EconPapers    
Economics at your fingertips  
 

Mathematical Modeling and Intensive Simulations Assess Chances for Recovery of the Collapsed Azov Pikeperch Population

Yuri V. Tyutyunov and Inna Senina ()
Additional contact information
Yuri V. Tyutyunov: Southern Scientific Centre of the Russian Academy of Sciences (SSC RAS), Chekhov Street, 41, Rostov-on-Don 344006, Russia
Inna Senina: The Pacific Community (SPC), BP D5, Noumea 98848, New Caledonia

Mathematics, 2025, vol. 13, issue 19, 1-16

Abstract: The main objective of the study is to evaluate the recovery potential of the collapsed semi-anadromous pikeperch population ( Sander lucioperca L.) in the Azov Sea during 2021–2030. We use a Ricker-based age-structured model that accounts for the effects of salinity and temperature on reproduction. In earlier work, the model predicted and explained the pikeperch stock collapse as the consequence of salinity and temperature exceeding the species’ tolerance limits. To assess the probability of stock recovery, we conducted a long-term retrospective validation and ran Monte Carlo projections under alternative climate scenarios with supplemental management actions. The results confirm that the dynamics of the pikeperch population in the Azov Sea are essentially environment-driven and negatively impacted by the large positive anomalies in both water temperature and salinity. Simulations suggest that either a substantial and persistent artificial restocking of juvenile recruits, or mostly unlikely scenarios of simultaneous reduction in salinity and temperature combined with additional restocking can provide conditions for the stock restoration within the decade considered. Based on these projections, we recommend a suite of urgent restoration measures to create the conditions required for future stock recovery.

Keywords: population dynamics; Monte Carlo simulation; quasi-extinction; risk assessment; water salinization; warming (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/13/19/3232/pdf (application/pdf)
https://www.mdpi.com/2227-7390/13/19/3232/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:13:y:2025:i:19:p:3232-:d:1767123

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-10-10
Handle: RePEc:gam:jmathe:v:13:y:2025:i:19:p:3232-:d:1767123