Early warning of critical transition in east Venezuela’s Sardine (Sardinella aurita, Valenciennes 1847) Fishing Area.

Early warning of critical transition in east Venezuela’s Sardine (Sardinella aurita, Valenciennes 1847) Fishing Area. | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 7 August 2025 V1 Latest version Share on Early warning of critical transition in east Venezuela’s Sardine (Sardinella aurita, Valenciennes 1847) Fishing Area. Authors : Alimar Molero-Lizarraga , Meimalin Moreno-Villalobos 0009-0007-3873-1553 , Jorge Payán-Alejo , and Carlos Méndez-Vallejo 0000-0001-7015-1910 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.175456833.35831799/v1 416 views 161 downloads Contents Abstract Authorship Author contributions: CRediT Acknowledgements Data availability Conflicts of interest Abstract Introduction Methods Results and discussion Conclusions Figure captions References Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Global warming is affecting the thermal tolerance of marine species and disrupting fisheries. Venezuelan sardine ( Sardinella aurita, Valenciennes 1847 ) fisheries are facing a decline possibly linked to climate change. Understanding the temperature trends along coastal areas versus the open ocean is crucial for effectively managing these sensitive species. This study examines Sea Surface Temperature (SST) variability in Venezuela’s Sardine Fishing Area and Exclusive Economic Zone (EEZ), detecting early warning signals (EWS) of critical transition. Using MODIS SST data (2002–2023), we assessed variability in both zones, calculating standard deviation (SD) and first-order autoregressive coefficient AR(1) as indicators. Results showed that while minimum SSTs were similar and stable, mean and maximum SSTs were higher in the EEZ. Coastal waters exhibited greater intra-annual mean temperature amplitude (4.34±0.7°C) than the EEZ (2.94±0.41°C), possibly driven by upwelling and thermal stratification. Minimum and mean SST SD remained stable, while maximum SST SD fluctuated, with a marked increase in coastal area, suggesting growing environmental pressures. AR(1) analysis reveals strong persistence increasing over time in minimum and mean SSTs (0.65 - 0.85), indicating reduced system resilience and proximity to a tipping point. Maximum SST AR(1) decreased, implying greater random variability in future extreme warming events. Unpredictable peak sea surface temperatures (SSTs) could destabilise S. aurita stocks, affecting their distribution, reproduction and survival. The decline in resilience and predictability will make adaptive management efforts more challenging. The study underscores the urgent need for further research into SST predictability and its ecological consequences. Early warning of critical transition in east Venezuela’s Sardine ( Sardinella aurita, Valenciennes 1847 ) Fishing Area. Authorship Alimar Molero-Lizarraga 1 , Meimalin Moreno-Villalobos 2 , Jorge Payán-Alejo 3 , Carlos Méndez-Vallejo 4* . 1 Laboratorio de Diversidad Biológica. Centro de Estudios de la Crisis Ambiental Global. Instituto Venezolano de Investigaciones Científicas. Carretera Panamericana, kilómetro 11, Caracas, 1020-A, Venezuela. [email protected] https://orcid.org/0000-0003-1646-9818 2 Laboratorio de Ecología de Ecosistemas y Cambio Global. Centro de Estudios de la Crisis Ambiental Global. Instituto Venezolano de Investigaciones Científicas. Carretera Panamericana, kilómetro 11, Caracas, 1020-A, Venezuela. [email protected] https://orcid.org/0009-0007-3873-1553 3 Facultad de Ciencias del Mar de la Universidad Autónoma de Sinaloa, Paseo Claussen S/N, Mazatlán, Sinaloa 82000, México [email protected] https://orcid.org/0000-0003-4636-0274 4 Laboratorio de Ecología de Ecosistemas y Cambio Global. Centro de Estudios de la Crisis Ambiental Global. Instituto Venezolano de Investigaciones Científicas. Carretera Panamericana, kilómetro 11, Caracas, 1020-A, Venezuela. [email protected] https://orcid.org/0000-0001-7015-1910 * Corresponding author: Carlos Méndez-Vallejo Author contributions: CRediT Alimar Molero-Lizarraga: Formal analysis, Funding acquisition, Writing – original draft. Meimalin Moreno-Villalobos: Conceptualization, Writing – original draft. Jorge Payán-Alejo: Supervision, Writing – review & editing. Carlos Méndez-Vallejo: Conceptualization, Methodology, Supervision, Writing – original draft. Acknowledgements This work was supported by the Ministry of Popular Power for Science and Technology, via the National Fund for Science and Technology (Project No. 174-2024). The authors would like to thank the anonymous reviewers and journal editors for their valuable feedback, as well as Pauline Arridell for her contribution to the text’s language. Data availability Sea Surface Temperature data, that support the findings of this study, were obtained in the Moderate Resolution Imaging Spectroradiometer (MODIS) on board NASA’s Aqua satellite at https://doi.org/10.5067/MODAM-1D4N9. Conflicts of interest The authors have no relevant financial or nonfinancial interest to disclose. DD MMMM YYYY \acceptedDD MMMM YYYY Abstract Global warming is affecting the thermal tolerance of marine species and disrupting fisheries. Venezuelan sardine ( Sardinella aurita, Valenciennes 1847 ) fisheries are facing a decline possibly linked to climate change. Understanding the temperature trends along coastal areas versus the open ocean is crucial for effectively managing these sensitive species. This study examines Sea Surface Temperature (SST) variability in Venezuela’s Sardine Fishing Area and Exclusive Economic Zone (EEZ), detecting early warning signals (EWS) of critical transition. Using MODIS SST data (2002–2023), we assessed variability in both zones, calculating standard deviation (SD) and first-order autoregressive coefficient AR(1) as indicators. Results showed that while minimum SSTs were similar and stable, mean and maximum SSTs were higher in the EEZ. Coastal waters exhibited greater intra-annual mean temperature amplitude (4.34±0.7°C) than the EEZ (2.94±0.41°C), possibly driven by upwelling and thermal stratification. Minimum and mean SST SD remained stable, while maximum SST SD fluctuated, with a marked increase in coastal area, suggesting growing environmental pressures. AR(1) analysis reveals strong persistence increasing over time in minimum and mean SSTs (0.65 - 0.85), indicating reduced system resilience and proximity to a tipping point. Maximum SST AR(1) decreased, implying greater random variability in future extreme warming events. Unpredictable peak sea surface temperatures (SSTs) could destabilise S. aurita stocks, affecting their distribution, reproduction and survival. The decline in resilience and predictability will make adaptive management efforts more challenging. The study underscores the urgent need for further research into SST predictability and its ecological consequences. Keywords climate change, fisheries, food security, variance, autoregressive coefficient, sea surface temperature, tipping point. DD MMMM YYYY \acceptedDD MMMM YYYY Introduction Global warming has accelerated over the past decade, significantly impacting Earth’s life systems (IPCC, 2023). One consequence is that systems such as the oceans, land, and biosphere are approaching critical thresholds. Once these points are crossed, a regime shift is triggered, leading to a new state that is often irreversible (Scheffer et al., 2009). Despite the advances in climate modelling, there are limitations in forecasting an uncertain future marked by unprecedented earth events, prompting the development of a new framework to detect critical transitions as early as possible, referred to as early warning signal of a regime shift (EWS) (Dylewsky et al., 2023; Scheffer et al., 2009). Based on the bifurcation theory, EWS are statistical indicators of system change dynamics during the approach to a critical transition, often to a new irreversible state (Dakos et al., 2012; Scheffer et al., 2009). After a decade of research, the EWS framework shows a consolidation in theory and models (Dylewsky et al., 2023), although the practical and experimental application is under development (Alegre Stelzer et al., 2021; Clements et al., 2019). This development implies a diversity of indicators, with the one-dimensional indices currently the most used approach (Xu et al., 2023). A variety of environments and systems have also been subject to the application of the EWS approach, including the classical examples of the shallow lake model and savanna forest transition classical examples (Scheffer et al., 1993; Staver et al., 2011). EWS application in aquatic and marine systems is common, although it is still under discussion which indicators and under which circumstances they are reliable (Alegre Stelzer et al., 2021). The early detection of tipping points in aquatic systems has gained critical importance given increasing anthropogenic and climatic pressures. Recent work by Gsell et al. (2016) has demonstrated that indicators derived from complex systems theory, particularly increased variance (SD) and autoregressive coefficient (AR(1)), can foreshadow critical transitions in natural aquatic ecosystems. However, their predictive power varies substantially with monitoring temporal scales and system-specific characteristics. These findings hold particular relevance for fisheries management, where timely identification of productivity regime shifts could inform adaptive management strategies (Zhang, 2020). Considering the recent report of decline of Venezuela fishery productivity of sardine ( Sardinella aurita, Valenciennes (Gómez Gaspar, 2022), we propose that the EWS framework would contribute to enhancing adaptive management. The Venezuelan fisheries sector contributes 0.23% to national Gross Domestic Product (GDP) (FAO, 2025), where the Sardinella aurita fishery demonstrates disproportionate socio-economic significance at the local and subnational level (Fréon & Mendoza, 2003). The sector sustains approximately 12,000 direct and indirect employment opportunities across the capture, processing, and distribution segments (CENIPA, pers. comm. April 20, 2022). It provides affordable protein that improves food security for coastal communities (Amponsah et al., 2017; Fréon & Mendoza, 2003; González & Eslava, 2000). This combination of employment generation and nutritional supply underscores the socioeconomic importance of fisheries despite their relatively small macroeconomic footprint. Specifically the S. aurita fishery is of vital importance, not only by the amount of protein that it provides to coastal human communities, but also by the influence on other related fisheries with higher market value. S. aurita serves as raw material for canning operations, fishmeal production, bait for other commercial fisheries, and direct human consumption (Iriarte, 1997; Suárez & Bethencourt, 1994). Different hypotheses have been proposed to explain a recent reduction in S. aurita fishery production in Venezuela. These include the effect of various national and local socioeconomic conditions, overexploitation of the fishery resource, and the increase in sea temperature due to climate change (Gómez Gaspar, 2022; Gómez Gaspar et al., 2012; Taylor et al., 2012). While climate is understood as the long-term synthesis of weather patterns, contemporary climate change is marked by a rise in global temperatures. This warming is not evenly distributed across the oceans, and the sea surface temperature (SST) exhibits regional variations. Although increases in SST in the southern Caribbean Sea were reported more than a decade ago by Taylor et al. (2012), a significant knowledge gap persists. Currently, we lack clear data differentiating temperature trends between coastal and open seawater. This differentiation is crucial to understanding the impacts on coastal pelagic species such as Sardinella aurita , since it is known that temperature variation in ocean seawater is lower than in coastal areas. More critically, the precise warming tipping point that could provoke a critical transition within the marine ecosystem of the southern Caribbean Sea remains unidentified, posing a significant challenge for conservation and adaptation efforts. Here, we studied the SST in the Venezuelan Exclusive Economic Zone and eastern Sardine Fishing Zone, applying SD and AR(1) as statistical indicators of regime shift, to determine the proximity of the southern Caribbean Sea system to a critical transition with possible implications for S. aurita fisheries. Methods 2.1 Study area This study focused on Venezuela’s Exclusive Economic Zone (EEZ) in the Caribbean Sea (8°N–15°N, 60°W–73°W), an area encompassing critical Sardinella aurita habitats, such as the Gulf of Cariaco, Araya Peninsula, and Margarita Island. The Sardine Fishing Area is situated in the northeastern region of Venezuela (Fig. 1), encompassing approximately 16,000 km² (10°30’N - 11°6’N; 64°6’W - 62°4’W). This region constitutes the primary fishing area for the S. aurita in the country. The area is characterised by a complex submarine topography, featuring islands (Margarita, Coche, and Cubagua), gulfs, bays, inlets (Gulf of Cariaco, Santa Fe, Tigrillo), submarine valleys (Araya and Carúpano), offshore banks (Cumberland or Los Testigos), and the Cariaco Trench. The climate of the area is semi-arid with two distinct seasons: a dry season from January to May, marked by intense east northeasterly (ENE) trade winds, and a rainy season from June to December with reduced wind intensity. Precipitation averages 3.5 mm/month during the dry period and 60-70 mm/month during the rainy period. Mean monthly wind speeds range from 3.6 m/s (February to May) to 1.6 m/s after May when trade winds weaken (Robaina, 1991). Air temperature fluctuates between 20°C and 37°C, with an annual average of 26.5°C. Peak temperatures occur in September and October, coinciding with minimal rainfall and wind activity (Okuda, 1975; Okuda et al., 1968). Oceanographically, the study area is influenced by the Guyana Current, which transports low-salinity waters from the Orinoco River, extending its influence to Margarita and La Blanquilla Islands (de Miró Orell, 1974). Two significant upwelling phenomena occur along the continental shelf edge to the west. These events bring cold, high-salinity, nutrient-rich waters to the surface, promoting high planktonic production (Gómez Gaspar, 1996). During the dry season, these upwelling events cause a decrease in water temperature of more than 5°C, accompanied by water rotation due to oceanic currents (Fukuoka, 1965a, 1965b, 1965c). This combination of oceanographic and climatic factors contributes to the area’s high productivity and its importance as a fishing ground for Sardinella aurita . 2.2 Data sources. Sea Surface Temperature (SST) (minimum, mean and maximum) data spanning 2002-2023 were obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board NASA’s Aqua satellite. The dataset comprised Level 3 Standard Mapped Images with a 4 km spatial resolution (0.0417° grid) and a monthly temporal resolution (NASA OBPG, 2020). 2.3 Indicators of critical transition. The most commonly used statistical indicators as EWS are variance, and a regressive coefficient (Gsell et al., 2016). Generally, variance is expressed as standard deviation (SD), and the first-order autoregressive coefficient AR(1) is used . We calculate SD (square root of (1/n-1 * (x i -mean(x)) 2 ) over rolling windows of half the size of SST data for the Venezuelan EEZ and Sardine Fishing Area to contrast open sea (EEZ) temperature to coastal (Sardine Fishing Area) temperature. The detrending to achieve stationary filtering, which removes long-term trends, was accomplished by subtracting a Gaussian kernel smoothing function from the data and using the residuals for the estimation of the autoregressive coefficient at lag 1 (Dakos et al., 2012). The AR(1) was computed by fitting an autoregressive model of order 1 of the form x t+1 = α 1 x t + ε t by using an ordinary least-squares (OLS) fitting method applied over residuals of the detrending process within a sliding window of fixed size of half the size of the time series. Time statistical correlation to SD and AR(1) was estimated using the Kendall non-parametric correlation tau (𝜏). Kendall’s Tau is a nonparametric measure of rank correlation: it assesses the strength and direction of association between two variables based on the concordance of their rank paired observations calculated as: 𝜏= (C − D) / [n(n − 1) / 2] where • n = number of paired observations • C = number of concordant pairs • D = number of discordant pairs All data were processed with the statistical software R Core Team (2024). Results and discussion 3.1. Minimum, mean and maximum SST Southern Caribbean Sea zonal SSTs varied greatly interannual through the 2002-2023 years. While the minimum SST was fairly similar between the coastal (Sardine Fishing Area) and the open sea (EEZ), with the lowest temperature ranging a small amount higher in the Sardine Fishing Area, the average (Fig. 1) and particularly the maximum SSTs were higher in the EEZ (Fig. 2). Concomitantly, the intra-annual mean temperature amplitude (warmer month-colder month) was greater within the coastal Sardine Fishing Area (4.34±0.7 °C) compared with EEZ (2.94±0.41 °C). Past studies have revealed strong differences between open seawaters and coastal waters, with far-reaching implications for coastal marine ecosystems and fisheries. In open seawaters, especially in the tropics, SST typically has negligible annual variability, usually less than 2°C (Stewart, 2008). This stability is largely due to the vast quantity of water and the presence of a permanent thermocline—a region below the surface mixed layer (which is 10 to 200 meters deep)—where significant temperature changes occur, impeding interaction with deeper, cold water (Stewart, 2008). Coastal regions experience much greater thermal fluctuation (Scrosati, 2020). These changes are caused by mechanisms such as upwelling, which results in cold nutrient-rich waters rising towards the surface (Lynn, 1967) and summer thermal stratification, where solar heating accumulates heat in the surface layer due to reduced mixing (Stewart, 2008). 3.2 Indicators of critical transition Analysis of the temporal change in the moving SD revealed distinct patterns between Sardine Fishing Area and EEZ, as well as among SST measures (i.e., minimum, mean, and maximum temperature) (Fig. 3). For minimum SST, SD revealed a persistent pattern over the years (𝜏= -0.2, p < 0.05 for both areas), with both areas showing similar values (SD ~1.6), indicating stability in lower temperature extremes. Similarly, mean SST has reflected stability of variation along the years (𝜏=-0.3 for Sardine Fishing Area and 𝜏=-0.2 for the EEZ, p < 0.05 for both), but with the Sardine Fishing Area having a considerably higher variability (SD~1.5 for Sardine Fishing Area and around SD~1.0 for the EEZ), revealing the influence of seasonality in the coast. An inverse trend was observed in the maximum SST; the SD along Sardine Fishing Area rose with time, but the EEZ presented a declining trend (𝜏= 0.7 for Sardine Fishing Area and 𝜏=-0.6 for the EEZ, p < 0.05 for both). This dissimilarity shows the differing environmental pressures experienced by these areas. Overall, while the SD tended to be stable for minimum and mean SST, there were wide variations for maximum SST. The autoregressive (AR(1)) coefficient is an estimation of interannual memory strength (autocorrelation) in SST. Surprisingly, minimum and mean SST showed significantly higher AR(1) values (from 0.65 to 0.85) than maximum SST (from 0.0 to 0.4). This indicates that lower and mean SST conditions tend to persist more inter-annual than extreme warm conditions (Fig. 4). For minimum SST, the Sardine Fishing Area always had higher persistence than the EEZ (𝜏=0.5 for Sardine Fishing Area and 𝜏=0.7 for the EEZ, p < 0.05 for both). Conversely, for mean SST, EEZ initially possessed higher persistence, but both areas experienced an increasing trend wherein the Sardine Fishing Area eventually overlapped or surpassed the EEZ’s persistence towards the last part of the analysis period (𝜏=0.7 for Sardine Fishing Area and 𝜏=0.5 for EEZ, p < 0.05 for both). The strong AR(1) in mean and minimum SST is as expected with the reported concept of large-scale oceanic processes, such as water mass thermal inertia that acts to suppress short-term interannual variability (Deser et al., 2010; Mantua & Hare, 2002), although its increasing value along the time indicates resilience reduction and proximity to the tipping point of the system (Dakos et al., 2008, 2012; Scheffer et al., 2009). This memory indicated by AR(1) in thermal conditions has the impact of setting up a relatively unstable environment to which marine ecosystems are not able to adapt, and it influences many ecosystem processes ranging from primary production to species distribution patterns, by changes in other sea physical properties such as salinity, density and stratification (Capotondi et al., 2012; Sen Gupta et al., 2020). Furthermore, AR(1) zonal variability for minimum and mean SST is substantial. This zonal variability highlights the influence of localised oceanographic features, such as coastal upwelling regimes or bathymetry, on the interannual SST memory. Coastal upwelling regions, at times characterised by strong frontal systems, such as the case of our study area that is impacted by trade winds, the Cariaco Pit, and the Amazon, Orinoco, Unare, and Tuy river systems, can enhance autocorrelation of increasing minimum and medium temperatures due to global warming (Muller‐Karger et al., 2001; Rueda-Roa & Muller-Karger, 2013). The increasing trend in AR(1) of mean SST across both areas, and particularly the coincidence of the Sardine Fishing Area with the higher EEZ AR(1), may be a pointer to more large-scale warming trends occurring within the seas that are influencing the overall thermal stability (Bindoff et al., 2019), indicating at the same time that heat accumulation was delayed in the coastal zone but that recently increased faster than in open seawater of the region. On the contrary, the maximum SST AR(1) coefficient presented a strong negative trend in both regions, mostly in the Sardine Fishing Area, from about 0.35 to nearly zero (𝜏=-0.7 for Sardine Fishing Area and 𝜏=-0.6 for the EEZ, p < 0.05). The lesser autocorrelation of maximum SST suggests that recent extreme warm events are progressively less representative of future extreme warm events. This may be a sign of interannual variability decoupling at the warmer end of the SST distribution, showing a trend towards more strongly variable extreme warm events, which is a particularly relevant finding considering the increased frequency and intensification of ocean heatwaves globally (Oliver et al., 2018). These alterations can be enforced by more local and transient atmospheric forces or by complex interactions with other climate modes, which are themselves growing less predictable at the interannual scale (Sen Gupta et al., 2020). 3.3 Sardine Fishery Implications Sea Surface Temperature (SST) variability profoundly impacts marine ecosystems and fisheries, with global warming amplifying the frequency, magnitude, and spatial extent of Marine Heatwaves (MHWs) (Cooley et al., 2022; Frölicher et al., 2018; Oliver et al., 2018). These extreme events can exceed the thermal tolerance of species like S. aurita —which typically inhabits 18-25°C (Balza et al., 2007; Martínez-Porchas, 2012) but shows high biomass at 25-29°C in specific regions (Rueda-Roa et al., 2017). While S. aurita tolerates a broad thermal range, it’s highly vulnerable beyond its thresholds. Temperatures below 9-10°C cause mass mortality (Guidetti et al., 2002). Conversely, excessively high temperatures can disrupt crucial physiological processes like growth, maturation, and recruitment (Esteve et al., 2009; Ganias, 2014; Meza Figueros, 2016; Pankhurst & Munday, 2011). This ultimately alters the distribution, abundance, and phenology of marine species, from plankton to marine mammals (Cooley et al., 2022). A special interest arose from findings that recently challenged the Temperature-Size Rule, which suggests that a rise in SST leads to smaller adult fish sizes (Johansen et al. 2024). For fisheries, these shifts translate to altered availability of commercial species, reduced catches, and urgent adaptation of harvesting strategies (Cooley et al., 2022; Miyama et al., 2023; Smale et al., 2019). For commercially important species such as Sardinella aurita , which is highly sensitive to climatic change, this reduced predictability of extreme warm SST events, as well as the revealed reduction of the system resilience, poses a serious issue. Possible shift regime to warmer water as well as MHWs caused changes in species distribution, breeding failure, and high mortality events, which ultimately influence recruitment and population dynamics as a whole, as well as impact an intricate food web (Cavole et al., 2016; Smale et al., 2019). Assuming predictability of heatwaves decreases, it becomes increasingly difficult for fisheries to implement effective and timely adaptive actions, such as dynamic spatial closures or precautionary catch quotas. Warmer water and increasing unpredictability of peak SST could lead to more erratic and persistent environmental stressors, potentially destabilizing S. aurita stocks and the ecosystems that depend on them. Subsequent studies should focus on identifying the causes of this reduced predictability and its broader ecological effects for other climate-sensitive marine organisms. Conclusions The study reveals significant differences in sea surface temperatures (SST) between the Venezuelan coastal Sardine Fishing Area and the Exclusive Economic Zone (EEZ) in the southern Caribbean Sea, with higher mean and maximum SSTs in the EEZ and greater intra-annual temperature variability in the coastal zone. AR(1) analysis showed that minimum and mean SSTs are increasing in a more stable way over time, with reduced resilience and possible proximity to tipping point, while maximum SSTs are becoming less predictable, indicating a shift towards more random extreme warm events. These findings pose substantial challenges for the Sardinella aurita fishery in Venezuela, as the reduced predictability of extreme warm SST events and warmer water can lead to shifts in species distribution, reproductive failures, and increased mortality, complicating the implementation of effective adaptive management strategies. The different persistence revealed by AR(1) suggests that the underlying physical mechanisms driving the ”memory” of the ocean differ depending on the SST metrics and geographical area. DD MMMM YYYY \acceptedDD MMMM YYYY DD MMMM YYYY \acceptedDD MMMM YYYY Figure captions Figure 1. Sea surface temperatures (SST) of the study area during the 2002-2023 period, showing Venezuelan Exclusive Economic Zone (EEZ) and the most important commercial sardine fishing area at the east of Venezuela. Figure 2. Minimum, mean and maximum SST in the Venezuelan EEZ and sardine fishing area during the period 2002-2023. Figure 3. Rolling standard deviation (SD) of minimum, mean and maximum SST in the Venezuelan EEZ and sardine fishing area during the period 2002-2023. Figure 4. Autoregressive coefficient of lag 1 (AR(1)) of minimum, mean and maximum SST in the Venezuelan EEZ and sardine fishing area during the period 2002-2023. \received DD MMMM YYYY \acceptedDD MMMM YYYY Figure 1. Figure 2. Figure 3. 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Keywords autoregressive coefficient climate change fisheries food security sea surface temperature tipping point Authors Affiliations Alimar Molero-Lizarraga Instituto Venezolano de Investigaciones Cientificas View all articles by this author Meimalin Moreno-Villalobos 0009-0007-3873-1553 Instituto Venezolano de Investigaciones Cientificas View all articles by this author Jorge Payán-Alejo Universidad Autonoma de Sinaloa Escuela Superior de Enfermeria Mazatlan View all articles by this author Carlos Méndez-Vallejo 0000-0001-7015-1910 [email protected] Instituto Venezolano de Investigaciones Cientificas View all articles by this author Metrics & Citations Metrics Article Usage 416 views 161 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Alimar Molero-Lizarraga, Meimalin Moreno-Villalobos, Jorge Payán-Alejo, et al. Early warning of critical transition in east Venezuela’s Sardine (Sardinella aurita, Valenciennes 1847) Fishing Area.. 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