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    Salmon lice in the Pacific Ocean show evidence of evolved resistance to parasiticide treatment

    BioassaysSalmon-louse bioassays were performed by the BC Centre for Aquatic Health Sciences (CAHS) as described in Saksida et al.10. Briefly, motile (i.e., pre-adult and adult) L. salmonis were collected from 11 salmon farms in the Broughton Archipelago (BA) between 2010 and 2021 and transported to CAHS in Campbell River, BC. Within 18 h of collection, healthy lice were separated by sex and randomly placed into petri dishes each containing approximately 10 lice (mean ± SD = 9.6 ± 1.1) and subjected to one of six EMB concentrations (either 0, 31.3, 62.5, 125, 250, and 500 ppb or 0, 62.5, 125, 250, 500, and 1000 ppb, depending on suspected variation in EMB sensitivity11). Each collection corresponded to one bioassay, and each bioassay contained roughly four replicates for each sex (4.0 ± 1.3 for females and 3.6 ± 0.9 for males). After 24 h of EMB exposure, lice were classified as alive if they could swim and attach to the petri dish, or moribund/dead otherwise. Lice were kept at 10 °C throughout the process. In total, 34 bioassays were conducted from 11 farms between October 2010 and November 2021.We analysed the proportion of lice that survived exposure to EMB, using standard statistical descriptions that accounted for within-assay dependencies (generalized linear mixed models (GLMMs) with logit link functions, fitted separately to the data from each bioassay). The models included fixed effects for EMB concentration, sex, and the interaction between the two, as well as a random intercept for petri dish. For each analysis, we centered concentration values and scaled them by one standard deviation. We used the GLMM fits to calculate the effective concentrations at which 50% of the lice survived (EC50) in each bioassay. The GLMM for one bioassay produced a singular fit because there was not enough variation in the female survival data to warrant the random-effects structure. We retained the EC50 values resulting from this singular fit because re-fitting without the random intercept yielded identical EC50 values, and removing the entire bioassay from the overall dataset did not qualitatively affect the subsequent analysis.To assess whether the sensitivity of salmon lice to EMB has decreased over time, we fitted a set of five standard GLMs with gamma error distributions and log link functions to the maximum-likelihood EC50 estimates. Each of these five models included binary effects for sex and for whether the farm’s stock had previously been treated, since both affect EMB sensitivity in lice10. The first model included only these two effects and served as a null model that assumed lice did not evolve EMB resistance over time. The second model added a fixed effect for time (i.e., the number of days since January 1, 2010), while the third model included an interaction between time and sex. The fourth and fifth models were identical to the second and third, but with a quadratic effect for time, to account for possible first-order nonlinearity. We were unable to add an effect for farm due to small sample sizes. We performed model selection using the Akaike Information Criterion penalized for small sample sizes AICc25, treating AICc differences of less than two as being indistinguishable in terms of statistical support and selecting the least complex model when that was the case26. The ΔAICc values for the EC50 models were 48.1, 6.1, 4.9, 0, 1.75, respectively.Field efficacyWe used relative salmon-louse counts after EMB treatment (i.e., the post-treatment count divided by the pre-treatment count) as our measure of EMB field resistance between 2010 and 2021 (higher relative counts imply lower treatment efficacy). We defined “pre-treatment” as one month prior to treatment and “post-treatment” as three months after treatment (roughly when one would expect to find the lowest counts in louse populations previously unexposed to EMB), as in Saksida et al.10. We excluded EMB treatments for which an additional, non-EMB treatment was performed within the following three months. In total, there were 73 EMB treatments for which we were able to calculate relative post-treatment counts.Salmon-louse counts were performed by farm staff as described by Godwin et al.27. In short, salmon-louse counts were usually performed at least one per month by capturing 20 stocked fish in each of three net pens using a box seine net, then placing the fish in an anesthetic bath of tricaine methanesulfonate (TMS, or MS-222) and assessing the fish for motile (i.e., pre-adult and adult) L. salmonis by eye.The treatment dataset included the date and type of every treatment that has been performed on a BA farm (i.e., not just the 11 farms with bioassay data). In total, 88 EMB treatments were conducted between 2010 and 2021, of which we were able to calculate relative post-treatment counts for 73 because some months lacked counts or had a non-EMB treatment performed within the following three months. An additional 22 non-EMB treatments (e.g., freshwater and hydrogen baths) were performed, all since the beginning of 2019, but we excluded these data from our analysis.To determine whether field efficacy of EMB treatments has decreased over time, we used GLM-based “hurdle models”—standard statistical descriptions used to accommodate an over-abundance of zeroes in data being analysed. A hurdle model uses two components—one model for whether a count is nonzero and another for the value of the nonzero count—to predict overall mean count. To this end, we fitted three binomial GLMs paired with three gamma GLMs to the relative-count data, each of the paired models being structurally identical in terms of predictors. All of these submodels included a binary fixed effect for previous treatment, as in the EC50 models. The null pair of submodels included no additional terms, the second pair of submodels included a fixed effect for time (i.e., the number of days since January 1, 2010), and the third pair of submodels included a quadratic effect of time (again, to account for possible first-order deviations nonlinearity). We were unable to add an effect for farm due to small sample sizes. We performed model selection of the hurdle models, again using the Akaike Information Criterion penalized for small sample sizes. The ΔAICc values for the three hurdle models were 39.6, 18.3, and 0, respectively. We performed our analyses in R 3.6.028, using the lme4 package29. More

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    Mapping the purple menace: spatiotemporal distribution of purple loosestrife (Lythrum salicaria) along roadsides in northern New York State

    Lázaro-Lobo, A. & Ervin, G. N. A global examination on the differential impacts of roadsides on native versus exotic and weedy plant species. Glob. Ecol. Conserv. 17(e00555), 1–13 (2019).
    Google Scholar 
    Christen, D. C. & Matlack, G. R. The habitat and conduit functions of roads in the spread of three invasive plant species. Biol. Invasions 11(2), 453–465 (2009).Article 

    Google Scholar 
    Mortensen, D. A., Rauschert, E. S., Nord, A. N. & Jones, B. P. Forest roads facilitate the spread of invasive plants. Invasive Plant Sci. Manag. 2(3), 191–199 (2009).Article 

    Google Scholar 
    Lemke, A., Kowarik, I. & von der Lippe, M. How traffic facilitates population expansion of invasive species along roads: The case of common ragweed in Germany. J. Appl. Ecol. 56(2), 413–422 (2019).Article 

    Google Scholar 
    Rauschert, E. S., Mortensen, D. A. & Bloser, S. M. Human-mediated dispersal via rural road maintenance can move invasive propagules. Biol. Invasions 19(7), 2047–2058 (2017).Article 

    Google Scholar 
    Meunier, G. & Lavoie, C. Roads as corridors for invasive plant species: New evidence from smooth bedstraw (Galium mollugo). Invasive Plant Sci. Manag. 5(1), 92–100 (2012).Article 

    Google Scholar 
    Mohit, S., Johnson, T. B. & Arnott, S. E. Recreational watercraft decontamination: Can current recommendations reduce aquatic invasive species spread?. Manag. Biol. Invasions 12(1), 148–164 (2021).Article 

    Google Scholar 
    Ferguson, L., Duncan, C. L., & Snodgrass, K. Backcountry road maintenance and weed management. United States: U.S. Department of Agriculture, Forest Service, Technology & Development Program. 22pp (2003). At https://www.google.com/books/edition/Backcountry_Road_Maintenance_and_Weed_Ma/y2amRwT1rIsC?hl=en&gbpv=0.Lelong, B., Lavoie, C., Jodoin, C. & Belzile, F. Expansion pathways of the exotic common reed (Phragmites australis): A historical and genetic analysis. Divers. Distrib. 13, 430–437 (2007).Article 

    Google Scholar 
    Joly, M. et al. Paving the way for invasive species: Road type and the spread of common ragweed (Ambrosia artemisiifolia). Environ. Manag. 48(3), 514–522 (2011).ADS 
    Article 

    Google Scholar 
    Thompson, D. Q., Stuckey, R. L. & Thompson, E. B. Spread, impact, and control of purple loosestrife (Lythrum salicaria) in North American wetlands. U. S. Fish and Wildlife Service (1987). At http://stoppinginvasives.com/dotAsset/670d2f92-cd0c-41ab-9955-7204f1a9a192.pdf.Stuckey, R. L. Distributional history of Lythrum salicaria (purple loosestrife) in North America. Bartonia 47, 3–20 (1980).
    Google Scholar 
    Blossey, B., Skinner, L. C. & Taylor, J. Impact and management of purple loosestrife (Lythrum salicaria) in North America. Biodivers. Conserv. 10(10), 1787–1807 (2001).Article 

    Google Scholar 
    Wilcox, D. A. Migration and control of purple loosestrife (Lythrum salicaria L.) along highway corridors. Environ. Manag. 13(3), 365–370 (1989).ADS 
    Article 

    Google Scholar 
    St. Louis, E., Stastny, M. & Sargent, R. D. The impacts of biological control on the performance of Lythrum salicaria 20 years post-release. Biol. Control. 140, 104–123 (2020).Article 

    Google Scholar 
    NYSDOT Environmental Science Bureau. Environmental Handbook for Transportation Operations: A Summary of the Environmental Requirements and Best Practices for Maintaining the Constructing Highways and Transportation Systems. Prepared by NYSDOT Environmental Science Bureau, (2011) At https://www.dot.ny.gov/divisions/engineering/environmental-analysis/repository/oprhbook.pdf.Blossey, B., Schroeder, D., Hight, S. D. & Malecki, R. A. Host specificity and environmental impact of two leaf beetles (Galerucella calmariensis and G. pusilla) for biological control of purple loosestrife (Lythrum salicaria). Weed Sci. 42, 134–140 (1994).Article 

    Google Scholar 
    Blossey, B. Before, during and after: The need for long-term monitoring in invasive plant species management. Biol. Invasions 1, 301–311 (1999).Article 

    Google Scholar 
    Blossey, B. & Hunt, T. R. Mass rearing methods for Galerucella calmariensis and G. pusilla (Coleoptera: Chrysomelidae), biological control agents of Lythrum salicaria (Lythraceae). J. Econ. Entomol. 92(2), 325–334 (1999).CAS 
    Article 

    Google Scholar 
    Grevstad, F. S. Ten-year impacts of the biological control agents Galerucella pusilla and G. calmariensis (Coleoptera: Chrysomelidae) on purple loosestrife (Lythrum salicaria) in Central New York State. Biol. Control 39(1), 1–8 (2006).Article 

    Google Scholar 
    Boag, A. E. & Eckert, C. G. The effect of host abundance on the distribution and impact of biocontrol agents on purple loosestrife (Lythrum salicaria, Lythraceae). Écoscience 20(1), 90–99 (2013).Article 

    Google Scholar 
    Lakoba, V. T., Brooks, R. K., Haak, D. C. & Barney, J. N. An Analysis of US State regulated weed lists: A discordance between biology and policy. Bioscience 70(9), 804–813 (2020).Article 

    Google Scholar 
    Welling, C. H. & Becker, R. L. Seed bank dynamics of Lythrum salicaria L.: Implications for control of this species in North America. Aquat. Bot. 38, 303–309 (1990).Article 

    Google Scholar 
    Brown, B. J. & Wickstrom, C. E. Adventitious root production and survival of purple loosestrife (Lythrum salicaria) shoot sections. Ohio J. Sci. 97, 2–4 (1997).
    Google Scholar 
    Farnsworth, E. J. & Ellis, D. R. Is purple loosestrife (Lythrum salicaria) an invasive threat to freshwater wetlands? Conflicting evidence from several ecological metrics. Wetlands 21(2), 199–209 (2001).Article 

    Google Scholar 
    Mahaney, W. M., Smemo, K. A. & Yavitt, J. B. Impacts of Lythrum salicaria invasion on plant community and soil properties in two wetlands in central New York, USA. Botany 84(3), 477–484 (2006).
    Google Scholar 
    Treberg, M. A. & Husband, B. C. Relationship between the abundance of Lythrum salicaria (purple loosestrife) and plant species richness along the Bar River Canada. Wetlands 19(1), 118–125 (1999).Article 

    Google Scholar 
    Hager, H. & Vinebrooke, R. E. Positive relationships between invasive purple loosestrife (Lythrum salicaria) and plant species diversity and abundance in Minnesota wetlands. Can. J. Bot. 82(6), 763–773 (2004).Article 

    Google Scholar 
    Lavoie, C. Should we care about purple loosestrife? The history of an invasive plant in North America. Biol. Invasions 12(7), 1967–1999 (2010).Article 

    Google Scholar 
    Fickbohm, S. S. & Zhu, W. X. Exotic purple loosestrife invasion of native cattail freshwater wetlands: Effects on organic matter distribution and soil nitrogen cycling. Appl. Soil. Ecol. 32(1), 123–131 (2006).Article 

    Google Scholar 
    Ramula, S. Annual mowing has the potential to reduce the invasion of herbaceous Lupinus polyphyllus. Biol. Invasions 22(10), 3163–3173 (2020).Article 

    Google Scholar 
    Milakovic, I., Fiedler, K. & Karrer, G. Management of roadside populations of invasive Ambrosia artemisiifolia by mowing. Weed Res. 54(3), 256–264 (2014).Article 

    Google Scholar 
    Vitalos, M. & Karrer, G. Dispersal of Ambrosia artemisiifolia seeds along roads: The contribution of traffic and mowing machines. Neobiota 8, 53–60 (2009).
    Google Scholar 
    Forman, R. T. & Alexander, L. E. Roads and their major ecological effects. Annu. Rev. Ecol. Syst. 29(1), 207–231 (1998).Article 

    Google Scholar 
    Milt, A. W. et al. Minimizing opportunity costs to aquatic connectivity restoration while controlling an invasive species. Conserv. Biol. 32(4), 894–904 (2018).Article 

    Google Scholar 
    RStudio Team. RStudio: Integrated Development Environment for R. RStudio, PBC. (2021). URL http://www.rstudio.com/.R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing. (2021). https://www.R-project.org/.U. S. Fish and Wildlife Service. National Wetlands Inventory. http://www.fws.gov/wetlands/ (2020).Yakimowski, S. B., Hager, H. A. & Eckert, C. G. Limits and effects of invasion by the nonindigenous wetland plant Lythrum salicaria (purple loosestrife): A seed bank analysis. Biol. Invasions 7, 687–698 (2005).Article 

    Google Scholar 
    Thomas, S. M. & Moloney, K. A. Combining the effects of surrounding land-use and propagule pressure to predict the distribution of an invasive plant. Biol. Invasions 17, 477–495 (2015).Article 

    Google Scholar 
    Barbier, E. B., Knowler, D., Gwatipedza, J., Reichard, S. H. & Hodges, A. R. Implementing policies to control invasive plant species. Bioscience 63(2), 132–138 (2013).Article 

    Google Scholar 
    Blossey, B. Measuring and Evaluating Ecological Outcomes of Biological Control Introductions. In Integrating Biological Control into Conservation Practice (eds Van Driesche, R. et al.) 161–188 (Wiley, 2016).Chapter 

    Google Scholar 
    Rowell, N. Warren County Purple Loosestrife Management Program Final Report. (2015). At https://www.warrenswcd.org/reports.html.Vanneste, T. et al. Plant diversity in hedgerows and road verges across Europe. J. Appl. Ecol. 57(7), 1244–1257 (2020).Article 

    Google Scholar 
    Auffret, A. G. & Lindgren, E. Roadside diversity in relation to age and surrounding source habitat: Evidence for long time lags in valuable green infrastructure. Ecol. Solut. Evid. 1(1), e12005 (2020).Article 

    Google Scholar 
    Mccleery, R. A., Holdorf, A. R., Hubbard, L. L. & Peer, B. D. Maximizing the wildlife conservation value of road right-of-ways in an agriculturally dominated lands. Plos one 10(3), e0120375 (2015).Article 

    Google Scholar 
    New York Invasive Species Information (NYISI). Purple Loosestrife. (2019). at http://nyis.info/invasive_species/purple-loosestrife.Rogers, J. Controlling purple loosestrife (Lythrum Salicaria) along roadsides in St. Lawrence County: Monitoring and biological controls. Adirondack J. Environ. Stud. 23(1), 5 (2019).
    Google Scholar 
    New York State Department of Transportation. Clear Zones. (2021). At https://www.dot.ny.gov/divisions/engineering/environmental-analysis/landscape/trees/rs-lsf-plant-photos.ESRI. ArcGIS Pro: Version 2.9: Environmental System Research Institute. (2021). At https://pro.arcgis.com/en/pro-app/latest/get-started/get-started.htm.IBM Corp. IBM SPSS Statistics for Windows, Version 25.0. Armonk, NY: IBM Corp. Released 2017. More

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    Spatial ecology, activity patterns, and habitat use by giant pythons (Simalia amethistina) in tropical Australia

    Seigel, R. A. & Ford, N. B. Reproductive ecology in Snakes: Ecology and Evolutionary Biology (eds. Seigel, R. A., Collins, J. T. &. Novak, S. S.). 210–252. (MacMillan Publishing, 1987).Kremen, C., Merenlender, A. M. & Murphy, D. D. Ecological monitoring: A vital need for integrated conservation and development programs in the tropics. Conserv. Biol. 8, 388–397 (1994).
    Google Scholar 
    Shine, R. & Bonnet, X. Snakes: A new ‘model organism’ in ecological research?. Trends Ecol. Evol. 15, 221–222 (2000).CAS 
    PubMed 

    Google Scholar 
    Vilela, B., Villalobos, F., Rodríguez, M. Á. & Terribile, L. C. Body size, extinction risk and knowledge bias in New World snakes. PLoS ONE 9, e113429 (2014).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Mathies, T. Reproductive cycles of tropical snakes. in Reproductive Biology and Phylogeny of Snakes (eds. Sever, D. & Aldridge, R.). 523–562. (CRC Press, 2016).Shine, R., Harlow, P. S. & Keogh, J. S. The allometry of life-history traits: Insights from a study of giant snakes (Python reticulatus). J. Zool. 244, 405–414 (1998).
    Google Scholar 
    Natusch, D. J., Lyons, J. A., Riyanto, A., Khadiejah, S. & Shine, R. Detailed biological data are informative, but robust trends are needed for informing sustainability of wildlife harvesting: A case study of reptile offtake in Southeast Asia. Biol. Conserv. 233, 83–92 (2019).
    Google Scholar 
    Freeman, A. & Freeman, A. Habitat use in a large rainforest python (Morelia kinghorni) in the wet tropics of north Queensland, Australia. Herpetol. Conserv. Biol. 4, 252–260 (2009).
    Google Scholar 
    Smith, S. N., Jones, M. D., Marshall, B. M. & Strine, C. T. Native Burmese pythons exhibit site fidelity and preference for aquatic habitats in an agricultural mosaic. Sci. Rep. 11, 7014 (2021).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kramer, D. L. & Chapman, M. R. Implications of fish home range size and relocation for marine reserve function. Environ. Biol. Fishes 55, 65–79 (1999).
    Google Scholar 
    Spong, G. Space use in lions, Panthera leo, in the Selous Game Reserve: Social and ecological factors. Behav. Ecol. Sociobiol. 52, 303–307 (2002).
    Google Scholar 
    Webb, J. K. & Shine, R. A field study of spatial ecology and movements of a threatened snake species, Hoplocephalus bungaroides. Biol. Conserv. 82, 203–217 (1997).
    Google Scholar 
    Fearn, S. & Sambono, J. A reliable size record for the scrub python Morelia amethistina (Serpentes: Pythonidae) in north east Queensland. Herpetofauna 30, 2–6 (2000).
    Google Scholar 
    Grow, D., Wheeler, S. & Clark, B. Reproduction of the Amethystine python Python amethystinus kinghorni at the Oklahoma City Zoo. Int. Zoo Year. 27, 241–244 (1988).
    Google Scholar 
    Feldman, A. & Meiri, S. Length–mass allometry in snakes. Biol. J. Linn. Soc. 108, 161–172 (2013).
    Google Scholar 
    Harvey, M. B., Barker, D. G., Ammerman, L. K. & Chippindale, P. T. Systematics of pythons of the Morelia amethistina complex (Serpentes: Boidae) with the description of three new species. Herpetol. Monogr. 14, 139–185 (2000).
    Google Scholar 
    Fearn, S., Schwarzkopf, L. & Shine, R. Giant snakes in tropical forests: A field study of the Australian scrub python, Morelia kinghorni. Wildl. Res. 32, 193–201 (2005).
    Google Scholar 
    Natusch, D. J. D., Lyons, J. A. & Shine, R. Rainforest pythons flexibly adjust foraging ecology to exploit seasonal concentrations of prey. J. Zool. 313, 114–123 (2021).
    Google Scholar 
    Martin, R. W. Field observation of predation on Bennett’s tree-kangaroo (Dendrolagus bennettianus) by an amethystine python (Morelia amethistina). Herpetol. Rev. 26, 74–75 (1995).
    Google Scholar 
    Natusch, D., Lyons, J., Mears, L. A. & Shine, R. Biting off more than you can chew: Attempted predation on a human by a giant snake (Simalia amethistina). Austral. Ecol. 46, 159–162 (2021).
    Google Scholar 
    Neldner, V. J. & Clarkson, J. R. Vegetation of Cape York Peninsula. (Department of Environment and Heritage, 1995).Bureau of Meteorology. Climate Data Online. http://www.bom.gov.au/climate/data/. Accessed 17 July 2020 (2020).Whitaker, P. B. & Shine, R. A radiotelemetric study of movements and shelter-site selection by free-ranging brownsnakes (Pseudonaja textilis, Elapidae). Herpetol. Monogr. 17, 130–144 (2003).
    Google Scholar 
    Harris, S. et al. Home-range analysis using radio-tracking data–A review of problems and techniques particularly as applied to the study of mammals. Mamm. Rev. 20, 97–123 (1990).
    Google Scholar 
    Fearn, S. & Sambono, J. Some ambush predation postures of the Scrub Python Morelia amethistina (Serpentes: Pythonidae) in north east Queensland. Herpetofauna 30, 39–44 (2000).
    Google Scholar 
    Caswell, H. Theory and models in ecology: A different perspective. Ecol. Model. 43, 33–44 (1988).
    Google Scholar 
    Silva, I., Crane, M., Marshall, B. M. & Strine, C. T. Reptiles on the wrong track? Moving beyond traditional estimators with dynamic Brownian bridge movement models. Move. Ecol. 8, 43 (2020).
    Google Scholar 
    Row, J. R. & Blouin-Demers, G. Kernels are not accurate estimators of home-range size for herpetofauna. Copeia 2006, 797–802 (2006).
    Google Scholar 
    Newman, P., Dwyer, R. G., Belbin, L. & Campbell, H. A. ZoaTrack—An online tool to analyse and share animal location data: User engagement and future perspectives. Aust. Zool. 41, 12–18. https://zoatrack.org/toolkit/doi (2020).Pearson, D. J. & Shine, R. Expulsion of interperitoneally-implanted radiotransmitters by Australian pythons. Herpetol. Rev. 33, 261–263 (2002).
    Google Scholar 
    Hale, V. L. et al. Radio transmitter implantation and movement in the wild timber rattlesnake (Crotalus horridus). J. Wildl. Dis. 53, 591–595 (2017).PubMed 

    Google Scholar 
    Martin, A. E., Jørgensen, D. & Gates, C. C. Costs and benefits of straight versus tortuous migration paths for Prairie Rattlesnakes (Crotalus viridis viridis) in seminatural and human-dominated landscapes. Can. J. Zool. 95, 921–928 (2017).
    Google Scholar 
    Glaudas, X., Rice, S. E., Clark, R. W. & Alexander, G. J. Male energy reserves, mate-searching activities, and reproductive success: Alternative resource use strategies in a presumed capital breeder. Oecologia 194, 415–425 (2020).ADS 
    PubMed 

    Google Scholar 
    Glaudas, X., Rice, S. E., Clark, R. W. & Alexander, G. J. The intensity of sexual selection, body size and reproductive success in a mating system with male–male combat: is bigger better?. Oikos 129, 998–1011 (2020).
    Google Scholar 
    Gannon, V. P. J. & Secoy, D. M. Seasonal and daily activity patterns in a Canadian population of the prairie rattlesnake, Crotalus viridus viridis. Can. J. Zool. 63, 86–91 (1985).
    Google Scholar 
    Heard, G. W., Black, D. & Robertson, P. Habitat use by the inland carpet python (Morelia spilota metcalfei: Pythonidae): Seasonal relationships with habitat structure and prey distribution in a rural landscape. Austral. Ecol. 29, 446–460 (2004).
    Google Scholar 
    Madsen, T. & Shine, R. Seasonal migration of predators and prey—A study of pythons and rats in tropical Australia. Ecology 77, 149–156 (1996).
    Google Scholar 
    Graves, B. M. & Duvall, D. Reproduction, rookery use, and thermoregulation in free-ranging, pregnant Crotalus v. viridis. J. Herpetol. 27, 33–41 (1993).
    Google Scholar 
    Chiaraviglio, M. The effects of reproductive condition on thermoregulation in the Argentina boa constrictor (Boa constrictor occidentalis) (Boidae). Herpetol. Monogr. 20, 172–177 (2006).
    Google Scholar 
    Smith, C. F., Schuett, G. W., Earley, R. L. & Schwenk, K. The spatial and reproductive ecology of the copperhead (Agkistrodon contortrix) at the northeastern extreme of its range. Herpetol. Monogr. 23, 45–73 (2009).
    Google Scholar 
    Shine, R. & Fitzgerald, M. Large snakes in a mosaic rural landscape: The ecology of carpet pythons Morelia spilota (Serpentes: Pythonidae) in coastal eastern Australia. Biol. Conserv. 76, 113–122 (1996).
    Google Scholar 
    Heard, G. W. et al. Canid predation: A potentially significant threat to relic populations of the Inland Carpet Python ‘Morelia spilota metcalfei’ (Pythonidae) in Victoria. Vic. Nat. 123, 68–74 (2006).
    Google Scholar 
    Downes, S. & Shine, R. Sedentary snakes and gullible geckos: Predator–prey coevolution in nocturnal rock-dwelling reptiles. Anim. Behav. 55, 1373–1385 (1998).CAS 
    PubMed 

    Google Scholar 
    Miller, A. K., Maritz, B., McKay, S., Glaudas, X. & Alexander, G. J. An ambusher’s arsenal: chemical crypsis in the puff adder (Bitis arietans). Proc. R. Soc. B 282, 20152182 (2015).PubMed 
    PubMed Central 

    Google Scholar 
    Maritz, B. & Alexander, G. J. Dwarfs on the move: Spatial ecology of the world’s smallest viper, Bitis schneideri. Copeia 2012, 115–120 (2012).
    Google Scholar 
    Stirrat, S. C. Seasonal changes in home-range area and habitat use by the agile wallaby (Macropus agilis). Wildl. Res. 30, 593–600 (2003).
    Google Scholar 
    Ayers, D. Y. & Shine, R. Thermal influences on foraging ability: Body size, posture and cooling rate of an ambush predator, the python Morelia spilota. Funct. Ecol. 11, 342–347 (1997).
    Google Scholar 
    Pearson, D., Shine, R. & Williams, A. Spatial ecology of a threatened python (Morelia spilota imbricata) and the effects of anthropogenic habitat change. Austral. Ecol. 30, 261–274 (2005).
    Google Scholar 
    Freeman, A. A study in power and grace: The amethystine python. Wildl. Aust. 53, 27–29 (2016).
    Google Scholar 
    Silva, I., Crane, M., Suwanwaree, P., Strine, C. & Goode, M. Using dynamic Brownian bridge movement models to identify home range size and movement patterns in king cobras. PLoS ONE 13, e0203449 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    Marshall, B. M. et al. Space fit for a king: Spatial ecology of king cobras (Ophiophagus hannah) in Sakaerat Biosphere Reserve, Northeastern Thailand. Amphibia-Reptilia 40, 163–178 (2019).
    Google Scholar 
    Udyawer, V., Simpfendorfer, C. A., Heupel, M. R. & Clark, T. D. Temporal and spatial activity-associated energy partitioning in free-swimming sea snakes. Funct. Ecol. 31, 1739–1749 (2017).
    Google Scholar 
    Smaniotto, N. P., Moreira, L. F., Rivas, J. A. & Strüssmann, C. Home range size, movement, and habitat use of yellow anacondas (Eunectes notaeus). Salamandra 56, 159–167 (2020).
    Google Scholar 
    Low, M. R. Rescue, rehabilitation and release of reticulated pythons in Singapore. in Global Reintroduction Perspectives: 2018. Case Studies from Around the Globe (ed. Soorae, P. S.) 78–81 (IUCN/SSC Reintroduction Specialist Group, 2018).Alexander, G. J. & Maritz, B. Sampling interval affects the estimation of movement parameters in four species of African snakes. J. Zool. 297, 309–318 (2015).
    Google Scholar 
    Smith, B. J. et al. Betrayal: Radio-tagged Burmese pythons reveal locations of conspecifics in Everglades National Park. Biol. Invasions 18, 3239–3250 (2016).
    Google Scholar  More

  • in

    DNA barcoding and phylogeography of the Hoplias malabaricus species complex

    Cardoso, Y. P. et al. A continental-wide molecular approach unraveling mtDNA diversity and geographic distribution of the Neotropical genus Hoplias. PLoS ONE 13(8), e0202024. https://doi.org/10.1371/journal.pone.0202024 (2018).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Bertollo, L. A. C., Born, G. G., Dergam, J. A., Fenocchio, A. S. & Moreira-Filho, O. A biodiversity approach in the Neotropical Erythrinidae fish, Hoplias malabaricus: Karyotypic survey, geographic distribution of karyomorphs and cytotaxonomic considerations. Chrom. Res. 8(7), 603–613 (2000).CAS 
    Article 

    Google Scholar 
    Oyakawa, O. T. Family Erythrinidae (Trahiras). in Check list of the freshwater fishes of South and Central America (Reis, R. E., Kullander, S. O. & Ferraris, C.). Edipucrs 238–240 (Porto Alegre, 2003).Dagosta, F. C. P. & de Pinna, M. C. C. The fishes of the Amazon: distribution and biogeographical patterns, with a comprehensive list of species. Bull. Am. Museum Nat. Hist. 431, 1–163 (2019).
    Google Scholar 
    Da Rosa, R., Vicari, M. R., Dias, A. L. & Giuliano-Caetano, L. New insights into the biogeographic and Karyotypic Evolution of Hoplias Malabaricus. Zebrafish 11(3), 198–206. https://doi.org/10.1089/zeb.2013.0953 (2014).CAS 
    Article 
    PubMed 

    Google Scholar 
    Santos, U. et al. Molecular and karyotypic phylogeography in the neotropical Hoplias malabaricus (Erythrinidae) fish in eastern Brazil. J. Fish Biol. 75(9), 2326–2343. https://doi.org/10.1111/j.1095-8649.2009.02489.x (2009).CAS 
    Article 
    PubMed 

    Google Scholar 
    Blanco, D. R., Lui, R. L., Bertollo, L. A. C., Diniz, D. & Filho, O. M. Characterization of invasive fish species in a river transposition region: Evolutionary chromosome studies in the genus Hoplias (Characiformes, Erythrinidae). Rev. Fish Biol. Fish. 20(1), 1–8. https://doi.org/10.1007/s11160-009-9116-3 (2010).Article 

    Google Scholar 
    Jacobina, U. P. et al. DNA barcode sheds light on systematics and evolution of neotropical freshwater trahiras. Genetica 146, 505. https://doi.org/10.1007/s10709-018-0043-x (2018).CAS 
    Article 
    PubMed 

    Google Scholar 
    Marques, D. F., Santos, F. A., da Silva, S. S., Sampaio, I. & Rodrigues, L. R. R. Cytogenetic and DNA barcoding reveals high divergence within the trahira, Hoplias malabaricus (Characiformes: Erythrinidae) from the lower Amazon River. Neotrop. Ichthyol. 11(2), 459–466. https://doi.org/10.1590/S1679-62252013000200015 (2013).Article 

    Google Scholar 
    Paz, F. P. C., Batista, J. S. & Porto, J. I. R. DNA barcodes of rosy tetras and allied species (Characiformes: Characidae: Hyphessobrycon) from the Brazilian Amazon Basin. PLoS ONE 9(5), e98603. https://doi.org/10.1371/journal.pone.0098603 (2014).ADS 
    CAS 
    Article 

    Google Scholar 
    Guimarães, K. L. A., de Sousa, M. P. A., Ribeiro, F. R. V., Porto, J. I. R. & Rodrigues, L. R. R. DNA barcoding of fish fauna from low order streams of Tapajós River basin. PLoS ONE 13(12), e0209430. https://doi.org/10.1371/journal.pone.0209430 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Machado, V. N. et al. One thousand DNA barcodes of piranhas and pacus reveal geographic structure and unrecognized diversity in the Amazon. Sci. Rep. 8, 8387. https://doi.org/10.1038/s41598-018-26550-x (2018).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Hebert, P. D. N., Cywinska, A., Ball, S. L. & Dewaard, J. R. Biological identifications through DNA barcodes. Philos. Trans. R. Soc. B 270(1512), 313–321. https://doi.org/10.1098/rspb.2002.2218 (2003).CAS 
    Article 

    Google Scholar 
    Pugedo, M. L., de Andrade Neto, F. R., Pessali, T. C., Birindelli, J. L. O. & Carvalho, D. C. Integrative taxonomy supports new candidate fish species in a poorly studied neotropical region: the Jequitinhonha River Basin. Genetica 144(3), 1–9. https://doi.org/10.1007/s10709-016-9903-4 (2016).Article 

    Google Scholar 
    Rosso, J. J. et al. Integrative taxonomy reveals a new species of the Hoplias malabaricus species complex (Teleostei: Erythrinidae). Ichthyol. Explor. Freshw. 1, 1–18. https://doi.org/10.23788/IEF-1076 (2018).Article 

    Google Scholar 
    Azpelicueta, M. M., Benítez, M., Aichino, D. & Mendez, C. M. D. A new species of the genus Hoplias (Characiformes, Erythrinidae), a tararira from the lower Paraná River, in Missiones, Argentina. Acta Zool. Lilloana 59(1–2), 71–82 (2015).
    Google Scholar 
    Rosso, J. J. et al. A new species of the Hoplias malabaricus species complex (Characiformes: Erythrinidae) from the La Plata River basin. Cybium 40(3), 199–208 (2016).
    Google Scholar 
    Cardoso, Y. P. & Montoya-Burgos, J. I. Unexpected diversity in the catfish Pseudancistrus brevispinis reveals dispersal routes in a Neotropical center of endemism: The Guyanas Region. Mol. Ecol. 18(5), 947–964. https://doi.org/10.1111/j.1365-294X.2008.04068.x (2009).CAS 
    Article 
    PubMed 

    Google Scholar 
    Hoorn, C., Wesselingh, F. P., Hovikoski, J. & Guerrero, J. The development of the Amazonian mega-wetland (Miocene; Brazil, Colombia, Peru, Bolivia). Amazon. Landsc. Species Evol. https://doi.org/10.1002/9781444306408.ch8 (2010).Article 

    Google Scholar 
    Albert, J. S. & Reis, R. E. Introduction to neotropical freshwaters. In Historical Biogeography of Neotropical Freshwater Fishes (eds Albert, J. S. & Reis, R. E.) 3–19 (University of California Press, 2011).
    Google Scholar 
    Leys, M., Keller, I., Räsänen, K., Gattolliat, J.-L. & Robinson, C. T. Distribution and population genetic variation of cryptic species of the Alpine mayfly Baetis alpinus (Ephemeroptera: Baetidae) in the Central Alps. BMC Evol. Biol. https://doi.org/10.1186/s12862-016-0643-y (2016).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Aljanabi, S. M. & Martinez, I. Universal and rapid salt-extraction of high quality genomic DNA for PCR-based techniques. Nucleic Acids Res. 25(22), 4692–4693 (1997).CAS 
    Article 

    Google Scholar 
    Vitorino, C. A., Oliveira, R. C. C., Margarido, V. P. & Venere, P. C. Genetic diversity of Arapaima gigas (Schinz, 1822) (Osteoglossiformes: Arapaimidae) in the Araguaia-Tocantins basin estimated by ISSR marker. Neotrop. Ichthyol. 13, 557–568. https://doi.org/10.1590/1982-0224-20150037 (2015).Article 

    Google Scholar 
    Ward, R. D., Zemlak, T. S., Innes, B. H., Last, P. R. & Hebert, P. D. N. DNA barcoding Australia’s fish species. Philos. Trans. R. Soc. B 359, 1847–1857. https://doi.org/10.1098/srtb.2005.1716 (2005).Article 

    Google Scholar 
    Dunn, I. S. & Blattner, F. R. Sharons 36 to 40: Multienzyme, high capacity, recombination deficient replacement vectors with polylinkers and polystuffers. Nucleic Acids Res. 15, 2677–2698 (1987).CAS 
    Article 

    Google Scholar 
    Thompson, J. D., Higgins, D. G. & Gibson, T. J. CLUSTAL W: Improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 22(22), 4673–4680 (1994).CAS 
    Article 

    Google Scholar 
    Castresana, J. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol. Biol. Evol. 17, 540–552. https://doi.org/10.1093/oxfordjournals.molbev.a026334 (2000).CAS 
    Article 

    Google Scholar 
    Ratnasingham, S. & Hebert, P. D. N. DNA-Based registry for all animal species: The Barcode Index Number (BIN) system. PLoS ONE 8(7), e66213. https://doi.org/10.1371/journal.pone.0066213 (2013).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Pons, J. et al. Sequence-based species delimitation for the DNA taxonomy of undescribed insects. Syst. Biol. 55(4), 595–609. https://doi.org/10.1080/10635150600852011 (2006).Article 
    PubMed 

    Google Scholar 
    Fujisawa, T. & Barraclough, T. G. Delimiting species using single-locus data and the generalized mixed yule coalescent approach: A revised method and evaluation on simulated data sets. Syst. Biol. 62(5), 707–724. https://doi.org/10.1093/sysbio/syt033 (2013).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Puillandre, N., Lambert, A., Brouillet, S. & Achaz, G. ABGD, automatic barcode gap discovery for primary species delimitation. Mol. Ecol. 21(8), 1864–1877. https://doi.org/10.1111/j.1365-294X.2011.05239.x (2012).CAS 
    Article 
    PubMed 

    Google Scholar 
    Drummond, A. & Rambaut, A. BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evol. Biol. 7, 214. https://doi.org/10.1186/1471-2148-7-214 (2007).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Posada, D. jModelTest: Phylogenetic model averaging. Mol. Biol. Evol. 25, 1253–1256. https://doi.org/10.1093/molbev/msn083 (2008).CAS 
    Article 
    PubMed 

    Google Scholar 
    R Core Team. R: A Language and Environment for Statistical Computing. https://www.R-project.org/ (2017).Ezard, T., Fujisawa, T. & Barraclough, T. splits: Species Limits by Threshold Statistics. R package version 1.0–19/r52. https://R-Forge.R-project.org/projects/splits/ (2017).Paradis, E. & Schliep, K. ape 5.0: An environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics 35, 526–528 (2018).Article 

    Google Scholar 
    Bermingham, E., McCafferty, S. S. & Martin, A. P. Fish biogeography and molecular clocks: Perspectives from the Panamanian Isthmus. In Molecular Systematics of Fishes (eds Kocher, T. D. & Stepien, C. A.) 113–128 (Academic Press, 1997).Chapter 

    Google Scholar 
    Thomaz, A. T., Malabarba, L. R., Bonatto, S. L. & Knowles, L. L. Testing the effect of palaeodrainages versus habitat stability on genetic divergence in riverine systems: Study of a Neotropical fish of the Brazilian coastal Atlantic Forest. J. Biogeogr. 42, 2389–2401. https://doi.org/10.1111/jbi.12597 (2015).Article 

    Google Scholar 
    Kimura, M. A simple method for estimating evolutionary rate of base substitutions through comparative studies of nucleotide sequences. J. Mol. Evol. 16, 111–120 (1980).ADS 
    CAS 
    Article 

    Google Scholar 
    Kumar, S., Stecher, G., Li, M., Knyaz, C. & Tamura, K. MEGA X: Molecular evolutionary genetics analysis across computing platforms. Mol. Biol. Evol. 35, 1547–1549. https://doi.org/10.1093/molbev/msy096 (2018).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Guillot, G., Renaud, S., Ledevin, R., Michaux, J. & Claude, J. A unifying model for the analysis of phenotypic, genetic and geograhic data. Syst. Biol. 61(6), 897–911. https://doi.org/10.1093/sysbio/sys038 (2012).Article 
    PubMed 

    Google Scholar 
    Excoffier, L., Laval, G. & Schneider, S. Arlequin: A Software for Population Data Analysis. Version 3.1. http://cmpg.unibe.ch/software/arlequin3 (2007).Wright, S. Evolution and the genetics of populations: Variability within and among natural populations. Univ. Chicago 4, 580 (1978).
    Google Scholar 
    Rozas, J. et al. DnaSP 6: DNA sequence polymorphism analysis of large datasets. Mol. Biol. Evol. 34, 3299–3302. https://doi.org/10.1093/molbev/msx248 (2017).CAS 
    Article 
    PubMed 

    Google Scholar 
    Bandelt, H. J., Forster, P. & Röhl, A. Median-joining networks for inferring intraspecific phylogenies. Mol. Biol. Evol. 16(1), 37–48 (1999).CAS 
    Article 

    Google Scholar 
    Leigh, J. W. & Bryant, D. POPART: Full-feature software for haplotype network construction. Methods Ecol. Evol. 6, 1110–1116. https://doi.org/10.1111/2041-210X.12410 (2015).Article 

    Google Scholar 
    Tajima, F. Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics 123, 585–595 (1989).CAS 
    Article 

    Google Scholar 
    Fu, Y. X. Statistical tests of neutrality of mutations against population growth, hitchhiking and background selection. Genetics 147, 915–925 (1997).CAS 
    Article 

    Google Scholar 
    Austin, M. P. Continuum concept, ordination methods, and niche theory. Annu. Rev. Ecol. Syst. 16(1), 39–61. https://doi.org/10.1146/annurev.es.16.110185.000351 (1985).MathSciNet 
    Article 

    Google Scholar 
    Graham, A., Atkinson, P. & Danson, F. Spatial analysis for epidemiology. Acta Trop. 91(3), 219–225. https://doi.org/10.1016/j.actatropica.2004.05.001 (2004).CAS 
    Article 
    PubMed 

    Google Scholar 
    Phillips, S. J., Anderson, R. P. & Schapire, R. E. Maximum entropy modeling of species geographic distributions. Ecol. Model. 190(3–4), 231–259. https://doi.org/10.1016/j.ecolmodel.2005.03.026 (2006).Article 

    Google Scholar 
    Guimarães, K. L. A., Rosso, J. J., Souza, M. F. B., de Astarloa, J. M. D. & Rodrigues, L. R. R. Integrative taxonomy reveals disjunct distribution and first record of Hoplias misionera (Characiformes: Erythrinidae) in the Amazon River basin: Morphological, DNA barcoding and cytogenetic considerations. Neotrop. Ichthyol. 19(2), e200110. https://doi.org/10.1590/1982-0224-2020-0110 (2021).Article 

    Google Scholar 
    Queiroz, L. J. et al. Evolutionary units delimitation and continental multilocus phylogeny of the hyperdiverse catfish genus Hypostomus. Mol. Phylogenet. Evol. 145, 106711. https://doi.org/10.1016/j.ympev.2019.106711 (2020).Article 

    Google Scholar 
    Phillips, J. D., Gillis, D. J. & Hanner, R. H. Incomplete estimates of genetic diversity within species: Implications for DNA barcoding. Ecol. Evol. https://doi.org/10.1002/ece3.4757 (2019).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Blaxter, M. L. The promise of a DNA taxonomy. Philos. Trans. R. Soc. B. 359(1444), 669–679. https://doi.org/10.1098/rstb.2003.1447 (2004).CAS 
    Article 

    Google Scholar 
    Nwani, C. D. et al. DNA barcoding discriminates freshwater fishes from southeastern Nigeria and provides river system-level phylogeographic resolution within some species. Mitochondrial DNA 22(1), 43–51. https://doi.org/10.3109/19401736.2010.536537 (2011).CAS 
    Article 
    PubMed 

    Google Scholar 
    Aguirre, W. E., Shervette, V. R., Navarrete, R., Calle, P. & Agorastos, S. Morphological and genetic divergence of Hoplias microlepis (Characiformes: Erythrinidae) in rivers and artificial impoundments of Western Ecuador. Copeia 2013(2), 312–323. https://doi.org/10.1643/ci-12-083 (2013).Article 

    Google Scholar 
    Pires, W. M. M., Barros, M. C. & Fraga, E. C. DNA Barcoding unveils cryptic lineages of Hoplias malabaricus from Northeastern Brazil. Braz. J. Biol. 81(4), 917–927. https://doi.org/10.1590/1519-6984.231598 (2020).Article 

    Google Scholar 
    Souza, F. H. S. et al. interspecific genetic differences and historical demography in South American Arowanas (Osteoglossiformes, Osteoglossidae, Osteoglossum). Genes 10(9), 693. https://doi.org/10.3390/genes10090693 (2019).CAS 
    Article 
    PubMed Central 

    Google Scholar 
    Torati, L. S. et al. Genetic diversity and structure in Arapaima gigas populations from Amazon and Araguaia-Tocantins river basins. BMC Genet. https://doi.org/10.1186/s12863-018-0711-y (2019).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Lovejoy, N. R. & Araujo, M. L. G. Molecular systematics, biogeography and population structure of Neotropical freshwater needlefishes of the genus Potamorrhaphis. Mol. Ecol. 9(3), 259–268. https://doi.org/10.1046/j.1365-294x.2000.00845.x (2000).CAS 
    Article 
    PubMed 

    Google Scholar 
    Mabesoone, J. M. Sedimentary Basins of Northeast Brazil (Federal University of Pernambuco, 1994).
    Google Scholar 
    Haffer, J. & Prance, G. T. Impulsos climáticos da evolução na Amazônia durante o Cenozóico: Sobre a teoria dos Refúgios da diferenciação biótica. Estudos Avançados USP 46, 175–208. https://doi.org/10.1590/S0103-40142002000300014 (2002).Article 

    Google Scholar 
    Riker, S. R. L., Lima, F. J. C., Motta, M. B. Evidências de glaciação Pleistocênica na Amazônia Brasileira. Anais do 14° Simpósio de Geologia da Amazônia, Sociedade Brasileira de Geologia 15–18 (2015).Albert, J. S., Val, P. & Hoorn, C. The changing course of the Amazon River in the Neogene: Center stage for Neotropical diversification. Neotrop. Ichthyol. 16(3), e180033. https://doi.org/10.1590/1982-0224-20180033 (2018).Article 

    Google Scholar 
    Lundberg, J. G. et al. The stage for Neotropical fish diversification: a history of tropical South American rivers. (eds. Malabarba, L. R., Reis, R. E., Vari, R. P., Lucena, Z. M., Lucena, C. A. S. Phylogeny and classification of Neotropical fishes). Edipucrs 13–48 (1998).Hubert, N. & Renno, J. F. Historical biogeography of South American freshwater fishes. J. Biogeogr. 33(8), 1414–1436. https://doi.org/10.1111/j.1365-2699.2006.01518.x (2006).Article 

    Google Scholar 
    Farias, I. P. & Hrbek, T. Patterns of diversification in the discus fishes (Symphysodon spp. Cichlidae) of the Amazon basin. Mol. Phylogenet. Evol. 49, 32–43. https://doi.org/10.1016/j.ympev.2008.05.033 (2008).CAS 
    Article 
    PubMed 

    Google Scholar 
    Tagliacollo, V. A., Bernt, M. J., Craig, J. M., Oliveira, C. & Albert, J. S. Model-based total evidence phylogeny of Neotropical electric knifefishes (Teleostei, Gymnoti-formes). Mol. Phylogenet. Evol. 95, 20–33. https://doi.org/10.1016/j.ympev.2015.11.007 (2015).Article 
    PubMed 

    Google Scholar 
    Hutchinson, G. E. Concluding remarks. Cold Spring Harbor Symposium. Quant. Biol. 22, 415–427 (1957).Article 

    Google Scholar 
    Wiens, J. J. & Graham, C. H. Niche conservatism: Inte-grating evolution, ecology, and conservation biology. Annu. Rev. Ecol. Evol. Syst. 36, 519–539 (2005).Article 

    Google Scholar 
    McNyset, K. M. Ecological niche conservatism in North American freshwater fishes. Biol. J. Lin. Soc. 96, 282–295 (2009).Article 

    Google Scholar 
    Silva, W. C., Marceniuk, A. P., Sales, J. B. L. & Araripe, J. Early pleistocene lineages of Bagre bagre (Linnaeus, 1766) (Siluriformes: Ariidae), from the Atlantic coast of South America, with insights into the demography and biogeography of the species. Neotrop. Ichthyol. https://doi.org/10.1590/1982-0224-20150184 (2016).Article 

    Google Scholar 
    Lemopoulos, A. & Covain, R. Biogeography of the freshwater fishes of the Guianas using a partitioned parsimony analysis of endemicity with reappraisal of ecoregional boundaries. Cladistics 35(2019), 106–124. https://doi.org/10.1111/cla.12341 (2018).Article 
    PubMed 

    Google Scholar 
    Hoorn, C. Marine incursions and the influence of Andean tectonics on the Miocene depositional history of northwestern Amazonia: Results of a palynostratigraphic study. Palaeogeogr. Palaeoclimatol. Palaeoecol. 105, 267–309. https://doi.org/10.1016/0031-0182(93)90087-Y (1993).Article 

    Google Scholar 
    Hoorn, C., Guerreiro, J. & Sarmiento, G. Andean tectonics as a cause for changing drainage patterns in Miocene Northern South America. Geology 23(3), 237–240. https://doi.org/10.1130/0091-7613(1995)023%3c0237:ATAACF%3e2.3.CO;2 (1995).ADS 
    Article 

    Google Scholar 
    Ribeiro, A. C. Tectonic history and the biogeography of the freshwater fishes from the coastal drainages of eastern Brazil: An example of faunal evolution associated with a divergent continental margin. Neotrop. Ichthyol. 4(2), 225–246. https://doi.org/10.1590/S1679-62252006000200009 (2006).Article 

    Google Scholar 
    Lovejoy, N. R., Albert, J. S. & Crampton, W. G. R. Miocene marine incursions and marine/freshwater transitions: Evidence from Neotropical fishes. J. S. Am. Earth Sci. 21(1–2), 5–13. https://doi.org/10.1016/j.jsames.2005.07.009 (2006).Article 

    Google Scholar  More

  • in

    Squid adjust their body color according to substrate

    Endler, J. A. Interactions between predators and prey. In Behavioural Ecology: An Evolutionary Approach 3rd edn (eds Krebs, J. R. & Davies, N. B.) 169–196 (Blackwell, 1991).
    Google Scholar 
    Stevens, M. & Merilaita, S. Animal camouflage: Current issues and new perspectives. Philos. Trans. R Soc. Lond. B 364, 423–427 (2009).
    Google Scholar 
    Stevens, M. & Merilaita, S. Animal camouflage: Function and mechanisms. In Animal Camouflage: Mechanisms and Function (eds Stevens, M. & Merilaita, S.) 1–17 (Cambridge University Press, 2011).
    Google Scholar 
    Reiter, S. & Laurent, G. Visual perception and cuttlefish camouflage. Curr. Opin. Neurobiol. 260, 47–54 (2020).
    Google Scholar 
    Cott, H. B. Adaptive Coloration in Animals (Methuen, 1940).
    Google Scholar 
    Cloney, R. A. & Florey, E. Ultrastructure of cephalopod chromatophore organs. Z. Zellforsch. Mikrosk. Anat. 89, 250–280 (1968).CAS 
    PubMed 

    Google Scholar 
    Borrelli, L., Gherardi, F. & Fiorito, G. A. Catalogue of Body Patterning in Cephalopoda (Firenze University Press, 2006).
    Google Scholar 
    Reiter, S. et al. Elucidating the control and development of skin patterning in cuttlefish. Nature 562, 361–366 (2018).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Barbosa, A., Allen, J. J., Mäthger, L. M. & Hanlon, R. T. Cuttlefish use visual cues to determine arm postures for camouflage. Proc. R Soc. B Biol. Sci. 279, 84–90 (2012).
    Google Scholar 
    Hanlon, R. T. Cephalopod dynamic camouflage. Curr. Biol. 17, R400-404 (2007).CAS 
    PubMed 

    Google Scholar 
    Hill, A. V. & Solandt, D. Y. Myograms from the chromatophores of Sepia. J. Physiol. Lond. 83, 13–14 (1935).
    Google Scholar 
    Williams, T. L. et al. Dynamic pigmentary and structural coloration within cephalopod chromatophore organs. Nat. Commun. 10, 1–5 (2019).
    Google Scholar 
    Hanlon, R. T. et al. Rapid adaptive camouflage in cephalopods. In Animal Camouflage: Mechanisms and Functions (eds Stevens, M. & Merilaita, S.) 145–163 (Cambridge Univ Press, 2011).
    Google Scholar 
    Hanlon, R. T. & Messenger, J. B. Adaptive coloration in young cuttlefish (Sepia officinalis L.): The morphology and development of body patterns and their relation to behavior. Philos. Trans. R Soc. Lond. B 320, 437–487 (1988).ADS 

    Google Scholar 
    Ferguson, G., Messenger, J. B. & Budelmann, B. Gravity and light influence the countershading reflexes of the cuttlefish Sepia officinalis. J. Exp. Biol. 191, 247–256 (1994).CAS 
    PubMed 

    Google Scholar 
    Shohet, A. J., Baddeley, R. J., Anderson, J. C., Kelman, E. J. & Osorio, D. Cuttlefish responses to visual orientation of substrates, water flow and a model of motion camouflage. J. Exp. Biol. 209, 4717–4723 (2006).CAS 
    PubMed 

    Google Scholar 
    Barbosa, A. et al. Disruptive coloration in cuttlefish: A visual perception mechanism that regulates ontogenetic adjustment of skin patterning. J. Exp. Biol. 210, 1139–1147 (2007).PubMed 

    Google Scholar 
    Chiao, C. C., Chubb, C. & Hanlon, R. T. Interactive effects of size, contrast, intensity and configuration of background objects in evoking disruptive camouflage in cuttlefish. Vis. Res. 47, 2223–2235 (2007).PubMed 

    Google Scholar 
    Nakajima, R. & Ikeda, Y. A catalog of the chromatic, postural, and locomotor behaviors of the pharaoh cuttlefish (Sepia pharaonis) from Okinawa Island, Japan. Mar. Biodivers. 47, 735–753 (2017).
    Google Scholar 
    Packard, A. Chromatophore fields in the skin of the octopus. J. Physiol. 238, 38–40 (1974).
    Google Scholar 
    Caldwell, R. L., Ross, R., Rodaniche, A. F. & Huffard, C. L. Behavior and body patterns of the larger pacific striped octopus. PLoS ONE 10, e0134152 (2015).PubMed 
    PubMed Central 

    Google Scholar 
    Gutnick, T., Shomrat, T., Mather, J. A. & Kuba, M. J. The cephalopod brain: Motion control, learning, and cognition. In Physiology of Molluscs: A Collection of Selected Reviews Vol. 2 (eds Salleudin, S. & Mukai, S.) 139–177 (Apple Academic Press, 2016).
    Google Scholar 
    Hanlon, R. T. & Messenger, J. B. Cephalopod Behaviour 2nd edn. (Cambridge University Press, 2018).
    Google Scholar 
    Cloney, R. & Brocco, S. Chromatophore organs, reflector cells, iridocytes, and leucophores. Am. Zool. 23, 581–592 (1983).
    Google Scholar 
    Mäthger, L. M. & Hanlon, R. T. Malleable skin coloration in cephalopods: Selective reflectance, transmission and absorbance of light by chromatophores and iridophores. Cell Tissue Res. 329, 179 (2007).PubMed 

    Google Scholar 
    Josef, N., Berenshtein, I., Fiorito, G., Sykes, A. V. & Shashar, N. Camouflage during movement in the European cuttlefish (Sepia officinalis). J. Exp. Biol. 218, 3391–3398 (2015).PubMed 

    Google Scholar 
    Josef, N. et al. Size matters: Observed and modeled camouflage response of European Cuttlefish (Sepia officinalis) to different substrate patch sizes during movement. Front. Physiol. 7, 671 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    Poulton, E. B. The Colours of Animals: Their Meaning and Use, Especially Considered in the Case of Insects (D. Appleton, 1890).
    Google Scholar 
    Zhang, Y. & Richardson, J. S. Unidirectional prey–predator facilitation: Apparent prey enhance predators’ foraging success on cryptic prey. Biol. Lett. 3, 348–351 (2007).PubMed 
    PubMed Central 

    Google Scholar 
    Troscianko, T., Benton, C. P., Lovell, P. G., Tolhurst, D. J. & Pizlo, Z. Camouflage and visual perception. Philos. Trans. R Soc. B 364, 449–461 (2009).
    Google Scholar 
    Land, M. F. & Nilsson, D. E. Animal Eyes (Oxford University Press, 2012).
    Google Scholar 
    Cronin, T. W., Johnsen, S., Marshall, N. J. & Warrant, E. J. Visual Ecology (Princeton University Press, 2014).
    Google Scholar 
    Hanlon, R. T. & Messenger, J. B. Cephalopod Behaviour (Cambridge University Press, 1996).
    Google Scholar 
    Staudinger, M. D., Hanlon, R. T. & Juanes, F. Primary and secondary defences of squid to cruising and ambush fish predators: Variable tactics and their survival value. Anim. Behav. 81, 585–594 (2011).
    Google Scholar 
    Ferguson, G. P. & Messenger, J. B. A countershading reflex in cephalopods. Proc. R. Soc. B 243, 63–67 (1991).ADS 

    Google Scholar 
    Zylinski, S. & Johnsen, S. Mesopelagic cephalopods switch between transparency and pigmentation to optimize camouflage in the deep. Curr. Biol. 21, 1937–1941 (2011).CAS 
    PubMed 

    Google Scholar 
    Young, R. E. & Roper, C. F. E. Bioluminescent countershading in mid water animals: Evidence from living squid. Science 191, 1046–1048 (1976).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Jereb, P. & Roper, C. F. E. Cephalopods of the World. An Annotated and Illustrated Catalogue of Cephalopod Species Known to Date. Myopsid and Oegopsid Squids Vol. 2 (FAO, 2010).
    Google Scholar 
    Okutani, T. Life history of the oval squid, Sepioteuthis lessoniana. Saibai Giken 13, 69–75 (1984) ((in Japanese)).
    Google Scholar 
    Segawa, S. Food consumption, food conversion and growth rates of the oval squid Sepioteuthis lessoniana by laboratory experiments. Nippon Suisan Gakkai Shi 56, 217–222 (1990).
    Google Scholar 
    Izuka, T., Segawa, S., Okutani, T. & Numachi, K. Evidence on the existence of three species in the oval squid Sepioteuthis lessoniana complex in Ishigaki Island, Okinawa, southwestern Japan, by isozyme analyses. Venus Jpn. J. Malacol/Kairuigaku Zasshi 53, 217–228 (1994).
    Google Scholar 
    Izuka, T. Biochemical study of the population heterogeneity and distribution of the oval squid Sepioteuthis lessoniana complex in southwestern Japan. Am. Malac. Bull. 12, 129–135 (1996).
    Google Scholar 
    Imai, H., & Aoki, M. Genetic diversity and genetic heterogeneity of bigfin reef squid “Sepioteuthis lessoniana” species complex in northwestern Pacific Ocean. in Analysis of Genetic Variation in Animals (Caliskan, M. ed). 151–166. (InTech, 2012).Cheng, S. H. et al. Molecular evidence for co-occurring cryptic lineages within the Sepioteuthis cf. lessoniana species complex in the Indian and Indo-West Pacific Oceans. Hydrobiologia 725, 165–188 (2014).CAS 

    Google Scholar 
    Tomano, S. et al. Contribution of Sepioteuthis sp. 1 and Sepioteuthis sp. 2 to oval squid fishery stocks in western Japan. Fish Sci 82, 585–596 (2016).CAS 

    Google Scholar 
    Okutani, T. Past, present and future studies on cephalopod diversity in tropical west Pacific. Phuket Mar. Biol. Center Res. Bull. 66, 39–50 (2005).
    Google Scholar 
    Lee, P. G., Turk, P. E., Yang, W. T. & Hanlon, R. T. Biological characteristics and biomedical applications of the squid Sepioteuthis lessoniana cultured through multiple generations. Biol. Bull. 186, 328–341 (1994).CAS 
    PubMed 

    Google Scholar 
    Nabhitabhata, J. & Ikeda, Y. Sepioteuthis lessoniana. In Cephalopod Culture (eds Iglesias, J. et al.) 315–347 (Springer, 2014).
    Google Scholar 
    Lajbner, Z. et al. Captive breeding of the oval squid (Aori-ika; Sepioteuthis sp.). in Cephalopod International Advisory Council Conference 2018, Book of Abstracts, St. Petersburg. 152. (2018)Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, i01 (2015).
    Google Scholar 
    R Core Team. R: A Language and Environment for Statistical Computing. http://www.R-project.org (R Foundation for Statistical Computing, 2019).RStudio Team. RStudio: Integrated Development for R. http://www.rstudio.com (RStudio, Inc., 2019)Kenward, M. & Roger, J. Small sample inference for fixed effects from restricted maximum likelihood. Biometrics 53, 983–997 (1997).CAS 
    PubMed 
    MATH 

    Google Scholar 
    Schneider, C. A., Rasband, W. S. & Eliceiri, K. W. NIH Image to ImageJ: 25 years of image analysis. Nat. Methods 9, 671–675 (2012).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Lin, C. Y., Tsai, Y. C. & Chiao, C. C. Quantitative analysis of dynamic body patterning reveals the grammar of visual signals during the reproductive behavior of the oval squid Sepioteuthis lessoniana. Front. Ecol. Evol. 5, 30 (2017).
    Google Scholar 
    Chung, W. S., Kurniawan, N. D. & Marshall, N. J. Toward an MRI-based mesoscale connectome of the squid brain. Iscience 23, 100816 (2020).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Messenger, J. B. Cephalopod chromatophores: Neurobiology and natural history. Biol. Rev. Camb. Philos. Soc. 76, 473–528 (2001).CAS 
    PubMed 

    Google Scholar 
    York, C. A. & Bartol, I. K. Anti-predator behavior of squid throughout ontogeny. J. Exp. Mar. Biol. Ecol. 480, 26–35 (2016).
    Google Scholar 
    Suzuki, M., Kimura, T., Ogawa, H., Hotta, K. & Oka, K. Chromatophore activity during natural pattern expression by the squid Sepioteuthis lessoniana: Contributions of miniature oscillation. PLoS ONE 6, e18244 (2011).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Liu, Y.C., Wang, W.C., & Grasse, B. Electrical coupling between chromatophore muscle fibers allows for versatile control of chromatophore expansion in squid. bioRxiv 2020.02.17.951715 (2020).Hadjisolomou, S. P., El-Haddad, R. W., Kloskowski, K., Chavarga, A. & Abramov, I. Quantifying the speed of chromatophore activity at the single-organ level in response to a visual startle stimulus in living, intact squid. Front. Physiol. 12, 675252. https://doi.org/10.3389/fphys.2021.675252 (2021).Article 
    PubMed 
    PubMed Central 

    Google Scholar  More

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    Swarms of ‘crazy ants’ that invade houses, cause electrical short circuits and overrun birds’ nests might have met their match: a naturally occurring parasite1.

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    doi: https://doi.org/10.1038/d41586-022-00888-9

    ReferencesLeBrun, E. G., Jones, M., Plowes, R. M. & Gilbert, L. E. Proc. Natl Acad. Sci. USA 119, e2114558119 (2022).PubMed 
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    Aggregated transfer factor of 137Cs in edible wild plants and its time dependence after the Fukushima Dai-ichi nuclear accident

    Comparison of T
    ag calculated from publicly available data and actual measurement dataThe calculated Tag (m2/kg-FM) in each year is summarized for each species in Supplemental Table 1:

    The geometric means (GMs) of Tag values calculated using the collected samples ranged from 8.1 × 10−6 to 2.5 × 10−2 m2/kg-FM; the minimum was for western bracken fern in 2019 and the maximum was for koshiabura in 2018 at Kawamata, Fukushima.

    The GMs of Tag values calculated using the publicly available data ranged from 1.6 × 10−5 to 1.2 × 10−2 m2/kg-FM and thus were similar to the actual measurement data. The minimum GM was for udo in 2019 and the maximum was for koshiabura in 2019. The geometric standard deviation (GSD) range was 1.5–4.5.

    Annual GMs of Tag values calculated from publicly available data and actual measurement data are compared in Fig. 1. The values for individual years are represented by different points. The Tag values were distributed close to the 1:1 line, which suggested that Tag values calculated from the publicly available data generally agreed with those calculated from actual measurements. Hence, an obvious overestimation of Tag from the publicly available data described above was not observed in the present data. We confirmed that Tag calculated from the publicly available food monitoring data and the total deposition data from the airborne survey are reliable surrogates for actual measurement samples. We discuss Tag calculated from the publicly available data hereafter.Figure 1Comparison of annual geometric means of the aggregated transfer factor (Tag) calculated from publicly available data and actual measurement data. Circles, diamonds, and triangles indicate deciduous perennial spermatophytes, deciduous tree spermatophytes, and deciduous perennial pteridophytes, respectively. Values for individual years are represented by different points. Error bars indicate the geometric standard deviation in cases where more than three samples were available.Full size imageRelationship between soil deposition and radioactivity in edible wild plants from publicly available dataWe confirmed the relationship between deposition and concentration of 137Cs for the publicly available data for butterbur scape, fatsia sprout, and western bracken fern in a year (Fig. 2), as a representative deciduous perennial and tree spermatophyte, and deciduous perennial pteridophyte, respectively, in the year of the maximum number of detections. Butterbur scape, fatsia sprout, and western bracken fern showed positive significant, nonsignificant, and weak negative significant correlations, respectively (Spearman’s rank correlation, butterbur scape, p = 0.001, rs = 0.45; fatsia sprout, p = 0.85, rs = − 0.03; western bracken fern, p = 0.03, rs = − 0.21). Among 29 subdata with more than 20 detections for each species in a year, in addition to the data shown in Fig. 2, 13 showed statistically significant positive correlations (Butterbur scape in 2014 and 2016; bamboo shoot in 2012, and 2014 − 2019; fatsia sprout in 2013 and 2016; koshiabura in 2013; and ostrich fern in 2012), and western bracken fern in 2017 showed a significant negative correlation. These weak correlations may be affected by uncertainty in the deposition data. We used a representative deposition value for each municipality and the original deposition data grid was of low resolution (see the “Methods” section Radiocesium deposition data from airborne survey). Especially for the cases lacking a clear positive correlation, the degree of radiocesium absorption by edible wild plants was largely different even in the same deposition. Radiocesium uptake by plants in an environment is also affected by other factors (e.g., soil characteristics25,26). The edible wild plants targeted in the present study were not cultivated but were collected in a variety of environments, such as forests with high organic matter content in the soil and paddy field margins with poorly drained soil high in clay content, although we cannot precisely confirm the growth environment of each species included in the present study.Figure 2Correlation between deposition and concentration of 137Cs in three edible wild plants. Circles, diamonds, and triangles indicate butterbur scape, fatsia sprout, and western bracken fern, respectively. The three species are representative deciduous perennial and tree spermatophyte, and deciduous perennial pteridophyte, respectively, in the year of the maximum number of detections.Full size imageTemporal change in T
    ag
    The time-dependence of Tag for each species in the period 2012–2019 is shown in Fig. 3. The Tag values of deciduous perennial spermatophytes and pteridophytes showed a decreasing trend with time. Given that the bioavailability of 137Cs in the soil in the plant root zone decreased with time, as observed in previous studies27,28, we also observed a decrease in Tag. The Tag of deciduous trees did not show a decreasing trend with time.Figure 3Temporal change in the aggregated transfer factor (Tag) in the period 2012–2019. Circles, diamonds, and triangles indicate deciduous perennial spermatophytes, deciduous tree spermatophytes (including bamboo shoot), and deciduous perennial pteridophytes, respectively. Single exponential fitted lines are shown. Solid lines indicate statistically significant parameters (see Table 2).Full size imageAfter the Chernobyl nuclear accident, radiocesium concentrations in deciduous tree leaves decreased with time owing to the effect of direct deposition at an early stage and the following root uptake effect29, and the Tag of tree leaves decreased accordingly. In previous studies conducted in orchards after the Chernobyl and Fukushima accidents, radiocesium concentrations in deciduous tree leaves showed a decreasing trend30,31. The lack of a declining trend for woody edible wild plants Tag in the present study may be due to a smaller effect of direct deposition at the early stage resulting from interception by tall tree canopies in the vicinity. The height of trees with edible wild plants is usually at eye level. The samples collected soon after the accident were possibly affected by direct deposition, whereas in the latter study period, many of the data were from trees grown after the accident. If the effect of direct deposition was large, a declining trend in Tag might have been observed as observed in orchards. Thus, the absence of a declining trend in Tag indicates that the effect of direct deposition was relatively small.As an additional possibility for the absence of a declining trend in tree Tag, the continuous supply of bioavailable radiocesium from the organic layer on the forest floor may affect the temporal change in Tag. Compared with the managed conditions in orchards of previous studies30,31, an organic layer develops on the soil surface in a forest and, therefore, reabsorption of radiocesium from the organic layer via the roots may be more active. Imamura et al.17 also observed a similar trend to that in the present study, namely that radiocesium concentrations in leaves of the canopies of the deciduous tree konara oak (Quercus serrata) did not show a temporal change from 2011 to 2015 in two Fukushima forests. These authors’ results included the effect of direct deposition on the tree bodies at an early stage of the accident, although the emergence of leaves was after the deposition. Nevertheless, a clear decreasing trend in the radiocesium concentration was not observed, which implies that a deciduous tree actively absorbs radiocesium via the roots in Fukushima forests, and a sufficient amount of radiocesium is absorbed to conceal a decline at an early stage owing to the effect of direct deposition.Single exponential fitted lines for each species are shown in Fig. 3. The estimated parameters and the Teff (year) calculated with Eq. (2) in “Methods” section are presented in Table 2. The Teff for Tag values that showed a decreasing trend was approximately 2 years, except for bamboo shoot. Tagami and Uchida10 reported that the Teff of the slow loss component for three edible wild plants of deciduous perennial spermatophytes was 970–3830 days. The 137Cs decline in pteridophytes, and deciduous shrub and herbaceous species on the floor of European forests was reported to be 1.2–8 years for Teff excluding the rapid loss component after the Chernobyl nuclear accident32. The present results are thus within the range of previous studies.Table 2 Estimated parameters and standard errors for correlations of Tag (m2/kg-FM) in the period 2012–2019 with time (day) calculated using Eq. (3) and effective half-lives [Teff, (year)] calculated using Eq. (2) for 11 parts of 10 edible wild plant species. A0 is estimated initial Tag, and λ (/day) is the 137Cs loss rate in edible parts of the plants.Full size tableFor bamboo shoot, applying a single exponential function, a relatively long Teff of 8.3 years was estimated. The Tag decreased between 2012 and 2014, and thereafter no notable change was observed. This observation may reflect the effect of rapid and a slow loss components. Indeed, we applied a two-component exponential function for bamboo shoot, and observed Teff of 0.7 years and − 7.8 years for the rapid and slow loss components, respectively. For edible wild tree species, statistically significant single exponential fitted lines were not observed, which reflected the absence of change in Tag with time, as discussed above in this section.The Tag varied for all species, varying by 1–3 orders of magnitude within a year that included more than two detections (Fig. 3, Supplemental Table 1). As demonstrated in previous studies5, the present study also showed substantial variation in Tag values, which may be for several reasons. Recently, Tagami et al.12 calculated Tag using the radiocesium concentration in edible wild plants measured by local municipalities from higher-resolution publicly available data (accurate to district level) for giant butterbur, bamboo shoot, fatsia sprout, and koshiabura. The municipalities in these authors’ study are located within the present study area. These authors’ results differed in being one or two orders of magnitude smaller than the present results. The lower resolution of the present deposition data may be one of the causes of the greater Tag variation. The other source of variation is the site dependency of radiocesium absorption by edible wild plants from the soil as described above. Clarification of factors that contribute to the variation in Tag other than 137Cs deposition, and its trends consistent with species, is necessary, which will decrease uncertainty and lead to more accurate estimation of Tag of 137Cs with wild plants.Summary of T
    ag for estimation of long-term ingestion dose to the publicTo estimate long-term potential ingestion dose to the public, Tag with small temporal variability excluding high values at the early stage after the accident is required. However, for the edible wild plant species in the present study, no Tag information in an equilibrium condition from before the Fukushima accident is available. Therefore, average values of Tag for the period after the decrease in Tag has weakened and a certain number of samples is available would be appropriate. The Teff for Tag showing a decreasing trend was approximately 2 years except for bamboo shoot, which has not shown any temporal variation since 2014. The Tag for the other species, udo, uwabamisou, momijigasa, fatsia sprout, koshiabura and Japanese royal fern, has not shown temporal variation throughout 2012–2019 (see the “Results and discussion” section Temporal change in Tag). Therefore, Tag values since 2014 are applicable for estimation of long-term potential ingestion dose to the public. The GMs and GSDs of the Tag values for 2014–2019 for each species are shown in Table 3 listed in order of decreasing GM.Table 3 Aggregated transfer factor (m2/kg-FM) calculated from publicly available data for 2014–2019 for 11 parts of 10 edible wild plant species.Full size tableSignificant differences in Tag were observed among the species (one-way ANOVA with Tukey’s post hoc test, p  More

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    An intergenerational approach to parasitoid fitness determined using clutch size

    Quicke, D. L. Parasitic Wasps (Chapman & Hall Ltd., 1997).
    Google Scholar 
    Godfray, H. C. J. Parasitoids: Behavioral and Evolutionary Ecology (Princeton University Press, 1994).
    Google Scholar 
    Mayhew, P. J. & van Alphen, J. J. M. Gregarious development in alysiine parasitoids evolved through a reduction in larval aggression. Anim. Behav. 58 , 131–141 (1999).Mayhew, P. J. & Hardy, I. C. W. Nonsiblicidal behavior and the evolution of clutch size in bethylid wasps. Am. Nat. 151, 409–424 (1998).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Schmidt, J. M. & Smith, J. J. B. Correlations between body angles and substrate curvature in the parasitoid wasp Trichogramma minutum: A possible mechanism of host radius measurement. J. Exp. Biol. 125, 271–285 (1986).
    Google Scholar 
    Boivin, G. & Baaren, J. The role of larval aggression and mobility in the transition between solitary and gregarious development in parasitoid wasps. Ecol. Lett. 3, 469–474 (2000).
    Google Scholar 
    Rosenheim, J. A., Wilhoit, L. R. & Armer, C. A. Influence of intraguild predation among generalist insect predators on the suppression of an herbivore population. Oecologia 96, 439–449 (1993).ADS 
    PubMed 

    Google Scholar 
    Mayhew, P. J. The evolution of gregariousness in parasitoid wasps. Proc. R. Soc. Lond. B Biol. 265, 383–389 (1998).
    Google Scholar 
    Harvey, P. H. & Partridge, L. Murderous mandibles and black holes in hymenopteran wasps. Nature 326, 128–129 (1987).ADS 

    Google Scholar 
    Pexton, J. J. & Mayhew, P. J. Competitive interactions between parasitoid larvae and the evolution of gregarious development. Oecologia 141, 179–190 (2004).ADS 
    PubMed 

    Google Scholar 
    Pexton, J. J. & Mayhew, P. J. Immobility: The key to family harmony? Trends Ecol. Evol. 16, 7–9 (2001).CAS 
    PubMed 

    Google Scholar 
    Godfray, H. C. J. The evolution of clutch size in parasitic wasps. Am. Nat. 129, 221–233 (1987).
    Google Scholar 
    Laing, J. E. & Corrigan, J. E. Intrinsic competition between the gregarious parasite, Cotesia glomeratus and the solitary parasite Cotesia rubecula (Hymenoptera: Braconidae) for their host Artogeia rapae (Lepidoptera: Pieridae). Entomophaga 32, 493–501 (1987).
    Google Scholar 
    Pexton, J. J. & Mayhew, P. J. Clutch size adjustment, information use and the evolution of gregarious development in parasitoid wasps. Behav. Ecol. Soc. 58, 99–110 (2005).
    Google Scholar 
    Reitz, S. R. & Adler, P. H. Fecundity and oviposition of Eucelatoria bryani, a gregarious parasitoid of Helicoverpa zea and Heliothis virescens. Entomol. Exp. Appl. 75, 175–181 (1995).
    Google Scholar 
    Wei, K., Tang, Y. L., Wang, X. Y., Cao, L. M. & Yang, Z. Q. The developmental strategies and related profitability of an idiobiont ectoparasitoid Sclerodermus pupariae vary with host size. Ecol. Entomol. 39, 101–108 (2014).
    Google Scholar 
    van Alphen, J. J. M. & Visser, M. E. Superparasitism as an adaptive strategy for insect parasitoids. Ann. Rev. Entomol. 35, 59–79 (1990).
    Google Scholar 
    Mayhew, P. J. & Glaizot, O. Integrating theory of clutch size and body size evolution for parasitoids. Oikos 92, 372–376 (2001).
    Google Scholar 
    Samková, A., Hadrava, J., Skuhrovec, J. & Janšta, P. Reproductive strategy as a major factor determining female body size and fertility of a gregarious parasitoid. J. Appl. Entomol. 143, 441–450 (2019).
    Google Scholar 
    Hardy, I. C. W., Griffiths, N. T. & Godfray, H. C. J. Clutch size in a parasitoid wasp: A manipulation experiment. J. Anim. Ecol. 61, 121–129 (1992).
    Google Scholar 
    Visser, M. E. The importance of being large: The relationship between size and fitness in females of the parasitoid Aphaereta minuta (Hymenoptera: Braconidae). J. Anim. Ecol. 63, 963–978 (1994).
    Google Scholar 
    Sagarra, L. A., Vincent, C. & Stewart, R. K. Body size as an indicator of parasitoid quality in male and female Anagyrus kamali (Hymenoptera: Encyrtidae). Bull. Entomol. Res. 91, 363–367 (2001).CAS 
    PubMed 

    Google Scholar 
    Bezemer, T. M. & Mills, N. J. Clutch size decisions of a gregarious parasitoid under laboratory and field conditions. Anim. Behav. 66, 1119–1128 (2003).
    Google Scholar 
    Takagi, M. The reproductive strategy of the gregarious parasitoid, Pteromalus puparum (Hymenoptera: Pteromalidae). Oecologia 68, 1–6 (1985).ADS 
    PubMed 

    Google Scholar 
    Jervis, M. A., Ferns, P. N. & Heimpel, G. E. Body size and the timing of egg production in parasitoid wasps: A comparative analysis. Funct. Ecol. 17, 375–383 (2003).
    Google Scholar 
    Waage, J. K. & Lane, J. A. The reproductive strategy of a parasitic wasp: II. Sex allocation and local mate competition in Trichogramma evanescens. J. Anim. Ecol. 53, 417–426 (1984).
    Google Scholar 
    Waage, J. K. & Ming, N. S. The reproductive strategy of a parasitic wasp: I. Optimal progeny and sex allocation in Trichogramma evanescens. J. Anim. Ecol. 53, 401–415 (1984).
    Google Scholar 
    Rabinovich, J. E., Jorda, M. T. & Bernstein, C. Local mate competition and precise sex ratios in Telenomus fariai (Hymenoptera: Scelionidae), a parasitoid of triatomine eggs. Behav. Ecol. Sociobiol. 48, 308–315 (2000).
    Google Scholar 
    Goubault, M., Mack, A. F. & Hardy, I. C. W. Encountering competitors reduces clutch size and increases offspring size in a parasitoid with female–female fighting. Proc. R. Soc. B Biol. 274, 2571–2577 (2007).
    Google Scholar 
    Duval, J. F., Brodeur, J., Doyon, J. & Boivin, G. Impact of superparasitism time intervals on progeny survival and fitness of an egg parasitoid. Ecol. Entomol. 43, 310–317 (2018).
    Google Scholar 
    Mesterton-Gibbons, M. & Hardy, I. C. W. The influence of contests on optimal clutch size: A game–theoretic model. Proc. R. Soc. Lond. B Biol. 271, 971–978 (2004).
    Google Scholar 
    Koppik, M., Thiel, A. & Hoffmeister, T. S. Adaptive decision making or differential mortality: What causes offspring emergence in a gregarious parasitoid? Entomol. Exp. Appl. 150, 208–216 (2014).
    Google Scholar 
    Heimpel, G. E. Host–parasitoid population dynamics. In Parasitoid population biology (eds Hochberg, M. E. & Ives, A. R.) 27–40 (Princeton, 2000).
    Google Scholar 
    Zaviezo, T. & Mills, M. Factors influencing the evolution of clutch size in a gregarious insect parasitoid. J. Anim. Ecol. 69, 1047–1057 (2000).
    Google Scholar 
    Kazmer, D. J. & Luck, R. F. Field tests of the size-fitness hypothesis in the egg parasitoid Trichogramma pretiosum. Ecology 76, 412–425 (1995).
    Google Scholar 
    Segoli, M. & Rosenheim, J. A. The effect of body size on oviposition success of a minute parasitoid in nature. Ecol. Entomol. 40, 483–485 (2015).
    Google Scholar 
    Gao, S. K., Wei, K., Tang, Z. L., Wang, X. Y. & Yang, Z. Q. Effect of parasitoid density on the timing of parasitism and development duration of progeny in Sclerodermus pupariae (Hymenoptera: Bethylidae). Biol. Control 97, 57–62 (2016).
    Google Scholar 
    Anderson, R. C. & Paschke, J. D. The biology and ecology of Anaphes flavipes (Hymenoptera: Mymaridae), an exotic egg parasite of the cereal leaf beetle. Ann. Entomol. Soc. Am. 61, 1–5 (1968).
    Google Scholar 
    Hoffman, G. D. & Rao, S. Oviposition site selection on oats: The effect of plant architecture, plant and leaf age, tissue toughness, and hardness on cereal leaf beetle, Oulema melanopus. Entomol. Exp. Appl. 141, 232–244 (2011).
    Google Scholar 
    Samková, A., Hadrava, J., Skuhrovec, J. & Janšta, P. Host population density and presence of predators as key factors influencing the number of gregarious parasitoid Anaphes flavipes offspring. Sci. Rep. UK 9, 1–7 (2019).ADS 

    Google Scholar 
    Hardy, I. C. W. Sex ratio and mating structure in the parasitoid Hymenoptera. Oikos 69, 3–20 (1994).
    Google Scholar 
    Godfray, H. C. J. Models for clutch size and sex ratio with sibling interaction. Theor. Popul. Biol. 30, 215–231 (1986).MATH 

    Google Scholar 
    Hardy, I. C. W. Non-binomial sex allocation and brood sex ratio variances in the parasitoid Hymenoptera. Oikos 65, 143–158 (1992).
    Google Scholar 
    Petersen, G. & Hardy, I. C. W. The importance of being larger: Parasitoid intruder–owner contests and their implications for clutch size. Anim. Behav. 51, 1363–1373 (1996).
    Google Scholar 
    Klomp, H. & Teerink, B. J. The significance of oviposition rates in the egg parasite, Trichogramma embryophagum Htg. Arch. Neerl. Zool. 17, 350–375 (1967).
    Google Scholar 
    May, R. M., Hassell, M. P., Anderson, R. M. & Tonkyn, D. W. Density dependence in host–parasitoid models. J. Anim. Ecol. 50, 855–865 (1981).MathSciNet 

    Google Scholar 
    Hoddle, M. S., Van Driesche, R. G., Elkinton, J. S. & Sanderson, J. P. Discovery and utilization of Bemisia argentifolii patches by Eretmocerus eremicus and Encarsia formosa (Beltsville strain) in greenhouses. Entomol. Exp. Appl. 87, 15–28 (1998).
    Google Scholar 
    Samková, A., Raška, J., Hadrava, J. & Skuhrovec, J. Scarcity of hosts for gregarious parasitoids indicates an increase of individual offspring fertility by reducing their own fertility. bioRxiv https://doi.org/10.1101/2021.03.05.434037 (2021).Article 

    Google Scholar 
    van Dijken, M. J. & Waage, J. K. Self and conspecific superparasitism by the egg parasitoid Trichogramma evanescens. Entomol. Exp. Appl. 43, 183–192 (1987).
    Google Scholar 
    van de Vijver, E. et al. Inter-and intrafield distribution of cereal leaf beetle species (Coleoptera: Chrysomelidae) in Belgian winter wheat. Environ. Entomol. 48, 276–283 (2019).PubMed 

    Google Scholar 
    Samková, A., Hadrava, J., Skuhrovec, J. & Janšta, P. Host specificity of the parasitic wasp Anaphes flavipes (Hymenoptera: Mymaridae) and a new defence in its hosts (Coleoptera: Chrysomelidae: Oulema spp.). Insects 11, 175 (2020).PubMed Central 

    Google Scholar 
    Bezděk, J. & Baselga, A. Revision of western Palaearctic species of the Oulema melanopus group, with description of two new species from Europe (Coleoptera: Chrysomelidae: Criocerinae). Acta Entomol. Mus. Nat. Pragae 55, 273–304 (2015).
    Google Scholar 
    Anderson, R. C. & Paschke, J. D. Additional observations on the biology of Anaphes flavipes (Hymenoptera: Mymaridae), with special reference to the effects of temperature and superparasitism on development. Ann. Entomol. Soc. Am. 62, 1316–1321 (1969).
    Google Scholar 
    R Core Team. A Language and Environment for Statistical Computing. R Foundation for Statistical Computing (R Core Team, 2020).
    Google Scholar 
    Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015). https://CRAN.R-project.org/package=lme4. More