Societal Impact Statement Understanding ecological interactions is increasingly important for biodiversity conservation. This study reveals a unique nursery pollination mutualism between Japanese endemic plants and sawflies. These partners exhibit tightly synchronized life cycles in riparian forests, making them sensitive to environmental changes. Importantly, our results reveal fine-scale geographic variation in floral morphology, proboscis length, and interaction strength, suggesting that local populations maintain distinct ecological and evolutionary patterns. These findings indicate that conservation strategies should consider not only species-level protection but also the maintenance of local interaction networks, ensuring the stability of these fragile, specialized ecological interactions and the diversity of both partners.
Societal Impact Statement Wheat is one of the world's most important staple crops, but its production is increasingly threatened by Fusarium head blight, a disease that reduces yield and grain quality. We mapped where wheat and its major disease‐causing fungi are likely to overlap now and under future climate change. Our results show that several major wheat‐producing regions may remain or become persistently vulnerable, including parts of North America, South America, Europe, East Asia, Australia, and New Zealand. These findings can help guide disease monitoring, resistant cultivar deployment and climate‐adaptive crop protection strategies to support global food security. Summary Fusarium head blight (FHB) is a major fungal disease threatening global wheat ( Triticum aestivum ) production and food security. Because climate change may alter the distributions of both wheat and its causal pathogens, this study aimed to assess current and future global FHB risk by identifying areas where host and pathogen suitability overlap. We modeled the potential distributions of wheat and two major FHB pathogens, Fusarium graminearum and F. asiaticum , using an ensemble framework integrating MaxEnt and random forest algorithms. Future projections were generated for 2050 and 2090 under two climate scenarios, SSP2‐4.5 and SSP5‐8.5, using multiple general circulation models. Fusarium graminearum was projected to remain globally widespread, with pronounced northward expansion in the Northern Hemisphere, whereas F. asiaticum was projected to expand further northward in Northeast Asia. Wheat suitability also showed a poleward shift, increasing spatial convergence between host and pathogen distributions. Persistently high‐risk regions were identified in the eastern United States, southeastern South America, Europe, East Asia, southeastern Australia, and New Zealand. These findings indicate that climate change may broaden and intensify global FHB risk by increasing the spatial alignment between wheat and major Fusarium pathogens. The study provides a scientific basis for proactive disease surveillance, targeted deployment of resistant cultivars, and climate‐adaptive management strategies to safeguard wheat production and global food security.
Societal Impact Statement Invasive weeds pose a global challenge to sustainable agriculture, threatening productivity while increasing the costs and uncertainty of crop management. Using 6 years of experimental evidence, we developed and evaluated three 10‐year action plans for controlling Amaranthus palmeri in maize crops in Aragón, Spain, accounting for biological and control‐effectiveness uncertainty. We found that economic outcomes depend on infestation levels and control effectiveness: High‐infestation scenarios generally remain profitable, whereas low but persistent infestations generate greater economic uncertainty. Short‐cycle systems are more resilient to management errors. These findings can help farmers and public authorities design adaptive control programs and allocate resources efficiently. Summary The spread of A. palmeri presents a serious threat to Spanish agriculture because of its remarkable adaptability and the substantial economic losses inflicted in affected areas. Despite the severe impact of this weed, limited information exists on the economic losses associated with the control measures that farmers could implement and the public expenditures incurred. This study aims to develop an action plan tailored for controlling A. palmeri under the maize cropping conditions in Aragón (Spain), while calculating the associated private and public costs. Based on the results of 6 years of field and laboratory experiments, we propose three distinct action plans over a 10‐year timeframe: one targeting fields with high infestation and two focusing on short‐ and long‐cycle maize. We evaluated the proposed action plans from an economic perspective, calculating the expected net present value (NPV) under three contexts: deterministic conditions, biological uncertainty, and control‐effectiveness uncertainty. The results reveal that in high‐infestation scenarios, most strategies maintain positive and stable profitability, providing strong economic security. Under low but persistent infestations, profitability is highly sensitive to both biological uncertainty and the effectiveness of control implementation. In short‐cycle systems, economic outcomes are more resilient, allowing the system to absorb management errors without compromising viability, which helps explain farmers' preference for these strategies. This is the first study in Europe to use experimental data to evaluate the economic impacts of A. palmeri , providing farmers and authorities with the essential information they need to design and adapt their control programs in uncertain contexts.
Societal Impact Statement Conserving rare plants requires understanding the ecological interactions that enable their reproduction. Most studied Cypripedium species are pollinated by bees, but the pollinators of many slipper orchids remain undocumented. We show that Cypripedium yatabeanum is pollinated by female aphidophagous hoverflies despite sharing broadly similar floral architecture with the closely related, bee‐pollinated Cypripedium guttatum . This contrast indicates that pollinators cannot be inferred from floral structure alone. Conservation strategies should therefore protect not only orchid populations but also their pollinators and the surrounding resources that sustain them, including flowering plants for adults and aphid‐rich habitats for larvae. Summary A deceptive flower must attract visitors and guide them into contact with its reproductive organs. This mechanical control is most pronounced in slipper orchids, whose pouch‐like labella trap insects and force them out through narrow basal apertures. Although most studied Cypripedium species are bee‐pollinated, fly pollination has been reported repeatedly. We investigated the previously undocumented pollination biology of Cypripedium yatabeanum , a member of section Bifolia with a pitcher‐shaped labellum, broad dorsal opening, glossy rim, and downward‐curved, ridged staminode. This architecture resembles that of the closely related, bee‐pollinated Cypripedium guttatum and several hoverfly‐pollinated Paphiopedilum species. Female Melanostoma interruptum and Melanostoma mellinum were legitimate pollinators. They hovered around flowers, landed on the staminode or adjacent glossy surfaces, and often slipped from the staminode into the pouch. Trapped flies escaped through basal apertures, contacting the stigma before acquiring a sticky pollen mass from an anther. A larger fly entered but could not escape, consistent with size‐dependent mechanical filtering. Exploratory scent analysis identified β‐myrcene, geraniol, and p ‐cresol as the main volatiles in the DVB/CAR/PDMS profile. A PDMS fiber also detected a trace of ( E )‐β‐farnesene. Cypripedium yatabeanum is therefore pollinated by female Melanostoma hoverflies through a Paphiopedilum ‐like trap. Its yellowish‐green display, prominent staminode, and glossy surfaces suggest anther/pollen and nectar mimicry, with volatiles as candidate supplementary signals. Comparison with bee‐pollinated C. guttatum shows that broadly similar trap architecture can accommodate different pollinator guilds, with divergence in attraction signals as a possible explanation.
Societal Impact Statement As of 2026, fewer than 23% of vascular plants have International Union for the Conservation of Nature (IUCN) Red List assessments, despite accelerating threats to biodiversity. Predictive models of extinction risk complement assessments and help prioritize conservation action but face a trade‐off between data resolution and species coverage. Using Ethiopian endemic flowering plants, we found that medium‐scale spatial data—similar to provinces or counties—strike a balance between resolution and coverage, improving predictive performance. Because these data can be obtained from multiple sources, including textual records, our approach can be implemented in future prediction models, helping experts direct limited resources toward species most at risk. Summary Extinction risk predictions complement conservation assessments but are limited by available data, creating a trade‐off between resolution and taxonomic completeness. Fine‐scale predictors offer greater resolution but exclude data‐limited species, whereas coarse‐scale predictors maximize species coverage but lack resolution—especially at smaller scales. Recent comprehensive extinction risk assessment of Ethiopia's endemic angiosperms provides an opportunity to investigate the robustness of extinction risk predictions and identify patterns or systematic biases at a national scale. Here, we interrogate the performance of coarse‐scale predictions from Bachman et al. (2024) for Ethiopian endemics, using patterns in misclassifications to identify additional (protected area) and refined (geographic range size and human footprint) predictors that could improve future models. We found that number of floristic regions (similar in scale to provinces) significantly outperformed point‐based range size metrics (extent of occurrence and area of occupancy), and that recalculating human footprint at floristic region‐scale improved predictive performance. Protected area coverage did not improve model performance. While coordinates can be impossible to pinpoint for many records, administrative units can be obtained from textual data, unlocking more possibilities for georeferencing. By leveraging medium‐scale predictors, our approach balances resolution and taxonomic completeness, offering a scalable path to substantially improve global extinction risk predictions.
