Philippa Kaur

Woollings, T., Hannachi, A. & Hoskins, B. Variability of the North Atlantic eddy-driven jet stream. Q J. R. Meteorol. Soc. 136, 856–868 (2010).ADS 
Article 

Google Scholar 
Coumou, D., Capua, D. I., Vavrus, G., Wang, L. S. & Wang, S. The influence of Arctic amplification on mid-latitude summer circulation. Nat. Commun. 9, 2959 (2018).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Belmecheri, S., Babst, F., Hudson, A. R., Betancourt, J. & Trouet, V. Northern Hemisphere jet stream position indices as diagnostic tools for climate and ecosystem dynamics. Earth Interact. 21, 1–23 (2017).Article 

Google Scholar 
Trouet, V., Babst, F. & Meko, M. Recent enhanced high-summer North Atlantic Jet variability emerges from three-century context. Nat. Commun. 9, 180 (2018).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Lehmann, J. & Coumou, D. The influence of mid-latitude storm tracks on hot, cold, dry and wet extremes. Sci. Rep. 5, 17491 (2015).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Mahlstein, I., Martius, O., Chevalier, C. & Ginsbourger, D. Changes in the odds of extreme events in the Atlantic basin depending on the position of the extratropical jet. Geophys. Res. Lett. 39, 1–6 (2012).
Google Scholar 
Röthlisberger, M., Pfahl, S. & Martius, O. Regional-scale jet waviness modulates the occurrence of midlatitude weather extremes. Geophys. Res. Lett. 43, 10,910–989,997 (2016).Article 

Google Scholar 
Brunner, L., Schaller, N., Anstey, J., Sillmann, J. & Steiner, A. K. Dependence of present and future European temperature extremes on the location of atmospheric blocking. Geophys. Res. Lett. 45, 6311–6320 (2018).ADS 
PubMed 
PubMed Central 

Google Scholar 
Dong, B., Sutton, R. T., Woollings, T. & Hodges, K. Variability of the North Atlantic summer storm track: mechanisms and impacts on European climate. Environ. Res. Lett. 8, 34037 (2013).Article 

Google Scholar 
Mann, M. E. et al. Influence of anthropogenic climate change on planetary wave resonance and extreme weather events. Sci. Rep. 7, 45242 (2017).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Coumou, D. & Rahmstorf, S. A decade of weather extremes. Nat. Clim. Change 2, 491–496 (2012).ADS 
Article 

Google Scholar 
Schumacher, D. L. et al. Amplification of mega-heatwaves through heat torrents fuelled by upwind drought. Nat. Geosci. 12, 712–717 (2019).ADS 
CAS 
Article 

Google Scholar 
Zscheischler, J. et al. Future climate risk from compound events. Nat. Clim. Change 8, 469–477 (2018).ADS 
Article 

Google Scholar 
Lobell, D. B., Schlenker, W. & Costa-Roberts, J. Climate trends and global crop production since 1980. Science 333, 616–620 (2011).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Buras, A., Rammig, A. & Zang, C. S. Quantifying impacts of the 2018 drought on European ecosystems in comparison to 2003. Biogeosciences 17, 1655–1672 (2020).ADS 
Article 

Google Scholar 
Reichstein, M. et al. Climate extremes and the carbon cycle. Nature 500, 287–295 (2013).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Frank, D. et al. Effects of climate extremes on the terrestrial carbon cycle: concepts, processes and potential future impacts. Glob. Change Biol. 21, 2861–2880 (2015).ADS 
Article 

Google Scholar 
Sillmann, J. et al. Understanding, modeling and predicting weather and climate extremes: challenges and opportunities. Weather Clim. Extrem. 18, 65–74 (2017).Article 

Google Scholar 
Barriopedro, D., Fischer, E. M., Luterbacher, J., Trigo, R. M. & García-Herrera, R. The hot summer of 2010: redrawing the temperature record map of Europe. Science 332, 220–224 (2011).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Ciais, P. et al. Europe-wide reduction in primary productivity caused by the heat and drought in 2003. Nature 437, 529–533 (2005).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Bastos, A., Gouveia, C. M., Trigo, R. M. & Running, S. W. Analysing the spatio-temporal impacts of the 2003 and 2010 extreme heatwaves on plant productivity in Europe. Biogeosciences 11, 3421–3435 (2014).ADS 
Article 

Google Scholar 
Fischer, E. M., Seneviratne, S. I., Vidale, P. L., Lüthi, D. & Schär, C. Soil moisture–atmosphere interactions during the 2003 european summer heat wave. J. Clim. 20, 5081–5099 (2007).ADS 
Article 

Google Scholar 
Perkins-Kirkpatrick, S. E. & Lewis, S. C. Increasing trends in regional heatwaves. Nat. Commun. 11, 3357 (2020).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Pan, Y. et al. A large and persistent carbon sink in the world’s forests. Science 333, 988–993 (2011).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Friedlingstein, P. et al. Global carbon budget 2020. Earth Syst. Sci. Data 12, 3269–3340 (2020).ADS 
Article 

Google Scholar 
Kalnay, E. et al. The NCEP/NCAR 40-year reanalysis project. Bull. Am. Meteorol. Soc. 77, 437–472 (1996).ADS 
Article 

Google Scholar 
Rammig, A. et al. Coincidences of climate extremes and anomalous vegetation responses: comparing tree ring patterns to simulated productivity. Biogeosciences 12, 373–385 (2015).ADS 
Article 

Google Scholar 
Spinoni, J., Naumann, G., Vogt, J. V. & Barbosa, P. The biggest drought events in Europe from 1950 to 2012. J. Hydrol. Reg. Stud. 3, 509–524 (2015).Article 

Google Scholar 
Madonna, E., Li, C., Grams, C. M. & Woollings, T. The link between eddy-driven jet variability and weather regimes in the North Atlantic-European sector. Q J. R. Meteorol. Soc. 143, 2960–2972 (2017).ADS 
Article 

Google Scholar 
Grams, C. M., Beerli, R., Pfenninger, S., Staffell, I. & Wernli, H. Balancing Europe’s wind-power output through spatial deployment informed by weather regimes. Nat. Clim. Change 7, 557–562 (2017).Article 

Google Scholar 
Seftigen, K., Frank, D. C., Björklund, J., Babst, F. & Poulter, B. The climatic drivers of normalized difference vegetation index and tree-ring-based estimates of forest productivity are spatially coherent but temporally decoupled in Northern Hemispheric forests. Glob. Ecol. Biogeogr. 27, 1352–1365 (2018).Article 

Google Scholar 
Babst, F. et al. Above-ground woody carbon sequestration measured from tree rings is coherent with net ecosystem productivity at five eddy-covariance sites. N. Phytol. 201, 1289–1303 (2014).CAS 
Article 

Google Scholar 
Zweifel, R. & Sterck, F. A conceptual tree model explaining legacy effects on stem growth. Front. Glob. Change 1, 9 (2018).Article 

Google Scholar 
Fatichi, S., Pappas, C., Zscheischler, J. & Leuzinger, S. Modelling carbon sources and sinks in terrestrial vegetation. N. Phytol. 221, 652–668 (2019).CAS 
Article 

Google Scholar 
Wu, X. et al. Differentiating drought legacy effects on vegetation growth over the temperate Northern Hemisphere. Glob. Chang. Biol. 24, 504–516 (2018).ADS 
PubMed 
Article 

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

Google Scholar 
Davini, P. & Cagnazzo, C. On the misinterpretation of the North Atlantic Oscillation in CMIP5 models. Clim. Dyn. 43, 1497–1511 (2014).Article 

Google Scholar 
Pfahl, S. & Wernli, H. Quantifying the relevance of atmospheric blocking for co-located temperature extremes in the Northern Hemisphere on (sub-)daily time scales. Geophys. Res. Lett. 39 (2012).Drouard, M. & Woollings, T. Contrasting mechanisms of summer blocking over western Eurasia. Geophys. Res. Lett. 45, 12,040–12,048 (2018).Article 

Google Scholar 
Bastos, A. et al. European land CO2 sink influenced by NAO and East-Atlantic pattern coupling. Nat. Commun. 7, 10315 (2016).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Ascoli, D. et al. Inter-annual and decadal changes in teleconnections drive continental-scale synchronization of tree reproduction. Nat. Commun. 8, 1–9 (2017).CAS 
Article 

Google Scholar 
Sousa, P. M. et al. Responses of European precipitation distributions and regimes to different blocking locations. Clim. Dyn. 48, 1141–1160 (2017).Article 

Google Scholar 
Hacket-Pain, A. J., Cavin, L., Friend, A. D. & Jump, A. S. Consistent limitation of growth by high temperature and low precipitation from range core to southern edge of European beech indicates widespread vulnerability to changing climate. Eur. J. Res. 135, 897–909 (2016).Article 

Google Scholar 
Cavin, L. & Jump, A. S. Highest drought sensitivity and lowest resistance to growth suppression are found in the range core of the tree Fagus sylvatica L. not the equatorial range edge. Glob. Chang. Biol. 23, 362–379 (2017).ADS 
PubMed 
Article 

Google Scholar 
Leuschner, C. Drought response of European beech (Fagus sylvatica L.): A review. Perspect. Plant Ecol. Evol. Syst. 47, 125576 (2020).Article 

Google Scholar 
Muffler, L. et al. Lowest drought sensitivity and decreasing growth synchrony towards the dry distribution margin of European beech. J. Biogeogr. 47, 1910–1921 (2020).Article 

Google Scholar 
Wang, F. et al. Seedlings from marginal and core populations of European beech (Fagus sylvatica L.) respond differently to imposed drought and shade. Trees 35, 53–67 (2021).CAS 
Article 

Google Scholar 
Hall, R. J., Jones, J. M., Hanna, E., Scaife, A. A. & Erdélyi, R. Drivers and potential predictability of summertime North Atlantic polar front jet variability. Clim. Dyn. 48, 3869–3887 (2017).Article 

Google Scholar 
Screen, J. A. & Simmonds, I. Amplified mid-latitude planetary waves favour particular regional weather extremes. Nat. Clim. Change 4, 704–709 (2014).ADS 
Article 

Google Scholar 
Kornhuber, K. et al. Extreme weather events in early summer 2018 connected by a recurrent hemispheric wave-7 pattern. Environ. Res. Lett. 14, 54002 (2019).Article 

Google Scholar 
Shepherd, T. G. Atmospheric circulation as a source of uncertainty in climate change projections. Nat. Geosci. 7, 703–708 (2014).ADS 
CAS 
Article 

Google Scholar 
Peings, Y., Cattiaux, J., Vavrus, S. J. & Magnusdottir, G. Projected squeezing of the wintertime North-Atlantic jet. Environ. Res. Lett. 13, 74016 (2018).Article 

Google Scholar 
Matsueda, M. & Endo, H. The robustness of future changes in Northern Hemisphere blocking: a large ensemble projection with multiple sea surface temperature patterns. Geophys. Res. Lett. 44, 5158–5166 (2017).ADS 
Article 

Google Scholar 
Kwon, Y. O., Camacho, A., Martinez, C. & Seo, H. North Atlantic winter eddy-driven jet and atmospheric blocking variability in the Community Earth System Model version 1 Large Ensemble simulations. Clim. Dyn. 51, 3275–3289 (2018).Article 

Google Scholar 
Cohen, J. et al. Divergent consensuses on Arctic amplification influence on midlatitude severe winter weather. Nat. Clim. Change 10, 20–29 (2020).ADS 
Article 

Google Scholar 
de Vries, H., Woollings, T., Anstey, J., Haarsma, R. J. & Hazeleger, W. Atmospheric blocking and its relation to jet changes in a future climate. Clim. Dyn. 41, 2643–2654 (2013).Article 

Google Scholar 
Woollings, T. et al. Blocking and its response to climate change. Curr. Clim. Chang. Rep. 4, 287–300 (2018).Article 

Google Scholar 
Anderegg, W. R. L. et al. Pervasive drought legacies in forest ecosystems and their implications for carbon cycle models. Science 349, 528–532 (2015).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Sousa-Silva, R. et al. Tree diversity mitigates defoliation after a drought-induced tipping point. Glob. Chang. Biol. 24, 4304–4315 (2018).ADS 
PubMed 
Article 

Google Scholar 
Magri, D. Patterns of post-glacial spread and the extent of glacial refugia of European beech (Fagus sylvatica). J. Biogeogr. 35, 450–463 (2008).Article 

Google Scholar 
Cailleret, M. et al. A synthesis of radial growth patterns preceding tree mortality. Glob. Chang. Biol. 23, 1675–1690 (2017).ADS 
PubMed 
Article 

Google Scholar 
Dorado-Liñán, I. et al. Geographical adaptation prevails over species-specific determinism in trees’ vulnerability to climate change at Mediterranean rear-edge forests. Glob. Chan. Biol. 25, 1296–1314 (2019).ADS 
Article 

Google Scholar 
DeSoto, L. et al. Low growth resilience to drought is related to future mortality risk in trees. Nat. Commun. 11, 545 (2020).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Hacket-Pain, A. J., Friend, A. D., Lageard, J. G. A. & Thomas, P. A. The influence of masting phenomenon on growth–climate relationships in trees: explaining the influence of previous summers’ climate on ring width. Tree Physiol. 35, 319–330 (2015).PubMed 
Article 

Google Scholar 
Bréda, N., Huc, R., Granier, A. & Dreyer, E. Temperate forest trees and stands under severe drought: a review of ecophysiological responses, adaptation processes and long-term consequences. Ann. Sci. 63, 625–644 (2006).Article 

Google Scholar 
Hacket-Pain, A. J. et al. Climatically controlled reproduction drives interannual growth variability in a temperate tree species. Ecol. Lett. 21, 1833–1844 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
Popkin, G. How much can forests fight climate change? Nature 565, 280–282 (2019).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Davini, P. & D’Andrea, F. Northern Hemisphere atmospheric blocking representation in global climate models: twenty years of improvements? J. Clim. 29, 8823–8840 (2016).ADS 
Article 

Google Scholar 
Barton, N. P. & Ellis, A. W. Variability in wintertime position and strength of the North Pacific jet stream as represented by re-analysis data. Int. J. Climatol. 29, 851–862 (2009).Article 

Google Scholar 
Doblas-Reyes, F. J., Casado, M. J. & Pastor, M. A. Sensitivity of the Northern Hemisphere blocking frequency to the detection index. J. Geophys. Res. Atmos. 107, D2 (2002).Article 

Google Scholar 
Cook, E. R. & Peters, K. The smoothing spline: a new approach to standardizing forest interior tree-ring width series for dendroclimatic studies. Tree-Ring Bull. 41, 45–53 (1981).
Google Scholar 
Sitch, S. et al. Recent trends and drivers of regional sources and sinks of carbon dioxide. Biogeosciences 12, 653–679 (2015).ADS 
Article 

Google Scholar 
Team, R. Core (2020). R A Lang. Environ. Stat. Comput. R Found. Stat. Comput. Vienna, Austria. URL https://www.R-project.org (2020).Bunn, A. G. A dendrochronology program library in R (dplR). Dendrochronologia 26, 115–124 (2008).Article 

Google Scholar 
Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, (2015).Kuznetsova, A., Brockhoff, P. B. & Christensen, R. H. B. lmerTest package: Tests in linear mixed effects models. J. Stat. Softw. 82, 1–26 (2017).Barton, K. Mu-MIn: Multi-model inference. R Package Version 0.12.2/r18, (2009) http://R-Forge.R-project.org/projects/mumin/ More

Mann, J. Behavioral sampling methods for cetaceans: A review and critique. Mar. Mammal Sci. 15, 102–122 (1999).Article 

Google Scholar 
Pompanon, F. et al. Who is eating what: Diet assessment using next generation sequencing. Mol. Ecol. https://doi.org/10.1111/j.1365-294X.2011.05403.x (2012).Article 

Google Scholar 
Deagle, B. E. et al. Counting with DNA in metabarcoding studies: How should we convert sequence reads to dietary data?. Mol. Ecol. 28, 391–406 (2019).Article 

Google Scholar 
Berry, T. E. et al. DNA metabarcoding for diet analysis and biodiversity: A case study using the endangered Australian sea lion (Neophoca cinerea). Ecol. Evol. 7, 5435–5453 (2017).Article 

Google Scholar 
Brassea-Pérez, E., Schramm, Y., Heckel, G., Chong-Robles, J. & Lago-Lestón, A. Metabarcoding analysis of the Pacific harbor seal diet in Mexico. Mar. Biol. 166, 1–14 (2019).Article 

Google Scholar 
Ford, M. J. et al. Estimation of a killer whale (Orcinus orca) population’s diet using sequencing analysis of DNA from feces. PLoS ONE 11, e0144956 (2016).Article 

Google Scholar 
Thomas, A. C., Deagle, B. E., Eveson, J. P., Harsch, C. H. & Trites, A. W. Quantitative DNA metabarcoding: Improved estimates of species proportional biomass using correction factors derived from control material. Mol. Ecol. Resour. 16, 714–726 (2016).CAS 
Article 

Google Scholar 
Deagle, B. E., Chiaradia, A., Mcinnes, J. & Jarman, S. N. Pyrosequencing faecal DNA to determine diet of little penguins: is what goes in what comes out? https://doi.org/10.1007/s10592-010-0096-6.Ando, H. et al. Methodological trends and perspectives of animal dietary studies by noninvasive fecal DNA metabarcoding. Environ. DNA 2, 391–406 (2020).Article 

Google Scholar 
Günther, B., Fromentin, J., Metral, L. & Arnaud-haond, S. Metabarcoding confirms the opportunistic foraging behaviour of Atlantic bluefin tuna and reveals the importance of gelatinous prey. PeerJ 9, e11757. https://doi.org/10.7717/peerj.11757 (2021).Article 

Google Scholar 
Simon, M., Hanson, M. B., Murrey, L., Tougaard, J. & Ugarte, F. From captivity to the wild and back: An attempt to release keiko the killer whale. Mar. Mammal Sci. 25, 693–705 (2009).Article 

Google Scholar 
Moore, M. et al. Rehabilitation and release of marine mammals in the United States: Risks and benefits. Mar. Mammal Sci. 23, 731–750 (2007).Article 

Google Scholar 
Leray, M. et al. A new versatile primer set targeting a short fragment of the mitochondrial COI region for metabarcoding metazoan diversity: Application for characterizing coral reef fish gut contents. Front. Zool. 10, 1–14 (2013).Article 

Google Scholar 
Geller, J., Meyer, C. & Parker, M. Redesign of PCR primers for mitochondrial cytochrome c oxidase subunit I for marine invertebrates and application in all-taxa biotic surveys. Mol. Ecol. Resour. 13(5), 851–861. https://doi.org/10.1111/1755-0998.12138 (2013).CAS 
Article 

Google Scholar 
Blaxter, M. L. et al. A molecular evolutionary framework for the phylum Nematoda. Nature https://doi.org/10.1038/32160 (1998).Article 

Google Scholar 
Sinniger, F. et al. Worldwide analysis of sedimentary DNA reveals major gaps in taxonomic knowledge of deep-sea benthos. Front. Mar. Sci. 3, 1–14 (2016).Article 

Google Scholar 
Brandt, M. I. et al. Bioinformatic pipelines combining denoising and clustering tools allow for more comprehensive prokaryotic and eukaryotic metabarcoding. Mol. Ecol. Resour. 21(6), 1904–1921 (2021).Article 

Google Scholar 
Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.journal https://doi.org/10.14806/ej.17.1.200 (2011).Article 

Google Scholar 
Callahan, B. J. et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583 (2016).CAS 
Article 

Google Scholar 
Antich, A., Palacin, C., Wangensteen, O. S. & Turon, X. To denoise or to cluster, that is not the question: Optimizing pipelines for COI metabarcoding and metaphylogeography. BMC Bioinform. 22, 1–25 (2021).Article 

Google Scholar 
Mahé, F., Rognes, T., Quince, C., de Vargas, C. & Dunthorn, M. Swarmv2: Highly-scalable and high-resolution amplicon clustering. PeerJ 2015, 1–12 (2015).
Google Scholar 
Quast, C. et al. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. https://doi.org/10.1093/nar/gks1219 (2013).Article 

Google Scholar 
Machida, R. J., Leray, M., Ho, S.-L. & Knowlton, N. Metazoan mitochondrial gene sequence reference datasets for taxonomic assignment of environmental samples. Sci. Data 4, 170027 (2017).CAS 
Article 

Google Scholar 
Wang, Q., Garrity, G. M., Tiedje, J. M. & Cole, J. R. Naıve Bayesian classifier for rapid assignment of rRNA sequences.pdf. Appl. Environ. Microbiol. 73, 5261–5267 (2007).ADS 
CAS 
Article 

Google Scholar 
Davis, N. M., Di Proctor, M., Holmes, S. P., Relman, D. A. & Callahan, B. J. Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data. Microbiome https://doi.org/10.1186/s40168-018-0605-2 (2018).Article 

Google Scholar 
Wangensteen, O. S., Palacín, C., Guardiola, M. & Turon, X. DNA metabarcoding of littoral hardbottom communities: High diversity and database gaps revealed by two molecular markers. PeerJ 2018, 1–30 (2018).
Google Scholar 
Schnell, I. B., Bohmann, K. & Gilbert, M. T. P. Tag jumps illuminated – reducing sequence-to-sample misidentifications in metabarcoding studies. Mol. Ecol. Resour. 15, 1289–1303 (2015).CAS 
Article 

Google Scholar 
Song, X. et al. A new deep-sea hydroid (Cnidaria:Hydrozoa ) from the Bering Sea Basin reveals high genetic relevance to Arctic and adjacent shallow-water species. Polar Biol. 39, 461–471 (2016).Article 

Google Scholar 
Frøslev, T. G. et al. Algorithm for post-clustering curation of DNA amplicon data yields reliable biodiversity estimates. Nat. Commun. 8, 1–11 (2017).Article 

Google Scholar 
Vacquié-Garcia, J., Lydersen, C., Ims, R. A. & Kovacs, K. M. Habitats and movement patterns of white whales Delphinapterus leucas in Svalbard, Norway in a changing climate. Mov. Ecol. 6, 1–12 (2018).Article 

Google Scholar 
Kastelein, R. A., Nieuwstraten, S. H. & Verstegen, M. W. A. Passage time of carmine red dye through the digestion tract . In The Biology of the Harbour Porpoise 235–245 (1997).Lesage, V., Lair, S., Turgeon, S. & Beland, P. Diet of St. Lawrence Estuary Beluga (Delphinapterus leucas) in a changing ecosystem. Can. Field-Nat. 134, 21–35 (2020).Article 

Google Scholar 
Bluhm, B. A. & Gradinger, R. Regional variability in food availability for arctic marine mammals. Ecol. Appl. 18, S77–S96 (2008).Article 

Google Scholar 
Quakenbush, L. T. et al. Diet of beluga whales, Delphinapterus leucas, in Alaska from stomach contents, March-November. Mar. Fish. Rev. 77, 70–84 (2015).Article 

Google Scholar 
Choy, E. S. et al. Variation in the diet of beluga whales in response to changes in prey availability: Insights on changes in the Beaufort Sea ecosystem. Mar. Ecol. Prog. Ser. 647, 195–210 (2020).ADS 
CAS 
Article 

Google Scholar 
Mychek-Londer, J. G., Chaganti, S. R. & Heath, D. D. Metabarcoding of native and invasive species in stomach contents of Great Lakes fishes. PLoS ONE 15, 1–22 (2020).Article 

Google Scholar 
Nedreaas, K. Food and feeding habits of young saithe, Pollachius virens (L.), on the coast of Western Norway. Fisk. Skr. Ser. Havundersokelser 18, 263–301 (1987).
Google Scholar 
Højgaard, D. P. Food and parasitic nematodes of saithe, Pollachius virens (L.), from the Faroe Islands. Sarsia 84, 473–478 (1999).Article 

Google Scholar 
Ekbaum, E. Notes on the occurrence of Acanthocephala in Pacific fishes: I. Echinorhynchus gadi (Zoega) Müller in salmon and E. lageniformis sp. nov. and Corynosoma strumosum (Rudolphi) in two species of flounder. Parasitology 30, 267–274 (1938).Article 

Google Scholar 
Baptista-Fernandes, T. et al. Human gastric hyperinfection by Anisakis simplex: A severe and unusual presentation and a brief review. Int. J. Infect. Dis. 64, 38–41 (2017).Article 

Google Scholar 
Hubert, B., Bacou, J. & Belveze, H. Epidemiology of human anisakiasis: Incidence and sources in France. Am. J. Trop. Med. Hyg. 40, 301–303 (1989).CAS 
Article 

Google Scholar 
Hays, R., Measures, L. N. & Huot, J. Capelin (Mallotus villosus) and herring (Clupea harengus) as paratenic hosts of Anisakis simplex, a parasite of beluga (Delphinapterus leucas) in the St. Lawrence estuary. Can. J. Zool. 78, 1411–1417 (1998).Article 

Google Scholar 
Yanong, R. P. E. Nematode (Roundworm) Infections in Fish Vol. 1, 1–9 (2002).Jauniaux, T. et al. Post-mortem findings and causes of death of harbour porpoises (Phocoena phocoena) stranded from 1990 to 2000 along the coastlines of Belgium and Northern France. J. Compar. Pathol. 126, 243–253 (2002).CAS 
Article 

Google Scholar  More

Phylogenetic placement of Saccharibacteria rhodopsins (SacRs) shows that these sequences form a sibling clade to characterized light-driven inward and outward H+ pumps (Fig. 1a). We selected three phylogenetically diverse SacRs from freshwater lakes (Table S1) and two related, previously uncharacterized sequences from the Gammaproteobacteria (Kushneria aurantia and Halomonas sp.) for synthesis and functional characterization (highlighted in Fig. 1a). All sequences have Asp–Thr–Ser (DTS) residues at the positions of D85–T96–D96 of bacteriorhodopsin (BR) in the third transmembrane helix (Fig. S1). These residues are known as the triplet DTD motif and represent key residues for proton pumping function in BR [6].Fig. 1: Characteristics of Saccharibacteria rhodopsins (SacRs).a Rhodopsin protein tree indicating that SacRs from freshwater lakes form a broad clade of proton pumps. b The ion-pumping activity of SacRs. Blue and green lines indicate the pH change with and without 10 μM CCCP, respectively. Yellow bars indicate the period of light illumination. c Time evolution of transient absorption changes of SacRNC335 in 100 mM NaCl, 20 mM HEPES–NaOH, pH 7.0, and POPE/POPG (molar ratio 3:1) vesicles with a lipid to protein molar ratio = 50. Time evolution at 406 nm (blue, representing the M accumulation), 561 nm (green, representing the bleaching of the initial state and the L accumulation), and 638 nm (red, representing the K and O accumulations). Yellow lines indicate fitting curves by a multi-exponential function. Inset: The photocycle of SacRNC335 based on the fitting in (c) and a kinetic model assuming a sequential photocycle. The lifetime (τ) of each intermediate is indicated by numbers as follow (mean ± S.D., fraction of the intermediate decayed with each lifetime in its double exponential decay is indicated in parentheses): I: τ = 1.7 ± 0.3 μs (42%), τ = 13 ± 1.8 μs (58%), II: τ = 118 ± 2 μs, III: τ = 1.6 ± 0.1 ms, IV: τ = 23.5 ± 1.0 ms, V: τ = 98.4 ± 6.4 ms (56%), τ = 384 ± 18 ms (44%). d Genomic context of SacRNC335. Neighboring genes with above-threshold KEGG annotations are indicated in gray with the highest-scoring HMM model. Genes without KEGG annotations are indicated in white.Full size imageProton transport assays for the SacRs and Gammaproteobacteria proteins expressed in Escherichia coli showed marked decrease of external pH upon light illumination (Fig. 1b and Fig. S2), indicating that these proteins are light-driven outward H+ pumps. The pH decrease was almost eliminated after adding the protonophore carbonyl cyanide m-chlorophenyl hydrazone (CCCP), which dissipates the H+ gradient, confirming that it was indeed formed upon illumination (Fig. 1b and Fig. S2). We also characterized the absorption spectra and the photocycle of the SacRs, showing that the three rhodopsins have an absorption peak around 550 nm (Fig. S3). The photocycle of the SacRs, determined by measuring the transient absorption change after nanosecond laser pulse illumination (Fig. 1c and Fig. S4), displays a blue-shifted M intermediate that represents the deprotonated state of the retinal chromophore. This has been observed for other H+ pumping rhodopsins [7, 8] and indicates that the proton bound to retinal is translocated during pumping.Given that SacRs function as outward proton pumps, we searched Saccharibacteria genomes for the F1Fo ATP synthase that would be required to harness the generated proton motive force for ATP synthesis. HMM searches showed that all genomes encoded the complete ATP synthase gene cluster and, furthermore, had c subunits with motifs consistent with H+ binding, instead of Na+ binding (Table S1 and Fig. S5). Together, our experimental and genomic analyses strongly suggest that some Saccharibacteria utilize rhodopsins for auxiliary energy generation in addition to their core fermentative capacities [6].Retinal is the rhodopsin chromophore that enables function of the complex upon illumination [9]. We found no evidence for the presence of β-carotene 15,15’-dioxygenase (blh), which produces all-trans-retinal (ATR) from β-carotene, in Saccharibacteria genomes encoding rhodopsin. This absence was likely not due to genome incompleteness, as genomic bins were generally of high quality (79–98% completeness, Table S1) and rhodopsin genomic loci were well-sampled. Additionally, no conserved hypothetical proteins were present in these regions, where blh is often found [10] (Fig. 1d, Fig. S6 and Table S2). As SacRs do contain the conserved lysine for retinal binding [4], we instead hypothesized that Saccharibacteria may uptake retinal from the environment, as has been previously observed for other microorganisms encoding rhodopsin but also lacking blh [11, 12].We tested the ability of SacR proteins to bind ATR from an external source by performing a retinal reconstitution assay. In contrast to the proton transport assays, where rhodopsin was expressed in the presence of ATR, here ATR was dissociated from the purified complex and the visible absorbance of rhodopsin was measured upon re-addition of ATR [13]. Both Gloeobacter rhodopsin (GR), a typical Type-1 outward H+ pump, and SacRs showed an increase in absorption in the visible region with time after the addition of ATR (Fig. 2a and Fig. S7). For all SacRs, the binding of ATR by their apoprotein was saturated within 30 sec after retinal addition (Fig. 2b), indicating that SacR is able to be efficiently functionalized using externally derived ATR. The observed reconstitution rate is substantially faster than that of GR (  > 20 min) and comparable to that of heliorhodopsin, which is used by other microorganisms also lacking a retinal synthetic pathway and rapidly binds ATR through a small opening in the apoprotein [12]. In the structure of SacRNC335 modeled by Alphafold2 [14, 15], a similar hole is visible in the protein moiety constructing the retinal binding pocket (Fig. S8). Hence, SacRs may also bind retinal through this hole in a similar manner to TaHeR (heliorhodopsin).Fig. 2: Binding of retinal by Saccharibacteria rhodopsins and context for biosynthesis.a UV-visible absorption spectra showing the regeneration of retinal binding to SacRNC335 and GR in 20 mM HEPES–NaOH, pH 7.0, 100 mM NaCl and 0.05% n-dodecyl-β-D-maltoside (DDM). In SacRNC335, a peak around 470 nm was transiently observed in the spectrum 30 s after the addition of ATR, suggesting that an intermediate species appears during the retinal incorporation process that involves formation of the Schiff base linkage. b Time evolution of visible absorption representing retinal binding to apo-protein. Numbers in parentheses in the legend indicate the absorption maxima of each rhodopsin. c Genetic potential for β-carotene 15,15’-dioxygenase (blh) production in freshwater lake metagenomes where SacRs are found. Fractions indicate the number of blh-encoding scaffolds taxonomically affiliated with the Actinobacteria in each sample. d Conceptual diagram illustrating potential retinal exchange between Saccharibacteria and host cells. ATR all-trans-retinal, GR Gloeobacter rhodopsin, AM Alinen Mustajärvi, Ki Kiruna, rhod. rhodopsin.Full size imageSaccharibacteria with rhodopsin must obtain retinal from other organisms. To evaluate possible sources of ATR, we investigated the genetic potential for retinal biosynthesis in 15 subarctic and boreal lakes [16] where Saccharibacteria with rhodopsin were present (Fig. S9). Blh-encoding scaffolds were found in 14 of the 15 metagenomes profiled (~93%) and, in nearly all cases, these scaffolds derived from Actinobacteria (Fig. 2c and Table S3). This is intriguing because Actinobacteria are known to be hosts of Saccharibacteria in the human microbiome [17, 18] and potentially more generally [4, 19]. BLAST searches against genome bins from the same samples indicated that these Actinobacteria were members of the order Nanopelagicales (Table S3) and often encode a rhodopsin (phylogenetically distinct from SacRs) in close genomic proximity to blh genes (Table S4). HMM searches revealed that these genomes also harbor homologs of the crtI, crtE, crtB, and crtY genes necessary for β-carotene production [20]. More

Fatty acid profilePlukenetia volubilisThe fatty acid composition of P. volubilis is the most well studied in the genus, and the results from the two P. volubilis accessions from Ecuador and Peru in the current study are similar to previous results. The most abundant fatty acid in the seed oil of P. volubilis from Ecuador and Peru, respectively, is α-linolenic acid (C18:3 n-3, ω-3, ALA; 51.5 ± 3.3 and 46.6 ± 1.2%), followed by linoleic acid (C18:2 n-6, ω-6, LA; 32.5 ± 3.9 and 36.5 ± 0.8%), oleic acid (C18:1, OA; 8.5 ± 1,2 and 8.3 ± 0,4%) and smaller amounts ( More

Ellis, E. C. & Ramankutty, N. Putting people in the map: anthropogenic biomes of the world. Frontiers in Ecology and the Environment 6, 439–447 (2008).Article 

Google Scholar 
Pecl, G. T. et al. Biodiversity redistribution under climate change: Impacts on ecosystems and human well-being. Science 355, (2017).Di Marco, M., Venter, O., Possingham, H. P. & Watson, J. E. Changes in human footprint drive changes in species extinction risk. Nature communications 9, 1–9 (2018).ADS 
Article 
CAS 

Google Scholar 
Kreidenweis, U. et al. Pasture intensification is insufficient to relieve pressure on conservation priority areas in open agricultural markets. Global change biology 24, 3199–3213 (2018).ADS 
PubMed 
Article 
PubMed Central 

Google Scholar 
Gong, P. et al. Annual maps of global artificial impervious area (GAIA) between 1985 and 2018. Remote Sensing of Environment 236, 111510 (2020).ADS 
Article 

Google Scholar 
Mu, H. et al. Evaluation of Light Pollution in Global Protected Areas from 1992 to 2018. Remote Sensing 13, 1849 (2021).ADS 
Article 

Google Scholar 
Wang, L. et al. Mapping population density in China between 1990 and 2010 using remote sensing. Remote sensing of environment 210, 269–281 (2018).ADS 
Article 

Google Scholar 
Raiter, K. G., Possingham, H. P., Prober, S. M. & Hobbs, R. J. Under the radar: mitigating enigmatic ecological impacts. Trends in ecology & evolution 29, 635–644 (2014).Article 

Google Scholar 
Nikhil, S. et al. Application of GIS and AHP Method in Forest Fire Risk Zone Mapping: a Study of the Parambikulam Tiger Reserve, Kerala, India. Journal of Geovisualization and Spatial Analysis 5, 1–14 (2021).Article 

Google Scholar 
Tucker, M. A. et al. Moving in the Anthropocene: Global reductions in terrestrial mammalian movements. Science 359, 466–469 (2018).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
Steffen W, et al. Planetary boundaries: Guiding human development on a changing planet. Science 347, (2015).Venter, O. et al. Sixteen years of change in the global terrestrial human footprint and implications for biodiversity conservation. Nature communications 7, 1–11 (2016).Article 
CAS 

Google Scholar 
Venter, O. et al. Global terrestrial Human Footprint maps for 1993 and 2009. Scientific data 3, 1–10 (2016).Article 

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

Google Scholar 
Mu, H. et al. Evaluation of the policy-driven ecological network in the Three-North Shelterbelt region of China. Landscape and Urban Planning 218, 104305 (2022).Article 

Google Scholar 
Hoffmann, S., Irl, S. D. & Beierkuhnlein, C. Predicted climate shifts within terrestrial protected areas worldwide. Nature communications 10, 1–10 (2019).Article 
CAS 

Google Scholar 
Sanderson, E. W. et al. The human footprint and the last of the wild: the human footprint is a global map of human influence on the land surface, which suggests that human beings are stewards of nature, whether we like it or not. Bioscience 52, 891–904 (2002).Article 

Google Scholar 
Williams, B. A. et al. Change in terrestrial human footprint drives continued loss of intact ecosystems. One Earth 3, 371–382 (2020).ADS 
Article 

Google Scholar 
Allan, J. R., Venter, O. & Watson, J. E. Temporally inter-comparable maps of terrestrial wilderness and the Last of the Wild. Scientific data 4, 1–8 (2017).Article 

Google Scholar 
Di Marco, M., Ferrier, S., Harwood, T. D., Hoskins, A. J. & Watson, J. E. Wilderness areas halve the extinction risk of terrestrial biodiversity. Nature 573, 582–585 (2019).ADS 
PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
Yang, R. et al. Cost-effective priorities for the expansion of global terrestrial protected areas: Setting post-2020 global and national targets. Science Advances 6, eabc3436 (2020).ADS 
PubMed 
Article 
PubMed Central 

Google Scholar 
Maxwell, S. L. et al. Area-based conservation in the twenty-first century. Nature 586, 217–227 (2020).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
Theobald, D. M. et al. Earth transformed: detailed mapping of global human modification from 1990 to 2017. Earth System Science Data 12, 1953–1972 (2020).ADS 
Article 

Google Scholar 
Kennedy, C. M., Oakleaf, J. R., Theobald, D. M., Baruch‐Mordo, S. & Kiesecker, J. Managing the middle: A shift in conservation priorities based on the global human modification gradient. Global Change Biology 25, 811–826 (2019).ADS 
PubMed 
Article 
PubMed Central 

Google Scholar 
Watson, J. E. et al. The exceptional value of intact forest ecosystems. Nature ecology & evolution 2, 599–610 (2018).Article 

Google Scholar 
Wolkovich, E., Cook, B., McLauchlan, K. & Davies, T. Temporal ecology in the Anthropocene. Ecology letters 17, 1365–1379 (2014).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
Olson, D. M. et al. Terrestrial Ecoregions of the World: A New Map of Life on EarthA new global map of terrestrial ecoregions provides an innovative tool for conserving biodiversity. Bioscience 51, 933–938 (2001).Article 

Google Scholar 
Li, X., Zhou, Y., Zhao, M. & Zhao, X. A harmonized global nighttime light dataset 1992–2018. Scientific data 7, 1–9 (2020).Article 
CAS 

Google Scholar 
Luck, G. W., Ricketts, T. H., Daily, G. C. & Imhoff, M. Alleviating spatial conflict between people and biodiversity. Proceedings of the National Academy of Sciences 101, 182–186 (2004).ADS 
CAS 
Article 

Google Scholar 
Gong, P., Li, X. & Zhang, W. 40-Year (1978–2017) human settlement changes in China reflected by impervious surfaces from satellite remote sensing. Science Bulletin 64, 756–763 (2019).ADS 
Article 

Google Scholar 
Hu, T., Yang, J., Li, X. & Gong, P. Mapping urban land use by using landsat images and open social data. Remote Sensing 8, 151 (2016).ADS 
CAS 
Article 

Google Scholar 
Li, X. et al. Mapping global urban boundaries from the global artificial impervious area (GAIA) data. Environmental Research Letters 15, 094044 (2020).ADS 
Article 

Google Scholar 
Li, X., Zhou, Y., Zhu, Z. & Cao, W. A national dataset of 30 m annual urban extent dynamics (1985–2015) in the conterminous United States. Earth System Science Data 12, 357–371 (2020).ADS 
Article 

Google Scholar 
Zhang, X. et al. Development of a global 30 m impervious surface map using multisource and multitemporal remote sensing datasets with the Google Earth Engine platform. Earth System Science Data 12, 1625–1648 (2020).ADS 
Article 

Google Scholar 
Li, X., Gong, P. & Liang, L. A 30-year (1984–2013) record of annual urban dynamics of Beijing City derived from Landsat data. Remote Sensing of Environment 166, 78–90 (2015).ADS 
Article 

Google Scholar 
Butchart, S. H. et al. Global biodiversity: indicators of recent declines. Science 328, 1164–1168 (2010).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
Tratalos, J., Fuller, R. A., Warren, P. H., Davies, R. G. & Gaston, K. J. Urban form, biodiversity potential and ecosystem services. Landscape and urban planning 83, 308–317 (2007).Article 

Google Scholar 
Fry, J. A. et al. Completion of the 2006 national land cover database for the conterminous United States. PE&RS. Photogrammetric Engineering & Remote Sensing 77, 858–864 (2011).
Google Scholar 
Elvidge, C. D., Baugh, K., Zhizhin, M., Hsu, F. C. & Ghosh, T. VIIRS night-time lights. International Journal of Remote Sensing 38, 5860–5879 (2017).ADS 
Article 

Google Scholar 
Zhou, Y., Li, X., Asrar, G. R., Smith, S. J. & Imhoff, M. A global record of annual urban dynamics (1992–2013) from nighttime lights. Remote Sensing of Environment 219, 206–220 (2018).ADS 
Article 

Google Scholar 
Li, X. & Zhou, Y. A stepwise calibration of global DMSP/OLS stable nighttime light data (1992–2013). Remote Sensing 9, 637 (2017).ADS 
Article 

Google Scholar 
Li, X. & Zhou, Y. Urban mapping using DMSP/OLS stable night-time light: a review. International Journal of Remote Sensing 38, 6030–6046 (2017).ADS 
Article 

Google Scholar 
Cincotta, R. P., Wisnewski, J. & Engelman, R. Human population in the biodiversity hotspots. Nature 404, 990–992 (2000).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
McKee, J. K., Sciulli, P. W., Fooce, C. D. & Waite, T. A. Forecasting global biodiversity threats associated with human population growth. Biological Conservation 115, 161–164 (2004).Article 

Google Scholar 
Lloyd, C. T. et al. Global spatio-temporally harmonised datasets for producing high-resolution gridded population distribution datasets. Big Earth Data 3, 108–139 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
Lloyd, C. T., Sorichetta, A. & Tatem, A. J. High resolution global gridded data for use in population studies. Scientific data 4, 1–17 (2017).Article 

Google Scholar 
Gaston, K. J., Bennie, J., Davies, T. W. & Hopkins, J. The ecological impacts of nighttime light pollution: a mechanistic appraisal. Biological reviews 88, 912–927 (2013).PubMed 
Article 
PubMed Central 

Google Scholar 
Zhao, M. et al. Applications of satellite remote sensing of nighttime light observations: Advances, challenges, and perspectives. Remote Sensing 11, 1971 (2019).ADS 
Article 

Google Scholar 
Folberth, C. et al. The global cropland-sparing potential of high-yield farming. Nature Sustainability 3, 281–289 (2020).Article 

Google Scholar 
Zabel, F. et al. Global impacts of future cropland expansion and intensification on agricultural markets and biodiversity. Nature communications 10, 1–10 (2019).ADS 
CAS 
Article 

Google Scholar 
Plummer, S., Lecomte, P. & Doherty, M. The ESA climate change initiative (CCI): A European contribution to the generation of the global climate observing system. Remote Sensing of Environment 203, 2–8 (2017).ADS 
Article 

Google Scholar 
Ramankutty N, Evan AT, Monfreda C, Foley JA. Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000. Global biogeochemical cycles 22, (2008).Poore, J. & Nemecek, T. Reducing food’s environmental impacts through producers and consumers. Science 360, 987–992 (2018).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
Trombulak, S. C. & Frissell, C. A. Review of ecological effects of roads on terrestrial and aquatic communities. Conservation biology 14, 18–30 (2000).Article 

Google Scholar 
Paton, D. G., Ciuti, S., Quinn, M. & Boyce, M. S. Hunting exacerbates the response to human disturbance in large herbivores while migrating through a road network. Ecosphere 8, e01841 (2017).Article 

Google Scholar 
Center For International Earth Science Information Network –Columbia University, Georgia ITOSUO. Global roads open access data set, version 1 (gROADSv1). Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC), (2013).Wolter, C. & Arlinghaus, R. Navigation impacts on freshwater fish assemblages: the ecological relevance of swimming performance. Reviews in Fish Biology and Fisheries 13, 63–89 (2003).Article 

Google Scholar 
Wolter, C. Conservation of fish species diversity in navigable waterways. Landscape and Urban Planning 53, 135–144 (2001).Article 

Google Scholar 
Lehner, B., Verdin, K. & Jarvis, A. New global hydrography derived from spaceborne elevation data. Eos, Transactions American Geophysical Union 89, 93–94 (2008).ADS 
Article 

Google Scholar 
Mu, H. et al. An annual global terrestrial Human Footprint dataset from 2000 to 2018. figshare https://doi.org/10.6084/m9.figshare.16571064.v5 (2021).Dinerstein, E. et al. An ecoregion-based approach to protecting half the terrestrial realm. Bioscience 67, 534–545 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
Arino, O. et al. Global land cover map for 2009 (GlobCover 2009). European Space Agency (ESA) & Université catholique de Louvain (UCL), PANGAEA https://doi.org/10.1594/PANGAEA.787668 (2012).Watson, J. E. et al. Catastrophic declines in wilderness areas undermine global environment targets. Current Biology 26, 2929–2934 (2016).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
Díaz, S. et al. Set ambitious goals for biodiversity and sustainability. Science 370, 411–413 (2020).PubMed 
Article 
PubMed Central 

Google Scholar 
Oakleaf, J. R. et al. Mapping global development potential for renewable energy, fossil fuels, mining and agriculture sectors. Scientific data 6, 1–17 (2019).Article 

Google Scholar 
Rehbein, J. A. et al. Renewable energy development threatens many globally important biodiversity areas. Global change biology 26, 3040–3051 (2020).ADS 
PubMed 
Article 
PubMed Central 

Google Scholar  More

Ministry of the Environment Government of Japan. Designation of Evacuation Zone (accessed 07 April 2021); https://www.env.go.jp/chemi/rhm/h29kisoshiryo/h29kiso-09-04-01.html. (in Japanese).Fukushima Prefectural Government, Japan. About the Transition of Evacuation Zone (accessed 07 April 2021); https://www.pref.fukushima.lg.jp/site/portal/cat01-more.html. (in Japanese).Chino, M. et al. Preliminary estimation of release amounts of 131I and 137Cs accidentally discharged from the Fukushima Daiichi Nuclear Power Plant into the atmosphere. J. Nucl. Sci. Technol. 48, 1129–1134 (2011).CAS 
Article 

Google Scholar 
Koarashi, J., Atarashi-Andoh, M., Takeuchi, E. & Nishimura, S. Topographic heterogeneity effect on the accumulation of Fukushima-derived radiocaesium on forest floor driven by biologically mediated processes. Sci. Rep. 4, 6853 (2014).ADS 
CAS 
Article 

Google Scholar 
Saito, R., Nemoto, Y. & Tsukada, H. Relationship between radiocaesium in muscle and physicochemical fractions of radiocaesium in the stomach of wild boar. Sci. Rep. 10, 6796. https://doi.org/10.1038/s41598-020-63507-5 (2020).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Tsukada, H. From soil to agricultural-plants-transfer and distribution of radiocaesium. Kagaku (Chemistry). 67, 20–23 (2012) (in Japanese).CAS 

Google Scholar 
Saito, R. & Tsukada, H. Chapter 23: Physicochemical fractions of radiocaesium in the stomach contents of wild boar and its transfer to muscle tissue. In Behavior of Radionuclides in the Environment III (eds Nanba, K. et al.) 495–505 (Springer, 2022).Chapter 

Google Scholar 
Ishii, Y., Hayashi, S. & Takamura, T. Radiocaesium transfer in forest insect communities after the Fukushima Dai-ichi Nuclear Power Plant accident. PLoS ONE 12, e0171133 (2017).Article 

Google Scholar 
Matsushima, N., Ihara, S., Takase, M. & Horiguchi, T. Assessment of radiocaesium contamination in frogs 18 months after the Fukushima Daiichi nuclear disaster. Sci. Rep. 5, 9712 (2015).ADS 
CAS 
Article 

Google Scholar 
Ishii, Y., Matsuzaki, S. S. & Hayashi, S. Different factors determine 137Cs concentration factors of freshwater fish and aquatic organisms in lake and river ecosystems. J. Environ. Radioact. 213, 106102 (2020).CAS 
Article 

Google Scholar 
Wada, T. et al. Strong contrast of cesium radioactivity between marine and freshwater fish in Fukushima. J. Environ. Radioact. 204, 132–142 (2019).CAS 
Article 

Google Scholar 
Morishita, D. et al. Spatial and seasonal variations of radiocaesium concentrations in an algae-grazing annual fish, ayu Plecoglossus altivelis collected from Fukushima Prefecture in 2014. Fish. Sci. 85, 561–569 (2019).CAS 
Article 

Google Scholar 
Saito, R., Kabeya, M., Nemoto, Y. & Oomachi, H. Monitoring 137Cs concentrations in bird species occupying different ecological niches; game birds and raptors in Fukushima Prefecture. J. Environ. Radioact. 197, 67–73 (2019).CAS 
Article 

Google Scholar 
Merz, S., Shozugawa, K. & Steinhauser, G. Analysis of Japanese radionuclide monitoring data of food before and after the Fukushima nuclear accident. Environ. Sci. Technol. 49, 2875–2885 (2015).ADS 
CAS 
Article 

Google Scholar 
Steinhauser, G. & Saey, P. R. J. 137Cs in the meat of wild boars: A comparison of the impacts of Chernobyl and Fukushima. J. Radioanal. Nucl. Chem. 307, 1801–1806 (2016).CAS 
Article 

Google Scholar 
Nemoto, Y., Saito, R. & Oomachi, H. Seasonal variation of caesium-137 concentration in Asian black bear (Ursus thibetanus) and wild boar (Sus scrofa) in Fukushima Prefecture, Japan. PLoS ONE 13, e0200797. https://doi.org/10.1371/journal.pone.0200797 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Nemoto, Y. et al. Effects of 137Cs contamination after the TEPCO Fukushima Dai-ichi Nuclear Power Station accident on food and habitat of wild boar in Fukushima Prefecture. J. Environ. Radioact. 225, 106342 (2020).CAS 
Article 

Google Scholar 
Saito, R., Oomachi, H., Nemoto, Y. & Osako, M. Estimation of the total amount of the radiocaesium in the wild boar in their body – each organs survey and incineration residue survey. J. Soc. Rem. Radioact. Contam. Environ. 7, 165–173 (2019) (in Japanese).
Google Scholar 
Cui, L. et al. Radiocaesium concentrations in wild boars captured within 20 km of the Fukushima Daiichi Nuclear Power Plant. Sci. Rep. 10, 9272. https://doi.org/10.1038/s41598-020-66362-6 (2020).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Tagami, K., Howard, B. J. & Uchida, S. The time-dependent transfer factor of radiocaesium from soil to game animals in Japan after the Fukushima Dai-ichi nuclear accident. Environ. Sci. Technol. 50, 9424–9431. https://doi.org/10.1021/acs.est.6b03011 (2016).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Fuma, S. et al. Radiocaesium contamination of wild boars in Fukushima and surrounding regions after the Fukushima nuclear accident. Environ. Radioact. 164, 60–64 (2016).CAS 
Article 

Google Scholar 
Fukushima Prefectural Government, Japan. Monitoring of Wild Animals. Accessed 7 Apr 2021. https://www.pref.fukushima.lg.jp/site/portal/wildlife-radiationmonitoring1.html. (in Japanese).Strebl, F. & Tataruch, F. Time trends (1986–2003) of radiocaesium transfer to roe deer and wild boar in two Austrian forest regions. J. Environ. Radioactiv. 98, 137–152 (2007).CAS 
Article 

Google Scholar 
Ohtsuka-Ito, E. & Kanzaki, N. Population trends of the Japanese wild boar during the Showa era. Wildl. Cons. Jpn. 3, 95–105 (1998).Article 

Google Scholar 
Ueda, H. & Jiang, Z. The use of Orchards and Abandoned Orchard by wild boars in Yamanashi. Mamm. Sci. 44, 23–33 (2004) (in Japanese).
Google Scholar 
Fukushima Prefectural Government, Japan. Fukushima Prefecture Wild Boar Management Plan (Phase 3) (accessed 07 April 2021); https://www.pref.fukushima.lg.jp/uploaded/life/497785_1296285_misc.pdf (in Japanese).Anderson, D. et al. A comparison of methods to derive aggregated transfer factors using wild boar data from the Fukushima Prefecture. J. Environ. Radioact. 197, 101–108 (2019).CAS 
Article 

Google Scholar 
Pröhl, G. et al. Ecological half-lives of 90Sr and 137Cs in terrestrial and aquatic ecosystems. J. Environ. Radioactiv. 91, 41–72 (2006).Article 

Google Scholar 
Palo, R. T., White, N. & Danell, K. Spatial and temporal variations of 137Cs in moose Alces alces and transfer to man in northern Sweden. Wildlife Biol. 9, 207–212 (2003).Article 

Google Scholar 
Kodera, Y., Kanzaki, N., Ishikawa, N. & Minagawa, A. Food habits of wild boar (Sus scrofa) inhabiting Iwami District, Shimane Prefecture, western Japan. J. Mammal. Soc. Jpn. 53, 279–287 (2013) (in Japanese).
Google Scholar 
Kodera, Y. & Kanzaki, N. Food habits and nutritional condition of Japanese wild boar in Iwami district, Shimane Prefecture, western Japan. Wildl. Cons. Jpn. 6, 109–117 (2001) (in Japanese).
Google Scholar 
Arita, S. et al. Radioactive cesium accumulation during developmental stages of Largemouth Bass, Micropterus salmoides. Proc. JSCE. G. (Environment) 71, 267–276 (2015).Article 

Google Scholar 
Kodera, Y. C. S. F. prevention of epidemics from a point of view of the ecology of wild boar. J. Vet. Epidemiol. 23, 4–8 (2019) (in Japanese).Article 

Google Scholar 
Calenge, C., Maillard, D., Vassant, J. & Brandt, S. Summer and hunting season home ranges of wild boar (Sus scrofa) in two habitats in France. Game Wildl. Sci. 19, 281–301 (2002).
Google Scholar 
Massei, G., Genov, P. V., Staines, B. W. & Gorman, M. L. Factors influencing home range and activity of wild boar (Sus scrofa) in a Mediterranean coastal area. J. Zool. 242, 411–423 (1997).Article 

Google Scholar 
Morelle, K. et al. Towards understanding wild boar Sus scrofa movement: A synthetic movement ecology approach. Mammal Rev. 45, 15–29 (2015).Article 

Google Scholar 
Kapata, J., Mnich, K., Mnich, S., Karpińska, M. & Bielawska, A. Time-dependence of 137Cs activity concentration in wild game meat in Knyszyn Primeval Forest (Poland). J. Environ. Radioactiv. 141, 76–81 (2015).Article 

Google Scholar 
Gulakov, A. V. Accumulation and distribution of 137Cs and 90Sr in the body of the wild boar (Sus scrofa) found on the territory with radioactive. J. Environ. Radioactiv. 127, 171–175 (2014).CAS 
Article 

Google Scholar 
Hohmann, U. & Huckschlag, D. Investigations on the radiocaesium contamination of wild boar (Sus scrofa) meat in Rhineland-Palatinate: A stomach content analysis. Eur. J. Wildl. Res. 51, 263–270 (2005).Article 

Google Scholar 
Škrkal, J., Rulík, P., Fantínová, K., Mihalík, J. & Timková, J. Radiocaesium levels in game in the Czech Republic. J. Environ. Radioactiv. 139, 18–23 (2015).Article 

Google Scholar 
Japan Atomic Energy Agency (JAEA). 5th airborne monitoring survey (accessed 07 April 2021); https://emdb.jaea.go.jp/emdb/en/portals/b1020201/Steinhauser, G. Monitoring and radioecological characteristics of radiocaesium in Japanese beef after the Fukushima nuclear accident. J. Radioanal. Nucl. Chem. 311, 1367–1373 (2017).CAS 
Article 

Google Scholar 
Merz, S., Shozugawa, K. & Steinhauser, G. Effective and ecological half-lives of 90Sr and 137Cs observed in wheat and rice in Japan. J. Radioanal. Nucl. Chem. 307, 1807–1810 (2016).CAS 
Article 

Google Scholar  More

Henrich, J. et al. Costly punishment across human societies. Science https://doi.org/10.1126/science.1127333 (2006).Ostrom, E. Governing the Commons: The Evolution of Institutions for Collective Action (Cambridge University Press, 1990).Ostrom, E., Walker, J. & Gardner, R. Covenants with and without a sword: self-governance is possible. Am. Polit. Sci. Rev. 86, 404–417 (1992).Article 

Google Scholar 
Fehr, E. & Gächter, S. Cooperation and punishment in public goods experiments. Am. Econ. Rev. 90, 980–994 (2000).Article 

Google Scholar 
Dreber, A., Rand, D. G., Fudenberg, D. & Nowak, M. A. Winners don’t punish. Nature https://doi.org/10.1038/nature06723 (2008).Rand, D. G., Ohtsuki, H. & Nowak, M. A. Direct reciprocity with costly punishment: generous tit-for-tat prevails. J. Theor. Biol. https://doi.org/10.1016/j.jtbi.2008.09.015 (2009).Ohtsuki, H., Iwasa, Y. & Nowak, M. A. Indirect reciprocity provides only a narrow margin of efficiency for costly punishment. Nature https://doi.org/10.1038/nature07601 (2009).Sethi, R. & Somanathan, E. Understanding reciprocity. J. Econ. Behav. Organ. 50, 1–27 (2003).Article 

Google Scholar 
Bowles, S. & Gintis, H. A Cooperative Species (Princeton Univ. Press, 2011).Hauert, C., Traulsen, A., Brandt, H., Nowak, M. A. & Sigmund, K. Via freedom to coercion: the emergence of costly punishment. Science https://doi.org/10.1126/science.1141588 (2007).Brandt, H., Hauert, C. & Sigmund, K. Punishment and reputation in spatial public goods games. Proc. R. Soc. B https://doi.org/10.1098/rspb.2003.2336 (2003).Helbing, D., Szolnoki, A., Perc, M. & Szabó, G. Evolutionary establishment of moral and double moral standards through spatial interactions. PLoS Comput. Biol. https://doi.org/10.1371/journal.pcbi.1000758 (2010).Helbing, D., Szolnoki, A., Perc, M. & Szabó, G. Punish, but not too hard: how costly punishment spreads in the spatial public goods game. New J. Phys. https://doi.org/10.1088/1367-2630/12/8/083005 (2010).Perc, M. & Szolnoki, A. Self-organization of punishment in structured populations. New J. Phys. https://doi.org/10.1088/1367-2630/14/4/043013 (2012).Boyd, R., Gintis, H. & Bowles, S. Coordinated punishment of defectors sustains cooperation and can proliferate when rare. Science https://doi.org/10.1126/science.1183665 (2010).Sigmund, K., De Silva, H., Traulsen, A. & Hauert, C. Social learning promotes institutions for governing the commons. Nature 466, 861–863 (2010).CAS 
Article 

Google Scholar 
Hilbe, C., Traulsen, A., Röhl, T. & Milinski, M. Democratic decisions establish stable authorities that overcome the paradox of second-order punishment. Proc. Natl Acad. Sci. USA 111, 752–756 (2014).CAS 
Article 

Google Scholar 
Murphy, B. The Punisher’s Brain: The Evolution of Judge and Jury. By Hoffman, Morris B. Pp. xi, 359. Cambridge/NY, Cambridge University Press, 2014, £21.99/$30.00. Heythrop J. https://doi.org/10.1111/heyj.12249_81 (2015).Gruter, M. & Masters, R. D. Ostracism as a social and biological phenomenon: an introduction. Ethol. Sociobiolo. https://doi.org/10.1016/0162-3095(86)90043-9 (1986).Molleman, L., Kölle, F., Starmer, C. & Gächter, S. People prefer coordinated punishment in cooperative interactions. Nat. Hum. Behav. https://doi.org/10.1038/s41562-019-0707-2 (2019).Szolnoki, A., Szabó, G. & Perc, M. Phase diagrams for the spatial public goods game with pool punishment. Phys. Rev. E https://doi.org/10.1103/PhysRevE.83.036101 (2011).Ostrom, E. Collective action and the evolution of social norms. J. Econ. Perspect. 14, 137–158 (2000).Article 

Google Scholar 
Platteau, J.-P. Institutions, Social Norms, and Economic Development Vol. 1 (Psychology Press, 2000).van den Bergh, J. C. J. M., Ferrer-i-Carbonell, A. & Munda, G. Alternative models of individual behaviour and implications for environmental policy. Ecol. Econ. 32, 43–61 (2000).Article 

Google Scholar 
Traulsen, A., Nowak, M. A. & Pacheco, J. M. Stochastic dynamics of invasion and fixation. Phys. Rev. E 74, 11909 (2006).Article 

Google Scholar 
Dequech, D. Institutions, social norms, and decision-theoretic norms. J. Econ. Behav. Organ. 72, 70–78 (2009).Article 

Google Scholar 
Dunn, S. P. Bounded rationality is not fundamental uncertainty: a post Keynesian perspective. J. Post Keynes. Econ. 23, 567–587 (2001).Article 

Google Scholar 
Levin, S. The trouble of discounting tomorrow. Solutions 3, 20–24 (2012).
Google Scholar 
Alford, R. P. The proliferation of international courts and tribunals: international adjudication in ascendance. In Proc. Annual Meeting of the American Society of International Law Vol. 94, 160–165 (Cambridge University Press, 2000).Dunn, L. A. Containing Nuclear Proliferation (International Institute for Strategic Studies, 1991).Potoski, M. Green clubs in building block climate change regimes. Climatic Change 144, 53–63 (2017).Article 

Google Scholar 
Trzyna, T. C., Margold, E. & Osborn, J. K. World Directory of Environmental Organizations: A Handbook of National and International Organizations and Programs—Governmental and Non-governmental—Concerned with Protecting the Earth’s Resources Vol. 5 (Earthscan, 1996).Dixit, A. & Levin, S. in The Theory of Externalities and Public Goods: Essays in Memory of Richard C. Cornes (eds Buchholz, W. and Rübbelke, D.) 127–143 (Springer, 2017); https://doi.org/10.1007/978-3-319-49442-5_7Vasconcelos, V. V., Santos, F. C. & Pacheco, J. M. A bottom-up institutional approach to cooperative governance of risky commons. Nat. Clim. Change 3, 797–801 (2013).Article 

Google Scholar 
Vasconcelos, V. V., Santos, F. C. & Pacheco, J. M. Cooperation dynamics of polycentric climate governance. Math. Model. Methods Appl. Sci. 25, 2503–2517 (2015).Article 

Google Scholar 
Ostrom, E. Beyond markets and states: polycentric governance of complex economic systems. Am. Econ. Rev. 100, 641–672 (2010).Article 

Google Scholar 
Vasconcelos, V. V., Hannam, P. M., Levin, S. A. & Pacheco, J. M. Coalition-structured governance improves cooperation to provide public goods. Sci. Rep. 10, 9194 (2020).CAS 
Article 

Google Scholar 
Nyborg, K. et al. Social norms as solutions. Science 354, 42–43 (2016).CAS 
Article 

Google Scholar 
Hannam, P. M., Vasconcelos, V. V., Levin, S. A. & Pacheco, J. M. Incomplete cooperation and co-benefits: deepening climate cooperation with a proliferation of small agreements. Climatic Change 144, 65–79 (2017).Article 

Google Scholar 
Markussen, T., Putterman, L. & Tyran, J.-R. Self-organization for collective action: an experimental study of voting on sanction regimes. Rev. Econ. Stud. 81, 301–324 (2014).Article 

Google Scholar 
Gürerk, Ö., Irlenbusch, B. & Rockenbach, B. The competitive advantage of sanctioning institutions. Science 312, 108–111 (2006).Article 

Google Scholar 
Dannenberg, A. & Gallier, C. The choice of institutions to solve cooperation problems: a survey of experimental research. Exp. Econ. https://doi.org/10.1007/s10683-019-09629-8 (2019).Bühren, C. & Dannenberg, A. The demand for punishment to promote cooperation among like-minded people. Eur. Econ. Rev. 138, 103862 (2021).Radzvilavicius, A. L., Kessinger, T. A. & Plotkin, J. B. Adherence to public institutions that foster cooperation. Nat. Commun. 12, 3567 (2021).CAS 
Article 

Google Scholar  More

Darwin, C. The Effects of Cross and Self Fertilisation in the Vegetable Kingdom (D. Appleton and Company, 1877).
Google Scholar 
Charlesworth, D. Androdioecy and the evolution of dioecy. Biol. J. Linn Soc. 22, 333–348 (1984).Article 

Google Scholar 
Charlesworth, D., Morgan, M. T. & Charlesworth, B. Inbreeding depression, genetic load, and the evolution of outcrossing rates in a multilocus system with no linkage. Evolution 44, 1469–1489 (1990).CAS 
Article 

Google Scholar 
Lande, R. & Schemske, D. W. The evolution of self-fertilization and inbreeding depression in plants. I. Genetic models. Evolution 39, 24–40 (1985).
Google Scholar 
Weeks, S. C. When males and hermaphrodites coexist: a review of androdioecy in animals. Integr. Comp. Biol. 46, 449–464 (2006).Article 

Google Scholar 
Pannell, J. The maintenance of gynodioecy and androdioecy in a metapopulation. Evolution 51, 10–20 (1997).Article 

Google Scholar 
Wolf, D. E. & Takebayashi, N. Pollen limitation and the evolution of androdioecy from dioecy. Am. Nat. 163, 122–137 (2004).Article 

Google Scholar 
Charlesworth, D. Theories of the evolution of dioecy. In Gender and Sexual Dimorphism in Flowering Plants (eds Geber, M. A. et al.) 33–60 (Springer, Berlin, 1999). https://doi.org/10.1007/978-3-662-03908-3_2.Chapter 

Google Scholar 
Denver, D. R., Clark, K. A. & Raboin, M. J. Reproductive mode evolution in nematodes: insights from molecular phylogenies and recently discovered species. Mol. Phylogenetics Evol. 61, 584–592 (2011).CAS 
Article 

Google Scholar 
Pires-daSilva, A. Evolution of the control of sexual identity in nematodes. Semin. Cell Dev. Biol. 18, 362–370 (2007).Article 

Google Scholar 
Kanzaki, N. et al. Description of two three-gendered nematode species in the new genus Auanema (Rhabditina) that are models for reproductive mode evolution. Sci. Rep. 7, 11135 (2017).ADS 
Article 

Google Scholar 
Tandonnet, S. et al. Sex- and gamete-specific patterns of X chromosome segregation in a trioecious nematode. Curr. Biol. 28, 93-99.e3 (2018).CAS 
Article 

Google Scholar 
Chaudhuri, J. et al. Mating dynamics in a nematode with three sexes and its evolutionary implications. Sci. Rep. 5, 17676 (2015).ADS 
CAS 
Article 

Google Scholar 
Félix, M.-A. Alternative morphs and plasticity of vulval development in a rhabditid nematode species. Dev. Genes Evol. 214, 55–63 (2004).Article 

Google Scholar 
Shakes, D. C., Neva, B. J., Huynh, H., Chaudhuri, J. & Pires-daSilva, A. Asymmetric spermatocyte division as a mechanism for controlling sex ratios. Nat. Commun. 2, 157 (2011).ADS 
Article 

Google Scholar 
Winter, E. S. et al. Cytoskeletal variations in an asymmetric cell division support diversity in nematode sperm size and sex ratios. Development 144, 3253–3263 (2017).CAS 

Google Scholar 
Robles, P. et al. Parental energy-sensing pathways control intergenerational offspring sex determination in the nematode Auanema freiburgensis. BMC Biol. 19, 102 (2021).CAS 
Article 

Google Scholar 
Zuco, G. et al. Sensory neurons control heritable adaptation to stress through germline reprogramming. bioRxiv 406033 (2018) https://doi.org/10.1101/406033.Colegrave, N., Kaltz, O. & Bell, G. The ecology and genetics of fitness in chlamydomonas. VIII. The dynamics of adaptation to novel environments after a single episode of sex. Evolution 56, 14–21 (2002).Article 

Google Scholar 
Goddard, M. R., Godfray, H. C. J. & Burt, A. Sex increases the efficacy of natural selection in experimental yeast populations. Nature 434, 636–640 (2005).ADS 
CAS 
Article 

Google Scholar 
Gray, J. C. & Goddard, M. R. Sex enhances adaptation by unlinking beneficial from detrimental mutations in experimental yeast populations. BMC Evol. Biol. 12, 43 (2012).Article 

Google Scholar 
Poon, A. & Chao, L. Drift increases the advantage of sex in RNA bacteriophage ⌽6. Genetics 166, 19 (2004).Article 

Google Scholar 
Stewart, A. D. & Phillips, P. C. Selection and maintenance of androdioecy in Caenorhabditis elegans. Genetics 160, 975–982 (2002).Article 

Google Scholar 
Stiernagle, T. Maintenance of C. elegans. WormBook: The Online Review of C. elegans Biology (WormBook, 2006).Avery, L. The genetics of feeding in Caenorhabditis elegans. Genetics 133, 897–917 (1993).CAS 
Article 

Google Scholar 
Bargmann, C. I. & Horvitz, H. R. Control of larval development by chemosensory neurons in Caenorhabditis elegans. Science 251, 1243–1246 (1991).ADS 
CAS 
Article 

Google Scholar 
Lenth, R. V. Emmeans: estimated marginal means, aka least-squares means (2021).Lipton, J., Kleemann, G., Ghosh, R., Lints, R. & Emmons, S. W. Mate searching in Caenorhabditis elegans: a genetic model for sex drive in a simple invertebrate. J. Neurosci. 24, 7427–7434 (2004).CAS 
Article 

Google Scholar 
Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).Article 

Google Scholar 
Pino, E. C., Webster, C. M., Carr, C. E. & Soukas, A. A. Biochemical and high throughput microscopic assessment of fat mass in Caenorhabditis elegans. J. Vis. Exp. https://doi.org/10.3791/50180 (2013).Article 

Google Scholar 
Hakim, A. et al. WorMachine: machine learning-based phenotypic analysis tool for worms. BMC Biol. 16, 8 (2018).Article 

Google Scholar 
Motola, D. L. et al. Identification of ligands for DAF-12 that govern dauer formation and reproduction in C. elegans. Cell 124, 1209–1223 (2006).CAS 
Article 

Google Scholar 
Ogawa, A., Streit, A., Antebi, A. & Sommer, R. J. A conserved endocrine mechanism controls the formation of dauer and infective larvae in nematodes. Curr. Biol. 19, 67–71 (2009).CAS 
Article 

Google Scholar 
Wang, Z. et al. Identification of the nuclear receptor DAF-12 as a therapeutic target in parasitic nematodes. Proc. Natl. Acad. Sci. 106, 9138–9143 (2009).ADS 
CAS 
Article 

Google Scholar 
Hu, P. Dauer. WormBook: The C. elegans Research Community (2007).Chaudhuri, J., Kache, V. & Pires-daSilva, A. Regulation of sexual plasticity in a nematode that produces males, females, and hermaphrodites. Curr. Biol. 21, 1548–1551 (2011).CAS 
Article 

Google Scholar 
Luciani, G. M. et al. Dafadine inhibits DAF-9 to promote dauer formation and longevity of Caenorhabditis elegans. Nat. Chem. Biol. 7, 891–893 (2011).CAS 
Article 

Google Scholar 
Adams, S., Pathak, P., Shao, H., Lok, J. B. & Pires-daSilva, A. Liposome-based transfection enhances RNAi and CRISPR-mediated mutagenesis in non-model nematode systems. Sci. Rep. 9, 483 (2019).ADS 
Article 

Google Scholar 
Andrews, S. FastQC: A Quality Control Tool for High Throughput Sequence Data [Online]. http://www.bioinformatics.babraham.ac.uk/projects/fastqc/ (2010).Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).CAS 
Article 

Google Scholar 
Grabherr, M. G. et al. Trinity: reconstructing a full-length transcriptome without a genome from RNA-Seq data. Nat. Biotechnol. 29, 644–652 (2011).CAS 
Article 

Google Scholar 
Haas, B. J. et al. De novo transcript sequence reconstruction from RNA-Seq: reference generation and analysis with Trinity. Nat. Protoc. 8, 1494 (2013).CAS 
Article 

Google Scholar 
Schmieder, R. & Edwards, R. Fast identification and removal of sequence contamination from genomic and metagenomic datasets. PLoS ONE 6, e17288 (2011).ADS 
CAS 
Article 

Google Scholar 
Huang, Y., Niu, B., Gao, Y., Fu, L. & Li, W. CD-HIT Suite: a web server for clustering and comparing biological sequences. Bioinformatics 26, 680–682 (2010).CAS 
Article 

Google Scholar 
Li, B. & Dewey, C. N. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinform. 12, 323 (2011).CAS 
Article 

Google Scholar 
Bendtsen, J. D., Nielsen, H., von Heijne, G. & Brunak, S. Improved prediction of signal peptides: SignalP 3.0. J. Mol. Biol. 340, 783–795 (2004).Article 

Google Scholar 
Bryant, D. M. et al. A tissue-mapped axolotl de novo transcriptome enables identification of limb regeneration factors. Cell Rep. 18, 762–776 (2017).CAS 
Article 

Google Scholar 
Finn, R. D., Clements, J. & Eddy, S. R. HMMER web server: interactive sequence similarity searching. Nucl. Acids Res. 39, W29–W37 (2011).CAS 
Article 

Google Scholar 
Andersen, C. L., Jensen, J. L. & Ørntoft, T. F. Normalization of real-time quantitative reverse transcription-PCR data: a model-based variance estimation approach to identify genes suited for normalization, applied to bladder and colon cancer data sets. Cancer Res. 64, 5245–5250 (2004).CAS 
Article 

Google Scholar 
McGhee, J. D. The C. elegans intestine. WormBook: The Online Review of C. elegans Biology [Internet] (WormBook, 2007).Mullaney, B. C. & Ashrafi, K. C. elegans fat storage and metabolic regulation. Biochim. Biophys. Acta (BBA) Mol. Cell Biol. Lipids 1791, 474–478 (2009).CAS 

Google Scholar 
O’Rourke, E. J., Soukas, A. A., Carr, C. E. & Ruvkun, G. C. elegans major fats are stored in vesicles distinct from lysosome-related organelles. Cell Metab. 10, 430–435 (2009).Article 

Google Scholar 
Mak, H. Y. Lipid droplets as fat storage organelles in Caenorhabditis elegans. J. Lipid Res. 53, 28–33 (2012).CAS 
Article 

Google Scholar 
Kroetz, S. M., Srinivasan, J., Yaghoobian, J., Sternberg, P. W. & Hong, R. L. The cGMP signaling pathway affects feeding behavior in the necromenic nematode Pristionchus pacificus. BMC Proc. 6, P27 (2012).Article 

Google Scholar 
Edgar, L. G. & McGhee, J. D. Embryonic expression of a gut-specific esterase in Caenorhabditis elegans. Dev. Biol. 114, 109–118 (1986).CAS 
Article 

Google Scholar 
Barr, M. M. & Sternberg, P. W. A polycystic kidney-disease gene homologue required for male mating behaviour in C. elegans. Nature 401, 386 (1999).ADS 
CAS 

Google Scholar 
Bendesky, A., Tsunozaki, M., Rockman, M. V., Kruglyak, L. & Bargmann, C. I. Catecholamine receptor polymorphisms affect decision-making in C. elegans. Nature 472, 313–318 (2011).ADS 
CAS 
Article 

Google Scholar 
Garrison, J. L. et al. Oxytocin/vasopressin-related peptides have an ancient role in reproductive behavior. Science 338, 540–543 (2012).ADS 
CAS 
Article 

Google Scholar 
Joo, H.-J. et al. Contribution of the peroxisomal acox gene to the dynamic balance of daumone production in Caenorhabditis elegans. J. Biol. Chem. 285, 29319–29325 (2010).CAS 
Article 

Google Scholar 
Yassin, L. et al. Characterization of the DEG-3/DES-2 receptor: a nicotinic acetylcholine receptor that mutates to cause neuronal degeneration. Mol. Cell. Neurosci. 17, 589–599 (2001).CAS 
Article 

Google Scholar 
Zhang, X., Wang, Y., Perez, D. H., Lipinski, R. A. J. & Butcher, R. A. Acyl-CoA oxidases fine-tune the production of ascaroside pheromones with specific side chain lengths. ACS Chem. Biol. https://doi.org/10.1021/acschembio.7b01021 (2018).Article 

Google Scholar 
Borne, F., Kasimatis, K. R. & Phillips, P. C. Quantifying male and female pheromone-based mate choice in Caenorhabditis nematodes using a novel microfluidic technique. PLoS ONE 87, 511 (2017).
Google Scholar 
Choe, A. et al. Sex-specific mating pheromones in the nematode Panagrellus redivivus. Proc. Natl. Acad. Sci. 109, 20949–20954 (2012).ADS 
CAS 
Article 

Google Scholar 
Duggal, C. L. Sex attraction in the free-living nematode panagrellus redivivus. Nematologica 24, 213–221 (1978).Article 

Google Scholar 
Andersson, M. Sexual Selection Vol. 72 (Princeton University Press, 1994).Book 

Google Scholar 
Bateman, A. J. Intra-sexual selection in Drosophila. Heredity 2, 349–368 (1948).CAS 
Article 

Google Scholar 
Kvarnemo, C. & Simmons, L. W. Polyandry as a mediator of sexual selection before and after mating. Philos. Trans. R. Soc. Lond. B Biol. Sci. 368, 20120042 (2013).Article 

Google Scholar 
Parker, G. A. & Birkhead, T. R. Polyandry: the history of a revolution. Philos. Trans. R. Soc. Lond. B Biol. Sci. 368, 20120335 (2013).Article 

Google Scholar 
Rhainds, M. Female mating failures in insects. Entomol. Exp. Appl. 136, 211–226 (2010).Article 

Google Scholar 
Hammond, K. A. Adaptation of the maternal intestine during lactation. J. Mammary Gland Biol. Neoplasia 2, 243–252 (1997).CAS 
Article 

Google Scholar 
Speakman, J. R. The physiological costs of reproduction in small mammals. Philos. Trans. R. Soc. B Biol. Sci. 363, 375–398 (2008).Article 

Google Scholar 
Reiff, T. et al. Endocrine remodelling of the adult intestine sustains reproduction in Drosophila. Elife 4, e06930 (2015).Article 

Google Scholar 
Kaliszewicz, A. Interference of asexual and sexual reproduction in the green hydra. Ecol. Res. 26, 147–152 (2011).Article 

Google Scholar 
Oyarzún, P. A., Nuñez, J. J., Toro, J. E. & Gardner, J. P. A. Trioecy in the Marine Mussel Semimytilus algosus (Mollusca, Bivalvia): stable sex ratios across 22 degrees of a latitudinal gradient. Front. Mar. Sci. 7, 348 (2020).Article 

Google Scholar 
Armoza-Zvuloni, R., Kramarsky-Winter, E., Loya, Y., Schlesinger, A. & Rosenfeld, H. Trioecy, a unique breeding strategy in the sea anemone aiptasia diaphana and its association with sex steroids. Biol. Reprod. 90, 122 (2014).Article 

Google Scholar 
Greene, J. S. et al. Balancing selection shapes density-dependent foraging behaviour. Nature. 539(7628), 254–258. https://doi.org/10.1038/nature19848 (2016).ADS 
CAS 
Article 

Google Scholar 
Kieninger, M. R. et al. The Nuclear Hormone Receptor NHR-40 Acts Downstream of the Sulfatase EUD-1 as Part of a Developmental Plasticity Switch in Pristionchus.Curr Biol 26(16), 2174–2179. https://doi.org/10.1016/j.cub.2016.06.018 (2016).Therrien, M., Rouleau, G. A., Dion, P. A., Parker, J. A. & Dupuy, D. Deletion of C9ORF72 Results in Motor Neuron Degeneration and Stress Sensitivity in C. elegans. PLoS ONE 8(12), e83450. https://doi.org/10.1371/journal.pone.0083450 (2013).Lee, B. H., Liu, J., Wong, D., Srinivasan, S., Ashrafi, K. & Kim, S. K. Hyperactive Neuroendocrine Secretion Causes Size Feeding and Metabolic Defects of C. elegans Bardet-Biedl Syndrome Mutants. PLoS Biol 9(12), e1001219. https://doi.org/10.1371/journal.pbio.1001219 (2011).CAS 
Article 

Google Scholar 
Li, C. & Kim, K. Family of FLP Peptides in Caenorhabditis elegans and Related Nematodes. Front Endocrinol. https://doi.org/10.3389/fendo.2014.00150 (2014). Buntschuh, I. et al. FLP-1 neuropeptides modulate sensory and motor circuits in the nematode Caenorhabditis elegans. PLoS ONE 13(1), e0189320. https://doi.org/10.1371/journal.pone.0189320 (2018).Topalidou, I. et al. The EARP Complex and Its Interactor EIPR-1 Are Required for Cargo Sorting to Dense-Core Vesicles. PLOS Genet 12(5), e1006074. https://doi.org/10.1371/journal.pgen.1006074 (2016).Maman, M. et al. A Neuronal GPCR is Critical for the Induction of the Heat Shock Response in the Nematode C. elegans. J Neurosci 33(14), 6102–6111. https://doi.org/10.1523/JNEUROSCI.4023-12.2013 (2013). More