Annastaycya Simsang Sangma, Biswajit Lahiri, Amitava Ghosh
et al.
Angling tourism is gaining popularity and offers an alternative livelihood opportunity for the fish farmers of the Garo Hills region of Meghalaya, India. This research aims to provide insights into the social value of angling tourism among the fish farmers involved in angling tourism in the area and to identify its determinants. A sample of one hundred fish farmers was selected using snowball sampling from five districts of the Garo Hills, and data were collected using a semi-structured interview schedule. Most farmers considered fisheries a secondary occupation and were sceptical of angling tourism. The multiple stepwise regression analyses revealed that entry fees for daily angling besides competition and secondary occupation negatively impacted social value scores. In contrast, the educational status of fish farmers, annual investment in angling tourism, fish farming experience, total registered anglers annually, and family type positively impacted social value scores. The study confirmed that angling tourism fosters sustainable development within rural communities by nurturing social values and augmenting biodiversity conservation, and economic benefits. Overall, the study provides valuable information on the scope and prospects of angling tourism in leveraging social values and its potential to uplift rural people's social and financial status.
Daniela Silva, Raquel Menezes, Gonçalo Araújo
et al.
Accurately identifying spatial patterns of species distribution is crucial for scientific insight and societal benefit, aiding our understanding of species fluctuations. The increasing quantity and quality of ecological datasets present heightened statistical challenges, complicating spatial species dynamics comprehension. Addressing the complex task of integrating multiple data sources to enhance spatial fish distribution understanding in marine ecology, this study introduces a pioneering five-layer Joint model. The model adeptly integrates fishery-independent and fishery-dependent data, accommodating zero-inflated data and distinct sampling processes. A comprehensive simulation study evaluates the model performance across various preferential sampling scenarios and sample sizes, elucidating its advantages and challenges. Our findings highlight the model's robustness in estimating preferential parameters, emphasizing differentiation between presence-absence and biomass observations. Evaluation of estimation of spatial covariance and prediction performance underscores the model's reliability. Augmenting sample sizes reduces parameter estimation variability, aligning with the principle that increased information enhances certainty. Assessing the contribution of each data source reveals successful integration, providing a comprehensive representation of biomass patterns. Empirical validation within a real-world context further solidifies the model's efficacy in capturing species' spatial distribution. This research advances methodologies for integrating diverse datasets with different sampling natures further contributing to a more informed understanding of spatial dynamics of marine species.
Umair Nawaz, Muhammad Zaigham Zaheer, Fahad Shahbaz Khan
et al.
Crops, fisheries and livestock form the backbone of global food production, essential to feed the ever-growing global population. However, these sectors face considerable challenges, including climate variability, resource limitations, and the need for sustainable management. Addressing these issues requires efficient, accurate, and scalable technological solutions, highlighting the importance of artificial intelligence (AI). This survey presents a systematic and thorough review of more than 200 research works covering conventional machine learning approaches, advanced deep learning techniques (e.g., vision transformers), and recent vision-language foundation models (e.g., CLIP) in the agriculture domain, focusing on diverse tasks such as crop disease detection, livestock health management, and aquatic species monitoring. We further cover major implementation challenges such as data variability and experimental aspects: datasets, performance evaluation metrics, and geographical focus. We finish the survey by discussing potential open research directions emphasizing the need for multimodal data integration, efficient edge-device deployment, and domain-adaptable AI models for diverse farming environments. Rapid growth of evolving developments in this field can be actively tracked on our project page: https://github.com/umair1221/AI-in-Agriculture
In fisheries ecology, species abundance data are often collected by multiple surveys, each with unique characteristics. This article is motivated by a dataset of Atlantic sea scallop abundance records along the northeast coast of the United States, collected from two bottom trawl surveys which cover a larger spatial domain but have low catch efficiency, and a dredge survey which is more efficient but more bounded in domain. Over the past decade, integrated species distribution models (ISDMs) that include common environmental effects along with correlated survey-specific spatial fields have been used to incorporate information from multiple surveys. While flexible, ISDMs can be susceptible to overfitting, which can complicate interpretability of the shared environmental effects, and potentially lead to poor predictive performance. To overcome these drawbacks, we introduce a novel single index ISDM, built from a single index (with spatial random effects) that represents a latent measure of the true species distribution, and survey-specific catch efficiency functions which map the single index to the survey-specific expected catch. In this article, these functions are constructed via logistic functions or semiparametric spline-based functions. Simulations and application to the motivating sea scallop abundance data demonstrate that the proposed single index ISDM offers more meaningful interpretations of the environmental effects and survey catch efficiency differences, while achieving similar to or better predictive performance than existing ISDMs.
Samitha Nuwan Thilakarathna, Ercan Avsar, Martin Mathias Nielsen
et al.
Accurate fisheries data are crucial for effective and sustainable marine resource management. With the recent adoption of Electronic Monitoring (EM) systems, more video data is now being collected than can be feasibly reviewed manually. This paper addresses this challenge by developing an optimized deep learning pipeline for automated fish re-identification (Re-ID) using the novel AutoFish dataset, which simulates EM systems with conveyor belts with six similarly looking fish species. We demonstrate that key Re-ID metrics (R1 and mAP@k) are substantially improved by using hard triplet mining in conjunction with a custom image transformation pipeline that includes dataset-specific normalization. By employing these strategies, we demonstrate that the Vision Transformer-based Swin-T architecture consistently outperforms the Convolutional Neural Network-based ResNet-50, achieving peak performance of 41.65% mAP@k and 90.43% Rank-1 accuracy. An in-depth analysis reveals that the primary challenge is distinguishing visually similar individuals of the same species (Intra-species errors), where viewpoint inconsistency proves significantly more detrimental than partial occlusion. The source code and documentation are available at: https://github.com/msamdk/Fish_Re_Identification.git
This study examined the development of biofouling assemblages on cage net panels submerged at different depths in a fish farm in the Red Sea. Experimental rafts equipped with Dyneema fibre nets were submerged at depths of 5, 10 and 15 m. Results showed significant variations (P < 0.05) in fouling biomass and the composition of fouling communities among the three depths. The highest biomass accumulation (average: 71.06 g dm−2 month−1) was recorded on panels at 5 m. The fouling community that settled on the net panels included macroalgae, sponges, bryozoans, hydrozoans, mussels and ascidians. Although the results indicated a distinct pattern of successional phases during the growth of the fouling community on the cage net panels, the abundance of dominant fouling organisms varied between depths. At 5 m, ascidians and algae were most abundant, whereas panels at 10 m were primarily colonized by ascidians, bryozoans and hydrozoans. At 15 m, ascidians and bryozoans were dominant. Overall, the findings suggest that fouling abundance decreases at greater depths, with the lowest colonization observed at 15 m. These results provide valuable insights for developing effective biofouling management strategies to mitigate excessive accumulation of dominant fouling organisms in this region.
Felipe Montealegre-Mora, Carl Boettiger, Carl J. Walters
et al.
In fishery science, harvest management of size-structured stochastic populations is a long-standing and difficult problem. Rectilinear precautionary policies based on biomass and harvesting reference points have now become a standard approach to this problem. While these standard feedback policies are adapted from analytical or dynamic programming solutions assuming relatively simple ecological dynamics, they are often applied to more complicated ecological settings in the real world. In this paper we explore the problem of designing harvest control rules for partially observed, age-structured, spasmodic fish populations using tools from reinforcement learning (RL) and Bayesian optimization. Our focus is on the case of Walleye fisheries in Alberta, Canada, whose highly variable recruitment dynamics have perplexed managers and ecologists. We optimized and evaluated policies using several complementary performance metrics. The main questions we addressed were: 1. How do standard policies based on reference points perform relative to numerically optimized policies? 2. Can an observation of mean fish weight, in addition to stock biomass, aid policy decisions?
Gabriel Ewig, Arezoo Hasankhani, Eugene Won
et al.
As emerging marine technologies lead to the development of new infrastructure across the ocean, they enter an environment that existing ecosystems and industries already rely on. Although necessary to provide sustainable sources of energy and food, careful planning will be important to make informed decisions and avoid conflicts. This paper examines several techniques used for marine spatial planning, an approach for analyzing and planning the use of marine resources. Using open source software including QGIS and Python, the potential for developing wave-powered offshore aquaculture farms using the RM3 wave energy converter along the Northeast coast of the United States is assessed and several feasible sites are identified. The optimal site, located at 43.7°N, 68.9°W along the coast of Maine, has a total cost for a 5-pen farm of \$56.8M, annual fish yield of 676 tonnes, and a levelized cost of fish of \$9.23 per kilogram. Overall trends indicate that the cost greatly decreases with distance to shore due to the greater availability of wave energy and that conflicts and environmental constraints significantly limit the number of feasible sites in this region.
We consider management of the fish species Plecoglossus altivelis altivelis, a major inland fishery resource in Japan playing important roles from economic, cultural, and recreational viewpoints. We firstly summarize the collected body weight data of the fish in the Hii River, Japan since 2016. The two kinds of data are available in each year with few exceptions: the historical data during summer and autumn collected with the help of an angular and the annual distribution data at the Toami (casting net) competition where we could obtain the data from many anglers during two hours in one day. We fit deterministic and uncertain logistic growth models to the data in each year and discuss their performance. The fitted uncertain logistic growth model is applied to an optimal harvesting problem of the fish subject to a sustainability concern and model distortion. Several numerical schemes for solving the problem are examined and compared both theoretically and numerically.
Linn Danielsen Evjemo, Qin Zhang, Hanne-Grete Alvheim
et al.
The significant growth in the aquaculture industry over the last few decades encourages new technological and robotic solutions to help improve the efficiency and safety of production. In sea-based farming of Atlantic salmon in Norway, Unmanned Underwater Vehicles (UUVs) are already being used for inspection tasks. While new methods, systems and concepts for sub-sea operations are continuously being developed, these systems generally does not take into account how their presence might impact the fish. This abstract presents an experimental study on how underwater robotic operations at fish farms in Norway can affect farmed Atlantic salmon, and how the fish behaviour changes when exposed to the robot. The abstract provides an overview of the case study, the methods of analysis, and some preliminary results.
The study aims to identify the influences of sodium acetate on the growth, hematologic parameter, carbohydrate metabolism and gut microbiota of largemouth bass (Micropterus salmoides) fed high carbohydrate diets. The trial diets were formulated including the suitable carbohydrate (9 %, SC), the high carbohydrate (18 %, HCD) and HCD supplemented with 0.15 % sodium acetate (HCSD), and fed M. salmoides (initial body weight: 3.70 ± 0.06 g) for 8 weeks. The overcomes demonstrated compared to the SC group, the fish fed HCD exhibited metabolic abnormalities and liver damage accompanied with high levels of glucose (GLU), hepatosomatic index (HSI), aspartate aminotransferase (AST) and hepatic glycogen as well as high activities of phosphoenolpyruvate carboxykinase (PEPCK) and glucose 6 phosphatase (G6P). However, inclusion of sodium acetate promoted the growth performance and lowered blood GLU and liver glycogen levels. Moreover, adding sodium acetate inhibited gluconeogenesis and promoted glycolysis via the Adenosine 5’-monophosphate (AMP)-activated protein kinase (AMPK) pathway. Additionally, in comparison with the HCD group, sodium acetate supplementation improved the composition of gut microbiota, inhibited the proportion of pathogens (Acinetobacter, Mycoplasma, Pseudomonas and Sediminibacterium) and increased the abundance of beneficial bacteria (Cetobacterium and Romboutsia). We concluded that sodium acetate mitigated effectively the adverse symptoms of M. salmoides fed HCD. More importantly, sodium acetate addition may improve the carbohydrate utilization by increasing the proportion of intestinal Cetobacterium and Romboutsia.
Carbonate saline-alkali water has significant potential in the development of saline-alkali fisheries, but the effects of bicarbonate stress on crustaceans have not been fully studied. In this study, we investigated the changes in osmotic regulation, immune, and antioxidant capacity of the Scylla paramamosain at 1, 7, and 28 d at different carbonate concentrations (CK: 220 mg/L; AB1: 300 mg/L; AB2: 380 mg/L; AB3: 700 mg/L), and conducted transcriptome analysis. The results showed that Ca2+/Mg2+-ATPase in the gills of the AB3 group was significantly lower than that of the AB2 group, while the AB2 group was lower than the CK group and the AB1 group (P<0.05). CA activity was positively correlated with bicarbonate concentration, while the AB3 group was significantly higher than the other groups. ALT and AST in groups AB1 and AB2 showed a trend of first increasing and then decreasing, and roughly returned to their initial levels at 28 d, while AB3 continued to increase with time and was significantly higher than the initial level. At 28 d, ACP and AKP in the AB3 group were significantly lower than those in the other groups. The MDA content in the hepatopancreas also showed similar trend, with a positive correlation between the T-AOC, GSH and bicarbonate concentration. At 28 d, the AB1 group was able to recover to its initial level, while the AB3 group decreased with time and reached its minimum value at 28 d. Transcriptomic analysis identified 283 DEGs, and KEGG enrichment analysis showed antioxidant pathways, including the ascendate and alderate metabolism, were up-regulated to cope with stress. In addition, it shows many immune related pathways, including the mTOR signaling pathway, were significantly down-regulated. This study explores the effects of bicarbonate stress on the S. paramamosain, providing theoretical guidance for the utilization of carbonate saline-alkali water.
Color pattern plays a vital role in animal survival and communication. The type, distribution, and pigment state of pigment cells, and the reflective ability of iridophores determines body color. It varies adaptively in response to external environmental changes and physiological states. The skin pigmentation pattern reflects the number and arrangement of chromatophores. Some fish with rich color patterns, including egg spot patterns, blotch patterns, melanism, horizontal stripe patterns, and vertical bar patterns, have been studied increasingly. This study observed the formation, distribution, and main pattern of chromatophores in 1–60-day-old Misgurnus anguillicaudatus after hatching. Larval melanocytes were first observed in the yolk sac of loach larvae at 3 h post-hatching. From the larval to juvenile stage at 21 days, larval melanocytes appeared on the loach body surface. From the juvenile stage at 22 days to the adult stage, adult melanocytes appeared on the loach body surface. Iridocytes were first observed in the eyes of one-day-old larvae but not on the body surface until they were 12 days old. Xanthophores appeared on the body surface of seven-day-old juveniles. At 2–21 days post-hatching, the melanocytes in the loaches were larval, and their shape changed from star-to snowflake-shaped before forming a black spot. From 22 days, different morphological adult melanocytes formed on the body surface of the loaches with three types of black spots. Chrysanthemum-shaped melanocytes regularly aggregated into large black spots on large black spot loaches. Round and dendritic melanocytes gathered to form small black spots on small black spot loaches. Dendritic melanocytes were evenly distributed on non-black spot loaches. The pigmentation-related mitfa gene was obtained from M. anguillicaudatus using the rapid amplification of cDNA ends (RACE) approach with the SMARTer RACE 5´/3´ Kit User Manual according to the manufacturer's recommendations and was analyzed using bioinformatics and quantitative methods. The results showed that the mitfa gene encoded a protein with 408 amino acids with a calculated molecular mass of 45.68 kDa and an estimated isoelectric point of 7.16. MITFa contained MITF_TFEB_C_3_N, bHLH-Zip, and DUF 3371 domains. MITFa was well-conserved compared to MITF of various species with a higher degree of sequence similarity with other fishes (58.8%–83.2%). The qRT-PCR results showed that the mitfa mRNA was expressed at all stages of embryonic development and reached a peak value at the fertilization stage. mitfa expression was detected in all examined tissues of the three types of loaches, and the highest level of expression was detected in both muscle and dorsal skin (P < 0.01). This study explored pigmentation formation and mitfa expression, serving as a foundation for gaining further insight into the genetic mechanism of body color formation in M. anguillicaudatus.
Methods for forecasting the stocks of pacific salmon in Khabarovsk Region are considered. Errors of the forecasts based on theoretical parent-offspring models are associated with variability in weather conditions on the spawning grounds. The progeny dynamics is modeled much better when weather factors are assimilated into the single- factor models. The errors reduction would be expected for multifactor models, assuming that they will be based on reliable data on the number of parents and offspring, though this condition seems questionable in the face of a growing shortage of qualified observers and modelers.
Bartholomew W. Green, Steven D. Rawles, Candis L. Ray
et al.
Abstract Intensified production of stocker‐size tilapia can be accomplished using the biofloc technology production system. Stocker‐size tilapia (ca. 10–200 g/fish) are raised for subsequent stocking for grow‐out to market size. The relationship between stocking rate and the production of stocker‐size hybrid tilapia (Oreochromis aureus × O. niloticus) was evaluated in two studies in outdoor mixotrophic biofloc tanks. Hybrid tilapia were stocked in 18.6‐m2 (15.7‐m3) tanks at 50–150 fish/m2 (59–178 fish/m3) in 25 fish/m2 (30 fish/m3) increments in Study 1 and grown for 141–143 days. Stocking rates evaluated in 4.7‐m2 (3.6‐m3) tanks during Study 2 over 78–79 days ranged from 100 to 300 fish/m2 (132–396 fish/m3) in 25 fish/m2 (33 fish/m3) increments. Linear regression models best described growth to stocker size in both studies. Fish yield increased linearly with stocking rate and ranged from 20.1 to 38.3 kg/m3. Individual weight at harvest was inversely related to stocking rate and ranged from 389.8 to 163.4 g/fish and 155.2 to 81.4 g/fish in Studies 1 and 2, respectively. Partial budget analyses suggested positive net changes in profit with incremental increases in stocking rate for producing a 75‐g stocker. Water quality concentrations were impacted directly by daily feed ration and total feed fed, which increased linearly with stocking rate. In Study 2, whole‐body dry matter, protein, protein retention, and lipid were unaffected by stocking rate, whereas whole‐body ash increased with stocking rate. Whole‐body energy retention significantly decreased with stocking rate. The outdoor mixotrophic biofloc production system is well suited for intensive production of hybrid tilapia stockers. However, additional replicated research and economic analysis are needed to evaluate stocking rate and culture duration to produce specific‐sized stocker hybrid tilapia.
M. Bosch-Belmar, G. Milisenda, Lorena Basso
et al.
Abstract Over the last 50 years there has been an increased frequency and severity of negative impacts affecting marine fishery and aquaculture sectors, which claimed significant economic losses due to the interference of stinging gelatinous organisms with daily operational activities. Nevertheless, original scientific information on jellyfish-related incidents, their consequences, and potential preventative and mitigation countermeasures is limited and scattered across gray literature, governmental technical reports, and communication media. A literature scan searching for records of any interactions between jellyfish and the marine fishery/aquaculture sectors was carried out. Out of 553 papers, 90 contained original information, referring to more than 130 cases worldwide of negative impacts of jellyfish on marine fishery/aquaculture over the last century. Calling attention on too often neglected socio-economic and ecological impacts of jellyfish blooms, the purpose of this paper is to review and analyze the most up-to-date research on this subject and to provide a global perspective on the importance of jellyfish impacts and their cascading effects on marine fishery and aquaculture sectors.