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High Mountain Conservation in a Changing World

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Book Series: Advances in Global Change Research ISSN: 1574-0919 / 2215-1621 ISBN: 9783319559810 9783319559827 Year: Pages: 413 DOI: https://doi.org/10.1007/978-3-319-55982-7 Language: English
Publisher: Springer Nature
Subject: Environmental Sciences
Added to DOAB on : 2017-11-24 13:16:26
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This book aims to provide case studies and a general view of the main processes involved in the ecosystem shifts occurring in the high mountains, and to analyse the implications for nature conservation. Although case studies from the Pyrenees are preponderant, conclusions are aimed at any mountain range surrounded by highly populated lowland areas. The chapters give emphasis to approaches from environmental geography, functional ecology, biogeography, and paleoenvironmental reconstructions. The introductory and closing chapters summarize the main challenges that nature conservation may face in mountain areas under the environmental shifting conditions.This interdisciplinary book will appeal to researchers in mountain ecosystems, students and nature professionals.

Impacts, Monitoring and Management of Forest Pests and Diseases

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ISBN: 9783039281664 9783039281671 Year: Pages: 198 DOI: 10.3390/books978-3-03928-167-1 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Biology --- Ecology
Added to DOAB on : 2020-04-07 23:07:09
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Forest pests have diverse negative impacts on forestry economy, ecosystem services, biodiversity, and sustainable ecosystem management. The first step towards effectively managing forest pests would be to monitor their occurrence and assess their impact on forest ecosystems. The monitoring results can provide basic information for effective management strategies. The data from monitoring programs can result in the development of new methods for monitoring, assessing impact, and developing management techniques. This special issue aims to share information to assist in the effective management of forest pests, by understanding the responses of forest pests to natural and anthropogenic changes, and discussing new studies on the monitoring, assessment, and management of forest pests. The fourteen papers included in this issue focus on monitoring, assessing, and managing forest pests, including one editorial providing an overall idea of the monitoring, assessment and management of forest pests, two articles reviewing long-term changes in forest pests and forests, four papers focusing on the monitoring of forest pests, three papers on the assessment of forest pests, and four papers on the management of forest pests. These papers provide a better understanding of the structures and processes in forest ecosystems and fundamental information for the effective management of forest pests.

Overcoming Data Scarcity in Earth Science

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ISBN: 9783039282104 / 9783039282111 Year: Pages: 94 DOI: 10.3390/books978-3-03928-211-1 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering --- Environmental Engineering
Added to DOAB on : 2020-06-09 16:38:57
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heavily Environmental mathematical models represent one of the key aids for scientists to forecast, create, and evaluate complex scenarios. These models rely on the data collected by direct field observations. However, assembly of a functional and comprehensive dataset for any environmental variable is difficult, mainly because of i) the high cost of the monitoring campaigns and ii) the low reliability of measurements (e.g., due to occurrences of equipment malfunctions and/or issues related to equipment location). The lack of a sufficient amount of Earth science data may induce an inadequate representation of the response’s complexity in any environmental system to any type of input/change, both natural and human-induced. In such a case, before undertaking expensive studies to gather and analyze additional data, it is reasonable to first understand what enhancement in estimates of system performance would result if all the available data could be well exploited. Missing data imputation is an important task in cases where it is crucial to use all available data and not discard records with missing values. Different approaches are available to deal with missing data. Traditional statistical data completion methods are used in different domains to deal with single and multiple imputation problems. More recently, machine learning techniques, such as clustering and classification, have been proposed to complete missing data. This book showcases the body of knowledge that is aimed at improving the capacity to exploit the available data to better represent, understand, predict, and manage the behavior of environmental systems at all practical scales.

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