河北省县域可持续发展评价指标体系的建立与应用研究

以可持续发展相关理论为基础,利用系统工程的理论和方法建立了河北省县域可持续发展指标体系及其评价标准,并在全省范围应用,对全省136个县(市)可持续发展能力做出了评价。结合评价结果,阐述了河北省县域可持续发展能力的特征,提出了河北省县域可持续发展的方向和思路。     

“十一五”期间辽河铁岭段及支流水质变化趋势

用Daniel的Spearman秩相关系数法对辽河铁岭段及支流在"十一五"期间水质进行趋势检验,确定各监测断面超标污染物及综合污染指数上升或下降趋势的显著性,结合铁岭市"十一五"期间的污染治理措施,分析各项污染物产生变化的原因,提出了今后的工作方向,为进一步加强环境管理提供了依据。     

Fiscal spending and the environment: Theory and empirics

During economic crises, governments often increase fiscal spending to stimulate the economy. While the fiscal spending surge may be temporary, spending composition is often altered in favor of expenditures on social programs and other public goods which may persist over time. We model and measure the impact of fiscal spending patterns on the environment. The model predicts that a reallocation of government spending composition towards social and public goods reduces pollution. However, increasing total government spending without altering its composition does not reduce pollution. We empirically test these predictions for air and water pollutants showing that they are fully supported.     

Household incidence of pollution control policies: A robust welfare analysis using general equilibrium effects

This study assesses the incidence of pollution control policies on households. In contrast to previous studies, we employ an integrated framework combining a multisector general equilibrium model with a stochastic dominance analysis using household-level data. We consider three policy instruments in a domestic emission trading system: (i) an output-based allocation (OBA) of permits; (ii) the use of the proceeds of permit sales to reduce payroll taxes (RPT); (iii) and the use of these proceeds to reduce consumption taxes instead (UCS). The general equilibrium results suggest that the return to capital is more negatively affected than the wage rate in all simulations, since polluting industries are capital intensive. Abstracting from pollution externalities, the dominance analysis suggests that all three policies have a normatively robust negative (positive) impact on welfare (poverty). Formal dominance tests indicate that RPT first-order welfare dominates OBA over all values of household incomes. UCS also first-order poverty dominates RPT for any choice of poverty line below $CAN 18,600, and poverty dominates for any poverty line (and thus welfare dominates) at the second order. Finally, while the three pollution control policies do not have a numerically large impact on inequality (in comparison to the base run), statistical tests indicate that inequality increases significantly more with OBA and RPT than with UCS.     

Using simulation to explore the functional relationships of terrestrial carnivore population indices

Population indices based on visits to detection stations commonly are used to monitor wildlife populations. Inferences about populations are based on 1 of 2 measures: (1) change in the proportion of stations visited at least once or (2) change in the cumulative number of visits by unique individuals. The functional relationships between index responses and population density is poorly understood and can lead to misinterpretation of index data when an incorrect functional relationship (e.g. linear) is assumed. We created a flexible simulation environment to study the response of detection-based population indices under a wide variety of conditions meant to reflect species life history and study design. Proportional indices exhibited non-linear saturating responses to changes in population density while cumulative indices responded linearly. Shapes of responses were functions of home range sizes, individual detection probabilities, and spatial arrangement of animals and sampling stations. Non-linear relationships of proportional indices lead to under-estimation of mean population density when data are aggregated from multiple detection stations deployed in a heterogeneous landscape. Cumulative indices have significant statistical advantages over proportional indices including smaller sample sizes required to detect density change, linearity, consistent index responses across a wide range of densities, and ability to aggregate data to meet minimum sample size requirements. Our simulation provides a flexible tool for the interpretation of station-based population indices.     

Estimating dyad association probability under imperfect and heterogeneous detection

In animal behaviour studies, association indices estimate the proportion of time two individuals (i.e. a dyad) spend in association. In terms of dyads, all association indices can be interpreted as estimators of the probability that a dyad is associated. However, traditional indices rely on the assumptions that the probability to detect a particular individual (p) is either approximately one and/or homogeneous between associated and not associated individuals. Based on marked individuals we develop a likelihood based model to estimate the probability a dyad is associated (ψ) accounting for p < 1 and possibly varying between associated and not associated individuals. The proposed likelihood based model allows for both individual and dyadic missing observations. In addition, the model can easily be extended to incorporate covariate information for modeling p and ψ. A simulation study showed that the likelihood based model approach yield reasonably unbiased estimates, even for low and heterogeneous individual detection probabilities, while, in contrast, traditional indices showed moderate to strong biases. The application of the proposed approach is illustrated using a real data set collected from a population of Commerson's dolphin (Cephalorhynchus commersonii) in Patagonia Argentina. Finally, we discuss possible extensions of the proposed model and its applicability in animal behaviour and ecological studies.     

Integrating soil carbon cycling with that of nitrogen and phosphorus in the watershed model SWAT: Theory and model testing

In this paper we describe and test a sub-model that integrates the cycling of carbon (C), nitrogen (N) and phosphorus (P) in the Soil Water Assessment Tool (SWAT) watershed model. The core of the sub-model is a multi-layer, one-pool soil organic carbon (S_C) algorithm, in which the decomposition rate of S_C and input rate to S_C (through decomposition and humification of residues) depend on the current size of S_C. The organic N and P fluxes are coupled to that of C and depend on the available mineral N and P, and the C:N and N:P ratios of the decomposing pools. Tillage explicitly affects the soil organic matter turnover rate through tool-specific coefficients. Unlike most models, the turnover of soil organic matter does not follow first order kinetics. Each soil layer has a specific maximum capacity to accumulate C or C saturation (S_x) that depends on texture and controls the turnover rate. It is shown in an analytical solution that S_x is a parameter with major influence in the model C dynamics. Testing with a 65-yr data set from the dryland wheat growing region in Oregon shows that the model adequately simulates the S_C dynamics in the topsoil (top 0.3 m) for three different treatments. Three key model parameters, the optimal decomposition and humification rates and a factor controlling the effect of soil moisture and temperature on the decomposition rate, showed low uncertainty as determined by generalized likelihood uncertainty estimation. Nonetheless, the parameter set that provided accurate simulations in the topsoil tended to overestimate S_C in the subsoil, suggesting that a mechanism that expresses at depth might not be represented in the current sub-model structure. The explicit integration of C, N, and P fluxes allows for a more cohesive simulation of nutrient cycling in the SWAT model. The sub-model has to be tested in forestland and rangeland in addition to agricultural land, and in diverse soils with extreme properties such high or low pH, an organic horizon, or volcanic soils.     

基于氮磷指数的小流域氮磷流失风险评价

识别区域氮磷流失综合风险分布状况并对氮磷流失进行综合调控是控制非点源污染的有效措施。但传统的研究往往局限于氮或磷流失风险的单独评估和调控,以密云水库沿湖集约化农区东庄小流域为例,应用氮指数、磷指数及氮磷综合指数法,对区域氮磷流失风险进行综合评价。结果表明：流域氮、磷流失风险总体上较小,80%以上的区域均处于氮、磷流失的无风险或低风险区,但氮、磷流失的空间分布存在较大差异。其中氮流失的高度风险区集中在山地中土壤侵蚀指数较大的果园;而磷流失的高风险区域主要分布在河流沿岸的农业用地。氮磷综合风险指数显示,93.1%的区域处于无风险和低风险区,中度以上风险区占总面积的6.9%,主要集中在流域中部有着较高的肥料施用、地势陡峭且处在河流沿岸的农业用地或山地中。单独考虑氮指数或磷指数都难以反映区域氮磷流失的综合风险状况,容易忽略磷指数高氮指数低、氮指数高和磷指数低以及氮、磷风险在中等的区域。因此,在氮、磷流失风险评估基础上,进行氮磷流失风险的综合评价,可为氮磷流失的综合调控提供指导。     

井冈山森林碳储量与LAI和材积的相关性

建立林木生物量模型是估算森林生物量的重要方法之一,叶面积指数（Leaf Area Index,简称LAI）和材积与林木密切相关,是否可通过建立森林生物量与LAI或材积的相关模型来估算森林生物量,进而估算森林碳储量,值得探索。以井冈山自然保护区两种典型森林类型（常绿阔叶林和人工杉木林）为研究对象,分乔木层、植被层和总体（植被层＋土壤层）3部分分别计算碳密度,并对它们与叶面积指数LAI和材积之间的相关性进行分析。结果表明：常绿阔叶林总体碳密度为38．915kg／m^2,高于人工杉木林的27．460kg／m^2;两种森林类型乔木层和植被层碳密度与材积具有很好的相关性（R^2〉0．97）,在与LAI的相关性分析中,人工杉木林乔木层和植被层碳密度与LAI相关系数达到0．7以上,相关关系显著,而常绿阔叶林各层碳密度与LAI的相关性不明显;在森林总体碳密度与LAI和材积的相关性分析中发现,只有常绿阔叶林总体碳密度与材积的R^2为0．7116,达到显著水平,其它相关性水平均不显著。因此,利用材积与生物量和碳储量的相关关系来推算井冈山森林生物量和碳储量的方法是可行的,通过叶面积指数来推算森林生物量和碳储量的方法还有待进一步研究探讨。     

近50年三江源地表湿润指数变化特征及其影响因素

基于三江源区1959—2008年月平均气温、最高气温、最低气温、相对湿度、降水量、风速和日照百分率等气候要素资料,应用修订的Penman-Monteith（P-M）模型计算了最大潜在蒸散量和地表湿润指数,分析其空间分布、年际和年代际变化特征及其主要气象因子的影响。结果表明：1959—2008年间,研究区年降水量呈增加趋势,降水量变化曲线线性拟合倾向率为5.316~13.047 mm.（10a）-1,春夏季增幅较大;最大潜在蒸散量呈增加趋势,年最大潜在蒸散量变化曲线线性拟合倾向率在5.073~10.712 mm.（10a）-1,夏季增幅最大;地表湿润指数变化也呈增加趋势,年地表湿润指数变化曲线线性拟合倾向率0.011~0.026（10a）-1,冬季增幅最大,在15年周期附近,出现了3~5个干湿交替期,1984年之后为偏湿期,在中高频区,1998—2006年有偏干振荡;影响三江源区地表湿润指数的主要因子是降水量、相对湿度和平均最高气温。