Response Of Marine Ecosystems Research Articles

Rhodobacteraceae are key players in microbiome assembly of the diatom Asterionellopsis glacialis.

Most, if not all, microeukaryotic organisms harbor an associated microbial community, termed the microbiome. The microscale interactions that occur between these partners have global-scale consequences, influencing marine primary productivity, carbon cycling, and harmful algal blooms to name but a few. Over the last decade, there has been a growing interest in the study of phytoplankton microbiomes, particularly within the context of bloom dynamics. However, long-standing questions remain regarding the process of phytoplankton microbiome assembly. The significance of our research is to tease apart the mechanism of microbiome assembly with a particular focus on identifying bacterial taxa, which may not merely be symbionts but architects of the phytoplankton microbiome. Our results strengthen the understanding of the ecological mechanisms that underpin phytoplankton-bacteria interactions in order to accurately predict marine ecosystem responses to environmental perturbations.

Combining mesocosms with models reveals effects of global warming and ocean acidification on a temperate marine ecosystem.

Ocean warming and species exploitation have already caused large-scale reorganization of biological communities across the world. Accurate projections of future biodiversity change require a comprehensive understanding of how entire communities respond to global change. We combined a time-dynamic integrated food web modeling approach (Ecosim) with previous data from community-level mesocosm experiments to determine the independent and combined effects of ocean warming, ocean acidification and fisheries exploitation on a well-managed temperate coastal ecosystem. The mesocosm parameters enabled important physiological and behavioral responses to climate stressors to be projected for trophic levels ranging from primary producers to top predators, including sharks. Through model simulations, we show that under sustainable rates of fisheries exploitation, near-future warming or ocean acidification in isolation could benefit species biomass at higher trophic levels (e.g., mammals, birds, and demersal finfish) in their current climate ranges, with the exception of small pelagic fishes. However, under warming and acidification combined, biomass increases at higher trophic levels will be lower or absent, while in the longer term reduced productivity of prey species is unlikely to support the increased biomass at the top of the food web. We also show that increases in exploitation will suppress any positive effects of human-driven climate change, causing individual species biomass to decrease at higher trophic levels. Nevertheless, total future potential biomass of some fisheries species in temperate areas might remain high, particularly under acidification, because unharvested opportunistic species will likely benefit from decreased competition and show an increase in biomass. Ecological indicators of species composition such as the Shannon diversity index decline under all climate change scenarios, suggesting a trade-off between biomass gain and functional diversity. By coupling parameters from multilevel mesocosm food web experiments with dynamic food web models, we were able to simulate the generative mechanisms that drive complex responses of temperate marine ecosystems to global change. This approach, which blends theory with experimental data, provides new prospects for forecasting climate-driven biodiversity change and its effects on ecosystem processes.

Intraseasonal response of marine planktonic ecosystem to summertime Madden-Julian Oscillation in the South China Sea: A model study

In summer, the Madden-Julian Oscillation (MJO) greatly influences the intraseasonal variability of the South China Sea (SCS). Previous studies have revealed MJO effects on surface chlorophyll (Chl) concentration, but the impact of the MJO on the ecosystem's structure and functionality remains unexplored. Here, we investigated the marine ecosystem response to the MJO by analyzing phytoplankton pigment data collected in cruises from 2010 to 2014. The results indicated the strong influence of the MJO on the structure of phytoplankton size classes (PSCs) in the upper 50 m of the SCS basin. To further explore the ecosystem's response to MJO, we utilized a well-calibrated physical-biogeochemical model (ROMS-CoSiNE) of the SCS to conduct numerical experiments with and without MJO forcings. Our model demonstrated that MJO-induced deep mixing and upwelling increased nutrients in the upper layer, increasing the Chl concentration with a higher proportion of nanophytoplankton (15 %) and a lower proportion of picophytoplankton (−20 %). Moreover, The MJO-forced model experiment exhibited a substantial enhancement in primary production (56 %) and export production (23 %), resulting in a notable decrease in the e-ratio. This reduction in the e-ratio cannot be attributed to changes in PSCs but can be explained by the time lag between primary and export production. This lag was prolonged by the physical processes of upwelling and mixing, which slows down the particle sinking. Our results emphasize the important role of MJO in regulating the ecosystem at intraseasonal scale, thus improving our comprehension of the nonsteady dynamics of ecosystems in the SCS.

Assessing transient changes in the ocean carbon cycle during the last deglaciation through carbon isotope modeling

Abstract. Atmospheric carbon dioxide concentration (pCO2) has increased by approximately 80 ppm from the Last Glacial Maximum (LGM) to the early Holocene. The change in this atmospheric greenhouse gas is recognized as a climate system response to gradual change in insolation. Previous modeling studies suggested that the deglacial increase in atmospheric pCO2 is primarily attributed to the release of CO2 from the ocean. Additionally, it has been suggested that abrupt change in the Atlantic meridional overturning circulation (AMOC) and associated interhemispheric climate changes are involved in the release of CO2. However, understanding remains limited regarding oceanic circulation changes and the factors responsible for changes in chemical tracers in the ocean during the last deglaciation and their impact on atmospheric pCO2. In this study, we investigate the evolution of the ocean carbon cycle during the last deglaciation (21 to 11 ka BP) using three-dimensional ocean fields from the transient simulation of the MIROC 4m climate model, which exhibits abrupt AMOC changes similar to those observed in reconstructions. We investigate the reliability of simulated changes in the ocean carbon cycle by comparing the simulated carbon isotope ratios with sediment core data, and we examine potential biases and overlooked or underestimated processes in the model. Qualitatively, the modeled changes in atmospheric pCO2 are consistent with ice core records. For example, during Heinrich Stadial 1 (HS1), atmospheric pCO2 increases by 10.2 ppm, followed by a reduction of 7.0 ppm during the Bølling–Allerød (BA) period and then by an increase of 6.8 ppm during the Younger Dryas (YD) period. However, the model underestimates the changes in atmospheric pCO2 during these events compared to values derived from ice core data. Radiocarbon and stable isotope signatures (Δ14C and δ13C) indicate that the model underestimates both the activated deep-ocean ventilation and reduced efficiency of biological carbon export in the Southern Ocean and the active ventilation in the North Pacific Intermediate Water (NPIW) during HS1. The relatively small changes in simulated atmospheric pCO2 during HS1 might be attributable to these underestimations of ocean circulation variation. The changes in Δ14C associated with strengthening and weakening of the AMOC during the BA and YD periods are generally consistent with values derived from sediment core records. However, although the data indicate continuous increase in δ13C in the deep ocean throughout the YD period, the model shows the opposite trend. It suggests that the model either simulates excessive weakening of the AMOC during the YD period or has limited representation of geochemical processes, including marine ecosystem response and terrestrial carbon storage. Decomposing the factors behind the changes in ocean pCO2 reveals that variations in temperature and alkalinity have the greatest impact on change in atmospheric pCO2. Compensation for the effects of temperature and alkalinity suggests that the AMOC changes and the associated bipolar climate changes contribute to the decrease in atmospheric pCO2 during the BA and the increase in atmospheric pCO2 during the YD period.

Two-decade satellite observations reveal variability in size-fractionated phytoplankton primary production in the South China Sea

Understanding variations in marine phytoplankton primary production (PP) is crucial for assessing the response of the marine environment to climate change and for quantifying the ocean carbon cycle. However, the spatiotemporal variability of size-fractionated PP in the South China Sea (SCS) remains ambiguous. Our study investigated the monthly, seasonal, and inter-annual variability of size-fractionated PP in the SCS using satellite observations from 2002 to 2022. There were noticeable seasonal and monthly variations in size-fractionated PP, with notably high PP values appearing during the cold season. The disparities in distribution and the distinct fluctuation patterns between size-fractionated PP suggest that total PP alone is not a comprehensive indicator of marine ecosystem health. Over the past two decades in the SCS, there were more pronounced decreases in total, pico-, and nano-PP, whereas micro-PP displayed no significant trend. The most pronounced decline occurred in the northern SCS, contrasted by increases in coastal areas. These size-fractionated PP anomalies showed strong correlations with climate change indices, highlighting the impact of environmental factors on these anomalies, such as sea surface temperature, mixed layer depth, and wind speed. Our findings emphasize the importance considering size-fractionated PP to gain a more nuanced understanding of the ocean carbon cycle and the marine ecosystem's response to climate changes.

Observing change in pelagic animals as sampling methods shift: the case of Antarctic krill

Understanding and managing the response of marine ecosystems to human pressures including climate change requires reliable large-scale and multi-decadal information on the state of key populations. These populations include the pelagic animals that support ecosystem services including carbon export and fisheries. The use of research vessels to collect information using scientific nets and acoustics is being replaced with technologies such as autonomous moorings, gliders, and meta-genetics. Paradoxically, these newer methods sample pelagic populations at ever-smaller spatial scales, and ecological change might go undetected in the time needed to build up large-scale, long time series. These global-scale issues are epitomised by Antarctic krill (Euphausia superba), which is concentrated in rapidly warming areas, exports substantial quantities of carbon and supports an expanding fishery, but opinion is divided on how resilient their stocks are to climatic change. Based on a workshop of 137 krill experts we identify the challenges of observing climate change impacts with shifting sampling methods and suggest three tractable solutions. These are to: improve overlap and calibration of new with traditional methods; improve communication to harmonise, link and scale up the capacity of new but localised sampling programs; and expand opportunities from other research platforms and data sources, including the fishing industry. Contrasting evidence for both change and stability in krill stocks illustrates how the risks of false negative and false positive diagnoses of change are related to the temporal and spatial scale of sampling. Given the uncertainty about how krill are responding to rapid warming we recommend a shift towards a fishery management approach that prioritises monitoring of stock status and can adapt to variability and change.

The role of subsurface instabilities for increasing chlorophyll concentrations in a warming southern Indian ocean

A warming climate is expected to intensify the stratification of the upper ocean in tropical and subtropical regions, which in turn results in decreases in the primary productivity for these oligotrophic areas. To assess if there is trended change in primary productivity in the southern Indian Ocean (IO) with known striking temperature increase, we use 17-years of satellite chlorophyll (Chl) data and model output to examine the trended changes in Chl. The results exhibited a surprisingly increase in Chl concentrations in part of the southern IO over the gyre area. To investigate the potential mechanisms underlying this Chl increase, we used temperature/salinity observations to re-evaluate stratification in the southern IO. The southern IO experienced basin-wide surface warming over the time series however there was a region of subsurface cooling at 50–100 m around 10°S. In the subtropical IO gyre, subsurface warming occurs at faster rates compare to the surface. Through the calculation of buoyancy frequency (N2), we have confirmed the presence of subsurface instabilities caused by these inhomogeneous trends in the vertical thermohaline structure. This was particularly true over the southern IO gyre, which experienced sustained increase of surface mixing disturbances over the last decade—resulting in a more favorable environment for vertical transport of nutrients into the euphotic zone. A mixed layer nutrient budget analysis suggested that entrainment due to mixed layer deepening is crucial in delivering nutrients into the gyre's upper mixed layer, which fueled phytoplankton activity. This emphasizes the importance of considering subsurface instabilities when interpreting the factors that influence surface Chl variabilities. This study highlights the importance of a three-dimensional framework for examining stratification to assess future marine ecosystem responses to a changing climate.

Response of Arctic benthic foraminiferal traits to past environmental changes

The Arctic is subjected to all-encompassing disruptions in marine ecosystems caused by anthropogenic warming. To provide reliable estimates of how future changes will affect the ecosystems, knowledge of Arctic marine ecosystem responses to past environmental variability beyond the instrumental era is essential. Here, we present a novel approach on how to evaluate the state of benthic marine biotic conditions during the deglacial and Holocene period on the Northeast Greenland shelf. Benthic foraminiferal species were assigned traits (e.g., oxygen tolerance, food preferences) aiming to identify past faunal changes as a response to external forcing mechanisms. This approach was applied on sediment cores from offshore Northeast Greenland. We performed numerical rate-of-change detection to determine significant changes in the benthic foraminiferal traits. That way, the significant abrupt trait changes can be assessed across sites, providing a better understanding of the impact of climate drivers on the traits. Our results demonstrate that during the last ~ 14,000 years, bottom water oxygen is the main factor affecting the variability in the benthic foraminiferal faunas in this area. Our results show that significant changes in the traits correspond to drastic climate perturbations. Specifically, the deglacial-Holocene transition and mid-Holocene warm period exhibited significant change, with several trait turnovers.

Forty years of ocean acidification observations (1983–2023) in the Sargasso Sea at the Bermuda Atlantic Time-series Study site

Ocean physical and biogeochemical conditions are rapidly changing over time. Forty years of observations from 1983 to 2023 collected at the Bermuda Atlantic Time-series Study (BATS) site near Bermuda in the North Atlantic Ocean shows continuing trends of surface warming, increase in salinity, loss of dissolved oxygen (DO), increase in carbon dioxide (CO2), and ocean acidification (OA) effects. Over this period, the ocean has warmed by about +1°C, increased in salinity by +0.136, and lost DO by 12.5 µmol kg−1 or ~6%. Since the 1980s, ocean dissolved inorganic carbon (DIC), total alkalinity (TA), a tracer of anthropogenic CO2 (CTrOCA), and fugacities/partial pressures of CO2 (i.e., fCO2 and pCO2) have continued to increase substantially, with no evidence of a reduction in the rates of change over time. Contemporaneously, ocean pH has decreased by ~0.1 pH units [with ocean acidity (i.e., H+) increasing by >30%], and the saturation states of calcium carbonate minerals (Ωcalcite and Ωaragonite) have decreased. These OA indicators show that the chemical conditions for calcification have become less favorable over the past 40 years. Updating of data and trends at the BATS site show how ocean chemistry of the 2020s is now outside the range observed in the 1980s, and how essential these data are for predicting the response of ocean chemistry and marine ecosystems to future shifting earth and ocean conditions.

Nearshore subtidal community response during and after sediment disturbance associated with dam removal

Dam removal is used increasingly to restore aquatic ecosystems and remove unnecessary or high-risk infrastructure. As the number of removals increases, there is a growing understanding about the hydrologic, geomorphic, and ecological responses to these removals. Most dam removal studies, however, focus on river and watershed responses to dam removal. The removal of two dams on the Elwha River provided a unique opportunity to characterize the response of nearshore (coastal) ecosystems. We conducted SCUBA surveys between 2011 and 2022 to quantify trajectories of change in a nearshore ecosystem during and after dam removal. We focused on the degree to which the abundances of kelp, benthic invertebrates, and fish changed in response to patterns of sediment fluxes during and after dam removal. Our findings point to two pathways of response depending on the disturbance mechanism and species type. Sites with persistent sediment deposition were characterized by wholesale community changes that did not recover to a before dam removal condition. Instead, the sites were colonized by new species that were largely absent prior to dam removal. Sites that experienced high turbidity but lacked persistent seafloor deposition were primarily characterized by a reduction in the abundance of kelp and other algae during dam removal and a rapid recovery after sediment flux to the nearshore declined. Dam removal influences on invertebrates and fish at these sites were more variable, benefiting some species and disadvantaging others. In addition to dam removal, sea star wasting syndrome and a marine heatwave exerted distinct controls on subtidal communities during the same period. The loss of the predatory sea star Pycnopodia helianthoides was associated with gains in some of its prey species, and kelp community changes reflected regional trends in ocean temperature and kelp abundance. The results presented here have important implications for understanding the response of marine ecosystems to future dam removals and similar sediment perturbation events.

Phytoplankton adaptive resilience to climate change collapses in case of extreme events – A modeling study

As climate change unravels, ecosystems are facing a warming of the climate and an increase in extreme heat events that are unprecedented in recent geological history. We know very little of the ability of oceanic phytoplankton communities, key players in the regulation of Earth's climate by the oceans, to adapt to these changes. Quantifying the resilience of phytoplankton communities to environmental stressors by means of adaptive evolution is however crucial to accurately predict the response of marine ecosystems to climate change. In this work, we use an eco-evolutionary model to simulate the adaptive response of marine phytoplankton to temperature changes in an initially temperate oligotrophic water-column. By exploring a wide range of scenarios of phytoplankton adaptive capacity, we find that phytoplankton can adapt to temperature increases –even very large ones– as long as they occur over the time scale of a century. However, when rapid and extreme events of temperature change are considered, the phytoplankton adaptive capacity breaks down in a number of our scenarios in which primary productivity plummets as a result. This suggests that current Earth System Models assuming perfect phytoplankton adaptatedness to temperature might be overestimating the phytoplankton's resilience to climate change.

An improved algorithm for detecting mesoscale ocean fronts from satellite observations: Detailed mapping of persistent fronts around the China Seas and their long-term trends

Mesoscale fronts are highly energetic ocean processes that dominate local biogeochemical processes and air-sea interactions and exert significant effects on ocean dynamics, ecology, and climate. An automatic front detection algorithm applied to satellite-based observations is a fundamental approach to acquiring frontal occurrence information. Histogram-based algorithms have been widely used in previous studies, and, despite being the most popular front detection algorithm, continuous improvements have been needed to address imperfect detection issues (undetected coastal fronts, discontinuities of fronts and repeated detection of fronts). In this study, a new algorithm is proposed to address the issues by coupling inverse distance weighting and mathematical morphology operators. Using 14,610 images acquired from 1982 to 2021, a series of comparisons between the new and existing algorithms have been implemented to validate the improvements. Statistical results suggest that the number of frontal pixels detected by our algorithm increased by 58.45% in the coastal domain when compared to previous methods. Statistical analysis also shows most of these increased fronts can be supported by a classic gradient-based method which is superior in detecting coastal fronts, which demonstrates the improvement of new algorithm in detecting coastal fronts. Furthermore, visual analyses suggest that our algorithm can better connect discontinuous fronts and reduce repeated detections, and statistical comparisons in the open seas present a 34.50% improvement in the average length of frontal segments. Moreover, based on an automated objective delineation method, an analysis of 40 years of seasonal frontal occurrences (as detected by our algorithm) produced a dataset that shows a detailed map of 59 persistent fronts around the China Seas. This map updates previously hand-delineated frontal positions and identifies some previously unreported persistent fronts. Further analyses show that the frontal occurrence or intensity of a majority of persistent fronts around the China Seas presents significant (P < 0.05) long-term variability over the last 40 years. The improved algorithm, together with its application in identifying persistent fronts around the China Seas, is expected to be extended to other waters to better investigate the response of marine ecosystems to front dynamics and predict the distribution of marine organisms within a changing climate.

Marine big data-driven ensemble learning for estimating global phytoplankton group composition over two decades (1997–2020)

Accurate monitoring of the spatial-temporal distribution and variability of phytoplankton group (PG) composition is of vital importance in better understanding of marine ecosystem dynamics and biogeochemical cycles. While existing bio-optical algorithms provide valuable information, relying solely on satellite ocean color data remains insufficient to obtain high-precision retrieval of PG due to the intricate nature of the bio-optical signal and PG composition itself. An interdisciplinary approach combining advancements in machine learning with big data from ocean observations and simulations offers a promising avenue for more accurate quantification of PG composition. In this study, an ensemble learning approach, called the spatial-temporal-ecological ensemble (STEE) model, is developed to construct a robust prediction model for eight distinct phytoplankton groups (i.e., Diatoms, Dinoflagellates, Haptophytes, Pelagophytes, Cryptophytes, Green Algae, Prokaryotes, and Prochlorococcus). The proposed method introduces multiple data simultaneously: ocean color, physical oceanographic, biogeochemical, and spatial and temporal information. An ensemble strategy is applied to increase the performance of the model by merging three advanced machine-learning algorithms. The combined validation of multiple cross-validation (CV) strategies (i.e., standard, spatial block, and temporal block CVs) shows that the proposed STEE model has superior robustness and generalization ability. In addition, the analysis shows a high degree of concordance between the independent datasets and the modeled estimations for long-time series sites, indicating that the STEE model is capable of effectively monitoring long-term trends in phytoplankton group composition. Finally, the proposed model was utilized to retrieve global monthly phytoplankton group products (STEE-PG) over an extended period (September 1997 to May 2020), and comparisons demonstrated better rationality of spatio-temporal distribution than existing satellite-derived phytoplankton group products. Hence, this new model comprehensively integrates all kinds of observation data and yields long-term global PG products with high accuracy, which will enhance our understanding of the response of marine ecosystems to environmental and climate change.

Modeling present and future distribution of plankton populations in a coastal upwelling zone: the copepod Calanus chilensis as a study case

Predicting species distribution in the ocean has become a crucial task to assess marine ecosystem responses to ongoing climate change. In the Humboldt Current System (HCS), the endemic copepod Calanus chilensis is one of the key species bioindicator of productivity and water masses. Here we modeled the geographic distribution of Calanus chilensis for two bathymetric ranges, 0–200 and 200–400 m. For the 0–200 m layer, we used the Bayesian Additive Regression Trees (BART) method, whereas, for the 200–400 m layer, we used the Ensembles of Small Models (ESMs) method and then projected the models into two future scenarios to assess changes in geographic distribution patterns. The models were evaluated using the multi-metric approach. We identified that chlorophyll-a (0.34), Mixed Layer Depth (0.302) and salinity (0.36) explained the distribution of C. chilensis. The geographic prediction of the BART model revealed a continuous distribution from Ecuador to the southernmost area of South America for the 0–200 m depth range, whereas the ESM model indicated a discontinuous distribution with greater suitability for the coast of Chile for the 200–400 m depth range. A reduction of the distribution range of C. chilensis is projected in the future. Our study suggests that the distribution of C. chilensis is conditioned by productivity and mesoscale processes, with both processes closely related to upwelling intensity. These models serve as a tool for proposing indicators of changes in the ocean. We further propose that the species C. chilensis is a high productivity and low salinity indicator at the HCS. We recommend further examining multiple spatial and temporal scales for stronger inference.

Cryptic speciation of benthic Prorocentrum (Dinophyceae) species and their potential as ecological indicators

The response of marine ecosystems to rapid climate changes has been well recognized but not studied extensively. Benthic microalgae, in contrast to the phytoplankton that is able to be transported by currents, have limited dispersal ability and thus are a better ecological indicator to climate changes. Here we performed sampling in the Yellow Sea, the East China Sea and South China Sea and established twenty-six strains of benthic Prorocentrum for detailed morphological and molecular examinations. Five Prorocentrum species, including P. concavum, P. fukuyoi, P. mexicanum, P. tsawwassenense, and P. cf. sculptile, were identified. Both P. concavum and P. fukuyoi displayed marked intraspecific divergences in large subunit (LSU) ribosomal RNA gene sequences, corresponding to their geographical origins. In contrast, P. mexicanum strains shared identical LSU sequence. Prorocentrum tsawwassenense and P. cf. sculptile are not suitable ecological indicators as they were rarely observed. Prorocentrum mexicanum is not recommended either as it is present across the region. In contrast, P. concavum and P. fukuyoi have advantages as ecological indicators for climate changes in the Western Pacific as they comprise several ribotypes with differentiated biogeography. Toxin analysis was also performed on all five species except P. fukuyoi by liquid chromatography coupled to tandem mass spectrometry, but okadaic acid was not detectable.

Middle to Late Holocene Sea Surface Temperature and Productivity Changes in the Northeast Pacific

AbstractVariations of the sea surface temperature (SST) and primary productivity in the northeast Pacific have far‐reaching implications. In addition to influencing the regional and global temperature and hydroclimate, these conditions also control marine ecosystems and their services, which subsequently impact regional economies. Yet, our understanding of the variability and controls of northeast Pacific SST and productivity on timescales exceeding observational records remains limited. Here, we use marine sediment records from seven locations, spanning 25.2°N–59.6°N, in the northeast Pacific to characterize the millennial‐scale variability of SST and productivity from 9,000 to 1,000 years BP. We explore the dynamics of their spatiotemporal evolution and compare these data with transient climate model outputs to identify potential drivers. Through a heat budget analysis and optimal fingerprinting analysis, we characterize the spatial pattern of forcings. We find that SST varied spatially in the northeast Pacific, with higher latitudes exhibiting greater magnitude changes than lower latitudes, which differs from previous work suggesting regional synchronicity and coherence during the Holocene. Our analysis did not find evidence for coherent variability of primary producer community nor carbon export, highlighting the difficulty of identifying the complex interactions between environmental conditions, producers, and carbon export. Model‐proxy disagreement demonstrates the need for higher resolution model frameworks, but shows nonetheless that observed variability in the proxy records can be explained by a combination of greenhouse gas and orbital forcing. We suggest that the complex SST variations and marine ecosystem responses to forced changes are important factors that can drive disagreements in model projections.

Shoreline sentinels of global change show the consequences of extreme events.

Anthropogenic climate change along with the more frequent extreme weather it prompts, are having direct and indirect effects on distributions and abundance of species with consequence for community structure-especially if habitat providers are lost. Rocky shores have long been recognized as tractable experimental arenas for ecology contributing to theory. They have also emerged as important sentinel systems for tracking climate change responses of marine biodiversity and ecosystems, capitalizing on both historic broadscale surveys and time series. Combining these twin traditions is a powerful approach for better understanding and forecasting climate change impacts. Sustained observing allows extreme events to be detected and explored by in-parallel experimentation.

Estimation of Phytoplankton Size Classes in the Littoral Sea of Korea Using a New Algorithm Based on Deep Learning

The size of phytoplankton (a key primary producer in marine ecosystems) is known to influence the contribution of primary productivity and the upper trophic level of the food web. Therefore, it is essential to identify the dominant sizes of phytoplankton while inferring the responses of marine ecosystems to change in the marine environment. However, there are few studies on the spatio-temporal variations in the dominant sizes of phytoplankton in the littoral sea of Korea. This study utilized a deep learning model as a classification algorithm to identify the dominance of different phytoplankton sizes. To train the deep learning model, we used field measurements of turbidity, water temperature, and phytoplankton size composition (chlorophyll-a) in the littoral sea of Korea, from 2018 to 2020. The new classification algorithm from the deep learning model yielded an accuracy of 70%, indicating an improvement compared with the existing classification algorithms. The developed classification algorithm could be substituted in satellite ocean color data. This enabled us to identify spatio-temporal variation in phytoplankton size composition in the littoral sea of Korea. We consider this to be highly effective as fundamental data for identifying the spatio-temporal variation in marine ecosystems in the littoral sea of Korea.

Responses of phytoplankton communities driven by differences of source water intrusions in the El Niño and La Niña events in the Taiwan Strait during the early spring

The El Niño Southern Oscillation (ENSO) is one of the most important drivers of interannual variations of marine ecosystems, especially monsoonal ecosystems. The channel effect in a strait amplifies the impact of monsoons and may be an ideal area to study ecosystem responses to ENSO events. Previous studies have shown that physical processes in the Taiwan Strait (TWS) vary during the different ENSO phases, but the biological responses are still unclear. In this study, we found clear differences in the physical, chemical, and biological characteristics of the TWS between different ENSO phases based on data from satellites and field cruises during the 2015–2016 El Niño and 2017–2018 La Niña events. Although the monsoonal patterns were similar during early spring cruises during two ENSO events, the influence of the China Coastal Current (CCC), which is characterized by low sea surface temperature, low salinity, and high nutrient concentrations, was 1.5 times greater during the 2015–2016 El Niño than the 2017–2018 La Niña. The average chlorophyll a concentration was therefore higher in 2016 than that in 2018. The phytoplankton consisted mainly of diatoms, dinoflagellates, and cryptophytes during the 2015–2016 El Niño, but concentrations of those phytoplankton groups decreased, and concentrations of prasinophytes, Synechococcus, and Prochlorococcus increased during the 2017–2018 La Niña. Their influence of the CCC and warm currents were associated with the variations in phytoplankton community structure in the TWS. The results of this study enhance understanding of the responses of marine ecosystems to climate variabilities, and of the changes that climate change may bring to strait ecosystems.

Two cosmopolitanism events driven by different extreme paleoclimate regimes

Cosmopolitanism represents the formation of globally homogenous biotas, usually of low-diversity, and normally form under unusual environmental conditions. But the factors driving such important biogeographic states remain unclear. The Carboniferous to Triassic encompasses the Late Paleozoic Ice Age (LPIA) and a hothouse beginning in the latest Permian and persisting through the Early Triassic. These dramatic environmental changes caused complex paleobiogeographic changes and were also associated with such severe biological events as the mid-Carboniferous biotic crisis, and the end-Permian and end-Triassic mass extinctions. This interval is a unique natural window for studying biogeographic patterns under different climate backgrounds and with greatly changed taxonomic composition. In this study, we apply multiple biogeographic indices to examine two episodes of cosmopolitanism based on global marine invertebrate fossil records during the Carboniferous to Triassic. The LPIA cosmopolitanism event was characterized by high faunal similarity at middle latitudes generated by diversity loss and complex glacial/interglacial climatic changes. By contrast, the EPME cosmopolitanism event was characterized by high faunal similarity globally resulting from a faunal changeover, when communities characterized by high richness were replaced by widespread and monotonous communities with high evenness and extremely low richness. The two cosmopolitanism events differed in durations, taxon preference and geographic influence, but in both cases their driving mechanisms were linked to extreme icehouse and hothouse climates. These two episodes illustrate the complexity of deep time marine ecosystem response to climatic changes and the multiple drivers of cosmopolitanism in the marine biosphere. • Two cosmopolitanism events are found in icehouse and greenhouse climate respectively. • Multiple methods are integrated to indicate biogeographic disparity changes. • Different mechanisms are behind cosmopolitanisms when climatic backgrounds differ. • Both biotic and abiotic factors functioned in causing these cosmopolitanism events. • Cosmopolitanism events had taxa group preference under different climates.