A climate-change vulnerability and adaptation assessment for Brazil's protected areas

Brazil hosts the largest expanse of tropical ecosystems within protected areas (PAs), which shelter biodiversity and support traditional human populations. We assessed the vulnerability to climate change of 993 terrestrial and coastal-marine Brazilian PAs by combining indicators of climatic-change hazard with indicators of PA resilience (size, native vegetation cover, and probability of climate-driven vegetation transition). This combination of indicators allows the identification of broad climate-change adaptation pathways. Seventeen PAs (20,611 km²) were highly vulnerable and located mainly in the Atlantic Forest (7 PAs), Cerrado (6), and the Amazon (4). Two hundred fifty-eight PAs (756,569 km²), located primarily in Amazonia, had a medium vulnerability. In the Amazon and western Cerrado, the projected severe climatic change and probability of climate-driven vegetation transition drove vulnerability up, despite the generally good conservation status of PAs. Over 80% of PAs of high or moderate vulnerability are managed by indigenous populations. Hence, besides the potential risks to biodiversity, the traditional knowledge and livelihoods of the people inhabiting these PAs may be threatened. In at least 870 PAs, primarily in the Atlantic Forest and Amazon, adaptation could happen with little or no intervention due to low climate-change hazard, high resilience status, or both. At least 20 PAs in the Atlantic Forest, Cerrado, and Amazonia should be targeted for stronger interventions (e.g., improvement of ecological connectivity), given their low resilience status. Despite being a first attempt to link vulnerability and adaptation in Brazilian PAs, we suggest that some of the PAs identified as highly or moderately vulnerable should be prioritized for testing potential adaptation strategies in the near future.     

Mainstreaming human and large carnivore coexistence through institutional collaboration

Achieving coexistence between large carnivores and humans in human-dominated landscapes (HDLs) is a key challenge for societies globally. This challenge cannot be adequately met with the current sectoral approaches to HDL governance and an academic community largely dominated by disciplinary sectors. Academia (universities and other research institutions and organizations) should take a more active role in embracing societal challenges around conservation of large carnivores in HDLs by facilitating cross-sectoral cooperation to mainstream coexistence of humans and large carnivores. Drawing on lessons from populated regions of Europe, Asia, and South America with substantial densities of large carnivores, we suggest academia should better embrace the principles and methods of sustainability sciences and create institutional spaces for the implementation of transdisciplinary curricula and projects; reflect on research approaches (i.e., disciplinary, interdisciplinary, or transdisciplinary) they apply and how their outcomes could aid leveraging institutional transformations for mainstreaming; and engage with various institutions and stakeholder groups to create novel institutional structures that can respond to multiple challenges of HDL management and human–large carnivore coexistence. Success in mainstreaming this coexistence in HDL will rest on the ability to think and act cooperatively. Such a conservation achievement, if realized, stands to have far-reaching benefits for people and biodiversity.     

Emerging applications of green coconut: A promising lignocellulosic biomass

Waste accumulation is a grave concern and becoming a transboundary challenge for environment. During Covid-19 pandemic, diverse type of waste were collected due to different practices employed in order to fight back the transmission rate of the virus. Covid-19 was proved to be capricious catastrophe of this 20th century and even not completely eradicated from the world. The havoc created by this imperceptible quick witted, pleomorphic deadly virus can't be ignored. Though a number of vaccines have been developed by the scientists but there is a fear of getting this virus again in our life. Medical studies prove that immunity drinks will help to reduce its reoccurrences. Coconut water is widely used among all drinks available globally. Its massive consumption created an incalculable pile of green coconut shells around the different corners of the world. This practice generating enormous problem of space acquisition for the environment. Both the environment and public health will benefit from an evaluation of quantity of coconut waste that is being thrown and its potential to generate value added products. With this context, present article has been planned to study different aspects like, coconut waste generation, its biological properties and environmental hazards associated with its accumulation. Additionally, this review illustrates, green technologies for production of different value added products from coconut waste.     

Modeling of a sequencing batch reactor treating municipal wastewater using multi-layer perceptron and radial basis function artificial neural networks

A sequencing batch reactor was modeled using multi-layer perceptron and radial basis function artificial neural networks (MLPANN and RBFANN). Then, the effects of influent concentration (IC), filling time (FT), reaction time (RT), aeration intensity (AI), SRT and MLVSS concentration were examined on the effluent concentrations of TSS, TP, COD and NH₄⁺-N. The results showed that the optimal removal efficiencies would be obtained at FT of 1 h, RT of 6 h, aeration intensity of 0.88 m³/min and SRT of 30 days. In addition, COD and TSS removal efficiencies decreased and TP and NH₄⁺-N removal efficiencies did not change significantly with increases of influent concentration. The TSS, TP, COD and NH₄⁺-N removal efficiencies were 86%, 79%, 94% and 93%, respectively. The training procedures of all contaminants were highly collaborated for both RBFANN and MLPANN models. The results of training and testing data sets showed an almost perfect match between the experimental and the simulated effluent of TSS, TP, COD and NH₄⁺-N. The results indicated that with low experimental values of input data to train ANNs the MLPANN models compared to RBFANN models are more precise due to their higher coefficient of determination (R²) and lower root mean squared errors (RMSE) values.     

基于复杂系统建模的水管理政策研究进展

基于Agent的建模方法（ABSS）通过自下而上的方式，考察系统中主体的不同状态和行为特征、主体与环境的作用、主体之间的作用，来表征系统的宏观特征，是进行复杂社会环境系统分析和政策研究的重要手段，在水资源、水环境管理系统中得到了有效的应用。本文在大量文献调研的基础上，讨论了ABSS建模方法的基本原理、主要特征、系统构成、分类方法和开发工具等特征，总结了其供水系统发展、水资源分配和流域水资源管理、农业土地和水资源利用、居民用水行为、农业污染控制及人类活动的水环境影响等方面的应用，分析了其在研究内容、研究方法、研究结果等方面的发展趋势，讨论了利用该方法研究我国水资源管理和水污染控制政策的必要性和重要性。     

三峡库区水土流失特点及其环境危害防治措施探讨

水土流失是三峡库区主要环境问题之一,也是库区产生大量泥沙的根本因素,更是造成库区人民生活贫困的根源。本文就三峡库区水土流失的特点及其环境危害作了分析,提出了相应的防治措施,为水土流失防治工程提供科学依据。     

生态文明建设对环境法理论变革的影响

随着人类社会由工业文明向生态文明的转变，环境法理论也随之发生着变革。近年来。众多学者对环境法理论的变革问题进行了热烈的讨论。生态文明的法律观。承认自然界及其生物具有内在价值。主张人与自然的和谐发展。为生态文明建设提供了坚实的法学理论支持。     

工业区群环境影响评价初探

阐述了开展工业区群环境影响评价的意义,比较了单个工业园区和工业区群环评的异同,以广州番禺区工业区群环评项目为例,简述了该环评的主要内容和特点,并提出了建议。     

EFFECTS OF ADJACENT AGRICULTURAL ACTIVITIES AND WATERSHED CHARACTERISTICS ON STREAM MACROINVERTEBRATE COMMUNITIES1

Benthic macroinvertebrate communities in streams adjacent to cornfields, streams where cows had unrestricted access, and reference locations without agriculture were compared to examine the effects of local land use and land use/land cover in the watershed. At each local site, macroinvertebrates and a variety of habitat parameters were measured upstream, adjacent, downstream, and farther downstream of the local land use. A geographic information system (GIS) was used to calculate drainage basin area, land use/land cover percentages in each basin, and the distance from sample sites to the stream source. Three‐way analysis of covariance (ANCOVA) tests with date, site type, and sampling location as main effects were used to explore differences in macroinvertebrate metrics using median substrate size, percent hay/pasture area, and stream depth as covariates. The covariates significantly improved model fit and showed that multiple contributing factors influence community composition. Local impacts were greatest at sites where cows had access, probably because of sedimentation and embeddedness in the substrate. Differences between the upstream and the adjacent and downstream locations were not as great as expected, perhaps because upstream recolonization was reduced by agricultural impacts or because of differences in the intensity or proximity of agriculture to riparian areas in the watershed. The results underscore the importance of both local and watershed factors in controlling stream community composition.