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We have just unveiled our latest data and analytics tool, the Online Reporting for Biodiversity (ORB) tool: https://orb.abmi.ca/areas The ORB tool, officially launched today, provides a user-friendly platform for generating biodiversity and land cover reports for different areas in the province, including natural regions, watershed boundaries, and municipalities or counties. These reports include interactive graphs, maps, and tables, covering human footprint, wetland area, biodiversity intactness, as well as other general information. "We're excited to introduce the ORB tool, which is in direct response to the needs of our data users," said Katherine Maxcy, Reporting and Analytics Lead. "With this tool, we aim to make land cover and biodiversity data more accessible for the wide range of partners and collaborators involved in land use planning and stewardship activities in Alberta." Key highlights of the ORB tool include its intuitive interface, tailored reports based on user-selected areas of interest, and its ability to present data in an easy-to-digest format. Additionally, the tool will be regularly updated with new features and data to ensure its relevance and usefulness over time. Users are encouraged to explore the ORB tool and share it with their networks. Watch a video tour demonstrating how to use the tool on our YouTube Channel: https://lnkd.in/d5uypB2k Financial support for the development of the ORB tool generously provided by the Government of Alberta.

Soundscapes and deep learning enable tracking biodiversity recovery in tropical forests Discover how soundscapes and deep learning are revolutionizing the way we track biodiversity recovery in tropical forests! Researchers have shown that the composition of vocalizing vertebrates, captured through innovative bioacoustic and metabarcoding techniques, accurately reflects ecosystem restoration in Ecuador's biodiversity hotspots. Automated monitoring tools provide robust, reproducible data, marking a significant advancement in our ability to gauge the success of forest recovery efforts. Read the full study for an in-depth look at these groundbreaking findings: https://lnkd.in/et2hbNpc

Exciting research like this inspires our work at Mefvo Research!! This study on Monitoring biodiversity from space using machine learning aligns with our vision of harnessing technology for ecosystem monitoring. As we gear up to advance our Tech-Driven Biodiversity Conservation project, we’re exploring how machine learning and scalable tech solutions can transform environmental monitoring—making it accessible and impactful for communities. Stay tuned as we continue building toward our goal of real-time, data-driven biodiversity insights! 🔗 Check out this fascinating study by Nature Scientific Reports: https://lnkd.in/eY33R7Ah #Biodiversity #MachineLearning #ConservationTech #EnvironmentalMonitoring #MefvoResearch

🌿 How do individual preferences influence the quality of data in ecological citizen science? A new study published in PloS One explores the dynamics of collective intelligence within the context of ecological citizen science, focusing on the global platform iNaturalist. The research, conducted by Ofer Arazy, Keren Kaplan Mintz, Dan Malkinson, and Yiftach Nagar, investigates how local community preferences can introduce biases into collectively generated biodiversity data. Key findings: 🔍 Observers' decisions on what, when, and where to monitor wildlife are influenced by factors like recordability, community value, personal preferences, and convenience. 🌍 These individual preferences can lead to spatial, temporal, and taxonomic biases, challenging the reliability of data for mapping species distribution. 📊 The study raises concerns about the use of unstructured citizen science data for determining species' spatiotemporal distributions, emphasizing the need for new methodologies to account for these biases. This research sheds light on the complexities of harnessing collective intelligence for ecological monitoring and offers critical insights for improving data quality in citizen science projects. It underscores the importance of addressing observer-based biases to ensure more accurate and actionable ecological data. Read the full publication here: https://lnkd.in/dcc2rRya #CitizenScience #CollectiveIntelligence #iNaturalist #DataQuality #BiodiversityMonitoring

A paper, published in the open access journal Sustainability MDPI, examines applicable examples where artificial intelligence (AI) offers opportunities for tackling complex ecological challenges. The research, mentioned in the World Economic Forum, discusses the utilisation of technology in supporting nature conservation efforts. Today, AI is emerging as a powerful tool for communities involved in conservation efforts, with applications ranging from wildlife monitoring to DNA collection. Read more about this research: https://brnw.ch/21wHXPf view the news story: https://brnw.ch/21wHXPe #SustainableDevelopmentGoals #OpenScience #OpenAccess

We need biodiversity data, but where do we need it most? Citizen science plays a crucial role in conservation planning and policy-making by generating vast amounts of biodiversity data. However, unstructured sampling—where volunteers choose what and where to record -often leads to spatial unevenness. While statistical techniques can address these biases, our new research led by Thomas Mondain-Monval provides evidence that using existing data to target future data collection can make a real impact. This is termed ‘adaptive sampling’. What we did : - A Simulation Study 💻: We simulated ecological assemblages across Great Britain using butterfly data and tested various sampling methods. What we found 🔎:  - Adaptive vs. Non-Adaptive Sampling: Adaptive sampling methods, particularly model-based ones, significantly improved species distribution models compared to non-adaptive methods. - Minimal Effort, Maximum Impact 📈: Even a small shift (1% uptake) in recorder behaviour towards adaptive sampling greatly enhanced model performance. - Strategic Recording 🎯: Directing volunteers to high-need areas based on model outputs can vastly improve data quality and model accuracy. This research underscores the power of strategic volunteer engagement in boosting the effectiveness of biodiversity monitoring. By integrating adaptive sampling into citizen science, we can improve our biodiversity with minimal changes in recorder behaviour. Check out the (open access) paper here! https://lnkd.in/gUi82zGE This work was part of the DECIDE project, a UK Centre for Ecology & Hydrology (UKCEH) led interdisciplinary project funded through the NERC: Natural Environment Research Council Constructing a Digital Environment programme.

British researchers' modeling unravels the enigma of the Amazon's biodiversity: The Amazon rainforest, with its incredible variety of plant and animal species, has always fascinated scientists. A new study led by the UK Centre for Ecology & Hydrology has used supercomputer modeling to shed light on the rainforest's evolution during the last Ice Age, from approximately 2.6 million to 11,700 years ago. The findings challenge old assumptions and highlight the Amazon's vulnerability to human-induced climate change and land use disruptions. This study, a collaboration between UKCEH, the Ontario Forest Research Institute, Kiel University in Germany, the Met Office in the UK, INPA in Brazil, and the Field Museum of Natural History in Chicago, integrates advanced climate and vegetation modeling techniques. Dr. Douglas Kelley, the lead author of the study, emphasizes the role of climate fluctuations in shaping the Amazon's past and emphasizes the urgency of addressing contemporary climate challenges. The study reveals a complex landscape of interconnected woodlands and savannas during the last Ice Age, refuting the idea of isolated "forest islands." Dr. Hiromitsu Sato of the Ontario Forest Research Institute highlights the study's pioneering nature in demystifying the Amazon's biodiversity origins and the potential for using integrated modeling methods to bridge gaps in biodiversity data. The researchers aim to further trace the divergence of Amazonian species over millennia, shedding light on the evolutionary paths of iconic creatures. Their relentless pursuit of knowledge offers hope for understanding the Amazon's heritage and protecting its unparalleled biodiversity for future generations.

Happy to share this article with you featuring our data services! "Taking ecological surveys and habitat monitoring into the age of big data and deep learning! Gentian uses high-resolution satellite imagery and AI analysis to scale and speed up land surveyance. Gentian's SaaS package enables urban planners, developers, and businesses to gather an ecological baseline for a particular location – something that is crucial to understanding biodiversity changes over time." - Habitat Maps and Urban Green Infrastructure Assessments. - Locate & Evaluate opportunity and risk for biodiversity - Pinpoint features and areas of special interest - Fast turnaround - Highly cost effective - Globally available across urban and rural landscapes - Annual update for monitoring and reporting https://lnkd.in/eZfWYhem #biodiversity #biodiversité #biodiversidad #bng #tnfd #csrd #habitat #AI

It's no secret that interconnected conservation lands create a feedback loop of benefits, enhancing biodiversity and ecosystem resilience. However, achieving accurate, large-scale identification of these opportunities can be challenging since keeping up the datasets requires extensive inter-organizational collaboration. Existing solutions like the National Conservation Easement Database (NCED) aim to aggregate conservation data, but maintaining national-level data with the local resolution required by many use cases is a complicated task. So, how did we tackle this for the Parcel-based Ecological Restoration Model (PERM)? Ultimately, we started with the NCED as a foundation and added a layer of invaluable "local knowledge." While our database begins with NCED, an inter-organizational user base can log in and edit a secondary "community" layer to update and expand on existing properties. These layers are then merged into one and treated the same. The result is an authoritative dataset enhanced with real-time, community-sourced information that fills the data gaps until NCED updates catch up. Though privacy concerns prevent us from making this dataset public, we’re open to sharing it with other nonprofit partners who could benefit from and contribute to its evolution. If you’re interested in collaborating on this effort, reach out—we’d love to connect. There's no cost...and everyone wins! #PERM #technology #conservation #ecology #gis #locationintelligence #geospatial #nced

🌊🌍 Harnessing Environmental DNA (EDNA) for Biodiversity Monitoring at Unki Mine 🌍🌊 In 2020, we embarked on an ambitious project to set up a Biodiversity Management Plan at Unki Mine. To ensure the effectiveness of this plan, we needed to accurately identify biodiversity indicators, and for this, we leveraged the innovative Environmental DNA (EDNA) water sampling technique. Here's how EDNA water sampling works:    Water Sampling: We collected water samples from various aquatic environments.    DNA Extraction: Extracted DNA from these samples, containing genetic material from organisms present.    Sequencing: Sequenced the DNA to identify the different species in the water.    Data Analysis: Analyzed the data to determine the presence, abundance, and diversity of species. This technique allowed us to monitor key biodiversity indicators such as species richness, composition, abundance, and community structure. The advantages of EDNA water sampling were instrumental to our success:    Non-invasive: No harm to organisms.    Cost-effective: Reduced sampling effort.    High sensitivity: Detection of rare or endangered species.    Real-time monitoring: Rapid assessment of biodiversity changes. My contributions to this project included:    Leading the water sampling efforts, ensuring comprehensive coverage of the aquatic environments.    Overseeing the DNA extraction and sequencing processes, maintaining high standards of accuracy and efficiency.    Conducting data analysis to provide detailed insights into the biodiversity of the ecosystems we studied.    Applying my expertise in environmental science to interpret the results and inform our Biodiversity Management Plan. The use of EDNA water sampling enabled us to effectively monitor aquatic ecosystems, detect invasive species, and track the impact of climate change on biodiversity. Our knowledge and application of this cutting-edge technique were crucial in the development and implementation of a robust Biodiversity Management Plan at Unki. This project not only highlighted the importance of innovative techniques in environmental conservation but also demonstrated the value of scientific knowledge in practical applications. 🌱🔬 #Biodiversity #EDNA #EnvironmentalScience #Sustainability #Innovation #Conservation #AquaticEcosystems #ClimateChange #UnkiMine #EnvironmentalManagement #Leadership #ScientificResearch