Evaluating the vulnerability of Tetracentron sinense habitats to climate-induced latitudinal shifts.

Exploring the changing process of the geographical distribution pattern of Tetracentron sinense Oliv. and its main influencing factors since the last interglacial period can provide a scientific basis for the effective protection and management of the species. The MaxEnt model was used to construct the potential distribution areas of T. sinense in different periods such as the last interglacial (LIG), the last glacial maximum (LGM), the mid-Holocene (MID), and the current and future (2050s and 2070s). On the premise of discussing the influence of dominant environmental factors on its distribution model, the suitable area changes of T. sinense under different ecological climate situations were quantitatively analyzed. (1) The AUC and TSS values predicted by the optimized model were 0.959 and 0.835, respectively, indicating a good predictive effect by the MaxEnt model; the potential suitable areas for T. sinense in the current period are mainly located in Southwest China, which are wider compared to the actual habitats. (2) Jackknife testing showed that the lowest temperature in the coldest month (Bio6), elevation (Elev), seasonal variation coefficient of temperature (Bio4), and surface calcium carbonate content (T-CACO3) are the dominant environmental factors affecting the distribution of T. sinense. (3) From the last interglacial period to the current period, the total suitable area of T. sinense showed a decreasing trend; the distribution points of T. sinense populations in mid-Holocene period may be the origin of the postglacial population, and Southwest China may be its glacial biological refuge. (4) Compared with the current period, the total suitable area ranges of T. sinense in China in the 2050s and 2070s decreased, and the centroid location of its total fitness area all migrated to the northwest, with the largest migration distance in 2070s under the SSPs 7.0 climate scenario. Temperature was the principal factor influencing the geographical distribution of T. sinense. With global warming, the range of T. sinense suitable areas will show a shrinking trend, with a shift toward higher-latitude regions. Ex situ conservation measures could be taken to preserve its germplasm resources.

Risk Factors and Effects of Climate Lag on Vibrio Parahaemolyticus Infection in Eastern Coastal Cities of China: A Study Based on Hangzhou City.

Bacterial foodborne diseases caused by Vibrio parahaemolyticus pose persistent challenges to coastal cities in China. In this study, we employed multiple logistic regression analysis and distributed lag non-linear models (DLNM) to investigate the epidemiological characteristics and associated risk factors of vibriosis in the metropolitan area of Hangzhou from 2014 to 2018. Analysis of foodborne cases indicated that certain demographics and occupational factors, including age between 16 and 44 years; houseworkers or unemployed individuals; preference for aquatic and meat products; and dining in collective canteens or catering services contribute to an increased likelihood of V. parahaemolyticus infection. Moreover, a higher per capita GDP and exposure to high temperatures were identified as risk factors for vibriosis. This study highlights the significance of the daily mean temperature as a meteorological factor influencing V. parahaemolyticus infection, with varying lag effects observed depending on temperature conditions. At low temperatures, the risk of infection occurs after a lag of 21 days, whereas at high temperatures, the risk is highest on the same day, while the second infection risk period occurs after a lag of 21 days. These findings provide a spatiotemporal perspective of the risk analysis of foodborne diseases, with a daily timescale and street spatial scale, which contributes to the development of public health strategies and food safety protocols in coastal cities.

[A longitudinal study of subjective olfactory function post-operatively in chronic rhinosinusitis patients with asthma and analysis of influencing factors].

Objective:To evaluate the subjective olfactory function in chronic sinusitis（CRS）patients with asthma after nasal endoscopic surgery and associated factors that may affect olfactory function. Methods：The study included 90 CRS patients with asthma from January 2008 to December 2020，and all of them underwent endoscopic sinus surgery（ESS）. VAS score of olfactory function before and after surgery were collected，and the data at baseline，3 months，6 months，1 year，3 years，5 years，8 years and 10 years after surgery were compared. Factors affecting olfactory function were analyzed in a generalized mixed linear model，which including age，surgical procedure，allergic rhinitis and so on.Results： The olfactory VAS scores were significantly lower at 3 months，6 months，1 year，3 years，and 5 years postoperatively compared with baseline，and the difference was statistically significant（P<0.05）.Olfactory VAS scores at 8 and 10 years postoperatively were not statistically different from baseline（P>0.05）.Age（≥60 years），aspirin intolerance syndrome，Lund-Kennedy score，modified sinus CT olfactory cleft score，and follow-up time were risk factors, and radical sinus surgery is a protective factor.Conclusion：Subjective olfactory scores in CRS patients with asthma after ESS remain relatively stable for 5 years postoperatively.Prior history of surgery did not affect postoperative subjective olfactory scores. Age，aspirin intolerance syndrome, Lund-Kennedy score，modified sinus CT olfactory cleft score, follow-up time，and surgical approach were strongly associated with subjective olfactory scores in CRS patients with asthma，and radical surgery had a protective effect on olfaction.

Analysis of dissolved oxygen influencing factors and concentration prediction using input variable selection technique: A hybrid machine learning approach.

Accurate quantification of dissolved oxygen (DO) is critically important for the protection and management of aquatic ecosystems. Successful applications have utilized mechanistic and data-driven models to simulate DO content in aquatic ecosystems. However, mechanistic models present challenges due to their complex and difficult-to-solve conditions, making them less portable. Additionally, data-driven model predictions are hindered by the challenge of numerous input variables, impacting both the running speed and prediction performance of the model. To address these challenges, water quality data and meteorological data of the Tanjiang River were obtained. The maximum information coefficient (MIC) input variable selection technique was employed to identify primary environmental factors influencing DO changes. Furthermore, coupled with support vector regression (SVR), two models (SVR and MIC-SVR) were employed to estimate the DO concentration of the Tanjiang River, and the optimal model was established. The results indicated a shift in the primary pollution factor from ammonia nitrogen to total phosphorus after recent treatment in the Tanjiang River. In comparison with the SVR model, the root mean square error (RMSE) of the MIC-SVR model was reduced by 4.46%, and the Nash-efficiency coefficient (NSE) was improved by 45.85%. In addition, study of kernel function selection revealed that considering as many kernel functions as possible is necessary for improving the performance of the SVR model. Conclusively, the proposed MIC-SVR model serves as an effective tool to analyze the relationship between DO and environmental factors, identifying the primary causes of low DO, and accurately predict the DO concentration in the Tanjiang River (especially in its middle and lower reaches), thus providing a reference for governmental decision-making on water environmental protection and water resource management.

Factors impacting human exposure to legacy and emerging contaminants in residential dust in Beijing, China: Characteristics of indoor microenvironment.

Exposure to indoor dust is of concern since dust may be contaminated by various toxic chemicals and people spend considerable time indoors. Factors impacting human exposure risks to contaminants in indoor dust may differ from those affecting the loadings of contaminants, but the dominant factors have not yet been well clarified. In this study, the occurrence, human exposure, and related influencing factors of several classes of legacy and emerging contaminants in residential dust across Beijing were investigated, including per- and polyfluoroalkyl substances (PFASs) and three types of flame retardants (FRs), i.e., organophosphate esters (OPEs), polybrominated diphenyl ethers (PBDEs), and novel halogenated FRs (NHFRs). OPEs (median: 3847 ng/g) were the most abundant group, followed by PBDEs (1046 ng/g) and NHFRs (520 ng/g). PFASs (14.3 ng/g) were one to two orders of magnitude lower than FRs. The estimated daily intakes of these contaminants were relatively higher for toddlers than other age groups, with oral ingestion being the main exposure pathway compared with dermal contact. Higher human exposure risks were found in new buildings or newly finished homes due to the elevated intake of emerging contaminants (such as OPEs). Furthermore, higher risks were also found in homes with wooden floors, which were mainly associated with higher levels of PFASs, chloroalkyl and alkyl OPEs, compared with tile floors. Citizens in the urban area also showed higher exposure risks than those in the suburban area. The quantity of household appliances and finishing styles (simple or luxurious) showed an insignificant impact on overall human exposure risks despite their significant effect on the levels of some of the dust contaminants. Results in this study are of importance in understanding human exposure to the co-existence of multiple contaminants in indoor dust.

Evidence of economic development revealed in centennial scale sedimentary records of organic pollutants in Huguangyan Marr Lake.

Sedimentary records of polycyclic aromatic hydrocarbons (PAHs) and phthalates could reflect energy consumption and industrial production adjustment. However, there is limited knowledge about their effects on variations of PAH and phthalate compositions in the sediment core. The PAH and phthalate sedimentary records in Huguangyan Maar Lake in Guangdong, China were constructed, and random forest models were adopted to quantify the associated impact factors. Sums of sixteen PAH (∑16 PAH) and seven phthalate (∑7 PAE) concentrations in the sediment ranged from 28.8 to 1110 and 246-4290 µg/kg dry weight in 1900-2020. Proportions of 5-6 ring PAHs to the ∑16 PAHs increased from 32.0 %-40.7 % in 1900-2020 with increased coal and petroleum consumption, especially after 1980. However, those of 2-3 ring PAHs decreased from 30.7 % to 23.6 % due to the biomass substitution with natural gas. The proportions of bis (2-ethylhexyl) phthalate to the ∑7 PAEs decreased from 52.3 %-29.1 % in 1900-2020, while those of di-isobutyl phthalate increased (13.7 % to 42.3 %). The shift from traditional plasticizers to non-phthalates drove this transformation, though the primary plastic production is increasing. Our findings underscore the effectiveness of optimizing energy structures and updating chemical products in reducing organic pollution in aquatic environments.

Interpreting and modelling the daily extreme sediment events in karst mountain watersheds.

Increasingly frequent extreme rainfall as a result of climate change is strongly damaging the global soil and water environment. However, few studies have focused on daily extreme sediment events (DESE) in heterogeneous karst watersheds based on long-term in-situ observations. This study quantitatively assessed the time effect of DESE on rainfall response, decoupled the impact of environmental factors on DESE by using structural equation modelling, and finally explored the modelling scheme of DESE based on the hybrid model. The results showed that DESE had the highest frequency of occurrence in May-July, with dispersed distribution in the value domain. Rainfall with a time lag of 1 day and a time accumulation of 2 or 3 days was an important contribution to DESE (P < 0.01, R = 0.47-0.68). Combined effects of environmental factors explained 53.6 %-64.1 % of the variation in DESE. Runoff and vegetation exerted the strongest direct and indirect effects on DESE, respectively (ß = 0.66/-0.727). Vegetation was the dominant driver of DESE in Dabanghe and Yejihe (ß = -0.725/-0.758), while the dominant driver in Tongzhihe was climate (ß = 0.743). In the future, the risk of extreme sediments should be prevented and resolved through the comprehensive regulation of multiple paths, such as runoff and vegetation. Hybrid models significantly improved the modelling performance of machine learning models. Generalized additive model-Extreme gradient boost had the best performance, while Partial least squares regression-Extreme gradient boost was the most valuable when considering performance and input data cost. Two methods can be used as recommended solutions for DESE modelling. This study provides new and in-depth insights into DESE in karst watersheds and helps the region develop forward-looking soil and water management models to cope with future extreme erosion hazards.

The Spatial Niche and Influencing Factors of Desert Rodents.

Resource partitioning may allow species coexistence. Sand dunes in the typical steppe of Alxa Desert Inner Mongolia, China, consisting of desert, shrub, and grass habitats, provide an appropriate system for studies of spatial niche partitioning among small mammals. In this study, the spatial niche characteristics of four rodents, Orientallactaga sibirica, Meriones meridianus, Dipus sagitta, and Phodopus roborovskii, and their responses to environmental changes in the Alxa Desert were studied from 2017 to 2021. Using the capture-mark-recapture method, we tested if desert rodents with different biological characteristics and life history strategies under heterogeneous environmental conditions allocate resources in spatial niches to achieve sympatric coexistence. We investigated the influence of environmental factors on the spatial niche breadth of rodents using random forest and redundancy analyses. We observed that the spatial niche overlap between O. sibirica and other rodents is extremely low (overlap index ≤ 0.14). P. roborovskii had the smallest spatial niche breadth. Spatial niche overlap was observed in two distinct species pairs, M. meridianus and D. sagitta, and P. roborovskii and D. sagitta. The Pielou evenness index of rodent communities is closely related to the spatial distribution of rodents, and the concealment of habitats is a key factor affecting the spatial occupation of rodents.

Formation of halonitromethanes from benzylamine during UV/chlorination: Impact factors, toxicity alteration, and pathways.

Halonitromethanes (HNMs), a representative nitrogen-containing disinfection byproduct, have gained significant concerns due to their higher cytotoxicity and genotoxicity. UV/chlorination is considered a promising alternative disinfection technology for chlorination. This study aimed to investigate the HNMs formation from benzylamine (BZA) during UV/chlorination. The experimental results revealed that the yields of HNMs initially raised to a peak then dropped over time. Higher chlorine dosage and BZA concentration promoted the formation of HNMs, whereas alkaline pH inhibited their formation. The presence of bromine ion (Br-) not only converted chlorinated-HNMs (Cl-HNMs) to brominated (chlorinated)-HNMs Br (Cl)-HNMs) and brominated-HNMs (Br-HNMs) but also enhanced the total concentration of HNMs. Besides, the calculated cytotoxicity index (CTI) and genotoxicity index (GTI) of HNMs were elevated by 68.97% and 60.66% as Br- concentration raised from 2 to 6 µM. The possible formation pathways of HNMs from BZA were proposed based on the intermediates identified by a gas chromatography/mass spectrometry (GC/MS). In addition, the formation rules of HNMs in actual water verified the results in deionized water during UV/chlorination. The results of this study provide basic data and a theoretical basis for the formation and control of HNMs, which is conducive to applying UV/chlorination.

An enhanced multi-attribute crowd evacuation model incorporating the effects of environmental impact factors.

We propose an enhanced floor field model (FFM) to analyze the behavioral characteristics of crowds with varying attributes proportions during evacuation. This model governs pedestrian movement through the Dynamic Floor Field (DFF) and the Static Floor Field (SFF). The DFF takes into account individual factors such as the gender, familiarity with the environment, and social relationships of evacuees, which influence safe evacuation. Concurrently, the SFF encapsulates the impact of environmental factors like obstacles, exits, and guidance effects. Subsequently, this refined FFM was applied and validated using a sports center evacuation scenario. The results demonstrated that the enhanced FFM accurately replicated evacuees' asymmetric behavior and queuing, and aligned well with other models when the number of evacuees fluctuated over time. In the absence of guidance, both environmental familiarity and gender emerged as primary factors influencing partial evacuation. Additionally, the gender of pedestrians significantly affected the overall evacuation. Notably, compared to pre-existing environmental information available to evacuees, the implementation of guidance to augment pedestrians' environmental familiarity resulted in a more efficient evacuation. The FFM model and these findings could be instrumental in simulating personnel evacuation and formulating emergency management strategies in crowded areas.

Plastic film mulching application improves potato yields, reduces ammonia emissions, but boosts the greenhouse gas emissions in China.

With global population growth and climate change, food security and global warming have emerged as two major challenges to agricultural development. Plastic film mulching (PM) has long been used to improve yields in rain-fed agricultural systems, but few studies have focused on soil gas emissions from mulched rainfed potatoes on a long-term and regional scale. This study integrated field data with the Denitrification-Decomposition (DNDC) model to evaluate the impacts of PM on potato yields, greenhouse gas (GHG) and ammonia (NH3) emissions in rainfed agricultural systems in China. We found that PM increased potato yield by 39.7 % (1505 kg ha-1), carbon dioxide (CO2) emissions by 15.4 % (123 kg CO2 eq ha-1), nitrous oxide (N2O) emissions by 47.8 % (1016 kg CO2 eq ha-1), and global warming potential (GWP) by 38.9 % (1030 kg CO2 eq ha-1), while NH3 volatilization decreased by 33.9 % (8.4 kg NH3 ha-1), and methane (CH4) emissions were little changed compared to CK. Specifically, the yield after PM significantly increased in South China (SC), North China (NC), and Northwest China (NWC), with increases of 66.1 % (2429 kg ha-1), 44.1 % (1173 kg ha-1), and 43.6 % (956 kg ha-1) compared to CK, respectively. The increase in GWP and greenhouse gas emission intensity (GHGI) under PM was more pronounced in the Northeast China (NEC) and NWC regions, with respective increases of 57.1 % and 60.2 % in GWP, 16.9 % and 10.3 % in GHGI. While in the Middle and Lower reaches of the Yangtze River (MLYR) and SC, PM decreased GHGI with 10.2 % and 31.1 %, respectively. PM significantly reduced NH3 emissions in all regions and these reductions were most significant in Southwest China (SWC), SCand MLYR, which were 41 %, 38.0 %, and 38.0 % lower than CK, respectively. In addition, climatic and edaphic variables were the main contributors to GHG and NH3 emissions. In conclusion, it is appropriate to promote the use of PM in the MLYR and SC regions, because of the ability to increase yields while reducing environmental impacts (lower GHGI and NH3 emissions). The findings provide a theoretical basis for sustainable agricultural production of PM potatoes.

Evidencing the impacts of health research: Insights from trials reported in the 2018 Australian Engagement and Impact Assessment.

ISSUE ADDRESSED: While definitions of impact may vary, they often refer to the wider benefits of research evidenced beyond academia. We evaluated case studies featuring randomised trials from the 2018 Engagement and Impact Assessment to better understand how the impacts of health research are evidenced and assessed within Australia. METHODS: We collated and evaluated 'high' scoring case studies submitted by higher education institutions with a focus on randomised trials across all areas of health research. A qualitative coding system was used for manual content analysis to assess the key characteristics of trials reported, subsequent impacts and the methods used to evidence impacts. RESULTS: A total of 14 case studies were identified citing 35 clinical trials. The majority of interventions were behavioural with a focus on mental, behavioural or neurodevelopmental disorders. Most trials were phase III, focused on the treatment of the indication and were funded by industry. Contribution to clinical guidelines was the highest cited research impact. While there was evidence of researchers seeking to maximise trial impact, case studies lacked details on the role of trial participants and other beneficiaries in generating impact. CONCLUSIONS: The impacts of health research can be improved through a better understanding of the priorities and agendas of funders, providing evidence of tangible impact rather than information that is contextual or predictive, and through the early development of impact strategies involving both researchers and beneficiaries. SO WHAT?: Large-scale impact exercises intended for a broad range of disciplines may not be reflective of the depth and scope of health sciences research including trials.

Spatiotemporal characteristics of air pollutants and their associated health risks in '2+26' cities in China during 2016-2020 heating seasons.

To understand characteristics of air pollutants and their associated health risks in recent heating seasons in China, ambient monitoring data of six air pollutants in '2 + 26' cities in Beijing-Tianjin-Hebei and its surrounding areas (known as the BTH2+26 cities) during 2016-2020 heating seasons was analyzed. Results show that daily average concentrations of PM2.5, PM10, SO2, NO2, and CO dropped significantly in BTH2+26 cities from the 2016-2017 heating season to 2019-2020 heating season, while 8h O3 increased markedly. During 2016-2020 heating seasons, annual average values of total excess risks (ERtotal) were 2.3% mainly contributed by PM2.5 (54.4%) and PM10 (36.1%). With PM2.5 pollution worsening, PM10 and NO2 were the important contribution factors of the enhanced ERtotal. Higher health-risk based air quality index (HAQI) values were mainly concentrated in the western Hebei and northern Henan. HAQI showed spatial agglomeration effect in four heating seasons. Impact factors of HAQI varied in different heating seasons. These findings can provide useful insights for China to further propose effective control strategies to alleviate air pollution in the future.

Pressure-driven membrane filtration technology for terminal control of organic DBPs: A review.

Disinfection by-products (DBPs), a series of undesired secondary contaminants formed during the disinfection processes, deteriorate water quality, threaten human health and endanger ecological safety. Membrane-filtration technologies are commonly used in the advanced water treatment and have shown a promising performance for removing trace contaminants. In order to gain a clearer understanding of the behavior of DBPs in membrane-filtration processes, this work dedicated to: (1) comprehensively reviewed the retention efficiency of microfiltration (MF), ultrafiltration (UF), nanofiltration (NF) and reverse osmosis (RO) for DBPs. (2) summarized the mechanisms involved size exclusion, electrostatic repulsion and adsorption in the membrane retention of DBPs. (3) In conjunction with principal component analysis, discussed the influence of various factors (such as the characteristics of membrane and DBPs, feed solution composition and operating conditions) on the removal efficiency. In general, the characteristics of the membranes (salt rejection, molecular weight cut-off, zeta potential, etc.) and DBPs (molecular size, electrical property, hydrophobicity, polarity, etc.) fundamentally determine the membrane-filtration performance on retaining DBPs, and the actual operating environmental factors (such as solute concentration, coexisting ions/NOMs, pH and transmembrane pressure) exert a positive/negative impact on performance to some extent. Current researches indicate that NF and RO can be effective in removing DBPs, and looking forward, we recommend that multiple factors should be taken into account that optimize the existed membrane-filtration technologies, rationalize the selection of membrane products, and develop novel membrane materials targeting the removal of DBPs.

Data-driven estimation of nitric oxide emissions from global soils based on dominant vegetation covers.

Soils are a major source of global nitric oxide (NO) emissions. However, estimates of soil NO emissions have large uncertainties due to limited observations and multifactorial impacts. Here, we mapped global soil NO emissions, integrating 1356 in-situ NO observations from globally distributed sites with high-resolution climate, soil, and management practice data. We then calculated global and national total NO budgets and revealed the contributions of cropland, grassland, and forest to global soil NO emissions at the national level. The results showed that soil NO emissions were explained mainly by N input, water input and soil pH. Total above-soil NO emissions of the three vegetation cover types were 9.4 Tg N year-1 in 2014, including 5.9 Tg N year-1 (1.04, 95% confidence interval [95% CI]: 0.09-1.99 kg N ha-1 year-1 ) emitted from forest, 1.7 Tg N year-1 (0.68, 95% CI: 0.10-1.26 kg N ha-1 year-1 ) from grassland, and 1.8 Tg N year-1 (0.98, 95% CI: 0.42-1.53 kg N ha-1 year-1 ) from cropland. Soil NO emissions in approximately 57% of 213 countries surveyed were dominated by forests. Our results provide updated inventories of global and national soil NO emissions based on robust data-driven models. These estimates are critical to guiding the mitigation of soil NO emissions and can be used in combination with biogeochemical models.

The occurrence and abundance of antibiotic resistance genes in rivers of tropical islands: a case of Hainan Island, China.

In this study, the occurrence and distribution of 49 antibiotic resistance genes (ARGs) and two integrase genes (intl1, intl2) in three major rivers of Hainan Island, China, were investigated in July 2021, and to explore the spatial distribution of the target genes in the three rivers with the potential influencing factors such as regional characteristics and environmental factors. The results showed that a total of 46 ARGs and two integrase genes were detected in water and sediment, and the absolute abundance of ARGs ranged from 1.16 × 103 to 2.97 × 107 copies/L and 3.34 × 103-1.55 × 107 copies/g. ARGs of macrolides, aminoglycosides, and sulfonamides were this study's main types of ARGs. The aadA2, tetE, ermF, tetX, aac(6')-Ib, tetW, and qnrS genes are predominant ARGs in the water and sediment of the three rivers. The relative abundance of ARGs shows higher abundance in the midstream and downstream and lower abundance in the upstream and estuarine. After conducting a correlation analysis, it was found that there was a significant positive correlation between the ARGs detected in the water of the three main rivers. However, in sediment, tetC was negatively correlated with tetQ, macB was negatively correlated with ermF and ereA (p < 0.05), while the remaining ARGs showed positive correlations. Specifically, there was no significant positive correlation between tetQ and tetC, macB and ereA, and ermF in the sediments. Among the nine environmental factors studied, pH was found to be the main factor associated with the occurrence of ARGs in the aquatic environment, but it was also significantly associated with only nine ARGs. Among the detected heavy metals, only Cd and Zn showed significant correlations with the two ARGs in the water bodies of the three main rivers. It indicated that the pollution of ARGs in the three major rivers was in the initial stage, the detection abundance was low, the influence of environmental factors was small, and the interaction between ARGs seemed to be the main driving force. This study provides a scientific basis for further understanding the occurrence of ARGs and their influencing factors in a tropical island environment, and lays a foundation for subsequent management.

[Impacts of Climate Change and Human Activities on NDVI Change in Eastern Coastal Areas of China].

Based on the datasets of normalized difference vegetation index (NDVI), temperature, precipitation, and solar radiation and the methods of trend, partial correlation, and residual analyses, this study explored the spatiotemporal variation in NDVI and its response to climate change from 1982 to 2019 in eastern coastal areas of China. Then, the effects of climate change and non-climatic factors (e.g., human activities) on NDVI trends were analyzed. The results showed that:① the NDVI trend varied greatly in different regions, stages, and seasons. On average, the growing season NDVI increased faster during 1982-2000 (stage I) than that during 2001-2019 (stage Ⅱ) in the study area. Moreover, NDVI in spring showed a more rapid increase than that in other seasons in both stages. ② For a given stage, the relationships between NDVI and each climatic factor varied in different seasons. For a given season, the major climatic factors associated with NDVI change were different between the two stages. The relationships between NDVI and each climatic factor showed great spatial differences in the study period. In general, the increase in growing season NDVI in the study area from 1982 to 2019 was closely related to the rapid warming. The increase in precipitation and solar radiation in stage Ⅱ also played a positive role. ③ In the past 38 years, climate change played a greater role in the change in growing season NDVI than non-climatic factors, including human activities. Whereas non-climatic factors dominated the increase in growing season NDVI during stage I, climate change played a major role during stage Ⅱ. We suggest that more attention should be paid to the impacts of various factors on vegetation cover variation during different periods to promote the understanding of terrestrial ecosystem changes.

Eutrophication and salinization elevate the dissolved organic matter content in arid lakes.

Dissolved organic matter (DOM) plays an essential role in the global lake carbon cycle. Understanding DOM composition and monitoring its spatiotemporal dynamics are of great significance for understanding the lake carbon cycle, controlling water pollution, and protecting water resources. However, previous studies have focused mainly on eutrophic freshwater lakes, with limited attention given to saline lakes. Based on in situ data collected in ten lakes in northwestern China, this study reported the changes in DOM components in different lake types. Parallel factor analysis (PARAFAC) was used to analyze the three-dimensional excitation emission matrix (EEMs) to obtain the DOM fluorescence components. The contributions of different environmental factors to the changes in DOM components were quantified by the generalized linear model (GLM). The results showed that the eutrophication index was significantly positively related to dissolved organic carbon (DOC) (R2 = 0.95, p < 0.01) and colored DOM (CDOM) (R2 = 0.96, p < 0.01) concentrations. Terrestrial humic-like and tryptophan-like components, which are highly correlated with human activities, explained 62% and 64% of the variations in DOC and CDOM, respectively. In sum, the contributions of human activities to the DOC and CDOM variations were 61% and 57%, respectively. Salinity also showed significant positive correlations with both DOC (R2 = 0.88, p < 0.01) and CDOM (R2 = 0.87, p < 0.01). Lake salinization led to increases in DOM concentration, and salinity contributed 20% and 16% to the DOC and CDOM variations, respectively. Therefore, human activities and salinity codetermined the DOM concentration and its composition in the western arid lakes. Based on these findings, this study proposed a feasible flowchart for remotely estimating DOM in saline lakes using satellite data. This study is significant for the long-term monitoring of the carbon cycle and the effective protection of lake water resources in saline lakes.

Environmental and agronomic factors that impact the regional identity of Cascade and Mosaic® hops grown in the Pacific Northwest.

BACKGROUND: Regional identity is a well-established concept of economic interest that has been identified as a source of unique quality traits of various agricultural products originating from a specific region. In the context of hops, the exploration of regional identity is still at a very early stage despite an increasing global demand for specialized aroma hops to enable more product diversity, especially in the growing craft beer industry. Thus, we conducted a large-scale investigation characterizing the growing environments of Cascade and Mosaic® hops at 39 field locations throughout two important valleys in the Pacific Northwest region of the United States to identify factors that significantly impact hop characteristics and to better understand how these impact hop regional identity. RESULTS: The Willamette Valley (Oregon) and the Yakima Valley (Washington) have distinctly different soil characteristics, soil chemistry, and climate. In turn, growers in these two regions apply unique agronomic practices in response to these differences. This investigation also revealed significant subregional differences in growing environment within each of these two valleys. Multivariate statistics, correlation, and regression analysis identified a number of environmental and agronomic factors like soil pH, the concentration of zinc, sulfur, and manganese in the soil, and the amount of applied zinc fertilization, which exhibited strong positive or negative correlations with specific hop quality traits depending on the hop variety, primarily in Oregon. CONCLUSION: This study provides new insights into understanding hop regional identity and represents an important step towards fully utilizing this effect. © 2023 Society of Chemical Industry.