Ecohydrological impact–assessment modeling: an example for terrestrial ecosystems in Noord-Holland, the Netherlands

In the Netherlands the increasing demand for ecohydrological models on a regional (provincial) scale has resulted in the development of an empirical statistical impact–assessment model for semi-natural terrestrial herbaceous ecosystems. This model, called ITORS, describes the relationship between plant species and site factors such as soil, groundwater and management. The model, developed for the region of Noord-Holland, is applied to support provincial policy on soil and water management. The empirical statistical approach required the collection of a large set of field data, describing the biotic and environmental variation of a variety of semi-natural terrestrial ecosystems in Noord-Holland. These data were used to calculate species response models with help of logistic regression, resulting in significant models for 130 out of 144 species. Significant species response models were incorporated in the computer program ITORS. With help of ITORS the effect of various management scenarios can be easily evaluated, which is demonstrated by an example. This revised version was published online in July 2006 with corrections to the Cover Date.     

Joint versus separate estimation of state and change in category frequencies from repeat stratified two-phase sampling with a fallible classifier

Joint maximum likelihood estimates (JML) of category frequencies and change from repeat stratified two-phase samplingsurveys with a fallible classifier are often seriously biased andhave large root mean square errors when they are obtained for small populations (<5000) with three or more categories and amoderate to small phase II sample size (<1000). JML estimates of state also depend on antecedent or posterior data, a recipe for inconsistency. In these situations, a separate maximum likelihood estimation (SML) of category frequenciesat each survey date appears preferable. SML estimates of net change are obtained as the difference in states. SML standard errors of change are obtained via an estimate of the temporal correlation and variances of state. A bivariate binarylogistic model of change provided the estimate of temporal correlation. SML generally outperformed JMLsignificantly in terms of bias and root mean square errors in eight case studies.     

Quantifying Habitat Requirements of Tree-Living Species in Fragmented Boreal Forests with Bayesian Methods

Abstract:  Quantitative conservation objectives require detailed consideration of the habitat requirements of target species. Tree-living bryophytes, lichens, and fungi are a critical and declining biodiversity component of boreal forests. To understand their requirements, Bayesian methods were used to analyze the relationships between the occurrence of individual species and habitat factors at the tree and the stand scale in a naturally fragmented boreal forest landscape. The importance of unexplained between-stand variation in occurrence of species was estimated, and the ability of derived models to predict species' occurrence was tested. The occurrence of species was affected by quality of individual trees. Furthermore, the relationships between occurrence of species at the tree level and size and shape of stands indicated edge effects, implying that some species were restricted to interior habitats of large, regular stands. Yet for the habitat factors studied, requirements of many species appeared similar. Species occurrence also varied between stands; most of the seemingly suitable trees in some stands were unoccupied. The models captured most variation in species occurrence at tree level. They also successfully accounted for between-stand variation in species occurrence, thus providing realistic simulations of stand-level occupancy of species. Important unexplained between-stand variation in species occurrence warns against a simplified view that only local habitat factors influence species' occurrence. Apparently, similar stands will host populations of different sizes due to historical, spatial, and stochastic factors. Thus, habitat suitability cannot be assessed simply by population sizes, and stands lacking a species may still provide suitable habitat and merit protection.     

Age at first marriage and its relation to fertility in Bangladesh

The 2007 Bangladesh Demographic and Health Survey(BDHS)data are exploited to examine the effects of socioeconomic and demographic factors on age at first marriage linkage to reproductive behavior of Bangladeshi women.The mean age at first marriage of women is found to be 15.48 years.Multivariate logistic regression technique shows that place of residence,religion,region,wealth index,education,and occupation are significantly important factors for determining age at first marriage.The relationship between marriage and fertility suggests that women who marry at a younger age produce more children than women who marry late.Findings of this study show that if the age at first marriage of adolescents is increased by 1 year,the age at first birth is postponed by 0.728 years.With the increase in age at first marriage,the fecundability of women sharply rises,whereas the proportion of temporary sterility decreases.Although there is a positive association between age at first marriage and age-specific marital fertility rates,the total parity per woman at the end of the reproductive period is expected to reduce by 0.196 for each 1-year delayed marriage.     

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.     

ARSENIC IN THE SHALLOW GROUND WATERS OF CONTERMINOUS UNITED STATES: ASSESSMENT,HEALTH RISKS,AND COSTS FOR MCL COMPLIANCE1

A methodology consisting of ordinal logistic regression (OLR) is used to predict the probability of occurrence of arsenic concentrations in different threshold limits in shallow ground waters of the conterminous United States (CONUS) subject to a set of influencing variables. The analysis considered a number of maximum contaminant level (MCL) options as threshold values to estimate the probabilities of occurrence of arsenic in ranges defined by a given MCL of 3, 5, 10, 20, and 50 μg/l and a detection limit of 1 μg/l. The fit between the observed and predicted probability of occurrence was around 83 percent for all MCL options. The estimated probabilities were used to estimate the median background concentration of arsenic in the CONUS. The shallow ground water of the western United States is more vulnerable than the eastern United States. Arizona, Utah, Nevada, and California in particular are hotspots for arsenic contamination. The risk assessment showed that counties in southern California, Arizona, Florida, and Washington and a few others scattered throughout the CONUS face a high risk from arsenic exposure through untreated ground water consumption. A simple cost effectiveness analysis was performed to understand the household costs for MCL compliance in using arsenic contaminated ground water. The results showed that the current MCL of 10 μg/l is a good compromise based on existing treatment technologies.     

Modelling of the location of vehicle recycling facilities: A case study in Poland

The technical progress causes that increasing number of used devices presents a threat for environment, particularly in the rural areas. It can be prevented by organizing a proper system of waste disposal. Currently, the most important problem to solve is recycling of vehicles. The key element for the improvement of the functioning of the recycling network in Poland is to redesign the system so that it will allow for a reduction of the total cost related to the vehicle recycling. This paper presents a modelling approach that could be used to establish one important part of the reverse logistics (RL) network for end-of-life vehicles (ELVs) by defining the optimum locations for dismantling facilities. The proposed modelling approach is illustrated using Mazovia province in Poland as an example. The optimization criteria for the location of the elements of the recycling network are the components of the total cost of the ELV's recycling. Due to high complexity of the model a genetic algorithm has been adapted for solving the model and getting a good solution in a reasonable run time. The criteria of optimization was cost of the following processes: transportation, storage, and dismantling of ELVs. The results of simulation proved that the transportation costs of parts and materials may amount to about 70%, and that the cost of dismantling may exceed 25% of the total cost of recycling. The obtained results confirmed that genetic algorithm method can be used effectively to location the ELV's dismantling facilities. The effect of changing the location of processing facilities on the location of dismantling stations was also studied. The developed model is universal and may be used to determine the locations of different kinds of facilities organized in a reverse recycling network.     

A Multiscale Landscape Approach to Predicting Bird and Moth Rarity Hotspots in a Threatened Pitch Pine–Scrub Oak Community

Abstract:  In the northeastern United States, pitch pine (  Pinus rigida Mill.)–scrub oak ( Quercus ilicifolia Wang.) communities are increasingly threatened by development and fire suppression, and prioritization of these habitats for conservation is of critical importance. As a basis for local conservation planning in a pitch pine–scrub oak community in southeastern Massachusetts, we developed logistic-regression models based on multiscale landscape and patch variables to predict hotspots of rare and declining bird and moth species. We compared predicted moth distributions with observed species-occurrence records to validate the models. We then quantified the amount of overlap between hotspots to assess the utility of rare birds and moths as indicator taxa. Species representation in hotspots and the current level of hotspot protection were also assessed. Predictive models included variables at all measured scales and resulted in average correct classification rates (optimal cut point) of 85.6% and 89.2% for bird and moth models, respectively. The majority of moth occurrence records were within 100 m of predicted habitat. Only 13% of all bird hotspots and 10% of all moth hotspots overlapped, and only a few small patches in and around Myles Standish State Forest were predicted to be hotspots for both taxa. There was no correlation between the bird and moth species-richness maps across all levels of richness ( r =−0.03, p = 0.62). Species representation in hotspots was high, but most hotspots had limited or no protection. Given the lack of correspondence between bird and moth hotspots, our results suggest that use of species-richness indicators for conservation planning may be ineffective at local scales. Based on these results, we suggest that local-level conservation planning in pitch pine–scrub oak communities be based on multitaxa, multiscale approaches.     

基于Logistic回归分析的农户参与水土流失治理状况研究——以鄂西地区为例

以鄂西地区利川市两类典型水土保持项目为例, 通过实地调查, 分析农户对水土保持工程的认知、行为特征及评价, 并采用Logistic模型分析了影响农户参与水土保持行为的因素。研究结果表明:农户对水土保持的参与认知度较高, 但是责任意识较差, 更多的寄于政府, 同时农户主要以参与水土保持工程建设的形式参与水土流失治理, 但在水土保持维护、组织、监督管理方面参与度较低;农户的教育水平越高, 其参与水土保持的程度越高;影响农户参与水土保持行为的因素主要是农户教育水平和水土保持外部环境;农户是否愿意参与水土保持与农户教育水平、政府采取的增收措施和工程补偿、水土保持工程进展呈显著性关系;农户主动参与水土保持工程与农户教育水平、是否检举破坏水土资源行为呈显著关系。结果对于揭示农户参与生态环境治理的行为机理有重要意义。     

中国电子垃圾回收企业的环保意识及行为的影响因素分析研究——以浙江为例

为了探索电子废弃物回收处理企业的环保意识及行为的影响因素,首先基于国内外研究学者的研究结果并结合中国电子废弃物回收处理企业的实践情况,提出一个假设结构框架。其次以浙江省为例,通过问卷调查法,将企业环保行为作为被解释变量,企业能力、管理者环境态度、消费者环境意识和企业经济效益作为解释变量,构建logistic回归模型,从而系统的揭示了企业进行环保处理的影响因素,研究结果表明:企业管理者环境态度对企业行为是否环保具有最重要的影响;企业经济效益对企业环保行为具有显著的正向作用;企业自身能力对企业环保行为具有一定程度的影响。最后,根据研究所得结果,提出了相应的促进企业进行环保处理的措施。