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Phytoplankton is a diverse group of photosynthetic organisms and accounts for almost half of global primary production. However, most existing marine ecosystem models incorporate limited phytoplankton diversity, overlook phytoplankton evolution, and treat phytoplankton as concentrations instead of particles. Here we present an individual-based phytoplankton model that captures three dimensions of phytoplankton traits (size, temperature, and light affinities) and allows phytoplankton cells to mutate in a one-dimensional (1D) water column. Other components of this ecosystem include dissolved inorganic nitrogen, twenty size classes of zooplankton, and detritus, all modelled as Eulerian fields. This hybrid plankton model can reproduce the general seasonal patterns of nutrients, chlorophyll, and primary production in the subtropical ocean. We expect that this model will be a useful tool for studying phytoplankton physiology, diversity and evolution in the ocean. [ABSTRACT FROM AUTHOR]

Variations in primary production in relation to selected physicochemical and biological parameters of the Oum Er Rbia River estuary were measured monthly from November 2018 to January 2020 at two stations using the clear and dark bottle method. Gross primary production (GPP) ranged from 9.28 to 467.07 mg C/m3/h; net primary production (NPP) ranged from 3.09 to 248.13 mg C/m3/h; and respiration (R) ranged from 4.03 to 262.73 mg C/m3/h. GPP, NPP and R are lowest in summer, increasing to peak in spring. In summer and winter, significantly positive correlations were observed between GPP and NPP on the one hand, and phaeopigments on the other. In summer, there is also a significant positive correlation between respiration and dissolved oxygen concentration. In winter, significant negative correlations were found between conductivity and salinity, on the one hand, and GPP, and in summer and winter, on the other, with NPP. Spatial and seasonal variations in productivity depend on the environmental and meteorological conditions at each station, including water temperature, salinity, conductivity, nutrient inputs and light availability. [ABSTRACT FROM AUTHOR]

Agglomeration economies can bring about positive externalities, while excessive agglomeration backfires. However, existing literature on place‐based policies mainly focuses on policies that enhance agglomeration economies. Few studies discuss dispersion policies coping with the negative externality from excessive agglomeration. Owing to the unclear effects of dispersion policies, we conduct empirical research on the noncapital function relief (NCFR) policy, which is implemented to decrease the agglomeration in Beijing, the capital of China, and promote the development of surrounding areas. Exploiting the difference‐in‐difference model, we find that the NCFR policy implementation significantly facilitates the economic growth of the surrounding areas of Beijing. Changes in the distribution of new firm entry and population are two main channels, while no significant effect on the productivity is found. Furthermore, areas that are less‐developed could benefit more from the NCFR policy. Our findings may enlighten other developing countries in urban economic management. [ABSTRACT FROM AUTHOR]

A natural plankton community from oligotrophic subtropical waters of the Atlantic near Gran Canaria, Spain, was subjected to varying degrees of ocean alkalinity enhancement (OAE) to assess the potential physiological effects, in the context of the application of ocean carbon dioxide removal (CDR) techniques. We employed 8.3 m3 mesocosms with a sediment trap attached to the bottom, creating a gradient in total alkalinity (TA). The lowest point on this gradient was 2400 μmol · L-1, which corresponded to the natural alkalinity of the environment, and the highest point was 4800 μmol · L-1. Over the course of the 33-day experiment, the plankton community exhibited two distinct phases. In phase-I (days 5–20), a notable decline in the photosynthetic efficiency (Fv/Fm) was observed. This change was accompanied by substantial reductions in the abundances of picoeukaryotes, small size nanoeukaryotes (nanoeukaryotes-1), and microplankton. The cell viability of picoeukaryotes, as indicated by fluorescein-di-acetate hydrolysis by cellular esterases (FDA- green fluorescence), slightly increased by the end of phase-I whilst the viability of nanoeukaryotes 1 and Synechococcus spp. did not change. Reactive oxygen species levels (ROS-green fluorescence) showed no significant changes for any of the functional groups. In contrast, in phase-II (days 21–33), a pronounced community response was observed. Increases in Fv/Fm in the intermediate OAE treatments of ∆900 to ∆1800 μmol · L-1 and in chlorophyll-a (Chl-a), chlorophyll-c2 (Chl-c2) , fucoxanthin and divinyl-Chl-a were attributed to the emergence of blooms of large size nanoeukaryotes (nanoeukaryotes-2) from the genera Chrysochromulina , as well as picoeukaryotes. Synechococcus spp. also flourished towards the end of this phase. In parallel, we observed a total 20 % significant change in the metaproteome of the phytoplankton community. This is considered a significant alteration in protein expression, having substantial impacts on cellular functions and the physiology of the organisms. Medium levels of ∆TA showed more upregulated and less downregulated proteins than higher ∆TA treatments. Under these conditions, cell viability significantly increased in pico and nanoeukaryotes-1 in intermediate alkalinity levels, while in Synechococcus spp., nanoeukaryotes-2 and microplankton remained stable. ROS levels did not significantly change in any functional group. The pigment ratios DD+DT : FUCO, and DD+DT : Chl-a increased in medium ∆TA treatments, supporting the idea of nutrient deficiency alleviation and the absence of physiological stress. Taken all data together, this study shows that there is minimal evidence indicating a harmful impact of high alkalinity on the plankton community. The OAE treatments did not result in physiological fitness impairment, thus OAE did not cause cellular stress in the phytoplankton community studied. [ABSTRACT FROM AUTHOR]

Phytoplankton are photosynthetic marine microbes that affect food webs, nutrient cycles and climate regulation. Their roles are determined by correlated phytoplankton functional traits including cell size, chlorophyll content and cellular composition. Here, we explore patterns of evolution in interrelated trait values and correlations. Because both chance events and natural selection contribute to phytoplankton trait evolution, we used population bottlenecks to diversify six genotypes of Thalassiosirid diatoms. We then evolved them as large populations in two environments. Interspecific variation and within-species evolution were visualized for nine traits and their correlations using reduced axes (a trait-scape). Our main findings are that shifts in trait values resulted in movement of evolving populations within the trait-scape in both environments, but were more frequent when large populations evolved in a novel environment. Which trait relationships evolved was population-specific, but greater departures from ancestral trait correlations were associated with lower population growth rates. There was no single master trait that could be used to understand multi-trait evolution. Instead, repeatable multi-trait evolution occurred along a major axis of variation defined by several diatom traits and trait relationships. Because trait-scapes capture changes in trait relationships and values together, they offer an insightful way to study multi-trait variation. [ABSTRACT FROM AUTHOR]

The Bay of Bengal (BoB) spans >2.2 million km2 in the northeastern Indian Ocean and is bordered by dense populations that depend upon its resources. Over recent decades, a shift from larger phytoplankton to picoplankton has been reported, yet the abundance, activity, and composition of primary producer communities are not well‐characterized. We analysed the BoB regions during the summer monsoon. Prochlorococcus ranged up to 3.14 × 105 cells mL−1 in the surface mixed layer, averaging 1.74 ± 0.46 × 105 in the upper 10 m and consistently higher than Synechococcus and eukaryotic phytoplankton. V1‐V2 rRNA gene amplicon analyses showed the High Light II (HLII) ecotype formed 98 ± 1% of Prochlorococcus amplicons in surface waters, comprising six oligotypes, with the dominant oligotype accounting for 65 ± 4% of HLII. Diel sampling of a coherent water mass demonstrated evening onset of cell division and rapid Prochlorococcus growth between 1.5 and 3.1 div day−1, based on cell cycle analysis, as confirmed by abundance‐based estimates of 2.1 div day−1. Accumulation of Prochlorococcus produced by ultradian growth was restricted by high loss rates. Alongside prior Arabian Sea and tropical Atlantic rates, our results indicate Prochlorococcus growth rates should be reevaluated with greater attention to latitudinal zones and influences on contributions to global primary production. [ABSTRACT FROM AUTHOR]

Tropospheric ozone significantly damages vegetation and reduces net primary productivity (NPP). We developed a stable linear NPP response model based on accumulated ozone exposure over a threshold of 40 parts per billion (ppb) (AOT40). We then estimated the effects of regional ozone damage on NPP for different vegetation types. The study suggests an average decrease in NPP of 24.7% due to ozone pollution in the North China Plain, similar to previous estimates ranging from 10.1% to 24.7%, with a maximum reduction exceeding 200 [g C m‐2 yr‐1] and more than 50%. Vegetation types such as broadleaf forests, needleleaf forest, crops, and grasses showed significant NPP decreases of 47.1%, 37.8%, 36.7%, and 44.6%, respectively. Declining NPP also had negative impacts on several Chinese crop species. Our work highlights the need for urgent and effective action to mitigate ozone pollution's substantial detrimental effects on ecosystem health and productivity. Plain Language Summary: Ozone pollution led to an average 25% decrease in net primary productivity in the North China Plain. This decline is consistent with previous estimates that ranged from 10% to 25%. Productivity of forest trees, crops, and grasses declined significantly, ranging from 36.7% to 47.1%. These results have implications for Chinese crops, as lower crop productivity can negatively affect crop yields. Our study highlights the urgent need for action to mitigate the detrimental effects of ozone pollution on ecosystem health and productivity. Key Points: We developed a stable model to estimate ozone impact on the productivity of plants'Ozone pollution resulted in an average decline in productivity of 25% per year in all ecosystem types in the North China Plain regionOzone pollution led to net primary productivity declines in forest, crops, and grasses, with reductions ranging from 36.7% to 47.1% [ABSTRACT FROM AUTHOR]

Nanoparticle pollution has been shown to affect various organisms. However, the effects of nanoparticles on species interactions, and the role of species traits, such as body size, in modulating these effects, are not well‐understood. We addressed this issue using competing freshwater phytoplankton species exposed to copper oxide nanoparticles. Increasing nanoparticle concentration resulted in decreased phytoplankton species growth rates and community productivity (both abundance and biomass). Importantly, we consistently found that nanoparticles had greater negative effects on species with smaller cell sizes, such that nanoparticle pollution weakened the competitive dominance of smaller species and promoted species diversity. Moreover, nanoparticles reduced the growth rate differences and competitive ability differences of competing species, while having little effect on species niche differences. Consequently, nanoparticle pollution reduced the selection effect on phytoplankton community abundance, but increased the selection effect on community biomass. Our results suggest cell size as a key functional trait to consider when predicting phytoplankton community structure and ecosystem functioning in the face of increasing nanopollution. [ABSTRACT FROM AUTHOR]

Transpiration (T) represents plant water use, while sun-induced chlorophyll fluorescence (SIF) emitted during photosynthesis, relates well to gross primary production. SIF can be influenced by vegetation structure, while uncertainties remain on how this might impact the relationship between SIF and T, especially for open and sparse woodlands. In this study, a method was developed to map T in riverine floodplain open woodland environments using satellite data coupled with a radiative transfer model (RTM). Specifically, we used FluorFLiES, a three-dimensional SIF RTM, to simulate the full spectrum of SIF for three open woodland sites with varying fractional vegetation cover. Five specific SIF bands were selected to quantify their correlation with field measured T derived from sap flow sensors. The coefficient of determination of the simulated far-red SIF and field measured T at a monthly scale was 0.93. However, when comparing red SIF from leaf scale to canopy scale to predict T, performance declined by 24%. In addition, varying soil reflectance and understory leaf area index had little effect on the correlation between SIF and T. The method developed can be applied regionally to predict tree water use using remotely sensed SIF datasets in areas of low data availability or accessibility. [ABSTRACT FROM AUTHOR]

India is the second-highest contributor to the post-2000 global greening. However, with satellite data, here we show that this 18.51% increase in Leaf Area Index (LAI) during 2001–2019 fails to translate into increased carbon uptake due to warming constraints. Our analysis further shows 6.19% decrease in Net Primary Productivity (NPP) during 2001–2019 over the temporally consistent forests in India despite 6.75% increase in LAI. We identify hotspots of statistically significant decreasing trends in NPP over the key forested regions of Northeast India, Peninsular India, and the Western Ghats. Together, these areas contribute to more than 31% of the NPP of India (1274.8 TgC.year−1). These three regions are also the warming hotspots in India. Granger Causality analysis confirms that temperature causes the changes in net-photosynthesis of vegetation. Decreasing photosynthesis and stable respiration, above a threshold temperature, over these regions, as seen in observations, are the key reasons behind the declining NPP. Our analysis shows that warming has already started affecting carbon uptake in Indian forests and calls for improved climate resilient forest management practices in a warming world. [ABSTRACT FROM AUTHOR]

Aims: Plants and soils are key factors in maintaining ecosystem multifunctionality (EMF). Yet, it remains unclear how climate factors regulate the EMF through soil properties and plant diversity of different plant functional groups in primary dark coniferous forests of subalpine regions. Methods: Nine functional indicators related to carbon, nitrogen, phosphorus cycling and plant productivity, four leaf functional traits, mean annual precipitation (MAP) and mean annual temperature (MAT) were collected from 50 primary dark coniferous forests in ten sites on the eastern Qinghai-Tibetan Plateau. The EMF was calculated using two approaches. The averaging approach involves converting and averaging the functional indicators, and the multiple threshold approach quantifies the number of functions across different thresholds. Results: MAP promoted EMF. Soil water content and shrub species richness had a significant positive effect on EMF, whereas herb species richness had a negative effect. Functional diversity and specific leaf area of tree species rather than richness had a significant positive effect on EMF, indicating the increase in functional traits was beneficial to EMF. Climatic factors could directly or indirectly affect EMF through species richness, functional diversity, and soil abiotic factors. Conclusions: The effects of species richness on EMF varied among different plant functional groups, possibly related to different mechanisms, and highlighted the role of functional diversity in maintaining EMF. Spatial variation in climate could modify soil properties and plant diversity, further affecting EMF in primary dark coniferous forests. Hence, these findings should be considered in future predictions of how a changing climate could affect EMF. [ABSTRACT FROM AUTHOR]

Defoliation, often induced by herbivores, and soil microbiomes are recognized as key drivers of plant diversity and productivity in grasslands. However, lack of experiments simultaneously manipulating defoliation and soil microbial diversity has constrained our understanding of how these two factors interactively influence both above‐ground and below‐ground net primary productivity (ANPP and BNPP).We employed a soil filtering approach to create the gradient of soil microbial diversity and removal of above‐ground biomass by clipping to simulate defoliation effect from herbivores. Our goal was to investigate how soil microbial diversity affected both ANPP and BNPP under the stress of defoliation.We found that defoliation and soil microbial diversity loss decreased the ANPP and BNPP of the plant community, and Medicago falcata (legume) was more responsive to these treatments than Leymus chinensis (grass) and Artemisia frigida (forb). ANPP was positively correlated with soil microbial richness only when plants suffered defoliation. By contrast, BNPP showed a closer relationship with soil fungal richness than bacteria, and defoliation enhanced this relationship. The structural equation model (SEM) showed that defoliation indirectly regulated ANPP by affecting plant P content, while soil bacterial diversity loss decreased the ANPP through altering plant P and fungal diversity loss directly decreased BNPP. The LEfSe and linear regression analysis revealed that the biomarkers of bacteria (e.g. Actinobacteria, Xanthobacteraceae) and fungi (e.g. Ascomycota, Glomerales) significantly contributed to the variation of ANPP and BNPP under defoliation treatment respectively. Defoliation enhanced phosphorus acquisition by soil microorganisms, further strengthening the microbial regulation of plant productivity.Overall, we provide novel insights on how defoliation enhances the positive effects of soil microbial diversity on above‐ and below‐ground net primary productivity. Our findings highlight that soil microorganisms associated with phosphorus cycling are mobilized to play a more active role in promoting productivity after defoliation. It may provide a new perspective on how to better utilize the role of soil microorganisms in grazed or managed grasslands. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

Marine algae are central to global carbon fixation, and their productivity is dictated largely by resource availability. Reduced nutrient availability is predicted for vast oceanic regions as an outcome of climate change; however, there is much to learn regarding response mechanisms of the tiny picoplankton that thrive in these environments, especially eukaryotic phytoplankton. Here, we investigate responses of the picoeukaryote Micromonas commoda , a green alga found throughout subtropical and tropical oceans. Under shifting phosphate availability scenarios, transcriptomic analyses revealed altered expression of transfer RNA modification enzymes and biased codon usage of transcripts more abundant during phosphate-limiting versus phosphate-replete conditions, consistent with the role of transfer RNA modifications in regulating codon recognition. To associate the observed shift in the expression of the transfer RNA modification enzyme complement with the transfer RNAs encoded by M. commoda , we also determined the transfer RNA repertoire of this alga revealing potential targets of the modification enzymes. Codon usage bias was particularly pronounced in transcripts encoding proteins with direct roles in managing phosphate limitation and photosystem-associated proteins that have ill-characterized putative functions in "light stress." The observed codon usage bias corresponds to a proposed stress response mechanism in which the interplay between stress-induced changes in transfer RNA modifications and skewed codon usage in certain essential response genes drives preferential translation of the encoded proteins. Collectively, we expose a potential underlying mechanism for achieving growth under enhanced nutrient limitation that extends beyond the catalog of up- or downregulated protein-encoding genes to the cell biological controls that underpin acclimation to changing environmental conditions. [ABSTRACT FROM AUTHOR]

In order to improve the understanding of the environmental impacts of polymetallic nodule mining, ecotoxicological studies were conducted on the growth of model phytoplankton species Skeletonema costatum and Prorocentrum donghaiense using cobalt and nickel. This study evaluated various physiological and ecological indicators, such as cell proliferation, chlorophyll a, pigments, total protein, and antioxidant enzyme markers. The results show that the introduction of low amounts of cobalt or nickel increased the growth rate of phytoplankton. The phytoplankton benefited from low concentrations of cobalt and nickel stress. The increased protein levels and decreased activity of antioxidant enzymes considerably impacted physiological responses during the promotion of cell abundance. High concentrations of cobalt or nickel resulted in decreased light-absorbing pigments, increased photoprotective pigments, an inactive chlorophyll content, decreased total proteins, and maximal antioxidant enzyme activity in phytoplankton. Throughout the experiment, both the phytoplankton protein and enzyme activity declined with prolonged stress, and the cells underwent age-induced damage. Thus, seabed mining's repercussions on phytoplankton could result in both short-term growth promotion and long-term damage. These consequences depend on the impurity concentrations infiltrating the water, their duration, and the organism's physiological responses. [ABSTRACT FROM AUTHOR]

Inspired by grassland biodiversity experiments studying the impact of plant diversity on primary productivity, the Crop Diversity Experiment setup in 2018 aimed at testing whether these biodiversity benefits also hold for annual crop systems and whether crop mixtures also achieved transgressive overyielding, i.e. yield in mixture that was higher than the most productive monoculture. The first 3 years of the experiment demonstrated that crop mixtures do not only increase yield compared with an average monoculture but often also compared with the highest yielding monoculture. The crop diversity effects were stronger under more stressful environmental conditions and were often achieved in mixtures with legume crops. However, we observed transgressive overyielding also under favorable conditions and in mixtures without legumes. With our investigation of the underlying mechanisms of the yield benefits we found both direct complementarities between crop species and indirect effects via other organisms. The former included chemical, spatial and temporal complementarity in N uptake, complementary root distribution leading to complementary water uptake, as well as spatial and temporal complementarity in light use. Among the indirect mechanisms we identified complementary suppression of weeds and more abundant plant growth-promoting microbes in crop mixtures, apart from complementarity in pest and disease suppression not yet studied in the Crop Diversity Experiment but demonstrated elsewhere. In consequence, the Crop Diversity Experiment supports not only the assumption that the ecological processes identified in biodiversity experiments also hold in crop systems, but that diversification of arable crop systems provides a valuable tool to sustainably produce food. [ABSTRACT FROM AUTHOR]

Recently, light use efficiency (LUE) models driven by remote sensing data have been widely employed to estimate the gross primary productivity (GPP) of different terrestrial ecosystems at global or regional scales. Furthermore, the two-leaf light use efficiency (TL-LUE) model has been reported to improve the accuracy of GPP estimation, relative to the big-leaf MOD17 model, by separating the entire canopy into sunlit and shaded leaves through the use of constant clumping index estimation (Ω). However, ignoring obvious seasonal changes in the vegetation clumping index (CI) most likely results in GPP estimation errors since the CI tends to present seasonal changes, especially with respect to the obvious presence or absence of leaves within the canopy of deciduous vegetation. Here, we propose a TL-CLUE model that considers the seasonal difference in the CI based on the TL-LUE model to characterize general changes in canopy seasonality. This method composites monthly CI values into two or three Ω values to capture the general seasonal changes in CI while attempting to reduce the potential uncertainty caused during CI inversion. In theory, CI seasonality plays an essential role in the distribution of photosynthetically active radiation absorbed by the canopy (APAR). Specifically, the seasonal difference in CI values mainly considers the state of leaf growth, which is determined by the MODIS land surface phenology (LSP) product (MCD12Q2). Therefore, the one-year cycle (OYC) of leaf life is divided into two (leaf-off and leaf-on) or three seasons (leaf-off, leaf-scattering, and leaf-gathering) according to this MODIS LSP product, and the mean CI of each corresponding season for each vegetation class is computed to smoothen the uncertainties within each seasonal section. With these two or three seasonal Ω values as inputs, the TL-CLUE model by which the seasonal differences in CI are incorporated into the TL-LUE model is run and evaluated based on observations from 84 eddy covariance (EC) tower sites across North America. The results of the analysis reveal that the TL-LUE model widely overestimates GPP for most vegetation types during the leaf-on season, particularly during the growth peak. Although the TL-LUE model shows that the temporal characteristics of GPP agree with the EC observations in terms of general trends, the TL-CLUE model further improves the accuracy of GPP estimation by considering the seasonal changes in the CI. The result of GPP estimation from the TL-CLUE model shows a lower error (RMSE = 2.46 g C m−2 d−1) than the TL-LUE model (RMSE = 2.75 g C m−2 d−1) and somewhat decreases the eight-day GPP overestimation in the TL-LUE model with a constant Ω by approximately 9.76 and 8.970% when adapting three and two Ωs from different seasons, respectively. The study demonstrates that the uncertainty of seasonal disturbance in the CI, quantified by a standard deviation of approximately 0.071 relative to the mean CI of 0.746, is diminished through simple averaging. The seasonal difference in CI should be considered in GPP estimation of terrestrial ecosystems, particularly for vegetation with obvious canopy changes, where leaves go through the complete physiological processes of germination, stretching, maturity, and falling within a year. This study demonstrates the potential of the MODIS CI application in developing ecosystem and hydrological models. [ABSTRACT FROM AUTHOR]

Ocean warming is associated with a decline in the global oxygen (O2) inventory, but the ratio of O2 loss to heat gain is poorly understood. We analyzed historical variability in temperature (T), O2, and nitrate NO3− $\left(\mathrm{N}{\mathrm{O}}_{3}^{-}\right)$ in hydrographic observations and model simulations of the North Atlantic, a relatively well‐sampled region that is important for deep ocean ventilation. Multidecadal fluctuations of O2 concentrations in subpolar thermocline waters (100–700 m) are correlated with changes in their heat content, with a slope 35% steeper than that expected from thermal solubility. Variations of O2 in excess of the solubility effect are correlated with observed decadal changes in NO3− $\mathrm{N}{\mathrm{O}}_{3}^{-}$ in the surface layer (0–50 m), which declines by ∼1 mmol N m−3 per degree of temperature anomaly. Enhanced biologically mediated drawdown of nutrients from the photic zone and associated respiration in deeper water account for the additional depletion of thermocline O2 during warm years. In model simulations, increased nutrient consumption in warm periods is driven by an early start of the phytoplankton growing season and faster phytoplankton growth rates at higher temperatures. Our results highlight a role for phytoplankton T‐dependent growth rates in amplifying ocean O2 loss. Key Points: Historical changes in observed and simulated O2 of the North Atlantic thermocline are 35% stronger than expected from thermal solubilitySurface nutrient drawdown and resulting subsurface respiration account for the additional O2 depletion during warm periodsEarlier spring blooms and faster plankton growth in warm periods allow surface biota to amplify deep ocean O2 loss [ABSTRACT FROM AUTHOR]

The gross primary production (GPP) of the terrestrial biosphere is a key source of variability in the global carbon cycle. It is modulated by hydrometeorological drivers (i.e. short-wave radiation, air temperature, vapour pressure deficit and soil moisture) and the vegetation state (i.e. canopy greenness, leaf area index) at instantaneous to interannual timescales. In this study, we set out to evaluate the ability of GPP models to capture this variability. Eleven models were considered, which rely purely on remote sensing data (RS-driven), meteorological data (meteo-driven, e.g. dynamic global vegetation models; DGVMs) or a combination of both (hybrid, e.g. light-use efficiency, LUE, models). They were evaluated using in situ observations at 61 eddy covariance sites, covering a broad range of herbaceous and forest biomes. The results illustrated how the determinant of temporal variability shifts from meteorological variables at sub-seasonal timescales to biophysical variables at seasonal and interannual timescales. RS-driven models lacked the sensitivity to the dominant drivers at short timescales (i.e. short-wave radiation and vapour pressure deficit) and failed to capture the decoupling of photosynthesis and canopy greenness (e.g. in evergreen forests). Conversely, meteo-driven models accurately captured the variability across timescales, despite the challenges in the prognostic simulation of the vegetation state. The largest errors were found in water-limited sites, where the accuracy of the soil moisture dynamics determines the quality of the GPP estimates. In arid herbaceous sites, canopy greenness and photosynthesis were more tightly coupled, resulting in improved results with RS-driven models. Hybrid models capitalized on the combination of RS observations and meteorological information. LUE models were among the most accurate models to monitor GPP across all biomes, despite their simple architecture. Overall, we conclude that the combination of meteorological drivers and remote sensing observations is required to yield an accurate reproduction of the spatio-temporal variability of GPP. To further advance the performance of DGVMs, improvements in the soil moisture dynamics and vegetation evolution are needed. [ABSTRACT FROM AUTHOR]

While numerous studies report shifts in vegetation phenology, in this regard eddy covariance (EC) data, despite its continuous high-frequency observations, still requires further exploration. Furthermore, there is no general consensus on optimal methodologies for data smoothing and extracting phenological transition dates (PTDs). Here, we revisit existing methodologies and present new prospects to investigate phenological changes in gross primary productivity (GPP) from EC measurements. First, we present a smoothing technique of GPP time series through the derivative of its smoothed annual cumulative sum. Second, we calculate PTDs and their trends from a commonly used threshold method that identifies days with a fixed percentage of the annual maximum GPP. A systematic analysis is performed for various thresholds ranging from 0.1 to 0.7. Lastly, we examine the relation of PTDs trends to trends in GPP across the years on a weekly basis. Results from 47 EC sites with long time series (> 10 years) show that advancing trends in start of season (SOS) are strongest at lower thresholds but for the end of season (EOS) at higher thresholds. Moreover, the trends are variable at different thresholds for individual vegetation types and individual sites, outlining reasonable concerns on using a single threshold value. Relationship of trends in PTDs and weekly GPP reveal association of advanced SOS and delayed EOS to increase in immediate primary productivity, but not to the trends in overall seasonal productivity. Drawing on these analyses, we emphasise on abstaining from subjective choices and investigating relationship of PTDs trend to finer temporal trends of GPP. Our study examines existing methodological challenges and presents approaches that optimize the use of EC data in identifying vegetation phenological changes and their relation to carbon uptake. [ABSTRACT FROM AUTHOR]

Marine viruses are a major driver of phytoplankton mortality and thereby influence biogeochemical cycling of carbon and other nutrients. Phytoplankton-targeting viruses are important components of ecosystem dynamics, but broad-scale experimental investigations of host-virus interactions remain scarce. Here, we investigated in detail a picophytoplankton (size 1 µm) host's responses to infections by species-specific viruses from distinct geographical regions and different sampling seasons. Specifically, we used Ostreococcus tauri and O. mediterraneus and their viruses (size ca. 100 nm). Ostreococcus sp. is globally distributed and, like other picoplankton species, play an important role in coastal ecosystems at certain times of the year. Further, Ostreococcus sp. is a model organism, and the Ostreococcus-virus system is well-known in marine biology. However, only few studies have researched its evolutionary biology and the implications thereof for ecosystem dynamics. The Ostreococcus strains used here stem from different regions of the Southwestern Baltic Sea that vary in salinity and temperature and were obtained during several cruises spanning different sampling seasons. Using an experimental cross-infection set-up, we explicitly confirm species and strain specificity in Ostreococcus sp. from the Baltic Sea. Moreover, we found that the timing of virus-host co-existence was a driver of infection patterns as well. In combination, these findings prove that host-virus co-evolution can be rapid in natural systems. [ABSTRACT FROM AUTHOR]

As a phytotoxic pollutant, surface ozone (O3) not only affects plant physiology but also influences meteorological fields and air quality by altering leaf stomatal functions. Previous studies revealed strong feedbacks of O3-vegetation coupling in China but with large uncertainties due to the applications of varied O3 damage schemes and chemistry-vegetation models. In this study, we quantify the O3 vegetation damage and the consequent feedbacks to surface meteorology and air quality in China by coupling two O3 damage schemes (S2007 vs. L2013) into a fully coupled regional meteorology-chemistry model. With different schemes and damaging sensitivities, surface O3 is predicted to decrease summertime gross primary productivity by 5.5 %–21.4 % and transpiration by 5.4 %–23.2 % in China, in which the L2013 scheme yields 2.5–4 times of losses relative to the S2007 scheme. The damages to photosynthesis of sunlit leaves are ~2.6 times that of shaded leaves in the S2007 scheme but show limited differences in the L2013 scheme. Though with large discrepancies in offline responses, the two schemes yield similar magnitude of feedback to surface meteorology and O3 air quality. The O3-induced damage to transpiration increases national sensible heat by 3.2–6.0 W m-2 (8.9 % to 16.2 %) while reduces latent heat by 3.3–6.4 W m-2 (-5.6 % to -17.4 %), leading to a 0.2–0.51 °C increase in surface air temperature and a 2.2–3.9 % reduction in relative humidity. Meanwhile, surface O3 concentrations on average increase by 1.3–3.3 μg m-3 due to the inhibitions of stomatal uptake and the anomalous enhancement in isoprene emissions, the latter of which is attributed to the surface warming by O3-vegetaion coupling. Our results highlight the importance of O3 control in China due to its adverse effects on ecosystem functions, deterioration of global warming, and exacerbation of O3 pollution through the O3-vegetation coupling. [ABSTRACT FROM AUTHOR]

Low bioavailability of the vital element iron (Fe) limits primary production in large regions of the Southern Ocean, thus impacting phytoplankton community structures. Primary productivity seems to be particularly sensitive to the reduced form of iron (Fe(II)), which is thought to be the most readily bioavailable redox form of Fe in the ocean. Here, we investigated the impact of temperature (3 °C, 5 °C and 7 °C) and Fe(II) additions (+ 5 nM) on growth of two Southern Ocean phytoplankton species Fragilariopsis cylindrus and Phaeocystis antarctica in coastal and open ocean water. At all tested temperatures, growth rates of P. antarctica were significantly higher with added iron, compared to the treatments without added iron in both waters. Temperature only had a significant effect on the growth rate of this species when it was raised to 7 °C in all treatments. For F. cylindrus, growth rates only significantly increased with iron addition at 7 °C in both water types. Temperature did not affect the growth rate of F. cylindrus except for a significant reduction without iron addition at 7 °C in coastal water. These results highlight the complex interactions between Fe bioavailability and temperature on Southern Ocean phytoplankton growth. Thus, certain Southern Ocean phytoplankton species may have higher growth rates in regions of the ocean that will warm the most and possibly experience greater Fe supply under future climate conditions, such as coastal regions. This may result in changes in phytoplankton community structures with implications for carbon sequestration efficiency under future climate conditions. [ABSTRACT FROM AUTHOR]

1.Freshwater ecosystems are being exposed to increasing salinisation, often because of pollution from road deicing salts, which is becoming more widely acknowledged. To address this issue, municipalities are turning towards the sodium salt alternatives of CaCl2 and MgCl2, which are marketed as being safer for the environment. However, research into the actual safety of these salts on aquatic plants is lacking.2.We investigated the effects of the most common road salt (NaCl) and two alternatives (MgCl2 and CaCl2) on the productivity of a common freshwater plant (i.e., Elodea canadensis) under three salt concentrations (control, 250, and 1,000 mg Cl−/L). Light‐bottle/dark‐bottle trials were performed to quantify net primary productivity, respiration, and gross primary productivity. These responses were tracked over time (1 vs. 3 weeks) to assess plant acclimation and lag effects under different levels of the three salts.3.We discovered that NaCl and CaCl2 altered these measures of plant metabolism, but MgCl2 had no effects. We also observed instances of acclimation (i.e. salt effects after 1 week that disappeared after 3 weeks) and lag effects (i.e. no salt effect after 1 week, but salt effects after 3 weeks). These impacts are likely to be the results of plant responses to salt at the cell and molecular levels, including short‐ and long‐term changes in photosynthetic pigments. Therefore, the plant responses were salt‐specific, with instances of plant acclimation and lag effects.4.This appears to be the first study of net primary productivity, respiration, and gross primary productivity in freshwater plants across a range of different salts, and it highlights how freshwater salinisation can have substantial effects on plant productivity. These effects will probably have an impact on the growth of macrophytes, which play key ecological roles in aquatic ecosystems. [ABSTRACT FROM AUTHOR]

Mesoscale eddies are common in the subtropical Northwest Pacific, however, relatively little is known about their spatial variability and temporal evolution, and how these impact upper ocean biogeochemistry. Here we investigate these using observations of a cyclonic eddy carried out along four sequential transects. Consistent with previous observations of cyclonic eddies, the eddy core had doming isopycnals, bringing elevated nutrient waters nearer to the surface. However, we also found that the upper layer of the eddy above the nutricline had significantly lower phosphate concentrations within its core relative to its edge. We attributed this to elevated N2 fixation within the eddy core, which was likely driven by enhanced subsurface iron supply, ultimately resulting in increased phosphate consumption. Eddy‐enhanced N2 fixation was additionally supported by the elevation of nitrate + nitrite to phosphate ratios below the euphotic zone. Moreover, we observed that while the upward displacement of isopycnals within the eddy core led to an increase in phytoplankton biomass in the lower euphotic zone, there was no significant increase in total phytoplankton biomass across the entire euphotic zone. Cyclonic eddies in the subtropical North Pacific are projected to be becoming more frequent, implying that such dynamics could become increasingly important for regulating nutrient biogeochemistry and ultimately productivity of the region. Plain Language Summary: Cyclonic eddies are oceanographic features leading to upward transfer of deep‐water nutrients that support phytoplankton growth in the sunlit surface ocean. In the low‐nutrient Northwest Pacific, cyclonic eddies are considered to be an extremely important nutrient source in alleviating nutrient limitation; however, their biogeochemical effects are not well‐examined, in particular in the upper layers where nutrients are below the detection limit of conventional techniques. By examining a cyclonic eddy with four sequential transect observations, our results showed that the eddy core had higher nutrient concentrations in the lower euphotic zone compared to the eddy edge, consistent with previous studies; in contrast, concentrations of phosphate in the upper surface layer had significantly lower values within the core relative to those at the edge. Surface rate measurements suggested that this lower phosphate was potentially driven by elevated N2 fixation, likely due to enhanced iron supply from depth, thereby resulting in additional consumption of excess surface phosphate. However, this increased nutrient supply did not lead to the enhancement of total phytoplankton biomass across the entire euphotic zone. Key Points: Lower phosphate concentrations were observed above the nutricline within the eddy core in comparison to the edgeEnhanced N2 fixation within the eddy core is proposed to have driven increased phosphate consumptionNo substantial total phytoplankton biomass increase was found within the eddy core [ABSTRACT FROM AUTHOR]

Land use and land cover change (LULCC) represents a key process of human‐Earth system interaction and has profound impacts on terrestrial ecosystem carbon cycling. As a key input for ecosystem models, future gridded LULCC data is typically spatially downscaled from regional LULCC projections by integrated assessment models, such as the Global Change Analysis Model (GCAM). The uncertainty associated with the different spatial downscaling methods and its impacts on the subsequent model projections have been historically ignored and rarely examined. This study investigated this problem using two representative spatial downscaling methods and focused on their impacts on the carbon cycle over the Arctic‐Boreal Vulnerability Experiment (ABoVE) domain, where extensive LULCC is expected. Specifically, we used the Future Land Use Simulation model (FLUS) and the Demeter model to generate 0.25° gridded LULCC data (i.e., LULCCFLUS and LULCCDemeter, respectively) with the same input of regional LULCC projections from GCAM, under both the low (i.e., SSP126) and high (i.e., SSP585) greenhouse gas emission scenarios. The two sets of downscaled LULCC were used to drive the Community Land Model version 5 and prognostically simulate the terrestrial carbon cycle dynamics over the 21st century. The results suggest large spatial‐temporal differences between LULCCFLUS and LULCCDemeter, and the spatial distributions of the needleleaf evergreen boreal tree, broadleaf deciduous boreal tree, broadleaf deciduous boreal shrub, and C3 arctic grass are particularly different under both SSP126 and SSP585. Additionally, the spatiotemporal differences are larger under SSP126 than SSP585, due to more intensive LULCC under SSP126 than SSP585 from GCAM projection. The differences in LULCC further lead to large discrepancies in the spatial patterns of projected gross primary productivity, ecosystem respiration, and net ecosystem exchange, which represent more than 79% of the contributions of future LULCC in 2100. Additionally, the difference in carbon flux under SSP126 is generally larger than those under SSP585. This study highlights the importance of considering the uncertainties induced by the spatial downscaling process in future LULCC projections and carbon cycle simulations. Plain Language Summary: Land use and land cover change (LULCC) affects the carbon cycle in ecosystems. To predict future LULCC and carbon cycle changes, scientists use spatial downscaling methods to create detailed LULCC maps. However, different methods can lead to different results and can impact carbon cycle projections. Our study found that using different spatial downscaling methods can contribute to a large portion of the uncertainty in future projections of LULCC and carbon cycle over the Arctic‐Boreal region. It is important to consider these uncertainties when studying future changes in land use and carbon cycle. Key Points: We identified a traditionally ignored source of uncertainty in model projected carbon cycle from the future land use and land cover change (LULCC) dataSpatial downscaling is a necessary step for generating gridded LULCC data, but different downscaling methods may lead to results with large spatial differencesThe impacts of using different spatial downscaling methods are more than 79% of the contributions of future LULCC to carbon cycle projections in 2100 [ABSTRACT FROM AUTHOR]

The article presents the discussion on PAR estimates indicate that a variety of physiological and ecological conditions can control the onset of spring blooms. Topics include satellite observations have started to report optimal light intensities for phytoplankton blooming in various physiological and ecological environments; and investigating the optimal light intensities required for phytoplankton spring bloom development in the East Sea (ES).

Ocean production and trophic transfer rates, including Net Community Production (NCP), Net Primary Production (NPP), Gross Oxygen Production (GOP), and microzooplankton grazing rates are key metrics for understanding marine ecosystem dynamics and impacts on biogeochemical cycles. Because of its temperate location and high dynamic range of environmental conditions and long-term human utilization, the long-term ecological research site in the coastal Northeastern U.S. Shelf (NES) of the Northwestern Atlantic Ocean offers an ideal opportunity to understand how productivity shifts in response to changes in planktonic community composition. While small phytoplankton usually dominate in the NES waters during the summer, a bloom of the large diatom genus Hemiaulus, with N2 fixing symbionts, was observed in the mid-shelf region during the summer of 2019. NCP was 2.5 to 9 times higher when Hemiaulus dominated compared to NCP throughout the same geographic area during the summers of 2020--2022. The Hemiaulus bloom in summer 2019 also coincided with higher trophic transfer efficiency from phytoplankton to microzooplankton, higher GOP and NPP, and higher sea surface temperatures than summers 2020-2022. This study shows that the presence of an atypical phytoplankton community that alters the typical size distribution of the primary producers can greatly influence productivity and trophic transfer, highlighting the dynamic nature of the coastal ocean. Notably, summer 2018 NCP levels were also high although no atypical phytoplankton community was present. A better understanding of the dynamics of the NES in terms of biological productivity is of primary importance, especially in the context of changing environmental conditions due to climate processes. [ABSTRACT FROM AUTHOR]

The Silk Road Economic Belt and the 21st Century Maritime Silk Road Initiative (BRI) proposed in 2013 by China has greatly accelerated the social and economic development of the countries along the Belt and Road (B&R) region. However, the international community has questioned its impact on the ecological environment and a comprehensive assessment of ecosystem quality changes is lacking. Therefore, this study proposes an objective and automatic method to assess ecosystem quality and analyzes the spatiotemporal changes in the B&R region. First, an ecosystem quality index (EQI) is established by integrating the vegetation status derived from three remote sensing ecological parameters including the leaf area index, fractional vegetation cover and gross primary productivity. Then, the EQI values are automatically categorized into five ecosystem quality levels including excellent, good, moderate, low and poor to illustrate their spatiotemporal changes from the years 2016 to 2020. The results indicate that the spatial distributions of the EQIs across the B&R region exhibited similar patterns in the years 2016 and 2020. The regions with excellent levels accounted for the lowest proportion of less than 12%, while regions with moderate, low and poor levels accounted for more than 68% of the study area. Moreover, based on the EQI pattern analysis between the years 2016 and 2020, the regions with no significant EQI change accounted for up to 99.33% and approximately 0.45% experienced a significantly decreased EQI. Therefore, this study indicates that the ecosystem quality of the B&R region was relatively poor and experienced no significant change in the five years after the implementation of the "Vision and Action to Promote the Joint Construction of the Silk Road Economic Belt and the 21st Century Maritime Silk Road". This study can provide useful information for decision support on the future ecological environment management and sustainable development of the B&R region. [ABSTRACT FROM AUTHOR]

Like many top consumers, parasites can regulate feeding of their prey via trait‐mediated means. If parasites modify the feeding behavior of ecologically important grazers, they may have cascading effects on the structure and functioning of whole plant communities. The extent to which parasites can influence plant communities in this way is largely dependent on the strength of their behavioral alteration, their prevalence in host grazers, and the density of those hosts. Recent experiments and comparative surveys in southeastern USA salt marshes revealed that common larval trematode parasites suppress the per capita grazing impacts of the marsh periwinkle Littoraria irrorata, generating a trophic cascade that protects foundational marsh plants from drought‐associated overgrazing. Here, we conducted a field manipulation wherein we modified grazer host density while holding infection prevalence constant at an ecologically relevant level (20%) to determine whether the indirect, facilitative effects of parasites on marsh plants varied with the density of grazers. We found that parasites had significant positive impacts on marsh net primary productivity at moderate densities of snails (≥50 snails/0.5 m2), but that the positive effects of parasites were negligible at lower densities. Our results confirm the findings of previous studies that parasites can protect marsh plants from overgrazing at sufficiently high prevalence, but show that their ability to do so depends on host density. [ABSTRACT FROM AUTHOR]

Nitrogen (N) and phosphorus (P) are essential elements whose availability promotes successful growth of phytoplankton and governs aquatic primary productivity. In this study, we investigated the effect of N and/or P deficiency on the sexual reproduction of Prorocentrum cordatum, the dinoflagellate with the haplontic life cycle which causes harmful algal blooms worldwide. In P. cordatum cultures, N and the combined N and P deficiency led to the arrest of the cell cycle in the G0/G1 phases and attenuation of cell culture growth. We observed, that P, but not N deficiency triggered the transition in the life cycle of P. cordatum from vegetative to the sexual stage. This resulted in a sharp increase in percentage of cells with relative nuclear DNA content 2C (zygotes) and the appearance of cells with relative nuclear DNA content 4C (dividing zygotes). Subsequent supplementation with phosphate stimulated meiosis and led to a noticeable increase in the 4C cell number (dividing zygotes). Additionally, we performed transcriptomic data analysis and identified putative phosphate transporters and enzymes involved in the phosphate uptake and regulation of its metabolism by P. cordatum. These include high- and low-affinity inorganic phosphate transporters, atypical alkaline phosphatase, purple acid phosphatases and SPX domain-containing proteins. [ABSTRACT FROM AUTHOR]

While numerous studies report shifts in vegetation phenology, in this regard eddy covariance (EC) data, despite its continuous high-frequency observations, still requires further exploration. Furthermore, there is no general consensus on optimal methodologies for data smoothing and extracting phenological transition dates (PTDs). Here, we revisit existing methodologies and present new prospects to investigate phenological changes in gross primary productivity (GPP) from EC measurements. First, we present a smoothing technique of GPP time series through the derivative of its smoothed annual cumulative sum. Second, we calculate PTDs and their trends from a commonly used threshold method that identifies days with a fixed percentage of the annual maximum GPP. A systematic analysis is performed for various thresholds ranging from 0.1 to 0.7. Lastly, we examine the relation of PTDs trends to trends in GPP across the years on a weekly basis. Results from 47 EC sites with long time series (> 10 years) show that advancing trends in start of season (SOS) are strongest at lower thresholds but for the end of season (EOS) at higher thresholds. Moreover, the trends are variable at different thresholds for individual vegetation types and individual sites, outlining reasonable concerns on using a single threshold value. Relationship of trends in PTDs and weekly GPP reveal association of advanced SOS and delayed EOS to increase in immediate primary productivity, but not to the trends in overall seasonal productivity. Drawing on these analyses, we emphasise on abstaining from subjective choices and investigating relationship of PTDs trend to finer temporal trends of GPP. Our study examines existing methodological challenges and presents approaches that optimize the use of EC data in identifying vegetation phenological changes and their relation to carbon uptake. [ABSTRACT FROM AUTHOR]

The high rate of production and use of copper oxide nanoparticles (CuO NPs) results in its accumulation in the environment. However, the effect of large quantities of CuO NPs on aquatic ecosystems is not fully known. In aquatic ecosystems, phytoplankton is the primary producer of organic matter and the basis of all the trophic interactions; accordingly, the potential effect of CuO NPs on the microalgae community is of great concern. This study established the main patterns of changes in morphological, structural, functional, fluorescent and cytometric parameters in the marine diatom Thalassiosira weissflogii after adding CuO NPs to the medium at concentrations of 250–2500 μg L−1. As shown, the investigated pollutant has cytotoxic, genotoxic and mechanical effect on the microalga covering almost all the aspects of cell functioning. A two-fold decrease in the culture abundance relative to the control is observed at the toxicant content of 550 μg L−1 in the medium. At CuO NPs content above 750 μg L−1, a pronounced inhibition of the alga growth is recorded, as well as a decrease in the efficiency of its photosynthetic apparatus, a disturbance of membrane integrity, an increase in cell volume, a rise in abundance of dead/inactive cells in the culture, enlargement and deformation of nuclei, an increase in reactive oxygen species production, and depolarisation of the mitochondrial membrane. Our results show that high CuO NPs concentrations in water can cause serious disruptions in phytoplankton functioning and in equilibrium of aquatic ecosystems in general. CuO nanoparticles (CuO NPs) have a cytotoxic, genotoxic and mechanical effect on the microalgae and affect almost all the aspects of cell functioning. CuO NPs inhibit the growth and photosynthesis of algae, damage cell membranes, induce deformation of nuclei, oxidative stress and depolarisation of the mitochondrial membrane. Our results indicate the potential danger of CuO NPs for the primary production link of aquatic ecosystems with an uncontrolled increase in their content in water. [ABSTRACT FROM AUTHOR]

Understanding of the primary production of phytoplankton in the Kara Sea (KS), the Laptev Sea (LS), and the East Siberian Sea (ESS) remains limited, despite the recognized importance of phytoplankton in the Arctic Ocean. To address this knowledge gap, we conducted three NABOS (Nansen and Amundsen Basins Observational System) expeditions in 2013, 2015, and 2018 to measure in situ primary production rates using a 13C-15N dual-tracer method and examine their major controlling factors. The main goals in this study were to investigate regional heterogeneity in primary production and derive its contemporary ranges in the KS, LS, and ESS. The daily primary production rates in this study (99 ± 62, 100 ± 77, and 56 ± 35 mg C m−2 d−1 in the KS, LS, and ESS, respectively) are rather different from the values previously reported in each sea mainly because of spatial and regional differences. Among the three seas, a significantly lower primary production rate was observed in the ESS in comparison to those in the KS and LS. This is likely mainly because of regional differences in freshwater content based on the noticeable relationship (Spearman, rs = −0.714, p < 0.05) between the freshwater content and the primary production rates observed in this study. The contemporary ranges of the annual primary production based on this and previous studies are 0.96–2.64, 0.72–50.52, and 1.68–16.68 g C m−2 in the KS, LS, and ESS, respectively. Further intensive field measurements are warranted to enhance our understanding of marine microorganisms and their community-level responses to the currently changing environmental conditions in these poorly studied regions of the Arctic Ocean. [ABSTRACT FROM AUTHOR]

To enable grasslands to serve a larger ecological and service role against the backdrop of climate change and human activity, management is essential following long-term fencing. Using desert grassland that had been fenced for 20 years, we conducted experiments on different mowing frequencies (once, twice, and three times a year) and different amounts of vegetation coverage (mowing removal, mowing, and in situ mulch; and mowing, in situ mulch, and additional coverage) and control (no mowing, no removal, and no cover). In 2021 and mid-August 2022, the aboveground biomass, species diversity, and vegetation cover of each species were assessed, and the impacts of species complementarity and competition on the productivity of the fenced grassland were examined. Our findings revealed several significant outcomes: (1) Two and three times of mowing per year promoted growth and development of annual or biennial plants and increased species diversity of the community. (2) The interaction impact of mowing and covering two and three times a year was the most important, as it encouraged compensatory development of plants, particularly the dominant species, and increased aboveground biomass of the fenced grassland (p < 0.05). (3) The number of complementary species groups was c. 11% lower for mowing and covering than for mowing removal, indicating that the interspecific relationship for the mowing and covering interaction was dominated by competition, which was more beneficial to the increase in community productivity. (4) Lespedeza potaninii Vass. (which dominated the semi-shrubs) and Agropyron mongolicum Keng (which dominated the tufted grasses) exhibited compensatory growth, which alleviated the change of mowing disturbance and precipitation fluctuation on the productivity of this grassland ecosystem. (5) Adding vegetation cover after mowing positively influenced community production but did not significantly impact litter decomposition. Our research provides data support for the sustainable development of long-term fenced desert grasslands. [ABSTRACT FROM AUTHOR]

The longleaf pine (Pinus palustris Mill.) and related ecosystem is an icon of the southeastern United States (US). Once covering an estimated 37 million ha from Texas to Florida to Virginia, the near-extirpation of, and subsequent restoration efforts for, the species has been well-documented over the past ca. 100 years. Although longleaf pine is one of the longest-lived tree species in the southeastern US—with documented ages of over 400 years—its use has not been reviewed in the field of dendrochronology. In this paper, we review the utility of longleaf pine tree-ring data within the applications of four primary, topical research areas: climatology and paleoclimate reconstruction, fire history, ecology, and archeology/cultural studies. Further, we highlight knowledge gaps in these topical areas, for which we introduce the Longleaf Tree-Ring Network (LTRN). The overarching purpose of the LTRN is to coalesce partners and data to expand the scientific use of longleaf pine tree-ring data across the southeastern US. As a first example of LTRN analytics, we show that the development of seasonwood chronologies (earlywood width, latewood width, and total width) enhances the utility of longleaf pine tree-ring data, indicating the value of these seasonwood metrics for future studies. We find that at 21 sites distributed across the species' range, latewood width chronologies outperform both their earlywood and total width counterparts in mean correlation coefficient (RBAR = 0.55, 0.46, 0.52, respectively). Strategic plans for increasing the utility of longleaf pine dendrochronology in the southeastern US include [1] saving remnant material (e.g., stumps, logs, and building construction timbers) from decay, extraction, and fire consumption to help extend tree-ring records, and [2] developing new chronologies in LTRN spatial gaps to facilitate broad-scale analyses of longleaf pine ecosystems within the context of the topical groups presented. [ABSTRACT FROM AUTHOR]

Fish habitat degradation, such as water pollution due to the rapid expansion of incompatible land uses, is one of the noteworthy challenges to freshwater ecosystems. Elevated contents of nutrients and contaminants in water are some of the imperative challenges. This research was conducted to investigate the link between water qualities and fish productivity in the Nyumba ya Mungu Dam, whose fishery potential had decreased by 95% between 1972 and 2018. Physicοchemical characteristics, namely, temperature, pH, dissolved oxygen (DO), turbidity, total nitrogen, total phosphorus, chlorophyll a, and the water depth of fishing net location, were assessed following standard procedure. Fish catches per unit effort representing fish biomass/productivity were monitored for twelve months from January to December 2019. Pearson's correlation analysis indicated that fish catch per unit effort was positively and significantly correlated with turbidity (r = 0.461, P < 0.01) and TP (r = 0.405, P < 0.01). Stepwise multiple regression model results indicated that turbidity, dissolved oxygen, and the depth of the fishing net location are the statistically significant predictors of fish catch per unit effort which represented fish biomass. Findings further indicated that the model combining turbidity and dissolved oxygen predicted a 24% change in fish catch per unit effort, whereas turbidity, dissolved oxygen, and the depth of fishing net location contributed a 28.9% change in fish catch per unit effort. In conclusion, fish productivity in the NMD is limited by organic matter availability and nutrient levels that cause algae bloom occurrence. Turbidity is an indicator of organic matter availability and the effect of algae bloom on fish productivity. Inflow of nutrients to the dam nourishes the algae biomass, thus creating vicious cycles on fish productivity as fish species in the dam failed to take advantage of high primary production by algae. [ABSTRACT FROM AUTHOR]

The agronomic potential of glutamate dehydrogenase 2 (GDH2) in maize kernel production was investigated by examining the impact of a mutation on the corresponding gene. Mu-insertion homozygous and heterozygous mutant lines lacking GDH2 activity were isolated and characterized at the biochemical, physiological and agronomic levels. In comparison to the wild type and to the homozygous ghd2 mutants, the heterozygous gdh2 mutant plants were characterized by a decrease in the root amino acid content, whereas in the leaves an increase of a number of phenolic compounds was observed. On average, a 30 to 40% increase in kernel yield was obtained only in the heterozygous gdh2 mutant lines when plants were grown in the field over two years. The importance of GDH2 in the control of plant productivity is discussed in relation to the physiological impact of the mutation on amino acid content, with primary carbon metabolism mostly occurring in the roots and secondary metabolism occurring in the leaves. [ABSTRACT FROM AUTHOR]

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The dynamics of the main photosynthetic structures are studied by mathematical modeling methods in this work. Chlorophyll portion variability in phytoplankton and formation of energy-intensive substances in the process of photosynthesis underlie the models. These cellular components are considered in terms of their participation in the growth of specific biomass. Computational experiments are conducted to simulate various degrees of environmental friendliness. The corresponding functions are built in accordance with seasonal fluctuations throughout the year in the Far East region of Russia. The stability of model solutions in long-term dynamics is also investigated. The models are tested for biological adequacy, and their effectiveness is compared. For the model selected as a result of the comparison, the optimal control problem was formulated and solved. This way reduces the space of the initial components of the model system. The main conclusion is that a step-by-step description of photosynthetic transformations gives a result close to the experimental description of phytoplankton production dynamics. [ABSTRACT FROM AUTHOR]

Accurate phenological extraction is important for estimating carbon uptake in terrestrial ecosystems under climate change. The emergence of remotely sensed vegetation indices (VIs) and solar‐induced chlorophyll fluorescence (SIF) provides multiple approaches for extracting land surface phenology. However, there is lacking studies to track phenological metrics via multiple VIs and SIF. Therefore, the advantage of combining VIs and SIF to estimate more accurate phenology requires exploration. In this study, we combined the advantages of the normalized difference, enhanced, green‐red, near‐infrared reflectance vegetation indices from MCD43A4 data set, and SIF from CSIF data set to estimate hybrid phenology at 20 eddy flux sites in North America. Results showed that the hybrid phenology derived from the best‐performing start (SOS) and end (EOS) of the growing season among multiple VIs and SIF for each plant functional type and site were both more consistent with those derived from gross primary production (GPP). Specifically, the R2 of hybrid phenology increased by 0.11–0.4 (0.04–0.4) for SOS, 0.01–0.24 (0.09–0.22) for EOS, 0.01–0.7 (0.05–0.34) for the length of the growing season (LOS) based on Gaussian (logistic) method. Moreover, hybrid phenology can improve the explanation of the seasonal and annual variations in GPP. The explanatory power of hybrid phenology for GPP variations increased by 0.05–0.15 (0.02–0.23) for SOS, 0–0.36 (0.11–0.27) for EOS, 0.01–0.51 (0.03–0.4) for LOS, 0.04–0.18 (0.04–0.16) for LOS × ${\times} $ seasonal GPP maximum based on Gaussian (logistic) method. These findings highlight the potential of combining high‐spatiotemporal structural and coarse‐spatiotemporal physiological vegetation indicators in tracking phenology and GPP. Plain Language Summary: Vegetation phenology illustrates the timing of plant growth phases and can serve as a valuable indicator for understanding plant responses and feedback mechanisms to climate change. Consequently, it is important to accurately estimate vegetation phenology in terrestrial ecosystems. The remotely sensed vegetation indices (VIs) and solar‐induced chlorophyll fluorescence (SIF) are widely employed to estimate land surface phenology such as the start (SOS), end (EOS), and thus LOS. However, there is lacking studies to track phenological metrics via multiple VIs and SIF. This study proposes two hybrid phenological metrics estimation approach that combines the best‐performing vegetation indicators estimated SOS and EOS among multiple VIs and SIF for each plant functional type and site. Results reveal that two hybrid phenological metrics significantly enhance the accuracy of phenology estimation, and provide a more robust interpretation of gross primary productivity. Key Points: Hybrid phenological metrics are derived by identifying the most effective vegetation indicators for capturing the start of growing season and the end of growing seasonHybrid phenological metrics can yield superior accuracy compared to single vegetation index or solar‐induced chlorophyll fluorescence derived phenologyHybrid phenological metrics can better track the seasonal and annual gross primary production dynamics [ABSTRACT FROM AUTHOR]

Salt pannes are marsh features in the supratidal zone that are devoid of macrophytic vegetation. Although these habitats appear barren, benthic microalgae (BMA) inhabit the sediments and are potentially important primary producers. In addition, salt pannes are habitats for dense accumulations of sand fiddler crabs (Leptuca pugilator; Bosc 1802). The purpose of this study was to determine the temporal changes in BMA biomass, community composition, and net primary productivity (NPP) for a supratidal salt panne and quantify sand fiddler crab grazing on BMA. The impact of crab grazing on BMA abundance in surface sediments was determined by measuring chl a concentrations in ungrazed and grazed sediments. BMA biomass peaked to a high of 16 µg chl a g sediment−1 in June and July, suggesting growth in the spring followed by a small decline in the warmer summer months. The BMA community was primarily composed of benthic diatoms, with lesser amounts of cyanobacteria. NPP increased to a median of 0.51 mmol O2 m−2 h−1 (6.12 mg C m−2 h−1) in July. In comparison with other BMA habitats in this estuary, NPP and biomass for salt pannes was lower than the other 5 habitat types (tall and short Spartina, intertidal mud and sandflats, phytoplankton, and submerged sediments). Sand fiddler crabs do not appear to consume significant amounts of BMA during grazing in salt pannes. This first ever study of BMA NPP demonstrates that estuarine salt pannes are likely a small contributor to ecosystem NPP. [ABSTRACT FROM AUTHOR]

As part of the HIPPO (HIgh-resolution Primary Production multi-prOxy archives) project, environmental monitoring was carried out between March and October 2021 in the Bay of Brest. The aim of this survey was to better understand the processes which drive the incorporation of chemical elements into scallop shells and their links with phytoplankton dynamics. For this purpose, biological samples (scallops and phytoplankton) as well as water samples were collected in order to analyze various environmental parameters (element chemical properties, nutrients, chlorophyll a , etc.). Given the large number of parameters that were measured, only the major results are presented and discussed here. However, the whole dataset, which has been made available, is much larger and can potentially be very useful for other scientists performing sclerochronological investigations, studying biogeochemical cycles or conducting various ecological research projects. The dataset is available at 10.17882/92043 (Siebert et al., 2023). [ABSTRACT FROM AUTHOR]

The gross primary production (GPP) of the terrestrial biosphere is a key source of variability in the global carbon cycle. It is modulated by hydrometeorological drivers (i.e., shortwave radiation, air temperature, vapor pressure deficit and soil moisture) and the vegetation state (i.e., canopy greenness, leaf area index) at instantaneous to interannual timescales. In this study, we set out to evaluate the ability of GPP-models to capture this variability. 11 models were considered, which rely purely on remote sensing data (RS-driven), meteorological data (meteo-driven, e.g., dynamic global vegetation models; DGVMs) or a combination of both (hybrid, e.g., light-use efficiency models; LUE). They were evaluated using in situ observations at 61 eddy covariance sites, covering a broad range of herbaceous and forest biomes. The results illustrated how the determinant of temporal variability shifts from meteorological variables at sub-seasonal timescales to biophysical variables at seasonal and interannual scale. RS-driven models lacked the sensitivity to the dominant drivers at short timescales (i.e., shortwave radiation and vapor pressure deficit), and failed to capture the decoupling of photosynthesis and canopy greenness (e.g., in evergreen forests). Conversely, meteo-driven models accurately captured the variability accross timescales, despite the challenges in the prognostic simulation of the vegetation state. Largest errors were found in water-limited sites, where the accuracy of the soil moisture dynamics determines the quality of the GPP estimates. In arid herbaceous sites, canopy greenness and photosynthesis were more tightly coupled, resulting in improved results with RS-driven models. Hybrid models capitalized on the combination of RS observations and meteorological information. LUE models were among the most accurate models to monitor GPP across all biomes, despite their simple architecture. Overall, we conclude that the combination of meteorological drivers and remote sensing observations is required to yield an accurate reproduction of the spatio-temporal variability of GPP. To further advance the performance of DGVMs, improvements in the soil moisture dynamics and vegetation evolution are needed. [ABSTRACT FROM AUTHOR]

The uptake of 3H‐labeled leucine into proteins, a widely used method for estimating bacterial carbon production (BCP), is suggested to underestimate or overestimate bacterial growth in the open ocean by a factor of 40 uncertainty. Meanwhile, an alternative BCP approach, by the dilution method, has untested concerns about potential overestimation of bacterial growth from dissolved substrates released by filtration. We compared BCPDil and BCPLeu estimates from three cruises across a broad trophic gradient, from offshore oligotrophy to coastal upwelling, in the California Current Ecosystem. Our initial analyses based on midday microscopical estimates of bacterial size and a priori assumptions of conversions relationships revealed a mean two‐fold difference in BCP estimates (BCPDil higher), but no systematic bias between low and high productivity stations. BCPDil and BCPLeu both demonstrated strong relationships with bacteria cell abundance. Reanalysis of results, involving a different cell carbon‐biovolume relationship and informed by forward angle light scatter from flow cytometry as a relative cell size index, demonstrated that BCPDil and BCPLeu are fully compatible, with a 1 : 1 fit for bacteria of 5 fg C cell−1. Based on these results and considering different strengths of the methods, the combined use of 3H‐labeled leucine and dilution techniques provide strong mutually supportive constraints on bacterial biomass and production. [ABSTRACT FROM AUTHOR]

Identification of the Sub1 gene for tolerance to flash flooding and its introgression into high-yielding rice cultivars are major targets in rice breeding for flood-prone rice agro-ecosystems for ensuring yield stability. However, knowledge is scant on the response of the modified genotypes under stagnant flooding (SF) to meet the challenge of finding a superior allele that may confer greater resilience to the plant under a stress-prone environment. In pursuance, we have tested the response of Sub1-introgression in two popular rice varieties, Swarna and Savitri to SF by comparing the biochemical factors in the control of flag leaf senescence and its primary production mechanisms of the parental lines' versus Sub1-introgressed lines. The activities of antioxidant enzymes like superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GR), and ascorbate peroxidase (APX) increased while various parameters of primary production like total chlorophyll content, stomatal conductance (gs), normalized difference vegetation index (NDVI) and photosynthetic activity (Pn) decreased progressively with passage of time in the flag leaf of the cultivars during the post-anthesis period and SF-treatment increased the enzyme activity while depressing primary production further. Introgression of Sub1 had no influence on these activities under control conditions but widened the margin of effects under SF. It was concluded that the functional ability of flag leaf in mega rice cultivars like Swarna and Savitri decreased significantly by SF because of an ethylene-mediated promotion of senescence of the flag leaf. The enhancement of antioxidant enzyme activity by SF could not sustain the stability of primary production in the flag leaf. The introgression of the Sub1 gene made the cultivars more vulnerable to SF because the gene induced overexpression of ethylene. [ABSTRACT FROM AUTHOR]

The fraction of absorbed photosynthetically active radiation (FPAR) is widely used in remote sensing-based production models to estimate gross or net primary production. The forest canopy is composed primarily of photosynthetically active vegetation (PAV, green leaves) and non-photosynthetic vegetation (NPV e.g., branches), which absorb PAR but only the PAR absorbed by PAV is used for photosynthesis. Green FPAR (the fraction of PAR absorbed by PAV) is essential for the accurate estimation of GPP. In this study, the scattering by arbitrary inclined leaves (SAIL) model was reconfigured to partition the PAR absorbed by forest canopies. The characteristics of green FPAR and its relationships with spectral vegetation indices (NDVI, EVI, EVI2, and SAVI) were analyzed. The results showed that green FPAR varied with the canopy structure. In the forests with high coverage, the green FPAR was close to the total FPAR, while in the open forests, the green FPAR was far smaller than the total FPAR. Plant area index had more important impacts on the green FPAR than the proportion of PAV and optical properties of PAV. The significant relationships were found between spectral vegetation indices and the green FPAR, but EVI was more suitable to describe the variation of canopy green FPAR. [ABSTRACT FROM AUTHOR]

Extreme weather events, such as ice storms, are increasing and have potentially large impacts on forests, including belowground structures such as fine roots and mycorrhizal fungi. Many forest trees rely on the mutualistic relationship between mycorrhizal fungi and plants; a relationship that, when disrupted, can negatively impact tree net primary productivity. We took advantage of a large‐scale ice storm manipulation in the northeastern United States to test the hypothesis that increasing ice storm intensity and frequency would reduce ectomycorrhizal fungal root tips per unit root length and arbuscular mycorrhizal fungal structures per unit root length, hereafter colonization. We found that ice storm intensity reduced spring ectomycorrhizal fungal and arbuscular mycorrhizal fungal colonization. However, these patterns changed in the fall, where ice storm intensity still reduced ectomycorrhizal fungal root tips, but arbuscular mycorrhizal fungal colonization was higher in ice storm treatments than controls. The amount of ectomycorrhizal fungal root tips and arbuscular mycorrhizal fungal colonization differed seasonally: ectomycorrhizal fungal root tips were 1.7× higher in the spring than in the fall, while arbuscular mycorrhizal fungal colonization was 3× higher in the fall than in the spring. Our results indicate that mycorrhizal fungal colonization responses to ice storm severity vary temporally and by mycorrhizal fungal type. Further, arbuscular mycorrhizal fungi may recover from ice storms relatively quickly, potentially aiding forests in their recovery, whereas ice storms may have a long lasting impact on ectomycorrhizal fungi. [ABSTRACT FROM AUTHOR]

The Bering Sea and other high‐latitude systems are experiencing unprecedented changes related to climate warming and the consequent loss of sea ice. Understanding how such changes influence primary production is a pressing question. Here, we quantify primary production rates in the southeastern Bering Sea over 4 years (2016–2019) at daily to weekly time resolution. A moored high‐resolution Profiling Crawler was used in combination with in situ sampling to collect physical and biological data in the ocean's upper 50 m. We used dissolved oxygen (O2) data to estimate gross and net primary production (NPP), and chlorophyll‐a (Chl‐a), temperature, and irradiance data to model NPP rates. We then assessed seasonal variation in phytoplankton production rates, phytoplankton community growth rates (poptb ${p}_{\text{opt}}^{b}$) and explored to what extent summer phytoplankton community growth rates may be influenced by nitrogen limitation. Our analyses revealed that the majority of gross primary production (GPP) and net community production occurs in association with the spring phytoplankton bloom. After the bloom, the water column generally experienced low GPP and net biological carbon consumption. Phytoplankton growth rates were commonly suppressed in late summer due to apparent nitrogen depletion. Using high temporal resolution vertically resolved measurements of O2 and Chl‐a, our analyses provides important insight into how biogeochemical cycles, phytoplankton community growth rates, and carbon available for export vary seasonally in the southeastern Bering Sea. Plain Language Summary: The Bering Sea is experiencing unprecedented changes related to climate warming and the consequent loss of sea ice. How such changes affect the growth and composition of phytoplankton at the base of the food web is a pressing concern. Here, we quantify phytoplankton and community production rates in the surface ocean in the southeastern Bering Sea over four years (2016–2019), using a moored Profiling Crawler that samples temperature, salinity, oxygen, and chlorophyll‐a data over the top 50 m. We then assessed seasonal and shorter‐term variations in phytoplankton production rates. Our analyses showed that the majority of phytoplankton production and organic carbon available for leaving the upper ocean occurs during the phytoplankton spring bloom. After the bloom, phytoplankton production was low for most of the summer, with phytoplankton growth rates limited by nutrient availability in late summer. Our high temporal resolution and vertically resolved measurements from the Profiling Crawler provide new insight into the seasonal primary production cycle in the southeastern Bering Sea. Key Points: The majority of phytoplankton production occurs during the spring bloomPhytoplankton growth rates appear limited by nutrient availability in late summerProfiling Crawlers provides new insight into the seasonal production cycle in the southeastern Bering Sea [ABSTRACT FROM AUTHOR]

Ozone is a phytotoxic pollutant that could damage the vegetation growth and lead to complicated impacts on air quality through meteorological and biogeochemical feedbacks. This study implements a semi‐empirical parameterization regarding the impacts of ozone exposure on photosynthesis rate and stomatal resistance into the Noah‐Multi‐parameterization (Noah‐MP) dynamic vegetation module of Weather Research and Forecasting with Chemistry (WRF/Chem) model. The gaseous dry deposition and biogenic emission algorithms are also coupled with Noah‐MP to enable the ozone‐vegetation coupling. This model reproduces the near‐surface meteorology, air pollutants and vegetation physiology in China, with a spatial correlation coefficient more than 0.9 and normalized mean bias from −0.19 to 0.42. The optimized model also improves the simulations of vegetation physiology (e.g., a reduction of model error by 18%–32%) and ozone dry deposition velocity. The elevated ozone damages plant photosynthesis, and decreases the national gross primary productivity (−28.85%) and leaf area index (−17.41%). The plant transpiration and surface heat flux, as well as air temperature (e.g., up to +0.16°C in summer) and other associated meteorological variables are also altered, finally contributing to 0.49 μg m−3 increase of surface ozone. Otherwise, the suppressed vegetation LAI and biogenic emissions, as well as the lower dry deposition velocity in response to the ozone‐vegetation coupling contribute to the remaining ozone changes by −1.07 μg m−3 and 1.18 μg m−3, jointly constituting the complicated ozone‐vegetation feedbacks on air quality. Our results highlight the necessity of including the ozone‐vegetation coupling in models for reliable prediction of regional climate and air quality. Plain Language Summary: Vegetation controls the land‐atmosphere carbon/water cycle and material exchange, and is thus important in global/regional climate and atmospheric environment. Chronic exposure to ozone could damage the vegetation growth and lead to complicated impacts on regional climate and air quality. This study considers the impacts of ozone exposure on plant photosynthesis and stomata using a semi‐empirical parameterization into the WRF/Chem‐Noah‐MP regional meteorology‐chemistry‐vegetation coupled model. The model well reproduces the near‐surface meteorology, air pollutants and vegetation characteristics in China, with moderate model improvements due to the optimized dynamic vegetation and dry deposition modules. The elevated ozone damages plant photosynthesis and decreases the national gross primary productivity (−28.85%) and leaf area index (−17.41%). Otherwise, the plant transpiration and surface heat flux, as well as air temperature (e.g., up to +0.16°C in summer) and other associated meteorological variables are also altered. The meteorological changes, along with the suppressed biogenic emissions from vegetation and lower dry deposition velocity due to the ozone‐vegetation damage jointly constitute the complicated ozone‐vegetation feedbacks on air quality and contribute to an average of −1.1∼1.2 μg m−3 surface ozone change. Our results highlight the necessity of including the ozone‐vegetation coupling for reliable model predictions. Key Points: The optimized model with ozone‐vegetation coupling improves the simulations of vegetation physiology and dry deposition velocity in ChinaThe O3‐damaged photosynthesis and stomatal conductance could affect regional meteorology, finally contributing to surface ozone increaseThe ozone‐vegetation coupling constitutes complex feedbacks on ozone itself by altered meteorology, biogenic emissions and dry deposition [ABSTRACT FROM AUTHOR]