Bridging gaps in demographic analysis with phylogenetic imputation

Phylogenetically informed imputation methods have rarely been applied to estimate missing values in demographic data but may be a powerful tool for reconstructing vital rates of survival, maturation, and fecundity for species of conservation concern. Imputed vital rates could be used to parameterize demographic models to explore how populations respond when vital rates are perturbed. We used standardized vital rate estimates for 50 bird species to assess the use of phylogenetic imputation to fill gaps in demographic data. We calculated imputation accuracy for vital rates of focal species excluded from the data set either singly or in combination and with and without phylogeny, body mass, and life-history trait data. We used imputed vital rates to calculate demographic metrics, including generation time, to validate the use of imputation in demographic analyses. Covariance among vital rates and other trait data provided a strong basis to guide imputation of missing vital rates in birds, even in the absence of phylogenetic information. Mean NRMSE for null and phylogenetic models differed by <0.01 except when no vital rates were available or for vital rates with high phylogenetic signal (Pagel's λ > 0.8). In these cases, including body mass and life-history trait data compensated for lack of phylogenetic information: mean normalized root mean square error (NRMSE) for null and phylogenetic models differed by <0.01 for adult survival and <0.04 for maturation rate. Estimates of demographic metrics were sensitive to the accuracy of imputed vital rates. For example, mean error in generation time doubled in response to inaccurate estimates of maturation time. Accurate demographic data and metrics, such as generation time, are needed to inform conservation planning processes, for example through International Union for Conservation of Nature Red List assessments and population viability analysis. Imputed vital rates could be useful in this context but, as for any estimated model parameters, awareness of the sensitivities of demographic model outputs to the imputed vital rates is essential.     

南京北郊秋季高污染大气背景下云凝结核活化特性研究

于2019年10月17日—11月16日在南京北郊地区,采用SMPS-CCNC联用的方式,对8.2~346 nm的气溶胶粒子展开了粒径分辨的CCN活化特征观测.根据PM_2.5浓度范围选取了清洁天和污染天进行分析发现,在高污染大气背景下,由于有机物浓度及占比较高,无机盐浓度较低,故CCN活化率低于清洁天.清洁天SOA组分占比较高,其大气氧化经历更长,氧化态更高,吸湿参数κ也更高;污染天在受到直接排放的影响下,大气氧化经历短,氧化态较低,POA占比相对较高,所以清洁天的吸湿参数κ大于污染天κ(0.28±0.07>0.24±0.09).清洁天的f₄₄平均值为0.14±0.02,污染天的f₄₄平均值为0.12±0.02,进一步表明清洁天的有机气溶胶氧化态更高.因此,高污染大气背景下由于大气中存在很多受排放影响的积聚模态的气溶胶,含有很多低吸湿性物质,降低了CCN的活化能力和吸湿性.     

基于ADAMS的机械式内割刀切割失效影响研究

割刀常因振动而折断刀片,造成切割设备失效,影响施工安全。为降低ND-J114型号机械式内割刀的事故率提高割刀使用寿命,采用多体动力学的方法,利用ADAMS软件对其切削套管的过程进行动态模拟,在不同钻压和转速情况下,对割刀切削力和角加速度的变化规律进行分析,从割刀振动的角度出发,通过降低割刀的振动来降低刀片折断的风险。分析结果表明:割刀在切削套管的过程中最优钻压为4 800 N,割刀运转平稳;切削力的大小跟钻压近似于成正比关系;割刀最优转速为29 r/min,割刀运转平稳;切割转速在10~30 r/min时,切割效果较好,切割设备越不易折断;转速对切削力大小的影响较小。     

互花米草对苏北滨海湿地表土有机碳更新的影响

自互花米草引入苏北滨海湿地后,逐渐替代本土植物盐蒿并形成单一植被的互花米草湿地.选择苏北地区盐蒿湿地及不同生长年限的互花米草湿地,采集其表层土壤样品,分别测定全土和分离的土壤粒径组分中总有机碳及δ13C值,分析湿地土壤有机碳浓度及其同位素组成的变化.结果表明,互花米草引入盐蒿湿地后,表层土壤有机碳浓度显著增加(增量达70%),且随着互花米草生长时间延长而明显增加.与盐蒿湿地相比,互花米草湿地土壤中大团聚体(>250mm)和微团聚体组分(53~250mm)有机碳浓度均显著增加,而粉粒组分(2~53mm)则无明显变化.互花米草湿地土壤原状土及各粒径组分的δ13C值均明显高于盐蒿土壤,源于互花米草的新碳在各粒径组分中均有分布,但主要富集在大团聚体组分中,占该组分总碳的31%~43%,说明互花米草生长对土壤有机碳浓度增加主要反映在粗粒径组分中,而对粉、黏粒组分则影响较小.     

化学工业园的系统动力学仿真与调控

化学工业园属行业类工业园,入区企业主要为生产和销售化学工业品的化工企业,其排放的化学品污染物极易造成水环境和大气环境质量的恶化,为避免环境风险事故,必须对化学工业园的发展过程进行模拟和控制.以泰兴经济开发区为研究对象,在其现阶段发展基础上,根据该园区的实际情况,采用系统动力学(System Dynamics)模拟不同情景下的远期发展目标.基础仿真结果表明,泰兴经济开发区的环境现状不容乐观,尤其是大气环境污染几乎达到环境容量极限.情景分析表明,该开发园区必须将产业发展速度控制在18%,同时降低工业能耗,提高脱硫效率至90%以上,污水处理厂规模日处理量达4.9×104 t,才能保证其持续、稳定、健康的发展.      

兰州市南北两山不同生境红砂种群数量动态研究

对兰州市南北两山不同生境天然分布的红砂种群进行数量动态研究,通过径级结构回归年龄结构,编制静态生命表,绘制生存函数曲线,计算动态指数及谱分析,结果表明:不同生境红砂种群均表现为幼龄个体多,中老龄个体少,种群在Ⅲ龄级时死亡率最高,随着年龄增加,死亡率有所降低,Ⅶ、Ⅷ龄级由于生理衰老死亡率上升,种群存活曲线均接近于Deevey-Ⅲ型,年龄结构均接近增长型,增长潜力阴坡山下(5.90%)>阳坡山下(5.62%)>阴坡山上(4.77%)>阳坡山上(3.79%),并存在明显的周期性,红砂种群的数量动态变化整体上受其生命周期中生物学特性的控制;由于坡向及海拔差异带来的环境异质性,阴坡山下红砂种群整体生长最佳,阴坡山上和阳坡山下次之,而阳坡山上的红砂种群危险系数最大,受环境和种内压力共同作用显著,应适当抚育,从而促进种群持续发育。     

Generation time and the maximum growth rate for populations with age-specific fecundities and unknown juvenile survival

In age-classified population models where all parameters are known, the generation time and growth rate are calculated in a straightforward manner. For many populations, some parameters, such as juvenile survival, are difficult to estimate accurately. In a simplified population model where fecundity and survival are constant from the onset of breeding, it is known that generation time may be calculated given only adult survival, age at first reproduction, and the population growth rate. However, the assumption of constant fecundity from the onset of breeding does not hold for many populations. An extended population model allows calculation of generation time with the additional knowledge of the ratio of age-specific fecundities compared to a maximum fecundity rate. When these relative fecundities are unknown, an ad hoc adjustment to the simplified model performs well.When the study population is in an ideal environment, the optimal generation time and maximum growth rate are linked, and both may be approximated knowing only adult survival, age at first reproduction, and the relative fecundities. The maximum growth rate has important conservation implications, and calculating it correctly is therefore important. Improper use of the simplified population model to calculate the maximum growth rate, combined with a simple decision rule, leads to an average overharvest of 36%, and >60% for three of six bird species studied, compared to the full population model. By comparison, using the approximation from the extended or adjusted models results in average overharvests of only 8% (extended model) and 5% (adjusted model), and <50% for all six species (either model).     

A simulation model to evaluate the impacts of invasive earthworms on soil carbon dynamics

Recent studies have reported that earthworm invasions alter native communities and impact nutrient cycling in terrestrial ecosystems. We developed a simulation model to evaluate the potential impacts of earthworm invasions on carbon dynamics, taking into consideration earthworm feeding strategies and priming effects on the microorganisms through their casting activities. Responses of carbon stocks (forest litter, soil organic matter, microbial biomass and earthworm populations) and carbon fluxes (litter decomposition, earthworm consumption, and microbial respiration) were used to evaluate an earthworm invasion of a forest ecosystem. Data from a northern temperate forest (Arnot Forest, New York) were adapted for model calibration and evaluation. Simulation results suggest that the impact and outcome of earthworm invasions are affected by pre-invasion resource availability (litter and soil organic matter), invasive earthworm assemblages (particularly feeding strategy), and invasion history (associated with earthworm population dynamics). The abovementioned factors may also determine invasion progress of earthworm species. The accuracy of the model could be improved by the addition of environmental modules (e.g., soil water regimes), precise parameters accounting for individual species attributes under different environmental conditions (e.g. utilization ability of different types of food resources), as well as earthworm population dynamics (size and structure) and interactions with predators and other invasive/indigenous species during the invasion progress. Such an earthworm invasion model could provide valuable evaluation of the complicated responses of carbon dynamics to earthworm invasions in a range of forest ecosystems, particularly under global change scenarios.     

Choosing classes for size projection matrix models

Projection matrix models are intensely used in ecology to model the dynamics of structured populations. When dealing with size-structured populations, there is no satisfactory algorithm to partition size into discrete classes. We show that the Vandermeer-Moloney algorithm for choosing classes is inconsistent with the Usher model, and systematically selects the finest classes. Considering that the matrix model is a discrete approximation of a continuous model, we define an approximation error as the sum of a distribution error (the difference between the discrete distribution and its continuous counterpart), and a sample error. The optimal partition of size into classes is the one that minimizes the approximation error. This method for choosing classes also shows that the choice of the class width cannot be disconnected from the choice of the time step. When applied to 520 trees of Dicorynia guianensis in French Guiana, this algorithm identified 8 classes of 11.4 cm in width, which is in agreement with the empirical choice of foresters.     

城市环境影响模拟的系统动力学研究

城市化进程的加快已导致严重的环境问题。对城市环境影响的模拟研究是确定合理的城市发展规模和制定科学的发展规划的重要依据,以采取措施从源头控制环境质量的恶化。城市环境属于复合多动态系统,传统的一些方法可以实现城市环境影响的模拟预测,但参数调控方面的功能较不完善。文章将基于信息反馈控制理论的系统动力学引入城市环境影响模拟中,构建城市环境、社会、经济之间的系统动力学模型,通过调整环保投入、科技投入、经济增长速率以及单位能耗等系统变量,对武汉市未来发展的主要污染物（SO2、COD）排放量和主要资源消耗量（能源、水）等进行了四种情景动态模拟。结果表明：（1）系统动力学适合于研究复杂系统行为,具有较强的模拟和调控能力,同时可以避免繁琐的计算和信息成本高等缺点;（2）＂两型＂发展模式（Ⅳ）下的资源消耗量和污染物排放量明显低于其它3种情景,但仍处于较高的水平。武汉市污染物削减、生态环境保护任务依然繁重,开发新的替代能源、提高资源利用率仍是今后工作的重点。