Ecology

Benhamou, S. Of scales and stationarity in animal movements. Ecol. Lett. 17, 261–272 (2014).PubMed 
Article 

Google Scholar 
Owen-Smith, N. Effects of temporal variability in resources on foraging behaviour. In Resource Ecology (eds. Prins, H. H. T. & Van Langevelde, F.) 159–181 (Springer Netherlands, 2008).Hutchinson, G. E. The multivariate niche. Cold Spring Harb. Symp. Quant. Biol. 22, 415–421 (1957).Article 

Google Scholar 
Kearney, M. Habitat, environment and niche: what are we modelling? Oikos 115, 186–191 (2006).Article 

Google Scholar 
Tauber, E., Last, K. S., Olive, P. J. W. & Kyriacou, C. P. Clock gene evolution and functional divergence. J. Biol. Rhythms 19, 445–458 (2004).CAS 
PubMed 
Article 

Google Scholar 
Pilorz, V., Helfrich-Förster, C. & Oster, H. The role of the circadian clock system in physiology. Pflug. Arch. – Eur. J. Physiol. 470, 227–239 (2018).CAS 
Article 

Google Scholar 
Levy, O., Dayan, T., Porter, W. P. & Kronfeld-Schor, N. Time and ecological resilience: can diurnal animals compensate for climate change by shifting to nocturnal activity? Ecol. Monogr. 89, e01334 (2019).Article 

Google Scholar 
Gaynor, K. M., Hojnowski, C. E., Carter, N. H. & Brashares, J. S. The influence of human disturbance on wildlife nocturnality. Science 360, 1232–1235 (2018).CAS 
PubMed 
Article 

Google Scholar 
Cox, D. T. C., Gardner, A. S. & Gaston, K. J. Diel niche variation in mammals associated with expanded trait space. Nat. Commun. 12, 1753 (2021).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Kronfeld-Schor, N. & Dayan, T. Partitioning of time as an ecological resource. Annu. Rev. Ecol. Evol. Syst. 34, 153–181 (2003).Article 

Google Scholar 
Kronfeld‐Schor, N. et al. On the use of the time axis for ecological separation: diel rhythms as an evolutionary constraint. Am. Nat. 158, 451–457 (2001).PubMed 
Article 

Google Scholar 
Austin, R. W. & Petzold, T. J. Spectral dependence of the diffuse attenuation coefficient of light in ocean waters. OE OPEGAR 25, 253471 (1986).Article 

Google Scholar 
Bandara, K., Varpe, Ø., Wijewardene, L., Tverberg, V. & Eiane, K. Two hundred years of zooplankton vertical migration research. Biol. Rev. 96, 1547–1589 (2021).PubMed 
Article 

Google Scholar 
Brierley, A. S. Diel vertical migration. Curr. Biol. 24, R1074–R1076 (2014).CAS 
PubMed 
Article 

Google Scholar 
Hays, G. C. A review of the adaptive significance and ecosystem consequences of zooplankton diel vertical migrations. In Migrations and Dispersal of Marine Organisms 163–170 (Springer, 2003).Aumont, O., Maury, O., Lefort, S. & Bopp, L. Evaluating the potential impacts of the diurnal vertical migration by marine organisms on marine biogeochemistry. Glob. Biogeochem. Cycles https://doi.org/10.1029/2018GB005886 (2018).Article 

Google Scholar 
Tarrant, A. M., McNamara-Bordewick, N., Blanco-Bercial, L., Miccoli, A. & Maas, A. E. Diel metabolic patterns in a migratory oceanic copepod. J. Exp. Mar. Biol. Ecol. 545, 151643 (2021).Article 

Google Scholar 
Cohen, J. H. & Forward, Jr. R. B. Zooplankton diel vertical migration—a review of proximate control. In Oceanography and Marine Biology (eds Gibson, R. N., Atkinson, R. J. A. & Gordon, J. D. M.) 89–122 (CRC Press, 2009).Benoit-Bird, K. J., Au, W. W. L. & Wisdoma, D. W. Nocturnal light and lunar cycle effects on diel migration of micronekton. Limnol. Oceanogr. 54, 1789–1800 (2009).Article 

Google Scholar 
Last, K. S., Hobbs, L., Berge, J., Brierley, A. S. & Cottier, F. Moonlight drives ocean-scale mass vertical migration of zooplankton during the Arctic Winter. Curr. Biol. 26, 244–251 (2016).CAS 
PubMed 
Article 

Google Scholar 
Omand, M. M., Steinberg, D. K. & Stamieszkin, K. Cloud shadows drive vertical migrations of deep-dwelling marine life. PNAS 118, e2022977118 (2021).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Strömberg, J.-O., Spicer, J. I., Liljebladh, B. & Thomasson, M. A. Northern krill, Meganyctiphanes norvegica, come up to see the last eclipse of the millennium? J. Mar. Biol. Assoc. UK 82, 919–920 (2002).Article 

Google Scholar 
Ludvigsen, M. et al. Use of an Autonomous Surface Vehicle reveals small-scale diel vertical migrations of zooplankton and susceptibility to light pollution under low solar irradiance. Sci. Adv. 4, eaap9887 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
Häfker, N. S. et al. Circadian clock involvement in zooplankton diel vertical migration. Curr. Biol. 27, 2194–2201 (2017).PubMed 
Article 
CAS 

Google Scholar 
Chen, C. et al. Drosophila Ionotropic Receptor 25a mediates circadian clock resetting by temperature. Nature 527, 516–520 (2015).CAS 
PubMed 
Article 

Google Scholar 
Epifanio, C. E. & Cohen, J. H. Behavioral adaptations in larvae of brachyuran crabs: a review. J. Exp. Mar. Biol. Ecol. 482, 85–105 (2016).Article 

Google Scholar 
Sorek, M. et al. Setting the pace: host rhythmic behaviour and gene expression patterns in the facultatively symbiotic cnidarian Aiptasia are determined largely by Symbiodinium. Microbiome 6, 83 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
Hobbs, L., Banas, N. S., Cottier, F. R., Berge, J. & Daase, M. Eat or sleep: availability of winter prey explains mid-winter and spring activity in an Arctic Calanus population. Front. Mar. Sci. 7, 541564 (2020).Article 

Google Scholar 
Urmy, S. S., Horne, J. K. & Barbee, D. H. Measuring the vertical distributional variability of pelagic fauna in Monterey Bay. ICES J. Mar. Sci. 69, 184–196 (2012).Article 

Google Scholar 
Berge, J. et al. Arctic complexity: a case study on diel vertical migration of zooplankton. J. Plankton Res. 36, 1279–1297 (2014).PubMed 
PubMed Central 
Article 

Google Scholar 
Berge, J. et al. In the dark: A review of ecosystem processes during the Arctic polar night. Prog. Oceanogr. https://doi.org/10.1016/j.pocean.2015.08.005 (2015).Article 

Google Scholar 
Pavlov, A. K. et al. The underwater light climate in Kongsfjorden and Its ecological implications. In The Ecosystem of Kongsfjorden, Svalbard (eds Hop, H. & Wiencke, C.) 137–170 (Springer International Publishing, 2019).Cohen, J. H. et al. Is ambient light during the high arctic polar night sufficient to act as a visual cue for Zooplankton? PLoS ONE 10, e0126247 (2015).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Veedin Rajan, V. B. et al. Seasonal variation in UVA light drives hormonal and behavioural changes in a marine annelid via a ciliary opsin. Nat. Ecol. Evol. 5, 204–218 (2021).PubMed 
Article 

Google Scholar 
Vinayak, P. et al. Exquisite light sensitivity of Drosophila melanogaster cryptochrome. PLoS Genet. 9, e1003615 (2013).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Verasztó, C. et al. Ciliary and rhabdomeric photoreceptor-cell circuits form a spectral depth gauge in marine zooplankton. eLife 7, e36440 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
Hobbs, L. et al. A marine zooplankton community vertically structured by light across diel to interannual timescales. Biol. Lett. 17, 20200810 (2021).PubMed 
PubMed Central 
Article 

Google Scholar 
Daase, M., Eiane, K., Aksnes, D. L. & Vogedes, D. Vertical distribution of Calanus spp. and Metridia longa at four Arctic locations. Mar. Biol. Res. 4, 193–207 (2008).Article 

Google Scholar 
Irigoien, X., Conway, D. V. P. & Harris, R. P. Flexible diel vertical migration behaviour of zooplankton in the Irish Sea. Mar. Ecol. Prog. Ser. 267, 85–97 (2004).Article 

Google Scholar 
Frost, B. W. & Bollens, S. M. Variability of diel vertical migration in the marine planktonic copepod Pseudocalanus newmani in relation to its predators. Can. J. Fish. Aquat. Sci. 49, 1137–1141 (1992).Article 

Google Scholar 
Tarling, G. A., Jarvis, T., Emsley, S. M. & Matthews, J. B. L. Midnight sinking behaviour in Calanus finmarchicus: a response to satiation or krill predation? Mar. Ecol. Prog. Ser. 240, 183–194 (2002).Article 

Google Scholar 
Hays, G. C., Proctor, C. A., John, A. W. G. & Warner, A. J. Interspecific differences in the diel vertical migration of marine copepods: the implications of size, color, and morphology. Limnol. Oceanogr. 39, 1621–1629 (1994).Article 

Google Scholar 
Gastauer, S., Nickels, C. F. & Ohman, M. D. Body size- and season-dependent diel vertical migration of mesozooplankton resolved acoustically in the San Diego Trough. Limnol. Oceanogr. 67, 300–313 (2021).Article 

Google Scholar 
Hardy, A. C. & Bainbridge, R. Experimental observations on the vertical migrations of plankton animals. J. Mar. Biol. Assoc. UK 33, 409–448 (1954).Article 

Google Scholar 
Musilova, Z. et al. Vision using multiple distinct rod opsins in deep-sea fishes. Science 364, 588–592 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Gornik, S. G. et al. Photoreceptor diversification accompanies the evolution of Anthozoa. Mol. Biol. Evol. 38, 1744–1760 (2021).CAS 
PubMed 
Article 

Google Scholar 
Cohen, J. H. et al. Photophysiological cycles in Arctic krill are entrained by weak midday twilight during the Polar Night. PLoS Biol. 19, e3001413 (2021).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Kopperud, K. L. & Grace, M. S. Circadian rhythms of retinal sensitivity in the Atlantic tarpon, Megalops atlanticus. Bull. Mar. Sci. https://doi.org/10.5343/bms.2016.1045 (2017).Article 

Google Scholar 
Ohguro, C., Moriyama, Y. & Tomioka, K. The compound eye possesses a self-sustaining Circadian Oscillator in the Cricket Gryllus bimaculatus. Zool. Sci. 38, 82–89 (2020).Article 

Google Scholar 
Brodrick, E. A., How, M. J. & Hemmi, J. M. Fiddler crab electroretinograms reveal vast circadian shifts in visual sensitivity and temporal summation in dim light. J. Exp. Biol. jeb.243693, https://doi.org/10.1242/jeb.243693 (2022).Kaartvedt, S., Røstad, A., Christiansen, S. & Klevjer, T. A. Diel vertical migration and individual behavior of nekton beyond the ocean’s twilight zone. Deep Sea Res. Part I: Oceanogr. Res. Pap. 103280, https://doi.org/10.1016/j.dsr.2020.103280 (2020).Flôres, D. E. F. L., Jannetti, M. G., Valentinuzzi, V. S. & Oda, G. A. Entrainment of circadian rhythms to irregular light/dark cycles: a subterranean perspective. Sci. Rep. 6, 34264 (2016).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Hays, G. C., Kennedy, H. & Frost, B. W. Individual variability in diel vertical migration of a marine copepod: why some individuals remain at depth when others migrate. Limnol. Oceanogr. 46, 2050–2054 (2001).Article 

Google Scholar 
Cohen, J. H. & Forward, R. B. Jr. Photobehavior as an inducible defense in the marine copepod Calanopia americana. Limnol. Oceanogr. 50, 1269–1277 (2005).Article 

Google Scholar 
Kvile, K. Ø., Altin, D., Thommesen, L. & Titelman, J. Predation risk alters life history strategies in an oceanic copepod. Ecology 102, e03214 (2021).PubMed 
Article 

Google Scholar 
Spaak, P. & Ringelberg, J. Differential behaviour and shifts in genotype composition during the beginning of a seasonal period of diel vertical migration. Hydrobiologia 360, 177–185 (1997).Article 

Google Scholar 
Buskey, E. J. & Swift, E. Behavioral responses of oceanic zooplankton to simulated bioluminescence. Biol. Bull. 168, 263–275 (1985).Article 

Google Scholar 
Berndt, A. et al. A novel photoreaction mechanism for the circadian blue light photoreceptor Drosophila cryptochrome. J. Biol. Chem. 282, 13011–13021 (2007).CAS 
PubMed 
Article 

Google Scholar 
Franz-Badur, S. et al. Structural changes within the bifunctional cryptochrome/photolyase CraCRY upon blue light excitation. Sci. Rep. 9, 9896 (2019).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Biscontin, A. et al. Functional characterization of the circadian clock in the Antarctic krill, Euphausia superba. Sci. Rep. 7, 17742 (2017).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Piccolin, F. et al. Photoperiodic modulation of circadian functions in Antarctic krill Euphausia superba Dana, 1850 (Euphausiacea). J. Crustacean Biol. 38, 707–715 (2018).
Google Scholar 
Piccolin, F., Pitzschler, L., Biscontin, A., Kawaguchi, S. & Meyer, B. Circadian regulation of diel vertical migration (DVM) and metabolism in Antarctic krill Euphausia superba. Sci. Rep. 10, 16796 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Häfker, N. S., Teschke, M., Hüppe, L. & Meyer, B. Calanus finmarchicus diel and seasonal rhythmicity in relation to endogenous timing under extreme polar photoperiods. Mar. Ecol. Prog. Ser. 603, 79–92 (2018).Article 
CAS 

Google Scholar 
Häfker, N. S. et al. Calanus finmarchicus seasonal cycle and diapause in relation to gene expression, physiology, and endogenous clocks. Limnol. Oceanogr. 63, 2815–2838 (2018).Article 

Google Scholar 
Hüppe, L. et al. Evidence for oscillating circadian clock genes in the copepod Calanus finmarchicus during the summer solstice in the high Arctic. Biol. Lett. 16, 20200257 (2020).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Dmitrenko, I. A. et al. Sea-ice and water dynamics and moonlight impact the acoustic backscatter diurnal signal over the eastern Beaufort Sea continental slope. Ocean Sci. 16, 1261–1283 (2020).CAS 
Article 

Google Scholar 
Hobbs, L., Cottier, F. R., Last, K. S. & Berge, J. Pan-Arctic diel vertical migration during the polar night. Mar. Ecol. Prog. Ser. 605, 61–72 (2018).Article 

Google Scholar 
Chittka, L., Stelzer, R. J. & Stanewsky, R. Daily changes in ultraviolet light levels can synchronize the circadian clock of Bumblebees (Bombus terrestris). Chronobiol. Int. 30, 434–442 (2013).PubMed 
Article 

Google Scholar 
Pauers, M. J., Kuchenbecker, J. A., Neitz, M. & Neitz, J. Changes in the colour of light cue circadian activity. Anim. Behav. 83, 1143–1151 (2012).PubMed 
PubMed Central 
Article 

Google Scholar 
Mouland, J. W., Martial, F., Watson, A., Lucas, R. J. & Brown, T. M. Cones support alignment to an inconsistent world by suppressing mouse circadian responses to the blue colors associated with twilight. Curr. Biol. 29, 4260–4267.e4 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Walmsley, L. et al. Colour as a signal for entraining the mammalian circadian clock. PLoS Biol. 13, e1002127 (2015).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Ashley, N. T., Schwabl, I., Goymann, W. & Buck, C. L. Keeping time under the midnight sun: behavioral and plasma melatonin profiles of free-living lapland longspurs (Calcarius lapponicus) during the Arctic Summer. J. Exp. Zool. Part A: Ecol. Genet. Physiol. 319, 10–22 (2013).CAS 
Article 

Google Scholar 
Nordtug, T. & Melø, T. B. Diurnal variations in natural light conditions at summer time in arctic and subarctic areas in relation to light detection in insects. Ecography 11, 202–209 (1988).Article 

Google Scholar 
Cohen, J. H. & Forward, R. B. Jr Diel vertical migration of the marine copepod Calanopia americana. II. Proximate role of exogenous light cues and endogenous rhythms. Mar. Biol. 147, 399–410 (2005).Article 

Google Scholar 
Maas, A. E., Blanco-Bercial, L., Lo, A., Tarrant, A. M. & Timmins-Schiffman, E. Variations in copepod proteome and respiration rate in association with diel vertical migration and circadian cycle. Biol. Bull. 000–000, https://doi.org/10.1086/699219 (2018).Berge, J. et al. Diel vertical migration of Arctic zooplankton during the polar night. Biol. Lett. 5, 69–72 (2009).PubMed 
Article 

Google Scholar 
Dale, T. & Kaartvedt, S. Diel patterns in stage-specific vertical migration of Calanus finmarchicus in habitats with midnight sun. ICES J. Mar. Sci. 57, 1800–1818 (2000).Article 

Google Scholar 
Hut, R. A., van Oort, B. E. H. & Daan, S. Natural entrainment without dawn and dusk: the case of the European Ground Squirrel (Spermophilus citellus). J. Biol. Rhythms 14, 290–299 (1999).CAS 
PubMed 
Article 

Google Scholar 
Williams, C. T., Barnes, B. M., Yan, L. & Buck, C. L. Entraining to the polar day: circadian rhythms in arctic ground squirrels. J. Exp. Biol. 220, 3095–3102 (2017).PubMed 
Article 

Google Scholar 
Daan, S. et al. Lab mice in the field: unorthodox daily activity and effects of a dysfunctional circadian clock allele. J. Biol. Rhythms 26, 118–129 (2011).PubMed 
Article 

Google Scholar 
Gattermann, R. et al. Golden hamsters are nocturnal in captivity but diurnal in nature. Biol. Lett. 4, 253–255 (2008).PubMed 
PubMed Central 
Article 

Google Scholar 
Green, E. W. et al. Drosophila circadian rhythms in seminatural environments: Summer afternoon component is not an artifact and requires TrpA1 channels. PNAS 112, 8702–8707 (2015).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Nagy, D. et al. A semi-natural approach for studying seasonal diapause in Drosophila melanogaster reveals robust photoperiodicity. J. Biol. Rhythms 33, 117–125 (2018).CAS 
PubMed 
Article 

Google Scholar 
Prabhakaran, P. M., De, J. & Sheeba, V. Natural conditions override differences in emergence rhythm among closely related Drosophilids. PLoS ONE 8, e83048 (2013).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Ruf, F. et al. Natural Zeitgebers under temperate conditions cannot compensate for the loss of a functional circadian clock in timing of a vital behavior in Drosophila. J. Biol. Rhythms 0748730421998112, https://doi.org/10.1177/0748730421998112 (2021).Dollish, H. K., Kaladchibachi, S., Negelspach, D. C. & Fernandez, F.-X. The Drosophila circadian phase response curve to light: conservation across seasonally relevant photoperiods and anchorage to sunset. Physiol. Behav. 245, 113691 (2022).CAS 
PubMed 
Article 

Google Scholar 
Shaw, B., Fountain, M. & Wijnen, H. Control of daily locomotor activity patterns in Drosophila suzukii by the circadian clock, light, temperature and social interactions. J. Biol. Rhythms 34, 463–481 (2019).CAS 
PubMed 
Article 

Google Scholar 
Chiesa, J. J., Aguzzi, J., García, J. A., Sardà, F. & de la Iglesia, H. O. Light intensity determines temporal niche switching of behavioral activity in deep-water Nephrops norvegicus (Crustacea: Decapoda). J. Biol. Rhythms 25, 277–287 (2010).PubMed 
Article 

Google Scholar 
DeCoursey, P. J. Light-sampling behavior in photoentrainment of a rodent circadian rhythm. J. Comp. Physiol. 159, 161–169 (1986).CAS 
Article 

Google Scholar 
Heard, E. Molecular biologists: let’s reconnect with nature. Nature 601, 9 (2022).CAS 
PubMed 
Article 

Google Scholar 
Deines, K. L. Backscatter estimation using Broadband acoustic Doppler current profilers. In Proc. IEEE Sixth Working Conference on Current Measurement 249–253 (1999).Darnis, G. et al. From polar night to midnight sun: diel vertical migration, metabolism and biogeochemical role of zooplankton in a high Arctic fjord (Kongsfjorden, Svalbard). Limnol. Oceanogr. 62, 1586–1605 (2017).CAS 
Article 

Google Scholar 
Cottier, F. R., Tarling, G. A., Wold, A. & Falk-Petersen, S. Unsynchronized and synchronized vertical migration of zooplankton in a high arctic fjord. Limnol. Oceanogr. 51, 2586–2599 (2006).Article 

Google Scholar 
Johnsen, G. et al. All-sky camera system providing high temporal resolution annual time series of irradiance in the Arctic. Appl. Opt. 60, 6456–6468 (2021).PubMed 
Article 

Google Scholar 
Pan, X. & Zimmerman, R. C. Modeling the vertical distributions of downwelling plane irradiance and diffuse attenuation coefficient in optically deep waters. J. Geophys. Res.: Oceans 115, C08016 (2010).
Google Scholar 
Hersbach, H. et al. The ERA5 global reanalysis. Q. J. R. Meteorol. Soc. 146, 1999–2049 (2020).Article 

Google Scholar 
Tidau, S. et al. Marine artificial light at night: An empirical and technical guide. Methods Ecol. Evol. 12, 1588–1601 (2021).Article 

Google Scholar 
Mobley, C. D. Light and Water: Radiative Transfer in Natural Waters (Academic Press Inc, 1994).Kostakis, I. et al. Development of a bio-optical model for the Barents Sea to quantitatively link glider and satellite observations. Philos. Trans. R. Soc. A: Math., Phys. Eng. Sci. 378, 20190367 (2020).CAS 
Article 

Google Scholar 
Buskey, E. J., Baker, K. S., Smith, R. C. & Swift, E. Photosensitivity of the oceanic copepods Pleuromamma gracilis and Pleuromamma xiphias and its relationship to light penetration and daytime depth distribution. Mar. Ecol. Prog. Ser. 55, 207–216 (1989).Article 

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Model structureWe used the PoPS (Pest or Pathogen Spread) Forecasting System11 version 2.0.0 to simulate the spread of SLF and calibrated the model (Fig. 6) using Approximate Bayesian Computation (ABC) with sequential Markov chain and a multivariate normal perturbation kernel18,19. We simulated the reproduction and dispersal of SLF groups (at the grid cell level) rather than individuals, as exact measures of SLF populations are not the goal of surveys conducted by USDA and state departments of agriculture. Reproduction was simulated as a Poisson process with mean β that is modified by local conditions. For example, if we have 5 SLF groups in a cell, a β value of 2.2, and a temperature coefficient of 0.7, our modified β value becomes 1.54 and we draw five numbers from a Poisson distribution with a λ value of 1.54. β and dispersal parameters were calibrated to fit the observed patterns of spread. For this application of PoPS, we replaced the long-distance kernel (α2) with a network dispersal kernel based on railroads, along which SLF and tree of heaven are commonly observed7. For each SLF group dispersing, if a railroad is in the grid cell with SLF, we used a Bernoulli distribution with mean of γ (probability of natural dispersal) to determine if an SLF group dispersed via the natural Cauchy kernel with scale (α) or along the rail network. This network dispersal kernel accounts for dispersal along railways if SLF is present in a cell containing a rail line. The network dispersal kernel added three new parameters to the PoPS model: a network file that contained the nodes and edges, minimum distance that each railcar travels, and the maximum distance that each railcar travels. Unlike typical network models, which simulate transport simply between nodes, our approach allows for SLF to disembark a railcar at any point along an edge, more closely mimicking their actual behavior. This network therefore captures the main pathway of SLF long-distance dispersal, i.e., along railways.Fig. 6: Model structure for spotted lanternfly (SLF, Lycorma delicatula).Unused modules in the PoPS model are gray in the equation. a The number of pests that disperse from a single host under optimal environmental conditions (β) is modified by the number of currently infested hosts (I) and environmental conditions in a location (i) at a particular time (t); environmental conditions include seasonality (X) and temperature (T) (see supplementary Fig. 3 for details on temperature). Dispersal is a function of gamma (γ), which is the probability of short-distance dispersal (alpha-1, α1) or long-distance via the rail network (N (dmin, dmax)). For the natural-distance Cauchy kernel, the direction is selected using 0-359 with 0 representing North. For the network kernel, the direction along the rail is selected randomly, and then travel continues in that direction until the drawn distance is reached. Once SLF has landed in a new location, its establishment depends on environmental conditions (X, T) and the availability of suitable hosts (number of susceptible hosts [S] divided by total number of potential hosts [N]). b We used a custom host map for tree of heaven (Ailanthus altissima) to determine the locations of susceptible hosts. The number of newly infested hosts (ψ) is predicted for each cell across the contiguous US.Full size imageSpotted lanternfly model calibrationWe used 2015–2019 data (over 300,000 total observations including both positive and negative surveys) provided by the USDA APHIS and the state Departments of Agriculture of Pennsylvania, New Jersey, Delaware, Maryland, Virginia, and West Virginia to calibrate model parameters (β, α1, γ, dmin, dmax). The calibration process starts by drawing a set of parameters from a uniform distribution. Simulated results for each model run are then compared to observed data within the year they were collected, and accuracy, precision, recall, and specificity are calculated for the simulation period. If each of these statistics is above 65% the parameter set is kept. This process repeats until 10,000 parameter sets are kept; then, the next generation of the ABC process begins: the mean of each accuracy statistic becomes the new accuracy threshold, and parameters are drawn from a multivariate normal distribution based on the means and covariance matrix of the first 10,000 kept parameters. This process repeats for a total of seven generations. Compared to the 2020 and 2021 observation data (over 100,000 total observations including both positive and negative surveys), the model performed well, with an accuracy of 84.4%, precision of 79.7%, recall of 91.55%, and specificity of 77.6%. In contrast, a model run using PoPS’ previous long-distance kernel (α2) instead of the network dispersal kernel had an accuracy of 76.5%, precision of 68.1%, recall of 92.68%, and specificity of 57.2%.We applied the calibrated parameters and their uncertainties (Fig. 7) to forecast the future spread of SLF, using the status of the infestation as of January 1, 2020 as a starting point and data for temperature and the distribution of SLF’s presumed primary host (tree of heaven, Ailanthus altissima) for the contiguous US at a spatial resolution of 5 km.Fig. 7: Parameter distributions.a Reproductive rate (β), b natural dispersal distance (α1), c percent natural dispersal (γ), d minimum distance (dmin), e maximum distance (dmax).Full size imageWeather dataOverwinter survival of SLF egg masses, and therefore spread, is sensitive to temperature (see ref. 2). To run a spread model in PoPS, all raw temperature values are first converted to indices ranging 0–1 to describe their impact on a species’ ability to survive and reproduce. We converted daily Daymet20 temperature into a monthly coefficient ranging 0–1 (Supplementary Fig. 1) and then rescaled from 1 to 5 km by averaging 1-km pixel values. We used weather data 1980–2019 and randomly drew from those historical data to simulate future weather conditions in our simulations, to account for uncertainty in future weather conditions.Tree of heaven distribution mappingSLF is known to feed on >70 species of mainly woody plants7, but tree of heaven is commonly viewed as necessary, or at least highly important, for SLF spread. Young nymphs are host generalists, but older nymphs and adults strongly prefer tree of heaven (in Korea21; in Pennsylvania, US22), and experiments in captivity23 and in situ9 have shown that adult survivorship is higher on the tree of heaven and grapevine than other host plants, likely due to the presence and proportion of sugar compounds important for SLF survival23. Secondary compounds found in tree of heaven also make adult SLF more unpalatable to avian predators24, and researchers have hypothesized that these protective compounds may be passed on to eggs21. For these reasons, tree of heaven is widely considered the primary host for SLF and linked to SLF spread1,25.We, therefore, used tree of heaven as the host in our spread forecast. We estimated the geographic range of tree of heaven using the Maximum Entropy (MaxEnt) model26,27. We chose to use niche modeling because tree of heaven has been in the US for over 200 years and is well past the early stage of invasion at which niche models perform poorly; instead, tree of heaven is well into the intermediate to equilibrium stage of invasion, when niche models perform well28. We obtained 19,282 presences for tree of heaven in the US from BIEN29,30 and EDDmaps31 and selected the most important variables from an initial MaxEnt model of all 19 WorldClim bioclimatic variables32. Our final climate variables were mean annual temperature, precipitation of the coldest quarter, and precipitation of the driest quarter. Given that tree of heaven is non-native and invasive in the US, prefers open and disturbed habitat, and is commonly found along roadsides and in urban landscapes33, we also included distance to major roads and railroads as an additional variable in our model, to account for the presence of disturbed habitat as well as approximate urbanization and anthropogenic degradation. For each 1-km cell in the extent, we calculated distance to the nearest road and nearest railroad using the US Census Bureau’s TIGER data set of primary roads and railroads34. We used our final MaxEnt model to generate the probability of the presence of tree of heaven for each 1-km cell, then reset all cells with a probability ≤0.2 to a value of 0 to minimize overprediction of the tree of heaven locations (because cells ≤0.2 contained less than 1% of the presences used to build the model). We rescaled the remaining probability values 0–1. We used 10% of the tree of heaven presence data to validate the model, which performed well: 95% of the validation data set locations had a probability of presence greater than 65%. We then rescaled the 1-km MaxEnt output to 5 km using the mean value of our 1-km cells, in order to reduce computational time.Forecasting spotted lanternflyWe used the Daymet temperature data and distribution of tree of heaven to simulate SLF spread with PoPS, assuming no further efforts to contain or eradicate either tree of heaven or SLF. We ran the spread simulation 10,000 times from 2020 to 2050 for the contiguous US. After running all 10,000 iterations, we created a probability of occurrence for each cell for each year by dividing the number of simulations in which a cell was simulated as being infested in that year by 10,000 (the total number of simulations). This gave us a probability of occurrence per year. We downscaled our probability of occurrence per year from 5 km to 1 km and set the probability to 0 in 1-km pixels with no tree of heaven occurrence.Data for mapping and comparisonWe compared our probability of occurrence map in 2050 to the SLF suitability map created by Wakie et al.1 using niche modeling to see how well the two modeling approaches would agree if SLF were allowed to spread unmanaged (Fig. 5). Wakie et al.1 categorized pixels below 8.359% as unsuitable, between 8.359% and 26.89% as low risk, between 26.89% and 51.99% as medium risk, and above 51.99% as high risk. To facilitate comparison, we used this same schema to categorize pixels as low, medium, or high probability of spread.We converted the yearly raster probability maps to county-level probabilities in order to examine the yearly risk to crops in counties. We performed this conversion using two methods: (1) the highest probability of occurrence in the county (Supplementary Movie 2) and (2) the mean probability of occurrence in the county (Fig. 1 and Supplementary Movie 1). The first method provides a simple, non-statistical estimate of the probability of SLF presence by assigning the county the value of the highest cell-level probability; the second accounts for all of the probabilities of the cells in the county and typically results in a higher county-level probability. We used USDA county-level production data10 for grapes, almonds, apples, walnuts, cherries, hops, peaches, plums, and apricots to determine the amount of production at risk each year (Fig. 2).Reporting summaryFurther information on research design is available in the Nature Research Reporting Summary linked to this article. More

Montzka SA, Dlugokencky EJ, Butler JH. Non-CO2 greenhouse gases and climate change. Nature 2011;476:43–50.CAS 
PubMed 
Article 

Google Scholar 
Masson-Delmotte V, Zhai P, Pirani A, Connors SL, Péan C, Berger S, et al. (eds). 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: Cambridge University Press; 2021. (in press).Wuebbles DJ. Nitrous oxide: no laughing matter. Science. 2009;326:56–7.CAS 
PubMed 
Article 

Google Scholar 
Kool DM, Dolfing J, Wrage N, van Groenigen JW. Nitrifier denitrification as a distinct and significant source of nitrous oxide from soil. Soil Biol Biochem. 2011;43:174–8.CAS 
Article 

Google Scholar 
Yoon S, Song B, Phillips RL, Chang J, Song MJ. Ecological and physiological implications of nitrogen oxide reduction pathways on greenhouse gas emissions in agroecosystems. FEMS Microbiol Ecol. 2019;95:fiz066.CAS 
PubMed 
Article 

Google Scholar 
Sanford RA, Wagner DD, Wu Q, Chee-Sanford JC, Thomas SH, Cruz-García C, et al. Unexpected nondenitrifier nitrous oxide reductase gene diversity and abundance in soils. Proc Natl Acad Sci USA. 2012;109:19709–14.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Hallin S, Philippot L, Löffler FE, Sanford RA, Jones CM. Genomics and ecology of novel N2O-reducing microorganisms. Trends Microbiol. 2018;26:43–55.CAS 
PubMed 
Article 

Google Scholar 
Graf DR, Jones CM, Hallin S. Intergenomic comparisons highlight modularity of the denitrification pathway and underpin the importance of community structure for N2O emissions. PLoS One. 2014;9:e114118.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Roco CA, Bergaust LL, Bakken LR, Yavitt JB, Shapleigh JP. Modularity of nitrogen‐oxide reducing soil bacteria: linking phenotype to genotype. Environ Microbiol. 2017;19:2507–19.CAS 
PubMed 
Article 

Google Scholar 
Jones CM, Graf DR, Bru D, Philippot L, Hallin S. The unaccounted yet abundant nitrous oxide-reducing microbial community: A potential nitrous oxide sink. ISME J. 2013;7:417–26.CAS 
PubMed 
Article 

Google Scholar 
Frostegård Å, Vick SH, Lim NY, Bakken LR, Shapleigh JP. Linking meta-omics to the kinetics of denitrification intermediates reveals pH-dependent causes of N2O emissions and nitrite accumulation in soil. ISME J. 2022;16:26–37.PubMed 
Article 
CAS 

Google Scholar 
Simon J, Einsle O, Kroneck PMH, Zumft WG. The unprecedented nos gene cluster of Wolinella succinogenes encodes a novel respiratory electron transfer pathway to cytochrome c nitrous oxide reductase. FEBS Lett. 2004;569:7–12.CAS 
PubMed 
Article 

Google Scholar 
Foley J, De Haas D, Yuan Z, Lant P. Nitrous oxide generation in full-scale biological nutrient removal wastewater treatment plants. Water Res. 2010;44:831–44.CAS 
PubMed 
Article 

Google Scholar 
Zheng J, Doskey PV. Simulated rainfall on agricultural soil reveals enzymatic regulation of short-term nitrous oxide profiles in soil gas and emissions from the surface. Biogeochemistry. 2016;128:327–38.CAS 
Article 

Google Scholar 
Kern M, Simon J. Three transcription regulators of the Nss family mediate the adaptive response induced by nitrate, nitric oxide or nitrous oxide in Wolinella succinogenes. Environ Microbiol. 2016;18:2899–912.CAS 
PubMed 
Article 

Google Scholar 
Suenaga T, Riya S, Hosomi M, Terada A. Biokinetic characterization and activities of N2O-reducing bacteria in response to various oxygen levels. Front Microbiol. 2018;9:697.PubMed 
PubMed Central 
Article 

Google Scholar 
Kim DD, Park D, Yoon H, Yun T, Song MJ, Yoon S. Quantification of nosZ genes and transcripts in activated sludge microbiomes with novel group-specific qPCR methods validated with metagenomic analyses. Water Res. 2020;185:116261.CAS 
PubMed 
Article 

Google Scholar 
Yoon S, Nissen S, Park D, Sanford RA, Löffler FE. Nitrous oxide reduction kinetics distinguish bacteria harboring clade I NosZ from those harboring clade II NosZ. Appl Environ Microbiol. 2016;82:3793–800.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Yoon H, Song MJ, Kim DD, Sabba F, Yoon S. A serial biofiltration system for effective removal of low-concentration nitrous oxide in oxic gas streams: mathematical modeling of reactor performance and experimental validation. Environ Sci Technol. 2019;53:2063–74.CAS 
PubMed 
Article 

Google Scholar 
Suenaga T, Hori T, Riya S, Hosomi M, Smets BF, Terada A. Enrichment, isolation, and characterization of high-affinity N2O-reducing bacteria in a gas-permeable membrane reactor. Environ Sci Technol. 2019;53:12101–12.CAS 
PubMed 
Article 

Google Scholar 
Conthe M, Wittorf L, Kuenen JG, Kleerebezem R, van Loosdrecht MC, Hallin S. Life on N2O: Deciphering the ecophysiology of N2O respiring bacterial communities in a continuous culture. ISME J. 2018;12:1142–53.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Henry S, Bru D, Stres B, Hallet S, Philippot L. Quantitative detection of the nosZ gene, encoding nitrous oxide reductase, and comparison of the abundances of 16S rRNA, narG, nirK, and nosZ genes in soils. Appl Environ Microbiol. 2006;72:5181–9.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Qi C, Zhou Y, Suenaga T, Oba K, Lu J, Wang G, et al. Organic carbon determines nitrous oxide consumption activity of clade I and II nosZ bacteria: Genomic and biokinetic insights. Water Res. 2022;209:117910.CAS 
Article 

Google Scholar 
Gao Y, Mania D, Mousavi SA, Lycus P, Arntzen MØ, Woliy K, et al. Competition for electrons favours N2O reduction in denitrifying Bradyrhizobium isolates. Environ Microbiol. 2021;23:2244–59.CAS 
PubMed 
Article 

Google Scholar 
Song MJ, Choi S, Bae WB, Lee J, Han H, Kim DD, et al. Identification of primary effecters of N2O emissions from full-scale biological nitrogen removal systems using random forest approach. Water Res. 2020;184:116144.CAS 
PubMed 
Article 

Google Scholar 
Ahn JH, Kim S, Park H, Rahm B, Pagilla K, Chandran K. N2O emissions from activated sludge processes, 2008−2009: results of a national monitoring survey in the United States. Environ Sci Technol. 2010;44:4505–11.CAS 
PubMed 
Article 

Google Scholar 
Bollmann A, Conrad R. Influence of O2 availability on NO and N2O release by nitrification and denitrification in soils. Glob Chang Biol 1998;4:387–96.Article 

Google Scholar 
Morris RL, Schmidt TM. Shallow breathing: Bacterial life at low O2. Nat Rev Microbiol. 2013;11:205–12.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Marchant HK, Ahmerkamp S, Lavik G, Tegetmeyer HE, Graf J, Klatt JM, et al. Denitrifying community in coastal sediments performs aerobic and anaerobic respiration simultaneously. ISME J. 2017;11:1799–812.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Camejo PY, Oyserman BO, McMahon KD, Noguera DR. Integrated omic analyses provide evidence that a “Candidatus Accumulibacter phosphatis” strain performs denitrification under microaerobic conditions. mSystems. 2019;4:e00193–18.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Yoon S, Sanford RA, Löffler FE. Shewanella spp. use acetate as an electron donor for denitrification but not ferric iron or fumarate reduction. Appl Environ Microbiol. 2013;79:2818–22.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
van den Berg EM, Boleij M, Kuenen JG, Kleerebezem R, van Loosdrecht M. DNRA and denitrification coexist over a broad range of acetate/N-NO3− ratios, in a chemostat enrichment culture. Front Microbiol. 2016;7:1842.PubMed 
PubMed Central 
Article 

Google Scholar 
Sander R. Compilation of Henry’s law constants (version 4.0) for water as solvent. Atmos Chem Phys. 2015;15:4399–981.CAS 
Article 

Google Scholar 
Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME2. Nat Biotechnol. 2019;37:852–7.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Binder BJ, Liu YC. Growth rate regulation of rRNA content of a marine Synechococcus (cyanobacterium) strain. Appl Environ Microbiol. 1998;64:3346–51.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Shrestha PM, Rotaru AE, Aklujkar M, Liu F, Shrestha M, Summers ZM, et al. Syntrophic growth with direct interspecies electron transfer as the primary mechanism for energy exchange. Environ Microbiol Rep. 2013;5:904–10.CAS 
PubMed 
Article 

Google Scholar 
Ritalahti KM, Amos BK, Sung Y, Wu Q, Koenigsberg SS, Löffler FE. Quantitative PCR targeting 16S rRNA and reductive dehalogenase genes simultaneously monitors multiple Dehalococcoides strains. Appl Environ Microbiol. 2006;72:2765–74.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Bolger AM, Lohse M, Usadel B. Trimmomatic: A flexible trimmer for Illumina sequence data. Bioinformatics 2014;30:2114–20.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Nurk S, Meleshko D, Korobeynikov A, Pevzner PA. metaSPAdes: A new versatile metagenomic assembler. Genome Res. 2017;27:824–34.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Hyatt D, Chen G-L, LoCascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: Prokaryotic gene recognition and translation initiation site identification. BMC Bioinform. 2010;11:1–11.Article 
CAS 

Google Scholar 
Buchfink B, Reuter K, Drost H-G. Sensitive protein alignments at tree-of-life scale using DIAMOND. Nat Methods. 2021;18:366–8.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Kanehisa M, Sato Y, Morishima K. BlastKOALA and GhostKOALA: KEGG tools for functional characterization of genome and metagenome sequences. J Mol Biol. 2016;428:726–31.CAS 
PubMed 
Article 

Google Scholar 
Edgar RC. MUSCLE: Multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004;32:1792–97.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Stamatakis A. RAxML version 8: A tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 2014;30:1312–13.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Huang Y, Gilna P, Li W. Identification of ribosomal RNA genes in metagenomic fragments. Bioinformatics 2009;25:1338–40.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Miller CS, Baker BJ, Thomas BC, Singer SW, Banfield JF. EMIRGE: reconstruction of full-length ribosomal genes from microbial community short read sequencing data. Genome Biol. 2011;12:R44.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, et al. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 2012;41:D590–6.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Wang Q, Garrity GM, Tiedje JM, Cole JR. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol. 2007;73:5261–7.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Li H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. Preprint arXiv:13033997. 2013.Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The sequence alignment/map format and SAMtools. Bioinformatics 2009;25:2078–9.PubMed 
PubMed Central 

Google Scholar 
Quinlan AR, Hall IM. BEDTools: A flexible suite of utilities for comparing genomic features. Bioinformatics 2010;26:841–2.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Nayfach S, Pollard KS. Toward accurate and quantitative comparative metagenomics. Cell 2016;166:1103–16.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinform. 2011;12:1–16.Article 

Google Scholar 
Li D, Liu C-M, Luo R, Sadakane K, Lam T-W. MEGAHIT: An ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics 2015;31:1674–6.CAS 
PubMed 
Article 

Google Scholar 
Kang DD, Froula J, Egan R, Wang Z. MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities. PeerJ 2015;3:e1165.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Parks DH, Rinke C, Chuvochina M, Chaumeil P-A, Woodcroft BJ, Evans PN, et al. Recovery of nearly 8,000 metagenome-assembled genomes substantially expands the tree of life. Nat Microbiol 2017;2:1533–42.CAS 
PubMed 
Article 

Google Scholar 
Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 2015;25:1043–55.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Olm MR, Brown CT, Brooks B, Banfield JF. dRep: A tool for fast and accurate genomic comparisons that enables improved genome recovery from metagenomes through de-replication. ISME J. 2017;11:2864–8.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Rodriguez-R LM, Gunturu S, Harvey WT, Rosselló-Mora R, Tiedje JM, Cole JR, et al. The Microbial Genomes Atlas (MiGA) webserver: taxonomic and gene diversity analysis of Archaea and Bacteria at the whole genome level. Nucleic Acids Res. 2018;46:W282–8.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Darling AE, Jospin G, Lowe E, Matsen FA IV, Bik HM, Eisen JA. PhyloSift: Phylogenetic analysis of genomes and metagenomes. PeerJ. 2014;2:e243.PubMed 
PubMed Central 
Article 

Google Scholar 
Talavera G, Castresana J. Improvement of phylogenies after removing divergent and ambiguously aligned blocks from protein sequence alignments. Syst Biol. 2007;56:564–77.CAS 
PubMed 
Article 

Google Scholar 
Salazar G, Paoli L, Alberti A, Huerta-Cepas J, Ruscheweyh H-J, Cuenca M, et al. Gene expression changes and community turnover differentially shape the global ocean metatranscriptome. Cell 2019;179:1068–83.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Milanese A, Mende DR, Paoli L, Salazar G, Ruscheweyh H-J, Cuenca M, et al. Microbial abundance, activity and population genomic profiling with mOTUs2. Nat Commun. 2019;10:1014.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Sunagawa S, Mende DR, Zeller G, Izquierdo-Carrasco F, Berger SA, Kultima JR, et al. Metagenomic species profiling using universal phylogenetic marker genes. Nat Methods. 2013;10:1196–9.CAS 
PubMed 
Article 

Google Scholar 
Yap CX, Henders AK, Alvares GA, Wood DL, Krause L, Tyson GW, et al. Autism-related dietary preferences mediate autism-gut microbiome associations. Cell 2021;184:5916–31.CAS 
PubMed 
Article 

Google Scholar 
Shan J, Sanford RA, Chee‐Sanford J, Ooi SK, Löffler FE, Konstantinidis KT, et al. Beyond denitrification: the role of microbial diversity in controlling nitrous oxide reduction and soil nitrous oxide emissions. Glob Chang Biol. 2021;27:2669–83.PubMed 
Article 

Google Scholar 
Jones CM, Spor A, Brennan FP, Breuil M-C, Bru D, Lemanceau P, et al. Recently identified microbial guild mediates soil N2O sink capacity. Nat Clim Chang. 2014;4:801–5.Kim J, Kim DD, Yoon S. Rapid isolation of fast-growing methanotrophs from environmental samples using continuous cultivation with gradually increased dilution rates. Appl Microbiol Biotechnol. 2018;102:5707–15.CAS 
PubMed 
Article 

Google Scholar 
Betlach MR, Tiedje JM. Kinetic explanation for accumulation of nitrite, nitric oxide, and nitrous oxide during bacterial denitrification. Appl Environ Microbiol. 1981;42:1074–84.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Bueno E, Mesa S, Bedmar EJ, Richardson DJ, Delgado MJ. Bacterial adaptation of respiration from oxic to microoxic and anoxic conditions: Redox control. Antioxid Redox Signal. 2012;16:819–52.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Rauhamäki V, Bloch DA, Wikström M. Mechanistic stoichiometry of proton translocation by cytochrome cbb3. Proc Natl Acad Sci USA. 2012;109:7286–91.PubMed 
PubMed Central 
Article 

Google Scholar 
Borisov VB, Gennis RB, Hemp J, Verkhovsky MI. The cytochrome bd respiratory oxygen reductases. Biochim Biophys Acta – Bioenerg. 2011;1807:1398–413.CAS 
Article 

Google Scholar 
Lee A, Winther M, Priemé A, Blunier T, Christensen S. Hot spots of N2O emission move with the seasonally mobile oxic-anoxic interface in drained organic soils. Soil Biol Biochem. 2017;115:178–86.CAS 
Article 

Google Scholar 
Orellana L, Rodriguez-R L, Higgins S, Chee-Sanford J, Sanford R, Ritalahti K, et al. Detecting nitrous oxide reductase (nosZ) genes in soil metagenomes: method development and implications for the nitrogen cycle. MBio 2014;5:e01193–14.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Ormeño-Orrillo E, Martínez-Romero E. A genomotaxonomy view of the Bradyrhizobium genus. Front Microbiol. 2019;10:1334.PubMed 
PubMed Central 
Article 

Google Scholar 
Tong W, Li X, Wang E, Cao Y, Chen W, Tao S, et al. Genomic insight into the origins and evolution of symbiosis genes in Phaseolus vulgaris microsymbionts. BMC Genom. 2020;21:186.CAS 
Article 

Google Scholar 
Conthe M, Lycus P, Arntzen MØ, da Silva AR, Frostegård Å, Bakken LR, et al. Denitrification as an N2O sink. Water Res. 2019;151:381–7.CAS 
PubMed 
Article 

Google Scholar 
Goldblatt C, Lenton TM, Watson AJ. Bistability of atmospheric oxygen and the Great Oxidation. Nature. 2006;443:683–6.CAS 
PubMed 
Article 

Google Scholar 
Brewer PG, Hofmann AF, Peltzer ET, Ussler W III. Evaluating microbial chemical choices: The ocean chemistry basis for the competition between use of O2 or NO3− as an electron acceptor. Deep Sea Res Part I Oceanogr Res Pap. 2014;87:35–42.CAS 
Article 

Google Scholar 
Bianchi D, Dunne JP, Sarmiento JL, Galbraith ED. Data‐based estimates of suboxia, denitrification, and N2O production in the ocean and their sensitivities to dissolved O2. Global Biogeochem Cycles 2012;26:GB2009.Stolper DA, Revsbech NP, Canfield DE. Aerobic growth at nanomolar oxygen concentrations. Proc Natl Acad Sci USA. 2010;107:18755–60.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Zakem E, Follows M. A theoretical basis for a nanomolar critical oxygen concentration. Limnol Oceanogr. 2017;62:795–805.Article 

Google Scholar 
Liengaard L, Nielsen LP, Revsbech NP, Priemé A, Elberling B, Enrich-Prast A, et al. Extreme emission of N2O from tropical wetland soil (Pantanal, South America). Front Microbiol. 2013;3:433.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Shcherbak I, Robertson GP. Nitrous oxide (N2O) emissions from subsurface soils of agricultural ecosystems. Ecosystems. 2019;22:1650–63.CAS 
Article 

Google Scholar 
Qu Z, Bakken LR, Molstad L, Frostegård Å, Bergaust LL. Transcriptional and metabolic regulation of denitrification in Paracoccus denitrificans allows low but significant activity of nitrous oxide reductase under oxic conditions. Environ Microbiol. 2016;18:2951–63.CAS 
PubMed 
Article 

Google Scholar 
Desloover J, Roobroeck D, Heylen K, Puig S, Boeckx P, Verstraete W, et al. Pathway of nitrous oxide consumption in isolated Pseudomonas stutzeri strains under anoxic and oxic conditions. Environ Microbiol. 2014;16:3143–52.CAS 
PubMed 
Article 

Google Scholar  More

Controlled fires can be used to reduce the risk of wildfires.Credit: David Hoffmann/Alamy

Indigenous oral accounts have helped scientists to reconstruct a 3,000-year history of a large fire-prone forest in California. The results suggest that parts of the forest are denser than ever before, and are at risk of severe wildfires1. The research is part of a growing effort to combine Indigenous knowledge with other scientific data to improve understanding of ecosystem histories.Wildfires are a substantial threat to Californian forests. Clarke Knight, a palaeo-ecosystem scientist at the US Geological Survey in Menlo Park, California, and her colleagues wanted to understand how Indigenous communities helped shape the forest by managing this risk in the state’s lush western Klamath Mountains. Specifically, they studied Indigenous peoples’ use of cultural burning — small, controlled fires that keep biomass low and reduce the risk of more widespread burning. The results are published in the Proceedings of the National Academy of Science.“When I was a little kid, my grandmother used to burn around the house,” says Rod Mendes, fire chief for the Yurok Tribe fire department, whose family is part of the Karuk Tribe of northern California. The Karuk and Yurok tribes have called the Klamath Mountains home for thousands of years. “She was just keeping the place clean. Native people probably did some of the first prescribed fire operations in history,” says Mendes.Understanding how Indigenous tribes used fire is essential for managing forests to reduce wildfire risk, says Knight. “We need to listen to Native people and learn and understand why they managed the landscape the way they did,” adds Mendes.Collaboration for corroborationTo map the region’s forest history, the team drew on historical accounts and oral histories from Karuk, Yurok and Hoopa Valley Tribe members collected by study co-author Frank Lake, a US Forest Service research ecologist in Arcata, California, and a Karuk descendant, as part of his PhD thesis in 2007. These accounts described the tribes’ fire and land use. For instance, members lit small fires to keep trails clear; this also reduced the amount of vegetation, preventing expansion of wildfires from lightning strikes. Larger fires, called broadcast burning, were used to improve visibility, hunting and nut-harvesting conditions in the forest. The effects of fire on the vegetation lasted for decades.Knight says that it was important to collaborate with the tribes given their knowledge of the region. The Karuk Resources Advisory Board approved a proposal for the study before it began. “In a way, it’s decolonizing the existing academic model that hasn’t been very inclusive of Indigenous histories,” says Lake.The researchers also analysed sediment cores collected near two low-elevation lakes in the Klamath Mountains that are culturally important to the tribes. Layers of pollen in the cores were used to infer the approximate tree density in the area at various times, and modelling helped date the cores so they could estimate how that density changed.The team also measured charcoal in the cores’ layers, which helped to map fluctuations in the amount of fire in the region. Burn scars on tree stumps pointed to specific instances of fire in between 1700-1900. Because the stumps’ rings serve as an ecological calendar, the researchers were able to compare periods of fire with corresponding tree-density data. They then pieced together how this density fluctuated with fire incidence. Although these empirical methods could not specifically confirm that the fires were lit by the tribes, patterns suggested when this was more probable, says Knight. For instance, increased burning in cool, wet periods, when fires caused by lightning were probably less common, suggested a human influence.Combining multiple lines of evidence, Knight and her team show that the tree density in this region of Klamath Mountains started to increase as the area was colonized, partly because the European settlers prevented Indigenous peoples from practising cultural burning. In the twentieth century, total fire suppression became a standard management practice, and fires of any kind were extinguished or prevented — although controlled burns are currently used in forest management. The team reports that in some areas, the tree density is higher than it has been for thousands of years, owing in part to fire suppression.Healthy forestA dense forest isn’t necessarily a healthy one, says Knight. The Douglas-fir, which dominate the low-land Klamath forests, are less fire resilient and more prone to calamitous wildfires. “This idea that we simply should let nature take its course is just not supported by this work,” she says. She adds that one of the study’s strengths is the multiple lines of evidence showing that past Indigenous burning helped to manage tree density.Fire ecologist Jeffrey Kane at the California State Polytechnic University Humboldt in Arcata says that the study’s findings of increased tree density are not surprising. He has made similar observations in the Klamath region. “There’s a lot more trees than were there just 120 years ago,” he says.Dominick DellaSala, chief scientist at forest-protection organization Wild Heritage in Talent, Oregon, points out that the results suggesting record tree densities cannot be applied to the entire Klamath region, owing to the limited range of the study’s lakeside data.Knight, however, says that the results can be extrapolated to other similar low-elevation lake sites that have similar vegetation types.More Indigenous voicesPalaeoecology studies are increasingly incorporating Indigenous knowledge — but there’s still a long way to go, says physical geographer Michela Mariani at the University of Nottingham, UK. In Australia, Mariani has also found that tree density began to increase after British colonization hampered cultural burning. “It’s very important that we now include Indigenous people in the discussion in fire management moving on,” Mariani says. “They have a deeper knowledge of the landscape we simply don’t have.”Including Indigenous voices in research is also crucial for decolonizing conventional scientific methods, Lake emphasizes. It “becomes a form of justice for those Indigenous people who have long been excluded, marginalized and not acknowledged”, he says. More

Gibbs, J. P. Wetland loss and biodiversity conservation. Conserv. Biol. 14, 314–317 (2000).Article 

Google Scholar 
Turner, R. K. et al. Ecological-economic analysis of wetlands: Scientific integration for management and policy. Ecol. Econ. 35, 7–23 (2000).Article 

Google Scholar 
Zedler, J. B. & Kercher, S. Wetland resources: Status trends ecosystem services and restorability. Annu. Rev. Environ. Resour. 15, 39–74 (2005).Article 

Google Scholar 
Euliss, N. H., Smith, L. M., Wilcox, D. A. & Browne, B. A. Lining ecosystem processes with wetland management goals: Chartering a course for a sustainable future. Wetlands 28, 553–562 (2008).Article 

Google Scholar 
Costanza, R. et al. Changes in the global value of ecosystem services. Glob. Environ. Change. 26, 152–158 (2014).Article 

Google Scholar 
Macreadie, P. J. et al. The future of blue carbon. Nat. Commun. 10, 3998 (2019).ADS 
Article 

Google Scholar 
RAMSAR. Wise use of wetlands, Ramsar Handbooks, 4th edition (2010).Kingsford, R. T., Basset, A. & Jackson, L. Wetlands: Conservation’s poor cousins. Aquat. Conserv. 26, 892–916 (2016).Article 

Google Scholar 
Beck, M. W., Heck, K. L. & Able, K. W. The Identification, Conservation, and Management of Estuarine and Marine Nurseries for Fish and Invertebrates: A better understanding of the habitats that serve as nurseries for marine species and the factors that create site-specific variability in nursery quality will improve conservation and management of these areas. Bioscience 51, 633–641 (2001).Article 

Google Scholar 
Canu, D. M. et al. Adressing sustainability of clam farming in the Venice Lagoon. Ecol. Soc. 16, 26 (2010).
Google Scholar 
Canu, D. M., Solidoro, C., Cossarini, G. & Giorgi, F. Effect of global change on bivalve rearing activity and the need for adaptive management. Clim. Res. 42, 13–26 (2011).Article 

Google Scholar 
Newton, A. et al. Anthropogenic pressures on Coastal Wetlands. Front. Ecol. Evol. 8, 144 (2020).Article 

Google Scholar 
Ayache, F. et al. Environmental characteristics landscape history and pressures on three coastal lagoons in the Southern Mediterranean Region: Merja Zerga (Morocco) Ghar El Melh (Tunisia) and Lake Manzala (Egypt). Hydrobiologia 622, 15–43 (2009).CAS 
Article 

Google Scholar 
Solidoro, C. et al. Response of Venice Lagoon ecosystem to natural and anthropogenic pressures over the last 50 years. In Coastal Lagoons—Critical Habitats of Environmental Change (eds. Kennish, M. J. & Paerl, H. W.) 483–511 (2010).Newton, A. et al. Assessing quantifying and valuing the ecosystem services of coastal lagoons. J. Nat. Conserv. 44, 50–65 (2018).Article 

Google Scholar 
Newton, A. et al. An overview of ecological status vulnerability and future perspectives of European large shallow semi-enclosed coastal systems lagoons and transitional waters. Estuar. Coast. Shelf Sci. 140, 95–122 (2014).ADS 
Article 

Google Scholar 
Béjaoui, B. et al. Random Forest model and TRIX used in combination to assess and diagnose the trophic status of Bizerte Lagoon, southern Mediterranean. Ecol. Indic. 71, 293–301 (2016).Article 

Google Scholar 
Ramdani, M. et al. North African wetland lakes: Characterization of nine sites included in the CASSARINA Project. Aquat. Ecol. 35, 281–302 (2001).Article 

Google Scholar 
Junk, W. J. et al. Current state of knowledge regarding the world’s wetlands and their future under global climate change: A synthesis. Aquat. Sci. 75, 151–167 (2013).CAS 
Article 

Google Scholar 
Ouni, H. et al. Numerical modeling of hydrodynamic circulation in Ichkeul Lake-Tunisia. Energy Rep. 6, 208–213 (2020).Article 

Google Scholar 
Hollis, G. E. et al. Modeling and management of the internationally important wetland at Garaet Ichkeul Tunisia. Numéro 4 de IWRB special publication, International Waterfowl Research Bureau, ISSN 0962–6271 Volume 4 de International Waterfowl Research Bureau Slimbridge: IWRB special publication (ed. International Waterfowl Research Bureau) 1–121 (1986).Casagranda, C. & Boudouresque, C. F. A first quantification of the overall biomass, from phytoplankton to birds, of a Mediterranean brackish lagoon: Revisiting the ecosystem of Lake Ichkeul (Tunisia). Hydrobiologia 637, 73–85 (2010).Article 

Google Scholar 
Hamdi, N., Touihri, M. & Charfi, F. Diagnostic Écologique du Parc National Ichkeul (Tunisie) après la construction des barrages: Cas des oiseaux d’eau. Rev. Ecol-Terre Vie. 67, 41–62 (2012).
Google Scholar 
UNESCO. Biosphere Reserve Information Tunisia Ichkeul, UNESCO-MAB. Biosphere Reserves Directory. (2009a).UNESCO. Ichkeul National Park http://whc.unesco.org/en/list/8/ (2009b).RAMSAR. Convention and Wetlands International. Information Sheet on Ramsar Wetlands Tunisia Ichkeul, Ramsar Sites Information Service. (2009).Tamisier, A., et al. Modelling aquatic ecosystems: Benefits, costs and risks, for a field biologist. Ichkeul Lake, Tunisia, a case study. In Limnology and Aquatic birds, Monitoring, modeling and management (eds. Comin, F. A., Herrera, J. A. & Ramirez, J.) 185–203 (2001).Giordani, G. et al. Nutrient fluxes in transitional zones of the Italian coast. LOICZ Reports & Studies No. 28, ii+157 pages, LOICZ, Texel, the Netherlands. (2005).Thomson, A. J., Giannopoulos, G., Pretty, J., Baggs, E. M. & Richardson, D. J. Biological sources and sinks of nitrous oxide and strategies to mitigate emissions. Phil. Trans. R. Soc. B367, 1157–1168 (2012).Article 

Google Scholar 
Chen, N., Wu, J., Chen, Z., Lu, T. & Wang, L. Spatial-temporal variation of dissolved N2 and denitrification in an agricultural river network, southeast China. Agric. Ecosyst. Environ. 189, 1–10 (2014).ADS 
CAS 
Article 

Google Scholar 
Loeks, B. M. & Cotner, J. B. Upper Midwest lakes are supersaturated with N2. Proc. Natl. Acad. Sci. USA 117, 17063–17067 (2020).Article 

Google Scholar 
Thomann, R. V., DiToro, D. M., Winfield, R. P. & O’Connor, D. J. Mathematical modelling of phytoplankton in Lake Ontario. Part 1. Model development and verification. U.S. Environmental Protection Agency, EPA-660/3-75-005, Corvallis, Oreg. 77 (1975).DiToro, D. M. & Connolly, J. P. Mathematical models of water quality in large lakes. Part 2: Lake Erie. U.S. Environmental Protection Agency, Duluth, Minnesota. EPA-600/3-80-065. 231. (1980)Jacobsen, O. S. & Jorgensen, S. E. A submodel for nitrogen release from sediments. Ecol. Model. 1, 147–151 (1975).CAS 
Article 

Google Scholar 
Jorgensen, S. E., Kamp-Neilsen, L. & Jacobsen, O. S. A submodel for anaerobic mud-water exchange of phosphate. Ecol. Model. 1, 133–146 (1975).Article 

Google Scholar 
Jorgensen, S. E. An Eutrophication model for a lake. Ecol. Model. 2, 147–165 (1976).Article 

Google Scholar 
Jorgensen, S. E., Mejer, H. & Friis, M. Examination of a Lake model. Ecol. Model. 4, 253–278 (1978).Article 

Google Scholar 
Chapelle, A., Mesnage, V., Mazouni, N., Deslous-Paoli, J. M. & Picot, B. Modélisation des cycles de l’azote et du phosphore dans les sédiments d’une lagune soumise à une exploitation conchylicole. Oceanol. Acta. 17, 609–620 (1994).CAS 

Google Scholar 
Raillard, O. & Ménesguen, A. An ecosystem box model for estimating the carrying capacity of a macrotidal shellfish system. Mar. Ecol. Prog. Ser. 115, 117–130 (1994).ADS 
Article 

Google Scholar 
Kremer, H. H. et al. Land–ocean interactions in the coastal zone: Science plan and implementation strategy, IGBP Report 51, IHDP Report 18. International Geosphere-Biosphere Programme. (2005).Strobl, R., Zaldivar, C. J., Somma, F., Stips, A. & Garcia, G. E. Application of the LOICZ Methodology to the Mediterranean Sea EUR 23936 EN. Luxembourg (Luxembourg): OPOCE. JRC52454. (2009).Swaney, D. P. & Giordani, G (Eds.). Proceedings of the LOICZ Workshop on Biogeochemical Budget Methodology and Applications, Providence RI, November 9–10, 2007. LOICZ Reports and Studies no. 37. GKSS Research Centre, Geesthacht. http://www.loicz.org/imperia/md/content/loicz/print/rsreports/biogeochemical_budget_methodology_and_applications.pdf (2011).Swaney, D. P., Smith, S. V. & Wulff, F. The LOICZ Biogeochemical Modeling Protocol and its Application to Estuarine Ecosystems. In Teratise on Estuarine and Coastal Ecosystem Science, Academic Press, Elsevier (eds. Bauer, J. E. & Bianchi, T. S.) 136–159 (2011).Glaeser, B., Kannen, A. & Kremer, H. Introduction: The future of coastal areas. Challenges for planning practice and research. Gaia-Ecol. Perspect. Sci. Soc. 18, 145–149 (2009).
Google Scholar 
Glaeser, B., Bruckmeier, K., Glaser, M. & Krause, G. Social-ecological systems analysis in coastal and marine areas: A path toward integration of interdisciplinary knowledge. In Current Trends in Human Ecology. Cambridge Scholars Publishing (eds. Lopes, P. & Begossi, A.) 183–203 (2009b).Glaser, M. & Glaeser, B. The social dimension in the management of social ecological change. In Treatise on Estuarine and Coastal Science, Vol. 11: Integrated Management of Estuaries and Coasts. München: Elsevier (eds. Kremer, H. & Pinckney, J.) 59 (2011).Glaser, M. & Glaeser, B. Towards a framework for cross-scale and multi-level analysis of coastal and marine social-ecological systems dynamics. Reg. Environ. Change. 14, 2039–2052 (2014).Article 

Google Scholar 
Vybernaite-Lubiene, I. et al. Biogeochemical budgets of nutrients and metabolism in the curonian lagoon (Southeast Baltic Sea): Spatial and temporal variations. Water 14, 164 (2022).CAS 
Article 

Google Scholar 
Yazidi, A., Saidi, S., Ben, M. N. & Darragi, F. Contribution of GIS to evaluate surface water pollution by heavy metals: Case of Ichkeul Lake (Northern Tunisia). J. Afr. Earth. Sci. 134, 166–173 (2017).ADS 
CAS 
Article 

Google Scholar 
Goudling, M. et al. Ecosystem-based management of Amazon fisheries and wetlands. Fish Fish. 20, 138–158 (2018).
Google Scholar 
Mitsch, W. J. & Gosselink, J. G. Wetlands 5th edn. (Wiley, 2015).
Google Scholar 
World Bank 2022.Affouri, H. & Sahraoui, O. The sedimentary organic matter from a Lake Ichkeul core (far northern Tunisia): Rock-Eval and biomarker approach. J. Afr. Earth. Sci. 129, 248–259 (2017).ADS 
CAS 
Article 

Google Scholar 
Vanderkelen, I., van Lipzig, N. P. M. & Thiery, A. Modelling the water balance of Lake Victoria (East Africa)–Part 1: Observational analysis. Hydrol. Earth Syst. Sci. 22, 1–17 (2018).Article 

Google Scholar 
Coe, M. T. & Foley, J. A. Human and natural impacts on the water resources of the Lake Chad basin. J. Geophys. Res. Atmos. 106, 3349–3356 (2001).ADS 
Article 

Google Scholar 
Gao, H., Bohn, T. J., Podest, E., McDonald, K. C. & Lettenmaier, D. P. On the causes of the shrinking of Lake Chad. Environ. Res. Lett. 6, 34021 (2011).Article 

Google Scholar 
Prange, M., Wilke, T. & Wesselingh, F. P. The other side of sea level change. Commun. Earth Environ. 1, 69 (2020).ADS 
Article 

Google Scholar 
Glausiusz, J. Environmental Science: New life for the DeaSea?. Nature 464, 1118–1120 (2010).CAS 
Article 

Google Scholar 
Gronewold, A. D. & Stow, C. A. Water Loss from the Great Lakes. Science 343, 1084–1085 (2014).ADS 
Article 

Google Scholar 
Mei, X., Dai, Z., Du, J. & Chen, J. Linkage between Three Gorges Dam impacts and the dramatic recessions in China’s largest freshwater lake, Poyang Lake. Sci. Rep. 5, 18197 (2015).ADS 
CAS 
Article 

Google Scholar 
Micklin, P. The aral sea disaster. Ann. Rev. Earth Planet. Sci. 35, 47–72 (2007).ADS 
CAS 
Article 

Google Scholar 
Feng, L., Han, X., Hu, C. & Chen, X. Four decades of wetland changes of the largest freshwater lake in China: Possible linkage to the Three Gorges Dam?. Remote Sens. Environ. 176, 43–55 (2016).ADS 
Article 

Google Scholar 
Downing, J. A. et al. The global abundance and size distribution of lakes, ponds, and impoundments. Limnol. Oceanogr. 51, 2388–2397 (2006).ADS 
Article 

Google Scholar 
Awange, J. L. et al. The falling lake victoria water level: GRACE, TRIMM and CHAMP satellite analysis of the lake basin. Water Resour. Manag. 22, 775–796 (2008).Article 

Google Scholar 
Carroll, M. L., Townshend, R. H. G., DiMiceli, C. M., Loboda, T. & Sohlberg, R. A. Shrinkage lakes of the Artic: Spatial relationships and trajectory of change. Geophys. Res. Lett. 38, 20406 (2011).ADS 
Article 

Google Scholar 
Lefebvre, G. et al. Predicting the vulnerability of seasonally-flooded wetlands to climate change across the Mediterranean Basin. Sci. Total Environ. 692, 546–555 (2019).ADS 
CAS 
Article 

Google Scholar 
Touaylia, S., Ghannem, S., Toumi, H., Béjaoui, M. & Garrido, J. Assessment of heavy metals status in northern Tunisia using contamination indices: Case of the Ichkeul steams system. Int. J. Environ. Res. Public Health. 3, 209–217 (2016).
Google Scholar 
Aouissi, J., Benabdallah, S., Lili, C. Z. & Cudennec, C. Modelling water quality to improve agricultural practices and land management in a Tunisian catchment using soil and water assessment tool. J. Environ. Qual. 43, 18–25 (2014).Article 

Google Scholar 
Aouissi, J., Lili, C. Z., Benabdallah, S. & Cudennec, C. Assessing the hydrological impacts of agricultural changes upstream of the Tunisian World Heritage sea-connected Ichkeul Lake. Proc. Int. Assoc. Hydrol. Sci. 365, 61–65 (2015).
Google Scholar 
Fathalli, A. et al. Molecular and phylogenetic characterization of potentially toxic cyanobacteria in Tunisian freshwaters. Syst. Appl. Microbiol. 34, 303–310 (2011).CAS 
Article 

Google Scholar 
Ouchir, N., Morin, S., Ben, A. L., Boughdiri, M. & Aydi, A. Periphytic diatom communities in tributaries around Lake Ichkeul, northern Tunisia: A preliminary assessment. Afr. J. Aquat. Sci. 42, 65–73 (2017).Article 

Google Scholar 
Chislock, M. F., Doster, E., Zitomer, R. A. & Wilson, A. E. Eutrophication: Causes, consequences, and controls in aquatic ecosystems. Nat. Educ. Knowl. 4, 10 (2013).
Google Scholar 
Paerl, H. W. & Huisman, J. Climate change: A catalyste for global expansion of harmful cyanobacteria blooms. Environ. Microb. Rep. 1, 27–37 (2009).CAS 
Article 

Google Scholar 
Paerl, H. W., Nathan, S. H. & Calandrino, E. S. Controlling harmful cyanobacteria blooms in a world experiencing anthropogenic and climatic-induced change. Sci. Total Environ. 409, 1739–1745 (2011).ADS 
CAS 
Article 

Google Scholar 
O’Neil, J. M., Davis, T. M., Burford, M. A. & Gobler, C. J. The rise of harmful cyanobacteria blooms: The potential roles of eutrophication and climate change. Harmful Algae 14, 313–334 (2012).Article 

Google Scholar 
Ben, S. F. et al. Pesticides in Ichkeul Lake-Bizerte Lagoon Watershed in Tunisia: Use, occurrence, and effects on bacteria and free-living marine nematodes. Environ. Sci. Pollut. Res. 23, 36–48 (2016).Article 

Google Scholar 
Bourhane, Z. et al. Microbial diversity alteration reveals biomarkers of contamination in soil-river-lake continuum. J. Hazard. Mater. 421, 126789 (2022).CAS 
Article 

Google Scholar 
Kolzau, S. et al. Seasonal patterns of nitrogen and phosphorus limitation in four German lakes and the predictability of limitation status from Ambient nutrient concentrations. PLoS ONE 9, e96065 (2014).ADS 
Article 

Google Scholar 
Abidi, M., Ben, A. R. & Gueddari, M. Assessment of the trophic status of the South Lagoon of Tunis (Tunisia, Mediterranean Sea); a Geochemical and Statistical Approaches. J. Chem. (2018).Saunders, D. L. & Kaffl, J. Denitrification rates in the sediments of Lake Memphremagog, Canda–USA. Water Res. 35, 1897–1904 (2001).CAS 
Article 

Google Scholar 
Davidson, E. A. & Seitzinger, S. The enigma of progress in denitrification research. Ecol. Appl. 16, 2057–2063 (2006).Article 

Google Scholar 
Medina-Galvan, J. et al. Comparing the biogeochemical functioning of two arid subtropical coastal lagoons: The effect of wastewater discharges. Ecosyst. Health Sustain. 7, 1 (2021).Article 

Google Scholar 
Piehler, M. F. & Smyth, A. R. Habitat-specific distinctions in estuarine denitrification affect both ecosystem function and services. Ecosphere. 2, 1–17 (2011).ADS 
Article 

Google Scholar 
Loeks-Johson, B. M. & Cotner, J. B. Upper Midwest lakes are supersaturated with N2. Proc. Natl. Acad. Sci. U S A. 117, 17063–17067 (2020).Reddy, K. R., Patrick, W. H. & Lindau, C. W. Nitrification-denitrification at the plant root sediment interface in Wetlands. Limnol. Oceanogr. 34, 1004–1013 (1989).ADS 
CAS 
Article 

Google Scholar 
Adrian, A. et al. Lakes as sentinels of climate change. Limnol. Oceanogr. 54, 2283–2297 (2009).ADS 
Article 

Google Scholar 
Seo, C. D. & DeLaune, R. D. Fungal and bacterial mediated denitrification in wetlands: Influence of sediment redox condition. Water Res. 44, 2441–2450 (2010).CAS 
Article 

Google Scholar 
Montzka, S. A., Dlugokencky, I. J. & Butler, J. H. Non-CO2 greenhouse gases and climate change. Nature 476, 43–50 (2011).CAS 
Article 

Google Scholar 
Sferratore, A., Billen, G. & Garnier, J. The S Modeling nutrient (N, P, Si ) budget in the Seine watershed: Application of the River Strahler model using data from local to global scale resolution Modeling nutrient (N, P, Si) budget in the Seine watershed: Application of the River Strahler model using data from local to global scale resolution. Glob. Biogeochem. Cycles. 19, 20 (2005).Article 

Google Scholar 
Béjaoui, B. et al. 3D modeling of phytoplankton seasonal variation and nutrient budget in a Southern Mediterranean Lagoon. Mar. Pollut. Bull. 114, 962–976 (2017).Article 

Google Scholar 
Shaiek, M., Fassatoui, C. & Romdhane, M. S. Past and present fish species recorded in the estuarine Lake Ichkeul, northern Tunisia. Afr. J. Aquat. Sci. 41, 171–180 (2016).Article 

Google Scholar 
INM. Données climatiques de la région de Bizerte. Institut National de Météorologie, Tunis, Tunisie. (2017).Rodier, J. et al. L’analyse de l’eau, Eaux naturelles, eaux résiduaires, eau de mer, Dunod Paris. (1996).Lorenzen, C. J. Determination of chlorophyll and pheopigments by spectrophotometric equations. Limnol. Oceanogr. 12, 343–346 (1967).ADS 
CAS 
Article 

Google Scholar 
Parsons, T. R., Maita, Y. & Lalli, C. M. A manual of chemical and biological methods for seawater analysis. Geol. Mag. 122, 570–570 (1980).
Google Scholar 
Redfield, A. C. The biological control of chemical factors in the environment. Sci. Prog. 11, 150–170 (1960).CAS 

Google Scholar 
Gordon, D. C. et al. LOICZ biogeochemical modelling guidelines. LOICZ Rep and Stud. 5, 1–96 (1996).
Google Scholar 
Seitzinger, S. P. Denitrification in freshwater and coastal marine ecosystems: Ecological and geochemical significance. Limnol. Oceanogr. 33, 702–724 (1988).ADS 
CAS 

Google Scholar 
Atkinson, M. J. & Smith, S. V. C:N: P ratios of benthic marine plants. Limnol. Oceanogr. 28, 568–574 (1983).ADS 
CAS 
Article 

Google Scholar 
APHA (American Public Health Association) Standard Methods for the Examination of Water and Wastewater. 18th Edition, American Public Health Association (APHA), American Water Works Association (AWWA) and Water Pollution Control Federation (WPCF), Washington DC (1992). More

Schwarzenbach RP, Escher BI, Fenner K, Hofstetter TB, Johnson CA, Von Gunten U, et al. The challenge of micropollutants in aquatic systems. Science (80-). 2006;313:1072–7.Article 

Google Scholar 
Deblonde T, Cossu-Leguille C, Hartemann P. Emerging pollutants in wastewater: a review of the literature. Int J Hyg Environ Health. 2011;214:442–8.Article 

Google Scholar 
Wang M, Cernava T. Overhauling the assessment of agrochemical-driven interferences with microbial communities for improved global ecosystem integrity. Environ Sci Ecotechnol. 2020;4:100061.Article 

Google Scholar 
Luo Y, Guo W, Ngo HH, Nghiem LD, Hai FI, Zhang J, et al. A review on the occurrence of micropollutants in the aquatic environment and their fate and removal during wastewater treatment. Sci Total Environ. 2014;473–474:619–41.Article 

Google Scholar 
Wang Z, Zhang XH, Huang Y, Wang H. Comprehensive evaluation of pharmaceuticals and personal care products (PPCPs) in typical highly urbanized regions across China. Environ Pollut. 2015;204:223–32.Article 

Google Scholar 
Eggen RIL, Hollender J, Joss A, Schärer M, Stamm C. Reducing the discharge of micropollutants in the aquatic environment: the benefits of upgrading wastewater treatment plants. Environ Sci Technol. 2014;48:7683–9.Article 

Google Scholar 
Vila-Costa M, Cerro-Gálvez E, Martínez-Varela A, Casas G, Dachs J. Anthropogenic dissolved organic carbon and marine microbiomes. ISME J. 2020;14:2646–8.Article 

Google Scholar 
da Silva GCX, Medeiros de Abreu CH, Ward ND, Belúcio LP, Brito DC, Cunha HFA, et al. Environmental impacts of dam reservoir filling in the East Amazon. Front Water. 2020;2:11.Article 

Google Scholar 
Kuroda K, Murakami M, Oguma K, Muramatsu Y, Takada H, Takizawa S. Assessment of groundwater pollution in Tokyo using PPCPs as sewage markers. Environ Sci Technol. 2012;46:1455–64.Article 

Google Scholar 
Liu WR, Zhao JL, Liu YS, Chen ZF, Yang YY, Zhang QQ, et al. Biocides in the Yangtze River of China: spatiotemporal distribution, mass load and risk assessment. Environ Pollut. 2015;200:53–63.Article 

Google Scholar 
Roberts J, Kumar A, Du J, Hepplewhite C, Ellis DJ, Christy AG, et al. Pharmaceuticals and personal care products (PPCPs) in Australia’s largest inland sewage treatment plant, and its contribution to a major Australian river during high and low flow. Sci Total Environ. 2016;541:1625–37.Article 

Google Scholar 
Rodea-Palomares I, Gonzalez-Pleiter M, Gonzalo S, Rosal R, Leganes F, Sabater S, et al. Hidden drivers of low-dose pharmaceutical pollutant mixtures revealed by the novel GSA-QHTS screening method. Sci Adv. 2016;2:1–12.Article 

Google Scholar 
Yang X, Chen F, Meng F, Xie Y, Chen H, Young K, et al. Occurrence and fate of PPCPs and correlations with water quality parameters in urban riverine waters of the Pearl River Delta, South China. Environ Sci Pollut Res. 2013;20:5864–75.Article 

Google Scholar 
Cerro-Gálvez E, Dachs J, Lundin D, Fernández-Pinos MC, Sebastián M, Vila-Costa M. Responses of coastal marine microbiomes exposed to anthropogenic dissolved organic carbon. Environ Sci Technol. 2021;55:9609–21.Article 

Google Scholar 
Martinez-Varela A, Cerro-Gálvez E, Auladell A, Sharma S, Moran MA, Kiene RP, et al. Bacterial responses to background organic pollutants in the northeast subarctic Pacific Ocean. Environ Microbiol. 2021;23:4532–46.Article 

Google Scholar 
Bob A, Shen D, Li S, Zhang L, Rashid A, Sun Q, et al. Strong impact of micropollutants on prokaryotic communities at the horizontal but not vertical scales in a subtropical reservoir, China. Sci Total Environ. 2020;721:137767.Article 

Google Scholar 
Tlili A, Corcoll N, Arrhenius Å, Backhaus T, Hollender J, Creusot N, et al. Tolerance patterns in stream biofilms link complex chemical pollution to ecological impacts. Environ Sci Technol. 2020;54:10745–53.Article 

Google Scholar 
Chalew TEA, Halden RU. Environmental exposure of aquatic and terrestrial biota to triclosan and triclocarban. J Am Water Resour Assoc. 2009;45:4–13.Article 

Google Scholar 
Zhang W, Yin K, Chen L. Bacteria-mediated bisphenol A degradation. Appl Microbiol Biotechnol. 2013;97:5681–9.Article 

Google Scholar 
Staples CA, Dorn PB, Klecka GM, O’Block ST, Harris LR. A review of the environmental fate, effects, and exposures of bisphenol A. Chemosphere. 1998;36:2149–73.Article 

Google Scholar 
Choi YJ, Lee LS. Aerobic soil biodegradation of bisphenol (BPA) alternatives bisphenol S and bisphenol AF compared to BPA. Environ Sci Technol. 2017;51:13698–704.Article 

Google Scholar 
McMurry LM, Oethinger M, Levy SB. Triclosan targets lipid synthesis [4]. Nature. 1998;394:531–2.Article 

Google Scholar 
Cabana H, Jiwan JLH, Rozenberg R, Elisashvili V, Penninckx M, Agathos SN, et al. Elimination of endocrine disrupting chemicals nonylphenol and bisphenol A and personal care product ingredient triclosan using enzyme preparation from the white rot fungus Coriolopsis polyzona. Chemosphere. 2007;67:770–8.Article 

Google Scholar 
Hu A, Ju F, Hou L, Li J, Yang X, Wang H, et al. Strong impact of anthropogenic contamination on the co-occurrence patterns of a riverine microbial community. Environ Microbiol. 2017;19:4993–5009.Article 

Google Scholar 
Boyd TJ, Smith DC, Apple JK, Hamdan LJ, Osburn CL, Montgomery MT. Evaluating PAH biodegradation relative to total bacterial carbon demand in coastal ecosystems: Are PAHs truly recalcitrant? In: Van Dijk T. (ed). Microbial Ecology Research Trends. Nova Science Publishers, 2008. pp 1–38.Okere UV, Cabrerizo A, Dachs J, Ogbonnaya UO, Jones KC, Semple KT. Effects of pre-exposure on the indigenous biodegradation of 14C-phenanthrene in Antarctic soils. Int Biodeterior Biodegrad. 2017;125:189–99.Article 

Google Scholar 
Coll C, Bier R, Li Z, Langenheder S, Gorokhova E, Sobek A. Association between aquatic micropollutant dissipation and river sediment bacterial communities. Environ Sci Technol. 2020;54:14380–92.Article 

Google Scholar 
Bender EA, Case TJ, Gilpin ME. Perturbation experiments in community ecology: Theory and practice. Ecology. 1984;65:1–13.Shade A, Peter H, Allison SD, Baho DL, Berga M, Bürgmann H, et al. Fundamentals of microbial community resistance and resilience. Front Microbiol. 2012;3:1–19.Article 

Google Scholar 
Buerger S, Spoering A, Gavrish E, Leslin C, Ling L, Epstein SS. Microbial scout hypothesis, stochastic exit from dormancy, and the nature of slow growers. Appl Environ Microbiol. 2012;78:3221–8.Article 

Google Scholar 
Lee SH, Sorensen JW, Grady KL, Tobin TC, Shade A. Divergent extremes but convergent recovery of bacterial and archaeal soil communities to an ongoing subterranean coal mine fire. ISME J. 2017;11:1447–59.Article 

Google Scholar 
Lennon JT, den Hollander F, Wilke-Berenguer M, Blath J. Principles of seed banks and the emergence of complexity from dormancy. Nat Commun. 2021;12:1–16.Article 

Google Scholar 
Philippot L, Griffiths BS, Langenheder S. Microbial community resilience across ecosystems and multiple disturbances. Microbiol Mol Biol Rev. 2021;85:e00026–20.Article 

Google Scholar 
Hu A, Li S, Zhang L, Wang H, Yang J, Luo Z, et al. Prokaryotic footprints in urban water ecosystems: a case study of urban landscape ponds in a coastal city, China. Environ Pollut. 2018;242:1729–39.Article 

Google Scholar 
Im J, Löffler FE. Fate of bisphenol A in terrestrial and aquatic environments. Environ Sci Technol. 2016;50:8403–16.Article 

Google Scholar 
Sun Q, Li M, Ma C, Chen X, Xie X, Yu CP. Seasonal and spatial variations of PPCP occurrence, removal and mass loading in three wastewater treatment plants located in different urbanization areas in Xiamen, China. Environ Pollut. 2016;208:371–81.Article 

Google Scholar 
Sun Q, Wang Y, Li Y, Ashfaq M, Dai L, Xie X, et al. Fate and mass balance of bisphenol analogues in wastewater treatment plants in Xiamen City, China. Environ Pollut. 2017;225:542–9.Article 

Google Scholar 
Sun Q, Li Y, Chou PH, Peng PY, Yu CP. Transformation of bisphenol A and alkylphenols by ammonia-oxidizing bacteria through nitration. Environ Sci Technol. 2012;46:4442–8.Article 

Google Scholar 
Zaayman M, Siggins A, Horne D, Lowe H, Horswell J. Investigation of triclosan contamination on microbial biomass and other soil health indicators. FEMS Microbiol Lett. 2017;364:1–6.Article 

Google Scholar 
Xie J, Zhao N, Zhang Y, Hu H, Zhao M, Jin H. Occurrence and partitioning of bisphenol analogues, triclocarban, and triclosan in seawater and sediment from East China Sea. Chemosphere. 2022;287:132218.Article 

Google Scholar 
Yamazaki E, Yamashita N, Taniyasu S, Lam J, Lam PKS, Moon HB, et al. Bisphenol A and other bisphenol analogues including BPS and BPF in surface water samples from Japan, China, Korea and India. Ecotoxicol Environ Saf. 2015;122:565–72.Article 

Google Scholar 
Kalyuzhny M, Shnerb NM. Dissimilarity-overlap analysis of community dynamics: opportunities and pitfalls. Methods Ecol Evol. 2017;8:1764–73.Article 

Google Scholar 
Wang J, Pan F, Soininen J, Heino J, Shen J. Nutrient enrichment modifies temperature-biodiversity relationships in large-scale field experiments. Nat Commun. 2016;7:1–9.
Google Scholar 
Hildebrand F, Tito RY, Voigt AY, Bork P, Raes J. Correction to: LotuS: an efficient and user-friendly OTU processing pipeline [Microbiome, 2, (2014), 30]. Microbiome. 2014;2:1–7.Article 

Google Scholar 
Edgar RC. UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nat Methods. 2013;10:996–8.Article 

Google Scholar 
Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, et al. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 2013;41:590–6.Article 

Google Scholar 
Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, et al. QIIME allows analysis of high- throughput community sequencing data Intensity normalization improves color calling in SOLiD sequencing. Nat Methods. 2010;7:335–6.Article 

Google Scholar 
Klappenbach JA, Saxman PR, Cole JR, Schmidt TM. Rrndb: the ribosomal RNA operon copy number database. Nucleic Acids Res. 2001;29:181–4.Article 

Google Scholar 
Wu L, Yang Y, Chen S, Zhao M, Zhu Z, Yang S, et al. Long-term successional dynamics of microbial association networks in anaerobic digestion processes. Water Res. 2016;104:1–10.Article 

Google Scholar 
Stegen JC, Lin X, Fredrickson JK, Chen X, Kennedy DW, Murray CJ, et al. Quantifying community assembly processes and identifying features that impose them. ISME J. 2013;7:2069–79.Article 

Google Scholar 
Stegen JC, Lin X, Fredrickson JK, Konopka AE. Estimating and mapping ecological processes influencing microbial community assembly. Front Microbiol. 2015;6:1–15.Article 

Google Scholar 
Webb CO, Ackerly DD, Kembel SW. Phylocom: software for the analysis of phylogenetic community structure and trait evolution. Bioinformatics. 2008;24:2098–2100.Article 

Google Scholar 
Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:1–21.Article 

Google Scholar 
Letunic I, Bork P. Interactive Tree of Life (iTOL) v4: recent updates and new developments. Nucleic Acids Res. 2019;47:2–5.Article 

Google Scholar 
Anderson MJ. Permutation tests for univariate or multivariate analysis of variance and regression. Can J Fish Aquat Sci. 2001;58:626–39.Article 

Google Scholar 
Oksanen AJ, Blanchet FG, Friendly M, Kindt R, Legendre P, Mcglinn D, et al. Vegan: community ecology package. Encyclopedia of Food and Agricultural Ethics. 2019; 2395–6.Bashan A, Gibson TE, Friedman J, Carey VJ, Weiss ST, Hohmann EL, et al. Universality of human microbial dynamics. Nature. 2016;534:259–62.Article 

Google Scholar 
Vila JCC, Liu YY, Sanchez A. Dissimilarity–overlap analysis of replicate enrichment communities. ISME J. 2020;14:2505–13.Article 

Google Scholar 
Ahlmann-Eltze C, Patil I. ggsignif: significance Brackets for ‘ggplot2’. R package version 0.6.1. 2021.Callahan BJ, McMurdie PJ, Holmes SP. Exact sequence variants should replace operational taxonomic units in marker-gene data analysis. ISME J. 2017;11:2639–43.Article 

Google Scholar 
Glassman SI, Martiny JBH. Broadscale ecological patterns are robust to use of exact. mSphere. 2018;3:e00148–18.Article 

Google Scholar 
Lindström ES, Östman Ö. The importance of dispersal for bacterial community composition and functioning. PLoS One. 2011;6:e25883.Article 

Google Scholar 
Shen D, Langenheder S, Jürgens K. Dispersal modifies the diversity and composition of active bacterial communities in response to a salinity disturbance. Front Microbiol. 2018;9:2188.Article 

Google Scholar 
Zhou NA, Lutovsky AC, Andaker GL, Gough HL, Ferguson JF. Cultivation and characterization of bacterial isolates capable of degrading pharmaceutical and personal care products for improved removal in activated sludge wastewater treatment. Biodegradation. 2013;24:813–27.Article 

Google Scholar 
Thelusmond JR, Strathmann TJ, Cupples AM. Carbamazepine, triclocarban and triclosan biodegradation and the phylotypes and functional genes associated with xenobiotic degradation in four agricultural soils. Sci Total Environ. 2019;657:1138–49.Article 

Google Scholar 
Danzl E, Sei K, Soda S, Ike M, Fujita M. Biodegradation of bisphenol A, bisphenol F and bisphenol S in seawater. Int J Environ Res Public Health. 2009;6:1472–84.Article 

Google Scholar 
Zaborowska M, Wyszkowska J, Borowik A. Soil microbiome response to contamination with Bisphenol A, Bisphenol F and Bisphenol S. Int J Mol Sci. 2020;21:3529.Article 

Google Scholar 
Freilich S, Zarecki R, Eilam O, Segal ES, Henry CS, Kupiec M, et al. Competitive and cooperative metabolic interactions in bacterial communities. Nat Commun. 2011;2:587–9.Article 

Google Scholar 
Pacheco AR, Moel M, Segrè D. Costless metabolic secretions as drivers of interspecies interactions in microbial ecosystems. Nat Commun. 2019;10:103.Article 

Google Scholar 
Oh S, Choi D, Cha C-J. Ecological processes underpinning microbial community structure during exposure to subinhibitory level of triclosan. Sci Rep. 2019;9:4598.Article 

Google Scholar 
Hagberg A, Gupta S, Rzhepishevska O, Fick J, Burmølle M, Ramstedt M. Do environmental pharmaceuticals affect the composition of bacterial communities in a freshwater stream? A case study of the Knivsta river in the south of Sweden. Sci Total Environ. 2021;763:142991.Article 

Google Scholar 
Gao H, LaVergne JM, Carpenter CMG, Desai R, Zhang X, Gray K, et al. Exploring co-occurrence patterns between organic micropollutants and bacterial community structure in a mixed-use watershed. Environ Sci Process Impacts. 2019;21:867–80.Article 

Google Scholar 
Wolff D, Krah D, Dötsch A, Ghattas AK, Wick A, Ternes TA. Insights into the variability of microbial community composition and micropollutant degradation in diverse biological wastewater treatment systems. Water Res. 2018;143:313–24.Article 

Google Scholar 
Bajić D, Vila JCC, Blount ZD, Sánchez A. On the deformability of an empirical fitness landscape by microbial evolution. Proc Natl Acad Sci USA. 2018;115:11286–91.Article 

Google Scholar 
Nemergut DR, Schmidt SK, Fukami T, O’Neill SP, Bilinski TM, Stanish LF, et al. Patterns and Processes of Microbial Community Assembly. Microbiol Mol Biol Rev. 2013;77:342–56.Article 

Google Scholar 
Zhou J, Ning D. Stochastic community assembly: does it matter in microbial ecology? Microbiol Mol Biol Rev. 2017;81:1–32.Article 

Google Scholar 
Vellend M. Conceptual synthesis in community ecology. Q Rev Biol. 2010;85:183–206.Article 

Google Scholar 
Svoboda P, Lindström ES, Ahmed Osman O, Langenheder S. Dispersal timing determines the importance of priority effects in bacterial communities. ISME J. 2018;12:644–6.Article 

Google Scholar 
Bernstein HC. Reconciling ecological and engineering design principles for building microbiomes. mSystems. 2019;4:1–5.Article 

Google Scholar 
Borchert E, Hammerschmidt K, Hentschel U, Deines P. Enhancing microbial pollutant degradation by integrating eco-evolutionary principles with environmental biotechnology. Trends Microbiol. 2021;29:908–18.Article 

Google Scholar 
Rocca JD, Muscarella ME, Peralta AL, Izabel-Shen D, Simonin M. Guided by microbes: applying community coalescence principles for predictive microbiome engineering. mSystems. 2021;6:e00538–21.Article 

Google Scholar 
Nemergut DR, Knelman JE, Ferrenberg S, Bilinski T, Melbourne B, Jiang L, et al. Decreases in average bacterial community rRNA operon copy number during succession. ISME J. 2016;10:1147–56.Article 

Google Scholar 
Frost LS, Leplae R, Summers AO, Toussaint A, Edmonton A. Mobile genetic elements: the agents of open source evolution. Nat Rev Microbiol. 2005;3:722–32.Ullastres A, Merenciano M, Guio L, Gonz J. Transposable elements: a toolkit for stress and environmental adaptation in bacteria. Stress Environ Regul Gene Expr Adapt Bact. 2016;1:137–45.
Google Scholar 
Chang CY, Vila JCC, Bender M, Li R, Mankowski MC, Bassette M, et al. Engineering complex communities by directed evolution. Nat Ecol Evol. 2021;5:1011–23.Article 

Google Scholar  More

Lal Mohan, R. S., Dey, S. C., Bairagi, S. P. & Roy, S. On a survey of the Ganges River dolphin Platanista gangetica of Bramaputra River, Assam. J. Bombay Nat. Hist. Soc. 94, 483–495 (1997).
Google Scholar 
Sinha, R.K., et al. Status and distribution of the Ganges susu (Platanista gangetica) in Ganges River system of India and Nepal in Biology and conservation of freshwater cetaceans in Asia (eds. Reeves, R. R., Smith, B. D. & Kasuya, T). 42–48 (Switzerland: Occasional Paper of the IUCN Species Survival Commission, 2000)Sinha, R. K. & Kannan, K. Ganges River dolphin: an overview of biology, ecology, and conservation status in India. Ambio. 43,1029–1046 (2014).
Google Scholar 
Anderson, J. Anatomical and Zoological Researches: Comprising an Account of the Zoological Results of the Two Expeditions to Western Yunnan in 1868 and 1875; and A Monograph of the Two Cetacean Genera, Platanista and Orcella-Vol. 1 (Text). Vol. 1 (Bernard Quaritch, 1878).Herald, E. S. et al. Blind river dolphin: first side-swimming cetacean. Science 166, 1408–1410 (1969).ADS 
CAS 

Google Scholar 
Herald, E. S. Field and aquarium study of the blind River Dolphin (Platanista Gangetica) (California Academy of Sciences San Fransico Steinhart Aquarium, 1969).Pilleri, G., Zbinden, K., Gihr, M. & Kraus, C. Sonar clicks, directionality of the emission field and echolocating behaviour of the Indus dolphin (Platanista indi, Blyth, 1859). Invest. Cetacea Brain Anat. Inst. Berne Switzerl. 13–43 (1976).Jensen, F. H. et al. Clicking in shallow rivers: short-range echolocation of Irrawaddy and Ganges river dolphins in a shallow, acoustically complex habitat. PLoS ONE 8, e59284 (2013).ADS 
CAS 

Google Scholar 
Pence, E.A. Monofilament gill net acoustic study. (National Mammal Laboratory, Contract 40-ABNF-5-1988,1986)Jefferson, T. A., Würsig, B. & Fertl, D. Cetacean Detection and Responses to Fishing Gear in Marine Mammal Sensory Systems (eds. Thomas, J.A., Kastelein, R.A. & Supin, A.Y.) 663–684 (Springer, 1992)
Google Scholar 
Mansur, E. F., Smith, B. D., Mowgli, R. M. & Diyan, M. A. A. Two incidents of fishing gear entanglement of Ganges River dolphins (Platanista gangetica gangetica) in waterways of the Sundarbans mangrove forest, Bangladesh. Aquat. Mamm. 34, 362 (2008).
Google Scholar 
Sinha, R. K. An alternative to dolphin oil as a fish attractant in the Ganges River system: conservation of the Ganges River dolphin.
Biol. Conserv. 107, 253–257 https://doi.org/10.1016/S0006-3207(02)00058-7 (2002).Article 

Google Scholar 
Qureshi, Q. et al. Development of conservation action plan for river dolphin. 228 (Wildlife Institute of India, Dehradun, Uttarakhand, 2018).Kolipakam, V. et al. Evidence for the continued use of river dolphin oil for bait fishing and traditional medicine: implications for conservation. Heliyon 6, e04690 (2020).
Google Scholar 
Wakid, A. Initiative to reduce the fishing pressures in and around identified habitats of endangered Gangetic dolphin in Brahmaputra River system. (Assam, 2010).Braulik, G.T. & Smith, B.D. Platanista gangetica (amended version of 2017
assessment). The IUCN Red List of Threatened Species, e.T41758A151913336. https://doi.org/10.2305/IUCN.UK.2017-3.RLTS.T41758A151913336.en (2019).Dawson, S. M., Northridge, S., Waples, D. & Read, A. J. To ping or not to ping: the use of active acoustic devices in mitigating interactions between small cetaceans and gillnet fisheries. Endanger. Species Res. 19, 201–221 (2013)
Google Scholar 
Reeves, R. R., McClellan, K. & Werner, T. B. Marine mammal bycatch in gillnet and other entangling net fisheries, 1990 to 2011. Endanger. Species Res. 20, 71–97 (2013).
Google Scholar 
Moore, M. J. et al. Fatally entangled right whales can die extremely slowly in OCEANS 2006. 1–3 (IEEE, 2006).Meÿer, M.A. et al. Trends and interventions in large whale entanglement along the South African coast. Afr. J. Mar. Sci. 33, 429–439 (2011).
Google Scholar 
Knowlton, A. R., Hamilton, P. K., Marx, M. K., Pettis, H. M. & Kraus, S. D. Monitoring North Atlantic right whale Eubalaena glacialis entanglement rates: a 30 year retrospective. Mar. Ecol. Prog. Ser. 466, 293–302 (2012).ADS 

Google Scholar 
Knowlton, A. R. et al. Effects of fishing rope strength on the severity of large whale entanglements. Conserv. Biol. 30, 318–328 (2016).
Google Scholar 
Pace, R. M. III., Cole, T. V. & Henry, A. G. Incremental fishing gear modifications fail to significantly reduce large whale serious injury rates. Endanger. Species Res. 26, 115–126 (2014).
Google Scholar 
Salvador, G., Kenney, J. & Higgins, J. 2008 Supplement to the Large whale gear research summary. NOAA/Fisheries Northeast Regional Office, Protected Resources Division, Gloucester, MA (2008).van der Hoop, J. M. et al. Assessment of management to mitigate anthropogenic effects on large whales. Conserv. Biol. 27, 121–133 (2013).
Google Scholar 
Hamilton, S. & Baker, G. B. Technical mitigation to reduce marine mammal bycatch and entanglement in commercial fishing gear: lessons learnt and future directions. Rev. Fish Biol. Fish. 29, 223–247 (2019).
Google Scholar 
Bordino, P., Mackay, A. I., Werner, T. B., Northridge, S. & Read, A. Franciscana bycatch is not reduced by acoustically reflective or physically stiffened gillnets. Endanger. Species Res. 21, 1–12 (2013).
Google Scholar 
Dawson, S. M. Incidental catch of Hector’s dolphin in inshore gillnets. Mar. Mamm. Sci. 7, 283–295 (1991).
Google Scholar 
Mooney, T. A., Nachtigall, P. E. & Au, W. W. Target strength of a nylon monofilament and an acoustically enhanced gillnet: predictions of biosonar detection ranges. Aquat. Mamm. 30, 220–226 (2004).
Google Scholar 
Northridge, S., Sanderson, D., Mackay, A. & Hammond, P. Analysis and mitigation of cetacean bycatch in UK fisheries. Final Report
to DEFRA, Project MF0726, Sea Mammal Research Unit, School of Biology, University of St. Andrews (2003).Mangel, J. C. et al. Illuminating gillnets to save seabirds and the potential for multi-taxa bycatch mitigation. R. Soc. Open Sci. 5, 180254 (2018).ADS 

Google Scholar 
Stephenson, P. C. & Wells, S. Evaluation of the effectiveness of reducing dolphin catches with pingers and exclusion grids in the Pilbara trawl fishery. (Department of Fisheries, Western Australia, 2006).Santana-Garcon, J. et al. Risk versus reward: Interactions, depredation rates, and bycatch mitigation of dolphins in demersal fish trawls. Can. J. Fish. Aquat. Sci. 75, 2233–2240 (2018).
Google Scholar 
Carretta, J., Barlow, J. & Enriquez, L. Acoustic pingers eliminate beaked whale bycatch in a gill net fishery. Mar. Mamm. Sci. 24, 956–961 (2008).
Google Scholar 
Bordino, P. et al. Reducing incidental mortality of Franciscana dolphin Pontoporia blainvillei with acoustic warning devices attached to fishing nets. Mar. Mamm. Sci. 18, 833–842 (2002).
Google Scholar 
Khan, U. & Willems, D. Report of the Trinational workshop on the Irrawaddy Dolphin, 1st to 4th December 2020. 41 (WWF, Pakistan & Netherlands, 2021).Deori, S. et al. PINGERS: can be the eyes of blind ganges dolphins (Platanista Gangetica Gangetica, Roxburgh 1801). J. Sci. Trans. Environ. Technov. 11, 169–178 (2018).
Google Scholar 
Kraus, S. D. The once and future ping: challenges for the use of acoustic deterrents in fisheries. Mar. Technol. Soc. J. 33, 90 (1999).
Google Scholar 
Mate, B. R. & Harvey, J. T. Acoustical deterrents in marine mammal conflicts with fisheries. a workshop held February 17–18, 1986 at Newport, Oregon. NTIS, SPRINGFIELD, VA(USA) (1987).Favaro, L., Gnone, G. & Pessani, D. Postnatal development of echolocation abilities in a bottlenose dolphin (Tursiops truncatus): Temporal organization. Zoo Biol. 32, 210–215 (2013).
Google Scholar 
Dey, M., Krishnaswamy, J., Morisaka, T. & Kelkar, N. Interacting effects of vessel noise and shallow river depth elevate metabolic stress in Ganges river dolphins. Sci. Rep. 9, 15426. https://doi.org/10.1038/s41598-019-51664-1 (2019).ADS 

Google Scholar 
Kastelein, R. A. et al. Effects of acoustic alarms, designed to reduce small cetacean bycatch in gillnet fisheries, on the behaviour of North Sea fish species in a large tank. Mar. Environ. Res. 64, 160–180 (2007).CAS 

Google Scholar 
Kraus, S. et al. Acoustic alarms reduce porpoise mortality. Nature 388, 525 (1997).ADS 
CAS 

Google Scholar 
Roberts, B. L. & Read, A. J. Field assessment of C-POD performance in detecting echolocation click trains of bottlenose dolphins (Tursiops truncatus). Mar. Mamm. Sci. 31, 169–190 (2015).
Google Scholar 
Wickham, H. ggplot2: elegant graphics for data analysis. (Springer-Verlag, New York, 2009).RStudio Team. RStudio: Integrated Development for R. RStudio, PBC, Boston, MA. http://www.rstudio.com/ (2021).Crawley, M. J. Statistics: An Introduction using R (Wiley, 2005).MATH 

Google Scholar 
Perrin, W. F., Donovan, G.P. & Barlow, J. Report of the workshop on mortality of cetaceans in passive fishing nets and traps. Rep. Int. Whal. Commn. 1–71 (Cambridge: IWC, 1994).Read, A. J., Drinker, P. & Northridge, S. Bycatch of marine mammals in US and global fisheries. Conserv. Biol. 20, 163–169 (2006).
Google Scholar 
Reeves, R. & Leatherwood, S. Action plan for the conservation of cetaceans: dolphins, porpoises, and whales. IUCN/SSC Cetacean Specialist Group (IUCN Cambridge, 1998).Smith, B. D. & Braulik, G. Susu and Bhulan : Platanista gangetica gangetica and P. g. minor in Encyclopedia of Marine Mammals. 1135–1139 (Academic Press Ltd – Elsevier Science Ltd, 2009).Wakid, A. Status and distribution of the endangered Gangetic dolphin (Platanista gangetica gangetica) in the Brahmaputra River within India in 2005. Curr. Sci., 97, 1143–1151 (2009).
Google Scholar 
D’agrosa, C., Lennert-Cody, C. E. & Vidal, O. Vaquita bycatch in Mexico’s artisanal gillnet fisheries: driving a small population to extinction. Conserv. Biol. 14, 1110–1119 (2000).
Google Scholar 
Jaramillo-Legorreta, A. et al. Saving the vaquita: immediate action, not more data. Conserv. Biol., 21, 1653–1655 (2007).
Google Scholar 
Turvey, S. T. et al. First human-caused extinction of a cetacean species?. Biol. Lett. 3, 537–540 (2007).
Google Scholar 
Bashir, T., Khan, A., Gautam, P. & Behera, S. K. Abundance and prey availability assessment of Ganges River dolphin (Platanista gangetica gangetica) in a stretch of Upper Ganges River, India. Aquat. Mamm. 36, 19–26 (2010).
Google Scholar 
Braulik, G.T. & Smith, B.D. Platanista gangetica. The IUCN Red List of Threatened Species, e.T41758A50383612. https://doi.org/10.2305/IUCN.UK.2017-3.RLTS.T41758A50383612.en (2017).Hastie, G. D., Wilson, B., Wilson, L., Parsons, K. M. & Thompson, P. M. Functional mechanisms underlying cetacean distribution patterns: hotspots for bottlenose dolphins are linked to foraging. Mar. Biol. 144, 397–403 (2004).
Google Scholar 
Smith, A. M. & Smith, B. D. Review of status and threats to river cetaceans and recommendations for their conservation. Environ. Rev. 6, 189–206 (1998).
Google Scholar 
Wedekin, L., Daura-Jorge, F., Piacentini, V. & Simões-Lopes, P. Seasonal variations in spatial usage by the estuarine dolphin, Sotalia guianensis (van Bénéden, 1864)(Cetacea; Delphinidae) at its southern limit of distribution. Brazil. J. Biol. 67, 1–8 (2007).CAS 

Google Scholar 
Omeyer, L. et al. Assessing the effects of banana pingers as a bycatch mitigation device for harbour porpoises (Phocoena phocoena). Front. Mar. Sci. 285 (2020).Barlow, J. & Cameron, G. A. Field experiments show that acoustic pingers reduce marine mammal bycatch in the California drift gill net fishery. Mar. Mamm. Sci. 19, 265–283 (2003).
Google Scholar 
Amano, M., Kusumoto, M., Abe, M. & Akamatsu, T. Long-term effectiveness of pingers on a small population of finless porpoises in Japan. Endanger. Species Res. 32, 35–40 (2017).
Google Scholar 
Clay, T. A., Alfaro-Shigueto, J., Godley, B. J., Tregenza, N. & Mangel, J. C. Pingers reduce the activity of Burmeister’s porpoise around small-scale gillnet vessels. Mar. Ecol. Prog. Ser. 626, 197–208 (2019).ADS 

Google Scholar 
Kyhn, L. A. et al. Pingers cause temporary habitat displacement in the harbour porpoise Phocoena phocoena. Mar. Ecol. Prog. Ser. 526, 253–265 (2015).ADS 

Google Scholar 
Sugimatsu, H. et al. Study of acoustic characteristics of Ganges river dolphin calf using echolocation clicks recorded during long-term in-situ observation in 2012 OCEANS. 1–7 (IEEE, 2012).Ayadi, A., Ghorbel, M. & Bradai, M. N. Do pingers reduce interactions between bottlenose dolphins and trammel nets around the Kerkennah Islands (Central Mediterranean Sea)?. Cahiers Biol. Mar. 54, 375–383 (2013).
Google Scholar 
Carretta, J. V. & Barlow, J. Long-term effectiveness, failure rates, and “dinner bell” properties of acoustic pingers in a gillnet fishery. Mar. Technol. Soc. J. 45, 7–19 (2011).
Google Scholar 
Read, A. J., Waples, D. M., Urian, K. W. & Swanner, D. Fine-scale behaviour of bottlenose dolphins around gillnets. Proc. R. Soc. Lond. Ser. B Biol. Sci. 270, S90–S92 (2003).
Google Scholar 
Olesiuk, P. F., Nichol, L. M., Sowden, M. J. & Ford, J. K. Effect of the sound generated by an acoustic harassment device on the relative abundance and distribution of harbor porpoises (Phocoena phocoena) in Retreat Passage, British Columbia. Mar. Mamm. Sci. 18, 843–862 (2002).
Google Scholar 
Cox, T. M., Read, A. J., Solow, A. & Tregenza, N. Will harbour porpoises (Phocoena phocoena) habituate to pingers?. J. Cetacean Res. Manag. 3, 81–86 (2001).
Google Scholar 
Bruno, C. A. et al. Acoustic deterrent devices as mitigation tool to prevent dolphin-fishery interactions in the Aeolian Archipelago (Southern Tyrrhenian Sea, Italy). Mediterr. Mar. Sci. 22, 408–421 (2021).
Google Scholar 
Enger, P. S. Frequency discrimination in teleosts—central or peripheral in Hearing and sound communication in fishes (eds. Tavolga, W. N. et al.) 243–255 (Springer-Verlag, New York, 1981).
Google Scholar 
Halvorsen, M. B., Casper, B. M., Matthews, F., Carlson, T. J. & Popper, A. N. Effects of exposure to pile-driving sounds on the lake sturgeon, Nile tilapia and hogchoker. Proc. R. Soc. B Biol. Sci. 279, 4705–4714 (2012).
Google Scholar 
Ladich, F. Sound communication in fishes and the influence of ambient and anthropogenic noise. Bioacoustics 17, 34–38 (2008).
Google Scholar 
McCauley, R. D., Fewtrell, J. & Popper, A. N. High intensity anthropogenic sound damages fish ears. J. Acoust. Soc. Am. 113, 638–642 (2003).ADS 

Google Scholar 
Slabbekoorn, H. et al. A noisy spring: the impact of globally rising underwater sound levels on fish. Trends Ecol. Evol. 25, 419–427 (2010).
Google Scholar 
Gazo, M., Gonzalvo, J. & Aguilar, A. Pingers as deterrents of bottlenose dolphins interacting with trammel nets. Fish. Res. 92, 70–75 (2008).
Google Scholar 
Waples, D. M. et al. A field test of acoustic deterrent devices used to reduce interactions between bottlenose dolphins and a coastal gillnet fishery. Biol. Conserv. 157, 163–171 (2013).
Google Scholar 
Leaper, R. & Calderan, S. Review of methods used to reduce risks of cetacean bycatch and entanglements. CMS Tech. Ser. 38 (UNEP/CMS Secretariat, Bonn, Germany, 2018). More