Landslide probability mapping by considering fuzzy numerical risk factor (FNRF) and landscape change for road corridor of Uttarakhand,India

Landslide poses severe threats to the natural landscape of the Lesser Himalayas and the lives and economy of the communities residing in that mountainous topography. This study aims to investigate whether the landscape change has any impact on landslide occurrences in the Kalsi-Chakrata road corridor by detailed investigation through correlation of the landslide susceptibility zones and the landscape change, and finally to demarcate the hotspot villages where influence of landscape on landslide occurrence may be more in future. The rational of this work is to delineate the areas with higher landslide susceptibility using the ensemble model of GIS-based multi-criteria decision making through fuzzy landslide numerical risk factor model along the Kalsi-Chakrata road corridor of Uttarakhand where no previous detailed investigation was carried out applying any contemporary statistical techniques. The approach includes the correlation of the landslide conditioning factors in the study area with the changes in land use and land cover (LULC) over the past decade to understand whether frequent landslides have any link with the physical and hydro-meteorological or, infrastructure, and socioeconomic activities. It was performed through LULC change detection and landslide susceptibility mapping (LSM), and spatial overlay analysis to establish statistical correlation between the said parameters. The LULC change detection was performed using the object-oriented classification of satellite images acquired in 2010 and 2019. The inventory of the past landslides was formed by visual interpretation of high-resolution satellite images supported by an intensive field survey of each landslide area. To assess the landslide susceptibility zones for 2010 and 2019 scenarios, the geo-environmental or conditioning factors such as slope, rainfall, lithology, normalized differential vegetation index (NDVI), proximity to road and land use and land cover (LULC) were considered, and the fuzzy LNRF technique was applied. The results indicated that the LULC in the study area was primarily transformed from forest cover and sparse vegetation to open areas and arable land, which is increased by 6.7% in a decade. The increase in built-up areas and agricultural land by 2.3% indicates increasing human interference that is continuously transforming the natural landscape. The landslide susceptibility map of 2019 shows that about 25% of the total area falls under high and very high susceptibility classes. The result shows that 80% of the high landslide susceptible class is contained by LULC classes of open areas, scrubland, and sparse vegetation, which point out the profound impact of landscape change that aggravate landslide occurrence in that area. The result acclaims that specific LULC classes, such as open areas, barren-rocky lands, are more prone to landslides in this Lesser Himalayan road corridor, and the LULC-LSM correlation can be instrumental for landslide probability assessment concerning the changing landscape. The fuzzy LNRF model applied has 89.6% prediction accuracy at 95% confidence level which is highly satisfactory. The present study of the connection of LULC change with the landslide probability and identification of the most fragile landscape at the village level has been instrumental in delineation of landslide susceptible areas, and such studies may help the decision-makers adopt appropriate mitigation measures in those villages where the landscape changes have mainly resulted in increased landslide occurrences and formulate strategic plans to promote ecologically sustainable development of the mountainous communities in India's Lesser Himalayas.

     

Ellenberg Indicator Values (EIVs) in Different Plant Communities in Subalpine Grasslands of the Giresun Mountains (Turkey)

Russian Journal of Ecology - In this paper, Ellenberg’s indicator values were estimated in order to soil nitrogen (N), pH (R) and soil moisture (M) in different subalpine grassland...     

Preparation of Viscose Fibres Stripped of Reactive Dyes and Wrinkle-Free Crosslinked Cotton Textile Finish

The chemical recycling of cellulosic fibres may represent a next-generation fibre–fibre recycling system for cotton textiles, though remaining challenges include how to accommodate fibre blends, dyes, wrinkle-free finishes, and other impurities from finishing. These challenges may disrupt the regeneration process steps and reduce the fibre quality. This study examines the impact on regenerated viscose fibre properties of a novel alkaline/acid bleaching sequence to strip reactive dyes and dimethyloldihydroxyethyleneureas (DMDHEU) wrinkle-free finish from cotton textiles. Potentially, such a bleaching sequence could advantageously be integrated into the viscose process, reducing the costs and environmental impact of the product. The study investigates the spinning performance and mechanical properties (e.g., tenacity and elongation) of the regenerated viscose fibres. The alkaline/acid bleaching sequence was found to strip the reactive dye and DMDHEU wrinkle-free finish from the cotton fabric, so the resulting pulp could successfully be spun into viscose fibres, though the mechanical properties of these fibres were worse than those of commercial viscose fibres. This study finds that reactive dyes and DMDHEU wrinkle-free finish affect the viscose dope quality and the regeneration performance. The results might lead to progress in overcoming quality challenges in cellulosic chemical recycling.     

Electrodisinfection of real swine wastewater for water reuse

Environmental Chemistry Letters - Swine production generates large volumes of wastewater, rich in organic matter, nutrients and pathogens. Electrodisinfection is used to remove organic matter and...     

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.     

Conservation optimism and reckoning with the future

Article impact statement: The optimism permeating biological conservation should be recalibrated considering the future that present times portend.     

Overestimation of self-reported driving exposure: Results from the SHRP2 Naturalistic Driving Study

Objectives: The accuracy of self-reported driving exposure has questioned the validity of using self-reported mileage to inform research questions. Studies examining the accuracy of self-reported driving exposure compared to objective measures find low validity, with drivers overestimating and underestimating driving distance. The aims of the current study were to (1) examine the discrepancy between self-reported annual mileage and driving exposure the following year and (2) investigate whether these differences depended on age and annual mileage.

Methods: Two estimates of drivers’ self-reported annual mileage collected during vehicle installation (obtained via prestudy questionnaires) and approximated annual mileage driven (based upon Global Positioning System data) were acquired from 3,323 participants who participated in the Strategic Highway Research Program 2 (SHRP2) Naturalistic Driving Study.

Results: A Wilcoxon signed rank test showed that there was a significant difference between self-reported and annual driving exposure during participation in SHRP 2, with the majority of self-reported responses overestimating annual mileage the following year, irrespective of whether an ordinal or ratio variable was examined. Over 15% of participants provided self-reported responses with over 100% deviation, which were exclusive to participants underestimating annual mileage. Further, deviations in reporting differed between participants who had low, medium, and high exposure, as well as between participants in different age groups.

Conclusions: These findings indicate that although self-reported annual mileage is heavily relied on for research, such estimates of driving distance may be an overestimate of current or future mileage and can influence the validity of prior research that has utilized estimates of driving exposure.