Understanding Open Access Publishing

Who owns scientific knowledge? It’s not researchers or universities, but a handful of obscure multinationals such as Elsevier, Springer, Wiley, and Taylor & Francis. Here's how it works. All scientific studies must be published in a peer-reviewed journal. Basically, researchers write articles, which are reviewed free of charge by other researchers, and edited – again, free of charge – by other researchers. It sounds like a kind of Wikipedia of science. Yes, it could be. But over the last few decades, multinationals have taken control of most academic journals. They continue to mobilise the voluntary work of researchers but they now resell articles them afterwars. Yes, researchers have to pay to have access to their own articles. Universities either pay subscription fees to access each journals (a few thousand euros per year per journal) or pay several thousand euros per article to have it published in open-access. In 2020, these fees amounted to 87.5 million euros for French institutions, according to Alternatives Economiques. On the corporate side, the profits are colossal: global revenues reaching 7.5 billion euros for the top six publishers, with margins as high as 40%. This is not surprising, since these companies do not pay the researchers who write, proofread, and edit during their university-paid hours. Given that these companies are paid in proportion to the number of articles they publish, it is in their interests to encourage publication and create more and more journals. As researchers, we need to be able to read and publish. These companies know this and do not hesitate to inflate prices. Open access publication fees tripled between 2013 and 2020. It's the perfect trap. With career prospects linked to the number of publications, publishers are taking advantage of the ‘publish or perish’ culture. What should we do? Individually, we could refuse to write, review, and edit for journals owned by for-profit businesses and favour journals with genuine free access. Collectively, we could take back control of journals. With fellow researchers, we have created the Degrowth Journal, a not-for-profit, cooperatively-run publication. Each university has the power to help their researchers create new journals while changing the criteria for evaluating researchers. Most fundamentally: we could regulate the publication market. Controlling prices, banning lucrative intellectual property, taxing publishers' excess profits so that all of them are reinvested in research. Universities, researchers and public authorities must send out a strong message: science is not for sale.  

Three more of the UK’s universities have just walked away from the Elsevier deal. (And honestly, I think more institutions will follow) We’ve normalised an unsustainable system where: - Taxpayers fund the research - Academics write the papers - Peers review them for free - Editors manage journals for free - Then universities pay AGAIN so staff can read the work And if we want to make our research open access so that the community doesn't have to pay to read it, we’re hit with £2,000–£4,000+ APCs per article That isn’t an “open access model”. It's a "pay-to-play model". The JISC national deal with the big 5 publishers was supposed to “solve” this and offer more affordable open-access publishing and reading for universities across the UK. Over the past few years, we spent £112m on these deals. Let this number sink in. I wonder, why won't we redirect this budget into shared and open infrastructure, building for example on Octopus[ac], that will support: - diamond open access - community-run outlets - pre-prints + repositories used as default Thoughts? #science #scientist #research #researcher #phd #postdoc #postdoctoral #professor #publishing #openaccess

Happy to share our recent publication in Current Research in Environmental Sustainability "What works, where and how? A systematic literature review of climate change adaptation measures in India". In this first-of-its-kind study, we conducted a systematic review of over 2,100 peer-reviewed articles (2017–2023) and found only 28 studies that clearly focused on climate change adaptation (CCA) measures in India using IPCC definitions of incremental and transformative adaptation. What we found: • Adaptation research is heavily skewed towards agriculture sector with a technocratic approach. • Most literature emphasizes incremental adaptation in agriculture (e.g., crop diversification, altered sowing cycles), with limited insights into transformative adaptation. • There’s a geographical gap, vulnerable regions like Northeast India are underrepresented, despite being on the frontlines of climate risk. • Gender, urban resilience, and soft adaptation measures (like education and capacity building) are majorly underrepresented. • A lack of clarity persists on how adaptation types are conceptualized in literature. Our review highlights the urgent need for more inclusive, transformative, and context-specific adaptation research to support climate-resilient development in India. Transformative adaptation is necessary as it reimagines and restructures systems to address the root causes of vulnerability, leading to long-term resilience and sustainability unlike incremental adaptation that focuses on small-scale adjustments within existing systems. It is an open access publication, we hope you will find it interesting. Thanks to my co authors Sumit Vij Surbhi Vyas Visakha G !

💡 Has science been helpful in providing measurement tools, especially indicators and metrics, to assess urban climate adaptation? Not yet. 🚀 While in Oslo for the Lead Authors Meeting of the IPCC Special Report on Climate Change and Cities, I’m pleased to share our latest article, now published in npj Urban Sustainability https://lnkd.in/eG2WT9J4 🪅 “Conventional approaches to indicators and metrics undermine urban climate adaptation” systematically examines how current measurement practices fall short of capturing real progress on adaptation in cities worldwide. Through a review of nearly 140 studies and more than 900 indicators and metrics, we uncover a highly fragmented measurement landscape that often fails to meet the needs of adaptation decision-making. Key findings include: 🧱 The dominance of input- and output-focused metrics that track effort and immediate results rather than long-term impact. 🏚️ A strong bias toward city-scale indicators, with far less attention to neighbourhood and household scales. 📜 Limited integration of governance, social, and economic dimensions in measurement frameworks. 🧠 A lack of theoretical grounding and practical guidance amid a sea of highly technical, uncontextualised proposals. 🫵 Insufficient attention to units of measurement, intended users, and real-world applications. This research is essential reading for scientist, practitioners, policymakers, and climate (adaptation) professionals seeking more meaningful urban adaptation, and more meaningful ways to measure it, for learning, accountability, and impact. Let's discuss. 💡 Indicators matter. In every field. But it’s not only about the indicator itself, it’s about the ecosystem of actors, applications, and interpretations around it. Global efforts such as the Global Goal on Adaptation (GGA) can help clarify measurement needs, but urban adaptation challenges are complex, cross-sectoral, and deeply interconnected. Much more work is needed to support practitioners, policymakers, and researchers in applying and learning from ongoing urban adaptations. 👉 https://lnkd.in/eG2WT9J4 #openaccess 🙏 This work has been a long time in the making, from early ideas, through a lengthy review process, to finally seeing it out. Huge thanks to all the co-authors (Andressa V. Mansur, Samraj Sahay, Ph.D, Laura Helmke-Long, Massimiliano Granceri Bradaschia, Ane Villaverde García, Leire Garmendia Arrieta, Prince Dacosta Aboagye, PhD, PISEP, Patricia Mwangi (PhD, MISK), William Lewis, Obed Asamoah, Patricia Mwangi (PhD, MISK), borja izaola, Dr Ellie Murtagh and Ira Feldman ) for their dedication, patience, and collaboration, and to International Platform on Adaptation Metrics for planting the seed that made this work possible. IMAGINE adaptation European Research Council (ERC) BC3 - Basque Centre for Climate Change 💭 Dr. Diana Reckien Dr Stacy-ann Robinson A/Prof Johanna Nalau Emilie Beauchamp Sean Goodwin

💡 I’m excited to share a new (open access!) study I’ve led with colleagues from Bahamas, Brazil, Ghana, Mozambique, and Sweden that takes a deep dive into a topic that’s often overlooked in discussions about climate mobility — immobility. As climate risks and impacts intensify, much of the attention goes to those who move such as climate migrants and displaced populations. But the majority of people around the world will not move. Some will choose to stay; others will be unable to leave due to financial, social, or cultural reasons. Understanding what it means to remain in place is critical for developing just and effective adaptation strategies. In this review, we critically assess the growing literature on immobility and draw from research across Africa, South America, Europe, and Small Islands to examine how staying put is experienced differently across contexts. We highlight the urgent need for more research on: ✅ Governance of immobility ✅ Connections between immobility, justice, and loss and damage ✅ The feasibility of immobility as an adaptive response Our goal is to shift the conversation from movement as the dominant narrative to a fuller understanding of what it means to stay in the face of climate change. 📄 Read the open access paper here: https://lnkd.in/eXbwWrPP Special thanks to my brilliant coauthors: Arunima Sircar Mumuni Abu Emily Boyd Lorraine Howe Patricia Pinho Murray Scown Carlos Shenga #ClimateChange #Adaptation #Immobility #LossAndDamage #ClimateJustice #Resilience Climate Analytics University of The Bahamas University of Ghana Lund University And thank you to Annual Reviews for making all papers open access!

📣 𝐇𝐨𝐰 𝐢𝐬 𝐭𝐡𝐞 𝐞𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞 𝐨𝐟 𝐜𝐥𝐢𝐦𝐚𝐭𝐞 𝐡𝐚𝐳𝐚𝐫𝐝𝐬 𝐥𝐢𝐧𝐤𝐞𝐝 𝐭𝐨 𝐜𝐥𝐢𝐦𝐚𝐭𝐞 𝐫𝐢𝐬𝐤 𝐩𝐞𝐫𝐜𝐞𝐩𝐭𝐢𝐨𝐧𝐬 𝐰𝐨𝐫𝐥𝐝𝐰𝐢𝐝𝐞? 🔥🌎 👉 Find out in my open access article published today in 𝘌𝘯𝘷𝘪𝘳𝘰𝘯𝘮𝘦𝘯𝘵𝘢𝘭 𝘙𝘦𝘴𝘦𝘢𝘳𝘤𝘩 𝘓𝘦𝘵𝘵𝘦𝘳𝘴: https://lnkd.in/daqEKJAM 🔧 𝐖𝐡𝐚𝐭’𝐬 𝐢𝐧 𝐭𝐡𝐞 𝐬𝐭𝐮𝐝𝐲? I analysed nationally representative survey data from 142 countries (N = 128,093) collected as part of World Risk Poll. The dataset includes information on whether (a) respondents experienced a climate-related hazard in the last five years, whether (b) they see climate change as a threat to their country in the next 20 years, and (c) a multidimensional resilience index combining individual, household, community, and societal resilience factors. 💡 𝐖𝐡𝐚𝐭 𝐝𝐢𝐝 𝐈 𝐟𝐢𝐧𝐝? 1️⃣ People who have experienced a climate-related hazard are more likely to consider climate change a 𝘷𝘦𝘳𝘺 𝘴𝘦𝘳𝘪𝘰𝘶𝘴 𝘵𝘩𝘳𝘦𝘢𝘵 compared to those who didn't within the same country. These effects are consistent across eleven hazard types and, for heatwaves, comparable in magnitude to the effect of having a university education. 2️⃣ At the same time, it is not the case that countries with widespread exposure to climate-related hazards show higher overall levels of climate risk perception. The data set allowed me to disentangle country-level patterns from the strong individual-effects described in 1️⃣ — in contrast to another recent large-scale study that did not measure individual-level exposure (but measured subjective attribution): https://lnkd.in/dk4rGVEt 3️⃣ Resilience does not clearly amplify or dampen the link between experience and perception. For some hazards, there seems to be a positive trend, for others a negative one. 4️⃣ There is marked variation between countries, and this appears to differ across hazards. For example, hurricanes, mudslides, and wildfires show similar effects across countries, while the effects of earthquakes, sandstorms, and droughts vary strongly across countries. 📄 The paper discusses these results, limitations, and avenues for future research: https://lnkd.in/daqEKJAM 🔥🌎 𝐖𝐡𝐚𝐭 𝐝𝐨𝐞𝐬 𝐭𝐡𝐢𝐬 𝐦𝐞𝐚𝐧 𝐟𝐨𝐫 𝐜𝐥𝐢𝐦𝐚𝐭𝐞 𝐚𝐜𝐭𝐢𝐨𝐧? Billions of people are already living with the impacts of climate change. As these experiences accumulate, we may see rising demand for climate action. But without political leadership and media that connect the dots, those experiences alone will not drive the transformation we need.

Flood science has historically been trapped between two extremes: hydrodynamic models that are highly accurate but computationally expensive, or global models that are too coarse (>1 km) to capture critical local vulnerabilities. Bridging this divide requires a fundamental shift from physics-based deduction to data-driven induction, a challenge that has defined my research over the last four years. This week, I am very happy to share that I have formalized this solution by submitting my Ph.D. thesis at Hong Kong Baptist University: "Towards GeoAI-based Data-driven Flood Management Solutions: A Synergistic Machine Learning and Earth Observation Framework" As illustrated, the thesis establishes a scalable GeoAI framework built on three synergistic pillars: 1. High-Dimensional Earth Observation (The Data) Leveraging multi-temporal global data streams (Landsat, Sentinel) to transition the field from data scarcity to data abundance. 2. Planetary-Scale Geo-Computation (The Platform) Utilizing cloud clusters (Google Earth Engine) and HPC (Shaheen-III) to democratize processing power, enabling the analysis of petabyte-scale geospatial data without traditional hardware constraints. 3. Machine Learning Analytics (The Engine) We systematically benchmarked 14 ML architectures to resolve the "accuracy-efficiency" trade-off, establishing a robust modeling engine. This framework was first operationalized across Pakistan's diverse landscapes to reveal that 95 million people reside in high-risk zones, before being scaled globally to produce the first harmonized 30 m flood susceptibility baseline. The Output: Global Flood Susceptibility Map (GFSM v1) By applying a climate modeling scheme (across 192 climate zones), we produced the first globally harmonized, 30 m resolution flood susceptibility baseline derived entirely from open-access data. This research addresses the "data equity deficit" in the Global South, where 89% of flood-exposed populations reside, often without high-resolution risk data. Next Steps: I will be releasing the open-source code, the GFSM v1 dataset, and the GEE web applications in the coming weeks. If you are interested in the work, feel free to drop a message to dicsuss further possibilities! For more info, feel free to check my updated portfolio: www.waleedgeo.com #geoai #earthengine #floodrisk #remotesensing #hkbu #datascience #gfsm #flood

Slightly late but here: Excited that this paper that examines the impact and cost-effectiveness of 40 commonly used interventions in #foodsecurity #nutrition and #climate #resilience is finally out. We did this paper jointly with the @Innovation Commission for Climate Change and I led the team from International Fund for Agricultural Development (IFAD), while also being an advisor overall. The nice thing about the paper is that for the first time (I think) there's an analyses of available causal evidence to understand and measure impact as well as cost-effectiveness in the food, climate resilience space. We reviewed more than 600 papers to understand and measure these. The analysis includes studies with experimental designs–such as randomized control trials–or high-quality quasi-experimental designs, as well as meta-analyses. To be included, studies had to measure primary outcomes associated with food security (yield, profit, income, consumption, etc.), nutrition (BMI, prevalence of anemia, etc.), and climate (reforestation, resilience to shock, etc.). We also distinguished between 'Great Evidence', Good evidence and make operational recommendations that can be used by funders to design high impact programmes. Here's the paper https://lnkd.in/eE2_3iVD and this is the ''money slide'' where the axes refer to the consistency and quantity of evidence. Cash and in-kind transfers and graduation programmes are great bets.... University of Chicago, Tilman Brück, Kyle Murphy, Jess Rudder, Maximo Torero, Karen Macours, Paul Winters, Joshua W. Deutschmann Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH, Federal Ministry for Economic Cooperation and Development (BMZ), Tisorn Songsermsawas, Lenyara Fundukova and many others.

Climate Data Analysis Toolkit: 6 Free Books That Will Transform Your Research After reviewing hundreds of resources, here are the 6 free, academically rigorous books that transformed my approach to climate data analysis. These are textbooks used at NASA, NOAA, MIT, and Cambridge. 1. "Climate Time Series Analysis: Classical Statistical and Bootstrap Methods." 👤 Manfred Mudelsee 📚 Springer (Open Access) 🔗 https://lnkd.in/dQCn-DdC The bible for climate statisticians. Covers persistence, trends, extremes, & spectral analysis with rigorous mathematical foundations. 2. "Statistics and Data Visualization in Climate Science with R and Python" 👤 Samuel S.P. Shen & Gerald R. North 📚 Cambridge University Press (Free codes available) 🔗 https://lnkd.in/dRAn2SmB The complete modern toolkit. Unlike books that teach statistics OR programming, this integrates both with real climate datasets. Download all Python and R codes free. 3. R Programming for Climate Data Analysis and Visualization 👤 Samuel S.P. Shen 📚 San Diego State University (Course manual) 🔗 https://lnkd.in/dDqPtrQy The practical entry point. Developed for NOAA's National Center for Environmental Information. Takes you from R basics to analyzing global temperature anomalies in 4 days. Perfect for students and professionals transitioning to open-source tools. 4. Statistical Methods for Climate Scientists 👤 Tapio Schneider & others 📚 Cambridge University Press 🔗 https://lnkd.in/daeV7g33 Requires no prior statistics background. Covers hypothesis testing, PCA, CCA, data assimilation, and extreme value analysis with climate-specific examples. 5. IPCC Guidelines on the Use of Scenario Data for Climate Impact Assessment 👤 IPCC Task Group on Data and Scenario Support 📚 IPCC (Official) 🔗 https://lnkd.in/dRzz7zCk Essential for anyone working with CMIP6 scenarios, downscaling methods, or climate impact assessments. Explains how to interpret GCM outputs without misleading decision-makers. 6. Climate Analysis: Atmospheric and Oceanographic Data 👤 Chester F. Ropelewski & Phillip A. Arkin 📚 Cambridge University Press (Front matter available) 🔗 https://lnkd.in/d4zixmZW #ClimateScience #DataAnalysis #RStats #Python #ClimateData #Statistics #OpenScience #FreeEducation #RemoteSensing #Hydrology #DataVisualization #TimeSeriesAnalysis #ClimateModeling #IPCC #NOAA #NASA #CambridgeUniversityPress #DataScience #MachineLearning #ClimateChange #EnvironmentalScience #EarthObservation #OpenAccess #AcademicResources #ResearchMethods #WaterResources #Cryosphere #DataAssimilation #ClimateScenarios #CMIP6 #BigData #GeospatialAnalysis #ClimateAdaptation #KnowledgeSharing #ClimateAction #SDG13 #OpenData

The Congo Basin and the Amazon together form the living green heart of our planet. Yet the Congo Basin remains far less studied, far less resourced and far less understood. Today, there are just over 100 publishing environmental scientists across Congo Basin countries, compared to more than 6,000 working in the Amazon. We undertook the work of the Science Panel for the Congo Basin: to bring together the scientific knowledge necessary to inform global climate policy and strengthen regional scientific capacity, to identify key knowledge gaps and to call for increased funding to train a generation of scientists. Last year at COP30 in Belém, we launched the Executive Summary of our report, Resilience and Sustainability in the Congo Basin: Retracing the Past, Looking to the Future. The full report is now being released as an open-access digital volume published by Springer, with chapters becoming available as they are finalised. This 40-chapter, 800-page work represents one of the most comprehensive scientific assessments ever undertaken on the Congo Basin. During the coming weeks, in my capacity as Special Envoy of the Science Panel for the Congo Basin and one of the editors-in-chief of the report, I will share some of these chapters with you as they become public, along with some thoughts from me on each of them, explaining and why the findings matter. I hope that will be of some interest to you. Today, to kick things off, here is the Executive Summary – which makes clear exactly why these rainforests, which for many years were my and my family’s home, matter. It can be found here: https://lnkd.in/e46FY36f It has truly been a privilege to serve as an editor-in-chief on this project, alongside Bila-Isia Inogwabini, Bonaventure Sonké and Lydie Stella Koutika, working closely with section editors Jean-Jacques Braun, Raphael Tshimanga, Kate Abernethy, Averti Suspense IFO and Denis Jean Sonwa, and with the support of the UN Sustainable Development Solutions Network, Springer Nature and our partners and sponsors. A central objective of this effort was to ensure the report would be fully open access. By doing so, we aim to strengthen scientific capacity across the region and ensure that researchers, students and institutions in Congo Basin countries have unrestricted access to the knowledge needed to understand and protect these globally critical forests. It is our hope that this work will help bring greater global attention, scientific investment and policy focus to the Congo Basin in the years ahead. I look forward to your thoughts on what we publish. Executive Summary: https://lnkd.in/eYwTDPNK Full volume (in progress): https://lnkd.in/exCxG-_Y