耕地集约利用影响因素的协整分析

耕地利用的集约度实质上是农户在其所面临的各种经济和制度环境约束条件下,所采取的不同耕种行为的直接结果和体现.本文试借助分析影响农户耕种行为的相关因素来探讨其对耕地集约利用的影响.利用Eviews 6.0统计软件,综合应用协整理论和误差修正模型,以湖北省为例,剖析耕地集约利用与其影响因素的长期均衡关系和短期波动效应.研究表明:在长期,户均农业劳动力人数、农业比较收入和耕地的产权保障对耕地利用的集约度存在正向影响,其增加1个百分点,将导致耕地利用的集约度分别提高0.166、0.430和0.035个百分点;农民家庭人均农业生产支出和农业生产资料价格指数对耕地利用的集约度存在负向影响,其增加1个百分点,将导致耕地利用的集约度分别下降0.004和0.008个百分点.而在短期,各影响因素对耕地利用集约度的作用方向相同而作用力大小不同.户均农业劳动力人数和农业比较收入对耕地集约利用的作用程度在短期与在长期是相似的;但耕地的产权保障和农业生产成本的变化对耕地集约利用的影响却更多体现在长期.因此,立足于稳定产权和降低农业生产成本的农业政策导向更有利于在长期保护耕地,提高耕地资源的配置和利用效率.     

水环境质量评价3种方法的应用对比

从众多水质评价方法中选取单项指数法、加权均值型指数法、模糊数学法进行介绍,并通过运用这3种方法对大汶河某年监测数据的平均值进行评价.经对比分析发现,加权均值型指数法是一种比较实用的水质评价方法,模糊数学法可以作为必要的补充.     

MapGIS技术支持下的宜宾市翠屏区宋家乡环境地球化学质量评价

采用地质累积指数和污染程度分析方法,结合MapGIS空间分析技术,对宜宾市翠屏区宋家乡项目区土地质量进行系统的环境地球化学质量评价,重点对调查区的重金属元素(As、Hg、Cd、Cr、Zn、Cu、Pb、Ni)情况进行土壤质量评价。结果显示,宋家乡研究区土壤中存在不同程度的Hg、Cd、Cr、Zn、Pb、Ni和Cu重金属超标,主要集中在洋坪村、丘陵村和大地村,而大地村的镉超标较为严重,整个研究区砷没有出现污染。为此,结合实际查明造成重金属污染的原因,为该区土壤资源、环境评价和农业经济发展规划提供实用的地球化学信息。     

多孔介质中污染物运移空间变异最优估计

论述了空间变异性分析的原理和方法,着重阐述不同估值方法在多孔介质污染物运移空间变异分析中的应用.实践表明,地质统计学方法能够弥补经典概率统计方法在评价区域化变量空间变异性方面的不足,从而对多孔介质中污染物运移的空间变异性做出更切合实际的分析与评价.     

Changes in bird‐migration patterns associated with human‐induced mortality

Many bird populations have recently changed their migratory behavior in response to alterations of the environment. We collected data over 16 years on male Great Bustards (Otis tarda), a species showing a partial migratory pattern (sedentary and migratory birds coexisting in the same breeding groups). We conducted population counts and radio tracked 180 individuals to examine differences in survival rates between migratory and sedentary individuals and evaluate possible effects of these differences on the migratory pattern of the population. Overall, 65% of individuals migrated and 35% did not. The average distance between breeding and postbreeding areas of migrant individuals was 89.9 km, and the longest average movement of sedentary males was 3.8 km. Breeding group and migration distance had no effect on survival. However, mortality of migrants was 2.4 to 3.5 times higher than mortality of sedentary birds. For marked males, collision with power lines was the main cause of death from unnatural causes (37.6% of all deaths), and migratory birds died in collisions with power lines more frequently than sedentary birds (21.3% vs 6.3%). The percentage of sedentary individuals increased from 17% in 1997 to 45% in 2012. These results were consistent with data collected from radio‐tracked individuals: The proportion of migratory individuals decreased from 86% in 1997–1999 to 44% in 2006–2010. The observed decrease in the migratory tendency was not related to climatic changes (temperatures did not change over the study period) or improvements in habitat quality (dry cereal farmland area decreased in the main study area). Our findings suggest that human‐induced mortality during migration may be an important factor shaping the migration patterns of species inhabiting humanized landscapes.     

The problem of estimating recent genetic connectivity in a changing world

Accurate understanding of population connectivity is important to conservation because dispersal can play an important role in population dynamics, microevolution, and assessments of extirpation risk and population rescue. Genetic methods are increasingly used to infer population connectivity because advances in technology have made them more advantageous (e.g., cost effective) relative to ecological methods. Given the reductions in wildlife population connectivity since the Industrial Revolution and more recent drastic reductions from habitat loss, it is important to know the accuracy of and biases in genetic connectivity estimators when connectivity has declined recently. Using simulated data, we investigated the accuracy and bias of 2 common estimators of migration (movement of individuals among populations) rate. We focused on the timing of the connectivity change and the magnitude of that change on the estimates of migration by using a coalescent‐based method (Migrate‐n) and a disequilibrium‐based method (BayesAss). Contrary to expectations, when historically high connectivity had declined recently: (i) both methods over‐estimated recent migration rates; (ii) the coalescent‐based method (Migrate‐n) provided better estimates of recent migration rate than the disequilibrium‐based method (BayesAss); (iii) the coalescent‐based method did not accurately reflect long‐term genetic connectivity. Overall, our results highlight the problems with comparing coalescent and disequilibrium estimates to make inferences about the effects of recent landscape change on genetic connectivity among populations. We found that contrasting these 2 estimates to make inferences about genetic‐connectivity changes over time could lead to inaccurate conclusions.     

Material and energy recovery from Automotive Shredded Residues (ASR) via sequential gasification and combustion

Shredding is the common end-of-life treatment in Europe for dismantled car wrecks. It produces the so-called Automotive Shredded Residue (ASR), usually disposed of in landfill. This paper summarizes the outcome of a study carried out by Politecnico di Milano and LEAP with the support of Actelios SpA on the prospects of a technology based on sequential gasification and combustion of this specific waste stream. Its application to the treatment of ASR allows the recovery of large fractions of metals as non-oxidized, easily marketable secondary raw materials, the vitrification of most of the ash content and the production of power via a steam cycle. Results show that despite the unfavourable characteristics of ASR, the proposed technology can reach appealing energy performances. Three of four environmental impact indicators and the cumulative energy demand index are favourable, the main positive contributes being electricity production and metal recovery (mainly aluminium and copper). The only unfavourable indicator is the global warming index because, since most of the carbon in ASR comes from fossil sources, the carbon dioxide emissions at the stack of the thermal treatment plant are mainly non-renewable and, at the same time, the avoided biogas production from the alternative disposal route of landfilling is minor.     

Modelling with uncertainty: Introducing a probabilistic framework to predict animal population dynamics

Predictive population models designed to assist managers and policy makers require an explicit treatment of inherent uncertainty and variability. These are particular concerns when modelling non-native and reintroduced species, when data have been collected within one geographical or ecological context but predictions are required for another, or when extending models to predict the consequences of environmental change (e.g., climate or land-use). We present an aspatial, probabilistic framework of hierarchical process models for predicting population growth even when data are sparse or of poor quality. Insight into the factors affecting population dynamics in real landscapes can be provided and Kullback–Leibler distances are used to compare the relative output of models. This flexible yet robust framework gives easily interpretable results, allowing managers as well as modellers to invalidate anomalous models and apply others to real-life scenarios.We illustrate the framework’s power with a meta-analysis of European wild boar (Sus scrofa) data. We test hypotheses about the effect of geographic region, hunting and mast years on wild boar population growth, to build models of wild boar dynamics for the UK. The framework quantifies the importance of hunting pressure as a driver of population growth, and confirms that reproductive success is greatly decreased in poor mast years, suggesting that the key to predicting wild boar dynamics is to ascertain local hunting pressure and to better understand changing food availability. Geography had no significant effect, indicating that it is not a good proxy for modelling the impact of change in climate or land-use on wild boar populations at the European scale. We use the framework to predict population abundance 9 years after an isolated population of wild boar established in the UK; in a comparison with the only field data and two independent modelling exercises, our framework provides the most robust and informative results.