Changes In Primary Production Research Articles

Global decline in net primary production underestimated by climate models

Marine net primary production supports critical ecosystem services and the carbon cycle. However, the lack of consensus in the direction and magnitude of projected change in net primary production from models undermines efforts to assess climate impacts on marine ecosystems with confidence. Here we use contemporary remote sensing net primary production trends (1998–2023) from six remote sensing algorithms to discriminate amongst fifteen divergent model projections. A model ranking scheme, based on the similarity of linear responses of net primary production to changes in sea surface temperature, chlorophyll-a and the mixed layer, finds that future declines in net primary production are more likely than presently predicted. Even the best ranking models still underestimate the sensitivity of declines in net primary production to ocean warming, suggesting shortcomings remain. Reproducing this greater temperature sensitivity may lead to even larger declines in future net primary production than presently considered for impact assessment.

Changes in Water and Carbon Fluxes in the USA Southern Great Plains Grassland Due to Evergreen Forest Encroachment

The southern Great Plains (SGP) grassland of the United States has been largely encroached by evergreen forest in recent decades. The response of the grassland water and carbon cycles to the encroachment is not clear yet. Given so, this study quantified the changes in gross primary production (GPP), evapotranspiration (ET), and ecosystem water use efficiency (EWUE) between grassland pixels with evergreen forest encroachment and neighboring pure grassland pixels (500 m). We also assessed the spatial variation of the changes in relation to precipitation (mm), air temperature (°C), and evergreen forest coverage (%). These analyses were repeated, respectively for the years of 2004, 2008, 2016, and 2019 as robustness check. Results suggest that across the 4 years, 62–72% of encroached grassland pixels exhibit higher annual GPP, 67–74% exhibit higher annual ET, whereas 65–71% exhibit lower annual EWUE. The change ratio of ET is positively correlated with that of GPP but negatively correlated with that of EWUE. Additionally, the spatial variation in the change ratios of annual GPP and ET can be explained to a certain degree by the encroachment amount. These results further clarify the response of water and carbon cycles to evergreen forest encroachment in the SGP grassland.

Development of a high-resolution ocean ensemble future projection dataset for the North Pacific incorporating simple biogeochemical processes

In this study, we developed a new version of the future ocean regional projection dataset in the North Pacific (FORP-NP10) by performing an ensemble of historical and multi-scenario future projection simulations from 1960 to 2100 using a high-resolution ocean downscaling model system driven by surface forcings based on the atmospheric data of the Coupled Model Intercomparison Project (Phase 5). This version is characterized by the inclusion of simple biogeochemical processes within the simulations of the multi-case (four forcing cases) and multi-future projection scenarios (representative concentration pathway 2.6 and 8.5) using a mesoscale eddy-resolving (approximately 10 km) horizontal resolution. The dataset reasonably represented the main biogeochemical properties in the North Pacific and around Japan, such as surface CO2 flux, pH, subsurface oxygen, surface nitrate, and chlorophyll, as well as the ocean physics of the regions, including the mesoscale/frontal structures of the Kuroshio, Kuroshio Extension, and mixed layer depth. We assessed the bias tendencies and structures of these properties by comparing them with observational reference data and the low-resolution model results. Our ensemble dataset consistently projected future upper-ocean warming, acidification, deoxygenation, and changes in nutrient and primary production in the twenty-first century (reported as global analyses in recent reports of the Intergovernmental Panel on Climate Change) in the regions surrounding Japan, revealing that the future changes exhibited spatial contrasts or varying tendencies in the regions.

Chlorophyll-a Outliers in the Banda Sea and its surroundings: Implications for Ecosystem Dynamics

Chlorophyll-a concentration is a critical indicator of marine ecosystem health, reflecting primary productivity and potential ecological changes. However, the occurrence of outlier data in the Banda Sea and its surroundings has not been sufficiently studied. This study aims to investigate the dynamics of chlorophyll-a concentration outliers in the Banda Sea, focusing on their spatial and temporal patterns from 2010 to 2022. Data were acquired from MODIS satellite imagery and analyzed using R Studio for time series decomposition, while spatial patterns were explored with ArcGIS 10.8 and Google Maps to pinpoint key hotspots of outlier activity. The findings reveal fluctuating chlorophyll-a outliers with extreme concentrations ranging from 14.39 to 81 mg·m⁻³. Temporally, these outliers are predominantly observed in the western Banda Sea during January to March and December, while in the eastern Banda Sea they occur from June to September. Spatially, these anomalies are concentrated in areas of significant human activity, particularly in Tolo Bay, suggesting a potential link between anthropogenic influences and ecological disruptions. Field monitoring in areas with persistent outliers is strongly recommended to verify actual conditions and assess their ecological impacts. While chlorophyll-a plays a vital role in marine productivity, excessive concentrations can disrupt ecosystems, potentially leading to harmful algal blooms or hypoxic conditions. This study underscores the importance of integrating remote sensing, field validation, and spatial analysis to effectively monitor and manage these anomalies. Enhanced understanding of these dynamics is critical for informed decision-making and sustainable marine management practices in the Banda Sea.

Patterns of siderophore production and utilization at Station ALOHA from the surface to mesopelagic waters

AbstractThe North Pacific subtropical gyre is a globally important contributor to carbon uptake despite being a persistently oligotrophic ecosystem. Supply of the micronutrient iron to the upper ocean varies seasonally to episodically, and when coupled with rapid biological consumption, results in low iron concentrations. In this study, we examined changes in iron uptake rates, along with siderophore concentrations and biosynthesis potential at Station ALOHA across time (2013–2016) and depth (surface to 500 m) to observe changes in iron acquisition and internal cycling by the microbial community. The genetic potential for siderophore biosynthesis was widespread throughout the upper water column, and biosynthetic gene clusters peaked in spring and summer along with siderophore concentrations, suggesting changes in nutrient delivery, primary production, and carbon export seasonally impact iron acquisition. Dissolved iron turnover times, calculated from iron‐amended experiments in surface (15 m) and mesopelagic (300 m) waters, ranged from 9 to 252 d. The shortest average turnover times at both depths were associated with inorganic iron additions (14 9 d) and the longest with iron bound to strong siderophores (148 225 d). Uptake rates of siderophore‐bound iron were faster in mesopelagic waters than in the surface, leading to high Fe : C uptake ratios of heterotrophic bacteria in the upper mesopelagic. The rapid cycling and high demand for iron at 300 m suggest differences in microbial metabolism and iron acquisition in the mesopelagic compared to surface waters. Together, changes in siderophore production and consumption over the seasonal cycle suggest organic carbon availability impacts iron cycling at Station ALOHA.

Spatio-Temporal Variation Characteristics and Influencing Factors of Vegetation Cover in Loess Plateau Based on Model of Spatial Autocorrelation and Geodetector

The Loess Plateau is located in the transition zone between subhumid, arid and semi-arid in China, where water resources are rare and ecological environment are fragile. Since 1999, the large-scale “Grain For Green” project has improved environment significantly. On the basis of summarizing the spatial variation characteristics of vegetation cover in the region, this study used spatial autocorrelation to analyze the correlation between Net Primary Production(NPP), precipitation and vegetation cover change. Natural factors such as temperature, precipitation, Digital Elevation Model(DEM) and soil moisture and human factors such as population density, Gross Domestic Production (GDP), road density and grain yield NPP were statistically divided by geodetector. The influence degree of each driving factor on Normalized Difference Vegetation Index (NDVI) was systematically discussed, and the spatial-temporal variation characteristics of vegetation in the basin and the driving force of the driving factors were explored.

Impact of Climate Change on the Spatiotemporal Change in Vegetation Gross Primary Productivity of Marsh Wetlands Across China

Impact of Climate Change on the Spatiotemporal Change in Vegetation Gross Primary Productivity of Marsh Wetlands Across China

Effects of climate change and methane-rich fluid activity on sedimentary sulfur geochemical records in the northern South China Sea since mid-Pleistocene

Microbial sulfate reduction (MSR) and associated pyritic sulfide formation are important diagenetic processes in marine sediments. The sulfur isotopic composition of pyrite (δ34Spyr) is proven to be sensitive to changes in sedimentation rates and the content and reactivity of organic carbon, especially on the continental shelves and upper slopes (water depth < 350 m). However, the diagenetic responses of sulfur to variations in climatic and depositional conditions in the deep-sea sediments are still poorly understood. This study combines element contents and isotopes to characterize diagenetic interplays of sulfur, organic carbon, and methane in the continental slope sediments of the northern South China Sea since the mid-Pleistocene. Our data suggest that the total organic carbon (TOC) increased during glacial times, implying enhanced primary productivity due to increased nutrient supply by the East Asian Winter Monsoon, in addition to efficient transfer of organic carbon and better preservation of organic carbon due to reduced bottom water oxygen. Total sulfur and chromium reduction sulfur contents varied concomitantly with the TOC, suggesting an increased burial of organic carbon that enhanced the organoclastic sulfate reduction (OSR) and the formation of authigenic pyrite. The environmental changes did not induce a significant shift in δ34Spyr, due most likely to relatively low sedimentation rates and large fractionation in sulfur isotope through OSR during the glacial-interglacial cycles. Instead, it is hypothesized that the sulfate-driven anaerobic methane oxidation promoted the formation of a higher amount of authigenic pyrite. Consequently, it created a closed diagenetic system leading to positive excursions in δ34Spyr at the sulfate-methane transition zone. Our results suggest the vulnerability of pyrite formation and its sulfur isotopic composition to the changes in monsoon-driven primary productivity and the methane-rich fluid migrations in the continental margin sediments. This study complements the growing evidence for the local diagenetic controls on sedimentary sulfur geochemical records by highlighting the importance of early diagenesis in paleoenvironment reconstruction based on the content and sulfur isotopic composition of pyrite.

Perturbations in a pelagic food web during the NE pacific large marine heatwave and persistent harmful diatom blooms

Unprecedented warm ocean conditions, driven by the Large Marine Heatwave (LMH) and the 2015–16 El Niño in the Northeast Pacific favored pervasive toxigenic Pseudo-nitzschia spp. blooms that caused widespread ecological impacts, but little is known about the magnitude to which marine food webs were altered. Here, we assessed the trophic transfer of domoic acid (DA; a neurotoxin) and changes in trophic position from multiple key species during the peak of the LMH and El Niño in 2015 in comparison with 2018, a reference non-anomalous warm year. DA and amino acid nitrogen isotopes (δ15N AAs) were quantified using liquid and gas chromatography mass spectrometry, respectively. Our integrative approach revealed extremely high levels of DA in anchovy viscera (>3000 μg/g) with contrasting baseline values (δ15N Phe) for southern California fish. These results together with data from northern CA revealed an unforeseen latitudinal isotopic variation in key DA vectors along California, possibly driven by anomalous restructuring of water masses. At the regional level, the observed cross-shore differences in baseline isotope values and DA toxicity suggest distinct pathways for DA trophic transfer for nearshore vs. offshore sites. Given the high levels of environmental disturbance during the LMH and persistence of toxigenic P. australis blooms, our resultant higher trophic position proxies in 2015 compared to 2018 were particularly unexpected. Such results highlight complex trophic interactions, where the trophic status of some species increased while others decreased in response to changes in net primary productivity, and biodiversity, and abundance of forage species. Our study demonstrates the use of δ15N AAs to identify pathways of N and DA trophic transfer and to quantify shifts in animal trophic position, a critical facet of understanding the response of food webs to climate change and DA production.

Modeling NPP and NDVI time series in different bioclimatic regions of Iran.

Vegetation is one of the important components of ecosystems that usually changes seasonally. An accurate parameterization of vegetation cover dynamics by developing time series models can strengthen our understanding of vegetation change. This research aims to investigate and model the temporal changes of net primary production (NPP) and normalized difference vegetation index (NDVI) across bioclimatic regions of Iran, including the Khazari, Baluchi, semi-desert, steppe, semi-steppe, and arid forests. We used Moderate Resolution Imaging Spectroradiometer (MODIS) sensor products for NPP and NDVI time series (MOD17A2 and MOD13Q1, respectively). The SARIMA (Seasonal Autoregressive Integrated Moving Average) time series model is developed for NPP and NDVI time series. The investigation of autocorrelation functions (ACF) showed a strong seasonality in NPP and NDVI at the 12-month lag time. Comparing the lag times from 1 to 24 month for different regions shows that the NPP variable has a stronger seasonality. The evaluation of error criteria which showed NPP time series models based on RMSE, R2, MRE, and CE criteria was better, while based on the ME criteria, the models perform better for NDVI time series (for example, in Khazari region for NPP and NDVI time series, respectively, ME = 3.67, 0.05, RMSE = 0.12, 0.18, R2 = 0.87, 0.63, MRE = 0.02, 0.12, and CE = 0.84, 0.12). The selected models provided a short-term forecasting of the NPP and NDVI index for study regions at 24-month time, which is useful for the planning and management to reduce vegetation degradation and preserve ecosystem and biodiversity.

Future directions for deep ocean climate science and evidence-based decision making

IntroductionA defining aspect of the Intergovernmental Panel on Climate Change (IPCC) assessment reports (AR) is a formal uncertainty language framework that emphasizes higher certainty issues across the reports, especially in the executive summaries and short summaries for policymakers. As a result, potentially significant risks involving understudied components of the climate system are shielded from view.MethodsHere we seek to address this in the latest, sixth assessment report (AR6) for one such component—the deep ocean—by summarizing major uncertainties (based on discussions of low confidence issues or gaps) regarding its role in our changing climate system. The goal is to identify key research priorities to improve IPCC confidence levels in deep ocean systems and facilitate the dissemination of IPCC results regarding potentially high impact deep ocean processes to decision-makers. This will accelerate improvement of global climate projections and aid in informing efforts to mitigate climate change impacts. An analysis of 3,000 pages across the six selected AR6 reports revealed 219 major science gaps related to the deep ocean. These were categorized by climate stressor and nature of impacts.ResultsHalf of these are biological science gaps, primarily surrounding our understanding of changes in ocean ecosystems, fisheries, and primary productivity. The remaining science gaps are related to uncertainties in the physical (32%) and biogeochemical (15%) ocean states and processes. Model deficiencies are the leading cited cause of low certainty in the physical ocean and ice states, whereas causes of biological uncertainties are most often attributed to limited studies and observations or conflicting results.DiscussionKey areas for coordinated effort within the deep ocean observing and modeling community have emerged, which will improve confidence in the deep ocean state and its ongoing changes for the next assessment report. This list of key “known unknowns” includes meridional overturning circulation, ocean deoxygenation and acidification, primary production, food supply and the ocean carbon cycle, climate change impacts on ocean ecosystems and fisheries, and ocean-based climate interventions. From these findings, we offer recommendations for AR7 to avoid omitting low confidence-high risk changes in the climate system.

Atmospheric Nitrogen Deposition Controls Interannual Variability of Net Primary Production in the Bohai Sea

AbstractIncreasing human activities and climate change have resulted in significant changes in net primary production (NPP) of the marginal sea in the past several decades. The Bohai Sea (BHS) is a shallow semi‐enclosed marginal sea of North China, the knowledge of the relative impacts of human activities and climate change on the NPP in the BHS remains limited. This study primarily aimed to elucidate the interannual variability of NPP and its influencing factors in the BHS during the 2002–2021 period by synthesizing four widely‐used global NPP models, namely the vertically generalized production model (VGPM), the Eppley‐VGPM, the size‐fractioned phytoplankton pigment absorption‐based model (SABPM), and the carbon, absorption, and fluorescence euphotic‐resolving model (CAFE). The multi‐model average NPP showed significant interannual variation, with an increasing trend from 2002 to 2012 and a decreasing trend from 2012 to 2021. The concentration of DIN in the BHS was primarily affected by atmospheric nitrogen deposition. The structural equation model demonstrated that chlorophyll‐a (Chl‐a) concentration, influenced by DIN concentration, had an important effect on NPP. In brief, atmospheric nitrogen deposition impacted the DIN concentration and thus controlled the Chl‐a concentration and NPP change in the BHS. Furthermore, atmospheric nitrogen deposition in the BHS have potential ecological impacts on the red tide features. These findings hold valuable implications for future marine resource planning and marine ecological management in the BHS.

Divergent apparent temperature sensitivity of forest-floor respiration across a managed boreal forest landscape

Understanding the apparent temperature sensitivity (Q10) of forest floor respiration (Q10Rff) and its plant autotrophic (Q10Ra) and soil heterotrophic (Q10Rh) components is critical for determining the strength and direction of forest carbon cycle-climate feedbacks. However, the spatial variability of Q10Rff and its controlling factors across the spatially heterogeneous boreal forest landscape remains poorly understood. In this study, we used chamber-based respiration measurements conducted on paired natural and trenching plots over three growing seasons (2016–2018) to determine Q10Rff, Q10Rh and Q10Ra to soil temperature across 50 diverse forest stands (ranging 5–211 years old) in a managed landscape in northern Sweden. Additionally, we estimated ecosystem- and landscape-scale Q10 based on conventional and tall tower eddy covariance measurements, respectively, conducted over the same landscape. Our results suggest manifold variations (i.e., 10th to 90th percentiles) of Q10Rff (1.7 to 6.6), with Q10Ra (0.9 to 7.4) showing a greater range than Q10Rh (1.6 to 5.3). Forest-floor understory biomass was the main control of variations in Q10Ra, whereas soil properties explained best those of Q10Rh. Furthermore, a seasonal hysteresis of Q10Rff was observed, with higher values mostly occurring during the late growing season. The magnitude of this hysteresis scaled with stand age in response to concurrent changes in net primary production. The Q10Rff to air temperature declined with increasing stand age, which was attributed to the increased decoupling of air and soil temperatures with canopy development. Despite the considerable stand-level variations, when averaged over the 50 forest stands, Q10Rff to air temperature converged with that of both ecosystem- and landscape-scale respiration. In conclusion, our study highlights the complexity of Q10Rff, which needs to be considered in predictions of the interactions of climate change and management with the carbon cycle of managed boreal forests.

Analyses of sea surface chlorophyll a trends and variability from 1998 to 2020 in the German Bight (North Sea)

Abstract. Satellite remote sensing of ocean colour properties allows observation of the ocean with high temporal and spatial coverage, facilitating the better assessment of changes in marine primary production. Ocean productivity is often assessed using satellite-derived chlorophyll a concentrations, a commonly used proxy for phytoplankton concentration. We used the Copernicus GlobColour remote sensing chlorophyll a surface concentration to investigate seasonal and non-seasonal variability, temporal trends, and changes in spring bloom chlorophyll a magnitude. Complementary, we analysed the chlorophyll a relationship with sea surface temperature and mixed-layer depth in the German Bight from 1998 to 2020. Empirical orthogonal functions were employed in order to investigate dominant spatial and temporal patterns (modes) related to the main processes of chlorophyll a variability. Multi covariance analysis was used to extract the dominant structures that maximize the covariance between chlorophyll a and sea surface temperature mixed-layer depth fields. High levels of chlorophyll a were found near the coast, showing a decreasing gradient towards offshore waters. A significant chlorophyll a positive trend was observed close to the Elbe estuary and adjacent area, while 55 % of the German Bight was characterized by a significant chlorophyll a negative trend. The chlorophyll a non-seasonal variability showed that the first four modes explained around 45 %, with the first and second modes related to inter- and intra-annual variability, respectively, observed in the temporal principal components spectral analyses. Monthly chlorophyll a concentration anomalies co-varied by 45 % with sea surface temperature anomalies and 23 % with mixed-layer depth anomalies. The monthly averages of chlorophyll a anomaly fields were suitable to investigate long-term trends and variability. The rising water temperature, combined with its indirect effects on other variables, can partially explain the observed trends in chlorophyll a.

Sedimentary record of primary productivity changes in a crater lake in Northeast China since the Last Glacial Maximum

High-resolution primary productivity records are valuable for identifying lacustrine ecosystem degradation in the context of long-term climatic variability. In this paper, we analyse primary productivity changes in a seasonally ice-covered crater lake (Lake Tuofengling) in northeast China since the Last Glacial Maximum using biogenic silica content and the carbon preference index of short-chain n-alkanes as proxies. Results show that primary productivity was lower during the cold and dry glacial period, whereas it was higher during the warm and humid Holocene. During the last deglaciation, primary productivity experienced a ∼ 1.5-kyr lagged response to Bølling-Allerød warming, and multiple oscillations during the Younger Dryas. Additionally, the peak productivity of the entire profile also occurred during this period. These fluctuations and the highest primary productivity are suggested to be the result of the combined influences of increased summer temperatures and regional permafrost melting. The current state of primary productivity in Lake Tuofengling is moderate but has been increasing since the abrupt increase in diatom productivity after ∼3 ka B.P. This stage is associated with increased dust deposition and longer ice-free periods under winter-warming conditions. We suggest that longer seasonal stratification under the current warmer winters and increased nutrient concentrations caused by decreased lake level will increase the risk of lake ecosystem degradation in the future.

European croplands under climate change: Carbon input changes required to increase projected soil organic carbon stocks

Increasing soil organic carbon (SOC) stocks in agricultural systems is a pivotal strategy for promoting soil health and mitigating climate change. Global initiatives have set ambitious targets, aspiring to achieve an annual SOC stock increase of 4 ‰. In the European Union, the recently approved Nature Restoration Law aims to increase SOC stock trends in the top 30 cm of cropland mineral soils. However, current monitoring and reporting practices in some countries rely on simplistic SOC models with default parameters, which may not provide reliable predictions.In this paper, we study the feasibility of a 4 ‰ target in European croplands (i.e., an aspirational target proposed by The international “4 per 1000” Initiative), through estimations of required C input changes. To ensure robust predictions, we propose a novel calibration approach that links model parameters to pedo-climatic variables via statistical relationships from 16 long-term experiments. The effectiveness of the method is evaluated for three SOC models across 4281 sites from the European LUCAS soil survey.Our findings demonstrate that the statistical calibration of the multi-model ensemble improves the accuracy of 2015 and 2018 SOC stock predictions, compared to default parameterization. This improvement was however mainly due to the substantial enhancement of one of the models. According to the weighted multi-model mean, median C input changes to reach a 4 ‰ target for Northern, Central, and Southern Europe stand at 1.85, 1.20, and 0.13 Mg C ha−1 yr−1 under RCP 2.6, and 2.21, 1.26, and −0.10 Mg C ha−1 yr−1 under RCP 6.0, respectively.To achieve the aspirational 4 ‰ target, estimated C input change requirements exceed the predicted changes in net primary productivity under RCP 2.6 and RCP 6.0. This emphasizes the importance of strategic land-use and land-management interventions to enhance SOC stocks.

Seasonal Variations of Ice-Covered Lake Ecosystems in the Context of Climate Warming: A Review

The period of freezing is an important phenological characteristic of lakes in the Northern Hemisphere, exhibiting higher sensitivity to regional climate changes and aiding in the detection of Earth’s response to climate change. This review systematically examines 1141 articles on seasonal frozen lakes from 1991 to 2021, aiming to understand the seasonal variations and control conditions of ice-covered lakes. For the former, we discussed the physical structure and growth characteristics of seasonal ice cover, changes in water environmental conditions and primary production, accumulation and transformation of CO2 beneath the ice, and the role of winter lakes as carbon sources or sinks. We also proposed a concept of structural stratification based on the differences in physical properties of ice and solute content. The latter provided an overview of the ice-covered period (−1.2 d decade−1), lake evaporation (+16% by the end of the 21st century), the response of planktonic organisms (earlier spring blooming: 2.17 d year−1) to global climate change, the impact of greenhouse gas emissions on ice-free events, and the influence of individual characteristics such as depth, latitude, and elevation on the seasonal frozen lakes. Finally, future research directions for seasonally ice-covered lakes are discussed. Considering the limited and less systematic research conducted so far, this study aims to use bibliometric methods to synthesize and describe the trends and main research points of seasonal ice-covered lakes so as to lay an important foundation for scholars in this field to better understand the existing research progress and explore future research directions.

Insights into Blue Whale (Balaenoptera musculus L.) Population Movements in the Galapagos Archipelago and Southeast Pacific.

The Galapagos Marine Reserve is vital for cetaceans, serving as both a stopover and residency site. However, blue whales, occasionally sighted here, exhibit poorly understood migratory behavior within the Galapagos and the broader Eastern Tropical Pacific. This study, the first to satellite tag blue whales in the Galapagos (16 tagged between 2021 and 2023), explored their behavior in relation to environmental variables like chlorophyll-a concentration, sea surface temperature (SST), and productivity. Key findings show a strong correlation between foraging behavior, high chlorophyll-a levels, productivity, and lower SSTs, indicating a preference for food-rich areas. Additionally, there is a notable association with geomorphic features like ridges, which potentially enhance food abundance. Most tagged whales stayed near the Galapagos archipelago, with higher concentrations observed around Isabela Island, which is increasingly frequented by tourist vessels, posing heightened ship strike risks. Some whales ventured into Ecuador's exclusive economic zone, while one migrated southward to Peru. The strong 2023 El Niño-Southern Oscillation event led to SST and primary production changes, likely impacting whale resource availability. Our study provides crucial insights into blue whale habitat utilization, informing adaptive management strategies to mitigate ship strike risks and address altered migration routes due to climate-driven environmental shifts.

Potential bottom-up and top-down control of large microzooplankton in response to contrasting productive scenarios in the tropical southwestern Atlantic

Large microzooplankton, comprising organisms generally between 64 and 200 μm, plays a significant trophic role in marine ecosystems as primary or secondary consumers. In oligotrophic systems such as the Tropical Southwestern Atlantic, where primary production is dominated by Cyanobacteria, they provide a pivotal link between the basis of food webs and higher trophic levels. In this region, seasonal variations in circulation and continental runoff and wind mixing induce heightened phytoplankton biomass during autumn when compared to a less productive scenario observed in spring, leading to increased abundances of higher trophic levels. In order to establish the connection between primary producers and these higher trophic levels, we investigated the dynamics of large microzooplankton abundance in response to variations in phytoplankton biomass across different systems in the Tropical Southwestern Atlantic. Our findings highlight the complex interactions between bottom-up and top-down control mechanisms that shape large microzooplankton assemblages in these ecosystems. The increase in primary production was accompanied by an observable increase in the abundances of large microzooplankton organisms over the continental shelf, thereby supporting the hypothesis of bottom-up control. In contrast, offshore, in the South Equatorial Current System, a lower abundance of large microzooplankton was observed in the more productive scenario. The intricate relationships between large microzooplankton and higher trophic levels, particularly planktonic cnidarians, appear to be a key driver of these contrasting patterns. The presence of voracious gelatinous predators in the offshore systems, suggests a scenario in which top-down predation may counteract the expected bottom-up response of large microzooplankton to increased phytoplankton biomass. This indicates the importance of considering the entire trophic web when analysing the responses of large microzooplankton to changes in primary production.

Modelling the bottom-up effects of climate change on primary production in the Gulf of St. Lawrence and eastern Scotian Shelf

The Gulf of St. Lawrence (GSL), along with the St. Lawrence Estuary, is the largest estuarine system in North America. It is a biologically productive sea and an important fishing ground in Canada. The objectives of this study are to determine how climate changes will affect primary production in the GSL and on the eastern Scotian Shelf, and to determine the drivers of the changes. We use a regional ocean model forced with downscaled output of the Max-Planck Institute Earth System Model to study the changes in net primary production under the climate change scenario of Representative Concentration Pathway 8.5 (RCP8.5). Results reveal a projected 13.4% decrease in annual primary production across the GSL system over the next 70 years. This decline primarily stems from reduced nutrient concentrations in the upper layer, despite the increase in nutrients supplied by rivers. Enhanced freshwater influx and ocean surface warming contribute to heightened stratification, that in turn reduce the vertical nutrient fluxes from deeper layers. This mechanism affects the upwelling of nutrient-rich water at the head of the Laurentian Channel in the Lower St. Lawrence Estuary, leading to a 22% reduction in the vertical nitrate flux in the future. Additionally, nutrient concentrations in the water masses entering the GSL at the Strait of Belle Isle and at Cabot Strait are also reduced. Due to declining sea-ice concentration, the phytoplankton bloom is expected to occur between 9 and 23 days earlier under a warmer climate, and last for up to 24 days longer, depending on the GSL subregions, compared to the historical period (2001-2020). Biological productivity at higher trophic levels, and thus fisheries productivity, could be negatively impacted under the RCP8.5 climate change scenario.