique with several comparisons. Results indicate that this technique is successful and reliable in mitigating the environmental and/or operational effects and notifying accurate structural states.

A novel reduced column section approach for the seismic protection of wind turbines

The rapid increase in global energy demand over the coming decades must be sustained by a more consistent increment of energy production from renewable sources of which wind energy is currently one of the fast-growing resources. New onshore and offshore wind farms will be rapidly constructed in challenging environments, especially in earthquake-prone areas. As a result, the mitigation of the dynamic vibrations of the wind turbines becomes a fundamental aspect of the seismic design to guarantee their normal operativity and structural safety. Different from past proposals based on traditional passive control devices such as tuned mass dampers or tuned liquid column dampers, this study aims to propose a novel approach, the Reduced Column Section (RCS), to derive an innovative mitigation device which replaces the traditional transition piece of the wind turbine. Analytical formulas to design the proposed RCS will be established. The benefits of the proposed device will be assessed on a real onshore wind turbine located in Italy. Modal properties obtained from the continuous dynamic monitoring of the wind turbine will be used to characterize the numerical finite element model. Therefore, a direct integration analysis with spectrum-compatible real earthquakes and an incremental dynamic analysis will be conducted to evaluate the dynamic mitigation induced by the proposed RCS. Soil-structure interaction effects will be also considered. This study shows that RCS can efficiently mitigate the effective stresses on the wind tower wall by up to 70% compared to the stresses computed on the existing structure.

A novel approach towards continuous monitoring of forest change dynamics in fragmented landscapes using time series Landsat imagery

Carbon emissions from forest ecosystems are greatly impacted by the acceleration of fragmentation and edge effects. Understanding these effects requires accurate monitoring of changes in fragmented forest landscapes. However, these changes are often low-intensity and small-scale, making it difficult to detect them using medium spatial resolution satellite images (e.g., Landsat). To address this challenge, this study developed the Pure Forest Index (PFI), which uses a combination of the existing vegetation index (VI) and spectral mixture analysis (SMA) to more effectively detect and characterize the contribution of forests to the observed spectral response of a pixel. The PFI was applied to detect forest changes in the Amazon rainforest from 1986 to 2020 using the Continuous Change Detection and Classification (CCDC) algorithm (hereafter referred to as the CCDC-PFI algorithm). The results showed reliable performance in mapping forest changes, with an overall accuracy of 0.94 (±0.03) at the spatial scale and a temporal accuracy of 91.1 % (within a two-year window). Comparison with other indices revealed that the PFI improves the ability to monitor forest dynamics with an increased overall accuracy of 0.02–0.35. The PFI also demonstrated advantages in enhancing sub-pixel forest information and suppressing non-forest backgrounds in various scenes compared to conventional VIs. The proposed approach is expected to benefit further research on forests and ecosystems.

The presence of microplastics (MPs) reduces the toxicity of cadmium (Cd) to Cirrhinus mrigala larva

Cumulative studies have shown that microplastics (MPs) and cadmium (Cd) co-exist widely, but their combined toxic effects on aquatic organisms are still not well understood. In this study, Cirrhinus mrigala larvae were exposed to single and binary combinations for 7 days, and the growth performance, survival, intestinal contaminant migration, intestinal histopathology, enzyme activity, and expression of antioxidant-related and detoxification-related genes were measured. The results showed that PS-MPs, Cd, and their combined exposure cause intestinal tissue damage, which in turn affects the growth and survival of C. mrigala larvae, and combined exposure of PS-MPs and Cd reduces stagnant growth and death caused by single Cd exposure. Under both single and binary exposure, PS-MPs can accumulate in the intestine of C. mrigala larvae, but Cd-induced damage to intestinal tissues can increase the accumulation of PS-MPs in the intestine of C. mrigala larvae. PS-MPs, Cd and their combined exposure can cause abnormalities in enzyme activity and expression of antioxidant genes and detoxification genes. The results of continuous 7-day dynamic monitoring showed that the relative expression of cat in the Cd exposure group was significantly higher than that of the control group on days 1, 2 and 4; the relative expression of gpx was significantly higher than that of the control group on days 3, 4 and 7; the relative expression of mnsod was significantly higher than that of the control group on days 1, 3 and 7; and the relative expression of cusod was significantly higher than that of the control group on days 4, 6 and 7. These results indicated that the presence of MPs acted as an antagonist, reducing the toxicity of Cd to aquatic organisms. Overall, this study contributes to further understanding of the inter-regulatory relationship between MPs and Cd and the combined toxic effects on aquatic organisms.

Remote sensing monitoring of mangrove growth rate at selected planted sites in Mauritius

Mangroves are highly productive and rich ecosystems that thrive at the interface of land and sea. They provide a wide range of essential goods and services, contribute highly to coastal protection and the livelihood of coastal communities, and are also carbon-rich biomes contributing to carbon sequestration. Mangroves are primarily threatened by anthropogenic activities; a loss in biodiversity has been observed in the past years in many countries including Mauritius. Given their value to the ecosystem, it is important to have effective continuous monitoring of mangrove dynamics. We studied the rate of increase of canopy coverage of planted Rhizophora mucronata forests in two selected sites (Le Morne and Grande Rivière Noire) on a southern African island – Mauritius – using Google Earth Pro historical Landsat 7 and Landsat 8 images. Data were processed using ImageJ software. To our knowledge, this technique has not yet been applied for monitoring mangrove growth. The mangrove sites were classified into four zones based on water level and tidal variations. On average, the rate of increase of canopy coverage expressed by a coefficient ‘b’ at Le Morne (b = 1.901) was higher than that at Grande Rivière Noire (b = 1.823). The coefficient ‘b’ positively correlated with the zonations (r ~ 0.8). Higher ‘b’ values (2.319–2.886) were observed in Zone 1, where the substrate is always covered with water at low tide. The use of remote sensing data along with image processing analysis proved to be an effective tool to obtain relevant information, not only for mapping mangroves but also for monitoring the canopy growth rates of planted mangroves.Significance: We describe a novel technique whereby remote sensing data are processed through image processing using ImageJ software, to effectively monitor planted mangrove canopy growth by pixel count. This study highlights the successful application of the technique to obtain relevant information for mapping and monitoring the canopy growth rates of planted mangroves. This technique can be further extended to identify potential areas for mangrove propagation worldwide based on tidal level variations.

A novel framework for vegetation change characterization from time series landsat images

Understanding terrestrial ecosystem dynamics requires a comprehensive examination of vegetation changes. Remote sensing technology has been established as an effective approach to reconstructing vegetation change history, investigating change properties, and evaluating the ecological effects. However, current remote sensing techniques are primarily focused on break detection but ignore long-term trend analysis. In this study, we proposed a novel framework based on a change detection algorithm and a trend analysis method that could integrate both short-term disturbance detection and long-term trends to comprehensively assess vegetation change. With this framework, we characterized the vegetation changes in Zhejiang Province from 1990 to 2020 using Landsat and landcover data. Benefiting from combining break detection and long-term trend analysis, the framework showcased its capability of capturing a variety of dynamics and trends of vegetation. The results show that the vegetation was browning in the plains while greening in the mountains, and the overall vegetation was gradually greening during the study period. By comparison, detected vegetation disturbances covered 57.71% of the province's land areas (accounting for 66.92% of the vegetated region) which were mainly distributed around the built-up areas, and most disturbances (94%) occurred in forest and cropland. There were two peak timings in the frequency of vegetation disturbances: around 2003 and around 2014, and the proportions of more than twice disturbances in a single location were low. The results illustrate that this framework is promising for the characterization of regional vegetation growth, including long-term trends and short-term features. The proposed framework enlightens a new direction for the continuous monitoring of vegetation dynamics.

Dynamic characteristics of microplastics under tidal influence and potential indirect monitoring methods

Rivers are an important channel for the transport of microplastics from inland areas to the ocean. It is of great significance to explore the dynamic changes in microplastic pollution characteristics under tidal fluctuations to understand the exchange of microplastics between rivers and oceans. In this study, the occurrence of microplastics in typical tidal channels in the lower reaches of the Dong River was investigated during the wet and dry weather seasons, and high frequency continuous dynamic monitoring of microplastics was carried out in a typical tidal cross section during a tidal cycle. The abundances of microplastics during wet and dry weather seasons were 3.97–102.87 ± 28.63 item/m3 and 5.43–56.43 ± 14.32 item/m3, respectively. The microplastics generally exhibited a fluctuating growth pattern, with low contents in the upstream area and high contents in the downstream area, and the abundance of microplastics differed greatly in the different functional zones. The dynamic monitoring results showed that the abundance of microplastics was clearly affected by the tides, in that it increased during the flood tide and decreased during the ebb tide, with abundances ranging from 11.15 to 95.26 item/m3. In addition, there was a significant linear relationship between the abundance of microplastics and flow in the typical tidal cross section. The relationship between the response of microplastic pollution characteristics and tides combined with local hydrometeorological factors may be a potentially effective real-time monitoring method for assessing microplastic pollution indirectly.

Application of FY-4B Geostationary Meteorological Satellite in Grassland Fire Dynamic Monitoring

In this study, the channel data related to fire point identification of Advanced Geostationary Radiation Imager on Fengyun-4B (FY-4B/AGRI) and Advanced Meteorological Imager on GEO-KOMPSAT 2A (GK-2A/AMI) were cross-compared. A total of 267 sampling points in China (Guangdong, Guangxi, Guizhou, Yunnan, Hainan) were selected to carry out fine positioning correction on the data in different elevation intervals. Then, a fire monitoring algorithm based on FY-4B was proposed, in which the self-adaptive threshold adjustment of the underlying surface parameters and the reprocessing module of fire point identification were added. The algorithm can realize the high-precision and stable monitoring of fire. The continuous dynamic monitoring was carried out using the grassland fire Mongolia from April 18 to 20, 2022 as an example. The results showed that the parameters of FY-4B/AGRI and GK2A/AMI channels have high consistency. The root mean square error (RMSE) of reflection channel was 1.33%, and the maximum RMSE of brightness temperature channel was less than 1.3 Kelvin (K). Through the positioning analysis in different elevation intervals, the average longitude offset of FY-4B satellite data was -0.5°–0° and the average latitude offset was -0.9°–0.6°. Overall, these findings indicate that the high-frequency observations of FY-4B can be fully utilized to monitor forest and grassland fires, which can continuously track the dynamic evolution of fire and can distinguish the spatial distribution of different fire intensities in large-scale fire field.