The destabilization of Earth's climate systems has emerged as a critical scientific and policy challenge, primarily driven by accumulation of greenhouse gas emissions Agriculture is the second-largest source of carbon emissions, and the move towards agricultural decarbonization and greening is necessary for future development. China has long been influenced by a system of political promotions based on GDP performance, but this has sacrificed the environment for economic growth. In recent years, China's attention has shifted to environmental governance. However, it is unknown whether local government environmental attention (GEA) expressed in documents has transitioned to the level of actual implementation and reduced agricultural-land carbon emissions (ACEs). The investigation is grounded in a comprehensive prefecture-level cities in China, we employ text analysis methods to measure GEA and utilize spatial econometric models to analyze its impact on ACEs. We found that local governments' GEA significantly reduced ACEs. Through establishing different distance weight matrices, we also found a spillover effect whereby neighboring areas within 400 km also showed reduced ACEs. The GEA affects ACEs primarily through two mechanisms: enhancing green technology innovation (Gti) and reducing agricultural pollutant use rate (Apr). The reduction of Apr and Gti have lowered agricultural ACEs levels, while generating a spillover effect on ACEs reduction in surrounding regions, facilitating interregional low-carbon agricultural transitions through knowledge diffusion and pollution control emulation. Heterogeneity analyses demonstrated that the effect of GEA on ACE reduction was stronger in China's main grain-producing areas, the central and western regions, and the southern cities.

Agricultural eco-efficiency (AEE) is a crucial indicator of the green development of agriculture. Agricultural socialized services (AS) provide services for the agricultural production process and they promote the effective input of production factors, such as science and technology, talent, information, and capital, into the agricultural production chain, deepening the division of labor and injecting vitality into agricultural development. We measured AEE based on field research data in Jiangxi Province, China. We also constructed an endogenous switching model to explore the impact of AS on AEE. Our results show that, based on the counterfactual assumption, the AEE increased by 13.19% among farmers who adopted the services compared to those who did not. From the perspective of scale and structural differences, the larger the scale of agricultural cultivation, the stronger the impact of AS on AEE. Furthermore, a large share of cash crops was found to inhibit the impact of AS on AEE. We also investigated whether farmers in close proximity to each other affect their neighbors through knowledge dissemination and technology spillover. The extent of the impact of AS on AEE depended on distance thresholds: it was more pronounced when we increased the distance threshold. Our results suggest that the government should improve the AS system, provide more public welfare services, and appropriately subsidize AS organizations. The AS for food crops should be emphasized; however, those for cash crops should not be ignored.

Solely focusing on the agricultural production function of cultivated land resources is not conducive to the various demands for meeting the UN's Sustainable Development Goals. Recognizing the multifunctionality of cultivated land and understanding the interrelationships between individual functions are crucial for the rational planning and utilization of resources. This paper introduces an "element coupling-function synergy" analytical framework for the sustainable utilization of cultivated land resources. The proposed framework is based on the causal relationships between elements and functions within the cultivated land system. Subsequently, a causal Bayesian belief network was constructed to identify trade-offs and synergies among multiple functions of cultivated land resources in Guangdong, China. The findings reveal trade-offs between food cleanliness and food production/social security, and synergistic relationships among food production, social security, and ecological regulation, as well as among ecological regulation, habitat maintenance and landscape culture. The study area was divided into eight functional zones: Green Agricultural Zone, Agro-inputs Control Zone, Urban Agricultural Zone, Major Grain-producing Zone, Modern Agricultural Zone, Agro-ecological Preservation Zone, Agro-ecological Tourism Zone, Quality Improvement Zone. Multi-objective management plans were formulated for optimizing multifunctional relationships within each zone. The analysis result reveals the importance of nutrient conditions and ecological environments for the sustainable management of cultivated land. Consequently, specific policy recommendations are proposed accordingly. This paper may not only advance understanding of the multifunctionality of cultivated land but can also provide valuable insights for land-use planning to ensure the judicious and sustainable management of cultivated land resources.

Navicula sp., a type of benthic diatom, plays a crucial role in the carbon cycle as a widely distributed algae in water bodies, making it an essential primary producer in the context of global carbon neutrality. However, using erythromycin (ERY) and levofloxacin (LEV) in medicine, livestock, and aquaculture has introduced a new class of pollutants known as antibiotic pollutants, which pose potential threats to human and animal health. This study aimed to investigate the toxic effects of ERY and LEV, individually or in combination, on the growth, antioxidant system, chlorophyll synthesis, and various cell osmotic pressure indexes (such as soluble protein, proline, and betaine) of Navicula sp. The results indicated that ERY (1 mg/L), LEV (320 mg/L), and their combined effects could inhibit the growth of Navicula sp. Interestingly, the combination of these two drugs exhibited a time-dependent effect on the chlorophyll synthesis of Navicula sp., with ERY inhibiting the process while LEV promoted it. Furthermore, after 96 h of exposure to the drugs, the activities of GSH-Px, POD, CAT, and the contents of MDA, proline, and betaine increased. Conversely, the actions of GST and the contents of GSH and soluble protein decreased in the ERY group. In the LEV group, the activities of POD and CAT and the contents of GSH, MDA, proline, and betaine increased, while the contents of soluble protein decreased. Conversely, the mixed group exhibited increased POD activity and contents of GSH, MDA, proline, betaine, and soluble protein. These findings suggest that antibiotics found in pharmaceutical and personal care products (PPCPs) can harm primary marine benthic eukaryotes. The findings from the research on the possible hazards linked to antibiotic medications in aquatic ecosystems offer valuable knowledge for ensuring the safe application of these drugs in environmental contexts.

Perfluoro octane sulfonate (PFOS) and cadmium (Cd) are toxic elements in the environment. As a micronutrient trace element, selenium (Se) can mitigate the adverse effects induced by PFOS and Cd. However, few studies have examined the correlation between Se, PFOS and Cd in fish. The present study focused on the antagonistic effects of Se on PFOS+Cd-induced accumulation in the liver of zebrafish. The fish was exposed to PFOS (0.08mg/L), Cd (1mg/L), PFOS+ Cd (0.08 mg/L PFOS+1 mg/L Cd), L-Se (0.07mg/L Sodium selenite +0.08mg/L PFOS+1mg/L Cd), M-Se (0.35mg/L Sodium selenite + 0.08mg/L PFOS+ 1 mg/L Cd), H-Se (1.75 mg/L Sodium selenite + 0.08 mg/L PFOS+ 1mg/L Cd) for 14d. The addition of selenium to fish exposed to PFOS and Cd has been found to have significant positive effects. Specifically, selenium treatments can alleviate the adverse effects of PFOS and Cd on fish growth, with a 23.10% improvement observed with the addition of T6 compared to T4. In addition, selenium can alleviate the negative effects of PFOS and Cd on antioxidant enzymes in zebrafish liver, thus reducing the liver toxicity caused by PFOS and Cd. Overall, the supplementation of selenium can reduce the health risks to fish and mitigate the injuries caused by PFOS and Cd in zebrafish.

Efficient monitoring of cultivated land quality (CLQ) plays a significant role in cultivated land protection. Soil spectral data can reflect the state of cultivated land. However, most studies have used crop spectral information to estimate CLQ, and there is little research on using soil spectral data for this purpose. In this study, soil hyperspectral data were utilized for the first time to evaluate CLQ. We obtained the optimal spectral variables from dry soil spectral data using a gradient boosting decision tree (GBDT) algorithm combined with the variance inflation factor (VIF). Two estimation algorithms (partial least-squares regression (PLSR) and back-propagation neural network (BPNN)) with 10-fold cross-validation were employed to develop the relationship model between the optimal spectral variables and CLQ. The optimal algorithms were determined by the degree of fit (determination coefficient, R2). In order to estimate CLQ at the regional scale, HuanJing-1A Hyperspectral Imager (HJ-1A HSI) data were transformed into dry soil spectral data using the linkage model of original soil spectral reflectance to dry soil spectral reflectance. This study was conducted in the Guangdong Province, China and the Conghua district within the same province. The results showed the following: (1) the optimal spectral variables selected from the dry soil spectral variables were 478 nm, 502 nm, 614 nm, 872 nm, 966 nm, 1007 nm, and 1796 nm. (2) The BPNN was the optimal model, with an R2(C) of 0.71 and a normalized root mean square error (NRMSE) of 12.20%. (3) The results showed the R2 of the regional-scale CLQ estimation based on the proposed method was 0.05 higher, and the NRMSE was 0.92% lower than that of the CLQ map obtained using the traditional method. Additionally, the NRMSE of the regional-scale CLQ estimation base on dry soil spectral variables from HJ-1A HSI data was 2.00% lower than that of the model base on the original HJ-1A HSI data.

Human activities have changed the global concentration of potentially toxic elements (PTEs) and significantly altered the marine ecosystem. Little is known about the concentrations of these PTEs around Hainan Island in China, or their distribution and human health risks. Understanding the variability of PTEs in marine sediments and how they accumulate is important not only for biodiversity and ecological conservation, but also for management of aquatic natural resources and human health risk assessments. This study showed that the concentrations of six PTEs (Cd, Cu, Zn, As, Pb, and Hg), sampled in nine different cities, were linked to human activities. In order to understand the ecological risks associated with PTE pollution, we calculated the contamination factor (CF), enrichment factor (EF), pollution load index (PLI), and geo-accumulation index (Igeo) of each element in each city. These indicators suggest that the pollution of Cd and Zn in the sediments of these cities is higher than that of the other PTEs. We also carried out a human health risk assessment which demonstrated the carcinogenic effects of Zn on children and adults in ChengMai, while Pb showed non-carcinogenic effects at all the studied sites, suggesting that Zn pollution in the sediments of ChengMai may pose human health risks. We would therefore advise that follow-up studies endeavor to monitor the levels of PTEs in the flora and fauna of these cities.

Aqueous solutions containing toxic elements (TEs) (such as hexavalent chromium (Cr (VI)) can be toxic to humans even at trace levels. Thus, removing TEs from the aqueous environment is essential for the protection of biodiversity, hydrosphere ecosystems, and humans. For plant fabrication of zinc oxide nanoparticles (PF-ZnONPs), Azolla pinnata plants were used, and X-ray diffraction (XRD), energy dispersive spectroscopy (EDS), SEM, and FTIR techniques were used for the identification of PF-ZnONPs and ZnONPs, which were used to remove Cr (VI) from aqueous solution. A number of adsorption parameters were studied, including pH, dose, concentration of metal ions, and contact time. The removal efficiency of PF-ZnONPs for Cr (VI) has been found to be 96% at a time (60 min), 69.02% at pH 4, and 70.43% at a dose (10 mg·L −1 ). It was found that the pseudo-second-order model best described the adsorption of Cr (VI) onto PF-ZnONPs, indicating a fast initial adsorption via diffusion. The experimental data were also highly consistent with the Langmuir isotherm model calculations.

Tumor necrosis factor ligand superfamily member 6 (TNFSF6), also known as FasL/CD95L, is essential for maintaining the body's immune homeostasis. However, the current reports on TNFSF6 in fish are relatively scarce. In the present study, we conducted functional analyses of a TNFSF6 (TroTNFSF6) from the teleost fish golden pompano (Trachinotus ovatus). TroTNFSF6 is composed of 228 amino acids and has a low similarity with other species (9.65%-58.79%). TroTNFSF6 was expressed in the 11 tissues tested and was significantly up-regulated after Edwardsiella tarda infection. In vivo, overexpression of TroTNFSF6 effectively stimulated the AKP and ACP activities, and reduced bacterial infection in fish tissues. Correspondingly, knockdown of TroTNFSF6 expression resulted in increasing bacterial dissemination and colonization in fish tissues. In vitro, recombinant TroTNFSF6 protein promoted the proliferation of T. ovatus head kidney lymphocytes (HKLs), and promoted the apoptosis of murine liver cancer cells (Hepa1-6). The results indicated that TroTNFSF6 plays an important role in the T. ovatus antibacterial immunity. These observations will facilitate the future in-depth study of teleost TNFSF6.

Abstract Domestic livestock grazing has caused dramatic changes in plant community composition across the globe. However, the response of plant species abundance in communities subject to grazing has not often been investigated through a functional lens, especially for belowground traits. Grazing directly impacts aboveground plant tissues, but the relationships between above‐ and belowground traits, and their influence on species abundance are also not well known. We collected plant trait and species relative abundance data in the grazed and nongrazed meadow plant communities in a species‐rich subalpine ecosystem of the Qinghai–Tibet Plateau. We measured three aboveground traits (leaf photosynthesis rate, specific leaf area, and maximum height) and five belowground traits (root average diameter, root biomass, specific root length, root tissue density, and specific root area). We tested for shifts in the relationship between species relative abundance and among all measured traits under grazing compared with the nongrazed meadow. We also compared the power of above‐ and belowground traits to predict species relative abundance. We observed a significant shift from a resource conservation strategy to a resource acquisition strategy. Moreover, this resource conservation versus resource acquisition trade‐off can also determine species relative abundance in the grazed and nongrazed plant communities. Specifically, abundant species in the nongrazed meadow had aboveground and belowground traits that are associated with high resource conservation, whereas aboveground and belowground traits that are correlated with high resource acquisition determined species relative abundance in the grazed meadow. However, belowground traits were found to explain more variances in species relative abundance than aboveground traits in the nongrazed meadow, while aboveground and belowground traits had comparable predictive power in the grazed meadow. We show that species relative abundance in both the grazed and the nongrazed meadows can be predicted by both aboveground traits and belowground traits associated with a resource acquisition versus conservation trade‐off. More importantly, we show that belowground traits have higher predictive power of species relative abundance than aboveground traits in the nongrazed meadow, whereas in the grazed meadows, above‐ and belowground traits had comparable high predictive power.

Rural revitalization is a global problem. The measures should be adjusted to local conditions to make targeted efforts. Natural and socioeconomic resource factors should be considered in rural revitalization. Therefore, this study focuses on the dike–pond system, which is an important traditional agricultural cultural heritage in the Pearl River Delta of China, to illustrate the importance of identifying the utilization mode of a certain land-use type in village integrated with socioeconomic factors to promote rural revitalization. The study used principal component analysis (PCA) and the variance inflation factor (VIF) to identify the main factors influencing the land-use modes of the dike–pond systems, systematic cluster analysis to identify the modes, and interpretive structural modeling to clarify the influence relationships and structures of the factors. We found that the seven modes reflected the different characteristics, organizational structures, and interaction relationships of the factors. There were significant differences in the ecological processes between the seven modes. More detailed village planning should be performed. Strengthening the economic affordability of the operator should be regarded as important in policy guidance and support measures. Agricultural support measures need to be adjusted to different land-use type systems, and localized resources should be revitalized by the theory of “human–earth–sphere”.

Long-term excessive applications of chemical fertilizers may result in adverse impacts on soil functions. This study was to evaluate soil organic carbon (SOC) sequestration efficiency under continuous paddy rice cultivation with an excessive nitrogen (N) fertilization over the period from1980 to 2017 in South China. The SOC and total nitrogen (TN) of total 108 soil samples from continuous paddy soils and new paddy soils collected in 2017 were accordingly compared with those of 54 samples from paddy soils and upland soils obtained in 1980. Results show a total SOC increase of 0.79 g kg-1 from the initial content of 12.82 g kg-1 over a 37-year period despite an increased input of about 550 kg N ha(-1)yr(-1 )from fertilizers and 2000 kg C kg(-1) yr(-1) from all straw incorporation after 1990. This small C sequestration rate (or 0.021 g C kg(-1) yr(-1)) was also observed to couple with a significantly elevated C:N ratio and badly weakened SOC-N correlation as of 2017, which is almost impossible to be revealed by normal fertilization experiments. The SOC sequestration rate of 0.145 g C kg(-1) yr(-1) of the new paddy soils that were developed from uplands since 1980 implies a declining tendency of SOC sequestration efficiency with rice cultivation time, which could be mainly attributed to both low soil N content and microbial activity rather than to SOC saturation. This case reminds of a need for more dedicated plot studies coupled with field observations on farmers' routine fertilization practices to elucidate why the low soil N content remains with an excessive N fertilizer input and how N interacts with SOC in the continuous paddy soils.

Soil nutrients play a vital role in plant growth and thus the rapid acquisition of soil nutrient content is of great significance for agricultural sustainable development. Hyperspectral remote-sensing techniques allow for the quick monitoring of soil nutrients. However, at present, obtaining accurate estimates proves to be difficult due to the weak spectral features of soil nutrients and the low accuracy of soil nutrient estimation models. This study proposed a new method to improve soil nutrient estimation. Firstly, for obtaining characteristic variables, we employed partial least squares regression (PLSR) fit degree to select an optimal screening algorithm from three algorithms (Pearson correlation coefficient, PCC; least absolute shrinkage and selection operator, LASSO; and gradient boosting decision tree, GBDT). Secondly, linear (multi-linear regression, MLR; ridge regression, RR) and nonlinear (support vector machine, SVM; and back propagation neural network with genetic algorithm optimization, GABP) algorithms with 10-fold cross-validation were implemented to determine the most accurate model for estimating soil total nitrogen (TN), total phosphorus (TP), and total potassium (TK) contents. Finally, the new method was used to map the soil TK content at a regional scale using the soil component spectral variables retrieved by the fully constrained least squares (FCLS) method based on an image from the HuanJing-1A Hyperspectral Imager (HJ-1A HSI) of the Conghua District of Guangzhou, China. The results identified the GBDT-GABP was observed as the most accurate estimation method of soil TN ( of 0.69, the root mean square error of cross-validation (RMSECV) of 0.35 g kg−1 and ratio of performance to interquartile range (RPIQ) of 2.03) and TP ( of 0.73, RMSECV of 0.30 g kg−1 and RPIQ = 2.10), and the LASSO-GABP proved to be optimal for soil TK estimations ( of 0.82, RMSECV of 3.39 g kg−1 and RPIQ = 3.57). Additionally, the highly accurate LASSO-GABP-estimated soil TK (R2 = 0.79) reveals the feasibility of the LASSO-GABP method to retrieve soil TK content at the regional scale.

农田有机碳库是唯一可在较短时间尺度上通过合理利用而进行适度调节的碳库,农田土壤有机碳高精度制图对进一步明析地理环境背景,提升区域土壤固碳潜力,促进碳交易、碳中和等具有重要的意义.本研究以广东省为研究区,在中大空间尺度区域综合特征分区的基础上,基于地理探测器确定农田土壤有机碳空间分异的变量结构,分区构建分层多元复合模型,根据208503个土壤采样点数据编制研究区高精度农田土壤有机碳密度空间分布图.结果表明:耦合自然地理特征和社会经济特征,引入多距离空间聚类进行中大空间尺度综合特征分区,能够显著收敛样本离散程度,土壤有机碳样本标准偏差均值、方差均值较未分区前分别下降0.55、3.53,Moran′s I指数上升0.08.受自然环境与人为扰动双重影响,农田土壤有机碳空间变异的变量众多,且不同综合特征分区内变量结构差异较大,年均降水量、海拔高度、地形坡度等变量在不同特征分区的影响力存在显著差异,土地利用方式及土壤理化性质等变量对不同特征分区均存在较大的影响力.基于地理探测器构建的分层多元复合模型,较好地解决了中大尺度和复杂情景下土壤有机碳空间分异规律与空间突变的同步表达矛盾,抑制了多变量插值噪声增加,其综合精度较地理加权回归模型(GWRK)、径向基函数神经网络(RBFNN)和普通克里格(OK)分别提升6.45％、10.45％和7.50％.在大密度样本集支持下,综合区域综合特征分区、地理探测器、分层多元复合模型等技术手段编制的广东省高精度农田土壤有机碳空间分布图,预测结果准确,空间细节表达清晰,为编制大空间尺度的土壤有机碳分布图探索了有效路径.

Effective degradation of N,N-Dimethylformamide (DMF), an important industrial waste product, is challenging as only few bacterial isolates are known to degrade DMF. Aerobic remediation has typically been used, whereas anoxic remediation attempts are recently made, using nitrate as one electron acceptor, and ideally include methane as a byproduct. Here, we analyzed 20,762 complete genomes and 28 constructed draft genomes for genes associated with DMF degradation. We identified 952 genomes that harbor genes involved in DMF degradation, expanding the known diversity of prokaryotes with these metabolic capabilities. Our findings suggest plasmids play important roles in DMF degradation in the order Rhizobiales and genus Paracoccus, but not in most other lineages. Degradation pathway analysis reveals that most putative DMF degraders using aerobic Pathway I will accumulate methylamine intermediate, while around 6% of the DMF degraders that are primarily members of Paracoccus, Rhodococcus, Achromobacter, and Pseudomonas could potentially mineralize DMF completely. The aerobic DMF degradation via Pathway II is more common than thought and is primarily present in alpha-, and beta-Proteobacteria and Actinobacteria. Around half (446/952) of putative DMF degraders could grow with nitrate anaerobically (Pathway III), however, genes for the use of methyl-CoM to produce methane were not found. These analyses suggest that microbial consortia could be more advantageous in DMF degradation than pure culture, particularly for methane production under the anaerobic condition. The identified genomes and plasmids form an important foundation for optimizing bioremediation of DMF-containing wastewaters.

Reforestation is an effective way to alleviate deforestation and its negative impacts on ecosystem services. In tropical rainforest ecosystem, however, frequent typhoons and heavy rainfall can result in landslides and uprooting of many seedlings, making reforestation efforts very difficult, especially within extremely degraded sites where soil conditions cannot support any plant life. Here, we described a reforestation protocol which is based on tropical rainforest successional processes to not only prevent landslides and tree uprooting due to frequent typhoon and heavy rain, but also accelerate tropical forest succession. This protocol first used the slope and soil layer of the undisturbed old-growth tropical rainforest as a reference to reconstruct slope and soil layers. Then multiple tropical tree species with high growth and survival rate were separately monocultured in the reconstructed soil layers. In the year of 2015 and 2016, we tested the effectiveness of this protocol to recover a 0.2 km 2 extremely degraded tropical rainforest which consists of bare rock and thus does not support any plant life, in Sanya city, China. Our results showed that, both typhoons and heavy rains did not result in landslide or any tree damages in the area this reforestation protocol was used. Moreover, our separately monocultured eight fast-growing tree species have much higher fast-growing related functional traits than those for tree species in the adjacent undisturbed tropical seasonal forest, which in turn resulted in large soil water and nutrient loss within 3 years. This seemed to simulate a quick transition from primary succession (consist of bare rock and cannot support any plant life) to mid-stage of secondary tropical rainforest succession (many fast-growing pioneer tree species induced high soil water and nutrient loss). Thus, mixing the late-successional tropical tree species with each of the separately monocultured eight fast-growing tree species can accelerate recovery to the undisturbed tropical rainforest as soon as possible. Overall, based on tropical rainforest successional processes, our research provides an effective protocol for quickly and effectively restoring an extremely degraded tropical rainforest ecosystem. We expect that this work will be important for the future recovery of other extremely degraded tropical rainforest ecosystems.

为了研究卵形鲳鲹肿瘤坏死因子配体6(TNFSF6)的功能,本研究构建了TNFSF6的原核表达载体并制备了其多克隆抗体,首先通过PCR扩增技术扩增获得了TroTNFSF6的开放阅读框序列,并构建了原核表达重组质粒pET-TroTNFSF6,随后将重组质粒转化至大肠杆菌表达菌株BL21中,进行原核表达并获得重组蛋白rTroTNFSF6.结果显示,重组蛋白rTroTNFSF6大小约46.5 kDa,其最适诱导温度为20℃,诱导时间为8h,IPTG的最佳浓度为0.6 mmol/L可溶性分析表明,重组蛋白rTroTNFSF6主要在沉淀中,以包涵体的形式存在.将纯化后的重组蛋白rTroTNFSF6免疫小鼠以制备多克隆抗体,ELISA检测结果表明其效价高达1∶32 000.本研究为进一步探究卵形鲳鲹TNFSF6的功能奠定了基础.

In experiments that test plant diversity–productivity relationships, the common practice of weeding unsown species and disallowing species colonization may have the unintended consequence of favoring priority effects that maintain niche complementarity in determining productivity. However, in naturally assembled communities where colonization occurs, resource competition may favor dominant traits, which eventually have the greatest influence on productivity. Here, in naturally developed long-term subalpine meadows (from 4-year to at least 40 years meadows) in the Qinghai-Tibetan Plateau, we investigated the relationships between species richness and productivity to testify whether positive diversity–productivity relationships can still exist in naturally developed long-term communities. We also measured five functional traits (specific leaf area, photosynthesis rate, leaf proline content, seed mass and seed germination rate) to calculate two functional diversity indices: community-weighted mean trait values (CWM) and Rao’s quadratic entropy (RaoQ) which are highly correlated to functional traits of dominating species and variety of functional trait among all species. Finally, we quantified the relative contribution of species diversity, functional traits of dominating species and functional diversity among all species to productivity along the succession. We demonstrated strong positively diversity–productivity relationships in the natural sub-alpine meadow communities across time. The five traits of dominating species explained a large proportion (54–80%) of the variation in productivity during succession, whereas species diversity and functional diversity (FD) for each of the five traits explained much less (24–48% for species richness and 0–40% for FD for each of the five traits respectively). We found unequivocal evidence that significantly positive diversity–productivity relationships in the natural sub-alpine meadow communities across time are up to superior performers (dominant traits) in naturally developed communities where colonization occurs. As a result, understanding diversity–productivity relationships under the full range of community assembly processes therefore merits further investigation.

Interleukins (ILs) are a subgroup of cytokines, which are molecules involved in the intercellular regulation of the immune system. These cytokines have been extensively studied in mammalian models, but systematic analyses of fish are limited. In the current study, 3 IL genes from golden pompano (Trachinotus ovatus) were characterized. The IL-1β protein contains IL-1 family signature motif, and four long helices (αA - αD) in IL-11 and IL-34, which were well conserved. All 3 ILs clustered phylogenetically with their respective IL relatives in mammalian and other teleost species. Under normal physiological conditions, the expression of IL-1β, IL-11, and IL-34 were detected at varied levels in the 11 tissues examined. Most of the 3 ILs examined were highly expressed in liver, spleen, kidney, gill, or skin. Following pathogenic bacterial, viral, or parasitic challenge, IL-1β, IL-11, and IL-34 exhibited distinctly different expression profiles in a time-, tissue-, and pathogen-dependent manner. In general, IL-1β was expressed at higher levels following challenge with all pathogens examined than was observed for IL-11 and IL-34. Furthermore, Streptococcus agalactiae and Cryptocaryon irritans caused higher levels of IL-1β and IL-11 expression than Vibrio harveyi and viral nervous necrosis virus (VNNV). The increased expression of IL-34 caused by VNNV and C. irritans were higher than that caused by V. harveyi and S. agalactiae. These results suggest that these 3 ILs in T. ovatus may play different effect pathogen type specific responses.

Soil heavy metals affect human life and the environment, and thus, it is very necessary to monitor their contents. Substantial research has been conducted to estimate and map soil heavy metals in large areas using hyperspectral data and machine learning methods (such as neural network), however, lower estimation accuracy is often obtained. In order to improve the estimation accuracy, in this study, a back propagation neural network (BPNN) was combined with the particle swarm optimization (PSO), which led to an integrated PSO-BPNN method used to estimate the contents of soil heavy metals: Cd, Hg, and As. This study was conducted in Guangdong, China, based on the soil heavy metal contents and hyperspectral data collected from 90 soil samples. The prediction accuracies from BPNN and PSO-BPNN were compared using field observations. The results showed that, 1) the sample averages of Cd, Hg, and As were 0.174 mg/kg, 0.132 mg/kg, and 9.761 mg/kg, respectively, with the corresponding maximum values of 0.570 mg/kg, 0.310 mg/kg, and 68.600 mg/kg being higher than the environment baseline values; 2) the transformed and combined spectral variables had higher correlations with the contents of the soil heavy metals than the original spectral data; 3) PSO-BPNN significantly improved the estimation accuracy of the soil heavy metal contents, with the decrease in the mean relative error (MRE) and relative root mean square error (RRMSE) by 68% to 71%, and 64% to 67%, respectively. This indicated that the PSO-BPNN provided great potential to estimate the soil heavy metal contents; and 4) with the PSO-BPNN, the Cd content could also be mapped using HuanJing-1A Hyperspectral Imager (HSI) data with a RRMSE value of 36%, implying that the PSO-BPNN method could be utilized to map the heavy metal content in soil, using both field spectral data and hyperspectral imagery for the large area.