in

Climate warming has compounded plant responses to habitat conversion in northern Europe

  • IPBES. Global assessment report of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES secretariat, 2019).

  • Newbold, T. et al. Global effects of land use on local terrestrial biodiversity. Nature 520, 45–50 (2015).

    Article 
    ADS 
    CAS 

    Google Scholar 

  • IPCC. Summary for Policymakers. in Climate Change 2022: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (Cambridge University Press, 2022).

  • Travis, J. M. J. Climate change and habitat destruction: a deadly anthropogenic cocktail. P. R. Soc. B. 270, 467–473 (2003).

    Article 
    CAS 

    Google Scholar 

  • Newbold, T. Future effects of climate and land-use change on terrestrial vertebrate community diversity under different scenarios. P. R. Soc. B. 285, 20180792 (2018).

    Article 

    Google Scholar 

  • Anderson, K. J., Allen, A. P., Gillooly, J. F. & Brown, J. H. Temperature-dependence of biomass accumulation rates during secondary succession. Ecol. Lett. 9, 673–682 (2006).

    Article 

    Google Scholar 

  • Fridley, J. D. & Wright, J. P. Temperature accelerates the rate fields become forests. Proc. Natl Acad. Sci. USA 115, 4702–4706 (2018).

    Article 
    ADS 
    CAS 

    Google Scholar 

  • Zellweger, F. et al. Forest microclimate dynamics drive plant responses to warming. Science 368, 772–775 (2020).

    Article 
    ADS 
    CAS 

    Google Scholar 

  • Auffret, A. G., Kimberley, A., Plue, J. & Waldén, E. Super-regional land-use change and effects on the grassland specialist flora. Nat. Commun. 9, 3464 (2018).

    Article 
    ADS 

    Google Scholar 

  • Auffret, A. G. & Thomas, C. D. Synergistic and antagonistic effects of land use and non-native species on community responses to climate change. Glob. Change Biol. 25, 4303–4314 (2019).

    Article 
    ADS 

    Google Scholar 

  • Hill, M. O. Local frequency as a key to interpreting species occurrence data when recording effort is not known. Methods Ecol. Evol. 3, 195–205 (2012).

    Article 

    Google Scholar 

  • Isaac, N. J. B., Strien, A. J., van, August, T. A., Zeeuw, M. Pde & Roy, D. B. Statistics for citizen science: extracting signals of change from noisy ecological data. Methods Ecol. Evol. 5, 1052–1060 (2014).

    Article 

    Google Scholar 

  • Tyler, T., Herbertsson, L., Olofsson, J. & Olsson, P. A. Ecological indicator and traits values for Swedish vascular plants. Ecol. Indic. 120, 106923 (2021).

    Article 
    CAS 

    Google Scholar 

  • Jiang, M., Bullock, J. M. & Hooftman, D. A. P. Mapping ecosystem service and biodiversity changes over 70 years in a rural English county. J. Appl. Ecol. 50, 841–850 (2013).

    Article 

    Google Scholar 

  • IPCC. Summary for Policymakers. in Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (Cambridge University Press, 2021).

  • Van Calster, H. et al. Unexpectedly high 20th century floristic losses in a rural landscape in northern France. J. Ecol. 96, 927–936 (2008).

    Article 

    Google Scholar 

  • Staude, I. R. et al. Replacements of small- by large-ranged species scale up to diversity loss in Europe’s temperate forest biome. Nat. Ecol. Evol. 4, 802–808 (2020).

    Article 

    Google Scholar 

  • Chen, I.-C., Hill, J. K., Ohlemüller, R., Roy, D. B. & Thomas, C. D. Rapid range shifts of species associated with high levels of climate warming. Science 333, 1024–1026 (2011).

    Article 
    ADS 
    CAS 

    Google Scholar 

  • Lenoir, J. et al. Species better track climate warming in the oceans than on land. Nat. Ecol. Evol. 4, 1044–1059 (2020).

    Article 

    Google Scholar 

  • Platts, P. J. et al. Habitat availability explains variation in climate-driven range shifts across multiple taxonomic groups. Sci. Rep. 9, 1–10 (2019).

    Article 
    ADS 
    MathSciNet 
    CAS 

    Google Scholar 

  • Macgregor, C. J. et al. Climate-induced phenology shifts linked to range expansions in species with multiple reproductive cycles per year. Nat. Commun. 10, 4455 (2019).

    Article 
    ADS 

    Google Scholar 

  • Dullinger, S. et al. Extinction debt of high-mountain plants under twenty-first-century climate change. Nat. Clim. Change 2, 619–622 (2012).

    Article 
    ADS 

    Google Scholar 

  • Svenning, J.-C. & Sandel, B. Disequilibrium vegetation dynamics under future climate change. Am. J. Bot. 100, 1266–1286 (2013).

    Article 

    Google Scholar 

  • Cannone, N. & Pignatti, S. Ecological responses of plant species and communities to climate warming: upward shift or range filling processes? Climatic Change 123, 201–214 (2014).

    Article 
    ADS 

    Google Scholar 

  • Wiens, J. J. Climate-Related Local Extinctions Are Already Widespread among Plant and Animal Species. PLOS Biol. 14, e2001104 (2016).

    Article 

    Google Scholar 

  • Hill, M. O. & Preston, C. D. Disappearance of boreal plants in southern Britain: habitat loss or climate change? Biol. J. Linn. Soc. 115, 598–610 (2015).

    Article 

    Google Scholar 

  • Lynn, J. S., Klanderud, K., Telford, R. J., Goldberg, D. E. & Vandvik, V. Macroecological context predicts species’ responses to climate warming. Glob. Change Biol. 27, 2088–2101 (2021).

    Article 
    ADS 
    CAS 

    Google Scholar 

  • Liu, D. et al. Species selection under long-term experimental warming and drought explained by climatic distributions. N. Phytol. 217, 1494–1506 (2018).

    Article 

    Google Scholar 

  • Buitenwerf, R., Sandel, B., Normand, S., Mimet, A. & Svenning, J.-C. Land surface greening suggests vigorous woody regrowth throughout European semi-natural vegetation. Glob. Change Biol. 24, 5789–5801 (2018).

    Article 

    Google Scholar 

  • Suggitt, A. J. et al. Extinction risk from climate change is reduced by microclimatic buffering. Nat. Clim. Change 8, 713–717 (2018).

    Article 
    ADS 

    Google Scholar 

  • De Frenne, P. et al. Latitudinal gradients as natural laboratories to infer species’ responses to temperature. J. Ecol. 101, 784–795 (2013).

    Article 

    Google Scholar 

  • Ash, J. D., Givnish, T. J. & Waller, D. M. Tracking lags in historical plant species’ shifts in relation to regional climate change. Glob. Change Biol. 23, 1305–1315 (2017).

    Article 
    ADS 

    Google Scholar 

  • Savage, J. & Vellend, M. Elevational shifts, biotic homogenization and time lags in vegetation change during 40 years of climate warming. Ecography 38, 546–555 (2015).

    Article 

    Google Scholar 

  • Gerstner, K., Dormann, C. F., Stein, A., Manceur, A. M. & Seppelt, R. Effects of land use on plant diversity—a global meta-analysis. J. Appl. Ecol. 51, 1690–1700 (2014).

    Article 

    Google Scholar 

  • 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).

    Article 

    Google Scholar 

  • Bilz, M., Kell, S. P., Maxted, N. & Lansdown, R. V. European Red List of Vascular Plants (Publications Office of the EU, 2011).

  • Timmermann, A., Damgaard, C., Strandberg, M. T. & Svenning, J.-C. Pervasive early 21st-century vegetation changes across Danish semi-natural ecosystems: more losers than winners and a shift towards competitive, tall-growing species. J. Appl. Ecol. 52, 21–30 (2015).

    Article 

    Google Scholar 

  • Staude, I. R. et al. Directional turnover towards larger-ranged plants over time and across habitats. Ecol. Lett. 25, 466–482 (2022).

    Article 

    Google Scholar 

  • Finderup Nielsen, T., Sand‐Jensen, K., Dornelas, M. & Bruun, H. H. More is less: net gain in species richness, but biotic homogenization over 140 years. Ecol. Lett. 22, 1650–1657 (2019).

    Article 

    Google Scholar 

  • Christiansen, D. M., Iversen, L. L., Ehrlén, J. & Hylander, K. Changes in forest structure drive temperature preferences of boreal understorey plant communities. J. Ecol. 110, 631–643 (2022).

    Article 

    Google Scholar 

  • Gossner, M. M. et al. Land-use intensification causes multitrophic homogenization of grassland communities. Nature 540, 266–269 (2016).

    Article 
    ADS 
    CAS 

    Google Scholar 

  • Duprè, C. et al. Changes in species richness and composition in European acidic grasslands over the past 70 years: the contribution of cumulative atmospheric nitrogen deposition. Glob. Change Biol. 16, 344–357 (2010).

    Article 
    ADS 

    Google Scholar 

  • Tyler, T. et al. Climate warming and land‐use changes drive broad‐scale floristic changes in Southern Sweden. Glob. Change Biol. 24, 2607–2621 (2018).

    Article 
    ADS 

    Google Scholar 

  • Steinbauer, M. J. et al. Accelerated increase in plant species richness on mountain summits is linked to warming. Nature 556, 231 (2018).

    Article 
    ADS 
    CAS 

    Google Scholar 

  • Halley, J. M., Monokrousos, N., Mazaris, A. D., Newmark, W. D. & Vokou, D. Dynamics of extinction debt across five taxonomic groups. Nat. Commun. 7, 12283 (2016).

    Article 
    ADS 
    CAS 

    Google Scholar 

  • Bertrand, R. et al. Changes in plant community composition lag behind climate warming in lowland forests. Nature 479, 517–520 (2011).

    Article 
    ADS 
    CAS 

    Google Scholar 

  • Kuussaari, M. et al. Extinction debt: a challenge for biodiversity conservation. Trends Ecol. Evol. 24, 564–571 (2009).

    Article 

    Google Scholar 

  • Plue, J. et al. Buffering effects of soil seed banks on plant community composition in response to land use and climate. Glob. Ecol. Biogeogr. 30, 128–139 (2021).

    Article 

    Google Scholar 

  • Honnay, O. & Bossuyt, B. Prolonged clonal growth: escape route or route to extinction? Oikos 108, 427–432 (2005).

    Article 

    Google Scholar 

  • Ozinga, W. A. et al. Dispersal failure contributes to plant losses in NW Europe. Ecol. Lett. 12, 66–74 (2009).

    Article 

    Google Scholar 

  • Svenning, J.-C., Normand, S. & Skov, F. Postglacial dispersal limitation of widespread forest plant species in nemoral Europe. Ecography 31, 316–326 (2008).

    Article 

    Google Scholar 

  • Lenoir, J., Gégout, J. C., Marquet, P. A., de Ruffray, P. & Brisse, H. A significant upward shift in plant species optimum elevation during the 20th century. Science 320, 1768–1771 (2008).

    Article 
    ADS 
    CAS 

    Google Scholar 

  • Thomas, C. D. et al. Extinction risk from climate change. Nature 427, 145–148 (2004).

    Article 
    ADS 
    CAS 

    Google Scholar 

  • Warren, R., Price, J., Graham, E., Forstenhaeusler, N. & VanDerWal, J. The projected effect on insects, vertebrates, and plants of limiting global warming to 1.5 °C rather than 2 °C. Science 360, 791–795 (2018).

    Article 
    CAS 

    Google Scholar 

  • Garrido, P. et al. Experimental rewilding may restore abandoned wood-pastures if policy allows. Ambio 50, 101–112 (2021).

    Article 

    Google Scholar 

  • Kowalczyk, R., Kamiński, T. & Borowik, T. Do large herbivores maintain open habitats in temperate forests? For. Ecol. Manag. 494, 119310 (2021).

    Article 

    Google Scholar 

  • Auffret, A. G., Schmucki, R., Reimark, J. & Cousins, S. A. O. Grazing networks provide useful functional connectivity for plants in fragmented systems. J. Veg. Sci. 23, 970–977 (2012).

    Article 

    Google Scholar 

  • Fricke, E. C., Ordonez, A., Rogers, H. S. & Svenning, J.-C. The effects of defaunation on plants’ capacity to track climate change. Science 375, 210–214 (2022).

    Article 
    ADS 
    CAS 

    Google Scholar 

  • Blomgren, E., Falk, E. & Herloff, B. Bohusläns Flora (Föreningen Bohusläns Flora, 2011).

  • Fries, H. Göteborgs och Bohus Läns Fanerogamer och Ormbunkar (Elanders Boktryckeri, 1945).

  • Lidberg, R. & Lindström, H. Medelpads Flora (The vascular plants of Medelpad) (SBF Förlaget, 2010).

  • Sterner, R. Flora der insel Öland Vol. IX (Almqvist & Wiksells, 1938).

  • Almquist, E. Upplands vegetation och flora. Acta Phytogeogr. Suec. 1, 1–622 (1929).

    Google Scholar 

  • Jonsell, L. Upplands Flora (SBF Förlaget, 2010).

  • Maad, J., Sundberg, S., Stolpe, P. & Jonsell, L. Floraförändringar i Uppland under 1900-talet—en analys från Projekt Upplands flora [Floristic changes during the 20th century in Uppland, east central Sweden; with English summary]. Sven. Botanisk Tidskr. 103, 67–104 (2009).

    Google Scholar 

  • Auffret, A. G. et al. HistMapR: Rapid digitization of historical land-use maps in R. Methods Ecol. Evol. 8, 1453–1457 (2017).

    Article 

    Google Scholar 

  • August, T. et al. sparta: Trend analysis for unstructured data. R package version 0.1.44 (2018).

  • Eichenberg, D. et al. Widespread decline in Central European plant diversity across six decades. Glob. Change Biol. 27, 1097–1110 (2021).

    Article 
    ADS 
    CAS 

    Google Scholar 

  • Redhead, J. W. et al. Potential landscape-scale pollinator networks across Great Britain: structure, stability and influence of agricultural land cover. Ecol. Lett. 21, 1821–1832 (2018).

    Article 

    Google Scholar 

  • Gillings, S. et al. Breeding and wintering bird distributions in Britain and Ireland from citizen science bird atlases. Glob. Ecol. Biogeogr. 28, 866–874 (2019).

    Article 

    Google Scholar 

  • Stroh, P. A., Walker, K. J., Humphrey, T. A., Pescott, O. L. & Burkmar, R. J. Plant Atlas 2020: Mapping Changes in the Distribution of the British and Irish Flora (Princeton, planned publication date: 21/03/2023).

  • Pearce-Higgins, J. W., Ausden, M. A., Beale, C. M., Oliver, T. H. & Crick, H. Q. P. Research on the assessment of risks & opportunities for species in England as a result of climate change – NECR175. Natural England Commissioned Reports Vol. 175 (2015).

  • R. Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2022).

  • Telfer, M. G., Preston, C. D. & Rothery, P. A general method for measuring relative change in range size from biological atlas data. Biol. Conserv. 107, 99–109 (2002).

    Article 

    Google Scholar 

  • Bates, D., Maechler, M., Bolker, B. M. & Walker, S. lme4: Linear mixed-effects models using Eigen and S4. R package version 1.1-7. http://CRAN.R-project.org/package=lme4 (2014).

  • Zuur, A. F., Ieno, E. N. & Elphick, C. S. A protocol for data exploration to avoid common statistical problems. Methods Ecol. Evol. 1, 3–14 (2009).

    Article 

    Google Scholar 

  • Dormann, C. F. et al. Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography 36, 27–46 (2013).

    Article 

    Google Scholar 

  • Schielzeth, H. Simple means to improve the interpretability of regression coefficients. Methods Ecol. Evol. 1, 103–113 (2010).

    Article 

    Google Scholar 

  • Nakagawa, S. & Schielzeth, H. A general and simple method for obtaining R2 from generalized linear mixed-effects models. Methods Ecol. Evol. 4, 133–142 (2013).

    Article 

    Google Scholar 

  • Borcard, D. & Legendre, P. All-scale spatial analysis of ecological data by means of principal coordinates of neighbour matrices. Ecol. Model. 153, 51–68 (2002).

    Article 

    Google Scholar 

  • Oksanen, J. et al. vegan: Community ecology package. R package version 2.3-5. http://CRAN.R-project.org/package=vegan (2016).

  • Meineri, E. & Hylander, K. Fine-grain, large-domain climate models based on climate station and comprehensive topographic information improve microrefugia detection. Ecography 40, 1003–1013 (2017).

    Article 

    Google Scholar 

  • Lüdecke, D., Ben-Shachar, M. S., Patil, I., Waggoner, P. & Makowski, D. performance: an R package for assessment, comparison and testing of statistical models. J. Open Source Softw. 6, 3139 (2021).

    Article 
    ADS 

    Google Scholar 

  • Breheny, P. & Burchett, W. Visualization of regression models using visreg. R. J. 9, 57–71 (2017).

    Article 

    Google Scholar 

  • Hijmans, R. J. raster: Geographic data analysis and modeling. R package version 2.5-8. http://CRAN.R-project.org/package=raster (2016).

  • Neolithic dental calculi provide evidence for environmental proxies and consumption of wild edible fruits and herbs in central Apennines

    Environmentally driven phenotypic convergence and niche conservatism accompany speciation in hoary bats