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Biodiversity loss is now recognised as one of the major challenges for humankind to address over the next few decades. Unless major actions are taken, the sixth mass extinction will lead to catastrophic effects on the Earth's biosphere and human health and well-being. ELIXIR can help address the technical challenges of biodiversity science, through leveraging its suite of services and expertise to enable data management and analysis activities that enhance our understanding of life on Earth and facilitate biodiversity preservation and restoration. This white paper, prepared by the ELIXIR Biodiversity Community, summarises the current status and responses, and presents a set of plans, both technical and community-oriented, that should both enhance how ELIXIR Services are applied in the biodiversity field and how ELIXIR builds connections across the many other infrastructures active in this area. We discuss the areas of highest priority, how they can be implemented in cooperation with the ELIXIR Platforms, and their connections to existing ELIXIR Communities and international consortia. The article provides a preliminary blueprint for a Biodiversity Community in ELIXIR and is an appeal to identify and involve new stakeholders., Competing Interests: No competing interests were disclosed., (Copyright: © 2024 Waterhouse RM et al.)

The article contributes to the research discussion around the human-natural and social-ecological systems by identification of a comprehensive list of global trends related to integrated interaction between environmental systems and human development, including climate change, pollution, new quality of economic growth, and challenges for education and healthcare. The foresight study behind it encompasses a combination of quantitative (big data ) and qualitative (expert) methods. This approach allows for a systemic vision of structural shifts, assessing their probability and impact. The outcomes of the study include the list of global environmental and human development trends and factors classified by STEEPV categories, their effects that split into opportunities and threats, and an assessment of their inter-relation and mutual impact. Policy implications focus on possible areas of intervention for sustainable growth., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Anomaly detection is the process of identifying unexpected data samples in datasets. Automated anomaly detection is either performed using supervised machine learning models, which require a labelled dataset for their calibration, or unsupervised models, which do not require labels. While academic research has produced a vast array of tools and machine learning models for automated anomaly detection, the research community focused on environmental systems still lacks a comparative analysis that is simultaneously comprehensive, objective, and systematic. This knowledge gap is addressed for the first time in this study, where 15 different supervised and unsupervised anomaly detection models are evaluated on 5 different environmental datasets from engineered and natural aquatic systems. To this end, anomaly detection performance, labelling efforts, as well as the impact of model and algorithm tuning are taken into account. As a result, our analysis reveals the relative strengths and weaknesses of the different approaches in an objective manner without bias for any particular paradigm in machine learning. Most importantly, our results show that expert-based data annotation is extremely valuable for anomaly detection based on machine learning., (Copyright © 2021. Published by Elsevier Ltd.)

Metal oxide nanoparticles (MeO-NPs) are among the most consumed NPs and also have wide applications in various areas which increased their release into the environmental system. Aquatic (water and sediments) and terrestrial compartments are predicted to be the destination of the released MeO-NPs. In these compartments, the particles are subjected to various dynamic processes such as physical, chemical and biological processes, and undergo transformations which drive them away from their pristine state. These transformation pathways can have strong implications for the fate, transport, persistence, bioavailability and toxic-effects of the NPs. In this critical review, we provide the state-of-the-knowledge on the transformation processes and bioavailability of MeO-NPs in the environment, which is the topic of interest to researchers. We also recommend future research directions in the area which will support future risk assessments by enhancing our knowledge of the transformation and bioavailability of MeO-NPs., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

The complexities of the dynamic processes and their control associated with biological and ecological systems offer many challenges for the control engineer. Over the past decades the application of dynamic modelling and control has aided understanding of their complexities. At the same time using such complex systems as test-beds for new control methods has highlighted their limitations (e.g. in relation to system identification) and has thus acted as a catalyst for methodological advance. This paper continues the theme of exploring opportunities and achievements in applying modelling and control in the bio- and ecological domains., (Copyright © 2006 Elsevier Ltd. All rights reserved.)