THE EVOLUTION OF ENVIRONMENTAL EDUCATION AS A DRIVER FOR IMPROVING THE TECHNOLOGIES OF MANAGING THE USE OF NATURAL RESOURCES

Purpose of the study: The aim of the article is to develop proposals for improving environmental education management technology. Main Findings: Analysis of the approaches used in the theory and practice of environmental education management has shown that it is most appropriate to form the development, consistency, and self-organization principles, as well as data of modern natural science and individual areas of ecology, namely, general ecology, human ecology, global ecology, and social ecology. It is revealed that additional important sources of environmental education should include geological ecology, engineering ecology, agroecology, and some other environmental disciplines. Applications of this study: It is proved that the introduction of special courses at various levels of education, which integratively reflect the content of new environmental disciplines, becomes a mandatory requirement. In this context, distinguishing the key concepts, which reflect the invariant phenomena and processes in different areas of ecology, in environmental education is quite essential. This allows justifying the internal unity of environmental disciplines and determining the optimal form of presentation of educational information. Novelty/Originality of this study: It is revealed that environmental education should be aimed at the development of environmental consciousness and education of the individual with an environmental outlook. Accordingly, environmental education should be continuous, systematic, and interdisciplinary. It should be supplemented by various sources of up-to-date information

Improving Inference of Gaussian Mixtures Using Auxiliary Variables

Expanding a lower-dimensional problem to a higher-dimensional space and then projecting back is often beneficial. This article rigorously investigates this perspective in the context of finite mixture models, namely how to improve inference for mixture models by using auxiliary variables. Despite the large literature in mixture models and several empirical examples, there is no previous work that gives general theoretical justification for including auxiliary variables in mixture models, even for special cases. We provide a theoretical basis for comparing inference for mixture multivariate models with the corresponding inference for marginal univariate mixture models. Analytical results for several special cases are established. We show that the probability of correctly allocating mixture memberships and the information number for the means of the primary outcome in a bivariate model with two Gaussian mixtures are generally larger than those in each univariate model. Simulations under a range of scenarios, including misspecified models, are conducted to examine the improvement. The method is illustrated by two real applications in ecology and causal inference

Text mining e network science per analizzare la complessità della lettura. Principi, metodi, esperienze di applicazione.

This paper proposes some reflections concerning the practice of reading, its conceptual structure and its transformations, the blurred profile of the information ecology in which it is inserted. At the same time illustrates some outcomes of a research project conducted with tools of text mining and network science on the social reading platform aNobii. The paper presents these main topics: a) general overview of reading's context; b) short discussion reading as a complex system; c) presentation of some central concepts of network science and of its applications; d) introduction to text mining with some results of analysis of aNobii's reviews; e) conclusions and prospectives

Mapping hypotheses and evidence in urban ecology: A perspective on knowledge synthesis with a focus on biotic homogenization

A city is a highly complex, anthropogenically constructed system – an urban ecosystem. Researchers that study this system come from very different academic fields, bringing with them their own methods and research questions. From the perspective of (biological) urban ecology, this thesis first takes a step back, and focuses on knowledge production in general academia (chapter 1). The concept knowledge in the dark, or short: dark knowledge, describes the gap between potential and actual knowledge. In chapter 1, several potential reasons for dark knowledge in general are discussed. Focusing on the acasemic system, these are for example loss of academic freedom, research and publication biases, a lack of reproducibility, financial interests and barriers in understanding each other among disciplines and different areas of society. We also discuss potential solutions. One important aspect is rethinking and improving research synthesis and finding ways to bridge language and information barriers both within and beyond the academic system. Chapters 2, 3 and 4 then take up a main theme from chapter 1: research synthesis, and within the setting of urban ecology show how different approaches to synthesis can help bridge communication between researchers within and beyond one discipline (biological urban ecology), identify biases and knowledge gaps, and visualize and summarize available knowledge. The chapters proceed from a very broad perspective on urban ecology to the topic of urban biotic homogenization, and then a very specific aspect within urban biodiversity research: the influence of mowing of urban lawns on arthropods, which is one specific cause of biotic homogenization in cities. In Chapter 2, together with a group of urban ecologists predominantly based in Berlin, I collected 62 research hypotheses from urban ecology. In a second step, my co-authors and I present a first map of these hypotheses in a structured, bipartite network. As urban ecology is a multi-disciplinary field that is of high interest to urban planners and administrations, knowledge transfer between different stakeholders is particularly important. The network we propose consists of four distinct clusters, into which the hypotheses we previously identified can be grouped: (i) Urban species traits & evolution, (ii) Urban communities, (iii) Urban habitats and (iv) Urban ecosystems. This work is intended to grow, and as an invitation to researchers, practitioners and others interested in urban ecology to contribute to collecting additional hypotheses, jointly fill the network (or rather the underlying Wikidata project) with empirical data. Chapter 2 is thus intended as a first step towards an open and community curated knowledge base for urban ecology. Chapter 3 focuses on one of the hypotheses from our network: urban biotic homogenization (UBH). Urbanization, which is restructuring ecosystems at an unprecedented pace, is hypothesized to cause the homogenization of urban species communities. This idea has also been applied to other biodiversity levels like genetic diversity, behavioural diversity, functional diversity, and the like. There is, however, good reason to also formulate a hypothesis predicting the opposite effect: biotic diversification, that predicts species communities (and other levels of biodiversity) to become biologically more diverse because of ongoing urbanization. In chapter 3, I disentangle the different connotations, scales and “auxiliary hypotheses”, i.e., hypotheses that often unspokenly accompany a tested research hypothesis, which have been applied in the research literature on urban biotic homogenization and diversification. Applying the hierarchy-of-hypotheses approach, I systematically map and structure the comprehensive body of literature on UBH, comprising 225 individual tests of the hypothesis from 145 publications. Interestingly, UBH is generally used with two very different connotations in relation to scale (i.e., homogenization across cities versus within cities). There are several strong research biases, for example in relation to taxonomic focus, scale, and study systems. We visualize support and biases in an evidence gap map and provide a bibliographic network of the field. Chapter 4 is a meta-analysis of the impact of reduced mowing frequencies on the abundance and diversity of arthropods on urban grassland sites. It is based on 46 datasets on arthropod abundance and 23 datasets on taxa richness, respectively. As in chapter 3, we report severe geographical biases. While we find a medium positive effect (effect size: g = 0.54) of reduced mowing on arthropod abundance, the effect that reduced mowing has on urban arthropod taxa richness is larger (g = 1.25). Some functional groups benefit more from reduced mowing, especially winged insects, and perceived non-pest species. In the final, General Discussion, I try to connect several points that can be traced to all four chapters and discuss them in the context of urban ecology. These are: knowledge gaps and biases, with a brief discussion of how the concept of dark knowledge can (and should) be relevant to researchers from urban ecology, and research and knowledge synthesis. I finish my thesis by reflecting on how these are important in the context of urban ecological knowledge in the Anthropocene, and how they should be extended in the face of planetary crisis

Evolution in agricultural systems: Moving toward the understanding of complexity

Agricultural fields are typically simplified ecosystems compared to natural sites, a characteristic that has long-attracted researchers in Ecology and Evolution. In recent years, there has been a rising interest in understanding how agricultural systems are shaped by evolution in the context of changing agricultural practices by integrating biological information of crop systems. This editorial introduces the special issue “Evolution in agricultural systems,” incorporating the articles published within this issue into three general areas of research: phenotypic and genetic responses to the environment, biotic interactions and the role of microbes. Together, this body of work unveils unforeseen complexity at all levels, from microbes to trophic chains. Understanding such complexity is critical not only to better understand natural systems, but also if we wish to improve the sustainability of the food system.info:eu-repo/semantics/publishedVersio

Traitement des incertitudes des avis à dire d'expert pour l'évaluation de la sûreté des digues

3rd European Conference on Flood Risk Management FLOODrisk 2016, Lyon, FRA, 17-/10/2016 - 21/10/2016International audienceIn France, levees remain most of the time badly maintained; these long linear structures show signs of weaknesses on numerous occasions. Only incomplete information is usually available. The general lack of data describing the behaviour of the infrastructure during unwanted events led to estimate their safety mainly from expert judgement. Thus the ability of the expert to predict the level of functioning of an infrastructure for a type of hazard and its intensity is crucial. An error of judgement can have very serious consequences and the production of reliable information requires the ability of the expert to report accurately the uncertainties in its estimations, as well as associated confidence. In order to meet this need, our research within Incertu project (French Ministry of Ecology funding) aims to produce relevant scientific approaches and tools for the collection and processing reliable experts'statements or combined with a confidence level in the context of uncertain information and input data

Inoculating an Infodemic: An Ecological Approach to Understanding Engagement With COVID-19 Online Information

As the global COVID-19 pandemic has been concurrently labelled an “infodemic,” researchers have sought to improve how the general public engages with information that is relevant, timely, and accurate. In this study, we provide an overview of the reasons why people engage and disengage with COVID-19 information. We use context-rich semi-structured interviews which invited participants to discuss online COVID-19-related content they encountered. This qualitative approach allows us to uncover subtle but important details of influences that drive online engagement. Participants both engaged and disengaged with content for individual and social reasons, with seven themes emerging connected to their engagement including actions in response to information, reasoning for engagement, content, motivating concerns, frequency of engagement with information, site of exposure, and given reason for not engaging. Many of these themes intersected and informed each other. Our findings suggest that researchers and public health communicators should approach engagement as an ecology of intersecting influences, both human and algorithmic, which change over time. This information could be potentially helpful to public health communicators who are trying to engage the public with the best information to keep them safe during the pandemic

Modelling seed germination in forest tree species through survival analysis. The Pinus pinea L. case study

The direct application of existing models for seed germination may often be inadequate in the context of ecology and forestry germination experiments. This is because basic model assumptions are violated and variables available to forest managers are rarely used. In this paper, we present a method which addresses the aforementioned shortcomings. The approach is illustrated through a case study of Pinus pinea L. Our findings will also shed light on the role of germination in the general failure of natural regeneration in managed forests of this species. The presented technique consists of a mixed regression model based on survival analysis. Climate and stand covariates were tested. Data for fitting the model were gathered from a 5-year germination experiment in a mature, managed P. pinea stand in the Northern Plateau of Spain in which two different stand densities can be found. The model predictions proved to be unbiased and highly accurate when compared with the training data. Germination in P. pinea was controlled through thermal variables at stand level. At microsite level, low densities negatively affected the probability of germination. A time-lag in the response was also detected. Overall, the proposed technique provides a reliable alternative to germination modelling in ecology/forestry studies by using accessible/ suitable variables. The P. pinea case study highlights the importance of producing unbiased predictions. In this species, the occurrence and timing of germination suggest a very different regeneration strategy from that understood by forest managers until now, which may explain the high failure rate of natural regeneration in managed stands. In addition, these findings provide valuable information for the management of P. pinea under climate-change conditions