Qualitative assessment of climate-driven ecological shifts in the Caspian Sea

Abstract

The worldwide occurrence of complex climate-induced ecological shifts in marine systems is one of the major challenges in sustainable bio-resources management. The occurrence of ecological environment-driven shifts was studied in the Southern Caspian Sea using the “shiftogram” method on available fisheries-related (i.e. commercially important bentho-pelagic fish stocks) ecological and climatic variables. As indicators of potential environmentally driven shift patterns we used indices for the North Atlantic Oscillation, the Southern Oscillation, the Siberian High, the East Atlantic-West Russia pattern, as well as Sea Surface Temperature and surface chlorophyll-a concentration. Given the explorative findings from the serial shift analyses, the cascading and serial order of multiple shift events in climatic-ecologic conditions of the southern Caspian Sea suggested a linkage between external forces and dynamics of ecosystem components and structures in the following order: global-scale climate forces lead to local environmental processes, which in turn lead to biological components dynamics. For the first time, this study indicates that ecological shifts are an integral component of bentho-pelagic subsystem regulatory processes and dynamics. Qualitative correspondence of biological responses of bentho-pelagic stocks to climatic events is one of the supporting evidences that overall Caspian ecosystem structures and functioning might have–at least partially–been impacted by global-scale climatic or local environmental shifts. These findings may help to foster a regional Ecosystem-based Approach to Management (EAM) as an integral part of bentho-pelagic fisheries management plans.

Relationships Between Northern Hemisphere Teleconnection Patterns and Phytoplankton Productivity in the Neva Estuary (Northeastern Baltic Sea)

“…There are even fewer studies on the effect of the EAWR teleconnection pattern on phytoplankton productivity. For example, an attempt was made to link the shift regime in the ecosystem of the Caspian Sea, which occurred in the late 1990s and mid-2000s with changes in the EAWR index, but statistically reliable results could not be obtained (Kashkooli et al, 2017). In our study, we also could not have obtained statistically significant correlations between phytoplankton productivity indicators in the Neva Estuary and EAWR teleconnection pattern (Table 2).…”

“…The impact of climate variability on marine and estuarine ecosystem has been extensively discussed in recent decades (e.g., Stenseth et al, 2002;Doney, 2006;Doney et al, 2012;Bogatov and Fedorovskiy, 2016;Le et al, 2019;Golubkov and Golubkov, 2020). Climate fluctuations are exogenous and hidden driving forces that are causing profound large-scale changes in marine ecosystems, affecting the state of their environment and biotic interactions on interannual and longer time scales (Andersen et al, 2011;Doney et al, 2012;Kashkooli et al, 2017;Golubkov, 2021). For instance, interannual fluctuations in air temperature and atmospheric precipitation lead to a change in the runoff of nutrients into the Baltic Sea from the catchment area, as well as to alterations in the composition and productivity of phytoplankton (Kotta et al, 2009;Teutschbein et al, 2017;Golubkov and Golubkov, 2020;Golubkov et al, 2021).…”

“…It is known that atmospheric circulation and weather conditions in different parts of the world are largely determined by teleconnection patterns, and their fluctuations are reasonably well predicted using climate indices (e.g., Krichak and Alpert, 2005;Baldwin et al, 2007;Popova, 2007;Ceglar et al, 2017;Yao and Luo, 2018). Due to this, a relationship between various biological processes and climatic indices has been found in many aquatic ecosystems (Straile and Adrian, 2000;Blenckner and Hillerbrand, 2002;Weyhenmeyer, 2008;Sharov et al, 2014;Gubelit, 2015;Kashkooli et al, 2017;Greaves et al, 2020;Maximov et al, 2021). Climatic indices are used to predict the productivity of open ocean waters (Le et al, 2019;Greaves et al, 2020) and inland seas (Kashkooli et al, 2017).…”

“…Due to this, a relationship between various biological processes and climatic indices has been found in many aquatic ecosystems (Straile and Adrian, 2000;Blenckner and Hillerbrand, 2002;Weyhenmeyer, 2008;Sharov et al, 2014;Gubelit, 2015;Kashkooli et al, 2017;Greaves et al, 2020;Maximov et al, 2021). Climatic indices are used to predict the productivity of open ocean waters (Le et al, 2019;Greaves et al, 2020) and inland seas (Kashkooli et al, 2017). Teleconnection patterns can also be used for paleoreconstructions (Diz et al, 2018), since there are examples of reconstructing data of their values back to 1675 (Luterbacher et al, 1999) or even to 1500 (Luterbacher et al, 2004).…”

Effects of environmental variability on abundance of commercial marine species in the northern Gulf of California

“…This function is an estimate of the association between two variables (CPUE and the physical environmental variables) at the significant temporal leads and lags (George et al 2005). Temporal lags in the relationship between predictors and the response variable were accounted for, because it has been reported that climate indices influence recruitment success of fish species several months and even years later (Kashkooli et al 2017). Positive time lags represent a positive correlation between driver and response and could indicate causality.…”