Ontogenetic symmetry and asymmetry in energetics

Body size ( $\equiv $ biomass) is the dominant determinant of population dynamical processes such as giving birth or dying in almost all species, with often drastically different behaviour occurring in different parts of the growth trajectory, while the latter is largely determined by food availability at the different life stages. This leads to the question under what conditions unstructured population models, formulated in terms of total population biomass, still do a fair job. To contribute to answering this question we first analyze the conditions under which a size-structured model collapses to a dynamically equivalent unstructured one in terms of total biomass. The only biologically meaningful case where this occurs is when body size does not affect any of the population dynamic processes, this is the case if and only if the mass-specific ingestion rate, the mass-specific biomass production and the mortality rate of the individuals are independent of size, a condition to which we refer as “ontogenetic symmetry”. Intriguingly, under ontogenetic symmetry the equilibrium biomass-body size spectrum is proportional to 1/size, a form that has been conjectured for marine size spectra and subsequently has been used as prior assumption in theoretical papers dealing with the latter. As a next step we consider an archetypical class of models in which reproduction takes over from growth upon reaching an adult body size, in order to determine how quickly discrepancies from ontogenetic symmetry lead to relevant novel population dynamical phenomena. The phenomena considered are biomass overcompensation, when additional imposed mortality leads, rather unexpectedly, to an increase in the equilibrium biomass of either the juveniles or the adults (a phenomenon with potentially big consequences for predators of the species), and the occurrence of two types of size-structure driven oscillations, juvenile-driven cycles with separated extended cohorts, and adult-driven cycles in which periodically a front of relatively steeply decreasing frequencies moves up the size distribution. A small discrepancy from symmetry can already lead to biomass overcompensation; size-structure driven cycles only occur for somewhat larger discrepancies.     

江西千烟洲不同恢复途径下白栎种群生物量

利用不同自变量和函数,建立白栎枝条和单株地上各器官的生物量模型,选择其中的最佳模型估算了千烟洲人工造林和自然封育两种恢复途径下白栎种群地上生物量及其年增长量,并利用地上生物量和地下生物量的线性关系,估算了白栎种群地下生物量及其年增长量.结果表明:模拟白栎枝条和单株地上各器官生物量的最佳函数均为幂函数,而最佳自变量分别为d²l和D²H.白栎种群各器官生物量和总生物量均为天然次生林大于人工湿地松林.次生林中白栎种群地上和地下生物量分别为3.592和1.723 t·hm^-2,其中树干生物量>枝生物量>叶生物量;湿地松林中白栎种群地上和地下生物量分别为0.666和0.462 t·hm^-2,其中树干生物量>叶生物量>枝生物量.2004—2006年,两种恢复途径下白栎种群地上、地下及总生物量的年增长量均逐年增加.其中地上生物量年增长量占总年增长量的比重呈逐年升高趋势,湿地松林中由54.35%增至62.20%,次生林中由67.27%增至68.94%.与次生林相比,湿地松林中白栎种群各器官生物量年增长量较小,但其相对增长速率较快.     

基于生态效应的水稻籽粒蛋白质含量预测模型研究

在中国、日本、泰国不同生态环境下进行多品种籼型和粳型水稻(Oryza sativa)的区域种植试验,通过分析水稻籽粒蛋白质含量与纬度、海拔、抽穗后温度和太阳辐射等气候生态因子的相互关系,确立了影响水稻籽粒蛋白质积累的主要气候生态因子函数,并使用权重系数来进一步修订各气候生态因子对水稻籽粒蛋白质的作用,构建出基于生态效应(主要气候生态因子函数)的水稻籽粒蛋白质含量预测模型。利用不同年份、不同生态点、不同品种类型的试验资料对所建模型进行了检验,籼稻和粳稻籽粒蛋白质含量的预测误差RMSE平均分别为0.27%和0.24%;籼稻试验点和粳稻试验点的预测误差平均为0.25%和0.22%,表明模型总体上具有较好的预测性和实用性。     

Asymptotic behaviour of solutions to abstract logistic equations

We analyze the asymptotic behaviour of solutions of the abstract differential equation u'(t)=Au(t)-F(u(t))u(t)+f. Our results are applicable to models of structured population dynamics in which the state space consists of population densities with respect to the structure variables. In the equation the linear term A corresponds to internal processes independent of crowding, the nonlinear logistic term F corresponds to the influence of crowding, and the source term f corresponds to external effects. We analyze three separate cases and show that for each case the solutions stabilize in a way governed by the linear term. We illustrate the results with examples of models of structured population dynamics -- a model for the proliferation of cell lines with telomere shortening, a model of proliferating and quiescent cell populations, and a model for the growth of tumour cord cell populations.     

海三棱蔗草种群的密度与生物量动态

本文研究了上海市南汇县东海农场海堤外侧滩涂上海三棱藨草种群的密度动态,高度生长动态、生物量动态以及它们之间及其与环境之间的相互关系。研究结果表明：在环境条件相对稳定的地带A和B内,海三棱藨草种群的高度、高度生长和生物量在生长期内符合Logisfic增长。种群生物量动态与密度动态可分为3个阶段,其中阶段Ⅱ符合Yoda等提出的-3/2自疏定律。地带B为海三棱藨草种群生长的最适地带。地带C内生境条件极不稳定,种群的数量动态变化亦相当剧烈。在不同环境条件下,密度制约因素和非密度制约因素对种群数量动态的相对作用是不同的。在环境条件较稳定的生境中(地带A和B),密度制约因素是决定种群数量动态的主要因素;在环境条件变化剧烈的生境中(地带C),非密度制约因素是决定种群数量动态的主要因素。     

Meteorological driven factors of population growth in brown planthopper,Nilaparvata lugens Stål (Hemiptera: Delphacidae), in rice paddies

Growth of brown planthopper (BPH) (Nilaparvata lugens Stål) in rice paddies is mainly driven by meteorological factors under similar management practices. By analyzing field investigation and meteorological data collected from 2008 to 2013 in Nanchang, China, we show that BPH population densities and monthly growth rates (BGR) changed greatly from May to October, and these changes were closely associated with meteorological factors. Stepwise regression and path analysis indicated average speed of winds (AW) in June and lowest temperature (LT) in July were the first factors entering analysis, which interpreted 46.20% and 31.90% of their influences on BGR. While highest temperature (HT) in August and average temperature (AT) in September were the most important factors affecting BGR, but their direct path coefficients were all smaller than their corresponding indirect path coefficients. In October, relative humidity (RH), AW and number of raining days (RD) had significant effects on BGR. According to the sum of each meteorological factor entering stepwise regression analysis sequences, we found AW had the utmost effect on BPH growth, followed by AT and RH, but LT and RD least. The work demonstrate dynamic meteorological factors driving BPH growth and outbreak in rice paddies, which would facilitate the development of durable approaches for forecasting and controlling this destructive rice pest.     

井冈山自然保护区12种常见灌木生物量的估测模型

灌木生物量模型是估测灌木生物量的重要方法之一。以井冈山自然保护区林下12种常见灌木为研究对象,根据树高（H）和地径（D）两个形态因子作为变量,进行回归分析构建模型。通过对比判别系数R 2的大小,筛选最佳生物量估测模型。方程W=a＋b X12 X2、W=a＋b X＋c X 2和W=a X b在模拟生物量时相关指数均较高,为0.904-0.991,达到极显著水平,可用于实际生物量估测,而方程W=a＋b X、W=a＋b X1＋c X2和W=a＋b ln X在模拟灌木生物量时结果较差。利用此类方法建立的生物量模型,精度高,简便易行,对以后估算井冈山自然保护区灌木生物量和碳储量具有十分重要的意义。     

Application of a rice simulation model in high temperature sensitivity study

以调试校正较高精度的ORYZA2000模型参数及高温敏感性模拟验证为目的, 为模型适应性和本地化提供依据, 利用江苏省9个试验点5个水稻(Oryza sativa)品种的田间观测数据及当地逐日气象数据, 采用ORYZA2000最新版本(V2.13)水稻生长模型, 首先挑选出5个试验点3个品种的观测数据进行模型参数适应性调试校正, 确定了水稻发育生长阶段的各项参数, 然后用该参数对独立样本的4个试验点2个水稻品种地上部分各器官生物量、叶面积指数动态变化过程及最终产量进行了动态模拟。通过t检验和质量评价指标对模拟结果进行了显著性检验。利用通过检验的模型及其参数在假设环境温度不同时间段的持续升高条件下, 开展了高温对水稻生物量及产量影响的模拟研究, 模拟结果的影响幅度与实际高温处理结果的影响幅度进行了比较。结果表明: 1)经过调试校正获得较高精度的水稻发育阶段各参数, 较准确地模拟了水稻生物量和叶面积指数的动态累积过程, 模拟值与观测值基本一致, 说明校正后参数的合理性和有效性; 2)调整参数后高温敏感性模拟结果表明, 孕穗期到开花期温度连续3天、5天、7天升高到35 ℃时, 总生物量、穗生物量和总产量与对照(CK)相比分别下降了12%-25%; 不同时间段连续升高到38 ℃时下降18%-31%; 不同时间段升高到41 ℃时, 各生物量与对照相比分别下降了20%-38%。模型模拟值与控制试验室的观测数据的下降幅度基本一致, 表明经过参数校正的ORYZA2000可以应用于水稻对气温升高响应的预测。     

水稻模拟模型在高温敏感性研究中的应用

以调试校正较高精度的ORYZA2000模型参数及高温敏感性模拟验证为目的, 为模型适应性和本地化提供依据, 利用江苏省9个试验点5个水稻(Oryza sativa)品种的田间观测数据及当地逐日气象数据, 采用ORYZA2000最新版本(V2.13)水稻生长模型, 首先挑选出5个试验点3个品种的观测数据进行模型参数适应性调试校正, 确定了水稻发育生长阶段的各项参数, 然后用该参数对独立样本的4个试验点2个水稻品种地上部分各器官生物量、叶面积指数动态变化过程及最终产量进行了动态模拟。通过t检验和质量评价指标对模拟结果进行了显著性检验。利用通过检验的模型及其参数在假设环境温度不同时间段的持续升高条件下, 开展了高温对水稻生物量及产量影响的模拟研究, 模拟结果的影响幅度与实际高温处理结果的影响幅度进行了比较。结果表明: 1)经过调试校正获得较高精度的水稻发育阶段各参数, 较准确地模拟了水稻生物量和叶面积指数的动态累积过程, 模拟值与观测值基本一致, 说明校正后参数的合理性和有效性; 2)调整参数后高温敏感性模拟结果表明, 孕穗期到开花期温度连续3天、5天、7天升高到35 ℃时, 总生物量、穗生物量和总产量与对照(CK)相比分别下降了12%-25%; 不同时间段连续升高到38 ℃时下降18%-31%; 不同时间段升高到41 ℃时, 各生物量与对照相比分别下降了20%-38%。模型模拟值与控制试验室的观测数据的下降幅度基本一致, 表明经过参数校正的ORYZA2000可以应用于水稻对气温升高响应的预测。     

Individual variability and population regulation: a model of the significance of within-generation density dependence

Most models of theoretical population ecology consider population density as a state variable and thus ignore the fact that populations are composed not of identical average individuals but of individuals which are usually different. However, this individual variability may be important for population regulation. We therefore analysed an individual-based population model which explicitly describes within-generation processes, i.e. individual growth, starvation, and resource dynamics. The results show that if population dynamics are dominated by slow changes in resource level, the population size in the model undergoes wide oscillation, often leading to extinction. If, on the other hand, fast within-generation processes predominate, such as starvation and sudden drops in resource levels, the population fluctuates to a limited extent around an average. Within-generation density dependence may thus be an important mechanism which is largely ignored in classic time-discrete state-variable models. We conclude that the individual-based approach provides important insights into the hierarchical organization of population dynamics, i.e. the relationship between fast processes at the individual level and slower processes at the population level.     

A Functional and Structural Mongolian Scots Pine (Pinus sylvestris var. mongolica) Model Integrating Architecture, Biomass and Effects of Precipitation

Mongolian Scots pine (Pinus sylvestris var. mongolica) is one of the principal tree species in the network of Three-North Shelterbelt for windbreak and sand stabilisation in China. The functions of shelterbelts are highly correlated with the architecture and eco-physiological processes of individual tree. Thus, model-assisted analysis of canopy architecture and function dynamic in Mongolian Scots pine is of value for better understanding its role and behaviour within shelterbelt ecosystems in these arid and semiarid regions. We present here a single-tree functional and structural model, derived from the GreenLab model, which is adapted for young Mongolian Scots pines by incorporation of plant biomass production, allocation, allometric rules and soil water dynamics. The model is calibrated and validated based on experimental measurements taken on Mongolian Scots pines in 2007 and 2006 under local meteorological conditions. Measurements include plant biomass, topology and geometry, as well as soil attributes and standard meteorological data. After calibration, the model allows reconstruction of three-dimensional (3D) canopy architecture and biomass dynamics for trees from one- to six-year-old at the same site using meteorological data for the six years from 2001 to 2006. Sensitivity analysis indicates that rainfall variation has more influence on biomass increment than on architecture, and the internode and needle compartments and the aboveground biomass respond linearly to increases in precipitation. Sensitivity analysis also shows that the balance between internode and needle growth varies only slightly within the range of precipitations considered here. The model is expected to be used to investigate the growth of Mongolian Scots pines in other regions with different soils and climates.     

Meteorological forcing of plankton dynamics in a large and deep continental European lake

The timing of various plankton successional events in Lake Constance was tightly coupled to a large-scale meteorological phenomenon, the North Atlantic Oscillation (NAO). A causal chain of meteorological, hydrological, and ecological processes connected the NAO as well as winter and early spring meteorological conditions to planktonic events in summer leading to a remarkable memory of climatic effects lasting over almost half a year. The response of Daphnia to meteorological forcing was most probably a direct effect of altered water temperatures on daphnid growth and was not mediated by changes in phytoplankton concentrations. High spring water temperatures during ”high-NAO years” enabled high population growth rates, resulting in a high daphnid biomass as early as May. Hence, a critical Daphnia biomass to suppress phytoplankton was reached earlier in high-NAO years yielding an early and longer-lasting clear-water phase. Finally, an earlier summer decline of Daphnia produced in a negative relationship between Daphnia biomass in July and the NAO. Meteorological forcing of the seasonal plankton dynamics in Lake Constance included simple temporal shifts of processes and successional events, but also complex changes in the relative importance of different mechanisms. Since Daphnia plays an important role in plankton succession, a thorough understanding of the regulation of its population dynamics provides the key for predictions of the response of freshwater planktonic food webs to global climate change. Received: 15 February 1999 / Accepted: 23 August 1999     

Growth model and metabolic activity of brewing yeast biofilm on the surface of spent grains: a biocatalyst for continuous beer fermentation

In the continuous systems, such as continuous beer fermentation, immobilized cells are kept inside the bioreactor for long periods of time. Thus an important factor in the design and performance of the immobilized yeast reactor is immobilized cell viability and physiology. Both the decreasing specific glucose consumption rate (q(im)) and intracellular redox potential of the cells immobilized to spent grains during continuous cultivation in bubble-column reactor implied alterations in cell physiology. It was hypothesized that the changes of the physiological state of the immobilized brewing yeast were due to the aging process to which the immobilized yeast are exposed in the continuous reactor. The amount of an actively growing fraction (X(im)act) of the total immobilized biomass (X(im)) was subsequently estimated at approximately X(im)act = 0.12 g(IB) g(C)(-1) (IB = dry immobilized biomass, C = dry carrier). A mathematical model of the immobilized yeast biofilm growth on the surface of spent grain particles based on cell deposition (cell-to-carrier adhesion and cell-to-cell attachment), immobilized cell growth, and immobilized biomass detachment (cell outgrowth, biofilm abrasion) was formulated. The concept of the active fraction of immobilized biomass (X(im)act) and the maximum attainable biomass load (X(im)max) was included into the model. Since the average biofilm thickness was estimated at ca. 10 microm, the limitation of the diffusion of substrates inside the yeast biofilm could be neglected. The model successfully predicted the dynamics of the immobilized cell growth, maximum biomass load, free cell growth, and glucose consumption under constant hydrodynamic conditions in a bubble-column reactor. Good agreement between model simulations and experimental data was achieved.     

蚤数量与宿生数量和气象因子的关系

根据内蒙古自治区鄂托克旗和鄂托克前旗１９７５—１９８９年长爪沙鼠密度、蚤指数监测数据和本地区气象站的７项气象因子资料,分别求出了蚤指数与鼠密度的直线和曲线的回归模型,与气象因子的最优回归子集模型和标准回归模型,给出了鼠蚤因子和气象因子间的典型相关分析。结论：宿主数量变化导致蚤指数变化;气象因子综合影响蚤指数湘对湿度和地表温度是影响蚤数量变动的重要因子;气象因子对蚤指数的影响大于对鼠密度的影响。     

青菜/油菜茬口下水稻栽植方式对温光资源利用和产量的影响

轻简化栽培和优质稻是当前我国水稻生产的主要方向,气象因子是对水稻生长发育和产量形成影响最大的环境因素,但在不同轻简化栽植方式下水稻产量与其田间小气候的关系鲜有研究。为探究西南地区不同前作下杂交稻各生育阶段温、光和水等气候因子与水稻产量形成的关系,在2019—2020年,以杂交籼稻‘宜香优2115'为试验材料,采用两因素裂区设计,主区为青菜和油菜2种前作,副区为机直播、毯苗机插和人工移栽3种栽植方式,研究杂交稻产量对气候因子的响应及水稻植株对温光资源的利用。结果表明: 与油菜-水稻模式相比,青菜-水稻模式下杂交稻积温生产效率和降水生产效率显著提高,进而提高了有效穗数、结实率和千粒重,2年产量分别提高了12.7%和8.3%。与人工移栽相比,机插稻提高了单位面积有效穗数、全生育期光能生产效率、积温生产效率、籽粒光能利用效率和降水生产效率,2年平均产量提高了4.6%;而机直播全生育期降水生产效率、光能生产效率、积温生产效率、籽粒光能利用效率、每穗粒数和千粒重都显著降低,导致2年平均产量下降了8.7%。与2019年相比,2020年机插稻和人工移栽稻在同一茬口下提前一个月播种造成花后生育期缩短、气温降低和降雨量增多,导致有效积温和光辐射量大幅减少,积温生产效率、光能生产效率、降水生产效率和籽粒光能利用效率以及每穗粒数、结实率和千粒重均大幅降低,进而导致产量严重降低。用偏最小二乘法回归分析建立的气象因子产量预报方程标准化回归系数显示,水稻产量与阶段生育期或全生育期内有效积温和总辐射量呈正相关关系,与全生育期内降水量呈显著负相关关系。综上,青菜-水稻模式下机插秧与西南地区稻季光温资源匹配度最高,更有利于温光资源的充分利用和获得高产,但不宜过早播种或移栽。     

Application-oriented deep learning model for early warning of rice blast in Taiwan

Rice blast is one of the most devastating diseases that threatens rice production in Taiwan. A rice blast forecasting model is required to guide the precise application of fungicide. Therefore, BlastGRU-TW model based on deep learning algorithms was developed in this study. The input data comprised approximately 1000 rice blast surveys, collected from 50 fields throughout Taiwan between 2014 and 2021, and the corresponding weather data retrieved from weather observation network in Taiwan. Common and easily accessible meteorological factors, i.e. temperature, humidity, precipitation, and wind, were converted into 20 daily meteorological features which were coupled with different time intervals between 1 and 30 days before survey (DBS) to train the model. The results showed that seven meteorological features (daily maximum temperature, daily mean temperature, daily minimum temperature, daily mean humidity, daily mean WV and daily mean Wu) and the interval from −4 to −24 DBS were informative in disease prediction, thereby indicating that the proposed model could predict the risk of rice blast by using meteorological data 4–24 days before new disease symptoms appeared. The proposed BlastGRU-TW model achieved an accuracy of 87.3%. Furthermore, on adding the 3 day forecast weather data from Weather Research and Forecasting (WRF) model in the proposed model, the forecast extended to 7 days ahead of the appearance of new symptoms. Moreover, the BLASTAM model developed in Japan was implemented and validated in Taiwan to evaluate its applicability in different geographical areas. Finally, a rice blast early warning system (https://mycolab.pp.nchu.edu.tw/blast_forecast/index_en.php) equipped with an interactive web-based map is now available for real-time forecasting of the risk of rice blast in paddy field across Taiwan.     

水稻内生优势成团泛菌GFP标记菌株的性质与标记丢失动力学

为研究内生细菌对宿主植物侵染定殖的机理和其共生生物学作用 ,对水稻内生优势成团泛菌 (Pantoeaagglomerans)YS19与绿色荧光蛋白 (GFP)标记的YS19B ::gfp菌株的生长动力学进行了比较研究 ,探讨了成团泛菌YS19B ::gfp的标记稳定性和荧光性质 .标记菌株与野生型菌株相比 ,最大比生长速率和最大生物量仅减小 12 4 %和 6 % ,代时延长 14 0 % .成团泛菌YS19B ::gfp在指数期连续传代培养 10 0代后 ,GFP标记的保持率为 89 1% ,建立了标记菌株在有标记丢失存在时的生长动力学模型 :dX+ dt =μ+ (1-p)X+ ,解析出细胞分裂时标记丢失的概率p =9 75 6× 10 -7,确定了方程的模型参数 .标记菌株的荧光光谱在激发波长为 4 0 0nm时 ,最大发射波长为 5 0 8nm ,与供体菌株完全相同 .在LB培养基上生长时 ,成团泛菌YS19B ::gfp的GFP产生时间在指数期末期到稳定期较快 ,并于培养至 2 0h时达到最高 ,同时单位菌体生物量的荧光强度也达到最大 .结果说明 ,在GFP标记后成团泛菌YS19B ::gfp的生长仅受到较小影响 ,不致对成团泛菌的生理活动造成大的改变 ,同时由于该菌对宿主的侵染能力比其它内生细菌要强得多 ,因而该菌对植物的侵染活性影响也较小 ,该菌仍然可以保持其内生优势地位 .该标记的稳定性比较高 ,荧光产生正常 ,很适     

A semi-empirical model of methane emission from flooded rice paddy soils

Reliable regional or global estimates of methane emissions from flooded rice paddy soils depend on an examination of methodologies by which the current high variability in the estimates might be reduced. One potential way to do this is the development of predictive models. With an understanding of the processes of methane production, oxidation and emission, a semi-empirical model, focused on the contributions of rice plants to the processes and also the influence of environmental factors, was developed to predict methane emission from flooded rice fields. A simplified version of the model was also derived to predict methane emission in a more practical manner. In this study, it was hypothesized that methanogenic substrates are primarily derived from rice plants and added organic matter. Rates of methane production in flooded rice soils are determined by the availability of methanogenic substrates and the influence of environmental factors. Rice growth and development control the fraction of methane emitted. The amount of methane transported from the soil to the atmosphere is determined by the rates of production and the emitted fraction. Model validation against observations from single rice growing seasons in Texas, USA demonstrated that the seasonal variation of methane emission is regulated by rice growth and development. A further validation of the model against measurements from irrigated rice paddy soils in various regions of the world, including Italy, China, Indonesia, Philippines and the United States, suggests that methane emission can be predicted from rice net productivity, cultivar character, soil texture and temperature, and organic matter amendments.