Next Article in Journal
Macro-Habitat Suitability for Threespine Stickleback (Gasterosteus aculeatus L.) Near the Southern Limit of Its Global Distribution: Implications for Species Management and Conservation
Next Article in Special Issue
Decadal Changes in the Annual Growth of Two Commercial Ommastrephid Species in the Pacific Ocean
Previous Article in Journal
Measuring the Green Total Factor Productivity in Chinese Aquaculture: A Zofio Index Decomposition
Previous Article in Special Issue
Allometry and Individual Growth of the Temperate Pacific Sardine (Sardinops sagax) Stock in the Southern California Current System
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Fishes
Volume 7
Issue 5
10.3390/fishes7050270
fishes-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Perceptions of the Impact of Climate Change on Performance of Fish Hatcheries in Bangladesh: An Empirical Study

by
Mohammad Abu Baker Siddique
1,
A. K. Shakur Ahammad
1,
Balaram Mahalder
2,
Md. Mehedi Alam
3,
Neaz A. Hasan
4,
Abul Bashar
2,
Jatish Chandra Biswas
5 and
Mohammad Mahfujul Haque
2,*
1
Department of Fisheries Biology and Genetics, Bangladesh Agricultural University, Mymensingh 2202, Bangladesh
2
Department of Aquaculture, Bangladesh Agricultural University, Mymensingh 2202, Bangladesh
3
Department of Fishery Resources Conservation and Management, Khulna Agricultural University, Khulna 9100, Bangladesh
4
Department of Fisheries and Marine Bioscience, Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj 8100, Bangladesh
5
Krishi Gobeshona Foundation, BARC Complex, Farmgate, Dhaka 1215, Bangladesh
*
Author to whom correspondence should be addressed.
Fishes 2022, 7(5), 270; https://doi.org/10.3390/fishes7050270
Submission received: 29 August 2022 / Revised: 22 September 2022 / Accepted: 28 September 2022 / Published: 2 October 2022
(This article belongs to the Special Issue Climate Change on the Growth of Marine Fishes)
Browse Figures
Review Reports Versions Notes

Abstract

:
The impacts of climate change (CC) on all spheres of human life are evident worldwide. Fish is the premier protein source, and its production in Bangladesh is mainly dependent on hatchery-based seed production. However, hatchery productivity is disrupted every year due to CC. This study assesses the impacts of CC on fish seed production in hatcheries from the perspective of hatchery owners. A semi-structured questionnaire survey was conducted with 60 hatchery owners in five sub-districts (Trishal, Mymensingh Sadar, Gouripur, Fulbaria, and Muktagacha) of the Mymensingh district, the highest aquaculture-producing zone in Bangladesh. Characteristically, hatchery owners are middle-aged and highly educated, with over a decade of experience in fish hatchery management. Likert scale results showed that hatchery owners concur with the evidence of CC, as seen by changes in air and water temperatures, rainfall, and sunlight intensity, as well as frequent natural disasters. Regression analysis showed that erratic rainfall, high temperature, and high solar radiation significantly influenced the hatchery owners’ perceptions of CC. Principal component analysis (PCA) was used to divide the impact of CC into 12 components. Maximum variance (>70%) observed could be explained by problems related to embryonic and physiological development of fish fry, environmental changes, disease outbreaks, and poor growth of broodfish. The first PCA explained over 50% of the variances, with significantly higher factor loadings, comprising poor gonadal maturation, low hatching rate, poor egg and seed quality, low fecundity, and poor sperm quality of broodfish. The first PCA confirmed that the impacts of CC on fish hatchery operations were severe. Planting trees on the hatchery premises, aeration of brood ponds, increased water supply, and temperature control can be implemented to address the negative impacts on fish hatcheries. Further research in the laboratory and hatchery environments is needed.

1. Introduction

Globally aquaculture has grown faster than any other animal production sector [1], and Bangladesh is one of the leading fish-producing countries in the world, with an annual production of 4.62 million MT [2]. Aquaculture contributes to approximately 57.10% [2] of the total fish production in Bangladesh, thus becoming a promising sector for ensuring the food security for an ever-increasing population in Bangladesh and worldwide [3]. Over the past decade, aquaculture production in Bangladesh has increased 2.34 times [4]. However, this productivity is threatened by climate change (CC), which is the most critical and rapidly evolving global environmental issue [5]. Bangladesh is one of the most climate-vulnerable countries on Earth, with CC expected to have a broad impact across ecosystems, thus affecting livelihoods and food supplies, including fisheries and aquaculture [6,7,8]. Although aquaculture in Bangladesh was initiated using natural seed, it is now almost entirely replaced by hatchery-produced seed [4]. Currently, in Bangladesh, 935 private and 103 government hatcheries supply finfish seed, and 27 government and 50 private hatcheries also produce shrimp post-larvae [4]. Therefore, hatcheries are the primary suppliers of fish seeds in Bangladesh [9]. However, these enterprises are facing economic losses because of a decline in natural resources caused due to CC, habitat destruction, and the degradation of the ecological balance [9]. Fish production could be boosted by increased seed supply, which would improve the economic viability of hatcheries.
A hatchery is a multi-component system that requires close attention and various skills to run efficiently and profitably. A study reported that a late breeding season, lack of capital, limited technical knowledge of hatchery operation and management, poor transportation facilities, high transportation costs, high labor costs, limited training, and high spawn prices are major concerns for the effective operation of hatcheries [10]. Several biological concerns, such as improper broodstock selection, indiscriminate hybridization, and inbreeding, have also been raised [11]. In addition to these concerns, CC substantially impacts fish hatcheries [12]. Temperature is the variable that influences fish seed production the most, followed by rainfall, humidity, and solar radiation intensity [13,14,15,16]. Unfavorable temperature impairs growth by changing the metabolic and developmental processes of fishes [17,18,19], ultimately affecting seed production [20,21]. Rearing temperature considerably affects egg production, hatching rate, and larval growth rate [22,23,24]. The effects of water temperature on the growth and development of fish have been observed for many species, including Oreochromis niloticus [15], Cyprinus carpio [25], Labeo rohita [13], Anguilla anguilla [26], and Takifugu obscurus [27]. From a commercial point of view, farmed fish species in Bangladesh can be broadly divided into four categories such as carp (Labeo rohita, Catla catla, Cirrhinus cirrhosus, Labeo calbasu, Labeo bata, Labeo gonius, Hypophthalmicthys molitrix, Aristichthys nobilis, Ctenopharyngodon idella, Cyprinus carpio), catfish (Pangasianodon hypophthalmus, Clarias batrachus, Heteropneoustes fossilis, Ompok pabda), tilapia (Oreochromis niloticus), mainly being cultured in freshwater, and shellfish (Penaeus monodon, Macrobrachium rosenbergii), being cultured in coastal areas [28]. Hatchery-based seed production of all these species, except C. carpio, mainly occurs during the period from March to August, i.e., during summer when the temperature ranges from 25 to 28 °C. For this reason, there is a subtle relationship existing between temperature fluctuation and hatchery-based fish seed production. That is why hatchery production is almost stopped in winter compared to the warm season [22]. The readiness, maturity, and gonadal development of broodfish during the spawning season are impacted by temperature fluctuations, as well as irregular rainfall [29]. Faruk et al. [15] stated that feeding and growth rates are reduced at temperatures higher or lower than the optimum levels, and feeding and growth nearly stops at ≤20 °C. A more severe effect of CC is the weakening of the immune system of fishes, resulting in increased diseases, which ultimately hampers fish production [30,31]. Decreased fish production causes economic losses for hatchery owners, nursery operators, fry sellers, and other stakeholders of the fisheries sector [11]. Although cost-effective mitigation measures are difficult to implement in practice, researchers from several countries have identified ways to limit the climatic effect on hatcheries and fish farms [21,32]. Despite the difficulties in implementing cost-effective mitigation and adaptation methods, several studies have reported positive outcomes at fish farms and hatcheries. In this regard, Alam et al. [32] claimed that commercial fish hatcheries using a shed over the brood hapa (i.e., the rearing of fish in a closed net system in a pond or open water) during high-temperature months yielded a greater number of eggs. According to a perception study conducted by Adhikari et al. [21] in Andhra Pradesh, Karnataka, Gujarat, Odisha, and West Bengal states of India, fish farmers used fresh water from nearby surface or sub-surface sources to lower water temperature, oxygen tablets to supplement oxygen during the summer, and nets in pond dikes to prevent fish from escaping during flooding.
In Bangladesh, studies on the impact of CC at the hatchery level are limited, and farmers’ perceptions and practical implications of CC on hatcheries remain undocumented. Moreover, participatory approaches including hatchery owners, farmers, traders, and government and non-government organizations have also been inconclusive [9]. Therefore, developing environmentally friendly solutions and considering farmers’ perceptions could boost aquaculture production in Bangladesh. The main objective of this study was to reveal how hatchery owners perceive and confront the impact of CC on hatchery production and to recommend mitigation and adaptation practices for sustainable hatchery production in Bangladesh.

2. Materials and Methods

2.1. Site and Hatchery Selection

This study was conducted in five sub-districts (Upazilas) of Mymensingh district, namely, Trishal, Mymensingh Sadar, Gouripur, Fulbaria, and Muktagacha (Figure 1), based on their contribution to districts’ national seed production. These Upazilas were selected because approximately 32% of hatcheries in Bangladesh are located in these regions [4,33]. Moreover, many private fish seed hatcheries in the study site possess appropriate agro-ecological conditions, namely, favorable climate, low-lying agricultural land, fertile soil, and abundant labor forces [34,35]. Population size data (complete list of hatcheries) from Upazila Fisheries Office, Department of Fisheries, Bangladesh, were considered to make the decision about number of hatcheries being surveyed in each Upazila. Before finalizing the sample size of hatcheries, the list of hatcheries collected from the UFO was validated with some lead hatchery owners applying key informant interview (KII) tool in each Upazila. From the entire list, 60 hatcheries that maintained regular production of fish seed commercially were randomly selected for this study. Final participation was based on ethical obligations, whereby hatchery owners consented to the use of their input for research purposes.

2.2. Data Collection

Hatchery owners were the preferred interviewees for data collection, owing to their technical capabilities for providing accurate answers. A questionnaire comprising two sections was developed for data collection. The questions in the first section were related to the demographic characteristics of the respondents, including name, age, gender, and education. The second section examined the primary purpose of the research, including the impact of CC on hatcheries, challenges, and mitigation strategies. The questionnaire was developed in a way that hatchery owners could understand and easily respond to. The draft questionnaire was pre-tested and validated by interviewing three respondents from each study site, followed by modifications based on respondent feedback. The final version of the questionnaire used for data collection was placed online via a Google form. In addition, data from the selected hatchery respondents were collected via face-to-face interviews from January to March 2021.

2.3. Data Analysis

The collected data were captured in MS Excel and rechecked to minimize errors. A brief descriptive statistical analysis was carried out to describe the general background of hatchery owners. Linear regression analysis was performed to assess the perceptions of hatchery owners on the impacts of CC. Principal component analysis (PCA) was undertaken to characterize the impacts of CC as perceived by hatchery owners, and to determine how hatchery owners’ experiences challenge adapting to climate variability and whether they are isolated or clustered. The PCA equation is as follows:
P C i = a 1 i V 1 + a 2 i V 2 … … … … … a n i V n
where PCi is the principal component i, and ani (n = 1…n) is the loading (correlation coefficient) of the original variable Vn [36,37].
A degree of subjectivity regarding the number of components was present in the PCA extraction. The standard stopping rule for determining the number of components is to stop when the eigenvalue drops below 1 because eigenvalues have standardized variances with mean 0 and standard deviation 1. Thus, components with an eigenvalue <1 are considered unimportant and were therefore excluded; however, components with an eigenvalue >1 are considered important and were therefore retained [38]. All statistical analyses were performed using the Statistical Package for Social Science (SPSS) 20 and Minitab 18.

3. Results

3.1. General Characteristics of Hatchery Owners

The hatchery owners in the study site were aged 15–65 years, with the majority falling within the middle age (31–50 years) category at 60%, followed by old age (51–65 years) category at 33.33%, and then young age (15–30 years) category at 6.67% (Table 1). Additionally, all hatchery owners were male, although female counterparts sometimes assisted in hatchery management. Among the respondents, 40% had completed class XI or higher, 38.33% had completed between class VI to X, 18% had completed between class I to V, and the remaining 1.67% were illiterate.
The majority (58.33%) of the hatcheries had been operating for 1–12 years, 30% for 13–24 years, and 11.67% for 25–36 years. Small hatcheries comprised 46.67%, medium hatcheries comprised 21.67%, and big hatcheries comprised 31.67% of the total hatcheries studied. Almost 51.67% of hatcheries had been producing commercial fish seed for at least ten years. All hatchery owners had received formal or informal training in hatchery operations for running their businesses efficiently. Moreover, upon answering a supplementary question, respondents indicated that they obtained information and skills through friends and relatives who had received official training from the Department of Fisheries, the Department of Youth Development, and non-governmental organizations.

3.2. Hatchery Owners’ Perceptions of CC and Its Effects

As per hatchery owners’ perceptions, 68.33% of respondents agreed with rising water temperature being the most evident effect of CC (Table 2). About 63% of respondents agreed with rising air temperature, and 45.76% of respondents agreed with natural calamities, including floods, cyclones, heavy rainfall, water logging, and flash flood, these being the next two important causes. Seven percent of respondents agreed that air temperature influenced pond water temperature.

3.3. Relationship between Hatchery Owners’ Perceptions and Key Weather Parameters

Three weather variables, namely, erratic rainfall, high temperatures, and solar radiation, significantly influenced hatchery owners’ perceptions of CC causes (Table 2). This was confirmed by the results of the Likert scale, where the values of multiple R and R-squared increased with the addition of independent variables from models 1 to 3 (Table 3). Approximately 27% of the variabilities were explained when erratic rainfall, high temperature, and solar radiation were considered together, as in the third model. The model showed a minimum error of the estimate and was highly statistically significant at the p < 0.05 probability level (Table 4).

3.4. Characteristics of CC Impacts on Fish Hatcheries

The PCA results (i.e., the rotated factor (varimax) matrix of independent variables with differential factor loadings) are summarized in Table 5. The first three principal components (PCs) explain 70.21% of the total variance and have Eigenvalues >1 (Table 5). The scree plot of all PCs is shown in Figure 2. The scree plot result of PCA extraction in SPSS, using a correlation matrix and standardized variables, indicated that factors are loaded and retained under three components. Moreover, in the PCA loading plot, three distinct clusters developed with three different types of variables (Figure 3). In this study, the content of each PC was best interpreted by examining the variables with factor loadings ≥0.5 (Figure 3).

3.4.1. Component 1: Poor Reproductive Performance of Fish

The first PC, which indicates the orientation of poor reproductive performance, explained 50.08% of the variance and demonstrated higher positive correlations with poor larval growth; poor gonadal maturation; poor quality of eggs, seeds, and sperm; low hatching rate; and low fecundity (Table 6). These extracted components, either collectively or individually, had significant positive factor loadings. Individually, poor larval growth, with a positive correlation coefficient (0.874), contributed the most to this component, followed by poor gonadal maturation (0.861), low hatching rate (0.859), poor egg quality (0.849), poor seed quality (0.823), low fecundity (0.784), and poor sperm quality (0.736) (Table 6).

3.4.2. Component 2: Poor Survival in Relation to Disease and Poor Water Quality

The second PC was positively correlated with 10.32% of the variance and mainly correlated with disease occurrence (0.810), poor survival of larvae (0.750), and poor water quality (0.530) (Table 6).

3.4.3. Component 3: Poor Growth of Broodstock

The third PC indicated poor digestion and had a positive correlation coefficient (0.701). Similarly, the hampered growth rate of broodstock (0.661) displayed a positive correlation coefficient (Table 6).

3.5. Mitigation Measures as Perceived by Hatchery Owners

The hatchery owners gave their opinions on how the impacts of CC on hatcheries could be mitigated. Approximately 85% of hatchery owners suggested that planting trees around the hatchery could reduce overheating and keep the environment cool (Figure 4). Sixty eight percent hatchery owners suggested that aeration in broodfish ponds could increase dissolved oxygen levels in water. More than 60% of hatchery owners suggested maintaining tolerable water temperatures in nurseries or broodfish ponds through regular water changes or additional water supply. Around 57% of hatchery owners suggested the need for constructing temperature-controlled hatcheries to produce fry. Approximately 37% of hatchery owners suggested that oxygen tablets could be used to overcome low oxygen levels in the water. More than 30% of hatchery owners suggested raising the pond dikes to prevent flooding of hatchery ponds.

4. Discussion

4.1. General Characteristics of Hatchery Owners

Although studies on the direct impact of CC on hatchery production in Bangladesh are limited, our findings related to general characteristics of hatchery owners are mostly consistent with those of other studies [39,40,41]. Most hatchery owners in Bangladesh are middle-aged, highly educated, have over ten years of experience, and are trained in fish hatchery management, which is consistent with the findings of Uddin et al. [42]. These hatchery owners continuously improve and modernize their operations to cope with CC and maintain the economic viability of their hatcheries.
In this study, most hatchery owners were middle-aged (31–50 years). Ali et al. [43] also reported that most fish farmers (>50%) in the Mymensingh district were aged between 31 and 40 years. Age groups vary depending on geographic regions within the country. For example, most hatchery owners (44%) in the Chandpur district were aged 41 to 60 years [39]. Pravakar et al. [39] reported that the age of fishermen in the Sundarbans ranged from 20 to 70 years, which is consistent with the current findings.
Approximately 40% of hatchery owners had a higher education than secondary school, which is important for improved hatchery management. In general, education can be essential in enabling farmers’ technical understanding and approach to constraints [41] and ultimately efficient hatchery management. The literacy rate of respondents in this study was higher than the national adult literacy level of 65% [44]. According to Ali et al. [45], 50% of the fish farmers had completed SSC level education, and 22% had completed HSC level education. In Bagmara, Rajshahi district, Bangladesh, approximately 6% of respondents were illiterate, while 4% of respondents held a bachelor’s degree. In contrast, Zaman et al. [46] found that 23.3% of fish farmers were illiterate, and 14.4, 8.9, and 6.7% were educated up to the primary, secondary, and higher secondary levels, respectively. Tasnoova et al. [47] found that 60% of alternate-rice-fish farmers and 50% of rice-cum-fish farmers held a graduate degree or higher level of education. Pravakar et al. [39] stated that the level of education influenced the use of ponds for fish farming, which is consistent with the current findings.
All hatchery owners received either formal or informal training to run their businesses efficiently. Family members, friends, and relatives provided informal training, whereas the Department of Fisheries, the Department of Youth Development, and non-governmental organizations provided formal training. According to the respondents, the training enabled them to manage their hatchery activities effectively. Islam et al. [48] and Uddin et al. [42] reported effective management of fish farms by farmers who had received training. Approximately 50% of the hatchery owners earned income from other sources, such as fish culture, rice farming, cattle rearing, and poultry production. However, over recent years, hatchery owners have faced many unavoidable challenges, such as the impact of COVID-19, seed marketing problems, financial problems, and diseases during the production cycle [49].

4.2. Hatchery Owners’ Perceptions on CC and Its Effects

All hatchery owners were professionals with extensive practical experience in hatchery management, and they agreed that the increasing water temperature was an effect of CC. Azad and Wadood [50] reported that high temperatures and erratic rainfall affect fish reproduction, growth, and migration patterns. Faruque and Kabir [51], in a case study of fish farmers in northwestern Bangladesh, claimed that the reduction in the overall total fish production was because of the decreased growth rate of cultured fish and increased fry and fingerling mortality caused by heat shock and diseases. As with fish farmers, fishermen perceived that the rise in temperature, frequency of tropical cyclones, and sea level, as well as the decrease in monsoon rainfall, had pronounced impacts on the declining fish population of the Bay of Bengal [52]. The findings of this study and the evidence included in the literature indicate that the perceptions held by hatchery owners on CC are realistic.

4.3. Relationship between Hatchery Owners’ Perceptions and Key Weather Parameters

Hatchery owners depend heavily on nature for producing and sustaining their livelihoods. Therefore, they shared their views, potential abilities, and valuable knowledge through this survey, all of which were significant. Erratic rainfall, high temperatures, and solar radiation significantly influenced hatchery owners’ perceptions of CC. According to a study in South Bengal, high temperatures, low rainfall, salinity intrusion, seasonal fluctuations, and prolonged droughts are the major effects of CC that affect pond fish farming [53]. Another study reported that aquaculture is vulnerable to several climatic factors, including global warming, rainfall variability, floods, droughts, temperature fluctuations, and salinity changes [54].

4.4. Characteristics of CC Impacts on Fish Hatcheries

4.4.1. Poor Reproductive Performance of Fish

The first PC addresses the adverse effects of CC on the embryonic and physiological development of fish fry, based on factor loadings. Poor larval growth had the highest loading, suggesting that larval growth of fishes was associated with favorable environmental conditions [55]. Several studies have highlighted that temperature has a strong influence on embryogenesis, hatching [24], and subsequent larval development, growth, and survival [56]. Moreover, temperature controls the physiological processes in fish, such as oxygen uptake rate, heart rate, locomotion, water balance, digestion, developmental rate, sex determination, and immune function [57]. Similarly, Aziz et al. [58] revealed that temperature strongly influences all physiological processes, particularly reproductive processes such as gamete development, ovulation and spermiation, spawning, embryogenesis, hatching, larval and juvenile development, and survival. Several reproductive functions, such as the gametogenesis and growth of larval and post-metamorphic individuals, are also temperature-dependent [59]. Extreme environmental temperatures affect the typical morphology of fish larvae, resulting in decreased egg, sperm, and seed quality [60]. Because fish are poikilotherms, changes in water temperature cause metabolic and developmental disorders, lowering larvae survival rates, reducing fecundity, and hampering gonadal maturation [56,61,62]. Additionally, incubation at temperatures below the optimum level delays embryo development, increasing disease susceptibility and reducing viability [63].

4.4.2. Poor Survival in Relation to Disease and Poor Water Quality

The disease occurrence and poor survival of larvae showed a positive correlation with CC, indicating that CC induces stress on fish larvae, thus leading to an increased susceptibility to disease, parasite infection, and death in fishes from hatcheries. Various studies have reported that the effects of CC are responsible for disease susceptibility in fishes [20,64,65]. Similar findings by Chiaramonte et al. [66] report that the increased susceptibility of fish larvae to pathogen attack caused by temperature change is a significant determinant of diseases, and is likely to be affected by direct and indirect thermal stressors. Harasawa et al. [67] reported that disease threats and invasive species induced by CC directly impact fish hatcheries. Rising water temperatures due to CC increase larval mortality in fishes [56]. Moreover, fish metabolism is directly related to surrounding water temperature, and changes in water temperature are known to affect their immune system [65]. Temperature fluctuation will likely accelerate the replication rate, virulence, life-cycle longevity, and transmission of pathogens among several fish species [68]. Additionally, CC is linked to water quality parameters because it gives rise to changes in the hydrology and hydrography of water systems [69]. The effect of CC has been described extensively, including the effect on water quality which disrupts host—pathogen interactions, sometimes creating beneficial conditions for pathogen amplification and spread or microbial and ecological dysbiosis [70,71,72,73]. Islam et al. [74] indicated that temperature fluctuation might be responsible for fish disease, water quality deterioration, oxygen deficiency in water, and larvae disfigurement. Ahmed and Diana [75] reported that changes in water temperature decrease primary productivity through water stratification and reduction in surface water nutrients. Furthermore, excessive heavy rainfall causes water turbidity, which reduces the growth of fish larvae by limiting sunlight penetration and hampering oxygen production [75]. Several studies showed the association of harmful algal bloom outbreaks with CC [76,77].

4.4.3. Poor Growth of Broodstock

Fish health, in terms of factors such as poor digestion and hampered growth rate of broodfish, has been positively linked to CC (Table 6). Abnormal fluctuations in water temperature causes loss of appetite in fish and larvae, and they stop feeding, which thus hinders their growth and development in hatcheries [19,78,79]. The effects of temperature on broodfish development, ovarian growth, egg production, and relative fecundity are profound [22]. The egg production capacity of broodfish decreases with the increase in water temperature [15]. Earlier studies observed maximal growth efficiency within a range of optimal water temperatures, with declining efficiency at both lower and higher temperatures [80]. Fang et al. [81] reported that water temperature directly impacts the activities of all enzymes, which in turn affect the digestibility and metabolism of nutrients such as proteins and lipids. In addition, the digestive processes and nutrient digestibility of fish larvae decreased at temperatures beyond the optimal range [82]. For example, fish feed more vigorously at higher water temperatures, and their digestive processes are accelerated [83]. In turn, cooler water temperatures reduce nutrient digestibility by reducing digestion rates, increasing gut transit time, and lowering gastrointestinal evacuation rates [84]. Furthermore, the metabolism and physiology, feeding behavior, and growth performance of fish are affected by prolonged temperature stress [68,85].

4.5. Mitigation Measures as Perceived by the Hatchery Owners

The impact of CC on hatchery productivity is multi-factorial and cost-effectively addressing its negative effects is challenging. In this study, most hatchery owners perceived that controlling water temperature and quality (Figure 4) are the prime mitigation and adaptation strategies. Fish farmers and hatchery owners have continued to produce fish for an extended period despite adverse climatic conditions. Hatchery-based seed production is critically impacted by climatic factors. As a result, fish hatchery seed production is impeded, affecting aquaculture productivity and resulting in economic losses. Sustainable mitigation strategies to combat poor climatic conditions have not been established yet in hatchery production and the aquaculture sector. The results of this survey revealed that farmers have observed benefits from implementing several mitigation measures and also highlighted that future mitigation measures, if cost-effective, could result in increased benefits. Farmers and hatchery owners are front-line stakeholders in fish production and have been attempting to adopt appropriate, cost-effective measures to tackle the adverse climatic conditions, as CC has a direct impact on fish farms and hatcheries. Several studies present cost-effective CC mitigation strategies for farms and fish hatcheries. Alam et al. [32] reported that commercial fish hatcheries should utilize cloth covered sheds for brood hapas to generate more eggs in the higher-temperature months. In addition, farmers pump freshwater into fish culture ponds to lower the temperature [21]. During the summer, several farmers use oxygen tablets in the ponds to increase the amount of oxygen in the water [32]. Adhikari et al. [32] reported that 60% of farmers maintain pond water levels by pumping water from boreholes, 48% used mesh-like structures in pond bunds to prevent fish from escaping in the event of flooding, and 16% used pumps to remove water. To operate their businesses, hatchery owners must be skilled in various areas to deal with increased technical issues. This study highlights this issue alongside other findings. Hemal et al. [10] reported that hatchery owners require more technical knowledge to run hatcheries effectively, and their capacity building is necessary for successfully producing hatchery-based seed and managing the related business.
According to Maulu et al. [20], mitigation and adaptation measures may help farming communities, ecosystems, and populations become more resilient to CC. Table 7 summarizes the existing mitigation techniques and future possible mitigation measures under adverse climatic conditions.
Several hatchery owners profited from implementing some of these mitigation measures; however, further research is needed to determine which mitigation practices and adaptation strategies are most suited for long-term hatchery seed production. Furthermore, to ensure sustainable output in the future, a long-term investigation of additional prospective mitigation techniques is required in laboratory and hatchery environments.

5. Conclusions

The overall findings of the present investigation showed that temperature, rainfall, and solar radiation influence hatchery productivity negatively. Therefore, the results of the present study on the perceptions of hatchery owners are appropriate and the most contextual in this regard. According to hatchery owners, the mitigation practices discussed in this study might have a positive impact on hatchery seed production, but the outcomes of several possible future mitigation measures are unknown. As a result, more laboratory and hatchery-based research is needed to increase hatchery seed production and sustainable aquaculture production under harsh climatic conditions.

6. New Insights

This paper investigated a different aspect from the perspective of hatchery owners on CC and expressed it in their language, which provides a new insight for readers.

Author Contributions

M.A.B.S.: introduction, methodology development, overall study and analysis of hatchery owners’ perception, analysis and presentation of mitigation strategies, data curation, and writing the original draft. A.K.S.A.: concept development, investigation, supervision, editing the draft. B.M.: analysis of general characteristics, visualization, data curation, contributed to writing the original draft. M.M.A.: principal component analysis, related data analysis, writing—original draft. N.A.H.: concept development, investigation, data analysis, editing the draft. A.B.: concept development, investigation, data analysis, editing the draft. J.C.B.: fund acquisition, writing—review and editing. M.M.H.: conceptualization, abstract writing, validation, investigation, roles/writing—original draft; writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This study was conducted under a collaborative project ‘Modelling climate change impact on Agriculture and developing mitigation and adaptation strategies for sustaining agricultural production in Bangladesh’ (grant number 2020/1201/KGF) funded by the Krishi Gobeshona Foundation (KGF), CRP-II (second phase).

Institutional Review Board Statement

This study was conducted in accordance with the declaration of, and approved by Ethical Standard of Research Committee formed by BAURES.

Informed Consent Statement

Not Applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Acknowledgments

The authors thank all the fish hatchery owners for willingly providing valuable data and information for this study.

Conflicts of Interest

The authors disclosed no conflict of interest to anybody or any organization.

References

  1. Henriksson, P.J.G.; Zhang, W.; Nahid, S.A.A.; Newton, R.; Phan, L.T.; Dao, H.M.; Zhang, Z.; Jaithiang, J.; Andong, R.; Chaimanuskul, K.; et al. Final LCA Case Study Report—Results of LCA Studies of Asian Aquaculture Systems for Tilapia, Catfish, Shrimp, and Freshwater Prawn; Leiden University: Leiden, The Netherlands, 2014; Volume D 3.5, 165p. [Google Scholar]
  2. DoF. National Fish Week 2022 Compendium; Department of Fisheries, Ministry of Fisheries and Livestock: Dhaka, Bangladesh, 2022; 160p. (In Bengali)
  3. Alam, M.M.; Haque, M.M.; Aziz, S.B.; Mondol, M.M.R. Development of pangasius–carp polyculture in Bangladesh: Understanding farm characteristics by, and association between, socio-economic and biological variables. Aquaculture 2019, 505, 431–440. [Google Scholar] [CrossRef]
  4. DoF. Yearbook of Fisheries Statistics 2019–2020; Fisheries Resources Survey System (FRSS), Department of Fisheries, Ministry of Fisheries and Livestock: Dhaka, Bangladesh, 2020; Volume 37, 141p.
  5. Dutta, J.; Sen, T.; Mitra, A.; Zaman, S.; Mitra, A. Brief commentary on the impact of global climate change on fisheries and aquaculture with special reference to India. Bangladesh J. Zool. 2020, 48, 457–463. [Google Scholar] [CrossRef]
  6. WorldFish Centre. Global Vulnerability of Fisheries Systems to Climate Change; ISSUES, Brief/1701; WorldFish Centre: Penang, Malaysia, 2007. [Google Scholar]
  7. Haque, M.M.; Alam, M.R.; Alam, M.M.; Basak, B.; Sumi, K.R.; Belton, B.; Murshed-E-Jahan, K. Integrated floating cage aquageoponics system (IFCAS): An innovation in fish and vegetable production for shaded ponds in Bangladesh. Aquac. Rep. 2015, 2, 1–9. [Google Scholar] [CrossRef] [Green Version]
  8. FAO. Climate Change Implications for Fisheries and Aquaculture. Summary of the findings of the IPCC Fifth Assessment Report. In FAO Fisheries and Aquaculture Circular: Vol. FIAP/C1122; Food and Agricultural Organization: Rome, Italy, 2016; 65p. [Google Scholar]
  9. Parvez, M.S.; Rahman, M.A.; Hasan, M.J.; Rasel, M.S.E.; Shaikh, M.M.; Molla, M.H.R.; Chowdhury, S.H.; Billah, M.M. Role of Hatchery on Fish Seed Production in Patuakhali District of Bangladesh: An Overview. Int. J. Chem. Environ. Biol. Sci. 2018, 6, 1–7. [Google Scholar]
  10. Hemal, S.; Uddin, M.S.; Uddin, M.S.; Majumdar, B.C.; Rasul, M.G.; Alam, M.T. Present status and problems of fish seed marketing in Sylhet district, Bangladesh. Res. Agric. Livest. Fish. 2017, 4, 45–54. [Google Scholar] [CrossRef] [Green Version]
  11. Debnath, S.; Hossen, S.; Sharker, M.R.; Ghosh, A.; Ferdous, A.; Zannat, L.K.; Ali, M.M. Fish Seed Producing Hatcheries in Southern Bangladesh: An Overview. Middle-East J. Sci. Res. 2020, 28, 199–206. [Google Scholar]
  12. Haque, M.M. Fisheries and Aquaculture in Seasonal Bangladesh: Implications of Climate Change. In Impacts of Climate Change on Livelihoods, Agriculture and Aquaculture & Fisheries Sector of Bangladesh; Wahab, M.A., Salam, M.A., Eds.; Department of Aquaculture, Bangladesh Agricultural University: Mymensingh, Bangladesh, 2009; pp. 47–53. [Google Scholar]
  13. Kausar, R.; Salim, M. Effect of Water Temperature on the Growth Performance and Feed Conversion Ratio of Labeo rohita. Pak. Vet. J. 2006, 26, 105–108. [Google Scholar]
  14. Khater, E.S.G.; Ali, S.A.; Mohamed, W.E. Effect of Water Temperature on Masculinization and Growth of Nile Tilapia Fish. J. Aquac. Res. Dev. 2017, 8, 8–12. [Google Scholar] [CrossRef]
  15. Faruk, M.A.R.; Mausumi, M.I.; Anka, I.Z.; Hasan, M.M. Effects of temperature on the egg production and growth of monosex Nile Tilapia Oreochromis niloticus fry. Bangladesh Res. Publ. J. 2012, 7, 367–377. [Google Scholar]
  16. Usman, I.; Auta, J.; Abdullahi, S.A. Effect of monthly variation in water temperature on artificial breeding of common carp (Cyprinus carpio L.) in Zaria, Nigeria. Int. J. Fish. Aquat. Stud. 2015, 3, 353–356. [Google Scholar]
  17. Remen, M.; Nederlof, M.A.J.; Folkedal, O.; Thorsheim, G.; Sitjà-Bobadilla, A.; Pérez-Sánchez, J.; Oppedal, F.; Olsen, R.E. Effect of temperature on the metabolism, behaviour and oxygen requirements of Sparus aurata. Aquac. Environ. Interact. 2015, 7, 115–123. [Google Scholar] [CrossRef] [Green Version]
  18. O’Gorman, E.J.; Ólafsson, Ó.P.; Demars, B.O.L.; Friberg, N.; Guðbergsson, G.; Hannesdóttir, E.R.; Jackson, M.C.; Johansson, L.S.; McLaughlin, Ó.B.; Ólafsson, J.S.; et al. Temperature effects on fish production across a natural thermal gradient. Glob. Chang. Biol. 2016, 22, 3206–3220. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  19. Mazumder, S.K.; De, M.; Mazlan, A.G.; Zaidi, C.C.; Rahim, S.M.; Simon, K.D. Impact of global climate change on fish growth, digestion and physiological status: Developing a hypothesis for cause and effect relationships. J. Water Clim. Chang. 2015, 6, 200–226. [Google Scholar] [CrossRef]
  20. Maulu, S.; Hasimuna, O.J.; Haambiya, L.H.; Monde, C.; Musuka, C.G.; Makorwa, T.H.; Munganga, B.P.; Phiri, K.J.; Nsekanabo, J.D.M. Climate Change Effects on Aquaculture Production: Sustainability Implications, Mitigation, and Adaptations. Front. Sustain. Food Syst. 2021, 5, 609097. [Google Scholar] [CrossRef]
  21. Adhikari, S.; Chaudhury, A.K.; Gangadhar, B.; Ramesh, R.; Mandal, R.N.; Sarosh, I.; Saha, G.S.; De, H.K.; Sivaraman, I.; Mahapatra, A.S.; et al. Adaptation and Mitigation Strategies of Climate Change Impact in Freshwater Aquaculture in some states of India. J. FisheriesSciences.com 2018, 12, 16–21. [Google Scholar]
  22. Hossan, M.S.; Ulka, S.B.; Motin, M.A.; Tarafder, M.A.K.; Sukhan, Z.P.; Rashid, H. Egg and fry production performance of female tilapia related to fluctuating temperature and size variation. In Proceedings of the 4th the International Conference on Environmental Aspects of Bangladesh, Fukuoka, Japan, 24–25 August 2013; pp. 105–108. [Google Scholar]
  23. Okunsebor, S.; Ofojekwu, P.; Kakwi, D.; Audu, B. Effect of Temperature on Fertilization, Hatching and Survival Rates of Heterobranchus bidorsalis Eggs and Hatchlings. Br. J. Appl. Sci. Technol. 2015, 7, 372–376. [Google Scholar] [CrossRef]
  24. Valeta, J.S.; Likongwe, J.S.; Kassam, D.; Maluwa, A.O. Temperature-dependent egg development rates, hatchability and fry survival rate of Lake Malawi Tilapia (Chambo), Oreochromis karongae (Pisces: Cichlidae). Int. J. Fish. Aquac. 2013, 5, 55–59. [Google Scholar]
  25. Hossain, M.I.; Khatun, M.; Kamal, B.M.M.; Habib, K.A.; Tumpa, A.S.; Subba, B.R.; Hossain, M.Y. Effects of Seasonal variation on Growth Performance of Mirror carp (Cyprinus carpio ver. specularis) in Earthen Nursery Ponds. Our Nat. 2015, 12, 8–18. [Google Scholar]
  26. Politis, S.N.; Mazurais, D.; Servili, A.; Zambonino-Infante, J.L.; Miest, J.J.; Sørensen, S.R.; Tomkiewicz, J.; Butts, I.A.E. Temperature effects on gene expression and morphological development of European eel, Anguilla anguilla larvae. PLoS ONE 2017, 12, e0182726. [Google Scholar] [CrossRef]
  27. Yoo, G.Y.; Lee, J.Y. The effect of feeding frequency, water temperature, and stocking density on the growth of river puffer Takifugu obscurus reared in a zero-exchange water system. Fish. Aquat. Sci. 2016, 19, 23. [Google Scholar] [CrossRef] [Green Version]
  28. Parvin, G.A.; Fujita, K.; Matsuyama, A.; Shaw, R.; Sakamoto, M. Climate Change, Flood, Food Security and Human Health: Cross-Cutting Issues in Bangladesh. In Food Security and Risk Reduction in Bangladesh; Habiba, U., Hassan, A.W.R., Abedin, M.A., Shaw, R., Eds.; Springer: Berlin/Heidelberg, Germany, 2015; pp. 187–212. [Google Scholar]
  29. Chowdhury, M.T.H.; Sukhan, Z.P.; Hannan, M.A. Climate change and its impact on fisheries resource in Bangladesh. In Proceedings of the International Conference on Environmental Aspects of Bangladesh (ICEAB10), Fukuoka, Japan, 4 September 2010; pp. 95–98. [Google Scholar]
  30. Mallick, A.; Panigrahi, A.K. Effect of temperature variation on disease proliferation of common fishes in perspective of climate change. Int. J. Exp. Res. Rev. 2018, 16, 40–49. [Google Scholar] [CrossRef]
  31. Islam, M.A.; Islam, M.S.; Wahab, M.A. Impacts of climate change on shrimp farming in the South-West coastal region of Bangladesh. Res. Agric. Livest. Fish. 2016, 3, 227–239. [Google Scholar] [CrossRef]
  32. Alam, S.M.A.; Sarkar, M.S.I.; Miah, M.M.A.; Rashid, H. Management strategies for Nile Tilapia (Oreochromis niloticus) hatchery in the face of climate change induced rising temperature. Aquac. Stud. 2021, 21, 55–62. [Google Scholar] [CrossRef]
  33. Hasan, N.A.; Heal, R.D.; Bashar, A.; Bablee, L.A.; Haque, M.M. Impacts of COVID-19 on the finfish aquaculture industry of Bangladesh: A case study. Mar. Policy 2021, 130, 104577. [Google Scholar] [CrossRef]
  34. Ahmed, N.; Toufique, K. Greening the blue revolution of small-scale freshwater aquaculture in Mymensingh, Bangladesh. Aquac. Res. 2015, 46, 2305–2322. [Google Scholar] [CrossRef]
  35. Alam, M.M.; Haque, M.M. Presence of antibacterial substances, nitrofuran metabolites and other chemicals in farmed pangasius and tilapia in Bangladesh: Probabilistic health risk assessment. Toxicol. Rep. 2021, 8, 248–257. [Google Scholar] [CrossRef]
  36. Malinowski, R.M. Factor Analysis in Chemistry, 2nd ed.; Wiley: New York, NY, USA, 1991; 368p. [Google Scholar]
  37. Statheropoulos, M.; Vassiliadis, N.; Pappa, A. Principal component and canonical correlation analysis for examining air pollution and meteorological data. Atmos. Environ. 1998, 32, 1087–1095. [Google Scholar] [CrossRef]
  38. Mabe, F.N.; Donkoh, S.A.; Al-Hassan, S. Technology adoption typology and rice yield differentials in Ghana: Principal component analysis approach. Afr. J. Sci. Technol. Innov. Dev. 2019, 11, 555–567. [Google Scholar] [CrossRef]
  39. Pravakar, P.; Sarker, B.S.; Rahman, M.; Hossain, M.B. Present Status of Fish Farming and Livelihood of Fish Farmers in Shahrasti Upazila of Chandpur District, Bangladesh. Am.-Eurasian J. Agric. Environ. Sci. 2013, 13, 391–397. [Google Scholar]
  40. Khatun, S.; Adhikary, R.K.; Rahman, M.; Nurul, M.; Sikder, A.; Hossain, M.B. Socioeconomic Status of Pond Fish Farmers of Charbata, Noakhali, Bangladesh. Int. J. Life Sci. Biotechnol. Pharma Res. 2013, 2, 2–12. [Google Scholar]
  41. Mithun, M.; Kowsari, M.; Sheheli, S. Socioeconomic characteristics and constraints of participatory pond fish farmers in Mymensingh district, Bangladesh. Int. J. Agric. Res. Innov. Technol. 2021, 10, 170–176. [Google Scholar] [CrossRef]
  42. Uddin, M.N.; Kabir, K.H.; Roy, D.; Hasan, M.T.; Sarker, M.A.; Dunn, E.S. Understanding the constraints and its related factors in tilapia (Oreochromis sp.) fish culture at farm level: A case from Bangladesh. Aquaculture 2021, 530, 735927. [Google Scholar] [CrossRef]
  43. Ali, H.; Azad, M.A.K.; Anisuzzaman, M.; Chowdhury, M.M.R.; Hoque, M.; Shariful, M.I. Livelihood status of the fish farmers in some selected areas of Tarakanda upazila of Mymensingh district. J. Agrofor. Environ. 2010, 3, 85–89. [Google Scholar]
  44. BBS. Statistical Yearbook of Bangladesh Bureau of Statistics; Statistical Division, Ministry of Planning, Government of the People’s Republic of Bangladesh: Dhaka, Bangladesh, 2002; 660p.
  45. Ali, M.; Hossain, M.D.; Hasan, A.N.G.M.; Bashar, M.A. Assessment of the livelihood status of the fish farmers in some selected areas of Bagmara Upazilla under Rajshahi district. J. Bangladesh Agric. Univ. 2008, 6, 367–374. [Google Scholar] [CrossRef] [Green Version]
  46. Zaman, T.; Jewel, M.A.S.; Bhuiyan, A.S. Present Status of Pond Fishery Resources and Livelihood of the Fish Farmers of Mohanpur Upazila in Rajshahi District. Univ. J. Zool. Rajshahi Univ. 2006, 25, 31–35. [Google Scholar] [CrossRef]
  47. Tasnoova, S.; Iqbal, K.M.; Iwamoto, I.; Haque, M.M. Economic performance of fish-based farming systems in Bangladesh. J. Fish. Aquat. Sci. 2008, 3, 206–212. [Google Scholar] [CrossRef] [Green Version]
  48. Islam, A.B.M.S.; Farouque, M.G.; Roy, D. Problem Confronted by the Fish Farmers in Practicing Semi-intensive climbing perch (Anabus testubineus) farming. Bangladesh J. Ext. Educ. 2013, 25, 53–61. [Google Scholar]
  49. Rahman, M.A.; Alam, M.M.; Barman, S.K.; Hossain, M.J.; Tikadar, K.K. Effect of COVID-19 on Fisheries Products Exported from Southwest Bangladesh: A Case Study. J. Bangladesh Agric. Univ. 2022, 20, 217–224. [Google Scholar] [CrossRef]
  50. Azad, A.K.; Wadood, S.N. The Impact of Climate Change on Fish Production in Bangladesh: An Assessment; Bureau of Economic Research (BER), University of Dhaka: Dhaka, Bangladesh, 2020. [Google Scholar] [CrossRef]
  51. Faruque, M.H.; Kabir, M.A. Climate change effects on aquaculture: A case study from north western Bangladesh. Int. J. Fish. Aquat. Stud. 2016, 4, 550–556. [Google Scholar]
  52. Alam, E.; Mallick, B. Climate change perceptions, impacts and adaptation practices of fishers in southeast Bangladesh coast. Int. J. Clim. Chang. Strateg. Manag. 2022, 14, 191–211. [Google Scholar] [CrossRef]
  53. Halim, M.A.; Mondal, D.K.; Salam, M.A.; Hossain, M.S. Impacts of climate change on pond fish farming in Amtoli, Borguna, Bangladesh. Int. J. Fish. Aquat. Stud. 2017, 5, 38–41. [Google Scholar]
  54. Rahman, M.L.; Shahjahan, M.; Ahmed, N. Tilapia farming in Bangladesh: Adaptation to climate change. Sustainability 2021, 13, 7657. [Google Scholar] [CrossRef]
  55. McNamara, J.M.; Barta, Z.; Klaassen, M.; Bauer, S. Cues and the optimal timing of activities under environmental changes. Ecol. Lett. 2011, 14, 1183–1190. [Google Scholar] [CrossRef] [PubMed]
  56. Pankhurst, N.W.; Munday, P.L. Effects of climate change on fish reproduction and early life history stages. Mar. Freshw. Res. 2011, 62, 1015–1026. [Google Scholar] [CrossRef] [Green Version]
  57. Alfonso, S.; Gesto, M.; Sadoul, B. Temperature increases and its effects on fish stress physiology in the context of global warming. J. Fish Biol. 2021, 98, 1496–1508. [Google Scholar] [CrossRef]
  58. Aziz, M.S.B.; Hasan, N.A.; Mondol, M.M.R.; Alam, M.M.; Haque, M.M. Decline in fish species diversity due to climatic and anthropogenic factors in HakalukiHaor, an ecologically critical wetland in northeast Bangladesh. Heliyon 2021, 7, e05861. [Google Scholar] [CrossRef]
  59. Dastansara, N.; Vaissi, S.; Mosavi, J.; Sharifi, M. Impacts of temperature on growth, development and survival of larval Bufo (Pseudepidalea) viridis (Amphibia: Anura): Implications of climate change. Zool. Ecol. 2017, 27, 228–234. [Google Scholar] [CrossRef]
  60. Pereira, B.F. Effect of Temperature on Sperm Motility in Fishes—A Review. Int. J. Sci. Res. Methodol. 2016, 5, 81–89. [Google Scholar]
  61. Muchlisin, Z.A. A General Overview on Some Aspects of Fish Reproduction. Aceh Int. J. Sci. Technol. 2014, 3, 43–52. [Google Scholar] [CrossRef]
  62. Karmakar, S.; Purkait, S.; Das, A.; Samanta, R.; Kumar, K. Climate change and inland fisheries: Impact and mitigation strategies. J. Exp. Zool. 2018, 21, 329–335. [Google Scholar]
  63. Tucker, J.W. Marine Fish Culture; Springer: Boston, MA, USA, 1998; 750p. [Google Scholar] [CrossRef]
  64. Stien, L.H.; Bracke, M.B.M.; Folkedal, O.; Nilsson, J.; Oppedal, F.; Torgersen, T.; Kittilsen, S.; Midtlyng, P.J.; Vindas, M.A.; Øverli, Ø. Salmon Welfare Index Model (SWIM 1.0): A semantic model for overall welfare assessment of caged Atlantic salmon: Review of the selected welfare indicators and model presentation. Rev. Aquac. 2013, 5, 33–57. [Google Scholar] [CrossRef]
  65. Cascarano, M.C.; Stavrakidis-Zachou, O.; Mladineo, I.; Thompson, K.D.; Papandroulakis, N.; Katharios, P. Mediterranean Aquaculture in a Changing Climate: Temperature Effects on Pathogens and Diseases of Three Farmed Fish Species. Pathogens 2021, 10, 1205. [Google Scholar] [CrossRef] [PubMed]
  66. Chiaramonte, L.; Munson, D.; Trushenski, J. Climate Change and Considerations for Fish Health and Fish Health Professionals. Fisheries 2016, 41, 396–399. [Google Scholar] [CrossRef]
  67. Harasawa, H.; Matsuoka, Y.; Takahashi, K.; Hijioka, Y.; Shimada, Y.; Munesue, Y.; Lal, M. Potential Impacts of Global Climate Change. In Climate Policy Assessment Asian-Pacific Integrated Modeling; Kainuma, Y.M., Matsuoka, Y., Morita, T., Eds.; Springer: Berlin/Heidelberg, Germany, 2003; pp. 37–54. [Google Scholar]
  68. Marcogliese, D.J. The impact of climate change on the parasites and infectious diseases of aquatic animals. Rev. Sci. Tech. 2008, 27, 467–484. [Google Scholar] [CrossRef]
  69. Cochrane, K.; De Young, C.; Soto, D.T.; Bahri, D.T. Climate Change Implications for Fisheries and Aquaculture: Overview of Current Scientific Knowledge; FAO Fisheries and Aquaculture Technical Paper No. 530; FAO: Rome, Italy, 2009. [Google Scholar]
  70. Burge, C.A.; Eakin, C.M.; Friedman, C.S.; Froelich, B.; Hershberger, P.K.; Hofmann, E.E.; Petes, L.E.; Prager, K.C.; Weil, E.; Willis, B.L.; et al. Climate Change Influences on Marine Infectious Diseases: Implications for Management and Society. Annu. Rev. Mar. Sci. 2014, 6, 249–277. [Google Scholar] [CrossRef] [Green Version]
  71. Harvell, C.D.; Mitchell, C.E.; Ward, J.R.; Altizer, S.; Dobson, A.P.; Ostfeld, R.S.; Samuel, M.D. Climate warming and disease risks for terrestrial and marine biota. Science 2002, 296, 2158–2162. [Google Scholar]
  72. Altizer, S.; Ostfeld, R.S.; Johnson, P.T.; Kutz, S.; Harvell, C.D. Climate change and infectious diseases: From evidence to apredictive framework. Science 2013, 341, 514–519. [Google Scholar] [CrossRef] [Green Version]
  73. Egan, S.; Gardiner, M. Microbial dysbiosis: Rethinking disease in marine ecosystems. Front. Microbiol. 2016, 7, 991. [Google Scholar] [CrossRef]
  74. Islam, M.A.; Akber, M.A.; Ahmed, M.; Rahman, M.M.; Rahman, M.R. Climate change adaptations of shrimp farmers: A case study from southwest coastal Bangladesh. Clim. Dev. 2019, 11, 459–468. [Google Scholar] [CrossRef]
  75. Ahmed, N.; Diana, J.S. Coastal to inland: Expansion of prawn farming for adaptation to climate change in Bangladesh. Aquac. Rep. 2015, 2, 67–76. [Google Scholar] [CrossRef] [Green Version]
  76. Lafferty, K.D. The ecology of climate change and infectious diseases. Ecology 2009, 90, 888–900. [Google Scholar] [CrossRef] [PubMed]
  77. Trainer, V.L.; Moore, S.K.; Hallegraeff, G.; Kudela, R.M.; Clement, A.; Mardones, J.I.; Cochlan, W.P. Pelagic harmful algal blooms and climate change: Lessons from nature’s experiments with extremes. Harmful Algae 2019, 91, 101591. [Google Scholar] [CrossRef]
  78. Shafland, P.L.; Pestrak, J.M. Lower lethal temperatures for fourteen non-native fishes in Florida. Environ. Biol. Fishes 1982, 7, 149–156. [Google Scholar] [CrossRef]
  79. Ngoan, L.D. Effects of climate change in aquaculture: Case study in Thua Thien Hue Province, Vietnam. Biomed. Int. J. Sci. Technol. Res. 2018, 10, 7551–7552. [Google Scholar] [CrossRef]
  80. Björnsson, B.; Tryggvadóttir, S.V. Effects of size on optimal temperature for growth and growth efficiency of immature Atlantic halibut (Hippoglossus hippoglossus L.). Aquaculture 1996, 142, 33–42. [Google Scholar] [CrossRef]
  81. Fang, J.; Tian, X.; Dong, S. The influence of water temperature and ration on the growth, body composition and energy budget of tongue sole (Cynoglossus semilaevis). Aquaculture 2010, 299, 106–114. [Google Scholar] [CrossRef]
  82. Amin, M.N.; Carter, C.G.; Barnes, R.S.K.; Adams, L.R. Protein and energy nutrition of brook trout (Salvelinus fontinalis) at optimal and elevated temperatures. Aquac. Nutr. 2016, 22, 527–540. [Google Scholar] [CrossRef]
  83. Charo, H.K. Selection for Growth of Nile tilapia (Oreochromis niloticus L.) in Low Input Environments. Ph.D. Thesis, Wageningen University, Wageningen, The Netherlands, 2006. [Google Scholar]
  84. Miegel, R.P.; Pain, S.J.; van Wettere, W.H.E.J.; Howarth, G.S.; Stone, D.A.J. Effect of water temperature on gut transit time, digestive enzyme activity and nutrient digestibility in yellowtail kingfish (Seriola lalandi). Aquaculture 2010, 308, 145–151. [Google Scholar] [CrossRef]
  85. Lemasson, A.J.; Hall-Spencer, J.M.; Fletcher, S.; Provstgaard-Morys, S.; Knights, A.M. Indications of future performance of native and nonnative adult oysters under acidification and warming. Mar. Environ. Res. 2018, 142, 178–189. [Google Scholar] [CrossRef]
Fishes 07 00270 g001 550
Figure 1. Study sites of the Mymensingh district.
Figure 1. Study sites of the Mymensingh district.
Fishes 07 00270 g001
Fishes 07 00270 g002 550
Figure 2. Scree plot (explained variance of each principal component) calculated for the factors.
Figure 2. Scree plot (explained variance of each principal component) calculated for the factors.
Fishes 07 00270 g002
Fishes 07 00270 g003 550
Figure 3. Loading plot corresponding to the top two principal components.
Figure 3. Loading plot corresponding to the top two principal components.
Fishes 07 00270 g003
Fishes 07 00270 g004 550
Figure 4. Responses of hatchery owners towards mitigation and adaptation to climate change.
Figure 4. Responses of hatchery owners towards mitigation and adaptation to climate change.
Fishes 07 00270 g004
Table
Table 1. General characteristics of hatchery owners and hatcheries.
Table 1. General characteristics of hatchery owners and hatcheries.
General Characteristics Number%
Age of hatchery ownersYoung age (15–30)46.67
Middle age (31–50)3660.00
Old age (51–65)2033.33
GenderMale60100.00
Female00.00
EducationIlliterate11.67
Adult literacy/informal education11.67
Class I to V1118.33
Class VI to X2338.33
Class XI to above2440.00
Age of hatchery1–12 Years3558.33
13–24 Years1830.00
25–36 Years711.67
Size of hatcherySmall2846.67
Medium1321.67
Large1931.67
Year of fish production1–5 Years1525.00
6–10 Years1423.33
Above 10 Years3151.67
Training experienceYes60100.00
No00.00
Run other businessYes3050.00
No3050.00
Challenges face in the hatchery
production		Yes60100.00
No00.00
Table
Table 2. Hatchery owners’ perceptions of climate change.
Table 2. Hatchery owners’ perceptions of climate change.
Perceptions of the Causes Responsible for Climate ChangeResponses (%)
Strongly AgreeAgreeNeutralDisagreeStrongly Disagree
Rising air temperature6.6763.3330.000.000.00
Rising water temperature6.6768.3325.000.000.00
Frequent natural calamities such as flood, cyclones, heavy rainfall, water logging, flash flood, etc.1.6945.7652.540.000.00
Prolonged drought0.0022.0376.271.690.00
River erosion0.0015.0083.331.670.00
Rising sea level0.0035.0063.331.670.00
Intense thunderstorm0.0021.6776.671.670.00
Table
Table 3. Model summary of the predictors.
Table 3. Model summary of the predictors.
Model Summary
ModelRR SquareAdjusted R SquareStd. Error of the Estimate
10.372 a0.1390.1221.495
20.493 b0.2430.2141.414
30.558 c0.3120.2701.362
a Predictors: (Constant), Erratic rainfall; b Predictors: (Constant), Erratic rainfall, high temperature; c Predictors: (Constant), Erratic rainfall, high temperature, solar radiation.
Table
Table 4. Analysis of Variance (ANOVA) of the regression model.
Table 4. Analysis of Variance (ANOVA) of the regression model.
ANOVA a
ModelSum of SquaresdfMean SquareFSig.
1Regression18.680118.6808.3630.006 b
Residual116.153522.234
Total134.83353
2Regression32.808216.4048.2000.001 c
Residual102.026512.001
Total134.83353
3Regression42.024314.0087.5470.000 d
Residual92.810501.856
Total134.83353
a Dependent Variable: Hatchery owners’ perceptions on climate change; b Predictors: (Constant), Erratic rainfall; c Predictors: (Constant), Erratic rainfall, high temperature; d Predictors: (Constant), Erratic rainfall, high temperature, solar radiation.
Table
Table 5. Eigenvalues of the correlation matrix.
Table 5. Eigenvalues of the correlation matrix.
Principal ComponentEigenvalueDifferenceProportion (%)Cumulative (%)
16.0094.77150.0850.08
21.2380.06010.3260.39
31.1780.2179.8270.21
40.9610.3338.0178.22
50.6280.0795.2383.45
60.5480.1034.5788.02
70.4450.0573.7191.73
80.3890.1293.2494.97
90.2600.1022.1797.14
100.1580.0471.3298.45
110.1110.0360.9399.38
120.075-0.62100.00
Table
Table 6. Rotated component matrix and correlation coefficients of the variables with significant components for characterizing climate change impacts on fish hatchery operation.
Table 6. Rotated component matrix and correlation coefficients of the variables with significant components for characterizing climate change impacts on fish hatchery operation.
Rotated Component Matrix a
Component
PC 1PC 2PC 3
Poor larval growth 0.874
Poor gonadal maturation 0.861
Low hatching rate 0.859
Poor egg quality 0.849
Poor seed quality 0.823
Low fecundity 0.784
Poor sperm quality 0.736
Disease occurrence 0.810
Poor survival of larvae 0.750
Poor water quality 0.530
Poor digestion 0.701
Hampered growth rate of broodstock 0.661
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a Rotation converged in 4 iterations.
Table
Table 7. Summary of the possible mitigation and adaptation measures under adverse climatic conditions as stated by hatchery owners.
Table 7. Summary of the possible mitigation and adaptation measures under adverse climatic conditions as stated by hatchery owners.
Mitigation and Adaptation StrategiesMethodTimeframeImpact
Increasing the inside air temperatureUse of polythene sheets to cover the hatcheryDuring the seed production cycle, when the temperature falls below the optimum Positive
Maintaining favorable nursery and broodfish pond water temperatureSupply clean additional water to increase the volume of water in the hatchery tank and broodfish pond If the seed and broodfish pond temperature exceeds tolerable limits. Positive
Maintaining water oxygen levelsUse of a simple aerator system and oxygen tablets If oxygen levels drop during hatchery seed production and pond broodfish management.Positive
Preventing fish from escaping during seasonal floodsRepairing and raising pond dikesIn the dry seasonUnknown
Creating a cool production environmentSuitable tree planting in pond dikes and the hatchery compoundIn the wet seasonEnvironmentally friendly hatchery compound
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Siddique, M.A.B.; Ahammad, A.K.S.; Mahalder, B.; Alam, M.M.; Hasan, N.A.; Bashar, A.; Biswas, J.C.; Haque, M.M. Perceptions of the Impact of Climate Change on Performance of Fish Hatcheries in Bangladesh: An Empirical Study. Fishes 2022, 7, 270. https://doi.org/10.3390/fishes7050270

AMA Style

Siddique MAB, Ahammad AKS, Mahalder B, Alam MM, Hasan NA, Bashar A, Biswas JC, Haque MM. Perceptions of the Impact of Climate Change on Performance of Fish Hatcheries in Bangladesh: An Empirical Study. Fishes. 2022; 7(5):270. https://doi.org/10.3390/fishes7050270

Chicago/Turabian Style

Siddique, Mohammad Abu Baker, A. K. Shakur Ahammad, Balaram Mahalder, Md. Mehedi Alam, Neaz A. Hasan, Abul Bashar, Jatish Chandra Biswas, and Mohammad Mahfujul Haque. 2022. "Perceptions of the Impact of Climate Change on Performance of Fish Hatcheries in Bangladesh: An Empirical Study" Fishes 7, no. 5: 270. https://doi.org/10.3390/fishes7050270

Article Metrics

Back to TopTop