Improving inferences about private land conservation by accounting for incomplete reporting

Private lands provide key habitat for imperiled species and are core components of function protectected area networks; yet, their incorporation into national and regional conservation planning has been challenging. Identifying locations where private landowners are likely to participate in conservation initiatives can help avoid conflict and clarify trade-offs between ecological benefits and sociopolitical costs. Empirical, spatially explicit assessment of the factors associated with conservation on private land is an emerging tool for identifying future conservation opportunities. However, most data on private land conservation are voluntarily reported and incomplete, which complicates these assessments. We used a novel application of occupancy models to analyze the occurrence of conservation easements on private land. We compared multiple formulations of occupancy models with a logistic regression model to predict the locations of conservation easements based on a spatially explicit social–ecological systems framework. We combined a simulation experiment with a case study of easement data in Idaho and Montana (United States) to illustrate the utility of the occupancy framework for modeling conservation on private land. Occupancy models that explicitly accounted for variation in reporting produced estimates of predictors that were substantially less biased than estimates produced by logistic regression under all simulated conditions. Occupancy models produced estimates for the 6 predictors we evaluated in our case study that were larger in magnitude, but less certain than those produced by logistic regression. These results suggest that occupancy models result in qualitatively different inferences regarding the effects of predictors on conservation easement occurrence than logistic regression and highlight the importance of integrating variable and incomplete reporting of participation in empirical analysis of conservation initiatives. Failure to do so can lead to emphasizing the wrong social, institutional, and environmental factors that enable conservation and underestimating conservation opportunities in landscapes where social norms or institutional constraints inhibit reporting.     

资阳市大气污染源排放清单研究

采用实地调研、资料收集等方式获得了2017年资阳市典型污染源的活动水平数据,参照城市大气污染物排放清单编制技术手册建立了基于排放因子法和物料衡算法的资阳市大气污染源排放清单,分析了主要污染物的行业排放特征和空间分布特征。结果表明,2017年资阳市SO₂、NO_X、CO、PM₁₀、PM_2.5、VOCs、NH₃总排放量分别为3.58kt、13.91kt、94.91kt、25.51kt、8.67kt、23.84kt和46.44kt。SO₂排放主要来自工业源;NOX排放主要来自移动源;CO排放主要来自工业过程及移动源;PM₁₀和PM_2.5、排放来自扬尘源和露天秸秆焚烧;VOCs主要来自溶剂使用源;NH₃主要来自农业活动。资阳市主要污染物排放分布在工业点源较为集中的雁江区和安岳县,乐至县污染物排放量相对较小。     

典型产业承接区土壤砷含量的空间分布特征及影响因素

本文以揭阳市为研究区域,采集了1330个表层土壤(0—20 cm)样品和331个深层土壤(150—200 cm)样品,利用富集因子法分析了表层土壤中As的污染状况,通过GIS空间分析技术以及单因素分析法探究了土壤As的空间分布特征以及影响因素.结果表明,研究区表层土壤As含量的均值为6.03 mg·kg^-1,低于该区土壤背景值(7.16 mg·kg^-1)及农用地土壤污染风险管控值(20 mg·kg^-1),大部分土壤为轻微污染和中度污染.揭阳市表层土壤As含量高值区分布于揭阳市东北部、中部和西南部地区,低值区分布于西北部和东南部地区.土壤类型、成土母质和土地利用类型是影响表层土壤As含量的重要因素,在不同土壤类型中,黄壤和赤红壤As含量相对较高;不同成土母质中,粉砂岩母质土壤As含量显著高于其他母质;在不同土地利用类型中,农用地土壤As含量最高.     

Microtargeting for conservation

Widespread human action and behavior change is needed to achieve many conservation goals. Doing so at the requisite scale and pace will require the efficient delivery of outreach campaigns. Conservation gains will be greatest when efforts are directed toward places of high conservation value (or need) and tailored to critical actors. Recent strategic conservation planning has relied primarily on spatial assessments of biophysical attributes, largely ignoring the human dimensions. Elsewhere, marketers, political campaigns, and others use microtargeting—predictive analytics of big data—to identify people most likely to respond positively to particular messages or interventions. Conservationists have not yet widely capitalized on these techniques. To investigate the effectiveness of microtargeting to improve conservation, we developed a propensity model to predict restoration behavior among 203,645 private landowners in a 5,200,000 ha study area in the Chesapeake Bay Watershed (U.S.A.). To isolate the additional value microtargeting may offer beyond geospatial prioritization, we analyzed a new high-resolution land-cover data set and cadastral data to identify private owners of riparian areas needing restoration. Subsequently, we developed and evaluated a restoration propensity model based on a database of landowners who had conducted restoration in the past and those who had not (n = 4978). Model validation in a parallel database (n = 4989) showed owners with the highest scorers for propensity to conduct restoration (i.e., top decile) were over twice as likely as average landowners to have conducted restoration (135%). These results demonstrate that microtargeting techniques can dramatically increase the efficiency and efficacy of conservation programs, above and beyond the advances offered by biophysical prioritizations alone, as well as facilitate more robust research of many social–ecological systems.     

基于支持向量回归机的南黄海浒苔分布面积预测模型

绿潮作为一种新型的海洋灾害,已经引起了各个国家的重视.依据2012年南黄海海域浒苔遥感监测分布面积数据,选取了温度、天气状况、风向、风力、浪高5种影响浒苔扩散的气候因子,建立了基于SVR的浒苔分布面积预测模型,并与经典的最近邻点插值模型、线性插值模型、3次样条函数插值模型和分段3次Hermite插值模型进行了回归效果的对比.分析结果表明,基于SVR的浒苔分布面积预测模型能够为浒苔遥感数据的插补提供一种方法,且回归效果优于传统的回归方法,为浒苔的防治提供辅助决策信息.     

2013年北京市PM2.5重污染日时空分布特征研究

根据2013年北京市环境保护监测中心监测的PM2.5数据,系统分析了北京市重污染日PM2.5污染的时空分布特征,并利用克里格插值初步统计了全年和重污染日PM2.5不同浓度区间的国土面积。2013年全市PM2.5年均浓度为89.5μg/m3,重污染日平均浓度为218μg/m3,重污染日主要集中在冬季;PM2.5年均浓度呈现明显的南高北低梯度分布特征,而重污染日空间分布较均匀,南部及城六区存在明显的高污染区,平均浓度在180μg/m3以上;2013年北京市重污染日PM2.5平均浓度为150~250μg/m3,其对应的国土面积约为12 656 km2,PM2.5平均浓度在250μg/m3以上的国土面积约为883 km2,而全年无PM2.5平均浓度在150μg/m3以上所对应的国土面积。     

大数据解析技术在大气环境监测中的应用研究

针对近年来新兴的大数据及挖掘、分析技术,对大数据解析技术在环境科学研究中的应用进行了分析和探析。以城市局部地区大气细颗粒污染物PM2.5浓度计算为例,筛选了PM2.5浓度历史数据、气象条件、交通状况、人群活动情况、网格道路状况等数据为影响特征量,分析了用神经网络法进行大数据解析和推演的原理和数学过程,是用数学、计算机、统计等方法研究解决多元、非线性复杂环境问题的一种新的探索。     

乌鲁木齐市近年来大气降尘变化规律及空间分布特征

基于乌鲁木齐市多年监测的降尘数据,对乌鲁木齐市城区的降尘量进行了统计分析,得出了乌鲁木齐市近10年来降尘的总体变化规律;利用方差分析方法检验了不同季节降尘的显著性差异,发现采暖期的降尘量明显大于非采暖期;按行政区分析降尘量的分布变化,结果为不同行政区存在差别;利用秩相关系数法对其进行了趋势分析。结果表明,乌鲁木齐市的降尘呈下降趋势。利用Arc GIS9.3中的普通克里格插值方法绘制了乌鲁木齐市城市自然降尘的空间分布图。     

Special needs hurricane shelters and the ageing population: development of a methodology and a case study application

Recent experience of hurricanes, particularly in the southeast United States, has heightened awareness of the multifaceted nature of and the challenges to effective disaster relief planning. One key element of this planning is providing adequate shelter at secure locations for people who evacuate. Some of these individuals will have ‘special needs’, yet there is little research on the relationship with shelter space. This study designed a geographic information systems‐based network optimisation methodology for the siting of special needs hurricane relief shelters, with a focus on the transportation component. It sought to find new locations for shelters that maximise accessibility by vulnerable populations, given capacity constraints, concentrating on the ageing population. The framework was implemented in a medium‐sized metropolitan statistical area in the state of Florida where data suggest a possible deficit in special needs shelter space. The study analysed options for increasing special needs shelter capacity, while considering potential uncertainties in transportation network availability.