Bird‐community responses to habitat creation in a long‐term,large‐scale natural experiment

Ecosystem function and resilience are compromised when habitats become fragmented due to land‐use change. This has led to national and international conservation strategies aimed at restoring habitat extent and improving functional connectivity (i.e., maintaining dispersal processes). However, biodiversity responses to landscape‐scale habitat creation and the relative importance of spatial and temporal scales are poorly understood, and there is disagreement over which conservation strategies should be prioritized. We used 160 years of historic post‐agricultural woodland creation as a natural experiment to evaluate biodiversity responses to habitat creation in a landscape context. Birds were surveyed in 101 secondary, broadleaf woodlands aged 10–160 years with ≥80% canopy cover and in landscapes with 0‐17% broadleaf woodland cover within 3000 m. We used piecewise structural equation modeling to examine the direct and indirect relationships between bird abundance and diversity, ecological continuity, patch characteristics, and landscape structure and quantified the relative conservation value of local and landscape scales for bird communities. Ecological continuity indirectly affected overall bird abundance and species richness through its effects on stand structure, but had a weaker influence (effect size near 0) on the abundance and diversity of species most closely associated with woodland habitats. This was probably because woodlands were rapidly colonized by woodland generalists in ≤10 years (minimum patch age) but were on average too young (median 50 years) to be colonized by woodland specialists. Local patch characteristics were relatively more important than landscape characteristics for bird communities. Based on our results, biodiversity responses to habitat creation depended on local‐ and landscape‐scale factors that interacted across time and space. We suggest that there is a need for further studies that focus on habitat creation in a landscape context and that knowledge gained from studies of habitat fragmentation and loss should be used to inform habitat creation with caution because the outcomes are not necessarily reciprocal.     

广州海洋观测网规划建设及观测数据应用探讨

阐述了广州海洋观测网建设的迫切性和必要性,对海洋观测网建设在海洋防灾减灾、海岸工程建设及海水养殖等方面的重要意义进行了分析说明。总结广州市海洋观测网建设现状和成果,并利用已有观测数据对2017年台风^“天鸽^”和^“帕卡^”期间广州海域水文气象特征、2015—2017年枯水期咸潮入侵特征进行了分析。研究表明, 现有观测数据对台风和咸潮活动均具有较明显的反应,且对海洋防灾减灾工作具有重要的意义;为更有效地利用已有观测数据,将观测数据价值最大化,对观测网建设及运行过程中观测工作机制及业务化流程、数据质量控制、观测站布设合理性以及数据应用分析这几个方面存在的问题进行了探讨,提出了广州海洋观测网的优化、改进措施及未来发展方向。     

Evaluating outcomes of conservation with multidimensional indicators of well-being

Many conservation interventions are hypothesized to be beneficial for both the environment and people's well-being, but this has rarely been tested rigorously. We examined the effects of adoption or nonadoption of a conservation intervention on 3 dimensions of people's well-being (material, relational, and subjective) over time. We focused on a fisheries bycatch management initiative intended to reduce environmental externalities associated with resource extraction. We collected panel data from fishers (n = 250) in villages with (adopters and nonadopters) and without (control) the conservation intervention 3 times over 2 years. We found no evidence that adoption reduced any of the 3 dimensions of well-being in the local populations affected by the intervention. There were modest improvements in material (t = –1.58) and subjective livelihood well-being (p = 0.04) for adopters relative to nonadopters over time. The variations in well-being experiences (in terms of magnitude of change) among adopters, nonadopters, and controls across the different domains over time affirmed the dynamic and social nature of well-being.     

Pulling force prediction using neural networks

Purpose. In ergonomics and human factors investigations, pulling force (PF) estimation has usually been achieved using various types of biomechanical models, and independent approximation of PF was done with the help of upper extremity joints. Recently, multiple regression methods have gained importance for task-relevant inputs in predicting PF. Artificial neural networks (ANNs) also play a vital role in fitting the data; however, their use in work-related biomechanics and ergonomics is inadequate. Therefore, the current research aimed to accomplish comparative investigation of ANN and regression models by assessing their capacity to predict PF values. Methods. Multipositional PF data were acquired from 200 subjects at three different handle heights and body locations. ANN and regression models were formed using a random sample of three subsets (75% training, 15% selection, 10% validation) for proving the outcomes. Results. The comparison of ANN and regression models shows that the predictions of ANN models had a profoundly explained variance and lower root mean square difference values for the PF data at three handle heights. Conclusions. These outcomes advise that ANNs offer a precise and robust substitute for regression methods, and should be considered a useful method in biomechanics and ergonomics task assessments.     

供水管网系统地震易损性风险评估

供水管网易损性风险评估就是通过识别和分析系统的易损性,找出管网中相对比较薄弱的部分,为确定安全策略和采取控制措施提供理论依据。借鉴网络脆弱性评估理论和方法,基于震后供水管网的连通性分析和水力分析结果,采用分层的分析方法,以管网的拓扑位置和节点服务特性作为影响管网易损性的因素,分配给各节点一定的权值,计算其易损性指标,采用定性与定量相结合的方法评判其易损性程度。对一实际管网进行地震易损性风险评估,说明了该方法的有效性与合理性。     

Rapid estimation of compost enzymatic activity by spectral analysis method combined with machine learning

The aim of this study was to investigate the feasibility of using visible near-infrared (VisNIR) diffuse reflectance spectroscopy (DRS) as an easy, inexpensive, and rapid method to predict compost enzymatic activity, which traditionally measured by fluorescein diacetate hydrolysis (FDA-HR) assay. Compost samples representative of five different compost facilities were scanned by DRS, and the raw reflectance spectra were preprocessed using seven spectral transformations for predicting compost FDA-HR with six multivariate algorithms. Although principal component analysis for all spectral pretreatments satisfactorily identified the clusters by compost types, it could not separate different FDA contents. Furthermore, the artificial neural network multilayer perceptron (residual prediction deviation = 3.2, validation r² = 0.91 and RMSE = 13.38 μg g^?1 h^?1) outperformed other multivariate models to capture the highly non-linear relationships between compost enzymatic activity and VisNIR reflectance spectra after Savitzky–Golay first derivative pretreatment. This work demonstrates the efficiency of VisNIR DRS for predicting compost enzymatic as well as microbial activity.     

Beyond the material grave: Life Cycle Impact Assessment of leaching from secondary materials in road and earth constructions

In industrialized countries, large amounts of mineral wastes are produced. They are re-used in various ways, particularly in road and earth constructions, substituting primary resources such as gravel. However, they may also contain pollutants, such as heavy metals, which may be leached to the groundwater. The toxic impacts of these emissions are so far often neglected within Life Cycle Assessments (LCA) of products or waste treatment services and thus, potentially large environmental impacts are currently missed. This study aims at closing this gap by assessing the ecotoxic impacts of heavy metal leaching from industrial mineral wastes in road and earth constructions. The flows of metals such as Sb, As, Pb, Cd, Cr, Cu, Mo, Ni, V and Zn originating from three typical constructions to the environment are quantified, their fate in the environment is assessed and potential ecotoxic effects evaluated. For our reference country, Germany, the industrial wastes that are applied as Granular Secondary Construction Material (GSCM) carry more than 45,000 t of diverse heavy metals per year. Depending on the material quality and construction type applied, up to 150 t of heavy metals may leach to the environment within the first 100 years after construction. Heavy metal retardation in subsoil can potentially reduce the fate to groundwater by up to 100%. One major challenge of integrating leaching from constructions into macro-scale LCA frameworks is the high variability in micro-scale technical and geographical factors, such as material qualities, construction types and soil types. In our work, we consider a broad range of parameter values in the modeling of leaching and fate. This allows distinguishing between the impacts of various road constructions, as well as sites with different soil properties. The findings of this study promote the quantitative consideration of environmental impacts of long-term leaching in Life Cycle Assessment, complementing site-specific risk assessment, for the design of waste management strategies, particularly in the construction sector.     

The green state and industrial decarbonisation

ABSTRACT

The large share of carbon emitted by energy-intensive industries in the extraction and processing of basic materials must be limited to decarbonise society and the economy. Ways in which the state can govern industrial decarbonisation and contributes to green state theory are explored by addressing a largely ignored issue: the green state’s industrial relations and its role in industrial governance. With insights from a Swedish case study, the tension between the state’s economic imperative and ecological concerns in greening industry are shown to persist. However, as the energy-intensive industry’s previously privileged position in the economy is weakening, industry is opened to decarbonisation strategies. While the case exposes a number of governance challenges, it also suggests potential areas where the state can pursue decarbonisation in energy-intensive industry and points the way to an active role of the green state in governing industrial decarbonisation and greening industry.     

Renewable energy consumption and its environmental impacts: A meta-regression analysis

This study involves a meta-analytical review of several articles, using the closest assumptions for the independent variable (renewable energy consumption), to determine the relationship with its environmental impacts. Furthermore, Sustainable Development Goal (SDG) in 2015 pays attention to related problems in both developing and developed countries. The effects of carbon emissions, natural resources, renewable energy consumption, and non-renewable energy on the environment are also reviewed. Following the separation of studies, the closest assumption was observed for the independent variable (energy source applications) of renewable energy. The meta-analysis was obtained using OpenMEE and JASP, and the results show the observed outcome, which was expressed in percentage. Based on the analysis, the Renewable Energy model has a value of 0.15, with the largest forest plots of 0.73, 0.69, and 0.80, recorded for studies 13, 19, and 23, respectively, while the least forest plots were recorded for studies 6, 11, 12, 15, 20, 22, 24, 25, 26, and 28. Therefore, renewable energy consumption, specifically in the mining industry, has the capacity to influence global warming. The respective industry has a unique influence on the processes that require renewable energy, for instance, the coal mining industry produces a smaller forest plot value, compared to oil and gas, or other mineral industries.     

Addressing challenges for future strategic‐level emergency management: reframing,networking, and capacity‐building

The mounting frequency and intensity of natural hazards, alongside growing interdependencies between social‐technical and ecological systems, are placing increased pressure on emergency management. This is particularly true at the strategic level of emergency management, which involves planning for and managing non‐routine, high‐consequence events. Drawing on the literature, a survey, and interviews and workshops with Australia's senior emergency managers, this paper presents an analysis of five core challenges that these pressures are creating for strategic‐level emergency management. It argues that emphasising ‘emergency management’ as a primary adaptation strategy is a retrograde step that ignores the importance of addressing socio‐political drivers of vulnerabilities. Three key suggestions are presented that could assist the country's strategic‐level emergency management in tackling these challenges: (i) reframe emergency management as a component of disaster risk reduction rather than them being one and the same; (ii) adopt a network governance approach; and (iii) further develop the capacities of strategic‐level emergency managers.