Climate warming enables easier access and operation in the Arctic, fostering industrial and urban development. However, there is no comprehensive pan-Arctic overview of industrial and urban development, which is crucial for the planning of sustainable development of the region. In this study, we utilize satellite-derived artificial light at night (ALAN) data to quantify the hotspots and the development of light-emitting human activity across the Arctic from 1992 to 2013. We find that out of 16.4 million km ² analyzed a total area of 839,710 km ² (5.14%) is lit by human activity with an annual increase of 4.8%. The European Arctic and the oil and gas extraction regions in Russia and Alaska are hotspots of ALAN with up to a third of the land area lit, while the Canadian Arctic remains dark to a large extent. On average, only 15% of lit area in the Arctic contains human settlement, indicating that artificial light is largely attributable to industrial human activity. With this study, we provide a standardized approach to spatially assess human industrial activity across the Arctic, independent from economic data. Our results provide a crucial baseline for sustainable development and conservation planning across the highly vulnerable Arctic region.

The rate and extent of global biodiversity change is surpassing our ability to measure, monitor and forecast trends. We propose an interconnected worldwide system of observation networks — a global biodiversity observing system (GBiOS) — to coordinate monitoring worldwide and inform action to reach international biodiversity targets.

Motivation The goal of the Russian Arctic Vegetation Archive (AVA‐RU) is to unite and harmonize data of plot‐based plant species and their abundance, vegetation structure and environmental variables from the Russian Arctic. This database can be used to assess the status of the Russian Arctic vegetation and as a baseline to document biodiversity changes in the future. The archive can be used for scientific studies as well as to inform nature protection and restoration efforts. Main types of variables contained The archive contains 2873 open‐access geobotanical plots. The data include the full species. Most plots include information on the horizontal (cover per species and morphological group) and vertical (average height per morphological group) structure of vegetation, site and soil descriptions and data quality estimations. In addition to the open‐access data, the AVA‐RU website contains 1912 restricted‐access plots. Spatial location and grain The plots of 1–100 m ² size were sampled in Arctic Russia and Scandinavia. Plots in Russia covered areas from the West to the East, including the European Russian Arctic (Kola Peninsula, Nenets Autonomous district), Western Siberia (Northern Urals, Yamal, Taza and Gydan peninsulas), Central Siberia (Taymyr peninsula, Bolshevik island), Eastern Siberia (Indigirka basin) and the Far East (Wrangel island). About 72% of the samples are georeferenced. Time period and grain The data were collected once at each location between 1927 and 2022. Major taxa and level of measurement Plots include observations of >1770 vascular plant and cryptogam species and subspecies. Software format CSV files (1 file with species list and abundance, 1 file with environmental variables and vegetation structure) are stored at the AVA‐RU website ( https://avarus.space/ ), and are continuously updated with new datasets. The open‐access data are available on Dryad and all the datasets have a backup on the server of the University of Zurich. The data processing R script is available on Dryad.

Arctic vegetation is crucial for fauna and the livelihoods of Northern peoples and is tightly linked to climate, permafrost soils, and water. Yet, a comprehensive understanding of climate change effects on Arctic vegetation is lacking. Protected areas cannot halt climate change but could reduce future pressure from additional drivers, like land use change and local industrial pollution. Therefore, it is crucial to understand the contribution of protected areas in safeguarding threatened Arctic vegetation types. We compare the present baseline with 2050 predictions of circumpolar Arctic vegetation type distributions and demonstrate an overrepresentation of dominant vegetation types and an underrepresentation of declining vegetation types within protected areas. Our study predicts five of eight assessed tundra vegetation types to be threatened by 2050, following International Union for Conservation of Nature criteria. Further, we mapped potential climate change refugia, areas with the highest potential for safeguarding threatened vegetation types. This study provides an essential first step assessing vegetation type vulnerability based on predictions covering 42 percent of Arctic landscapes. The co-development of new protective measures by policymakers and Indigenous peoples at a pan-Arctic scale requires more robust and spatially complete vegetation predictions, as increasing pressures from resource exploration and infrastructure development threaten the sustainable development of the rapidly thawing and greening Arctic.

Lagoonal mangrove ecosystems are vital for carbon capture, protection of coastlines and conservation of biodiversity. Yet, they are decreasing globally at a higher rate than other mangrove ecosystems. In addition to human drivers, local environmental factors influence the functioning of lagoonal mangrove ecosystems, but their importance and combined effects are relatively unknown. Here, we investigate the drivers of mangrove functioning, approximated by mangrove aboveground biomass (AGB), in a protected lagoonal mangrove ecosystem on Aldabra Atoll, Seychelles. Based on a survey of the mangrove forest structure in 54 plots, we estimated that the mean mangrove forest AGB was 82 ± 13 Mg ha⁻¹. The total AGB of the mangrove area (1720 ha) was nearly 140,600 Mg, equivalent to about 66,100 Mg of carbon stored in the standing biomass on Aldabra. To assess the direct and indirect effects of soil nutrient content, water level variation and soil salinity on mangrove AGB, we used a structural equation model. Our structural equation model explained 82 % of the variation in mangrove AGB. The soil nutrient content (concentration of essential macronutrients in the soil column) had the greatest influence on mangrove AGB variation. Additionally, high variation in water level (change in water depth covering a location) increased mangrove AGB by increasing nutrient content levels. Our results highlight the important contribution of Aldabra's lagoonal ecosystem to Seychelles' carbon storage and the role of hydroperiod as a regulator controlling the availability of crucial nutrients needed for the functioning of mangroves within lagoonal systems. We suggest conservation managers worldwide focus on a holistic ecosystem-level perspective for successful mangrove conservation, including the protection and maintenance of nutrient cycling and hydrological processes.