The Sensitivity of Population Viability Analysis to Uncertainty about Habitat Requirements: Implications for the Management of the Endangered Southern Brown Bandicoot

Abstract:  Whenever population viability analysis (PVA) models are built to help guide decisions about the management of rare and threatened species, an important component of model building is the specification of a habitat model describing how a species is related to landscape or bioclimatic variables. Model-selection uncertainty may arise because there is often a great deal of ambiguity about which habitat model structure best approximates the true underlying biological processes. The standard approach to incorporate habitat models into PVA is to assume the best habitat model is correct, ignoring habitat-model uncertainty and alternative model structures that may lead to quantitatively different conclusions and management recommendations. Here we provide the first detailed examination of the influence of habitat-model uncertainty on the ranking of management scenarios from a PVA model. We evaluated and ranked 6 management scenarios for the endangered southern brown bandicoot ( Isoodon obesulus ) with PVA models, each derived from plausible competing habitat models developed with logistic regression. The ranking of management scenarios was sensitive to the choice of the habitat model used in PVA predictions. Our results demonstrate the need to incorporate methods into PVA that better account for model uncertainty and highlight the sensitivity of PVA to decisions made during model building. We recommend that researchers search for and consider a range of habitat models when undertaking model-based decision making and suggest that routine sensitivity analyses should be expanded to include an analysis of the impact of habitat-model uncertainty and assumptions.     

The Influence of Atmospheric N Deposition on Nitrous Oxide and Nitric Oxide Fluxes and Soil Ammonium and Nitrate Concentrations

The deposition of atmospheric N to soils provides sources of available N to the nitrifying and denitrifying microbial community and subsequently influences the rate of NO and N₂O emissions from soil. We have investigated the influence of three different sources of enhanced N deposition on NO and N₂O emissions 1) elevated NH₃ deposition to woodlands downwind of poultry and pig farms, 2) increased wet cloud and occult N deposition to upland forest and moorland and 3) enhanced N deposition to trees as NO ₃ ^– and NH ₄ ⁺ aerosol. Flux measurements of NO and N₂O were made using static chambers in the field or intact and repacked soil cores in the laboratory and determination of N₂O by gas chromatography and of NO by chemiluminescence analysis. Rates of N deposition to our study sites were derived from modelled estimates of N deposition, NH₃ concentrations measured by passive diffusion and inference from measurements of the ²¹⁰Pb inventory of soils under tree canopies compared with open grassland. NO and N₂O emissions and KCl-extractable soil NH ₄ ⁺ and NO ₃ ^– concentrations all increased with increasing N deposition rate. The extent of increase did not appear to be influenced by the chemical form of the N deposited. Systems dominated by dry-deposited NH₃ downwind of intensive livestock farms or wet-deposited NH ₄ ⁺ and NO ₃ ^– in the upland regions of Britain resulted in approximately the same linear response. Emissions of NO and N₂O from these soils increased with both N deposition and KCl extractable NH ₄ ⁺ , but the relationship between NH ₄ ⁺ and N deposition (ln NH ₄ ⁺ = 0.62 ln N_deposition + 0.21, r ² = 0.33, n = 43) was more robust than the relationship between N deposition and soil NO and N₂O fluxes.     

OPTIMIZING THE PROBABILITIES OF WATER YIELD FOR THE RIDAURA AQUIFER (SPAIN)1

ABSTRACT: Aquifer pumping represents, in many geographical locations, an alternative and/or a complementary source of water to surface water supplies. Several Catalonian coastal towns in the northeastern corner of Spain are in this situation. Also, since pumped water is used to supply drinking water, the main purpose in managing these water resources is to supply, no matter the cost, the amount needed at every moment. In other words, the managers of these aquifers attempt to optimize firm water yield. If we think of these aquifers as underground reservoirs with fixed storage capacity, most of the techniques which are applied to surface reservoirs can be implemented. In this paper we use a Stochastic Dynamic Programming model to optimize the yield from the aquifer of the Ridaura River. The objective function in this model was chosen with the aim of maximizing the reliability of the target yields in each of four seasons.     

污水塘自净作用及环境因素的影响

本文研究了在自然状况下污水塘的净化作用及其效率,通过对总氮、总磷、COD_(Cr)和BOD_5等在进、出水中的含量与水温进行回归分析,建立了三者之间的相关性方程。同时讨论了水温对污水塘的自净效率的影响。     

影响食品行业社会组织参与食品安全风险治理能力的主要因素研究

事实再次证明,单纯由政府主导的食品安全监管模式已无法满足人们对于食品安全的消费需求。政府和市场在食品安全风险治理中出现的政府公权和市场私权的"双重失灵",迫切需要社会组织的参与。本文通过深度访问和问卷调查的形式,基于主成分分析方法将影响食品行业社会组织参与食品安全风险治理能力的影响因素指标融合为互不相关的综合指标,并由此构建了多元线性回归模型,研究了影响食品行业的社会组织参与食品安全风险治理能力的主要因素。研究结果表明,社会组织的公信力、与政府的关系、政府支持力度、社会组织的信息公开程度、专职人员的数量与质量等因素与其参与治理能力存在较强的正相关;社会组织法定代表人年龄、现职国家机关公务人员在组织内担任职务的比例与其参与治理的能力存在较高的负相关。因此,社会组织在食品安全的风险治理中是否能发挥自身独有的优势,弥补政府和市场在食品安全风险中的双重失灵,内在地取决于社会组织的外部环境、内部治理结构与内部管理水平。构建具有中国特色的食品安全社会共治体系亟需逐步完善社会组织的立法,明确社会组织的法律地位,确保社会组织在法律框架下按照各自的章程自主性地开展的各种活动,政府在法律框架下履行支持社会组织发展的职能力度;同时优化内部人员结构,建设具有数量充足、能力结构基本完备的工作人员队伍,并依据改革要求,优化法定代表人的结构,建立诚信信息服务平台,提升自身的社会公信度,由此保障社会组织在参与食品安全风险治理过程中的独立性,发挥自身专业性、自治性等优势。     

A method to combine non-probability sample data with probability sample data in estimating spatial means of environmental variables

In estimating spatial means of environmental variables of a region from datacollected by convenience or purposive sampling, validity of the results canbe ensured by collecting additional data through probability sampling. Theprecision of the estimator that uses the probability sample can beincreased by interpolating the values at the nonprobability sample points tothe probability sample points, and using these interpolated values as anauxiliary variable in the difference or regression estimator. Theseestimators are (approximately) unbiased, even when the nonprobability sampleis severely biased such as in preferential samples. The gain in precisioncompared to the estimator in combination with Simple Random Samplingis controlled by the correlation between the target variable andinterpolated variable. This correlation is determined by the size (density)and spatial coverage of the nonprobability sample, and the spatialcontinuity of the target variable. In a case study the average ratio of thevariances of the simple regression estimator and estimator was 0.68for preferential samples of size 150 with moderate spatial clustering, and0.80 for preferential samples of similar size with strong spatialclustering. In the latter case the simple regression estimator wassubstantially more precise than the simple difference estimator.     

基于多元线性回归的煤矿驾驶员情绪预测模型*

为研究煤矿人车驾驶员情绪状态不良引发的煤矿驾驶事故问题,设计眼动实验并建立基于多元线性回归的驾驶员情绪状况预测模型对驾驶员情绪状况进行预测;通过眼动仪采集煤矿驾驶员良好情绪与不良情绪状态下的各项眼动指标,记录其主观情绪状态;使用多元线性回归方程对数据进行分析与建模,采用平均相对误差对预测模型进行评估。结果表明:每秒注视点个数、平均扫视速度、反应时间、危险源辨识个数在情绪变化前后存在显著差异,且与情绪状态呈较强相关;基于多元线性回归的驾驶员情绪状况预测模型预测精度较高,平均相对误差为8.16%。模型适用于煤矿人车驾驶员的情绪监测,可为煤矿驾驶员安全行驶提供保障。     

Hydrogen explosion incident mitigation in steam reforming units through enhanced inspection and forecasting corrosion tools implementation

Hydrogen (H₂) explosion effects recently examined, are confirming the devastating loss scenarios to humans, environment, assets, and associated business interruption. H₂ production is a core process in refineries used in further process steps. Steam reforming of natural gas or a mix with naphtha or LPG is a common hydrogen production technique, where the latest technologies have adopted enhanced metallurgies to minimize explosion risk and the associated maintenance cost following plant degradation owing to corrosion effects. However, corrosion rates are still high in specific areas of piping and process equipment. The aim of this paper is to present a methodology based on semi-quantitative RBI modeling according to regulations by API and recent EN standards, adopting a family of linear regression forecasting models that depict the yearly corrosion rate (per corrosion loop) of a hydrogen production steam reforming unit; this is done under different operating conditions (e.g., temperature, pressure, and fluid speed), metallurgy and other related physicochemical variables. The model is based on the examination of both ultrasonic wall thinning measurements and the examination of quantitative crosslinking total corrosion effects along with the physicochemical properties prevailing in different plant corrosion loops. The outcome of the regression analysis is an expansive family of multivariable equations describing, with a defined accuracy, the yearly corrosion rate and associated lifespan forecast per corrosion loop, and per examined part. These equations were further utilized in a custom-made database that can be used as an additional loss prevention tool by the hydrogen production unit management team. Evaluation results regarding the tool efficiency are presented in the following of this paper.     

粤北某离子吸附型稀土矿山土壤和地表水重金属分布及风险评价

对粤北某离子吸附型稀土矿24个土壤样品中的As、Cd、Cr、Cu、Mn、Ni、Pb、Zn和Hg,以及15个地表水样品中的As、Cd、Cu、Hg、Mn、Pb和Zn进行了检测,并以多元统计分析与土壤潜在生态风险指数法、地表水健康风险评价模型相结合的方式,研究了重金属的分布特征及风险水平。结果表明:在土壤中,Mn、Zn、Cd和Pb的平均含量均超过了背景值;Mn、Cr、Ni、Cu、Cd和Zn在采区有较明显集聚,As、Pb和Hg的高含量分布相对均匀;Cr、Ni、Cu和Pb含量主要受区域背景影响,Zn、As、Cd和Hg含量与矿区人类活动关系密切,Mn含量受自然和人为因素共同控制;重金属造成的土壤潜在生态风险整体处于轻微水平,Ⅱ采区和Ⅶ采区生态风险较高;Cd和Hg是造成土壤生态危害的主要重金属元素。在地表水中,Mn的平均浓度超过了《地表水环境质量标准》(GB 3838-2002)规定的限值,其余重金属的含量均满足该标准中的Ⅲ类水质要求;重金属浓度在靠近采区及位于河流中下游的位置偏高;Mn、Cd、Pb、Zn和Cu浓度受稀土开采影响较大,As、Hg浓度主要受自然因素影响;重金属产生的健康总风险(9.39×10^-7~1.01×10^-6 a^-1)低于国际辐射防护委员会推荐的参考标准(5×10^-5 a^-1),但儿童通过饮水途径受到的健康风险(1.01×10^-6 a^-1)略超过部分机构的推荐限值;Cd和As是地表水中产生健康风险的主要重金属元素。综上,研究区重金属污染风险管理的主要对象是Cd和Mn。     

Degradation–environment–society spiral: A spatial auto‐logistic model in Thailand

In this contemporary interpretation of the widespread land degradation problem in Southeast Asia, it is hypothesized that spatial interplay of environmental and socioeconomic predictors determines the occurrence of land degradation. Village surveys, remote sensing and spatial auto‐logistic modelling of the relationship between degradation and land use dynamics in Lam Phra Phloeng watershed of Thailand enabled 80.2% of land to be classified correctly in terms of the presence or absence of erosion and explained 53.2% of the total variation. Cultivation and dependence on agriculture for livelihood positively and significantly affect degradation. Lack of access to institutional credit and land titles significantly increased the probability of occurrence of degradation. On the other hand, education and social cohesion are negatively associated with the occurrence of degradation. The Relative Operating Characteristic (ROC) curve was used to measures the performance of the model. The calculated area under the curve (0.879) suggests that significant predictor variables in the model can be confidently used to forecast the likelihood of occurrence of degradation and thus to identify priority areas for intervention. Policies to reduce land degradation should include measures to reduce pressure on the land, including alternative income sources. Policies could mobilize capital to invest in encouraging nature‐based tourism and other off‐farm income options.