Condition Index Research Articles

Novel approach for forest road maintenance using smartphone sensor data and deep learning methods

ABSTRACT High costs primarily pose challenges to forest management in planning and executing the repair of forest roads. With budget limitations and inadequate oversight, it has become critically essential to monitor the state of these roads. Monitoring the condition of forest roads has become imperative, driven by budget constraints and a lack of effective supervision. While smartphones have proven effective in detecting road defects on public roads, their application on forest roads is hindered by the absence of suitable indices and software infrastructure. Addressing this gap, this research focuses on the development of the Forest Road Pavement Condition Index (FRPCI) to facilitate smartphone-based monitoring. We collected and compared data from 4 kilometers of forest roads, employing two traditional harvesting methods alongside smartphone sensor data. Utilizing deep learning methods, including Convolutional Neural Network (CNN), Long-Short Term Memory (LSTM), and CNN-LSTM, we processed the collected data. Signal processing using GPS data, coupled with wavelet transformation, demonstrated promising results with an accuracy and recall exceeding 80%. The proposed system functions as a distributed information system, transitioning data from organizational mode to field mode. It measures damage, assesses forest road conditions, and leverages image processing and GPS technologies. This monitoring system technology offers capabilities for preparing, storing, updating, maintaining, and analyzing diverse information. Importantly, adopting this method can significantly reduce operating costs, making forest road monitoring for maintenance purposes more feasible.

Recovery of the Seagrass Zostera noltei and Commercial Bivalve Populations After Shellfish Harvesting

Conservation efforts have raised awareness about the impact of small-scale fisheries on the distribution of seagrass plants. The patterns of recovery of the seagrass Zostera noltei and of the commercial bivalves Cerastoderma edule, Ruditapes decussatus and Ruditapes philippinarum after shellfish harvesting were studied in a field experiment in a shellfish bed in NW Spain. Sample plots were subjected to a single disturbance in two types of shellfish harvesting treatments in three zones characterized by different harvesting frequency and seagrass density. The photosynthetic efficiency (Fv/Fm), shoot density, leaf length and carbohydrate content of Z. noltei were monitored every three months during one year, and the C and N content of leaves and biomass of plants were measured one year after the disturbance. The abundance of adults, juveniles and recruits and the condition index of adult bivalves were quantified after the experimental harvesting. Shoot density and biomass of Z. noltei remained low during the ten months after the disturbance but recovered to control values after one year. Carbohydrate contents of apical rhizomes were lower in disturbed (treated) plots, whereas no effect was observed on Fv/Fm. Denser and more complex seagrass patches recovered faster. The abundance of adult bivalves below commercial size was lower in the disturbed plots, while the abundance of adults of commercial size, juveniles and recruits did not vary, indicating that abundance and condition were not hampered by harvesting pressure. The findings also suggest that Z. noltei meadows can recover within one year of the impact of shellfish harvesting if the harvesting areas are rotated and dense patches are preserved.

Characteristics of life-cycle carbon dioxide emissions of arterial highway maintenance and the influencing factors

With the focus of highway development transitioning from construction to maintenance, a comprehensive understanding of the characteristics and influencing factors of carbon dioxide (CO2) emissions from highway maintenance activities is crucial for formulating effective strategies to promote the low-carbon development of road infrastructure. However, the quantitative relationships between CO2 emissions from highway maintenance schemes and factors such as pavement deterioration, traffic volume, and road grade remain unclear owing to a lack of comprehensive, multi-category, and real data. Using real maintenance data from 340 arterial highway segments in China, this study conducts the life cycle assessment (LCA) to estimate CO2 emissions from maintenance activities and examines the primary emission sources among various structural layers and materials. Furthermore, multiple linear regression (MLR) analysis is conducted to investigate the impact of traffic volume, road grade, and pavement deterioration on CO2 emissions from maintenance projects, and factors influencing the early-stage degradation of pavement performance. The results demonstrate that average CO2 emissions from heavy rehabilitation projects are 6.97 times higher than those from medium rehabilitation projects. Emissions from heavy rehabilitation projects exhibit a significantly negative linear relationship with the riding quality index (RQI) before maintenance (p < 0.05), and emissions from medium rehabilitation projects show a significant negative linear relationship with the pavement condition index (PCI) before maintenance (p < 0.05). Emissions from heavy and medium rehabilitation projects are significantly positively correlated with heavy vehicle traffic volume before maintenance (p < 0.05). Moreover, the early-stage degradation of PCI after heavy rehabilitation and RQI after medium rehabilitation exhibit significantly negative linear relationships with their respective indicators before maintenance (p < 0.05). The early-stage degradation of RQI after heavy rehabilitation is significantly positively correlated with CO2 emissions from the base course and cushion layers (p < 0.05). The findings emphasize that timely maintenance and reduction of CO2 emissions from asphalt mixing equipment are essential for mitigating emissions from road maintenance. This study offers valuable insights for advancing the low-carbon development of highways in temperate regions.

Anchovy and sardine condition and energy content in the North Aegean Sea (eastern Mediterranean) in relation to their contrasting reproductive strategies.

Forage species with high biomass, such as anchovies and sardines, play a key role in pelagic ecosystems and make up a significant proportion of the world's capture fisheries production. In recent years, condition indices have gained interest as significant indicators for assessing the effects of environmental and human pressures on these species and the quality of their habitats. In the present study, we examined, for the first time in the North Aegean Sea (eastern Mediterranean), the year-round variation in somatic and gonadal condition, energy density, and percentage of lipid content of anchovy (Engraulis encrasicolus) and sardine (Sardina pilchardus). Energy density was measured with bomb calorimetry and percentage lipid content with the fatmeter, a portable electronic device. Finally, the monthly changes in gonadal and energetic condition were examined in relation to the annual cycle of temperature and mesozooplankton biomass, simulated by the implementation of a coupled hydrodynamic-biogeochemical model (POM-ERSEM). There was a strong relationship between fish energy density (kJ g-1) and percentage dry weight. Furthermore, the mean monthly energy density and fatmeter measurements were strongly correlated, especially in sardine. Overall, the monthly changes in energetic condition were indicative of the species' different strategies for energy acquisition and allocation to reproduction (capital vs. income breeding): sardine exhibited low energy density and percentage lipid content during the winter spawning period (November-March) and markedly higher energetic condition from spring to autumn (April-October). Anchovy spawning period, as inferred from gonadal condition, lasted from April to September, i.e., during the warm period of the year but its energy density and percentage lipid content did not exhibit any seasonal changes and were markedly lower than in sardine from April to October. Finally, the simulated mesozooplankton biomass was higher from January to July, which corresponded to the second half of the spawning season for sardine, but first half of the spawning season for anchovy.

Airfield pavement performance prediction using Clustered Markov Chain Models

This study pairs unsupervised learning methods of clustering and classification with discrete-time Markov Chain models for airport pavement performance prediction, with the goal of allowing the clustering algorithm to take the place of typical pre-analysis grouping of pavement sections. The influences of cluster method, number of clusters, input years, interval time span, and training data on prediction results are analysed. Results indicate that clustering using the deterioration profiles of Pavement Condition Index (PCI) before applying the Markov Chain is sufficient to reduce the error by half in predicted pavement conditions for most cases. The initial pavement degradation is a reliable source for clustering and future condition prediction using the appropriately matched Markov Chain. This approach minimises the data required to predict pavement condition and proves the early deterioration rate of a pavement section can be used to predict its overall lifespan.

Annual gametogenic development of the Asiatic hard clam, Meretrix meretrix, collected from the west coast of Moheshkhali Island, Cox's Bazar, Bangladesh

AbstractWe investigated the annual gametogenic development of the Asiatic hard clam, Meretrix meretrix, collected from the west coast of Moheshkhali Island, Cox's Bazar, Bangladesh, by using biometry and histology through monthly sampling from July 2018 to June 2019. After biometric measurements, cross sections were cut for histology to determine the sex and gonadal maturity of the clams. Condition index (CI) showed two distinct peaks in July and December, which indicated that clams were ripe during these months, and a subsequent decrease in CI reflected spawning, which was consistent with histology. Our study revealed a biannual spawning cycle of the clams and gametogenesis starting in October and June. Spawning occurred from February to May and July to September. Maturity index (MI) showed two distinct peaks in July (3.50) and January (3.60) when most of the clams were in late developing or ripe stages. A gradual increase in temperature from annual minima in conjunction with decreasing salinity levels may trigger spawning in February, but spawning in July was initiated when salinity levels increased from annual minima. The data could be used by resource managers for the conservation of this commercial species and to time harvesting for the best quality clams without interrupting spawning activity.

Effects of blood extraction and ecophysiological experiments on stress in adult males of Liolaemus attenboroughi.

Stress during laboratory experiments can affect the outcomes of ecophysiological studies. The serum corticosterone concentration (CORT), the leukocyte profile, heterophil/lymphocyte ratio (H/L), and the presence of blood endoparasites were analyzed as a proxy of stress and immunological state in adult males of the lizard Liolaemus attenboroughi, endemic to Patagonia, Argentina. The results of the ecophysiological variables (preferred temperature, running speed, locomotor endurance, and body condition index, BCI) were analyzed in relation to stress indicators obtained from blood samples taken at three different times: at capture, and on the third and seventh days in the laboratory. Males at capture showed a high percentage of lymphocytes and heterophils and a low of basophils, monocytes, and eosinophils. Haemogregorina-type endoparasites have been recorded in the genus Liolaemus for the first time. The proportion of infected males remained stable during captivity; however, these males showed higher CORT levels, increased percentages of basophils, and decreased percentages of lymphocytes. There was a significant increment in CORT and H/L, and a decrease in BCI during laboratory experiments, compared with baseline values at capture. The performance was not related to the CORT or the repeated blood sampling. The BCI decreased, possibly due to energy reserve mobilization caused by acute stress. This study shows that blood extraction and ecophysiological experiments over 7 days have a minor effect on the stress indicators used.

Predicting bridge condition index using an improved back-propagation neural network

The predicted Bridge Condition Index (BCI) is a guiding indicator for formulating preventive maintenance strategies for bridges and is hardly available even if using the most advanced neural network prediction model, owing to the few measured BCIs and neural network model defects. In this paper, an improved Back-Propagation Neural Network (BPNN) model named CPSO-BP-MC is proposed to predict BCI, which has a BPNN as its core, combined with the Coordinated Particle Swarm Optimization (CPSO) algorithm aims to faster convergence and avoid local optimal solution even with less training sample, and the Markov Chain (MC) algorithm aims to further revise the fluctuation of CPSO-BP prediction output due to maintenance and reinforcement. A case study is presented to demonstrate the efficiency of CPSO-BP-MC predicting BCI with fewer training samples. Comparing the predicted BCI of CPSO-BP-MC with the measured BCI and other models, the results show that CPSO-BP-MC converges faster than other models, and can predict the BCI more stably and accurately, and the error between prediction and measured BCI is less than 3 %.

PaveSAM – segment anything for pavement distress

Automated pavement monitoring using computer vision can analyse pavement conditions more efficiently and accurately than manual methods. Accurate segmentation is essential for quantifying the severity and extent of pavement defects and consequently, the overall condition index used for prioritising maintenance activities. Deep-learning-based segmentation models are however, often supervised and require pixel-level annotations, which can be costly and time-consuming. While the recent evolution of zero-shot segmentation models can generate pixel-wise labels for unseen classes without any training data, they struggle with irregularities of cracks and textured pavement backgrounds. This research proposes a zero-shot segmentation model, PaveSAM, which can segment pavement distresses using bounding box prompts. By retraining SAM's mask decoder with just 180 images, pavement distress segmentation is revolutionised, enabling efficient distress segmentation using boundingbox prompts, a capability not found in current segmentation models. This drastically reduces labelling costs and establishing the pioneering use of SAM in pavement distress segmentation.

Effects of mussel-phytoplankton interactions on the aquatic environment

A five-day in situ experiment was conducted in plastic enclosures to investigate the effects of different densities of the mussel Mytilus edulis, and sampling time on water variables, and phytoplankton community structure in Sanggou Bay (Shandong, China). The tested mussel densities were low (LD300: 300 g/m3), medium (MD600: 600 g/m3), high (HD900: 900 g/m3), and sampling times were at 6:00 and 17:00 h. The water variables analyzed as indicators were pH, dissolved oxygen, nutrients, carbonate system, pCO2, and chlorophyll-a (Chl-a). The results showed that density and sampling time had highly significant effects on all water parameters and phytoplankton abundance, except for dissolved oxygen (P<0.01). At the same sampling time, pH, c[CO32-] and Chl-a concentrations in the water column of LD300 treatment were much higher than those of MD600 and HD900 treatments, while c[HCO3-], c[CO2] and pCO2 were significantly lower than those of MD600 and HD900 treatments (P<0.01). Phosphate was the main limiting nutrient for phytoplankton growth. Chl-a concentrations increased and then decreased significantly in LD300 and MD600 treatments, while it diminished continuously in HD900 treatment. The higher M. edulis density showed higher correlation with picophytoplankton abundance and Chl-a concentrations. Not only the phytoplankton structure was affected, but also the condition index of the HD900 treatment was significantly reduced (P<0.05). The present study showed LD300 and MD600 treatments significantly promoted the growth of picophytoplankton. The selective filtration of M. edulis for microphytoplankton and nanophytoplankton were much higher than those for picophytoplankton. The combined decrease in competitors (micro- and nanophytoplankton) led to a substantial increase of picophytoplankton abundance in shellfish farming areas. The interactions between mussel and phytoplankton significantly affected the water environment. However, well designed integrated shellfish and algae aquaculture might mitigate the adverse impacts.

Monitoring agricultural drought using different indices based on remote sensing data in the Brazilian biomes of Cerrado and Atlantic Forest.

Several remote sensing indices have been used to monitor droughts, mainly in semi-arid regions with limited coverage by meteorological stations. The objective of this study was to estimate and monitor agricultural drought conditions in the Jequitinhonha Valley region, located in the Brazilian biomes of the Cerrado and Atlantic Forest, from 2001 to 2021, using vegetation indices and the meteorological drought index from remote sensing data. Linear regression was applied to analyze drought trends and Pearson's correlation coefficient was applied to evaluate the relationship between vegetation indices and climatic conditions in agricultural areas using the Standardized Precipitation Index. The results revealed divergences in the occurrences of regional droughts, predominantly covering mild to moderate drought conditions. Analysis spatial of drought trends revealed a decreasing pattern, indicating an increase in drought in the Middle and Low Jequitinhonha sub-regions. On the other hand, a reduction in drought was observed in the High Jequitinhonha region. Notably, the Vegetation Condition Index demonstrated the most robust correlation with the Standardized Precipitation Index, with R values ​​greater than 0.5 in all subregions of the study area. This index showed a strong association with precipitation, proving its suitability for monitoring agricultural drought in heterogeneous areas and with different climatic attributes. The use of remote sensing technology made it possible to detect regional variations in the spatio-temporal patterns of drought in the Jequitinhonha Valley. This vision helps in the implementation of personalized strategies and public policies, taking into account the particularities of each area, in order to mitigate the negative impacts of drought on agricultural activities in the region.

A thematic review on the elements of facilities condition index (FCI) as facilities performance indicator

Purpose This paper aims to review the elements of facilities condition index (FCI) as one of the most widely used metrics for describing the physical condition of facilities and as a measure of financial indicator related to maintenance activity. This research will benefit future studies that focus on implementation of FCI and encourage the best practice when assessing the physical condition to evaluate the performance of facilities as well as to plan for maintenance action to be taken and financial implication involved based on the findings from FCI. Design/methodology/approach A total of 33 studies from 2012 to 2022 were identified and extracted from four academic databased, named Scopus, Google Scholar, Web of Science and Mendeley. These published studies were selected because it matches with the inclusion requirements for research question, “What are the elements of facilities condition index discussed in the literature from 2012 to 2022?”. To answer the research question, the studies in ATLAS.ti were grouped into five major themes based on the codes and categories found. Findings This paper presents the findings of a thematic analysis of the current literature discussed about FCI. A total of 33 studies from 2012 to 2022 were identified and extracted from four academic databased, named Scopus, Google Scholar, Web of Science and Mendeley. A themed review was conducted, and five themes were identified as elements of FCI, which are named as follows: “Condition Assessment”, “Deferred Maintenance”, “Facilities Performance”, “Financial and Fund Allocation” and “Decision Making”. Originality/value This paper fulfils the fundamental elements on current FCI practices as well as intended to highlight existing practices that are essential to evaluate facilities performance and planning for maintenance strategies.

Comparison of Juvenile Pacific Salmon abundance, distribution, and body condition between Western and Eastern Bering Sea using spatiotemporal models

Recent changes in climate have had generally negative impacts on salmon stocks in the eastern and positive effects in the western Bering Sea (WBS). Eastern Bering Sea (EBS) salmon stocks have periodically experienced reduced productivity, size, and survival, whereas salmon stocks in the western Bering Sea (WBS) have tended to be more stable, with some stocks increasing in abundance. This difference could be partially attributed to the different habitats that juvenile salmon occupy during their first marine year, which often determines recruitment. Here, we used salmon surveys in the EBS and WBS to compare the status of juveniles in these two large marine ecosystems. We applied spatio-temporal vector autoregressive spatio-temporal (VAST) models to adjust for differences in timing, vessels and trawl gear used, and to compare the relative abundance and body condition indices (length, weight, and Fulton's condition factor) of three juvenile salmon species pink, chum and sockeye salmon (Oncorhynchus gorbuscha, O. keta, and O.nerka respectively) between the WBS and EBS from 2002 to 2022. Juvenile salmon in WBS exhibited a consistent trend of larger size and higher Fulton's condition factor, with greater abundance compared to EBS in even years. A clear even-odd year pattern, which is believed to be driven by pink salmon, occurred in all species’ relative abundance and body condition in the WBS, with a limited impact of interannual temperature changes. Conversely, temperature had a significant impact on EBS salmon, with much of the variation in relative abundance and body condition occurring between warm and cold periods, and even/odd patterns were found only in pink salmon relative abundance and body condition. We detected different WBS-EBS migration patterns, with EBS juveniles dispersing from nearshore habitats earlier than WBS juveniles but migrating offshore later that is connected to bathymetry and the broad shelf in the EBS.

A case study on microlitter and chemical contaminants: Assessing biological effects in the southern coast of the Gulf of Finland (Baltic sea) using the mussel Mytilus trossulus as a bioindicator

Chemical and microlitter (ML) pollution in three Estonian coastal areas (Baltic Sea) was investigated using mussels (Mytilus trossulus). Polycyclic aromatic hydrocarbons (PAH) in mussel tissues were observed in moderate levels with high bioaccumulation factors for the more hydrophilic and low molecular weight PAH (LMW PAH), namely anthracene and fluorene. Tissue concentrations of polybrominated diphenyl ethers (PBDE) and cadmium within mussel populations exceeded the Good Environmental Status thresholds by more than 200% and 60%, respectively. Multiple contamination at the Muuga Harbour site by tributyltin, high molecular weight PAH, including the highly toxic benzo[c]fluorene and PBDE, coincided with the inhibition of acetylcholinesterase activity and a lower condition index of the mussels. The metabolization and removal of bioaccumulated LMW PAH, reflected in the dominance of oxy-PAH such as anthracene-9,10-dione, is likely associated with the increased activity of glutathione S-transferase in caged mussels. Only a few microplastic particles were observed among the ML in mussel tissues, with coloured cellulose-based microfibers being the most prevalent. The average concentration of ML in mussels was significantly higher at the harbour area than at other sites. The integrated biomarker response index values allowed for the differentiation of pollution levels across studied locations representing high, intermediate, and low pollution levels within the studied area.

Assessing Multifaceted Effects of Speed Humps and Bumps: Travel Time, Safety, and Environmental Considerations

This study focuses on investigating the significant impacts of speed breakers on various parameters, including travel time delays, vehicle speeds, fuel consumption, pavement maintenance costs, and vehicular exhaust emissions. Field data was collected and analyzed to assess the effects of different types of traffic calming measures on these parameters. The findings provide valuable insights into the implications of speed breakers on road safety, environmental pollution, and overall road infrastructure management. The results reveal that the implementation of speed humps, speed bumps, and triple bumps effectively slows down vehicles, as evidenced by considerable reductions in the 85th percentile speeds. The reduction percentages were 41.65% for speed humps, 73.52% for speed bumps, and 86.27% for triple bumps. This indicates the effectiveness of these traffic calming measures in improving road safety by reducing vehicle speeds. However, the presence of speed breakers also leads to increased travel time delays. On average, traversing stretches with speed humps, speed bumps, and triple bumps resulted in delays of 9.31, 16.42, and 29.51 seconds, respectively. While the individual delay times may appear relatively short, the cumulative effect of multiple speed obstacles along a road needs to be considered. Another significant impact observed is the increased fuel consumption associated with speed breakers. The study found that for every 100 km of travel, motorcycles and passenger cars consumed approximately 12.07 km and 27.37 km of additional fuel, respectively, when the density of speed breakers was 1.33/km. This translates to a fuel consumption increase of 13.73% for motorcycles and 37.74% for passenger cars. Furthermore, the presence of speed humps was found to contribute to pavement deterioration, as indicated by decreased Pavement Condition Index (PCI) values. The study also revealed that sections with speed humps incurred significantly higher maintenance costs compared to sections without speed humps. The increase in maintenance cost ranged from 100 to 264% across different road sections, with higher traffic volumes leading to greater cost escalation. Additionally, the study confirms that lower vehicle speeds, particularly between 0-15 km/hr, are associated with higher emissions of pollutants, including carbon monoxide (CO) and other pollutants. This highlights the environmental implications of speed breakers and their contribution to urban air pollution. Doi: 10.28991/CEJ-2024-010-07-07 Full Text: PDF

Bibliometric Analysis Of Flexural Pavement Road Damage On Airport-Port Main Corridor Roads Using The Pavement Condition Index (PCI) Method

Bibliometric analysis of the use of PCI methods on roads, main corridors, airports and ports is a network of research from around the world on related topics. The main objective of this study is to see trends that continue to develop in various points of view. By capturing various studies from 2000 to 2023 using Crossref sources, 1000 studies with related topics were produced. This research accompaniment uses the help of Publish or Perish, which is then processed in the VOSviewer application with the Research Information Systems (RIS) format. There is a reasonably broad relationship in research keywords produced with the dominance of rigid pavement keywords (299 studies), pavement condition index (112 studies), road damage (79 studies), rehabilitation (63 studies), and other keywords with different number variations. The results of the conclusion data regarding the development of research on pavement condition index continue to increase continuously, with the highest number in 2022 (86 studies).

Assessing the Impact of Heatwaves on Wheat Crop Health in Ludhiana District Using Remote Sensing Technologies

Climate change is becoming one of the major constraints for agricultural production. Impact on the crop yield due to unseasonal rain, hailstorms, and sudden temperature rise is becoming more frequent. The study assesses the damage done by the heat wave in the Ludhiana district of Punjab in the year 2021-22. Satellite datasets have been used named Sentinel-2 and MODIS datasets. By using the Sentinel-2 Images crop discrimination was performed and wheat crop mask was generated for the year 2018-19 to 2021-22. A comparison of the Normalized Difference Vegetation Index (NDVI) was performed for the study period. MODIS dataset was used to calculate the Temperature Condition Index (TCI) and Temperature Stress Index, which reflects the effect of the heat wave that happened in March 2022. APY (Area, Production, Yield) and data on the procurement of wheat for the year 2021-22 and normal years were compared to visualize the impact of heat wave on the various market dynamics such as production, productivity, etc.

A dataset of annual TCI, VCI, VHI and TVDI with the resolution of 1 km in the Yellow River Basin (2003–2022)

Primarily situated in arid and semi-arid climatic zones, characterized by naturally limited water resources, the Yellow River Basin is the most drought-affected among China's major basins. As global environmental and climate change continue to evolve, droughts in the Yellow River Basin have become increasingly frequent, making drought monitoring research a current focal point. Based on MODIS vegetation data and surface temperature products, this dataset undergoes quality control procedures such as cloud removal and data reconstruction to collect the data of annual Temperature Condition Index (TCI), Vegetation Condition Index (VCI), Vegetation Health Index (VHI) and Temperature Vegetation Dryness Index (TVDI) in the Yellow River Basin from 2003 to 2022. The spatial scope of this dataset ranges from 32°10′N–41°50′N，95°53′E–119°05′E. The dataset is in GeoTiff format with a spatial resolution of 1km. It can provide foundational data and scientific support for drought disaster monitoring in the Yellow River Basin.

Effect of selected environmental factors on the growth and survivability of the larvae of the Chinese sleeper Perccottus glenii Dybowski 1877

The aim of this study was to determine the influence of the temperature (range 15 to 25°C), pH (6 to 9) and salinity of water (between 0 to 10‰) on the growth, condition and survival of larvae of the Chinese sleeper. During the 28‐day experimental rearing, the highest average body weight of 81.3 ± 16.3 mg was reached in fish from the group maintained at a water temperature 25°C, and was almost five times higher than the weight at the temperature of 15°C (15.6 ± 2.2 mg). A significantly higher body weight of Chinese sleeper larvae was also recorded in the group reared in alkaline water (pH 9), compared to those kept in acidic and neutral water. Statistically significant differences between the groups (p≤0.05) were recorded for the condition index (K) values and relative body weight (SGR) only in the experiment with different water temperatures of fish rearing. The highest number (16% of the initial stock) of abnormal larvae, associated with a lower jaw and vertebral structure deformities, was recorded in the group reared at 5‰ salinity (Z5). Simultaneously, 100% mortality of the stock was noted by the 10th day of rearing in the 10‰ salinity. The cumulative mortality of the Chinese sleeper larvae related to cannibalism Types I and II in all the experimental rearing was low, oscillating between 0.5% and 11.5% in the groups bred in water with a pH 9 and 0‰ salinity, respectively. The study results may help determine the critical values of water parameters that promote or limit development in the early stages of the Chinese sleeper and could be used in activities related to eradicating or significantly reducing the increasing abundance of this alien invasive fish species in freshwater ecosystems.

Life-history parameters of adult females of Merluccius capensis (Gadidae) off the south coast of South Africa.

This study explores the life-history parameters of female Merluccius capensis off South Africa (N = 1819) during 2014-2016, including gonadosomatic index (GSI), length-at-maturity, length-weight relationships, and condition indices (relative condition [k] and Fulton's condition factor [K]). We detected weak indications of two peaks of spawning within the year, the first in austral autumn from March to May, whereas the other in austral spring around August. GSI was slightly higher in spring and autumn, though still low at all maturity stages (≤7%), though the opposite was true for the actively spawning stage (≥7%) as well as access to less such data during winter- and summertime. The length (L) at 50% maturity was around 38 cm (L50), though differences occurred between the two applied staging methods, histology and visual (macroscopic) classification, when L approached infinity. The latter method presented underestimated length at maturity values at the 75 and 95 percentiles (48 and 60 cm) compared to the corresponding percentiles given by histology (50 and 65 cm). There were trivial across-method differences in L50. However, we found a clear reduction in L50 in view of published information in prior years when this estimate was 48 (1985), 42 (2008), 53 (2011), and 24.8 (2015) cm. Overall, L explained 90% of the variation in whole body weight (W). As the bootstrapped, grand mean growth coefficient was b = 2.98, indicating a slight allometric growth function, there were no significant variations between years, though an isometric growth existed for 2016 with b = 3.0, whereas for 2014 and 2015 this b was 2.98 and 2.93, respectively. In terms of demography, females <60 cm generally showed isometric growth (b = 3) as opposed to allometric growth (b = 2.95) at >60 cm. The relative condition index (k = 1) exhibited higher values than Fulton's K, which was 0.80. Overall, the maternal stock of M. capensis along the south coast seems to be in good condition and likely spawns throughout the year, but we found that the macroscopic data tend to give biased maturity ogives.