Ecology

Whitman, W. B., Coleman, D. C. & Wiebe, W. J. Prokaryotes: the unseen majority. Proc. Natl Acad. Sci. USA 95, 6578–6583 (1998).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Locey, K. J. & Lennon, J. T. Scaling laws predict global microbial diversity. Proc. Natl Acad. Sci. USA 113, 5970–5975 (2016).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Louca, S. et al. Function and functional redundancy in microbial systems. Nat. Ecol. Evol. 2, 936–943 (2018).PubMed 

Google Scholar 
Dinsdale, E. A. et al. Functional metagenomic profiling of nine biomes. Nature 452, 629–632 (2008).ADS 
CAS 
PubMed 

Google Scholar 
Nayfach, S. et al. A genomic catalog of Earth’s microbiomes. Nat. Biotechnol. 39, 499–509 (2021).CAS 
PubMed 

Google Scholar 
Thompson, L. R. et al. A communal catalogue reveals Earth’s multiscale microbial diversity. Nature 551, 457–463 (2017).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Song, S. J. et al. Comparative analyses of vertebrate gut microbiomes reveal convergence between birds and bats. MBio 11, e02901-19 (2020).Ley, R. E. et al. Evolution of mammals and their gut microbes. Science 320, 1647–1651 (2008).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
McDonald, D. et al. American Gut: an open platform for citizen science microbiome research. mSystems 3, e00031-18 (2018).Minich, J. J. et al. Temporal, environmental, and biological drivers of the mucosal microbiome in a wild marine fish, Scomber japonicus. mSphere 5, e00401-20 (2020).Sullam, K. E. et al. Environmental and ecological factors that shape the gut bacterial communities of fish: a meta-analysis. Mol. Ecol. 21, 3363–3378 (2012).PubMed 

Google Scholar 
Youngblut, N. D. et al. Host diet and evolutionary history explain different aspects of gut microbiome diversity among vertebrate clades. Nat. Commun. 10, 2200 (2019).ADS 
PubMed 
PubMed Central 

Google Scholar 
Bosco, N. & Noti, M. The aging gut microbiome and its impact on host immunity. Genes Immun. 22, 289–303 (2021).PubMed 
PubMed Central 

Google Scholar 
McKenzie, V. J. et al. The effects of captivity on the mammalian gut microbiome. Integr. Comp. Biol. 57, 690–704 (2017).PubMed 
PubMed Central 

Google Scholar 
Groussin, M. et al. Unraveling the processes shaping mammalian gut microbiomes over evolutionary time. Nat. Commun. 8, 14319 (2017).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Ross, A. A., Müller, K. M., Weese, J. S. & Neufeld, J. D. Comprehensive skin microbiome analysis reveals the uniqueness of human skin and evidence for phylosymbiosis within the class Mammalia. Proc. Natl Acad. Sci. USA 115, E5786–E5795 (2018).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Hobbie, J. E., Daley, R. J. & Jasper, S. Use of nuclepore filters for counting bacteria by fluorescence microscopy. Appl. Environ. Microbiol. 33, 1225–1228 (1977).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Prussin, A. J. 2nd, Garcia, E. B. & Marr, L. C. Total virus and bacteria concentrations in indoor and outdoor air. Environ. Sci. Technol. Lett. 2, 84–88 (2015).CAS 
PubMed 
PubMed Central 

Google Scholar 
Gomez, D., Sunyer, J. O. & Salinas, I. The mucosal immune system of fish: the evolution of tolerating commensals while fighting pathogens. Fish. Shellfish Immunol. 35, 1729–1739 (2013).CAS 
PubMed 
PubMed Central 

Google Scholar 
Lowrey, L., Woodhams, D. C., Tacchi, L. & Salinas, I. Topographical mapping of the Rainbow Trout (Oncorhynchus mykiss) microbiome reveals a diverse bacterial community with antifungal properties in the skin. Appl. Environ. Microbiol. 81, 6915–6925 (2015).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Minich, J. J. et al. Microbial ecology of Atlantic Salmon (Salmo salar) hatcheries: impacts of the built environment on fish mucosal microbiota. Appl. Environ. Microbiol. 86, 20 (2020).Minich, J. J. et al. Impacts of the marine hatchery built environment, water and feed on mucosal microbiome colonization across ontogeny in Yellowtail Kingfish, Seriola lalandi. Front. Mar. Sci. 0, 676731 (2021).Minich, J. J. et al. The Southern Bluefin Tuna mucosal microbiome is influenced by husbandry method, net pen location, and anti-parasite treatment. Front. Microbiol. 11, 2015 (2020).PubMed 
PubMed Central 

Google Scholar 
Ruiz-Rodríguez, M. et al. Host species and body site explain the variation in the microbiota associated to wild sympatric Mediterranean teleost fishes. Microb. Ecol. 80, 212–222 (2020).PubMed 

Google Scholar 
Tarnecki, A. M., Burgos, F. A., Ray, C. L. & Arias, C. R. Fish intestinal microbiome: diversity and symbiosis unravelled by metagenomics. J. Appl. Microbiol. 123, 2–17 (2017).CAS 
PubMed 

Google Scholar 
Liu, H. et al. The gut microbiome and degradation enzyme activity of wild freshwater fishes influenced by their trophic levels. Sci. Rep. 6, 24340 (2016).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Egerton, S., Culloty, S., Whooley, J., Stanton, C. & Ross, R. P. The gut microbiota of marine fish. Front. Microbiol. 9, 873 (2018).PubMed 
PubMed Central 

Google Scholar 
Woodhams, D. C. et al. Host-associated microbiomes are predicted by immune system complexity and climate. Genome Biol. 21, 23 (2020).PubMed 
PubMed Central 

Google Scholar 
Karachle, P. K. & Stergiou, K. I. Gut length for several marine fish: relationships with body length and trophic implications. Mar. Biodivers. Rec. 3, 1–10 (2010).Ghilardi, M. et al. Phylogeny, body morphology, and trophic level shape intestinal traits in coral reef fishes. Ecol. Evol. 11, 13218–13231 (2021).PubMed 
PubMed Central 

Google Scholar 
Clements, K. D., Angert, E. R., Linn Montgomery, W. & Howard Choat, J. Intestinal microbiota in fishes: what’s known and what’s not. Mol. Ecol. 23, 1891–1898 (2014).PubMed 

Google Scholar 
Zhu, D., Delgado-Baquerizo, M., Ding, J., Gillings, M. R. & Zhu, Y.-G. Trophic level drives the host microbiome of soil invertebrates at a continental scale. Microbiome 9, 189 (2021).CAS 
PubMed 
PubMed Central 

Google Scholar 
Minich, J. J. et al. KatharoSeq enables high-throughput microbiome analysis from low-biomass samples. mSystems 3, e00218-17 (2018).Davis, C. Enumeration of probiotic strains: review of culture-dependent and alternative techniques to quantify viable bacteria. J. Microbiol. Methods 103, 9–17 (2014).CAS 
PubMed 

Google Scholar 
Rastogi, G., Tech, J. J., Coaker, G. L. & Leveau, J. H. J. A PCR-based toolbox for the culture-independent quantification of total bacterial abundances in plant environments. J. Microbiol. Methods 83, 127–132 (2010).CAS 
PubMed 

Google Scholar 
Stämmler, F. et al. Adjusting microbiome profiles for differences in microbial load by spike-in bacteria. Microbiome 4, 28 (2016).PubMed 
PubMed Central 

Google Scholar 
Tourlousse, D. M. et al. Synthetic spike-in standards for high-throughput 16S rRNA gene amplicon sequencing. Nucleic Acids Res. 45, e23 (2017).PubMed 

Google Scholar 
Gloor, G. B., Macklaim, J. M., Pawlowsky-Glahn, V. & Egozcue, J. J. Microbiome datasets are compositional: and this is not optional. Front. Microbiol. 8, 2224 (2017).PubMed 
PubMed Central 

Google Scholar 
Morton, J. T. et al. Establishing microbial composition measurement standards with reference frames. Nat. Commun. 10, 2719 (2019).ADS 
PubMed 
PubMed Central 

Google Scholar 
Louca, S., Doebeli, M. & Parfrey, L. W. Correcting for 16S rRNA gene copy numbers in microbiome surveys remains an unsolved problem. Microbiome 6, 41 (2018).PubMed 
PubMed Central 

Google Scholar 
Smith, N. C., Rise, M. L. & Christian, S. L. A comparison of the innate and adaptive immune systems in cartilaginous fish, ray-finned fish, and lobe-finned fish. Front. Immunol. 10, 2292 (2019).CAS 
PubMed 
PubMed Central 

Google Scholar 
Azam, F. et al. The ecological role of water-column microbes in the sea. Mar. Ecol. Prog. Ser. 10, 257–263 (1983).ADS 

Google Scholar 
Fuhrman, J. A., Cram, J. A. & Needham, D. M. Marine microbial community dynamics and their ecological interpretation. Nat. Rev. Microbiol. 13, 133–146 (2015).CAS 
PubMed 

Google Scholar 
Chong-Seng, K. M., Mannering, T. D., Pratchett, M. S., Bellwood, D. R. & Graham, N. A. J. The influence of coral reef benthic condition on associated fish assemblages. PLoS ONE 7, e42167 (2012).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Yahel, G. et al. Fish activity: a major mechanism for sediment resuspension and organic matter remineralization in coastal marine sediments. Mar. Ecol. Prog. Ser. 372, 195–209 (2008).ADS 
CAS 

Google Scholar 
Glover, C. N., Bucking, C. & Wood, C. M. The skin of fish as a transport epithelium: a review. J. Comp. Physiol. B 183, 877–891 (2013).CAS 
PubMed 

Google Scholar 
León-Zayas, R., McCargar, M., Drew, J. A. & Biddle, J. F. Microbiomes of fish, sediment and seagrass suggest connectivity of coral reef microbial populations. PeerJ 8, e10026 (2020).PubMed 
PubMed Central 

Google Scholar 
Hess, S., Wenger, A. S., Ainsworth, T. D. & Rummer, J. L. Exposure of clownfish larvae to suspended sediment levels found on the Great Barrier Reef: impacts on gill structure and microbiome. Sci. Rep. 5, 10561 (2015).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Sparagon, W. J. et al. Fine scale transitions of the microbiota and metabolome along the gastrointestinal tract of herbivorous fishes. Anim. Microbiome 4, 33 (2022).CAS 
PubMed 
PubMed Central 

Google Scholar 
Edward Stevens, C. & Hume, I. D. Comparative Physiology of the Vertebrate Digestive System (Cambridge University Press, 2004).Wilson, J. M. & Castro, L. F. C. Morphological diversity of the gastrointestinal tract in fishes. Fish Physiol. 1–55 https://doi.org/10.1016/s1546-5098(10)03001-3 (2010).Shirakashi, S. et al. Morphology and distribution of blood fluke eggs and associated pathology in the gills of cultured Pacific bluefin tuna, Thunnus orientalis. Parasitol. Int. 61, 242–249 (2012).PubMed 

Google Scholar 
Ogawa, K. & Fukudome, M. Mass mortality caused by Blood Fluke(Paradeontacylix) among Amberjack(Seriola dumeili) imported to Japan. Fish. Pathol. 29, 265–269 (1994).
Google Scholar 
Wilson, J. M. & Laurent, P. Fish gill morphology: inside out. J. Exp. Zool. 293, 192–213 (2002).PubMed 

Google Scholar 
Huang, Q. et al. Diversity of gut microbiomes in marine fishes is shaped by host-related factors. Mol. Ecol. 29, 5019–5034 (2020).CAS 
PubMed 
PubMed Central 

Google Scholar 
Kohl, K. D., Amaya, J., Passement, C. A., Dearing, M. D. & McCue, M. D. Unique and shared responses of the gut microbiota to prolonged fasting: a comparative study across five classes of vertebrate hosts. FEMS Microbiol. Ecol. 90, 883–894 (2014).CAS 
PubMed 

Google Scholar 
Lall, S. P. & Tibbetts, S. M. Nutrition, feeding, and behavior of fish. Vet. Clin. North Am. Exot. Anim. Pract. 12, 361–372 (2009). xi.PubMed 

Google Scholar 
Hacquard, S. et al. Microbiota and host nutrition across plant and animal kingdoms. Cell Host Microbe 17, 603–616 (2015).CAS 
PubMed 

Google Scholar 
Day, R. D., German, D. P. & Tibbetts, I. R. Why can’t young fish eat plants? Neither digestive enzymes nor gut development preclude herbivory in the young of a stomachless marine herbivorous fish. Comp. Biochem. Physiol. Part B: Biochem. Mol. Biol. 158, 23–29 (2011).
Google Scholar 
Lim, S. J. & Bordenstein, S. R. An introduction to phylosymbiosis. Proc. Biol. Sci. 287, 20192900 (2020).PubMed 
PubMed Central 

Google Scholar 
Brucker, R. M. & Bordenstein, S. R. The hologenomic basis of speciation: gut bacteria cause hybrid lethality in the genus Nasonia. Science 341, 667–669 (2013).ADS 
CAS 
PubMed 

Google Scholar 
Mazel, F. et al. Is host filtering the main driver of phylosymbiosis across the tree of life? mSystems 3, e00097-18 (2018).Ross, A. A., Rodrigues Hoffmann, A. & Neufeld, J. D. The skin microbiome of vertebrates. Microbiome 7, 79 (2019).PubMed 
PubMed Central 

Google Scholar 
Javůrková, V. G. et al. Unveiled feather microcosm: feather microbiota of passerine birds is closely associated with host species identity and bacteriocin-producing bacteria. ISME J. 13, 2363–2376 (2019).PubMed 
PubMed Central 

Google Scholar 
Doane, M. P. et al. The skin microbiome of elasmobranchs follows phylosymbiosis, but in teleost fishes, the microbiomes converge. Microbiome 8, 93 (2020).PubMed 
PubMed Central 

Google Scholar 
Chiarello, M. et al. Skin microbiome of coral reef fish is highly variable and driven by host phylogeny and diet. Microbiome 6, 147 (2018).PubMed 
PubMed Central 

Google Scholar 
Sylvain, F.-É. et al. Fish skin and gut microbiomes show contrasting signatures of host species and habitat. Appl. Environ. Microbiol. 86, e00789-20 (2020).Smith, C. C. R., Snowberg, L. K., Gregory Caporaso, J., Knight, R. & Bolnick, D. I. Dietary input of microbes and host genetic variation shape among-population differences in stickleback gut microbiota. ISME J. 9, 2515–2526 (2015).CAS 
PubMed 
PubMed Central 

Google Scholar 
Human Microbiome Project Consortium. Structure, function and diversity of the healthy human microbiome. Nature 486, 207–214 (2012).ADS 

Google Scholar 
Choat, J. H. & Clements, K. D. Vertebrate herbivores in marine and terrestrial environments: a nutritional ecology perspective. Annu. Rev. Ecol. Syst. 29, 375–403 (1998).
Google Scholar 
Sale, P. F. Reef fish communities: open nonequilibrial systems. In The Ecology of Fishes on Coral Reefs. 564–598. https://doi.org/10.1016/b978-0-08-092551-6.50024-6 (Academic Press Inc., San Diego, 1991).Reese, A. T. & Dunn, R. R. Drivers of microbiome biodiversity: a review of general rules, feces, and ignorance. MBio 9, e01294-18 (2018).Press, C. McL & Evensen, Ø. The morphology of the immune system in teleost fishes. Fish Shellfish Immunol. 9, 309–318 (1999).Koppang, E. O., Kvellestad, A. & Fischer, U. Fish mucosal immunity: gill. In Mucosal Health in Aquaculture (eds Beck, B. & Peatman, E.) 93–133. https://doi.org/10.1016/b978-0-12-417186-2.00005-4 (Elsevier Inc., 2015).Esteban, M. Á. & Cerezuela, R. Fish mucosal immunity: skin. In Mucosal Health in Aquaculture (eds Beck, B. & Peatman, E.) 67–92. https://doi.org/10.1016/b978-0-12-417186-2.00004-2 (Elsevier Inc., 2015).Song, S. J. et al. Preservation methods differ in fecal microbiome stability, affecting suitability for field studies. mSystems 1, e00021-16 (2016).Rabosky, D. L. et al. An inverse latitudinal gradient in speciation rate for marine fishes. Nature 559, 392–395 (2018).ADS 
CAS 
PubMed 

Google Scholar 
Love, M. S., Bizzarro, J. J., Maria Cornthwaite, A., Frable, B. W. & Maslenikov, K. P. Checklist of marine and estuarine fishes from the Alaska–Yukon Border, Beaufort Sea, to Cabo San Lucas, Mexico. Zootaxa 5053, 1–285 (2021).PubMed 

Google Scholar 
Allen, L. G. & Horn, M. H. The Ecology of Marine Fishes: California and Adjacent Waters (University of California Press, 2006).Al-Hussaini, A. H. On the functional morphology of the alimentary tract of some fish in relation to differences in their feeding habits; anatomy and histology. Q. J. Microsc. Sci. 90(Pt. 2), 109–139 (1949).PubMed 

Google Scholar 
Maddock, L., Bone, Q. & Rayner, J. M. V. (eds). In Mechanics and Physiology of Animal Swimming (Press Syndicate-of the University of Cambridge, 1994).Gonzalez, A. et al. Qiita: rapid, web-enabled microbiome meta-analysis. Nat. Methods 15, 796–798 (2018).CAS 
PubMed 
PubMed Central 

Google Scholar 
Cruz, G. N. F., Christoff, A. P. & de Oliveira, L. F. V. Equivolumetric protocol generates library sizes proportional to total microbial load in 16S amplicon sequencing. Front. Microbiol. 12, 638231 (2021).PubMed 
PubMed Central 

Google Scholar 
Minich, J. J. et al. Quantifying and understanding well-to-well contamination in microbiome research. mSystems 4, e00186-19 (2019).Minich, J. J. et al. High-throughput miniaturized 16S rRNA amplicon library preparation reduces costs while preserving microbiome integrity. mSystems 3, e00166-18 (2018).Walters, W. et al. Improved bacterial 16S rRNA gene (V4 and V4–5) and fungal internal transcribed spacer marker gene primers for microbial community surveys. mSystems 1, e00009-15 (2016).Amir, A. et al. Deblur rapidly resolves single-nucleotide community sequence patterns. mSystems 2, e00191-16 (2017).Whittaker, R. J., Willis, K. J. & Field, R. Scale and species richness: towards a general, hierarchical theory of species diversity. J. Biogeogr. 28, 453–470 (2001).
Google Scholar 
Bolyen, E. et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. 37, 852–857 (2019).CAS 
PubMed 
PubMed Central 

Google Scholar 
Lozupone, C., Lladser, M. E., Knights, D., Stombaugh, J. & Knight, R. UniFrac: an effective distance metric for microbial community comparison. ISME J. 5, 169–172 (2011).PubMed 

Google Scholar 
McDonald, D. et al. Striped UniFrac: enabling microbiome analysis at unprecedented scale. Nat. Methods 15, 847–848 (2018).CAS 
PubMed 
PubMed Central 

Google Scholar 
Lozupone, C. & Knight, R. UniFrac: a new phylogenetic method for comparing microbial communities. Appl. Environ. Microbiol. 71, 8228–8235 (2005).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Janssen, S. et al. Phylogenetic placement of exact amplicon sequences improves associations with clinical information. mSystems 3, e00021-18 (2018).Anderson, M. J. A new method for non-parametric multivariate analysis of variance. Austral Ecol. 26, 32–46 (2001).
Google Scholar 
Minich, J. J. et al. Microbial effects of livestock manure fertilization on freshwater aquaculture ponds rearing tilapia (Oreochromis shiranus) and North African catfish (Clarias gariepinus). Microbiologyopen 7, e00716 (2018).PubMed 
PubMed Central 

Google Scholar 
Van Doan, H. et al. Host-associated probiotics: a key factor in sustainable aquaculture. Rev. Fish. Sci. Aquac. 28, 16–42 (2020).
Google Scholar 
Kumar, S., Stecher, G., Suleski, M. & Hedges, S. B. TimeTree: a resource for timelines, timetrees, and divergence times. Mol. Biol. Evol. 34, 1812–1819 (2017).CAS 
PubMed 

Google Scholar  More

Williams, G. C. Natural selection, the costs of reproduction, and a refinement of lack’s principle. Am. Nat. 100, 687–690 (1966).
Google Scholar 
Stearns, S. C. The evolution of life histories. (Oxford University Press, 1992).Kirkwood, T. B. L. Evolution of ageing. Nature 270, 301–304 (1977).ADS 
CAS 
PubMed 

Google Scholar 
Partridge, L., Prowse, N. & Pignatelli, P. Another set of responses and correlated responses to selection on age at reproduction in Drosophila melanogaster. Proc. R. Soc. B. 266, 255–261 (1999).CAS 
PubMed 
PubMed Central 

Google Scholar 
Metcalfe, N. Growth versus lifespan: Perspectives from evolutionary ecology. Exp. Gerontol. 38, 935–940 (2003).PubMed 

Google Scholar 
Lee, W.-S., Monaghan, P. & Metcalfe, N. B. Experimental demonstration of the growth rate–lifespan trade-off. Proc. R. Soc. B. 280, 20122370 (2013).PubMed 
PubMed Central 

Google Scholar 
Lemaître, J.-F. et al. Early-late life trade-offs and the evolution of ageing in the wild. Proc. R. Soc. B. 282, 20150209 (2015).PubMed 
PubMed Central 

Google Scholar 
Jehan, C., Sabarly, C., Rigaud, T. & Moret, Y. Late-life reproduction in an insect: Terminal investment, reproductive restraint or senescence. J. Anim. Ecol. 90, 282–297 (2021).PubMed 

Google Scholar 
Pawelec, G. Age and immunity: What is “immunosenescence”?. Exp. Gerontol. 105, 4–9 (2018).CAS 
PubMed 

Google Scholar 
Schwenke, R. A., Lazzaro, B. P. & Wolfner, M. F. Reproduction–immunity trade-offs in insects. Annu. Rev. Entomol. 61, 239–256 (2016).CAS 
PubMed 

Google Scholar 
Maklakov, A. A. & Chapman, T. Evolution of ageing as a tangle of trade-offs: Energy versus function. Proc. R. Soc. B. 286, 20191604 (2019).CAS 
PubMed 
PubMed Central 

Google Scholar 
Hamel, S. et al. Fitness costs of reproduction depend on life speed: empirical evidence from mammalian populations: Fitness costs of reproduction in mammals. Ecol. Lett. 13, 915–935 (2010).PubMed 

Google Scholar 
Graham, A. L., Allen, J. E. & Read, A. F. Evolutionary causes and consequences of immunopathology. Annu. Rev. Ecol. Evol. Syst. 36, 373–397 (2005).
Google Scholar 
Sorci, G. & Faivre, B. Inflammation and oxidative stress in vertebrate host–parasite systems. Phil. Trans. R. Soc. B. 364, 71–83 (2009).PubMed 

Google Scholar 
Ashley, N. T., Weil, Z. M. & Nelson, R. J. Inflammation: Mechanisms, costs, and natural variation. Annu. Rev. Ecol. Evol. Syst. 43, 385–406 (2012).
Google Scholar 
Babin, A., Moreau, J. & Moret, Y. Storage of carotenoids in crustaceans as an adaptation to modulate immunopathology and optimize immunological and life history strategies. BioEssays 41, 1800254 (2019).
Google Scholar 
Vasto, S. et al. Inflammatory networks in ageing, age-related diseases and longevity. Mech. Ageing Dev. 128, 83–91 (2007).CAS 
PubMed 

Google Scholar 
Finch, C. E. & Crimmins, E. M. Inflammatory exposure and historical changes in human life-spans. Science 305, 1736–1739 (2004).ADS 
CAS 
PubMed 

Google Scholar 
Licastro, F. et al. Innate immunity and inflammation in ageing: A key for understanding age-related diseases. Immun. Ageing 2, 8 (2005).PubMed 
PubMed Central 

Google Scholar 
Pawelec, G., Goldeck, D. & Derhovanessian, E. Inflammation, ageing and chronic disease. Curr. Opin. Immunol. 29, 23–28 (2014).CAS 
PubMed 

Google Scholar 
Pursall, E. R. & Rolff, J. Immune responses accelerate ageing: Proof-of-principle in an insect model. PLoS ONE 6, e19972 (2011).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Khan, I., Agashe, D. & Rolff, J. Early-life inflammation, immune response and ageing. Proc. R. Soc. B. 284, 20170125 (2017).PubMed 
PubMed Central 

Google Scholar 
Vigneron, A., Jehan, C., Rigaud, T. & Moret, Y. Immune defenses of a beneficial pest: The mealworm beetle, Tenebrio molitor. Front. Physiol. 10, 138 (2019).PubMed 
PubMed Central 

Google Scholar 
Jehan, C., Chogne, M., Rigaud, T. & Moret, Y. Sex-specific patterns of senescence in artificial insect populations varying in sex-ratio to manipulate reproductive effort. BMC Evol. Biol. 20, 18 (2020).PubMed 
PubMed Central 

Google Scholar 
Jehan, C., Sabarly, C., Rigaud, T. & Moret, Y. Age-specific fecundity under pathogenic threat in an insect: Terminal investment versus reproductive restraint. J. Anim. Ecol. 91, 101–111 (2022).PubMed 

Google Scholar 
Chung, K.-H. & Moon, M.-J. Fine structure of the hemopoietic tissues in the mealworm beetle, Tenebrio molitor. Entomol. Res. 34, 131–138 (2004).
Google Scholar 
Urbański, A., Adamski, Z. & Rosiński, G. Developmental changes in haemocyte morphology in response to Staphylococcus aureus and latex beads in the beetle Tenebrio molitor L.. Micron 104, 8–20 (2018).PubMed 

Google Scholar 
Vommaro, M. L., Kurtz, J. & Giglio, A. Morphological characterisation of haemocytes in the mealworm beetle Tenebrio molitor (Coleoptera, Tenebrionidae). Insects 12, 423 (2021).PubMed 
PubMed Central 

Google Scholar 
Söderhäll, K. & Cerenius, L. Role of the prophenoloxidase-activating system in invertebrate immunity. Curr. Opin. Immunol. 10, 23–28 (1998).PubMed 

Google Scholar 
Siva-Jothy, M. T., Moret, Y. & Rolff, J. Insect immunity: an evolutionary ecology perspective. in Advances in Insect Physiology vol. 32 1–48 (Elsevier, 2005).Nappi, A. J. & Ottaviani, E. Cytotoxicity and cytotoxic molecules in invertebrates. BioEssays 22, 469–480 (2000).CAS 
PubMed 

Google Scholar 
Sadd, B. M. & Siva-Jothy, M. T. Self-harm caused by an insect’s innate immunity. Proc. R. Soc. B. 273, 2571–2574 (2006).PubMed 
PubMed Central 

Google Scholar 
Daukšte, J., Kivleniece, I., Krama, T., Rantala, M. J. & Krams, I. Senescence in immune priming and attractiveness in a beetle: Immunosenescence in a beetle. J. Evol. Biol. 25, 1298–1304 (2012).PubMed 

Google Scholar 
Krams, I. et al. Trade-off between cellular immunity and life span in mealworm beetles Tenebrio molitor. Curr. Zool. 59, 340–346 (2013).
Google Scholar 
Moon, H. J., Lee, S. Y., Kurata, S., Natori, S. & Lee, B. L. Purification and molecular cloning of cDNA for an inducible antibacterial protein from larvae of the coleopteran, Tenebrio molitor. J. Biochem. 116, 53–58 (1994).CAS 
PubMed 

Google Scholar 
Lee, Y. J. et al. Structure and expression of the tenecin 3 gene in Tenebrio molitor. Biochem. Biophys. Res. Comm. 218, 6–11 (1996).CAS 
PubMed 

Google Scholar 
Kim, D. H. et al. Bacterial expression of tenecin 3, an insect antifungal protein isolated from Tenebrio molitor, and its efficient purification. Mol. Cells 8, 786–789 (1998).CAS 
PubMed 

Google Scholar 
Roh, K.-B. et al. Proteolytic cascade for the activation of the insect toll pathway induced by the fungal cell wall component. J. Biol. Chem. 284, 19474–19481 (2009).CAS 
PubMed 
PubMed Central 

Google Scholar 
Park, J.-W. et al. Beetle Immunity. in Invertebrate Immunity (ed. Söderhäll, K.) vol. 708 163–180 (Springer US, 2010).Chae, J.-H. et al. Purification and characterization of tenecin 4, a new anti-Gram-negative bacterial peptide, from the beetle Tenebrio molitor. Dev. Comp. Immunol. 36, 540–546 (2012).CAS 
PubMed 

Google Scholar 
Haine, E. R., Pollitt, L. C., Moret, Y., Siva-Jothy, M. T. & Rolff, J. Temporal patterns in immune responses to a range of microbial insults (Tenebrio molitor). J. Insect Physiol. 54, 1090–1097 (2008).CAS 
PubMed 

Google Scholar 
Dhinaut, J., Chogne, M. & Moret, Y. Immune priming specificity within and across generations reveals the range of pathogens affecting evolution of immunity in an insect. J. Anim. Ecol. 87, 448–463 (2018).PubMed 

Google Scholar 
Hoffmann, J. A., Reichhart, J.-M. & Hetru, C. Innate immunity in higher insects. Curr. Opin. Immunol. 8, 8–13 (1996).CAS 
PubMed 

Google Scholar 
Moret, Y. Explaining variable costs of the immune response: selection for specific versus non-specific immunity and facultative life history change. Oikos 102, 213–216 (2003).
Google Scholar 
Khan, I., Prakash, A. & Agashe, D. Immunosenescence and the ability to survive bacterial infection in the red flour beetle Tribolium castaneum. J. Anim. Ecol. 85, 291–301 (2016).PubMed 

Google Scholar 
Rolff, J. Effects of age and gender on immune function of dragonflies (Odonata, Lestidae) from a wild population. Can. J. Zool. 79, 2176–2180 (2001).
Google Scholar 
Doums, C., Moret, Y., Benelli, E. & Schmid-Hempel, P. Senescence of immune defence in Bombus workers. Ecol. Entomol. 27, 138–144 (2002).
Google Scholar 
Schmid, M. R., Brockmann, A., Pirk, C. W. W., Stanley, D. W. & Tautz, J. Adult honeybees (Apis mellifera L.) abandon hemocytic, but not phenoloxidase-based immunity. J. Insect Physiol. 54, 439–444 (2008).CAS 
PubMed 

Google Scholar 
Moret, Y. & Schmid-Hempel, P. Immune responses of bumblebee workers as a function of individual and colony age: senescence versus plastic adjustment of the immune function. Oikos 118, 371–378 (2009).
Google Scholar 
Armitage, S. A. O. & Boomsma, J. J. The effects of age and social interactions on innate immunity in a leaf-cutting ant. J. Insect Physiol. 56, 780–787 (2010).CAS 
PubMed 

Google Scholar 
Korner, P. & Schmid-Hempel, P. In vivo dynamics of an immune response in the bumble bee Bombus terrestris. J. Invert. Pathol. 87, 59–66 (2004).CAS 

Google Scholar 
Li, T., Yan, D., Wang, X., Zhang, L. & Chen, P. Hemocyte changes during immune melanization in Bombyx Mori infected with Escherichia coli. Insects 10, 301 (2019).PubMed Central 

Google Scholar 
Chase, M. R., Raina, K., Bruno, J. & Sugumaran, M. Purification, characterization and molecular cloning of prophenoloxidases from Sarcophaga bullata. Insect Biochem. Mol. Biol. 30, 953–967 (2000).CAS 
PubMed 

Google Scholar 
Kanost, M. R. & Gorman, M. J. Phenoloxidases in insect immunity. in Insect Immunology 69–96 (Elsevier, 2008).Sadd, B. M. et al. Modulation of sexual signalling by immune challenged male mealworm beetles (Tenebrio molitor L.): Evidence for terminal investment and dishonesty. J. Evol. Biol. 19, 321–325 (2006).CAS 
PubMed 

Google Scholar 
Gálvez, D. & Chapuisat, M. Immune priming and pathogen resistance in ant queens. Ecol. Evol. 4, 1761–1767 (2014).PubMed 
PubMed Central 

Google Scholar 
Armitage, S. A. O. & Siva-Jothy, M. T. Immune function responds to selection for cuticular colour in Tenebrio molitor. Heredity 94, 650–656 (2005).CAS 
PubMed 

Google Scholar 
Armitage, S. A. O., Thompson, J. J. W., Rolff, J. & Siva-Jothy, M. T. Examining costs of induced and constitutive immune investment in Tenebrio molitor. J. Evol. Biol. 16, 1038–1044 (2003).CAS 
PubMed 

Google Scholar 
Kokoza, V. A. et al. Transcriptional regulation of the mosquito vitellogenin gene via a blood meal-triggered cascade. Gene 274, 47–65 (2001).CAS 
PubMed 

Google Scholar 
Isaac, P. G. & Bownes, M. Ovarian and fat-body vitellogenin synthesis in Drosophila melanogaster. Europ. J. Biochem. 123, 527–534 (2005).
Google Scholar 
Hoffmann, J. A. The immune response of Drosophila. Nature 426, 33–38 (2003).ADS 
CAS 
PubMed 

Google Scholar 
Tzou, P. et al. Tissue-specific inducible expression of antimicrobial peptide genes in Drosophila surface epithelia. Immunity 13, 737–748 (2000).CAS 
PubMed 

Google Scholar 
Haine, E. R., Moret, Y., Siva-Jothy, M. T. & Rolff, J. Antimicrobial defense and persistent infection in insects. Science 322, 1257–1259 (2008).ADS 
CAS 
PubMed 

Google Scholar 
Moret, Y. & Siva-Jothy, M. T. Adaptive innate immunity? Responsive-mode prophylaxis in the mealworm beetle, Tenebrio molitor. Proc. R. Soc. B. 270, 2475–2480 (2003).CAS 
PubMed 
PubMed Central 

Google Scholar 
Du Rand, N. & Laing, M. D. Determination of insecticidal toxicity of three species of entomopathogenic spore-forming bacterial isolates against Tenebrio molitor L. (Coleoptera: Tenebrionidae). Afr. J. Microbiol. Res. 5, 2222–2228 (2011).
Google Scholar 
Jurat-Fuentes, J. L. & Jackson, T. Bacterial entomopathogens. In Insect Pathology 2nd edn (eds Kaya, H. & Vera, F.) 265–349 (Elsevier Academic Press, Cambridge, Mass, 2012).
Google Scholar 
Dhinaut, J., Balourdet, A., Teixeira, M., Chogne, M. & Moret, Y. A dietary carotenoid reduces immunopathology and enhances longevity through an immune depressive effect in an insect model. Sci. Rep. 7, 12429 (2017).ADS 
PubMed 
PubMed Central 

Google Scholar 
Moreau, J., Martinaud, G., Troussard, J.-P., Zanchi, C. & Moret, Y. Trans-generational immune priming is constrained by the maternal immune response in an insect. Oikos 121, 1828–1832 (2012).
Google Scholar 
Lee, H. S. et al. The pro-phenoloxidase of coleopteran insect, Tenebrio molitor, larvae was activated during cell clump/cell adhesion of insect cellular defense reactions. FEBS Lett. 444, 255–259 (1999).CAS 
PubMed 

Google Scholar 
Zanchi, C., Troussard, J.-P., Martinaud, G., Moreau, J. & Moret, Y. Differential expression and costs between maternally and paternally derived immune priming for offspring in an insect. J. Anim. Ecol. 80, 1174–1183 (2011).PubMed 

Google Scholar 
Moret, Y. ‘Trans-generational immune priming’: Specific enhancement of the antimicrobial immune response in the mealworm beetle, Tenebrio molitor. Proc. R. Soc. B. 273, 1399–1405 (2006).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Dubuffet, A. et al. Trans-generational immune priming protects the eggs only against gram-positive bacteria in the mealworm beetle. PLoS Pathog. 11, e1005178 (2015).PubMed 
PubMed Central 

Google Scholar  More

PTM concentrationsIn Table 1, the descriptive statistics of PTMs in 50 dust samples from Qom city are described. The background values were used based on the concentrations of metals in the Upper Continental Crust. The mean concentration of As, Cd, Cu, Mo, Pb, Sb, and, Zn exceeded the background value. Also, Cd, Cu, Mo, Pb, Sb, and, Zn had a coefficient of variation (C.V.) greater than 50%, indicating a severe variability in PTMs concentrations in the atmospheric dust of the studied area2. Metals with C.V.  Pb  > Zn  > As  > Cd  > Cu  > Mo  > Cr  > Mn  > Ni = Co. Antimony (38.55) and Pb (35.13) had the highest average EF values, which means they were enriched very high in the windowsill dust. Also, they had a wide range of EF values in the 50 stations: from 4.0 to 227.0 for Sb, and from 8.3 to 140.8 for Pb which might reflect the existence of discrete multiple sources in the studied area. The degree of enrichment for Pb and Sb in the industrial sector was extreme and in the commercial sector was very high; also, the other sectors were significantly enriched. Zinc and As had a more homogenous enrichment in the area. In all the functional sectors, 95% and 84% of stations were significantly enriched by As and Zn, respectively. Copper, Cd, and Mo were moderately enriched in all functional sectors, but the greenspace sector had minimal enrichment by these elements. Some areas in the industrial sector had significant to very high enrichment of Cd. The EF value indicated Co, Cr, Mn, and Ni were minimally enriched in all the stations.Figure 2Box plot of the (a) enrichment factor (EF), and (b) geo accumulation index (Igeo) for the dust samples in the studied area.Full size imageThe highest average values of Igeo were obtained in the order of Pb  > Sb  > As  > Zn. PTMs included Co, Cr, Ni, Fe, and Mn were categorized as unpolluted and Cd, Cu, and Mo were in the category of unpolluted to moderately polluted. In the industrial zone, the windowsill dust was extremely polluted with Sb and Pb. The sequence of contamination intensity with Pb, Zn and Sb according to land use was: industrial  > commercial  > residential  > greenspace. The highest concentration of arsenic in the study area belongs to the industrial area.To evaluate the pollution level based on land use, PLI and mCd indices were utilized (Fig. 3). These cumulative indices showed that the dust in Qom city is considerably contaminated with PTMs. According to the PLI index, all the stations were categorized as polluted sites. The PLIzone values were in the order of industrial (3.77)  > commercial (2.05)  > residential (1.67)  > green space (1.38). This pattern was also repeated with the mCd index. The mCd for the industrial sector ranged from 6.98 (high contamination level) to 39.60 (ultra-high contamination level). In the commercial sector, fifty percent of dust samples were classified as having a high degree of contamination. All the greenspace stations were in the moderate pollution category. This shows the possible effect of tree density in diminishing the risk of dust pollution to the receptors.Figure 3Pollution level indexes (a) mCd and (b) PLI, based on four functional areas.Full size imageSpatial distribution of PTMsThe As, Cd, Cu, Sb, Pb, and Zn content in 100% of the dust samples exceeded the background value. Spatial distribution maps were generated for the hotspot PTMs (As, Sb, Pb, Cd, Cu, Mo and Zn) by applying the inverse distance weighted (IDW) interpolation method (ArcGIS 10.3). Figure 4 demonstrates that PTMs dispersions were slightly influenced by the prevailing wind direction (from the west), suggesting they came from the point- or area- sources. On the other hand, the K–S test showed that the overall distribution of PTMs was not normal in the studied region. This might signify the influence of industrial activities and the presence of multiple sources of dust.Figure 4Spatial distribution maps of seven PTMs in windowsill dusts of Qom, Iran. This map was constructed using ArcGIS version 10.3. (https://www.esri.com/en-us/arcgis/products/arcgisdesktop/overview).Full size imageThe highest pollution load of PTMs belonged to the industrial section. The level of pollution gradually decreased from Shokouhieh to Mahmoudabad industrial zones. The reason is related to more active industries, a closed environment, and more construction existing in Shokouhieh industrial town than in Mahmoudabad industrial town.There is a clear decreasing trend from the central part to southern (downtown area) and southwestern (suburb area) parts of the city. In fact, these parts are diffusely populated and the southwestern part is almost new with lots of barren lands. Copper, Mo, and Cd show high concentrations toward the central part of the city. Educational, cultural and commercial activities are mainly located in the central part of the city. Also, historical and religious districts in the city center are accompanied by a huge influx of tourists throughout the year. For this reason, the central part of the city has various public transportations such as bus stands and taxi stations, and is dominated by a high load of motorcycles.In the eastern part of the city, some hotspots can be observed (Fig. 4). This part includes an important transportation system (like highways and a complex interchange) where exhaust traffic emissions might be a probable source of As, Sb, Pb, and Zn. Unlike Pb and Zn, several peaks of As are scattered in the western part, suggesting an area source might exist in the region. It is noteworthy that the western area is densely populated with lots of residential buildings. Bisht et al. (2022)35 also observed hotspots of As in the residential area of Dehradun, India.PTM potential sourcesTo evaluate the relationship between PTMs in dust samples, the Spearman correlation and PCA were developed (Fig. 5) and more details are given in Table S7. Statistical analysis can help to identify the potential source of contamination in urban dust. The Spearman correlation was significant at p  residential ≈ greenspace. The five PTMs with the highest overall HI are ranked as follows: Pb  > As  > Cr  > Mn  > Sb (Fig. 7). The HI values in all the sections were lower than the permissible level (1.00), except for Pb. In the industrial section, Pb recorded the highest HI value for children (HI = 1.73) which exceeded the acceptable value. The HI values were 10 times higher for children than adults indicating they are more susceptible to PTMs in the dust.The dominant pathway for noncancerous risk was ingestion followed by dermal contact and inhalation. The trend is in line with previous research25,51,52. However, for Co and Mn, the descending order was different as follows ingestion  > inhalation  > dermal contact. The highest contribution of HQinh and HQderm to HI was measured for Co (34.0%) and Cd (29.0%), respectively.In this study, the carcinogenic risk from windowsill dust was estimated for the carcinogens including Cd, Co, Cr and Ni, Pb, and As through the possible routes (Fig. 8, Table S9). The contribution of PTMs to CR decreased in the order of Cr (3.24E−05)  > As (2.05E−05)  > Pb (2.52E−06)  > Co (6.91E−09)  > Ni (1.72E−09)  > Cd (2.58E−10). The average CR values for target PTMs through inhalation ranged from 7.9E−10 to 1.7E−07, which remained in the safety zone (CR  inhalation  > dermal (Fig. 8). While the contribution of Cr to carcinogenic risk was higher through inhalation than ingestion. The reports concluded that the primary exposure route of Cr is inhalation54. Considering the predominant forms of Cr in the environment, CrVI is more toxic than CrIII. Exposure to CrVI can cause immunological diseases, dental effects and carcinogenic effects (lung cancer, nose and nasal sinus cancer, suspected laryngeal and stomach cancers)54,55.The result of health risk from target PTMs in windowsills of Qom indicates significant chronic exposure to Pb can take place for children in the industrial zone. The ingestion route is the most probable pathway for children due to their hand–to–mouth behavior56. Lead can bio-accumulate in the body without any obvious symptoms of toxicity56. The total CR values for Pb, Cr and As in different land-use types were in the range of tolerable carcinogenic risk (1 × 10−4  More

Kristensen, T. N. et al. A test of quantitative genetic theory using Drosophila- effects of inbreeding and rate of inbreeding on heritabilities and variance components. J. Evol. Biol. 18, 763–770 (2005).CAS 
PubMed 

Google Scholar 
Angeloni, F., Ouborg, N. J. & Leimu, R. Meta-analysis on the association of population size and life history with inbreeding depression in plants. Biol. Conserv. 144, 35–43 (2011).
Google Scholar 
Caballero, A., Bravo, I. & Wang, J. Inbreeding load and purging: implications for the short-term survival and the conservation management of small populations. Heredity 118, 177–185 (2017).CAS 
PubMed 

Google Scholar 
Park, D. S., Ellison, A. M. & Davis, C. C. Mating system does not predict niche breath. Glob. Ecol. Biogeogr. 27, 804–813 (2018).
Google Scholar 
Buckley, J., Daly, R., Cobbold, C. A., Burgess, K. & Mable, B. K. Changing environments and genetic variation: natural variation in inbreeding does not compromise short-term physiological responses. Proc. R. Soc. B Biol. Sci. 286, 20192109 (2019).
Google Scholar 
Grossenbacher, D., Briscoe Runquist, R., Goldberg, E. E. & Brandvain, Y. Geographic range size is predicted by plant mating system. Ecol. Lett. 18, 706–713 (2015).PubMed 

Google Scholar 
Wright, S. I., Lauga, B. & Charlesworth, D. Rates and patterns of molecular evolution in inbred and outbred arabidopsis. Mol. Biol. Evol. 19, 1407–1420 (2002).CAS 
PubMed 

Google Scholar 
Atwell, S. et al. Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred lines. Nature 465, 627–631 (2010).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Platt, A. et al. The scale of population structure in Arabidopsis thaliana. PLoS Genet. 6, e1000843 (2010).PubMed 
PubMed Central 

Google Scholar 
Lynch, M., Conery, J. & Burger, R. Mutation accumulation and the extinction of small populations. Am. Nat. 146, 489–518 (1995).
Google Scholar 
Willis, J. H. The role of genes of large effect on inbreeding depression in Mimulus guttatus. Evolution 53, 1678–1691 (1999).CAS 
PubMed 

Google Scholar 
Coron, C., Méléard, S., Porcher, E. & Robert, A. Quantifying the mutational meltdown in diploid populations. Am. Nat. 181, 623–636 (2013).PubMed 

Google Scholar 
Kyriazis, C. C., Wayne, R. K. & Lohmueller, K. E. Strongly deleterious mutations are a primary determinant of extinction risk due to inbreeding depression. Evol. Lett. https://doi.org/10.1002/evl3.209 (2020).Barrett, S. C. H. & Charlesworth, D. Effects of a change in the level of inbreeding on the genetic load. Nature 352, 522–524 (1991).ADS 
CAS 
PubMed 

Google Scholar 
Hedrick, P. W. & Garcia-Dorado, A. Understanding inbreeding depression, purging, and genetic rescue. Trends Ecol. Evol. 31, 940–952 (2016).PubMed 

Google Scholar 
Robinson, J. A., Brown, C., Kim, B. Y., Lohmueller, K. E. & Wayne, R. K. Purging of strongly deleterious mutations explains long-term persistence and absence of inbreeding depression in island foxes. Curr. Biol. 28, 3487–3494.e4 (2018).CAS 
PubMed 
PubMed Central 

Google Scholar 
Khan, A. et al. Genomic evidence for inbreeding depression and purging of deleterious genetic variation in Indian tigers. Proc. Natl. Acad. Sci. USA 118, e2023018118 (2021).Byers, D. L. & Waller, D. M. Do plant populations purge their genetic load? Effects of population size and mating history on inbreeding depression. Annu. Rev. Ecol. Syst. 30, 479–513 (1999).
Google Scholar 
Goodwillie, C., Kalisz, S. & Eckert, C. G. The evolutionary enigma of mixed mating systems in plants: occurrence, theoretical explanations, and empirical evidence. Annu. Rev. Ecol. Evol. Syst. 36, 47–79 (2005).
Google Scholar 
Hill, W. G. & Robertson, A. The effect of linkage on limits to artificial selection. Genet. Res. 8, 269–294 (1966).CAS 
PubMed 

Google Scholar 
Covert, A. W. III, Lenski, R. E., Wilke, C. O. & Ofria, C. Experiments on the role of deleterious mutations as stepping stones in adaptive evolution. Proc. Natl Acad. Sci. USA 110, E3171–E3178 (2013).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Castellano, D., Coronado-Zamora, M., Campos, J. L., Barbadilla, A. & Eyre-Walker, A. Adaptive evolution is substantially impeded by hill–robertson interference in Drosophila. Mol. Biol. Evol. 33, 442–455 (2016).CAS 
PubMed 

Google Scholar 
Anderson, J. T., Lee, C.-R., Rushworth, C. A., Colautti, R. I. & Mitchell-Olds, T. Genetic trade-offs and conditional neutrality contribute to local adaptation. Mol. Ecol. 22, 699–708 (2013).PubMed 

Google Scholar 
Hämälä, T. & Savolainen, O. Genomic patterns of local adaptation under gene flow in arabidopsis lyrata. Mol. Biol. Evol. 36, 2557–2571 (2019).
Google Scholar 
Taylor, M. A. et al. Large-effect flowering time mutations reveal conditionally adaptive paths through fitness landscapes in Arabidopsis thaliana. Proc. Natl Acad. Sci. USA 116, 17890–17899 (2019).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Storz, J. F. Causes of molecular convergence and parallelism in protein evolution. Nat. Rev. Genet. 17, 239–250 (2016).CAS 
PubMed 
PubMed Central 

Google Scholar 
Mimura, M. & Aitken, S. N. Local adaptation at the range peripheries of Sitka spruce. J. Evol. Biol. 23, 249–258 (2010).CAS 
PubMed 

Google Scholar 
Stanton-Geddes, J., Tiffin, P. & Shaw, R. G. Role of climate and competitors in limiting fitness across range edges of an annual plant. Ecology 93, 1604–1613 (2012).PubMed 

Google Scholar 
Vergeer, P. & Kunin, W. E. Adaptation at range margins: common garden trials and the performance of Arabidopsis lyrata across its northwestern European range. N. Phytol. 197, 989–1001 (2013).
Google Scholar 
Volis, S., Ormanbekova, D. & Shulgina, I. Role of selection and gene flow in population differentiation at the edge vs. interior of the species range differing in climatic conditions. Mol. Ecol. 25, 1449–1464 (2016).CAS 
PubMed 

Google Scholar 
Glémin, S., Bazin, E. & Charlesworth, D. Impact of mating systems on patterns of sequence polymorphism in flowering plants. Proc. R. Soc. B Biol. Sci. 273, 3011–3019 (2006).
Google Scholar 
Almeida‐Rocha, J. M., Soares, L. A. S. S., Andrade, E. R., Gaiotto, F. A. & Cazetta, E. The impact of anthropogenic disturbances on the genetic diversity of terrestrial species: A global meta‐analysis. Mol. Ecol. 29, 4812–4822 (2020).PubMed 

Google Scholar 
Schrader, L. et al. Transposable element islands facilitate adaptation to novel environments in an invasive species. Nat. Commun. 5, 5495 (2014).ADS 
CAS 
PubMed 

Google Scholar 
Lu, L. et al. Tracking the genome-wide outcomes of a transposable element burst over decades of amplification. Proc. Natl Acad. Sci. USA 114, E10550–E10559 (2017).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Schrader, L. & Schmitz, J. The impact of transposable elements in adaptive evolution. Mol. Ecol. 28, 1537–1549 (2019).PubMed 

Google Scholar 
Habig, M., Lorrain, C., Feurtey, A., Komluski, J. & Stukenbrock, E. H. Epigenetic modifications affect the rate of spontaneous mutations in a pathogenic fungus. Nat. Commun. 12, 1–13 (2021).
Google Scholar 
Wicker, T. et al. DNA transposon activity is associated with increased mutation rates in genes of rice and other grasses. Nat. Commun. 7, 1–9 (2016).
Google Scholar 
Dubin, M. J., Mittelsten Scheid, O. & Becker, C. Transposons: a blessing curse. Curr. Opin. Plant Biol. 42, 23–29 (2018).CAS 
PubMed 

Google Scholar 
Stapley, J., Santure, A. W. & Dennis, S. R. Transposable elements as agents of rapid adaptation may explain the genetic paradox of invasive species. Mol. Ecol. 24, 2241–2252 (2015).CAS 
PubMed 

Google Scholar 
Sultana, T., Zamborlini, A., Cristofari, G. & Lesage, P. Integration site selection by retroviruses and transposable elements in eukaryotes. Nat. Rev. Genet. 18, 292–308 (2017).CAS 
PubMed 

Google Scholar 
Baduel, P. et al. Genetic and environmental modulation of transposition shapes the evolutionary potential of Arabidopsis thaliana. Genome Biol. 22, 1–26 (2021).
Google Scholar 
Quesneville, H. Twenty years of transposable element analysis in the Arabidopsis thaliana genome. Mob. DNA 11, 28 (2020).PubMed 
PubMed Central 

Google Scholar 
Ossowski, S. et al. The rate and molecular spectrum of spontaneous mutations in Arabidopsis thaliana. Science 327, 92–94 (2010).ADS 
CAS 
PubMed 

Google Scholar 
Coulondre, C., Miller, J. H., Farabaugh, P. J. & Gilbert, W. Molecular basis of base substitution hotspots in Escherichia coli. Nature 274, 775–780 (1978).ADS 
CAS 
PubMed 

Google Scholar 
Duncan, B. K. & Miller, J. H. Mutagenic deamination of cytosine residues in DNA. Nature 287, 560–561 (1980).ADS 
CAS 
PubMed 

Google Scholar 
Linquist, S. et al. Distinguishing ecological from evolutionary approaches to transposable elements. Biol. Rev. 88, 573–584 (2013).PubMed 

Google Scholar 
Dupeyron, M., Singh, K. S., Bass, C. & Hayward, A. Evolution of Mutator transposable elements across eukaryotic diversity. Mob. DNA 10, 1–14 (2019).
Google Scholar 
Batstone, R. T. Genomes within genomes: nested symbiosis and its implications for plant evolution. New Phytol. https://doi.org/10.1111/nph.17847 (2021).Pietzenuk, B. et al. Recurrent evolution of heat-responsiveness in Brassicaceae COPIA elements. Genome Biol. 17, 209 (2016).PubMed 
PubMed Central 

Google Scholar 
Horváth, V., Merenciano, M. & González, J. Revisiting the relationship between transposable elements and the eukaryotic stress response. Trends Genet. 33, 832–841 (2017).PubMed 

Google Scholar 
Liu, S. et al. Role of H1 and DNA methylation in selective regulation of transposable elements during heat stress. N. Phytol. 229, 2238–2250 (2021).CAS 

Google Scholar 
Mao, H. et al. A transposable element in a NAC gene is associated with drought tolerance in maize seedlings. Nat. Commun. 6, 1–13 (2015).ADS 
CAS 

Google Scholar 
Castelletti, S., Tuberosa, R., Pindo, M. & Salvi, S. A MITE transposon insertion is associated with differential methylation at the maize flowering time QTL vgt1. G3 Genes, Genomes, Genet. 4, 805–812 (2014).CAS 

Google Scholar 
Legrand, S. et al. Differential retention of transposable element-derived sequences in outcrossing Arabidopsis genomes. Mob. DNA 10, 30 (2019).PubMed 
PubMed Central 

Google Scholar 
Quadrana, L. et al. Transposition favors the generation of large effect mutations that may facilitate rapid adaption. Nat. Commun. 10, 1–10 (2019).CAS 

Google Scholar 
Teschendorf, A. E. & Relton, C. L. Statistical and integrative system-level analysis of DNA methylation data. Nat. Rev. Genet. 19, 129–147 (2019).
Google Scholar 
Bonchev, G. & Willi, Y. Accumulation of transposable elements in selfing populations of Arabidopsis lyrata supports the ectopic recombination model of transposon evolution. N. Phytol. 219, 767–778 (2018).CAS 

Google Scholar 
Lockton, S., Ross-Ibarra, J. & Gaut, B. S. Demography and weak selection drive patterns of transposable element diversity in natural populations of Arabidopsis lyrata. Proc. Natl Acad. Sci. USA 105, 13965–13970 (2008).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Lockton, S. & Gaut, B. S. The evolution of transposable elements in natural populations of self-fertilizing Arabidopsis thaliana and its outcrossing relative Arabidopsis lyrata. BMC Evol. Biol. 10, 10 (2010).PubMed 
PubMed Central 

Google Scholar 
Mable, B. K., Dart, A. V. R., Berardo, C., Di & Witham, L. Breakdown of self-incompatibility in the perennial Arabidopsis lyrata (Brassicaceae) and its genetic consequences. Evolution 59, 1437–1448 (2005).PubMed 

Google Scholar 
Foxe, J. P. et al. Reconstructing origins of loss of self-incompatibility and selfing in North American Arabidopsis lyrata: a population genetic context. Evolution 64, 3495–3510 (2010).PubMed 

Google Scholar 
Quadrana, L. et al. The Arabidopsis thaliana mobilome and its impact at the species level. Elife 5, e15716 (2016).Stuart, T. et al. Population scale mapping of transposable element diversity reveals links to gene regulation and epigenomic variation. Elife 5, e20777 (2016).Willi, Y. Mutational meltdown in selfing Arabidopsis lyrata. Evolution 67, 806–815 (2013).PubMed 

Google Scholar 
Joschinski, J., van Kleunen, M. & Stift, M. Costs associated with the evolution of selfing in North American populations of Arabidopsis lyrata? Evol. Ecol. 29, 749–764 (2015).
Google Scholar 
Koonin, E. V. & Krupovic, M. Evolution of adaptive immunity from transposable elements combined with innate immune systems. Nat. Rev. Genet. 16, 184–192 (2015).CAS 
PubMed 

Google Scholar 
Li, Z.-W. et al. Transposable elements contribute to the adaptation of Arabidopsis thaliana. Genome Biol. Evol. 10, 2140–2150 (2018).CAS 
PubMed 
PubMed Central 

Google Scholar 
Catlin, N. S. & Josephs, E. B. The important contribution of transposable elements to phenotypic variation and evolution. Curr. Opin. Plant Biol. 65, 102140 (2022).CAS 
PubMed 

Google Scholar 
Casacuberta, E. & González, J. The impact of transposable elements in environmental adaptation. Mol. Ecol. 22, 1503–1517 (2013).CAS 
PubMed 

Google Scholar 
Baduel, P., Quadrana, L., Hunter, B., Bomblies, K. & Colot, V. Relaxed purifying selection in autopolyploids drives transposable element over-accumulation which provides variants for local adaptation. Nat. Commun. 10, 1–10 (2019).
Google Scholar 
Wos, G., Choudhury, R. R., Kolář, F. & Parisod, C. Transcriptional activity of transposable elements along an elevational gradient in Arabidopsis arenosa. Mob. DNA 12, 7 (2021).CAS 
PubMed 
PubMed Central 

Google Scholar 
Stebbins, G. L. Self fertilization and population variability in the higher plants. Am. Nat. 91, 337–354 (1957).
Google Scholar 
Takebayashi, N. & Morrell, P. L. Is self-fertilization an evolutionary dead end? Revisiting an old hypothesis with genetic theories and a macroevolutionary approach. Am. J. Bot. 88, 1143–1150 (2001).CAS 
PubMed 

Google Scholar 
Igic, B. & Busch, J. W. Is self‐fertilization an evolutionary dead end? N. Phytol. 198, 386–397 (2013).
Google Scholar 
Goldberg, E. E. et al. Species selection maintains self-incompatibility. Science 330, 493–495 (2010).ADS 
CAS 
PubMed 

Google Scholar 
Abu Awad, D. & Billiard, S. The double edged sword: The demographic consequences of the evolution of self-fertilization. Evolution 71, 1178–1190 (2017).PubMed 

Google Scholar 
Fijarczyk, A. & Babik, W. Detecting balancing selection in genomes: limits and prospects. Mol. Ecol. 24, 3529–3545 (2015).CAS 
PubMed 

Google Scholar 
Wu, Q. et al. Long-term balancing selection contributes to adaptation in Arabidopsis and its relatives. Genome Biol. 18, 1–15 (2017).CAS 

Google Scholar 
Kerwin, R. et al. Natural genetic variation in Arabidopsis thaliana defense metabolism genes modulates field fitness. Elife 2015, 1–28 (2015).
Google Scholar 
Waller, D. M. Addressing Darwin’s dilemma: can pseudo-overdominance explain persistent inbreeding depression and load? Evolution 75, 779–793 (2021).CAS 
PubMed 

Google Scholar 
Gilbert, K. J., Pouyet, F., Excoffier, L. & Peischl, S. Transition from background selection to associative overdominance promotes diversity in regions of low recombination. Curr. Biol. 30, 101–107.e3 (2020).CAS 
PubMed 

Google Scholar 
Buckley, J. et al. R-gene variation across Arabidopsis lyrata subspecies: effects of population structure, selection and mating system. BMC Evol. Biol. 16, 93 (2016).PubMed 
PubMed Central 

Google Scholar 
Schmickl, R., Jørgensen, M. H., Brysting, A. K. & Koch, M. A. Phylogeographic implications for the north american boreal-arctic Arabidopsis lyrata complex. Plant Ecol. Divers. 1, 245–254 (2008).
Google Scholar 
Buckley, J., Holub, E. B., Koch, M. A., Vergeer, P. & Mable, B. K. Restriction associated DNA-genotyping at multiple spatial scales in Arabidopsis lyrata reveals signatures of pathogen-mediated selection. BMC Genomics 19, 1–21 (2018).
Google Scholar 
Flutre, T., Duprat, E., Feuillet, C. & Quesneville, H. Considering transposable element diversification in de novo annotation approaches. PLoS ONE 6, e16526 (2011).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Luu, K., Bazin, E. & Blum, M. G. B. pcadapt: an R package to perform genome scans for selection based on principal component analysis. in. Mol. Ecol. Resour. 17, 67–77 (2017).CAS 
PubMed 

Google Scholar 
Privé, F., Luu, K., Vilhjálmsson, B. J. & Blum, M. G. B. Performing highly efficient genome scans for local adaptation with R Package pcadapt Version 4. Mol. Biol. Evol. 37, 2153–2154 (2020).PubMed 

Google Scholar 
Foll, M. & Gaggiotti, O. A genome-scan method to identify selected loci appropriate for both dominant and codominant markers: a Bayesian perspective. Genetics 180, 977–993 (2008).PubMed 
PubMed Central 

Google Scholar 
Charlesworth, J. & Eyre-Walker, A. The McDonald-Kreitman test and slightly deleterious mutations. Mol. Biol. Evol. 25, 1007–1015 (2008).CAS 
PubMed 

Google Scholar 
Hernandez, R. D. et al. Ultrarare variants drive substantial cis heritability of human gene expression. Nat. Genet. 51, 1349–1355 (2019).CAS 
PubMed 
PubMed Central 

Google Scholar 
Williamson, R. J. et al. Evidence for widespread positive and negative selection in coding and conserved noncoding regions of capsella grandiflora. PLoS Genet. 10, e1004622 (2014).PubMed 
PubMed Central 

Google Scholar 
Brooks, M. E. et al. glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. R. J. 9, 378–400 (2017).
Google Scholar 
Mattila, T. M., Tyrmi, J., Pyhäjärvi, T. & Savolainen, O. Genome-wide analysis of colonization history and concomitant selection in Arabidopsis lyrata. Mol. Biol. Evol. 34, 2665–2677 (2017).CAS 
PubMed 

Google Scholar  More

Phung, T. X., Nascimento, J. C. S., Novarro, A. J. & Wiens, J. J. Correlated and decoupled evolution of adult and larval body size in frogs. Proc. R. Soc. Lond. B 287, 20201474–10 (2020).
Google Scholar 
Hall, B. K. & Wake, M. H. The Origin and Evolution of Larval Forms (Gulf Professional Publishing, 1999).Hime, P. M. et al. Phylogenomics reveals ancient gene tree discordance in the amphibian tree of life. Syst. Biol. 70, 49–66 (2021).CAS 
PubMed 

Google Scholar 
Duellman, W. E. & Trueb, L. Biology of Amphibians (Johns Hopkins University Press, 1994).Nunes-de-Almeida, C. H., Batista Haddad, C. F. & Toledo, L. F. A revised classification of the amphibian reproductive modes. Salamandra 57, 413–427 (2021).
Google Scholar 
Vences, M. & Köhler, J. Global diversity of amphibians (Amphibia) in freshwater. Hydrobiologia 595, 569–580 (2007).
Google Scholar 
Blackburn, D. G. Evolution of vertebrate viviparity and specializations for fetal nutrition: a quantitative and qualitative analysis. J. Morphol. 276, 961–990 (2015).PubMed 

Google Scholar 
AmphibiaWeb. Electronic Database (University of California, Berkeley, CA, USA, 2019). https://amphibiaweb.org.Frost, D. R. Amphibian Species of the World: an Online Reference. Version 6.0 (date of access: 01.08.2019). Electronic Database (American Museum of Natural History, New York, USA, 2019). https://amphibiansoftheworld.amnh.org/.Bonett, R. M., Ledbetter, N. M., Hess, A. J., Herrboldt, M. A. & Denoël, M. Repeated ecological and life cycle transitions make salamanders an ideal model for evolution and development. Developmental Dynamics 251, 957–972 (2022).Salthe, S. N. Reproductive modes and the number and sizes of ova in the urodeles. Am. Midl. Naturalist 81, 467490 (1969).
Google Scholar 
Salthe, S. N. & Duellman, W. E. in Evolutionary Biology of the Anurans (ed. Vial, J. L.) 229–249 (University of Missouri Press Columbia, 1973).Haddad, C. & Prado, C. P. A. Reproductive modes in frogs and their unexpected diversity in the Atlantic Forest of Brazil. BioScience 55, 207–217 (2005).
Google Scholar 
Lutz, B. Ontogenetic evolution in frogs. Evolution 2, 29–39 (1948).CAS 
PubMed 

Google Scholar 
Crump, M. L. Anuran reproductive modes: evolving perspectives. J. Herpetol. 49, 1–16 (2015).
Google Scholar 
Schoch, R. Evolution of life cycles in early amphibians. Annu. Rev. Earth Planet. Sci. 37, 135–162 (2009).ADS 
CAS 

Google Scholar 
Meegaskumbura, M. et al. Patterns of reproductive-mode evolution in Old World tree frogs (Anura, Rhacophoridae). Zool. Scr. 44, 509–522 (2015).
Google Scholar 
Portik, D. M. & Blackburn, D. C. The evolution of reproductive diversity in Afrobatrachia: A phylogenetic comparative analysis of an extensive radiation of African frogs. Evolution 70, 2017–2032 (2016).PubMed 
PubMed Central 

Google Scholar 
San Mauro, D. et al. Life-history evolution and mitogenomic phylogeny of caecilian amphibians. Mol. Phylogenet. Evol. 73, 177–189 (2014).PubMed 

Google Scholar 
Pereira, E. B., Collevatti, R. G., de Carvalho Kokubum, M. N., de Oliveira Miranda, N. E. & Maciel, N. M. Ancestral reconstruction of reproductive traits shows no tendency toward terrestriality in leptodactyline frogs. BMC Evol. Biol. 15, 91 (2015).Gomez-Mestre, I., Pyron, R. A. & Wiens, J. J. Phylogenetic analyses reveal unexpected patterns in the evolution of reproductive modes in frogs. Evolution 66, 3687–3700 (2012).PubMed 

Google Scholar 
Wake, D. B. & Hanken, J. Direct development in the lungless salamanders: what are the consequences for developmental biology, evolution and phylogenesis? Int. J. Dev. Biol. 40, 859–869 (1996).CAS 
PubMed 

Google Scholar 
Dubois, A. Developmental pathway, speciation and supraspecific taxonomy in amphibians: 1. Why are there so many frog species in Sri Lanka? Alytes 22, 19–37 (2004).
Google Scholar 
Hedges, S. B., Duellman, W. E. & Heinicke, M. P. New World direct-developing frogs (Anura: Terrarana): molecular phylogeny, classification, biogeography, and conservation. Zootaxa 1737, 1–182 (2008).
Google Scholar 
Dugo-Cota, Á., Vilà, C., Rodríguez, A. & Gonzalez-Voyer, A. Ecomorphological convergence in Eleutherodactylus frogs: a case of replicate radiations in the Caribbean. Ecol. Lett. 22, 884–893 (2019).PubMed 

Google Scholar 
Simpson, G. G. The Major Features of Evolution (Columbia University Press, 1953).Vági, B., Végvári, Z., Liker, A., Freckleton, R. P. & Szekely, T. Parental care and the evolution of terrestriality in frogs. Proc. R. Soc. Lond. B 286, 20182737–10 (2019).
Google Scholar 
Furness, A. I. & Capellini, I. The evolution of parental care diversity in amphibians. Nat. Commun. 10, 1–12 (2019).CAS 

Google Scholar 
Furness, A. I., Venditti, C. & Capellini, I. Terrestrial reproduction and parental care drive rapid evolution in the trade-off between offspring size and number across amphibians. PLoS Biol. 20, e3001495 (2022).CAS 
PubMed 
PubMed Central 

Google Scholar 
Wollenberg, K. C., Vieites, D. R., Glaw, F. & Vences, M. Speciation in little: the role of range and body size in the diversification of Malagasy mantellid frogs. BMC Evol. Biol. 11, 217 (2011).PubMed 
PubMed Central 

Google Scholar 
Cayuela, H. et al. Determinants and consequences of dispersal in vertebrates with complex life cycles: a review of pond-breeding amphibians. Q. Rev. Biol. 95, 1–36 (2020).
Google Scholar 
Phillimore, A. B., Freckleton, R. P., Orme, C. D. L. & Owens, I. P. F. Ecology predicts large‐scale patterns of phylogenetic diversification in birds. Am. Nat. 168, 220–229 (2006).PubMed 

Google Scholar 
Chen, J.-M. et al. An integrative phylogenomic approach illuminates the evolutionary history of Old World tree frogs (Anura: Rhacophoridae). Mol. Phylogenet. Evol. 145, 106724 (2020).PubMed 

Google Scholar 
Zimkus, B. M., Lawson, L., Loader, S. P. & Hanken, J. Terrestrialization, miniaturization and rates of diversification in African Puddle Frogs (Anura: Phrynobatrachidae). PLoS ONE 7, e35118 (2012).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Moen, D. S. Improving inference and avoiding over-interpretation of hidden-state diversification models: specialized plant breeding has no effect on diversification in frogs. Evolution 76, 373–384 (2022).PubMed 

Google Scholar 
Eastman, J. M. & Storfer, A. Correlations of life-history and distributional-range variation with salamander diversification rates: evidence for species selection. Syst. Biol. 60, 503–518 (2011).PubMed 

Google Scholar 
Bonett, R. M., Steffen, M. A., Lambert, S. M., Wiens, J. J. & Chippindale, P. T. Evolution of paedomorphosis in plethodontid salamanders: ecological correlates and re-evolution of metamorphosis. Evolution 68, 466–482 (2014).PubMed 

Google Scholar 
Akaike, H. A new look at the statistical-model identification. IEEE Trans. Autom. Control 19, 716–723 (1974).ADS 
MathSciNet 
MATH 

Google Scholar 
Wagenmakers, E.-J. & Farrell, S. AIC model selection using Akaike weights. Psychon. Bull. Rev. 11, 192–196 (2004).PubMed 

Google Scholar 
Beaulieu, J. M., Oliver, J. C., O’Meara, B. & Boyko, J. R package ‘corHMM’: hidden markov models of character evolution. (2020).Pagel, M. & Meade, A. BayesTraits, version 4. University of Reading, Berkshire, UK. http://www.evolution.rdg.ac.uk (2022).Pagel, M. & Meade, A. Bayesian analysis of correlated evolution of discrete characters by reversible-jump Markov chain Monte Carlo. Am. Nat. 167, 808–825 (2006).PubMed 

Google Scholar 
Maddison, W., Midford, P. & Otto, S. Estimating a binary character’s effect on speciation and extinction. Syst. Biol. 56, 701–710 (2007).PubMed 

Google Scholar 
FitzJohn, R. G., Maddison, W. P. & Otto, S. P. Estimating trait-dependent speciation and extinction rates from incompletely resolved phylogenies. Syst. Biol. 58, 595–611 (2009).PubMed 

Google Scholar 
Beaulieu, J. M. & O’Meara, B. C. Detecting hidden diversification shifts in models of trait-dependent speciation and extinction. Syst. Biol. 65, 583–601 (2016).PubMed 

Google Scholar 
Herrera-Alsina, L., van Els, P. & Etienne, R. S. Detecting the dependence of diversification on multiple traits from phylogenetic trees and trait data. Syst. Biol. 68, 317–328 (2018).
Google Scholar 
Strathmann, R. R. Hypotheses on the origins of marine larvae. Annu. Rev. Ecol. Syst. 24, 89–117 (1993).
Google Scholar 
Wray, G. A. Evolution of larvae and developmental modes. In Ecology of Marine Invertebrate Larvae. (ed. McEdward, L.) 413–447 (CRC Press, 1995).Raff, R. A. Origins of the other metazoan body plans: the evolution of larval forms. Philos. T R. Soc. B 363, 1473–1479 (2008).
Google Scholar 
Collin, R. & Moran, A. in Evolutionary Ecology of Marine Invertebrate Larvae 50–66 (Oxford University Press, 2018).Collin, R. & Miglietta, M. P. Reversing opinions on Dollo’s Law. Trends Ecol. Evol. 23, 602–609 (2008).PubMed 

Google Scholar 
Wiens, J. J. Re-evolution of lost mandibular teeth in frogs after more than 200 million years, and re-evaluating Dollo’s law. Evolution 65, 1283–1296 (2011).PubMed 

Google Scholar 
Wiens, J. J., Kuczynski, C. A., Duellman, W. E. & Reeder, T. W. Loss and re-evolution of complex life cycles in marsupial frogs: does ancestral trait reconstruction mislead? Evolution 61, 1886–1899 (2007).CAS 
PubMed 

Google Scholar 
Chippindale, P. T., Bonett, R. M., Baldwin, A. S. & Wiens, J. J. Phylogenetic evidence for a major reversal of life-history evolution in plethodontid salamanders. Evolution 58, 2809–2815 (2004).CAS 
PubMed 

Google Scholar 
Castroviejo-Fisher, S. et al. Phylogenetic systematics of egg-brooding frogs (Anura: Hemiphractidae) and the evolution of direct development. Zootaxa 4004, 1–75 (2015).PubMed 

Google Scholar 
Naumann, B., Schweiger, S., Hammel, J. U. & Müller, H. Parallel evolution of direct development in frogs—skin and thyroid gland development in African Squeaker Frogs (Anura: Arthroleptidae: Arthroleptis). Dev. Dyn. 250, 584–600 (2021).PubMed 

Google Scholar 
Goldberg, J., Taucce, P. P. G., Quinzio, S. I., Haddad, C. F. B. & Candioti, F. V. Increasing our knowledge on direct-developing frogs: the ontogeny of Ischnocnema henselii (Anura: Brachycephalidae). Zool. Anz. 284, 78–87 (2020).
Google Scholar 
Wassersug, R. J. & Duellman, W. E. Oral structures and their development in egg-brooding hylid frog embryos and larvae: evolutionary and ecological implications. J. Morphol. 182, 1–37 (1984).PubMed 

Google Scholar 
Kerney, R. R., Blackburn, D. C., Müller, H. & Hanken, J. Do larval traits re-evolve? Evidence from the embryogenesis of a direct-developing salamander, Plethodon cinereus. Evolution 66, 252–262 (2011).PubMed 

Google Scholar 
Theska, T. Musculoskeletal development of the Central African caecilian Idiocranium russeli (Amphibia: Gymnophiona: Indotyphlidae) and its bearing on the re-evolution of larvae in caecilian amphibians. Zoomorphology 138, 137–158 (2019).
Google Scholar 
Laslo, M., Denver, R. J. & Hanken, J. Evolutionary conservation of thyroid hormone receptor and deiodinase expression dynamics in ovo in a direct-developing frog, Eleutherodactylus coqui. Front. Endocrinol. 10, 307 (2019).
Google Scholar 
Gao, W. et al. Genomic and transcriptomic investigations of the evolutionary transition from oviparity to viviparity. Proc. Natl Acad. Sci. USA 116, 3646–3655 (2019).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Altig, R. & Crother, B. I. The evolution of three deviations from the biphasic anuran life cycle: alternatives to selection. Herpetol. Rev. 37, 321–356 (2006).
Google Scholar 
Venturelli, D. P., da Silva, W. R. & Giaretta, A. A. Tadpoles’ resistance to desiccation in species of Leptodactylus (Anura, Leptodactylidae). J. Herpetol. 55, 265–270 (2021).
Google Scholar 
Seymour, R. S. Respiration of aquatic and terrestrial amphibian embryos. American Zoologist 39, 261–270 (1999).Blackburn, D. G. Convergent evolution of viviparity, matrotrophy, and specializations for fetal nutrition in reptiles and other vertebrates. Am. Zool. 32, 313–321 (1992).
Google Scholar 
Buckley, D., Alcobendas, M., García-París, M. & Wake, M. H. Heterochrony, cannibalism, and the evolution of viviparity in Salamandra salamandra. Evol. Dev. 9, 105–115 (2007).PubMed 

Google Scholar 
Kusrini, M. D., Rowley, J. J. L., Khairunnisa, L. R., Shea, G. M. & Altig, R. The reproductive biology and larvae of the first tadpole-bearing frog, Limnonectes larvaepartus. PLoS ONE 10, e116154–e116159 (2015).ADS 
PubMed 
PubMed Central 

Google Scholar 
Lanza, B. & Leo, P. Sul primo caso sicuro di riproduzione vivipara nel genere Speleomantes. 1–54 (2000).Lunghi, E. et al. Comparative reproductive biology of European cave salamanders (Genus Hydromantes): nesting selection and multiple annual breeding. Salamandra 54, 101–108 (2018).
Google Scholar 
Liedtke, H. C. et al. Terrestrial reproduction as an adaptation to steep terrain in African toads. Proc. R. Soc. Lond. B 284, 20162598–20162599 (2017).
Google Scholar 
Wake, M. H. The reproductive biology of Eleutherodactylus jasperi (Amphibia, Anura, Leptodactylidae), with comments on the evolution of live-bearing systems. J. Herpetol. 12, 121–133 (1978).
Google Scholar 
Jennings, D. H. & Hanken, J. Mechanistic basis of life history evolution in anuran amphibians: thyroid gland development in the direct-developing frog, Eleutherodactylus coqui. Gen. Comp. Endocr. 111, 225–232 (1998).CAS 
PubMed 

Google Scholar 
Callery, E. M. & Elinson, R. P. Thyroid hormone-dependent metamorphosis in a direct developing frog. Proc. Natl Acad. Sci. USA 97, 2615–2620 (2000).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Callery, E. M., Hung, F. & Elinson, R. P. Frogs without polliwogs: evolution of anuran direct development. BioEssays 23, 233–241 (2001).CAS 
PubMed 

Google Scholar 
Buckley, L. B. & Jetz, W. Environmental and historical constraints on global patterns of amphibian richness. Proc. R. Soc. Lond. B 274, 1167–1173 (2007).
Google Scholar 
Pyron, R. A. & Wiens, J. J. Large-scale phylogenetic analyses reveal the causes of high tropical amphibian diversity. Proc. R. Soc. Lond. B 280, 20131622 (2013).
Google Scholar 
Gómez-Rodríguez, C., Baselga, A. & Wiens, J. J. Is diversification rate related to climatic niche width? Glob. Ecol. Biogeogr. 24, 383–395 (2015).
Google Scholar 
Moen, D. S. & Wiens, J. J. Microhabitat and climatic niche change explain patterns of diversification among frog families. Am. Nat. 190, 29–44 (2017).PubMed 

Google Scholar 
Kozak, K. H. & Wiens, J. J. Accelerated rates of climatic-niche evolution underlie rapid species diversification. Ecol. Lett. 13, 1378–1389 (2010).PubMed 

Google Scholar 
Jaramillo, A. F. et al. Vastly underestimated species richness of Amazonian salamanders (Plethodontidae: Bolitoglossa) and implications about plethodontid diversification. Mol. Phylogenet. Evol. 149, 106841 (2020).PubMed 

Google Scholar 
Jetz, W. & Pyron, R. A. The interplay of past diversification and evolutionary isolation with present imperilment across the amphibian tree of life. Nat. Ecol. Evol. 2, 850–858 (2018).PubMed 

Google Scholar 
Bars-Closel, M., Kohlsdorf, T., Moen, D. S. & Wiens, J. J. Diversification rates are more strongly related to microhabitat than climate in squamate reptiles (lizards and snakes). Evolution 71, 2243–2261 (2017).PubMed 

Google Scholar 
Cyriac, V. P. & Kodandaramaiah, U. Digging their own macroevolutionary grave: fossoriality as an evolutionary dead end in snakes. J. Evolution. Biol. 31, 587–598 (2018).CAS 

Google Scholar 
Zamudio, K. R., Bell, R. C., Nali, R. C., Haddad, C. F. B. & Prado, C. P. A. Polyandry, predation, and the evolution of frog reproductive modes. Am. Nat. 188, S41–S61 (2016).PubMed 

Google Scholar 
Lion, M. B. et al. Global patterns of terrestriality in amphibian reproduction. Glob. Ecol. Biogeogr. 4, 679–13 (2019).
Google Scholar 
Müller, H. et al. Forests as promoters of terrestrial life-history strategies in East African amphibians. Biol. Lett. 9, 20121146–20121146 (2013).PubMed 
PubMed Central 

Google Scholar 
Velo-Antón, G., García-París, M., Galán, P. & Cordero Rivera, A. The evolution of viviparity in Holocene islands: ecological adaptation versus phylogenetic descent along the transition from aquatic to terrestrial environments. J. Zool. Syst. Evol. Res. 45, 345–352 (2007).
Google Scholar 
Liedtke, H. C. AmphiNom: an amphibian systematics tool. Syst. Biodivers. 17, 1–6 (2019).
Google Scholar 
R Core Team. R: a language and environment for statistical computing (R Foundation for Statistical Computing, Vienna, Austria, 2020). http://www.R-project.org/.IUCN. IUCN 2020. The IUCN Red List of Threatened Species. Version 2020-2. https://www.iucnredlist.org (2019).AmphibiaChina. The database of Chinese amphibians. Electronic Database (Kunming Institute of Zoology (CAS), Kunming, Yunnan, China, 2019) http://www.amphibiachina.org/.Ron, S. R., Yanez-Muñoz, M. H., Merino-Viteri, A. & Ortiz, D. A. Anfibios del Ecuador. Version 2019.0 (Museo de Zoología, Pontificia Universidad Católica del Ecuador, 2019). https://bioweb.bio/faunaweb/amphibiaweb.Greven, H. In Reproductive Biology and Phylogeny of Urodela 447–475 (Taylor & Francis, 2003).Marks, S. B. & Collazo, A. Direct development in Desmognathus aeneus (Caudata: Plethodontidae): a staging table. Copeia 1998, 637–648 (1998).
Google Scholar 
Müller, H., Loader, S. P., Ngalason, W., Howell, K. M. & Gower, D. J. Reproduction in brevicipitid frogs (Amphibia: Anura: Brevicipitidae)—evidence from Probreviceps m. macrodactylus. Copeia 2007, 726–733 (2007).
Google Scholar 
Velo-Antón, G., Santos, X., Sanmartín-Villar, I., Cordero-Rivera, A. & Buckley, D. Intraspecific variation in clutch size and maternal investment in pueriparous and larviparous Salamandra salamandra females. Evol. Ecol. 29, 185–204 (2014).
Google Scholar 
Beaulieu, J. M., O’Meara, B. C. & Donoghue, M. J. Identifying hidden rate changes in the evolution of a binary morphological character: the evolution of plant habit in campanulid angiosperms. Systematic biology 62, 725–737 (2013).Pupko, T., Pe’er, I., Shamir, R. & Graur, D. A fast algorithm for joint reconstruction of ancestral amino acid sequences. Mol. Biol. Evol. 17, 890–896 (2000).CAS 
PubMed 

Google Scholar 
Bollback, J. P. SIMMAP: stochastic character mapping of discrete traits on phylogenies. BMC Bioinforma. 7, 88 (2006).
Google Scholar 
Plummer, M., Best, N., Cowles, K. & Vines, K. CODA: convergence diagnosis and output analysis for MCMC. R. News 6, 7–11 (2006).
Google Scholar 
Tuffley, C. & Steel, M. Modeling the covarion hypothesis of nucleotide substitution. Math. Biosci. 147, 63–91 (1998).MathSciNet 
CAS 
PubMed 
MATH 

Google Scholar 
Xie, W., Lewis, P. O., Fan, Y., Kuo, L. & Chen, M. H. Improving marginal likelihood estimation for Bayesian phylogenetic model selection. Syst. Biol. 60, 150–160 (2011).PubMed 

Google Scholar 
Nakov, T., Beaulieu, J. M. & Alverson, A. J. Diatoms diversify and turn over faster in freshwater than marine environments. Evolution 73, 2497–2511 (2019).PubMed 

Google Scholar 
Etienne, R. S. et al. Diversity-dependence brings molecular phylogenies closer to agreement with the fossil record. Proc. R. Soc. Lond. B 279, 1300–1309 (2011).
Google Scholar  More

The effects of extreme drought on soil biochemical propertiesAs shown in Fig. 1A, the range of SOC during the early, midterm and late extreme drought experiments, were 73.53–251.44 g kg−1, 54.75–256.16 g kg−1, and 66.37–282.16 g kg−1, respectively. Concomitantly, DOC was 171.85–323.74 mg kg−1, 158.15 – 504.62 mg kg−1, and 166.63–418.43 mg kg−1, MBC was 247.80 – 461.69 mg kg−1, 257.90–450.98 mg kg−1, and 264.10–458.15 mg kg−1, respectively (Fig. 1B, C). The variation ranges of soil TN were 3.50–16.60 g kg−1, 4.70–34.5 g kg−1, and 6.70–32.50 g kg−1, respectively (Fig. 1D). Similarly, the variation ranges of NH4+ were 5.96–12.03 g kg−1, 5.39–12.59 g kg−1, and 5.74–13.03 g kg−1, NO3− were 2.27–8.79 mg kg−1, 5.07–9.62 mg kg−1, and 5.09–9.52 mg kg−1, respectively (Fig. 1E, F). The changes of SOC and NH4+ with soil depth were significantly different in different extreme drought periods and decreased significantly with the increase of soil depth (Table 1, P  More

We investigated whether ricefield mosquito larval control and/or rice cultivation practices are associated with malaria vector densities through a systematic review and meta-analysis. Forty-seven experimental studies were eligible for inclusion in the qualitative analysis and thirty-three studies were eligible for the meta-analysis. It was demonstrated that the use of fish, chemical and biological larvicides in rice fields were effective in controlling larval malaria vector densities at all developmental stages. Intermittent irrigation, however, could only significantly reduce late-stage larvae. Based on a limited number of studies, meta-analyses on other forms of larval control such as monomolecular surface films (MSFs), neem, copepods and Azolla failed to demonstrate any consistent reduction in anopheline numbers. Similarly, rice cultivation practices such as plant variety and density, type of levelling and pesticide application were not generally associated with reduced malaria vectors. Nonetheless, in one study, minimal tillage was observed to reduce average numbers of larvae throughout a cropping season. In another study, herbicide application increased larval abundance over a 4-week period, as did one-time drainage in a third study.
Despite their different modes of action, the use of chemical and bacterial larvicides and MSFs were all relatively effective measures of larval control in rice fields, varying between a 57% to 76% reduction in vector abundance compared to no larviciding. Their effects were highest (often reaching 100% reduction) only shortly following application but did not persist for longer than two weeks. These larvicides mostly had short residual half-lives because they were applied to paddy water which was naturally not completely stagnant: there was a small but constant process of water loss (through drainage, evapotranspiration and percolation) and replacement through irrigation. Hence, even with a residual formulation, weekly re-application would be needed for sustained control47,40,41,50. This would be very labour- and cost-intensive to scale-up, to ensure that larvicides are evenly distributed across vast areas (even at plot/sub-plot level) throughout at least one 5-month long rice-growing season per year42,51. Aerial application (including unmanned aerial vehicles), although widely used in the US and Europe, is unlikely to be a feasible delivery system for smallholders in SSA, even in large irrigation schemes26,27,48,49. Furthermore, if synthetic organic chemicals were to be considered for riceland malaria vector control, their management in the current landscape of insecticide resistance across Africa must be considered.Biological control using fish was found to be, in general, slightly more effective than (chemical, bacterial and MSF) larviciding. The degree of effectiveness was dependent on the fish species and their feeding preferences: surface-feeding, larvivorous species provided better anopheline control than bottom-feeding selective feeders4,43. Selecting the most suitable fish for local rice fields is not straightforward; many criteria need to be considered4,52,53. Generally, fish were well-received by rice farmers, perceived to contribute to increased yield by reducing weeds and pests and providing fertiliser through excrement43,44. This was reportedly also observed in Guangxi, China, where a certain proportion of the field had to be deepened into a side-trench where the fish could take shelter when the fields were drained. Even with this reduction in rice production area, carp rearing still increased yields by 10% and farmer’s income per hectare by 70%53. Unfortunately, none of the eligible studies in this review had included yield or water use as an outcome. Future entomological studies need to measure these critical agronomic variables so that studies of vector control in rice can be understood by, and transferred to, agronomists. In SSA, irrigated rice-fish farming can be scaled up provided that an inventory of fish species suitable for specific locations is available and that water is consistently available in fields (an important limiting factor in African irrigation schemes)54. Lessons can be learnt from successful large-scale rice-fish systems in Asia, where they have served as win–win solutions for sustainable food production and malaria control16,55.Overall, there was only limited evidence that intermittent irrigation is effective at reducing late-instar anopheline larvae in rice fields. This finding contrasts with prior reviews, which found mixed results (regardless of larval stage) but emphasised that success was site-specific4,17,56. This contrast is presumably due to the inclusion criteria of our systematic review. These reviews excluded studies in various geographical settings and some older studies that reported successful anopheline control with intermittent irrigation but lacked either a contemporaneous control arm, adequate replication or adequate differentiation between culicines and anophelines16,57,50,51,52,61. It seems, from our review, that intermittent irrigation does not prevent the recruitment of early instars (and in one case, may have encouraged oviposition31) but tends to prevent their development into late-stage immatures. This important conclusion is, however, based only on four studies; more evidence is urgently needed where future trials should consider the basic principles of modern trials with adequate replication, controls and differentiation between larval instars and species.Generally, it is observed that drainage, passive or active, did not reliably reduce overall numbers of mosquito immatures. In India and Kenya, closer inspection revealed that soils were not drying sufficiently, so any stranded larvae were not killed31,46. Highlighted by van der Hoek et al.29 and Keiser et al.17, water management in rice fields is very dependent on the physical characteristics of the soil and the climate and is most suited to places that not only favour rapid drying, but also have a good control of water supply17,56. Moreover, repeated drainage, although directed against mosquitoes, can also kill their aquatic predators62. Since mosquitoes can re-establish themselves in a newly flooded rice field more quickly than their predators, intermittent irrigation with more than a week between successive drying periods can permit repeated cycles of mosquito breeding without any predation pressure. Its efficacy against malaria vectors is therefore highly reliant on the timing of the wetting and drying periods. Further site-specific research on timing, especially with regards to predator–prey interactions within the rice agroecosystem, is required to find the perfect balance.Another limitation in intermittent irrigation is that it cannot be applied during the first two to three weeks following transplanting, because rice plants must remain flooded to recover from transplanting shock. Unfortunately, this time coincides with peak vector breeding. Thus, other methods of larval control would be required to fill this gap. To agronomists, intermittent irrigation provides benefits to farmers, as it does not penalise yield but significantly reduces water consumption. Nonetheless, farmer compliance seems to be variable, especially in areas where water availability is inconsistent and intermittent irrigation would potentially require more labour31,32,39. Importantly, rice farmers doubted their ability to coordinate water distribution evenly amongst themselves, suggesting that there may be sharing issues, as in the “tragedy of the commons”63. Instead, they said that they preferred to have an agreed authority to regulate water46.No general conclusions could be made on the effect on malaria vectors of other rice cultivation practices (apart from water management) because only one study was eligible for each practice. Nevertheless, these experiments on pesticide application, tillage and weed control, as well as another study on plant spacing (not eligible since glass rods were used to simulate rice plants), do illustrate that small changes in agronomic inputs and conditions can have considerable effects on mosquito densities, not just rice yield36,38,64. Moreover, in partially- or shallowly-flooded plots, the larvae are often concentrated in depressions (usually footprints), suggesting that rice operations which leave or remove footprints (e.g. hand-weeding, drum seeders, levelling) will influence vector breeding4.Our study has some important limitations. First, in most trials, the units of intervention were replicate plots of rice, and success was measured as a reduction in larval densities within treated plots. This design focuses on the identification of effective and easy-to-implement ways of growing rice without growing mosquitoes, on the assumption that higher vector densities are harmful. However, from a public health perspective, the need for epidemiological outcomes is often, and reasonably, stressed22,65. Nonetheless, from a farmers’ perspective, it is also important to consider whether the vectors emerging from their rice fields significantly contribute to the local burden of malaria and to determine how this contribution can be minimised. There is evidence that riceland vectors do increase malaria transmission, since human biting rates are much higher in communities living next to rice schemes than their non-rice counterparts66 and that additional riceland vectors may intensify transmission and malaria prevalence in rice communities15. Hence, when investigating how rice-attributed malaria risk can be minimised, mosquito abundance as measured in the experimental rice trials is a useful indicator of potential impact on epidemiological outcomes.Second, larval density was not always separated into larval developmental stages. This can be misleading because some interventions work by reducing larval survival (but not by preventing oviposition) and development to late instars and pupae. Therefore, an intervention could completely eliminate late-stage larvae and pupae but have little effect on the total number of immatures. This was illustrated in our meta-analyses of intermittent irrigation in Table 3 and Supplementary Table 5, and could have been the case for some studies that failed to demonstrate consistent reductions in overall anopheline numbers but did not differentiate between larval instars34,45,67,60,69. We infer that when monitoring mosquito immatures in rice trials, it is important to distinguish between larval instars and pupae. Pupae should always be counted separately since its abundance is the most direct indicator of adult productivity70.Third, experimental trials rarely reported the timing of intervention application or accounted for different rice-growing phases, or “days after transplantation”, in the outcome. Both aspects are important to consider since an intervention may be suited to control larvae during certain growth phases but not others. This is illustrated by Djegbe et al.38, where, compared to deep tillage, minimal tillage could significantly reduce larvae during the early stages of rice cultivation but not during tillering and maturation38. In contrast, other interventions, such as Azolla and predatory copepods, took time to grow and accumulate, and were more effective during the later stages of a rice season45,67,71. This differentiation is important because it can identify components that could potentially form a complementary set of interventions against riceland malaria vectors, each component being effective at different parts of the season. Since rice fields, and hence the dynamics of riceland mosquito populations, vary from place to place, this set of interventions must also be robust. Special attention must be paid to the early stages of rice cultivation, particularly the first few weeks after transplanting (or sowing), since, with many vector species, a large proportion of adult mosquitoes are produced during this time.Fourth, the analysis of entomological counts is often inadequate. Many studies failed to provide the standard deviation (or any other measure of error) for larval counts and could not be included in the quantitative analysis. Often, due to the extreme (and not unexpected) variability of larval numbers, sample sizes were insufficient to calculate statistically significant differences between treatments. Fifth, a high risk of bias was found across both CTS and CITS studies, including high heterogeneity and some publication bias. Study quality was, in general, a shortcoming and limited the number of eligible studies for certain interventions, including intermittent irrigation. Moreover, there are conspicuous a priori reasons for bias in such experimental trials: trial locations are frequently chosen to maximise the probability of success.Finally, few studies were conducted in African countries, where the relationship between rice and malaria is most important because of the efficiency, and the “rice-philic” nature, of the vector An. gambiae s.l.15. In particular, there was a lack of studies on the effectiveness and scalability of biological control and rice cultivation practices. There is also very little information (particularly social science studies) on the views and perspectives of African rice farmers on mosquitoes in rice and interventions to control them72,73.In the future, as malaria declines (particularly across SSA), the contribution of rice production to increased malaria transmission is likely to become more conspicuous15. Unless this problem is addressed, rice growing will probably become an obstacle to malaria elimination. Current default methods of rice production provide near-perfect conditions for the larvae of African malaria vectors. Therefore, we need to develop modified rice-growing methods that are unfavourable to mosquitoes but still favourable for the rice. Although larviciding and biological control may be appropriate, their unsustainable costs remain the biggest barrier to uptake amongst smallholder farmers. Future investigations into riceland vector control should pay more attention to interventions that may be useful to farmers.Supported by medical entomologists, agronomists should lead the research task of identifying cultivation methods that achieve high rice productivity whilst suppressing vector productivity. Rice fields are a major global source of greenhouse gases, and agronomists have responded by successfully developing novel cultivation methods that minimise these emissions while maintaining yield. We need the same kind of response from agronomists, to achieve malaria control co-benefits within rice cultivation. At present, only a few aspects of rice cultivation have been investigated for their effects on mosquitoes, and the potential of many other practices for reducing anopheline numbers are awaiting study. Due to the spatial and temporal heterogeneity of rice agroecosystems, it is likely that no single control method can reduce mosquito numbers throughout an entire cropping season and in all soil types and irrigation methods. Thus, effective overall control is likely to come from a combination of local, site-specific set of complementary methods, each of which is active and effective during a different phase of the rice-growing season. More

Meat, Milk and More: Policy Innovations to Shepherd Inclusive and Sustainable Livestock Systems in Africa (Malabo Montpellier Panel, 2020).Value of Agricultural Production (FAO, accessed August 25, 2022); https://www.fao.org/faostat/en/#data/QVJayne, T. & Sanchez, P. A. Agricultural productivity must improve in sub-Saharan Africa. Science 372, 1045–1047 (2021).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Dangal, S. R. S. et al. Methane emission from global livestock sector during 1890–2014: magnitude, trends and spatiotemporal patterns. Glob. Change Biol. 23, 4147–4161 (2017).Article 
ADS 

Google Scholar 
Mottet, A. et al. Climate change mitigation and productivity gains in livestock supply chains: insights from regional case studies. Reg. Env. Change 17, 129–141 (2016).Article 

Google Scholar 
Valin, H. et al. Agricultural productivity and greenhouse gas emissions: trade-offs or synergies between mitigation and food security? Environ. Res. Lett. 8, 035019 (2013).Article 
ADS 
CAS 

Google Scholar 
González-Quintero, R. et al. Yield gap analysis to identify attainable milk and meat productivities and the potential for greenhouse gas emissions mitigation in cattle systems of Colombia. Agric. Syst. 195, 103303 (2022).Article 

Google Scholar 
Crops and Livestock Products (FAO, accessed August 17,2022); https://www.fao.org/faostat/en/#data/QCLLedo, J. et al. Persistent challenges in safety and hygiene control practices in emerging dairy chains: the case of Tanzania. Food Control 105, 164–173 (2019).Article 

Google Scholar 
Häsler, B. et al. Integrated food safety and nutrition assessments in the dairy cattle value chain in Tanzania. Glob. Food Sec. 18, 102–113 (2018).Article 

Google Scholar 
Supply Utilization Accounts (FAO, accessed August 26, 2022); https://www.fao.org/faostat/en/#data/SCLMichael, S. et al. Tanzania Livestock Master Plan (International Livestock Research Institute, 2018).Tanzania Livestock Sector Analysis (2016/2017–2030/2031) (United Republic of Tanzania Ministry of Livestock and Fisheries, 2017); https://www.mifugouvuvi.go.tz/uploads/projects/1553602287-LIVESTOCK%20SECTOR%20ANALYSIS.pdfNicholson, C. et al. Assessment of Investment Priorities for Tanzania’s Dairy Sector: Report on Activities and Accomplishments (International Livestock Research Institute, 2021).Chagunda, M. G. C., Romer, D. A. M. & Roberts, D. J. Effect of genotype and feeding regime on enteric methane, non-milk nitrogen and performance of dairy cows during the winter feeding period. Livest. Sci. 122, 323–332 (2009).Article 

Google Scholar 
Notenbaert, A. et al. Towards environmentally sound intensification pathways for dairy development in the Tanga region of Tanzania. Reg. Environ. Change 20, 138 (2020).Yesuf, G. A. et al. Embedding stakeholders’ priorities into the low-emission development of the East African dairy sector. Env. Res. Lett. 16, 064032 (2021).Article 
CAS 

Google Scholar 
GLS (Greening Livestock Survey) (International Livestock Research Institute, 2019); https://data.ilri.org/portal/dataset/greeninglivestockIntended Nationally Determined Contributions (United Republic of Tanzania, 2021); https://unfccc.int/sites/default/files/NDC/2022-06/TANZANIA_NDC_SUBMISSION_30%20JULY%202021.pdfNdung’u, P. W. et al. Farm-level emission intensities of smallholder cattle (Bos indicus; B. indicus–B. taurus crosses) production systems in highlands and semi-arid regions. Animal 16, 100445 (2022).Article 
PubMed 

Google Scholar 
Goopy, J. P. et al. Severe below-maintenance feed intake increases methane yield from enteric fermentation in cattle. Br. J. Nutr. 123, 1239–1246 (2020).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Goopy, J. P. et al. A new approach for improving emission factors for enteric methane emissions of cattle in smallholder systems of East Africa—results for Nyando, Western Kenya. Agric. Syst. 161, 72–80 (2018).Article 

Google Scholar 
Supporting Low Emissions Development in the Tanzanian Dairy Cattle Sector—Reducing Enteric Methane for Food Security and Livelihoods (FAO, 2019).Gerssen-Gondelach, S. J. et al. Intensification pathways for beef and dairy cattle production systems: impacts on GHG emissions, land occupation and land use change. Agric. Ecosyst. Environ. 240, 135–147 (2017).Article 

Google Scholar 
Havlik, P. et al. Climate change mitigation through livestock system transitions. Proc. Natl Acad. Sci. USA 111, 3709–3714 (2014).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Herrero, M. et al. Greenhouse gas mitigation potentials in the livestock sector. Nat. Clim. Change 6, 452–461 (2016).Article 
ADS 

Google Scholar 
Dizyee, K., Baker, D. & Omore, A. Upgrading the smallholder dairy value chain: a system dynamics ex-ante impact assessment in Tanzania’s Kilosa district. J. Dairy Res. 86, 440–449 (2019).Article 
CAS 
PubMed 

Google Scholar 
Simões, A. R. P., Nicholson, C. F., Novakovicc, A. M. & Protil, R. M. Dynamic impacts of farm-level technology adoption on the Brazilian dairy supply chain. Int. Food Agribus. Manag. Rev. 23, 71–84 (2020).Article 

Google Scholar 
Rahimi, J. et al. Heat stress will detrimentally impact future livestock production in East Africa. Nat. Food. 2, 88–96 (2021).Article 

Google Scholar 
Mbululo, Y. & Nyihirani, F. Climate characteristics over southern highlands Tanzania. Atmos. Clim. Sci. 2, 454–463 (2012).
Google Scholar 
Kihoro, E. M., Schoneveld, G. C. & Crane, T. A. Pathways toward inclusive low-emission dairy development in Tanzania: producer heterogeneity and implications for intervention design. Agric. Syst. 190, 103073 (2021).Mruttu, H. et al. Animal Genetics Strategy and Vision for Tanzania (Tanzania Ministry of Agriculture, Livestock and Fisheries and ILRI, 2016).Agricultural Sample Survey 2018/19 Report on Livestock and Livestock Characteristics (Private Peasant Holdings) (Central Statistical Agency, 2019).2019/20 National Sample Census of Agriculture Main Report (Tanzania National Bureau of Statistics, 2022).Robinson, T. P. et al. Global Livestock Production Systems (FAO, 2011).Herrero, M. et al. Biomass use, production, feed efficiencies and greenhouse gas emissions from global livestock systems. Proc. Natl Acad. Sci. USA 110, 20888–20893 (2013).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Baseline Study of the Tanzania Dairy Value Chain (United Republic of Tanzania Ministry of Agriculture, Livestock and Fisheries, 2016).Mbwambo, N., Nandonde, S., Ndomba, C. & Desta, S. Assessment of Animal Feed Resources in Tanzania (Tanzania Ministry of Agriculture, Livestock and Fisheries and ILRI, 2016).Hartung, C., Lerer, A., Anokwa, Y., Tseng, C., Brunette, W., & Borriello, G. Open data kit: tools to build information services for developing regions. Proc. 4th ACM/IEEE International Conference on Information and Communication Technologies and Development (Association for Computing Machinery, 2010).R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2022).https://www.r-project.orgRufino, M. C. et al. Lifetime productivity of dairy cows in smallholder farming systems of the central highlands of Kenya. Animal 3, 1044–1056 (2009).Article 
CAS 
PubMed 

Google Scholar 
Hawkins, J. et al. Feeding efficiency gains can increase the greenhouse gas mitigation potential of the Tanzanian dairy sector. Sci. Rep. 11, 4190 (2021).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Python Software Foundation (Python Software Foundation, 2019); https://www.python.org/psf/Kashoma, I. P. B. et al. Predicting body weight of Tanzania shorthorn zebu cattle using heart girth measurements. Livest. Res. Rural. Dev. 23, Table 1 (2011).Galukande, E. B., Mahadevan, P. & Black, J. G. Milk production in East African zebu cattle. Anim. Sci. 4, 329–336 (1962).Article 

Google Scholar 
Gillah, K. A., Kifaro, G. C. & Madsen, J. Effects of pre partum supplementation on milk yield, reproduction and milk quality of crossbred dairy cows raised in a peri urban farm of Morogoro town Tanzania. Livest. Res. Rural. Dev. 26 (2014).Njau, F. B. C., Lwelamira, J. & Hyandye, C. Ruminant livestock production and quality of pastures in the communal grazing land of semi-arid central Tanzania. Livest. Res. Rural. Dev. 8, Table 4 (2013).Mwambene, P. L. et al. Selecting indigenous cattle populations for improving dairy production in the Southern Highlands and Eastern Tanzania. Livest. Res. Rural. Dev. 26 (2014).Rege, J. E. O. et al. Cattle of Kenya: Uses, Performance, Farmer Preferences, Measures of Genetic Diversity and Options for Improved Use (International Livestock Research Institute, 2001).Beffa, L. M. Genotype × Environment Interaction in Afrikaner Cattle. PhD thesis, Univ. of the Free State (2005).Meaker, H. J., Coetsee, T. P. N. & Lishman, A. W. The effects of age at 1st calving on the productive and reproductive-performance of beef-cows. S. Afr. J. Anim. Sci. 10, 105–113 (1980).
Google Scholar 
Chenyambuga, S. W. & Mseleko, K. F. Reproductive and lactation performances of Ayrshire and Boran crossbred cattle kept in smallholder farms in Mufindi district, Tanzania. Livest. Res. Rural. Dev. 21, 100 (2009).
Google Scholar 
Ojango, J. M. K. et al. Dairy production systems and the adoption of genetic and breeding technologies in Tanzania, Kenya, India and Nicaragua. Anim. Genet. Resour. 59, 81–95 (2016).Article 

Google Scholar 
Feedipedia—Animal Feed Resources Information System (FAO, accessed 2021); https://www.feedipedia.org/Lukuyu, B. et al. (eds) Feeding Dairy Cattle in East Africa (East Africa Dairy Development Project, 2012).Rubanza, C. D. K. et al. Biomass production and nutritive potential of conserved forages in silvopastoral traditional fodder banks (Ngitiri) of Meatu District of Tanzania. Asian-Aust. J. Anim. Sci. 19, 978–983 (2006).Article 

Google Scholar 
Food Balances (2010-) (FAO, accessed September 29, 2021); http://www.fao.org/faostat/en/#data/FBSCrop Data for the United Republic of Tanzania (FAO, accessed September 22, 2021); http://www.fao.org/faost at/en/#data/QCGilbert, M. et al. Global distribution data for cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in 2010. Sci. Data. 5, 180227 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
2014/15 Annual Agricultural Sample Survey Report (The United Republic of Tanzania, 2016).Basic Data for Livestock and Fisheries (The United Republic of Tanzania Ministry of Livestock and Fisheries, 2013).IPCC Guidelines for National Greenhouse Gas Inventories Vol. 4 Agriculture, Forestry and Other Land Use (IPCC, 2006).2019 Refinement to the IPCC Climate Change 2014: Synthesis Report (eds Core Writing Team, Pachauri, R. K. & Meyer L. A.) (IPCC, 2019).Fertilizers by Nutrient (FAO, accessed July 6, 2022); https://www.fao.org/faostat/en/#data/RFNHutton, M. O. et al. Toward a nitrogen footprint calculator for Tanzania. Env. Res. Lett. 12, 034016 (2017).Article 

Google Scholar 
Tanzania Fertilizer Assessment (International Fertilizer Development Center, 2012); http://tanzania.countrystat.org/fileadmin/user_upload/countrystat_fenix/congo/docs/Tanzania%20Fertilizer%20Assessment%202012.pdfA Common Carbon Footprint Approach for the Dairy Sector: The IDF Guide to Standard Life Cycle Methodology (International Dairy Federation, 2015); https://www.fil-idf.org/wp-content/uploads/2016/09/Bulletin479-2015_A-common-carbon-footprint-approach-for-the-dairy-sector.CAT.pdfBruzzone, L., Bovolo, F. & Arino, O. European Space Agency land cover climate change initiative. ESA LC CCI data: high resolution land cover data via Centre for Environmental Data Analysis; https://climate.esa.int/en/projects/high-resolution-land-cover/ (2021)Characteristics of Markets for Animal Feeds Raw Materials in the East African Community: Focus on Maize Bran and Sunflower Seed Cake (Kilimo Trust, 2017).Ngunga, D. & Mwendia, S. Forage Seed System in Tanzania: A Review Report (Alliance of Biodiversity and CIAT, 2020).Nkombe, B.M. Investigation of the Potential for Forage Species to Enhance the Sustainability of Degraded Rangeland and Cropland Soils. MSc thesis, Ohio State Univ. (2016).Producer Prices (FAO, accessed 2021); http://www.fao.org/faostat/en/#data/PP More