Food security or economic profitability? Projecting the effects of climate and socioeconomic changes on global skipjack tuna fisheries under three management strategies

We investigate the interactions between anthropogenic climate change, socioeconomic developments and tuna fishery management strategies. For this purpose, we use the APECOSM-E model to map the effects of climate change and commercial fishing on the distribution of skipjack tuna biomass in the three oceans, combined with a new bioeconomic module representing the rent or profit of skipjack fisheries. For forcing, we use Representative Concentration Pathway (RCP) 8.5, the highest emission scenario for greenhouse gas concentrations presented in the IPCC’s Fifth Assessment Report (AR5), and the IPCC Socioeconomic Shared Pathway (SSP) 3, which is characterized by low economic development and a strong increase in the world population. We first investigate the impact of climate change on regional skipjack abundance, catches and profits in three oceans (Atlantic, Indian and Pacific) in 2010, 2050 and 2095. We then study the effects of three management strategies (maximum sustainable yield or MSY, maximum economic yield or MEY, and zero rent or ZR) on the future distribution of fishing fleets between oceans and on global economic rent.Our model projections for 2050 and 2095 show an increase in global skipjack biomass compared to 2010 and major changes in its distribution, impacting local and regional fishing efforts. The Pacific Ocean will continue to dominate the skipjack market.In our modeling of management strategies, the currently predominant MSY strategy would have been unprofitable in 2010, due to a decreased catch per unit effort (CPUE). In the future, however, technological developments should increase fishing efficiency and make MSY profitable.In all the scenarios, a MEY strategy is more profitable than MSY but leads to the lowest catches and the highest prices. This raises ethical questions in a world where food security may become a top priority.In the scenarios where MSY generates an economic loss (e.g. 2010), a ZR strategy allows global stocks to be exploited at high but still profitable levels. Conversely, in the scenarios where MSY is profitable, (e.g. 2095) ZR leads to overfishing and smaller global catches.We conclude that the most appropriate management strategy at any time is likely to change as environmental and socioeconomic conditions evolve. The decision to follow one or other strategy is a complex one that must be regularly reviewed and updated.     

A brief introduction to the issue of climate and marine fisheries

Climatic variability has profound effects on the distribution, abundance and catch of oceanic fish species around the world. The major modes of this climate variability include the El Niño-Southern Oscillation (ENSO) events, the Pacific Decadal Oscillation (PDO) also referred to as the Interdecadal Pacific Oscillation (IPO), the Indian Ocean Dipole (IOD), the Southern Annular Mode (SAM) and the North Atlantic Oscillation (NAO). Other modes of climate variability include the North Pacific Gyre Oscillation (NPGO), the Atlantic Multidecadal Oscillation (AMO) and the Arctic Oscillation (AO). ENSO events are the principle source of interannual global climate variability, centred in the ocean–atmosphere circulations of the tropical Pacific Ocean and operating on seasonal to interannual time scales. ENSO and the strength of its climate teleconnections are modulated on decadal timescales by the IPO. The time scale of the IOD is seasonal to interannual. The SAM in the mid to high latitudes of the Southern Hemisphere operates in the range of 50–60 days. A prominent teleconnection pattern throughout the year in the Northern Hemisphere is the North Atlantic Oscillation (NAO) which modulates the strength of the westerlies across the North Atlantic in winter, has an impact on the catches of marine fisheries. ENSO events affect the distribution of tuna species in the equatorial Pacific, especially skipjack tuna as well as the abundance and distribution of fish along the western coasts of the Americas. The IOD modulates the distribution of tuna populations and catches in the Indian Ocean, whilst the NAO affects cod stocks heavily exploited in the Atlantic Ocean. The SAM, and its effects on sea surface temperatures influence krill biomass and fisheries catches in the Southern Ocean. The response of oceanic fish stocks to these sources of climatic variability can be used as a guide to the likely effects of climate change on these valuable resources.     

Consequences of global change for oceans: A review

The possible effects of global climate change on the oceans are described through a review of the results produced by GCM's that explicitly incorporate the dynamics of the interior of world oceans. Changes at asymptotic equilibrium influence the whole water column, but equilibrium in the deep sea is reached after several thousands years. The transient response of these models after 25 years following the onset of the perturbation (doubling or quadrupling of atmospheric CO₂) affects the upper layer of the oceans (<1000 m) producing an increase in temperature between 2–4 °C. Models with realistic geography, as compared with simplified ones with N-S symmetry, produce warming near the north pole but a small cooling close to the antarctic continent. The main impacts of the predicted changes upon marine ecosystems are identified within several possible scenarios. Special mention is made of the expansion/contraction of pelagic habitats, oceanic island habitats, ocean wide distributional changes and the dynamical effects upon bioproduction.     

Modelling the impact of climate change on Pacific skipjack tuna population and fisheries

IPCC-type climate models have produced simulations of the oceanic environment that can be used to drive models of upper trophic levels to explore the impact of climate change on marine resources. We use the Spatial Ecosystem And Population Dynamics Model (SEAPODYM) to investigate the potential impact of Climate change under IPCC A2 scenario on Pacific skipjack tuna (Katsuwonus pelamis). IPCC-type models are still coarse in resolution and can produce significant anomalies, e.g., in water temperature. These limitations have direct and strong effects when modeling the dynamics of marine species. Therefore, parameter estimation experiments based on assimilation of historical fishing data are necessary to calibrate the model to these conditions before exploring the future scenarios. A new simulation based on corrected temperature fields of the A2 simulation from one climate model (IPSL-CM4) is presented. The corrected fields led to a new parameterization close to the one achieved with more realistic environment from an ocean reanalysis and satellite-derived primary production. Projected changes in skipjack population under simple fishing effort scenarios are presented. The skipjack catch and biomass is predicted to slightly increase in the Western Central Pacific Ocean until 2050 then the biomass stabilizes and starts to decrease after 2060 while the catch reaches a plateau. Both feeding and spawning habitat become progressively more favourable in the eastern Pacific Ocean and also extend to higher latitudes, while the western equatorial warm pool is predicted to become less favorable for skipjack spawning.     

Detecting climate impacts with oceanic fish and fisheries data

Anthropogenic climate change is affecting the environment of all oceans, modifying ocean circulation, temperature, chemistry and productivity. While evidence for changes in physical signals is often distinct, impacts on fishes inhabiting oceanic systems are not easily identified, and therefore, quantification of responses is less common. Correctly attributing changes associated with a changing climate from other drivers is important for the implementation of effective harvest and management strategies and for addressing associated socio-economic impacts, particularly for countries highly dependent on oceanic resources. Data supporting investigation of responses of oceanic species to climate impacts include fisheries catch, fisheries-independent surveys, and conventional and electronic tagging data. However, there are a number of challenges associated with detecting climatic responses with these data, including (i) data collection costs (ii) small sample sizes (iii) limited time series relative to temporal scales at which environmental variability occurs, (iv) changing fisher and fisheries behavior due to non-climate drivers and (v) changes in population dynamics due to natural climate variability and non-climate drivers. We highlight potential biases and suggest strategies that should be considered when using oceanic fish and fisheries data in the evaluation of climate change impacts. Consideration of these factors is important when assessing variability in exploited species and designing management responses to climate or fisheries threats.     

Attributing analysis on the model bias in surface temperature in the climate system model FGOALS-s2 through a process-based decomposition method

This study uses the coupled atmosphere–surface climate feedback–response analysis method(CFRAM) to analyze the surface temperature biases in the Flexible Global Ocean–Atmosphere–Land System model, spectral version 2(FGOALS-s2)in January and July. The process-based decomposition of the surface temperature biases, defined as the difference between the model and ERA-Interim during 1979–2005, enables us to attribute the model surface temperature biases to individual radiative processes including ozone, water vapor, cloud, and surface albedo; and non-radiative processes including surface sensible and latent heat fluxes, and dynamic processes at the surface and in the atmosphere. The results show that significant model surface temperature biases are almost globally present, are generally larger over land than over oceans, and are relatively larger in summer than in winter. Relative to the model biases in non-radiative processes, which tend to dominate the surface temperature biases in most parts of the world, biases in radiative processes are much smaller, except in the sub-polar Antarctic region where the cold biases from the much overestimated surface albedo are compensated for by the warm biases from nonradiative processes. The larger biases in non-radiative processes mainly lie in surface heat fluxes and in surface dynamics,which are twice as large in the Southern Hemisphere as in the Northern Hemisphere and always tend to compensate for each other. In particular, the upward/downward heat fluxes are systematically underestimated/overestimated in most parts of the world, and are mainly compensated for by surface dynamic processes including the increased heat storage in deep oceans across the globe.     

Capelin migrations and climate change – a modelling analysis

The capelin is a small pelagic fish that performs long distance migrations. It is a key species in the Barents Sea ecosystem and its distribution is highly climate dependent. Here we use an individual based model to investigate consequences of global warming on capelin distribution and population dynamics. The model relies on input on physics and plankton from a biophysical ocean model, and the entire life cycle of capelin including spawning of eggs, larval drift and adult movement is simulated. Spawning day and adult movement strategies are adapted by a genetic algorithm. Spawning has to take place in designated near-shore spawning areas. The output generated by the model is capelin migration/distribution and population dynamics. We present simulations with present day climate and a future climate scenario. For the present climate the model evolves a spatial distribution resembling typical spatial dynamics of capelin with the coasts of Northern Norway and Murman as the main spawning areas. For the climate change simulation, the capelin is predicted to shift spawning eastwards and also utilize new spawning areas along Novaya Zemlya. There is also a shift in the adult distribution towards the north eastern part of the Barents Sea and earlier spawning associated with the warming.     

Effects of climate change on oceanic fisheries in the tropical Pacific: implications for economic development and food security

The four species of tuna that underpin oceanic fisheries in the tropical Pacific (skipjack, yellowfin, bigeye and albacore tuna) deliver great economic and social benefits to Pacific Island countries and territories (PICTs). Domestic tuna fleets and local fish processing operations contribute 3–20 % to gross domestic product in four PICTs and licence fees from foreign fleets provide an average of 3–40 % of government revenue for seven PICTs. More than 12,000 people are employed in tuna processing facilities and on tuna fishing vessels. Fish is a cornerstone of food security for many PICTs and provides 50–90 % of dietary animal protein in rural areas. Several PICTs have plans to (1) increase the benefits they receive from oceanic fisheries by increasing the amount of tuna processed locally, and (2) allocate more tuna for the food security of their rapidly growing populations. The projected effects of climate change on the distribution of tuna in the tropical Pacific Ocean, due to increases in sea surface temperature, changes in velocity of major currents and decreases in nutrient supply to the photic zone from greater stratification, are likely to affect these plans. PICTs in the east of the region with a high dependence on licence fees for government revenue are expected to receive more revenue as tuna catches increase in their exclusive economic zones. On the other hand, countries in the west may encounter problems securing enough fish for their canneries as tuna are redistributed progressively to the east. Changes in the distribution of tuna will also affect the proportions of national tuna catches required for food security. We present priority adaptations to reduce the threats to oceanic fisheries posed by climate change and to capitalise on opportunities.     

A Review of Potential Vorticity and its Possible Application in the moist Atmospheric Flow

Potential vorticity (PV) has been served as a powerful and useful dynamic tracer for the understanding of the large-scale dynamics and synoptic variations in the atmosphere and oceans. Significant progress has been made on the application of PV. In recent decades there has been a substantial amount of work done on PV in a general moist atmosphere. In this paper PV and the generalized moist potential vorticity (GMPV) and their application in the tropical cyclones and mesoscale meteorological field are reviewed. The GMPV is derived for a real atmosphere (neither totally dry nor saturated) by introducing a generalized potential temperature instead of the potential temperature or equivalent potential temperature. Such a generalization can depict the moist effect on PV anomaly in the non-uniformly saturated atmosphere. A new convective vorticity vector (CVV) is introduced in connection with GMPV in order to diagnose the development of tropical deep convections.     

Comparison of Winter Precipitation Measurements by Six Tretyakov Gauges at the Valdai Experimental Site

Analyses of long-term (1991–2010) intercomparison data quantify the consistency of winter precipitation observations by six identical Tretyakov gauges at the Valdai research station in Russia. Relative to the standard Tretyakov gauge, the mean catch ratios are 97 to 106% for dry snow, 94 to 104% for wet snow, 87 to 109% for blowing snow, 96 to 103% for mixed precipitation, and 98 to 101% for winter rain. The differences between the highest and lowest mean catches are about 10 to 11% for snow, 7% for mixed precipitation, and 3% for rain. On average, this difference is about 0.2?mm over the 12-hour observation period. The catch difference for blowing snow is much higher, up to 22%, or an average of 0.6?mm per observation. Comparisons of 12-hour observations show better consistency in gauge performance for low snowfall events and a large variation in gauge catch for high snowfall events. The differences in 12-hour snow catches are mostly less than 2?mm among the six gauges. The differences in the 12-hour observations are less than 1% for rain and 4% for mixed precipitation. Close linear relationships exist between the 12-hour gauge observations for all precipitation types. The maximum differences in gauge snow catches increase very weakly with wind speed, and higher differences are associated with warmer temperatures, from ?5°C to 0°C. There is, however, no significant relationship between the maximum catch difference and the mean wind speed or temperature over the 12-hour period.     

Transient responses of North-American grasslands to changes in climate

Our objective was to evaluate the transient responses of grasslands in the central grassland region of North America to changes in climate. We used an individual plant-based gap dynamics simulation model (STEPPE-GP) linked with a soil water model (SOILWAT) to evaluate the effects of changes in climate on the composition and structure of grassland vegetation. Five functional types of plants were simulated based upon lifeform, physiology, and rooting distribution with depth. C₃ and C₄ perennial grasses with either a shallow or deep rooting distribution, and deeply rooted C₃ shrubs were simulated under current climatic conditions and under a GFDL climate change scenario for nine sites representative of the temperature and precipitation regimes in the grassland region.Although vegetation at the sites responded differently to climate change, shifts in functional types occurred within 40 years of the start of the climate change. C₄ grasses increased in dominance or importance at all sites with a change in climate, primarily as a result of increases in temperature in all months at all sites. The coolest sites that arc currently dominated by C₃ grasses were predicted to shift to a dominance by C₄ grasses, whereas sites that are currently dominated by C₄ grasses had an increase in importance of this functional type with a change in climate. Current annual temperature was the best predictor of changes in C₃ biomass, and C₃ and C₄ biomass combined; current annual precipitation was the best predictor of changes in C₄ biomass. These predicted shifts in dominance and importance of C₃ versus C₄ grasses would have important implications for the management of natural grasslands as well as the cultivation of crops in the central grassland region.     

A dissection of the surface temperature biases in the Community Earth System Model

Based upon the climate feedback-responses analysis method, a quantitative attribution analysis is conducted for the annual-mean surface temperature biases in the Community Earth System Model version 1 (CESM1). Surface temperature biases are decomposed into partial temperature biases associated with model biases in albedo, water vapor, cloud, sensible/latent heat flux, surface dynamics, and atmospheric dynamics. A globally-averaged cold bias of ?1.22 K in CESM1 is largely attributable to albedo bias that accounts for approximately ?0.80 K. Over land, albedo bias contributes ?1.20 K to the averaged cold bias of ?1.45 K. The cold bias over ocean, on the other hand, results from multiple factors including albedo, cloud, oceanic dynamics, and atmospheric dynamics. Bias in the model representation of oceanic dynamics is the primary cause of cold (warm) biases in the Northern (Southern) Hemisphere oceans while surface latent heat flux over oceans always acts to compensate for the overall temperature biases. Albedo bias resulted from the model’s simulation of snow cover and sea ice is the main contributor to temperature biases over high-latitude lands and the Arctic and Antarctic region. Longwave effect of water vapor is responsible for an overall warm (cold) bias in the subtropics (tropics) due to an overestimate (underestimate) of specific humidity in the region. Cloud forcing of temperature biases exhibits large regional variations and the model bias in the simulated ocean mixed layer depth is a key contributor to the partial sea surface temperature biases associated with oceanic dynamics. On a global scale, biases in the model representation of radiative processes account more for surface temperature biases compared to non-radiative, dynamical processes.     

Effects of climate variability on the distribution and fishing conditions of yellowfin tuna (Thunnus albacares) in the western Indian Ocean

Variations in the abundance and distribution of pelagic tuna populations have been associated with large-scale climate indices such as the Southern Oscillation Index in the Pacific Ocean and the North Atlantic Oscillation in the Atlantic Ocean. Similarly to the Pacific and Atlantic, variability in the distribution and catch rates of tuna species have also been observed in association with the Indian Ocean Dipole (IOD), a basin-scale pattern of sea surface and subsurface temperatures that affect climate in the Indian Ocean. The environmental processes associated with the IOD that drive variability in tuna populations, however, are largely unexplored. To better understand these processes, we investigated longline catch rates of yellowfin tuna and their distributions in the western Indian Ocean in relation to IOD events, sea surface water temperatures (SST) and estimates of net primary productivity (NPP). Catch per unit effort (CPUE) was observed to be negatively correlated to the IOD with a periodicity centred around 4 years. During positive IOD events, SSTs were relatively higher, NPP was lower, CPUE decreased and catch distributions were restricted to the northern and western margins of the western Indian Ocean. During negative IOD events, lower SSTs and higher NPP were associated with increasing CPUE, particularly in the Arabian Sea and seas surrounding Madagascar, and catches expanded into central regions of the western Indian Ocean. These findings provide preliminary insights into some of the key environmental features driving the distribution of yellowfin tuna in the western Indian Ocean and associated variability in fisheries catches.     

Testing for a Temperature Effect on an Early Catch Record

In conjunction with early climate records, catch records from pre-industrialfisheries are a potentially valuable sourceof information about the effect of climate on fisheries. This paper describesa test for a temperature effect on an18th century catch record of Icelandic cod. The results of the test, which isbased on a model that incorporatesboth internal population dynamics and a potential temperature effect, supportthe existence of a temperature effect.     

The effects of increased stream temperatures on juvenile steelhead growth in the Yakima River Basin based on projected climate change scenarios

Stakeholders within the Yakima River Basin expressed concern over impacts of climate change on mid-Columbia River steelhead (Oncorhynchus mykiss), listed under the Endangered Species Act. We used a bioenergetics model to assess the impacts of changing stream temperatures—resulting from different climate change scenarios—on growth of juvenile steelhead in the Yakima River Basin. We used diet and fish size data from fieldwork in a bioenergetics model and integrated baseline and projected stream temperatures from down-scaled air temperature climate modeling into our analysis. The stream temperature models predicted that daily mean temperatures of salmonid-rearing streams in the basin could increase by 1–2 °C and our bioenergetics simulations indicated that such increases could enhance the growth of steelhead in the spring, but reduce it during the summer. However, differences in growth rates of fish living under different climate change scenarios were minor, ranging from about 1–5 %. Because our analysis focused mostly on the growth responses of steelhead to changes in stream temperatures, further work is needed to fully understand the potential impacts of climate change. Studies should include evaluating changing stream flows on fish activity and energy budgets, responses of aquatic insects to climate change, and integration of bioenergetics, population dynamics, and habitat responses to climate change.     

Global streamflow and thermal habitats of freshwater fishes under climate change

Climate change will affect future flow and thermal regimes of rivers. This will directly affect freshwater habitats and ecosystem health. In particular fish species, which are strongly adapted to a certain level of flow variability will be sensitive to future changes in flow regime. In addition, all freshwater fish species are exotherms, and increasing water temperatures will therefore directly affect fishes’ biochemical reaction rates and physiology. To assess climate change impacts on large-scale freshwater fish habitats we used a physically-based hydrological and water temperature modelling framework forced with an ensemble of climate model output. Future projections on global river flow and water temperature were used in combination with current spatial distributions of several fish species and their maximum thermal tolerances to explore impacts on fish habitats in different regions around the world. Results indicate that climate change will affect seasonal flow amplitudes, magnitude and timing of high and low flow events for large fractions of the global land surface area. Also, significant increases in both the frequency and magnitude of exceeding maximum temperature tolerances for selected fish species are found. Although the adaptive capacity of fish species to changing hydrologic regimes and rising water temperatures could be variable, our global results show that fish habitats are likely to change in the near future, and this is expected to affect species distributions.     

Predicting the impact of climate change on the spatial pattern of freshwater fish yield capability in eastern Canadian lakes

Equations of fish yield in lakes as a function of mean annual air temperature have been published for lake whitefish, northern pike, and walleye. Using the contouring and modelling features of a geographic information system (Tydac Technologies' SPANS), we prepared maps of (i) species distribution, (ii) mean annual air temperature, and (iii) temperature increases predicted by the Goddard Institute for Space Studies' global climate model (GISS-GCM). We combined these maps with the yield equations for the three study species to form a regional model predicting the spatial distribution of yield capability in eastern Canada with and without climate change. The GISS-GCM predicts temperature increases of 2.5 to 7.7 °C (mean = 4.5 °C) in eastern Canada, midway between the values predicted by two other GCMs considered. The regional model predicts a substantial spatial re-distribution of fishery capabilities. Areas now supporting high yields become marginal and areas at the margin of, or outside, the current species range become optimal. Without efforts to prevent temperature increases or large artificial efforts to redistribute preferred fish species, Canadian freshwater fisheries will suffer major disruptions given the temperature increases predicted by the GISS-GCM.     

Evaluating the Tree Population Density and Its Impacts in CLM-DGVM

Vegetation population dynamics play an essential role in shaping the structure and function of terrestrial ecosystems.However,large uncertainties remain in the parameterizations of population dynamics in current Dynamic Global Vegetation Models(DGVMs).In this study,the global distribution and probability density functions of tree population densities in the revised Community Land Model-Dynamic Global Vegetation Model(CLM-DGVM) were evaluated,and the impacts of population densities on ecosystem characteristics were investigated.The results showed that the model predicted unrealistically high population density with small individual size of tree PFTs(Plant Functional Types) in boreal forests,as well as peripheral areas of tropical and temperate forests.Such biases then led to the underestimation of forest carbon storage and incorrect carbon allocation among plant leaves,stems and root pools,and hence predicted shorter time scales for the building/recovering of mature forests.These results imply that further improvements in the parameterizations of population dynamics in the model are needed in order for the model to correctly represent the response of ecosystems to climate change.     

Sustainability implications of honouring the Code of Conduct for Responsible Fisheries

The Code of Conduct for Responsible Fisheries developed in 1995 by the Food and Agriculture Organization (FAO) of the United Nations includes a set of recommendations for reducing the negative impacts of fishing activities on marine ecosystems. The Code is widely believed to be an important tool for fisheries management and, although the Code is voluntary, all stakeholders concerned with the management and development of fisheries, and conservation of fishery resources, are actively encouraged to implement it. Previous analysis at global scale showed widespread low compliance with the Code of Conduct that may be partly due to a lack of empirical support for the overall ecological benefits of adhering to the Code. Here we evaluated these ecological effects by comparing compliance with the Code to changes in five ecological indicators that quantify the ecosystem effects of fishing. We used the loss in production index and the related probability of sustainable fishing index, the mean trophic level of the catch, total catches, and the primary production required to sustain the catch. We also tested if regional differences and development status of countries influenced the results of ecological indicators. Results indicate that countries with higher levels of compliance with the FAO Code of Conduct in 2008 experienced a decrease in the Loss in Production index and an increase in fisheries sustainability from the 1990s to 2000s. We conclude that better implementation of the Code of Conduct may have had overall positive ecological effects with time. A significant decrease in total catch and primary production required with higher compliance was also observed. While a significant increase in ecosystem sustainability was observed after a decade of adoption of the Code at high levels of compliance, further ecosystem degradation had taken place where compliance with the Code was below a given threshold (4, from a ranking of 0–10). Therefore, since compliance with the Code is still low or very low worldwide, these results may encourage individual countries to adopt well-established fishery management measures in order to increase the ecological sustainability of marine resources.     

Correlation analyses between sea surface temperature anomalies in the eastern equatorial Pacific and the world ocean

Based on data from the Comprehensive Ocean-Atmosphere Data Set (COADS), objective analyses of the monthly mean sea surface temperature (SST) were prepared at GFDL for each month of the 110-year period 1870–1979. Time series of various indices characterizing the SST anomalies averaged over the eastern equatorial Pacific (EEP), the tropical oceans and the world ocean are presented for monthly, yearly and decadal time-averaging periods. Global correlations maps are given for each decade of the 1870–1979 period. They show the spatial connections between the monthly SST anomalies in the EEP and in other parts of the world ocean and how these connections vary for the different decades. On the intermonthly time scale the SST anomalies in the EEP and those in the tropical and world oceans are found to be highly correlated, with maximum correlations values of 0.91 at zero lag for the tropical oceans during the 1950–1959 decade and 0.81 for the world ocean during the 1970–1979 decade. Positive correlation values of r0.36 persist on average from about 4 months before to about 8 months after the EEP anomalies occur. There is a clear tendency for the tropical and world ocean anomalies to lag behind the EEP anomalies. Comparing different oceans, we find the tendency for the tropical SST anomalies in the Indian and Atlantic Oceans to lag behind those in the EEP region by about 1 and 3 months, respectively. On the interannual time scale the EEP anomalies are also well correlated with those in the other regions, having an average correlation of 0.84 for the tropical oceans and of about 0.7 for the world ocean.