Variable Nutrient Research Articles

In-field assessment of the variability in water and nutrient use efficiency among potato farmers in a semi-arid climate

Precise water management is imperative for sustainable crop production under irrigation in semi-arid regions with increasingly variable rainfall. Water use efficiencies achieved by farmers often differ widely, even within regions with homogenous agro-ecological conditions. To better understand the drivers of this variability and derive management recommendations, detailed measurements of water and associated nutrient dynamics were conducted on 20 potato farms in two regions of South Africa. Crop characteristics and typical growing conditions in South Africa make potato cultivation sensitive to water and nutrient losses. Water and nutrient inputs and losses through drainage and plant uptake were measured in potato and the follow-up crop, along with yield and weather variables. Seasonal mean irrigation and evapotranspiration were lower in winter crops (240 mm irrigation, 236 mm evapotranspiration) than in summer crops (598 mm irrigation, 608 mm evapotranspiration). Seasonal field water balances were often close to zero, indicating that estimations of evapotranspiration and drainage were representative for the greater field. Lysimeter observations however appeared more representative in sandy unstructured soils than in heavier structured soils. Rainfall during cropping reduced demand for irrigation and increased water use efficiency based on irrigation water, but caused substantial drainage. Leaching of N and K was considerable (on average 30 kg N, 55 kg K ha−1, much higher in some fields), while P leaching was negligible, with the exception of one field (51 kg P ha−1). Variation in water and nutrients use efficiencies was the result of management decisions and environmental factors, such as rainfall and soil type. Without substantial rainfall, application of irrigation scheduling tools can keep drainage and nutrient losses to a minimum, as was observed on almost half the fields, even on sandy soils with a low water holding capacity. Potato yields greatly varied among farmers (9.1–24.7 t dry matter tuber ha−1). Efficient farmers included those who used water sparsely and had minimal drainage, but also farmers who used inputs judiciously and obtained excellent productivity. The role of follow-up crops as users of surplus nutrients and water left behind by the potato crop was not always evident.

Anthropogenic disturbances influence mineral and elemental constituents of freshwater lake sediments.

Lake sediments can provide valuable insights into anthropogenic disturbances such as intensive aquaculture and land use changes. These disturbances often manifest as elevated levels of nutrients and elements within the sediments. This paper uses several analytical techniques, i.e., FTIR (Fourier-transform infrared spectroscopy), XRD (X-ray diffraction), EDS (energy-dispersive X-ray spectroscopy), and SEM (scanning electron microscopy), to examine the elemental constituents of lake sediments, along with their relative mineral abundances and surface morphology. The selected freshwater lakes are from the Central Gangetic Plain. The analysis provides a "fingerprint" of geogenic and biogenic mineral constituents of the sediments. Physicochemical, mineralogical, and elemental analysis shows that intensive aquaculture activities in lake alter the sediment chemistry as evidenced by the increase in pH, organic carbon, organic matter, and total phosphorus which is not observed in the lake where aquaculture is prohibited. Freshwater lake sediment is characterized by a high content of biogenic silica and carbonate minerals. The variations in sediment nutrients and mineral fluxes of the selected lakes are mainly attributed to diverse anthropogenic pressures, differences in lake productivity, and the overall ecological condition of the lakes. In the selected three lakes, major variation was reported in the autochthonous sediments in comparison to the allochthonous sediments. The study concludes that catchment and biotic deposit variations in the lakes cannot be evened out by in-lake mixing mechanisms due to variations in the terrigenous and pelagic deposits of the lake. The results highlight the importance of studying annual fluctuations and spatial variations in geogenic and biogenic mineral particle fluxes in lakes. Such investigations provide valuable insights into the annual dynamics of minerals within lakes, contributing to a more comprehensive understanding of their behavior and distribution.

Space-time dynamics and potential drivers of soil moisture and soil nutrients variation in a coal mining area of semi-arid, China

The spatial–temporal variability of soil moisture plays a pivotal role in the reconstruction and management of ecosystems in mining areas. However, the actual driving mechanisms behind long-term, continuous mining disturbances remain unclear due to a lack of continuous data. To address this gap, a network of instrumented sites, known as Disturbed Critical Zone Observatories (DCZO), has been established for ecological monitoring in mining areas. In this study, we used Sentinel-1A images of the Dafosi Mine from 2014 to 2022 and one year of continuous DCZO monitoring data. We employed Theil-Sen median trend analysis, empirical orthogonal function (EOF), and structural equation modeling (SEM) to quantitatively explore the factors influencing the variability of soil moisture and soil nutrients under continuous mining disturbances. The results showed: (1) Inter-annual variations in soil moisture differed among coal seams mined in various years, with the steepest decline observed in seams mined in 2021–2022 > 2018–2020 > 2015–2017 > 2013–2014. (2) Mining areas exhibited a significant reduction in Available Nitrogen (AN), Available Phosphorus (AP), and Available Potassium (AK), with decreases of 25.12 %, 25.38 %, and 22.59 %, respectively, compared to non-mining areas. (3) The first two EOFs explained 80.42 % of the observed spatiotemporal soil moisture pattern, 77.69 % of AN, 70.21 % of AP, and 88.32 % of AK, accounting for the total variability in soil moisture and soil nutrients. (4) The contribution rates of mining to soil moisture and nutrient variation were 27.31 % and 13.91 %, with subsidence having the most pronounced negative impact. Additionally, our study revealed that while soil moisture can partially recover through natural processes, soil nutrients require artificial reclamation during mining. This study offers valuable insights for sustainable mining management.

Nutrient profiling of Wild Aonla (Emblica officinalis Gaertn.) populations in Northeast India: Assessing the potential of this fruit tree for ecological and human health restoration

Assessing the potential of native species like Emblica officinalis (Aonla) is vital for various reasons. It supports biodiversity conservation, sustainable agriculture, ecological equilibrium, human well-being, and climate resilience. This study, conducted across 30 diverse locations in Arunachal Pradesh, Northeast India, unveiled substantial morphological and nutrient variations among Aonla genotypes. Notable findings include G24's high total soluble solids content, G1's maximum acidity, and G13's elevated total carbohydrate content. G29 stood out with increased pectin, vitamin C, and phosphorus, while G19 exhibited higher total chlorophyll, carotenoids, and potassium. Additionally, genotypes displayed differences in crude protein, total starch, crude fibre, and total phenol content. Four promising genotypes (G29, G19, G24, and G1) hold the potential for genetic crop enhancement, offering benefits in local nutrition, health, soil quality, and water retention, not only in Northeast India but also beyond. This research underscores the significance of understanding and utilizing native resources to foster both ecosystems and human communities.

Phytoplankton carbon biomass: Insights from the eastern Indian Ocean

The study of phytoplankton carbon biomass is limited but has the potential to provide important insights into several oceanographic processes, such as the vertical carbon export and yield from the oceanic food web. In this study, we estimated the carbon biomass of the whole phytoplankton community in the eastern Indian Ocean (EIO) during spring of 2021 using flow cytometry and microscopy. We also examined the effect of physicochemical parameters on the spatial distribution of phytoplankton carbon biomass (phytoplankton-C). In the EIO, the range of phytoplankton-C was between 0.03 and 33.96 μg C L-1, with picophytoplankton (≤2 μm) accounting for 92.41 ± 8.95% and 89.06 ± 13.21% of the total phytoplankton-C in the surface and deep chlorophyll maximum (DCM) layer, respectively. Among various phytoplankton groups, Prochlorococcus and picoeukaryotes accounted for a major part of the phytoplankton-C in the EIO, contributing (57 ± 12%) and (25 ± 7%) to the depth-integrated carbon biomass, respectively. This was followed by Synechococcus (6 ± 4%), diatoms (6 ± 4%) and dinoflagellates (3 ± 1%). Phytoplankton-C exhibited significant variations in both horizontal and vertical distribution within the study area. Horizontally, the distribution of phytoplankton-C was markedly influenced by physical events in the EIO, such as freshwater inputs in the Bay of Bengal, Wyrtki Jet at the Equator and Southern Equatorial Current in the southern EIO. Vertically, different phytoplankton groups exhibited varying distribution patterns in carbon biomass with increasing depths, primarily due to their diverse responses to the vertical variation of irradiance and nutrients in the water column. The total phytoplankton-C in the surface layer (9.56 ± 3.01 μg C L-1) and the DCM layer (9.07 ± 3.75 μg C L-1) did not show a significant difference between each other (t-test, p > 0.1, n = 42), indicating that DCM didn't correspond to a phytoplankton-C maximum but rather a physiological adaptation of C: Chl a ratios of phytoplankton cells in the EIO. Therefore, vertical profiles of Chl a should be interpreted with caution when establishing their ecological significance in the study area. The carbon biomass of the entire phytoplankton community in the EIO was reported in this study, which could enhance our understanding of the contribution of different phytoplankton groups to the carbon pool and their role in the biogeochemical cycle in the EIO.

Seasonal and Tidal variations of DO, BOD, and Nutrients in Major Rivers within Eastern Niger Delta, Nigeria

River channels within the Oil producing Area of Nigeria are highly impacted by the activities of the Oil Companies. This work examined the Dissolved oxygen (DO), Biochemical oxygen demand (BOD), Nitrate (NO3-), Phosphate (PO43-), and sulphate (SO42-) in Calabar, Cross River, Imo, Great Kwa, and Qua-Iboe Rivers using standard procedures. Results showed that, DO, BOD, NO3-, and SO42- were within their limits by NESREA whereas, PO43- was higher than the limit. Mean levels of NO3-, PO43-, and SO42- were higher during the dry season and low tidal regime while DO and BOD showed higher levels in wet season and high tidal regime. Results also indicated that, DO belong to the slightly polluted class, BOD, NO3-, and SO42- belong to the non-polluted class whereas, PO43- varied between moderately polluted and the severely polluted classes in the studied aquatic channels. Generally, the relationships among the parameters varied from one parameter to the other. Principal component analysis (PCA) identified mainly the anthropogenic factor and moderately the natural factor as being responsible for the levels of the parameters assessed in the studied rivers. Hierarchical clusters analysis (HCA) recorded common associations and sources for the DO and BOD, PO43- and SO42- while NO3- had a separate and personal cluster. The study revealed the existing relationships among the studied parameters and their related impact on the health of the aquatic ecosystems investigated.

Changjiang and Kuroshio contributions to oxygen depletion on the Zhejiang Coast

In recent decades, intensified anthropogenic activities have resulted in increasing occurrence of hypoxia in the East China Sea. Kuroshio, as a natural factor, also threatens the oxygen content over the continental shelf. There have been many studies investigating the different contributions of Changjiang and Kuroshio to oxygen depletion over the continental shelf. This study revisited this issue and further investigated the mechanisms controlling the different role of Changjiang and Kuroshio in oxygen depletion and focused mainly on the Zhejiang Coast. A coupled high-resolution physical-biogeochemical model was used to investigate the connections between the variations in nutrients, chlorophyll, stratification, and oxygen and the delivery of Changjiang diluted water and Kuroshio subsurface water over the shelf, especially on the Zhejiang Coast in the summer of 2017. The distinct features of hypoxia off the Changjiang estuary (severe but transient) and that along the Zhejiang Coast (mild but prolonged) are caused by the different dynamic environments and nutrients sources. North of 30˚N, intense oxygen depletion and bottom hypoxia are typically under the constraint of Changjiang diluted water. While the impacts of upwelled materials associated with the Kuroshio subsurface water enhance southward with the simultaneously weakened impacts from the Changjiang diluted water. Besides confirming the support of upwelling on surface phytoplankton bloom along the Zhejiang Coast, this study detected subsurface chlorophyll maximum immediately underneath the main pycnocline offshore of the Zhejiang Coast during upwelling. This indicated that the upwelled oceanic nutrients were transported further offshore along isopycnals and also fertilized phytoplankton growth at the subsurface. The exacerbation of either anthropogenic or natural factors could potentially intensify oxygen depletion along the Zhejiang Coast.

Correction: agricultural land use and morphometry explain substantial variation in nutrient and ion concentrations in lakes across Canada

Correction: agricultural land use and morphometry explain substantial variation in nutrient and ion concentrations in lakes across Canada

Assessment of land use and land cover, water nutrient and metal concentration related to illegal mining activities in an Austral semi–arid river system: A remote sensing and multivariate analysis approach

The mining sector in various countries, particularly in the sub–Saharan African region, faces significant impact from the emergence of small–scale unlicensed artisanal mines. This trend is influenced by the rising demand and prices for minerals, along with prevalent poverty levels. Thus, the detrimental impacts of these artisanal mines on the natural environment (i.e., rivers) have remained poorly understood particularly in the Zimbabwean context. To understand the consequences of this situation, a study was conducted in the Umzingwane Catchment, located in southern Zimbabwe, focusing on the variations in water nutrient and metal concentrations in rivers affected by illegal mining activities along their riparian zones. Using multi–year Sentinel–2 composite data and the random forest machine learning algorithm on the Google Earth Engine cloud–computing platform, we mapped the spatial distribution of illegal mines in the affected regions and seven distinct land use classes, including artisanal mines, bare surfaces, settlements, official mines, croplands, and natural vegetation, with an acceptable overall and class accuracies of ±70 % were identified. Artisanal mines were found to be located along rivers and this was attributed to their large water requirements needed during the mining process. The water quality analysis revealed elevated nutrient concentrations, such as ammonium and nitrate (range 0.10–20.0 mg L−1), which could be attributed to mine drainage from the use of ammonium nitrate explosives during mining activities. Additionally, the prevalence of croplands in the area may have potentially contributed to increased nutrient concentrations. The principal component analysis and hierarchical cluster analysis revealed three clusters, with one of these clusters showing parameters like Ca, Mg, K, Hg and Na, which are usually associated with mineral gypsum found in the drainage of artisanal mines in the selected rivers. Cluster 2 consisted of B, Cu, Fe, Pb, and Mn, which are likely from the natural environment and finally, cluster 3 contained As, Cd, Cr, and Zn, which were likely associated with both legal and illegal mining operations. These findings provide essential insights into the health of the studied river system and the impacts of human activities in the region. They further serve as a foundation for developing and implementing regulatory measures aimed at protecting riverine systems, in line with sustainable development goal 15.1 which focuses on preserving and conserving terrestrial and inland freshwater ecosystems, including rivers. By acting on this information, authorities can work towards safeguarding these vital natural resources and promoting sustainable development in the area.

Rice bacterial leaf blight drives rhizosphere microbial assembly and function adaptation.

Our results suggest that rhizosphere bacteria are more sensitive to bacterial leaf blight (BLB) than fungi. BLB infection decreased the diversity of the rhizosphere bacterial community but increased the complexity and size of the rhizosphere microbial community co-occurrence networks. In addition, the relative abundance of the genera Streptomyces, Chitinophaga, Sphingomonas, and Bacillus increased significantly. Finally, these findings contribute to the understanding of plant-microbiome interactions by providing critical insight into the ecological mechanisms by which rhizosphere microbes respond to phyllosphere diseases. In addition, it also lays the foundation and provides data to support the use of plant microbes to promote plant health in sustainable agriculture, providing critical insight into ecological mechanisms.

Multi-year hyperspectral remote sensing of a comprehensive set of crop foliar nutrients in cranberries

Hyperspectral remote sensing has emerged as an efficient tool to quantify the spatial and temporal variations in crop foliar nutrients, thus reducing the burden on in-situ tissue sampling and traditional chemical assays. However, the physical mechanism of hyperspectral remote sensing of foliar nutrients is under-explored, especially for those lacking absorption features. Using four-year data collected from a cranberry farm, we demonstrate the capacity of leaf and imaging spectroscopy to quantify a comprehensive set of crop foliar nutrients, including seven macronutrients (N, P, K, Mg, Ca, S, Na) and five micronutrients (Fe, Mn, B, Cu, Zn). Specifically, we: 1) compared the performance of four data-driven approaches to estimate foliar nutrients at both leaf and canopy scales, including partial least square regression (PLSR), support vector regression (SVR), Gaussian process regression (GPR) and random forest regression (RFR); and 2) explored the physical basis of hyperspectral remote sensing of foliar nutrients. Our results showed that: 1) at leaf scales linear approaches PLSR and SVR performed best for nine nutrients (P, Mg, Ca, S, Na, Fe, B, Cu and Zn), whereas nonlinear approaches GPR and RFR performed best only for three nutrients (N, K and Mn); 2) at canopy scales no data-driven approach significantly outperformed others; 3) the best modelling accuracy varied with foliar nutrients (leaf scales: R2 from 0.30 to 0.93 and RRMSE from 9 to 51%; canopy scales: R2 from 0.15 to 0.81 and RRMSE from 7 to 37%). The physical basis of hyperspectral remote sensing of foliar nutrients was mainly attributed to their strong correlations with leaf compounds that have apparent absorption features. More specifically, at leaf scales the correlation between foliar nutrients and LMA (leaf mass per area) was leveraged by models to predict foliar nutrients from leaf spectra; at canopy scales the correlation of foliar nutrients with leaf chlorophyll and canopy LAI (Leaf area index) was leveraged by models to predict foliar nutrients from canopy spectra. This study revealed the importance of trait correlations in predicting foliar nutrients, and improved our understanding of the physical mechanisms in hyperspectral remotes sensing of foliar nutrients.

Relationship between rumen bacterial community and milk fat in dairy cows.

Milk fat is the most variable nutrient in milk, and recent studies have shown that rumen bacteria are closely related to milk fat. However, there is limited research on the relationship between rumen bacteria and milk fatty. Fatty acids (FAs) are an important component of milk fat and are associated with various potential benefits and risks to human health. In this experiment, forty-five healthy Holstein dairy cows with alike physiological and productive conditions were selected from medium-sized dairy farms and raised under the same feeding and management conditions. The experimental period was two weeks. During the experiment, raw milk and rumen fluid were collected, and milk components were determined. In this study, 8 high milk fat percentage (HF) dairy cows and 8 low milk fat percentage (LF) dairy cows were selected for analysis. Results showed that the milk fat percentage in HF group was significantly greater than that of the dairy cows in the LF group. 16S rRNA gene sequencing showed that the rumen bacterial abundance of HF dairy cows was significantly higher than that in LF dairy cows; at the genus level, the bacterial abundances of Prevotellaceae_UCG-001, Candidatus_Saccharimonas, Prevotellaceae_UCG-003, Ruminococcus_1, Lachnospiraceae_XPB1014_group, Lachnospiraceae_AC2044_group, probable_genus_10 and U29-B03 in HF group were significantly higher than those in the LF group. Spearman rank correlation analysis indicated that milk fat percentage was positively related to Prevotellaceae_UCG-001, Candidatus_Saccharimonas, Prevotellaceae_UCG-003, Ruminococcus_1, Lachnospiraceae_XPB1014_group, Lachnospiraceae_AC2044_group, probable_genus_10 and U29-B03. Furthermore, Prevotellaceae_UCG-001 was positively related to C14:0 iso, C15:0 iso, C18:0, Ruminococcus_1 with C18:1 t9, Lachnospiraceae_AC2044_group with C18:1 t9 and C18:1 t11, U29-B03 with C15:0 iso. To sum up, rumen bacteria in dairy cows are related to the variation of milk fat, and some rumen bacteria have potential effects on the deposition of certain fatty acids in raw milk.

Interaction between temperature and nutrients: How does the phytoplankton community cope with climate change?

Climate change and increasing nutrient concentrations are two major threats to lake ecosystems. Furthermore, warming is exacerbating the symptoms of eutrophication in freshwaters. Facing both environmental challenges simultaneously is more urgent than ever to preserve and recover water quality and protect the remaining biodiversity. Here, we used long-term observational data to investigate the phytoplankton response to the interaction between temperature and nutrient variations in a deep mesotrophic subalpine lake (L. Iseo, Italy). Despite the existing management programs, we observed a deterioration of the physicochemical status of the lake between 1993 and 2021 in the water column. The average rate of temperature increase was 0.02 °C y−1 across the studied period and accelerated after the last complete mixing events (2005 and 2006), particularly during the last decade (0.08 °C y−1). Water warming caused severe impacts on nutrient cycling, reflected by the overall increase in nutrient concentrations. The direct effect of warming was of great importance for phytoplankton, leading to an increase in total biovolume and a loss of diversity and promoting the dominance of Cyanobacteria. Nutrient variations, especially TN and the DSi:TP ratio, considerably structured the community composition. The modification of physicochemical parameters caused by the last complete mixing events led to a remarkable, long-term taxonomical and functional reorganization of the phytoplankton community. This study illustrates that phytoplankton in deep subalpine lakes will experience severe changes in the upcoming years, and that complete mixing events may constitute a threshold for community transformation. Our results stress the importance of using powerful interpretative models with multifaceted long-term datasets to disentangle the pathways by which temperature and nutrients could regulate the phytoplankton community. Our conclusions will help to integrate climate change into mitigation strategies to preserve ecosystem structure and functions.

Calibration versus computation: Comparison between 1D and 3D phytoplankton simulations in western Lake Erie

Abstract Numerical models are commonly used tools to simulate hydrodynamics and water quality of lakes. Model dimensionality (0D, 1D, 2D, or 3D) requires different simplification levels of physical-biogeochemical processes, computational power and calibration strategies and metrics against observations. To investigate these modelling considerations, the 1D (vertical) Aquatic Ecosystem Dynamics – General Lake Model and the 3D Aquatic Ecosystem Model were applied to western Lake Erie in 2008 and 2011-14. The performance of the models was evaluated by comparing the simulations against observations of water temperature, total phosphorus, orthophosphate, nitrate, total chlorophyll-a and cyanobacteria at three stations located along a transect from the Maumee River mouth to mid-basin, as well as to the basin-averaged cyanobacteria index. The 3D model showed better skill in qualitatively reproducing seasonal and spatial variations of nutrients and phytoplankton and had lower average root-mean-square error, especially through the algal plume near the Maumee River mouth. However, the horizontally averaged 1D model performed better in qualitatively capturing the cyanobacteria bloom years, as this model was extensively calibrated to basin-average values. We conclude that models should be selected and calibrated to provide the required decision support information, rather than the highest resolution or lowest error metrics at discrete sites.

Comparing the predictive ability of Sentinel-2 multispectral imagery and a proximal hyperspectral sensor for the estimation of pasture nutritive characteristics in an intensive rotational grazing system

Using remote sensing to estimate the nutritive characteristics of pasture in livestock systems is a rapidly developing area that has the potential to improve pasture management and utilisation and in turn improve livestock productivity. The Copernicus Sentinel-2 paired satellites have shown promise in predicting pasture nutritive characteristics and have a pixel size small enough to be able to identify intra-paddock nutrient variation in rotational dairy grazing systems where paddock sizes are small. This study sought to develop nutrient prediction models using a dataset of nine Sentinel-2A and -2B satellite images, by linking imagery to perennial ryegrass dairy pasture samples cut within known pixels of the images in the days directly after each cloud-free overpass. Just before destructive pasture sampling, a handheld, proximal, hyperspectral sensor was used to gather spectral signatures (400–2500 nm) from areas to be sampled. Pasture samples (n = 200) were analysed using wet chemistry techniques for seven nutritive characteristics. The dry matter concentration of the samples was also measured, creating eight variates to be modelled in total. The Sentinel-2 data from within the selected pixels was extracted and used to create input features for Random Forest prediction models. Input features included the raw multispectral bands, common vegetation indices, and independent variables ‘season’ and ‘month’. Predictive models were also developed from the hyperspectral sensor data using Partial Least Squares Regression. For both modelling types, variable selection was used to reduce model inputs to only those sensitive to each nutrient. Results comparing the final models in an independent validation test showed similar predictive performance of the Sentinel-2 satellite and the proximal hyperspectral sensor for all variates of interest, shown by mean absolute errors that were not significantly different. In each case, the dry matter concentration was the best predicted variable (Lin’s concordance correlation coefficient (LCCC) > 0.90) with excellent potential to be quantified by Sentinel-2 satellites. Crude protein, metabolisable energy, neutral detergent fibre, non-fibre carbohydrate, and water-soluble carbohydrate concentrations were also predicted with good to moderate accuracy by both sensors (LCCC between 0.50 and 0.80). These models would be sufficiently accurate for making qualitative predictions (e.g., grouping into high to low categories). Ash and acid detergent fibre concentrations were poorly predicted (LCCC < 0.50) and these models would not be recommended for further use. It was concluded that multispectral data from Sentinel-2 has great potential to estimate pasture nutrient concentrations for intensively grazed pastures such as those used in dairy systems in temperate regions.

Nutrient coordination mechanism of tiger nut induced by rhizosphere soil nutrient variation in an arid area, China

Nutrient coordination mechanism of tiger nut induced by rhizosphere soil nutrient variation in an arid area, China

Influencia de la variación de nutrientes en la alimentación sobre la acumulación de AbrB, esporulación y expresión de cry1Ac durante cultivos por lote alimentado de Bacillus thuringiensis

The biological control agent Bacillus thuringiensis (Bt) coordinates metabolic and gene regulation functions to enter to the differentiation process for the synthesis of spores and Cry toxin proteins. The master regulator for sporulation initiation is Spo0A, while AbrB regulator coordinate cellular functions during vegetative and transition growth. To understand how differentiation is modified during fed-batch cultures (FBC) of Bt under variable nutrient conditions, we conducted fermentations with two different nutrient concentration and feeding times using an industrial medium. Since sporulation efficiency has been lower in FBCs than in batch cultures, AbrB was monitored by Western blot during these cultures. Kinetic parameters were used to stablish timing of cell differentiation process, and fermentations were monitored on-line using impedance spectroscopy. AbrB was accumulated during the entire fed-batch culture, when a medium with the highest concentration of carbon and nitrogen sources (FBC1) were fed. Under these conditions, sporulation efficiency and cry1Ac expression were negatively affected, compared to the wild-type strain. Conversely, when the feeding concentration was only half of FBC1, AbrB accumulates in minor proportion, and sporulation efficiency and cry1Ac expression increased (FBC2). These results suggest that variable nutrient conditions can cause an imbalance in the accumulation of transition state regulators such as AbrB during FBCs, which can be detrimental to produce spores and Cry proteins, that are the main Bt products for biological control of agricultural pests.

Phytochemical diversity impacts herbivory in a tropical rainforest tree community.

Metabolomics provides an unprecedented window into diverse plant secondary metabolites that represent a potentially critical niche dimension in tropical forests underlying species coexistence. Here, we used untargeted metabolomics to evaluate chemical composition of 358 tree species and its relationship with phylogeny and variation in light environment, soil nutrients, and insect herbivore leaf damage in a tropical rainforest plot. We report no phylogenetic signal in most compound classes, indicating rapid diversification in tree metabolomes. We found that locally co-occurring species were more chemically dissimilar than random and that local chemical dispersion and metabolite diversity were associated with lower herbivory, especially that of specialist insect herbivores. Our results highlight the role of secondary metabolites in mediating plant-herbivore interactions and their potential to facilitate niche differentiation in a manner that contributes to species coexistence. Furthermore, our findings suggest that specialist herbivore pressure is an important mechanism promoting phytochemical diversity in tropical forests.

Multi-scenario simulation of runoff and nutrient loads in a rapidly urbanizing watershed during China's Dual Carbon periods

Apprehending the hydrological and nutrient variations in rapidly urbanizing watersheds under changing environments is crucial for pollution control and water resource management. However, existing studies have primarily focused on hydrological processes, neglecting water quality aspects, and comprehensive assessment of future runoff and nutrient loads in these watersheds during China's Dual Carbon periods is limited. This study firstly bridges these gaps by constructing multi-scenario with different levels of “Urban Development - Ecological Conservation” and utilizing latest bias-corrected General Circulation Models or Global Climate Models (GCMs) projections to evaluate future runoff and nutrient loads in the Shenzhen River. The calibrated and validated models display satisfactory performance in simulating runoff, nutrient loads, and land use types. The bias-corrected GCMs projections exhibit enhanced accuracy for temperature variables, particularly during the wet season. Implementing effective ecological protection measures is paramount in mitigating water quantity fluctuations and controlling total nitrogen pollution, which is closely associated with urban development and human activities. Conversely, total phosphorus loads demonstrate greater simulation uncertainty, particularly during the dry season of the Carbon Neutrality period, requiring further exploration. Compared to the baseline period, runoff changes minimally, with notable seasonal variations. The findings highlight the escalating uncertainty in load predictions as time progresses. Additionally, addressing uncertainties in precipitation projections driven by GCMs is imperative, given their substantial influence on runoff and nutrient load simulations, particularly during challenging dry seasons. While further research is needed to reduce simulation uncertainty, our study provides valuable insights into nitrogen-phosphorus pollution control and sustainable water resource management in rapidly urbanizing watersheds, especially during the near-term period.

Nutrient dynamics in the Bohai and North Yellow seas from seasonal to decadal scales: Unveiling Bohai Sea eutrophication mitigation in the 2010s

The eutrophication status in the central Bohai Sea tends to be mitigated in recent years. To explore the recent nutrient status, seasonal surveys were carried out from 2018 to 2021, covering both the Bohai Sea and the adjacent North Yellow Sea. In recent cold seasons, both dissolved inorganic nitrogen concentration (DIN) and the ratio of DIN to soluble reactive phosphorus were lower than those in 2016. In warm seasons, the variations in nutrients and apparent oxygen utilization were correlated with each other, roughly following the traditional Redfield ratio of N:P:O2 of approximately 16:1:(−138). When historical data for N*, which is the excess DIN related to soluble reactive phosphorus, was collated, the Bohai Sea showed a decreasing trend for N* at a rate of −0.64 ± 0.12 μmol N* kg−1 a−1 between 2011 and 2021. During the same period, the North Yellow Sea N* concentrations (i.e., the oceanic end-member of the Bohai Sea N* dynamics) and the local atmospheric nitrogen (N) deposition (atmospheric end-member) were estimated to decline at rates of −0.22 ± 0.04 μmol N* kg−1 a−1 and − 0.93 ± 0.34 kg N ha−1 a−2, respectively. Consequently, the oceanic and atmospheric changes accounted for 25.7 % ± 28.4 % and 69.0 % ± 42.6 %, respectively, of the Bohai Sea eutrophication mitigation in 2011–2021. On the long-term changes of the Bohai Sea eutrophication, the terrestrial nutrient source has only minor (likely <10 %) impacts, although it certainly affects the spatial distribution of nutrients. This study has implied that coastal eutrophication is a dynamic process that is subject to sea–land–air interactions, and its mitigation needs both local pollution controls and regional environment management. The latter contains the understanding of oceanic changes and external effects of the air pollution control.