Finnish Environment Institute

• We applied the Life Framework in combination with PPGIS data on landscape values. • We identified three life frames: living with/in , living from , and living as nature. • Living in/with related to mapping intrinsic values in protected areas. • The spatial distribution of the life frames showed high variability and overlaps. • Using life frames with PPGIS revealed protected areas heterogeneous meanings.

Carbon payments have been proposed as a means of incentivizing forest management that jointly optimizes timber production and carbon storage benefits. We analyze the impacts of such payment schemes on forest biodiversity using a detailed model describing Finland’s forest resources, timber markets, and forest and energy industries. In the model, forest-owners’ heterogenous valuations of forest amenities affect their harvesting behavior and willingness to join a carbon payment scheme. We measure forest biodiversity using an ecosystem condition index based on habitat-specific structural components. Our results indicate that forest carbon payments have a small to moderate positive effect on forest ecosystem condition. The improvements in ecosystem condition result from longer rotations and greater volumes of broadleaved trees and dead wood. The effects are weakest on low productivity sites. Under a partial-coverage carbon payment scheme, impacts on ecosystem condition vary according to forest-owner type, but are positive in aggregate. According to our sensitivity analysis, the ecosystem condition-improving effect of carbon payments is stronger under high demand for harvested wood products. Our results suggest that forest carbon payments are likely to have biodiversity co-benefits in boreal conditions, but halting biodiversity loss will require additional biodiversity-targeted policies.

Abstract Rivers are increasingly fragmented and degraded, yet the European Union Nature Restoration Regulation calls for restoring at least 25,000 kilometres of free-flowing rivers by 2030. Translating this ambition into effective implementation remains challenging because restoration priorities differ across ecological, social, economic, and governance contexts. Here, we synthesize expert knowledge from 45 countries through a structured, multi-step prioritization process to identify research priorities for restoring free-flowing rivers in Europe. We identified 27 priorities and analysed how expert background and spatial context influenced their ranking. Restoration priorities differed systematically depending on whether experts emphasized ecological integrity, community engagement, economic considerations, or governance capacity, revealing clear patterns in how disciplinary and professional perspectives shape implementation pathways. This demonstrates that restoration strategies cannot be universal but must be adapted to local and regional political, institutional, and ecological conditions. Building on these findings, we propose a structured prioritisation framework that links barrier removal, connectivity restoration, governance mechanisms, and policy instruments to context-specific needs. Together, our results provide an empirically grounded and implementation-oriented roadmap to support European Union Member States in delivering ambitious river restoration targets in a context-sensitive and socially robust manner.

Digital geoscientific and geospatial datasets are rapidly growing in both number and size. These data present powerful new resources for understanding the evolution of the earth, but working with them requires computational skills are not part of typical geoscience curricula at universities. To leverage the power of these growing geoscientific and geospatial data, students need targeted educational resources that provide basic computational skills.The new textbook Introduction to Python for Geographic Data Analysis provides a framework for learning to work with (geospatial) datasets of varying size from loading the data to producing interactive visualizations of processed data. Part 1 of the book covers the basics of programming using the Python language, introducing both programming concepts and their Python syntax. It also covers the analysis of tabular data using the pandas Python library and the basics of data visualization. Part 2 introduces working with geospatial data, including fundamental geospatial concepts, working with vector and raster data, geospatial data visualization, and loading data from online sources. Part 3 includes several case studies that build on things presented in the first two parts to demonstrate what can be done with the readers’ new skills. Finally, the appendices provide information about best practices in programing, version control with git and GitHub, and other practical coding tips that promote open, reproducible science.The book materials are freely available online at https://pythongis.org, and we anticipate that hard copies of the book will be available later in 2026. We hope the book will appeal to a broad range of “geo” scientists, including teachers who provide courses on introductory programming or data analysis for geology and geography students, those interested in learning to interact with and batch process large datasets, and those interested in finding open-source alternatives to commercial GIS software packages.

We introduce a comprehensive observation and measurement framework designed to monitor ecosystem-level changes in a former peat extraction area using advanced instrumentation and digitalisation tools. This system aims to deliver accurate scientific data to support peatland management decisions and provide reference measurements for carbon emission calculations in the land use sector. In Finland, peat extraction for energy is being phased out as part of the green transition. Former extraction sites are commonly restored through rewetting, yet the short- and long-term impacts on water quality, greenhouse gas (GHG) emissions, and terrestrial and aquatic ecosystems remain poorly understood. To address this knowledge gap, we have established an intensive monitoring site at the Turvesuo–Miehonsuo peat extraction area in the Sanginjoki catchment near Oulu, Finland. Peat extraction ended in 2023, and rewetting is planned for 2025–2026. Our monitoring integrates online and cloud-based data transfer, model input, and visualisation from: 1) continuous high-frequency water quality and aquatic gas measurements, 2) eddy covariance and chamber-based GHG flux monitoring, 3) drone surveys for spatial variability assessment, 4) hydrological monitoring of surface and groundwater, 5) microbial and algal community analyses, and 6) detailed vascular plant and bryophyte inventories. This approach will provide a robust dataset for evaluating the environmental impacts of peatland rewetting using latest technological advances.

<strong class="journal-contentHeaderColor">Abstract.</strong> <span style="font-weight: 400;">The Southern Ocean plays a vital role in regulating Earth&rsquo;s climate by absorbing large quantities of carbon dioxide, but its productivity is strongly limited by the availability of iron needed for phytoplankton growth. Sea ice is a crucial seasonal reservoir of iron; however, the processes responsible for its enrichment remain poorly understood. Here we use a process-based model to show that frazil ice formation, a common feature of winter sea-ice growth in the Southern Ocean, can scavenge dissolved iron from seawater and concentrate it in newly formed ice. First-order estimates scaled to the Antarctic sea-ice zone suggest that frazil-origin ice could supply ~16&ndash;33% of the seasonal dissolved iron pool in the upper 10 m. Because this iron is released as a short-lived but intense pulse upon melt, frazil ice provides a pathway that can trigger phytoplankton blooms, linking polar sea-ice processes directly to global carbon cycling.</span>