Growth and survival of juvenile red drum,Sciaenops ocellatus,acclimated to freshwater at three different stocking densities in a partial recirculation system

Preliminary technical baseline information for the inland culture of juvenile red drum, Sciaenops ocellatus, in a freshwater fish hatchery is presented. Three initial stocking densities (d₁ = 83, d₂ = 167, and d₃ = 250 fish/m³) were tested in a semirecirculation system for 575 days using a commercially available feed (48.1% protein, 25% lipids, and 0.13% fiber). Initial and final mean fish weight were 7.11 ± 0.02 g and 287.6 ± 27 g. As carrying capacity appeared to have been reached, only data from Days 1–333 were analyzed. One‐way ANOVA analyses indicated that the survival rate of the smaller density (d₁ =40 ± 3.7%) was significantly different from the other two densities (d₃ = 21 ± 1.1% and d₂ = 23 ± 1.0%), which did not differ between them. Absolute growth rate (0.87 ± 0.02 g/day) was not significantly different between densities (F = 0.23. p = .801). Neither was weight significantly different between treatments. There were significant differences in the feed conversion rate (FCR) between densities (F = 8.54; p = .02). FCR for d₁ was significantly lower than for the two other densities, which did not differ from each other. A von Bertalanffy growth model was adjusted (R² = 0.95), and weight–length relationship presented negative allometric values (b = 2.85, R² = 0.98).     

Mapping the current and future distributions of Onosma species endemic to Iran

Climate change may cause shifts in the natural range of species especially for those that are geographically restricted and/or endemic species. In this study, the spatial distribution of five endemic and threatened species belonging to the genus Onosma (including O. asperrima, O. bisotunensis, O. kotschyi, O. platyphylla, and O. straussii) was investigated under present and future climate change scenarios: RCP2.6 (RCP, representative concentration pathway; optimistic scenario) and RCP8.5 (pessimistic scenario) for the years 2050 and 2080 in Iran. Analysis was conducted using the maximum entropy (MaxEnt) model to provide a basis for the protection and conservation of these species. Seven environmental variables including aspect, depth of soil, silt content, slope, annual precipitation, minimum temperature of the coldest month, and annual temperature range were used as main predictors in this study. The model output for the potential habitat suitability of the studied species showed acceptable performance for all species (i.e., the area under the curve (AUC)>0.800). According to the models generated by MaxEnt, the potential current patterns of the species were consistent with the observed areas of distributions. The projected climate maps under optimistic and pessimistic scenarios (RCP2.6 and RCP8.5, respectively) of 2050 and 2080 resulted in reductions and expansions as well as positive range changes for all species in comparison to their current predicted distributions. Among all species, O. bisotunensis showed the most significant and highest increase under the pessimistic scenario of 2050 and 2080. Finally, the results of this study revealed that the studied plant species have shown an acute adaptability to environmental changes. The results can provide useful information to managers to apply appropriate strategies for the management and conservation of these valuable Iranian medicinal and threatened plant species in the future.     

热处理对低温胁迫下黄瓜活性氧代谢和膜脂组分的影响

为探讨热处理减轻黄瓜果实低温冷害的作用机理,本试验研究了47℃热水浸泡5 min处理对黄瓜果实在4℃贮藏期间活性氧代谢和膜脂组分的影响。结果表明,47℃热水5 min处理可显著抑制黄瓜果实冷害的发生,贮藏15 d后果实冷害指数较对照(CK)低20.87%。此外,热处理还可抑制黄瓜相对电导率及丙二醛(MDA)含量的上升,提高黄瓜果实超氧化物歧化酶(SOD)、过氧化物酶(DOD)、过氧化氢酶(CAT)和抗坏血酸过氧化物酶(APX)的活性,抑制超氧阴离子($\mathop{{O}}_{2}^{{\mathop{}_{\ ·}^{-}}}$)及过氧化氢(H₂O₂)的产生,同时降低脂氧合酶的活性,保持较低的饱和脂肪酸含量、较高的不饱和脂肪酸含量和膜脂不饱和度。综上,热处理可维持黄瓜果实活性氧代谢的平衡,抑制膜脂的过氧化作用,从而提高黄瓜果实的抗冷性,减轻果实冷害损伤。     

基于氧同位素的玉米农田蒸散发估算和区分

农田蒸散发(evapotranspiration,ET)的估算和区分是土壤-植物-大气连续体中的重要研究内容,是农业水资源高效利用的重要基础。该研究分析了土壤水、蒸发水汽、蒸腾水汽和大气背景混合水汽氧同位素组成分布特征,并采用2种同位素的方法对玉米农田蒸散发进行估算和区分:1)结合Keeling plot和Craig-Gordon模型的同位素方法(Iso-CG);2)基于土壤水同位素守恒和水量平衡的方法(Iso-WB)。结果表明,在玉米生育期内Iso-WB方法与Iso-CG方法所计算的玉米蒸腾比例分别为0.64~0.91和0.52~0.91,平均值分别为0.80和0.78。玉米蒸散发总量在前期、中期和后期均值分别为3.95、5.30和4.98 mm/d。通过比较参数并与前人研究结果对比分析,表明采用Iso-CG方法估算区分ET相对精确,采用Iso-WB方法计算蒸散发要求的测量精度相对较高,计算误差较大。该研究成果不仅为玉米农田制定灌溉制度及提高用水效率提供了理论依据,而且对深入探索氧同位素水文学领域具有重要意义。     

基于改进极限学习机的水体溶解氧预测方法

为了有效地指导水产养殖生产，提高溶解氧浓度预测的精度，提出了基于因子筛选和改进极限学习机（Extreme Learning Machine，ELM）的水产养殖溶解氧预测模型。首先，利用皮尔森相关系数法计算各影响因子与溶解氧浓度间的相关系数，提取强关联因子，降低预测模型的输入量维度；采用偏最小二乘算法（Partial Least Square, PLS）优化传统ELM神经网络，避免网络中隐含层共线性问题，保障输出权值的稳定性；然后，结合新型激活函数，构建水体溶解氧浓度预测模型。最后，将SPLS-ELM（Selection Based Partial Least Square Optimized Extreme Learning Machine）预测模型应用到江苏省无锡市南泉基地某试验池塘的水体溶解氧预测中。试验结果表明：该模型的预测均方根误差为0.3232，与最小二乘支持向量机（Least Square Support Vector Machine，LSSVM）、BP神经网络、粒子群（Particle Swarm Optimization，PSO）优化LSSVM和遗传算法（Genetic Algorithm, GA）优化BP神经网络相比分别降低40.98%、44.48%、34.73%和44.18%。且该模型的运行时间仅0.6231s，预测精度和运行效率明显优于其他模型。该模型的溶解氧预测曲线接近真实溶解氧变化曲线，能够满足水产养殖实际生产对水体溶解氧预测的要求。     

生态文明视域下草原治理体系构建研究

草原是我国面积最大的陆地生态系统，既是我国重要的生态安全屏障，也是广大农牧民赖以生存的家园。为深入贯彻习近平生态文明思想，落实山水林田湖草沙系统治理的理念，推进草原保护修复和高效利用，本研究结合"十四五"林业和草原保护发展规划纲要，提出了构建草原监测评价体系、草原保护体系、草原生态修复体系、草原执法监管体系、现代草业体系、支撑保障体系等草原治理体系，旨在为推进草原治理体系和治理能力现代化提供参考。     

渠堤化城镇河岸带的植被特征及其用地影响

渠堤化是干扰城镇河流的常见建设方式，掌握植物特征及对其产生显著影响的用地因素，对于优化渠化的城镇河岸植被带具有重要意义。采用样带全面调查的方法，对北京段已基本全线渠堤化潮白河河岸带植物进行调查，通过多重比较分析河岸带植物丰富度在不同空间位置的差异，并利用NMDS非约束排序拟合解译的周边缓冲区土地利用数据，探讨对渠堤化河岸带植物丰富度和种类分布产生显著影响的因素。结果表明:1）河岸带植物种类174种（乔、灌、草分别为52、29、90种），以草本为主；2）全线渠堤化城镇河流河岸带植物群落种类及丰富度均存在建成区和非建成区的显著差异，总体植物、乔木和灌木植物丰富度在建成区显著大于非建成区，但入侵植物沿渠堤化河岸带不存在空间位置的差异，入侵可能沿渠堤蔓延；3）周边缓冲区道路、其他不透水地表面积是城镇地区全线渠堤化河岸带植物丰富度的显著正相关影响因子，对主要观赏灌木和乔木种类分布存在积极影响，对原生灌木和草本种类分布存在消极影响，这种分布特征受人工干扰影响。     

山西云顶山亚高山草甸优势种种间关系分析

为揭示山西云顶山亚高山草甸植物群落优势种的种间关系,本研究通过种间联结性和相关性测定,对其植物群落13个优势种78个种对的种间关系进行研究。结果表明:13个优势种间大部分种对的种间关联不显著,种间联结不紧密,说明山西云顶山亚高山草甸植物群落结构不很稳定,存在一定程度的生态退化风险;多数原生优势种在群落中占据主要位置,同时也出现少数非原生优势种优势明显,有逐渐取代典型原生优势种的逆行演替趋势,这是由于人类频繁的旅游扰动所致。因此,应当合理的控制旅游开发强度与游客数量,保持亚高山草甸生态系统的稳定与自我维持,以持续高效的维持云顶山亚高山草甸的经济及生态价值。     

Research of dissolved oxygen prediction in recirculating aquaculture systems based on deep belief network

Recirculating aquaculture has received more and more attention because of its high efficiency of treatment and recycling of aquaculture wastewater. The content of dissolved oxygen is an important indicator of control in recirculating aquaculture, its content and dynamic changes have great impact on the healthy growth of fish. However, changes of dissolved oxygen content are affected by many factors, and there is an obvious time lag between control regulation and effects of dissolved oxygen. To ensure the aquaculture production safety, it is necessary to predict the dissolved oxygen content in advance. The prediction model based on deep belief network has been proposed in this paper to realize the dissolved oxygen content prediction. A variational mode decomposition (VMD) data processing method has been adopted to evaluate the original data space, it takes the data which has been decomposed by the VMD as the input of deep belief network (DBN) to realize the prediction. The VMD method can effectively separate and denoise the raw data, highlight the relations among data features, and effectively improve the quality of the neural network input. The proposed model can quickly and accurately predict the dissolved oxygen content in time series, and the prediction performance meets the needs of actual production. When compared with bagging, AdaBoost, decision tree and convolutional neural network, the VMD-DBN model produces higher prediction accuracy and stability.