More stories

  • in

    Integrating biochar, compost, and chemical fertilizer improves maize yield and soil health in the guinea savannah: evidence from two cropping seasons in Northern Ghana

    AbstractMaize production by smallholder farmers in sub-Saharan Africa is constrained by declining soil fertility due to low input use and poor nutrient management. This study evaluated the individual and combined effects of biochar, compost, and chemical fertilizer on maize growth, yield, and soil chemical properties during the 2023 and 2024 cropping seasons in Northern Ghana. A randomized complete block design was used with six treatments: control, biochar alone (B), compost alone (C), chemical fertilizer (CF), biochar + compost (½ B + ½ C), and biochar + compost + chemical fertilizer (½ B + ½ C + ½ CF). Data were analyzed using analysis of variance (ANOVA), and treatment means were separated using the least significant difference (LSD) test at a 5% probability level. The biochar + compost + chemical fertilizer (½ B + ½ C + ½ CF) treatment significantly increased maize grain yield by 105.7% in 2023 and 127.4% in 2024 compared to the control. Soil organic carbon, nitrogen, and phosphorus improved by 115.8%, 685%, and 40.2%, respectively, under this integrated treatment. The SPAD chlorophyll index, cob number, seed weight, and harvest index also increased significantly. Grain yield correlated strongly with soil pH (r = 0.88***), electrical conductivity (r = 0.94***), organic carbon (r = 0.84***), and phosphorus (r = 0.86***). The results demonstrate that integrating biochar, compost, and mineral fertilizer enhances maize productivity and soil fertility, while biochar addition contributes to increased soil carbon storage in semi-arid, low-input systems of West Africa.

    Data availability

    The datasets generated and/or analysed during the current study are available upon request.
    ReferencesFAO. FAOSTAT statistical database. Food and agriculture organization of the united nations. http://www.fao.org/faostat/ (2021)Shiferaw, B., Prasanna, B. M., Hellin, J. & Bänziger, M. Crops that feed the world 6. Past successes and future challenges to the role played by maize in global food security. Food Secur. 3, 307–327 (2011).
    Google Scholar 
    Badu-Apraku, B., Fakorede, M. A. B., Menkir, A., Kamara, A. Y. & Melaku, G. Breeding for drought and nitrogen stress tolerance in maize in sub-Saharan Africa (Springer, 2012).
    Google Scholar 
    Agyeman, P. C., Tetteh, F. M. & Abunyewa, A. A. Soil fertility decline and maize production in Ghana: a review. West Afr. J. Appl. Ecol. 28(1), 63–75 (2020).
    Google Scholar 
    Vanlauwe, B. et al. Integrated soil fertility management operational definition: agricultural systems approach. Outlook Agric. 39(1), 17–24 (2010).
    Google Scholar 
    Saaka, M., Abunyewa, A. A. & Denkyirah, E. K. Soil degradation in the Guinea Savanna: Implications for food security in Ghana. Sustainability 13(5), 2512 (2021).
    Google Scholar 
    Ministry of Food and Agriculture (MoFA). Agriculture in Ghana: Facts and figures (2018). statistics, research and information directorate (SRID) Accra. (2019)Adjei-Nsiah, S. & Bagamsah, T. T. Comparative study of different soil fertility management practices in the Guinea Savanna zone of Ghana. Agric. Sci. 3(6), 768–775 (2012).
    Google Scholar 
    Abdulai, H., Alhassan, Y. B. & Mohammed, A. Integrated soil fertility management options for maize production in northern Ghana: lessons for sustainable intensification. J. Soil Sci. Environ. Manag. 14(2), 45–57 (2023).
    Google Scholar 
    Chivenge, P., Vanlauwe, B. & Six, J. Integrated soil fertility management: contributions of organic inputs and mineral fertilizers to soil productivity. Nutr. Cycl. Agroecosyst. 119, 1–15 (2021).
    Google Scholar 
    Vanlauwe, B. et al. Integrated soil fertility management in sub-Saharan Africa: From concept to practice. Nutr. Cycl. Agroecosyst. 109, 1–18 (2015).
    Google Scholar 
    Jeffery, S., Verheijen, F. G. A., Van der Velde, M. & Bastos, A. C. A quantitative review of the effects of biochar application to soils on crop productivity using meta-analysis. Agric. Ecosyst. Environ. 144, 175–187 (2017).
    Google Scholar 
    Lehmann, J., & Joseph, S. Biochar for environmental management: science, technology and implementation (2nd ed.) Routledge. (2015)Glaser, B., Lehmann, J. & Zech, W. Ameliorating the nutrient availability in highly weathered soils through charcoal application. Biol. Fertil. Soils 35(4), 219–230 (2002).
    Google Scholar 
    Agegnehu, G., Bass, A. M., Nelson, P. N. & Bird, M. I. Benefits of biochar, compost and biochar–compost for soil quality, maize yield and greenhouse gas emissions in tropical agricultural soils. Sci. Total Environ. 543, 295–306. https://doi.org/10.1016/j.scitotenv.2015.11.054 (2016).
    Google Scholar 
    Agegnehu, G., Bass, A. M., Nelson, P. N. & Bird, M. I. Benefits of biochar, compost and biochar–compost for soil quality, maize yield and greenhouse gas emissions in a tropical agricultural soil. Sci. Total Environ. 543, 295–306. https://doi.org/10.1016/j.scitotenv.2015.11.054 (2016).
    Google Scholar 
    Laird, D. A. et al. Biochar impact on nutrient leaching from a Midwestern agricultural soil. Geoderma 158(3–4), 436–442. https://doi.org/10.1016/j.geoderma.2010.05.012 (2010).
    Google Scholar 
    Woolf, D. et al. Sustainable biochar to mitigate global climate change. Nat. Commun. 1, 56. https://doi.org/10.1038/ncomms1053 (2010).
    Google Scholar 
    Liu, X., Ye, Y. & Ding, W. Biochar’s effect on nutrient leaching and soil fertility in maize systems: a meta-analysis. Field Crops Res. 221, 230–242 (2018).
    Google Scholar 
    Sohi, S. P., Krull, E., Lopez-Capel, E. & Bol, R. A review of biochar and its use and function in soil. Adv. Agron. 105, 47–82 (2010).
    Google Scholar 
    Adekiya, A. O. et al. Biochar and poultry manure effects on soil properties and radish yield. Commun. Soil Sci. Plant Anal. 51(1), 1–16. https://doi.org/10.1080/00103624.2019.1694468 (2020).
    Google Scholar 
    Yawson, D. O., Tetteh, F. M. & Frimpong, K. A. Application of organic amendments and fertilizer in the Guinea Savanna: effects on soil fertility and maize yield. Arch. Agron. Soil Sci. 62(11), 1549–1562 (2016).
    Google Scholar 
    Yawson, D. O., Tetteh, F. M. & Ofori, C. S. Effects of compost and inorganic fertilizer on maize yield and soil properties in the Guinea Savanna Zone of Ghana. Ghana J. Agric. Sci. 51(1), 45–54 (2016).
    Google Scholar 
    Asare-Bediako, E. et al. Effects of organic and inorganic amendments on maize yield in the Guinea Savanna of Ghana. Agron. J. 112(5), 4075–4085 (2020).
    Google Scholar 
    Asare-Bediako, E., Kwakye, P. K. & Biney, J. Effect of biochar application on soil chemical properties and maize yield in the semi-deciduous forest zone of Ghana. West Afr. J. Appl. Ecol. 28(1), 28–39 (2020).
    Google Scholar 
    Edwards, C. A., Arancon, N. Q. & Sherman, R. Vermiculture Technology: Earthworms, Organic Wastes, and Environmental Management (CRC Press, 2011).
    Google Scholar 
    Lazcano, C. & Domínguez, J. The use of vermicompost in sustainable agriculture: Impact on plant growth and soil fertility. In Vermiculture Technology (eds Edwards, C. A. et al.) 401–424 (CRC Press, 2011).
    Google Scholar 
    Mensah, A. K., Frimpong, K. A. & Yeboah, S. Combined application of biochar and inorganic fertilizer improves maize yield in the Guinea Savanna. J. Plant Nutr. Soil Sci. 181(6), 871–878 (2018).
    Google Scholar 
    Abukari, I., Tetteh, F. M. & Yakubu, I. Biochar application improves maize yield and soil properties in the Guinea Savanna of Ghana. Agric. Food Secur. 8, 12. https://doi.org/10.1186/s40066-019-0253-6 (2019).
    Google Scholar 
    Fianko, A. K. et al. Integrating organics with mineral fertilizers enhances maize yield in the Guinea Savanna. Soil Tillage Res. 230, 105631 (2023).
    Google Scholar 
    Onawumi, O. et al. Integrating biochar and fertilizer for maize production in West Africa: evidence from multi-season field trials. Agronomy 14(1), 155 (2024).
    Google Scholar 
    McLean, E. O. Soil pH and lime requirement. In Methods of Soil Analysis: Part 2 (ed. Page, A. L.) 199–224 (ASA, 1982).
    Google Scholar 
    Rhoades, J. D. Salinity: electrical conductivity and total dissolved solids. In Methods of Soil Analysis: Part 3, Chemical Methods (ed. Sparks, D. L.) 417–435 (ASA, 1996).
    Google Scholar 
    Walkley, A. & Black, I. A. An examination of the Degtjareff method for determining organic carbon in soils. Soil Science 37(1), 29–38 (1934).
    Google Scholar 
    Bremner, J. M. & Mulvaney, C. S. Nitrogen–total. In Methods of Soil Analysis: Part 2, Chemical and Microbiological Properties (ed. Page, A. L.) 595–624 (ASA, 1982).
    Google Scholar 
    Bray, R. H. & Kurtz, L. T. Determination of total, organic, and available forms of phosphorus in soils. Soil Sci. 59(1), 39–46 (1945).
    Google Scholar 
    Knudsen, D., Peterson, G. A. & Pratt, P. F. Lithium, sodium, and potassium. In Methods of Soil Analysis: Part 2 (ed. Page, A. L.) 225–246 (ASA, 1982).
    Google Scholar 
    Brady, N. C. & Weil, R. R. The nature and properties of soils 15th edn. (Pearson, 2016).
    Google Scholar 
    Chen, J. H., Xu, J. M. & He, P. Soil organic carbon and nitrogen dynamics in degraded tropical soils. Soil Biol. Biochem. 42(2), 233–239 (2010).
    Google Scholar 
    Sainju, U. M. et al. Phosphorus thresholds for maize productivity in tropical soils. Nutr. Cycl. Agroecosyst. 100, 125–137 (2014).
    Google Scholar 
    Ministry of Food and Agriculture (MoFA). Maize production guide for extension and farmers in ghana. MoFA, Accra. (2010)Ezike, K. N., Oti, N. N. & Okpara, S. C. Comparative effects of organic and inorganic fertilizers on maize performance in Nigeria. J. Agric. Ecol. Res. Int. 7(3), 1–9 (2016).
    Google Scholar 
    Rukundo, P. et al. Chlorophyll content and yield components as predictors of maize productivity. Field Crops Res. 265, 108108 (2021).
    Google Scholar 
    Zhang, H. et al. Correlation of chlorophyll content and grain yield in maize under different nutrient management practices. Agron. J. 112(3), 1855–1867 (2020).
    Google Scholar 
    Lehmann, J. et al. Biochar effects on soil biota – a review. Soil Biol. Biochem. 43(9), 1812–1836 (2011).
    Google Scholar 
    Liu, Z. et al. Biochar and nitrogen fertilizer co-application improves maize yield and nitrogen use efficiency. J. Soils Sediments 20, 3027–3039 (2020).
    Google Scholar 
    Ye, L. et al. Biochar effects on crop yields with and without fertilizer: a meta-analysis of field studies. Soil Use Manag. 36(1), 2–18 (2020).
    Google Scholar 
    Chimdi, A., Yli-Halla, M. & Gebrekidan, H. Soil acidity and liming potential of biochar in acid soils of Ethiopia. Afr. J. Agric. Res. 7(47), 6741–6746 (2012).
    Google Scholar 
    Nguyen, T. T. N. et al. Effects of biochar on soil carbon and nutrient dynamics: a global meta-analysis. GCB Bioenergy 14, 25–43 (2022).
    Google Scholar 
    Amarasinghe, U. A. et al. Biochar and compost interactions improve soil fertility and crop performance in degraded soils: a review. Environ. Adv. 7, 100159. https://doi.org/10.1016/j.envadv.2021.100159 (2022).
    Google Scholar 
    Download referencesFundingNo funding was received for this study. Declarations Competing interests T he authors declare no competing interests.Author informationAuthors and AffiliationsCSIR-Savanna Agricultural Research Institute, P.O. Box TL 52, Tamale, GhanaAbdul-Latif Abdul-Aziz, Abdulai Haruna & Alhassan Yamyolya BaakoAuthorsAbdul-Latif Abdul-AzizView author publicationsSearch author on:PubMed Google ScholarAbdulai HarunaView author publicationsSearch author on:PubMed Google ScholarAlhassan Yamyolya BaakoView author publicationsSearch author on:PubMed Google ScholarContributionsAll authors reviewed and approved the final manuscript. **ALAA** conceived and designed the study, conducted the investigation, and prepared the original manuscript draft. **ALAA, AH, and AYB** contributed to methodology refinement, supervised data collection and analysis, and participated in manuscript review and editing.Corresponding authorCorrespondence to
    Abdul-Latif Abdul-Aziz.Ethics declarations

    Competing interests
    The authors declare no competing interests.

    Consent for publication
    All authors have granted their permission for publication.

    Additional informationPublisher’s noteSpringer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Rights and permissions
    Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
    Reprints and permissionsAbout this articleCite this articleAbdul-Aziz, AL., Haruna, A. & Baako, A.Y. Integrating biochar, compost, and chemical fertilizer improves maize yield and soil health in the guinea savannah: evidence from two cropping seasons in Northern Ghana.
    Sci Rep (2025). https://doi.org/10.1038/s41598-025-31886-2Download citationReceived: 26 July 2025Accepted: 05 December 2025Published: 13 December 2025DOI: https://doi.org/10.1038/s41598-025-31886-2Share this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy shareable link to clipboard
    Provided by the Springer Nature SharedIt content-sharing initiative
    KeywordsBiocharCompostGuinea savannaIntegrated nutrient managementMaize productivitySoil chemical properties More

  • in

    Optimizing crop clustering to minimize pathogen invasion in agriculture

    AbstractThe initial rate of pathogen invasion in crops is influenced by the spatial clustering of susceptible crops and the characteristics of pathogen dispersal. Previous studies have shown that various degrees of crop clustering can effectively reduce this invasion rate. However, the optimal degrees of clustering that minimize pathogen invasion have not previously been identified. This study aims to determine analytically the range of crop clustering that minimizes the initial rate of pathogen invasion. We studied artificial agricultural landscapes with crop areas arranged in identical square clusters on a regular square lattice. For pathogen dispersal, we used several common dispersal kernels, including Gaussian, negative exponential, and power-law. The optimal degree of clustering, defined by cluster size and separation distance, was calculated using a new analytical approximation for the pathogen invasion rate, which showed strong agreement with computer simulations. Additionally, we analysed a realistic cassava landscape at risk of invasion by cassava brown streak virus. We identified a range of optimal cluster sizes and corresponding separation distances that minimize pathogen invasion rates for various dispersal kernels and landscapes with clusters of crop fields arranged on a regular square lattice. The methods can be extended to other geometrical configurations, such as long narrow fields. Using a cassava landscape as an example, we show how optimal crop clustering strategies can be derived to mitigate the potential invasion of cassava brown streak virus. The methods provides analytical insights that can help farmers and agricultural planners to optimize the spatial structure of agricultural landscapes to minimize initial pathogen invasion rates.

    Data availability

    The datasets analysed during the current study were sourced from the previously published work by Suprunenko et al. (2024) [39] and are available in the Figshare repository, https://doi.org/10.6084/m9.figshare.25804702.
    ReferencesBolker, B. Analytic models for the patchy spread of plant disease. Bull. Math. Biol. 61, 849–874 (1999).
    Google Scholar 
    Park, A. W., Gubbins, S. & Gilligan, C. A. Invasion and persistence of plant parasites in a spatially structured host population. Oikos 94, 162–174 (2001).
    Google Scholar 
    Gilligan, C. A. An epidemiological framework for disease management. Adv. Bot. Res. 38, 1–64 (2002).
    Google Scholar 
    Stacey, A. J., Truscott, J. E., Asher, M. J. C. & Gilligan, C. A. A model for the invasion and spread of rhizomania in the united kingdom: implications for disease control strategies. Phytopathology 94, 209–215 (2004).
    Google Scholar 
    Brown, D. & Bolker, B. M. The effects of disease dispersal and host clustering on the epidemic threshold in plants. Bull. Math. Biol. 66, 341–371 (2004).
    Google Scholar 
    Plantegenest, M., Le May, C. & Fabre, F. Landscape epidemiology of plant diseases. J. R Soc. Interface. 4, 963–972 (2007).
    Google Scholar 
    Gilligan, C. A., Truscott, J. E. & Stacey, A. J. Impact of scale on the effectiveness of disease control strategies for epidemics with cryptic infection in a dynamical landscape: an example for a crop disease. J. R Soc. Interface. 4, 925–934 (2007).
    Google Scholar 
    Sackett, K. E. & Mundt, C. C. Effect of plot geometry on epidemic velocity of wheat yellow rust. Plant. Pathol. 58, 370–377 (2009).
    Google Scholar 
    Mundt, C. C., Sackett, K. E. & Wallace, L. D. Landscape heterogeneity and disease spread: experimental approaches with a plant pathogen. Ecol. Appl. 21, 321–328 (2011).
    Google Scholar 
    Cunniffe, N. J. et al. Thirteen challenges in modelling plant diseases. Epidemics 10, 6–10 (2015).
    Google Scholar 
    Mikaberidze, A., Mundt, C. C. & Bonhoeffer, S. Invasiveness of plant pathogens depends on the Spatial scale of host distribution. Ecol. Appl. 26, 1238–1248 (2016).
    Google Scholar 
    North, A. R. & Godfray, H. C. J. The dynamics of disease in a metapopulation: the role of dispersal range. J. Theor. Biol. 418, 57–65 (2017).
    Google Scholar 
    Xing, Y. et al. Global cropland connectivity: A risk factor for invasion and saturation by emerging pathogens and pests. BioScience 70, 744–758 (2020).
    Google Scholar 
    Lustig, A., Stouffer, D. B., Doscher, C. & Worner, S. P. Landscape metrics as a framework to measure the effect of landscape structure on the spread of invasive insect species. Landsc. Ecol. 32, 2311–2325 (2017).
    Google Scholar 
    Etienne, L., Franck, P., Rusch, A. & Lavigne, C. Apple pest and pathogen reduction in landscapes with large patch size and small area of orchards: a national-scale analysis. Landsc. Ecol. 39 (2024).Mundt, C. C. Effect of host genotype unit area on development of focal epidemics of bean rust and common maize rust in mixtures of resistant and susceptible plants. Phytopathology 76, 895–900 (1986).
    Google Scholar 
    Mundt, C. C. & Leonard, K. J. Analysis of factors affecting disease increase and spread in mixtures of immune and susceptible plants in computer-simulated epidemics. Phytopathology 76, 832–840 (1986).
    Google Scholar 
    Skelsey, P., Rossing, W. A. H., Kessel, G. J. T. & Van Der Werf, W. Invasion of phytophthora infestans at the landscape level: how do Spatial scale and weather modulate the consequences of Spatial heterogeneity in host resistance? Phytopathology® 100, 1146–1161 (2010).
    Google Scholar 
    Papaïx, J., Touzeau, S., Monod, H. & Lannou, C. Can epidemic control be achieved by altering landscape connectivity in agricultural systems? Ecol. Model. 284, 35–47 (2014).
    Google Scholar 
    Beasley, E. M., Aristizábal, N., Bueno, E. M. & White, E. R. Spatially explicit models predict coffee rust spread in fragmented landscapes. Landsc. Ecol. 37, 2165–2178 (2022).
    Google Scholar 
    Précigout, P. A., Renard, D., Sanner, J., Claessen, D. & Robert, C. Crop mixtures outperform rotations and landscape mosaics in regulation of two fungal wheat pathogens: a simulation study. Landsc. Ecol. 38, 77–97 (2023).
    Google Scholar 
    Rimbaud, L. et al. Models of plant resistance deployment. Annu. Rev. Phytopathol. 59, 125–152 (2021).
    Google Scholar 
    Meentemeyer, R. K., Haas, S. E. & Václavík, T. Landscape epidemiology of emerging infectious diseases in natural and Human-Altered ecosystems. Annu. Rev. Phytopathol. 50, 379–402 (2012).
    Google Scholar 
    Suprunenko, Y. F., Cornell, S. J. & Gilligan, C. A. Predicting the effect of landscape structure on epidemic invasion using an analytical estimate for infection rate. R Soc. Open. Sci. 12, 240763 (2025).
    Google Scholar 
    Suprunenko, Y. F. & Gilligan, C. A. Computer code for: optimizing crop clustering to minimize pathogen invasion in agriculture. Figshare (2025). https://doi.org/10.6084/m9.figshare.26038006CunniffeN. J., Cobb, R. C., Meentemeyer, R. K., Rizzo, D. M. & Gilligan, C. A. Modeling when, where, and how to manage a forest epidemic, motivated by sudden oak death in California. Proc. Natl. Acad. Sci. U S A. 113, 5640–5645 (2016).
    Google Scholar 
    Nguyen, V. A., Bartels, D. W. & Gilligan, C. A. Modelling the spread and mitigation of an emerging vector-borne pathogen: citrus greening in the U.S. PLoS Comput. Biol. 19, e1010156 (2023).
    Google Scholar 
    Nweke, F. I., Lynam, J. K. & Spencer, D. S. C. The Cassava Transformation: Africa’s Best-Kept Secret (Michigan State University, 2002).Alicai, T. et al. Re-emergence of cassava brown streak disease in Uganda. Plant Dis. 91, 24–29 (2007).
    Google Scholar 
    Muhindo, H. et al. Optimum time for harvesting cassava tubers to reduce losses due to cassava brown streak disease in northeastern DRC. JAS 12, 70 (2020).
    Google Scholar 
    Godding, D. et al. Developing a predictive model for an emerging epidemic on cassava in sub-Saharan Africa. Sci. Rep. 13, 12603 (2023).
    Google Scholar 
    Szyniszewska, A. M. CassavaMap, a fine-resolution disaggregation of cassava production and harvested area in Africa in 2014. Sci. Data. 7, 159 (2020).
    Google Scholar 
    van den Bosch, F., Helps, J. & Cunniffe, N. J. The basic-reproduction number of infectious diseases in spatially structured host populations. Oikos https://doi.org/10.1111/oik.10616 (2024).
    Google Scholar 
    Suprunenko, Y. F., Cornell, S. J. & Gilligan, C. A. Analytical approximation for invasion and endemic thresholds, and the optimal control of epidemics in spatially explicit individual-based models. J. R Soc. Interface. 18, 20200966 (2021). rsif.2020.0966.
    Google Scholar 
    Wadkin, L. E. et al. Estimating the reproduction number, R 0, from individual-based models of tree disease spread. Ecol. Model. 489, 110630 (2024).
    Google Scholar 
    Ovaskainen, O. et al. A general mathematical framework for the analysis of Spatiotemporal point processes. Theor. Ecol. 7, 101–113 (2014).
    Google Scholar 
    Cornell, S. J., Suprunenko, Y. F., Finkelshtein, D. & Somervuo, P. Ovaskainen, O. A unified framework for analysis of individual-based models in ecology and beyond. Nat. Commun. 10, 4716 (2019).
    Google Scholar 
    Nathan, R., Klein, E., Robledo-Arnuncio, J. J. & Revilla, E. Dispersal kernels: review. In Dispersal ecology and evolution vol. 15, 187–210 (Oxford Univ Press, 2012).Suprunenko, Y. F., Cornell, S. J. & Gilligan, C. A. Data from: Predicting the effect of landscape structure on epidemic invasion using an analytical estimate for infection rate. Figshare https://doi.org/10.6084/m9.figshare.25804702 (2024).Fitt, B. D. L., Gregory, P. H., Todd, A. D., McCartney, H. A. & Macdonald, O. C. Spore dispersal and plant disease Gradients; a comparison between two empirical models. J. Phytopathol. 118, 227–242 (1987).
    Google Scholar 
    Mundt, C. C., Sackett, K. E., Wallace, L. D., Cowger, C. & Dudley, J. P. Aerial dispersal and Multiple-Scale spread of epidemic disease. EcoHealth 6, 546–552 (2009).
    Google Scholar 
    Benincà, E., Hagenaars, T., Boender, G. J., Van De Kassteele, J. & Van Boven, M. Trade-off between local transmission and long-range dispersal drives infectious disease outbreak size in spatially structured populations. PLoS Comput. Biol. 16, e1008009 (2020).
    Google Scholar 
    Godding, D. et al. Predicting the cross-continental spread of the cassava brown streak disease epidemic in sub-Saharan Africa. bioRxiv https://doi.org/10.1101/2025.10.10.681618 (2025).
    Google Scholar 
    Gilligan, C. A. Sustainable agriculture and plant diseases: an epidemiological perspective. Phil Trans. R Soc. B. 363, 741–759 (2008).
    Google Scholar 
    Jeanneret, P. et al. Agroecology landscapes. Landsc. Ecol. 36, 2235–2257 (2021).
    Google Scholar 
    Vega, D., Ibarra, S., Varela Pardo, R. A. & Poggio, S. L. Agroecological management of crop diseases: a review. Agroecol. Sustain. Food Syst. 47, 919–949 (2023).
    Google Scholar 
    Download referencesAcknowledgementsThe authors are grateful to Dr Stephen Cornell for useful discussions at early stages of this work, and to Dr Alison Scott-Brown for helpful comments on the manuscript.FundingC.A.G. acknowledges financial support from the Gates Foundation (INV-010472).Author informationAuthors and AffiliationsDepartment of Plant Sciences, University of Cambridge, Downing Street, Cambridge, CB2 3EA, UKYevhen F. Suprunenko & Christopher A. GilliganAuthorsYevhen F. SuprunenkoView author publicationsSearch author on:PubMed Google ScholarChristopher A. GilliganView author publicationsSearch author on:PubMed Google ScholarContributionsBoth authors contributed to the study conception. YFS developed analytical approximations, performed analysis and calculations, and generated figures. YFS and CAG reviewed and discussed the results. The first draft of the manuscript was written by YFS. Both authors reviewed the manuscript and approved the final manuscript.Corresponding authorCorrespondence to
    Yevhen F. Suprunenko.Ethics declarations

    Competing interests
    The authors declare no competing interests.

    Additional informationPublisher’s noteSpringer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Supplementary InformationBelow is the link to the electronic supplementary material.Supplementary Material 1Rights and permissions
    Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
    Reprints and permissionsAbout this articleCite this articleSuprunenko, Y.F., Gilligan, C.A. Optimizing crop clustering to minimize pathogen invasion in agriculture.
    Sci Rep (2025). https://doi.org/10.1038/s41598-025-30635-9Download citationReceived: 07 July 2025Accepted: 26 November 2025Published: 13 December 2025DOI: https://doi.org/10.1038/s41598-025-30635-9Share this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy shareable link to clipboard
    Provided by the Springer Nature SharedIt content-sharing initiative More

  • in

    Morph-specific selection drives phenotypic divergence in color polymorphic tawny owls (Strix aluco) in Northern Europe

    AbstractThere is a long tradition in using genetically based color polymorphisms in natural populations to study evolutionary processes. Despite growing evidence for continuous phenotypic variation within discrete morphs, we still know little about how this shapes selective dynamics. Here, using 43 years of plumage color data from a Finnish tawny owl population (Strix aluco), we show that gray and brown morphs exhibit substantial intra-morph variation, which has diverged over time. Plumage in the brown morph became increasingly pigmented, while the gray morph showed an abrupt shift toward lighter coloration. By examining both adult and offspring plumage, we identified morph-specific drivers of these trends: in gray owls, reduced pigmentation appears linked to extreme winters that eroded standing genetic variation, likely constraining their evolutionary response. In contrast, brown morph dynamics were shaped by an interaction between plumage coloration, reproductive success, and breeding timing, along with stronger temperature effects during the pre-fledging period. These findings suggest that intra-morph variation determines each morph’s response to selection pressures, potentially influencing their ability to track shifting phenotypic optima. Our work highlights the relevance of phenotypic variation within genetically discrete morphs for evolutionary processes, including how populations respond to environmental change.

    Data availability

    We have archived all data necessary to reproduce the results and figures in an online data repository: https://doi.org/10.5281/zenodo.1539270371.
    ReferencesCuthill, I. C. et al. The biology of color. Science 357, eaan0221 (2017).
    Google Scholar 
    Roulin, A. The evolution, maintenance and adaptive function of genetic colour polymorphism in birds. Biol. Rev. 79, 815–848 (2004).
    Google Scholar 
    White, T. E. & Kemp, D. J. Colour polymorphism. Curr. Biol. 26, R517–R518 (2016).
    Google Scholar 
    Corl, A., Davis, A. R., Kuchta, S. R. & Sinervo, B. Selective loss of polymorphic mating types is associated with rapid phenotypic evolution during morphic speciation. Proc. Natl. Acad. Sci. USA. 107, 4254–4259 (2010).
    Google Scholar 
    McKinnon, J. S. & Pierotti, M. E. R. Colour polymorphism and correlated characters: genetic mechanisms and evolution. Mol. Ecol. 19, 5101–5125 (2010).
    Google Scholar 
    Svensson, E. I. Back to basics: using colour polymorphisms to study evolutionary processes. Mol. Ecol. 26, 2204–2211 (2017).
    Google Scholar 
    Rankin, K. J., McLean, C. A., Kemp, D. J. & Stuart-Fox, D. The genetic basis of discrete and quantitative colour variation in the polymorphic lizard, Ctenophorus decresii. BMC Evol. Biol. 16, 179 (2016).
    Google Scholar 
    Paterson, J. E. & Blouin-Demers, G. Distinguishing discrete polymorphism from continuous variation in throat colour of tree lizards, Urosaurus ornatus. Biol. J. Linn. Soc. Lond. 121, 72–81 (2017).
    Google Scholar 
    Davison, A., Jackson, H. J., Murphy, E. W. & Reader, T. Discrete or indiscrete? Redefining the colour polymorphism of the land snail Cepaea nemoralis. Heredity 123, 162–175 (2019).
    Google Scholar 
    Mould, M. C. et al. Beyond morphs: inter-individual colour variation despite strong genetic determinism of colour morphs in a wild bird. J. Evol. Biol. 36, 82–94 (2023).
    Google Scholar 
    San-Jose, L. M. & Roulin, A. Genomics of coloration in natural animal populations. Philos. Trans. R. Soc. Lond. B Biol. Sci. 372, 20160337 (2017).
    Google Scholar 
    Kunte, K. et al. doublesex is a mimicry supergene. Nature 507, 229–232 (2014).
    Google Scholar 
    López-Rull, I., Salaberría, C. & Fargallo, J. A. Plastic plumage colouration in response to experimental humidity supports Gloger’s rule. Sci. Rep. 13, 858 (2023).
    Google Scholar 
    Corl, A. et al. The genetic basis of adaptation following plastic changes in coloration in a novel environment. Curr. Biol. 28, 2970–2977.e7 (2018).
    Google Scholar 
    Roff, D. A. The evolution of threshold traits in animals. Q. Rev. Biol. 71, 3–35 (1996).
    Google Scholar 
    Gilby, A. J., Pryke, S. R. & Griffith, S. C. The historical frequency of head-colour morphs in the Gouldian Finch (Erythrura gouldiae). Emu 109, 222–229 (2009).
    Google Scholar 
    Madsen, T., Stille, B., Ujvari, B., Bauwens, D. & Endler, J. A. Negative frequency-dependent selection on polymorphic color morphs in adders. Curr. Biol. 32, 3385–3388.e3 (2022).
    Google Scholar 
    Le Rouzic, A., Hansen, T. F., Gosden, T. P. & Svensson, E. I. Evolutionary time-series analysis reveals the signature of frequency-dependent selection on a female mating polymorphism. Am. Nat. 185, E182–E196 (2015).
    Google Scholar 
    Dudaniec, R. Y., Yong, C. J., Lancaster, L. T., Svensson, E. I. & Hansson, B. Signatures of local adaptation along environmental gradients in a range-expanding damselfly (Ischnura elegans). Mol. Ecol. 27, 2576–2593 (2018).
    Google Scholar 
    Wellenreuther, M., Svensson, E. I. & Hansson, B. Sexual selection and genetic colour polymorphisms in animals. Mol. Ecol. 23, 5398–5414 (2014).
    Google Scholar 
    Forsman, A., Ahnesjö, J., Caesar, S. & Karlsson, M. A model of ecological and evolutionary consequences of color polymorphism. Ecology 89, 34–40 (2008).
    Google Scholar 
    Mundy, N. I. A window on the genetics of evolution: MC1R and plumage colouration in birds. Proc. Biol. Sci. 272, 1633–1640 (2005).
    Google Scholar 
    Hoekstra, H. E., Hirschmann, R. J., Bundey, R. A., Insel, P. A. & Crossland, J. P. A single amino acid mutation contributes to adaptive beach mouse color pattern. Science 313, 101–104 (2006).
    Google Scholar 
    Ducrest, A.-L., Keller, L. & Roulin, A. Pleiotropy in the melanocortin system, coloration and behavioural syndromes. Trends Ecol. Evol. 23, 502–510 (2008).
    Google Scholar 
    Karell, P., Ahola, K., Karstinen, T., Valkama, J. & Brommer, J. E. Climate change drives microevolution in a wild bird. Nat. Commun. 2, 208 (2011).
    Google Scholar 
    Morosinotto, C. et al. Fledging mass is color morph specific and affects local recruitment in a wild bird. Am. Nat. 196, 609–619 (2020).
    Google Scholar 
    Baltazar-Soares, M., Karell, P., Wright, D., Nilsson, J. -Å & Brommer, J. E. Genomic basis of melanin-associated phenotypes suggests colour-specific environmental adaptations in tawny owls. Mol. Ecol. 33, e17247 (2024).
    Google Scholar 
    Koskenpato, K., Ahola, K., Karstinen, T. & Karell, P. Is the denser contour feather structure in pale grey than in pheomelanic brown tawny owls Strix aluco an adaptation to cold environments?. J. Avian Biol. 47, 1–6 (2016).
    Google Scholar 
    Koskenpato, K., Lehikoinen, A., Lindstedt, C. & Karell, P. Gray plumage color is more cryptic than brown in snowy landscapes in a resident color polymorphic bird. Ecol. Evol. 10, 1751–1761 (2020).
    Google Scholar 
    Perrault, C., Morosinotto, C., Brommer, J. E. & Karell, P. Camouflage efficiency in a colour-polymorphic predator is dependent on environmental variation and snow presence in the wild. Ecol. Evol. 13, e10824 (2023).
    Google Scholar 
    Passarotto, A., Rodríguez-Caballero, E., Cruz-Miralles, Á & Avilés, J. M. Ecogeographical patterns in owl plumage colouration: climate and vegetation cover predict global colour variation. Glob. Ecol. Biogeogr. 31, 515–530 (2022).
    Google Scholar 
    Tian, L. & Benton, M. J. Predicting biotic responses to future climate warming with classic ecogeographic rules. Curr. Biol. 30, R744–R749 (2020).
    Google Scholar 
    Delhey, K. A review of Gloger’s rule, an ecogeographical rule of colour: definitions, interpretations and evidence. Biol. Rev. 94, 1294–1316 (2019).
    Google Scholar 
    Van Valen, L. Morphological variation and width of ecological niche. Am. Nat. 99, 377–390 (1965).
    Google Scholar 
    Luquet, E., Léna, J.-P., Miaud, C. & Plénet, S. Phenotypic divergence of the common toad (Bufo bufo) along an altitudinal gradient: evidence for local adaptation. Heredity 114, 69–79 (2015).
    Google Scholar 
    Brommer, J. E., Ahola, K. & Karstinen, T. The colour of fitness: plumage coloration and lifetime reproductive success in the tawny owl. Proc. Biol. Sci. 272, 935–940 (2005).
    Google Scholar 
    Roulin, A., Ducret, B., Ravussin, P. A. & Altwegg, R. Female colour polymorphism covaries with reproductive strategies in the tawny owl Strix aluco. J. Avian Biol. 34, 393–401 (2003).
    Google Scholar 
    Lande, R. Natural selection and random genetic drift in phenotypic evolution. Evolution 30, 314–334 (1976).
    Google Scholar 
    Karell, P., Ahola, K., Karstinen, T., Zolei, A. & Brommer, J. E. Population dynamics in a cyclic environment: consequences of cyclic food abundance on tawny owl reproduction and survival. J. Anim. Ecol. 78, 1050–1062 (2009).
    Google Scholar 
    Briggs, C. W., Wommack, E. A., Sawtelle, S. E., Reynolds, C. & Amar, A. A population bottleneck did not affect polymorphism rates in California Swainson’s hawks. J. Raptor Res. 57, 61–68 (2023).
    Google Scholar 
    Voje, K. L. et al. Does lack of evolvability constrain adaptation? If so, on what timescales? In Evolvability: A unifying concept in evolutionary biology? (eds Hansen, T. F., Houle, D., M. Pavličev, M., Pélabon, C.) (MIT Press, 2023).Lenormand, T. Gene flow and the limits to natural selection. Trends Ecol. Evol. 17, 183–189 (2002).
    Google Scholar 
    Passarotto, A. et al. Cold winters have morph-specific effects on natal dispersal distance in a wild raptor. Behav. Ecol. 33, 419–427 (2022).
    Google Scholar 
    Gasparini, J. et al. Strength and cost of an induced immune response are associated with a heritable melanin-based colour trait in female tawny owls. J. Anim. Ecol. 78, 608–616 (2009).
    Google Scholar 
    Järvistö et al. Carry-over effects of conditions at the wintering grounds on breeding plumage signals in a migratory bird: roles of phenotypic plasticity and selection. J. Evol. Biol. 29, 1569–1584 (2016).
    Google Scholar 
    Piault, R., Gasparini, J., Bize, P., Jenni-Eiermann, S. & Roulin, A. Pheomelanin-based coloration and the ability to cope with variation in food supply and parasitism. Am. Nat. 174, 548–556 (2009).
    Google Scholar 
    Emaresi, G. et al. Melanin-specific life-history strategies. Am. Nat. 183, 269–280 (2014).
    Google Scholar 
    Lürig, M. D. & Matthews, B. Dietary-based developmental plasticity affects juvenile survival in an aquatic detritivore. Proc. Biol. Sci. 288, 20203136 (2021).
    Google Scholar 
    Stevens, M. Color change, phenotypic plasticity, and camouflage. Front. Ecol. Evol. 4, 51 (2016).
    Google Scholar 
    Tollrian, R. & Heibl, C. Phenotypic plasticity in pigmentation in Daphnia induced by UV radiation and fish kairomones. Funct. Ecol. 18, 497–502 (2004).
    Google Scholar 
    Roulin, A. & Ducrest, A.-L. Genetics of colouration in birds. Semin. Cell Dev. Biol. 24, 594–608 (2013).
    Google Scholar 
    Kemp, D. & Jones, R. Phenotypic plasticity in field populations of the tropical butterfly Hypolimnas bolina (L.) (Nymphalidae). Biol. J. Linn. Soc. Lond. 72, 33–45 (2001).
    Google Scholar 
    Perry, B. W., Schield, D. R. & Castoe, T. A. Evolution: plasticity versus selection, or plasticity and selection?. Curr. Biol. 28, R1104–R1106 (2018).
    Google Scholar 
    Hoekstra, H. E. Genetics, development and evolution of adaptive pigmentation in vertebrates. Heredity 97, 222–234 (2006).
    Google Scholar 
    Takahashi, Y., Kagawa, K., Svensson, E. I. & Kawata, M. Evolution increased phenotypic diversity enhances population performance reducing sexual harassment damselflies. Nat. Commun. 5, 4468 (2014).
    Google Scholar 
    Gray, S. M. & McKinnon, J. S. Linking color polymorphism maintenance and speciation. Trends Ecol. Evol. 22, 71–79 (2007).
    Google Scholar 
    Jamie, G. A. & Meier, J. I. The persistence of polymorphisms across species radiations. Trends Ecol. Evol. 35, 795–808 (2020).
    Google Scholar 
    Brennan, R. S., Garrett, A. D., Huber, K. E., Hargarten, H. & Pespeni, M. H. Rare genetic variation and balanced polymorphisms are important for survival in global change conditions. Proc. Biol. Sci. 286, 20190943 (2019).
    Google Scholar 
    Roulin, A. Melanin-based colour polymorphism responding to climate change. Glob. Chang. Biol. 20, 3344–3350 (2014).
    Google Scholar 
    Koskenpato, K., Lehikoinen, A., Morosinotto, C., Gunko, R. & Karell, P. Regional variation in climate change alters the range-wide distribution of colour polymorphism in a wild bird. Ecol. Evol. 13, e10311 (2023).
    Google Scholar 
    Hegyi, G., Laczi, M., Kötél, D. & Csörgő, T. Melanin-based ornament darkness positively correlates with across-season nutritional condition. Ecol. Evol. 10, e10311 (2020).
    Google Scholar 
    R. Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2024).Wood, S. N. Generalized Additive Models: An Introduction with R, 2nd edn (CRC Press, 2017).Covarrubias-Pazaran, G. Genome-assisted prediction of quantitative traits using the R package sommer. PLoS ONE 11, e0156744 (2016).
    Google Scholar 
    Kruuk, L. E. B. & Hadfield, J. D. How to separate genetic and environmental causes of similarity between relatives. J. Evo. Biol. 20, 1890–1903 (2007).
    Google Scholar 
    Passarotto, A. et al. Dear territory or dear partner? Causes and consequences of breeding dispersal in a highly territorial bird of prey with a strong pair bond. Behav. Ecol. Sociobiol. 77, 108 (2023).
    Google Scholar 
    Saladin, V., Ritschard, M., Roulin, A., Bize, P. & Richner, H. Analysis of genetic parentage in the tawny owl (Strix aluco) reveals extra-pair paternity is low. J. Ornithol. 148, 113–116 (2007).
    Google Scholar 
    Class, B., Dingemanse, N. J., Araya-Ajoy, Y. G. & Brommer, J. E. A statistical methodology for estimating assortative mating for phenotypic traits that are labile or measured with error. Methods Ecol. Evol. 8, 1910–1919 (2017).
    Google Scholar 
    Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D. & R Core Team. nlme: Linear and Nonlinear Mixed Effects Models (R Core Team, 2017).Rosseel, Y. lavaan: an R package for structural equation modeling. J. Stat. Softw. 48, 1–36 (2012).
    Google Scholar 
    Passarotto, A., Lürig, M. D., Aaltonen, E. & Karell, P. Data supporting the paper “Morph-specific selection pressures drive phenotypic divergence in a color polymorphic bird”. Zenodo. Dataset and codes https://doi.org/10.5281/zenodo.15392703 (2025).Download referencesAcknowledgementsThis paper is dedicated to the memory of Kari Ahola, who passed away during the writing of the manuscript. Without him, this and many other projects would not have been possible. We greatly thank Teuvo Karstinen and the other members of KBP for the many hours spent conducting fieldwork and data sharing. We also thank Glaucia Del-Rio, Arthur Porto, and Edward Iwimey-Cook for commenting on a draft of the manuscript and advice on animal models. The work was supported by the Swedish Cultural Foundation (grant numbers 168034 and 188919 to P.K.). A.P. was supported by a Margarita Salas fellowship from the University of Seville (MSALAS-2022-22312). M.D.L. was supported by a Marie Sklodowska Curie Individual fellowship awarded by the European Commission (PhenoDim; Grant No. 898932). This is paper number 25 from Kimpari Bird Projects (KBP).FundingOpen access funding provided by Lund University.Author informationAuthor notesThese authors contributed equally: Arianna Passarotto, Moritz David Lürig.Authors and AffiliationsEvolutionary Ecology Unit, Department of Biology, Lund University, Lund, SwedenArianna Passarotto, Moritz David Lürig & Patrik KarellUniversidad de Sevilla, Seville, SpainArianna PassarottoSchool of Biodiversity, One Health and Veterinary Medicine, University of Glasgow, Glasgow, Scotland, UKArianna PassarottoFlorida Museum of Natural History, University of Florida, Gainesville, FL, USAMoritz David LürigIndependent researcher, Lohja, FinlandEsa AaltonenAuthorsArianna PassarottoView author publicationsSearch author on:PubMed Google ScholarMoritz David LürigView author publicationsSearch author on:PubMed Google ScholarEsa AaltonenView author publicationsSearch author on:PubMed Google ScholarPatrik KarellView author publicationsSearch author on:PubMed Google ScholarContributionsA.P., M.D.L., and P.K. conceived the study. E.A. and P.K. collected the data in the field. A.P. and M.D.L. analyzed the data. A.P. and M.D.L. wrote the first draft with inputs from P.K. All authors (A.P., M.D.L., E.A., and P.K.) revised and commented on the manuscript and approved the final version.Corresponding authorCorrespondence to
    Arianna Passarotto.Ethics declarations

    Competing interests
    The authors declare no competing interests.

    Peer review

    Peer review information
    Communications Biology thanks Katja Räsänen and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editors: Michele Repetto and George Inglis. A peer review file is available.

    Additional informationPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Supplementary informationTransparent Peer Review fileSupplementary InformationReporting SummaryRights and permissions
    Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
    Reprints and permissionsAbout this articleCite this articlePassarotto, A., Lürig, M.D., Aaltonen, E. et al. Morph-specific selection drives phenotypic divergence in color polymorphic tawny owls (Strix aluco) in Northern Europe.
    Commun Biol (2025). https://doi.org/10.1038/s42003-025-09365-1Download citationReceived: 16 November 2024Accepted: 03 December 2025Published: 13 December 2025DOI: https://doi.org/10.1038/s42003-025-09365-1Share this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy shareable link to clipboard
    Provided by the Springer Nature SharedIt content-sharing initiative More

  • in

    Pollen morphology of three invasive Impatiens species in Europe under varying habitat conditions—a case study from Poland

    AbstractThe effect of the habitat conditions on the pollen features of invasive species has not been studied so far, and may affect the quality of their generative reproduction and contribute to the development of more effective methods of their control. Three species invasive in Europe and Poland were selected for the study – Impatiens parviflora DC., Impatiens glandulifera Royle and Impatiens capensis Meerb. The morphology and intraspecific variability of pollen grains in three Impatiens species growing under different habitat conditions were examined. Specimens were sampled from 198 sites throughout Poland, covering 10 ecologically distinct habitat types. In total, 5940 pollen grains were analysed in respect to the length of the polar axis (P), equatorial diameter (E), exine thickness (Exp), P/E, Exp/P ratios, and exine ornamentation and ectocolpi arrangement. Our research showed that the three studied species can be distinguished based on their palynomorphology. The most important traits were: exine ornamentation and ectocolpi arrangement, pollen size (P, E) and exine thickness (Exp). A relationship between the habitat conditions prevailing in the analysed habitats and the pollen grain characteristics was found, especially in I. glandulifera. In this species pollen size (P, E) increases in the optimal habitat conditions such as edges of reservoirs and watercourses, and decreases in the suboptimal habitat conditions such as anthropogenic habitats. A similar pattern is observed in I. parviflora, where optimal habitats such as mesic mixed coniferous forest favour larger pollen grains, whereas suboptimal habitats like swamp forest are associated with reduced pollen size. In I. capensis, optimal conditions also correspond to edges of watercourses, while suboptimal conditions include swamp forest. Additionally, exine thickness (Exp) may represent an adaptive trait, reflecting plant response to growth and development in unfavorable environments.

    Data availability

    Data concerning pollen grain measurements will be made available by the corresponding author, whereas the remaining data are included in the manuscript and the supplementary materials.
    ReferencesJanssens, S. B., Knox, E. B., Dessein, S. & Smets, E. F. Impatiens msisimwanensis (Balsaminaceae): Description, pollen morphology and phylogenetic position of a new East African species. S Afr. J. Bot. 75, 104–109. https://doi.org/10.1016/j.sajb.2008.08.003 (2009).
    Google Scholar 
    POWO. Plants of the World Online. http://www.plantsoftheworldonline.org (Facilitated by the Royal Botanic Gardens, 2024).Adamowski, W. Balsams on the offensive: the role of planting in the invasion of Impatiens species. In Plant Invasions: Human Perception, Ecological Impacts and Management (eds Tokarska-Guzik, B. et al.) (Backhuys, 2008).Trepl, L. Über Impatiens parviflora DC. Agriophyt in mitteleuropa. Diss Bot. 73, 1–400 (1984).
    Google Scholar 
    NOBANIS. European Network on Invasive Alien Species. http://www.NOBANIS.org (2024).Myśliwy, M. Habitat preferences of some neophytes, with a reference to habitat disturbances. Pol. J. Ecol. 63, 509–524. https://doi.org/10.3161/104.062.0311 (2014).
    Google Scholar 
    Reczyńska, K., Świerkosz, K. & Dajdok, Z. The spread of Impatiens parviflora DC. in central European oak forests – another stage of invasion? Acta Soc. Bot. Pol. 84, 401–411. https://doi.org/10.5586/asbp.2015.039 (2015).
    Google Scholar 
    Obidziński, T. & Symonides, E. The influence of the groundlayer structure on the invasion of small Balsam (Impatiens parviflora DC.) to natural and degraded forests. Acta Soc. Bot. Pol. 69, 1–8. https://doi.org/10.5586/asbp.2000.041 (2000).
    Google Scholar 
    Hejda, M. What is the impact of Impatiens parviflora on diversity and composition of herbal layer communities of temperate forests? PLoS One. 7, e39571. https://doi.org/10.1371/journal.pone.0039571 (2012).
    Google Scholar 
    Helsen, K. et al. Biological flora of central Europe: Impatiens glandulifera Royle. PPEES 50, 125609. https://doi.org/10.1016/j.ppees.2021.125609 (2021).
    Google Scholar 
    Lhotská, M. & Kopecký, K. Zur verbreitungsbiologie und Phytozönologie von Impatiens glandulifera royle an Den flussystemen der Svitava, Svratka und oberen Odra. Preslia 38, 376–385 (1966).
    Google Scholar 
    Beerling, D. J. & Perrins, J. M. Impatiens glandulifera Royle (Impatiens roylei Walp). J. Ecol. 81, 367–382. https://doi.org/10.2307/2261507 (1993).
    Google Scholar 
    Tokarska-Guzik, B. The Establishment and Spread of Alien Plant Species (Kenophytes) in the Flora of Poland (Wydawnictwo Uniwersytetu Śląskiego, 2005).Čuda, J., Skálová, H. & Pyšek, P. Spread of Impatiens glandulifera from riparian habitats to forests and Ist associated impacts: insights from a new invasion. Weed Res. 60, 8–15. https://doi.org/10.1111/wre.12400 (2020).
    Google Scholar 
    Commission Implementing Regulation (EU). 2017/1263 of 12 July 2017 updating the list of invasive alien species of Union concern established by Implementing Regulation (EU) 2016/1141 pursuant to Regulation (EU) No 1143/2014 of the European Parliament and of the Council (OJ L 182, 13.7.2017, p. 37). http://data.europa.eu/eli/reg_impl/2017/1263/oj (2017).Gaggini, L., Rusterholz, H-P. & Baur, B. The invasive plant Impatiens glandulifera affects soil fungal diversity and the bacterial community in forests. Appl. Soil. Ecol. 124, 335–343. https://doi.org/10.1016/j.apsoil.2017.11.021 (2017).
    Google Scholar 
    Tanner, R. A. An Ecological Assessment of Impatiens Glandulifera in its Introduced and Native Range and the Potential for its Classical Biological Control (PhD thesisUniversity of London, 2011).Ruckli, R., Rusterholz, H-P. & Baur, B. Invasion of Impatiens glandulifera affects terrestrial gastropods by altering microclimate. Acta Oecol. 47, 16–23. https://doi.org/10.1016/j.actao.2012.10.011 (2013).
    Google Scholar 
    Rusterholz, H. P., Salamon, J. A., Ruckli, R. & Baur, B. Effects of the annual invasive plant Impatiens glandulifera on the collembola and Acari communities in a deciduous forest. Pedobiologia 57, 285–291. https://doi.org/10.1016/j.pedobi.2014.07.001 (2014).
    Google Scholar 
    Ruckli, R., Hesse, K., Glauser, G., Rusterholz, H-P. & Baur, B. Inhibitory potential of naphthoquinones leached from leaves and exuded from roots of the invasive plant Impatiens glandulifera. J. Chem. Ecol. 40, 371–378. https://doi.org/10.1007/s10886-014-0421-5 (2014).
    Google Scholar 
    Kiełtyk, P. & Delimat, A. Im pact of the alien plant Impatiens glandulifera on species diversity invaded vegetation in the Northern foothills of the Tatra Mountains, Central Europe. Plant. Ecol. 220, 1–12. https://doi.org/10.1007/s11258-018-0898-z (2019).
    Google Scholar 
    Chittka, L. & Schürkens, S. Successful invasion of a floral market. Nature 411, 653. https://doi.org/10.1038/35079676 (2001).
    Google Scholar 
    Najberek, K., Solarz, W., Wysoczański, W., Węgrzyn, E. & Olejniczak, P. Flowers of impatiens glandulifera as hubs for both pollinators and pathogens. NeoBiota 87, 1–26. https://doi.org/10.3897/neobiota.87.102576 (2023).
    Google Scholar 
    Perring, F. M. & Walters, S. M. Atlas of the British Flora: 96 (Thomas Nalson and Sons Ltd, 1962).Fournier, P. Les quatre flores de France. In (ed. Chevalier, P.) (FFESSM, 1961).Akiyama, S. A new record of Impatiens (Balsaminaceae) in Honshu. Bull. Nation Sci. Mus. B (Tokyo). 26, 61–65 (2000).
    Google Scholar 
    Zika, P. F. Impatiens ×pacifica (Balsaminaceae), a new hybrid Jewelweed from the Pacific Northwest Coast of North America. Novon 16, 443–448 (2006). 10.3417/1055–3177(2006)16[443:IPBANH]2.0.CO;2.
    Google Scholar 
    Rewicz, A., Myśliwy, M., Rewicz, T., Adamowski, W. & Kolanowska, M. Contradictory effect of climate change on American and European populations of Impatiens capensis Meerb. – is this herb a global threat? Sci. Total Environ. 850, 157959. https://doi.org/10.1016/j.scitotenv.2022.157959 (2022).
    Google Scholar 
    Tokarska-Guzik, B. et al. Alien plants in Poland with particular reference to invasive species (Generalna Dyrekcja ochrony Środowiska, [in Polish with English summary]. (2012).Regulation of the Council of Ministers of 9. December 2022 on the list of invasive alien species posing a threat to the Union and the list of invasive alien species posing a threat to Poland, remedial actions, and measures aimed at restoring the natural state of ecosystems (Journal of Laws of 16 December 2022, item 2649) https://isap.sejm.gov.pl/isap.nsf/DocDetails.xsp?id=WDU20220002649 [in Polish] (2022).Pawlaczyk, P. & Adamowski, W. Impatiens capensis (Balsaminaceae) – a new species in the flora of Poland. Fragm Flor. Geobot. 35, 225–232 (1991). [in Polish].
    Google Scholar 
    Matthews, J. et al. Risks and management of non-native Impatiens species in the Netherlands http://repository.ubn.ru.nl/handle/2066/149286 (Radboud University, FLORON, Naturalis Biodiversity Center, 2015).Rewicz, A., Myśliwy, M., Adamowski, W., Podlasiński, M. & Bomanowska, A. Seed morphology and sculpture of invasive Impatiens capensis Meerb. from different habitats. PeerJ 8, e10156. https://doi.org/10.7717/peerj.10156 (2020).
    Google Scholar 
    Jakubska-Busse, A., Czeluśniak, I., Hojniak, M., Myśliwy, M. & Najberek, K. Chemical insect attractants produced by flowers of Impatiens spp. (Balsaminaceae) and list of floral visitors. Int. J. Mol. Sci. 24, 17259. https://doi.org/10.3390/ijms242417259 (2023).
    Google Scholar 
    Yu, S. X. et al. Phylogeny of Impatiens (Balsaminaceae): integrating molecular and morphological evidence into a new classification. Cladistics 32, 179–197. https://doi.org/10.1111/cla.12119 (2016).
    Google Scholar 
    Soó, R. & Priszter, S. A. Systematic and Geobotanical Synopsis of the Flora and Vegetation of Hungary: Phytogeography of Hungary and the Systematic Treatment and Ecological–Phytogeographical Characterization of Its Higher Organized (Vascular) Plants (Akadémiai Kiadó, 1996) [in Hungarian].Botta-Dukát, Z. & Balogh, L. The Most Important Invasive Plants in Hungary (Institute of Ecology and Botany Hungarian Academy of Sciences, 2008).Ellenberg, H. & Leuschner, C. Vegetation Mitteleuropas Mit Den Alpen: in ökologischer, Dynamischer Und Historischer Sicht (Neografia, 2010). [in German].Myśliwy, M. et al. Could alien impatiens capensis invade habitats of native I. noli-tangere in Europe? – Contrasting effects of microhabitat conditions on species growth and reproduction. NeoBiota 99, 171–200. https://doi.org/10.3897/neobiota.99.142196 (2025).
    Google Scholar 
    Grey-Wilson, C. Impatiens of Africa (CRC, 1980).Grey-Wilson, C. Hybridisation in African Impatiens. Studies in balsaminaceae. Kew. Bull. 34, 689–722. https://doi.org/10.2307/4119063 (1980b).
    Google Scholar 
    Janssens, S. B. et al. A total evidence approach using palynological characters to infer the complex evolutionary history of the Asian Impatiens (Balsaminaceae). Taxon 61, 355–367. https://doi.org/10.1002/tax.612007 (2012).
    Google Scholar 
    Rahman, F. et al. Palynological characterization and taxonomic delimitation of the genus Impatiens L. in Pakistan: an LM and SEM study. Microsc Res. Tech. 88, 2512–2527. https://doi.org/10.1002/jemt.24843 (2025).
    Google Scholar 
    Song, Y. X., Hu, T., Peng, S., Cong, Y. Y. & Hu, G. W. Palynological and macroscopic characters evidence infer the evolutionary history and insight into pollination adaptation in Impatiens (Balsaminaceae). J. Syst. Evol. 62, 403–420. https://doi.org/10.1111/jse.12959 (2024).
    Google Scholar 
    Janssens, S. et al. Palynological variation in balsaminoid Ericales. II. Balsaminaceae, Tetrameristaceae, Pellicieraceae and general conclusions. Ann. Bot. 96, 1061–1073. https://doi.org/10.1093/aob/mci257 (2005).
    Google Scholar 
    Pechimuthu, M., Arumugam, R. & Ponnusamy, S. Pollen morphology of the genus Impatiens L. (Balsaminaceae) and its systematic implications. Acta Biol. Szeged. 64, 207–219. https://doi.org/10.14232/abs.2020.2.207-219 (2020).
    Google Scholar 
    Janssens, S. B., Vinckier, S., Bosselaers, K., Smets, E. F. & Huysmans, S. Palynology of African Impatiens (Balsaminaceae). Palynol 43, 621–630. https://doi.org/10.1080/01916122.2018.1509149 (2018).
    Google Scholar 
    Cai XiuZhenCai, X. Z. et al. SEM observation on the pollen grains of ten species in Impatiens L. (Balsaminaceae). Bull. Bot. Res. 3, 279–283 (2007).
    Google Scholar 
    Halbritter, H., Heigl, H. & Auer, W. Impatiens parviflora. In PalDat – A Palynological Database. https://www.paldat.org/pub/Impatiens_parviflora/306261 (2021).Halbritter, H., Heigl, H. & Auer, W. Impatiens glandulifera. In PalDat – A Palynological Database. https://www.paldat.org/pub/Impatiens_glandulifera/306259 (2021).Huynh, K. L. Morphologie du pollen des Tropaeolacées et des Balsaminacées. I. Morphologie du pollen des Tropaeolacées. Grana 8, 88–184. https://doi.org/10.1080/00173136809427463 (1968).
    Google Scholar 
    Erdtman, G. Pollen Morphology and Plant Taxonomy (Hafner, 1971).He, H. et al. Studies on the characteristics of Impatiens pollen and its taxonomic significance from Yunnan-Guizhou Plateau. Preprint at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4254836 (2022).Wrońska-Pilarek, D. et al. How do pollen grains of Convallaria majalis L. Respond. Different Habitat Conditions? Diversity. 15, 501. https://doi.org/10.3390/d15040501 (2023).
    Google Scholar 
    Wiatrowska, B. et al. Intra-and interspecific pollen morphology variation of invasive Reynoutria taxa (Polygonaceae) in their response to different habitat conditions. NeoBiota 98, 61–92. https://doi.org/10.3897/neobiota.98.138657 (2025a).
    Google Scholar 
    Wiatrowska, B. et al. The effect of soil physicochemical properties on intraspecific variability of pollen morphology in Staphylea pinnata L. Sci. Rep. 15 https://doi.org/10.1038/s41598-025-14136-3 (2025).Khaleghi, E., Karamnezhad, F. & Moallemi, N. Study of pollen morphology and salinity effect on the pollen grains of four Olive (Olea europaea) cultivars. S Afr. J. Bot. 127, 51–57. https://doi.org/10.1016/j.sajb.2019.08.031 (2019).
    Google Scholar 
    Vasilevskaya, N. Pollution of the environment and pollen: A review. Stresses 2, 515–530. https://doi.org/10.3390/stresses2040035 (2022).
    Google Scholar 
    Mehmood, M., Tanveer, N. A., Joyia, F. A., Ullah, I. & Mohamed, H. I. Effect of high temperature on pollen grains and yield in economically important crops: a review. Planta 261, 141. https://doi.org/10.1007/s00425-025-04714-0 (2025).
    Google Scholar 
    Zając, A. & Zając, M. Distribution Atlas of Vascular Plants in Poland (Uniwersytet Jagielloński w Krakowie, 2001). [in Polish].Zając, A. & Zając, M. Distribution Atlas of Vascular Plants in Poland: Appendix (Uniwersytet Jagielloński w Krakowie, 2019) [in Polish].Wrońska-Pilarek, D., Jagodziński, A. M., Bocianowski, J. & Janyszek, M. The optimal sample size in pollen morphological studies using the example of Rosa canina L. Rosaceae. Palynol 39, 56–75. https://doi.org/10.1080/01916122.2014.933748 (2015).
    Google Scholar 
    Erdtman, G. Pollen Morphology and Plant Taxonomy. Angiosperms. An Introduction To Palynology (Almquist and Wiksell, 1952).Erdtman, G. The acetolysis method. A revised description. Sven Bot. Tidskr. 54, 561–564 (1960).
    Google Scholar 
    Punt, W., Hoen, P. P., Blackmore, S., Nilsson, S. & Le Thomas, A. Glossary of pollen and spore terminology. Rev. Palaeobot Palynol. 143, 1–81. https://doi.org/10.1016/j.revpalbo.2006.06.008 (2007).
    Google Scholar 
    Halbritter, H. et al. Illustrated Pollen Terminology. Second Edition (Springer, 2018).Sikorska, E. & Lasota, J. Typological habitat classification system and phytosociological habitat assessment. Studia I Materiały Centrum Edukacji Przyrodniczo-Leśnej. 9, 44–51 (2007). (in Polish).
    Google Scholar 
    Matuszkiewicz, W. Guide To Identifying Plant Communities in Poland (Wydawnictwo Naukowe PWN, 2022). [in Polish].Shapiro, S. S. & Wilk, M. B. An analysis of variance test for normality (complete samples). Biometrika 52, 591–611 https://doi.org/10.1093/biomet/52.3-4.591 (1965).Mahalanobis, P. C. On the generalized distance in statistics. Proc. Natl. Acad. Sci. India A. 12, 49–55 (1936). (1936).
    Google Scholar 
    Core Team, R. R: A Language and Environment for Statistical Computing (R. Core Team, 2025).Bigazzi, M. & Selvi, F. Pollen morphology in the Boragineae (Boraginaceae) in relation to the taxonomy of the tribe. Pl Syst. Evol. 213, 121–151. https://doi.org/10.1007/BF00988912 (1998).
    Google Scholar 
    Erdtman, G. Pollen Morphology and Plant Taxonomy 3rd edn (E.J. Brill, 1986).Tuler, A. C. et al. Taxonomic significance of pollen morphology for species delimitation in Psidium (Myrtaceae). Pl Syst. Evol. 303, 317–327. https://doi.org/10.1007/s00606-016-1373-8 (2017).
    Google Scholar 
    Grímsson, F., Grimm, G. W. & Zetter, R. Evolution of pollen morphology in Loranthaceae. Grana 57, 16–116. https://doi.org/10.1080/00173134.2016.1261939 (2018).
    Google Scholar 
    Rull, V. An updated review of fossil pollen evidence for the study of the origin, evolution and diversification of Caribbean mangroves. Plants. 12, 3852 https://doi.org/10.3390/plants12223852 (2023).Attique, R. et al. Pollen morphology of selected melliferous plants and its taxonomic implications using microscopy. Microsc Res. Tech. 85, 2361–2380. https://doi.org/10.1002/jemt.24091 (2022).
    Google Scholar 
    Stace, C. A. Plant Taxonomy and Biosystematics (Cambridge University Press, 1989).Wrońska–Pilarek, D. et al. The effect of herbicides on morphological features of pollen grains in Prunus serotina Ehrh. In the context of elimination of this Invasive species from European forests. Sci. Rep. 13, 4657. https://doi.org/10.1038/s41598-023-31010-2 (2023).
    Google Scholar 
    Wang, R. & Dobritsa, A. A. Exine and aperture patterns on the pollen surface: their formation and roles in plant reproduction. Annu. Plant. Rev. Online. 1, 1–40. https://doi.org/10.1002/9781119312994.apr0625 (2018).
    Google Scholar 
    Rejón, J. D. et al. The pollen coat proteome: At the cutting edge of plant reproduction. Proteome. 4, 5 https://doi.org/10.3390/proteomes4010005 (2016).Katifori, E., Alben, S., Cerda, E., Nelson, D. R. & Dumais, J. Foldable structures and the natural design of pollen grains. Proc. Natl. Acad. Sci. U.S.A. 107, 7635–7639 https://doi.org/10.1073/pnas.0911223107 (2010).Oorts, K. C. In Heavy Metals in Soils: Trace Metals and Metalloids in Soils and their Bioavailability, Environ. Pollut. (ed. Alloway B. J.) 22, 367–394 (2010).Matamoro-Vidal, A. et al. Links between morphology and function of the pollen wall: an experimental approach. Bot. J. Linn. Soc. 180, 478–490. https://doi.org/10.1111/boj.12378 (2016).
    Google Scholar 
    Lisci, M., Tanda, C. & Pacini, E. Pollination ecophysiology of Mercurialis annua L. (Euphorbiaceae), an anemophilous species flowering all year round. Ann. Bot. 74, 125–135. https://doi.org/10.1006/anbo.1994.1102 (1994).
    Google Scholar 
    Agarwala, S. C., Chatterjee, C., Sharma, P. N., Sharma, C. P. & Nautiyal, N. Pollen development in maize plants subjected to molybdenum deficiency. Can. J. Bot. 57, 1946–1950. https://doi.org/10.1139/b79-244 (1979).
    Google Scholar 
    Pandey, N., Gupta, M. & Sharma, C. P. Ultrastructural changes in pollen grains of green gram subjected to copper deficiency. Geophytology 25, 147–150 (1996).
    Google Scholar 
    Sancenón, V. et al. The Arabidopsis copper transporter COPT1 functions in root elongation and pollen development. J. Biol. Chem. 279, 15348–15355. https://doi.org/10.1074/jbc.M313321200 (2004).
    Google Scholar 
    Bertin, R. I. Paternity in plants. In Plant Reproductive Ecology. Patterns and Strategies (eds Doust, J. L. & Doust, L. L.) (Oxford University Press, 1988).Pyšek, P. & Prach, K. Invasion dynamics of Impatiens glandulifera—a century of spreading reconstructed. Biol. Conserv. 74, 41–48. https://doi.org/10.1016/0006-3207(95)00013-T (1995).
    Google Scholar 
    Follak, S. et al. Invasive alien plants along roadsides in Europe. EPPO Bull. 48, 256–4265. https://doi.org/10.1111/epp.12465 (2018).
    Google Scholar 
    Kostrakiewicz-Gieralt, K. The effect of habitat conditions on the abundance of populations and selected individual and floral traits of Impatiens glandulifera Royle. Biodiv Res. Conserv. 37, 15–22. https://doi.org/10.1515/biorc-2015-0002 (2015).
    Google Scholar 
    Pyšek, P. & Prach, K. Plant invasions and the role of riparian habitats a comparison of four species alien to central Europe. J. Biogeogr. 20, 413–420. https://doi.org/10.1007/978-1-4612-4018-1_23 (1993).
    Google Scholar 
    Hejda, M. & Pyšek, P. What is the impact of Impatiens glandulifera on species diversity of invaded riparian vegetation? Biol. Conserv. 123, 143–152. https://doi.org/10.1016/j.biocon.2006.03.025 (2006).
    Google Scholar 
    Download referencesFundingThe publication was financed by the Polish Minister of Science and Higher Education as part of the Strategy of the Poznań University of Life Sciences for 2024–2026 in the field of improving scientific research and development work in priority research areas and co-financed by the Minister of Science under the “Regional Excellence Initiative” Program for 2024–2027 (RID/SP/0045/2024/01) and statutory funds of the Institute of Marine and Environmental Sciences, University of Szczecin, Poland.Author informationAuthors and AffiliationsDepartment of Botany and Forest Habitats, Poznań University of Life Sciences, Wojska Polskiego 71d, 60-625, Poznań, PolandDorota Wrońska-Pilarek, Kacper Lechowicz & Blanka WiatrowskaDepartment of Mathematical and Statistical Methods, Poznań University of Life Sciences, Wojska Polskiego 28, 60-637, Poznań, PolandKonrad BanaśDepartment of Environmental Ecology, Institute of Marine and Environmental Sciences, University of Szczecin, Adama Mickiewicza 16, 70-383, Szczecin, PolandMonika MyśliwyInstitute of Biology, Biotechnology and Environmental Protection, Faculty of Natural Sciences, University of Silesia in Katowice, Jagiellońska 28, 40-032, Katowice, PolandBarbara Tokarska-GuzikWigry National Park, Krzywe 82, 16-402, Suwałki, PolandLech KrzysztofiakAuthorsDorota Wrońska-PilarekView author publicationsSearch author on:PubMed Google ScholarKacper LechowiczView author publicationsSearch author on:PubMed Google ScholarKonrad BanaśView author publicationsSearch author on:PubMed Google ScholarMonika MyśliwyView author publicationsSearch author on:PubMed Google ScholarBarbara Tokarska-GuzikView author publicationsSearch author on:PubMed Google ScholarLech KrzysztofiakView author publicationsSearch author on:PubMed Google ScholarBlanka WiatrowskaView author publicationsSearch author on:PubMed Google ScholarContributionsDWP: Writing – original draft, Writing – review & editing, Methodology, Investigation, Formal analysis, Data curation. KL: Writing – original draft, Writing – review & editing, Methodology, Investigation, Visualization, Data curation. KB: Writing – original draft, Methodology, Investigation, Software, Visualization, Formal analysis, Data curation. MM: Investigation, Writing – original draft, Writing – review & editing, Data curation. BT-G: Investigation, Writing – original draft, Data curation. LK: Data curation. B.W: Conceptualization, Writing – original draft, Writing – review & editing, Methodology, Investigation, Formal analysis, Data curation.Corresponding authorCorrespondence to
    Dorota Wrońska-Pilarek.Ethics declarations

    Competing interests
    The authors declare no competing interests.

    Additional informationPublisher’s noteSpringer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Supplementary InformationBelow is the link to the electronic supplementary material.Supplementary Material 1Rights and permissions
    Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
    Reprints and permissionsAbout this articleCite this articleWrońska-Pilarek, D., Lechowicz, K., Banaś, K. et al. Pollen morphology of three invasive Impatiens species in Europe under varying habitat conditions—a case study from Poland.
    Sci Rep (2025). https://doi.org/10.1038/s41598-025-32427-7Download citationReceived: 17 September 2025Accepted: 10 December 2025Published: 13 December 2025DOI: https://doi.org/10.1038/s41598-025-32427-7Share this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy shareable link to clipboard
    Provided by the Springer Nature SharedIt content-sharing initiative
    Keywords
    Impatiens parviflora

    I. glandulifera

    I. capensis
    Invasive alien speciesPollen morphologyPollen sizeP/EHabitat conditions More

  • in

    Episodic-like memory in a simulation of cuttlefish behavior

    AbstractEpisodic memory involves remembering the what, when, and where components of an event. It has been observed in humans, other vertebrates, and the invertebrate cuttlefish. In clever behavioral experiments, cuttlefish have been shown to have episodic-like memory, where they demonstrate the ability to remember when and where a preferred food source will appear. The present work replicates this behavior with a parsimonious model of episodic memory. To further test this model and explore episodic-like memory, we introduce a predator-prey scenario in which the agent must remember what creatures (e.g. predator, desirable prey, or less desirable prey) appear at a given time and region of the model environment. This simulates similar situations that cuttlefish face in the wild. They will typically hide when predators are in the area, and hunt for prey when available. When the memory model is queried for an action (e.g., hunt or hide), the cuttlefish agent hunts for preferred food, like shrimp, when available, and hides at other times when a predator appears. When the memory model is queried for a place, the cuttlefish agent acts opportunistically, seeking less-preferred food (e.g., crabs) if it is located farther from a predator. These differences show how behavior can be altered depending on how memory is accessed. Querying the model over time might mimic mental time travel, a hallmark of episodic memory. Although developed with cuttlefish in mind, the model shares similarities with the hippocampal indexing theory and captures aspects of vertebrate episodic memory. This suggests that the underlying mechanisms supporting episodic-like behavior in the present model may be an example of convergent cognitive evolution.

    Data availability

    The source code for these simulations is written in Python and publicly available at: https://github.com/jkrichma/EpisodicLikeMemoryModel.git
    ReferencesTulving, E. Episodic memory: From mind to brain. Annual Rev. Psychol. 53, 1–25 (2002).
    Google Scholar 
    Davies, J. R. & Clayton, N. S. Is episodic-like memory like episodic memory?. Philosophical Trans. R. Soc. B: Biol. Sci. 379, 20230397. https://doi.org/10.1098/rstb.2023.0397 (2024).
    Google Scholar 
    Clayton, N. S. & Dickinson, A. Episodic-like memory during cache recovery by scrub jays. Nature 395, 272–274 (1998).
    Google Scholar 
    Jozet-Alves, C., Bertin, M. & Clayton, N. S. Evidence of episodic-like memory in cuttlefish. Curr. Biol. 23, R1033-5 (2013).
    Google Scholar 
    Schnell, A. K., Clayton, N. S., Hanlon, R. T. & Jozet-Alves, C. Episodic-like memory is preserved with age in cuttlefish. Proc. R. Soc. B: Biol. Sci. 288, 20211052. https://doi.org/10.1098/rspb.2021.1052 (2021).
    Google Scholar 
    Poncet, L., Desnous, C., Bellanger, C. & Jozet-Alves, C. Unruly octopuses are the rule: Octopus vulgaris use multiple and individually variable strategies in an episodic-like memory task. J. Exp. Biol. 225, jeb244234 (2022).Schnell, A. K., Boeckle, M., Rivera, M., Clayton, N. S. & Hanlon, R. T. Cuttlefish exert self-control in a delay of gratification task. Proc. Ro. Soc. B: Biol. Sci. 288, 20203161 (2021).
    Google Scholar 
    Hanlon, R. T. & Messenger, J. B. Cephalopod Behaviour (Cambridge University Press, 2018), second edn.Nixon, M. & Young, J. Z. The Brains and Lives of Cephalopods (Oxford University Press, 2003).Shomrat, T., Turchetti-Maia, A. L., Stern-Mentch, N., Basil, J. A. & Hochner, B. The vertical lobe of cephalopods: an attractive brain structure for understanding the evolution of advanced learning and memory systems. J. Comp. Physiol. A Neuroethol. Sens. Neural. Behav. Physiol. 201, 947–56 (2015).
    Google Scholar 
    Young, J. Z. Computation in the learning system of cephalopods. Biol. Bull. 180, 200–208 (1991).
    Google Scholar 
    Shomrat, T. et al. Alternative sites of synaptic plasticity in two homologous “fan-out fan-in’’ learning and memory networks. Curr. Biol. 21, 1773–82 (2011).
    Google Scholar 
    Teyler, T. J. & DiScenna, P. The hippocampal memory indexing theory. Behavioral Neurosci. 100, 147–154 (1986).
    Google Scholar 
    Teyler, T. J. & Rudy, J. W. The hippocampal indexing theory and episodic memory: Updating the index. Hippocampus 17, 1158–1169 (2007).
    Google Scholar 
    Kolibius, L. D. et al. Hippocampal neurons code individual episodic memories in humans. Nat. Hum. Behaviour 7, 1968–1979 (2023).
    Google Scholar 
    Hopfield, J. J. & Tank, D. W. “neural’’ computation of decisions in optimization problems. Biol. Cybern. 52, 141–152 (1985).
    Google Scholar 
    Krotov, D. & Hopfield, J. J. Dense associative memory for pattern recognition. In Lee, D., Sugiyama, M., Luxburg, U., Guyon, I. & Garnett, R. (eds.) Advances in Neural Information Processing Systems, 29 (Curran Associates, Inc., 2016).Pfeiffer, M. A. et al. Cuttlebot: Emulating cuttlefish behavior and intelligence in a novel robot design. In Brock, O. & Krichmar, J. (eds.) From Animals to Animats 17, 93–105 (Springer Nature Switzerland, 2025).Birch, J., Schnell, A. K. & Clayton, N. S. Dimensions of animal consciousness. Trends Cognit. Sci. 24, 789–801 (2020).
    Google Scholar 
    Banino, A. et al. Vector-based navigation using grid-like representations in artificial agents. Nature 557, 429–433 (2018).
    Google Scholar 
    Espino, H., Bain, R. & Krichmar, J. L. A rapid adapting and continual learning spiking neural network path planning algorithm for mobile robots. IEEE Robot. Autom. Lett. 9, 9542–9549 (2024).
    Google Scholar 
    Foster, D. J., Morris, R. G. & Dayan, P. A model of hippocampally dependent navigation, using the temporal difference learning rule. Hippocampus 10, 1–16 (2000).
    Google Scholar 
    Stachenfeld, K. L., Botvinick, M. M. & Gershman, S. J. The hippocampus as a predictive map. Nat. Neurosci. 20, 1643–1653 (2017).
    Google Scholar 
    Eichenbaum, H. Time cells in the hippocampus: a new dimension for mapping memories. Nat. Rev. Neurosci. 15, 732–744. (2014).https://doi.org/10.1038/nrn3827https://www.nature.com/453 articles/nrn3827.pdf.Umbach, G. et al. Time cells in the human hippocampus and entorhinal cortex support episodic memory. Proc. Nat. Acad. Sci. 117, 28463–28474 (2020).Matell, M. S. & Meck, W. H. Cortico-striatal circuits and interval timing: coincidence detection of oscillatory processes. Cognit. Brain Res. 21, 139–170 (2004).
    Google Scholar 
    Aimone, J. B. Computational modeling of adult neurogenesis. Cold Spring Harb. Perspect Biol. 8, a018960 (2016).
    Google Scholar 
    Aimone, J. B., Deng, W. & Gage, F. H. Adult neurogenesis: integrating theories and separating functions. Trends Cogn. Sci. 14, 325–37 (2010).
    Google Scholar 
    Chung, W.-S., López-Galán, A., Kurniawan, N. D. & Marshall, N. J. The brain structure and the neural network features of the diurnal cuttlefish sepia plangon. iScience 26, 105846 (2023).Park, J. S. et al. Generative agents: Interactive simulacra of human behavior. In Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology, UIST ’23 (Association for Computing Machinery, New York, NY, USA, 2023). https://doi.org/10.1145/3586183.3606763.Rolls, E. T. & Treves, A. A theory of hippocampal function: New developments. Prog. Neurobiol. 238, 102636 (2024).
    Google Scholar 
    Sanchez-Aguilera, A. et al. An update to hippocampome.org by integrating single-cell phenotypes with circuit function in vivo. PLoS Biol. 19, e3001213 (2021).Treves, A. & Rolls, E. T. Computational constraints suggest the need for two distinct input systems to the hippocampal ca3 network. Hippocampus 2, 189–99 (1992).
    Google Scholar 
    Kolibius, L. D., Josselyn, S. A. & Hanslmayr, S. And yet, the hippocampus codes conjunctively. Trends Cognit. Sci. 29, 689–690. https://doi.org/10.1016/j.tics.2025.06.013 (2025).
    Google Scholar 
    Kolibius, L. D., Josselyn, S. A. & Hanslmayr, S. On the origin of memory neurons in the human hippocampus. Trends Cognit. Sci. 29, 421–433 (2025).
    Google Scholar 
    Quian Quiroga, R. Conjunctive or context-invariant coding in the human hippocampus?. Trends in Cognitive Sciences 29, 687–688. https://doi.org/10.1016/j.tics.2025.05.006 (2025).
    Google Scholar 
    George, D. et al. Clone-structured graph representations enable flexible learning and vicarious evaluation of cognitive maps. Nat. Commun. 12, 2392 (2021).
    Google Scholar 
    Byrne, P., Becker, S. & Burgess, N. Remembering the past and imagining the future: a neural model of spatial memory and imagery. Psychol. Rev. 114, 340 (2007).
    Google Scholar 
    Whittington, J. C. et al. The tolman-eichenbaum machine: unifying space and relational memory through generalization in the hippocampal formation. Cell 183, 1249–1263 (2020).
    Google Scholar 
    Brea, J., Clayton, N. S. & Gerstner, W. Computational models of episodic-like memory in food-caching birds. Nat. Commun. 14, 2979 (2023).
    Google Scholar 
    Alonso, N. & Krichmar, J. L. A sparse quantized hopfield network for online-continual memory. Nat. Commun. 15, 3722 (2024).
    Google Scholar 
    Molom-Ochir, T., Taylor, B., Li, H. & Chen, Y. R. Advancements in content-addressable memory (cam) circuits: State-of-the-art, applications, and future directions in the ai domain. Ieee Trans. Circuits Syst. I-Regular Papers 72, 3971–3982 (2025).
    Google Scholar 
    Hwu, T. & Krichmar, J. Neurorobotics: Connecting the Brain, Body and Environment (MIT Press, Cambridge, MA, 2022).
    Google Scholar 
    Krichmar, J. L. & Hwu, T. J. Design principles for neurorobotics. Front. Neurorobot. 16 (2022).Marr, D. Vision: A Computational Investigation into the Human Representation and Processing of Visual Information (W.H. Freeman, San Francisco, CA, 1982).
    Google Scholar 
    Download referencesAcknowledgementsThe authors would like to thank members of the CuttleBot team for many valuable discussions. The authors would also like to thank Professor Nicola Clayton for valuable comments on an earlier version of the manuscript.FundingThe CuttleBot team was supported by the UC Irvine California Institute for Telecommunications and Information Technology (CALIT2) in collaboration with the UC Irvine Undergraduate Research Opportunities Program (UROP). J.K. was supported in part by National Institute of Neurological Disorders and Stroke award R01 NS135850-02.Author informationAuthors and AffiliationsDepartment of Cognitive Sciences, University of California, Irvine, CA, 92697-5100, USASriskandha Kandimalla, Qian Ying Wong & Jeffrey L. KrichmarDepartment of Computer Science, University of California, Irvine, CA, 92697-7085, USAKary Zheng & Jeffrey L. KrichmarAuthorsSriskandha KandimallaView author publicationsSearch author on:PubMed Google ScholarQian Ying WongView author publicationsSearch author on:PubMed Google ScholarKary ZhengView author publicationsSearch author on:PubMed Google ScholarJeffrey L. KrichmarView author publicationsSearch author on:PubMed Google ScholarContributionsS.K., Q.W., and J.K. designed the experiment. Q.W., K.Z. and J.K. implemented the model. All authors analyzed the results. All authors wrote the manuscript. All authors reviewed the manuscript.Corresponding authorCorrespondence to
    Jeffrey L. Krichmar.Ethics declarations

    Competing interests
    The authors declare no competing interests.

    Additional informationPublisher’s noteSpringer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Rights and permissions
    Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
    Reprints and permissionsAbout this articleCite this articleKandimalla, S., Wong, Q.Y., Zheng, K. et al. Episodic-like memory in a simulation of cuttlefish behavior.
    Sci Rep (2025). https://doi.org/10.1038/s41598-025-31950-xDownload citationReceived: 30 October 2025Accepted: 05 December 2025Published: 13 December 2025DOI: https://doi.org/10.1038/s41598-025-31950-xShare this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy shareable link to clipboard
    Provided by the Springer Nature SharedIt content-sharing initiative More

  • in

    Short-chain fatty acids mediate interactions between immune responses and commensal bacteria in high altitude yaks

    AbstractThe complex interplay between host and commensal gut microbiota affects the major biological functions such as metabolism and stress adaptation, and displays pronounced seasonality in mammals. However, the seasonal dynamic patterns of immune responses and microbiota, and their interactions remain uncertain in animals inhabiting extreme environments. We analyzed monthly hormones, immunoglobulins and fecal microbiota from yaks grazing on the Tibetan plateau. Clear seasonal patterns were observed: glucocorticoid levels peaked in the cold season, while concentrations of IgA, IgG, IgM, and short-chain fatty acids (SCFAs) increased during the warm season. Yak fecal microbiota also fluctuated seasonally, with lowest diversity in the warm season but accompanied by an enrichment of Firmicutes and Actinobacteria. Taxa such as Alistipes, Bacteroides, Romboutsia and Arthrobacter contributed to seasonal shifts in the levels of SCFAs and immunoglobulins. These results indicate that yaks synchronize peak immune activation and energy production with the nutrient-rich warm season, suggesting a role for microbiome plasticity in driving immune flexibility for high-altitude animals.

    Data availability

    Raw data generated or analyzed during this study are included in this published article (and its supplementary information files). 16S rRNA gene sequencing raw data are deposited in the dryad database at http://datadryad.org/stash/share/lwsE1wTCwixFVpOgtytCDENrx3hgvxJmOTKSkpzqslo.
    Code availability

    The R code used to generate the main results of this study is available publicly on Zenodo (https://doi.org/10.5281/zenodo.17622103)75.
    ReferencesAlexander, M. & Turnbaugh, P. J. Deconstructing mechanisms of diet-microbiome-immune interactions. Immunity 53, 264–276 (2020).
    Google Scholar 
    Ansaldo, E., Farley, T. K. & Belkaid, Y. Control of immunity by the microbiota. Annu. Rev. Immunol. 39, 449–479 (2021).
    Google Scholar 
    Penny, H. A. et al. Rhythmicity of intestinal IgA responses confers oscillatory commensal microbiota mutualism. Sci. Immunol. 7, eabk2541 (2022).
    Google Scholar 
    Couch, C. E. et al. Diet and gut microbiome enterotype are associated at the population level in African buffalo. Nat. Commun. 12, 2267 (2021).
    Google Scholar 
    Baniel, A. et al. Seasonal shifts in the gut microbiome indicate plastic responses to diet in wild geladas. Microbiome 9, 26 (2021).
    Google Scholar 
    Kartzinel, T. R. et al. Covariation of diet and gut microbiome in African megafauna. Proc. Natl. Acad. Sci. USA. 116, 23588–23593 (2019).
    Google Scholar 
    Graham, A. L. Naturalizing mouse models for immunology. Nat. Immuno. 22, 111–117 (2021).
    Google Scholar 
    Guo, N. et al. Seasonal dynamics of diet-gut microbiota interaction in adaptation of yaks to life at high altitude. npj Biofilms Microbi 7, 38 (2021).
    Google Scholar 
    Li, H. et al. Mucosal or systemic microbiota exposures shape the B cell repertoire. Nature 584, 273–278 (2020).
    Google Scholar 
    Sonnenburg, E. D. & Justin, L. Starving our microbial self: the deleterious consequences of a diet deficient in microbiota-accessible carbohydrates. Cell Metab 20, 779–786 (2014).
    Google Scholar 
    Takeuchi, T. et al. Acetate differentially regulates IgA reactivity to commensal bacteria. Nature 595, 560–564 (2021).
    Google Scholar 
    Lavelle, A. & Sokol, H. Gut microbiota-derived metabolites as key actors in inflammatory bowel disease. Nat. Rev. Gastroenterol. Hepatol. 17, 223–237 (2020).
    Google Scholar 
    Mann, E. R., Lam, Y. K. & Uhlig, H. H. Short-chain fatty acids: linking diet, the microbiome and immunity. Nat. Rev. Immunol. 24, 577–595 (2024).
    Google Scholar 
    Sun, M., Wu, W., Liu, Z. & Cong, Y. Microbiota metabolite short-chain fatty acids, GPCR, and inflammatory bowel diseases. J. Gastroenterol. 52, 1–8 (2017).
    Google Scholar 
    Thomas, S. P. & Denu, J. M. Short-chain fatty acids activate acetyltransferase p300. eLife 10, e72171 (2021).
    Google Scholar 
    Nabhani, Z. A. et al. A weaning reaction to microbiota is required for resistance to immunopathologies in the adult. Immunity 50, 1276–1288 (2019).
    Google Scholar 
    Luck, H. et al. Gut-associated IgA (+) immune cells regulate obesity-related insulin resistance. Nat. Commun. 10, 3650 (2019).
    Google Scholar 
    Nagai, M. et al. Fasting-refeeding impacts immune cell dynamics and mucosal immune responses. Cell 178, 1072–1087 (2019).
    Google Scholar 
    Huus, K. E., Petersen, C. & Finlay, B. B. Diversity and dynamism of IgA-microbiota interactions. Nat. Rev. Immunol. 21, 514–525 (2021).
    Google Scholar 
    Metrione, L. C., Hunter, D. & Penfold, L. M. Seasonal changes in fecal glucocorticoid metabolite concentrations in Bison (Bison bison) living with or without wolves (Canis lupus). J. Wildlife Dis. 56, 175–178 (2020).
    Google Scholar 
    Place, N. J. & Kenagy, G. J. Seasonal changes in plasma testosterone and glucocorticosteroids in free-living male yellow-pine chipmunks and the response to capture and handling. J. Comp. Physiol. B. 170, 245–251 (2000).
    Google Scholar 
    Boswell, T., Woods, S. & Kenagy, G. J. Seasonal changes in body mass, insulin, and glucocorticoids of free-living golden-mantled ground squirrels. Gen. Comp. Endocr 96, 339–346 (1994).
    Google Scholar 
    Crespi, E. J., Williams, T. D., Jessop, T. S. & Delehanty, B. Life history and the ecology of stress: how do glucocorticoid hormones influence life-history variation in animals?. Funct. Ecol. 27, 93–106 (2013).
    Google Scholar 
    Tendler, A. et al. Hormone seasonality in medical records suggests circannual endocrine circuits. Proc. Natl. Acad. Sci. USA 2118, e2003926118 (2021).
    Google Scholar 
    Crill Matzke, C., Kusch, J. M., Janz, D. M. & Lane, J. E. Perceived predation risk predicts glucocorticoid hormones, but not reproductive success in a colonial rodent. Horm. Behav. 143, 105200 (2022).
    Google Scholar 
    Romero, M. L. et al. Seasonal glucocorticoid responses to capture in wild free-living mammals. Am. J. Physiol-Reg. I 294, 614–622 (2008).
    Google Scholar 
    Charbonnel, N. et al. Stress and Demographic Decline: A potential effect mediated by impairment of reproduction and immune function in cyclic vole populations. Physiol. Biochem. Zool. 81, 63–73 (2008).
    Google Scholar 
    Christopherson, R. J., Hudson, R. J. & Richmond, R. J. Comparative winter bioenergetics of American bison, yak, Scottish highland and Hereford calves. Acta Theriol 23, 49–54 (1978).
    Google Scholar 
    Peterson, D. A., McNulty, N. P., Guruge, J. L. & Gordon, J. I. IgA response to symbiotic bacteria as a mediator of gut homeostasis. Cell Host Microbe 2, 328–339 (2007).
    Google Scholar 
    Yawoot, N., Govitrapong, P., Tocharus, C. & Tocharus, J. Ischemic stroke, obesity, and the anti-inflammatory role of melatonin. BioFactors 47, 41–58 (2021).
    Google Scholar 
    Wang, X. T. et al. Gut microbiota-derived metabolites mediate the neuroprotective effect of melatonin in cognitive impairment induced by sleep deprivation. Microbiome 11, 17 (2023).
    Google Scholar 
    Zhang, B. et al. Gut microbiota dysbiosis induced by decreasing endogenous melatonin mediates the pathogenesis of Alzheimer’s disease and obesity. Front. Immunol. 13, 900132 (2022).
    Google Scholar 
    Wu, Y. L. et al. Melatonin alleviates titanium nanoparticles induced osteolysis via activation of butyrate/GPR109A signaling pathway. J. Nanobiotechnol. 19, 170 (2021).
    Google Scholar 
    Kim, M., Qie, Y. Q., Park, J. & Kim, C. H. Gut microbial metabolites fuel host antibody responses. Cell Host Microbe 20, 202–214 (2016).
    Google Scholar 
    Bjork, J. R. et al. Synchrony and idiosyncrasy in the gut microbiome of wild baboons. Nat. Ecol. Evol. 6, 955–964 (2022).
    Google Scholar 
    Long, R. J., Apori, S. O., Castroc, F. B. & Ørskov, E. R. Feed value of native forages of the Tibetan Plateau of China. Anim. Feed Sci. Technol. 80, 101–113 (1999).
    Google Scholar 
    Ley, R. E. et al. Evolution of mammals and their gut microbes. Science 320, 1647–1651 (2008).
    Google Scholar 
    Bensch, H. M., Tolf, C., Waldenström, J., Lundin, D. & Zöttl, M. Bacteroidetes to Firmicutes: captivity changes the gut microbiota composition and diversity in a social subterranean rodent. Animal Microbiome 5, 9 (2023).
    Google Scholar 
    Eckburg, P. B. et al. Diversity of the human intestinal microbial flora. Science 308, 1635–1638 (2005).
    Google Scholar 
    Sommer, F. et al. The gut microbiota modulates energy metabolism in the hibernating brown bear Ursus arctos. Cell Reports 14, 1655–1661 (2016).
    Google Scholar 
    Springer, A. et al. Patterns of seasonality and group membership characterize the gut microbiota in a longitudinal study of wild Verreaux’s sifakas (Propithecus verreauxi). Ecol. Evol. 7, 5732–5745 (2017).
    Google Scholar 
    Staudacher, H. M. et al. Fermentable carbohydrate restriction reduces luminal bifidobacterial and gastrointestinal symptoms in patients with irritable bowel syndrome. Nutr. J. 142, 1510–1518 (2012).
    Google Scholar 
    Turnbaugh, P. J., Backhed, F., Fulton, L. & Gordon, J. I. Diet induced obesity is linked to marked but reversible alterations in the mouse distal gut microbiome. Cell Host Microbe 3, 213–223 (2008).
    Google Scholar 
    Wu, G. D. et al. Linking long-term dietary patterns with gut microbial enterotypes. Science 334, 105–105 (2011).
    Google Scholar 
    Binda, C. et al. Actinobacteria: A relevant minority for the maintenance of gut homeostasis. Digest. Liver Dis. 50, 421–428 (2018).
    Google Scholar 
    Lyons, A. et al. Bacterial strain-specific induction of Foxp3+ T regulatory cells is protective in murine allergy models. Clin. Exp. Allergy. 40, 811–819 (2010).
    Google Scholar 
    Wexler, H. M. & Goodman, A. L. An insider’s perspective: Bacteroides as a window into the microbiome. Nat. Microbiol. 2, 17026 (2017).
    Google Scholar 
    Kokou, F. et al. Core gut microbial communities are maintained by beneficial interactions and strain variability in fish. Nat. Microbiol. 4, 2456–2465 (2019).
    Google Scholar 
    Ding, L. M. & Long, R. J. The use of herbage n-alkanes as markers to estimate the diet composition of yaks on the Qinghai-Tibetan Plateau. Asian-Aust. J. Anim. Sci. 23, 61–67 (2010).
    Google Scholar 
    Kubinak, J. L. & Round, J. L. Do antibodies select a healthy microbiota?. Nat. Rev. Immunol. 16, 767–774 (2016).
    Google Scholar 
    Sutherland, D. B., Suzuki, K. & Fagarasan, S. Fostering of advanced mutualism with gut microbiota by Immunoglobulin A. Immunol. Rev. 270, 20–31 (2016).
    Google Scholar 
    Donaldson, G. P. et al. Gut microbiota utilize immunoglobulin A for mucosal colonization. Science 360, 795–800 (2018).
    Google Scholar 
    Ruff, W. E., Greiling, T. M. & Kriegel, M. A. Host-microbiota interactions in immune-mediated diseases. Nat. Rev. Microbiol. 18, 521–538 (2020).
    Google Scholar 
    Arpaia, N. et al. Metabolites produced by commensal bacteria promote peripheral regulatory T-cell generation. Nature 504, 451–455 (2013).
    Google Scholar 
    Trompette, A. et al. Gut microbiota metabolism of dietary fiber influences allergic airway disease and hematopoiesis. Nat. Med. 20, 159–166 (2014).
    Google Scholar 
    Zhao, H. et al. Meta-analysis identifying gut microbial biomarkers of Qinghai-Tibet Plateau populations and the functionality of microbiota-derived butyrate in high-altitude adaptation. Gut Microbes 16, 2350151 (2024).
    Google Scholar 
    Jing, X. P. et al. Tibetan sheep have a high capacity to absorb and to regulate metabolism of SCFA in the rumen epithelium to adapt to low energy intake. Br. J. Nutr. 123, 721–731 (2020).
    Google Scholar 
    Li, H. et al. Diet simplification selects for high gut microbial diversity and strong fermenting ability in high-altitude pikas. Appl. Microbiol. Biotechnol. 102, 6739–6751 (2018).
    Google Scholar 
    Paramastri, Y. et al. Urinary and fecal immunoglobulin A, cortisol and dioxoandrostanes, and serum cortisol in metabolic cage housed female cynomolgus monkeys (Macaca fascicularis). J. Med. Primatol. 36, 355–364 (2007).
    Google Scholar 
    Reese, A. T. & Kearney, S. M. Incorporating functional trade-offs into studies of the gut microbiota. Curr. Opin. Microbiol. 50, 20–27 (2019).
    Google Scholar 
    Vijendravarma, R. K. et al. Gut physiology mediates a trade-off between adaptation to malnutrition and susceptibility to food-borne pathogens. Ecol. Lett. 18, 1078–1086 (2015).
    Google Scholar 
    Congiu, M. et al. Predicting feed efficiency of Angus steers using the gastrointestinal microbiome. Animal 18, 101102 (2024).
    Google Scholar 
    Mendes, L. W. et al. Taxonomy and functional diversity in the fecal microbiome of beef cattle reared in Brazilian traditional and semi-intensive production systems. Front. Microbiol. 12, 768480 (2021).
    Google Scholar 
    Myer, P. R., Freetly, H. C., Wells, J. E., Smith, T. P. L. & Kuehn, L. A. Analysis of the gut bacterial communities in beef cattle and their association with feed intake, growth, and efficiency. J. Anim. Sci. 95, 3215–3224 (2017).
    Google Scholar 
    von der Ohe, C. G. & Servheen, C. Measuring stress in mammals using fecal glucocorticoids: opportunities and challenges. Wildlife Soc. B. 30, 1215–1225 (2002).
    Google Scholar 
    Burgener, N., Gusset, M. & Schmid, H. Frustrated appetitive foraging behavior, stereotypic pacing, and fecal glucocorticoid levels in Snow Leopards (Uncia uncia) in the Zurich Zoo. J. Appl. Anim. Welf. Sci. 11, 74–83 (2008).
    Google Scholar 
    Crill, C. et al. Investigation of the utility of feces and hair as non-invasive measures of glucocorticoids in wild black-tailed prairie dogs (Cynomys ludovicianus). Gen. Comp. Endocrinol. 275, 15–24 (2019).
    Google Scholar 
    Zhang, Z. G. et al. Convergent evolution of rumen microbiomes in high-altitude mammals. Curr. Biol. 26, 1873–1879 (2016).
    Google Scholar 
    Takahashi, S. et al. Development of a prokaryotic universal primer for simultaneous analysis of Bacteria and Archaea using next-generation sequencing. PLoS ONE 9, e105592 (2014).
    Google Scholar 
    Bolyen, E. et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. 37, 852–857 (2019).
    Google Scholar 
    Oksanen, J. et al. Vegan: community ecology package. R Package Version 1.17-4 (2006).De Caceres, M. & Pierre, L. Associations between species and groups of sites: Indices and statistical inference. Ecology 90, 3566–3574 (2009).
    Google Scholar 
    Sang, J. N. et al. Convergent and divergent age patterning of gut microbiota diversity in humans and nonhuman primates. mSystems 7, e01512-21 (2022).
    Google Scholar 
    Otasek, D. et al. Cytoscape automation: empowering workflow-based network analysis. Genome Biol 20, 185 (2019).
    Google Scholar 
    Guo, N. et al. Short-chain fatty acids mediate interactions between immune responses and commensal bacteria in high altitude yaks. [Dataset and Code] Zenodo https://doi.org/10.5281/zenodo.17622103 (2025).Download referencesAcknowledgementsThis work was supported by the Second Tibetan Plateau Expedition (2019QZKK0302), the Natural Science Foundation of China (U21A20183; 32471581; 32102498), the Science-based Advisory Program of The Alliance of National and International Science Organizations for the Belt and Road Regions (ANSO-SBA-2023-02), Natural Science Foundation Youth Program of Shandong Province (ZR2024QC346), the State Key Laboratory of Hulless Barley and Yak Germplasm Resources and Genetic Improvement (XZNKY-CZ-2022-016-10), and the Open Project of Qinghai Key Laboratory of Adaptive Management of Alpine Grasslands (2023-GHSYS-KF-02).Author informationAuthor notesThese authors contributed equally: Na Guo, Nana Gou, Fuyu Shi.Authors and AffiliationsState Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, College of Ecology, Lanzhou University, Lanzhou, ChinaNa Guo, Nana Gou, Fuyu Shi, Wenyin Wang, Shanshan Li, Sisi Bi, Jianxin Jiao, Binyu Luo, Mei Huang & Zhanhuan ShangSchool of Life Sciences, Shandong University, Qingdao, ChinaNa Guo & Fuyu ShiDesert Animal Adaptations and Husbandry, Wyler Department of Dryland Agriculture, Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Beer Sheva, IsraelA. Allan DegenAuthorsNa GuoView author publicationsSearch author on:PubMed Google ScholarNana GouView author publicationsSearch author on:PubMed Google ScholarFuyu ShiView author publicationsSearch author on:PubMed Google ScholarWenyin WangView author publicationsSearch author on:PubMed Google ScholarShanshan LiView author publicationsSearch author on:PubMed Google ScholarSisi BiView author publicationsSearch author on:PubMed Google ScholarJianxin JiaoView author publicationsSearch author on:PubMed Google ScholarBinyu LuoView author publicationsSearch author on:PubMed Google ScholarMei HuangView author publicationsSearch author on:PubMed Google ScholarA. Allan DegenView author publicationsSearch author on:PubMed Google ScholarZhanhuan ShangView author publicationsSearch author on:PubMed Google ScholarContributionsN.G, N.N.G and F.Y.S collected field data and samples; N.G and F.Y.S analyzed the data; N.N.G and F.Y.S analyzed samples; W.Y.W, S.S.L, S.S.B, J.X.J, B.Y.L and M.H assisted with the field work; N.G wrote the first draft; A.A.D and Z.H.S contributed to interpretation of data and writing the manuscript; and Z.H.S designed and supported the study. All authors contributed to the final version of the manuscript.Corresponding authorsCorrespondence to
    A. Allan Degen or Zhanhuan Shang.Ethics declarations

    Competing interests
    The authors declare no competing interests.

    Peer review

    Peer review information
    Communications Biology thanks Richard Nyamota, Hongfang Wang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editors: Silvio Waschina and Mengtan Xing.

    Additional informationPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Supplementary informationSupplementary informationReporting-summaryRights and permissions
    Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
    Reprints and permissionsAbout this articleCite this articleGuo, N., Gou, N., Shi, F. et al. Short-chain fatty acids mediate interactions between immune responses and commensal bacteria in high altitude yaks.
    Commun Biol (2025). https://doi.org/10.1038/s42003-025-09351-7Download citationReceived: 09 April 2025Accepted: 01 December 2025Published: 13 December 2025DOI: https://doi.org/10.1038/s42003-025-09351-7Share this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy shareable link to clipboard
    Provided by the Springer Nature SharedIt content-sharing initiative More

  • in

    Breeding male mole-rats (Fukomys) use strong bites to defend reproductive monopoly

    AbstractBite force is a simple trait indicating an animal’s performance related to foraging, social dominance, and defence, all of which influence individual reproductive success. We examine the effect of breeding status on bite force in four social species of Fukomys, a genus of subterranean African rodents (Bathyergidae). These species are cooperative breeders, where reproduction is limited typically to a breeding pair. We collected in vivo bite force data, head width, and upper incisors width from 404 individuals from 75 families and tested whether breeders exhibit stronger bite force. We reveal that breeding males of all four species outperform non-breeders, with bite force in non-breeding males and females being 12% and 22% lower, respectively. In contrast, breeding females underperform relative to other categories, with bite force approximately 31% lower than in breeding males, and many are reluctant to bite. Head width and upper incisors width corroborate these findings. We propose that breeding males require a stronger bite force because of repeated competition with non-related males that may try to enter the family. In contrast, there is much less competition for the breeding position among females, as females rarely intrude into established families.

    Data availability

    The raw data (Supplementary Data 1 and Supplementary Data 2) used to calculate the results and generate the figures presented in this study are available in the Figshare repository, as part of this record: https://doi.org/10.6084/m9.figshare.2942328898.
    Code availability

    The R code (Supplementary Data 3) used to calculate the results and generate the figures presented in this study is available in the Figshare repository, as part of this record: https://doi.org/10.6084/m9.figshare.2942328898.
    ReferencesPalanza, P., Mainardi, D., Brain, P. F. & Parmigiani, S. Male and female competitive strategies of wild house mice pairs (Mus musculus domesticus) confronted with intruders of different sex and age in artificial territories. Behaviour 133, 863–882 (1996).
    Google Scholar 
    Packer, C. & Pusey, A. E. Adaptations of female lions to infanticide by incoming males. Am. Nat. 121, 716–728 (1983).Clutton-Brock, T. H. et al. Intrasexual competition and sexual selection in cooperative mammals. Nature 444, 1065–1068 (2006).
    Google Scholar 
    Emlen, S. T. Predicting family dynamics in social vertebrates. in Behavioural Ecology: an Evolutionary Approach (eds Krebs, J. R. & Davies, N. B.) 228–253 (Blackwell Scientific, 1997).Sharp, S. P. & Clutton-Brock, T. H. Competition, breeding success and ageing rates in female meerkats: competition and senescence in meerkats. J. Evol. Biol. 24, 1756–1762 (2011).
    Google Scholar 
    Krebs, J. R. & Davies, N. B. Fighting and assessment. in An Introduction to Behavioural Ecology (eds Krebs, J. R. & Davies, N. B.) 147–174 (Blackwell Scientific Publication, 1993).Husak, J. F., Kristopher Lappin, A., Fox, S. F. & Lemos-Espinal, J. A. Bite-force performance predicts dominance in male venerable collared lizards (Crotaphytus antiquus). Copeia 2006, 301–306 (2006).Lailvaux, S. P., Herrel, A., VanHooydonck, B., Meyers, J. J. & Irschick, D. J. Performance capacity, fighting tactics and the evolution of life–stage male morphs in the green anole lizard (Anolis carolinensis). Proc. R. Soc. Lond. B Biol. Sci. 271, 2501–2508 (2004).
    Google Scholar 
    Anderson, R. A., Mcbrayer, L. D. & Herrel, A. Bite force in vertebrates: opportunities and caveats for use of a nonpareil whole-animal performance measure. Biol. J. Linn. Soc. 93, 709–720 (2008).
    Google Scholar 
    Herrel, A., De Smet, A., Aguirre, L. F. & Aerts, P. Morphological and mechanical determinants of bite force in bats: Do muscles matter?. J. Exp. Biol. 211, 86–91 (2008).
    Google Scholar 
    van der Meijden, A., González-Gómez, J. C., Pulido-Osorio, M. D. & Herrel, A. Measurement of voluntary bite forces in large carnivores using a semi-automated reward-driven system. J. Exp. Biol. 226, jeb245255 (2023).
    Google Scholar 
    Aguirre, L. F., Herrel, A., Van Damme, R. & MatThysen, E. The implications of food hardness for diet in bats. Funct. Ecol. 17, 201–212 (2003).
    Google Scholar 
    Christiansen, P. & Wroe, S. Bite forces and evolutionary adaptations to feeding ecology in carnivores. Ecology 88, 347–358 (2007).
    Google Scholar 
    Maestri, R., Patterson, B. D., Fornel, R., Monteiro, L. R. & De Freitas, T. R. O. Diet, bite force and skull morphology in the generalist rodent morphotype. J. Evol. Biol. 29, 2191–2204 (2016).
    Google Scholar 
    Santana, S. E., Dumont, E. R. & Davis, J. L. Mechanics of bite force production and its relationship to diet in bats. Funct. Ecol. 24, 776–784 (2010).
    Google Scholar 
    Verwaijen, D., Van Damme, R. & Herrel, A. Relationships between head size, bite force, prey handling efficiency and diet in two sympatric lacertid lizards. Funct. Ecol. 16, 842–850 (2002).
    Google Scholar 
    Gowan, T. A., Mcbrayer, L. D. & Rostal, D. C. Seasonal variation in testosterone and performance in males of a non-territorial lizard species. Physiol. Behav. 100, 357–363 (2010).
    Google Scholar 
    Husak, J. F., Lappin, A. K. & Van Den Bussche, R. A. The fitness advantage of a high-performance weapon. Biol. J. Linn. Soc. 96, 840–845 (2009).
    Google Scholar 
    Lappin, A. K. & Husak, J. F. Weapon performance, not size, determines mating success and potential reproductive output in the collared lizard (Crotaphytus collaris). Am. Nat. 166, 426–436 (2005).
    Google Scholar 
    Zablocki-Thomas, P., Lailvaux, S., Aujard, F., Pouydebat, E. & Herrel, A. Maternal and genetic correlations between morphology and physical performance traits in a small captive primate, Microcebus murinus. Biol. J. Linn. Soc. 134, 28–39 (2021).
    Google Scholar 
    Herrel, A. et al. Do adult phenotypes reflect selection on juvenile performance? A comparative study on performance and morphology in lizards. Integr. Comp. Biol. 56, 469–478 (2016).
    Google Scholar 
    Begall, S., Burda, H. & Šumbera, R. Graumulle: Cryptomys und Fukomys (VerlagsKG Wolf, 2018).Bennett, N. C. & Faulkes, C. G. African Mole-Rats—Ecology and Eusociality (Cambridge University Press, 2000).Rodrigues, H. G., Šumbera, R., Hautier, L. & Herrel, A. Digging up convergence in fossorial rodents: insights into burrowing activity and morpho-functional specializations of the masticatory apparatus. in Convergent Evolution: Animal Form and Function (eds Bels, V. L. & Russell, A. P.) 37–63. https://doi.org/10.1007/978-3-031-11441-0_3 (Springer International Publishing, 2023).Kraus, A. et al. Bite force in the strictly subterranean rodent family of African mole-rats (Bathyergidae): the role of digging mode, social organization and ecology. Funct. Ecol. 36, 2344–2355 (2022).
    Google Scholar 
    Hite, N. J. et al. The better to eat you with: bite force in the naked mole-rat (Heterocephalus glaber) is stronger than predicted based on body size. Front. Integr. Neurosci. 13, 70 (2019).
    Google Scholar 
    van Daele, P. A. A. G., Herrel, A. & Adriaens, D. Biting performance in teeth-digging African mole-rats (Fukomys, Bathyergidae, Rodentia). Physiol. Biochem. Zool. 82, 40–50 (2009).
    Google Scholar 
    Gomes Rodrigues, H. & Damette, M. Incipient morphological specializations associated with fossorial life in the skull of ground squirrels (Sciuridae, Rodentia). J. Morphol. 284, e21540 (2023).
    Google Scholar 
    Hildebrand, M. Digging of Quadrupeds. in Functional Vertebrate Morphology (eds Hildebrand, M., Bramble, D. M., Liem, K. F. & Wake, D. B.) 89–109 (Harvard University Press, 1985).Burda, H., Honeycutt, R. L., Begall, S., Locker-Grutjen, O. & Scharff, A. Are naked and common mole-rats eusocial and if so, why?. Behav. Ecol. Sociobiol. 47, 293–303 (2000).
    Google Scholar 
    Bishop, J. M., Jarvis, J. U. M., Spinks, A. C., Bennett, N. C. & O’Ryan, C. Molecular insight into patterns of colony composition and paternity in the common mole-rat Cryptomys hottentotus hottentotus. Mol. Ecol. 13, 1217–1229 (2004).
    Google Scholar 
    Braude, S. Dispersal and new colony formation in wild naked mole-rats: evidence against inbreeding as the system of mating. Behav. Ecol. 11, 7–12 (2000).
    Google Scholar 
    Braude, S., Hess, J. & Ingram, C. Inter-colony invasion between wild naked mole-rat colonies. J. Zool. 313, 37–42 (2021).
    Google Scholar 
    Burland, T. M., Bennett, N. C., Jarvis, J. U. M. & Faulkes, C. G. Colony structure and parentage in wild colonies of co-operatively breeding Damaraland mole-rats suggest incest avoidance alone may not maintain reproductive skew. Mol. Ecol. 13, 2371–2379 (2004).
    Google Scholar 
    Mynhardt, S., Harris-Barnes, L., Bloomer, P. & Bennett, N. C. Spatial population genetic structure and colony dynamics in Damaraland mole-rats (Fukomys damarensis) from the southern Kalahari. BMC Ecol. Evol. 21, 221 (2021).
    Google Scholar 
    Patzenhauerová, H., Šklíba, J., Bryja, J. & Šumbera, R. Parentage analysis of Ansell’s mole-rat family groups indicates a high reproductive skew despite relatively relaxed ecological constraints on dispersal. Mol. Ecol. 22, 4988–5000 (2013).
    Google Scholar 
    Monadjem, A., Taylor, P. J., Denys, C. & Cotterill, F. P. D. Rodents of Sub-Saharan Africa: a Biogeographic and Taxonomic Synthesis. (De Gruyter, 2015).Thorley, J., Bensch, H. M., Finn, K., Clutton-Brock, T. & Zöttl, M. Damaraland mole-rats do not rely on helpers for reproduction or survival. Evol. Lett. 7, 203–215 (2023).
    Google Scholar 
    Young, A. J. & Bennett, N. C. Intra-sexual selection in cooperative mammals and birds: why are females not bigger and better armed? Philos. Trans. R. Soc. Lond. B Biol. Sci. 368, 20130075 (2013).
    Google Scholar 
    Zöttl, M., Thorley, J., Gaynor, D., Bennett, N. C. & Clutton-Brock, T. Variation in growth of Damaraland mole-rats is explained by competition rather than by functional specialization for different tasks. Biol. Lett. 12, 20160820 (2016).
    Google Scholar 
    Caspar, K. R., Müller, J. & Begall, S. Effects of sex and breeding status on skull morphology in cooperatively breeding Ansell’s mole-rats and an appraisal of sexual dimorphism in the Bathyergidae. Front. Ecol. Evol. 9, 638754 (2021).
    Google Scholar 
    Thorley, J., Katlein, N., Goddard, K., Zöttl, M. & Clutton-Brock, T. Reproduction triggers adaptive increases in body size in female mole-rats. Proc. R. Soc. B Biol. Sci. 285, 20180897 (2018).
    Google Scholar 
    Young, A. J. & Bennett, N. C. Morphological divergence of breeders and helpers in wild Damaraland mole-rat societies. Evolution 64, 3190–3197 (2010).
    Google Scholar 
    Freeman, P. W. & Lemen, C. A. A simple morphological predictor of bite force in rodents. J. Zool. 275, 418–422 (2008).
    Google Scholar 
    McIntosh, A. F. & Cox, P. G. Functional implications of craniomandibular morphology in African mole-rats (Rodentia: Bathyergidae). Biol. J. Linn. Soc. 117, 447–462 (2016).
    Google Scholar 
    Bennett, N. C. Behaviour and social organization in a colony of the Damaraland mole-rat Cryptomys damarensis. J. Zool. 220, 225–247 (1990).
    Google Scholar 
    Francioli, Y., Thorley, J., Finn, K., Clutton-Brock, T. & Zöttl, M. Breeders are less active foragers than non-breeders in wild Damaraland mole-rats. Biol. Lett. 16, 20200475 (2020).
    Google Scholar 
    Houslay, T. M., Vullioud, P., Zöttl, M. & Clutton-Brock, T. H. Benefits of cooperation in captive Damaraland mole-rats. Behav. Ecol. 31, 711–718 (2020).
    Google Scholar 
    Lövy, M., Šklíba, J. & Šumbera, R. Spatial and temporal activity patterns of the free-living giant mole-rat (Fukomys mechowii), the largest social Bathyergid. PLoS ONE 8, e55357 (2013).
    Google Scholar 
    Šklíba, J., Lövy, M., Burda, H. & Šumbera, R. Variability of space-use patterns in a free living eusocial rodent, Ansell’s mole-rat indicates age-based rather than caste polyethism. Sci. Rep. 6, 37497 (2016).
    Google Scholar 
    Wroe, S., McHenry, C. & Thomason, J. Bite club: comparative bite force in big biting mammals and the prediction of predatory behaviour in fossil taxa. Proc. R. Soc. B Biol. Sci. 272, 619–625 (2005).
    Google Scholar 
    Deeming, D. C., Harrison, S. L. & Sutton, G. P. Inter-relationships among body mass, jaw musculature and bite force in birds. J. Zool. 317, 129–137 (2022).
    Google Scholar 
    Herrel, A., Mcbrayer, L. D. & Larson, P. M. Functional basis for sexual differences in bite force in the lizard Anolis carolinensis. Biol. J. Linn. Soc. 91, 111–119 (2007).
    Google Scholar 
    Rebol, E. J. & Anderson, D. J. Sex-specific aging in bite force in a wild vertebrate. Exp. Gerontol. 159, 111661 (2022).
    Google Scholar 
    Thomas, P. et al. Sexual dimorphism in bite force in the grey mouse lemur. J. Zool. 296, 133–138 (2015).
    Google Scholar 
    Becerra, F., Echeverría, A., Vassallo, A. I. & Casinos, A. Bite force and jaw biomechanics in the subterranean rodent Talas tuco-tuco (Ctenomys talarum) (Caviomorpha: Octodontoidea). Can. J. Zool. 89, 334–342 (2011).
    Google Scholar 
    Herrel, A., Spithoven, L., Van Damme, R. & De Vree, F. Sexual dimorphism of head size in Gallotia galloti: testing the niche divergence hypothesis by functional analyses. Funct. Ecol. 13, 289–297 (1999).
    Google Scholar 
    Kay, R. F., Plavcan, J. M., Glander, K. E. & Wright, P. C. Sexual selection and canine dimorphism in new world monkeys. Am. J. Phys. Anthropol. 77, 385–397 (1988).
    Google Scholar 
    Morris, J. S. & Brandt, E. K. Specialization for aggression in sexually dimorphic skeletal morphology in grey wolves (Canis lupus). J. Anat. 225, 1–11 (2014).
    Google Scholar 
    Russell, A. F., Carlson, A. A., McIlrath, G. M., Jordan, N. R. & Clutton-Brock, T. Adaptive size modification by dominant female meerkats. Evolution 58, 1600–1607 (2004).
    Google Scholar 
    Magalhães, A. R., Damasceno, E. M. & Astúa, D. Bite force sexual dimorphism in Canidae (Mammalia: Carnivora): Relations between diet, sociality and bite force intersexual differences. Hystrix 31, 1–6 (2020).
    Google Scholar 
    Jarvis, J. U. M. & Bennett, N. C. Eusociality has evolved independently in two genera of bathyergid mole-rats—but occurs in no other subterranean mammal. Behav. Ecol. Sociobiol. 33, 253–260 (1993).
    Google Scholar 
    Šumbera, R. et al. Burrow architecture, family composition and habitat characteristics of the largest social African mole-rat: The giant mole-rat constructs really giant burrow systems. Acta Theriol. 57, 121–130 (2012).
    Google Scholar 
    Torrents-Ticó, M., Bennett, N. C., Jarvis, J. U. M. & Zöttl, M. Sex differences in timing and context of dispersal in Damaraland mole-rats (Fukomys damarensis). J. Zool. 306, 252–257 (2018).
    Google Scholar 
    van Daele, P. A. A. G., Desmet, N., Šumbera, R. & Adriaens, D. Work behaviour and biting performance in the cooperative breeding Micklem’s mole-rat Fukomys micklemi (Bathyergidae, Rodentia). Mamm. Biol. 95, 69–76 (2019).
    Google Scholar 
    Rotics, S., Bensch, H. M., Resheff, Y. S., Clutton-Brock, T. & Zöttl, M. Workload distribution in wild Damaraland mole-rat groups. Philos. Trans. R. Soc. Lond. B Biol. Sci. 380, 20230276 (2025).
    Google Scholar 
    Johnston, R. A. et al. Morphological and genomic shifts in mole-rat ‘queens’ increase fecundity but reduce skeletal integrity. eLife 10, e65760 (2021).
    Google Scholar 
    Jarvis, J. U. M., O’Riain, M. J. & McDaid, E. Growth and factors affecting body size in naked mole-rats. in The Biology of the Naked Mole-Rat (eds Sherman, P. W., Jarvis, J. U. M. & Alexander, R. D.) 358–383. https://doi.org/10.1515/9781400887132-015 (Princeton University Press, 1991).Lacey, E. A. & Sherman, P. W. Social organization of naked mole-rat colonies: Evidence for divisions of labor. in The Biology of the Naked Mole-rat (eds Sherman, P. W., Jarvis, J. U. M. & Alexander, R. D.) 275–336. https://doi.org/10.1515/9781400887132-013 (Princeton University Press, 1991).Speakman, J. R. The physiological costs of reproduction in small mammals. Philos. Trans. R. Soc. Lond. B Biol. Sci. 363, 375–398 (2008).
    Google Scholar 
    Dammann, P., Šumbera, R., Massmann, C., Scherag, A. & Burda, H. Extended longevity of reproductives appears to be common in Fukomys mole-rats (Rodentia, Bathyergidae). PloS ONE 6, e18757 (2011).
    Google Scholar 
    Wallace, E. D. & Bennett, N. C. The colony structure and social organization of the giant Zambian mole-rat, Cryptomys mechowi. J. Zool. 244, 51–61 (1998).
    Google Scholar 
    Dammann, P. & Burda, H. Sexual activity and reproduction delay ageing in a mammal. Curr. Biol. 16, R117–R118 (2006).
    Google Scholar 
    Begall, S., Bottermann, L. & Caspar, K. R. Self-domestication underground? Testing for social and morphological correlates of animal personality in cooperatively-breeding Ansell’s mole-rats (Fukomys anselli). Front. Ecol. Evol. 10, 862082 (2022).
    Google Scholar 
    Burda, H. Individual recognition and incest avoidance in eusocial common mole-rats rather than reproductive suppression by parents. Experientia 51, 411–413 (1995).
    Google Scholar 
    Sharp, S. P. & Clutton-Brock, T. H. Reluctant challengers: why do subordinate female meerkats rarely displace their dominant mothers? Behav. Ecol. 22, 1337–1343 (2011).
    Google Scholar 
    Cooney, R. Colony defense in Damaraland mole-rats, Cryptomys damarensis. Behav. Ecol. 13, 160–162 (2002).
    Google Scholar 
    Jacobs, D. S., Reid, S. & Kuiper, S. Out-breeding behaviour and xenophobia in the damaraland mole-rat, Cryptomys damarensis. South Afr. J. Zool. 33, 189–194 (1998).
    Google Scholar 
    Hazell, R. W. A., Bennett, N. C., Jarvis, J. U. M. & Griffin, M. Adult dispersal in the co-operatively breeding Damaraland mole-rat (Cryptomys damarensis): a case study from the Waterberg region of Namibia. J. Zool. 252, 19–25 (2000).
    Google Scholar 
    Griffin, A. S. et al. A genetic analysis of breeding success in the cooperative meerkat (Suricata suricatta). Behav. Ecol. 14, 472–480 (2003).
    Google Scholar 
    Nelson-Flower, M. J., Hockey, P. A. R., O’Ryan, C. & Ridley, A. R. Inbreeding avoidance mechanisms: Dispersal dynamics in cooperatively breeding southern pied babblers. J. Anim. Ecol. 81, 876–883 (2012).
    Google Scholar 
    Šumbera, R. Thermal biology of a strictly subterranean mammalian family, the African mole-rats (Bathyergidae, Rodentia) – a review. J. Therm. Biol. 79, 166–189 (2019).
    Google Scholar 
    Patzenhauerová, H., Šklíba, J., Bryja, J. & Šumbera, R. Parentage analysis of A nsell’s mole-rat family groups indicates a high reproductive skew despite relatively relaxed ecological constraints on dispersal. Mol. Ecol. 22, 4988–5000 (2013).
    Google Scholar 
    Šumbera, R. et al. The biology of an isolated Mashona mole-rat population from southern Malawi, with implications for the diversity and biogeography of the genus Fukomys. Org. Divers. Evol. 23, 603–620 (2023).
    Google Scholar 
    van Daele, P. A. A. G., Verheyen, E., Brunain, M. & Adriaens, D. Cytochrome b sequence analysis reveals differential molecular evolution in African mole-rats of the chromosomally hyperdiverse genus Fukomys (Bathyergidae, Rodentia) from the Zambezian region. Mol. Phylogenet. Evol. 45, 142–157 (2007).
    Google Scholar 
    Borges, L. R. et al. The role of soil features in shaping the bite force and related skull and mandible morphology in the subterranean rodents of genus Ctenomys (Hystricognathi: Ctenomyidae). J. Zool. 301, 108–117 (2017).
    Google Scholar 
    Ginot, S., Herrel, A., Claude, J. & Hautier, L. Skull size and biomechanics are good estimators of in vivo bite force in murid rodents. Anat. Rec. 301, 256–266 (2018).
    Google Scholar 
    R Core Team. R: A Language and Environment for Statistical Computing. https://www.R-project.org/ (Vienna, 2024).Bürkner, P. Bayesian item response modeling in R with brms and Stan. J. Stat. Softw. 100, 1–54 (2021).
    Google Scholar 
    Neal, R. MCMC using Hamiltonian dynamics. In Handbook of Markov Chain Monte Carlo (eds Brooks, S., Gelman, A., Jones, G. L. & Meng, X.-L.) 116–62 (Chapman & Hall/CRC Press, 2011).Vehtari, A., Gelman, A., Simpson, D., Carpenter, B. & Bürkner, P.-C. Rank-normalization, folding, and localization: an improved Rˆ for assessing convergence of MCMC (with discussion). Bayesian Anal. 16, 667–718 (2021).
    Google Scholar 
    Gelman, A., Hwang, J. & Vehtari, A. Understanding predictive information criteria for Bayesian models. Stat. Comput. 24, 997–1016 (2014).
    Google Scholar 
    Vehtari, A., Simpson, D., Gelman, A., Yao, Y. & Gabry, J. Pareto smoothed importance sampling. J. Mach. Learn. Res. 25, 1–58 (2024).
    Google Scholar 
    Vehtari, A., Gelman, A. & Gabry, J. Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC. Stat. Comput. 27, 1413–1432 (2017).
    Google Scholar 
    Burnham, K. P. & Anderson, D. R. Model Selection and Multimodel Inference: a Practical Information-Theoretical Approach (Springer, 2002).Gabry, J., Simpson, D., Vehtari, A., Betancourt, M. & Gelman, A. Visualization in Bayesian workflow. J. R. Stat. Soc. A 182, 389–402 (2019).
    Google Scholar 
    Lenth, R. emmeans: estimated marginal means, aka least-squares means. R Package Version 1.10.4 https://CRAN.R-project.org/package=emmeans (2024).Šumbera, R. et al. Breeding males, but not females, of Fukomys mole-rats use stronger bites to defend reproductive monopoly. [Data set]. Figshare https://doi.org/10.6084/m9.figshare.29423288 (2025).Download referencesAcknowledgementsWe thank Helder Gomes Rodrigues, David Gaynor and Kyle Finn for help with data collection and logistics, and Radka Pešková for taking care of experimental animals. We are grateful to Tim H. Clutton-Brock for access to Damaraland mole-rats in the facility at the Kuruman River Reserve supported by European Research Council under the European Union’s 2020 research and innovation programme (Grants No. 742808 and 294494). This study was supported by the Czech Science Foundation project no. 20-10222S.Author informationAuthors and AffiliationsDepartment of Zoology, Faculty of Science, University of South Bohemia, České Budějovice, Czech RepublicRadim Šumbera, Andrea Kraus, Ondřej Mikula, Jan Okrouhlík & Matěj LövyInstitute of Vertebrate Biology, Czech Academy of Sciences, Brno, Czech RepublicOndřej MikulaCentre for Invasion Biology, Department of Botany & Zoology, Stellenbosch University, Stellenbosch, South AfricaJohn MeaseyDepartment of General Zoology, Faculty of Biology, University of Duisburg-Essen, Essen, GermanySabine BegallMammal Research Institute, Department of Zoology and Entomology, University of Pretoria, Pretoria, South AfricaNigel C. BennettDepartment of Biology and Environmental Science, Centre for Ecology and Evolution in Microbial Model Systems (EEMIS), Linnaeus University, Kalmar, SwedenMarkus ZöttlKalahari Research Centre, Kuruman River Reserve, Van Zylsrus, South AfricaMarkus ZöttlDépartement Adaptations du Vivant, UMR 7179 MECADEV C.N.R.S/M.N.H.N., Paris, FranceAnthony HerrelAuthorsRadim ŠumberaView author publicationsSearch author on:PubMed Google ScholarAndrea KrausView author publicationsSearch author on:PubMed Google ScholarOndřej MikulaView author publicationsSearch author on:PubMed Google ScholarJan OkrouhlíkView author publicationsSearch author on:PubMed Google ScholarJohn MeaseyView author publicationsSearch author on:PubMed Google ScholarSabine BegallView author publicationsSearch author on:PubMed Google ScholarNigel C. BennettView author publicationsSearch author on:PubMed Google ScholarMarkus ZöttlView author publicationsSearch author on:PubMed Google ScholarAnthony HerrelView author publicationsSearch author on:PubMed Google ScholarMatěj LövyView author publicationsSearch author on:PubMed Google ScholarContributionsR.Š., A.K. and M.L. conceptualized the study. R.Š., A.K., J.O. and M.L. carried out the investigation, and R.Š., A.K. and M.L. curated the data. O.M. performed the formal analyses and, together with M.L., developed the methodology and prepared the figures. R.Š., A.K., J.M., S.B., N.C.B., M.Z. and A.H. provided resources. R.Š. and M.L. wrote the original draft. All authors reviewed and edited the manuscript.Corresponding authorCorrespondence to
    Radim Šumbera.Ethics declarations

    Competing interests
    The authors declare no competing interests.

    Peer review

    Peer review information
    Communications Biology thanks Frederik Püffel and Helder Gomes Rodrigues for their contribution to the peer review of this work. Primary Handling Editor: Michele Repetto. A peer review file is available.

    Additional informationPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Supplementary informationSupplementary InformationReporting SummaryTransparent Peer Review fileRights and permissions
    Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
    Reprints and permissionsAbout this articleCite this articleŠumbera, R., Kraus, A., Mikula, O. et al. Breeding male mole-rats (Fukomys) use strong bites to defend reproductive monopoly.
    Commun Biol (2025). https://doi.org/10.1038/s42003-025-09334-8Download citationReceived: 10 December 2024Accepted: 25 November 2025Published: 13 December 2025DOI: https://doi.org/10.1038/s42003-025-09334-8Share this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy shareable link to clipboard
    Provided by the Springer Nature SharedIt content-sharing initiative More

  • in

    Green manure-induced shifts in nematode communities associated with soil bacterial and fungal biomes

    AbstractGreen manures are widely used to enhance soil health and suppress plant-parasitic nematodes, and their effects on the broader soil food web have been studied. Beyond direct suppression, the role of green manures in supporting and sustaining soil food webs has attracted increasing attention. In this study, we evaluated the use of DNA sequencing to identify various nematode genera and their microbial associates in a field trial using oat (Avena sativa) and hairy vetch (Vicia villosa) as green manures. Nematode index analysis revealed that the oat treatment promoted a structured nematode community. Furthermore, the nematode community structure observed in the oat treatment was linked to specific bacterial and fungal genera. Several beneficial fungi were identified, indicating that oats, used as a green manure, actively enhanced the microbiome. Our results showed that enriching the micro-food web through organic fertilizers can help in the detection of beneficial microorganisms, with the nematode index serving as a potential indicator.

    Data availability

    Sequence data that support the findings of this study have been deposited in the National Center for Biotechnology Information with the BioSample IDs: SAMN48745011, SAMN48745012, and SAMN48745013.
    Code availability

    Not applicable.
    Materials availability

    Not applicable.
    ReferencesFageria, N. K. Green manuring in crop production. J. Plant. Nutr. 30 (5), 691–719. https://doi.org/10.1080/01904160701289529 (2007).
    Google Scholar 
    Kumar, K. & Goh, K. M. Crop residues and management practices: effects on soil quality, soil nitrogen dynamics, crop yield, and nitrogen recovery. Adv. Agron. 68, 197–319. https://doi.org/10.1016/S0065-2113(08)60846-9 (1999).
    Google Scholar 
    Ndiaye, E. L., Sandeno, J. M., McGrath, D. & Dick, R. P. Integrative biological indicators for detecting change in soil quality. Amer J. Altern. Agricul. 15 (1), 26–36 (2000). https://www.jstor.org/stable/44503132
    Google Scholar 
    Schutter, M. E. & Dick, R. P. Microbial community profiles and activities among aggregates of winter fallow and cover-cropped soil. Soil. Sci. Soc. Am. J. 66 (1), 142–153. https://doi.org/10.2136/sssaj2002.1420 (2002).
    Google Scholar 
    Wang, K. H., Sipes, B. S. & Schmitt, D. P. Crotalaria as a cover crop for nematode management: a review. Nematropica 35–58. (2002).McSorley, R. Host suitability of potential cover crops for root-knot nematodes. J. Nematol. 31 (4S), 619 (1999).
    Google Scholar 
    Djian-Caporalino, C. et al. Evaluating sorghums as green manure against root-knot nematodes. Crop Prot. 122, 142–150. https://doi.org/10.1016/j.cropro.2019.05.002 (2019).
    Google Scholar 
    Dutta, T. K., Khan, M. R. & Phani, V. Plant-parasitic nematode management via biofumigation using brassica and non-brassica plants: current status and future prospects. Curr. Plant. Biol. 17, 17–32. https://doi.org/10.1016/j.cpb.2019.02.001 (2019).
    Google Scholar 
    Lord, J. S., Lazzeri, L., Atkinson, H. J. & Urwin, P. E. Biofumigation for control of pale potato cyst nematodes: activity of brassica leaf extracts and green manures on Globodera pallida in vitro and in soil. J. Agricul Food Chem. 59 (14), 7882–7890. https://doi.org/10.1021/jf200925k (2011).
    Google Scholar 
    Sánchez-Moreno, S., Cano, M., López-Pérez, A. & Benayas, J. M. R. Microfaunal soil food webs in mediterranean semi-arid agroecosystems. Does organic management improve soil health? Appl. Soil. Ecol. 125, 138–147. https://doi.org/10.1016/j.apsoil.2017.12.020 (2018).
    Google Scholar 
    Li, Y. et al. Organic management practices enhance soil food web biomass and complexity under greenhouse conditions. Appl. Soil. Ecol. 167, 104010. https://doi.org/10.1016/j.apsoil.2021.104010 (2021).
    Google Scholar 
    Milkereit, J. et al. Interactions between nitrogen availability, bacterial communities, and nematode indicators of soil food web function in response to organic amendments. Appl. Soil. Ecol. 157, 103767. https://doi.org/10.1016/j.apsoil.2020.103767 (2021).
    Google Scholar 
    Bongers, T. The maturity index: an ecological measure of environmental disturbance based on nematode species composition. Oecologia 83, 14–19. https://doi.org/10.1007/BF00324627 (1990).
    Google Scholar 
    Ferris, H., Bongers, T. & de Goede, R. G. A framework for soil food web diagnostics: extension of the nematode faunal analysis concept. Appl. Soil. Ecol. 18 (1), 13–29. https://doi.org/10.1016/S0929-1393(01)00152-4 (2001).
    Google Scholar 
    Yang, B. et al. Impact of land use type and organic farming on the abundance, diversity, community composition and functional properties of soil nematode communities in vegetable farming. Agricul Ecosys Environ. 318, 107488. https://doi.org/10.1016/j.agee.2021.107488 (2021).
    Google Scholar 
    Matoute, A. et al. Meat-borne-parasite: A nanopore-based meta-barcoding work-flow for parasitic microbiodiversity assessment in the wild fauna of French Guiana. Curr. Issues Mol. Biol. 46 (5), 3810–3821. https://doi.org/10.3390/cimb46050237 (2024).
    Google Scholar 
    Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41 (D1), D590–D596. https://doi.org/10.1093/nar/gks1219 (2013).
    Google Scholar 
    Rognes, T., Flouri, T., Nichols, B., Quince, C. & Mahé, F. VSEARCH: a versatile open source tool for metagenomics. PeerJ, 4, e2584. (2016). https://doi.org/10.7717/peerj.2584 (2016).Faith, D. P. Conservation evaluation and phylogenetic diversity. Biol. Conserv. 61 (1), 1–10. https://doi.org/10.1016/0006-3207(92)91201-3 (1992).
    Google Scholar 
    Gardes, M. & Bruns, T. D. ITS primers with enhanced specificity for basidiomycetes-application to the identification of mycorrhizae and rusts. Mol. Ecol. 2 (2), 113–118. https://doi.org/10.1111/j.1365-294X.1993.tb00005.x (1993).
    Google Scholar 
    White, T. J., Bruns, T., Lee, S. J. W. T. & Taylor, J. Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics. PCR Protocols: Guide Methods Appl. 18 (1), 315–322. https://doi.org/10.1016/B978-0-12-372180-8.50042-1 (1990).
    Google Scholar 
    Bolyen, E. et al. Reproducible, interactive, scalable and extensible Microbiome data science using QIIME 2. Nat. Biotech. 37 (8), 852–857. https://doi.org/10.1038/s41587-019-0252-6 (2019).
    Google Scholar 
    Abarenkov, K. et al. The UNITE database for molecular identification and taxonomic communication of fungi and other eukaryotes: sequences, taxa and classifications reconsidered. Nucleic Acids Res. 5 (D1), D791–D797. https://doi.org/10.1093/nar/gkad1039 (2024).
    Google Scholar 
    Sapkota, R. & Nicolaisen, M. High-throughput sequencing of nematode communities from total soil DNA extractions. BMC Ecol. 15, 1–8. https://doi.org/10.1186/s12898-014-0034-4 (2015).
    Google Scholar 
    Porazinska, D. L. et al. Evaluating high-throughput sequencing as a method for metagenomic analysis of nematode diversity. Mol. Ecol. Resource. 9 (6), 1439–1450. https://doi.org/10.1111/j.1755-0998.2009.02611.x (2009).
    Google Scholar 
    Baker, H. V. et al. A new taxonomic database for analysis of nematode community data. Phytobiomes J. 7 (3), 385–391. https://doi.org/10.1094/PBIOMES-07-22-0042-R (2023).
    Google Scholar 
    González, I. & Déjean, S. C. C. A. Canonical Correlation Analysis. R package version 1.2.2, (2023). https://CRAN.R-project.org/package=CCAWickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer-, 2016).DeJong, T. M. A comparison of three diversity indices based on their components of richness and evenness. Oikos 222–227. https://doi.org/10.2307/3543712 (1975).Zhou, X. G. & Everts, K. L. Suppression of fusarium wilt of watermelon enhanced by hairy Vetch green manure and partial cultivar resistance. Plant. Health Progress. 7 (1), 23. https://doi.org/10.1094/PHP-2006-0405-01-RS (2006). (2006).
    Google Scholar 
    Martin, T. & Sprunger, C. D. Soil food web structure and function in annual row-crop systems: how can nematode communities infer soil health? Appl. Soil. Ecol. 178, 104553. https://doi.org/10.1016/j.apsoil.2022.104553 (2022).
    Google Scholar 
    Wang, K. H. et al. Relationships between soil tillage systems, nematode communities and weed seed predation. Horticulturae 8 (5), 425. https://doi.org/10.3390/horticulturae8050425 (2022).
    Google Scholar 
    Ferris, H. & Benavides, I. V. Opinions and suggestions on nematode faunal analysis. J. Nematol. 56 (1), 20240049. https://doi.org/10.2478/jofnem-2024-0049 (2024).
    Google Scholar 
    Zhou, D. et al. Rhizosphere microbiomes from root knot nematode non-infested plants suppress nematode infection. Microb. Ecol. 78 (2), 470–481. https://doi.org/10.1007/s00248-019-01319-5 (2019).
    Google Scholar 
    Topalović, O., Hussain, M. & Heuer, H. Plants and associated soil microbiota cooperatively suppress plant-parasitic nematodes. Front. Microbiol. 11, 313. https://doi.org/10.3389/fmicb.2020.00313 (2020).
    Google Scholar 
    Khan, S. A. et al. Plant growth promotion and Penicillium citrinum. BMC microbiol. 8, 231. https://doi.org/10.1186/1471-2180-8-231 (2008).
    Google Scholar 
    Radhakrishnan, R., Kang, S. M., Baek, I. Y. & Lee, I. J. Characterization of plant growth-promoting traits of Penicillium species against the effects of high soil salinity and root disease. J. Plant. Interact. 9 (1), 754–762. https://doi.org/10.1080/17429145.2014.930524 (2014).
    Google Scholar 
    Daroodi, Z., Taheri, P. & Tarighi, S. Acrophialophora jodhpurensis: an endophytic plant growth promoting fungus with biocontrol effect against Alternaria alternata. Front. Plant. Sci. 13, 984583. https://doi.org/10.3389/fpls.2022.984583 (2022).
    Google Scholar 
    Download referencesAcknowledgementsWe thank the former students in our laboratory (Tanioka K., Sawada H., Senoo Y., Nezu Y., Ueda K., Hayashi D., Matsumoto R., Iwamoto N., Tanaka T., Hashimoto T., Hashimoto M., Onishi F., Sato A., Watanabe R. and Yoshimoto T.) for their dedicated efforts in both fieldwork and laboratory work, particularly in handling soil samples. We are grateful to Dr. Wang, KH. at the University of Hawaii for critical reading of this manuscript. This research was supported by a grant (2021-2022) from the Research Institute for Food and Agriculture, Ryukoku University.FundingThis research was supported by a grant (2021–2022) from the Research Institute for Food and Agriculture, Ryukoku University.Author informationAuthors and AffiliationsDepartment of Life Sciences, Faculty of Agriculture, Ryukoku University, 1-5 Yokotani Seta Oe-cho, Otsu, 520-2194, Shiga, JapanAtsuya Sudo & Erika AsamizuDepartment of Agricultural Sciences, Faculty of Agriculture, Ryukoku University, 1-5 Yokotani Seta Oe-cho, Otsu, 520-2194, Shiga, JapanDaisuke Yoshimura & Hiroyuki DaimonGraduate School of Life Sciences, Tohoku University, 2-1-1 Katahira, Aoba-ku, Sendai, 980-857, Miyagi, JapanShusei SatoAuthorsAtsuya SudoView author publicationsSearch author on:PubMed Google ScholarDaisuke YoshimuraView author publicationsSearch author on:PubMed Google ScholarHiroyuki DaimonView author publicationsSearch author on:PubMed Google ScholarShusei SatoView author publicationsSearch author on:PubMed Google ScholarErika AsamizuView author publicationsSearch author on:PubMed Google ScholarContributionsE.A. conceived the conception of this study, performed analyses, wrote the manuscript. A.S. and D.Y. performed field practices, acquired data. H.D. and S.S. designed the methodology and interpreted the results. All authors read and approved the manuscript.Corresponding authorCorrespondence to
    Erika Asamizu.Ethics declarations

    Ethical approval and consent to participate
    Not applicable.

    Consent for publication
    Not applicable.

    Competing interests
    The authors declare no competing interests.

    Additional informationPublisher’s noteSpringer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Supplementary InformationBelow is the link to the electronic supplementary material.Supplementary Material 1Supplementary Material 2Rights and permissions
    Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
    Reprints and permissionsAbout this articleCite this articleSudo, A., Yoshimura, D., Daimon, H. et al. Green manure-induced shifts in nematode communities associated with soil bacterial and fungal biomes.
    Sci Rep (2025). https://doi.org/10.1038/s41598-025-31442-yDownload citationReceived: 23 May 2025Accepted: 02 December 2025Published: 13 December 2025DOI: https://doi.org/10.1038/s41598-025-31442-yShare this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy shareable link to clipboard
    Provided by the Springer Nature SharedIt content-sharing initiative
    KeywordsGreen manureNematode indexOat (Avena sativa)rRNA amplicon sequenceSoil bacteriaSoil fungi More