Ficetola, G. F. et al. Dynamics of ecological communities following current retreat of glaciers. Annu. Rev. Ecol. Evol. Syst. 52, 405–426 (2021).
Pothula, S. K. & Adams, B. J. Community assembly in the wake of glacial retreat: a meta-analysis. Glob. Chang. Biol. 28, 6973–6991 (2022).
Bosson, J. B. et al. Future emergence of new ecosystems caused by glacial retreat. Nature 620, 562–569 (2023).
Rounce, D. R. et al. Global glacier change in the 21st century: every increase in temperature matters. Science 379, 78–83 (2023).
Zimmer, A., Beach, T., Klein, J. A. & Recharte Bullard, J. The need for stewardship of lands exposed by deglaciation from climate change. Wiley Interdiscip. Rev. Clim. Change 13, e753 (2022).
Taberlet, P., Bonin, A., Zinger, L. & Coissac, E. Environmental DNA: For Biodiversity Research and Monitoring (Oxford Univ. Press, 2018).
Hock, R. et al. GlacierMIP — a model intercomparison of global-scale glacier mass-balance models and projections. J. Glaciol. 65, 453–467 (2019).
Lee, J. R. et al. Climate change drives expansion of Antarctic ice-free habitat. Nature 547, 49–54 (2017).
Körner, C. Mountain biodiversity, its causes and function. Ambio 33, 11–17 (2004).
Palomo, I. Climate change impacts on ecosystem services in high mountain areas: a literature review. Mt. Res. Dev. 37, 179–187 (2017).
La Farge, C., Williams, K. H. & England, J. H. Regeneration of Little Ice Age bryophytes emerging from a polar glacier with implications of totipotency in extreme environments. Proc. Natl Acad. Sci. USA 110, 9839–9844 (2013).
Donhauser, J. & Frey, B. Alpine soil microbial ecology in a changing world. FEMS Microbiol. Ecol. 94, fiy099 (2018).
Hågvar, S. et al. Ecosystem birth near melting glaciers: a review on the pioneer role of ground-dwelling arthropods. Insects 11, 644 (2020).
Cauvy-Fraunié, S. & Dangles, O. A global synthesis of biodiversity responses to glacier retreat. Nat. Ecol. Evol. 3, 1675–1685 (2019).
Hugonnet, R. et al. Accelerated global glacier mass loss in the early twenty-first century. Nature 592, 726–731 (2021).
Moore, J. W. et al. Mining stakes claim on salmon futures as glaciers retreat. Science 382, 887–889 (2023).
Poorter, L. et al. Multidimensional tropical forest recovery. Science 374, 1370–1376 (2021).
Walker, L. R., Wardle, D. A., Bardgett, R. D. & Clarkson, B. D. The use of chronosequences in studies of ecological succession and soil development. J. Ecol. 98, 725–736 (2010).
Connell, J. H. & Slatyer, R. O. Mechanisms of succession in natural communities and their role in community stability and organization. Am. Nat. 111, 1119–1144 (1977).
Hanusch, M., He, X., Ruiz-Hernández, V. & Junker, R. R. Succession comprises a sequence of threshold-induced community assembly processes towards multidiversity. Commun. Biol. 5, 424 (2022).
Pulsford, S. A., Lindenmayer, D. B. & Driscoll, D. A. A succession of theories: purging redundancy from disturbance theory. Biol. Rev. 91, 148–167 (2016).
Rosero, P. et al. Multi-taxa colonisation along the foreland of a vanishing equatorial glacier. Ecography 44, 1010–1021 (2021).
Fan, K. et al. Soil biodiversity supports the delivery of multiple ecosystem functions in urban greenspaces. Nat. Ecol. Evol. 7, 113–126 (2023).
Khedim, N. et al. Topsoil organic matter build-up in glacier forelands around the world. Glob. Chang. Biol. 27, 1662–1677 (2021).
Lutz, S. et al. The biogeography of red snow microbiomes and their role in melting arctic glaciers. Nat. Commun. 7, 11968 (2016).
Rime, T., Hartmann, M. & Frey, B. Potential sources of microbial colonizers in an initial soil ecosystem after retreat of an alpine glacier. ISME J. 10, 1625–1641 (2016).
Zimmer, A. et al. Soil temperature and local initial conditions drive carbon and nitrogen build-up in young proglacial soils in the Tropical Andes and European Alps. Catena 235, 107645 (2024).
Bardgett, R. D. et al. Heterotrophic microbial communities use ancient carbon following glacial retreat. Biol. Lett. 3, 487–490 (2007).
Hunter, B. D., Roering, J. J., Silva, L. C. R. & Moreland, K. C. Geomorphic controls on the abundance and persistence of soil organic carbon pools in erosional landscapes. Nat. Geosci. 17, 151–157 (2024).
Draebing, D., Mayer, T., Jacobs, B. & McColl, S. T. Alpine rockwall erosion patterns follow elevation-dependent climate trajectories. Commun. Earth Environ. 3, 21 (2022).
Erhart, H. La Génèse Des Sols En Tant Que Phénomène Géologique: Esquisse d’une Théorie Géologique et Géochimique: Biostasie et Rhexistasie (Masson, 1951).
Salazar, A., Warshan, D., Vasquez-Mejia, C. & Andrésson, Ó. S. Environmental change alters nitrogen fixation rates and microbial parameters in a subarctic biological soil crust. Oikos 2022, e09239 (2022).
Sepp, S.-K. et al. Global diversity and distribution of nitrogen-fixing bacteria in the soil. Front. Plant Sci. 14, 1100235 (2023).
Bahram, M. et al. Structure and function of the global topsoil microbiome. Nature 560, 233–237 (2018).
Angert, A. L., Huxman, T. E., Chesson, P. & Venable, D. L. Functional tradeoffs determine species coexistence via the storage effect. Proc. Natl Acad. Sci. USA 106, 11641–11645 (2009).
Peyre, G. et al. The fate of páramo plant assemblages in the sky islands of the northern Andes. J. Veg. Sci. 31, 967–980 (2020).
Vellend, M. et al. Assessing the relative importance of neutral stochasticity in ecological communities. Oikos 123, 1420–1430 (2014).
Martiny, J. B. H. et al. Microbial biogeography: putting microorganisms on the map. Nat. Rev. Microbiol. 4, 102–112 (2006).
Ohlmann, M. et al. Mapping the imprint of biotic interactions on β-diversity. Ecol. Lett. 21, 1660–1669 (2018).
Tscherko, D., Hammesfahr, U., Zeltner, G., Kandeler, E. & Böcker, R. Plant succession and rhizosphere microbial communities in a recently deglaciated alpine terrain. Basic Appl. Ecol. 6, 367–383 (2005).
Losapio, G. et al. Network motifs involving both competition and facilitation predict biodiversity in alpine plant communities. Proc. Natl Acad. Sci. USA 118, e2005759118 (2021).
Sint, D., Kaufmann, R., Mayer, R. & Traugott, M. Resolving the predator first paradox: arthropod predator food webs in pioneer sites of glacier forelands. Mol. Ecol. 28, 336–347 (2019).
Bennett, J. A. et al. Plant–soil feedbacks and mycorrhizal type influence temperate forest population dynamics. Science 355, 181–184 (2017).
Calderón-Sanou, I. et al. Cascading effects of moth outbreaks on subarctic soil food webs. Sci. Rep. 11, 15054 (2021).
Houlton, B. Z., Wang, Y.-P., Vitousek, P. M. & Field, C. B. A unifying framework for dinitrogen fixation in the terrestrial biosphere. Nature 454, 327–330 (2008).
Tedersoo, L., Bahram, M. & Zobel, M. How mycorrhizal associations drive plant population and community biology. Science 367, eaba1223 (2020).
Cantera, I. et al. The importance of species addition ‘versus’ replacement varies over succession in plant communities after glacier retreat. Nat. Plants 10, 256–267 (2024).
Pugnaire, F. I. et al. Climate change effects on plant–soil feedbacks and consequences for biodiversity and functioning of terrestrial ecosystems. Sci. Adv. 5, eaaz1834 (2019).
Guerra, C. A. et al. Global hotspots for soil nature conservation. Nature 610, 693–698 (2022).
Sytsma, M. L. T., Lewis, T., Bakker, J. D. & Prugh, L. R. Successional patterns of terrestrial wildlife following deglaciation. J. Anim. Ecol. 92, 723–737 (2023).
Butler, D. R., Anzah, F., Goff, P. D. & Villa, J. Zoogeomorphology and resilience theory. Geomorphology 305, 154–162 (2018).
Zemp, M. et al. Global glacier mass changes and their contributions to sea-level rise from 1961 to 2016. Nature 568, 382–386 (2019).
Marta, S. et al. The retreat of mountain glaciers since the Little Ice Age: a spatially explicit database. Data 6, 107 (2021).
Dickie, I. A. et al. Towards robust and repeatable sampling methods in eDNA-based studies. Mol. Ecol. Resour. 18, 940–952 (2018).
Guerrieri, A. et al. Metabarcoding data reveal vertical multitaxa variation in topsoil communities during the colonization of deglaciated forelands. Mol. Ecol. https://doi.org/10.1111/mec.16669 (2023).
Rime, T. et al. Vertical distribution of the soil microbiota along a successional gradient in a glacier forefield. Mol. Ecol. 24, 1091–1108 (2015).
Guerrieri, A. et al. Effects of soil preservation for biodiversity monitoring using environmental DNA. Mol. Ecol. 30, 3313–3325 (2021).
Bray, R. H. & Kurtz, L. T. Determination of total organic and available forms of phosphorus in soils. Soil Sci. 59, 39–46 (1945).
Olsen, S. R. Estimation of Available Phosphorus in Soils by Extraction with Sodium Bicarbonate (US Department of Agriculture, 1954).
Marta, S. et al. Heterogeneous changes of soil microclimate in high mountains and glacier forelands. Nat. Commun. https://doi.org/10.21203/rs.3.rs-2017904/v1 (2023).
Smith, P. & Metcalfe, P. dynatop: An implementation of dynamic TOPMODEL hydrological model in R. GitHub https://github.com/waternumbers/dynatop (2022).
Paruelo, J. M., Epstein, H. E., Lauenroth, W. K. & Burke, I. C. ANPP estimates from NDVI for the central grassland region of the United States. Ecology 78, 953–958 (1997).
Rumpf, S. B. et al. From white to green: snow cover loss and increased vegetation productivity in the European Alps. Science 376, 1119–1122 (2022).
Lillesand, T., Kiefer, R. W. & Chipman, J. Remote Sensing and Image Interpretation 7th edn (Wiley, 2015).
Liu, Y. et al. Evaluation of consistency among three NDVI products applied to High Mountain Asia in 2000–2015. Remote Sens. Environ. 269, 112821 (2022).
Aybar, C. et al. rgee: R bindings for calling the ‘Earth Engine’ API. GitHub https://github.com/google/earthengine-api (2022).
Ficetola, G. F. & Taberlet, P. Towards exhaustive community ecology via DNA metabarcoding. Mol. Ecol. https://doi.org/10.1111/mec.16881.
Guardiola, M. et al. Deep-sea, deep-sequencing: metabarcoding extracellular DNA from sediments of marine canyons. PLoS ONE 10, e0139633 (2015).
Moll, J. & Hoppe, B. Evaluation of primers for the detection of deadwood-inhabiting archaea via amplicon sequencing. PeerJ 10, e14567 (2022).
Hathaway, J. J. M., Moser, D. P., Blank, J. G. & Northup, D. E. A comparison of primers in 16S rRNA gene surveys of Bacteria and Archaea from volcanic caves. Geomicrobiol. J. 38, 741–754 (2021).
Epp, L. S. et al. New environmental metabarcodes for analysing soil DNA: potential for studying past and present ecosystems. Mol. Ecol. 21, 1821–1833 (2012).
Taberlet, P. et al. Power and limitations of the chloroplast trnL (UAA) intron for plant DNA barcoding. Nucleic Acids Res. 35, e14 (2007).
Janssen, P. et al. Present conditions may mediate the legacy effect of past land-use changes on species richness and composition of above- and below-ground assemblages. J. Ecol. 106, 306–318 (2018).
Bienert, F. et al. Tracking earthworm communities from soil DNA. Mol. Ecol. 21, 2017–2030 (2012).
Lunghi, E. et al. Environmental DNA of insects and springtails from caves reveals complex processes of eDNA transfer in soils. Sci. Total Environ. 826, 154022 (2022).
Coissac, E. OligoTag: a program for designing sets of tags for next-generation sequencing of multiplexed samples. Methods Mol. Biol. 888, 13–31 (2012).
Zinger, L. et al. DNA metabarcoding — need for robust experimental designs to draw sound ecological conclusions. Mol. Ecol. 28, 1857–1862 (2019).
Boyer, F. et al. obitools: A unix-inspired software package for DNA metabarcoding. Mol. Ecol. Resour. 16, 176–182 (2016).
Brown, S. P. et al. Scraping the bottom of the barrel: are rare high throughput sequences artifacts? Fungal Ecol. 13, 221–225 (2015).
Alberdi, A., Aizpurua, O., Gilbert, M. T. P. & Bohmann, K. Scrutinizing key steps for reliable metabarcoding of environmental samples. Methods Ecol. Evol. 9, 134–147 (2018).
Bonin, A., Guerrieri, A. & Ficetola, G. F. Optimal sequence similarity thresholds for clustering of molecular operational taxonomic units in DNA metabarcoding studies. Mol. Ecol. Resour. 23, 368–381 (2023).
Calderón‐Sanou, I., Münkemüller, T., Boyer, F., Zinger, L. & Thuiller, W. From environmental DNA sequences to ecological conclusions: how strong is the influence of methodological choices? J. Biogeogr. 47, 193–206 (2020).
Bálint, M. et al. Millions of reads, thousands of taxa: microbial community structure and associations analyzed via marker genes. FEMS Microbiol. Rev. 40, 686–700 (2016).
Ficetola, G. F. et al. Replication levels, false presences and the estimation of the presence/absence from eDNA metabarcoding data. Mol. Ecol. Resour. 15, 543–556 (2015).
Ariza, M. et al. Plant biodiversity assessment through soil eDNA reflects temporal and local diversity. Methods Ecol. Evol. 14, 415–430 (2023).
Pansu, J. et al. Long-lasting modification of soil fungal diversity associated with the introduction of rabbits to a remote sub-Antarctic archipelago. Biol. Lett. 11, 20150408 (2015).
Foucher, A. et al. Persistence of environmental DNA in cultivated soils: implication of this memory effect for reconstructing the dynamics of land use and cover changes. Sci. Rep. 10, 10502 (2020).
O’Malley, M. A., Simpson, A. G. B. & Roger, A. J. The other eukaryotes in light of evolutionary protistology. Biol. Philos. 28, 299–330 (2013).
Whittaker, R. H. New concepts of kingdoms or organisms. Evolutionary relations are better represented by new classifications than by the traditional two kingdoms. Science 163, 150–160 (1969).
Simpson, A. G. B., Slamovits, C. H. & Archibald, J. M. in Handbook of the Protists (eds Archibald, J. M., Simpson, A. G. B. & Slamovits, C. H.) 1–21 (Springer International, 2017).
Anthony, M. A., Bender, S. F. & van der Heijden, M. G. A. Enumerating soil biodiversity. Proc. Natl Acad. Sci. USA 120, e2304663120 (2023).
Fierer, N., Strickland, M. S., Liptzin, D., Bradford, M. A. & Cleveland, C. C. Global patterns in belowground communities. Ecol. Lett. 12, 1238–1249 (2009).
Bar-On, Y. M., Phillips, R. & Milo, R. The biomass distribution on Earth. Proc. Natl Acad. Sci. USA 115, 6506–6511 (2018).
Zinger, L. et al. Body size determines soil community assembly in a tropical forest. Mol. Ecol. 28, 528–543 (2019).
Johnson, E. A. & Miyanishi, K. Testing the assumptions of chronosequences in succession. Ecol. Lett. 11, 419–431 (2008).
Makoto, K. & Wilson, S. D. New multicentury evidence for dispersal limitation during primary succession. Am. Nat. 187, 804–811 (2016).
Rydgren, K., Halvorsen, R., Töpper, J. P. & Njøs, J. M. Glacier foreland succession and the fading effect of terrain age. J. Veg. Sci. 25, 1367–1380 (2014).
Tampucci, D. et al. Plant and arthropod colonisation of a glacier foreland in a peripheral mountain range. Biodiversity 16, 213–223 (2015).
Vater, A. E. & Matthews, J. A. Succession of pitfall-trapped insects and arachnids on eight Norwegian glacier forelands along an altitudinal gradient: patterns and models. Holocene 25, 108–129 (2015).
Damgaard, C. A critique of the space-for-time substitution practice in community ecology. Trends Ecol. Evol. 34, 416–421 (2019).
Smith, J. et al. BioDeepTime: a database of biodiversity time series for modern and fossil assemblages. Global Ecol. Biogeogr. 32, 1680–1689 (2023).
Foster, B. L. & Tilman, D. Dynamic and static views of succession: testing the descriptive power of the chronosequence approach. Plant Ecol. 146, 1–10 (2000).
Erschbamer, B., Niederfriniger Schlag, R., Carnicero, P. & Kaufmann, R. Long-term monitoring confirms limitations of recruitment and facilitation and reveals unexpected changes of the successional pathways in a glacier foreland of the Central Austrian Alps. Plant Ecol. 224, 373–386 (2023).
Fickert, T. & Grüninger, F. High-speed colonization of bare ground — permanent plot studies on primary succession of plants in recently deglaciated glacier forelands. Land Degrad. Dev. 29, 2668–2680 (2018).
Mächler, E., Walser, J.-C. & Altermatt, F. Decision-making and best practices for taxonomy-free environmental DNA metabarcoding in biomonitoring using Hill numbers. Mol. Ecol. 30, 3326–3339 (2021).
McMurdie, P. J. & Holmes, S. Waste not, want not: why rarefying microbiome data is inadmissible. PLoS Comput. Biol. 10, e1003531 (2014).
Bürkner, P.-C. brms: An R package for bayesian multilevel models using Stan. J. Stat. Softw. 80, 1–28 (2017).
Ren, Z. & Gao, H. Abundant and rare soil fungi exhibit distinct succession patterns in the forefield of Dongkemadi glacier on the central Qinghai-Tibet Plateau. Sci. Total Environ. 828, 154563 (2022).
Bjornstad, O. N. & Cai, J. ncf: Spatial covariance functions. CRAN https://doi.org/10.32614/CRAN.package.ncf (2022).
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).
Körner, C. Alpine Plant Life: Functional Plant Ecology of High Mountain Ecosystems (Springer Nature, 2021).
Paulsen, J. & Körner, C. A climate-based model to predict potential treeline position around the globe. Alp. Botany 124, 1–12 (2014).
Lefcheck, J. S. piecewiseSEM: Piecewise structural equation modelling in R for ecology, evolution, and systematics. Methods Ecol. Evol. 7, 573–579 (2016).
Delavaux, C. S., Ramos, R. J., Sturmer, S. L. & Bever, J. D. Environmental identification of arbuscular mycorrhizal fungi using the LSU rDNA gene region: an expanded database and improved pipeline. Mycorrhiza 32, 145–153 (2022).
Delavaux, C. S. et al. Mycorrhizal types influence island biogeography of plants. Commun. Biol. 4, 1128 (2021).
Bollen, K. A., Harden, J. J., Ray, S. & Zavisca, J. BIC and alternative Bayesian information criteria in the selection of structural equation models. Struct. Equ. Modeling 21, 1–19 (2014).
Hertzog, L. R. How robust are structural equation models to model miss-specification? A simulation study. Preprint at arXiv https://doi.org/10.48550/arXiv.1803.06186 (2019).
Lin, L.-C., Huang, P.-H. & Weng, L.-J. Selecting path models in SEM: a comparison of model selection criteria. Struct. Equ. Modeling 24, 855–869 (2017).
Oberski, D. lavaan.survey: An R package for complex survey analysis of structural equation models. J. Stat. Softw. 57, 1–27 (2014).
Shipley, B. & Douma, J. C. Generalized AIC and chi-squared statistics for path models consistent with directed acyclic graphs. Ecology 101, e02960 (2020).
Douma, J. C. & Shipley, B. Testing model fit in path models with dependent errors given non-normality, non-linearity and hierarchical data. Struct. Equ. Modeling 30, 222–233 (2023).
Westland, J. C. Structural Equation Models: From Paths to Networks (Springer, 2020).
Dormann, C. F. et al. Methods to account for spatial autocorrelation in the analysis of species distributional data: a review. Ecography 30, 609–628 (2007).
Lichstein, J., Simons, T., Shriner, S. & Franzreb, K. Spatial autocorrelation and autoregressive models in ecology. Ecol. Monogr. 72, 445–463 (2002).
Roser, L. G., Ferreyra, L. I., Saidman, B. O. & Vilardi, J. C. EcoGenetics: an R package for the management and exploratory analysis of spatial data in landscape genetics. Mol. Ecol. Resour. 17, e241–e250 (2017).
Shipley, B. Cause and Correlation in Biology: A User’s Guide to Path Analysis, Structural Equations and Causal Inference with R (Cambridge Univ. Press, 2016).
Legendre, P., Lapointe, F.-J. & Casgrain, P. Modeling brain evolution from behavior: a permutational regression approach. Evolution 48, 1487–1499 (1994).
Martinez-Almoyna, C. et al. Multi-trophic β-diversity mediates the effect of environmental gradients on the turnover of multiple ecosystem functions. Funct. Ecol. 33, 2053–2064 (2019).
Lichstein, J. W. Multiple regression on distance matrices: a multivariate spatial analysis tool. Plant Ecol. 188, 117–131 (2007).