East Monsoon Research Articles

Trajectory of microplastic particles with 2-dimensional hydrodynamic modelling approach at Pekalongan waters, Central Java, Indonesia.

This research aims to understand the extent of microplastic contamination in Pekalongan waters, Central Java, and its potential impact on fishing grounds, aligning with Indonesia's National Action Plan for Handling Marine Debris 2018-2025. The study employs a 2D hydrodynamics modelling approach with Mike 21 Software to map the spatial distribution of microplastic movement concerning fishing areas during the west and east monsoon seasons. The results showed that microplastic particles follow tidal currents in Pekalongan waters, with their movement influenced by factors such as current, wind, and tidal conditions. The trajectory of microplastics entering fishing ground areas poses potential contamination risk for fish caught by fishermen, threatening the health of marine ecosystems and the stability of their structure and function.

Characteristics and Distribution of Chemical-Biological Parameters in The Seawaters of Eastern Java Sea

The Java Sea is influenced by the west and east monsoons, which have an impact on hydrodynamic processes and chemical-biological water quality. Chemical-biological parameters play an important role in the food chain cycle that occurs in these waters. The quality of the eastern Java Sea waters is still limited by chemical-biological parameters, so the characteristics and distribution of these waters can be comprehensively known. chemical-biological. This study aimed to analyze the characteristics and distribution of nitrate, phosphate, oxygen, chlorophyll-A, and NPP parameters in the eastern Java Sea waters. This study used secondary data with daily temporal resolution from January to December 2020. Spatial analysis uses the climatological averaging method for 6 months as a statistical representative of the west monsoon and east monsoon. For each parameter, a vertical analysis was conducted to compare parameter values between the coastal waters of Tuban, Java Sea, and Banjarmasin Waters. Correlation analysis between parameters was conducted using the Pearson correlation method. Nitrate, phosphate, oxygen, chlorophyll-A, and NPP concentrations have temporal and spatial variability. Monsoon factors in Indonesia have a strong influence on the variability of nitrate, phosphate, oxygen, chlorophyll- A, and NPP concentrations. During the east monsoon, the concentration of chemical-biological parameters decreases, while in the west monsoon, the concentration increases and reaches its highest value. Generally, high concentrations occur in the northern and southern parts of the study site, around the coastal areas of Java and Kalimantan. Key Word: Chemical-Biological Parameters, Java Sea, Tuban Waters

Detection Of The Thermal Front Using The Cayula-Cornillon Alghorithm: A Case Study Of The State Fisheries Management Area 713, Indonesia

Thermal fronts are pivotal in shaping the marine ecosystem, influencing the presence and distribution of marine species. This study delves into the fluctuating patterns of thermal fronts in Indonesian waters, specifically focusing on the State Fisheries Management Area of the Republic of Indonesia, known as WPPNRI, 713. We identified the distribution and frequency of thermal fronts across different monsoon seasons. Utilizing the extended Cayula Cornillon Algorithm – Single Image Edge Detection (CCA-SIED), we deploy a precise methodology for detecting these fronts, relying on sea surface temperature (SST) gradients to identify specific periods and regions. Our analysis encompasses extensive satellite data collected from Moderate Resolution Imaging Spectroradiometer (MODIS) level 3. Our findings unveil distinct seasonal variations, with a decrease in thermal fronts during the west monsoon and a surge during the east monsoon. Moreover, we identify regional disparities, with denser thermal fronts observed in the southern and middle regions compared to the northern areas. Furthermore, our study underscores the critical need to integrate oceanographic data with fisheries management strategies to address the impacts of climate variability on marine resources. The observed relationships between thermal fronts, nutrient distribution, and fish migration emphasize the necessity for ongoing, localized monitoring to develop adaptive management solutions. This research marks a significant step in characterizing thermal fronts in WPPNRI 713, laying the groundwork for future investigations into other ecologically significant fronts, including those related to chlorophyll, salinity, and nutrients, thereby enhancing our understanding of marine ecosystem dynamics.Keywords: Cayula Cornillon; Fishing Zone; Marine Ecosystem; Sea Surface Temperature; Thermal Fronts

The impact of weather Condition Changes on Vertical Distribution of Sulfides in Lake Maninjau Based on Observation Data

Sulfide is a crucial parameter in volcanic lakes, as its levels and fluctuations in the lake determine the origin of sulfide and the extent of its impact on the lake ecosystem. In stratified lakes, the sulfide produced tends to be retained beneath the oxic layer. The sulfides rise towards the surface as the oxic layer thins triggered by decreased water column thermal stratification. Meanwhile, the strength or weakness of thermal stratification is greatly influenced by weather conditions. Lake Maninjau is a volcanic lake with a relatively high sulfide content. Its vertical distribution in the water column is highly dependent on the stratification of the water column. When stratification disappears, sulfide rises to the surface (locally known as tubo belerang) and has a negative impact on surface biota. The objective of this study is to examine the distribution of sulfides in the water column of Lake Maninjau under two different weather conditions. We perform two surveys to measure physicochemical parameters and sulfide concentration on 26‒29 November 2022 and 25‒26 August 2023 considering the seasonal pattern. We found that air temperatures and sunshine duration combined with precipitation and wind speed drive the thermal stratification of the water column. The lower air temperature, shorter sunshine duration, higher precipitation, and stronger wind speed in the first survey (west monsoon) compared with the second survey (east monsoon) resulted in lower stratification and triggered the elevated sulfide to the surface. In the middle of the lake, the surface sulfide measured during the first survey was 4.16 µg/L. Meanwhile, in the second survey, it was only observed at 1.16 µg/L. The distribution of sulfides within the water column of Lake Maninjau is regulated by the stratification of the water column, a process directly impacted by weather conditions.

Analysis of Spatial Differentiation of NDVI and Climate Factors on the Upper Limit of Montane Deciduous Broad-Leaved Forests in the East Monsoon Region of China

The vertical transition zone of mountain vegetation is characterized by high species diversity, and the width of the transition zone may serve as an indirect indicator of climate change. However, research into the differential characteristics of vegetation response to climate changes at the boundary of vertical transition zones has been limited. This study employs MODIS and climate data spanning 2001 to 2018 to investigate spatiotemporal trends in precipitation (PRE), temperature (TMP), radiation (RAD), and Normalized Difference Vegetation Index (NDVI) across nine montane deciduous broad-leaved forests in the eastern monsoon region of China. It explores the time-lag and -accumulation effects of climatic variables on NDVI, quantifying their relative contributions to both its short-term and interannual variations. Results show that, notably, with the Qinling-Daba Mountains as a demarcation, northern regions exhibit significant increases in RAD (0.874–2.047 W m−2/a), whereas southern regions demonstrate notable rises in TMP (0.59–0.73 °C/10a). Areas of lower annual PRE correspond to the most rapid increases in annual average NDVI (5.045 × 10−3/a). NDVI’s lag time and cumulative duration responses to TMP are the shortest (0 and 2~4 periods), while its correlation with RAD is the strongest (0.815–0.975), generally decreasing from higher to lower latitudes. TMP significantly affects NDVI variations, impacting both short-term and interannual trends, with PRE driving short-term fluctuations and RAD dictating long-term shifts. This research provides critical data and a theoretical framework that enhances our understanding of how regional vegetation’s vertical zonation responds to climate change, thereby making a substantial contribution to the study of mountain vegetation’s diverse adaptability to climatic variations.

Hazard estimation in urban home garden soils in an industrial area using microarthropods, soil properties and GIS modelling: an integrated approach.

The use of soil microarthropods as indicators of soil pollution in home gardens of an industrial area has been covered in this study. Soil samples were collected from 25 home gardens in three zones in Eloor during summer and North East monsoon from 2014 to 2018, for the study of soil microarthropods, soil properties, soil nutrients, and trace elements. The relationships among QBS-ar, microarthropod abundance, soil properties, and soil nutrients, were used to estimate the pollution hazard of the industrial area. The microarthropods present in the study area were Coleoptera, Hymenoptera, Diplopoda, and Araneae. A prominent study area feature was the absence of Collembola and Acari. The QBS-ar index score in these regions showed that the home gardens located adjacent to the industrial area showed low soil quality, with soil quality class values ranging from 1 to 2 throughout the study period. Discriminant analysis of soil nutrients with soil properties and microarthropod abundance showed that in Zone 1 and Zone 2, the data in 2018 was very well discriminated compared to other years. The hazard assessment in the Eloor region showed various levels of hazard zonation: Zone 1 with high-hazard and medium-hazard areas, Zone 2 with medium-hazard areas, and Zone 3 with low- and medium-hazard areas. The study is one of the first kinds that have used QBS-ar scores and soil properties along with soil nutrients and trace elements for estimating the level of hazard in home garden agroecosystems and thus points to an easy, simple, and practical approach in the monitoring and management of soil ecosystems.

Spatiotemporal Patterns and Environmental Drivers of Particulate Inorganic Carbon (PIC) Variability in the Southern Waters of Sumatra‐Java Islands

AbstractThe southern waters of the Sumatra‐Java Islands, within the Indo‐Pacific Warm Pool, are highly susceptible to global climate change impacts. Understanding particulate inorganic carbon (PIC) dynamics and environmental responses in this region is critical for assessing climate change effects on marine ecosystems. Utilizing two decades of remote sensing PIC data (2003–2022), we identified five sub‐regions via K‐means clustering: the Sunda Strait, southern coastal/offshore waters of Sumatra Island, and southern coastal/offshore waters of Java Island. Self‐Organizing Map explored interannual PIC variations, while Generalized Additive Models delineated driving factors. In the Sunda Strait, PIC dynamics are influenced by water exchanges between the Indonesian Seas (ISs) and eastern Indian Ocean (EIO). Seasonally, PIC concentrations peak during the east monsoon (boreal summer); decreasing during positive Indian Ocean Dipole (+IOD) and El Niño events. Along the southern Sumatra, PIC variations positively correlate with rainfall and photosynthetically active radiation (PAR). Along the southern Sumatra, upwelling drives PIC variations, with higher concentrations during mature summer monsoon induced upwelling periods. PIC increases during +IOD and decreases during El Niño. Our study highlights the nexus between nutrients, physical factors (e.g., rainfall), and climatic events (e.g., El Niño) on PIC concentrations. Climate‐induced changes in oceanic physical processes modulate nutrient concentrations, thereby governing PIC variations. We propose a mechanistic model to elucidate PIC variations in upwelling areas. Findings suggest that prospective climate variability, encompassing alterations in climate events, rainfall, and temperature, may escalate PIC concentrations within the study area, advocating PIC as a forward‐looking climate change indicator.

IJCM_281A: Climatic Factors And Vector Indices In The Occurrence Of Dengue Fever Cases In Northern Kerala

Background: The number of dengue cases reported to WHO increased over 8-fold over the last two decades, from 505,430 cases in 2000, to over 2.4 million in 2010, and 5.2 million in 2019. The disease is now endemic in more than 128 countries with Asia representing ~70% of the global burden of disease. The transmission of dengue is dependent on various environmental factors and socio-demographic and economic factors. This study aimed to describe the climatic factors and vector Indices in the occurrence of dengue fever cases in Northern Kerala. Objectives: 1) To describe the epidemiological factors for occurrence of dengue cases in Northern Kerala. 2) Serological typing of Dengue confirmed cases admitted in a tertiary care Centre in Northern Kerala. Methodology: Data of dengue fever cases admitted to a tertiary care centre in Northern Kerala for a period of one year were collected from Regional Prevention of Epidemics and Infectious Diseases Cell (R-PEID CELL). Vector indices data obtained from District vector control unit. Serology details were collected from Microbiology lab of the tertiary centre and Regional Virus Research and Diagnostic Laboratory (RVRDL). Geographical mapping and analysis of occurrence of dengue cases with rainfall done. Results: Total 518 cases were admitted to the tertiary centre during January 23-October 23. 68% Male and 32% female.77.7% Cases were reported from Kozhikode district.25 % cases were belonging to age group 20-29. Admission of cases were more during October followed by August. Serological typing of sub sample showed DEN2 as the predominant serotype. DEN1 and DEN3 serotypes were also identified. Conclusion: There is increased case transmission occurred during rainy season i.e. in North East and South West Monsoon which is in accordance with district vector indices data. DEN2 was the predominant serotype followed by DEN1.

Estimation of Suspended Particulate Matter Using Landsat 9 Imagery: Generating Algorithms and Spatio-Temporal Distributions

The fluctuation of suspended particulate matter (SPM) is essential to the biogeochemical cycle and ecological health of coastal waters. Anthropogenic activities potentially trigger an increase in SPM, so it needs to be monitored continuously. Spatial and temporal monitoring of SPM can be carried out cost-effectively with broad coverage using a remote sensing application. This study aims to build the SPM algorithm and estimate its temporal variability. The algorithm model in this study is based on an empirical formula between field data and reflectance data with the same acquisition. Water samples were taken from 100 stations in July 2022. Half were used for model building and the other for model validation. Suspended Particulate Matter was determined gravimetrically and estimated their temporal variability was based on Landsat 9 image records from December 2021 - November 2022. The results of the analysis show that the best algorithm for SPM estimation can be built based on coastal aerosol canals (B1), blue canals (B2), and green canals (B3) with the accuracy test result of (R2 = 0.68; RMSE = 5.551 mg.L-1; MAPE= 7.07%; Bias= 0.28). The SPM temporal fluctuations were generally higher in the west monsoon and lowered in the east monsoon, ranging from 30 to 70 mg.L-1. On the other hand, the spatial distribution shows a higher magnitude in the estuary than in the offshore waters, with a deviation of about 30 mg.L-1. Regional authorities can use the results obtained to improve the management of coastal water quality and monitoring systems.

CHIRPS rainfall product application for analyzing rainfall concentration and seasonality in Johor river basin, Malaysia

It is crucial to carry out a spatiotemporal evaluation of rainfall concentration in the Johor river basin (JRB) given that erratic rainfall can lead to floods. The study utilized the CHIRPS rainfall dataset from 1983 to 2018 to determine rainfall concentration using the Concentration Index (CI). To further define the rainfall regime, the Seasonality Index (SI) and Precipitation Concentration Index (PCI) were examined. The Mann-Kendall (MK) test was utilized to examine the trend at a 95% level of significance. The results showed the better accuracy of SI than PCI in classifying the rainfall regime in the JRB, defined as “equable but with a definite wetter season” type. The CI values ranged from 0.61 to 0.72 and were typically high all over the basin, with the northwestern and western regions having the highest values. At 27 grid points on the eastern border of the upper and middle parts of the basin, CI has significantly increased as a result of an upsurge in rainfall concentration brought on by climate change. More than 67% and up to 83% of the yearly rainfall for all grid locations was accounted for by the North East monsoon (NEM), with the 25% wettest days caused by high-intensity rainfall events.

A Short-Term Autoregressive Model for the Prediction of Daily Average NO2 Concentration in Nagercoil, Tamil Nadu, India

Nitrogen dioxide (NO2) is one of the pollutants that can cause potential damage to the ecosystem. NO2 emitted from vehicles forms the primary precursor for ground-level ozone. In this study, an analysis of the daily average of NO2 concentration with meteorology measured for two years 2021 and 2022 is being carried out. It is evident from the analysis that NO2 concentration followed an apparent diurnal pattern with a maximum value in the morning hours and a minimum during the afternoon hours. Summer months recorded the highest, and North East Monsoon (NEM) recorded the lowest values of NO2. A statistically significant positive correlation was found between NO2 and Temperature. An autoregressive model was formulated to forecast the daily average values of NO2 concentration. Unit root test was performed to check the stationarity of the data points, which is important in determining trends and seasonal changes. From the model procedure, the order that best fits the data was identified as AR (4), in which the process has the current value based on the previous three values. The Akaike Information Criterion (AIC) and Schwartz Criterion (SC), which are estimators of prediction error for AR (4), are low. The Jarque confirmed the normal distribution-Bera test, which again approves the satisfactoriness of the model.

Evaluation of Historic Trends for Monthly, Seasonal, and Annual Rainfall Series of Tenkasi, Tamil Nadu, India

Analyzing the variability and trends of rainfall plays a major role in water resource planning and management. Changes in rainfall patterns significantly influence the water availability in the irrigation structures and agronomical practices of crops. This study aimed to investigate the trends and estimate the magnitudes of monthly, seasonal, and annual rainfall series in Tenkasi, Tamil Nadu, India, using 49 years of rainfall data from 1971 to 2019. Sen’s Innovative trend analysis (ITA) method, Mann-Kendall (MK), and Simple Linear Regression (SLR) test were applied to assess the trends at 5 and 10 % significance levels. Trend magnitudes were estimated by Sen’s slope estimator (SSE) and SLR method. Changes in rainfall magnitude with mean values in percentage were estimated for all three slope estimation methods. The results revealed that the ITA method detected more significant trends of rainfall series over other methods. Significant downward trends were exhibited by October and north east monsoon (NEM) rainfall series had a trend magnitude of -0.43 mm/year and -0.04 mm/year. The percentage change in magnitude of the trend from mean values for October and the NEM series was -11.5% and -0.39%. Sub-trends within the October and NEM rainfall series showed that the low rainfall sub-series exhibited no trend, medium and high rainfall sub-series showed a downward trend. This study concluded that, in comparison to traditional trend analysis methods, the ITA method demonstrated a more rigorous investigation of trends. The significant decrease in rainfall during the NEM necessitates greater attention to water resources planning and management, serving as valuable scientific information for both crop planning and water resource management.

Operational Assessment of High Resolution Weather Radar Based Precipitation Nowcasting System

North East Monsoon (NEM) is the major source of rainfall for the south-eastern parts of peninsular India. Short time rainfall prediction data (i.e., nowcasting) are based on the observations from Doppler weather radars which has a high spatial and temporal resolution. This study focuses on the short-term ensemble prediction system using weather radar data to predict precipitation during the NEM and is the first of its kind in the Indian region to make an assessment of the operational performance of the prediction system. Six rainfall events have been studied for the assessment of short-term prediction system where the precipitation systems are different and include a tropical storm observed over different days during the 2022 NEM season. To assess the performance of the system, Fractional Skill Scores (FSS) at a 1 km window have been computed for a lead time of 0–2 h for all the rainfall events with more than 750 samples using different optical flow methods and ensemble sizes. The best average skill score and maximum skill score obtained at a 2 h lead time is 0.65 and 0.78 for tropical storms, 0.5 and 0.78 for stratiform and 0.15 and 0.38 for convective precipitation. It has found that the performance of the model is best for precipitation systems that are widespread and have a longer life period.

The effect of intake channel length on water temperature at the intake point of the power plant at Muara Karang power plant

Muara Karang Power Plant (MKPP) is one of the main power plants on Java Island in Indonesia. Presently, the Jakarta provincial government has issued a reclamation project on Island G in the marine waters around MKPP. This reclamation effort is predicted to lead to a rise in the seawater temperature around the intake, which MKPP will address with the addition of intake channel of 250 - 957 m. Therefore, this study aimed to determine the effect of intake channel extension on the water temperature at the intake point using numerical modeling comprising hydrodynamics and dispersion advection modules. A total of 10 scenarios were modeled by varying intake channel length and season. The result showed that adding intake channel was less effective because the average water temperature was less than 0.24oC with an effectiveness below 0.78%. Based on the validation of the modeling results on the measurement data, the NRMSD values in west and east seasons were 9.13% and 12.63%, respectively. Under existing conditions, the average and maximum seawater temperatures were 31.40oC and 32.08oC. Meanwhile, by extending intake channel, the average and maximum water temperatures were 31.16oC and 31.60oC. These results showed that by extending intake channel, the temperature at the intake point was generally lower than the existing conditions. Intake channel length was more effective in reducing the temperature at the intake point during west monsoon than east monsoon. Vertically, the temperature at the bottom was relatively colder than near the surface. In west monsoon, the average temperature difference between the bottom and the surface ranged from 0.16-0.21oC, while in east, it was between 0.23 and 0.50oC. In conclusion, the addition of subsequent structures to increase effectiveness was necessary, specifically to hold hot water in east monsoon.

The study of phytoplankton in the Banggai Deep Sea: The study case of Banggai Upwelling Dynamics and Ecosystem Experiment (BUDEE)

The upwelling process in the Banggai deep-sea water occurs yearly during the east monsoon. The upwelling process is characterized by low surface water temperatures compared to the surrounding waters, high nutrient values of phosphate, nitrate, and silicate, and high values of primary productivity. The aim of this research was to determine the types of phytoplankton that are abundant in the Banggai deep-sea waters during the upwelling process. Phytoplankton sampling was conducted at 36 stations using a phytoplankton net from a depth of 150 m to the water surface. The mesh size of the phytoplankton net was 80 µm with a net length of 100 cm. Phytoplankton samples were preserved using 4% formalin. Based on the research results, the highest total abundance of phytoplankton was found at station 13 (315.457 cells.m-3), followed by stations 20 (234.746 cells.m-3), 26 (213.865 cells.m-3), station 14 (202.371 cells.m-3), station 18 (196.983 cells.m-3) and station 46 (187397 cells.m-3). Meanwhile, the other stations had an abundance of <150,000 cells/m3. The highest abundance at station 13 was dominated by the genera Bellerochea (64.068 cells.m-3), Chaetoceros (42.407 cells.m-3) and Nitzschia (35.390 cells.m-3). The high abundance of phytoplankton at Station 13 was due to upwelling.

Modelling of ocean currents and distribution of total suspended solids in Citarum River estuary

The Citarum River is an important river in West Java, which empties into the Java Sea carrying large suspended sediment concentrations. The purpose of this study is to examine the interaction of current patterns and distribution of total suspended solids (TSS) in the Northwest and Southeast Monsoons using hydrodynamic Modelling. The flow model and TSS used were 2-dimensional models with the OpenFlows FLOOD software. The ocean tide model results were validated using the Root Mean Square Error (RMSE) method with a value of 0.10. The current velocity in the West and East monsoons ranges from 0.07 - 0.35 m/s. Currents flow north and northeast during high-tide conditions and move south and southwest during low-tide conditions in both seasons. The movement of TSS was influenced by the current patterns. The highest concentration of TSS is in the Northwest Monsoon at low tide, which was in the range of 560–575 mg/L. The lowest TSS concentration was in the Southeast Monsoon during high tide conditions, ranging from 80 to 120 mg/L. The high concentration of TSS in the Northwest Monsoon was influenced by higher rainfall, with an average in January and only 23.2 mm/day while in the Southeast Monsoon it is only 7.8 mm/day.

Application of relative importance metrics for CMIP6 models selection in projecting basin-scale rainfall over Johor River basin, Malaysia

The most recent set of General Circulation Models (GCMs) derived from the Coupled Model Intercomparison Project Phase 6 (CMIP6) was used in this work to analyse the spatiotemporal patterns of future rainfall distribution across the Johor River Basin (JRB) in Malaysia. A group of 23 GCMs were chosen for comparative assessment in simulating basin-scale rainfall based on daily rainfall from the historical period of the Climate Hazards Group InfraRed Precipitation with Station Data (CHIRPS). The methodological novelty of this study lies in the application of relative importance metrics (RIM) to rank and select historical GCM simulations for reproducing rainfall at 109 CHIRPS grid points within the JRB. In order to choose the top GCMs, the rankings given by RIM were aggregated using the compromise programming index (CPI) and Jenks optimised classification (JOC). It was found that ACCESS-ESM1–5 and CMCC-ESM2 were ranked the highest in most of the grid. The final GCM was then bias-corrected using the linear scaling method before being ensemble based on the Bayesian model averaging (BMA) technique. The spatiotemporal assessment of the ensemble model for the different months over the near-future period 2021–2060 and far-future period 2061–2100 was compared with those under Shared Socioeconomic Pathways (SSPs), namely, SSP1-2.6, SSP2-4.5, SSP3–7.0, and SSP5-8.5. Heterogeneous changes in rainfall were projected across the JRB, with both increasing and decreasing trends. In the near-future and far-future scenarios, higher rainfall was projected for December, indicating an elevated risk of flooding during the end of the North East monsoon (NEM). Conversely, August showed a decreasing trend in rainfall, implying an increasing risk of severe drought. The findings of this study provide valuable insights for effective water resource management and climate change adaptation in the region.

The Characteristics Of The Mixed Layer Depth During La Niña, El Niño, And Normal Years In The North Natuna Sea

The Natuna Sea is one of the seas located in the northern part of Indonesia, which is influenced by several oceanographic climate phenomena, including the El Nino-Southern Oscillation (ENSO) system, such as La Nina and El Nino, which cause vertical temperature dynamics. This study aims to examine the relationship between La Nina, El Nino, and normal years on the variability of the mixed layer depth in the Natuna Sea. The study utilizes temperature data from the World Ocean Database (WOD) and Marine Copernicus for a period of 3 years, including years with La Nina, El Nino, and normal conditions, as well as mixed layer depth (defined by sigma theta) data from Marine Copernicus. The occurrence of La Nina, El Nino, and normal years is obtained from the Southern Oscillation Index (SOI). The research findings indicate a correlation between the SOI values and the Maximum Mixed Layer Depth (MLD) during weak and very weak El Nino and La Nina conditions, while the correlation is weak during normal years. During the La Nina, normal, and El Nino periods, the deepest MLD occurs during the west monsoon season at depths ranging from 7 to 60 meters. The shallowest MLD occurs during the first transition season at depths ranging from 7 to 25 meters. The MLD values during the east monsoon season range from 7 to 43 meters, and during the second transition season, the MLD ranges from 7 to 44 meters.

Diversity of Platygastroidea Species in Coffee Ecosystem at Thadiyankudisai, Tamil Nadu

During a one-year study from January, 2018 to January, 2019 at the Horticultural Research Station, Thadiyankudisai, Tamil Nadu, a combined count of 550 individuals of Platygastroidea species were documented under two family platygastridae (1 species) and scelionidae (9 species). Among the species diversity comprised of Telenomus sp. (52.0%) followed by Scelio sp. (11.4%), Calliscelio sp. (9.1%), Sparasion sp. (6.9%), Idris sp. (5.8%) and Baryconus sp. (4.0%). The least population was recorded in Tritelia sp. (2.2%). Researches on seasonal abundance exposed that the winter season exhibited the highest species population at 32.55%, with the South West Monsoon (SWM) following closely at 30.36%, while the North East Monsoon (NEM) period recorded the lowest species count at 16.54%. The prevalence of insect pests poses a significant challenge to achieving optimal yields in horticultural crops. Consequently, the examination of Platygastroidea species diversity assumes a pivotal role in the success of biological control strategies.

Seasonal comparison of catch abundance and size of blue swimming crab (Portunus pelagicus) in Rembang, Central Java

Considering the blue swimming crab (Portunus pelagicus) was exported as pasteurized crab meat, the quality of fresh meat (stock and size) could have been influenced by the season and needed to be considered. This study aimed to analyse the effect of the season on the crab’s abundance and size in Rembang Water, Central Java. The study period includes four seasons, namely west monsoon, first transition, east monsoon, and second transition from July 2021 to June 2022. The crab samples from the fishermen were analysed in term of the fishing trips, weight, and carapace width at the fishing ground location. Descriptive statistics and univariate one-way ANOVA was used to analyze the data. The average abundance, weight, and size of crabs caught in Rembang waters during the year were 1,8 kilograms per trip a day (one-day fishing). The abundance of crabs in the west monsoons was greater than in the east monsoons. The pattern of crabs caught was higher at the beginning of the west monsoon (December–January), then it decreased in February until the start of the first transition (March), then gradually increased in April before decreasing again in June until the end of the second transition (October). The ANOVA test showed that the size of crabs in every season had significant differences. It was clearly shown on the boxplot that the catch in the west monsoon and the first transition was smaller than the east monsoon and second transition. These results can provide insightful information for fishers, managers, and policy makers as a basis for developing sustainable fisheries management.