Zooplankton occupy a pivotal position in marine ecosystems. As the principal consumers of phytoplankton, they convert microscopic plant production into animal biomass that can be passed to higher trophic levels, including commercially important fish stocks. They also play an outsized role in biogeochemical cycling, influencing the exchange of carbon dioxide between the atmosphere and the surface ocean and packaging organic carbon into fecal pellets that sink toward the deep sea. Any sustained change in their abundance therefore ripples outward, affecting nutrient cycling, water quality, fisheries yields, and the ocean’s capacity to sequester carbon. Yet despite their importance, zooplankton dynamics in the Indian Ocean have received far less attention than in other ocean basins, partly because quality-controlled, gridded biogeochemical data for the region have long been scarce.

To overcome this data gap, the team drew on the Coastal and Oceanic Plankton Ecology, Production, and Observation Database, known as COPEPOD, a global archive containing more than 400,000 records of copepods and other plankton taxa, with observations stretching back to around 1913. The biomass fields from the upper epipelagic layer, typically between the surface and 200 meters, were converted into carbon mass and merged into a single gridded product at one-degree horizontal resolution. The researchers then evaluated how well seven Earth system models participating in the sixth phase of the Coupled Model Intercomparison Project, or CMIP6, could reproduce the observed patterns, integrating model zooplankton values down to 200 meters for the historical period 1975 to 2014 and for future scenarios running from 2061 to 2100.

The observed picture is strikingly asymmetric. Zooplankton concentration in the Arabian Sea averages about 15.6 milligrams of carbon per cubic meter, roughly 20 percent higher than in the Bay of Bengal, where the mean is about 13.0 milligrams per cubic meter. The difference stems from the fundamentally different hydrography of the two basins. The Arabian Sea experiences monsoon-driven upwelling, winter convective mixing, and high evaporation that produces dense, salty surface water which sinks and stirs the water column, all of which replenish nutrients in the sunlit layer. The Bay of Bengal, by contrast, is drenched by freshwater runoff from major rivers, which suppresses salinity, strengthens stratification, and blocks the upward transport of nutrient-rich subsurface water. Only near river mouths, where terrigenous nutrients locally offset the stratification, does the Bay of Bengal show elevated zooplankton concentrations.

The seasonal rhythm of zooplankton in the Arabian Sea is equally distinctive. Biomass peaks twice each year. The dominant peak arrives during the summer monsoon from July to September, when the strong southwesterly winds drive coastal and open-ocean upwelling, particularly along the western Arabian Sea, where the northward-flowing Somali Current lifts nutrient-laden deep water to the surface. A secondary peak occurs in winter from December to February, when the dry northeast monsoon cools the surface waters of the northern Arabian Sea, weakens thermal stratification, and allows convective mixing to fertilize the euphotic zone. Concentrations bottom out in April and May, when intense solar heating strengthens stratification and cuts off the vertical nutrient supply. The Bay of Bengal, in contrast, shows remarkably little seasonal variability, with a modest maximum in August and September.

Before projecting the future, the authors rigorously tested the models against observations. Statistical measures including correlation coefficients, root mean square errors, and skewness revealed that GFDL-ESM4, MPI-ESM1-2-HR, and IPSL-CM6A-LR performed best at capturing both the spatial pattern and the temporal variability of zooplankton over the Indian Ocean, with correlations between roughly 0.58 and 0.68, significant at the 99.9 percent level. Other models fared poorly: CanESM5 showed the worst performance, while CESM2 produced an abruptly high error of 9.06 milligrams of carbon per cubic meter. The team constructed a multi-model mean from the three best performers, a strategy that prioritizes spatial pattern fidelity over ensemble size. The authors also caution that converting modeled zooplankton biomass from nitrogen to carbon units introduces uncertainty, since plausible copepod carbon-to-nitrogen ratios alone can shift estimated biomass by 10 to 40 percent, though model bias generally explains the larger discrepancies.

The future projections are sobering. Under the moderate SSP2-4.5 scenario and the very high SSP5-8.5 scenario, zooplankton concentration declines across the entire basin, with regional reductions ranging from 5 to 40 percent. The steepest losses, exceeding 5 milligrams of carbon per cubic meter or roughly 40 percent, are projected for the western and central Arabian Sea under the high-warming pathway, while the southern Bay of Bengal is more affected than the north. When the researchers linearly detrended the datasets to remove long-term warming signals, the projected differences became statistically insignificant, confirming that greenhouse-gas-driven climate change, rather than natural variability, is the dominant cause of the decline. Notably, the projected zooplankton losses exceed the 5 to 20 percent declines in chlorophyll and net primary productivity reported in earlier CMIP5 and CMIP6 studies, hinting at a trophic amplification of climate impacts as warming effects cascade from primary producers to secondary consumers.

The mechanism behind the decline is a familiar one in ocean-climate science but is here documented with unusual regional detail. As the ocean warms, sea surface temperatures rise and sea surface salinity falls, and the upper layers of the Arabian Sea heat faster than the deeper waters. This sharpens the density contrast between surface and subsurface layers, strengthening vertical stratification and shoaling the mixed layer. A thinner, more isolated surface layer receives less nutrient-rich deep water through upwelling and entrainment, so phytoplankton growth slows and zooplankton, which depend on that grazing resource, decline in turn. Because zooplankton also mediate the biological carbon pump, reduced biomass could weaken the export of organic carbon to the deep ocean and increase remineralization in surface waters, with consequences for the ocean’s role in the global carbon budget.

Perhaps the most intriguing finding concerns the changing relationship between zooplankton and the great modes of natural climate variability, the El Niño-Southern Oscillation and the Indian Ocean Dipole. In the historical period, the El Niño-Southern Oscillation is significantly negatively correlated with zooplankton concentration over most of the Arabian Sea and the southern and central Bay of Bengal. Under future warming, however, that negative correlation over the Arabian Sea weakens almost to vanishing, suggesting that long-term stratification and warming trends will override interannual climate signals there. Process-based analysis supports this: ENSO-driven thermocline deepening and weakened wind stress curl anomalies suppress Ekman pumping and upwelling, cutting off the nutrient supply. In the Bay of Bengal and the equatorial Indian Ocean, the opposite occurs, with ENSO and the Indian Ocean Dipole projected to enhance zooplankton concentrations through thermocline shoaling and increased upwelling, potentially making those ecosystems more volatile from year to year.

The regional divergence carries real-world consequences. A more stable but steadily declining zooplankton base in the Arabian Sea, and more erratic swings in the Bay of Bengal, could translate into greater uncertainty in fish catches for the densely populated coastlines that border both basins, threatening food security across Indian Ocean rim countries. The authors acknowledge important limitations: CMIP6 models represent zooplankton as a single aggregated functional group, so shifts in community composition, body size, and trophic efficiency remain invisible to the analysis, even though warming is known to favor smaller, warm-adapted taxa that produce more slowly sinking fecal pellets and export less carbon. Coarse model resolution may also miss vertical redistribution of biomass through diel migration. Even so, the simulated decline in biomass is robust across models, and the study underscores an urgent need for sustained ocean monitoring, taxonomically resolved ecosystem models, and adaptation strategies to manage the changing marine ecosystems of the Indian Ocean.

Subject of Research: Upper-ocean zooplankton variability and projected climate-driven decline in the Indian Ocean using COPEPOD observations and CMIP6 model simulations

Article Title: Understanding upper ocean zooplankton variability in the Indian Ocean using observations and CMIP6 models

Article References: Understanding upper ocean zooplankton variability in the Indian Ocean using observations and CMIP6 models. (n.d.). https://doi.org/10.1007/s44289-026-00177-7

Image Credits: AI Generated

DOI: 10.1007/s44289-026-00177-7

Keywords: zooplankton, Indian Ocean, Arabian Sea, Bay of Bengal, CMIP6, climate change, ocean stratification, upwelling, ENSO, Indian Ocean Dipole, marine food web, monsoon