Contrasting climate oscillations impacts on phytoplankton in the western and eastern tropical Pacific

Domain: earth_science
Published: 2025-12-08
Editorial outcome: major_revision

Abstract
Climate oscillations like the El Niño-Southern Oscillation and Pacific Decadal Oscillation significantly impact marine ecosystems. Traditionally, warm events are thought to suppress nutrient availability, reduce phytoplankton biomass, and change community structure. However, using two decades of field observations, remote sensing, Copernicus reanalysis, and Earth system modeling, we find very different responses in the western tropical Pacific. During El Niño, chlorophyll concentrations and diatom contributions increase, while La Niña reverses that trend. The further amplification of these El Niño-Southern Oscillation-driven contrasts by the Pacific Decadal Oscillation can be attributed to its effects on regional circulation, including the enhancement of eddy activity that facilitates upwelling of nutrients and stimulates phytoplankton production. These findings go beyond the simple narrative of community structure shifts and suggest more complex physical-biological responses in the tropical Pacific. Consideration of these mechanisms will be crucial for improvement of climate change predictions and development of strategies for sustainable management.

Introduction
The El Niño-Southern Oscillation (ENSO) is the most prominent interannual climatic cycle on Earth and exerts a profound and wide-ranging influence on marine ecosystems and humanity1,2. The alternate periods of warming (El Niño) and cooling (La Niña) in the tropical Pacific stem from the intricate interactions between the atmosphere and ocean3, and they have very different impacts on ecosystems. Phytoplankton, which account for most of the primary production in the ocean, play a crucial role in sustaining marine ecosystems and enabling the services they provide4,5. Changes in the community structures of phytoplankton driven by climate change profoundly affect primary production and biogeochemical cycles6. The effects of ENSO events depend on the phases of the Pacific Decadal Oscillation (PDO), which can either intensify or mitigate the changes driven by ENSO7–9. PDO and ENSO are in phase when El Niño coexists with a positive PDO or La Niña with a negative PDO. Such in-phase conditions may lead to relatively complex responses from marine ecosystems. Understanding these interactions is essential for accurate assessment of the impacts of climate change and the formulation of effective adaptation and mitigation strategies.

Typically, El Niño events give rise to elevated sea surface temperatures, intensified stratification, and a deepening of the nitracline in the equatorial Pacific. These changes lead in turn to negative chlorophyll a anomalies10,11. These impacts reflect changes of the longitudinal slope of the thermocline, which influence the allochthonous supply of nutrients, phytoplankton community structure, and biological productivity8,12. During the extreme El Niño of 1997–1998, the depletion of nitrate led to a substantial reduction of primary production in the central and eastern equatorial Pacific13. During La Niña conditions, there is often an increase of diatom abundance and decrease of the concentrations of cyanobacteria14. Recent studies have indicated that under future climate conditions, interannual variability in the western Pacific will be more strongly correlated with ENSO events15,16.

The western tropical Pacific is characterized by off-equatorial negative sea surface temperature (SST) anomalies and positive sea level pressure (SLP) anomalies during El Niño events, is a unique hydrodynamic environment that differs markedly from that of the eastern tropical Pacific16–18. This see-saw behavior of sea level in the tropical Pacific has attracted much attention from scientists, and some studies have found that the PDO further modulates these effects by amplifying the sea level changes under in-phase conditions19. The North Equatorial Current (NEC) in the western Pacific and the nearby Mindanao Eddy (ME) clearly demonstrate the diverse impacts of climate oscillations in this region20,21. The temporal variation of the bifurcation latitude of the NEC is consistent with the concurrent PDO index22. The unexpected association between enhanced upwelling in the region around the ME during El Niño events revealed by recent studies has indicated that the biological implications of these climate oscillations may be even broader18,23. The discovery of phenomena unexpected on the basis of traditional understanding makes it difficult to fully anticipate the impact of climatic oscillations on marine ecosystems and in particular to accurately predict the response of phytoplankton communities in the western tropical Pacific to those oscillations and to anticipate the related consequences.

To address this concern, we carry out a comprehensive analysis of field observations made on four cruises during 2015–2019 in conjunction with reanalysis datasets and satellite observations made during 2003–2020 and the second-generation Community Earth System Model (CESM2). We hypothesize that the alterations of large-scale circulation and mesoscale eddies attributed to ENSO in the northwestern tropical Pacific give rise to biogeochemical responses different from those commonly witnessed in the eastern tropical Pacific. Specifically, we hypothesize that during El Niño events, there is an increase of chlorophyll a concentrations and a shift of phytoplankton community composition driven by changes in physical and chemical conditions in the northwestern tropical Pacific. We further hypothesize that the positive phase of the PDO amplifies these responses by promoting more favorable conditions for phytoplankton growth, particularly for groups such as diatoms. Our goal is to elucidate the biogeochemical responses to the combined effects of ENSO and PDO in the northwestern tropical Pacific. The results of this study provide insights into a mechanism that drives the dynamics of phytoplankton communities in response to climatic variability. This study emphasizes the contrast between the responses of the eastern and western tropical Pacific to climate oscillations and offers a more comprehensive view of how these ecosystems evolve under future climate scenarios. This broader understanding is needed to better predict the effect of climate change and to develop strategies for the sustainable management of marine resources in a rapidly changing world.

Results
Physiochemical dynamics under ENSO and PDO
We initially examined ENSO events spanning 216 months from January 2003 to December 2020. We focused on the 130°E meridian from 2–21°N. The SST anomalies (SSTA) were predominantly negative during El Niño events and positive during La Niña events (Figs. 1d and 2b). Evaluation of monthly variations of the sea level anomaly (SLA) associated with ocean currents and dynamic processes during this period (Figs. 1e and 2a) revealed that the SLA anomalies were similar to the distribution of SSTA—negative during El Niño and positive during La Niña (Figs. 1d and 2b). There was a significant correlation between SLA and the Multivariate ENSO Index Version 2 (MEI.v2) index (n=216, slope = −0.067 [95% CI: −0.076, −0.059], R2=0.52, p<0.0001, see Supplementary Table 4 for full statistical results) (Fig. 1f). We subsequently compared observational data from four cruises in this region, including two during the El Niño years (2015 and 2018) and two during neutral years (2016 and 2019) (Fig. 3). Along the 130°E transect, the ME occupied most of the area at latitudes of 5–10°N during the El Niño events of 2015 and 2018, and it was characterized by low sea surface height (SSH), high zonal velocity, and greater intensity than during the neutral years of 2016 and 2019 (Fig. 3 and Supplementary Fig. S5). The clear uplift of the vertical structures of temperature and salinity in the subsurface layer between depths of about 100 and 200 m during El Niño years implied that upwelling anomalies occurred during El Nino years. Specifically, the region near the ME was characterized by cold (<17.5°C), low-salinity (<34.75), nutrient-rich water (>15μmol L−1) at depths of 50–150 m during the two El Niño events, in contrast to neutral years (Supplementary Fig. S5). Additional analyses revealed that there was intensified mesoscale eddy activity in the northwestern Pacific (5°N–15°N, 120°E–160°E) during El Niño events (Supplementary Figs. S2, S3).

We then analyzed the long-term trends of the main physical and chemical parameters. Temporal variations of mixed layer depth anomalies (MLDA) (averaged over 2–21°N) were basically consistent with the variations of SSTA and SLA (Fig. 2a–c). Both the SLA and SSTA were significantly lower during El Niños (−0.03±0.06 m and −0.47±0.74°C, respectively) than during La Niñas (0.11±0.04 m and 0.79±0.92°C). This difference was confirmed by a Welch’s two-sided t-test (Fig. 2a, t(99.2)=−13.9, p<0.0001, Cohen’s d=−2.68 [95% CI: −3.22, −2.14]) and supported by a Mann–Whitney test (Fig. 2b, W=379, r=0.627, p<0.0001). The MLD was shallower during El Niños (−0.35±0.89 m), and it deepened during La Niñas (0.14±0.92 m) (t(100)=−2.71, p=0.0080, Cohen’s d=−0.547 [95% CI: −0.950, −0.144], Student’s t test), see Supplementary Table 4 for full statistical results. Except for the surface layer, in which the nitrate concentration was low throughout the section, the nitrate supply was greater during El Niños than during La Niñas (Supplementary Fig. S7). These physical changes associated with ENSO events did not occur during every El Niño or La Niña (for example, the 2006/2007 and 2019/2020 El Niño events). After smoothing of the timeseries data, we observed that the overall increase and decrease appeared to be correlated with warm and cold phases of the PDO, respectively (Fig. 2e). A positive PDO amplified the biogeochemical effects of El Niño, and a negative PDO enhanced those of La Niña. This pattern was particularly apparent in the SSTA and SLA. The implication is that the biogeochemical impacts of ENSO events can be either magnified or diminished by the PDO at certain tines. The result is nonlinear changes of oceanic conditions (Figs. 2 and 4).

Biological dynamics under ENSO and PDO
Our analysis of chlorophyll a water column inventories across the equatorial Pacific revealed a pronounced contrast in the responses of the eastern and western Pacific to ENSO events (Fig. 1a, b). Specifically, we observed opposite phytoplankton responses between the tropical northwestern Pacific and the eastern tropical Pacific, particularly in the Equatorial Upwelling region (120°W–90°W, 5°S–5°N). During El Niño events, chlorophyll a concentration increased in the western Pacific but decreased in the eastern tropical Pacific. During La Niña events, this pattern was reversed. The result was an antiphase distribution of chlorophyll a concentrations (Fig. 1a, b), but the pattern was not perfectly antisymmetric (Supplementary Fig. S4). During El Niño, there was a pronounced decline of chlorophyll a in the east (−0.019±0.002 mg m⁻³) but only a moderate increase in the west (0.010±0.002 mg m⁻³). Additional analyses revealed enhanced mesoscale eddy activity in the northwestern Pacific during El Niño (Supplementary Figs. S2, S3) that contributed to the localized enhancement of chlorophyll a and underscored the role of regional physical processes in shaping the response.

The average surface chlorophyll a concentrations gradually decreased from south to north over the period 2003–2020 (Fig. 1c). We analyzed major phytoplankton communities based on results of high performance liquid chromatography (HPLC)-CHEMTAX at a depth of 50 m (Fig. 3c–f). Prochlorococcus accounted for more than 32% of the chlorophyll a and was the dominant phytoplankton group during the four cruises. However, there were differences in the concentrations of diatoms and haptophytes during those four cruises. The average concentrations of diatom chlorophyll a were 0.01±0.02 mg m−3 and 0.04±0.10 mg m−3 in 2015 and 2018, respectively. The average concentrations of haptophyte chlorophyll a were 0.04±0.05 mg m−3 and 0.05±0.06 mg m−3 in 2015 and 2018, respectively. High values were found mainly near the ME and were consistent with the increase of total chlorophyll a during the two El Niño events (Fig. 3 and Supplementary Fig. S8). In contrast, the phytoplankton communities during the two neutral years were dominated by Prochlorococcus, and the total chlorophyll a concentrations were lower. The lead–lag correlation analysis revealed temporal associations between chlorophyll a and various environmental variables, with SLA peaking at zero lag, while other factors exhibited more complex temporal patterns that collectively influenced the distribution of chlorophyll a (Supplementary Table S3).

We used satellite observations between 2003 and 2020 to analyze the surface distributions of chlorophyll a and major phytoplankton communities (Prochlorococcus, haptophytes, and diatoms) (Supplementary Fig. S6). During the prolonged El Niño from 2014 to 2016, the haptophyte concentration increased. The abundance of haptophytes in surface waters increased during nearly every El Niño when the PDO was positive and decreased during La Niña when the PDO was negative (Figs. 4, 5a, and Supplementary Fig. S6). The 2018/2019 and 2019/2020 El Niños were characterized by positive anomalies of diatom concentrations (Supplementary Figs. S6 and 5a) that were not observed during other El Niños. To study the long-term changes of chlorophyll a concentrations at different depths, we chose five depths (5, 50, 100, 150, and 200 m) in the upper 200 m. Supplementary Fig. S7 shows the changes of average chlorophyll a concentrations at those depths during the cold and warm periods. The concentrations of chlorophyll a at depths of 50 m and 100 m in low-latitude areas and the southern tropical-gyre branch of the NEC were higher during El Niños than La Niñas. Nitrate concentrations also increased during El Niños (Supplementary Fig. S7). However, there were no variations of the chlorophyll a concentrations at those depths in the northern branch of the subtropical gyre of the NEC and Subtropical Countercurrent.

Methods
Field observations
The field data were collected on repeated transects from 2°N to 21°N along the 130°E meridian during four cruises of the R/V Kexue from 2015 to 2019. Supplementary Table S1 summarizes information about these cruises. Figure 1c shows the approximate distribution of the main currents in the northwestern tropical Pacific. We identified the currents and mesoscale eddies (the Halmahera Eddy [HE] and the ME) along the 130°E transect based on sea surface height, zonal velocities, and results of previous studies20,26.

We measured profiles of temperature and salinity at each station using a calibrated conductivity-temperature-depth (CTD) profiler (Seabird SBE CTD 911 plus). Nutrient samples were collected at 5 or 6 discrete depths from 5 to 200 m. Nitrate (NO3−-N) concentrations were measured using the cadmium reduction method; the detection limit was 0.01 µmol L⁻¹37. The analysis was performed with an automated analyzer (Technicon Auto Analyzer AA3) manufactured by Bran + Luebbe (Germany). The system uses a gas-segmented continuous flow analyzer (SCFA) that enables automated analysis of samples.

Seawater samples of 6–8 L were collected for phytoplankton pigment analysis from at least five depths (5, 50, 100, 150, and 200 m). The water was filtered through GF/F membranes with a 25-mm diameter, wrapped in aluminum foil, and kept in liquid nitrogen tanks. The photosynthetic pigments on the filter membrane were extracted by first removing surface moisture with filter paper. The membrane was then carefully unfolded and placed into a 1.5 mL amber test tube. N,N-Dimethylformamide (DMF) was added as the extraction solvent, and the mixture was kept in the dark at –20°C for 1–2 hours. After extraction, the extract was mixed with a 1 mol L⁻¹ ammonium acetate solution in a 1:1 ratio and stored at –20°C. The HPLC was used to identify photosynthetic pigments38. The main phytoplankton groups were then calculated with CHEMTAX V1.95 software based on characteristic photosynthetic pigment concentrations39,40. The pigment analyses enabled us to identify nine phytoplankton groups: dinoflagellates (Dino), diatoms (Diat), haptophytes_8 (Hapt_8), haptophytes_6 (Hapt_6), chlorophytes (Chlo), cryptophytes (Cryp), Prochlorococcus (Proc), Synechococcus (Syne), and prasinophytes (Pras).

Datasets
Climate indices. The MEI.v2 combines oceanic and atmospheric variables to assess ENSO with a single index41 (available at https://psl.noaa.gov/enso/mei/). Negative values represent a cold ENSO event (La Niña), whereas positive values represent a warm ENSO event (El Niño) (Fig. 1d). Between 2003 and 2020, there were a total of seven El Niño and five La Niña events according to the National Climate Center of China Meteorological Administration (NCC/CMA)42.

The PDO index is a metric that characterizes climate patterns and intensities based on variations of sea surface temperature in the North Pacific (https://psl.noaa.gov/data/correlation/pdo.data). A positive PDO index indicates a predominantly warm phase, whereas a negative index suggests a cold phase (Fig. 2e). The abbreviations PDO+ and PDO− denote the positive and negative PDO index, respectively. ENSO+ and ENSO− refer to El Niño and La Niña events, respectively (Supplementary Table S2).

Satellite data. If the datasets were available, satellite-based observations of annual average surface chlorophyll a concentrations were derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) database Level-3 products at 4-km pixel resolution (available at https://oceancolor.gsfc.nasa.gov/) (Fig. 1c). We used satellite data distributed by the Copernicus Marine and Environment Monitoring Service (CMEMS) to examine the spatiotemporal variations of surface phytoplankton communities in the northwestern tropical Pacific during 2003–2020. This dataset—including surface concentrations of chlorophyll a, diatoms, Prochlorococcus, and haptophytes—was obtained from the Bio-Geo-Chemical (BGC) products at 4-km resolution, generated using the Copernicus-GlobColour processor, which integrates observations from multiple sensors using a multi-algorithm, bias-corrected merging framework (available at https://doi.org/10.48670/moi-00281) (Fig. 2e and Supplementary Fig. S6). For all the phytoplankton groups, the satellite-derived concentrations were validated against field observations (the coefficient of determination R2 > 0.5, except for Prochlorococcus cells, for which the correlation was relatively weak), and the relationship was characterized by a low bias and slope close to 1 at the global level43. This product has been used in previous studies to identify and differentiate between phytoplankton communities in the surface ocean at different spatial scales43–45. Furthermore, ENSO-related phytoplankton responses were cross-validated using two independent satellite products (OC-CCI and GlobColour CMEMS) (Supplementary Fig. S1) to ensure the robustness of the results against known limitations such as sensor drift and inter-mission biases46. To clarify the mechanisms responsible for the dynamic changes of sea level over the tropical Northwest Pacific under the influence of ENSO, we used monthly 0.25°×0.25° gridded fields of SLA derived from satellite altimetry and distributed by CMEMS with the product identifier SEALEVEL_GLO_PHY_L4_MY_008_047 (https://doi.org/10.48670/moi-00148). This product was estimated by Optimal Interpolation, which is a method used to merge Level 3 along-track altimetry measurements from different satellite missions47. All datasets used in this analyses were from the period 2003–2020.

Reanalysis data and model data
The monthly SST, SSH, and surface geostrophic currents reanalysis data with 0.083° resolution were obtained from the GLORYS12V1 product (product ID: GLOBAL_MULTIYEAR_PHY_001_030, https://doi.org/10.48670/moi-00021). The monthly concentrations of nitrate and chlorophyll a (0.25°×0.25° resolution) from depths of 5 to 200 m were based on the PISCES biogeochemical model48. The specific product identifier of the dataset used in this study was the “GLOBAL_MULTIYEAR_BGC_001_029” (https://doi.org/10.48670/moi-00019). The MLD was estimated from a combination of a variable threshold on density profiles and a 0.2°C threshold on temperature profiles49. The MLD was obtained at a 0.25°×0.25° resolution during 2003–2020 (available at https://doi.org/10.48670/moi-00052). A preliminary study has compared the results of field observations and reanalysis data in this region and has verified the reliability of the Copernicus reanalysis results50.

The simulated data used in this study to analyze biogeochemical characteristics during different combinations of ENSO and PDO phases were derived from the second-generation Community Earth System Model (CESM2), which includes components for the atmosphere, ocean, sea ice, land, land ice, river runoff, and waves51. The ocean model employs the Parallel Ocean Program Version 2 (POP2) with a horizontal resolution of ~1°. The Marine Biogeochemistry Library (MARBL) module is used for simulating marine ecosystems and biogeochemical cycles and has been extensively validated against observational datasets51,52. We used the ocean-sea-ice coupled configuration (G compset, GIAF_JRA) to conduct hindcast simulations under an historical climate scenario. We used the Japanese 55-year atmospheric reanalysis (JRA-55) dataset as the atmospheric forcing conditions, which covers a period of 61 years (1958–2018)53. The JRA-55 forcing was conducted cyclically for spin-up for a total duration of 280 model years, divided into four complete cycles followed by an additional 36 years. The goal of the spin-up was to achieve a quasi-steady-state condition in the upper ocean layers. In reaching a quasi-steady state, we used the simulation results from the fifth cycle, and we focused on the period 2003–2018, which includes monthly SST, SSH, and two phytoplankton functional groups: diatoms and small phytoplankton (typically within the pico- to nano-size range).

Statistical analysis
In order to eliminate seasonal patterns, the abnormal changes of SST, MLD, chlorophyll a, and phytoplankton functional type (PFT) were quantified by their standardized anomalies, X’i,j:
X’i,j = (Xi,j − mean(Xj)) / std(Xj) (j=1, 2, ..., 12) (1)
where i is the year, j is the month, and std is the standard deviation of the data. We then used locally weighted scatter plot smoothing (Lowess Smooth) to filter out small fluctuations to highlight long-term trends.

Statistical significance was assessed using Welch’s t test, Mann–Whitney test, and Student’s t test for pairwise comparisons. One-way ANOVA followed by Tukey’s HSD test was used for multiple-group comparisons. If the parameters did not satisfy the assumptions of normality or homoscedasticity, the nonparametric Kruskal–Wallis (KW) test was used instead of ANOVA. Values of the type-I error rate (p) < 0.05 were considered statistically significant, and p<0.01 and p<0.001 were characterized as highly and very highly significant, respectively. Pearson’s correlation coefficient was used to determine the correlation between two variables. Timeseries analysis based on remote sensing and reanalysis data was conducted for the period from January 2003 to December 2020 using zonal averages along the 130°E transect (2°–21°N). A Lowess smoothing filter was applied to remove high-frequency fluctuations. Although the cruise-based observations were temporally discontinuous, the sampling design and resolution helped minimize potential autocorrelation effects. To evaluate the influence of the PDO, we built multiple linear regression models with and without PDO as a predictor variable, and we used the Akaike Information Criterion (AIC) to assess model performance.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This paper deals with the response of the Equatorial Pacific Ocean to ENSO and PDO, and contrasts the responses and the underpinning mechanisms in the eastern and western sides of the ocean. The paper is well-written, so it was a pleasure to be able to concentrate on the science without the distraction of grammatical mistakes, typos and poor organisation.\nThe relevance of the findings for discussions around the response of phytoplankton concentration and community structure to climate variability and climate change is well articulated. Implications for climate models and Earth system models are presented.\nThe novelty of the work lies in the juxtaposition of the responses in the eastern and western sides of the ocean, and in highlighting the complex interplay between ENSO and PDO. A suite of data (field and satellite) and models have been brought to bear on the problem, and the points made are well supported by data.\nI recommend the paper for publication.\nDetails:\nIt is disappointing that the authors chose to use MERIS data from recent years in this work. NASA has acknowledged that the sensor is in a drifting orbit, and a recent study (Pauthenet et al. 2024) has suggested that the drift in its product is evident from 2016-17 onwards. The same study has also concluded that the GlobColour products are not suitable for studying climate trends. Some globcolour products are also used in this study. It would be good to double check all the calculations and the inferences from the results to make sure that they are not compromised by the drift and degradation in MODIS, or by the use of GlobColour products for an application they were not designed for. Though the paper is not dedicated to trend analyses, there are nevertheless comparisons of moderate and extreme El Niño events.\nThe paper emphasises the see-saw nature of the phytoplankton response to ENSO/PDO in the western and eastern parts of the Equatorial Pacific. However, the counterbalance of increase noted in the western part is limited to what appears to be a much smaller area than that affected in the eastern part. The see-saw imagery implies equal and opposite effects, which may not be a true representation of the case. It would add value to the paper if the two opposing effects could be quantified and compared, so that one would be able to say whether the overall effect is net zero, positive, or negative, at least for the total phytoplankton concentration.\nReference:\nPauthenet, E., Martinez, E., Gorgues, T., Roussillon, J., Drumetz, L., Fablet, R., & Roux, M. (2024). Contrasted trends in chlorophyll‐a satellite products. Geophysical Research Letters, 51, e2024GL108916. https://doi.org/10.1029/ 2024GL108916", "reviewer_2": "COMMENT SHEET\nfor\nPAPER NUMBER: NCOMMS-24-63214\nJOURNAL: Nature communications\nTITLE: Contrasting Climate Oscillations Impacts on Phytoplankton in the Western and Eastern Tropical Pacific\nThe manuscript by Lina An et al. uses comprehensive datasets including field observations, satellite data, reanalysis datasets, and Earth system modeling outputs, and presents a challenge to the traditional understanding of ENSO's impact on marine ecosystems, particularly highlighting differences between the eastern and western tropical Pacific regions.\nHowever, while the authors attempt to build a compelling argument using a various data sets, the manuscript is poorly written and falls short due to insufficient information and a lack of robust support for their interpretations. The study is primarily descriptive, lacks critical details, and requires significant revisions before it can be considered for publication. Additionally, the manuscript contains writing errors and inappropriate expressions. The major and minor issues are detailed below:\n1. One of my main concerns is the small research area in the western Pacific, which appears to have been selected without sufficient justification. Even if the cruise observations were conducted exclusively in this region, the authors could consider expanding the study area to include regions that show covariance with the current research area. For instance, reanalysis or satellite data could be used to identify these covarying regions through simple correlation mapping. Overall, the authors need to provide a strong rationale for focusing specifically on the western Pacific.\n2. Another significant concern is that the seesaw pattern of the biological response and its mechanisms, as proposed in the manuscript, do not appear to be novel findings, despite the authors’ claims of distinction from previous studies. Opposing responses in the western and eastern Pacific have been well-documented in earlier research, and the considerable impact of eddies near islands and boundary areas has also been previously reported. Furthermore, the relative contributions of the PDO and ENSO to the biological response seem to align with expected outcomes.\n3. The proposed mechanisms, such as the role of the Mindanao Eddy and mixed-layer depth variations, are compelling but not rigorously tested. Correlative analyses dominate, and causation remains speculative The manuscript is largely descriptive and lacks essential details, particularly regarding the eddy impact. The authors should conduct further analyses to disentangle and quantify the eddy's influence. For instance, a nutrient or phytoplankton biomass budget analysis could be performed using modeling outputs.\n4. Given the nature of this journal, it would be desirable to expand the discussion to a broader application, by connecting findings with global-scale biogeochemical cycles and potential impacts on fisheries or carbon sequestration.\n5. Other minor comments are as follows.\n- Line 562: Are the SST and sea level anomalies shown in Fig. 1d and 1f averaged indices for the northwestern Pacific region? Which one is the MEI? These need to be clarified in the figure caption.\n- Line 190: it should be “observations”\n- Figure 3 caption: More detailed info is necessary to understand the figure.", "reviewer_3": "The study underscores the differentiate regional impact of the large-scale climate oscillations ENSO and PDO in the tropical Pacific on biogeochemical and phytoplankton composition. Results are based on an extensive dataset including decadal satellite observations of chlorophyll and phytoplankton taxonomic groups, biogeochemical models and ship-based measurements. While impacts of large-scale climate oscillations have been shown previously, the finding of this study gains particular relevance in light of observed contrasting impacts in the western tropical Pacific on phytoplankton composition and underlying mechanisms.\nGeneral comments:\nThe article is very clear in its writing, effectively conveying and discussing the results. The study is topical and interesting, but I have some concerns with the study the authors need to clarify:\n1) One major concern with the study is the novelty of the findings that ENSO impacts show unexpected responses in the western tropical Pacific. Differentiate regional impacts of ENSO and PDO in the eastern and western tropical Pacific have been shown in previous findings, see reference 2 in this article and others on phytoplankton, see ref 1. The latter study shows increased chlorophyll under El Niño in the Western Pacific, similar to their findings. I suggest that the authors acknowledge these studies and clearly communicate in which ways their findings go beyond previous studies. I also suggest that the authors clarify by what they mean with ‘more complex’, like more complex to what? I assume that this is related to the assumption of low chlorophyll in warm periods and reverse in cold. As such, I suggest to improve this in the abstract, introduction and discussion sections. Similarly, the authors state that effects of ENSO and PDO are seldom considered, however there are some studies that include both ENSO and PDO effects or regional indices derived from PDO, for example see references 2,3, and others.\n2) Related to the comment above, the authors emphasize the inclusion of comprehensive ship-based studies, however it is not clear how these measurements support the conclusions. The ‘real’ data of these field observations are illustrated in graphical drawings in Figs. 3 c and d and observed values described in the text. I would suggest to show the measured data in a figure to better comprehend the results as this is not clear to see with the intervals included in the text. Moreover, the clarity of Figs. 3c and d should be improved by included axes ticks and units.\n3) The statistical analysis needs improvement and the approach clearly described what test was used to address which particular hypothesis/question. The method report ANOVA and Kruskal-Wallis tests, yet the analyses are time series and biases and pitfalls in time series and spatial analyses should be considered and described.\n4) The amplification of ENSO with positive PDO values is rather descriptive but this is not tested quantitatively. Could the authors use a model and test if AIC values, or similar, improve if PDO is included as a predictor variable?\n5) I suggest to improve the labelling of the figures by describing the results (figures) in chronological order in the text as the ordering of figures are difficult to follow.\nMinor comments:\nL 25. Can you make this sentence more informative ‘… we reveal unexpected responses …’, like ‘ … opposite responses …’?\nL 59. Should this be picocyanobacterial? Good if this is specified.\nL 81. I suggest to change ‘We believe’ to ‘We hypothesise …’ or similar\nL 84. Can you motivate your assumption of a shift in phytoplankton community composition? What is the rationale behind this hypothesis? I guess this is a consequence of physical and chemical changes, so can you speculate what functional groups should change?\nL 95. Please clarify to which region these results relate to, similar in following paragraphs like L 113.\nL 111. Should ‘normal years’ be replaced with ‘ENSO neutral years’ to make clear what this is related to?\nL 128-130. Is this a result sentence? Since no reference is given to previous studies, the sentence feels out of context.\nL 100 and 117ff. Please include the test that is used for the analysis and report R2 and related statistical out as reporting only a p-value in isolation is not very informative. Is there a need to account for temporal or spatial autocorrelation?\nL 145 – 148. Can these results be shown in a figure instead? It is difficult to comprehend, especially given the relative sizes of the intervals. Also, what are the intervals representing? SD, SE or CI?\nL 157. ‘As expected’. This is out of context without further discussion. Better to remove.\nL 174. Please include a reference to this statement.\nL 276. Please clarify how nutrient samples were treated and measured, similar to phytoplankton samples.\nL 280. Remove “subsequently”. It leads the thought towards a size-fractionated filtering procedure, which is not the case here. Or was the water from different depth strata combined?\nL 282. Spell out HPLC? Or refer to a previously published protocol. Also, mention how pigments were extracted.\nL 351. Please clarify what is meant by ‘small phytoplankton’\nL 362. Statistical analysis: this needs better description. Clarify what you use the statistical tests for.\nL 560. Can you clarify what is meant by ‘study area’ particularly as the previous figure shows a larger region? I guess this the regional area this study focuses on, this should be clearly communicated in the results. Is this the red box in Fig 1a?\nL 561. Please specify which area the SSTA relates to?\nL563. Why is the x-axis, latitude, shown in reverse order as to c? Please include x-axis labelling.\nL578. I suggest to include a sentence such as ‘Box plots represent values within specific periods, with the line ….’, or similar\nL585. Please clarify figures Fig 3 c and d.\nL596. SSHA – should this be SLA as in previous figures? Please check throughout.\nReferences\n1. Chen, R., Wu, B., Li, Z. & Wang, S. Impacts of ENSO on Tropical Pacific Chlorophyll Biomass Under Historical and RCP8.5 Scenarios. J. Geophys. Res. Oceans 129, e2023JC020720 (2024).\n2. Cloern, J. E. et al. Biological communities in San Francisco Bay track large-scale climate forcing over the North Pacific: CLIMATE PATTERNS AND ESTUARINE ECOLOGY. Geophys. Res. Lett. 37, n/a-n/a (2010).\n3. Beaufort, L. & Grelaud, M. A 2700-year record of ENSO and PDO variability from the Californian margin based on coccolithophore assemblages and calcification. Prog. Earth Planet. Sci. 4, 5 (2017). Climatic effects on the phenology of lake processes. Glob. Change Biol. 10, 1844–1856 (2004).", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "Responses to the comments of the Reviewers\nAuthors’ response to reviewers:\nWe thank the four anonymous reviewers for their constructive comments and suggestions that greatly improved the quality of this manuscript. We have made revisions according to the reviewers’ comments, with detailed point-by-point responses provided below. Comments of the reviewers are printed in black, and responses are printed in blue. The modified part of the revised manuscript is shown in red.\nReviewer #1 (Remarks to the Author):\nThis paper deals with the response of the Equatorial Pacific Ocean to ENSO and PDO, and contrasts the responses and the underpinning mechanisms in the eastern and western sides of the ocean. The paper is well-written, so it was a pleasure to be able to concentrate on the science without the distraction of grammatical mistakes, typos and poor organisation.\nThe relevance of the findings for discussions around the response of phytoplankton concentration and community structure to climate variability and climate change is well articulated. Implications for climate models and Earth system models are presented.\nThe novelty of the work lies in the juxtaposition of the responses in the eastern and western sides of the ocean, and in highlighting the complex interplay between ENSO and PDO. A suite of data (field and satellite) and models have been brought to bear on the problem, and the points made are well supported by data.\nI recommend the paper for publication.\nRE: Thank you for affirming the significance of our research. We are also extremely grateful for your suggestions. Below are our detailed responses and the corresponding revised content.\nDetails:\n1. It is disappointing that the authors chose to use MERIS data from recent years in this work. NASA has acknowledged that the sensor is in a drifting orbit, and a recent study (Pauthenet et al. 2024) has suggested that the drift in its product is evident from 2016-17 onwards. The same study has also concluded that the GlobColour products are not suitable for studying climate trends. Some globcolour products are also used in this study. It would be good to double check all the calculations and the inferences from the results to make sure that they are not compromised by the drift and degradation in MODIS, or by the use of GlobColour products for an application they were not designed for. Though the paper is not dedicated to trend analyses, there are nevertheless comparisons of moderate and extreme El Niño events.\nRE: We sincerely appreciate the reviewer’s comments regarding the use of MODIS and GlobColour data in our study. We acknowledge the concerns related to the orbital drift of MODIS, as highlighted by NASA and further examined by Pauthenet et al. (2024). To address these concerns, we have carefully assessed potential biases introduced by sensor drift and data product limitations. Specifically, we have cross-validated our findings using independent datasets where available and ensured that our key conclusions remain robust despite known uncertainties in satellite-derived products. Pauthenet et al. (2024) have discussed the surface chlorophyll a concentrations (Schl) estimated from six merged products and five Schl mono sensors (Fig. R1). Their analysis suggests that Globcolour-GSM has been significantly influenced by the anomalous trend introduced by VIIRS after 2012/2016, while uncertainties arise toward the end of the OC-CCI time series, when an apparent increase of Schl was likely attributed to biases from MODIS. In our study, it is important to clarify that MODIS-Aqua data were used solely in Fig. 1c to illustrate the regional climatological background of chlorophyll a concentration rather than for temporal trend analyses (see Methods–Satellite Data for details). Then our study utilized the OCEANCOLOUR_GLO_BGC_L4_MY_009_104 dataset (https://doi.org/10.48670/ moi-00281) to estimate surface chlorophyll a concentrations and phytoplankton functional types (PFTs), as presented in Fig. 2e and Fig. S6. This dataset is provided by the Copernicus Marine Service and is derived from multiple satellite sensors, including SeaWiFS, MODIS, MERIS, VIIRS-SNPP & JPSS1, and OLCI-S3A & S3B. Observations from these sensors were processed to generate biogeochemical variables such as chlorophyll a and PFT. According to the Quality Information Document for this product, the global 4-km product validation shows a good relationship between in-situ measurements and chlorophyll a concentration. For daily estimates, the statistics show a coefficient of determination (R2) of 0.75 associated with the optimal regression line 1:1 while the cloud-free (interpolated) product shows a small degradation, but the R2 still reached 0.71 for the Global product at 4 km. For all the phytoplankton groups, the coefficient of determination (R2) between observed and predicted data exceeded 0.5 (except for the small Prochlorococcus cells, for which the correlation was relatively weak), and the relationship was characterized by a low bias and slope close to 1 at the global level. Consistency between different sensors (e.g., MODIS, VIIRS, and OLCI) is ensured by comparing the chlorophyll a data generated by each sensor. If anomalies are detected in the data from a particular sensor, the system makes corresponding adjustments or excludes the data. Similar to the GlobColour CMEMS product (OCEANCOLOUR‐GLO‐BGC‐L3‐MY‐009‐103) mentioned by Pauthenet et al. (2024), this product does not exhibit significant drift issues; the problematic one is GlobColour GSM (Fig. R1). The Globcolour-GSM product also merges inter-sensor reflectance observations, but it uses a different atmospheric correction and semi-analytical bio-optical model, and it does not perform inter-mission bias correction. On the contrary, due to its multi-algorithm weighted averaging approach, GlobColour CMEMS may exhibit a certain buffering effect against the impact of MODIS sensor drift (Pauthenet et al. 2024).\nThe chlorophyll a concentration data used to analyze temporal variations and their associations with climate oscillations across different depths (Fig. S4) were obtained from the GLOBAL_MULTIYEAR_BGC_001_029 dataset (DOI: 10.48670/moi-00019). This dataset is primarily based on numerical modeling and utilizes the PISCES biogeochemical model within the NEMO modeling framework. From the Quality Information Document, it is forced by daily mean fields of ocean, sea ice, and atmosphere. Ocean and sea ice forcings come from the numerical simulation FREEGLORYS2V4 produced at Mercator-Ocean, and the atmospheric forcings come from the ERA-Interim2 reanalysis produced at ECMWF. Fig. R2 shows a comparison between model and observations (Globcolour product) of annual surface chlorophyll computed for the years 1998–2017. On the global ocean scale, the modelled chlorophyll has a Root Mean Square (RMS) difference of 0.371 for the period 1997-2017 at the sea surface in comparison with daily satellite chlorophyll observations. The modeled mean annual chlorophyll a field shows a good agreement with satellite-derived estimates at the global scale. In the tropical band of the Pacific Ocean, the model correctly reproduces the westward pointing “arrowhead” shape of the chlorophyll tongue. However, the tongue is slightly too wide, expands too far westwards, and its south/north boundaries are too diffuse. This can be observed on Fig. R2 (bottom right), where there is a positive anomaly on the border of the tropical tongue. However, such differences do not affect our analysis of interannual and decadal-scale climate oscillations. Furthermore, our findings have been cross-validated against alternative datasets where available, confirming that the principal conclusions remain robust to known uncertainties inherent in satellite-derived products (Fig. S1). Specifically, we conducted a comparative analysis of ENSO-driven responses between two independent ocean-color products: the OC-CCI dataset and the GlobColour CMEMS product.\nLines 368–373\nThis dataset—including surface concentrations of chlorophyll a, diatoms, Prochlorococcus, and haptophytes—was obtained from the Bio-Geo-Chemical (BGC) products at 4-km resolution, generated using the Copernicus-GlobColour processor, which integrates observations from multiple sensors using a multi-algorithm, bias-corrected merging framework (available at https://doi.org/10.48670/moi-00281) (Fig. 2e and Fig. S6).\nLines 378–381\nFurthermore, ENSO-related phytoplankton responses were cross-validated using two independent satellite products (OC-CCI and GlobColour CMEMS) (Fig.S1) to ensure the robustness of the results against known limitations such as sensor drift and inter-mission biases 46.\nFig. R1. Spatial weighted average of Schl for each merged products (a) and for several sensors reprocessed by Globcolour‐GSM (b).\nPanel (a) displays the median Schl concentration by month (thin line) and smoothed with a locally estimated scatterplot smoothing (loess, thick line). The overall shift between products is mostly due to the different numbers of valid points in each product (Pauthenet et al. 2024).\nFig. R2. (top) Annual mean of surface chlorophyll averaged over the period 1998-2017 (mg m-3). (left) model; (right) Globcolour observations. (bottom-left) RMS difference computed with monthly chlorophyll means during the period 1997–2017.\nColorbar is in log scale; (bottom-right) mean difference (model minus obs) over the period 1997-2017 (mg.m-3).\nFig.S1. Response of chlorophyll a anomaly to ENSO: comparison of OC-CCI and GlobColour CMEMS Products. Time series of chlorophyll a anomaly (Chl a A, mg m−3) averaged over 2–21°N, 130°E, comparing the responses to ENSO events between the OC-CCI product (OCEANCOLOUR_GLO_BGC_L4_MY_009_108) and the GlobColour CMEMS product (OCEANCOLOUR_GLO_BGC_L4_MY_009_104).\n2. The paper emphasises the see-saw nature of the phytoplankton response to ENSO/PDO in the western and eastern parts of the Equatorial Pacific. However, the counterbalance of increase noted in the western part is limited to what appears to be a much smaller area than that affected in the eastern part. The see-saw imagery implies equal and opposite effects, which may not be a true representation of the case. It would add value to the paper if the two opposing effects could be quantified and compared, so that one would be able to say whether the overall effect is net zero, positive, or negative, at least for the total phytoplankton concentration.\nRE: We sincerely appreciate your insightful feedback. We acknowledge that the term seesaw may imply a symmetrical response, which may not fully capture the spatial and dynamical asymmetries in phytoplankton variations across the equatorial Pacific. We have recalculated the areas according to your suggestions and revised the manuscript accordingly (New Fig. 1). To provide a more rigorous quantification, we conducted additional analyses (New Fig. S1–S4) comparing the total impact of mesoscale eddies in the northwestern Pacific, as well as the magnitude and spatial extent of phytoplankton changes in the western and eastern regions.\nIn the eastern equatorial Pacific, large-scale upwelling processes exert a dominant control on phytoplankton dynamics, with El Niño events suppressing upwelling and thereby reducing vertical nutrient fluxes (New Fig. 1). The scale of these processes results in phytoplankton anomalies spanning a broad spatial region. In contrast, the western equatorial Pacific is primarily influenced by mesoscale eddies, which operate over smaller spatial scales (tens to hundreds of kilometers). These mesoscale processes play a pivotal role in oligotrophic, low-latitude regions, where their cumulative impact, despite the localized nature of individual eddies, can be substantial (Fig. R3) (Liu et al., 2023). To further examine the role of mesoscale eddies in modulating ENSO-driven phytoplankton variability, we quantified eddy activity across the northwestern Pacific (120°E–160°E, 5°N–15°N) from 2003 to 2020 (new Fig. S2 and S3). Our analysis revealed that eddy intensity, as indicated by eddy speed, strengthens during El Niño events, accompanied by a positive chlorophyll a anomaly within eddy interiors. Eddy speeds were obtained from the Aviso eddy dataset (https://www.aviso.altimetry.fr), and the eddy rotational velocities of cyclonic and anticyclonic eddies were analyzed within the 5°N–15°N, 120°E–160°E region during El Niño and La Niña periods from 2003 to 2020. Chlorophyll a concentrations were sourced from the OCEANCOLOUR_GLO_BGC_L4_MY_009_104 dataset. To characterize chlorophyll a anomalies within eddies, we extracted chlorophyll a anomaly values that spatiotemporally matched the eddy locations and then computed monthly averages. A key feature of our study region is the Mindanao Eddy, a semi-permanent structure exerting a persistent influence on local oceanographic conditions. Its impact on the northwestern Pacific is profound, shaping regional circulation patterns, nutrient transport, and biological productivity. These findings highlight the important role of mesoscale processes in shaping phytoplankton responses to climate variability.\nFurthermore, we have conducted a quantitative comparison of differences of chlorophyll a anomalies during ENSO events in both the western and eastern equatorial Pacific (new Fig. S4). Our findings reveal a distinct antiphase dynamical pattern characterized by regional asymmetries, with significant variations in both the magnitude and variability of the anomalies across regions. Specifically, during El Niño events, chlorophyll concentrations in the eastern Pacific exhibit a significant decline (mean ± SE: −0.019 ± 0.002 mg m−3), whereas in the western Pacific, they increase (0.010 ± 0.002 mg m−3). Conversely, La Niña conditions lead to a chlorophyll enhancement in the eastern Pacific (0.006 ± 0.004 mg m−3) and a decline in the western Pacific (−0.001 ± 0.001 mg m−3). While the opposite responses in the two basins reflect an antiphase dynamic, we acknowledge that the spatial extent and intensity of these changes are not perfectly symmetric. The net chlorophyll anomaly, integrated over both regions, does not sum to zero. The implication is that ENSO exerts a net impact on basin-scale primary production rather than a strict redistribution of production. This asymmetry may arise from inherent differences in nutrient dynamics, upwelling intensity, and biological productivity between the two regions. We have clarified this issue in the revised manuscript and included additional discussion on the implications of the observed asymmetry for large-scale biogeochemical cycling.\nLines 118-119\nAdditional analyses revealed that there was intensified mesoscale eddy activity in the northwestern Pacific (5°N–15°N, 120°E–160°E) during El Niño events (Fig. S2 and S3).\nLines 145-151\nThe result was an antiphase distribution of chlorophyll a concentrations (Fig. 1a and 1b), but the pattern was not perfectly antisymmetric (Fig. S4). During El Niño, there was a pronounced decline of chlorophyll a in the east (−0.019 ± 0.002 mg m⁻³) but only a moderate increase in the west (0.010 ± 0.002 mg m⁻³). Additional analyses revealed enhanced mesoscale eddy activity in the northwestern Pacific during El Niño (Fig. S2 and S3) that contributed to the localized enhancement of chlorophyll a and underscored the role of regional physical processes in shaping the response.\nFig. 1. ENSO-induced antiphase patterns in biophysical dynamics of the equatorial Pacific.\nDistribution of chlorophyll a water column inventory anomaly (Chl a A, mg m-2) above 50 m during El Niño (a) and La Niña (b). The boxes represent different areas: the Equatorial Upwelling region (120°W–90°W, 5°S–5°N) and the northwestern Pacific region (125°E–150°E, 2–10°N). (c) Schematic of major currents and the field observation transect (indicated by the black line; 2–21°N, 130°E). The background is the average satellite observations of surface chlorophyll a (Chl a_sat, mg m−3). (d) Time series of sea surface temperature anomaly (SSTA, °C) and monthly MEI.v2 index averaged over the field observation transect (2–21°N, 130°E) during 2003–2020. The MEI is represented by red (positive) and blue (negative) bars, corresponding to MEI > 0 and MEI < 0, respectively. The gray lines in Fig. 1d. denote four field observation cruises. (e) The variabilities of sea level anomaly (SLA, m) along the meridional 130°E transect. (f) The relationship between sea level anomaly (SLA, m) and the MEI.v2 index. The MEI.v2 values are shown on the x-axis and correspond to the SLA anomalies on the y-axis. The straight line is an ordinary least squares regression. Both SSTA and SLA are averaged over the field observation transect (130°E, 2–21°N). STCC, Subtropical Countercurrent; NEC, North Equatorial Current; NECC, North Equatorial Counter Current; HE, the Halmahera Eddy; ME, the Mindanao Eddy.\nFig. R3. Time series of the monthly generated numbers of (A) Short-lived cyclonic and anticyclonic eddies (CEs and AEs), monthly regional averaged (B) SLA, (C) eddy kinetic energy (EKE, log ), (D) monthly regional average of relative vorticity (ξ) in 10\nthe area bounded by 2°–10°N, 125°–180° E for the period 1993–2017 (Liu et al., 2023).\nFig. S2. Frequency of occurrence of mesoscale eddies in the northwestern Pacific from 2003 to 2020. (a) cyclonic eddies and (b) anticyclonic eddies.\nFig. S3. Mean eddy velocity (m s⁻¹) of cyclonic (a) and anticyclonic (b) eddies, and chlorophyll a anomaly (Chl a A, mg m⁻³) in cyclonic (c) and anticyclonic (d) eddies, within the region bounded by 5°N–15°N, 120°E–160°E from 2003 to 2020. All panels illustrate variability in response to ENSO events. The red lines represent relative changes of eddy speed, which were estimated by a lowess smoother. The shaded red and blue represent El Niño and La Niña events, respectively.\nFig. S4. Antiphase pattern of chlorophyll a response to ENSO in the Equatorial Pacific.\nChlorophyll a anomaly difference (mg m−3) in the eastern (120°W–90°W, 5°S–5°N) and western (120°E–160°E, 5°N–15°N) Equatorial Pacific during El Niño and La Niña events. Chlorophyll a anomalies are deviations from the neutral baseline. Positive (negative) values indicate elevated (reduced) concentrations relative to neutral conditions.\nReviewer #2 (Remarks to the Author):\nThe manuscript by Lina An et al. uses comprehensive datasets including field observations, satellite data, reanalysis datasets, and Earth system modeling outputs, and presents a challenge to the traditional understanding of ENSO's impact on marine ecosystems, particularly highlighting differences between the eastern and western tropical Pacific regions.\nHowever, while the authors attempt to build a compelling argument using a various data sets, the manuscript is poorly written and falls short due to insufficient information and a lack of robust support for their interpretations. The study is primarily descriptive, lacks critical details, and requires significant revisions before it can be considered for publication. Additionally, the manuscript contains writing errors and inappropriate expressions.\nRE: Thanks for your comments and suggestions. We have made modifications accordingly, and we have been careful to add relevant description and discussions as you suggested.\nThe major and minor issues are detailed below:\n1. One of my main concerns is the small research area in the western Pacific, which appears to have been selected without sufficient justification. Even if the cruise observations were conducted exclusively in this region, the authors could consider expanding the study area to include regions that show covariance with the current research area. For instance, reanalysis or satellite data could be used to identify these covarying regions through simple correlation mapping. Overall, the authors need to provide a strong rationale for focusing specifically on the western Pacific.\nRE: Thanks for your suggestion. We agree that spatial representativity is crucial, and we thank the reviewer for the opportunity to clarify this aspect. We have recalculated the areas according to your suggestions and revised the manuscript accordingly.\nIn the previous version, the study area was based on multiple field cruise observations and the biophysical characteristics of the region. Considering the comparability of the regional scale, we have redefined the study area in combination with observational data (new Fig. 1).\nTo further substantiate our regional focus, we have conducted a broader temporal analysis and a comparative assessment between the western and eastern Pacific using reanalysis datasets (new Fig. S2–S4). The fact that this region of the northwestern Pacific is where mesoscale eddies exhibit the strongest response to ENSO events makes it particularly suitable for investigating ENSO-driven phytoplankton dynamics. These additional analyses confirm that chlorophyll-a variability in our selected region is strongly coherent with adjacent areas, particularly within the western Pacific warm pool and its associated mesoscale eddy fields (new Figs. S2 and S3). When expanding the study area to a scale comparable to that of the eastern Pacific, our key results remain unchanged. This suggests that the observed ENSO-driven phytoplankton responses in the western Pacific are robust and representative of a broader regional pattern.\nWhile expanding the study area could provide additional context, it may also introduce variability unrelated to our primary research question. To maintain clarity in linking ENSO to phytoplankton community responses, we have focused on a well-defined region with strong observational and analytical support. Nonetheless, we recognize the value of a broader-scale investigation and will consider it for future studies.\nLines 234-240\nWe recognize that results of a study of this specific region may not be broadly applicable. While expanding the study area to include regions that covary with the western Pacific could provide additional context (Fig.S2 and S3), it is essential to consider the unique characteristics of the region under investigation. Future research could address this limitation by inclusion of cruises to explore analogous phenomena across a broader geographical range and thereby provide a more comprehensive understanding of the spatial heterogeneity of phytoplankton responses to ENSO.\nFig. 1. ENSO-induced antiphase patterns in biophysical dynamics of the equatorial Pacific.\nDistribution of chlorophyll a water column inventory anomaly (Chl a A, mg m-2) above 50 m during El Niño (a) and La Niña (b). The boxes represent different areas: the Equatorial Upwelling region (120°W–90°W, 5°S–5°N) and the northwestern Pacific region (125°E–150°E, 2–10°N). (c) Schematic of major currents and the field observation transect (indicated by the black line; 2–21°N, 130°E). The background is the average satellite observations of surface chlorophyll a (Chl a_sat, mg m−3). (d) Time series of sea surface temperature anomaly (SSTA, °C) and monthly MEI.v2 index averaged over the field observation transect (2–21°N, 130°E) during 2003–2020. The MEI is represented by red (positive) and blue (negative) bars, corresponding to MEI > 0 and MEI < 0, respectively. The gray lines in Fig. 1d. denote four field observation cruises. (e) The variabilities of sea level anomaly (SLA, m) along the meridional 130°E transect. (f) The relationship between sea level anomaly (SLA, m) and the MEI.v2 index. The MEI.v2 values are shown on the x-axis and correspond to the SLA anomalies on the y-axis. The straight line is an ordinary least squares regression. Both SSTA and SLA are averaged over the field observation transect (130°E, 2–21°N). STCC, Subtropical Countercurrent; NEC, North Equatorial Current; NECC, North Equatorial Counter Current; HE, the Halmahera Eddy; ME, the Mindanao Eddy.\n2. Another significant concern is that the seesaw pattern of the biological response and its mechanisms, as proposed in the manuscript, do not appear to be novel findings, despite the authors’ claims of distinction from previous studies. Opposing responses in the western and eastern Pacific have been well-documented in earlier research, and the considerable impact of eddies near islands and boundary areas has also been previously reported. Furthermore, the relative contributions of the PDO and ENSO to the biological response seem to align with expected outcomes.\nRE: Thank you for pointing this out. We acknowledge that the opposite biological responses between the western and eastern Pacific during ENSO events have been documented in previous studies. However, our study provides a new dimension by quantitatively characterizing the magnitude, variability, and spatial coherence of these responses using long-term observations, satellite data, and reanalysis products. Unlike prior research, which often focused on basin-scale chlorophyll anomalies, our study explicitly links mesoscale eddy activity in the western Pacific to large-scale ENSO variability and highlights the role of mesoscale eddy activity as a key modulator of phytoplankton dynamics.\nIn addition, while the influences of ENSO and PDO on biological productivity have been recognized, their relative contributions remain a subject of ongoing debate (new Fig. S9). Our analysis disentangles these effects by leveraging long-term datasets to assess their distinct impacts on interannual and decadal timescales. This differentiation is crucial for understanding how climate variability influences ecosystem resilience and predictability. To clarify these points, we have revised the discussion to better articulate the novelty of our approach; we have emphasized how our findings build upon and extend previous studies.\nLines 280-289\nOur findings reveal that phytoplankton communities in the northwestern tropical Pacific respond to climate variability in ways more complex than previously recognized. While the roles of ENSO and the PDO in shaping regional chlorophyll patterns are well established, our multi-cruise observations revealed taxon-specific responses to different phases of ENSO that reflected distinct ecological strategies and were modulated by mesoscale eddies. These results underscored the need to integrate physical, chemical, and biological processes when assessing ecosystem responses to climate forcing. In particular, strong or prolonged ENSO events may drive structural shifts of community composition that highlight the nonlinear, scale-dependent dynamics that must be considered in future climate–ecosystem projections.\n3. The proposed mechanisms, such as the role of the Mindanao Eddy and mixed-layer depth variations, are compelling but not rigorously tested. Correlative analyses dominate, and causation remains speculative The manuscript is largely descriptive and lacks essential details, particularly regarding the eddy impact. The authors should conduct further analyses to disentangle and quantify the eddy's influence. For instance, a nutrient or phytoplankton biomass budget analysis could be performed using modeling outputs.\nRE: We sincerely appreciate your thoughtful and constructive feedback. We acknowledge the importance of quantitatively assessing eddy-driven biogeochemical processes and agree that modeling efforts are a necessary step. A comprehensive framework would require coupling physical dynamics with ecological processes, explicitly resolving phytoplankton functional groups. However, such an approach remains challenging because of the complexity of parameterization and the limitations of current eddy-resolving Earth system models. Further optimization of parameter settings is essential to improve model performance. In addition, a multi-scale approach bridging basin-scale dynamics with high-resolution simulations is needed to fully capture the impact of the eddy, yet key methodological steps remain to be refined. On the other hand, the fact that observational and reanalysis datasets still exhibit discrepancies complicates direct validation.\nNonetheless, our study provides critical empirical evidence and data to guide future modeling efforts. Our previous study builds upon earlier single-cruise analyses in this region, which have already quantified the impact of mesoscale eddies on phytoplankton communities (Fig. R4) (An et al., 2024). These findings show the spatial variability of eddy-driven phytoplankton responses across different oceanic regions. Indeed, our results support the notion that mesoscale eddies exert heterogeneous influences—while some eddies trigger pronounced biological responses, others have more subdued effects that depend on the physical properties of the eddies and the surrounding environmental conditions.\nWe fully agree that modeling is a critical tool for quantifying eddy-induced nutrient fluxes and phytoplankton growth dynamics. We are actively considering and developing a modeling framework to further validate and extend our findings. However, the lack of key observational constraints, particularly on nutrient uptake rates, presents a significant challenge in accurately parameterizing biogeochemical processes. We are currently working to supplement these critical data gaps through additional field measurements. Moreover, our preliminary model results indicate that proper calibration is essential, because current biogeochemical models still exhibit uncertainties in representing eddy-driven nutrient transport and phytoplankton growth. In future work, we aim to refine these models with improved observational constraints to allow for a more comprehensive assessment of eddy impacts over varying temporal and spatial scales. We have also incorporated relevant discussions on this topic as follows:\nLines 204-209\nOur results provided critical empirical evidence that phytoplankton functional groups exhibit distinct, context-dependent responses to mesoscale eddies and climate oscillations. While mechanistic interpretations remain constrained by model uncertainties and observational limitations, this study established a basis for future integrative efforts combining high-resolution, physical-biogeochemical modeling with targeted field observations to better quantify eddy-driven ecological variability.\nFig. R4. Redundancy analysis for the relationships between phytoplankton community and environmental factors in the different mesoscale eddies during the cruise in October 2018.\nRed arrows represent the environmental factors, whereas blue arrows represent the phytoplankton communities. Temp: temperature, Sal: salinity, nitrate, phosphate, silicate, latitude, SSH: sea surface height, TChl a: total chlorophyll a. Different colored dots represent stations affected by mesoscale eddies. HE, the Halmahera Eddy; ME, the Mindanao Eddy and CE, cyclonic eddy. Yellow dots represent CE, red dots represent HE, blue dots represent ME, and black dots represent other stations (An et al., 2024).\n4. Given the nature of this journal, it would be desirable to expand the discussion to a broader application, by connecting findings with global-scale biogeochemical cycles and potential impacts on fisheries or carbon sequestration.\nRE: Thank you very much for your valuable feedback. We fully concur that the discussion should extend beyond the regional scale to highlight the broader implications of our findings. The ENSO-driven shifts in phytoplankton communities we observed in the equatorial Pacific are not isolated phenomena but are intricately linked to global-scale biogeochemical cycles. Shifts in dominant phytoplankton groups may affect large-scale ecosystem productivity because they can alter elemental stoichiometry and the efficiency of nutrient recycling. Moreover, these taxonomic shifts may contribute to the variability of oceanic carbon sequestration efficiency across climate regimes through their influence on the vertical export of organic matter and the long-term storage of carbon in the deep ocean. Changes in phytoplankton community structure can propagate through trophic pathways and in that way reshape food web dynamics and fisheries productivity. Migratory species such as tuna are particularly sensitive to fluctuations in prey availability and distribution, which are in turn governed by phytoplankton-driven primary production. Understanding how climate oscillations and eddy activity reconfigure lower trophic levels is thus essential for anticipating ecosystem responses and ensuring sustainable fishery practices in a changing ocean.\nTo address this broader perspective, we have expanded the discussion to connect our results with their potential impact on global carbon cycling and fisheries sustainability. The additional relevant sentences are as follows:\nLines 298-307\nThese community-level shifts in phytoplankton composition, particularly among functional groups such as diatoms and haptophytes, can cascade through the marine food web and thereby reshape trophic energy transfer and ecosystem stability. For example, an increase of diatom dominance may enhance the export of fast-sinking, nutrient-rich particulate matter that supports zooplankton and higher trophic levels. Such changes can directly affect the spatial distribution, foraging efficiency, and recruitment success of pelagic fish species, including tuna and other migratory predators that are highly sensitive to fluctuations in plankton-based productivity. These findings highlight the ecological significance of phytoplankton functional diversity in shaping fisheries dynamics under climate-driven ocean variability.\n5. Other minor comments are as follows.\n1) Line 562: Are the SST and sea level anomalies shown in Fig. 1d and 1f averaged indices for the northwestern Pacific region? Which one is the MEI? These need to be clarified in the figure caption.\nRE: Thank you for pointing this out. We have clarified the relevant details in the revised figure caption. Specifically, the SST and SLA anomalies shown in Figs. 1d and 1f are averaged over the observational transect (130°E, 2–21°N). In Fig. 1d, the MEI is represented by red and blue bars, with positive values indicating MEI > 0 and negative values indicating MEI < 0. In Fig. 1f, the MEI is the x-axis and is plotted against the corresponding SLA.\nFig. 1. ENSO-induced antiphase patterns in biophysical dynamics of the equatorial Pacific.\nDistribution of chlorophyll a water column inventory anomaly (Chl a A, mg m-2) above 50 m during El Niño (a) and La Niña (b). The boxes represent different areas: the Equatorial Upwelling region (120°W–90°W, 5°S–5°N) and the northwestern Pacific region (125°E–150°E, 2–10°N). (c) Schematic of major currents and the field observation transect (indicated by the black line; 2–21°N, 130°E). The background is the average satellite observations of surface chlorophyll a (Chl a_sat, mg m−3). (d) Time series of sea surface temperature anomaly (SSTA, °C) and monthly MEI.v2 index averaged over the field observation transect (2–21°N, 130°E) during 2003–2020. The MEI is represented by red (positive) and blue (negative) bars, corresponding to MEI > 0 and MEI < 0, respectively. The gray lines in Fig. 1d. denote four field observation cruises. (e) The variabilities of sea level anomaly (SLA, m) along the meridional 130°E transect. (f) The relationship between sea level anomaly (SLA, m) and the MEI.v2 index. The MEI.v2 values are shown on the x-axis and correspond to the SLA anomalies on the y-axis. The straight line is an ordinary least squares regression. Both SSTA and SLA are averaged over the field observation transect (130°E, 2–21°N). STCC, Subtropical Countercurrent; NEC, North Equatorial Current; NECC, North Equatorial Counter Current; HE, the Halmahera Eddy; ME, the Mindanao Eddy.\n2) Line 190: it should be “observations”\nRE: We have corrected this spelling error in the revised manuscript.\nLine 202\nThese observations were in agreement with previous studies.\n3) Figure 3 caption: More detailed info is necessary to understand the figure.\nRE: Thank you for your suggestion. We have revised the caption for Figure 3 to provide more detailed information and thereby ensure better clarity and understanding of the figure. In addition, following the suggestion of Reviewer 3, we have modified Figure 3 by integrating it with the in-situ data from the appendix. The revised figure and its updated caption are as follows:\nFig. 3. Schematic of currents and chlorophyll a with phytoplankton composition.\nMajor currents and observation stations during neutral years (a) and El Niño events (b). The points with different shapes represent four cruises of observation stations. The background is the sea surface height (SSH, m, colored), and the surface geostrophic currents (vectors). (c–f) Spatiotemporal distributions of chlorophyll a concentration (mg m−3) and phytoplankton community composition at a depth of 50 m based on the HPLC-CHEMTAX analysis during four cruises. Dino, dinoflagellates; Diat, diatoms; Hapt (T8), haptophytes (Type 8); Hapt (T6), haptophytes (Type 6); Chlo, chlorophytes; Cryp, cryptophytes; Proc, Prochlorococcus; Syne, Synechococcus; Pras, prasinophytes. STCC, Subtropical Countercurrent; NEC, North Equatorial Current; NECC, North Equatorial Counter Current; HE, the Halmahera Eddy; ME, the Mindanao Eddy. (g) and (h) Schematic diagram of spatiotemporal distributions of chlorophyll a concentration and phytoplankton community composition in different climatic states.\nReviewer #3 (Remarks to the Author):\nThe study underscores the differentiate regional impact of the large-scale climate oscillations ENSO and PDO in the tropical Pacific on biogeochemical and phytoplankton composition. Results are based on an extensive dataset including decadal satellite observations of chlorophyll and phytoplankton taxonomic groups, biogeochemical models and ship-based measurements. While impacts of large-scale climate oscillations have been shown previously, the finding of this study gains particular relevance in light of observed contrasting impacts in the western tropical Pacific on phytoplankton composition and underlying mechanisms.\nRE: Thanks for your comments and suggestions. We have carefully addressed your feedback by incorporating the relevant descriptions and expanding the discussion where appropriate. In addition, we have clarified the novelty of our study to better highlight its scientific contribution, refined the methodological section, and updated the figures to enhance their interpretability. We hope these revisions adequately reflect your suggestions and improve the overall quality of the manuscript.\nGeneral comments:\nThe article is very clear in its writing, effectively conveying and discussing the results. The study is topical and interesting, but I have some concerns with the study the authors need to clarify:\n1. One major concern with the study is the novelty of the findings that ENSO impacts show unexpected responses in the western tropical Pacific. Differentiate regional impacts of ENSO and PDO in the eastern and western tropical Pacific have been shown in previous findings, see reference 2 in this article and others on phytoplankton, see ref 1. The latter study shows increased chlorophyll under El Niño in the Western Pacific, similar to their findings. I suggest that the authors acknowledge these studies and clearly communicate in which ways their findings go beyond previous studies. I also suggest that the authors clarify by what they mean with ‘more complex’, like more complex to what? I assume that this is related to the assumption of low chlorophyll in warm periods and reverse in cold. As such, I suggest to improve this in the abstract, introduction and discussion sections. Similarly, the authors state that effects of ENSO and PDO are seldom considered, however there are some studies that include both ENSO and PDO effects or regional indices derived from PDO, for example see references 2,3, and others.\nRE: Thank you very much for your constructive comments. We acknowledge the valuable contributions of previous works that have explored the regional impacts of ENSO and PDO on phytoplankton dynamics in the tropical Pacific (e.g., Chen et al., 2024; Cloern et al., 2010). We have now cited these references in the revised manuscript and explicitly discussed how our findings relate to and extend beyond these studies. We have carefully revised the manuscript to more clearly articulate how our study builds upon but extends previous work.\nFirst, unlike earlier studies that primarily focused on chlorophyll a concentrations or specific phytoplankton taxa, our study employs multi-cruise, in-situ observations conducted during the same month across different ENSO phases, combined with model outputs, to investigate the ecosystem-level responses in the northwestern tropical Pacific. Such synchronized, field-based datasets across different climate modes are rare and offer unique insight into the community-level dynamics of phytoplankton under varying climate regimes.\nSecond, previous observations of such responses have often been isolated, region-specific, or related to individual eddies, and they lacked a broader ecosystem-level perspective. Our study emphasizes that the responses of phytoplankton communities to climate modes are shaped by diverse physical drivers—including both large-scale (e.g., ENSO, PDO) and mesoscale (e.g., eddies) processes. Our analyses go beyond previous findings by exploring taxon-specific phytoplankton responses to ENSO. While our work is inspired by and consistent with prior studies, it systematically extends them by identifying differential responses of distinct phytoplankton groups under contrasting climatic conditions and thereby highlights the divergent ecological strategies employed by various taxa.\nThird, we frame our interpretation through a multi-disciplinary lens, integrating physical (e.g., SLA, SST), chemical (e.g., nutrients), and biological (e.g., community structure) parameters. This systems-level approach represents a step forward in understanding how large-scale climate oscillations orchestrate ecosystem functioning.\nFourth, in response to the reviewer’s query about the term “more complex”, we have now clarified in the manuscript that this refers to the complexity of both physical (multi-scale) and ecological (taxon-specific) mechanisms driving community responses. Intense or prolonged ENSO events may lead to structural shifts in the planktonic community that may alter trophic pathways and long-term productivity.\nLastly, while we fully acknowledge existing studies that jointly consider ENSO and PDO (e.g., Beaufort & Grelaud, 2017), our work distinguishes itself by focusing on the ecological dimension of these climate modes, particularly in terms of community-level transformations rather than bulk chlorophyll trends. We believe that this ecological framework provides new and deeper insights into the cascading impacts of coupled climate modes. These clarifications have been incorporated into the Abstract, Introduction, and Discussion sections as recommended. We hope this revised version better communicates the contribution and significance of our findings.\nLines 280-289\nOur findings reveal that phytoplankton communities in the northwestern tropical Pacific respond to climate variability in ways more complex than previously recognized. While the roles of ENSO and the PDO in shaping regional chlorophyll patterns are well established, our multi-cruise observations revealed taxon-specific responses to different phases of ENSO that reflected distinct ecological strategies and were modulated by mesoscale eddies. These results underscored the need to integrate physical, chemical, and biological processes when assessing ecosystem responses to climate forcing. In particular, strong or prolonged ENSO events may drive structural shifts of community composition that highlight the nonlinear, scale-dependent dynamics that must be considered in future climate–ecosystem projections.\n2. Related to the comment above, the authors emphasize the inclusion of comprehensive ship-based studies, however it is not clear how these measurements support the conclusions. The ‘real’ data of these field observations are illustrated in graphical drawings in Figs. 3 c and d and observed values described in the text. I would suggest to show the measured data in a figure to better comprehend the results as this is not clear to see with the intervals included in the text. Moreover, the clarity of Figs. 3c and d should be improved by included axes ticks and units.\nRE: We appreciate this valuable suggestion. We have revised the figure accordingly and included the updated version in the revised manuscript. To enhance clarity, we have revised Figure 3 by adding measured data and axis units. In the original manuscript, our measured data were presented in Figure S1 in the appendix. In the revised version, we have incorporated these data into the main text by merging the two figures for better clarity and accessibility.\nFig. 3. Schematic of currents and chlorophyll a with phytoplankton composition.\nMajor currents and observation stations during neutral years (a) and El Niño events (b). The points with different shapes represent four cruises of observation stations. The background is the sea surface height (SSH, m, colored), and the surface geostrophic currents (vectors). (c–f) Spatiotemporal distributions of chlorophyll a concentration (mg m−3) and phytoplankton community composition at a depth of 50 m based on the HPLC-CHEMTAX analysis during four cruises. Dino, dinoflagellates; Diat, diatoms; Hapt (T8), haptophytes (Type 8); Hapt (T6), haptophytes (Type 6); Chlo, chlorophytes; Cryp, cryptophytes; Proc, Prochlorococcus; Syne, Synechococcus; Pras, prasinophytes. STCC, Subtropical Countercurrent; NEC, North Equatorial Current; NECC, North Equatorial Counter Current; HE, the Halmahera Eddy; ME, the Mindanao Eddy. (g) and (h) Schematic diagram of spatiotemporal distributions of chlorophyll a concentration and phytoplankton community composition in different climatic states.\n3. The statistical analysis needs improvement and the approach clearly described what test was used to address which particular hypothesis/question. The method report ANOVA and Kruskal-Wallis tests, yet the analyses are time series and biases and pitfalls in time series and spatial analyses should be considered and described.\nRE: We agree that more rigorous statistical clarity is essential. In the revised manuscript, we have clearly stated the statistical methods used. Relevant information has been provided as follows:\nLines 426-438\nStatistical significance was assessed using independent sample t-tests and one-way ANOVA to compare phytoplankton responses during different phases of the ENSO and PDO. If the parameters did not satisfy the assumptions of normality and homoscedasticity, a nonparametric Kruskal‐Wallis (KW) test was used instead of ANOVA. Values of the type-I error rate (p) < 0.05 were considered statistically significant, and p < 0.01 and p < 0.001 were characterized as highly and very highly significant, respectively. Pearson's correlation coefficient was used to determine the correlation between two variables. Time series analysis based on remote sensing and reanalysis data was conducted for the period from January 2003 to December 2020 using zonal averages along the 130°E transect (2°–21°N). A Lowess smoothing filter was applied to remove high-frequency fluctuations. Although the cruise-based observations were temporally discontinuous, the sampling design and resolution helped minimize potential autocorrelation effects. To evaluate the influence of the PDO, we built multiple linear regression models with and without PDO as a predictor, and we used the Akaike Information Criterion (AIC) to assess model performance.\n4. The amplification of ENSO with positive PDO values is rather descriptive but this is not tested quantitatively. Could the authors use a model and test if AIC values, or similar, improve if PDO is included as a predictor variable?\nRE: We agree that the amplification of ENSO impacts during positive PDO phases warrants a more quantitative assessment. In the revised version, we have now included an additional statistical analysis by incorporating PDO as a predictor variable in multiple linear regression models. We compared models with and without PDO using the Akaike Information Criterion (AIC). The results showed that including PDO significantly improved the model performance and thereby supported the synergistic influence of ENSO and PDO on phytoplankton dynamics (Fig. S9). These additions have been incorporated into the Discussion and Methods sections accordingly.\nLines 266-272\nTo quantify the role of the PDO in modulating ENSO-driven biological responses, we conducted a model comparison with and without the PDO as a predictor variable (Fig. S9). In the region rich in mesoscale eddies (5°N–15°N, 120°E–160°E), inclusion of the PDO significantly improved the model's ability to capture anomalies of chlorophyll a from 2003 to 2020. This result indicated that the PDO acted to either amplify or dampen the biological effects of ENSO and was thus evidence of its role as a secondary, yet influential, driver of interannual variability of phytoplankton biomass.\nFig. S9. Model comparison with and without PDO as a predictor variable. Comparison of chlorophyll a anomalies in the mesoscale eddy region (5°N–15°N, 120°E–160°E) from 2003 to 2020, with and without the inclusion of PDO as a predictor.\n5. I suggest to improve the labelling of the figures by describing the results (figures) in chronological order in the text as the ordering of figures are difficult to follow.\nRE: Thank you for the helpful suggestion. We have now reorganized the order in which the figures are introduced in the main text to ensure they follow a clear chronological and logical sequence. Figure labels and references have been revised accordingly to improve clarity and readability.\nMinor comments:\nL 25. Can you make this sentence more informative ‘… we reveal unexpected responses …’, like ‘ … opposite responses …’?\nRE: We have revised the relevant expressions.\nL 59. Should this be picocyanobacterial? Good if this is specified.\nRE: Thank you for your comment. The term 'cyanobacteria' is directly cited from Rousseaux and Gregg (2012) (Reference 14 in our manuscript), where it refers to a broader category than 'picocyanobacteria.' To ensure consistency with the original literature, we retained 'cyanobacteria' to accurately reflect the full range of cyanobacterial groups analyzed.\nL 81. I suggest to change ‘We believe’ to ‘We hypothesise …’ or similar\nRE: We have revised the corresponding terms based on your suggestion.\nLine 84\nWe hypothesized that the alterations of large-scale circulation and mesoscale eddies attributed to ENSO in the northwestern tropical Pacific would give rise to biogeochemical responses different from those commonly witnessed in the eastern tropical Pacific.\nL 84. Can you motivate your assumption of a shift in phytoplankton community composition? What is the rationale behind this hypothesis? I guess this is a consequence of physical and chemical changes, so can you speculate what functional groups should change?\nRE: The assumption of a shift in phytoplankton community composition is motivated by the observed and well-documented variability of physical (e.g., SST, stratification) and chemical (e.g., nutrient availability) conditions under different ENSO phases. These environmental shifts are known to favor different phytoplankton functional groups based on their ecological strategies. We have clarified this point in the revised manuscript.\nLines 86-91\nSpecifically, we hypothesized that during El Niño events, there would be an increase of chlorophyll a concentrations and a shift of phytoplankton community composition driven by changes in physical and chemical conditions in the northwestern tropical Pacific. We further hypothesized that the positive phase of the PDO would amplify these responses by promoting more favorable conditions for phytoplankton growth, particularly for groups such as diatoms.\nL 95. Please clarify to which region these results relate to, similar in following paragraphs like L 113.\nRE: We have clarified the corresponding region.\nLines 101-102\nWe initially examined ENSO events spanning 216 months from January 2003 to December 2020. We focused on the 130°E meridian from 2–21°N.\nL 111. Should ‘normal years’ be replaced with ‘ENSO neutral years’ to make clear what this is related to?\nRE: We agree that “ENSO neutral years” is more accurate, and we have revised the terminology accordingly throughout the manuscript.\nL 128-130. Is this a result sentence? Since no reference is given to previous studies, the sentence feels out of context.\nRE: We have removed the sentence because it was not directly related to the results.\nL 100 and 117ff. Please include the test that is used for the analysis and report R2 and related statistical out as reporting only a p-value in isolation is not very informative. Is there a need to account for temporal or spatial autocorrelation?\nRE: We thank the reviewer for this valuable comment. We agree that reporting the p-value alone is insufficient to fully describe the strength and nature of the relationship. In the revised manuscript, we have clarified the statistical methods used and included additional metrics such as the R². This information has been added to the Results section\nRegarding temporal or spatial autocorrelation, we acknowledge the potential influence of these factors in climate datasets. We initially performed an Ordinary Least Squares (OLS) regression to examine the relationship between the Multivariate El Niño Index (MEI) and sea level anomaly (SLA). The OLS model yielded an R² of 0.52, with a statistically significant negative slope for MEI (slope = −0.067, p < 0.001). However, the Durbin-Watson test revealed a strong, positive temporal autocorrelation in the residuals (DW = 0.35, p < 0.001). Time series data (monthly resolution from January 2003 to December 2020) are prone to serial autocorrelation due to climatic persistence. To address this, we applied a Generalized Least Squares (GLS) model with AR(1) correction for temporal autocorrelation (Fig. RR1). The GLS model substantially improved the model fit (R² = 0.85), with an estimated AR(1) coefficient of 0.86, indicating strong serial correlation. After adjustment, the MEI slope remained negative (slope = −0.043, p = 0.587). While the AR(1)-corrected relationship loses traditional statistical significance, this attenuation primarily reflects the substantial temporal autocorrelation inherent to climate time series. The conserved negative slope directionality remains physically consistent with SLA responses during ENSO events, and the marked improvement in model explanatory power (ΔR² = +0.33) underscores the importance of autocorrelation control. We think that the identified coupling maintains physical plausibility despite statistical marginality, motivating future verification through state-space modeling or high-resolution dynamical to resolve underlying ocean processes.\nIn the case of spatial structure, the variables were averaged across 2–21°N at 130°E. This averaging reduced the spatial dependence and minimized the spatial autocorrelation concerns. For intergroup comparisons (e.g., among ENSO–PDO phase combinations), we ensured statistical validity by using one-way ANOVA with Tukey’s HSD test, which assumes independent samples.\nFig. RR1. Comparison of the effect of fitting with OLS and GLS (AR1 correction) in regression analysis of MEI and SLA.\nSea level anomaly (SLA) plotted against the MEI.v2 index, with model fits from ordinary least squares (OLS; red line) and generalized least squares with AR(1) correction (GLS; blue dashed line).\nL 145 – 148. Can these results be shown in a figure instead? It is difficult to comprehend, especially given the relative sizes of the intervals. Also, what are the intervals representing? SD, SE or CI?\nRE: Thank you for your valuable suggestion. We have revised Figure 3 to present the data more clearly. The intervals represent Standard Deviations (SDs), and the updated figure now more effectively conveys the results.\nL 157. ‘As expected’. This is out of context without further discussion. Better to remove.\nRE: The phrase \"As expected\" has been removed from the manuscript as suggested.\nLine 170\nDuring the prolonged El Niño from 2014 to 2016, there was a significant increase of the concentration of haptophytes.\nL 174. Please include a reference to this statement.\nRE: Thanks for your suggestion. We have added the reference in the revised manuscript.\nLines 185-186\nTraditional understanding of ENSO's impact on marine ecosystems is often a simplistic portrayal of the relationship between climate oscillations and biological responses 9,17.\nL 276. Please clarify how nutrient samples were treated and measured, similar to phytoplankton samples.\nRE: Thank you for your comment. We have clarified the treatment and measurement of nutrient samples in the revised manuscript.\nLine 324-328\nNitrate (NO ⁻-N) concentrations were measured using the cadmium reduction method; 3\nthe detection limit was 0.01 µmol L⁻¹ 37. The analysis was performed with an automated analyzer (Technicon Auto Analyzer AA3) manufactured by Bran+Luebbe (Germany). The system uses a gas-segmented continuous flow analyzer (SCFA) that enables automated analysis of samples.\nL 280. Remove “subsequently”. It leads the thought towards a size-fractionated filtering procedure, which is not the case here. Or was the water from different depth strata combined?\nRE: Thank you for your suggestion. We have removed the term \"subsequently\" to avoid ambiguity. Our procedure did not involve combining water from different depth strata; samples from each depth were processed separately.\nLines 331-332\nThe water was filtered through GF/F membranes with a 25-mm diameter, wrapped in aluminum foil, and kept in liquid nitrogen tanks.\nL 282. Spell out HPLC? Or refer to a previously published protocol. Also, mention how pigments were extracted.\nRE: Thanks for your suggestion. We have clarified the meaning of HPLC as high-performance liquid chromatography (HPLC) in line 155 of the Results section. In addition, we have added the pigment extraction method in the Methods section.\nLines 332-337\nThe photosynthetic pigments on the filter membrane were extracted by first removing surface moisture with filter paper. The membrane was then carefully unfolded and placed into a 1.5 mL amber test tube. N,N-Dimethylformamide (DMF) was added as the extraction solvent, and the mixture was kept in the dark at –20°C for 1–2 hours. After extraction, the extract was mixed with a 1 mol L⁻¹ ammonium acetate solution in a 1:1 ratio and stored at –20°C.\nL 351. Please clarify what is meant by ‘small phytoplankton’\nRE: We have clarified the definition of \"small phytoplankton\" in the revised manuscript.\nLine 412-415\nIn reaching a quasi-steady state, we used the simulation results from the fifth cycle, and we focused on the period 2003–2018, which includes monthly SST, SSH, and two phytoplankton functional groups: diatoms and small phytoplankton (typically within the pico- to nano-size range).\nL 362. Statistical analysis: this needs better description. Clarify what you use the statistical tests for.\nRE: We have made the necessary revisions to the section on statistical analysis for better clarity.\nL 560. Can you clarify what is meant by ‘study area’ particularly as the previous figure shows a larger region? I guess this the regional area this study focuses on, this should be clearly communicated in the results. Is this the red box in Fig 1a?\nRE: We have made the necessary revisions to the figure legend of Fig. 1.\nL 561. Please specify which area the SSTA relates to?\nRE: We have revised the relevant expression in the figure legend of Fig. 1.\nL563. Why is the x-axis, latitude, shown in reverse order as to c? Please include x-axis labelling.\nRE: Thank you for your suggestion. Fig. 1e presents the temporal evolution of sea level anomaly (SLA) along the 130°E transect, spanning latitudes 2°N–21°N. Consistent with panel d, the x-axis represents chronological years. For enhanced clarity, we inverted the y-axis orientation (with 5°N positioned at the top) and explicitly labeled the corresponding years beneath the x-axis.\nFig. 1. ENSO-induced antiphase patterns in biophysical dynamics of the equatorial Pacific.\nDistribution of chlorophyll a water column inventory anomaly (Chl a A, mg m-2) above 50 m during El Niño (a) and La Niña (b). The boxes represent different areas: the Equatorial Upwelling region (120°W–90°W, 5°S–5°N) and the northwestern Pacific region (125°E–150°E, 2–10°N). (c) Schematic of major currents and the field observation transect (indicated by the black line; 2–21°N, 130°E). The background is the average satellite observations of surface chlorophyll a (Chl a_sat, mg m−3). (d) Time series of sea surface temperature anomaly (SSTA, °C) and monthly MEI.v2 index averaged over the field observation transect (2–21°N, 130°E) during 2003–2020. The MEI is represented by red (positive) and blue (negative) bars, corresponding to MEI > 0 and MEI < 0, respectively. The gray lines in Fig. 1d. denote four field observation cruises. (e) The variabilities of sea level anomaly (SLA, m) along the meridional 130°E transect. (f) The relationship between sea level anomaly (SLA, m) and the MEI.v2 index. The MEI.v2 values are shown on the x-axis and correspond to the SLA anomalies on the y-axis. The straight line is an ordinary least squares regression. Both SSTA and SLA are averaged over the field observation transect (130°E, 2–21°N). STCC, Subtropical Countercurrent; NEC, North Equatorial Current; NECC, North Equatorial Counter Current; HE, the Halmahera Eddy; ME, the Mindanao Eddy.\nL578. I suggest to include a sentence such as ‘Box plots represent values within specific periods, with the line ….’, or similar\nRE: We have added the following sentence to clarify the box plots in the manuscript.\nLines 654-656\nBox plots represent values within specific periods. The thick horizontal lines indicate the median, and the boundaries of the boxes denote the 25th and 75th percentiles.\nL585. Please clarify figures Fig 3 c and d.\nRE: We have made the corresponding revisions.\nL596. SSHA – should this be SLA as in previous figures? Please check throughout.\nRE: Thank you for your suggestion. We have made the necessary revisions to ensure consistency throughout the manuscript.\nLine 680\n(b) and (f) sea level anomaly (SLA, m)\nReferences：\nAn, L., et al. Different responses of plankton community to mesoscale eddies in the western equatorial Pacific Ocean. Deep-Sea Res. Part I Oceanogr. Res. Pap. 203, 104219, doi: https://doi.org/10.1016/j.dsr.2023.104219 (2024).\nBeaufort, L. & Grelaud, M. A 2700-year record of ENSO and PDO variability from the Californian margin based on coccolithophore assemblages and calcification. Prog. in Earth and Planet. Sci. 4, 5, doi: https://doi.org/10.1186/s40645-017-0123-z (2017).\nChen, R., Wu, B., Li, Z. & Wang, S. Impacts of ENSO on tropical Pacific chlorophyll biomass under historical and RCP8.5 scenarios. J. Geophys. Res.: Oceans 129, doi: https://doi.org/10.1029/2023JC020720 (2024).\nCloern, J. E. et al. Biological communities in San Francisco Bay track large-scale climate forcing over the North Pacific. Geophys. Res. Lett. 37, doi: https://doi.org/10.1029/2010GL044774 (2010).\nLiu S., et al. Spatial-temporal variations of short-lived mesoscale eddies and their environmental effects. Front. Mar. Sci. 10, 1069897, doi: https://doi.org/10.3389/fmars.2023.1069897 (2023).\nPauthenet, E., et al. Contrasted trends in chlorophyll‐a satellite products. Geophysical Research Letters 51, e2024GL108916, doi: https://doi.org/10.1029/ 2024GL108916 (2024)."}, {"round": 2, "reviewer_comments": {"reviewer_2": "I appreciate the authors’ efforts in revising the manuscript and addressing the initial concerns. The authors have effectively addressed my previous comments, and the revised version now has improved in structure and clarity. I also reviewed the comments from other reviewers and agreed that the study presents novel insights of scientific value. I would recommend that the manuscript be accepted for publication.", "reviewer_3": "The authors have addressed by comments and I do not have further comments.", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": ""}]

Decision letter