Variability Of Primary Production Research Articles

Quantitative analysis of the impact of climate change and oasification on changes in net primary productivity variation in mid-Tianshan Mountains from 2001 to 2020

Net primary productivity (NPP) has been substantially changed under the intense oasification in the urban agglomerations on the northern slopes of mid-Tianshan Mountain (UANSTM) and climate change. However, the temporal variations of NPP under the oasification remain unclear, and the relative contribution of oasification and climate change on annual NPP variation is still under debate. By using remote sensing data, reanalysis data, modified Carnegie–Ames-Stanford Approach (CASA) model, and a machine learning method, we explored the spatial–temporal variation of NPP in the UANSTM region and quantified the contribution of oasification and climate change to NPP variation from 2001 to 2020. Our study indicated that: (1) the NPP presents an overall increasing trend in the most of region and the region presented decreasing trend mainly due to the cropland conversion to the urban area; (2) the oasification-dominated NPP area concentrated in the built-up land and cropland; (3) during 2001–2020, the NPP increased by about 5.4 Tg·C, and the contribution of climatic and oasification to NPP increase were quantified (73.1% and 26.9%, respectively); (4) water-related factors was the main driver of NPP variation in the UANSTM region.

Spatiotemporal Characteristics Prediction and Driving Factors Analysis of NPP in Shanxi Province Covering the Period 2001–2020

The advent of a range of high-precision NPP products, including MODIS NPP, MOD17 NPP, and GIMMS NPP, has sparked growing interest in the study of Earth’s ecosystems. In order to enhance comprehension of ecosystem health, in order to facilitate the development of rational resource management and environmental conservation policies, this investigation employs the MOD17A3 dataset to analyze historical variations in Net Primary Productivity (NPP) within Shanxi Province from 2001 to 2020, while also exploring future trends. The Theil–Sen median trend analysis and Mann–Kendall test are commonly used methods for analyzing time series data, employed to study the spatiotemporal trends and variations in NPP. The Grey Wolf Optimization–Support Vector Machine (GWO–SVM) model combines optimization algorithms and machine learning methods, enhancing the predictive capacity of the model for future NPP time series changes. Conversely, the Hurst exponent utilizes historical NPP trends to assess the persistence characteristics of NPP and predict future spatial variations in NPP. This study additionally investigates the natural driving factors of NPP using the Geographic Detector approach. The key findings of this study are as follows. (1) Overall, NPP in Shanxi Province exhibits a fluctuating upward trend from 2001 to 2020, with an average value of 206.278 gCm−2a−1. Spatially, NPP exhibits a northwest–low and southeast–high pattern, with significant spatial heterogeneity and considerable variability. (2) The average Hurst exponent is 0.86, indicating a characteristic of strong persistence in growth in future NPP. Regions with strong or higher persistent growth account for 95.54% of the total area. (3) According to the CMIP6 climate scenarios, NPP is projected to gradually increase from 2025 to 2030. (4) The interactive effects between natural factors contribute more to NPP variations than individual factors, with the rainfall–elevation interaction having the highest contribution percentage.

Variation of gross primary productivity dominated by leaf area index in significantly greening area

Variation of gross primary productivity dominated by leaf area index in significantly greening area

Hidden demographic impacts of fishing and environmental drivers of fecundity in a sea turtle population.

Fisheries bycatch is a critical threat to sea turtle populations worldwide, particularly as turtles are vulnerable to multiple gear types. The Canary Current is an intensely fished region, yet there has been no demographic assessment integrating bycatch and population management information of the globally significant Cabo Verde loggerhead turtle (Caretta caretta) population. Using Boa Vista island (Eastern Cabo Verde) subpopulation data from capture-recapture and nest monitoring (2013-2019), we evaluated population viability in combination with estimated regional bycatch rates (2016-2020) in longline, trawl, purse-seine and artisanal fisheries. We further evaluated current nesting trends in the context of bycatch estimates, existing hatchery conservation measures, and environmental (net primary productivity) variability in turtle foraging grounds. Current bycatch mortality rates present a risk of near extinction this century, when projecting the Boa Vista subpopulation with matrix population models. Bycatch reduction could increase finite population growth rate by 1.95%, and 1.76% for longline fisheries alone. Hatchery conservation increases hatchling production and reduces extinction risk, but cannot achieve population growth alone. Short-term increases in nest counts (2013-2021), putatively driven by temporary increases in net primary productivity, may be crucially masking ongoing long-term population declines. When fecundity was linked to net primary productivity, our hindcast models simultaneously predicted these opposing long-term and short-term trends. Consequently, our results show conservation management must diversify from land-based management. The masking effect we found has broad-reaching implications for monitoring sea turtle populations worldwide, demonstrating the importance of directly estimating adult survival and that nest counts might inadequately reflect underlying population trends. This article is protected by copyright. All rights reserved.

Seeking for the best conditions for fish fossil preservation in Las Hoyas Konservat-Lagerstätte using microbial mats

ABSTRACT Actuotaphonomic experiments demonstrate how microbial mats prevent or delay destructive processes. The rate at which carcasses are covered is a key to their preservation. Because of the growth rate of microbial mats depends on environmental conditions, a set of experiments have been carried out emulating the Barremian environmental conditions, analysed for temperatures at 14°C and 26°C (cooler and warmer seasons respectively) and atmospheric pCO2 (1000 ppm). For this purpose, the microbial mats were grown in mesocosms within an environmental chamber. Variations in primary production were quantified by measuring changes in dissolved O2 concentration in the water. Zebrafish carcasses were laid on the mats, and their coverage rates were calculated from the daily surface area covered by the mat. The results showed that the fish was covered twice as fast at 26°C, in coincidence with the highest values for the gross primary production and community respiration of the microbial mats. Therefore, for these Barremian conditions, the early stages of carcasses preservation would take place most effectively during the warmer seasons as decomposing activity would release nutrients that would enhance, together with temperature, the growth of mats.

Soil moisture dominates the variation of gross primary productivity during hot drought in drylands

The frequency and severity of hot drought will increase in the future due to impact of climate change and human activities, threatening the sustainability of terrestrial ecosystems and human societies. Hot drought is a typical type of drought event, high vapor pressure deficit (VPD) and low soil moisture (SM) are its main characteristics of hot drought, with increasing water stress on vegetation and exacerbating hydrological drought and ecosystem risks. However, our understanding of the effects of high VPD and low SM on vegetation productivity is limited, because these two variables are strongly coupled and influenced by other climatic drivers. The southwestern United States experienced one of the most severe hot drought events on record in 2020. In this study, we used SM and gross primary productivity (GPP) datasets from Soil Moisture Active and Passive (SMAP), as well as VPD and other meteorological datasets from gridMET. We decoupled the effects of different meteorological factors on GPP at monthly and daily scales using partial correlation analysis, partial least squares regression, and binning methods. We found that SM anomalies contribute more to GPP anomalies than VPD anomalies at monthly and daily scales. Especially at the daily scale, as the decoupled SM anomalies increased, the GPP anomalies increased. However, there is no significant change in GPP anomalies as VPD increases. For all the vegetation types and arid zones, SM dominated the variation in GPP, followed by VPD or maximum temperature. At the flux tower scale, decoupled soil water content (SWC) also dominated changes in GPP, compared to VPD. In the next century, hot drought will occur frequently in dryland regions, where GPP is one of the highest uncertainties in terrestrial ecosystems. Our study has important implications for identifying the strong coupling of meteorological factors and their impact on vegetation under climate change.

Natural and human-induced ecosystem change in SE Europe since AD 1700 derived from a partially varved sediment record from Lake Vouliagmeni (Greece)

To reconstruct naturally and anthropogenically induced environmental change in SE Europe since the Little Ice Age, we have examined five partially varved sediment cores from coastal Lake Vouliagmeni, Greece. Our reconstructions are based on a multi-proxy approach including microfacies analysis, X-ray fluorescence core scanning, radionuclide dating (210Pb, 137Cs, and 241Am), and palynological analysis (pollen, spores, and dinoflagellate cysts). A 131 -cm-long composite record that encompasses the past c. 300 years reveals 181 varves of endogenic and mixed clastic-biogenic types. The formation of these varves was controlled by seasonal variability in clastic input and primary productivity. The non-varved intervals consist of homogenous lake sediments and turbidite deposits. Based on a chronology developed through radionuclide dating, varve counting and exclusion of turbidites from the sequence, we have compared our proxy data with meteorological data and historical records of earthquakes and human activities. Our results suggest that the surroundings of Lake Vouliagmeni experienced relatively wet conditions during the late solar Maunder Minimum (1645–1715 AD) and relatively dry conditions during the Dalton Minimum (1790–1830 AD), which highlights the hydroclimatic heterogeneity in SE Europe during the Little Ice Age. The evaluation of historical documentation suggests that the majority of the turbidites is related to lake-slope instabilities following earthquake shocks. Human impact on Lake Vouliagmeni includes (i) a change in aquatic biota following the artificial connection of the lake to the sea at c. 1880 AD, and (ii) expansion of agricultural areas and reduction of natural forests around the lake due to population growth over the past 300 years.

Spatial–Temporal Patterns of Interannual Variability in Planted Forests: NPP Time-Series Analysis on the Loess Plateau

Investigating how the productivity dynamics of planted forests vary over time is important for understanding the resilience of forests against disturbance and for maximizing ecological restoration and replanting efforts. In this study, the patterns of interannual variability in net primary production (NPP) were analyzed for planted forests as indicated by the inverse of the coefficient of variation (ICV) time series at a ten-year moving window on the Loess Plateau, China, from 2000 to 2021. The spatial–temporal patterns were defined based on the increase or decrease trend obtained using the ordinary least squares method between abrupt change points performed by a Mann–Kendall test in an ICV time series, as follows: only one linear trend, increase (LI), and decrease (LD); at least two trends, increase firstly and decrease lastly (ID) and decrease firstly and increase lastly (DI); and other trends. The results showed that 82.74% of the ICV on the Loess Plateau displayed LD and ID patterns, indicating an increasing variability of forest productivity in this region. Overall, 73.83% of the ICV had a lower degree of rate decrease in the last phase than during the initial increase. Thus, the variability was in an early stage of increasing degree. The ICV time series showed an LI pattern in the eastern Gansu and the southern Shanxi, indicating a decreased variability, due partly to the improved forest restoration. When the plantation age was considered, the newly planted forests (less than 19 a) exhibited a decreasing variability, indicating the proactive role of forest management and restoration in averting environmental disruptions in dry environments.

Landscape heterogeneity increases the stability of wild ungulate populations facing climatic variability in Mediterranean ecosystems

Mediterranean environments are characterized by strong intra- and inter-annual fluctuations in plant primary production, which are likely to regulate the carrying capacity and density-dependent responses of ungulate populations. These effects may, however, vary across spatial and temporal scales. Habitat heterogeneity, particularly when associated to differentiated phenological responses, may allow wild ungulates to mitigate temporal fluctuations in plant production by using different resources along the year. In this work, we use a 15-years dataset (including remote-sensing data on vegetation distribution, phenology and production, as well as ungulate population counts) to assess how temporal variability in plant primary production and livestock abundance influence the population dynamics of two wild ungulates: native red deer, Cervus elaphus, and introduced fallow deer, Dama dama. Results show that temporal alternation in the phenological cycles of the four different vegetation types increased plant production, thus food availability for ungulates, within each year. Furthermore, complementarity in the responses of different vegetation types to variations in the amount and timing of rainfall increased the predictability of food availability across different years. This complementarity effect was further increased by the contrasting responses of ungulate populations to variation in the production of different vegetation types. Furthermore, domestic ungulates had positive effects on wild ungulate density at low to intermediate abundances, but high livestock densities decreased ungulate density and constrained the stability of the plant-ungulate system in response to the impact of climatic variation, particularly under climate change. Our findings deepen the knowledge on vegetation-ungulate interactions in Mediterranean areas, potentially contributing to develop better management strategies of ungulate populations and adapt them to ongoing climate change.

Changes in Carbon Dioxide Balance Associated with Land Use and Land Cover in Brazilian Legal Amazon Based on Remotely Sensed Imagery

The Amazon region comprises the largest tropical forest on the planet and is responsible for absorbing huge amounts of CO2 from the atmosphere. However, changes in land use and cover have contributed to an increase in greenhouse gas emissions, especially CO2, and in endangered indigenous lands and protected areas in the region. The objective of this study was to detect changes in CO2 emissions and removals associated with land use and land cover changes in the Brazilian Legal Amazon (BLA) through the analysis of multispectral satellite images from 2009 to 2019. The Gross Primary Production (GPP) and CO2Flux variables were estimated by the MODIS sensor onboard Terra and Aqua satellite, representing carbon absorption by vegetation during the photosynthesis process. Atmospheric CO2 concentration was estimated from the GOSAT satellite. The variables GPP and CO2Flux showed the effective flux of carbon in the BLA to atmosphere, which were weakly correlated with precipitation (r = 0.191 and 0.133). The forest absorbed 211.05 TgC annually but, due to its partial conversion to other land uses, the loss of 135,922.34 km2 of forest area resulted in 5.82 TgC less carbon being absorbed. Pasture and agriculture, which comprise the main land conversions, increased by 100,340.39 km2 and absorbed 1.32 and 3.19 TgC less, and emitted close to twice more, than forest in these areas. Atmospheric CO2 concentrations increased from 2.2 to 2.8 ppm annually in BLA, with hotspots observed in the southeast Amazonia, and CO2 capture by GPP showed an increase over the years, mainly after 2013, in the north and west of the BLA. This study brings to light the carbon dynamics, by GPP and CO2Flux models, as related to the land use and land cover in one of the biggest world carbon reservoirs, the Amazon, which is also important to fulfillment of international agreements signed by Brazil to reduce greenhouse gas emissions and for biodiversity conservation and other ecosystem services in the region.

Community structure of abyssal macrobenthos of the South and equatorial Atlantic Ocean - Identifying patterns and environmental controls

The DIVA (Latitudinal Gradients of Deep-sea BiodDIVersity in the Atlantic) expeditions studied benthic biodiversity of the abyssal Equatorial and South Atlantic as part of the Census of the Diversity of Abyssal Marine Life (CeDAMar), the abyssal component of the ten-year programme Census of Marine Life (2000–2010). Three expeditions were carried out from RV Meteor between 2000 and 2009. Samples were taken along a latitudinal gradient spanning the Cape, Angola, and Guinea basins in the SE Atlantic and the Argentine and Brazilian basins in the SW Atlantic. The objectives of this study were to analyse patterns of epi- and suprabenthic macrofaunal density and composition at higher taxon level from epibenthic sledge (EBS) taken during the DIVA sampling campaigns and how they relate to differences in environmental conditions. In particular, the different oceanic basins are characterized by variation in surface primary productivity, sedimentary properties, and depth. We expected this difference to be reflected in the structure of the abyssal benthic communities. Consistent with this hypothesis, we found significant differences in macrofauna density between different deep-sea basins, mainly related to food availability. However, only subtle differences in community composition were observed. We found that stations in close proximity to one another showed great variability in both macrofaunal density and composition. We conclude that smaller spatial scale sampling should be paired with higher taxonomic resolution analyses of macrofaunal samples to better understand the factors contributing to variations of macrobenthic communities in the deep sea.

Estuarine dam water discharge enhances summertime primary productivity near the southwestern Korean coast

The gate opening of estuarine dams discharge a large amount of freshwater into coastal zones during the summer monsoon in northeast Asia. We investigated seasonal and spatial variations in primary productivity (PP) and community structures of phytoplankton on a downstream macrotidal flat and examined the dam discharge effects. Our harmonic analysis of the PP revealed a clear seasonality with a unimodal peak in summer, possibly driven by high ammonium loading through internal recycling. External nitrate supply from the dam-water discharge promoted PP during July–August, generating conspicuous blooms near the discharging site. Phytoplankton community was characterized by a predominance of diatoms all year round and seasonal dominances from dinoflagellates, cryptophytes, and prasinophytes in spring to chlorophytes in summer, reflecting spatiotemporal patterns in ammonium and nitrate supply. Our findings provide new insights into the summer phytoplankton bloom linked to monsoonal rainfall in the shallow coastal seas along the Northeast Asian coast.

Assessing the effectiveness of a central flux tower in representing the spatial variations in gross primary productivity in a semi-arid pine forest

Assessing the effectiveness of a central flux tower in representing the spatial variations in gross primary productivity in a semi-arid pine forest

Integrating multiple plant functional traits to predict ecosystem productivity

Quantifying and predicting variation in gross primary productivity (GPP) is important for accurate assessment of the ecosystem carbon budget under global change. Scaling traits to community scales for predicting ecosystem functions (i.e., GPP) remain challenging, while it is promising and well appreciated with the rapid development of trait-based ecology. In this study, we aim to integrate multiple plant traits with the recently developed trait-based productivity (TBP) theory, verify it via Bayesian structural equation modeling (SEM) and complementary independent effect analysis. We further distinguish the relative importance of different traits in explaining the variation in GPP. We apply the TBP theory based on plant community traits to a multi-trait dataset containing more than 13,000 measurements of approximately 2,500 species in Chinese forest and grassland systems. Remarkably, our SEM accurately predicts variation in annual and monthly GPP across China (R2 values of 0.87 and 0.73, respectively). Plant community traits play a key role. This study shows that integrating multiple plant functional traits into the TBP theory strengthens the quantification of ecosystem primary productivity variability and further advances understanding of the trait-productivity relationship. Our findings facilitate integration of the growing plant trait data into future ecological models.

Functional diversity and soil nutrients regulate the interannual variability in gross primary productivity

Abstract Global change, encompassing rising temperatures and an increase in extreme precipitation events, has influenced vegetation photosynthesis; this can be seen in the gross primary productivity (GPP) of terrestrial ecosystems, which, over time affects the global carbon cycle. The impact of climate on interannual variability in GPP (GPPIAV) has been extensively explored in the literature. Other changing factors driven by global change, such as biodiversity and soil nutrient availability, are vital in predicting the future of the biosphere. However, the roles of these factors remain unclear. We combined (i) data from 454 community plots collected using standard protocols from 2013 to 2019 across China, (ii) plant trait data and phylogenetic information of more than 2500 plant species, and (iii) soil nutrient data that we measured. Using these data from 72 “real‐world” ecosystems located across a range of environmental conditions and species pools, we investigated the role of environmental factors including temperature, precipitation and soil nutrients and multifaceted diversity (i.e. species richness, hypervolume‐based functional diversity, and phylogenetic diversity) in mediating the magnitude of GPPIAV using multi‐model averaging and structural equation modelling. We found that soil nutrients and functional diversity are the main determinants of the magnitude of GPPIAV and that climate effects are predominantly mediated by multifaceted diversity. Synthesis. We provide strong evidence that ecosystems with higher biodiversity have less variable annual biomass production and decrease the extent of GPPIAV through compensatory effects across diverse ecosystems. Nutrient‐rich ecosystems are likely to buffer the impact of climate variability on ecosystem carbon uptake better than nutrient‐poor ecosystems. Our results demonstrate that biodiversity plays a crucial role in buffering the effects of environmental variability on carbon uptake in terrestrial ecosystems.

Simulation and Key Physical Drivers of Primary Productivity in a Temperate Lake during the Ice-Covered Period: Based on the VGPM Model

The primary productivity of seasonal ice-covered water bodies is an important variable for understanding how temperate lake ecosystems are changing due to global warming. But there have been few studies on the complete change process of primary productivity during the ice-covered period, and the connection between ice physical and associated biological production has not been fully understood. In this study, a Vertically Generalized Production Model (VGPM) suitable for the ice-covered period was used to calculate the primary productivity of a temperate lake, and the key physical controlling factor was analyzed in the process of primary productivity change in the ice-covered period. The results showed that there was a high level of primary productivity, (189.1 ± 112.6) mg C·m−2·d−1, under the ice in the study site, Hanzhang Lake. The phytoplankton production under the ice was not as severely restricted by light as commonly thought. The water temperature played a more crucial role in the changes of primary productivity than the light beneath the ice. The study highlighted the variability in primary productivity covering the whole ice-covered age, and provided a better understanding of how the aquatic environment of lakes in seasonal ice-covered areas was affected by warmer temperatures.

Across-model spread and shrinking in predicting peatland carbon dynamics under global change.

Large across-model spread in simulating land carbon (C) dynamics has been ubiquitously demonstrated in model intercomparison projects (MIPs), and became a major impediment in advancing climate change prediction. Thus, it is imperative to identify underlying sources of the spread. Here, we used a novel matrix approach to analytically pin down the sources of across-model spread in transient peatland C dynamics in response to a factorial combination of two atmospheric CO2 levels and five temperature levels. We developed a matrix-based MIP by converting the C cycle module of eight land models (i.e., TEM, CENTURY4, DALEC2, TECO, FBDC, CASA, CLM4.5 and ORCHIDEE) into eight matrix models. While the model average of ecosystem C storage was comparable to the measurement, the simulation differed largely among models, mainly due to inter-model difference in baseline C residence time. Models generally overestimated net ecosystem production (NEP), with a large spread that was mainly attributed to inter-model difference in environmental scalar. Based on the sources of spreads identified, we sequentially standardized model parameters to shrink simulated ecosystem C storage and NEP to almost none. Models generally captured the observed negative response of NEP to warming, but differed largely in the magnitude of response, due to differences in baseline C residence time and temperature sensitivity of decomposition. While there was a lack of response of NEP to elevated CO2 (eCO2 ) concentrations in the measurements, simulated NEP responded positively to eCO2 concentrations in most models, due to the positive responses of simulated net primary production. Our study used one case study in Minnesota peatland to demonstrate that the sources of across-model spreads in simulating transient C dynamics can be precisely traced to model structures and parameters, regardless of their complexity, given the protocol that all the matrix models were driven by the same gross primary production and environmental variables.

Quantifying the contributions of climate factors and human activities to variations of net primary productivity in China from 2000 to 2020

Net primary productivity (NPP) plays a vital role in the globe carbon cycle. Quantitative assessment of the effects of climate changes and human activities on net primary productivity dynamics is vital for understanding the driving mechanisms of vegetation change and sustainable development of ecosystems. This study investigates the contributions of climatic factors and human activities to vegetation productivity changes in China from 2000 to 2020 based on the residual trend analysis (RESTREND) method. The results showed that the annual average net primary productivity in China was 325.11 g C/m2/year from 2000 to 2020 and net primary productivity showed a significantly increasing trend (p<0.05) at a rate of 2.32 g C/m2/year. Net primary productivity increased significantly (p<0.05) across 40.90% of China over the study period, while only 1.79% showed a significantly declining trend (p<0.05). The contributions of climatic factors and human activities to net primary productivity increase were 1.169 g C/m2/year and 1.142 g C/m2/year, respectively. Climate factors contributed positively mainly in Sichuan Basin, the Loess Plateau, the Mongolian Plateau, and Northeast China Plain. Positive contributions of human activities to net primary productivity mainly occurred in the Loess Plateau, Central China, and the Greater Khingan Mountains. The effects of climatic factors and human activities on net primary productivity changes varied among sub-regions. In Tropical Monsoon Climate Region and Subtropical Monsoon Climate Region, human activities had greater impacts on net primary productivity increase than climate factors, while climate factors were the dominant factor for net primary productivity recovery in other sub-regions. In addition, during 2000–2020, net primary productivity was dominated by both climate factors and human activities in 49.84% of China, while areas dominated solely by climate factors and human activities accounted for 13.67% and 10.92%, respectively. Compared to changed land cover types, the total net primary productivity as well as the increase of total net primary productivity in China was mostly contributed by unchanged land cover types, which contributed more than 90%.

Cetaceans in the Mediterranean Sea: Encounter Rate, Dominant Species, and Diversity Hotspots

We investigated the presence and diversity of cetaceans in the Mediterranean Sea, analysing the data collected by 32 different research units, over a period of 15 years (2004–2018), and shared on the common web-GIS platform named Intercet. We used the encounter rate, the species prevalence, and the Shannon diversity index as parameters for data analysis. The results show that cetacean diversity, in the context of the Mediterranean basin, is generally quite low when compared with the eastern Atlantic, as few species, namely the striped dolphin, the bottlenose dolphin, the fin whale, and the sperm whale, dominate over all the others. However, some areas, such as the Alboran Sea or the north-western Mediterranean Sea, which includes the Pelagos Sanctuary (the Specially Protected Area of Mediterranean Interest located in the northern portion of the western basin), show higher levels of diversity and should be considered hotspots to be preserved. Primary production and seabed profile seem to be the two main drivers influencing the presence and distribution of cetaceans, with the highest levels of diversity observed in areas characterized by high levels of primary production and high bathymetric variability and gradient. This collective work underlines the importance of data sharing to deepen our knowledge on marine fauna at the scale of the whole Mediterranean Sea and encourages greater efforts in the networking process, also to accomplish the requirements of the Marine Strategy Framework Directive, with particular reference to Descriptor 1: biological diversity is maintained.

A seasonal transition in biological carbon pump efficiency in the northern Scotia Sea, Southern Ocean

The biological carbon pump (BCP) contributes to the oceanic CO2 sink by transferring particulate organic carbon (POC) into the deep ocean. The magnitude and efficiency of the BCP is likely to vary on timescales of days to seasons, however characterising this variability from shipboard observations is challenging. High resolution, sustained observations of primary production and particle fluxes by autonomous vehicles offer the potential to fill this knowledge gap. Here we present a 4 month, daily, 1 m vertical resolution glider dataset, collected in the high productivity bloom, downstream of South Georgia, Southern Ocean. The dataset reveals substantial temporal variability in primary production, POC flux and attenuation. During the pre-bloom peak phase we find high export efficiency, implying minimal heterotrophic POC consumption, i.e. productivity is decoupled from upper ocean remineralisation processes. As the bloom progresses from its peak through its declining phase, export flux decreases, but transfer efficiency within the upper 100 m of the mesopelagic increases. Conversely, transfer efficiency in the lower mesopelagic decreases in the post-bloom phase, implying that the flux attenuation processes operating in the upper and lower mesopelagic are effectively decoupled. This finding underscores an important limitation of using a single parameter, such as Martin's ‘b’, to characterise POC flux attenuation in a given location or season. Frequent pulses of export flux are observed throughout the deployment, indicating decoupling between primary production and the processes driving export of material from the upper ocean. The mechanisms underlying the observed seasonal changes in BCP magnitude and efficiency are unclear, as temperature and oxygen concentration changed minimally, although the nature of the sinking particles changed substantially as the bloom progressed. Our results highlight the difficulty of capturing temporal variability and episodic flux events with traditional shipboard observations, which affects our conceptual understanding of the BCP. The increasing use of autonomous vehicles to observe particle fluxes will be essential to characterising the temporal variability in magnitude and functioning of the BCP.