PLOS sustainability and transformation最新文献

{"title":"Science journalism and a multi-directional science-policy-society dialogue are needed to foster public awareness for biodiversity and its conservation","authors":"Jonas Geschke, Matthias C. Rillig, Katrin Böhning-Gaese, Thomas Potthast, Adina Arth, Lynn V. Dicks, Fritz Habekuss, Daniela Kleinschmit, Harald Lesch, Eva M. Spehn, Silvio Wenzel, Markus Fischer, Alexandra-Maria Klein","doi":"10.1371/journal.pstr.0000083","DOIUrl":"https://doi.org/10.1371/journal.pstr.0000083","url":null,"abstract":"Biodiversity is the manifestation of life on our planet and provides manifold benefits for humans. Yet we destroy ecosystems and drive species to extinction. We submit that anthropogenic biodiversity loss does not yet receive sufficient public attention, although biodiversity conservation and its sustainable use are key to mitigate global crises. Effective communication of biodiversity-related knowledge with diverse audiences is therefore crucial and should contribute to ensuring that evidence guides environmental decision-making. In this context, it is essential to stimulate multi-directional dialogues between science, policy, and society. Here, we suggest Dos and Don’ts that can guide science communication for scientists working in biodiversity research and beyond. Moreover, we emphasize the role of science journalism and other institutions specialized in science communication in critically mediating the complexity of scientific knowledge.","PeriodicalId":476828,"journal":{"name":"PLOS sustainability and transformation","volume":"14 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135217954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An evidence-based approach to national Sustainable Development Goal assessment: The case of Ireland","authors":"Enda Murphy, Patrick Paul Walsh, Ethan Murphy","doi":"10.1371/journal.pstr.0000082","DOIUrl":"https://doi.org/10.1371/journal.pstr.0000082","url":null,"abstract":"With less than seven years remaining before the 2030 target date of the United Nations Sustainable Development Goals (SDGs), Ireland is currently unable to adequately assess national SDG performance. This paper presents an index that has been created to combat this critical research gap. In this respect, an index has been developed for each of the unique SDG indicators (n = 159) identified during the early stages of the indicator selection process where national performance is assessed relative to the best and worst performers in the European Union (EU). Ireland’s performance in individual indicators is then aggregated revealing the country’s performance in several critical dimensions of the SDGs, including society, economy, environment, as well as means-of-implementation (MoI), linkage indicators, and the SDGs as a whole. Further, annual time series data has been collected, allowing for the assessment of the country’s relative performance in 140 SDG indicators from 2015-to-2021. Its extensive indicator framework makes this index the most accurate and comprehensive assessment of Ireland’s SDG performance, to date. Similarly, as illustrated throughout this paper, our unique peer-based approach, and the positive peer-learning environment that it engenders, hold the potential to catalyse the development of efficient and effective national SDG policy. As such, the results from this index should be used to inform future national SDG monitoring, reporting, and policy initiatives, including future voluntary national reviews.","PeriodicalId":476828,"journal":{"name":"PLOS sustainability and transformation","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136078894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Low-carbon lifestyle revolution: China’s recent progress toward a personal carbon market","authors":"Wensha Xu, Kaiwen Zhou, Sifan Hu, Yang Yang, Pinghan Liang, Rong Pan, Yan Sun, Tien Ming Lee","doi":"10.1371/journal.pstr.0000079","DOIUrl":"https://doi.org/10.1371/journal.pstr.0000079","url":null,"abstract":"Meeting climate change targets requires inclusive carbon policies to encourage mass public participation. As a bottom-up strategy allows participation from all walks of society, personal carbon market may promote low-carbon behavior and further encourage technological innovation. We analyze the advantages of Personal Carbon Trading (PCT), examples of its application in other countries, and its limitations. To promote a low carbon emissions lifestyle, China has proposed and rapidly developed Inclusive carbon credits (ICC), which is a voluntary PCT scheme. We compare the government-led and enterprise-led ICC platforms with relevant examples in China and highlighted the need for academic-industry-government partnerships. Furthermore, we identify the barriers, opportunities, and the path forward with integrating ICC into the carbon market regarding technology and public participation. We hope that the understanding of ICC and China’s recent exploration of the personal carbon market could serve as an example to revolutionize the low-carbon lifestyle worldwide.","PeriodicalId":476828,"journal":{"name":"PLOS sustainability and transformation","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135591075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using life cycle assessments to guide reduction in the carbon footprint of single-use lab consumables","authors":"Isabella Ragazzi, Martin Farley, Kate Jeffery, Isabela Butnar","doi":"10.1371/journal.pstr.0000080","DOIUrl":"https://doi.org/10.1371/journal.pstr.0000080","url":null,"abstract":"Scientific research pushes forward the boundaries of human knowledge, but often at a sizable environmental cost. The reliance of researchers on single-use plastics and disposable consumables has come under increased scrutiny as decarbonisation and environmental sustainability have become a growing priority. However, there has been very little exploration of the contribution of laboratory consumables to ‘greenhouse gas’ (GHG) carbon emissions. Carbon footprint exercises, if capturing consumables at all, typically rely on analyses of inventory spend which broadly aggregate plastic and chemical products, providing inaccurate data and thus limited insight as to how changes to procurement can reduce emissions. This paper documents the first effort to quantify the carbon footprint of common, single-use lab consumables through emission factors derived from life cycle assessments (LCAs). A literature review of LCAs was conducted to develop emission factors for lab consumables, considering the emission hotspots along each product’s life cycle to identify where emission reduction policies can be most effective. Results can be used as inputs for lab practitioners seeking to understand and mitigate their carbon footprint.","PeriodicalId":476828,"journal":{"name":"PLOS sustainability and transformation","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135195347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Do clinical practice guidelines follow sustainable healthcare principles? A review of respiratory guidance","authors":"Naba Khan, Sarah C. Walpole, Olga M. Rostkowska, James N. Smith, Fiona A. Miller","doi":"10.1371/journal.pstr.0000078","DOIUrl":"https://doi.org/10.1371/journal.pstr.0000078","url":null,"abstract":"Respiratory care is an important site for climate action, given that common treatments for conditions such as asthma and COPD produce significant greenhouse gas emissions, even as respiratory health is negatively impacted by climate change. Clinical guidelines provide key information for healthcare professionals and can promote approaches to healthcare that can mitigate negative environmental impacts, and optimise patient treatment, care delivery, and equitable outcomes, and bring awareness and legitimacy to sustainable healthcare practices.\u0000\u0000\u0000\u0000Twenty national and international clinical respiratory guidelines were purposively selected and screened for inclusion of four principles of sustainable clinical practice: prevention, patient empowerment and self-care, lean service delivery, and low carbon alternatives. A screening framework specific to respiratory care implications was developed and used to review each guideline for mention of relevant topics, recommendations, and explicit links to sustainability in relation to each principle.\u0000\u0000\u0000\u0000Sustainable clinical care principles were evident in most guidelines reviewed, environmental sustainability was mentioned infrequently. Many guidelines emphasised prevention (more secondary than primary) and support for patient preference and streamlining care, yet there was rarely mention of how these recommendations could contribute to lowering the environmental impacts of health systems. Low carbon alternatives were mentioned in only three guidelines.\u0000\u0000\u0000\u0000While many clinical respiratory guidelines make recommendations in accordance with the principles of prevention, patient empowerment and self-care, and lean service delivery, reducing the carbon footprint of healthcare was rarely mentioned in the guidelines. Including explicit attention to the environmental impact of clinical care in guidance could support efforts to reduce the wider harms of healthcare, meanwhile, noting the clinical benefits of sustainable approaches could promote the uptake of recommendations.","PeriodicalId":476828,"journal":{"name":"PLOS sustainability and transformation","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136059575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Accurate detection and identification of insects from camera trap images with deep learning","authors":"Kim Bjerge, Jamie Alison, Mads Dyrmann, Carsten Eie Frigaard, Hjalte M. R. Mann, Toke Thomas Høye","doi":"10.1371/journal.pstr.0000051","DOIUrl":"https://doi.org/10.1371/journal.pstr.0000051","url":null,"abstract":"Reported insect declines have dramatically increased the global demand for standardized insect monitoring data. Image-based monitoring can generate such data cost-efficiently and non-invasively. However, extracting ecological data from images is more challenging for insects than for vertebrates because of their small size and great diversity. Deep learning facilitates fast and accurate insect detection and identification, but the lack of training data for coveted deep learning models is a major obstacle for their application. We present a large annotated image dataset of functionally important insect taxa. The primary dataset consists of 29,960 annotated insects representing nine taxa including bees, hoverflies, butterflies and beetles across more than two million images recorded with ten time-lapse cameras mounted over flowers during the summer of 2019. The insect image dataset was extracted using an iterative approach: First, a preliminary detection model identified candidate insects. Second, candidate insects were manually screened by users of an online citizen science platform. Finally, all annotations were quality checked by experts. We used the dataset to train and compare the performance of selected You Only Look Once (YOLO) deep learning algorithms. We show that these models detect and classify small insects in complex scenes with unprecedented accuracy. The best performing YOLOv5 model consistently identifies nine dominant insect species that play important roles in pollination and pest control across Europe. The model reached an average precision of 92.7% and recall of 93.8% in detection and classification across species. Importantly, when presented with uncommon or unclear insects not seen during training, our model detects 80% of individuals and usually interprets them as closely related species. This is a useful property to (1) detect rare insects for which training data are absent, and (2) generate new training data to correctly identify those insects in future. Our camera system, dataset and deep learning framework show promising results in non-destructive monitoring of insects. Furthermore, resulting data are useful to quantify phenology, abundance, and foraging behaviour of flower-visiting insects. Above all, this dataset represents a critical first benchmark for future development and evaluation of deep learning models for insect detection and identification.","PeriodicalId":476828,"journal":{"name":"PLOS sustainability and transformation","volume":"173 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135553695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}