The impact of climate variables on marine fish production: an empirical evidence from Bangladesh based on autoregressive distributed lag (ARDL) approach

Begum, Mahfuza; Masud, Muhammad Mehedi; Alam, Lubna; Mokhtar, Mazlin; Amir, Ahmad Aldrie

doi:10.1007/s11356-022-21845-z

Cited by 16 publications

(27 citation statements)

References 77 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…According to Ref. [ 83 ], carbon dioxide has a short-run impact on maize production. Precipitation (PRPT) affects maize output (MZP) in the short run at the 10 % significance level (coefficient = −0.141, p-value = 0.062) [ 84 ], which is supported by the current study.…”

Section: Discussionmentioning

confidence: 99%

Resilience in maize production for food security: Evaluating the role of climate-related abiotic stress in Pakistan

Rizwanullah,

Yang,

Nasrullah

et al. 2023

Heliyon

View full text Add to dashboard Cite

Section: Discussionmentioning

confidence: 99%

Resilience in maize production for food security: Evaluating the role of climate-related abiotic stress in Pakistan

Rizwanullah,

Yang,

Nasrullah

et al. 2023

Heliyon

View full text Add to dashboard Cite

“…, 2021; Emenekwe et al. , 2022; Baig et al ., 2022a, b; Begum et al. , 2022) have also used the AIC criterion to determine the number of lag lengths in the ADF test.…”

Section: Resultsmentioning

confidence: 99%

“…The AIC suggests that lag 4 is the optimal lag value for rice crop in the model and Figure 4 shown the top 20 models selected on the basis of AIC. Other studies (Ali et al, 2019a(Ali et al, , b, 2020(Ali et al, , 2021Nasrulla et al, 2021;Emenekwe et al, 2022;Baig et al, 2022a, b;Begum et al, 2022) have also used the AIC criterion to determine the number of lag lengths in the ADF test. Additionally, the polynomial graph was used to confirm the appropriate lag length under the VAR method, as shown in Figure 3, where the dots inside the circle validate the accuracy of the results.…”

Section: Lag Selection Criteriamentioning

confidence: 99%

An analysis of long-term and short-term impact of climate change on rice production in India

Singh,

Arora,

Babu

2024

CAER

View full text Add to dashboard Cite

PurposeClimate change-related weather events significantly affect rice production. In this paper, we investigate the impact of and interrelationships between agriculture inputs, climate change factors and financial variables on rice production in India from 1970–2021.Design/methodology/approachThis study is based on the time series analysis; the unit root test has been employed to unveil the integration order. Further, the study used various econometric techniques, including vector autoregression estimates (VAR), cointegration test, autoregressive distributed lag (ARDL) model and diagnostic test for ARDL, fully modified least squares (FMOLS), canonical cointegrating regression (CCR), impulse response functions (IRF) and the variance decomposition method (VDM) to validate the long- and short-term impacts of climate change on rice production in India of the scrutinized variables.FindingsThe study's findings revealed that the rice area, precipitation and maximum temperature have a significant and positive impact on rice production in the short run. In the long run, rice area (ß = 1.162), pesticide consumption (ß = 0.089) and domestic credit to private sector (ß = 0.068) have a positive and significant impact on rice production. The results show that minimum temperature and direct institutional credit for agriculture have a significant but negative impact on rice production in the short run. Minimum temperature, pesticide consumption, domestic credit to the private sector and direct institutional credit for agriculture have a negative and significant impact on rice production in the long run.Originality/valueThe present study makes valuable and original contributions to the literature by examining the short- and long-term impacts of climate change on rice production in India over 1970–2021. To the best of the authors’ knowledge, The majority of the studies examined the impact of climate change on rice production with the consideration of only “mean temperature” as one of the climatic variables, while in the present study, the authors have considered both minimum as well as maximum temperature. Furthermore, the authors also considered the financial variables in the model.

show abstract

“…Furthermore, alterations in ocean conditions—such as vegetation or water column depth or structure—can directly affect the availability of suitable habitats for fish. Fish may require time to discover and become acclimated to new habitats, resulting in a lag in their distributional response 30 . Our findings on the time-lagged effect on catch rates are corroborated by a study on Pacific billfish 31 .…”

Section: Discussionmentioning

confidence: 99%

Impact of climatic oscillations on marlin catch rates of Taiwanese long-line vessels in the Indian Ocean

Mondal,

Ray,

Osuka

et al. 2023

Sci Rep

View full text Add to dashboard Cite

This study explored the influence of climatic oscillations on the striped, blue, and silver marlin catch rates in the Indian Ocean by using logbook data from Taiwanese large-scale fishing vessels and climate records from 1994 to 2016. Only the Madden–Julian oscillation (MJO) and the subtropical Indian Ocean dipole (SIOD) had immediate effects on the striped and silver marlin catch rates. The positive and negative phases of the IOD at the lags of 7 and 3 years corresponded to increased and decreased catch rates, respectively, for both the striped and blue marlin, contrasting to the reverse pattern for the silver marlin. Similarly, all three marlin species experienced decreased and increased catch rates respectively during the positive and negative phases of the Pacific decadal oscillation. The striped and blue marlin catch rates decreased and increased during the positive and negative phases, respectively, of the SIOD and MJO with various lags. Our results suggest that the impacts of climatic oscillations on fish species are crucial for policymakers and coastal communities for managing marine resources, forecasting changes in marine ecosystems, and developing strategies to adapt to and mitigate the effects of climate variability.

show abstract

The impact of climate variables on marine fish production: an empirical evidence from Bangladesh based on autoregressive distributed lag (ARDL) approach

Cited by 16 publications

References 77 publications

Resilience in maize production for food security: Evaluating the role of climate-related abiotic stress in Pakistan

Resilience in maize production for food security: Evaluating the role of climate-related abiotic stress in Pakistan

An analysis of long-term and short-term impact of climate change on rice production in India

Impact of climatic oscillations on marlin catch rates of Taiwanese long-line vessels in the Indian Ocean

Contact Info

Product

Resources

About