Drought weakens tree defenses, predisposing Norway spruce (Picea abies) to spruce bark beetle (Ips typographus) attack. The extreme 2018 summer drought in Sweden triggered an unprecedented bark beetle outbreak. Our objective was to quantify how weather, soil moisture, and tree provenance influence Norway spruce defense capacity to a necrotrophic beetle-associated pathogen. Trees at three sites in Sweden were inoculated with the phytopathogenic fungus Leptographium europhioides on four occasions during each of the 2019 and 2021 growing seasons. At each site, we inoculated spruce provenances of Swedish or East European origin, with early and late spring bud burst, respectively. Tree defense capacity, expressed as the extent of necrotic lesion formation following fungal inoculation, was used as a proxy for resistance to bark beetle attack. Spruce defense capacity (i.e. lesion size) differed with water availability (both precipitation and soil moisture conditions) but not with the timing of spring bud burst. There were within-season differences, with trees having less efficient defenses (producing larger lesions) in the early season (June). On intermediate soil moisture sites, lesions were larger in 2019 than in 2021. In both years, there was a significant negative correlation between lesion size and water availability in the autumn of the previous year. Spruce defense capacity varied with local environmental conditions but not with provenance phenology. Variations between study years reflected the sensitivity of spruce defenses to climatic variability and the partial recovery of tree resistance 3 years after the 2018 drought.
Water hyacinth is among the world’s most damaging aquatic invasive plants, forming dense mats that disrupt ecosystem functioning, fisheries, navigation, and livelihoods across tropical and subtropical freshwater systems. Its rapid spread is driven by clonal propagation, short life cycles, and prolific seed production, particularly under nutrient-enriched conditions. Although mechanical, chemical, and biological control methods are widely applied, their long-term effectiveness remains uncertain when underlying eutrophication persists. Here, we present a large-scale, one-time water hyacinth removal campaign in Lake Tana, Ethiopia’s largest lake and a UNESCO Biosphere Reserve, as a representative nutrient-rich tropical freshwater system. Using high-resolution satellite imagery, we quantified coverage one month before removal, one month after removal, and one year later. We integrated SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis with a socio-ecological system map to assess mitigation mechanisms and identify sustainable management pathways capable of providing long-term solutions to halt water hyacinth proliferation in freshwater bodies. The campaign removed over 75
The ISMC-GEWEX SoilWat 2025 Meeting What: The International Soil Modeling Consortium (ISMC)-Global Energy and Water Exchanges project (GEWEX) Soil and GEWEX Water Initiative (SoilWat) 2025 meeting brought together a diverse group of similar to 40 experts from the subsurface modeling community (broadly represented by members of the ISMC) and the climate modeling community (represented by those active in GEWEX). The main objective of the meeting was to identify the next frontiers and challenges relating to the modeling of soil and subsurface processes in weather and climate models. When: 14-16 July 2025 Where: University of Reading, Reading, United Kingdom, and online streaming (https://www.gewexevents.org/meetings/ismc-soilwat2025/)
Excessive tree mortality is a global concern and remains poorly understood as it is a complex phenomenon. We lack global and temporally continuous coverage on tree mortality data. Ground-based observations on tree mortality, e.g., derived from national inventories, are very sparse, and may not be standardized or spatially explicit. Earth observation data, combined with supervised machine learning, offer a promising approach to map overstory tree mortality in a consistent manner over space and time. However, global-scale machine learning requires broad training data covering a wide range of environmental settings and forest types. Low altitude observation platforms (e.g., drones or airplanes) provide a cost-effective source of training data by capturing high-resolution orthophotos of overstory tree mortality events at centimeter-scale resolution. Here, we introduce deadtrees.earth, an open-access platform hosting more than two thousand centimeter-resolution orthophotos, covering more than 1,000,000 ha, of which more than 58,000 ha are manually annotated with live/dead tree classifications. This community-sourced and rigorously curated dataset can serve as a comprehensive reference dataset to uncover tree mortality patterns from local to global scales using space-based Earth observation data and machine learning models. This will provide the basis to attribute tree mortality patterns to environmental changes or project tree mortality dynamics to the future. The open nature of deadtrees.earth, together with its curation of high-quality, spatially representative, and ecologically diverse data will continuously increase our capacity to uncover and understand tree mortality dynamics.
Climate change forces species to adapt rapidly to avoid extinction. To directly observe rapid adaptation and extinction, we conducted synchronized evolution experiments with Arabidopsis thaliana in 30 locations across Western Europe, the Mediterranean, the Levant, and North America. Whole-genome pooled sequencing of ~70,000 surviving plants revealed repeatable allele frequency shifts in similar climates but divergent shifts across contrasting ones, indicating evolutionary adaptation. We identified genetic variants linked to climate adaptation, including genes involved in processes ranging from thermal-stress sensing to spring-flowering timing. Evolutionary trends were often predictable, but variable, across environments. In warmer climates, evolutionary predictability correlated with population survival over 5 years, whereas erratic changes preceded extinction. These results show that rapid climate adaptation is possible, but understanding its limits will be crucial for biodiversity forecasting.
