Biome-BGC模型参数的敏感性和时间异质性

生态过程模型为研究陆表生态系统水、碳、氮等物质的循环提供了一种有效的手段。模型与数据同化结合可建立模拟与观测之间的桥梁,同时提高模型与观测两种方法揭示地表真实状况的有效性。但模型参数的特性,将直接影响到模型模拟及数据同化的精度。传统观念认为,生态过程模型参数在相同植被类型条件下是固定不变的,但近期研究已开始关注其时空异质性。本文以Biome-BGC模型为例,利用美国哈佛森林Environmental Monitoring Site(EMS)通量观测站的相关数据,对哈佛森林地区水、碳通量进行模拟。首先对模型参数进行敏感性分析;然后应用模拟退火算法,构造目标函数,使待优化的敏感参数在合理阈值范围内不断变动反复迭代,获取逐月的最优参数值;通过引入变异系数,对敏感参数的时间异质性进行分析。结果表明:生态过程模型参数最优值并非常量,而会随时间表现出异质性,而且各参数时间异质性大小差异显著。文中对Biome-BGC模型的敏感参数按时间异质性大小划分了相应的等级。研究结果有助于加深对生态过程模型参数特性的认识,为参数的合理取值及动态优化提供思路与依据,有助于进一步提高模型模拟和数据同化的精度与效率。     

景观生态网络研究进展

作为生态学重要的概念与方法,生态网络是景观生态学研究的热点问题,也是耦合景观结构、生态过程和功能的重要途径。景观生态网络对于保护生物多样性、维持生态平衡、增加景观连接度具有重要意义。从景观生态网络的相关理论、研究进展、研究方法模型等进行分析,并对其应用前景进行展望,主要介绍了传统景观格局分析、网络分析、模型模拟等方法的适用性与特点,并分析了景观生态网络在城市景观格局优化、自然保护区规划、生物多样性保护、土地规划等领域的应用,最后提出了研究的主要问题。     

AGNPS模型机理与预测偏差影响因素

农业非点源污染已引起了严重和广泛的生态环境和水质问题,受到各种土地利用类型的潜在影响,并与污染源的扩散和防控措施的地理位置有关,涉及到复杂的生态过程和景观格局,由于监测极为困难或成本昂贵,研究方法一般采用模型模拟预测,AGNPS是应用广泛的模型之一。文章介绍了AnnAGNPS4．0模型的特点、时间空间应用范围及其局限性,主要分析了模型的不确定性和预测偏差的影响因素。通过分析认为,美国农业部农业研究局编制的模型参数手册和703号农业手册中参数取值并不适合中国大部分地区,提出了在使用模型时要根据研究地区的实际情况确定参数的取值,并对国内外模型应用结果进行了综合分析,为模型在中国的正确使用提供参考。     

基于参数优化的人工灌丛生态系统碳水通量模拟

荒漠草原是陆地生态系统中最为脆弱且受人类干扰较为严重的生态类型之一,精准模拟其碳水通量及对人为干扰的响应,不仅能够揭示其复杂的生态学过程,而且还可为人为生态修复和保护提供决策依据。生态模型能够有效地模拟陆地生态系统的碳水循环过程,但模型众多的参数及其取值的合理性限制了其普遍应用,故探索参数优化是提升生态模型应用的有效途径。利用PEST参数优化方法和涡度相关观测数据对Biome-BGC模型的生理生态参数进行优化,在评估参数优化效果的基础上模拟了1986-2018年宁夏盐池荒漠草原区人工灌丛生态系统的总初级生产力（Gross primary productivity,GPP）和蒸散（Evapotranspiration,ET）。结果表明：（1）参数优化可以改善Biome-BGC模型对荒漠草原区人工灌丛生态系统GPP和ET的模拟效果,参数优化后模拟的GPP和ET均更接近于观测值,其中月尺度的模拟效果更佳;（2）基于PEST的Biome-BGC模型参数优化方法具有较强的普适性,优化后的参数可推广应用于荒漠草原区人工灌丛生态系统长时间序列的GPP和ET模拟;（3）宁夏盐池荒漠草原区人工灌丛生态系统的GPP在1986-2018年呈缓慢上升趋势,增幅为1.47 g C m^-2 a^-1,但ET的年际变化率较大,且无显著变化趋势。     

基于多模型结合的土地利用结构多情景优化模拟

土地生态服务功能的重要性越来越受到人们的重视,以河北省卢龙县为案例区,以土地生态服务功能和经济功能提升为目标,基于100 m×100 m尺度的遥感解译图像,分别利用CLUE-S及基于MOP和CLUE-S整合模型对研究区土地利用结构进行数量及空间优化模拟。结果表明:到2020年,单模型模拟的土地经济功能有所提升,但生态服务功能却减退;基于MOP和CLUE-S优化整合模型模拟的生态服务功能和经济功能分别比2013年提升8.40%及8.20%。耕地、建设用地、林地面积都有所增加,其它用地减少较多。研究表明,MOP和CLUE-S整合模型与单模型相比,到2020年土地两项功能值之和有所增加,特别是生态功能增加幅度较大,MOP和CLUE-S模型结合的优化方案优于CLUE-S单模型优化方案。     

腹主动脉瘤生长过程的蠕变力学模型

基于增强对腹主动脉瘤生长过程的理解、为腹主动脉瘤临床手术提供参考的目的,本文根据腹主动脉瘤的生长物理机制,提出了以蠕变力学为基础模拟腹主动脉瘤生长过程的模型.建立了腹主动脉瘤简化模型,利用有限元方法进行模拟计算.结果显示蠕变模型能够有效模拟腹主动脉瘤生长过程中的形态变化.参数优化模型模拟结果符合临床统计数据所示的腹主动脉瘤生长过程.本文还讨论了腹主动脉材料力学参数对模型的影响.     

不同步长尺度下BEPS碳循环模型的协同应用

小时步长的BEPSHourly模型可以模拟植被日内生态生理过程,但模型的结构及解算过程复杂耗时,常适用于站点尺度进行参数优化及总初级生产力(GPP)、净初级生产力(NPP)的日内变化分析;日步长的BEPSDaily模型解算日光合速率方法简单,不涉及众多的迭代过程,模型耗时较少,适用于模拟计算区域初级生产力及分析区域碳源/汇空间分布.本研究根据BEPSDaily及BEPSHourly各自的模型特点及适用性,提出了小时步长及日步长BEPS模型的协同应用研究方法.首先利用BEPSHourly模型在站点尺度进行主要光合作用参数——最大羧化速率(V_{c max})、最大电子传递速率(J_max)的优化,将优化后主要光合作用参数引入区域BEPSDaily模型进行参数修正,再基于优化修正后的区域BEPSDaily模型进行区域NPP估测.结果表明: 基于通量数据对光合作用主要参数进行优化可以提高模型的模拟能力;2011年,帽儿山地区不同森林类型的初级生产能力依次为阔叶林>针阔混交林>针叶林;本研究提出的不同步长尺度碳循环模型协同应用研究方法能够有效地进行主要光合作用参数的优化,模拟GPP、NPP的月平均日内变化,快速估测区域NPP并分析碳源/汇空间分布.     

基于实码遗传算法的湖泊水质模型参数优化

参数的合理取值决定着模型的模拟效果,因此确定研究区域的模型结构后,需要对模型的参数进行优化.湖泊水质模型(Simulation by means of an Analytical Lake Model,SALMO)利用常微分方程描述湖泊的营养物质循环和食物链动态,考虑了多个生态过程,包含104个参数.由于参数较多,不适宜采用传统参数优化方法进行优化.利用太湖梅梁湾2005年数据,采用实码遗传算法优化了SALMO模型中相对敏感的参数,运用优化后的模型,模拟了梅梁湾2006年的水质.对比分析参数优化前后模型的效果表明遗传算法能高效地对SALMO进行参数优化,优化后的模拟精度得到了显著提高,能更好地模拟梅梁湾的水质变化.     

景观生态学中生态连接度研究进展

生态连接度对生物迁移扩散、基因流动、干扰扩散等生态过程具有重要作用,是目前景观生态学研究的热点内容.生态连接度是测度景观对于资源斑块间运动的促进或者阻碍作用程度的指标.它主要基于渗透和图论两大理论,通过实验、模型模拟以及指数等量化方法描述区域景观结构和功能的变化,广泛应用在自然景观和城市景观格局优化中,对生物多样性保护以及城市开放空间规划具有重要作用.介绍生态连接度的理论基础、评价方法,应用以及主要结论,并对景观生态学中生态连接度的未来研究方向进行展望,以促进生态连接度研究的进一步发展.     

P.chrysosporium分批发酵木素过氧化物酶动力学模型

目的:为研究黄孢原毛平革菌(P.chrysosporium AS5.776)液态分批发酵产木素过氧化物酶(LiP)发酵动力学规律,实现其发酵过程的优化,达到进一步提高酶产量.方法:对P.chrysosporium AS5.776进行5L液态分批发酵,根据发酵过程中菌体生长、基质消耗及LiP形成规律,基于Logistic方程和Luedeking-Piret方程建立了P.chrysosporium AS5.776液态分批发酵的过程动力学模型,并对模型进行了参数拟合、方差分析及验证比较.结果:模型模拟计算结果与实验值能较好地吻合,R2分别为0.9891、0.995 6和0.9925,模型显著性极高.验证实验显示所构建模型平均相对误差分别为2.9％、3.6％和12.5％.结论:该模型能较好揭示木素过氧化物酶发酵代谢过程的特征,可为工业化应用提供理论依据.     

基于FLUXNET观测数据与VPM模型的森林生态系统光合作用关键参数优化及验证

生态系统总初级生产力(GPP)是全球生态系统碳循环研究的重要组成部分.植被最大光能利用率(ε_max)是陆地生态系统GPP模拟的关键参数.本文基于植被光合模型(VPM)和全球通量网(FLUXNET)40个站点(179条站点年数据)的涡度相关通量观测数据,采用单因素轮换法对VPM模型进行参数敏感性分析,并利用交叉验证法对全球森林生态系统的光合作用关键参数进行优化和验证.结果表明:森林生态系统GPP模型受ε_max、光合最高温度(T_max)以及光合最适温度(T_opt)的影响最大;优化后的ε_max在不同植被类型之间存在明显差异,介于0.05～0.08 μmol CO₂·μmol^-1 PAR,常绿阔叶林>常绿针叶林>混交林>落叶阔叶林;优化后的森林生态系统T_max为38～48 ℃,T_opt为18～22 ℃;利用分植被类型优化后的模型关键参数,VPM模型可较好地模拟全球主要森林生态系统GPP的季节和年际变化.     

A novel force field parameter optimization method based on LSSVR for ECEPP

In this paper, we propose a novel force field parameter optimization method based on LSSVR and optimize the torsion energy parameters of ECEPP force field. In this method force field parameter optimization problem is turned into a support vector regression problem. Protein samples for regression model training are chosen from Protein Data Bank. The experiments show that the optimized force-field parameters make both α-helix and β-hairpin structures more consistent with the experimental implications than the original parameters.     

Numerical Simulation of Solar Cell Plasmonics for Small and Large Metal Nano Clusters Using Discrete Dipole Approximation

We suggest a numerical model for nano-modified plasmonic optical structure, which facilitates photons to travel larger distances inside a thin-film silicon wafer, to enhance overall absorption in thin-film silicon solar cell. The absorption and scattering calculation is done using the discrete dipole approximation technique which is valid for both small and large-particle regimes. Relaxed geometrical topologies beyond quasi static approximation were addressed in the present model. The model gives a wide range of flexibility to optimize various parameters accurately. The model establishes that aspect ratio 0.5–0.6 and particle size of 140 nm for ellipsoidal shape are optimized parameters for efficient light trapping in 900–1,100 nm spectral range.     

Use of decoys to optimize an all-atom force field including hydration

A novel method of parameter optimization is proposed. It makes use of large sets of decoys generated for six nonhomologous proteins with different architecture. Parameter optimization is achieved by creating a free energy gap between sets of nativelike and nonnative conformations. The method is applied to optimize the parameters of a physics-based scoring function consisting of the all-atom ECEPP05 force field coupled with an implicit solvent model (a solvent-accessible surface area model). The optimized force field is able to discriminate near-native from nonnative conformations of the six training proteins when used either for local energy minimization or for short Monte Carlo simulated annealing runs after local energy minimization. The resulting force field is validated with an independent set of six nonhomologous proteins, and appears to be transferable to proteins not included in the optimization; i.e., for five out of the six test proteins, decoys with 1.7- to 4.0-Å all-heavy-atom root mean-square deviations emerge as those with the lowest energy. In addition, we examined the set of misfolded structures created by Park and Levitt using a four-state reduced model. The results from these additional calculations confirm the good discriminative ability of the optimized force field obtained with our decoy sets.     

Statistical optimization of medium for the production of pyruvate oxidase by the recombinant Escherichia coli

Pyruvate oxidase (PyOD) is a very useful enzyme for clinical diagnostic applications and environmental monitor. Optimization of the fermentation medium for maximization of PyOD constitutively, production by Escherichia coli DH5α/pSMLPyOD was carried out. Response surface methodology (RSM) was used to optimize the medium constituents. A 2^6–2 fractional factorial design (first order model) was carried out to identify the significant effect of medium components towards PyOD production. Statistical analysis of results shows that yeast extract, ammonium sulfate and composite phosphate were significant factors on PyOD production. The optimized values of these three factors were obtained by RSM based on the result of a 2³ central composite rotatable design. Under these proposed optimized medium, the model predicted a PyOD activity of 610 U/L and via experimental rechecking the model, an activity of 670 U/L was attained.     

Biotransformation optimization of betulin into betulinic acid production catalysed by cultured Armillaria luteo‐virens Sacc ZJUQH100‐6 cells

Aims: Betulinic acid has attracted attention in terms of its important biological and pharmacological characteristics. The main objective of this work was to optimize the variables of biotransformation process in order to enhance betulinic acid production from betulin catalysed by fungus Armillaria luteo‐virens Sacc ZJUQH100‐6. Methods and Results: Fractional factorial design and response surface methodology were applied to optimize the main parameters that affect betulinic acid production in the growing‐cells system. Results indicated that the addition of Tween 80 and substrate concentration were identified as the significant factors on betulinic acid formation, and the central composite experimental design was then adopted to derive a statistical model for optimizing biotransformation conditions. The optimum conditions were observed at pH 6·0, 0·57% Tween 80, 15 mg l^?1 betulin and at 3 days of stage of inoculation. Conclusions: Under the optimized conditions, the highest productivity of betulinic acid predicted was 9·32%, which increased by 74·53% in comparison with that of the nonoptimized. The verified experiment revealed that the model can well simulate betulin biotransformation. Moreover, the bioconversion of betulin and betulin‐28‐monooxygenase activities was compared between the optimized and the nonoptimized conditions. Significance and Impact of the Study: Current data imply that betulinic acid production from betulin can be effectively enhanced through biotransformation optimization strategy.     

Maximization of fructose esters synthesis by response surface methodology

Enzymatic synthesis of fructose fatty acid ester was performed in organic solvent media, using a purified lipase from Candida antartica B immobilized in acrylic resin. Response surface methodology with a central composite rotatable design based on five levels was implemented to optimize three experimental operating conditions (temperature, agitation and reaction time). A statistical significant cubic model was established. Temperature and reaction time were found to be the most significant parameters. The optimum operational conditions for maximizing the synthesis of fructose esters were 57.1°C, 100 rpm and 37.8 h. The model was validated in the identified optimal conditions to check its adequacy and accuracy, and an experimental esterification percentage of 88.4% (±0.3%) was obtained. These results showed that an improvement of the enzymatic synthesis of fructose esters was obtained under the optimized conditions.     

产γ-谷氨基甲酰胺合成酶菌株的筛选及产酶条件研究

以假单胞菌(Pseudomonas sp.)为出发菌株,通过紫外诱变筛选得到一株γ-谷氨基甲酰胺合成酶高产菌株UV-19,其酶活提高32.54%。以突变株UV-19为供试菌株,对γ-谷氨基甲酰胺合成酶的发酵条件进行优化。首先利用Plackett-Burman设计筛选出影响较大的4个因素:葡萄糖、蛋白胨、起始pH值、装液量。在此基础上再利用CCD响应面分析法进行优化,得到最佳产酶培养条件为(g/L):葡萄糖15、蛋白胨12、NaCl 5.0、MgSO4.7H2O 0.2、K2HPO4.3H2O 0.5、甲胺盐酸盐1.0g/L、起始pH值6.5、装液量72mL/250mL。该优化条件下进行产酶培养,假单胞菌发酵产γ-谷氨基甲酰胺合成酶酶活力可达32.68U/mL。     

Production of Cold-Adapted Amylase by Marine Bacterium <Emphasis Type="Italic">Wangia</Emphasis> sp. C52: Optimization,Modeling, and Partial Characterization

The aim of this work was to optimize the fermentation parameters in the shake-flask culture of marine bacterium Wangia sp. C52 to increase cold-adapted amylase production using two statistical experimental methods including Plackett–Burman design, which was applied to find the key ingredients for the best medium composition, and response surface methodology, which was used to determine the optimal concentrations of these components. The results showed starch, tryptone, and initial pH had significant effects on the cold-adapted amylase production. A central composite design was then employed to further optimize these three factors. The experimental results indicated that the optimized composition of medium was 6.38 g L⁻¹ starch, 33.84 g L⁻¹ tryptone, 3.00 g L⁻¹ yeast extract, 30 g L⁻¹ NaCl, 0.60 g L⁻¹ MgSO₄ and 0.56 g L⁻¹ CaCl₂. The optimized cultivation conditions for amylase production were pH 7.18, a temperature of 20°C, and a shaking speed of 180 rpm. Under the proposed optimized conditions, the amylase experimental yield (676.63 U mL⁻¹) closely matched the yield (685.60 U mL⁻¹) predicted by the statistical model. The optimization of the medium contributed to tenfold higher amylase production than that of the control in shake-flask experiments.