Human Population Numbers as a Function of Food Supply

Human population growth has typically been seen as the primary causative factor of other ecologically destructive phenomena. Current human disease epidemics are explored as a function of population size. That human population growth is itself a phenomenon with clearly identifiable ecological/biological causes has been overlooked. Here, human population growth is discussed as being subject to the same dynamic processes as the population growth of other species. Contrary to the widely held belief that food production must be increased to feed the growing population, experimental and correlational data indicate that human population growth varies as a function of food availability. By increasing food production for humans, at the expense of other species, the biologically determined effect has been, and continues to be, an increase in the human population. Understanding the relationship between food increases and population increases is proposed as a necessary first step in addressing this global problem. Resistance to this perspective is briefly discussed in terms of cultural bias in science.     

城市适度人口规模研究

一个城市的适度人口规模既与经济发展水平密切相关,它是由所在地区的资源、环境等因素决定的。秦皇岛市是中国北方极度缺水的城市一,水资源构成了限制城市发展的短板因素。通过调整用水结构和采用节水技术,虽可使城市居民的用水份额适度增加,但总量约束决定了该城市的人口规模要保持在与水资源相适应的限度内。     

前置反硝化工艺外碳源投加串级控制策略研究

反硝化反应需要以有机碳源为电子受体.由于污水厂的进水负荷时刻在变化,当进水碳氮比较低时,需要外投加碳源.为了有效地控制外碳源投加量,提出了由两个PI控制器组成的外碳源投加串级控制策略,可以控制出水硝酸氮浓度以及缺氧区末端硝酸氮浓度.由Matlab/Simulink模拟表明,该控制器具有良好的动态品质、抗冲击负荷强,可快速响应进水负荷的变化,能在降低出水硝酸氮和总氮浓度的同时,大大降低外碳源投量.     

浙江省资源安全策略初探

随着浙江省城市化、工业化进程的加快,自然资源特别是水土资源的紧缺,已对全省经济和社会的可持续发展构成严重威胁。基于这样一个背景,文章以浙江省为研究对象,从区域资源安全的内涵出发,在分析了省域资源条件及供给现状的基础上,提出了构建区域资源安全体系的总体思路。根据浙江省的省情特点,构建区域资源安全体系的途径主要从建立集约型的区域资源利用体系、建立开放型的自然资源供给体系、建立综合型的资源安全保育体系、建立适用型的资源技术体系、建立预警型的资源管理体系等5个方面入手。     

Selecting parameters for calibration via sensitivity analysis: An individual-based model of mosquitofish population dynamics

A stochastic individual-based model (IBM) of mosquitofish population dynamics in experimental ponds was constructed in order to increase, virtually, the number of replicates of control populations in an ecotoxicology trial, and thus to increase the statistical power of the experiments. In this context, great importance had to be paid to model calibration as this conditions the use of the model as a reference for statistical comparisons. Accordingly, model calibration required that both mean behaviour and variability behaviour of the model were in accordance with real data. Currently, identifying parameter values from observed data is still an open issue for IBMs, especially when the parameter space is large. Our model included 41 parameters: 30 driving the model expectancy and 11 driving the model variability. Under these conditions, the use of “Latin hypercube” sampling would most probably have “missed” some important combinations of parameter values. Therefore, complete factorial design was preferred. Unfortunately, due to the constraints of the computational capacity, cost-acceptable “complete designs” were limited to no more than nine parameters, the calibration question becoming a parameter selection question. In this study, successive “complete designs” were conducted with different sets of parameters and different parameter values, in order to progressively narrow the parameter space. For each “complete design”, the selection of a maximum of nine parameters and their respective n values was carefully guided by sensitivity analysis. Sensitivity analysis was decisive in selecting parameters that were both influential and likely to have strong interactions. According to this strategy, the model of mosquitofish population dynamics was calibrated on real data from two different years of experiments, and validated on real data from another independent year. This model includes two categories of agents; fish and their living environment. Fish agents have four main processes: growth, survival, puberty and reproduction. The outputs of the model are the length frequency distribution of the population and the 16 scalar variables describing the fish populations. In this study, the length frequency distribution was parameterized by 10 scalars in order to be able to perform calibration. The recently suggested notion of “probabilistic distribution of the distributions” was also applied to our case study, and was shown to be very promising for comparing length frequency distributions (as such).     

Detecting Extinction Risk from Climate Change by IUCN Red List Criteria

Anthropogenic climate change is a key threat to global biodiversity. To inform strategic actions aimed at conserving biodiversity as climate changes, conservation planners need early warning of the risks faced by different species. The IUCN Red List criteria for threatened species are widely acknowledged as useful risk assessment tools for informing conservation under constraints imposed by limited data. However, doubts have been expressed about the ability of the criteria to detect risks imposed by potentially slow‐acting threats such as climate change, particularly because criteria addressing rates of population decline are assessed over time scales as short as 10 years. We used spatially explicit stochastic population models and dynamic species distribution models projected to future climates to determine how long before extinction a species would become eligible for listing as threatened based on the IUCN Red List criteria. We focused on a short‐lived frog species (Assa darlingtoni) chosen specifically to represent potential weaknesses in the criteria to allow detailed consideration of the analytical issues and to develop an approach for wider application. The criteria were more sensitive to climate change than previously anticipated; lead times between initial listing in a threatened category and predicted extinction varied from 40 to 80 years, depending on data availability. We attributed this sensitivity primarily to the ensemble properties of the criteria that assess contrasting symptoms of extinction risk. Nevertheless, we recommend the robustness of the criteria warrants further investigation across species with contrasting life histories and patterns of decline. The adequacy of these lead times for early warning depends on practicalities of environmental policy and management, bureaucratic or political inertia, and the anticipated species response times to management actions. Detección del Riesgo de Extinción a partir del Cambio Climático por medio del Criterio de la Lista Roja de la UICNKeith et al.     

Dynamics of a low‐density tiger population in Southeast Asia in the context of improved law enforcement

Recovering small populations of threatened species is an important global conservation strategy. Monitoring the anticipated recovery, however, often relies on uncertain abundance indices rather than on rigorous demographic estimates. To counter the severe threat from poaching of wild tigers (Panthera tigris), the Government of Thailand established an intensive patrolling system in 2005 to protect and recover its largest source population in Huai Kha Khaeng Wildlife Sanctuary. Concurrently, we assessed the dynamics of this tiger population over the next 8 years with rigorous photographic capture‐recapture methods. From 2006 to 2012, we sampled across 624–1026 km² with 137–200 camera traps. Cameras deployed for 21,359 trap days yielded photographic records of 90 distinct individuals. We used closed model Bayesian spatial capture‐recapture methods to estimate tiger abundances annually. Abundance estimates were integrated with likelihood‐based open model analyses to estimate rates of annual and overall rates of survival, recruitment, and changes in abundance. Estimates of demographic parameters fluctuated widely: annual density ranged from 1.25 to 2.01 tigers/100 km², abundance from 35 to 58 tigers, survival from 79.6% to 95.5%, and annual recruitment from 0 to 25 tigers. The number of distinct individuals photographed demonstrates the value of photographic capture–recapture methods for assessments of population dynamics in rare and elusive species that are identifiable from natural markings. Possibly because of poaching pressure, overall tiger densities at Huai Kha Khaeng were 82–90% lower than in ecologically comparable sites in India. However, intensified patrolling after 2006 appeared to reduce poaching and was correlated with marginal improvement in tiger survival and recruitment. Our results suggest that population recovery of low‐density tiger populations may be slower than anticipated by current global strategies aimed at doubling the number of wild tigers in a decade.     

大型浅水湖泊太湖霍甫水丝蚓次级生产力的研究

作为湖泊底栖动物优势种类的霍甫水丝蚓在长江中下游湖泊分布广泛,在湖泊生态系统的能流和物流中占有十分重要的地位。为了了解霍甫水丝蚓在大型浅水湖泊中的种群动态规律、生活史和周年生产量等的状况,于2005年1~12月对太湖霍甫水丝蚓进行周年的研究,以期为了解太湖这一优势种类的生产力状况及合理利用这一资源提供理论依据。研究发现,2005年太湖霍甫水丝蚓年均密度和生物量分别为3 274ind./m~2(0~13 800ind./m~2)和4.70g/m2(0~29.15g/m~2),一般均在冬季达到高峰,空间分布上霍甫水丝蚓密度和生物量呈现出明显的差异性,在太湖北部梅梁湾和竺山湾及西部河口湖区分布较高,而在其它区域的现存量均较低。根据体长频数分布的周年变化特征,推测太湖霍甫水丝蚓约为一年三代,繁殖可能发生在3、7和11月份期间。2005年太湖霍甫水丝蚓年生产量为480.21g·m~(-2)·yr-1,P/B为14.17,与同类研究报道相比属于较高水平。分析表明太湖霍甫水丝蚓的高世代数导致其高P/B系数,而高周年生产量与其所处的营养水平相对较高有关,这对于太湖渔产潜力具有显著意义。     

基于DMSP/OLS与土地利用的江苏省人口数据空间化研究

准确、高分辨率的人口分布信息是人地关系研究的重要前提。人口数据空间化可实现人口统计数据与空间信息集成,重构人口空间分布特征,为区域可持续发展研究提供数据支持。基于DMSP/OLS夜间灯光数据与土地利用数据,以遥感与地理信息系统理论与方法为基础,采用空间滞后回归模型模拟了江苏省2010年人口空间分布状况,并得到1km×1km的人口密度网格图。通过从县级、乡镇级两种空间尺度对人口数据空间化结果进行检验,结果表明基于DMSP/OLS与土地利用的人口数据空间化能够正确地表达人口空间分布规律,尤其对于人口较为密集地区,具有很高的数据重现精度;但是对于人口密度畸高或畸低的地区,由于人口空间分布异质性较大,数据重现的准确性下降。     

总量控制约束下区域用水结构调控策略及动态模拟

在既定水资源供给下,通过调控区域用水结构,提高用水效率与效益,使经济社会发展与用水总量限制的水资源约束相适应,是目前区域经济社会发展面临与亟待解答的关键科学问题。选择若干指标定量描述用水系统与社会经济系统耦合关系的基础上,以国民经济部门划分和用水主体划分相结合的方式,细化第一、二、三产业、生活和生态用水指标,建立了江苏省用水结构与产业结构、用水需求与经济社会发展指标互动反馈的模拟调控的系统动力学模型。在对当前发展模式下的江苏省用水总量发展趋势模拟预测分析基础上,选择对系统影响显著的参数作为调控变量,设计了5种对比情景,动态模拟水资源供求变化和用水结构变化情况,提出了江苏省用水总量控制下用水结构调控方案和对策,为区域落实最严格水资源管理制度提供决策依据。