Ecology

AbstractSpiders, a keystone predatory group for terrestrial ecosystem balance, have underexplored gut microbiotas. We collected 1090 spiders from 34 families in southwestern China, performing 16S rRNA sequencing to investigate their gut microbiota. Wandering and ambushing spiders exhibited higher α-diversity, while web-building spiders showed the lowest α-diversity with the highest endosymbiont infection rates. Gut microbiota diversity was significantly higher in Guizhou-region spiders than in Sichuan-region spiders. All spiders showed high amount of endosymbiont ASVs, which varied with foraging strategies and regions. Additionally, closer geographic distances between spiders were associated with more similar gut microbiota diversity levels. Environmental factor analysis preliminary revealed a positive correlation between precipitation and gut microbiota diversity, though its generalizability is limited by geographic sampling. Random processes were the primary drivers of spiders’ gut microbial community assembly. Our findings highlight that spider gut microbiota assembly is predominantly driven by stochastic processes but regulated by foraging strategies and geographic factors, providing a framework for understanding predator-microbe interactions in spiders.

Data availability

The raw sequencing reads from this study have been submitted to the China National GeneBank Database (CNP0007324; CNGBdb, https://db.cngb.org/) and Genome Sequence Archive database (PRJCA051897: CRA034046; GSA, https://ngdc.cncb.ac.cn/gsa/).
Code availability

The analysis code has been submitted to GitHub (https://github.com/WJiao95/16S-spider) and Zenodo85 (DOI: 10.5281/zenodo.17640349).
ReferencesGao, Y., Wu, P. F., Cui, S. Y., Ali, A. & Zheng, G. Divergence in gut bacterial community between females and males in the wolf spider Pardosa astrigera. Ecol. Evol. 12, https://doi.org/10.1002/ece3.8823 (2022).Zhang, L. H., Zhang, G. M., Yun, Y. L. & Peng, Y. Bacterial community of a spider, Marpiss magister (Salticidae). 3 Biotech 7, https://doi.org/10.1007/s13205-017-0994-0 (2017).Zhang, L. H., Yun, Y. L., Hu, G. W. & Peng, Y. Insights into the bacterial symbiont diversity in spiders. Ecol. Evol. 8, 4899–4906 (2018).
Google Scholar 
Kennedy, S. R., Tsau, S., Gillespie, R. & Krehenwinkel, H. Are you what you eat? A highly transient and prey-influenced gut microbiome in the grey house spider Badumna longinqua. Mol. Ecol. 29, 1001–1015 (2020).
Google Scholar 
Fan, Y. & Pedersen, O. Gut microbiota in human metabolic health and disease. Nat. Rev. Microbiol. 19, 55–71 (2021).
Google Scholar 
Clemente, J. C., Ursell, L. K., Parfrey, L. W. & Knight, R. The impact of the gut microbiota on human health: an integrative view. Cell 148, 1258–1270 (2012).
Google Scholar 
Weng, M. & Walker, W. A. The role of gut microbiota in programming the immune phenotype. J. Dev. Orig. Health Dis. 4, 203–214 (2013).
Google Scholar 
Brown, E. M., Clardy, J. & Xavier, R. J. Gut microbiome lipid metabolism and its impact on host physiology. Cell Host Microbe 31, 173–186 (2023).
Google Scholar 
Ross, F. C. et al. The interplay between diet and the gut microbiome: implications for health and disease. Nat. Rev. Microbiol. 22, 671–686 (2024).
Google Scholar 
Sun, J. A. et al. Gut microbiota as a new target for anticancer therapy: from mechanism to means of regulation. npj Biofilms Microbiomes 11, https://doi.org/10.1038/s41522-025-00678-x (2025).Muegge, B. D. et al. Diet drives convergence in gut microbiome functions across mammalian phylogeny and within humans. Science 332, 970–974 (2011).Yatsunenko, T. et al. Human gut microbiome viewed across age and geography. Nature 486, 222 (2012).
Google Scholar 
Yao, R. et al. Fly-over phylogeny across invertebrate to vertebrate: the giant panda and insects share a highly similar gut microbiota. Comput Struct. Biotechnol. 19, 4676–4683 (2021).
Google Scholar 
Chen, L. J., Li, Z. Z., Liu, W. & Lyu, B. Impact of high temperature and drought stress on the microbial community in wolf spiders. Ecotoxicol. Environ. Safe 283, https://doi.org/10.1016/j.ecoenv.2024.116801 (2024).Rezác, M., Rezácová, V. & Heneberg, P. Differences in the abundance and diversity of endosymbiotic bacteria drive host resistance of a dominant spider of central European orchards, to selected insecticides. J. Environ. Manag. 373, https://doi.org/10.1016/j.jenvman.2024.123486 (2025).Perez-Lamarque, B., Krehenwinkel, H., Gillespie, R. G. & Morlon, H. Limited evidence for microbial transmission in the phylosymbiosis between Hawaiian spiders and their microbiota. mSystems 7, e0110421 (2022).
Google Scholar 
Meehan, C. J., Olson, E. J., Reudink, M. W., Kyser, T. K. & Curry, R. L. Herbivory in a spider through exploitation of an ant-plant mutualism. Curr. Biol. 19, R892–R893 (2009).
Google Scholar 
Szymkowiak, P. & Grabowski, P. Morphological differentiation of ventral tarsal setae and surface sculpturing of theraphosids (araneae: theraphosidae) with different types of lifestyles. Ann. Entomol. Soc. Am. 115, 314–323 (2022).
Google Scholar 
Ramírez, D. S. et al. Deciphering the diet of a wandering spider (Phoneutria boliviensis; Araneae: Ctenidae) by DNA metabarcoding of gut contents. Ecol. Evol. 11, 5950–5965 (2021).
Google Scholar 
Uetz, G. W. Foraging strategies of spiders. Trends Ecol. Evol. 7, 155–159 (1992).
Google Scholar 
Schmitz, A. Respiration in spiders (Araneae). J. Comp. Physiol. B 186, 403–415 (2016).
Google Scholar 
Groussin, M. et al. Unraveling the processes shaping mammalian gut microbiomes over evolutionary time. Nat. Commun. 8, https://doi.org/10.1038/ncomms14319 (2017).Deschasaux, M. et al. Depicting the composition of gut microbiota in a population with varied ethnic origins but shared geography. Nat. Med. 24, 1526 (2018).
Google Scholar 
Rocafort, M. et al. HIV-associated gut microbial alterations are dependent on host and geographic context. Nat. Commun. 15, https://doi.org/10.1038/s41467-023-44566-4 (2024).Weng, H. D. et al. Humid heat environment causes anxiety-like disorder via impairing gut microbiota and bile acid metabolism in mice. Nat. Commun. 15, https://doi.org/10.1038/s41467-024-49972-w (2024).Duron, O., Hurst, G. D. D., Hornett, E. A., Josling, J. A. & Engelstädter, J. High incidence of the maternally inherited bacterium in spiders. Mol. Ecol. 17, 1427–1437 (2008).
Google Scholar 
White, J. A. et al. Endosymbiotic bacteria are prevalent and diverse in agricultural spiders. Micro. Ecol. 79, 472–481 (2020).
Google Scholar 
Goodacre, S. L., Martin, O. Y., Thomas, C. F. G. & Hewitt, G. M. Wolbachia and other endosymbiont infections in spiders. Mol. Ecol. 15, 517–527 (2006).
Google Scholar 
Douglas, A. E. The microbial dimension in insect nutritional ecology. Funct. Ecol. 23, 38–47 (2009).
Google Scholar 
Rosenwald, L. C., Sitvarin, M. I. & White, J. A. Endosymbiotic Rickettsiella causes cytoplasmic incompatibility in a spider host. Proc. Biol. Sci. 287, https://doi.org/10.1098/rspb.2020.1107 (2020).Wang, X. Y. et al. Age-, sex- and proximal-distal-resolved multi-omics identifies regulators of intestinal aging in non-human primates. Nat. Aging 4, https://doi.org/10.1038/s43587-024-00572-9 (2024).Zhang, X. Y. et al. Sex- and age-related trajectories of the adult human gut microbiota shared across populations of different ethnicities. Nat. Aging 1, 87 (2021).
Google Scholar 
Kroon, S. et al. Sublethal systemic LPS in mice enables gut-luminal pathogens to bloom through oxygen species-mediated microbiota inhibition. Nat. Commun. 16, https://doi.org/10.1038/s41467-025-57979-0 (2025).Minich, J. J. et al. Host biology, ecology and the environment influence microbial biomass and diversity in 101 marine fish species. Nat. Commun. 13, https://doi.org/10.1038/s41467-022-34557-2 (2022).Schmiedová, L., Tomásek, O., Pinkasová, H., Albrecht, T. & Kreisinger, J. Variation in diet composition and its relation to gut microbiota in a passerine bird. Sci. Rep. 12, https://doi.org/10.1038/s41598-022-07672-9 (2022).Welch, K., Haynes, K. & Harwood, J. Prey-specific foraging tactics in a web-building spider. Agric. Forest Entomol. 15, https://doi.org/10.1111/afe.12023 (2013).Pyke, G. H. Optimal foraging theory – a critical review. Annu. Rev. Ecol. Syst. 15, 523–575 (1984).
Google Scholar 
Nyffeler, M. Prey selection of spiders in the field. J. Arachnol. 27, 317–324 (1999).
Google Scholar 
Ludy, C. Prey selection of orb-web spiders (Araneidae) on field margins. Agr. Ecosyst. Environ. 119, 368–372 (2007).
Google Scholar 
Mishra, A., Kumar, B. & Rastogi, N. Predation potential of hunting and web-building spiders on rice pests of Indian subcontinent. Int. J. Trop. Insect Sc. 41, 1027–1036 (2021).
Google Scholar 
Wright, S. & Goodacre, S. L. Evidence for antimicrobial activity associated with common house spider silk. Bmc Res. Notes 5, 326 (2012).
Google Scholar 
Tahir, H. M., Qamar, S., Sattar, A., Shaheen, N. & Samiullah, K. Evidence for the antimicrobial potential of silk of cyclosa confraga (Thorell, 1892) (Araneae: Araneidae). Acta Zool. Bulg. 69, 593–595 (2017).
Google Scholar 
Sarkar, A. et al. Microbial transmission in animal social networks and the social microbiome. Nat. Ecol. Evol. 4, 1020–1035 (2020).
Google Scholar 
Ramalho, M. O., Bueno, O. C. & Moreau, C. S. Microbial composition of spiny ants (Hymenoptera:Formicidae:Polyrhachis) across their geographic range. BMC Evol. Biol. 17, https://doi.org/10.1186/s12862-017-0945-8 (2017).Armstrong, E. E. et al. A holobiont view of island biogeography: Unravelling patterns driving the nascent diversification of a Hawaiian spider and its microbial associates. Mol. Ecol. 31, 1299–1316 (2022).
Google Scholar 
Tyagi, K., Tyagi, I. & Kumar, V. Interspecific variation and functional traits of the gut microbiome in spiders from the wild: the largest effort so far. Plos ONE 16, e0251790 (2021).
Google Scholar 
Qiu, Y. P. et al. Climate warming suppresses abundant soil fungal taxa and reduces soil carbon efflux in a semi-arid grassland. Mlife 2, 389–400 (2023).
Google Scholar 
Jactel, H. et al. Positive biodiversity-productivity relationships in forests: climate matters. Biol. Lett. 14, https://doi.org/10.1098/rsbl.2017.0747 (2018).Niu, B. & Fu, G. Response of plant diversity and soil microbial diversity to warming and increased precipitation in alpine grasslands on the Qinghai-Xizang Plateau – A review. Sci. Total Environ. 912, https://doi.org/10.1016/j.scitotenv.2023.168878 (2024).Mittermeier, R. A., Turner, W. R., Larsen, F. W., Brooks, T. M. & Gascon, C. Global Biodiversity Conservation: The Critical Role of Hotspots.in Biodiversity Hotspots: Distribution and Protection of Conservation Priority Areas (eds Frank E. Zachos & Jan Christian Habel) 3–22 (Springer Berlin Heidelberg, 2011).Wang, C. Y. et al. Extreme drought shapes the gut microbiota composition and function of common cranes wintering in Poyang Lake. Front. Microbiol. 15, https://doi.org/10.3389/fmicb.2024.1489906 (2024).Williams, C. E. et al. Sustained drought, but not short-term warming, alters the gut microbiomes of wild anolis lizards. Appl. Environ. Microbiol. 88, e0053022 (2022).
Google Scholar 
Du, X. Y. et al. Proximity-based defensive mutualism between Streptomyces and Mesorhizobium by sharing and sequestering iron. ISME J. 18, https://doi.org/10.1093/ismejo/wrad041 (2024).Shah, V. & Subramaniam, S. Bradyrhizobium japonicum USDA110: a representative model organism for studying the impact of pollutants on soil microbiota. Sci. Total Environ. 624, 963–967 (2018).
Google Scholar 
Riahi, H. S., Heidarieh, P. & Fatahi-Bafghi, M. Genus Pseudonocardia: what we know about its biological properties, abilities and current application in biotechnology. J. Appl. Microbiol. 132, 890–906 (2022).
Google Scholar 
Yun, J. H. et al. Insect gut bacterial diversity determined by environmental habitat, diet, developmental stage, and phylogeny of host. Appl. Environ. Microbiol. 80, 5254–5264 (2014).
Google Scholar 
Gurung, K., Wertheim, B. & Salles, J. F. The microbiome of pest insects: it is not just bacteria. Entomol. Exp. Appl. 167, 156–170 (2019).
Google Scholar 
Shin, N. R., Whon, T. W. & Bae, J. W. Proteobacteria: microbial signature of dysbiosis in gut microbiota. Trends Biotechnol. 33, 496–503 (2015).
Google Scholar 
Vanthournout, B. & Hendrickx, F. Endosymbiont dominated bacterial communities in a dwarf spider. Plos ONE 10, https://doi.org/10.1371/journal.pone.0117297 (2015).Jing, X. F. et al. The bacterial communities in plant phloem-sap-feeding insects. Mol. Ecol. 23, 1433–1444 (2014).
Google Scholar 
Baumann, P. Biology of bacteriocyte-associated endosymbionts of plant sap-sucking insects. Annu. Rev. Microbiol. 59, 155–189 (2005).
Google Scholar 
Weiss, B. L. et al. Interspecific transfer of bacterial endosymbionts between tsetse fly species: infection establishment and effect on host fitness. Appl. Environ. Microbiol. 72, 7013–7021 (2006).
Google Scholar 
Wang, S., Hua, X. G. & Cui, L. Characterization of microbiota diversity of engorged ticks collected from dogs in China. J. Vet. Sci. 22, https://doi.org/10.4142/jvs.2021.22.e37 (2021).Baumann, P. et al. Genetics, physiology, and evolutionary relationships of the Genus Buchnera – intracellular symbionts of aphids. Annu. Rev. Microbiol. 49, 55–94 (1995).
Google Scholar 
Li, C. F., He, M., Yun, Y. L. & Peng, Y. Co-infection with Wolbachia and Cardinium may promote the synthesis of fat and free amino acids in a small spider, Hylyphantes graminicola. J. Invertebr. Pathol. 169, https://doi.org/10.1016/j.jip.2019.107307 (2020).Zhou, J. Z. & Ning, D. L. Stochastic community assembly: does it matter in microbial ecology? Microbiol. Mol. Biol. R. 81, https://doi.org/10.1128/MMBR.00002-17 (2017).Huang, G. P. et al. Global landscape of gut microbiome diversity and antibiotic resistomes across vertebrates. Sci. Total Environ. 838, https://doi.org/10.1016/j.scitotenv.2022.156178 (2022).Pan, B. Z. et al. Geographical distance, host evolutionary history and diet drive gut microbiome diversity of fish across the Yellow River. Mol. Ecol. 32, 1183–1196 (2023).
Google Scholar 
Sheffer, M. M. et al. Tissue- and population-level microbiome analysis of the wasp spider argiope bruennichi identified a novel dominant bacterial symbiont. Microorganisms 8, https://doi.org/10.3390/microorganisms8010008 (2020).Millar, E. N., Surette, M. G. & Kidd, K. A. Altered microbiomes of aquatic macroinvertebrates and riparian spiders downstream of municipal wastewater effluents. Sci. Total Environ. 809, https://doi.org/10.1016/j.scitotenv.2021.151156 (2022).Caporaso, J. G. et al. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J. 6, 1621–1624 (2012).
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 
Callahan, B. J. et al. DADA2: high-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581 (2016).
Google Scholar 
Price, M. N., Dehal, P. S. & Arkin, A. P. FastTree: computing large minimum evolution trees with profiles instead of a distance matrix. Mol. Biol. Evol. 26, 1641–1650 (2009).
Google Scholar 
Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596 (2013).
Google Scholar 
Dixon, P. VEGAN, a package of R functions for community ecology. J. Veg. Sci. 14, 927–930 (2003).
Google Scholar 
Liu, C., Cui, Y. M., Li, X. Z. & Yao, M. J. Microeco: an R package for data mining in microbial community ecology. FEMS Microbiol. Ecol. 97, https://doi.org/10.1093/femsec/fiaa255 (2021).Wickham, H. ggplot2: elegant graphics for data analysis. Springer, https://doi.org/10.1007/978-3-319-24277-4. (2016).Kassambara, A. ggpubr: ‘ggplot2’ Based Publication Ready Plots. R package version 00, https://rpkgs.datanovia.com/ggpubr/ (2023).Bardou, P., Mariette, J., Escudié, F., Djemiel, C. & Klopp, C. Jvenn: an interactive Venn diagram viewer. BMC Bioinform. 15, https://doi.org/10.1186/1471-2105-15-293 (2014).Hijmans, R. J. Geosphere: spherical trigonometry. R Package Version 1, 5–20 (2024).
Google Scholar 
Taiyun Wei, V. S. R package ‘corrplot’: visualization of a correlation matrix. R Package Version 0.95, (2024).Ning, D. L. et al. A quantitative framework reveals ecological drivers of grassland microbial community assembly in response to warming. Nat. Commun. 11, https://doi.org/10.1038/s41467-020-18560-z (2020).Gao, Y., Zhang, G., Jiang, S. & Liu, Y. X. Wekemo Bioincloud: a user-friendly platform for meta-omics data analyses. Imeta 3, e175 (2024).
Google Scholar 
WJiao95/16S-spider: Spider16S-v1.0 v. v1.0 (Zenodo, 2025).Download referencesAcknowledgementsWe especially thank Professor Hao Yu at the College of Life Sciences, Guizhou Normal University for the sample collection in Guizhou. We also express our gratitude to the members of our research group for their hard work in the field of sample collection in Sichuan. They are Mian Wei, Qiuqiu Zhang, Qian Chen, Xuewei Geng, Yiting He, Xuelian Weng, Hanlin Wang, and Yuanhao Du.Author informationAuthor notesThese authors contributed equally: Jiao Wang, Shuqiao Wang.Authors and AffiliationsKey Laboratory of Bio-Resources and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu, ChinaJiao Wang, Shuqiao Wang, Qian Chen, Chuang Zhou, Zhenxin Fan & Yucheng linSichuan Key Laboratory of Conservation Biology on Endangered Wildlife, College of Life Sciences, Sichuan University, Chengdu, ChinaJiao Wang, Shuqiao Wang, Qian Chen, Zhenxin Fan & Yucheng linCollege of Life Sciences, Sichuan Normal University, Chengdu, ChinaChuang ZhouAuthorsJiao WangView author publicationsSearch author on:PubMed Google ScholarShuqiao WangView author publicationsSearch author on:PubMed Google ScholarQian ChenView author publicationsSearch author on:PubMed Google ScholarChuang ZhouView author publicationsSearch author on:PubMed Google ScholarZhenxin FanView author publicationsSearch author on:PubMed Google ScholarYucheng linView author publicationsSearch author on:PubMed Google ScholarContributionsJiao Wang and Shuqiao Wang performed the bioinformatics analyses; Jiao Wang wrote the manuscript; Shuqiao Wang, Chuang Zhou, and Qian Chen collected the samples; Zhenxin Fan and Yuchen Lin revised the manuscript, designed, and supervised the study.Corresponding authorsCorrespondence to
Zhenxin Fan or Yucheng lin.Ethics declarations

Competing interests
The authors declare no competing interests.

Peer review

Peer review information
Communications Biology thanks Marc Domènech, Evgeniia Propistsova, Hirokazu Toju, Jordan Cuff and the other anonymous reviewer(s) for their contribution to the peer review of this work. Primary handling editors: Hannes Schuler and Tobias Goris.

Additional informationPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Supplementary informationSupplementary InformationDescription of Additional Supplementary FilesSupplementary Data 1–11Reporting 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 articleWang, J., Wang, S., Chen, Q. et al. Foraging strategies and geographic factors jointly shape gut microbiota of spiders in the Sichuan and Guizhou regions of China.
Commun Biol (2025). https://doi.org/10.1038/s42003-025-09358-0Download citationReceived: 27 May 2025Accepted: 02 December 2025Published: 13 December 2025DOI: https://doi.org/10.1038/s42003-025-09358-0Share 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

AbstractIn this study, the spatial and temporal variations and distribution characteristics of the carbon dioxide (CO2) concentration on Hainan Island are analyzed using GOSAT L3 data from 2011 to 2024, and the effects of various factors impacting the CO2 concentration on Hainan Island are discussed. The results indicate that from 2011 to 2024, the CO2 concentration on Hainan Island showed an increasing trend, with a fast growth rate in the early period and a slow growth rate in recent years with the implementation of the dual-carbon strategy. The spatial distribution is affected by anthropogenic activities, topography, vegetation and solar radiation, and the overall CO2 concentration pattern is high in the north and low in the south. Human activities are the most important source of carbon on Hainan Island, vegetation is the most important carbon sink, and elements such as surface temperature, precipitation, and total solar radiation play roles in suppressing CO2. The CO2 concentration on Hainan Island is expected to continue to increase at a slow rate and may display a decreasing trend in the future.

ReferencesThe state of. Greenhouse gases in the atmosphere based on global observations through 2010. WMO Greenh. Gas Bull. 7(21) (2011).Zhang, S. et al. Policy recommendations for the zero energy building promotion towards carbon neutral in Asia-Pacific Region. Energy Policy https://doi.org/10.1016/j.enpol.2021.112661 (2021).
Google Scholar 
Gregg, J. S., Andres, R. J., Marland, G. & China Emissions pattern of the world leader in CO2 emissions from fossil fuel consumption and cement production. Geophys. Res. Lett. 35 (8), 135–157 (2008).
Google Scholar 
Etheridge, D. M. et al. Natural and anthropogenic changes in atmospheric CO2 over the last 1000 years froin air in Antarctic ice and firn. J. Geophys. Research: Atmos. 101(D2), 4115 (1996).
Google Scholar 
Li, C., Li, H. & Qin, X. Spatial heterogeneity of carbon emissions and its influencing factors in china: evidence from 286 prefecture-level cities. Int. J. Environ. Res. Public Health. 19 (3), 1226 (2022).
Google Scholar 
Zhang, M. N. et al. Elevated CO2 moderates the impact of climate change on future bamboo distribution in Madagascar. Sci. Total Environ. 810, 152235 (2022).
Google Scholar 
Jung, M. et al. Compensatory water effects link yearly global land CO2 sink changes to temperature. Nature 541 (7638), 516–520 (2017).
Google Scholar 
Yamagishi, H. et al. Role of nitrification and denitrification on the nitrous oxide cycle in the Eastern tropical North Pacific and Gulf of California. J. Geophys. Research:Biogeosciences. https://doi.org/10.1029/2006JG000227 (2007).
Google Scholar 
Humphrey, V. et al. Sensitivity of atmospheric CO2 growth rate to observed changes in terrestrial water storage. Nature 560 (7720), 628–631 (2018).
Google Scholar 
Yi, L. I. U. et al. Advances in technologies and methods for satellite remote sensing of atmospheric CO2. Remote Sens. Technol. Application. 26 (2), 247–254 (2011).
Google Scholar 
Wang, Q., Chiu, Y. H. & Chiu, C. R. Driving factors behind carbon dioxide emissions in china: A modified production-theoretical decomposition analysis. Energy Econ. 51, 252–260 (2015).
Google Scholar 
Heyntann, J. et al. Consistent satellite X CO2 retrievals from SCIAMACHY and GOSAT using the BESD algorithm. Atmos. Meas. Tech. 8 (2), 2961–2980 (2015).
Google Scholar 
Takagi, H. et al. On the benefit of GOSAT observationsto the Estimation of regional CO2 fluxes. Sola 7, 161–164 (2011).
Google Scholar 
Buchwitz, M. et al. Atmospheric Methaneand carbon dioxide from SCIAMACHY satellite data: initial comparison with chemistry and transportmodels. Atmos. Chem. Phys. 5 (4), 941:962 (2005).
Google Scholar 
Yizhen, J. I. A. et al. Spatial and Temporal distribution of XCO2 and XCH4 in China based on satellite remote sensing. J. Atmospheric Environ. Opt. 17 (6), 679692 (2022).
Google Scholar 
Yokota, T. et al. Global concentrations of CO2 and CH4 retireved from GOSAT: first preliminary results. Sola 5, 160163 (2009).
Google Scholar 
Guo, M. et al. Assessment of Global Carbon Dioxide Concentration Using MODIS and GOSAT Data. Sensors https://doi.org/10.3390/s121216368 (2012).
Google Scholar 
Da-zhang, H. E. & Sheng-ling, Z. H. A. N. G. The Reginal climate division of Hainan Island. ACTA Geogr. SINACA. 40 (2), 169–178 (1985).
Google Scholar 
Bo-Sun, W. A. N. G. et al. Diversity of tropical forest landscape-type in Hainan Island, China. Acta Ecol. Sin. 27 (5), 1690–1695 (2007).
Google Scholar 
Long, J. Y. et al. Spatial autocorrelation analysis of Chinese provincial carbon dioxide emissions. Ecol. Econ. https://doi.org/10.1109/CSO.2009.147 (2011).
Google Scholar 
WEI, P. et al. Spatial and Temporal characteristics of vegetation resilience to drought in China. Sci. China Earth Sci. 68(07), 2310–2327 (2025).
Google Scholar 
Zhang, C., Li, S. & Wan, J. H. The warmest year 2015 in the instrumental record and its comparison with year 1998. Atmospheric Ocean. Sci. Lett. 9 (6), 487–494 (2016).
Google Scholar 
Niinistö & Kellomäki Silvola. Seasonality in a boreal forest ecosystem affects the use of soil temperature and moisture as predictors of soil CO2 efflux. Biogeosciences Discuss. 8 (8), 2811–2849 (2011).
Google Scholar 
Huimin, Y. et al. Multiple cropping intensity in China derived from Agro-meteorological observations and MODIS data. Chin. Geogra. Sci. 24 (02), 205–219 (2014).
Google Scholar 
Doughty, C. E. & Goulden, M. L. Are tropical forests near a high temperature threshold?. J. Geophys. Res. : Biogeosc 113 113, G00B07 (2008).
Google Scholar 
Cox, P. M. et al. Sensitivity of tropical carbon to climate change constrained by carbon dioxide variability. Nature 494, 341–344 (2013).
Google Scholar 
Li, G. et al. Analysis and prediction of global vegetation dynamics:past variations and future perspectives. J. Forestry Res. 34 (02), 317–332 (2023).
Google Scholar 
Tadesse, K. B. & Dinka, M. O. .Application of SARIMA model to forecasting monthly flows in Waterval River, South Africa. J. Water Land. Dev. https://doi.org/10.1515/jwld-2017-0088 (2017).
Google Scholar 
Aboelnour, M. A. et al. Leveraging ERA5-Land reanalysis precipitation data for urban flood vulnerability and water security assessments: A global perspective. Earth Syst. Environ. 9 (3), 2335–2353 (2025).
Google Scholar 
GoovaertsP Kriging interpolation. Geographic Inform. Sci. Technol. Body Knowl. https://doi.org/10.22224/gistbok/2019.4.4 (2019).
Google Scholar 
YU Yan-sheng, C. H. E. N. & Xing-wei Analysis of future trend characteristics of hydrological time series based on R/S and Mann-Kendall methods. J. Water Resour. Water Enigineering. 19 (3), 4144 (2008).
Google Scholar 
Download referencesFundingThis study is supported by the National Key Research and Development Program (2023YFC3008001);Natural science foundation of China(Grant No.42465006, Grant No.U21A6001).Hainan Provincial Natural Science Foundation of China(424QN364).Data availability statement.The Data used and during the current study are publicly available in repositories:1. GOSAT data is available at https://data2.gosat.nies.go.jp/index_en.html.2. EVI、PAR 、LST and GPP data are available at https://modis.gsfc.nasa.gov/.3. Meteorological data are available at https://cds.climate.copernicus.eu/datasets/reanalysis-era5-land-monthly-means.4. Population, GDP, and energy data are available at https://en.hainan.gov.cn/hainan/tjnj/list3.shtml.Author informationAuthors and AffiliationsHainan Institute of Meteorological Science, Haikou, 570203, ChinaQi Luo, Jing Han & Shaojun LiuSansha Marine Meteorology Field Experiment Station of CMA, Sansha, 573199, ChinaQi LuoSouth China Sea Marine Meteorology Hainan Observation and Research Station, Sansha, 573199, ChinaJing Han & Shaojun LiuAuthorsQi LuoView author publicationsSearch author on:PubMed Google ScholarJing HanView author publicationsSearch author on:PubMed Google ScholarShaojun LiuView author publicationsSearch author on:PubMed Google ScholarContributionsLuo wrote the main manuscript text and prepared the figures. Han dowload the satellite and reanlysis data. Liu provided technical guidance and revised the article.All authors reviewed the manuscript.Corresponding authorCorrespondence to
Qi Luo.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 articleLuo, Q., Han, J. & Liu, S. Characterization of spatial and temporal variations of CO2 concentration on tropical Island and analysis of influencing factors.
Sci Rep (2025). https://doi.org/10.1038/s41598-025-32647-xDownload citationReceived: 15 May 2025Accepted: 11 December 2025Published: 13 December 2025DOI: https://doi.org/10.1038/s41598-025-32647-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
KeywordsTropical islandCO2 concentrationInfluencing factorsVariation trend More

AbstractThe endosymbiont Wolbachia can both benefit host nutrition and manipulate host reproduction to its own advantage. However, the mechanisms of its nutritional benefits remain unclear. We show that Wolbachia enhances ovarian development in the small brown planthopper Laodelphax striatellus by boosting energy production. Wolbachia-infected females have increased fecundity, accelerated ovarian development, and prolonged oviposition. Enhanced activity of mitochondrial complex I is linked to increased ATP production and the expression of energy metabolism-related genes. We further identify that Wolbachia-synthesized riboflavin is crucial for ATP production and ovarian development. A riboflavin transporter, slc52a3a, positively correlates with Wolbachia density and is required for normal ovarian maturation. Our findings demonstrate that Wolbachia-produced riboflavin drives energy production and accelerates ovarian maturation, thus improving host fecundity. This research reveals insights into symbiont-host metabolic interactions and underscores the role of nutrient delivery in symbiosis.

Data availability

The RNA-seq data generated in this study have been deposited in the NCBI GenBank database under accession code PRJNA1195149, PRJNA1195150, and PRJNA1195152. Source data are provided with this paper.
ReferencesPodsiadło, E., Michalik, K., Michalik, A. & Szklarzewicz, T. Yeast-like microorganisms in the scale insect Kermes quercus (Insecta, Hemiptera, Coccomorpha: Kermesidae). Newly acquired symbionts?. Arthropod Struct. Dev. 47, 56–63 (2018).
Google Scholar 
Mathé-Hubert, H., Kaech, H., Ganesanandamoorthy, P. & Vorburger, C. Evolutionary costs and benefits of infection with diverse strains of Spiroplasma in pea aphids. Evolution 73, 1466–1481 (2019).
Google Scholar 
Paniagua Voirol, L. R., Frago, E., Kaltenpoth, M., Hilker, M. & Fatouros, N. E. Bacterial symbionts in Lepidoptera: their diversity, transmission, and impact on the host. Front. Microbiol. 9, 556 (2018).
Google Scholar 
Pina, T. et al. Molecular characterization of Cardinium, Rickettsia, Spiroplasma and Wolbachia in mite species from citrus orchards. Exp. Appl. Acarol. 81, 335–355 (2020).
Google Scholar 
Porter, J. & Sullivan, W. The cellular lives of Wolbachia. Nat. Rev. Microbiol. 21, 750–766 (2023).
Google Scholar 
Serbus, L. R., Casper-Lindley, C., Landmann, F. & Sullivan, W. The genetics and cell biology of Wolbachia-host interactions. Annu. Rev. Genet. 42, 683–707 (2008).
Google Scholar 
Newton, I. L. G. & Rice, D. W. The Jekyll and Hyde symbiont: could Wolbachia be a nutritional mutualist? J. Bacteriol. 202, e00589–19 (2020).
Google Scholar 
Zug, R. & Hammerstein, P. Bad guys turned nice? A critical assessment of Wolbachia mutualisms in arthropod hosts. Biol. Rev. 90, 89–111 (2015).
Google Scholar 
Brownlie, J. C. et al. Evidence for metabolic provisioning by a common invertebrate endosymbiont, Wolbachia pipientis, during periods of nutritional stress. PLoS Pathog 5, e1000368 (2009).
Google Scholar 
Unckless, R. L. & Jaenike, J. Maintenance of a male-killing Wolbachia in Drosophila innubila by male-killing dependent and male-killing independent mechanisms. Evolution 66, 678–689 (2012).
Google Scholar 
Dedeine, F. et al. Removing symbiotic Wolbachia bacteria specifically inhibits oogenesis in a parasitic wasp. Proc. Natl. Acad. Sci. USA. 98, 6247–6252 (2001).
Google Scholar 
Pannebakker, B. A., Loppin, B., Elemans, C. P. H., Humblot, L. & Vavre, F. Parasitic inhibition of cell death facilitates symbiosis. Proc. Natl. Acad. Sci. USA. 104, 213–215 (2007).
Google Scholar 
Hosokawa, T., Koga, R., Kikuchi, Y., Meng, X.-Y. & Fukatsu, T. Wolbachia as a bacteriocyte-associated nutritional mutualist. Proc. Natl. Acad. Sci. USA. 107, 769–774 (2010).
Google Scholar 
Ju, J.-F. et al. Wolbachia supplement biotin and riboflavin to enhance reproduction in planthoppers. ISME J. 14, 676–687 (2020).
Google Scholar 
Moriyama, M., Nikoh, N., Hosokawa, T. & Fukatsu, T. Riboflavin provisioning underlies Wolbachia’s fitness contribution to its insect host. mBio 6, e01732–01715 (2015).
Google Scholar 
Depeint, F., Bruce, W. R., Shangari, N., Mehta, R. & O’Brien, P. J. Mitochondrial function and toxicity: role of the B vitamin family on mitochondrial energy metabolism. Chem. Biol. Interact. 163, 94–112 (2006).
Google Scholar 
Zhao, R.-Z., Jiang, S., Zhang, L. & Yu, Z.-B. Mitochondrial electron transport chain, ROS generation and uncoupling (Review). Int. J. Mol. Med. 44, 3–15 (2019).
Google Scholar 
Noda, H., Koizumi, Y., Zhang, Q. & Deng, K. Infection density of Wolbachia and incompatibility level in two planthopper species, Laodelphax striatellus and Sogatella furcifera. Insect Biochem. Mol. Biol. 31, 727–737 (2001).
Google Scholar 
Huang, H.-J., Cui, J.-R., Chen, J., Bing, X.-L. & Hong, X.-Y. Proteomic analysis of Laodelphax striatellus gonads reveals proteins that may manipulate host reproduction by Wolbachia. Insect Biochem. Mol. Biol. 113, 103211 (2019).
Google Scholar 
Bing, X.-L., Zhao, D.-S., Peng, C.-W., Huang, H.-J. & Hong, X.-Y. Similarities and spatial variations of bacterial and fungal communities in field rice planthopper (Hemiptera: Delphacidae) populations. Insect Sci 27, 947–963 (2020).
Google Scholar 
Duan, X.-Z. et al. Recent infection by Wolbachia alters microbial communities in wild Laodelphax striatellus populations. Microbiome 8, 104 (2020).
Google Scholar 
Hu, Q.-L. et al. Chromosome-level assembly, dosage compensation and sex-biased gene expression in the small brown planthopper, Laodelphax striatellus. Genome Biol. Evol. 14, evac160 (2022).
Google Scholar 
Jin, C. et al. Riboflavin transporters RFVT/SLC52A mediate translocation of riboflavin, rather than FMN or FAD, across plasma membrane. Biol. Pharm. Bull. 40, 1990–1995 (2017).
Google Scholar 
Gnainsky, Y. et al. Systemic regulation of host energy and oogenesis by microbiome-derived mitochondrial coenzymes. Cell Rep. 34, 108583 (2021).
Google Scholar 
Li, T.-P. et al. Stable establishment of Cardinium spp. in the brown planthopper Nilaparvata lugens despite decreased host fitness. Appl. Environ. Microbiol. 86, e02509–19 (2020).
Google Scholar 
Chen, Y. et al. SOAPnuke: a MapReduce acceleration-supported software for integrated quality control and preprocessing of high-throughput sequencing data. GigaScience 7, gix120 (2018).
Google Scholar 
Chen, S., Zhou, Y., Chen, Y. & Gu, J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 34, i884–i890 (2018).
Google Scholar 
Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).
Google Scholar 
Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15, 550 (2014).
Google Scholar 
R Core Team. R: a language and environment for statistical computing (R Foundation for Statistical Computing, 2024).Langfelder, P. & Horvath, S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics 9, 559 (2008).
Google Scholar 
Yu, G., Wang, L.-G., Han, Y. & He, Q.-Y. clusterProfiler: an R package for comparing biological themes among gene clusters. Omics J. Integr. Biol. 16, 284–287 (2012).
Google Scholar 
Golbach, J. L., Chalova, V. I., Woodward, C. L. & Ricke, S. C. Adaptation of Lactobacillus rhamnosus riboflavin assay to microtiter plates. J. Food Compos. Anal. 20, 568–574 (2007).
Google Scholar 
Pan, X., Lu, K., Qi, S., Zhou, Q. & Zhou, Q. The content of amino acids in artificial diet influences the development and reproduction of brown planthopper, Nilaparvata lugens (STÅL). Arch. Insect Biochem. Physiol. 86, 75–84 (2014).
Google Scholar 
Li, T.-P. et al. Two newly introduced Wolbachia endosymbionts induce cell host differences in competitiveness and metabolic responses. Appl. Environ. Microbiol. 87, e0147921 (2021).
Google Scholar 
Jiang, W. & Zhu, T. F. Targeted isolation and cloning of 100-kb microbial genomic sequences by Cas9-assisted targeting of chromosome segments. Nat. Protoc. 11, 960–975 (2016).
Google Scholar 
Mendiburu, F. D. & Simon, R. Agricolae – ten years of an open source statistical tool for experiments in breeding, agriculture and biology. PeerJ Prepr. 3, e1404v1401 (2015).Download referencesAcknowledgementsWe thank Prof. Fei-Rong Ren from Henan University, Dr. Xiang Sun and Tianyu Wang from Shenyang Agricultural University for their technical and material support in riboflavin detection experiments. We also thank Hao Zhang from Nanjing Agricultural University for his help in preparing RNA-seq samples. This work was supported by the Key Research and Development Project of Hainan Province (ZDYF2024XDNY249 to X.Y.H.), the National Natural Science Foundation of China (32572809 to X.L.B. and 32020103011 to X.Y.H.), and the Young Elite Scientists Sponsorship Program by Jiangsu Association for Science and Technology (TJ-2023-038 to X.L.B.). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Author informationAuthors and AffiliationsState Key Laboratory of Agricultural and Forestry Biosecurity, College of Plant Protection, Nanjing Agricultural University, Nanjing, Jiangsu, ChinaYue-Di Niu, Qi-Hang Fan, Zi-Han Wang, Meng-Ke Wang, Dian-Shu Zhao, Meng-Ru Wang, Bing-Xuan Wu, Xiao-Yue Hong & Xiao-Li BingAuthorsYue-Di NiuView author publicationsSearch author on:PubMed Google ScholarQi-Hang FanView author publicationsSearch author on:PubMed Google ScholarZi-Han WangView author publicationsSearch author on:PubMed Google ScholarMeng-Ke WangView author publicationsSearch author on:PubMed Google ScholarDian-Shu ZhaoView author publicationsSearch author on:PubMed Google ScholarMeng-Ru WangView author publicationsSearch author on:PubMed Google ScholarBing-Xuan WuView author publicationsSearch author on:PubMed Google ScholarXiao-Yue HongView author publicationsSearch author on:PubMed Google ScholarXiao-Li BingView author publicationsSearch author on:PubMed Google ScholarContributionsThe authors contributed to the present study as follows: Y.D.N., X.L.B., and X.Y.H. designed the research; Y.D.N., Q.H.F., Z.H.W., M.K.W., D.S.Z., M.R.W., B.X.W., and X.L.B. performed the research and analyzed the data; Y.D.N., X.L.B., and X.Y.H. wrote and edited the manuscript; all authors read and approved the manuscript.Corresponding authorsCorrespondence to
Xiao-Yue Hong or Xiao-Li Bing.Ethics declarations

Competing interests
The authors declare no competing interests.

Peer review

Peer review information
Nature Communications thanks the anonymous, reviewer(s) for their contribution to the peer review of this work. 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 InformationDescriptions of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Reporting SummaryTransparent Peer Review fileSource dataSource Data 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 articleNiu, YD., Fan, QH., Wang, ZH. et al. Wolbachia enhances ovarian development in the rice planthopper Laodelphax striatellus through elevated energy production.
Nat Commun (2025). https://doi.org/10.1038/s41467-025-67660-1Download citationReceived: 02 March 2025Accepted: 05 December 2025Published: 13 December 2025DOI: https://doi.org/10.1038/s41467-025-67660-1Share 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

AbstractMosquitoes of the Anopheles, Aedes, and Culex genera are responsible for transmitting major vector-borne diseases. Malaria remains a significant public health concern in Odisha, primarily due to the state’s conducive environment for Anopheles mosquito breeding. This study, conducted between March 2021 and February 2023 across 11 traditionally hyper-endemic districts in southern Odisha, aimed to assess seasonal variations in Anopheles diversity, composition, and abundance. A total of 10,807 Anopheles mosquito’s species were collected manually indoors (house dwellings and cattle sheds) and outdoors (burrows, vegetation, tree holes, and culverts). Morphological identification revealed 18 Anopheles species. An. subpictus was the predominant species during the summer of 2021, with (328; 42.99%), and during the rainy season, with (1151; 46.60%), although its prevalence declined in subsequent years. An. culicifacies, a primary malaria vector, exhibited a consistent presence with (780; 31.58%) in the rainy season of 2021 and (798; 38.35%) in the rainy season of 2022. An. varuna remained scarce during summer and rainy seasons but peaked sharply in winter, with the highest prevalence in winter 2021–2022 (730; 35.56%) and winter 2022–2023 (485; 25.18%). Diversity indices (Shannon’s, Simpson’s, Pielou’s) and Correspondence Analysis identified Ganjam as the district with the highest species diversity (1.26–2.2). Seasonal variation had a statistically significant impact on species diversity (p < 0.001), surpassing the influence of district level factors. These findings show that seasonality strongly influences Anopheles populations and highlight the need for localized, evidence-based vector control. Monitoring of mosquito diversity is vital for shaping malaria interventions suited to Odisha’s transmission ecology.

Data availability

All data generated or analysed during this study are included in this published article.
AbbreviationsDDT:
Dichloro-diphenyl-trichloroethane
IVM:
Integrated vector management
H’:
Shannon’s diversity index
D:
Simpson’s index
J’:
Pielou index
CA:
Correspondence analysis
OWMS:
Odisha weather monitoring systems
LLINs:
Long-lasting insecticidal nets
ReferencesSharma, G., Chittora, S. & Ojha, R. Study on mosquito (Diptera: Culicidae) diversity in Jodhpur district of the Rajasthan state. Int. J. Mosq. Res. 8, 16–19 (2021).
Google Scholar 
(PDF) The Culicidae (Diptera): A Review Of Taxonomy, Classification And Phylogeny *. ResearchGate (2025). https://doi.org/10.5281/zenodo.180118Vander Does, A., Labib, A. & Yosipovitch, G. Update on mosquito bite reaction: itch and hypersensitivity, pathophysiology, prevention, and treatment. Front. Immunol. 13, 1024559 (2022).
Google Scholar 
Hawkes, F. M. & Hopkins, R. J. in Mosquitopia Place Pests Healthy World (eds. Hall, M. & Tamïr, D.)Routledge, at (2022).http://www.ncbi.nlm.nih.gov/books/NBK585164/Carvajal-Lago, L., Ruiz-López, M. J. & Figuerola, J. Martínez-de La Puente, J. Implications of diet on mosquito life history traits and pathogen transmission. Environ. Res. 195, 110893 (2021).
Google Scholar 
Ellwanger, J. H., Cardoso, J. C. & Chies, J. A. B. Variability in human attractiveness to mosquitoes. Curr. Res. Parasitol. Vector-Borne Dis. 1, 100058 (2021).
Google Scholar 
Sum of World Malaria Report. (2021). at https://www.who.int/india/health-topics/malaria/summary-of-world-malaria-report-2021Malaria :: National Center for Vector Borne Diseases Control (NCVBDC). at https://ncvbdc.mohfw.gov.in/index1.php?lang=1&level=1&sublinkid=5784&lid=3689Lindsay, S. W. & Birley, M. H. Climate change and malaria transmission. Ann. Trop. Med. Parasitol. 90, 573–588 (1996).
Google Scholar 
Karmakar, M. & Pradhan, M. M. Climate change and public health: a study of vector-borne diseases in Odisha, India. Nat. Hazards J. Int. Soc. Prev. Mitig Nat. Hazards. 102, 659–671 (2020).
Google Scholar 
Mosquito Borne Diseases in Wetland zones. at https://iictenvis.nic.in/Database/Mosquito_1453.aspx(PDF) Species diversity and community composition of mosquitoes in a filariasis endemic area in Banyuasin District, South Sumatra, Indonesia. ResearchGate (2025). https://doi.org/10.13057/biodiv/d200222Nh, O. Climate change and vector-borne diseases of public health significance. FEMS Microbiol. Lett. 364, fnx186 (2017).
Google Scholar 
Cator, L. J., Lynch, P. A., Thomas, M. B. & Read, A. F. Alterations in mosquito behaviour by malaria parasites: potential impact on force of infection. Malar. J. 13, 164 (2014).
Google Scholar 
Mosquito-Borne Diseases Emergence/Resurgence and How to Effectively Control It Biologically. at https://www.mdpi.com/2076-0817/9/4/310Steiger, D. B. M., Ritchie, S. A. & Laurance, S. G. W. Land use influences mosquito communities and disease risk on remote tropical islands: A case study using a novel sampling technique. Am. J. Trop. Med. Hyg. 94, 314–321 (2016).
Google Scholar 
Machault, V. et al. Highly focused anopheline breeding sites and malaria transmission in Dakar. Malar. J. 8, 138 (2009).
Google Scholar 
Malaria Parasite, Mosquito, and Human Host | NIAID: National Institute of Allergy and Infectious Diseases. at https://www.niaid.nih.gov/diseases-conditions/malaria-parasite(PDF) Prevalence of Malaria and Associated Risk Factors Among Febrile Children Under Five Years: A Cross-Sectional Study in Arba Minch Zuria District, South Ethiopia. ResearchGate https://doi.org/10.2147/IDR.S223873Franklinos, L. H. V., Jones, K. E., Redding, D. W. & Abubakar, I. The effect of global change on mosquito-borne disease. Lancet Infect. Dis. 19, e302–e312 (2019).
Google Scholar 
Numerical Modeling of the Dynamics of Malaria Transmission in a Highly Endemic Region of India | Scientific Reports. at(2019) https://www.nature.com/articles/s41598-019-47212-6Sahu, S. S. et al. Response of malaria vectors to conventional insecticides in the Southern districts of Odisha State, India. Indian J. Med. Res. 139, 294–300 (2014).
Google Scholar 
Batson, J. et al. Single mosquito metatranscriptomics identifies vectors, emerging pathogens and reservoirs in one assay. eLife 10, e68353 (2021).
Google Scholar 
Namias, A., Jobe, N. B., Paaijmans, K. P. & Huijben, S. The need for practical insecticide-resistance guidelines to effectively inform mosquito-borne disease control programs. eLife 10, e65655 (2021).
Google Scholar 
Ranson, H. et al. Insecticide resistance in Anopheles gambiae: data from the first year of a multi-country study highlight the extent of the problem. Malar. J. 8, 299 (2009).
Google Scholar 
Handbook for integrated vector management. at https://www.who.int/publications/i/item/9789241502801Hemingway, J. et al. Tools and strategies for malaria control and elimination: what do we need to achieve a grand convergence in malaria? PLoS Biol. 14, e1002380 (2016).
Google Scholar 
Rakotonirina, A., Maquart, P. O., Flamand, C., Sokha, C. & Boyer, S. Mosquito diversity (Diptera: Culicidae) and medical importance in four Cambodian forests. Parasit. Vectors. 16, 110 (2023).
Google Scholar 
Odisha, I. N. Climate Zone, Monthly Weather Averages and Historical Data. at https://weatherandclimate.com/india/odishaNikookar, S. H., Maleki, A., Fazeli-Dinan, M., Shabani Kordshouli, R. & Enayati, A. Entomological surveillance of the invasive Aedes species at Higher-Priority entry points in Northern iran: exploratory report on a field study. JMIR Public. Health Surveill. 8, e38647 (2022).
Google Scholar 
Kumar, A., Sonia, T., Dash, S., Krishnamoorthy, N. & Sahu, S. S. Impact of long-lasting insecticidal Nets on host seeking behaviour of Anopheles fluviatilis and Anopheles culicifacies in hyper endemic falciparum area of Odisha state. Int. J. Mosq. Res. 5, 28–33 (2018).
Google Scholar 
Sahu, S. S. et al. Bionomics of Anopheles fluviatilis and Anopheles culicifacies (Diptera: Culicidae) in relation to malaria transmission in East-Central India. J. Med. Entomol. 54, 821–830 (2017).
Google Scholar 
Christophers, S. R. The fauna of British India, including Ceylon and Burma. Diptera.Vol. IV. Family Culicidae. Tribe Anophelini (Taylor and Francis, 1933).
Google Scholar 
Shannon, C. E. AMathematical theory of communication. Bell Syst. Tech. J. 27, 379–423 (1948).
Google Scholar 
Magurran, A. E. In in Ecol. Divers. Its Meas (ed. Magurran, A. E.) 7–45 (Springer, 1988). https://doi.org/10.1007/978-94-015-7358-0_2.
Google Scholar 
Khoobdel, M., Keshavarzi, D., Mossa-Kazemi, S. H. & Sobati, H. Species diversity of mosquitoes of the genus culex (Diptera, Culicidae) in the coastal areas of the Persian Gulf. AIMS Public. Health. 6, 99–106 (2019).
Google Scholar 
Pielou, E. C. Shannon’s formula as a measure of specific diversity: its use and misuse. Am. Nat. 100, 463–465 (1966).
Google Scholar 
Odisha, W. Monitoring System (OWMS). at https://rainfall.nic.in/rainfallnew/PublicDistWiseMonthlyReport.aspxPradhan, N., Mahapatra, R. K. & Hazra, R. K. A snapshot of few biological and bionomical characteristics ofanopheles culicifacies and Anopheles annularis in three malariogenically stratified districts of Odisha, India. J. Egypt. Soc. Parasitol. 50, 689–697 (2020).
Google Scholar 
Potential future malaria transmission in Odisha due to climate change | Scientific Reports. at https://www.nature.com/articles/s41598-022-13166-5Sahu, S. S., Gunasekaran, K., Vanamail, P. & Jambulingam, P. Persistent foci of falciparum malaria among tribes over two decades in Koraput district of Odisha State, India. Malar. J. 12, 72 (2013).
Google Scholar 
Drugs, I. of M. (US) C. on the E. of A., Arrow, K. J., Panosian, C. & Gelband, H. in Sav. Lives Buy. Time Econ. Malar. Drugs Age Resist. (National Academies Press (US), at (2004). https://www.ncbi.nlm.nih.gov/books/NBK215619/Afrane, Y. A., Githeko, A. K. & Yan, G. The ecology of Anopheles mosquitoes under climate change: case studies from the effects of deforestation in East African highlands. Ann. N Y Acad. Sci. 1249, 204–210 (2012).
Google Scholar 
Beck-Johnson, L. M. et al. The effect of temperature on Anopheles mosquito population dynamics and the potential for malaria transmission. PloS One. 8, e79276 (2013).
Google Scholar 
Agyekum, T. P. et al. A systematic review of the effects of temperature on Anopheles mosquito development and survival: implications for malaria control in a future warmer climate. Int. J. Environ. Res. Public. Health. 18, 7255 (2021).
Google Scholar 
Baril, C. et al. The influence of weather on the population dynamics of common mosquito vector species in the Canadian prairies. Parasit. Vectors. 16, 153 (2023).
Google Scholar 
Singh, U. S. et al. Characterisation of Anopheles species composition and genetic diversity in Meghalaya, Northeast India, using molecular identification tools. Infect. Genet. Evol. J. Mol. Epidemiol. Evol. Genet. Infect. Dis. 112, 105450 (2023).
Google Scholar 
Ak, S. & Sb, P. Study of Diversity and Abundance of Anopheline Mosquitoes in Meghalaya, India. at https://austinpublishinggroup.com/infectious-diseases/fulltext/ajid-v2-id1016.phpDas, N. G., Gopalakrishnan, R., Talukdar, P. K. & Baruah, I. Diversity and seasonal densities of vector anophelines in relation to forest fringe malaria in district Sonitpur, Assam (India). J. Parasit. Dis. Off Organ. Indian Soc. Parasitol. 35, 123–128 (2011).
Google Scholar 
Operational manual for integrated vector management in India. at (2016). https://nvbdcp.gov.in/WriteReadData/l892s/IVM10_March_2016.pdfRao, M. R. K., Padhy, R. N. & Das, M. K. Surveillance on malaria and dengue vectors fauna across in angul district of Odisha, india: an approach to determine their diversity and Abundance, correlation with the ecosystem. J. Entomol. Zool. Stud. 3, 459–469 (2015).
Google Scholar 
Anopheles subpictus carry human malaria parasites in an urban area of Western India and may facilitate perennial malaria transmission | Malaria Journal | Full Text. at https://malariajournal.biomedcentral.com/articles/https://doi.org/10.1186/s12936-016-1177-xThomas, S. et al. Resting and feeding preferences of Anopheles stephensi in an urban setting, perennial for malaria. Malar. J. 16, 111 (2017).
Google Scholar 
Kumari, S., Das, S. & Mahapatra, N. Anopheles subpictus B and its role in transmission of malaria in Odisha, India. Trop. Biomed. 30, 710–717 (2013).
Google Scholar 
Kulkarni, S. Detection of sporozoites in Anopheles subpictus in baster district, Madhya Pradesh. Indian J. Malariol. 20, 159–160 (1983).
Google Scholar 
Das, M. et al. Anopheles culicifacies sibling species in Odisha, Eastern india: first appearance of Anopheles culicifacies E and its vectorial role in malaria transmission. Trop. Med. Int. Health TM IH. 18, 810–821 (2013).
Google Scholar 
Panda, B. B., Mohanty, I., Rath, A., Pradhan, N. & Hazra, R. K. Perennial malaria transmission and its association with rainfall at Kalahandi district of Odisha, Eastern india: A retrospective analysis. Trop. Biomed. 36, 610–619 (2019).
Google Scholar 
Tripathy, A. et al. Distribution of sibling species of Anopheles culicifacies s.l. And Anopheles fluviatilis s.l. And their vectorial capacity in eight different malaria endemic districts of Orissa, India. Mem. Inst. Oswaldo Cruz. 105, 981–987 (2010).
Google Scholar 
Das, B. et al. Vectorial capacity and genetic diversity of Anopheles annularis (Diptera: Culicidae) mosquitoes in Odisha, India from 2009 to 2011. Acta Trop. 137, 130–139 (2014).
Google Scholar 
Gunasekaran, K., Sahu, S. S. & Jambulingam, P. Estimation of vectorial capacity of Anopheles minimus Theobald & An. fluviatilis James (Diptera: Culicidae) in a malaria endemic area of Odisha State, India. Indian J. Med. Res. 140, 653–659 (2014).
Google Scholar 
Sahu, S. S. et al. Multiple insecticide resistance in Anopheles culicifacies s.l. (Diptera: Culicidae) in east-central India. Pathog Glob Health. 113, 352–358 (2019).
Google Scholar 
Rath, A. et al. A shift in resting habitat and feeding behavior of Anopheles fluviatilis sibling species in the Keonjhar district of Odisha, India. Trans. R Soc. Trop. Med. Hyg. 109, 730–737 (2015).
Google Scholar 
Möhlmann, T. W. R. et al. Community analysis of the abundance and diversity of mosquito species (Diptera: Culicidae) in three European countries at different latitudes. Parasit. Vectors. 10, 510 (2017).
Google Scholar 
Poonja, M. Study of seasonal and Spatial variation of mosquito species in Kalyan, Maharashtra. Int. J. Entomol. Res. 9, 90–95 (2024).
Google Scholar 
Barrientos-Roldán, M. J., Abella-Medrano, C. A., Ibáñez-Bernal, S. & Sandoval-Ruiz, C. A. Landscape anthropization affects mosquito diversity in a deciduous forest in southeastern Mexico. J. Med. Entomol. 59, 248–256 (2022).
Google Scholar 
Kaboré, D. P. A. et al. Mosquito (Diptera: Culicidae) populations in contrasting areas of the Western regions of Burkina faso: species diversity, abundance and their implications for pathogen transmission. Parasit. Vectors. 16, 438 (2023).
Google Scholar 
Download referencesAcknowledgementsWe extend sincere appreciation to Malaria Elimination Research Alliance (MERA) India for providing the essential funding that made this project possible. We are also deeply grateful to the technical staff for their invaluable assistance throughout the study. Furthermore, we acknowledge the support and cooperation of the inhabitants of all sampling sites and the dedicated volunteers whose significant contributions during fieldwork were indispensable. This research would not have been possible without their collective efforts.Author informationAuthor notesThese authors contributed equally: Muhammed Mustafa Baig and Divya Teja Koppula.Authors and AffiliationsICMR-Vector Control Research Centre Field Unit, Near Hati lane, Koraput, Odisha, 764 020, IndiaMuhammed Mustafa Baig, Dilip Kumar Panigrahi, Dolly Choudhary, Premalatha Acharya & Manoj PatnaikICMR-Vector Control Research Centre, Medical Complex, Indira Nagar, Puducherry, IndiaDivya Teja Koppula, B. Vijayakumar, K. Gunasekaran, Ashwani Kumar, Manju Rahi & A. N. ShriramAuthorsMuhammed Mustafa BaigView author publicationsSearch author on:PubMed Google ScholarDivya Teja KoppulaView author publicationsSearch author on:PubMed Google ScholarDilip Kumar PanigrahiView author publicationsSearch author on:PubMed Google ScholarB. VijayakumarView author publicationsSearch author on:PubMed Google ScholarDolly ChoudharyView author publicationsSearch author on:PubMed Google ScholarPremalatha AcharyaView author publicationsSearch author on:PubMed Google ScholarManoj PatnaikView author publicationsSearch author on:PubMed Google ScholarK. GunasekaranView author publicationsSearch author on:PubMed Google ScholarAshwani KumarView author publicationsSearch author on:PubMed Google ScholarManju RahiView author publicationsSearch author on:PubMed Google ScholarA. N. ShriramView author publicationsSearch author on:PubMed Google ScholarContributionsConceptualization and design: ANS, and AK.Writing – original draft preparation: DTK, MMB and ANS; Conducting the field study and supervision: DKP, DC, PA, MP and MMBWriting – review and editing with inputs from all other authors: ANS, AK, DTK and MR; Acquisition of data, analysis and interpretation: VK, DTK and ANSRevising it critically for intellectual content and the final approval of the version to be published: AK, ANS and MR. All authors provided critical feedback. All authors have read and agreed to the final version of the manuscript and to be accountable for all aspects of the work.Corresponding authorCorrespondence to
A. N. Shriram.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-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 articleBaig, M.M., Koppula, D.T., Panigrahi, D.K. et al. Seasonal dynamics and species diversity of Anopheles mosquitoes in malaria endemic districts of Southern Odisha India.
Sci Rep (2025). https://doi.org/10.1038/s41598-025-28997-1Download citationReceived: 09 June 2025Accepted: 13 November 2025Published: 13 December 2025DOI: https://doi.org/10.1038/s41598-025-28997-1Share 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
KeywordsMalariaOdishaShannon’sSimpson’sAnd pielou’s
Anopheles diversity More

AbstractWild edible fruits are rich in micronutrients and serve as an essential source of nutrition for the poor in developing countries, where malnutrition is widespread. The morphological and nutritional compositions of Bauhinia thonningii pod and seed were evaluated using samples collected from two distinct agroecological zones, the warm moist lowlands (WMLL) and tepid sub-moist mid-highlands (TSMMHL), in the Tselemti district, Ethiopia. Data were analyzed using independent sample t-test, ANOVA with a general linear model, and Principal component analysis (PCA) for morphological traits, proximate composition, and mineral content to determine their association with agroecological zones. The results showed that morphological traits such as the mean pod length (p < 0.000), pod width (p = 0.036), pod thickness (p = 0.005), pericarp weight (p = 0.006), total seed weight (p = 0.003), individual seed weight (p = 0.005), and number of seeds per pod (p < 0.000) differed significantly between the two agroecological zones (p < 0.05). Higher mean values of pod length (18.34 cm), width (2.87 cm), thickness (0.85 cm), total pod weight (11.56 g), total seed weight (8.93 g), and number of seeds per pod (51 ns) were recorded in the warm moist lowlands compared to the tepid sub-moist mid-highlands. The moisture content of the B. thonningii pod (9.02%) and seed (7.02%) was higher in tepid sub-moist mid-highlands than in the warm moist lowlands. The crude protein (9.74 and 30.73%), crude fat (0.96 and 2.48%), crude fiber (26.03 and 32.86%), total carbohydrates (56.30 and 33.70%), and energy values (1106.36 and 1103.87 kJ/100 g) of the pod and seed, respectively, were higher in the WMLL compared to the TSMMHL. All proximate compositions of the B. thonningii pod and seed varied significantly between the two agroecological zones (p < 0.05), except for ash content. Most mineral concentrations in the pod and seeds, such as calcium (152.26 and 36.77 mg/100 g), magnesium (129.59 and 8.04 mg/100 g), potassium (1325.44 and 130.61 mg/100 g), and sodium (8.99 and 16.90 mg/100 g), were significantly higher in the warm moist lowland agroecology. This may be attributed to higher humidity, soil mineralization, evaporative concentration, and increased soil nutrient movement under warm lowland environmental conditions. Significant differences were observed in the concentrations of all minerals in the pods and seeds between the agroecologies, except for magnesium and zinc in the seed analysis. Overall, the findings indicate that understanding the morphological, proximate, and mineral compositions of B. thonningii is valuable for its sustainable utilization, conservation, domestication, and breeding. The pods and seeds of B. thonningii possess high nutritional potential and could be used for both human and animal nutrition following further detailed investigation.

Data availability

Data are available from the corresponding author upon reasonable request. Requests should include a detailed rationale for data access and a commitment to using the data solely for the stated purpose, in compliance with ethical guidelines.
ReferencesChauke, S., Shelembe, B. G., Otang-Mbeng, W. & Ndhlovu, P. T. Ethnobotanical appraisal of wild fruit species used in Mpumalanga Province, South Africa: A systematic review. S. Afr. J. Bot. 171, 602–633. https://doi.org/10.1016/j.sajb.2024.06.047 (2024).
Google Scholar 
Khan, M. N. et al. An in-depth investigation of the nutraceutical value and medicinal perspectives of wild medicinal plants in Ojhor Valley, Hindukush Range, Chitral Pakistan. Genet. Resour. Crop Evol. https://doi.org/10.1007/s10722-024-01996-3 (2024).
Google Scholar 
Asprilla-Perea, J. & Díaz-Puente, J. M. Importance of wild foods to household food security in tropical forest areas. Food Sec. 11, 15–22. https://doi.org/10.1007/s12571-018-0846-8 (2019).
Google Scholar 
Suwardi, A. B. & Navia, Z. I. Sustainable use and management of wild edible fruit plants: A Case Study in the Ulu Masen Protected Forest, West Aceh. Indonesia. J. Sustain. For. 42(8), 811–830. https://doi.org/10.1080/10549811.2022.2123355 (2023).
Google Scholar 
Anbessa, B., Lulekal, E., Getachew, P. & Hymete, A. Ethnobotanical study of wild edible plants in Dibatie district, Metekel zone, Benishangul Gumuz Regional State, western Ethiopia. J. Ethnobiol. Ethnomed. 20(27). https://doi.org/10.1186/s13002-024-00671-2 (2024).Priyadarshini, S., Tudu, S., Dash, S. S., Biswal, A. K. & Sahu, S. C. Wild edible plants: diversity, use pattern and livelihood linkage in Eastern India. Genet. Resour. Crop Evol. https://doi.org/10.1007/s10722-023-01833-z (2024).
Google Scholar 
Angami, T. et al. Exploring the nutritional potential and anti-nutritional components of wild edible fruits of the Eastern Himalayas. Food Measure 18, 150–167. https://doi.org/10.1007/s11694-023-02147-5 (2024).
Google Scholar 
Okello, J., Okullo, J. B., Eilu, G., Nyeko, P. & Obua, J. Mineral composition of Tamarindus indica LINN (Tamarind) pulp and seeds from different agro-ecological zones of Uganda. Food Sci. Nutr. 5(5), 959–966. https://doi.org/10.1002/fsn3.490 (2017).
Google Scholar 
Amarteifio, J. O. & Mosase, M. O. The chemical composition of selected indigenous fruits of Botswana. J. Appl. Sci. Environ. Manag. 10(2), 43–47. https://doi.org/10.4314/jasem.v10i2.43659 (2006).
Google Scholar 
Biswas, S. C. et al. Nutritional composition and antioxidant properties of the wild edible fruits of Tripura Northeast India. Sustainability 14(19), 12194. https://doi.org/10.3390/su141912194 (2022).
Google Scholar 
Rymbai, H., Verma, V. K., Talang, H., Assumi, S. R., Devi, M. B., Vanlalruati, Sangma, R. H. C. H., Biam, K. P., Chanu, L. J., Makdoh, B., Singh, A. R., Mawleiñ, J., Hazarika, S. & Mishra, V. K. Biochemical and antioxidant activity of wild edible fruits of the eastern Himalaya, India. Front Nutr. 10, 1039965. https://doi.org/10.3389/fnut.2023.1039965 (2023).Beleta, K. G., Jiru, D. B. & Tolera, K. D. Assessment of edible woody plants’ diversity, their threats, and local people’s perception in Borecha Woreda of Buno Bedele Zone Southwestern Ethiopia. Int. J. For. Res. 2024, 7269154. https://doi.org/10.1155/2024/7269154 (2024).
Google Scholar 
Jimoh, F. O. & Oladiji, A. T. Preliminary studies on Piliostigma thonningii seeds: proximate analysis, mineral composition and phytochemical screening. Afr. J. Biotechnol. 4(12), 1439–1442 (2005).
Google Scholar 
Bekele-Tesemma, A. Useful trees of Ethiopia: identification, propagation and management in 17 agroecological zones. Nairobi: RELMA in ICRAF Project, 552 (2007).Chidumayo, E. N. Growth responses of an African savanna tree, Bauhinia thonningii Schumacher, to defoliation, fire and climate. Trees 21(2), 231–238. https://doi.org/10.1007/s00468-006-0115-x (2007).
Google Scholar 
Ozolua, R. I., Alonge, P. & Igbe, I. Effects of leaf extracts of Piliostigma thonningii Schum on Aortic ring contractility and bleeding time in Rats. J. Herbs Spices Med. plants 15(4), 326–333. https://doi.org/10.1080/10496470903507874 (2010).
Google Scholar 
Yahia, E. M., García-Solís, P. & Celis, M. E. M. Chapter 2-Contribution of fruits and vegetables to human nutrition and health, Editor(s): Elhadi M. Yahia, Postharvest Physiology and Biochemistry of Fruits and Vegetables, Woodhead Publishing, 19–45, ISBN 9780128132784. https://doi.org/10.1016/B978-0-12-813278-4.00002-6 (2019).Kaparapu, J., Pragada, P. M. & Geddada, M. N. R. Fruits and vegetables and its nutritional benefits. In: Egbuna, C., Dable Tupas, G. (eds) Functional Foods and Nutraceuticals. Springer, Cham., pages 241–260. https://doi.org/10.1007/978-3-030-42319-3_14 (2020).Ighodaro, O. M., Agunbiade, S. O., Omole, J. O. & Kuti, O. A. Evaluation of the chemical, nutritional, antimicrobial and antioxidant-vitamin profiles of Piliostigma thonningii leaves (Nigerian species). Res. J. Med. Plant 6(7), 537–543. https://doi.org/10.3923/rjmp.2012.537.543 (2012).
Google Scholar 
Dieng, S. I. M. et al. Evaluation of the antioxidant activity of hydro-ethanolic leaf and bark extracts of Piliostigma thonningii Schumach. Int. J. Biol. Chem. Sci. 11(2), 768–776. https://doi.org/10.4314/ijbcs.v11i2.19 (2017).
Google Scholar 
Ibewuike, J. C., Ogungbamila, F. O., Ogundaini, A. O., Okeke, I. N. & Bohlin, L. Antiinflammatory and antibacterial activities of c-methylflavonols from Piliostigma thonningii. Phytother. Res. 11(4), 281–284 (1997).
Google Scholar 
Akinpelua, D. A. & Obuotor, E. M. Antibacterial activity of Piliostigma thonningii stem bark. Fitoterapia 71, 442–443. https://doi.org/10.1016/S0367-326X(00)00136-2 (2000).
Google Scholar 
Egharevba, H. O. & Kunle, F. O. Preliminary phytochemical and proximate analysis of the leaves of Piliostigma thonningii (Schumach) Milne-Redhead. Ethnobot Leaflets 14(5), 570–577 (2010).
Google Scholar 
Ayenew, A., Tolera, A., Nurfeta, A. & Assefa, G. Utilization and nutritive value of Piliostigma thonningii as ruminant feed in North Western Ethiopia. Ethiop. J. Appl. Sci. Technol. 10(2), 1–10 (2019).
Google Scholar 
Zenda, M. & Rudolph, M. A Systematic review of agroecology strategies for adapting to climate change impacts on smallholder crop farmers’ livelihoods in South Africa. Climate 12(3), 33. https://doi.org/10.3390/cli12030033 (2024).
Google Scholar 
Munialo, S. et al. Systematic review of the agro-ecological, nutritional, and medicinal properties of the neglected and underutilized plant species Tylosema fassoglense. Sustainability 16(14), 6046. https://doi.org/10.3390/su16146046 (2024).
Google Scholar 
Brym, Z. T. & Reeve, J. R. Agroecological principles from a bibliographic analysis of the term agroecology. In Lichtfouse, E. (eds) Sustainable Agriculture Reviews. Sustainable Agriculture Reviews, Vol 19. Springer, Cham. https://doi.org/10.1007/978-3-319-26777-7_5 (2016).Sinclair, F., Wezel, A., Mbow, C., Chomba, S., Robiglio, V. & Harrison, R. The contribution of agroecological approaches to realizing climate-resilient agriculture. Rotterdam and Washington, DC. Available online at www.gca.org (2019).Kerr, R. B. et al. Can agroecology improve food security and nutrition?. A review. Glob. Food Secur. 29, 100540. https://doi.org/10.1016/j.gfs.2021.100540 (2021).
Google Scholar 
Reguera, M. et al. The impact of different agroecological conditions on the nutritional composition of quinoa seeds. Peer J. 6, e4442. https://doi.org/10.7717/peerj.444 (2018).
Google Scholar 
Okello, J., Okullo, J. B. L., Eilu, G., Nyeko, P. & Obua, J. Physicochemical composition of Tamarindus indica L. (Tamarind) Fruits in the agro-ecological zones of Uganda. Food Sci. Nutr. 6, 1179–1189. https://doi.org/10.1002/fsn3.627 (2018).Gebregerges, T., Tessema, Z. K. & Birhane, E. Effect of exclosure ages on woody plant structure, diversity and regeneration potential in the western Tigray region of Ethiopia. J. For. Res. 29(3), 697–707. https://doi.org/10.1007/s11676-017-0512-6 (2018).
Google Scholar 
EIAR. New agroecological map of Ethiopia. Coordination of national agricultural research system, Ethiopia. Ethiopian Institute of Agricultural Research, Addis Ababa: EIAR. (2011).Gebramlak, G. D., Abadi, N. & Hizikias, E. B. Socioeconomic contribution of Oxytenanthera abyssinica (A.Rich) Munro and determinants of growing in homestead agroforestry system in Northern Ethiopia. Ethnobot. Res. Appl. 14, 479–490. https://doi.org/10.17348/era.14.0.479-490 (2016).
Google Scholar 
Hernadez-Unzon, H. Y. & Laksminarayana, S. Biochemical changes during development and ripening of Tamarind Fruit (Tamarindus indica L.). Hort. Science 17(6), 940–942. https://doi.org/10.21273/HORTSCI.17.6.940 (1982).
Google Scholar 
Tadesse, D., Masresha, G., Lulekal, E. & Alemu, A. Ethnobotanical study of wild edible plants in Metema and Quara districts Northwestern Ethiopia. J. Ethnobiol. Ethnomed. 21, 7. https://doi.org/10.1186/s13002-025-00761-9 (2025).
Google Scholar 
AOAC. Official Methods of Analysis. 17th ed. Washington, DC, USA: Association of Official Analytical Chemists. (2000).FAO, Food energy–methods of analysis and conversion factors. Report of a Technical Workshop. Food Nutrition 77 (2003).Fadel, F. et al. Morphometric and physicochemical characteristics of carob pods in three geographical regions of Morocco. SN Appl. Sci. 2, 2173. https://doi.org/10.1007/s42452-020-03963-w (2020).
Google Scholar 
Datir, S., Tetali, P. & Kumatkar, P. Nutritional evaluation from Nesphostylis bracteata (Syn: Sphenostylis bracteata): potentially important underutilized wild legume of the Northern Western Ghats of India. Genet. Resour. Crop Evol. https://doi.org/10.1007/s10722-024-02101-4 (2024).
Google Scholar 
Girmay, H., Tewolde-Berhan, S., Hishe, H., Asfaw, Z., Morgan, R. & Alison, P. Use and management of tamarind (Tamarindus indica L., Fabaceae) local morphotypes by communities in Tigray, Northern Ethiopia. For. Trees Livelihoods 29(2), 81–98. https://doi.org/10.1080/14728028.2020.1737582 (2020).Van den Bilcke, N., Alaerts, K., Ghaffaripour, S., Simbo, D. J. & Samson, R. Physico-chemical properties of tamarind (Tamarindus indica L.) fruits from Mali: selection of elite trees for domestication. Genet. Resour. Crop Evol. 61, 537–553. https://doi.org/10.1007/s10722-014-0080-y (2014)Nasar‐Abbas, S. M., e‐Huma, Z., Vu, T. H., Khan, M. K., Esbenshade, H. & Jayasena, V. Carob kibble: A bioactive‐rich food ingredient. Compr. Rev. Food Sci. Food Saf. 15(1), 63–72. https://doi.org/10.1111/1541-4337.12177 (2016)Pandey, D. K., Singh, S., Dubey, S. K., Mehra, T. S., Mounika, V., Dixit, S. & Sawargaonkar, G. Nutrient profiling of Lablab bean [(Lablab purpureus L.) Sweet] accessions from Northeast India: Diversity exploration leading to mitigation of nutritional vulnerability. https://doi.org/10.21203/rs.3.rs-2237030/v1 (2022).Aina, A. I. et al. Morphological characterization and variability analysis of African yam bean (Sphenostylis stenocarpa Hochst ex. A. Rich) Harms Int. J. Plant Res. 10(3), 45–52. https://doi.org/10.5923/j.plant.20201003.01 (2020).
Google Scholar 
Shitta, N. S. et al. Morphological characterization and genotypic identity of African yam bean (Sphenostylis stenocarpa Hochst ex. A. Rich. Harms) germplasm from diverse ecological zones. Plant Genet. Res. 19(1), 58–66. https://doi.org/10.1017/S1479262121000095 (2021).
Google Scholar 
Ebifa Othieno, E., Kabasa, J. D., Nyeko, P., Nakimbugwe, D. & Mugisha, A. Nutritional potential of tamarind (Tamarindus indica L.) from semi-arid and sub humid zones of Uganda. J. Food Meas. Charact. 14, 1125–1134. https://doi.org/10.1007/s11694-019-00362-7 (2020).
Google Scholar 
Animashahun, R., Idowu, A., Alabi, O., Olawoye, S., Animashahun, A., Okeniyi, F. & Oluwafemi, P. Comparative study on proximate, phytochemicals and mineral components of different parts of Parkia biglobosa (pod, seed, and leaf). J. Xi’an Shiyou Univ. Nat. Sci. Ed. 20(02), 48–52. http://xisdxjxsu.asia (2024).Vadivel, V. & Janardhanan, K. Nutritional and antinutritional characteristics of seven south Indian Wild legumes. Plant Foods Hum. Nutr. 60, 69–75. https://doi.org/10.1007/s11130-005-5102-y (2005).
Google Scholar 
Andualem, B. & Gessesse, A. Proximate composition, mineral content and antinutritional factors of Brebra (Millettia ferruginea) seed flour as well as physicochemical characterization of its seed oil. Springerplus 3, 298. https://doi.org/10.1186/2193-1801-3-298 (2014).
Google Scholar 
Varkekara, N. J. & Singh, N. I. Assessment of physical, nutritional and functional attributes of Parkia biglandulosa W & A: An underexplored semi-wild tree legume species of Parkia genera. Indian J. Tradit. Know. 19(4), 736–743. https://doi.org/10.56042/ijtk.v19i4.44516 (2020).
Google Scholar 
Altuntas, E. & Demirtola, H. Effect of moisture content on physical properties of some grain legume seeds. N. Z. J. Crop Hortic. Sci. 35(4), 423–433. https://doi.org/10.1080/01140670709510210 (2007).
Google Scholar 
Melesse, A., Steingass, H., Schollenberger, M., Holstein, J. & Rodehutscord, M. Nutrient compositions and in vitro methane production profiles of leaves and whole pods of twelve tropical multipurpose tree species cultivated in Ethiopia. Agroforest Syst 93, 135–147. https://doi.org/10.1007/s10457-017-0110-9 (2019).
Google Scholar 
Toumi, S. et al. Morphobiometric characterisation of carob tree pods cultivated in Algeria and evaluation of physicochemical, nutritional, and sensory properties of their powders. Proc. Latvian Acad. Sci. Section. B. 78(2), 153–163. https://doi.org/10.2478/prolas-2024-0023 (2024).
Google Scholar 
Kalpanadevi, V. & Mohan, V. R. Nutritional and anti-nutritional assessment of underutilized legume D. lablab var. vulgaris L.. Bangladesh J. Sci. Ind. Res. 48(2), 119–130 (2013).
Google Scholar 
Bakhtiar, Z., Hassandokht, M., Naghavi, M. R. & Mirjalili, M. H. Variability in proximate composition, phytochemical traits and antioxidant properties of Iranian agro-ecotypic populations of fenugreek (Trigonella foenum-graecum L.). Sci. Rep. 14(1), 87. https://doi.org/10.1038/s41598-023-50699-9 (2024).
Google Scholar 
Ouedraogo, S., Sanou, L., Savadogo, P. & Kabore-Zoungrana, C. Y. Comparative nutritional evaluation of the two leguminous fodder trees Prosopis africana and Piliostigma thonningii: Effects of different levels of pod-based supplementation on the growth performance of Djallonke sheep. Int. J. Biol. Chem. Sci. 16(5), 1831–1846. https://doi.org/10.4314/ijbcs.v16i5.2 (2022).
Google Scholar 
Akpata, M. I. & Miachi, O. E. Proximate composition and selected functional properties of Detarium microcarpum. Plant Foods Hum. Nutr. 56(4), 297–302. https://doi.org/10.1023/A:1011836332105 (2001).
Google Scholar 
Tharanathan, R. N. & Mahadevamma, S. Grain legumes-a boon to human nutrition. Trends Food Sci. Technol. 14(12), 507–518. https://doi.org/10.1016/j.tifs.2003.07.002 (2003).
Google Scholar 
Yaméogo, G., Yelemou, B. & Traoré, D. Farmer’s practices and perception in agroforestry park creating in Vipalogo area (Burkina Faso). Biotechnol. Agron. Soc. Environ. 9(4), 241–248 (2005).
Google Scholar 
Semba, R. D., Ramsing, R., Rahman, N., Kraemer, K. & Bloem, M. W. Legumes as a sustainable source of protein in human diets. Glob. Food Secur. 28, 100520. https://doi.org/10.1016/j.gfs.2021.100520 (2021).
Google Scholar 
Weber, C. W., Kohlhepp, P., Idouraine, A. & Osman, M. Chemical and nutritional composition of tree legume seeds and pods from Southwestern United States and Sonora Mexico. Ecol. Food. Nutr. 37, 57–72. https://doi.org/10.1080/03670244.1998.9991537 (1998).
Google Scholar 
N. A. P. Dietary reference intakes for energy, carbohydrate, fiber, fat, fatty acids, cholesterol, protein, and amino acids (2005). http://www.nal.usda.gov/fnic/DRI/DRI_Energ y/energy_full_repor t.pdf (2005).Termote, C. et al. Nutrient composition of Parkia biglobosa pulp, raw and fermented seeds: A systematic review. Crit. Rev. Food Sci. Nutr. 62(1), 119–144. https://doi.org/10.1080/10408398.2020.1813072 (2022).
Google Scholar 
Anavi, S. Nutrition and Health-the Importance of Potassium. International Potash Institute (IPI), (Switzerland, 2013). https://doi.org/10.3235/978-3-905887-08-2.Pajarillo, E. A. B., Lee, E. & Kang, D. K. Trace metals and animal health: Interplay of the gut microbiota with iron, manganese, zinc, and copper. Anim. Nutr. 7(3), 750–761. https://doi.org/10.1016/j.aninu.2021.03.005 (2021).
Google Scholar 
Abbaspour, N., Hurrell, R. & Kelishadi, R. Review on iron and its importance for human health. J. Res. Med. Sci. 19(2), 164–174 (2014).
Google Scholar 
Towett, E. K. et al. Total elemental composition of soils in Sub-Saharan Africa and relationship with soil forming factors. Geoderma Reg. 5, 157–168 (2015).
Google Scholar 
Lambers, H. & Oliveira, R. S. Mineral nutrition. In Plant Physiological Ecology. (Springer, Cham, 2019). https://doi.org/10.1007/978-3-030-29639-1_9.Butler, B. M. et al. Mineral–nutrient relationships in African soils assessed using cluster analysis of x-ray powder diffraction patterns and compositional methods. Geoderma 375, 114474. https://doi.org/10.1016/j.geoderma.2020.114474 (2020).
Google Scholar 
Download referencesAcknowledgementsThe authors are most grateful for financial support from the MU-NMBU Phase IV Project through Mekelle University and the McKnight Foundation’s Collaborative Crop Research Program. We extend our gratitude to Dr. Zenebe Girmay, the field assistants, the technical and laboratory staff, and the farmers whose fields we visited during data collection. Their invaluable contributions were essential to compiling this manuscript. Additionally, we acknowledge the Institute of International Education-Scholars Rescue Fund (IIE-SRF), and Nord University, Faculty of Bioscience and Aquaculture (FBA), and the NORGLOBAL 2 project “Towards a climate-smart policy and management framework for conservation and use of dry forest ecosystem services and resources in Ethiopia [grant number: 303600]” for supporting the research stay of Emiru Birhane at NMBU.FundingThe research fund for this study was obtained from the MU-HU-NMBU collaborative project through Mekelle University and the Ethiopian Ministry of Education.Author informationAuthors and AffiliationsDepartment of Land Resources Management and Environmental Protection, College of Dryland Agriculture and Natural Resources, Mekelle University, P. O. Box 231, Mekelle, EthiopiaTesfaye Gebre, Mitiku Haile & Emiru BirhaneFaculty of Bioscience and Aquaculture, Nord University, P. O. Box 2501, 7729, Steinkjer, NorwayEmiru BirhaneInstitute of Climate and Society, P. O. Box 231, Mekelle, EthiopiaEmiru BirhaneDepartment of Food Science and Postharvest Technology, Mekelle University, Mekelle, EthiopiaSarah Tewolde-BerhanAuthorsTesfaye GebreView author publicationsSearch author on:PubMed Google ScholarMitiku HaileView author publicationsSearch author on:PubMed Google ScholarSarah Tewolde-BerhanView author publicationsSearch author on:PubMed Google ScholarEmiru BirhaneView author publicationsSearch author on:PubMed Google ScholarContributionsT.G. data collection, investigation, data curation, methodology, formal analysis, writing—original draft, writing—review and editing. M.H. supervised, conceptualization, review, and editing the original draft and manuscript. S.T.B. conceptualization, conceived and designed the experiments, contributed materials and training, and review and editing. E.B. supervised, conceptualization, writing—original draft, review and editing the manuscript critically.Corresponding authorCorrespondence to
Tesfaye Gebre.Ethics declarations

Competing interests
The authors declare no competing interests.

Ethical approval
The study was conducted with formal approval from the Vice President for Research and Technology Transfer at Mekelle University. An official permission letter from the department of land resources management and environmental protection was submitted to the administrative offices of Tselemti district, and the Tselemti Agricultural and Rural Development Office. Verbal consent was obtained from all relevant authorities and farmers in the district. This was done after the main objectives of the study were clearly explained with the assistance of local language translators. No endangered or threatened species were collected or included in the study.

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 articleGebre, T., Haile, M., Tewolde-Berhan, S. et al. Morphological and nutritional composition of Bauhinia thonningii pods and seeds in Northern Ethiopia.
Sci Rep (2025). https://doi.org/10.1038/s41598-025-32054-2Download citationReceived: 08 May 2025Accepted: 08 December 2025Published: 13 December 2025DOI: https://doi.org/10.1038/s41598-025-32054-2Share 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
KeywordsFodder treeNutritional valueProximate compositionSeed traitsUnderutilized treeWild edible fruits More

AbstractPaddy rice exacerbates climate warming through greenhouse gas emissions but also cools the land surface by enhancing evapotranspiration. While the former effect has received extensive attention, the biophysical cooling effect remains poorly quantified, partly due to the lack of high-quality global paddy rice data. Here, we address this gap by developing a universal rice mapping framework that integrates the strengths of phenology-based and curve-matching methods to construct the global, long-term rice dataset (GlobalRice500) with daily temporal and 500 m spatial resolution. Our analysis reveals that paddy fields annually reduce daytime land surface temperature by 0.21 ((pm)0.0057)–0.27 ((pm)0.0063) °C during the growing season compared to other croplands, with stronger cooling observed in larger fields and partial spillover to surrounding landscapes. These findings provide robust evidence of the surface cooling effect of paddy rice and call for a comprehensive evaluation of its role in climate regulation.

Data availability

The GlobalRice50031 dataset generated in this study have been deposited in the Zenodo database (https://doi.org/10.5281/zenodo.17460919). The mean values and uncertainty quantification underlying the Figures generated in this study are provided in the Supplementary Information and Source Data file. Publicly available data used in this study are referenced. Source data are provided with this paper.
Code availability

The MPD_DTW30 code is available at https://doi.org/10.5281/zenodo.17679402. The source code is freely available for non-commercial research and educational purposes, provided that proper attribution is given. Modification and redistribution are permitted under the same conditions. Commercial use of the software is strictly prohibited.
ReferencesYuan, S. et al. Sustainable intensification for a larger global rice bowl. Nat. Commun. 12, 7163 (2021).
Google Scholar 
Qian, H. et al. Greenhouse gas emissions and mitigation in rice agriculture. Nat. Rev. Earth Environ. 4, 716–732 (2023).
Google Scholar 
Null, N., Jensen, M. E. & Allen, R. G. Evaporation, Evapotranspiration, and Irrigation Water Requirements. https://doi.org/10.1061/9780784414057 (American Society of Civil Engineers, 2016).Chen, Z., Balasus, N., Lin, H., Nesser, H. & Jacob, D. J. African rice cultivation linked to rising methane. Nat. Clim. Change https://doi.org/10.1038/s41558-023-01907-x (2024).
Google Scholar 
Yan, X., Akiyama, H., Yagi, K. & Akimoto, H. Global estimations of the inventory and mitigation potential of methane emissions from rice cultivation conducted using the 2006 Intergovernmental Panel on Climate Change Guidelines. Glob. Biogeochem. Cycles 23, GB2002 (2009).Zhang, G. et al. Fingerprint of rice paddies in spatial–temporal dynamics of atmospheric methane concentration in monsoon Asia. Nat. Commun. 11, 554 (2020).
Google Scholar 
Nikolaisen, M. et al. Methane emissions from rice paddies globally: a quantitative statistical review of controlling variables and modelling of emission factors. J. Clean. Prod. 409, 137245 (2023).
Google Scholar 
Li, Y. et al. Biophysical impacts of earth greening can substantially mitigate regional land surface temperature warming. Nat. Commun. 14, 121 (2023).
Google Scholar 
Alkama, R. et al. Vegetation-based climate mitigation in a warmer and greener World. Nat. Commun. 13, 606 (2022).
Google Scholar 
Li, Y. et al. Observed different impacts of potential tree restoration on local surface and air temperature. Nat. Commun. 16, 2335 (2025).
Google Scholar 
Li, Y. et al. Local cooling and warming effects of forests based on satellite observations. Nat. Commun. 6, 6603 (2015).
Google Scholar 
Alkama, R. & Cescatti, A. Biophysical climate impacts of recent changes in global forest cover. Science 351, 600–604 (2016).
Google Scholar 
Gillner, S., Vogt, J., Tharang, A., Dettmann, S. & Roloff, A. Role of street trees in mitigating effects of heat and drought at highly sealed urban sites. Landsc. Urban Plan. 143, 33–42 (2015).
Google Scholar 
Li, G. et al. Global urban greening and its implication for urban heat mitigation. Proc. Natl. Acad. Sci. USA 122, e2417179122 (2025).
Google Scholar 
Bonfils, C. & Lobell, D. Empirical evidence for a recent slowdown in irrigation-induced cooling. Proc. Natl. Acad. Sci. USA 104, 13582–13587 (2007).
Google Scholar 
Thiery, W. et al. Warming of hot extremes alleviated by expanding irrigation. Nat. Commun. 11, 290 (2020).
Google Scholar 
Bo, Y. et al. Improved alternate wetting and drying irrigation increases global water productivity. Nat. Food 5, 1005–1013 (2024).
Google Scholar 
Yokohari, M., Brown, R. D., Kato, Y. & Yamamoto, S. The cooling effect of paddy fields on summertime air temperature in residential Tokyo, Japan. Landsc. Urban Plan. 53, 17–27 (2001).
Google Scholar 
Liu, W. et al. Biophysical effects of paddy rice expansion on land surface temperature in Northeastern Asia. Agric. For. Meteorol. 315, 108820 (2022).
Google Scholar 
Xue, W., Jeong, S., Ko, J. & Yeom, J.-M. Contribution of biophysical factors to regional variations of evapotranspiration and seasonal cooling effects in Paddy Rice in South Korea. Remote Sens. 13, 3992 (2021).
Google Scholar 
Portmann, F. T., Siebert, S. & Döll, P. MIRCA2000—Global monthly irrigated and rainfed crop areas around the year 2000: A new high-resolution data set for agricultural and hydrological modeling. Glob. Biogeochem. Cycles 24, 2008GB003435 (2010).
Google Scholar 
Grogan, D., Frolking, S., Wisser, D., Prusevich, A. & Glidden, S. Global gridded crop harvested area, production, yield, and monthly physical area data circa 2015. Sci. Data 9, 15 (2022).
Google Scholar 
Tang, F. H. M. et al. CROPGRIDS: a global geo-referenced dataset of 173 crops. Sci. Data 11, 413 (2024).
Google Scholar 
Leff, B., Ramankutty, N. & Foley, J. A. Geographic distribution of major crops across the world. Glob. Biogeochem. Cycles 18, GB1009 (2004).Iizumi, T. & Sakai, T. The global dataset of historical yields for major crops 1981–2016. Sci. Data 7, 97 (2020).
Google Scholar 
Iizumi, T. et al. Uncertainties of potentials and recent changes in global yields of major crops resulting from census- and satellite-based yield datasets at multiple resolutions. PLOS ONE 13, e0203809 (2018).
Google Scholar 
Iizumi, T. et al. Historical changes in global yields: major cereal and legume crops from 1982 to 2006. Glob. Ecol. Biogeogr. 23, 346–357 (2014).
Google Scholar 
Carrasco, L., Fujita, G., Kito, K. & Miyashita, T. Historical mapping of rice fields in Japan using phenology and temporally aggregated Landsat images in Google Earth Engine. ISPRS J. Photogramm. Remote Sens. 191, 277–289 (2022).
Google Scholar 
Jo, H.-W. et al. Recurrent U-Net based dynamic paddy rice mapping in South Korea with enhanced data compatibility to support agricultural decision making. GIScience Remote Sens. 60, 2206539 (2023).
Google Scholar 
Weng, W. MPD_DTW. Zenodo https://doi.org/10.5281/ZENODO.17679402 (2025).
Google Scholar 
Weng, W. GlobalRice500. Zenodo https://doi.org/10.5281/ZENODO.17460918 (2025).
Google Scholar 
Chiueh, Y.-W., Tan, C.-H. & Hsu, H.-Y. The value of a decrease in temperature by one degree celsius of the regional microclimate—The cooling effect of the paddy field. Atmosphere 12, 353 (2021).
Google Scholar 
Yang, M. et al. Mitigating urban heat island through neighboring rural land cover. Nat. Cities 1, 522–532 (2024).
Google Scholar 
Martilli, A., Krayenhoff, E. S. & Nazarian, N. Is the Urban Heat Island intensity relevant for heat mitigation studies?. Urban Clim. 31, 100541 (2020).
Google Scholar 
Lee, X. et al. Observed increase in local cooling effect of deforestation at higher latitudes. Nature 479, 384–387 (2011).
Google Scholar 
Zhang, T., Zhou, Y., Zhu, Z., Li, X. & Asrar, G. R. A global seamless 1 km resolution daily land surface temperature dataset (2003–2020). Earth Syst. Sci. Data 14, 651–664 (2022).
Google Scholar 
Wan, Z. New refinements and validation of the collection-6 MODIS land-surface temperature/emissivity product. Remote Sens. Environ. 140, 36–45 (2014).
Google Scholar 
Rubel, F., Brugger, K., Haslinger, K. & Auer, I. The climate of the european alps: shift of very high resolution köppen-geiger climate zones 1800–2100. Meteorol. Z. 26, 115–125 (2017).
Google Scholar 
Wang, H., Yue, C. & Luyssaert, S. Reconciling different approaches to quantifying land surface temperature impacts of afforestation using satellite observations. Biogeosciences 20, 75–92 (2023).
Google Scholar 
IPCC. Climate Change 2021 – The Physical Science Basis. (Cambridge University Press, 2023). https://doi.org/10.1017/9781009157896Kritee, K. et al. High nitrous oxide fluxes from rice indicate the need to manage water for both long- and short-term climate impacts. Proc. Natl. Acad. Sci. USA 115, 9720–9725 (2018).
Google Scholar 
FAO. FAOSTAT Statistical Database. https://www.fao.org/faostat/ (accessed 10 Sep 2024).Bright, R. M. et al. Local temperature response to land cover and management change driven by non-radiative processes. Nat. Clim. Change 7, 296–302 (2017).
Google Scholar 
Zeng, Z. et al. Climate mitigation from vegetation biophysical feedbacks during the past three decades. Nat. Clim. Change 7, 432–436 (2017).
Google Scholar 
Zhang, X. et al. Monitoring vegetation phenology using MODIS. Remote Sens. Environ. 84, 471–475 (2003).
Google Scholar 
Chandrasekar, K., Sesha Sai, M. V. R., Roy, P. S. & Dwevedi, R. S. Land Surface Water Index (LSWI) response to rainfall and NDVI using the MODIS Vegetation Index product. Int. J. Remote Sens. 31, 3987–4005 (2010).
Google Scholar 
Huang, J., Wang, X. & Wang, F. Uncertainty in Paddy Rice Remote Sensing (Zhejiang University Press, 2013).Chen, J. et al. A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky–Golay filter. Remote Sens. Environ. 91, 332–344 (2004).
Google Scholar 
Chen, J. et al. Global land cover mapping at 30m resolution: A POK-based operational approach. ISPRS J. Photogramm. Remote Sens. 103, 7–27 (2015).
Google Scholar 
Boschetti, M. et al. PhenoRice: a method for automatic extraction of spatio-temporal information on rice crops using satellite data time series. Remote Sens. Environ. 194, 347–365 (2017).
Google Scholar 
Sakoe, H. & Chiba, S. Dynamic programming algorithm optimization for spoken word recognition. IEEE Trans. Acoust. Speech Signal Process. 26, 43–49 (1978).
Google Scholar 
Petitjean, F., Inglada, J. & Gancarski, P. Satellite Image Time Series Analysis Under Time Warping. IEEE Trans. Geosci. Remote Sens. 50, 3081–3095 (2012).
Google Scholar 
Hou, M., Hu, Y. & He, Y. Modifications in vegetation cover and surface albedo during rapid urbanization: a case study from South China. Environ. Earth Sci. 72, 1659–1666 (2014).
Google Scholar 
Yang, J. et al. Characterizing the thermal effects of vegetation on urban surface temperature. Urban Clim. 44, 101204 (2022).
Google Scholar 
Burke, M., Hsiang, S. M. & Miguel, E. Global non-linear effect of temperature on economic production. Nature 527, 235–239 (2015).
Google Scholar 
Moore, F. C., Baldos, U., Hertel, T. & Diaz, D. New science of climate change impacts on agriculture implies higher social cost of carbon. Nat. Commun. 8, 1607 (2017).
Google Scholar 
Han, J. et al. NESEA-Rice10: high-resolution annual paddy rice maps for Northeast and Southeast Asia from 2017 to 2019. Earth Syst. Sci. Data 13, 5969–5986 (2021).
Google Scholar 
Sun, C. et al. Twenty-meter annual paddy rice area map for mainland Southeast Asia using Sentinel−1 synthetic-aperture-radar data. Earth Syst. Sci. Data 15, 1501–1520 (2023).
Google Scholar 
USDA National Agricultural Statistics Service. Cropland Data Layer. USDA-NASS.Download referencesAcknowledgementsThis research has been financially supported by the National Natural Science Foundation of China (No. 42171314) and the National Key Research and Development Program (No. 2023YFD2300300).Author informationAuthors and AffiliationsState Key Laboratory of Soil Pollution Control and Safety, Zhejiang University, Hangzhou, ChinaWei Weng & Jingfeng HuangKey Laboratory of Environmental Remediation and Ecological Health, Ministry of Education, Zhejiang University, Hangzhou, ChinaWei Weng & Jingfeng HuangInstitute of Applied Remote Sensing and Information Technology, Zhejiang University, Hangzhou, ChinaWei Weng, Jingfeng Huang, Zhenhao Lyu, Yuanjun Xiao & Shengcheng LiCollege of Natural Resources and Environment, Northwest A&F University, Yangling, ChinaChao YueState Key Laboratory of Soil and Water Conservation and Desertification Control, Northwest A&F University, Yangling, ChinaChao YueInstitute of Soil and Water Conservation, Northwest A&F University, Yangling, ChinaChao YueSchool of Automation, Xiasha Higher Education Zone, Hangzhou Dianzi University, Hangzhou, ChinaRan HuangKey Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, ChinaDailiang PengKey Laboratory of National Forestry and Grassland Administration on Forest Ecosystem Protection and Restoration of Poyang Lake Watershed, College of Forestry, Jiangxi Agricultural University, Nanchang, ChinaChao HuangNational Institute of Statistics of Rwanda, Kigali, RwandaFlorent BigirimanaCollege of Computer and Information Technology, China Three Gorges University, Yichang, Hubei, ChinaLi LiuDepartment of Geography and Spatial Information Techniques, Ningbo University, Ningbo, ChinaWeiwei LiuAuthorsWei WengView author publicationsSearch author on:PubMed Google ScholarJingfeng HuangView author publicationsSearch author on:PubMed Google ScholarChao YueView author publicationsSearch author on:PubMed Google ScholarZhenhao LyuView author publicationsSearch author on:PubMed Google ScholarYuanjun XiaoView author publicationsSearch author on:PubMed Google ScholarShengcheng LiView author publicationsSearch author on:PubMed Google ScholarRan HuangView author publicationsSearch author on:PubMed Google ScholarDailiang PengView author publicationsSearch author on:PubMed Google ScholarChao HuangView author publicationsSearch author on:PubMed Google ScholarFlorent BigirimanaView author publicationsSearch author on:PubMed Google ScholarLi LiuView author publicationsSearch author on:PubMed Google ScholarWeiwei LiuView author publicationsSearch author on:PubMed Google ScholarContributionsJ.H. proposed the research idea. W.W. and J.H. designed the research. W.W. led the experiments and wrote the first draft. C.Y. provided theoretical guidance. Z.L., S.L., R.H., and F.B. contributed to data collection. W.W. and Z.L. performed data preprocessing. Y.X. provided technical support. Y.X., D.P., C.H., L.L., and W. L. contributed to the interpretation and the preparation of the manuscript. W.W., C.Y., and J.H. led the revisions. All authors reviewed and approved the final paper.Corresponding authorCorrespondence to
Jingfeng Huang.Ethics declarations

Competing interests
The authors declare no competing interests.

Peer review

Peer review information
Nature Communications thanks Anne Gobin and the other, anonymous, reviewer for their contribution to the peer review of this work. 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 InformationTransparent Peer Review fileSource dataSource dataRights 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 articleWeng, W., Huang, J., Yue, C. et al. Widespread land surface cooling from paddy rice cultivation revealed by global satellite mapping.
Nat Commun (2025). https://doi.org/10.1038/s41467-025-67549-zDownload citationReceived: 28 May 2025Accepted: 03 December 2025Published: 13 December 2025DOI: https://doi.org/10.1038/s41467-025-67549-zShare 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

AbstractSoybean (Glycine max) is an important source of plant-based protein and oil, but its cultivation is highly sensitive to climate conditions. In Poland, interest in soybean is growing due to climate change and increasing demand for protein-rich crops. However, cultivation of photophilic crops is still limited. This study presents results from field trials conducted in Northern Poland from 2017 to 2019, involving 13 registered soybean cultivars tested at 10 locations. The aim of the study was to evaluate seed yield, protein and fat content and protein yield under varying environmental conditions. Weather variability, particularly temperature and rainfall, had a greater influence on results than the cultivar tested. Advanced statistical analyses showed that, of all 13 tested cultivars, Moravians (mid-late) had the most favorable WAAS and GSI values in terms of protein yield. According to WTOP3 score, the Kofu (late) cultivar had the highest adaptability for seeds yield and protein yield. Protein yield is the most important indicator of the profitablility of soybean cultivation in countries with a deficit of feed plant protein. The study supports targeted cultivar selection to improve soybean production under changing climate conditions in countries located at higher latitudes, such as Poland.

Data availability

All data generated or analyzed during this study are included in this published article.
ReferencesBebeley, J. F. et al. Modelling the potential impact of climate change on the productivity of soybean in the Nigeria Savannas. PLoS ONE 20, e0313786 (2025).
Google Scholar 
Folberth, C. et al. Increase of simultaneous soybean failures due to climate change. Earth Future. 11(4), e2022EF003106 (2023).
Google Scholar 
Lesk, C., Rowhani, P. & Ramankutty, N. Influence of extreme weather disasters on global crop production. Nature 529(7584), 84–87 (2016).
Google Scholar 
Zampieri, M. et al. Wheat yield loss attributable to heat waves, drought and water excess at the global, national and subnational scales. Environ. Res. Lett. 12(6), 064008. https://doi.org/10.1088/1748-9326/aa723b (2017).
Google Scholar 
van der Wiel K, Bintanja R. Contribution of climatic changes in means and variability to temperature and precipitation extremes. InEGU General Assembly Conference Abstracts 2020 May (p. 7852).Knight, C., Khouakhi, A. & Waine, T. W. The impact of weather patterns on inter-annual crop yield variability. Sci. Total Environ. 10(955), 177181. https://doi.org/10.1016/j.scitotenv.2024.177181 (2024).
Google Scholar 
Asseng, S. et al. Rising temperatures reduce global wheat production. Nat. Clim. Chang. 5, 143–147 (2015).
Google Scholar 
Li, Y. et al. A case study on the impacts of future climate change on soybean yield and countermeasures in Fujin city of Heilongjiang province, China. Front. Agron. 25(6), 1257830. https://doi.org/10.3389/fagro.2024.1257830 (2024).
Google Scholar 
Łabędzki L. Susze rolnicze: zarys problematyki oraz metody monitorowania i klasyfikacji. Wydawnictwo Instytut Melioracji i Użytków Zielonych; 2006.Polska Soja 2021, https://www.sps.com.pl/aktualnosci.htmFlorek, J., Czerwińska-Kayzer, D. & Jerzak, M. A. Aktualny stan i wykorzystanie produkcji upraw roślin strączkowych. Frag. Agronom 29, 45–55 (2012).
Google Scholar 
Jerzak, M., Czerwińska-Kayzer, D., Florek, J. & Śmiglak-Krajewska, M. Determinanty produkcji roślin strączkowych jako alternatywnego źródła białka-w ramach nowego obszaru polityki rolnej w Polsce. Roczniki Naukowe Ekonomii Rolnictwa i Rozwoju Obszarów Wiejskich. 99(1), 113–120 (2012).
Google Scholar 
COBORU, Wyniki plonowania odmian roślin rolniczych w doświadczeniach porejestrowych w województwie łódzkim, Soja 2020, Centralny Ośrodek Badania Odmian Roślin Uprawnych SDOO (2021).Dorszewski, P., Sobczyński, T. & Wenda-Piesik, A. Soja w województwach kujawsko-pomorskim i wielkopolskim – innowacyjne rozwiązania w uprawie i skarmianiu dla gospodarstw rolnych, Raport z badań dla Konsorcjum „Moja Soja” (2019).Gawęda, D., Cierpiała, R., Bujak, K. & Wesołowski, K. Soybean yield under different tillage systems. Acta Sci. Pol. Hortorum Cultus 13, 43–54 (2014).
Google Scholar 
Kurasiak-Popowska, D. et al. Stability of early maturing soybean genotypes in Poland. Agriculture 14(12), 2202 (2024).
Google Scholar 
Banaś, K. et al. Assessment of early, mid-early, and mid-late soybean (Glycine max) varieties in Northern Poland. Agronom 13, 2879 (2023).
Google Scholar 
Bednarczyk, M., Helios, W., Kotecki, A., Kozak, M., Lewandowska, S.,Malarz, W., Markowicz, M., Serafin-Andrzejewska, M., Włodarczyk, M. Studia Nad Uprawą Soi Zwyczajnej (Glycine max (L.) Merrill) w Południowo-Zachodniej Polsce; Kotecki, A.; Lewandowska, S., Eds.; Wydawnictwo Uniwersytetu Przyrodniczego we Wrocławiu: Wrocław, Poland, 2020; p. 33 (In Polish).Peel, M. C., Finlayson, B. L. & McMahon, T. A. Updated world map of the Köppen–Geiger climate classification. Hydrol. Earth Syst. Sci. 11, 1633–1644. https://doi.org/10.5194/hess-11-1633-2007 (2007).
Google Scholar 
Polska. Warunki Naturalne. Klimat (Poland. Environmental Conditions. Climate). Available online: https://encyklopedia.pwn.pl/haslo/;4575156 (Accessed on 3 Nov 2025). (In Polish)Charakterystyka Wybranych Elementów Klimatu w Polsce w 2023 Roku–Podsumowanie (Characteristics of Selected Climate Elements in Poland in 2023-Summary). Available online: https://www.imgw.pl/wydarzenia/charakterystyka-wybranych-elementow-klimatu-w-polsce-w-2023-roku-podsumowanie (accessed on 3 November 2025). (In Polish)COBORU- Methodology for Testing the Value of Cultivars for Cultivation and Use, COBORU (1998).Polish Soil Classification, Systematyka Gleb Polski, Polskie Towarzystwo Glebo znawcze, Komisja Genezy Klasyfikacji i Kartografii Gleb; Wydawnictwo Uniwersytetu Przyrodniczego we Wrocławiu, Polskie Towarzystwo Gleboznawcze: Wrocław/Warszawa, Poland, 29, (2019).IUSS Working Group WRB World Reference Base for Soil Resources, International Soil Classification System for Naming Soils and Creating Legends for Soil Maps, 4th ed,; International Union of Soil Sciences (IUSS): Vienna, Austria (2022).AOAC, Official Methods of Analysis, 18th ed, (Association of Official Analytical Chemists (2012).Gauch, H. G. Jr. A simple protocol for AMMI analysis of yield trials. Crop Sci. 53(5), 1860–1869 (2013).
Google Scholar 
Ward, J. H. Jr. Hierarchical grouping to optimize an objective function. J. Am. Stat. Assoc. 58(301), 236–244. https://doi.org/10.1080/01621459.1963.10500845( (1963).
Google Scholar 
Olivoto, T. et al. Mean performance and stability in multi-environment trials I: Combining features of AMMI and BLUP techniques. Agron, J. 111(6), 2949–2960. https://doi.org/10.2134/agronj2019.03.0220 (2019).
Google Scholar 
Mohammadi, R. & Amri, A. Genotype × environment interaction and genetic improvement for yield and yield stability of rainfed durum wheat in Iran. Euphytica 192, 227–249 (2013).
Google Scholar 
Fox, P. N. et al. Yield and adaptation of hexaploid spring triticale. Euphytica 47, 57–64 (1990).
Google Scholar 
Serafin-Andrzejewska, M., Helios, W., Białkowska, M., Kotecki, A. & Kozak, M. Sowing date as a factor affecting soybean yield—A case study in Poland. Agriculture 14(7), 970. https://doi.org/10.3390/agriculture14070970 (2024).
Google Scholar 
Assefa, Y. et al. Spatial characterization of soybean yield and quality (amino acids, oil, and protein) for United States. Sci, Rep 8, 14653 (2018).
Google Scholar 
Assefa, Y. et al. Assessing variation in US soybean seed composition (protein and oil). Front. Plant Sci. 11, 10 (2019).
Google Scholar 
Haegele, J, W, & Below, F, E, The six secrets of soybean success: improving management practices for high yield soybean production, Available at: http://cropphysiol-ogy,cropsci,illinois,edu/documents/2012%20Six%20Secrets%20of%20Soybean%20Success%20report,pdf, Accessed on: 8 Nov 2015Anderson, W. K. Closing the gap between actual and potential yield of rainfed wheat: The impacts of environment, management, and cultivar. Field Crops Res 116, 14–22 (2010).
Google Scholar 
Annicchiarico, P., Chiapparino, E. & Perenzin, M. Response of common wheat varieties to organic and conventional production systems across Italian locations and implications for selection. Field. Crops Res. 116, 230–238 (2010).
Google Scholar 
Pecetti, L. et al. Response of mediterranean tall fescue cultivars to contrasting agricultural environments and implications for selection. J. Agronom. Crop Sci. 197, 12–20 (2011).
Google Scholar 
Paderewski, J. & Mądry, W. Zastosowania modelu AMMI do analizy reakcji odmian na środowiska. Biuletyn Instytutu Hodowli i Aklimatyzacji Roślin. 29(263), 161–188 (2012).
Google Scholar 
Popovic, V. et al. Effect of agroecological factors on variations in yield, protein and oil contents in soybean grain. Romanian Agric. Res. 30, 241–247 (2013).
Google Scholar 
Bujak, K. & Frant, M. Wpływ mieszanek herbicydów na plonowanie i zachwaszczenie pięciu odmian soi. Acta Agrophys. 13, 601–613 (2009).
Google Scholar 
Bury, M. & Nawaracała, J. Wstępna ocena potencjału plonowania odmian soi (Glycine max (L.) Merrill) uprawianych w rejonie Szczecina. Rośliny Oleiste 25, 415–422 (2004).
Google Scholar 
Michałek, S. & Borowski, E. Plonowanie oraz zawartość tłuszczu, kwasów tłuszczowych i białka w nasionach krajowych odmian soi w warunkach suszy. Acta Agrophys 8, 459–471 (2006).
Google Scholar 
Fogelberg, F. & Recknagel, J. Developing soy production in central and northern Europe, In Legumes in Cropping Systems (Murphy-Bokern, D,, Stoddard, F, L, & Watson, C, A,, Eds,), pp, 109–124, CAB International, Wallingford, UK (2017).Döttinger, C. A., Hahn, V., Leiser, W. L. & Würschum, T. Do we need to breed for regional adaptation in soybean?—Evaluation of genotype-by-location interaction and trait stability of soybean in Germany. Plants. 12(4), 756 (2023).
Google Scholar 
Brumm, T. J. & Hurburgh, C. R. Changes in long-term soybean compositional patterns. J. Am. Oil Chem. Soc 83, 981–983 (2006).
Google Scholar 
Yaklich, R. W. & Vinyard, B. T. A method to estimate soybean seed protein and oil concentration before harvest. J. Am. Oil Chem. Soc. 81(11), 1021–1027 (2004).
Google Scholar 
Szwejkowska, B. Effect of cultivation intensity on protein content and yields in field pea. Acta Sci. Pol. Agric 4, 153–161 (2005).
Google Scholar 
Michałek, S. Plonowanie oraz zawartość białka i tłuszczu w nasionach soi w warunkach okresowej suszy. Zesz. Nauk. Akad. Rol. H. Kołłątaja w Krakowie 364, 139–142 (2000).
Google Scholar 
Rotundo, J. L., Miller-Garvin, J. E. & Naeve, S. L. Regional and temporal variation in soybean seed protein and oil across the United States. Crop Sci. 56, 797–808 (2016).
Google Scholar 
Šarčević, H. et al. Stability of protein and oil content in soybean across dry and normal environments—A case study in Croatia. Agronom. 12(4), 915. https://doi.org/10.3390/agronomy12040915 (2022).
Google Scholar 
Piper, E. L. & Boote, K. J. Temperature and cultivar effects on soybean seed oil and protein concentrations. J. Am. Oil Chem. Soc. 76, 1233–1241 (1999).
Google Scholar 
Balesevic-Tubic, S., Djordjevic, V., Miladinovic, J., Djukic, V. & Tatic, M. Stability of soybean seed composition. Genetika 43, 217–227 (2011).
Google Scholar 
Download referencesFundingThe APC/BPC is financed/co-financed by Wrocław University of Environmental and Life Sciences and Research Centre for Cultivar Testing (COBORU) in Słupia Wielka, Poland.Author informationAuthors and AffiliationsResearch Centre for Cultivar Testing, Słupia Wielka 34, 63-022, Słupia Wielka, PolandBeata Kaliska & Henryk BujakInstitute of Agroecology and Plant Production, Wrocław University of Environmental and Life Sciences, Grunwaldzki Sq. 24 A, 50-363, Wrocław, PolandAndrzej Kotecki, Magdalena Serafin-Andrzejewska & Anna Jama-RodzeńskaInstitute of Soil Science, Plant Nutrition and Environmental Protection, Wrocław University of Environmental and Life Sciences, 50-363, Wroclaw, PolandBernard GałkaDepartment of Genetics, Plant Breeding and Seed Production, Wrocław University of Environmental and Life Sciences, Grunwaldzki Sq. 24a, 50-363, Wrocław, PolandHenryk BujakAuthorsBeata KaliskaView author publicationsSearch author on:PubMed Google ScholarAndrzej KoteckiView author publicationsSearch author on:PubMed Google ScholarBernard GałkaView author publicationsSearch author on:PubMed Google ScholarMagdalena Serafin-AndrzejewskaView author publicationsSearch author on:PubMed Google ScholarHenryk BujakView author publicationsSearch author on:PubMed Google ScholarAnna Jama-RodzeńskaView author publicationsSearch author on:PubMed Google ScholarContributionsB.K., H.B.- Conceptualization; B.K., A.K., B.G.- Investigation; M.S.A., A.J.R., B.K.-wrote the main manucript; M.S.A, A.J.R.-literature and visualisation; A.K.,B.G. and H.B.-Supervising.Corresponding authorsCorrespondence to
Magdalena Serafin-Andrzejewska or Anna Jama-Rodzeńska.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 1.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 articleKaliska, B., Kotecki, A., Gałka, B. et al. Assessment of soybean cultivars’responses to diverse climatic conditions in Northern Poland in terms of yield and seed composition.
Sci Rep (2025). https://doi.org/10.1038/s41598-025-31124-9Download citationReceived: 18 July 2025Accepted: 29 November 2025Published: 13 December 2025DOI: https://doi.org/10.1038/s41598-025-31124-9Share 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
KeywordsClimate changeCultivarsSeed yieldProtein contentFat contentAMMI analysisGSIWAAS More

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