Philippa Kaur

Lander, E. A. A colonialidade do saber: eurocentrismo e ciencias sociais. Perspectivas latino-americanas (CLACSO, 2005).Césaire, A. Guaraguao 20, 157–193 (2005).
Google Scholar 
Fanon, F. Black Skin, White Masks (Pluto, 1986).Mbembe, A. Arts Humanit. High. Educ. 15, 29–45 (2016).Article 

Google Scholar 
Rivera Cusicanqui, S. Ch’ixinakax utxiwa: una reflexión sobre prácticas y discursosdescolonizadores (Tinta Limón, 2010).Castro-Gómez, S. & Grosfoguel, R. El Giro Decolonial (Siglo del hombre, 2007).Grosfoguel, R. Rev. (Fernand Braudel Center) 25, 203–224 (2002).
Google Scholar 
Quijano, A. Int. Sociol. 15, 215–232 (2000).Article 

Google Scholar 
Visvanathan, S. in Science and Citizens: Globalization and the Challenge of Engagement (eds Leach, M. et al.) 83–97 (Zed Books, 2005).Spivak, G. C. Can the Subaltern Speak? (Routledge, 1994).Bhargava, R. Glob. Policy 4, 413–417 (2013).Article 

Google Scholar 
Bhambra, G. K. Crit. Times 4, 73–89 (2021).Article 

Google Scholar 
Sousa Santos, B. Rev. (Fernand Braudel Center) 30, 45–89 (2007).
Google Scholar 
Maas, B. et al. Conserv. Lett. 14, e12797 (2021).Article 

Google Scholar 
Nuñez, M. A. et al. J. Appl. Ecol. 56, 4–9 (2019).Article 

Google Scholar 
Mohammed, R. S. et al. Am. Nat. 200, 140–155 (2022).Article 

Google Scholar 
Rau, J. et al. Ecol. Austral 27, 312–496 (2017).Article 

Google Scholar 
Raja, N. B. et al. Nat. Ecol. Evol. 6, 145–154 (2022).Article 

Google Scholar 
Trisos, C. H., Auerbach, J. & Katti, M. Nat. Ecol. Evol. 6, 1205–1212 (2021).Article 

Google Scholar 
Eichhorn, M. P., Baker, K. & Griffiths, M. Front. Biogeogr. 12, 1–7 (2020).
Google Scholar 
Baker, K., Eichhorn, M. P. & Griffiths, M. Biotropica 51, 288–292 (2019).Article 

Google Scholar 
Brandt, S. et al. Ecol. Evol. 10, 12450–12456 (2020).Article 

Google Scholar 
McGill, B. M. et al. Ecol. Evol. 11, 3636–3645 (2021).Article 

Google Scholar 
Melles, S. J. et al. Ecoscience 26, 323–340 (2019).Article 

Google Scholar 
Adebisi, F. Decolonisation is not about ticking a box: it must disrupt. criticallegalthinking.com, https://criticallegalthinking.com/2020/03/12/decolonisation-is-not-about-ticking-a-box/ (12 March 2020).Güttler, N. Ber. Wiss. 42, 235–258 (2019).
Google Scholar 
Worster, D. J. Nature’s Economy: A History of Ecological Ideas, 2nd edn (Cambridge Univ. Press, 1994).Nicolson, M. Hist. Sci. 26, 183–200 (1988).Article 

Google Scholar 
Lewinsohn, T. M. Filos. História Biol. 11, 347–381 (2016).
Google Scholar 
Raby, M. The Study of Ecology in Latin America and the Caribbean (Oxford Univ Press, 2021).Mignolo, W. D. Coloniality at Large: Time and the Colonial Difference (Taylor & Francis, 2020).Simpson, D. Y., Beatty, A. E. & Ballen, C. J. Trends Ecol. Evol. 36, 4–8 (2021).Article 

Google Scholar 
Smith, L. T. Decolonizing Methodologies: Research and Indigenous Peoples (Zed Books, 2013).Grosfoguel, R. Tabula Rasa 24, 123–143 (2016). More

Dudgeon, D. Multiple threats imperil freshwater biodiversity in the Anthropocene. Curr. Biol. 29, R942–R995 (2019).Article 

Google Scholar 
Betts, M. G. et al. Global forest loss disproportionately erodes biodiversity in intact landscapes. Nature 547, 441–444 (2017).Article 
CAS 

Google Scholar 
Arrigo, K. R. et al. Synergistic interactions among growing stressors increase risk to an Arctic ecosystem. Nat. Commun. 11, 6255 (2020).Article 
CAS 

Google Scholar 
Kopf, R. K., Finlayson, C. M., Humphries, P., Sims, N. C. & Hladyz, S. Anthropocene baselines: assessing change and managing biodiversity in human-dominated aquatic ecosystems. Bioscience 65, 798–811 (2015).Article 

Google Scholar 
Chapin, F. S. et al. Ecosystem stewardship: sustainability strategies for a rapidly changing planet. Trends Ecol. Evol. 25, 241–249 (2010).Article 

Google Scholar 
Seastedt, T. R., Hobbs, R. J. & Suding, K. N. Management of novel ecosystems: are novel approaches required? Front. Ecol. Environ. 6, 547–553 (2008).Article 

Google Scholar 
Hughes, T. P. et al. Coral reefs in the Anthropocene. Nature 546, 82–90 (2017).Article 
CAS 

Google Scholar 
Bellwood, D. R. et al. Coral reef conservation in the Anthropocene: confronting spatial mismatches and prioritizing functions. Biol. Conserv. 236, 604–615 (2019).Article 

Google Scholar 
Graham, N. A. J., Cinner, J. E., Norström, A. V. & Nyström, M. Coral reefs as novel ecosystems: embracing new futures. Curr. Opin. Environ. Sustain. 7, 9–14 (2014).Article 

Google Scholar 
Hughes, T. P. et al. Spatial and temporal patterns of mass bleaching of corals in the Anthropocene. Science 359, 80–83 (2018).Article 
CAS 

Google Scholar 
Sully, S., Burkepile, D. E., Donovan, M. K., Hodgson, G. & van Woesik, R. A global analysis of coral bleaching over the past two decades. Nat. Commun. 10, 1264 (2019).Article 
CAS 

Google Scholar 
Fisher, R. et al. Species richness on coral reefs and the pursuit of convergent global estimates. Curr. Biol. 25, 500–505 (2015).Article 
CAS 

Google Scholar 
Brandl, S. J. et al. Coral reef ecosystem functioning: eight core processes and the role of biodiversity. Front. Ecol. Environ. 17, 445–454 (2019).Article 

Google Scholar 
Teh, L. S. L., Teh, L. C. L. & Sumaila, U. R. A global estimate of the number of coral reef fishers. PLoS ONE 8, e65397 (2013).Article 
CAS 

Google Scholar 
Ferrario, F. et al. The effectiveness of coral reefs for coastal hazard risk reduction and adaptation. Nat. Commun. 5, 3794 (2014).Article 
CAS 

Google Scholar 
Skirving, W. J. et al. The relentless march of mass coral bleaching: a global perspective of changing heat stress. Coral Reefs 38, 547–557 (2019).Article 

Google Scholar 
Donovan, M. K. et al. Local conditions magnify coral loss after marine heatwaves. Science 372, 977–980 (2021).Article 
CAS 

Google Scholar 
Gilmour, J. P., Smith, L. D., Heyward, A. J., Baird, A. H. & Pratchett, M. S. Recovery of an isolated coral reef system following severe disturbance. Science 340, 69–71 (2013).Article 

Google Scholar 
Diaz-Pulido, G. & McCook, L. J. The fate of bleached corals: patterns and dynamics of algal recruitment. Mar. Ecol. Prog. Ser. 232, 115–128 (2002).Article 

Google Scholar 
Bellwood, D. R., Hughes, T. P., Folke, C. & Nyström, M. Confronting the coral reef crisis. Nature 429, 827–833 (2004).Article 
CAS 

Google Scholar 
Jouffray, J. B. et al. Parsing human and biophysical drivers of coral reef regimes. Proc. R. Soc. B Biol. Sci. 286, 20182544 (2019).Article 

Google Scholar 
Reverter, M., Helber, S. B., Rohde, S., Goeij, J. M. & Schupp, P. J. Coral reef benthic community changes in the Anthropocene: biogeographic heterogeneity, overlooked configurations, and methodology. Glob. Chang. Biol. 28, 1956–1971 (2022).Article 

Google Scholar 
Cheal, A. J., MacNeil, M. A., Emslie, M. J. & Sweatman, H. The threat to coral reefs from more intense cyclones under climate change. Glob. Chang. Biol. 23, 1511–1524 (2017).Article 

Google Scholar 
Done, T. in Perspectives on Coral Reefs (ed. Barnes, D. J.) 107–147 (Brian Clouston, 1983).Bruno, J. F., Côté, I. M. & Toth, L. T. Climate change, coral loss, and the curious case of the parrotfish paradigm: why don’t marine protected areas improve reef resilience? Ann. Rev. Mar. Sci. 11, 307–334 (2019).Article 

Google Scholar 
Gardner, T. A., Cote, I. M., Gill, J. A., Grant, A. & Watkinson, A. R. Long-term region-wide declines in Caribbean corals. Science 301, 958–960 (2003).Article 
CAS 

Google Scholar 
Schutte, V. G. W., Selig, E. R. & Bruno, J. F. Regional spatio-temporal trends in Caribbean coral reef benthic communities. Mar. Ecol. Prog. Ser. 402, 115–122 (2010).Article 

Google Scholar 
Hughes, T. P. Catastrophes, phase shifts and large-scale degradation of a Caribbean coral reef. Science 265, 1547–1551 (1994).Article 
CAS 

Google Scholar 
Souter, D. et al. Status of Coral Reefs of the World: 2020 (Global Coral Reef Monitoring Network, 2021).Bruno, J. F. & Selig, E. R. Regional decline of coral cover in the Indo-Pacific: timing, extent, and subregional comparisons. PLoS One 2, e711 (2007).Article 

Google Scholar 
Ateweberhan, M., McClanahan, T. R., Graham, N. A. J. & Sheppard, C. R. C. Episodic heterogeneous decline and recovery of coral cover in the Indian Ocean. Coral Reefs 30, 739–752 (2011).Article 

Google Scholar 
Bellwood, D. R., Hemingson, C. R. & Tebbett, S. B. Subconscious biases in coral reef fish studies. Bioscience 70, 621–627 (2020).Article 

Google Scholar 
Kench, P. S. et al. Sustained coral reef growth in the critical wave dissipation zone of a Maldivian atoll. Commun. Earth Environ. 3, 9 (2022).Article 

Google Scholar 
Eddy, T. D. et al. Global decline in capacity of coral reefs to provide ecosystem services. One Earth 4, 1278–1285 (2021).Article 

Google Scholar 
Mumby, P. J., Hastings, A. & Edwards, H. J. Thresholds and the resilience of Caribbean coral reefs. Nature 450, 98–101 (2007).Article 
CAS 

Google Scholar 
Roff, G. & Mumby, P. J. Global disparity in the resilience of coral reefs. Trends Ecol. Evol. 27, 404–413 (2012).Article 

Google Scholar 
Bruno, J. F., Sweatman, H., Precht, W. F., Selig, E. R. & Schutte, V. G. W. Assessing evidence of phase shifts from coral to macroalgal dominance on coral reefs. Ecology 90, 1478–1484 (2009).Article 

Google Scholar 
Renema, W. et al. Hopping hotspots: global shifts in marine biodiversity. Science 321, 654–657 (2008).Article 
CAS 

Google Scholar 
Bellwood, D. R., Goatley, C. H. R. & Bellwood, O. The evolution of fishes and corals on reefs: form, function and interdependence. Biol. Rev. 92, 878–901 (2017).Article 

Google Scholar 
Roff, G. Evolutionary history drives biogeographic patterns of coral reef resilience. Bioscience 71, 26–39 (2021).
Google Scholar 
Siqueira, A. C., Bellwood, D. R. & Cowman, P. F. The evolution of traits and functions in herbivorous coral reef fishes through space and time. Proc. R. Soc. B Biol. Sci. 286, 20182672 (2019).Article 

Google Scholar 
Birrell, C. L., McCook, L. J., Willis, B. L. & Diaz-Pulido, G. A. Effects of benthic algae on the replenishment of corals and the implications for the resilience of coral reefs. Oceanogr. Mar. Biol. Annu. Rev. 46, 25–63 (2008).
Google Scholar 
Speare, K. E., Duran, A., Miller, M. W. & Burkepile, D. E. Sediment associated with algal turfs inhibits the settlement of two endangered coral species. Mar. Pollut. Bull. 144, 189–195 (2019).Article 
CAS 

Google Scholar 
Diaz-Pulido, G., Harii, S., McCook, L. J. & Hoegh-Guldberg, O. The impact of benthic algae on the settlement of a reef-building coral. Coral Reefs 29, 203–208 (2010).Article 

Google Scholar 
Johns, K. A. et al. Macroalgal feedbacks and substrate properties maintain a coral reef regime shift. Ecosphere 9, e02349 (2018).Article 

Google Scholar 
Houk, P. et al. Commercial coral-reef fisheries across Micronesia: a need for improving management. Coral Reefs 31, 13–26 (2012).Article 

Google Scholar 
Edwards, C. B. et al. Global assessment of the status of coral reef herbivorous fishes: evidence for fishing effects. Proc. R. Soc. B Biol. Sci. 281, 20131835 (2014).Article 
CAS 

Google Scholar 
Choat, J. H. & Clements, K. D. Vertebrate herbivores in marine and terrestrial environments: a nutritional ecology perspective. Annu. Rev. Ecol. Syst. 29, 375–403 (1998).Article 

Google Scholar 
Tebbett, S. B., Morais, R. A., Goatley, C. H. R. & Bellwood, D. R. Collapsing ecosystem functions on an inshore coral reef. J. Environ. Manag. 289, 112471 (2021).Article 

Google Scholar 
Cornwall, C. E. et al. Global declines in coral reef calcium carbonate production under ocean acidification and warming. Proc. Natl Acad. Sci. USA. 118, e2015265118 (2021).Article 
CAS 

Google Scholar 
Diaz-Pulido, G. et al. Greenhouse conditions induce mineralogical changes and dolomite accumulation in coralline algae on tropical reefs. Nat. Commun. 5, 3310 (2014).Article 

Google Scholar 
Nash, M. C. et al. Dolomite-rich coralline algae in reefs resist dissolution in acidified conditions. Nat. Clim. Chang. 3, 268–272 (2013).Article 
CAS 

Google Scholar 
Lyons, M., Larsen K. & Skone, M. Allen Coral Atlas. Imagery, maps and monitoring of the world’s tropical coral reefs. Zenodo https://doi.org/10.5281/zenodo.3833242 (2020).Tebbett, S. B. & Bellwood, D. R. Algal turf sediments on coral reefs: what’s known and what’s next. Mar. Pollut. Bull. 149, 110542 (2019).Article 
CAS 

Google Scholar 
Nugues, M. M. & Bak, R. P. M. Long-term dynamics of the brown macroalga Lobophora variegata on deep reefs in Curaçao. Coral Reefs 27, 389–393 (2008).Article 

Google Scholar 
Tsounis, G. & Edmunds, P. J. Three decades of coral reef community dynamics in St. John, USVI: a contrast of scleractinians and octocorals. Ecosphere 8, e01646 (2017).Article 

Google Scholar 
Toth, L. T. et al. Do no-take reserves benefit Florida’s corals? 14 years of change and stasis in the Florida Keys National Marine Sanctuary. Coral Reefs 33, 565–577 (2014).Article 

Google Scholar 
Smith, J. E. et al. Re-evaluating the health of coral reef communities: baselines and evidence for human impacts across the central Pacific. Proc. R. Soc. B Biol. Sci. 283, 20151985 (2016).Article 

Google Scholar 
Wolfe, K., Kenyon, T. M. & Mumby, P. J. The biology and ecology of coral rubble and implications for the future of coral reefs. Coral Reefs 40, 1769–1806 (2021).Article 

Google Scholar 
Harris, J. L., Lewis, L. S. & Smith, J. E. Quantifying scales of spatial variability in algal turf assemblages on coral reefs. Mar. Ecol. Prog. Ser. 532, 41–57 (2015).Article 

Google Scholar 
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G. & Group, T. P. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 6, e1000097 (2009).Article 

Google Scholar 
Crisp, S. K., Tebbett, S. B. & Bellwood, D. R. A critical evaluation of benthic phase shift studies on coral reefs. Mar. Environ. Res. 178, 105667 (2022).Article 
CAS 

Google Scholar 
WebPlotDigitizer v. 4.3 (A. Rohatgi, 2020); https://automeris.io/WebPlotDigitizerKulbicki, M. et al. Global biogeography of reef fishes: a hierarchical quantitative delineation of regions. PLoS ONE 8, e81847 (2013).Article 

Google Scholar 
Spalding, M. D. et al. Marine ecoregions of the world: a bioregionalization of coastal and shelf areas. Bioscience 57, 573–583 (2007).Article 

Google Scholar 
R Core Team: R: A Language and Environment for Statistical Computing. (R Foundation for Statistical Computing, 2020).Zychaluk, K., Bruno, J. F., Clancy, D., McClanahan, T. R. & Spencer, M. Data-driven models for regional coral-reef dynamics. Ecol. Lett. 15, 151–158 (2012).Article 

Google Scholar 
Dudgeon, S. R., Aronson, R. B., Bruno, J. F. & Precht, W. F. Phase shifts and stable states on coral reefs. Mar. Ecol. Prog. Ser. 413, 201–216 (2010).Article 

Google Scholar 
Jost, L., Chao, A. & Chazdon, R. L. in Biological Diversity: Frontiers in Measurement and Assessment (eds Magurran, A. E. & McGill, B. J.) 66–84 (Oxford Univ. Press, 2011).Oksanen, J. F. et al. Vegan: Community ecology package. R package version 2.5-6 (2019).Calenge, C. The package “adehabitat” for the R software: a tool for the analysis of space and habitat use by animals. Ecol. Modell. 197, 516–519 (2006).Article 

Google Scholar 
Worton, B. J. Kernel methods for estimating the utilization distribution in home‐range studies. Ecology 70, 164–168 (1989).Article 

Google Scholar 
Blonder, B. Hypervolume concepts in niche- and trait-based ecology. Ecography 41, 1441–1455 (2018).Article 

Google Scholar 
Wood, S. N. Generalized Additive Models: an Introduction with R 2nd edn (Chapman & Hall/CRC, 2017).Gräler, B., Pebesma, E. & Heuvelink, G. Spatio-temporal interpolation using gstat. R. J. 8, 204–218 (2016).Article 

Google Scholar 
Hartig, F. DHARMa: Residual diagnostics for hierarchical (multi-level/mixed) regression models. R package version 0.3.3.0 (2020).Lenth, R. emmeans: Estimated marginal means, aka least-squares means. R package version 1.5.1 (2020).Wickham, H. et al. tidyverse: easily install and load the ‘tidyverse’. J. Open Source Softw. 4, 1686 (2019).Article 

Google Scholar 
Pebesma, E. Simple features for R: standardized support for spatial vector data. R. J. 10, 439–446 (2018).Article 

Google Scholar 
South, A. rnaturalearth: World map data from natural earth. R package version 0.1.0 (2017).Hamilton, N. E. & Ferry, M. ggtern: ternary diagrams using ggplot2. J. Stat. Softw., Code Snippets 87, 1–17 (2018).
Google Scholar 
Pedersen, T. L. patchwork: The composer of plots. R package version 1.1.1 (2020). More

Samples collection and preparationFreshwater and sediment samples were collected from 5 irrigation drains (EL-Shikah, EL- Tramsa, EL-Mahrosa, EL-Aslia, and EL-Rawy) located in the geographical area of Qena city, the capital of Qena Governorate, 600 km south of Cairo, (Figs. 1 and 2). 3 sites inside each drain were randomly selected as sampling site; one of these sites represents the outlet of the drain into the Nile River. In addition, one site facing each drain in the main stream of the Nile River was selected to collect freshwater only, thus the total number of samples are 20 freshwater and 15 sediment samples.Figure 1Location map of the area under study (ArcGIS software 10.8.1; ArcGIS Online).Full size imageFigure 2Irrigation drain under study.Full size imagePolyethylene Marinelli beakers with a capacity of 1.4 L are used as collection and measuring containers. The beakers were washed with dilute hydrochloric acid and distilled water before use, filled to brim, and then pressed the tight lid to eliminate the internal air. Drops of HNO3 were added to the samples to prevent the adhesive of radionuclides with bottle walls8.Sediment samples were collected by Ekman grab sediment sampler. The collected samples were dried using electrical oven at a temperature of 105℃ for 24 h, then sieved through 200 mesh size. The dried samples were filled in hermetical sealed 500 ml polyethylene beakers. The prepared water and sediment samples were stored for 4 weeks to reach a secular equilibrium of radium and thorium with their progenies9.Measuring systemsGamma-ray spectrometer consisting of ″3 × 3″ NaI (Tl) detector enclosed in 5 cm thick cylindrical lead shield to reduce the background radiation and connected with 1024 multichannel analyzer was used. The spectrometer was calibrated for energy using 60Co and 137Cs standard point sources, and calibrated for efficiency using a multi-nuclides standard solution which covers a wide range of energy10. The spectrum was accumulated from each sample over 24 h and analyzed by Maestro software. The background was measured under the same condition of sample measurement.226Ra was determined using 214Bi and 214Pb gamma-lines at 609 keV and 352 keV, respectively, while 232Th from gamma-lines of 228Ac (911 keV) and 212Pb (238 keV). 40K was determined from its single gamma-line at 1460 keV. The activity concentration was calculated using the following formula (Eq. 1)11.$$A = frac{{C_{n} }}{{T times varepsilon { } times {text{P}} times {text{V }}left( {{text{or}}} right){text{M}}}}$$
(1)

where A is the activity concentration (Bq kg−1) or (Bq l−1), Cn is the net counts under a given peak area, T the sample counting time, (varepsilon) is the detection efficiency at measured energy, P is the emission probability and V is the sample volume in liter, M is the sample mass in kilogram. Minimum detectable activity (MDA) was estimated according to Currie definition using Eq. 212 and the MDA values were 0.031, 0.035 and 1.94 Bq L−1 for 226Ra, 232Th, and 40K, respectively.$${text{MDA}} = frac{2.71 + 465sqrt B }{{T times varepsilon times P times V}}$$
(2)

where B is the background counts under a given peak area,T,ɛ, P, and V are defined above.Doses for aquatic organismsThe external and internal absorbed dose rate for aquatic organisms (Phytoplankton, Mollusca, and Crustacean) in the studied irrigation drains was calculated based on the measured activity concentrations of 226Ra, 232Th, and 40K in environmental media (water and sediment) and using dose conversion coefficients of a given radionuclide for the reference organisms according to the method outlined by Brown et al. described below13,14.$$begin{aligned}& left( {Sediment,, conc. ,,wet} right)_{radionuclide} = (Sediment ,,conc. ,,dry)_{radionuclide} times left( {solids ,,fraction} right) \& qquad qquad + (water ,,conc.)_{radionuclide} times (1 – left( {solids ,,fraction} right). \ end{aligned}$$
(3)
$$begin{aligned}& left( {user2{External ,,dose ,,rate}} right)_{radionuclide,, organism} = DPUC_{radionuclide, ,organism}^{external} times left[ {Sediment ,conc. ,wet_{radionuclide} times left( {fsed_{organism} + fsedsur_{organism} /2} right)} right. \& quad quad left. { + left( {fwater_{organism} + fsedsur_{organism} /2} right) times water ,conc._{radionuclide } /1000} right] \ end{aligned}$$
(4)
$$left( {user2{Internal,dose,rate}} right)_{{radionuclide,,organism}} = ~left( {water,conc.} right)_{{radionuclide}} times CF_{{radionuclide}}^{{organism}} times DPUC_{{radionuclide,,organism}}^{{internal}}$$
(5)

where sediment conc. is the sediment activity concentration of a given radionuclide in Bq kg−1,water conc. is the water activity concentration of a given radionuclide in Bq m−3, CF is distribution coefficient factors for given radionuclide in freshwater sediment in m3 kg−1, DPUC is the dose rate per unit concentration coefficients (fresh weight) in μGy h−1 per Bq kg−1 weighted for radiation type (alpha = 10, low energy beta = 3, and high energy beta and gamma = 1), solids fraction of wet sediment (0.4), fsed organism is the time fraction spends by organism in sediment, fsedsur organism is the time fraction spends by organism at the sediment/water interface, fwater organism is the time fraction spends by organism in the water column. All parameters used in calculation are taken from Pröhl (2003)15 and Vives i Battle et al. (2004)16. The total dose is then calculated by summating the external and internal doses. More

Biomass yield and WUEBiomass increased with precipitation, as expected and reported in Lee3. There was less water uptake in intercropping compared to sole oat and pea. In general, intercropping represented the median of the two sole cropping treatments, where oat had the highest biomass and WUE while pea had the lowest, and where pea had the highest mineral content and oat had the lowest3. Intercropping resulted in advantages in forage yield stability and was not associated with changes to the AMF community.Alpha diversityWe found differences in AMF species richness estimates in the roots across treatment combinations (i.e., intercropping systems × N fertilizer rate) in 2019 (Chao1, p  More

Griggs, D. et al. Sustainable development goals for people and planet. Nature 495, 305–307 (2013).Article 
CAS 

Google Scholar 
Charlop-Powers, Z. et al. Urban park soil microbiomes are a rich reservoir of natural product biosynthetic diversity. Proc. Natl Acad. Sci. USA 113, 14811 (2016).Article 
CAS 

Google Scholar 
Delgado-Baquerizo, M. et al. Global homogenization of the structure and function in the soil microbiome of urban greenspaces. Sci. Adv. 7, eabg5809 (2021).Article 
CAS 

Google Scholar 
Martínez, J. L. Antibiotics and antibiotic resistance genes in natural environments. Science 321, 365–367 (2008).Article 

Google Scholar 
Forsberg, K. J. et al. The shared antibiotic resistome of soil bacteria and human pathogens. Science 337, 1107–1111 (2012).Article 
CAS 

Google Scholar 
Byrnes, J. E. K. et al. Investigating the relationship between biodiversity and ecosystem multifunctionality: challenges and solutions. Methods Ecol. Evolution 5, 111–124 (2014).Article 

Google Scholar 
Gamfeldt, L. & Roger, F. Revisiting the biodiversity–ecosystem multifunctionality relationship. Nat. Ecol. Evolution 1, 0168 (2017).Article 

Google Scholar 
Lefcheck, J. S. et al. Biodiversity enhances ecosystem multifunctionality across trophic levels and habitats. Nat. Commun. 6, 6936 (2015).Article 
CAS 

Google Scholar 
Zavaleta, E. S. et al. Sustaining multiple ecosystem functions in grassland communities requires higher biodiversity. Proc. Natl Acad. Sci. USA 107, 1443 (2010).Article 
CAS 

Google Scholar 
Delgado-Baquerizo, M. et al. Microbial diversity drives multifunctionality in terrestrial ecosystems. Nat. Commun. 7, 10541 (2016).Article 
CAS 

Google Scholar 
Wagg, C. et al. Soil biodiversity and soil community composition determine ecosystem multifunctionality. Proc. Natl Acad. Sci. USA 111, 5266 (2014).Article 
CAS 

Google Scholar 
van der Heijden, M. G. A. et al. Mycorrhizal fungal diversity determines plant biodiversity, ecosystem variability and productivity. Nature 396, 69–72 (1998).Article 

Google Scholar 
Delgado-Baquerizo, M. et al. Multiple elements of soil biodiversity drive ecosystem functions across biomes. Nat. Ecol. Evol. 4, 210–220 (2020).Article 

Google Scholar 
Ramirez, K. S. et al. Biogeographic patterns in below-ground diversity in New York City’s Central Park are similar to those observed globally. Proc. R. Soc. B 281, 20141988 (2014).Article 

Google Scholar 
Schittko, C. et al. Biodiversity maintains soil multifunctionality and soil organic carbon in novel urban ecosystems. J. Ecol. https://doi.org/10.1111/1365-2745.13852 (2022).Maestre, F. T. et al. Plant species richness and ecosystem multifunctionality in global drylands. Science 335, 214–218 (2012).Article 
CAS 

Google Scholar 
Jing, X. et al. The links between ecosystem multifunctionality and above-and belowground biodiversity are mediated by climate. Nat. Commun. 6, 1–8 (2015).Article 

Google Scholar 
Kadowaki, K. et al. Mycorrhizal fungi mediate the direction and strength of plant–soil feedbacks differently between arbuscular mycorrhizal and ectomycorrhizal communities. Commun. Biol. 1, 196 (2018).Article 

Google Scholar 
Soliveres, S. et al. Biodiversity at multiple trophic levels is needed for ecosystem multifunctionality. Nature 536, 456–459 (2016).Article 
CAS 

Google Scholar 
Berman, J. J. in Taxonomic Guide to Infectious Diseases (ed. Berman, J. J.) 37–47 (Academic Press, 2012).Berman, J. J. in Taxonomic Guide to Infectious Diseases (ed. Berman, J. J.) 25–31 (Academic Press, 2012).Busse, H.-J. in Methods in Microbiology (eds Rainey, F. & Oren. A.) Vol. 38, 239–259 (Academic Press, 2011).van den Hoogen, J. et al. Soil nematode abundance and functional group composition at a global scale. Nature 572, 194–198 (2019).Article 

Google Scholar 
van Bergeijk, D. A. et al. Ecology and genomics of Actinobacteria: new concepts for natural product discovery. Nat. Rev. Microbiol. 18, 546–558 (2020).Article 

Google Scholar 
Orellana, L. H. et al. Verrucomicrobiota are specialist consumers of sulfated methyl pentoses during diatom blooms. ISME J. 16, 630–641 (2022).Article 
CAS 

Google Scholar 
Fincker, M. et al. Metabolic strategies of marine subseafloor Chloroflexi inferred from genome reconstructions. Environ. Microbiol. 22, 3188–3204 (2020).Article 
CAS 

Google Scholar 
Stralis-Pavese, N. et al. Analysis of methanotroph community composition using a pmoA-based microbial diagnostic microarray. Nat. Protoc. 6, 609–624 (2011).Article 
CAS 

Google Scholar 
Berube, P. M. et al. Physiology and evolution of nitrate acquisition in Prochlorococcus. ISME J. 9, 1195–1207 (2015).Article 
CAS 

Google Scholar 
Liang, J.-L. et al. Novel phosphate-solubilizing bacteria enhance soil phosphorus cycling following ecological restoration of land degraded by mining. ISME J. 14, 1600–1613 (2020).Article 
CAS 

Google Scholar 
Hättenschwiler, S. & Gasser, P. Soil animals alter plant litter diversity effects on decomposition. Proc. Natl Acad. Sci. USA 102, 1519 (2005).Article 

Google Scholar 
Erktan, A. et al. The physical structure of soil: determinant and consequence of trophic interactions. Soil Biol. Biochem. 148, 107876 (2020).Article 
CAS 

Google Scholar 
Grime, J. P. Benefits of plant diversity to ecosystems: immediate, filter and founder effects. J. Ecol. 86, 902–910 (1998).Article 

Google Scholar 
Barberán, A. et al. Why are some microbes more ubiquitous than others? Predicting the habitat breadth of soil bacteria. Ecol. Lett. 17, 794–802 (2014).Article 

Google Scholar 
Chen, Q. L. et al. Rare microbial taxa as the major drivers of ecosystem multifunctionality in long-term fertilized soils. Soil Biol. Biochem. 141, 107686 (2020).Article 
CAS 

Google Scholar 
Zhang, Z. et al. Rare species-driven diversity-ecosystem multifunctionality relationships are promoted by stochastic community assembly. mBio. mBio. 13, e00449–22 (2022).Article 

Google Scholar 
Domínguez-García, V. et al. Unveiling dimensions of stability in complex ecological networks. Proc. Natl Acad. Sci. USA 116, 25714 (2019).Article 

Google Scholar 
Zhang, L. et al. Signal beyond nutrient, fructose, exuded by an arbuscular mycorrhizal fungus triggers phytate mineralization by a phosphate solubilizing bacterium. ISME J. 12, 2339–2351 (2018).Article 
CAS 

Google Scholar 
Couturier, M. et al. Lytic xylan oxidases from wood-decay fungi unlock biomass degradation. Nat. Chem. Biol. 14, 306–310 (2018).Article 
CAS 

Google Scholar 
Steinberg, G. et al. A lipophilic cation protects crops against fungal pathogens by multiple modes of action. Nat. Commun. 11, 1608 (2020).Article 
CAS 

Google Scholar 
Johnston, A. S. A. & Sibly, R. M. The influence of soil communities on the temperature sensitivity of soil respiration. Nat. Ecol. Evol. 2, 1597–1602 (2018).Article 

Google Scholar 
Watson, C. J. et al. Ecological and economic benefits of low-intensity urban lawn management. J. Appl. Ecol. 57, 436–446 (2020).Article 

Google Scholar 
Williams, N. S. G. et al. A conceptual framework for predicting the effects of urban environments on floras. J. Ecol. 97, 4–9 (2009).Article 

Google Scholar 
Trabucco, A. & Zomer, R. Global Aridity Index and Potential Evapotranspiration (ET0) Climate Database v2 (figshare, 2019); https://doi.org/10.6084/m9.figshare.7504448.v3Kettler, T. A. et al. Simplifed method for soil particle-size determination to accompany soil-quality analyses. Soil Sci. Soc. Am. J. 65, 849–852 (2001).Article 
CAS 

Google Scholar 
Delgado-Baquerizo, M. et al. Changes in belowground biodiversity during ecosystem development. Proc. Natl Acad. Sci. USA 116, 6891 (2019).Article 
CAS 

Google Scholar 
Ramirez, K. S. et al. Biogeographic patterns in below-ground diversity in New York City’s Central Park are similar to those observed globally. Proc. Biol. Sci. 281, 22 (2014).
Google Scholar 
Callahan, B. J. et al. DADA2: high-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583 (2016).Article 
CAS 

Google Scholar 
Tedersoo, L. et al. Regional-scale in-depth analysis of soil fungal diversity reveals strong pH and plant species effects in Northern Europe. Front. Microbiol. 11, 1953 (2020).Article 

Google Scholar 
Bastida, F. et al. Microbiological degradation index of soils in a semiarid climate. Soil Biol. Biochem. 38, 3463–3473 (2006).Article 
CAS 

Google Scholar 
Lugato, E. et al. Different climate sensitivity of particulate and mineral-associated soil organic matter. Nat. Geosci. 14, 295–300 (2021).Article 
CAS 

Google Scholar 
Delgado-Baquerizo, M. et al. The influence of soil age on ecosystem structure and function across biomes. Nat. Commun. 11, 4721 (2020).Article 
CAS 

Google Scholar 
Frostegård, Å. et al. Use and misuse of PLFA measurements in soils. Soil Biol. Biochem. 43, 1621–1625 (2011).Article 

Google Scholar 
Olsson, P. A. et al. The use of phospholipid and neutral lipid fatty acids to estimate biomass of arbuscular mycorrhizal fungi in soil. Mycol. Res. 99, 623–629 (1995).Article 
CAS 

Google Scholar 
Campbell, C. D. et al. A rapid microtiter plate method to measure carbon dioxide evolved from carbon substrate amendments so as to determine the physiological profiles of soil microbial communities by using whole soil. Appl. Environ. Microbiol. 69, 3593–3599 (2003).Article 
CAS 

Google Scholar 
Bell, C. W. et al. High-throughput fluorometric measurement of potential soil extracellular enzyme activities. J. Vis. Exp. 15, e50961 (2013).
Google Scholar 
Nguyen, N. H. et al. FUNGuild: an open annotation tool for parsing fungal community datasets by ecological guild. Fungal Ecol. 20, 241–248 (2016).Article 

Google Scholar 
Fierer, N. et al. Cross-biome metagenomic analyses of soil microbial communities and their functional attributes. Proc. Natl Acad. Sci. USA 109, 21390–21395 (2012).Article 
CAS 

Google Scholar 
Fierer, N. et al. Reconstructing the microbial diversity and function of pre-agricultural tallgrass prairie soils in the United States. Science 342, 621–624 (2013).Article 
CAS 

Google Scholar 
Buchfink, B., Reuter, K. & Drost, H. G. Sensitive protein alignments at tree-of-life scale using DIAMOND. Nat. Methods 18, 366–368 (2021).Article 
CAS 

Google Scholar 
Manning, P. et al. Redefining ecosystem multifunctionality. Nat. Ecol. Evolution 2, 427–436 (2018).Article 

Google Scholar 
Legendre, P. & Legendre, L. Interpretation of Ecological Structures Numerical Ecology 3rd English edn (Elsevier Science BV, 2012).Grace, J. B. Structural Equation Modeling and Natural Systems (Cambridge University Press, 2006).Subramanian, S. et al. Persistent gut microbiota immaturity in malnourished Bangladeshi children. Nature 510, 417 (2014).Article 
CAS 

Google Scholar 
Fan, K. et al. Soil biodiversity supports the delivery of multiple ecosystem functions in urban greenspaces. figshare https://doi.org/10.6084/m9.figshare.21175492.v3 (2022). More

Hughes, T. P. et al. Global warming and recurrent mass bleaching of corals. Nature 543, 373–377 (2017).Article 
CAS 

Google Scholar 
Arkema, K. K., Fisher, D. M., Wyatt, K., Wood, S. A. & Payne, H. J. Advancing sustainable development and protected area mManagement with social media-based tourism data. Sustainability 13, 2427 (2021).Article 

Google Scholar 
Tourism in the 2030 Agenda (UNWTO, 2015); https://www.unwto.org/tourism-in-2030-agendaCowburn, B., Moritz, C., Birrell, C., Grimsditch, G. & Abdulla, A. Can luxury and environmental sustainability co-exist? Assessing the environmental impact of resort tourism on coral reefs in the Maldives. Ocean Coast. Manag. 158, 120–127 (2018).Article 

Google Scholar 
Lin, B. Close encounters of the worst kind: reforms needed to curb coral reef damage by recreational divers. Coral Reefs 40, 1429–1435 (2021).Article 

Google Scholar 
Asner, G. P. et al. Large-scale mapping of live corals to guide reef conservation. Proc. Natl Acad. Sci. USA 117, 33711–33718 (2020).Article 
CAS 

Google Scholar 
Wood, S. A., Guerry, A. D., Silver, J. M. & Lacayo, M. Using social media to quantify nature-based tourism and recreation. Sci. Rep. 3, 2976 (2013).Article 

Google Scholar 
Wood, S. A. et al. Next-generation visitation models using social media to estimate recreation on public lands. Sci. Rep. 10, 15419 (2020).Article 
CAS 

Google Scholar 
Hausmann, A. et al. Social media data can be used to understand tourists’ preferences for nature-based experiences in protected areas. Conserv. Lett. 11, e12343 (2018).Article 

Google Scholar 
Tenkanen, H. et al. Instagram, Flickr, or Twitter: assessing the usability of social media data for visitor monitoring in protected areas. Sci. Rep. 7, 17615 (2017).Article 

Google Scholar 
Sessions, C., Wood, S. A., Rabotyagov, S. & Fisher, D. M. Measuring recreational visitation at U.S. National Parks with crowd-sourced photographs. J. Environ. Manag. 183, 703–711 (2016).Article 

Google Scholar 
Mancini, F., Coghill, G. M. & Lusseau, D. Using social media to quantify spatial and temporal dynamics of nature-based recreational activities. PLoS One 13, e0200565 (2018).Article 

Google Scholar 
Spalding, M. et al. Mapping the global value and distribution of coral reef tourism. Mar. Policy 82, 104–113 (2017).Article 

Google Scholar 
van Zanten, B. T. et al. Continental-scale quantification of landscape values using social media data. Proc. Natl Acad. Sci. USA 113, 12974–12979 (2016).Article 

Google Scholar 
Department of Land and Natural Resources. Beach Access (Office of Conservation and Coastal Lands, 2013); https://dlnr.hawaii.gov/occl/beach-access/Mobile LTE Coverage Map (Federal Communications Commission, 2021).Arkema, K. K. et al. Embedding ecosystem services in coastal planning leads to better outcomes for people and nature. Proc. Natl Acad. Sci. USA 112, 7390–7395 (2015).Article 
CAS 

Google Scholar 
Neuvonen, M., Pouta, E., Puustinen, J. & Sievänen, T. Visits to national parks: effects of park characteristics and spatial demand. J. Nat. Conserv. 18, 224–229 (2010).Article 

Google Scholar 
Rodgers, K., Cox, E. & Newtson, C. Effects of mechanical fracturing and experimental trampling on hawaiian corals. Environ. Manag. 31, 0377–0384 (2003).Article 

Google Scholar 
Downs, C. A. et al. Toxicopathological effects of the sunscreen UV filter, oxybenzone (benzophenone-3), on coral planulae and cultured primary cells and its environmental contamination in Hawaii and the U.S. Virgin Islands. Arch. Environ. Contam. Toxicol. 70, 265–288 (2016).Article 
CAS 

Google Scholar 
Côté, I. M., Darling, E. S. & Brown, C. J. Interactions among ecosystem stressors and their importance in conservation. Proc. R. Soc. B. 283, 20152592 (2016).Article 

Google Scholar 
Bruno, J. F. & Valdivia, A. Coral reef degradation is not correlated with local human population density. Sci. Rep. 6, 29778 (2016).Article 
CAS 

Google Scholar 
Johnson, J. V., Dick, J. T. A. & Pincheira-Donoso, D. Local anthropogenic stress does not exacerbate coral bleaching under global climate change. Glob. Ecol. Biogeogr. (2022).Darling, E. S., McClanahan, T. R. & Côté, I. M. Combined effects of two stressors on Kenyan coral reefs are additive or antagonistic, not synergistic. Conserv. Lett. 3, 122–130 (2010).Article 

Google Scholar 
Severino, S. J. L., Rodgers, K. S., Stender, Y. & Stefanak, M. Hanauma Bay Biological Carrying Capacity Survey 2019–20 2nd Annual Report https://www.honolulu.gov/rep/site/dpr/hanaumabay_docs/Hanauma_Bay_Carrying_Capacity_Report_August_2020.pdf (City and County of Honolulu Parks and Recreation Department, 2020).Selenium WebDriver (Software Freedom Conservancy, 2022); https://www.selenium.dev/documentation/en/webdriver/Geospatial Data Portal. Hawaii Statewide GIS Program (Hawaii State Office of Planning, 2017); https://geoportal.hawaii.gov/Wedding, L. M. et al. Advancing the integration of spatial data to map human and natural drivers on coral reefs. PLoS One 13, e0189792 (2018).Article 

Google Scholar 
Nguyen, T., Liquet, B., Mengersen, K. & Sous, D. Mapping of coral reefs with multispectral satellites: a review of recent papers. Remote Sens. 13, 4470 (2021).Article 

Google Scholar 
Wicaksono, P., Aryaguna, P. A. & Lazuardi, W. Benthic habitat mapping model and cross validation using machine-learning classification algorithms. Remote Sens. 11, 1279 (2019).Article 

Google Scholar  More

Swift, M. J., Heal, O. W. & Anderson, J. M. Decomposition in Terrestrial Ecosystems. Vol. 5.5 (Blackwell, 1979).Aerts, R. Climate, leaf litter chemistry and leaf litter decomposition in terrestrial ecosystems: a triangular relationship. Oikos 79, 439 (1997).Article 

Google Scholar 
Makkonen, M. et al. Highly consistent effects of plant litter identity and functional traits on decomposition across a latitudinal gradient. Ecol. Lett. 15, 1033–1041 (2012).Article 

Google Scholar 
Coûteaux, M. M., Bottner, P. & Berg, B. Litter decomposition, climate and liter quality. Trends Ecol. Evol. 10, 63–66 (1995).Article 

Google Scholar 
Cornwell, W. K. et al. Plant species traits are the predominant control on litter decomposition rates within biomes worldwide. Ecol. Lett. 11, 1065–1071 (2008).Article 

Google Scholar 
Bradford, M. A. et al. Climate fails to predict wood decomposition at regional scales. Nat. Clim. Change 4, 625–630 (2014).Article 
CAS 

Google Scholar 
Bradford, M. A., Berg, B., Maynard, D. S., Wieder, W. R. & Wood, S. A. Understanding the dominant controls on litter decomposition. J. Ecol. 104, 229–238 (2016).Article 
CAS 

Google Scholar 
Joly, F.-X. et al. Tree species diversity affects decomposition through modified micro-environmental conditions across European forests. New Phytol. 214, 1281–1293 (2017).Article 
CAS 

Google Scholar 
Bradford, M. A. et al. A test of the hierarchical model of litter decomposition. Nat. Ecol. Evol. 1, 1836–1845 (2017).Article 

Google Scholar 
Berg, B. et al. Litter mass loss rates in pine forests of Europe and Eastern United States: some relationships with climate and litter quality. Biogeochemistry 20, 127–159 (1993).Article 

Google Scholar 
Powers, J. S. et al. Decomposition in tropical forests: a pan-tropical study of the effects of litter type, litter placement and mesofaunal exclusion across a precipitation gradient. J. Ecol. 97, 801–811 (2009).Article 
CAS 

Google Scholar 
Djukic, I. et al. Early stage litter decomposition across biomes. Sci. Total Environ. 628–629, 1369–1394 (2018).Article 

Google Scholar 
Cornelissen, J. H. C. & Thompson, K. Functional leaf attributes predict litter decomposition rate in herbaceous plants. New Phytol. 135, 109–114 (1997).Article 
CAS 

Google Scholar 
Coq, S., Souquet, J.-M., Meudec, E., Cheynier, V. & Hättenschwiler, S. Interspecific variation in leaf litter tannins drives decomposition in a tropical rain forest of French Guiana. Ecology 91, 2080–2091 (2010).Article 

Google Scholar 
Sun, T. et al. Contrasting dynamics and trait controls in first-order root compared with leaf litter decomposition. Proc. Natl Acad. Sci. USA 115, 10392–10397 (2018).Article 
CAS 

Google Scholar 
Baeten, L. et al. A novel comparative research platform designed to determine the functional significance of tree species diversity in European forests. Perspect. Plant Ecol. Evol. Syst. 15, 281–291 (2013).Article 

Google Scholar 
Hobbie, S. E. et al. Tree species effects on decomposition and forest floor dynamics in a common garden. Ecology 87, 2288–2297 (2006).Article 

Google Scholar 
von Arx, G., Graf Pannatier, E., Thimonier, A. & Rebetez, M. Microclimate in forests with varying leaf area index and soil moisture: potential implications for seedling establishment in a changing climate. J. Ecol. 101, 1201–1213 (2013).Article 

Google Scholar 
Ayres, E. et al. Home-field advantage accelerates leaf litter decomposition in forests. Soil Biol. Biochem. 41, 606–610 (2009).Article 
CAS 

Google Scholar 
Freschet, G. T., Aerts, R. & Cornelissen, J. H. C. Multiple mechanisms for trait effects on litter decomposition: moving beyond home-field advantage with a new hypothesis. J. Ecol. 100, 619–630 (2012).Article 

Google Scholar 
Meentemeyer, V. Macroclimate and lignin control of litter decomposition rates. Ecology 59, 465–472 (1978).Article 
CAS 

Google Scholar 
Currie, W. S. et al. Cross-biome transplants of plant litter show decomposition models extend to a broader climatic range but lose predictability at the decadal time scale. Glob. Change Biol. 16, 1744–1761 (2010).Article 

Google Scholar 
Canessa, R. et al. Relative effects of climate and litter traits on decomposition change with time, climate and trait variability. J. Ecol. 109, 447–458 (2021).Article 

Google Scholar 
García-Palacios, P., Shaw, E. A., Wall, D. H. & Hättenschwiler, S. Temporal dynamics of biotic and abiotic drivers of litter decomposition. Ecol. Lett. 19, 554–563 (2016).Article 

Google Scholar 
Prescott, C. E. Litter decomposition: what controls it and how can we alter it to sequester more carbon in forest soils? Biogeochemistry 101, 133–149 (2010).Article 
CAS 

Google Scholar 
Prescott, C. E. & Vesterdal, L. Decomposition and transformations along the continuum from litter to soil organic matter in forest soils. For. Ecol. Manage. 498, 119522 (2021).Article 

Google Scholar 
Stadler, S. J. in Encyclopedia of World Climatology 89–94 (Springer, 2005).Moore, T. R., Bubier, J. L. & Bledzki, L. Litter decomposition in temperate peatland ecosystems: the effect of substrate and site. Ecosystems 10, 949–963 (2007).Article 

Google Scholar 
Austin, A. T. Has water limited our imagination for aridland biogeochemistry. Trends Ecol. Evol. 26, 229–235 (2011).Article 

Google Scholar 
Joly, F.-X., Kurupas, K. & Throop, H. Pulse frequency and soil-litter mixing alter the control of cumulative precipitation over litter decomposition. Ecology 98, 2255–2260 (2017).Article 

Google Scholar 
Scherer-Lorenzen, M., Bonilla, J. L. & Potvin, C. Tree species richness affects litter production and decomposition rates in a tropical biodiversity experiment. Oikos 116, 2108–2124 (2007).Article 

Google Scholar 
Vivanco, L. & Austin, A. T. Tree species identity alters forest litter decomposition through long-term plant and soil interactions in Patagonia, Argentina. J. Ecol. 96, 727–736 (2008).Article 
CAS 

Google Scholar 
Fanin, N. et al. Home‐field advantage of litter decomposition: from the phyllosphere to the soil. New Phytol. 231, 1353–1358 (2021).Article 

Google Scholar 
Hättenschwiler, S., Tiunov, A. V. & Scheu, S. Biodiversity and litter decomposition in terrestrial ecosystems. Annu. Rev. Ecol. Evol. Syst. 36, 191–218 (2005).Article 

Google Scholar 
Keuskamp, J. A., Dingemans, B. J. J., Lehtinen, T., Sarneel, J. M. & Hefting, M. M. Tea Bag Index: a novel approach to collect uniform decomposition data across ecosystems. Methods Ecol. Evol. 4, 1070–1075 (2013).Article 

Google Scholar 
Thakur, M. P. et al. Reduced feeding activity of soil detritivores under warmer and drier conditions. Nat. Clim. Change 8, 75–78 (2018).Article 

Google Scholar 
Harrison, A. F., Latter, P. M. & Walton, D. W. H. (eds) Cotton Strip Assay: An Index of Decomposition in Soils (Institute of Terrestrial Ecology, 1988).García-Palacios, P., Maestre, F. T., Kattge, J. & Wall, D. H. Climate and litter quality differently modulate the effects of soil fauna on litter decomposition across biomes. Ecol. Lett. 16, 1045–1053 (2013).Article 

Google Scholar 
Garnier, E. et al. Plant functional markers capture ecosystem properties during secondary succession. Ecology 85, 2630–2637 (2004).Article 

Google Scholar 
Dawud, S. M. et al. Tree species functional group is a more important driver of soil properties than tree species diversity across major European forest types. Funct. Ecol. 31, 1153–1162 (2017).Article 

Google Scholar 
Pollastrini, M. et al. Taxonomic and ecological relevance of the chlorophyll a fluorescence signature of tree species in mixed European forests. New Phytol. 212, 51–65 (2016).Article 
CAS 

Google Scholar 
R Development Core Team. R: A Language and Environment for Statistical Computing (R Core Team, 2013).Bates, D., Mächler, M., Bolker, B. M. & Walker, S. C. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).Article 

Google Scholar 
Lefcheck, J. S. piecewiseSEM: piecewise structural equation modelling in R for ecology, evolution, and systematics. Methods Ecol. Evol. 7, 573–579 (2016).Article 

Google Scholar  More

Adeleye, M. A., Haberle, S. G., Gallagher, R., Andrew, S. C. & Herbert, A. Nat. Ecol. Evol., https://doi.org/10.1038/s41559-022-01943-4 (2023).Mokany, K. et al. Ecography 2022, e06426 (2022).Article 

Google Scholar 
Violle, C. et al. Oikos 116, 882–892 (2007).Article 

Google Scholar 
Birks, H. J. B. Front. Ecol. Evol. 8, 166 (2020).Article 

Google Scholar 
Reitalu, T. et al. J. Veg. Sci. 26, 911–922 (2015).Article 

Google Scholar 
Brussel, T. & Brewer, S. C. Front. Ecol. Evol. 8, 564609 (2021).Article 

Google Scholar 
van der Sande, M. T. et al. Ecol. Lett. 22, 925–935 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Veeken, A., Santos, M. J., McGowan, S., Davies, A. L. & Schrodt, F. Ecol. Lett. 25, 1937–1951 (2022).Article 
PubMed 
PubMed Central 

Google Scholar 
Suárez-Castro, A. F., Raymundo, M., Bimler, M. & Mayfield, M. M. Ecography 2022, e05844 (2022).Article 

Google Scholar 
Biggs, C. R. et al. Ecosphere 11, e03184 (2020).Article 

Google Scholar  More