Assessing the vulnerability of rare plants using climate change velocity,habitat connectivity,and dispersal ability: a case study in Alberta,Canada

Climate change generally requires species to migrate northward or to higher elevation to maintain constant climate conditions, but migration requirement and migration capacity of individual species can vary greatly. Individual populations of species occupy different positions in the landscape that determine their required range shift to maintain similar climate, and likewise the migration capacity depends on habitat connectivity. Here, we demonstrate an approach to quantifying species vulnerabilities to climate change for 419 rare vascular plants in Alberta, Canada, based on a multivariate velocity of climate change metric, local habitat fragmentation, and migration capacity. Climate change velocities indicated that future migration requirements ranged from 1 to 5 km/year in topographically complex landscapes, such as the Alberta Foothills and Rocky Mountains. In contrast, migration requirements to maintain constant climate in relatively flat Boreal Plains, Parkland, and Grassland ranged from 4 to 8 km/year. Habitat fragmentation was also highest in these flat regions, particularly the Parkland Natural Region. Of the 419 rare vascular plants assessed, 36 were globally threatened (G1–G3 ranking). Three globally threatened species were ranked as extremely vulnerable and five species as highly vulnerable to the interactions among climate change velocity, habitat fragmentation, and migration capacity. Incorporating dispersal characteristics and habitat fragmentation with local patterns in climate change velocity improves the assessment of climate change threats to species and may be applied to guide monitoring efforts or conservation actions.     

Framing for resilience through social learning: impacts of environmental stewardship on youth in post-disturbance communities

Civic ecology practices, such as community gardening and citizen-led urban reforestation and wetland restoration, provide opportunities for social learning. Because social learning is an important component of community resilience, we suggest that civic ecology practices can be a strategy for responding to and mitigating environmental disturbances in an era threatened by climate change. Despite the links between civic ecology, social learning and community resilience, empirical research that systematically considers these connections is limited. This study addresses this gap by introducing ‘frames’ as an approach to considering social learning outcomes and process. More specifically, we provide a model for investigating the role civic ecology education programs play in shaping youths’ capacity to understand and respond to environmental disturbance. We used participant observation and cognitive mapping to assess social learning among three youth restoration programs working in the wake of Hurricane Sandy in New York, NY, and after the 2013 floods in Boulder, CO. In all three programs, youth demonstrated social learning and cognitive change by shifting their emphasis from the impacts of disturbance towards a solutions-based framing that focused on community, action, and mitigation. However, the depth of these changes was not uniform across all programs, suggesting that variations in program length, community context, social identity, and opportunities for self-defined action may shape overall impacts of programs and youth capacity for future action.     

Ecological literacy and beyond: Problem-based learning for future professionals

Ecological science contributes to solving a broad range of environmental problems. However, lack of ecological literacy in practice often limits application of this knowledge. In this paper, we highlight a critical but often overlooked demand on ecological literacy: to enable professionals of various careers to apply scientific knowledge when faced with environmental problems. Current university courses on ecology often fail to persuade students that ecological science provides important tools for environmental problem solving. We propose problem-based learning to improve the understanding of ecological science and its usefulness for real-world environmental issues that professionals in careers as diverse as engineering, public health, architecture, social sciences, or management will address. Courses should set clear learning objectives for cognitive skills they expect students to acquire. Thus, professionals in different fields will be enabled to improve environmental decision-making processes and to participate effectively in multidisciplinary work groups charged with tackling environmental issues.     

Twentieth century droughts and agriculture: Examples from impacts on soybean production in Kentucky,USA

Drought is a significant natural hazard that slowly evolves over time. Because of its character, drought is difficult to monitor and impacts are often poorly documented. Agriculture is one of the most sensitive sectors that are prone to drought. The objective of this research is to assess the impacts of drought on soybean production and revenue in Kentucky. Soybeans are one of Kentucky’s most important commodities. In this study, impacts of 1930–1931, 1940–1942, 1952–1955, 1987–1988, 1999–2000, and 2007 droughts were considered. It was found that over the recent years, up to 56 % of the revenue from soybeans was lost due to drought. During the first half of the twentieth century, revenue loss reached up to 77 %. This research is valuable to the general public as well as planners and policy makers. Proper documentation of impacts of past droughts will help identify drought vulnerabilities and results in better risk management and mitigation.     

生物滴滤塔净化挥发性有机废气动力学模型研究

通过对生物滴滤塔净化VOCs废气过程的分析,建立了动力学模型,简化处理后得出了基于生物降解为一级反应动力学和零级反应动力学的污染物浓度沿填料层高度变化的方程,并通过实验数据对方程进行了验证,结果表明基于生物降解一级反应动力学的方程能较好地与实验数据吻合,但常数ξα/Q却随入口浓度Cgi的增大而升高。最后,采用实验数据回归出了ξα/Q随Cg变化的曲线。     

Production of new concrete with leather tannery waste used as partial replacement of the natural sand

Journal of Material Cycles and Waste Management - Leather production is a technology that boosts the economy because of its versatility and durability. However, the wastes generated throughout the...     

Face mask and medical waste generation in the City of Baguio,Philippines: its current management and GHG footprint

Journal of Material Cycles and Waste Management - The daily use of facemask to prevent virus transmission increases the negative effect on the environment because of improper waste disposal. Due to...     

Zinc removal from synthetic waters using magnetite/graphene oxide composites

The removal of heavy metals from wastewater has become a global challenge, which demands the continuous study of efficient and low-cost treatment alternatives such as adsorption. In this research, the removal of zinc was evaluated using batch adsorption processes with nonconventional materials such as graphene oxide (GO), magnetite (MG), and their composites (GO:MG), formulated with three weight ratios (2:1, 1:1, and 1:2). Graphene was synthesized by the modified Marcano method, using pencil lead graphite as a precursor. MG and the composites were synthesized by chemical coprecipitation of ferrous sulfate and ferric chloride. The materials were characterized by Raman and Fourier transform infrared spectroscopies, scanning electron microscopy, X-ray diffraction, and the Brunauer–Emmett–Teller method to determine the functional groups, microstructural and morphological characteristics, and specific surface area. Batch adsorption tests were carried out to optimize the adsorbent dose and contact time with zinc solutions of 10 ppm. Zinc adsorption reached equilibrium at 2 h, with an optimal dose between 0.25 and 1.0 g/L. The maximum zinc removal efficiencies/adsorption capacities were 98.6%/165.6, 83.4%/47.6, 83.5%/21.9, 72.8%/19.9, and 82.2%/9.25 mg/g using GO, 2GO:1MG, 1GO:1MG, 1GO:2MG, and MG, respectively. Furthermore, the analysis of the isotherm and adsorption kinetics models determined that the adsorption processes using MG and the composites fit the Sips and pseudo-second-order models.