Summer heatwaves promote harmful algal blooms in the Fuchunjiang Reservoir, an important drinking water source.

Extensive outbreaks of harmful algal blooms (HABs) occurred in the Fuchunjiang Reservoir in 2022, a crucial urban drinking water source, coinciding with extreme summer heatwaves. We hypothesize that these heatwaves contributed to HABs formation and expansion. Leveraging Landsat 8 and Sentinel-2 data, we employed clustering and machine learning methods to quantify the HABs distribution and area. Concurrent meteorological and water quality data aided in uncovering the effects of heatwave on HABs. When applying different methods to extract HABs from remote sensing images, random forest (RF) analyses indicated accuracies of 99.3% and 99.8% for Landsat 8 and Sentinel-2 data, respectively, while classification and regression tree (CART) analyses indicated 99.1% and 99.7% accuracies, respectively. Support vector machine (SVM) exhibited lower accuracies (83.5% and 97.4%). Thus RF, given its smaller differences between satellites and high accuracy, was selected for further analysis. Both satellites detected extensive HABs in 2022, with Sentinel-2 recording a peak area of 24.13 km2 (44.6% of cloud-free water area) on August 11, 2022. Increasing trends with amplified durations were observed for summer heatwaves in Jiande and Tonglu around the Fuchunjiang Reservoir. Notably, these areas experienced extreme heatwaves for 63 and 58 days in 2022, respectively, more than double the 1980-2022 average. From June 1 to October 8, 2022, water temperature peaks significantly coincided with expansive HABs and elevated chlorophyll a (Chl-a) concentration from 4.8 µg/L to 119.2 µg/L during the summer heatwaves. Our findings indicated that the reservoir became more HAB-prone during heatwave events, escalating the drinking water safety risk. These results emphasize the challenges faced by reservoir managers in dealing with climate-induced extreme heatwaves and underscore the urgency for heightened attention from water source management departments.

Decreasing denitrification rates poses a challenge to further decline of nitrogen concentration in Lake Taihu, China.

Nitrogen (N) concentrations in many lakes have decreased substantially in recent years due to external load reduction to mitigate harmful algal blooms. However, little attention has been paid to the linkage between the lakes' nitrogen removal efficiency and improved water quality in lakes, especially the variation of denitrification rate (DNR) under decreasing N concentrations. To understand the efficiency of N removal under improving water quality and its influence on the N control targets in Lake Taihu, a denitrification model based on in situ experimental results was developed and long-term (from 2007 to 2022) water quality and meteorological observations were used to estimate DNR and relate it to the amount of N removal (ANR) from the lake. The concentration of total nitrogen (TN) in Lake Taihu decreased from 3.28 mg L-1 to 1.41 mg L-1 from 2007 to 2022 but the reduction showed spatial heterogeneity. The annual mean DNR decreased from 45.6 µmol m-2 h-1 to 4.2 µmol m-2 h-1, and ANR decreased from 11.85×103 t yr-1 to 1.17×103 t yr-1 during the study years. N budget analysis suggested that the amount of N removed by denitrification accounted for 23.3 % of the external load in 2007, but decreased to only 4.0 % in 2022. Thus, the contribution of N removal by internal N cycling decreased significantly as water quality improved. Notably, the proportion of ANR in winter to total ANR increased from 14 % in 2007 to 23 % in 2022 due to warming. This could potentially lead to N deficiencies in spring and summer, thus limiting the availability of N to phytoplankton. A TN concentration of less than 1.0 mg L-1 in the lake and 1.5 mg L-1 in the inflowing lake zones in spring contribute to local N-limitation in Lake Taihu for cyanobacteria control. Our study revealed a general pattern that N removal efficiency decreases with improved water quality, which is instructive for eutrophic lakes in nitrogen management.

Streamlined measurement of chimeric antigen receptor T-cell concentration, size, viability and two-color phenotyping during manufacturing.

BACKGROUND AIMS: The successful development of CD19-targeted chimeric antigen receptor (CAR) T-cell therapies has led to an exponential increase in the number of patients recieving treatment and the advancement of novel CAR T products. Therefore, there is a strong need to develop streamlined platforms that allow rapid, cost-effective, and accurate measurement of the key characteristics of CAR T cells during manufacturing (i.e., cell number, cell size, viability, and basic phenotype). METHODS: In this study, we compared the novel benchtop cell analyzer Moxi GO II (ORFLO Technologies), which enables simultaneous evaluation of all the aforementioned parameters, with current gold standards in the field: the Multisizer Coulter Counter (cell counter) and the BD LSRFortessa (flow cytometer). RESULTS: Our results demonstrated that the Moxi GO II can accurately measure cell number and cell size (i.e., cell volume) while simultaneously assessing simple two-color flow cytometry parameters, such as CAR T-cell viability and CD4 or CAR expression. CONCLUSIONS: These measurements are comparable with those of gold standard instruments, demonstrating that the Moxi GO II is a promising platform for quickly monitoring CAR T-cell growth and phenotype in research-grade and clinical samples.

Applicability analysis of flame height estimation based on Byram's fireline intensity model under flat and windless conditions.

Forest fire have a serious impact on forest ecosystems, the safety of people's lives and property, and social stability. The height of surface flames, as the main indicator of forest fire behavior, which is an important parameter for forest fire management. The relationship between fireline intensity and flame height proposed by Byram has been widely used in estimating flame height; however, its applicability to the surface fuel of typical forest stands in the Yunnan-Guizhou Plateau of China has not yet been analyzed. In this study, the surface fuel in the area was taken as the research object, and the flame height of different fuel bed characteristics was measured through an indoor burning experiment. The applicability of three methods-the directly used Byram's model, corrected model, and re-established prediction model-was analyzed to estimate the flame height in the Yunnan-Guizhou Plateau. We found that the flame height of the typical forest stands in the Yunnan-Guizhou Plateau ranged from 0.05 to 1.2 m and was significantly affected by the moisture content, load, and height of the fuel bed. Although the fireline intensity exhibited a significant linear relationship with the flame height, directly using Byram's method to predict the flame height of surface fires was impractical, as its mean prediction error exceeded 150%. The mean relative errors of the prediction model obtained by modifying Byram's method and that based on the characteristics of the fuel bed were both within 15%, which is significantly lower than that of the original Byram's method. Based on the results of this study, we propose two methods that are suitable for predicting the flame height of surface fires in the typical forests of the Yunnan-Guizhou Plateau in China, which is of great significance for further understanding the relationship between flame height, fireline intensity, and scientific forest fire management.

An optical mechanism-based deep learning approach for deriving water trophic state of China's lakes from Landsat images.

Widespread eutrophication has been considered as the most serious environment problems in the world. Given the critical roles of lakes in human society and serious negative effects of water eutrophication on lake ecosystems, it is thus fundamentally important to monitor and assess water trophic status of lakes. However, a reliable model for accurately estimating the trophic state index (TSI) of lakes across a large-scale region is still lacking due to their high complexity. Here, we proposed an optical mechanism-based deep learning approach to remotely estimate TSI of lakes based on Landsat images. The approach consists of two steps: (1) determining the optical indicators of TSI and modeling the relationship between them, and (2) developing an approach for remotely deriving the determined optical indicator from Landsat images. With a large number of in situ datasets measured from lakes (2804 samples from 88 lakes) across China with various optical properties, we trained and validated three machine learning methods including deep neural network (DNN), k-nearest neighbors (KNN) and random forest (RF) to model TSI with the optical indicators and TSI and derive the determined optical indicator from Landsat images. The results showed that (1) the total absorption coefficients of optically active constituents at 440 nm (at-w(440)) performs best in characterizing TSI, and (2) DNN outperforms other models in the inversion of both TSI and at-w(440). Overall, our proposed optical mechanism-based deep learning approach demonstrated a robust and satisfactory performance in assessing TSI using Landsat images (root mean squared error (RMSE) = 5.95, mean absolute error (MAE) = 4.81). This highlights its merit as a nationally-adopted method in lake water TSI estimation, enabling the convenience of the acquisition of water eutrophic information in large scale, thereby assisting us in managing lake ecology. Therefore, we assessed water TSI of 961 lakes (>10 km2) across China using the proposed approach. The resulting at-w(440) and TSI ranged from 0.01 m-1 to 31.42 m-1 and from 6 to 96, respectively. Of all these studied lakes, 96 lakes (11.40 %) were oligotrophic, 338 lakes were mesotrophic (40.14 %), 360 lakes were eutrophic (42.76 %), and 48 were hypertrophic (5.70 %) in 2020.

Terrestrial dissolved organic matter inputs accompanied by dissolved oxygen depletion and declining pH exacerbate CO2 emissions from a major Chinese reservoir.

Terrestrial inputs and subsequent degradation of dissolved organic matter (DOM) in lake ecosystems can result in rapid depletion of dissolved oxygen (DO). Inputs of terrestrial DOM including organic acids can also lead to decreases in pH. However, to date, few studies have investigated the linkages between terrestrial DOM inputs, DO and pH levels in the water column, and carbon dioxide (CO2) emissions from lake ecosystems. Based on monthly field sampling campaigns across 100 sites in Lake Qiandao, a major man-made drinking water reservoir in China, from May 2020 to April 2021, we estimated an annual CO2 efflux (FCO2) of 37.2 ± 29.0 gC m-2 yr-1, corresponding to 0.02 ± 0.02 TgC yr-1 from this lake. FCO2 increased significantly with decreasing DO, chlorophyll-a (Chl-a) and δ2H-H2O, while FCO2 increased with increasing specific UV absorbance (SUVA254) and a terrestrial humic-like component (C2). We found that DO concentration and pH declined with increasing terrestrial DOM inputs, i.e. increased SUVA254 and terrestrial humic-like C2 levels. Vertical profile sampling revealed that the partial pressure of CO2 (pCO2) increased with increasing terrestrial DOM fluorescence (FDOM), while DO, pH, and δ13C-CO2 declined with increasing terrestrial FDOM. These results highlight the importance of terrestrial DOM inputs in altering physico-chemical environments and fueling CO2 emissions from this lake and potentially other aquatic ecosystems.

The impact of extreme heat on lake warming in China.

Global lake ecosystems are subjected to an increased occurrence of heat extremes, yet their impact on lake warming remains poorly understood. In this study, we employed a hybrid physically-based/statistical model to assess the contribution of heat extremes to variations in surface water temperature of 2260 lakes in China from 1985 to 2022. Our study indicates that heat extremes are increasing at a rate of about 2.08 days/decade and an intensity of about 0.03 °C/ day·decade in China. The warming rate of lake surface water temperature decreases from 0.16 °C/decade to 0.13 °C/decade after removing heat extremes. Heat extremes exert a considerable influence on long-term lake surface temperature changes, contributing 36.5% of the warming trends within the studied lakes. Given the important influence of heat extremes on the mean warming of lake surface waters, it is imperative that they are adequately accounted for in climate impact studies.

Terrestrial dissolved organic matter inputs drive the temporal dynamics of riverine bacterial ecological networks and assembly processes.

Rivers receive, transport, and are reactors of terrestrial dissolved organic matter (DOM) and are highly influenced by changes in hydrological conditions and anthropogenic disturbances, but the effect of DOM composition on the dynamics of the bacterial community in rivers is poorly understood. We conducted a seasonal field sampling campaign at two eutrophic river mouth sites to examine how DOM composition influences the temporal dynamics of bacterial community networks, assembly processes, and DOM-bacteria associations. DOM composition and seasonal factors explained 34.7% of the variation in bacterial community composition, and 14.4% was explained purely by DOM composition where specific UV absorbance (SUVA254) as an indicator of aromaticity was the most important predictor. Significant correlations were observed between SUVA254 and the topological features of subnetworks of interspecies and DOM-bacteria associations, indicating that high DOM aromaticity results in more complex and connected networks of bacteria. The bipartite networks between bacterial taxa and DOM molecular formulae (identified by ultrahigh-resolution mass spectrometry) further revealed less specialized bacterial processing of DOM molecular formulae under the conditions of high water level and DOM aromaticity in summer than in winter. A shift in community assembly processes from stronger homogeneous selection in summer to higher stochasticity in winter correlated with changes in DOM composition, and more aromatic DOM was associated with greater similarity in bacterial community composition. Our results highlight the importance of DOM aromaticity as a predictor of the temporal dynamics of riverine bacterial community networks and assembly.

Optical measurements of dissolved organic matter as proxies for CODMn and BOD5 in plateau lakes.

The presence of organic matter in lakes profoundly impacts drinking water supplies, yet treatment processes involving coagulants and disinfectants can yield carcinogenic disinfection by-products. Traditional assessments of organic matter, such as chemical oxygen demand (CODMn) and biochemical oxygen demand (BOD5), are often time-consuming. Alternatively, optical measurements of dissolved organic matter (DOM) offer a rapid and reliable means of obtaining organic matter composition data. Here we employed DOM optical measurements in conjunction with parallel factor analysis to scrutinize CODMn and BOD5 variability. Validation was performed using an independent dataset encompassing six lakes on the Yungui Plateau from 2014 to 2016 (n = 256). Leveraging multiple linear regressions (MLRs) applied to DOM absorbance at 254 nm (a254) and fluorescence components C1-C5, we successfully traced CODMn and BOD5 variations across the entire plateau (68 lakes, n = 271, R2 > 0.8, P < 0.0001). Notably, DOM optical indices yielded superior estimates (higher R2) of CODMn and BOD5 during the rainy season compared to the dry season and demonstrated increased accuracy (R2 > 0.9) in mesotrophic lakes compared to oligotrophic and eutrophic lakes. This study underscores the utility of MLR-based DOM indices for inferring CODMn and BOD5 variability in plateau lakes and highlights the potential of integrating in situ and remote sensing platforms for water pollution early warning.

Increased dominance of terrestrial component in dissolved organic matter in Chinese lakes.

The source composition of chromophoric dissolved organic matter (CDOM) in lakes is closely related to regional environmental changes, human activities, and the carbon cycle. The spectral slope ratio (SR) is an important parameter of CDOM optical components, and combined with remote sensing technology, the source composition of CDOM can be tracked comprehensively and efficiently in large regions. Here, we proposed a CDOM source tracking remote sensing model (CDOM-SR) based on the hue angle (α) to assess the spatial pattern and long-term trend of the CDOM source composition in Chinese lakes (surface area ≥ 1 km2) from 1986 to 2021. Validation results show that the CDOM-SR model has a good SR estimation performance with a median absolute percentage difference, root mean square deviation, median ratio, and median deviation of 17.91 %, 0.23, 1.02, and 0.03, respectively. We found that the average SR of Chinese lakes presents an obvious spatial pattern of high in the west and low in the east due to the difference in human activity intensity and the natural geographical environment. Additionally, we found that the average SR of Chinese lakes from 1986 to 2021 decreased at a rate of - 0.06/10 years, of which 64.37 % of lakes decreased significantly, 15.42 % of lakes had no significant change, and only 20.20 % of lakes increased. The widespread decrease in the average SR indicates that the increasing human activity discharge of terrestrial organic matter has had an important impact on the source composition of the CDOM in Chinese lakes. Our results provide a new resource for remote sensing monitoring of CDOM sources and important insights into lake carbon cycling under the influence of ongoing human activities.

Safety and efficacy of a novel anti-CD19 chimeric antigen receptor T cell product targeting a membrane-proximal domain of CD19 with fast on- and off-rates against non-Hodgkin lymphoma: a first-in-human study.

BACKGROUND: Commercial anti-CD19 chimeric antigen receptor T-cell therapies (CART19) are efficacious against advanced B-cell non-Hodgkin lymphoma (NHL); however, most patients ultimately relapse. Several mechanisms contribute to this failure, including CD19-negative escape and CAR T dysfunction. All four commercial CART19 products utilize the FMC63 single-chain variable fragment (scFv) specific to a CD19 membrane-distal epitope and characterized by slow association (on) and dissociation (off) rates. We hypothesized that a novel anti-CD19 scFv that engages an alternative CD19 membrane-proximal epitope independent of FMC63 and that is characterized by faster on- and off-rates could mitigate CART19 failure and improve clinical efficacy. METHODS: We developed an autologous CART19 product with 4-1BB co-stimulation using a novel humanized chicken antibody (h1218). This antibody is specific to a membrane-proximal CD19 epitope and harbors faster on/off rates compared to FMC63. We tested h1218-CART19 in vitro and in vivo using FMC63-CART19-resistant models. We conducted a first-in-human multi-center phase I clinical trial to test AT101 (clinical-grade h1218-CART19) in patients with relapsed or refractory (r/r) NHL. RESULTS: Preclinically, h1218- but not FMC63-CART19 were able to effectively eradicate lymphomas expressing CD19 point mutations (L174V and R163L) or co-expressing FMC63-CAR19 as found in patients relapsing after FMC63-CART19. Furthermore, h1218-CART19 exhibited enhanced killing of B-cell malignancies in vitro and in vivo compared with FMC63-CART19. Mechanistically, we found that h1218-CART19 had reduced activation-induced cell death (AICD) and enhanced expansion compared to FMC63-CART19 owing to faster on- and off-rates. Based on these preclinical results, we performed a phase I dose-escalation trial, testing three dose levels (DL) of AT101 (the GMP version of h1218) using a 3 + 3 design. In 12 treated patients (7 DLBCL, 3 FL, 1 MCL, and 1 MZL), AT101 showed a promising safety profile with 8.3% grade 3 CRS (n = 1) and 8.3% grade 4 ICANS (n = 1). In the whole cohort, the overall response rate was 91.7%, with a complete response rate of 75.0%, which improved to 100% in DL-2 and -3. AT101 expansion correlates with CR and B-cell aplasia. CONCLUSIONS: We developed a novel, safe, and potent CART19 product that recognizes a membrane-proximal domain of CD19 with fast on- and off-rates and showed significant efficacy and promising safety in patients with relapsed B-cell NHL. TRIAL REGISTRATION: NCT05338931; Date: 2022-04-01.

Effects of Transglutaminase on Myofibrillar Protein Composite Gels with Addition of Non-Meat Protein Emulsion.

The emulsions prepared by three non-meat proteins, sodium caseinate (SC), soy protein isolate (SPI) and egg white protein (EPI), were individually added to the continuous phase of myofibrillar protein (MP) sol to form MP composite gels to simulate meat products. The research aimed to investigate the effects of Transglutaminase (TGase) on the physicochemical properties, microstructure and water phase distribution of non-meat protein emulsion MP composite gels. The results of this study revealed that TGase played a crucial role in forming a tight gel network structure in the composite gels. This enhanced their ability to retain water and improved their overall gel strength. Additionally, TGase increased the gel formation temperature of myofibrillar proteins. Electrophoresis analysis showed that when catalyzed by TGase, there was a lighter band compared to those not catalyzed by TGase. This indicated that the addition of TGase facilitated cross-linking interactions between meat proteins and non-meat proteins in the composite gels. Furthermore, microscopy observations demonstrated that composite gels treated with TGase exhibited a more uniform microstructure. This could be attributed to an acceleration in relaxation time T2. The uniform network structure restricted the movement of water molecules in the gel matrix, thereby improving its water-holding capacity. Overall, these findings highlight how incorporating non-meat proteins into myofibrillar systems can be effectively achieved through enzymatic treatment with TGase. Such modifications not only enhanced important functional properties but also contributed towards developing alternative meat products with improved texture and moisture retention abilities.

Alternative splicing of its 5'-UTR limits CD20 mRNA translation and enables resistance to CD20-directed immunotherapies.

Aberrant skipping of coding exons in CD19 and CD22 compromises the response to immunotherapy in B-cell malignancies. Here, we showed that the MS4A1 gene encoding human CD20 also produces several messenger RNA (mRNA) isoforms with distinct 5' untranslated regions. Four variants (V1-4) were detected using RNA sequencing (RNA-seq) at distinct stages of normal B-cell differentiation and B-lymphoid malignancies, with V1 and V3 being the most abundant. During B-cell activation and Epstein-Barr virus infection, redirection of splicing from V1 to V3 coincided with increased CD20 positivity. Similarly, in diffuse large B-cell lymphoma, only V3, but not V1, correlated with CD20 protein levels, suggesting that V1 might be translation-deficient. Indeed, the longer V1 isoform contained upstream open reading frames and a stem-loop structure, which cooperatively inhibited polysome recruitment. By modulating CD20 isoforms with splice-switching morpholino oligomers, we enhanced CD20 expression and anti-CD20 antibody rituximab-mediated cytotoxicity in a panel of B-cell lines. Furthermore, reconstitution of CD20-knockout cells with V3 mRNA led to the recovery of CD20 positivity, whereas V1-reconstituted cells had undetectable levels of CD20 protein. Surprisingly, in vitro CD20-directed chimeric antigen receptor T cells were able to kill both V3- and V1-expressing cells, but the bispecific T-cell engager mosunetuzumab was only effective against V3-expressing cells. To determine whether CD20 splicing is involved in immunotherapy resistance, we performed RNA-seq on 4 postmosunetuzumab follicular lymphoma relapses and discovered that in 2 of them, the downregulation of CD20 was accompanied by a V3-to-V1 shift. Thus, splicing-mediated mechanisms of epitope loss extend to CD20-directed immunotherapies.

Alternative splicing of its 5'-UTR limits CD20 mRNA translation and enables resistance to CD20-directed immunotherapies.

Aberrant skipping of coding exons in CD19 and CD22 compromises responses to immunotherapy for B-cell malignancies. Here, we show that the MS4A1 gene encoding human CD20 also produces several mRNA isoforms with distinct 5' untranslated regions (5'-UTR). Four variants (V1-4) were detectable by RNA-seq in distinct stages of normal B-cell differentiation and B-lymphoid malignancies, with V1 and V3 being the most abundant by far. During B-cell activation and Epstein-Barr virus infection, redirection of splicing from V1 to V3 coincided with increased CD20 positivity. Similarly, in diffuse large B-cell lymphoma only V3, but not V1, correlated with CD20 protein levels, suggesting that V1 might be translation-deficient. Indeed, the longer V1 isoform was found to contain upstream open reading frames (uORFs) and a stem-loop structure, which cooperatively inhibited polysome recruitment. By modulating CD20 isoforms with splice-switching Morpholino oligomers, we enhanced CD20 expression and anti-CD20 antibody rituximab-mediated cytotoxicity in a panel of B-cell lines. Furthermore, reconstitution of CD20-knockout cells with V3 mRNA led to the recovery of CD20 positivity, while V1-reconstituted cells had undetectable levels of CD20 protein. Surprisingly, in vitro CD20-directed CAR T cells were able to kill both V3- and V1-expressing cells, but the bispecific T cell engager mosunetuzumab was only effective against V3-expressing cells. To determine whether CD20 splicing is involved in immunotherapy resistance, we performed RNA-seq on four post-mosunetuzumab follicular lymphoma relapses and discovered that in two of them downregulation of CD20 was accompanied by the V3-to-V1 shift. Thus, splicing-mediated mechanisms of epitope loss extend to CD20-directed immunotherapies. Key Points: In normal & malignant human B cells, CD20 mRNA is alternatively spliced into four 5'-UTR isoforms, some of which are translation-deficient.The balance between translation-deficient and -competent isoforms modulates CD20 protein levels & responses to CD20-directed immunotherapies. Explanation of Novelty: We discovered that in normal and malignant B-cells, CD20 mRNA is alternatively spliced to generate four distinct 5'-UTRs, including the longer translation-deficient V1 variant. Cells predominantly expressing V1 were still sensitive to CD20-targeting chimeric antigen receptor T-cells. However, they were resistant to the bispecific anti-CD3/CD20 antibody mosunetuzumab, and the shift to V1 were observed in CD20-negative post-mosunetuzumab relapses of follicular lymphoma.

The unprecedented 2022 extreme summer heatwaves increased harmful cyanobacteria blooms.

Heatwaves are increasing and expected to intensify in coming decades with global warming. However, direct evidence and knowledge of the mechanisms of the effects of heatwaves on harmful cyanobacteria blooms are limited and unclear. In 2022, we measured chlorophyll-a (Chla) at 20-s intervals based on a novel ground-based proximal sensing system (GBPSs) in the shallow eutrophic Lake Taihu and combined in situ Chla measurements with meteorological data to explore the impacts of heatwaves on cyanobacterial blooms and the potential relevant mechanisms. We found that three unprecedented summer heatwaves (July 4-15, July 22-August 16, and August 18-23) lasting a total of 44 days were observed with average maximum air temperatures (MATs) of 38.1 ± 1.9 °C, 38.7 ± 1.9 °C, and 40.2 ± 2.1 °C, respectively, and that these heatwaves were characterized by high air temperature, strong PAR, low wind speed and rainfall. The daily Chla significantly increased with increasing MAT and photosynthetically active radiation (PAR) and decreasing wind speed, revealing a clear promotion effect on harmful cyanobacteria blooms from the heatwaves. Moreover, the combined effects of high temperature, strong PAR and low wind, enhanced the stability of the water column, the light availability and the phosphorus release from the sediment which ultimately boosted cyanobacteria blooms. The projected increase in heatwave occurrence under future climate change underscores the urgency of reducing nutrient input to eutrophic lakes to combat cyanobacteria growth and of improving early warning systems to ensure secure water management.

Climate change drives rapid warming and increasing heatwaves of lakes.

Climate change could seriously threaten global lake ecosystems by warming lake surface water and increasing the occurrence of lake heatwaves. Yet, there are great uncertainties in quantifying lake temperature changes globally due to a lack of accurate large-scale model simulations. Here, we integrated satellite observations and a numerical model to improve lake temperature modeling and explore the multifaceted characteristics of trends in surface temperatures and lake heatwave occurrence in Chinese lakes from 1980 to 2100. Our model-data integration approach revealed that the lake surface waters have warmed at a rate of 0.11 °C 10a-1 during the period 1980-2021, being only half of the pure model-based estimate. Moreover, our analysis suggested that an asymmetric seasonal warming rate has led to a reduced temperature seasonality in eastern plain lakes but an amplified one in alpine lakes. The durations of lake heatwaves have also increased at a rate of 7.7 d 10a-1. Under the high-greenhouse-gas-emission scenario, lake surface temperature and lake heatwave duration were projected to increase by 2.2 °C and 197 d at the end of the 21st century, respectively. Such drastic changes would worsen the environmental conditions of lakes subjected to high and increasing anthropogenic pressures, posing great threats to aquatic biodiversity and human health.

Urbanization shifts long-term phenology and severity of phytoplankton blooms in an urban lake through different pathways.

Climate change can induce phytoplankton blooms (PBs) in eutrophic lakes worldwide, and these blooms severely threaten lake ecosystems and human health. However, it is unclear how urbanization and its interaction with climate impact PBs, which has implications for the management of lakes. Here, we used multi-source remote sensing data and integrated the Virtual-Baseline Floating macroAlgae Height (VB-FAH) index and OTSU threshold automatic segmentation algorithm to extract the area of PBs in Lake Dianchi, China, which has been subjected to frequent PBs and rapid urbanization in its vicinity. We further explored long-term (2000-2021) trends in the phenological and severity metrics of PBs and quantified the contributions from urbanization, climate change, and also nutrient levels to these trends. When comparing data from 2011-2021 to 2000-2010, we found significantly advanced initiation of PBs (28.6 days) and noticeably longer duration (51.9 days) but an insignificant trend in time of disappearance. The enhancement of algal nutrient use efficiency, likely induced by increased water temperature and reduced nutrient concentrations, presumably contributed to an earlier initiation and longer duration of PBs, while there was a negative correlation between spring wind speed and the initiation of PBs. Fortunately, we found that both the area of the PBs and the frequency of severe blooms (covering more than 19.8 km2 ) demonstrated downward trends, which could be attributed to increased wind speed and/or reduced nutrient levels. Moreover, the enhanced land surface temperature caused by urbanization altered the thermodynamic characteristics between the land and the lake, which, in turn, possibly caused an increase in local wind speed and water temperature, suggesting that urbanization can differently regulate the phenology and severity of PBs. Our findings have significant implications for the understanding of the impacts of urbanization on PB dynamics and for improving lake management practices to promote sustainable urban development under global change.

Bloom-induced internal release controlling phosphorus dynamics in large shallow eutrophic Lake Taihu, China.

High phosphorus (P) concentrations are commonly observed in lakes during algal blooms despite massive efforts on external nutrient reduction. However, the knowledge about the relative contribution of internal P loading linked with algal blooms on lake phosphorus (P) dynamics remains limited. To quantify the effect of internal loading on P dynamics, we conducted extensive spatial and multi-frequency nutrient monitoring from 2016 to 2021 in Lake Taihu, a large shallow eutrophic lake in China, and its tributaries (2017-2021). The in-lake P stores (ILSP) and external loading were estimated and then internal P loading was quantified from the mass balance equation. The results showed that the in-lake total P stores (ILSTP) ranged from 398.5 to 1530.2 tons (t), and exhibited a dramatic intra- and inter-annual variability. The annual internal TP loading released from sediment ranged from 1054.3 to 1508.4 t, which was equivalent to 115.6% (TP loading) of the external inputs on average, and responsible for the fluctuations of ILSTP on a weekly scale. High-frequency observations exemplified that ILSTP increased by 136.4% during algal blooms in 2017, while by only 47.2% as a result of external loading after heavy precipitation in 2020. Our study demonstrated that both bloom-induced internal loading and storm-induced external loading are likely to run counter significantly to watershed nutrient reduction efforts in large shallow lakes. More importantly, bloom-induced internal loading is higher than storm-induced external loading over the short term. Given the positive feedback loop between internal P loadings and algal bloom in eutrophic lakes, which explains the significant fluctuation of P concentration while nitrogen concentration decreased. It is emphasized that internal loading and ecosystem restoration are unignorable in shallow lakes, particularly in the algal-dominated region.

Nutrient reduction mitigated the expansion of cyanobacterial blooms caused by climate change in Lake Taihu according to Bayesian network models.

Although nutrient reduction has been used for lake eutrophication mitigation worldwide, the use of this practice alone has been shown to be less effective in combatting cyanobacterial blooms, primarily because of climate change. In addition, quantifying the climate change contribution to cyanobacterial blooms is difficult, further complicating efforts to set nutrient reduction goals for mitigating blooms in freshwater lakes. This study employed a continuous variable Bayesian modeling framework to develop a model to predict spring cyanobacterial bloom areas and frequencies (the responses) using nutrient levels and climatic factors as predictors. Our results suggested that both spring climatic factors (e.g., increasing temperature and decreasing wind speed) and nutrients (e.g., total phosphorus) played vital roles in spring blooms in Lake Taihu, with climatic factors being the primary drivers for both bloom areas and frequencies. Climate change in spring had a 90% probability of increasing the bloom area from 35 km2 to 180 km2 during our study period, while nutrient reduction limited the bloom area to 170 km2, which helped mitigate expansion of cyanobacterial blooms. For lake management, to ensure a 90% probability of the mean spring bloom areas remaining under 154 km2 (the 75th percentile of the bloom areas in spring), the total phosphorus should be maintained below 0.073 mg·L-1 under current climatic conditions, which is a 46.3% reduction from the current level. Our modeling approach is an effective method for deriving dynamic nutrient thresholds for lake management under different climatic scenarios and management goals.