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...     

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.     

Promoting e-mobility in India: challenges,framework, and future roadmap

The purpose of the research is to identify the critical challenges that are impeding the adoption of e-mobility in India. It also aims to give a roadmap how to address these challenges while taking into considerations concerns of all the relevant stakeholders. Based on an in-depth literature review, an exploratory research design is employed to delve deep into various aspects of e-mobility. This is followed by a three-phase Delphi technique to identify and rate the e-mobility challenges in the Indian context. The study successfully identifies four different categories of challenges and proposes integrative framework for e-mobility. Further, the research goes on to lay out the future roadmap for mass adoption of electric vehicles (EVs) in India. The research is novel in terms of presenting a holistic viewpoint on e-mobility in India. Its originality lies in identifying the major inhibitors obstructing EVs adoption in India and then suggesting the roadmap how to overcome these impediments for mass adoption of e-mobility.     

A fragment constant QSAR model for evaluating the EC50 values of organic chemicals to Daphnia magna.

The quantitative relationship between the median effective concentration (EC50) of organic chemicals to Daphnia magna and the number of molecular fragments was investigated based on experimental EC50 values for 217 chemicals derived from the literature. A fragment constant model was developed based on a multivariate linear regression between the number of fragments and the logarithmically transformed reciprocal values of EC50. Functional correction factors were introduced into the model. The model was verified using an independent set of randomly selected data. The mean residual of the final model was 0.4 log-units. The robustness of the model was discussed based on the results of three jackknife tests.     

Using fuzzy set theory to address the uncertainty of susceptibility to drought

This paper presents the technical aspects of a new methodology for assessing the susceptibility of society to drought. The methodology consists of a combination of inference modelling and fuzzy logic applications. Four steps are followed: (1) model input variables are selected—these variables reflect the main factors influencing susceptibility in a social group, population or region, (2) fuzzification—the uncertainties of the input variables are made explicit by representing them as ‘fuzzy membership functions’, (3) inference modelling—the input variables are used to construct a model made up of linguistic rules, and (4) defuzzification—results from the model in linguistic form are translated into numerical form, also through the use of fuzzy membership functions. The disadvantages and advantages of this methodology became apparent when it was applied to the assessment of susceptibility from three disciplinary perspectives: Disadvantages include the difficulty in validating results and the subjectivity involved with specifying fuzzy membership functions and the rules of the inference model. Advantages of the methodology are its transparency, because all model assumptions have to be made explicit in the form of inference rules; its flexibility, in that informal and expert knowledge can be incorporated through ‘fuzzy membership functions’ and through the rules in the inference model; and its versatility, since numerical data can be converted to linguistic statements and vice versa through the procedures of ‘fuzzification’ and ‘defuzzification’.