Influence of climate drivers and fishing effort on fish stock condition using dynamic factor analysis: a case study from the Caspian Sea

Hasan Fazli; Gholam Reza Daryanabard; Akbar Pourgholami; Seyed Abbas Hoseini; Mohammad Reza Mirzaei; Parto Bahreini

doi:10.3989/scimar.05546.089

Authors

Hasan Fazli Caspian Sea Ecology Research Centre, Iranian Fisheries Science Research Institute, Agricultural Research, Education and Extension Organization (AREEO) https://orcid.org/0000-0003-1172-105X
Gholam Reza Daryanabard Caspian Sea Ecology Research Centre, Iranian Fisheries Science Research Institute, Agricultural Research, Education and Extension Organization (AREEO) https://orcid.org/0000-0002-5099-9196
Akbar Pourgholami Inland Waters Aquaculture Research, Iranian Fisheries Science Research Institute, Agricultural Research, Education and Extension Organization (AREEO) https://orcid.org/0000-0002-5020-7523
Seyed Abbas Hoseini Inland Water Stocks Research Centre, Iranian Fisheries Science Research Institute, Agricultural Research, Education and Extension Organization (AREEO) https://orcid.org/0000-0003-3650-2945
Mohammad Reza Mirzaei Offshore Fisheries Research Centre, Iranian Fisheries Science Research Institute, Agricultural Research, Education and Extension Organization (AREEO) https://orcid.org/0000-0003-0885-162X
Parto Bahreini Colangelo College of Business, Grand Canyon University https://orcid.org/0009-0000-1476-2020

DOI:

https://doi.org/10.3989/scimar.05546.089

Keywords:

Abundance, condition factor, overfishing indicators, climate-driven, fishing effort, dynamic factor analysis, coastal waters

Abstract

We explored the potential impact of climate-driven factors [East Atlantic-West Russian pattern, sea surface level (SSL), sea surface temperature (SST) and river discharge] alongside fishing effort (E) on shifts in aquatic species demographics. Dynamic factor analysis (DFA) was employed for indices of annual catch (Cat), Abundance (Abu), fingerlings released, spawning stock biomass (SSB), percentage of immature (Imm), mega spawners and relative condition factor from datasets of Chelon aurata and Rutilus kutum over 30 years. Of 324 DFA models, the optimal model for both species included a “diagonal and unequal“ R matrix with SST, SSL and E as exploratory covariates, revealing one common trend for C. aurata and SST and SSL and two common trends for R. kutum. Within the common trend for C. aurata, Abu and SSB displayed a strong positive correlation with trend 1. In the case of R. kutum, the first common trend showed a positive correlation with Cat, Abu, and SSB and a negative one with Imm. Also, rising SST and decreasing SSL negatively affect species’ health. This study emphasizes integrated monitoring and management to sustain fish species and the ecosystem, advocating adaptive strategies to counter environmental stressors and anthropogenic effects.

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