Abstract
Genetic monitoring is a powerful tool to reveal human impact on genetic diversity and genetic differentiation in times of land use and climate change. Unfortunately, it is not yet frequently applied in wild plant nature conservation at present. Consequently, we conducted a genetic monitoring study of the rare and endangered arable weed Sherardia arvensis, which continuously decreased in the recent decades due to environmental changes. Therefore, detecting a possible shift in genetic diversity and differentiation is highly relevant for conservation. We applied multiplexed ISSR genotyping by sequencing (MIG-seq) to compare genetic variation within and among eight populations, as well as effective population size of the species using samples collected at the same sites in 2007 and 2020. We obtained 371 SNPs from 160 analysed individuals. In contrast to our expectations, we observed nearly similar levels of genetic diversity and differentiation within and among populations in 2007 and 2020, although 25% of the investigated populations went extinct in the study period. Effective population sizes showed some differences between the study years, depending on the analysis. The observed maintenance of genetic diversity and differentiation patterns may most likely be explained by the longevity of seeds in the soil, which is generally high in many arable weeds. In the case of S. arvensis seeds may persist in the soil for up to ten years. This allows the regeneration of populations and contributes to the maintenance of genetic variation. A potential impact of population loss and decrease of effective population size on genetic diversity and differentiation may therefore be delayed, comparable to the already described phenomenon of an extinction debt in other species. Our study clearly underlines, that long-term genetic monitoring over long time periods is needed to reveal potential changes of genetic diversity and differentiation in the Anthropocene.
Data availability
The datasets generated during the current study are available in the European Nucleotide Archive (ENA) under the accession number PRJEB85125.
References
Johnson, C. N. et al. Biodiversity losses and conservation responses in the anthropocene. Science 356, 270–275 (2017).
Eichenberg, D. et al. Widespread decline in central European plant diversity across six decades. Glob Change Biol. 27, 1097–1110 (2021).
Kruess, A. & Tscharntke, T. Habitat fragmentation, species loss, and biological control. Science 264, 1581–1584 (1994).
Exposito-Alonso, M. et al. Genetic diversity loss in the anthropocene. Science 377, 1431–1435 (2022).
Almeida-Rocha, J. M. et al. The impact of anthropogenic disturbances on the genetic diversity of terrestrial species: A global meta‐analysis. Mol. Ecol. 29, 4812–4822 (2020).
Margules, C. R. Conservation Biology: The Science of Scarcity and Diversity, JSTOR (1987).
Frankham, R. et al. Introduction to conservation genetics, Cambridge university press (2002).
Juergens, N. Monitoring of biodiversity. Biodivers. Struct. Funct. -I. 1, 229 (2009).
Kempel, A. et al. Nationwide revisitation reveals thousands of local extinctions across the ranges of 713 threatened and rare plant species. Conserv. Lett. 13, e12749 (2020).
Lüttgert, L. et al. Repeated habitat mapping data reveal gains and losses of plant species. Ecosphere 13, e4244 (2022).
Kull, T. et al. Necessity and reality of monitoring threatened European vascular plants. Biodivers. Conserv. 17, 3383–3402 (2008).
Straubinger, C. et al. Effects of historical management on the vegetation and habitat properties of wet meadows in Germany. Restor. Ecol. 31, e13839 (2023).
Pearman, P. B. et al. Monitoring of species’ genetic diversity in Europe varies greatly and overlooks potential climate change impacts. Nat. Ecol. Evol. 8, 267–281 (2024).
CBD. Decision Adopted by the Conference of the Parties to the Convention on Biological Diversity CBD/COP/DEC/15/4 Kunming-Montreal Global Biodiversity Framework (2022).
Hoban, S. et al. Global genetic diversity status and trends: towards a suite of essential biodiversity variables (EBVs) for genetic composition. Biol. Rev. 97, 1511–1538 (2022).
Waples, R. S. The idiot’s guide to effective population size. Mol. Ecol. https://doi.org/10.1111/mec.17670 (2025).
Clarke, S. H. et al. Global assessment of effective population sizes: consistent taxonomic differences in meeting the 50/500 rule. Mol. Ecol. 33, e17353 (2024).
Thormann, I. et al. Genotypic and phenotypic changes in wild barley (Hordeum vulgare subsp. spontaneum) during a period of climate change in Jordan. Genet. Resour. Crop Evol. 64, 1295–1312 (2017).
Bonnin, I. et al. Explaining the decrease in the genetic diversity of wheat in France over the 20th century. Agric. Ecosyst. Environ. 195, 183–192 (2014).
Khoury, C. K. et al. Crop genetic erosion: Understanding and responding to loss of crop diversity. New. Phytol. 233, 84–118 (2022).
Forgiarini, C. et al. The impact of ex situ cultivation on the genetic variation of endangered plant species – Implications for restoration. Biol. Conserv. 284, 110221 (2023).
Lauterbach, D. et al. Rapid genetic differentiation between ex situ and their in situ source populations: an example of the endangered Silene Otites (Caryophyllaceae). Bot. J. Linn. Soc. 168, 64–75 (2012).
Brütting, C. et al. Ex situ cultivation affects genetic structure and diversity in arable plants. Plant. Biol. 15, 505–513 (2013).
Morris, A. B. et al. Genetic variation and structure in natural and reintroduced populations of the endangered legume, pyne’s ground Plum (Astragalus bibullatus). Conserv. Genet. 22, 443–454 (2021).
Wei, X. & Jiang, M. Meta-analysis of genetic representativeness of plant populations under ex situ conservation in contrast to wild source populations. Conserv. Biol. 35, 12–23 (2021).
Finger, A. et al. Genetic monitoring for effective plant conservation: an example using the threatened Saxifraga hirculus L. in Scotland. PLANTS PEOPLE PLANET. 6, 381–398 (2024).
Hoban, S. et al. Genetic diversity targets and indicators in the CBD post-2020 global biodiversity framework must be improved. Biol. Conserv. 248, 108654 (2020).
Hoban, S. et al. Global Commitments to Conserving and Monitoring Genetic Diversity Are Now Necessary and Feasible. BioScience 71, 964–976 (2021).
Hunter, M. E. et al. Next-generation conservation genetics and biodiversity monitoring. Evol. Appl. 11, 1029–1034 (2018).
Korneck, D. et al. Warum Verarmt unsere flora? Auswertung der Roten liste der farn-und Blütenpflanzen Deutschlands. Schriftenreihe Für Veg. 29, 299–444 (1998).
Lang, M. et al. Reintroduction of rare arable plants in extensively managed fields: effects of crop type, sowing density and soil tillage. Agric. Ecosyst. Environ. 306, 107187 (2021).
Meyer, S. et al. Dramatic losses of specialist arable plants in central Germany since the 1950s/60s – a cross-regional analysis. Divers. Distrib. 19, 1175–1187 (2013).
Richner, N. et al. Dramatic decline in the Swiss arable flora since the 1920s. Agric. Ecosyst. Environ. 241, 179–192 (2017).
Schneider, C. et al. Biologisch-ökologische Grundlagen des Schutzes gefährdeter Segetalpflanzen, Bundesamt für Naturschutz (1994).
Fried, G. et al. Arable weed decline in Northern france: crop edges as refugia for weed conservation? Biol. Conserv. 142, 238–243 (2009).
Brooker, R. W. et al. Facilitation and sustainable agriculture: a mechanistic approach to reconciling crop production and conservation. Funct. Ecol. 30, 98–107 (2016).
Metzing, D. et al. Rote Liste gefährdeter Tiere, Pflanzen und Pilze Deutschlands. Band 7: Pflanzen. In 7 (2018).
Scheuerer, M. & Ahlmer, W. Rote liste gefährdeter Gefäßpflanzen Bayerns Mit regionalisierter florenliste. Schriftenreihe Bayer Landesamtes Für Umweltschutz. 165, 1–372 (2003).
Listl, D. & Reisch, C. Genetic variation of Sherardia arvensis L. – How land use and fragmentation affect an arable weed. Biochem. Syst. Ecol. 55, 164–169 (2014).
Jäger, E. J. et al. (eds) Exkursionsflora Von Deutschland (Spektrum Akademischer, 2013).
Knuth, P. Handbuch der Blütenbiologie, Engelmann (1898).
Wäldchen, J. et al. Zur Diasporen-Keimfähigkeit von Segetalpflanzen. Beitr. Für Forstwirtsch Landschaftsökologie. 39, 145–156 (2005).
Poschlod, P. Geschichte Der Kulturlandschaft: Entstehungsursachen Und Steuerungsfaktoren Der Entwicklung Der Kulturlandschaft, Lebensraum- Und Artenvielfalt in Mitteleuropa 2nd edn (Verlag Eugen Ulmer, 2017).
Rogers, S. O. & Bendich, A. J. Extraction of total cellular DNA from plants, algae and fungi. In Plant Molecular Biology Manual (eds, S. B. &, R. A.) 183–190 (Springer Netherlands, 1994).
Reisch, C. Genetic structure of Saxifraga tridactylites (Saxifragaceae) from natural and man-made habitats. Conserv. Genet. 8, 893–902 (2007).
Kusuma, Y. W. C. et al. Genetic diversity and structure of Hopea bilitonensis, an endemic dipterocarp from Belitung Island, Indonesia. J. Asia-Pac Biodivers. 17, 400–405 (2024).
Takata K, Taninaka H, Nonaka M, Iwase F, Kikuchi T, Suyama Y, Nagai S, Yasuda N. 2019. Multiplexed ISSR genotyping by sequencing distinguishes two precious coral species (Anthozoa: Octocorallia: Coralliidae) that share a mitochondrial haplotype. PeerJ 7:e7769, https://doi.org/10.7717/peerj.7769
Hirano, T. et al. Role of ancient lakes in genetic and phenotypic diversification of freshwater snails. Mol. Ecol. 28, 5032–5051 (2019).
Sakaba, T. et al. Phylogeography of the temperate grassland plant tephroseris Kirilowii (Asteraceae) inferred from multiplexed inter-simple sequence repeat genotyping by sequencing (MIG-seq) data. J. Plant. Res. 136, 437–452 (2023).
Suyama, Y. & Matsuki, Y. MIG-seq: an effective PCR-based method for genome-wide single-nucleotide polymorphism genotyping using the next-generation sequencing platform. Sci. Rep. 5, 16963 (2015).
Bolger, A. M. et al. Trimmomatic: a flexible trimmer for illumina sequence data. Bioinformatics 30, 2114–2120 (2014).
Catchen, J. et al. Stacks: an analysis tool set for population genomics. Mol. Ecol. 22, 3124–3140 (2013).
Kassambara, A. rstatix: Pipe-Friendly Framework for Basic Statistical Tests 0.7.2 (2019).
Peakall, R. & Smouse, P. E. GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research—an update. Bioinformatics 28, 2537–2539 (2012).
Pritchard, J. K. et al. Documentation for structure software: Version 2.3.
Evanno, G. et al. Detecting the number of clusters of individuals using the software structure: a simulation study. Mol. Ecol. 14, 2611–2620 (2005).
Li, Y. & Liu, J. StructureSelector: A web-based software to select and visualize the optimal number of clusters using multiple methods. Mol. Ecol. Resour. 18, 176–177 (2018).
Francis, R. M. Pophelper: an R package and web app to analyse and visualize population structure. Mol. Ecol. Resour. 17, 27–32 (2017).
Jombart, T. & Ahmed, I. Adegenet 1.3-1: new tools for the analysis of genome-wide SNP data. Bioinformatics 27, 3070–3071 (2011).
Do, C. et al. NeEstimator v2: re-implementation of software for the estimation of contemporary effective population size (N e) from genetic data. Mol. Ecol. Resour. 14, 209–214 (2014).
Waples, R. S. A bias correction for estimates of effective population size based on linkage disequilibrium at unlinked gene loci*. Conserv. Genet. 7, 167–184 (2006).
Waples, R. S. & Do, C. Linkage disequilibrium estimates of contemporary Ne using highly variable genetic markers: a largely untapped resource for applied conservation and evolution. Evol. Appl. 3, 244–262 (2010).
Hill, W. G. Estimation of effective population size from data on linkage disequilibrium. Genet. Res. 38, 209–216 (1981).
Jorde, P. E. & Ryman, N. Unbiased estimator for genetic drift and effective population size. Genetics 177, 927–935 (2007).
Lévêque, A. et al. Levels and Spatial patterns of effective population sizes in the Southern damselfly (Coenagrion mercuriale): on the need to carefully interpret Single-Point and Temporal estimations to set conservation guidelines. Evol. Appl. 17, e70062 (2024).
Colbach, N. et al. The response of weed and crop species to shading: which parameters explain weed impacts on crop production? Field Crops Res. 238, 45–55 (2019).
Rühl, A. T. et al. Future challenge for endangered arable weed species facing global warming: low temperature Optima and narrow moisture requirements. Biol. Conserv. 182, 262–269 (2015).
Bürger, J. et al. Populations of arable weed species show intra-specific variability in germination base temperature but not in early growth rate. PLOS ONE. 15, e0240538 (2020).
Reinermann, S. et al. The effect of droughts on vegetation condition in germany: an analysis based on two decades of satellite Earth observation time series and crop yield statistics. Remote Sens. 11, 1783 (2019).
Rühl, A. T. et al. Distinct germination response of endangered and common arable weeds to reduced water potential. Plant. Biol. 18, 83–90 (2016).
Reisch, C. & Bernhardt-Römermann, M. The impact of study design and life history traits on genetic variation of plants determined with AFLPs. Plant. Ecol. 215, 1493–1511 (2014).
Duminil, J. et al. Plant traits correlated with generation time directly affect inbreeding depression and mating system and indirectly genetic structure. BMC Evol. Biol. 9, 177 (2009).
Yang, X. et al. Global patterns of potential future plant diversity hidden in soil seed banks. Nat Commun 12, 7023 (2021). https://doi.org/10.1038/s41467-021-27379-1
Ottewell, K. M. et al. Can a seed bank provide demographic and genetic rescue in a declining population of the endangered shrub acacia pinguifolia? Conserv. Genet. 12, 669–678 (2011).
Honnay, O. et al. Can a seed bank maintain the genetic variation in the above ground plant population? Oikos 117, 1–5 (2008).
Vitalis, R. et al. When genes go to sleep: the population genetic consequences of seed dormancy and monocarpic perenniality. Am. Nat. 163, 295–311 (2004).
Iberl, K. et al. A source of hidden diversity: soil seed bank and aboveground populations of a common herb contain similar levels of genetic variation. Plant. Biol. 25, 1035–1045 (2023).
Münzbergová, Z. et al. Historical habitat connectivity affects current genetic structure in a grassland species. Plant. Biol. 15, 195–202 (2013).
Reisch, C. et al. Genetic diversity of calcareous grassland plant species depends on historical landscape configuration. BMC Ecol. 17, 19 (2017).
Krauss, J. et al. Habitat fragmentation causes immediate and time-delayed biodiversity loss at different trophic levels. Ecol. Lett. 13, 597–605 (2010).
Helm, A. et al. Slow response of plant species richness to habitat loss and fragmentation. Ecol. Lett. 9, 72–77 (2006).
Lehmair, T. A. et al. Genetic variation of litter meadow species reflects gene flow by hay transfer and mowing with agricultural machines. Conserv. Genet. 21, 879–890 (2020).
Reisch, C. et al. Drivers of genetic diversity in plant populations differ between semi-natural grassland types. Biodivers. Conserv. 30, 3549–3561 (2021).
Acknowledgements
The authors thank Petra Schitko and Lina Begemann for their support in the lab and with data analysis, as well as Sabine Fischer for assistance with the map.
Funding
Open Access funding enabled and organized by Projekt DEAL.
Author information
Authors and Affiliations
Contributions
E.G. and C.R. developed the study design; D.L. & E.G. identified and collected the plant material; E.G. and Y.S. collected the genetic data; E.G. and L.W. analysed the data, C.R. led the writing of the manuscript; all authors contributed to manuscript writing.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Supplementary Material 1
Supplementary Material 2
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 permissions
About this article
Cite this article
Gradl, E., Shimono, Y., Listl, D.M. et al. Genetic monitoring of an endangered arable weed reveals local maintenance of genetic variation in times of land use and climate change.
Sci Rep (2026). https://doi.org/10.1038/s41598-026-38363-4
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41598-026-38363-4
Keywords
- Sherardia arvensis
- Rare species
- MIG-seq
- Conservation genetics
- Next-generation-sequencing
- Agrobiodiversity
Source: Ecology - nature.com
