Microbial evolution-An under-appreciated driver of soil carbon cycling.
biogeochemistry
carbon cycle
evolution
global change
microbe
Journal
Global change biology
ISSN: 1365-2486
Titre abrégé: Glob Chang Biol
Pays: England
ID NLM: 9888746
Informations de publication
Date de publication:
Apr 2024
Apr 2024
Historique:
revised:
18
03
2024
received:
20
12
2023
accepted:
18
03
2024
medline:
2
4
2024
pubmed:
2
4
2024
entrez:
2
4
2024
Statut:
ppublish
Résumé
Although substantial advances in predicting the ecological impacts of global change have been made, predictions of the evolutionary impacts have lagged behind. In soil ecosystems, microbes act as the primary energetic drivers of carbon cycling; however, microbes are also capable of evolving on timescales comparable to rates of global change. Given the importance of soil ecosystems in global carbon cycling, we assess the potential impact of microbial evolution on carbon-climate feedbacks in this system. We begin by reviewing the current state of knowledge concerning microbial evolution in response to global change and its specific effect on soil carbon dynamics. Through this integration, we synthesize a roadmap detailing how to integrate microbial evolution into ecosystem biogeochemical models. Specifically, we highlight the importance of microscale mechanistic soil carbon models, including choosing an appropriate evolutionary model (e.g., adaptive dynamics, quantitative genetics), validating model predictions with 'omics' and experimental data, scaling microbial adaptations to ecosystem level processes, and validating with ecosystem-scale measurements. The proposed steps will require significant investment of scientific resources and might require 10-20 years to be fully implemented. However, through the application of multi-scale integrated approaches, we will advance the integration of microbial evolution into predictive understanding of ecosystems, providing clarity on its role and impact within the broader context of environmental change.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e17268Subventions
Organisme : Schmidt Futures Program
Organisme : H2020 Marie Skłodowska-Curie Actions
ID : 891576
Organisme : H2020 European Research Council
ID : 101001608
Informations de copyright
© 2024 The Authors. Global Change Biology published by John Wiley & Sons Ltd.
Références
Abramoff, R., Xu, X., Hartman, M., O'Brien, S., Feng, W., Davidson, E., Finzi, A., Moorhead, D., Schimel, J., Torn, M., & Mayes, M. A. (2018). The Millennial model: In search of measurable pools and transformations for modeling soil carbon in the new century. Biogeochemistry, 137(1), 51–71.
Abramoff, R. Z., Guenet, B., Zhang, H., Georgiou, K., Xu, X., Viscarra Rossel, R. A., Yuan, W., & Ciais, P. (2022). Improved global‐scale predictions of soil carbon stocks with Millennial Version 2. Soil Biology & Biochemistry, 164, 108466.
Abrams, P. A. (2001). Modelling the adaptive dynamics of traits involved in inter‐and intraspecific interactions: An assessment of three methods. Ecology Letters, 4(2), 166–175.
Abrams, P. A., Matsuda, H., & Harada, Y. (1993). Evolutionarily unstable fitness maxima and stable fitness minima of continuous traits. Evolutionary Ecology, 7(5), 465–487.
Abs, E., Chase, A. B., & Allison, S. D. (2023). How do soil microbes shape ecosystem biogeochemistry in the context of global change? Environmental Microbiology, 25(4), 780–785.
Abs, E., Leman, H., & Ferrière, R. (2020). A multi‐scale eco‐evolutionary model of cooperation reveals how microbial adaptation influences soil decomposition. Communications Biology, 3(1), 520.
Abs, E., Saleska, S., & Ferriere, R. (2022). Microbial eco‐evolutionary responses amplify global soil carbon loss with climate warming. Research Square. https://doi.org/10.21203/rs.3.rs‐1984500/v1
Allen White, R., Borkum, M. I., Rivas‐Ubach, A., Bilbao, A., Wendler, J. P., Colby, S. M., Köberl, M., & Jansson, C. (2017). From data to knowledge: The future of multi‐omics data analysis for the rhizosphere. Rhizosphere, 3, 222–229.
Allison, S. D. (2005). Cheaters, diffusion and nutrients constrain decomposition by microbial enzymes in spatially structured environments. Ecology Letters, 8(6), 626–635.
Allison, S. D. (2012). A trait‐based approach for modelling microbial litter decomposition. Ecology Letters, 15(9), 1058–1070.
Allison, S. D. (2014). Modeling adaptation of carbon use efficiency in microbial communities. Frontiers in Microbiology, 5, 571.
Arevalo, P., VanInsberghe, D., Elsherbini, J., Gore, J., & Polz, M. F. (2019). A reverse ecology approach based on a biological definition of microbial populations. Cell, 178(4), 820–834.e14.
Averill, C., Cates, L. L., Dietze, M. C., & Bhatnagar, J. M. (2019). Spatial vs. temporal controls over soil fungal community similarity at continental and global scales. The ISME Journal, 13(8), 2082–2093.
Averill, C., Waring, B. G., & Hawkes, C. V. (2016). Historical precipitation predictably alters the shape and magnitude of microbial functional response to soil moisture. Global Change Biology, 22(5), 1957–1964.
Baltrus, D. A. (2013). Exploring the costs of horizontal gene transfer. Trends in Ecology & Evolution, 28(8), 489–495.
Bassar, R. D., Coulson, T., Travis, J., & Reznick, D. N. (2021). Towards a more precise‐ and accurate‐view of eco‐evolution. Ecology Letters, 24(4), 623–625.
Bendall, M. L., Stevens, S. L., Chan, L.‐K., Malfatti, S., Schwientek, P., Tremblay, J., Schackwitz, W., Martin, J., Pati, A., Bushnell, B., Froula, J., Kang, D., Tringe, S. G., Bertilsson, S., Moran, M. A., Shade, A., Newton, R. J., McMahon, K. D., & Malmstrom, R. R. (2016). Genome‐wide selective sweeps and gene‐specific sweeps in natural bacterial populations. The ISME Journal, 10(7), 1589–1601.
Blazanin, M., & Turner, P. E. (2021). Community context matters for bacteria‐phage ecology and evolution. The ISME Journal, 15(11), 3119–3128.
Bolker, B., & Pacala, S. W. (1997). Using moment equations to understand stochastically driven spatial pattern formation in ecological systems. Theoretical Population Biology, 52(3), 179–197.
Bonan, G. B., Hartman, M. D., Parton, W. J., & Wieder, W. R. (2013). Evaluating litter decomposition in Earth system models with long‐term litterbag experiments: An example using the Community Land Model version 4 (CLM4). Global Change Biology, 19(3), 957–974. https://doi.org/10.1111/gcb.12031
Bouin, E., Calvez, V., Meunier, N., Mirrahimi, S., Perthame, B., Raoul, G., & Voituriez, R. (2012). Invasion fronts with variable motility: Phenotype selection, spatial sorting and wave acceleration. Comptes Rendus Mathematique, 350(15–16), 761–766.
Brockhurst, M. A., Colegrave, N., Hodgson, D. J., & Buckling, A. (2007). Niche occupation limits adaptive radiation in experimental microcosms. PLoS One, 2(2), e193.
Calabrese, S., Mohanty, B. P., & Malik, A. A. (2022). Soil microorganisms regulate extracellular enzyme production to maximize their growth rate. Biogeochemistry, 158(3), 303–312.
Chakrawal, A., Herrmann, A. M., Koestel, J., Jarsjö, J., Nunan, N., Kätterer, T., & Manzoni, S. (2020). Dynamic upscaling of decomposition kinetics for carbon cycling models. Geoscientific Model Development, 13(3), 1399–1429.
Chakrawal, A., Lindahl, B. D., & Manzoni, S. (2024). Modelling optimal ligninolytic activity during plant litter decomposition. The New Phytologist. https://doi.org/10.1111/nph.19572
Chase, A. B., Arevalo, P., Brodie, E. L., Polz, M. F., Karaoz, U., & Martiny, J. B. H. (2019). Maintenance of sympatric and allopatric populations in free‐living terrestrial bacteria. mBio, 10(5), e02361‐19. https://doi.org/10.1128/mBio.02361‐19
Chase, A. B., Gomez‐Lunar, Z., Lopez, A. E., Li, J., Allison, S. D., Martiny, A. C., & Martiny, J. B. H. (2018). Emergence of soil bacterial ecotypes along a climate gradient. Environmental Microbiology, 20(11), 4112–4126.
Chase, A. B., Karaoz, U., Brodie, E. L., Gomez‐Lunar, Z., Martiny, A. C., & Martiny, J. B. H. (2017). Microdiversity of an abundant terrestrial bacterium encompasses extensive variation in ecologically relevant traits. mBio, 8(6), e01809‐17. https://doi.org/10.1128/mBio.01809‐17
Chase, A. B., Weihe, C., & Martiny, J. B. H. (2021). Adaptive differentiation and rapid evolution of a soil bacterium along a climate gradient. Proceedings of the National Academy of Sciences of the United States of America, 118(18), 54118. https://doi.org/10.1073/pnas.2101254118
Chen, J., Zhang, Y., Kuzyakov, Y., Wang, D., & Olesen, J. E. (2023). Challenges in upscaling laboratory studies to ecosystems in soil microbiology research. Global Change Biology, 29(3), 569–574.
Choi, J., Yang, F., Stepanauskas, R., Cardenas, E., Garoutte, A., Williams, R., Flater, J., Tiedje, J. M., Hofmockel, K. S., Gelder, B., & Howe, A. (2017). Strategies to improve reference databases for soil microbiomes. The ISME Journal, 11(4), 829–834.
Cohan, F. M. (2006). Towards a conceptual and operational union of bacterial systematics, ecology, and evolution. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 361(1475), 1985–1996.
Crowther, T. W., van den Hoogen, J., Wan, J., Mayes, M. A., Keiser, A. D., Mo, L., Averill, C., & Maynard, D. S. (2019). The global soil community and its influence on biogeochemistry. Science, 365(6455), 550. https://doi.org/10.1126/science.aav0550
Cruz‐Paredes, C., Tájmel, D., & Rousk, J. (2023). Variation in temperature dependences across Europe reveals the climate sensitivity of soil microbial decomposers. Applied and Environmental Microbiology, 89(5), e0209022.
Day, T. (2005). Modelling the ecological context of evolutionary change: Déjà vu or something new? In K. Cuddington & B. E. Beisner (Eds.), Ecological paradigms lost: Routes of theory change (pp. 273–309). Academic Press.
Doolittle, W. F. (1999). Phylogenetic classification and the universal tree. Science, 284(5423), 2124–2129.
Dukovski, I., Bajić, D., Chacón, J. M., Quintin, M., Vila, J. C. C., Sulheim, S., Pacheco, A. R., Bernstein, D. B., Riehl, W. J., Korolev, K. S., Sanchez, A., Harcombe, W. R., & Segrè, D. (2021). A metabolic modeling platform for the computation of microbial ecosystems in time and space (COMETS). Nature Protocols, 16(11), 5030–5082.
Dutkiewicz, S., Follows, M. J., & Bragg, J. G. (2009). Modeling the coupling of ocean ecology and biogeochemistry. Global Biogeochemical Cycles, 23(4), 3405.
Falkowski, P. G., Fenchel, T., & Delong, E. F. (2008). The microbial engines that drive Earth's biogeochemical cycles. Science, 320(5879), 1034–1039.
Feist, A. M., & Palsson, B. O. (2010). The biomass objective function. Current Opinion in Microbiology, 13(3), 344–349.
Folse, H. J., 3rd, & Allison, S. D. (2012). Cooperation, competition, and coalitions in enzyme‐producing microbes: Social evolution and nutrient depolymerization rates. Frontiers in Microbiology, 3, 338.
Fraser, C., Alm, E. J., Polz, M. F., Spratt, B. G., & Hanage, W. P. (2009). The bacterial species challenge: Making sense of genetic and ecological diversity. Science, 323(5915), 741–746.
Geritz, S. A. H., Kisdi, É., Meszéna, G., & Metz, J. A. J. (1998). Evolutionarily singular strategies and the adaptive growth and branching of the evolutionary tree. Evolutionary Ecology, 12(1), 35–57. https://doi.org/10.1023/a:1006554906681
Glassman, S. I., Weihe, C., Li, J., Albright, M. B. N., Looby, C. I., Martiny, A. C., Treseder, K. K., Allison, S. D., & Martiny, J. B. H. (2018). Decomposition responses to climate depend on microbial community composition. Proceedings of the National Academy of Sciences of the United States of America, 115(47), 11994–11999.
Gophna, U., Charlebois, R. L., & Doolittle, W. F. (2004). Have archaeal genes contributed to bacterial virulence? Trends in Microbiology, 12(5), 213–219.
Grenfell, B. T., Wilson, K., Isham, V. S., Boyd, H. E., & Dietz, K. (1995). Modelling patterns of parasite aggregation in natural populations: Trichostrongylid nematode‐ruminant interactions as a case study. Parasitology, 111(Suppl), S135–S151.
Harrison, S. P., Cramer, W., Franklin, O., Prentice, I. C., Wang, H., Brännström, Å., de Boer, H., Dieckmann, U., Joshi, J., Keenan, T. F., Lavergne, A., Manzoni, S., Mengoli, G., Morfopoulos, C., Peñuelas, J., Pietsch, S., Rebel, K. T., Ryu, Y., Smith, N. G., … Wright, I. J. (2021). Eco‐evolutionary optimality as a means to improve vegetation and land‐surface models. The New Phytologist, 231(6), 2125–2141.
Henry, L. P., Bruijning, M., Forsberg, S. K. G., & Ayroles, J. F. (2021). The microbiome extends host evolutionary potential. Nature Communications, 12(1), 5141.
Hultman, J., Waldrop, M. P., Mackelprang, R., David, M. M., McFarland, J., Blazewicz, S. J., Harden, J., Turetsky, M. R., McGuire, A. D., Shah, M. B., VerBerkmoes, N. C., Lee, L. H., Mavrommatis, K., & Jansson, J. K. (2015). Multi‐omics of permafrost, active layer and thermokarst bog soil microbiomes. Nature, 521(7551), 208–212.
Iwasa, Y., Pomiankowski, A., & Nee, S. (1991). The evolution of costly mate preferences. II. The “handicap” principle. Evolution, 45(6), 1431–1442.
Jansson, J. K., & Baker, E. S. (2016). A multi‐omic future for microbiome studies. Nature Microbiology, 1, 16049.
Jing, W., Souganidis, P. E., & Tran, H. V. (2017). Stochastic homogenization of viscous superquadratic Hamilton–Jacobi equations in dynamic random environment. Publications of the Research Institute for Mathematical Sciences, 4(1), 6.
Kaiser, C., Franklin, O., Richter, A., & Dieckmann, U. (2015). Social dynamics within decomposer communities lead to nitrogen retention and organic matter build‐up in soils. Nature Communications, 6, 8960.
Kallenbach, C. M., Frey, S. D., & Grandy, A. S. (2016). Direct evidence for microbial‐derived soil organic matter formation and its ecophysiological controls. Nature Communications, 7, 13630.
Karaoz, U., & Brodie, E. L. (2022). microTrait: A toolset for a trait‐based representation of microbial genomes. Frontiers in Bioinformatics, 2, 918853.
Kattge, J., & Knorr, W. (2007). Temperature acclimation in a biochemical model of photosynthesis: A reanalysis of data from 36 species. Plant, Cell & Environment, 30(9), 1176–1190.
Kisdi, E., & Geritz, S. A. H. (2010). Adaptive dynamics: A framework to model evolution in the ecological theatre. Journal of Mathematical Biology, 61(1), 165–169.
Lässig, M., Mustonen, V., & Walczak, A. M. (2017). Predicting evolution. Nature Ecology & Evolution, 1(3), 77.
Lehmann, J., Hansel, C. M., Kaiser, C., Kleber, M., Maher, K., Manzoni, S., Nunan, N., Reichstein, M., Schimel, J. P., Torn, M. S., Wieder, W. R., & Kögel‐Knabner, I. (2020). Persistence of soil organic carbon caused by functional complexity. Nature Geoscience, 13(8), 529–534.
Leman, H., Meleard, S., & Mirrahimi, S. (2014). Influence of a spatial structure on the long time behavior of a competitive Lotka‐Volterra type system. arXiv [math.AP]. http://arxiv.org/abs/1401.1182
Levin, S. A. (1992). The problem of pattern and scale in ecology: The Robert H. Macarthur award lecture. Ecology, 73(6), 1943–1967.
Li, S., Xiao, J., Sun, T., Yu, F., Zhang, K., Feng, Y., Xu, C., Wang, B., & Cheng, L. (2022). Synthetic microbial consortia with programmable ecological interactions. Methods in Ecology and Evolution, 13(7), 1608–1621.
Lion, S. (2018). Theoretical approaches in evolutionary ecology: Environmental feedback as a unifying perspective. The American Naturalist, 191(1), 21–44.
Lion, S., Sasaki, A., & Boots, M. (2023). Extending eco‐evolutionary theory with oligomorphic dynamics. Ecology Letters, 26, S22–S46. https://doi.org/10.1111/ele.14183
Lombardozzi, D. L., Bonan, G. B., Smith, N. G., Dukes, J. S., & Fisher, R. A. (2015). Temperature acclimation of photosynthesis and respiration: A key uncertainty in the carbon cycle‐climate feedback. Geophysical Research Letters, 42(20), 8624–8631.
Loreau, M., Jarne, P., & Martiny, J. B. H. (2023). Opportunities to advance the synthesis of ecology and evolution. Ecology Letters, 26, S11–S15. https://doi.org/10.1111/ele.14175
Manzoni, S., Čapek, P., Mooshammer, M., Lindahl, B. D., Richter, A., & Šantrůčková, H. (2017). Optimal metabolic regulation along resource stoichiometry gradients. Ecology Letters, 20(9), 1182–1191.
Manzoni, S., Chakrawal, A., & Ledder, G. (2023). Decomposition rate as an emergent property of optimal microbial foraging. Frontiers in Ecology and Evolution, 11, 4269. https://doi.org/10.3389/fevo.2023.1094269
Martiny, J. B. H., Jones, S. E., Lennon, J. T., & Martiny, A. C. (2015). Microbiomes in light of traits: A phylogenetic perspective. Science, 350(6261), 9323. https://doi.org/10.1126/science.aac9323
Martiny, J. B. H., Martiny, A. C., Brodie, E., Chase, A. B., Rodríguez‐Verdugo, A., Treseder, K. K., & Allison, S. D. (2023). Investigating the eco‐evolutionary response of microbiomes to environmental change. Ecology Letters, 26, S81–S90. https://doi.org/10.1111/ele.14209
McDowell, N. G., Allen, C. D., Anderson‐Teixeira, K., Aukema, B. H., Bond‐Lamberty, B., Chini, L., Clark, J. S., Dietze, M., Grossiord, C., Hanbury‐Brown, A., Hurtt, G. C., Jackson, R. B., Johnson, D. J., Kueppers, L., Lichstein, J. W., Ogle, K., Poulter, B., Pugh, T. A. M., Seidl, R., … Xu, C. (2020). Pervasive shifts in forest dynamics in a changing world. Science, 368(6494), 9463. https://doi.org/10.1126/science.aaz9463
Melillo, J. M., Frey, S. D., DeAngelis, K. M., Werner, W. J., Bernard, M. J., Bowles, F. P., Pold, G., Knorr, M. A., & Grandy, A. S. (2017). Long‐term pattern and magnitude of soil carbon feedback to the climate system in a warming world. Science, 358(6359), 101–105.
Polz, M. F., Alm, E. J., & Hanage, W. P. (2013). Horizontal gene transfer and the evolution of bacterial and archaeal population structure. Trends in Genetics: TIG, 29(3), 170–175.
Rodríguez‐Verdugo, A. (2021). Evolving interactions and emergent functions in microbial consortia. mSystems, 6(4), e0077421.
Rodríguez‐Verdugo, A., & Ackermann, M. (2021). Rapid evolution destabilizes species interactions in a fluctuating environment. The ISME Journal, 15(2), 450–460.
Romero‐Olivares, A. L., Taylor, J. W., & Treseder, K. K. (2015). Neurospora discreta as a model to assess adaptation of soil fungi to warming. BMC Evolutionary Biology, 15, 198.
Rosselló‐Mora, R., & Amann, R. (2001). The species concept for prokaryotes. FEMS Microbiology Reviews, 25(1), 39–67.
Scales, N. C., Chase, A. B., Finks, S. S., Malik, A. A., Weihe, C., Allison, S. D., Martiny, A. C., & Martiny, J. B. H. (2022). Differential response of bacterial microdiversity to simulated global change. Applied and Environmental Microbiology, 88(6), e0242921.
Shapiro, B. J., Friedman, J., Cordero, O. X., Preheim, S. P., Timberlake, S. C., Szabó, G., Polz, M. F., & Alm, E. J. (2012). Population genomics of early events in the ecological differentiation of bacteria. Science, 336(6077), 48–51.
Shen, S., & Clairambault, J. (2020). Cell plasticity in cancer cell populations. F1000Research, 9, 635. https://doi.org/10.12688/f1000research.24803.1
Slatkin, M. (1980). Ecological character displacement. Ecology, 61, 163–177. https://doi.org/10.2307/1937166
Strickland, M. S., Keiser, A. D., & Bradford, M. A. (2015). Climate history shapes contemporary leaf litter decomposition. Biogeochemistry, 122(2), 165–174.
Stuart Chapin, F., III, McFarland, J., David McGuire, A., Euskirchen, E. S., Ruess, R. W., & Kielland, K. (2009). The changing global carbon cycle: Linking plant‐soil carbon dynamics to global consequences. The Journal of Ecology, 97(5), 840–850.
Stump, S. M., Johnson, E. C., & Klausmeier, C. A. (2018). Local interactions and self‐organized spatial patterns stabilize microbial cross‐feeding against cheaters. Journal of the Royal Society, Interface, 15(140), 20170822. https://doi.org/10.1098/rsif.2017.0822
Sulman, B. N., Phillips, R. P., Christopher Oishi, A., Shevliakova, E., & Pacala, S. W. (2014). Microbe‐driven turnover offsets mineral‐mediated storage of soil carbon under elevated CO2. Nature Climate Change, 4(12), 1099–1102. https://doi.org/10.1038/nclimate2436
Tang, J., & Riley, W. J. (2014). Weaker soil carbon–climate feedbacks resulting from microbial and abiotic interactions. Nature Climate Change, 5(1), 56–60.
Terrer, C., Phillips, R. P., Hungate, B. A., Rosende, J., Pett‐Ridge, J., Craig, M. E., van Groenigen, K. J., Keenan, T. F., Sulman, B. N., Stocker, B. D., Reich, P. B., Pellegrini, A. F. A., Pendall, E., Zhang, H., Evans, R. D., Carrillo, Y., Fisher, J. B., Van Sundert, K., Vicca, S., & Jackson, R. B. (2021). A trade‐off between plant and soil carbon storage under elevated CO2. Nature, 591(7851), 599–603.
Travisano, M., & Lenski, R. E. (1996). Long‐term experimental evolution in Escherichia coli. IV. Targets of selection and the specificity of adaptation. Genetics, 143(1), 15–26.
Turelli, M., & Barton, N. H. (1990). Dynamics of polygenic characters under selection. Theoretical Population Biology, 38(1), 1–57.
Urban, M. C., Strauss, S. Y., Pelletier, F., Palkovacs, E. P., Leibold, M. A., Hendry, A. P., De Meester, L., Carlson, S. M., Angert, A. L., & Giery, S. T. (2020). Evolutionary origins for ecological patterns in space. Proceedings of the National Academy of Sciences of the United States of America, 117(30), 17482–17490.
Wang, B., & Allison, S. D. (2019). Emergent properties of organic matter decomposition by soil enzymes. Soil Biology & Biochemistry, 136, 107522.
Wang, C., Qu, L., Yang, L., Liu, D., Morrissey, E., Miao, R., Liu, Z., Wang, Q., Fang, Y., & Bai, E. (2021). Large‐scale importance of microbial carbon use efficiency and necromass to soil organic carbon. Global Change Biology, 27(10), 2039–2048.
Wieder, W. R., Grandy, A. S., Kallenbach, C. M., & Bonan, G. B. (2014). Integrating microbial physiology and physio‐chemical principles in soils with the MIcrobial‐MIneral Carbon Stabilization (MIMICS) model. Biogeosciences, 11(14), 3899–3917. https://doi.org/10.5194/bg‐11‐3899‐2014
Wieder, W. R., Grandy, A. S., Kallenbach, C. M., Taylor, P. G., & Bonan, G. B. (2015). Representing life in the Earth system with soil microbial functional traits in the MIMICS model. Geoscientific Model Development Discussions, 8(2), 2011–2052.
Wielgoss, S., Barrick, J. E., Tenaillon, O., Wiser, M. J., Dittmar, W. J., Cruveiller, S., Chane‐Woon‐Ming, B., Médigue, C., Lenski, R. E., & Schneider, D. (2013). Mutation rate dynamics in a bacterial population reflect tension between adaptation and genetic load. Proceedings of the National Academy of Sciences of the United States of America, 110(1), 222–227.
Williams, M., Rastetter, E. B., Fernandes, D. N., Goulden, M. L., Shaver, G. R., & Johnson, L. C. (1997). Predicting gross primary productivity in terrestrial ecosystems. Ecological Applications, 7(3), 882–894.
Woolf, D., & Lehmann, J. (2019). Microbial models with minimal mineral protection can explain long‐term soil organic carbon persistence. Scientific Reports, 9(1), 6522.
Ye, J.‐S., Bradford, M. A., Dacal, M., Maestre, F. T., & García‐Palacios, P. (2019). Increasing microbial carbon use efficiency with warming predicts soil heterotrophic respiration globally. Global Change Biology, 25(10), 3354–3364.
Yoshida, T., Jones, L. E., Ellner, S. P., Fussmann, G. F., & Hairston, N. G. (2003). Rapid evolution drives ecological dynamics in a predator–prey system. Nature, 424(6946), 303–306.
Young, I. M., & Crawford, J. W. (2004). Interactions and self‐organization in the soil‐microbe complex. Science, 304(5677), 1634–1637.