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    Factors influencing lion movements and habitat use in the western Serengeti ecosystem, Tanzania

    Pacifici, M., Di Marco, M. & Watson, J. E. M. Protected areas are now the last strongholds for many imperiled mammal species. Conserv. Lett. 13, 1–7 (2020).
    Google Scholar 
    Cardillo, M. et al. Human population density and extinction risk in the world’s carnivores. PLoS Biol. 2, 909–914 (2004).CAS 

    Google Scholar 
    Steffen, W., Broadgate, W., Deutsch, L., Gaffney, O. & Ludwig, C. The trajectory of the anthropocene: the great acceleration. Anthr. Rev. 2, 81–98 (2015).
    Google Scholar 
    Wolf, C. & Ripple, W. J. Range contractions of the world’s large carnivores. R. Soc. Open Sci. 4, 170052 (2017).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Wolf, C. & Ripple, W. J. Prey depletion as a threat to the world’s large carnivores. R. Soc. Open Sci. 3, 160252 (2016).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ripple, W. J. et al. Status and ecological effects of the world’s largest carnivores. Science 343, 1241484 (2014).PubMed 

    Google Scholar 
    Geldmann, J. et al. Effectiveness of terrestrial protected areas in reducing habitat loss and population declines. Biol. Conserv. 161, 230–238 (2013).
    Google Scholar 
    Benítez-López, A. et al. The impact of hunting on tropical mammal and bird populations. Science 356, 180–183 (2017).ADS 
    PubMed 

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

    Google Scholar 
    Rija, A. A., Critchlow, R., Thomas, C. D. & Beale, C. M. Global extent and drivers of mammal population declines in protected areas under illegal hunting pressure. PLoS One 15, 1–14 (2020).
    Google Scholar 
    Bamford, A. J., Ferrol-Schulte, D. & Wathan, J. Human and wildlife usage of a protected area buffer zone in an area of high immigration. Oryx 48, 504–513 (2014).
    Google Scholar 
    Snyder, K. D., Mneney, P. B. & Wittemyer, G. Predicting the risk of illegal activity and evaluating law enforcement interventions in the western Serengeti. Conserv. Sci. Pract. 1, 1–13 (2019).
    Google Scholar 
    Woodroffe, R. & Ginsberg, J. R. Edge effects and the extinction of populations inside protected areas. Science 280, 2126–2128 (1998).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Lynagh, F. M. & Urich, P. B. A critical review of buffer zone theory and practice: A Philippine case study. Soc. Nat. Resour. 15, 129–145 (2002).
    Google Scholar 
    Paolino, R. M. et al. Buffer zone use by mammals in a Cerrado protected area. Biota Neotrop. 16, (2016).
    Mills, K. L. et al. Comparable space use by lions between hunting concessions and national parks in West Africa. J. Appl. Ecol. 57, 975–984 (2020).ADS 

    Google Scholar 
    Lindsey, P. A. et al. The performance of African protected areas for lions and their prey. Biol. Conserv. 209, 137–149 (2017).
    Google Scholar 
    Tyrrell, P., Russell, S. & Western, D. Seasonal movements of wildlife and livestock in a heterogenous pastoral landscape: Implications for coexistence and community based conservation. Glob. Ecol. Conserv. 12, 59–72 (2017).
    Google Scholar 
    Veldhuis, M. P. et al. Cross-boundary human impacts compromise the Serengeti-Mara ecosystem. Science 363, 1424–1428 (2019).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Everatt, K. T., Andresen, L. & Somers, M. J. The influence of prey, pastoralism and poaching on the hierarchical use of habitat by an apex predator. Afr. J. Wildl. Res. 45, 187–196 (2015).
    Google Scholar 
    Oriol-Cotterill, A., Macdonald, D. W., Valeix, M., Ekwanga, S. & Frank, L. G. Spatiotemporal patterns of lion space use in a human-dominated landscape. Anim. Behav. 101, 27–39 (2015).
    Google Scholar 
    Schuette, P., Creel, S. & Christianson, D. Coexistence of African lions, livestock, and people in a landscape with variable human land use and seasonal movements. Biol. Conserv. 157, 148–154 (2013).
    Google Scholar 
    Beattie, K., Olson, E. R., Kissui, B., Kirschbaum, A. & Kiffner, C. Predicting livestock depredation risk by African lions (Panthera leo) in a multi-use area of northern Tanzania. Eur. J. Wildl. Res. 66, 1–4 (2020).
    Google Scholar 
    Loveridge, A. J., Hemson, G., Davidson, Z. & Macdonald, D. W. African lions on the edge: Reserve boundaries as ‘attractive sinks’. In Biology and Conservation of Wild Felids (eds. Macdonald, D. W. & Loveridge, A. J.) 283–304 (Oxford University Press, 2010).Boyers, M., Parrini, F., Owen-Smith, N., Erasmus, B. F. N. & Hetem, R. S. How free-ranging ungulates with differing water dependencies cope with seasonal variation in temperature and aridity. Conserv. Physiol. 7, 1–12 (2019).
    Google Scholar 
    Abade, L. et al. The relative effects of prey availability, anthropogenic pressure and environmental variables on lion (Panthera leo) site use in Tanzania’s Ruaha landscape during the dry season. J. Zool. 310, 135–144 (2020).
    Google Scholar 
    Hopcraft, J. G. C., Sinclair, A. R. E. & Packer, C. Planning for success: Serengeti lions seek prey accessibility rather than abundance. J. Anim. Ecol. 74, 559–566 (2005).
    Google Scholar 
    Treves, A. & Karanth, K. U. Human-carnivore conflict and perspectives on carnivore management worldwide. Conserv. Biol. 17, 1491–1499 (2003).
    Google Scholar 
    Kisingo, A. W. Governance of Protected Areas in the Serengeti Ecosystem, Tanzania (University of Victoria, 2013).UNEP-WCMC & IUCN. Protected planet: the world database on protected areas (WDPA). www.protectedplanet.net (2020).Zella, A. Y. The management of protected areas in Serengeti ecosystem: A case study of Ikorongo and Grumeti Game Reserves (IGGRs). Int. J. Eng. Sci. 6, 22–50 (2016).
    Google Scholar 
    IUCN. Ngorongoro Conservation Area conservation outlook assessment. The IUCN World Heritage Outlook https://worldheritageoutlook.iucn.org/explore-sites/wdpaid/2010 (2020).Kittle, A. M., Bukombe, J. K., Sinclair, A. R. E., Mduma, S. A. R. & Fryxell, J. M. Landscape-level movement patterns by lions in western Serengeti: Comparing the influence of inter-specific competitors, habitat attributes and prey availability. Mov. Ecol. 4, 1–18 (2016).
    Google Scholar 
    Packer, C. et al. Ecological change, group territoriality, and population dynamics in Serengeti lions. Science 307, 390–393 (2005).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Mwampeta, S. B. et al. Lion and spotted hyena distributions within a buffer area of the Serengeti-Mara ecosystem. Sci. Rep. 11, 1–8 (2021).
    Google Scholar 
    Grumeti Fund. Protecting wildlife and human lives in the western corridor of the Serengeti. https://www.grumetifund.org/blog/updates/protecting-wildlife-and-human-lives-in-the-western-corridor-of-the-serengeti/ (2020).IUCN. Serengeti National Park conservation outlook assessment. The IUCN World Heritage Outlook https://worldheritageoutlook.iucn.org/explore-sites/wdpaid/2575 (2017).Veldhuis, M. P. et al. Data from: Cross-boundary human impacts compromise the Serengeti-Mara ecosystem. Dryad https://doi.org/10.5061/dryad.b303788 (2021).Larsen, F. et al. Wildebeest migration drives tourism demand in the Serengeti. Biol. Conserv. 248, 108688 (2020).
    Google Scholar 
    Norton-Griffiths, M., Herlocker, D. & Pennycuick, L. The patterns of rainfall in the Serengeti Ecosystem, Tanzania. Afr. J. Ecol. 13, 347–374 (1975).
    Google Scholar 
    McNaughton, S. J. Serengeti grassland ecology: The role of composite environmental factors and contingency in community organization. Ecol. Monogr. 53, 291–320 (1983).
    Google Scholar 
    Buchhorn, M. et al. Copernicus global land service: land cover 100m: version 3 globe 2015-2019. Copernicus Global Land Operations. Zenodo. https://doi.org/10.5281/zenodo.3938963.Boone, R. B., Thirgood, S. J. & Hopcraft, J. G. C. Serengeti wildebeest migratory patterns modeled from rainfall and new vegetation growth. Ecology 87, 1987–1994 (2006).PubMed 

    Google Scholar 
    Ogutu, J. O. & Dublin, H. T. The response of lions and spotted hyaenas to sound playbacks as a technique for estimating population size. Afr. J. Ecol. 36, 83–95 (1998).
    Google Scholar 
    Fyumagwa, R. D. et al. Comparison of anaesthesia and cost of two immobilization protocols in free-ranging lions. S. Afr. J. Wildl. Res. 42, 67–70 (2012).
    Google Scholar 
    Rija, A. A. Spatial Pattern of Illegal Activities and the Impact on Wildlife Populations in Protected Areas in the Serengeti Ecosystem. (University of York, 2017).Kideghesho, J. R. Wildlife Conservation and Local Land Use Conflicts in Western Serengeti Corridor, Tanzania (Norwegian University of Science and Technology, 2006).Holmern, T., Muya, J. & Røskaft, E. Local law enforcement and illegal bushmeat hunting outside the Serengeti National Park, Tanzania. Environ. Conserv. 34, 55–63 (2007).
    Google Scholar 
    Schmitt, J. A. Improving Conservation Efforts in the Serengeti Ecosystem, Tanzania: An Examination of Knowledge, Benefits, Costs, and Attitudes (University of Minnesota, 2010).Kaaya, E. & Chapman, M. Micro-credit and community wildlife management: Complementary strategies to improve conservation outcomes in Serengeti National Park, Tanzania. Environ. Manag. 60, 464–475 (2017).ADS 

    Google Scholar 
    Kideghesho, J. R., Røskaft, E. & Kaltenborn, B. P. Factors influencing conservation attitudes of local people in Western Serengeti, Tanzania. Biodivers. Conserv. 16, 2213–2230 (2007).
    Google Scholar 
    Kegamba, J. J., Sangha, K. K., Wurm, P. & Garnett, S. T. A review of conservation-related benefit-sharing mechanisms in Tanzania. Glob. Ecol. Conserv. 33, e01955 (2022).
    Google Scholar 
    Rija, A. A. & Kideghesho, J. R. Poachers’ strategies to surmount anti-poaching efforts in Western Serengeti, Tanzania. In Protected Areas in Northern Tanzania (eds. Durrant, J. O. et al.) 91–112 (Springer Nature Switzerland AG, 2020).Mfunda, I. M. & Røskaft, E. Wildlife or crop production: The dilemma of conservation and human livelihoods in Serengeti, Tanzania. Int. J. Biodivers. Sci. Ecosyst. Serv. Manag. 7, 39–49 (2011).
    Google Scholar 
    Kideghesho, J. R. Reversing the trend of wildlife crime in Tanzania: Challenges and opportunities. Biodivers. Conserv. 25, 427–449 (2016).
    Google Scholar 
    Sisya, E., Frankfurt Zoological Society & Tanzania National Parks Authority. Serengeti Park Roads. Serengeti GIS and Data Centre and ArcGIS Online. ArcGIS online https://www.arcgis.com/home/item.html?id=f8d9e2cb6ab24b92bd6d645a0d659963. (2018).Maliti, H., von Hagen, C., Frankfurt Zoological Society, Tanzania National Parks Authority & Hopcraft, J. G. C. Serengeti Park rivers. https://serengetidata.weebly.com/rivers-and-lakes.html (2008).Worldpop & Center for International Earth Science Information Network. The spatial distribution of population density in 2018, Tanzania. https://doi.org/10.5258/SOTON/WP00674 (2018).Gilbert, M. et al. Global cattle distribution in 2010 (5 minutes of arc). Harvard Dataverse, Version 3. https://doi.org/10.7910/DVN/GIVQ7 (2018).Gilbert, M. et al. [dataset] Global goat distribution in 2010 (5 minutes of arc). Harvard Dataverse, Version 3. https://doi.org/10.7910/DVN/OCPH42 (2018).Gilbert, M. et al. Global sheep distribution in 2010 (5 minutes of arc). Harvard Dataverse, Version 3. https://doi.org/10.7910/DVN/BLWPZN (2018).Gilbert, M. et al. Global distribution data for cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in 2010. Sci. Data 5, 1–11 (2018).
    Google Scholar 
    Swihart, R. K. & Slade, N. A. Testing for independence of observations in animal movements. Ecology 66, 1176–1184 (1985).
    Google Scholar 
    Seaman, D. E. & Powell, R. A. An evaluation of the accuracy of kernel density estimators for home range analysis. Ecology 77, 2075–2085 (1996).
    Google Scholar 
    Calenge, C. The package adehabitat for the R software: Tool for the analysis of space and habitat use by animals. Ecol. Model. 197, 516–519 (2006).
    Google Scholar 
    R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Version 4.0.4. https://www.r-project.org/ (2021).Dormann, C. F. et al. Collinearity: A review of methods to deal with it and a simulation study evaluating their performance. Ecography (Cop.) 36, 27–46 (2013).
    Google Scholar 
    Thomas, D. L. & Taylor, E. J. Study designs and tests for comparing resource use and availability II. J. Wildl. Manag. 70, 324–336 (2006).
    Google Scholar 
    Swets, J. A. Measuring the accuracy of diagnostic systems. Science 240, 1285–1293 (1988).ADS 
    MathSciNet 
    CAS 
    PubMed 
    MATH 

    Google Scholar 
    Sommer, S. & Huggins, R. M. Variables selection using the Wald test and a robust CP. J. R. Stat. Soc. 45, 15–29 (1996).MATH 

    Google Scholar 
    Burnham, K. P. & Anderson, D. D. Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach (Springer, 2002).Lenth, R. emmeans: Estimated Marginal Means, aka Least-Squares Means. (2020).Ogutu, J. O. & Dublin, H. T. Demography of lions in relation to prey and habitat in the Maasai Mara National Reserve, Kenya. Afr. J. Ecol. 40, 120–129 (2002).
    Google Scholar 
    Henschel, P. et al. Determinants of distribution patterns and management needs in a critically endangered lion (Panthera leo) population. Front. Ecol. Evol. 4, 1–14 (2016).
    Google Scholar 
    Melubo, K. & Lovelock, B. Living inside a UNESCO World Heritage Site: The perspective of the Maasai community in Tanzania. Tour. Plan. Dev. 16, 197–216 (2019).
    Google Scholar 
    Makupa, E. E. Conservation Efforts and Local Livelihoods in Western Serengeti, Tanzania: Experiences from Ikona Community Wildlife Management Area (University of Victoria, 2013).Ndibalema, V. G. & Songorwa, A. N. Illegal meat hunting in serengeti: Dynamics in consumption and preferences. Afr. J. Ecol. 46, 311–319 (2008).
    Google Scholar 
    Geldmann, J., Joppa, L. N. & Burgess, N. D. Mapping change in human pressure globally on land and within protected areas. Conserv. Biol. 28, 1604–1616 (2014).PubMed 

    Google Scholar 
    Tuqa, J. H. et al. Impact of severe climate variability on lion home range and movement patterns in the Amboseli ecosystem, Kenya. Glob. Ecol. Conserv. 2, 1–10 (2014).
    Google Scholar 
    Blackburn, S., Hopcraft, J. G. C., Ogutu, J. O., Matthiopoulos, J. & Frank, L. Human–wildlife conflict, benefit sharing and the survival of lions in pastoralist community-based conservancies. J. Appl. Ecol. 53, 1195–1205 (2016).
    Google Scholar 
    Thirgood, S. et al. Can parks protect migratory ungulates? The case of the Serengeti wildebeest. Anim. Conserv. 7, 113–120 (2004).
    Google Scholar 
    Wittemyer, G., Elsen, P., Bean, W. T., Burton, A. C. O. & Brashares, J. S. Accelerated human population growth at protected area edges. Science 321, 123–126 (2008).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Hayward, M. W. & Kerley, G. I. H. Prey preferences and dietary overlap amongst Africa’s large predators. S. Afr. J. Wildl. Res. 38, 93–108 (2008).
    Google Scholar 
    Mkonyi, F. J., Estes, A. B., Lichtenfeld, L. L. & Durant, S. M. Large carnivore distribution in relationship to environmental and anthropogenic factors in a multiple-use landscape of northern Tanzania. Afr. J. Ecol. 56, 972–983 (2018).
    Google Scholar 
    Hill, J. E., De Vault, T. L. & Belant, J. L. A review of ecological factors promoting road use by mammals. Mamm. Rev. 51, 214–227 (2021).
    Google Scholar 
    Hägerling, H. G. & Ebersole, J. J. Roads as travel corridors for mammals and ground birds in Tarangire National Park, Tanzania. Afr. J. Ecol. 55, 701–704 (2017).
    Google Scholar 
    Bateman, P. W. & Fleming, P. A. Are negative effects of tourist activities on wildlife over-reported? A review of assessment methods and empirical results. Biol. Conserv. 211, 10–19 (2017).
    Google Scholar 
    de Boer, W. F. et al. Spatial distribution of lion kills determined by the water dependency of prey species. J. Mammal. 91, 1280–1286 (2010).
    Google Scholar 
    Loveridge, A. J., Valeix, M., Elliot, N. B. & Macdonald, D. W. The landscape of anthropogenic mortality: How African lions respond to spatial variation in risk. J. Appl. Ecol. 54, 815–825 (2017).
    Google Scholar 
    Suraci, J. P. et al. Behavior-specific habitat selection by African lions may promote their persistence in a human-dominated landscape. Ecology 100, 1–11 (2019).
    Google Scholar 
    Snyman, A., Raynor, E., Chizinski, C., Powell, L. & Carroll, J. African lion (Panthera leo) space use in the Greater Mapungubwe Transfrontier Conservation Area. Afr. J. Wildl. Res. 48, 023001 (2018).
    Google Scholar 
    Mwakaje, A. G. et al. Community-based conservation, income governance, and poverty alleviation in Tanzania: The case of the Serengeti Ecosystem. J. Environ. Dev. 22, 51–73 (2013).
    Google Scholar 
    Everatt, K. T., Moore, J. F. & Kerley, G. I. H. Africa’s apex predator, the lion, is limited by interference and exploitative competition with humans. Glob. Ecol. Conserv. 20, e00758 (2019).
    Google Scholar  More

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    The diel vertical distribution and carbon biomass of the zooplankton community in the Caroline Seamount area of the western tropical Pacific Ocean

    Roemmich, D. & Mcgowan, J. Climatic warming and the decline of zooplankton in the California current. Science 267(5202), 1324–1326 (1995).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Biard, T. et al. In situ imaging reveals the biomass of giant protists in the global ocean. Nature 532, 504–507 (2016).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Irigoien, X., Huisman, J. & Harris, R. P. Global biodiversity patterns of marine phytoplankton and zooplankton. Nature 429, 863–867 (2004).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Ware, D. M. & Thomson, R. E. Bottom-up ecosystem trophic dynamics determine fish production in the Northeast Pacific. Science 308(5726), 1280–1284 (2005).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Beaugrand, G., Edwards, M. & Legendre, L. Marine biodiversity, ecosystem functioning, and carbon cycles. Proc. Natl. Acad. Sci. 107, 10120–10124 (2010).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ewald, W. F. Über Orientierung Lokomotion und Lichtreaktionen einiger Cladoceren und deren Bedeutung für die Theorie der Tropismen. Biol. Zentralblatt 30, 1–16 (1910).
    Google Scholar 
    Dam, H. G., Roman, M. R. & Youngbluth, M. J. Downward export of respiratory carbon and dissolved nitrogen by diel-migrant mesozooplankton at the JGOFS Bermuda time-series station. Deep Sea Res. Part I Oceanogr. Res. Pap. 42, 1187–1197 (1995).ADS 
    CAS 

    Google Scholar 
    Morales, C. E. Carbon and nitrogen fluxes in the ocean: the contribution by zooplankton migrants to active transport in the North Atlantic during the Joint Global Flux Study. J. Plankton Res. 21, 1799–1808 (1999).
    Google Scholar 
    Steinberg, D. K., Cope, J. S., Wilson, S. E. & Kobari, T. A comparison of mesopelagic mesozooplankton community structure in the subtropical and subarctic North Pacific Ocean. Deep Sea Res. Part II Top. Stud. Oceanogr. 55(14–15), 1615–1635 (2008).ADS 

    Google Scholar 
    Brugnano, C., Granata, A., Guglielmo, L. & Zagami, G. Spring diel vertical distribution of copepod abundances and diversity in the open Central Tyrrhenian Sea (Western Mediterranean). J. Mar. Syst. 105, 207–220 (2012).
    Google Scholar 
    Werner, T. & Buchholz, F. Diel vertical migration behaviour in Euphausiids of the northern Benguela current: seasonal adaptations to food availability and strong gradients of temperature and oxygen. J. Plankton Res. 35(4), 792–812 (2013).CAS 

    Google Scholar 
    Palmer, M. R. & Pearson, P. N. A 23,000-year record of surface water pH and PCO2 in the western equatorial Pacific Ocean. Science 300(5618), 480–482 (2003).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Collins, M. et al. The impact of global warming on the tropical Pacific Ocean and El Nino. Nat. Geosci. 3(6), 391–397 (2010).ADS 
    CAS 

    Google Scholar 
    Hu, D. et al. Pacific western boundary currents and their roles in climate. Nature 522, 299–308 (2015).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Epp, D. & Smoot, N. C. Distribution of seamounts in the North Atlantic. Nature 337, 254–257 (1989).ADS 

    Google Scholar 
    Yesson, C., Clark, M. R., Taylor, M. L. & Rogers, A. D. The global distribution of seamounts based on 30 arc seconds bathymetry data. Deep Sea Res. Part I Oceanogr. Res. Pap. 58(4), 442–453 (2011).ADS 

    Google Scholar 
    Rogers, A. D. The biology of seamounts: 25 Years on. Adv. Mar. Biol. 79, 137–224 (2018).PubMed 

    Google Scholar 
    Rowden, A. A., Dower, J. F., Schlacher, T. A., Consalvey, M. & Clark, M. R. Paradigms in seamount ecology: fact, fiction and future. Mar. Ecol. 31, 226–241 (2010).ADS 

    Google Scholar 
    Wilson, R. R. & Kaufmann, R. S. Seamount biota and biogeography. Geophys. Monogr. Ser. 43, 355–377 (2013).ADS 

    Google Scholar 
    Clark, M. R., Schlacher, T. A., Rowden, A. A., Stocks, K. I. & Consalvey, M. Science priorities for seamounts: research links to conservation and management. PLoS ONE 7(1), e29232 (2012).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Schlacher, T. A., Rowden, A. A., Dower, J. F. & Consalvey, M. Seamount science scales undersea mountains: new research and outlook. Mar. Ecol. 31, 1–13 (2010).ADS 

    Google Scholar 
    Stocks, K. I. et al. CenSeam, an international program on seamounts within the census of marine life: achievements and lessons learned. PLoS ONE 7(2), e32031 (2012).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Cascao, I., Domokos, R., Lammers, M. O., Santos, R. S. & Silva, M. A. Seamount effects on the diel vertical migration and spatial structure of micronekton. Prog. Oceanogr. 175, 1–13 (2019).ADS 

    Google Scholar 
    Denda, A., Stefanowitsch, B. & Christiansen, B. From the epipelagic zone to the abyss: trophic structure at two seamounts in the subtropical and tropical Eastern Atlantic – Part II Benthopelagic fishes. Deep Sea Res I Oceanogr. Res. Pap. 130, 78–92 (2017).ADS 
    CAS 

    Google Scholar 
    Dai, L. et al. Zooplankton abundance, biovolume and size spectra down to 3000 m depth in the western tropical North Pacific during autumn 2014. Deep Sea Res. Part I Oceanogr. Res. Pap. 121, 1–13 (2017).ADS 

    Google Scholar 
    Sun, D., Zhang, D. S., Zhang, R. Y. & Wang, C. S. Different vertical distribution of zooplankton community between North Pacific Subtropical Gyre and Western Pacific Warm Pool: its implication to carbon flux. Acta Oceanol. Sin. 38(6), 32–45 (2019).CAS 

    Google Scholar 
    Behrenfeld, M. J. et al. Global satellite-observed daily vertical migrations of ocean animals. Nature 576, 257–261 (2019).CAS 
    PubMed 

    Google Scholar 
    Haury, L., Fey, C., Newland, C. & Genin, A. Zooplankton distribution around four eastern North Pacific seamounts. Prog. Oceanogr. 45(1), 69–105 (2000).ADS 

    Google Scholar 
    Genin, A. Bio-physical coupling in the formation of zooplankton and fish aggregations over abrupt topographies. J. Mar. Syst. 50(1–2), 3–20 (2004).
    Google Scholar 
    Valle-Levinson, A., Castro, A. T., de Velasco, G. G. & Armas, R. G. Diurnal vertical motions over a seamount of the southern Gulf of California. J. Mar. Syst. 50(1–2), 61–77 (2004).
    Google Scholar 
    Martin, B. & Christiansen, B. Distribution of zooplankton biomass at three seamounts in the NE Atlantic. Deep Sea Res. Part II Top. Stud. Oceanogr. 56, 2671–2682 (2009).ADS 
    CAS 

    Google Scholar 
    Rawlinson, K. A., Davenport, J. & Barnes, D. K. A. Vertical migration strategies with respect to advection and stratification in a semi-enclosed lough: a comparison of mero- and holozooplankton. Mar. Biol. 144, 935–946 (2004).
    Google Scholar 
    Forward, R. B. Diel vertical migration: zooplankton photobiology and behaviour. Oceanogr. Mar. Biol. Ann. Rev. 26, 361–393 (1988).
    Google Scholar 
    Tao, Z. C., Wang, Y. Q., Wang, J. J., Liu, M. T. & Zhang, W. C. Photobehaviors of the calanoid copepod Calanus sinicus from the Yellow Sea to visible and UV-B radiation as a function of wavelength and intensity. J. Oceanol. Limnol. 37(4), 1289–1300 (2019).ADS 

    Google Scholar 
    Fragopoulu, N. & Lykakis, J. J. Vertical distribution and nocturnal migration of zooplankton in relation to the development of the seasonal thermocline in Patraikos Gulf. Mar. Biol. 104(3), 381–387 (1990).
    Google Scholar 
    Lougee, L. A., Bollens, S. M. & Avent, S. R. The effects of haloclines on the vertical distribution and migration of zooplankton. J. Exp. Mar. Biol. Ecol. 278(2), 111–134 (2002).
    Google Scholar 
    Saltzman, J. & Wishner, K. F. Zooplankton ecology in the eastern tropical Pacific oxygen minimum zone above a seamount: 2. Vertical distribution of copepods. Deep Sea Res. Part I Oceanogr. Res. Pap. 44(6), 931–954 (1997).ADS 
    CAS 

    Google Scholar 
    Antezana, T. Species-specific patterns of diel migration into the oxygen minimum zone by euphausiids in the Humboldt Current Ecosystem. Prog. Oceanogr. 83, 228–236 (2009).ADS 

    Google Scholar 
    Johnsen, G. H. & Jakobsen, P. J. The effect of food limitation on vertical migration in Daphnia longispina. Limnol. Oceanogr. 32(4), 873–880 (1987).ADS 

    Google Scholar 
    Spinelli, M. et al. Diel vertical distribution of the larvacean Oikopleura dioica in a North Patagonian tidal frontal system (42 degrees-45 degrees S) of the SW Atlantic Ocean. Mar. Biol. Res. 11(6), 633–643 (2015).
    Google Scholar 
    Guillam, M. et al. Vertical distribution of brittle star larvae in two contrasting coastal embayments: implications for larval transport. Sci. Rep. 10(1), 1–5 (2020).
    Google Scholar 
    Stramma, L. et al. Expansion of oxygen minimum zones may reduce available habitat for tropical pelagic fishes. Nat. Clim. Change 2(1), 33–37 (2012).ADS 
    CAS 

    Google Scholar 
    Ma, J. et al. The OMZ and its influence on POC in the Tropical Western Pacific Ocean: based on the survey in March 2018. Front. Earth Sci. 9, 632229 (2021).
    Google Scholar 
    Sun, Q. Q., Song, J. M., Li, X. G., Yuan, H. M. & Wang, Q. D. The bacterial diversity and community composition altered in the oxygen minimum zone of the Tropical Western Pacific Ocean. J. Oceanol. Limnol. 39(5), 1690–1704 (2021).ADS 
    CAS 

    Google Scholar 
    Wang, Q. D. et al. Characteristics and biogeochemical effects of oxygen minimum zones in typical seamount areas, Tropical Western Pacific. J. Oceanol. Limnol. 39(5), 1651–1661 (2021).ADS 
    CAS 

    Google Scholar 
    Fernández-Álamo, M. A. & Färber-Lorda, J. Zooplankton and the oceanography of the eastern tropical Pacific: a review. Prog. Oceanogr. 69(2–4), 318–359 (2006).ADS 

    Google Scholar 
    Wishner, K. F., Gowing, M. M. & Gelfman, C. Living in suboxia: Ecology of an Arabian Sea oxygen minimum zone copepod. Limnol. Oceanogr. 45(7), 1576–1593 (2000).ADS 

    Google Scholar 
    Wishner, K. F. et al. Vertical zonation and distributions of calanoid copepods through the lower oxycline of the Arabian Sea oxygen minimum zone. Prog. Oceanogr. 78(2), 163–191 (2008).ADS 

    Google Scholar 
    Ekau, W., Auel, H., Portner, H. O. & Gilbert, D. Impacts of hypoxia on the structure and processes in pelagic communities (zooplankton, macro-invertebrates and fish). Biogeosciences 7(5), 1669–1699 (2010).ADS 
    CAS 

    Google Scholar 
    Hernández-León, S. et al. Zooplankton and micronekton active flux across the tropical and subtropical Atlantic Ocean. Front. Mar. Sci. 6, 535 (2019).
    Google Scholar 
    Steinberg, D. K. & Landry, M. R. Zooplankton and the ocean carbon cycle. Ann. Rev. Mar. Sci. 9, 413–444 (2017).PubMed 

    Google Scholar 
    Le Borgne, R. & Rodier, M. Net zooplankton and the biological pump: a comparison between the oligotrophic and mesotrophic equatorial Pacific. Deep Sea Res. Part II Top. Stud. Oceanogr. 44, 2003–2023 (1997).ADS 

    Google Scholar 
    Al-Mutairi, H. & Landry, M. R. Active export of carbon and nitrogen at Station ALOHA by diel migrant zooplankton. Deep Sea Res. Part II Top. Stud. Oceanogr. 48, 2083–2103 (2001).ADS 
    CAS 

    Google Scholar 
    Ge, R., Chen, H., Zhuang, Y. & Liu, G. Active carbon flux of mesozooplankton in South China Sea and Western Philippine Sea. Front. Mar. Sci. 8, 1324 (2021).
    Google Scholar 
    Steinberg, D. K. et al. Bacterial vs. zooplankton control of sinking particle flux in the ocean’s twilight zone. Limnol. Oceanogr. 53(4), 1327–1338 (2008).ADS 

    Google Scholar 
    Hirch, S., Martin, B. & Christiansen, B. Zooplankton metabolism and carbon demand at two seamounts in the NE Atlantic. Deep Sea Res. Part II Top. Stud. Oceanogr. 56(25), 2656–2670 (2009).ADS 
    CAS 

    Google Scholar 
    Denda, A. & Christiansen, B. Zooplankton distribution patterns at two seamounts in the subtropical and tropical NE Atlantic. Mar. Ecol. 35(2), 159–179 (2014).ADS 

    Google Scholar 
    Dower, J. F. & Mackas, D. L. “Seamount effects” in the zooplankton community near Cobb Seamount. Deep Sea Res. Part I Oceanogr. Res. Pap. 43, 837–858 (1996).ADS 

    Google Scholar 
    Ma, J. et al. Analysis of differences in nutrients chemistry in seamount seawaters in the Kocebu and M5 seamounts in Western Pacific Ocean. J. Oceanol. Limnol. 39(5), 1662–1674 (2021).ADS 

    Google Scholar 
    Denda, A., Mohn, C., Wehrmann, H. & Christiansen, B. Microzooplankton and meroplanktonic larvae at two seamounts in the subtropical and tropical NE Atlantic. J. Mar. Biol. Assoc. U. K. 97(1), 1–27 (2017).
    Google Scholar 
    Tutasi, P. & Escribano, R. Zooplankton diel vertical migration and downward C flux into the oxygen minimum zone in the highly productive upwelling region off northern Chile. Biogeosciences 17(2), 455–473 (2020).ADS 
    CAS 

    Google Scholar 
    Harris, R., Wiebe, P., Lenz, J., Skjoldal, H. R. & Huntley, M. ICES Zooplankton Methodology Manual (Academic Press, 2000).
    Google Scholar 
    Zhang, X. & Dam, H. G. Downward export of carbon by diel migrant mesozooplankton in the central equatorial Pacific. Deep Sea Res. Part II Top. Stud. Oceanogr. 44, 2191–2202 (1997).ADS 
    CAS 

    Google Scholar 
    Isla, A., Scharek, R. & Latasa, M. Zooplankton diel vertical migration and contribution to deep active carbon flux in the NW Mediterranean. J. Mar. Syst. 143, 86–97 (2015).
    Google Scholar 
    Ikeda, T. Respiration and ammonia excretion by marine metazooplankton taxa: synthesis toward a global-bathymetric model. Mar. Biol. 161(12), 2753–2766 (2014).CAS 

    Google Scholar 
    Steinberg, D. K. et al. Zooplankton vertical migration and the active transport of dissolved organic and inorganic carbon in the Sargasso Sea. Deep Sea Res. Part I Oceanogr. Res. Pap. 47(1), 137–158 (2000).ADS 
    CAS 

    Google Scholar 
    Andersen, V. et al. Vertical distributions of zooplankton across the Almeria-Oran frontal zone (Mediterranean Sea). J. Plankton Res. 26(3), 275–293 (2004).
    Google Scholar  More

  • in

    Long term environmental variability modulates the epigenetics of maternal traits of kelp crabs in the coast of Chile

    Gibney, E. R. & Nolan, C. M. Epigenetics and gene expression. Heredity 105, 4–13 (2010).CAS 
    PubMed 

    Google Scholar 
    Vogt, G. Facilitation of environmental adaptation and evolution by epigenetic phenotype variation: Insights from clonal, invasive, polyploid, and domesticated animals. Environ. Epigenet. 3, 1–17 (2017).
    Google Scholar 
    Beal, A., Rodriguez-Casariego, J., Rivera-Casas, C., Suarez-Ulloa, V. & Eirin-Lopez, J. M. Environmental Epigenomics and Its Applications in Marine Organisms 325–359 (Springer, 2018). https://doi.org/10.1007/13836_2018_28.Book 

    Google Scholar 
    Hofmann, G. E. Ecological epigenetics in marine metazoans. Front. Mar. Sci. 4, 1–7 (2017).CAS 

    Google Scholar 
    Richards, C. L. et al. Ecological plant epigenetics: Evidence from model and non-model species, and the way forward. Ecol. Lett. 20, 1576–1590 (2017).PubMed 

    Google Scholar 
    Ryu, T., Veilleux, H. D., Donelson, J. M., Munday, P. L. & Ravasi, T. The epigenetic landscape of transgenerational acclimation to ocean warming. Nat. Clim. Chang. 8, 504–509 (2018).ADS 

    Google Scholar 
    Liew, Y. J. et al. Epigenome-associated phenotypic acclimatization to ocean acidification in a reef-building coral. Sci. Adv. 4, 6 (2018).
    Google Scholar 
    Anastasiadi, D., Díaz, N. & Piferrer, F. Small ocean temperature increases elicit stage-dependent changes in DNA methylation and gene expression in a fish, the European sea bass. Sci. Rep. 7, 1–12 (2017).CAS 

    Google Scholar 
    Strader, M. E., Wong, J. M., Kozal, L. C., Leach, T. S. & Hofmann, G. E. Parental environments alter DNA methylation in offspring of the purple sea urchin, Strongylocentrotus purpuratus. J. Exp. Mar. Bio. Ecol. 517, 54–64 (2019).
    Google Scholar 
    Rey, O. et al. Linking epigenetics and biological conservation: Towards a conservation epigenetics perspective. Funct. Ecol. 34, 414–427 (2020).
    Google Scholar 
    Eirin-Lopez, J. M. & Putnam, H. Editorial: Marine environmental epigenetics. Front. Mar. Sci. 8, 5 (2021).
    Google Scholar 
    Herrera, C. M. & Bazaga, P. Untangling individual variation in natural populations: Ecological, genetic and epigenetic correlates of longterm inequality in herbivory. Mol. Ecol. 20, 1675–1688 (2011).CAS 
    PubMed 

    Google Scholar 
    Varriale, A. DNA methylation, epigenetics, and evolution in vertebrates: Facts and challenges. Int. J. Evol. Biol. 2014, 1–7 (2014).
    Google Scholar 
    Liebl, A. L., Wesner, J. S., Russell, A. F. & Schrey, A. W. Methylation patterns at fledging predict delayed dispersal in a cooperatively breeding bird. PLoS ONE 16, e0252227 (2021).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Metzger, D. C. H. & Schulte, P. M. Persistent and plastic effects of temperature on DNA methylation across the genome of threespine stickleback (Gasterosteus aculeatus). Proc. R. Soc. B Biol. Sci. 284, 5 (2017).
    Google Scholar 
    Putnam, H. M., Davidson, J. M. & Gates, R. D. Ocean acidification influences host DNA methylation and phenotypic plasticity in environmentally susceptible corals. Evol. Appl. 9, 1165–1178 (2016).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Watson, R. G. A., Baldanzi, S., Pérez-Figueroa, A., Gouws, G. & Porri, F. Morphological and epigenetic variation in mussels from contrasting environments. Mar. Biol. 165, 8 (2018).
    Google Scholar 
    Baldanzi, S., Watson, R., McQuaid, C. D., Gouws, G. & Porri, F. Epigenetic variation among natural populations of the South African sandhopper Talorchestia capensis. Evol. Ecol. 31, 77–91 (2017).
    Google Scholar 
    Ardura, A., Zaiko, A., Morán, P., Planes, S. & Garcia-Vazquez, E. Epigenetic signatures of invasive status in populations of marine invertebrates. Sci. Rep. 7, 5 (2017).
    Google Scholar 
    Baldanzi, S., Storch, D., Navarrete, S. A., Graeve, M. & Fernández, M. Latitudinal variation in maternal investment traits of the kelp crab Taliepus dentatus along the coast of Chile. Mar. Biol. 165, 1 (2018).
    Google Scholar 
    Sobarzo, M., Bravo, L., Donoso, D., Garcés-Vargas, J. & Schneider, W. Coastal upwelling and seasonal cycles that influence the water column over the continental shelf off central Chile. Prog. Oceanogr. 75, 363–382 (2007).ADS 

    Google Scholar 
    Letelier, J., Pizarro, O. & Nuñez, S. Seasonal variability of coastal upwelling and the upwelling front off central Chile. J. Geophys. Res. Ocean. 114, 12009 (2009).ADS 

    Google Scholar 
    Vargas, C. A. et al. Species-specific responses to ocean acidification should account for local adaptation and adaptive plasticity. Nat. Ecol. Evol. 1, 1–7 (2017).CAS 

    Google Scholar 
    Pérez, C. A. et al. Influence of climate and land use in carbon biogeochemistry in lower reaches of rivers in central southern Chile: Implications for the carbonate system in river-influenced rocky shore environments. J. Geophys. Res. Biogeosciences 120, 673–692 (2015).ADS 

    Google Scholar 
    Saldías, G. S. et al. Satellite-measured interannual variability of turbid river plumes off central-southern Chile: Spatial patterns and the influence of climate variability. Prog. Oceanogr. 146, 212–222 (2016).ADS 

    Google Scholar 
    Lara, C. et al. Coastal biophysical processes and the biogeography of rocky intertidal species along the south-eastern Pacific. J. Biogeogr. 46, 420–431 (2019).
    Google Scholar 
    Wieters, E. A. Upwelling control of positive interactions over mesoscales: A new link between bottom-up and top-down processes on rocky shores. Mar. Ecol. Prog. Ser. 301, 43–54 (2005).ADS 

    Google Scholar 
    Pérez-Matus, A., Carrasco, S. A., Gelcich, S., Fernandez, M. & Wieters, E. A. Exploring the effects of fishing pressure and upwelling intensity over subtidal kelp forest communities in Central Chile. Ecosphere 8, e01808 (2017).
    Google Scholar 
    Iranon, N. N. & Miller, D. L. Interactions between oxygen homeostasis, food availability, and hydrogen sulfide signaling. Front. Genet. 3, 5 (2012).
    Google Scholar 
    Ramajo, L., Lagos, N. A. & Duarte, C. M. Seagrass Posidonia oceanica diel pH fluctuations reduce the mortality of epiphytic forams under experimental ocean acidification. Mar. Pollut. Bull. 146, 247–254 (2019).CAS 
    PubMed 

    Google Scholar 
    Aiken, C. & Navarrete, S. Environmental fluctuations and asymmetrical ­dispersal: Generalized stability theory for studying metapopulation persistence and marine protected areas. Mar. Ecol. Prog. Ser. 428, 77–88 (2011).ADS 

    Google Scholar 
    Baldanzi, S. et al. Combined effects of temperature and hypoxia shape female brooding behaviors and the early ontogeny of the Chilean kelp crab Taliepus dentatus. Mar. Ecol. Prog. Ser. 646, 93–107 (2020).ADS 
    CAS 

    Google Scholar 
    Moran, A. L. & McAlister, J. S. Egg size as a life history character of marine invertebrates: Is it all it’s cracked up to be?. Biol. Bull. 216, 226–242 (2009).PubMed 

    Google Scholar 
    Doherty-Weason, D. et al. Bioenergetics of parental investment in two polychaete species with contrasting reproductive strategies: The planktotrophic Boccardia chilensis and the poecilogonic Boccardia wellingtonensis (Spionidae). Mar. Ecol. 41, 1 (2020).
    Google Scholar 
    Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: A practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B 57, 289–300 (1995).MathSciNet 
    MATH 

    Google Scholar 
    Steneck, R. S. et al. Kelp forest ecosystems: Biodiversity, stability, resilience and future. Environ. Conserv. 29, 436–459 (2002).
    Google Scholar 
    Sayols-Baixeras, S., Irvin, M. R., Arnett, D. K., Elosua, R. & Aslibekyan, S. W. Epigenetics of lipid phenotypes. Curr. Cardiovasc. Risk Rep. 10, 1–205 (2016).
    Google Scholar 
    Adam, A. C. et al. Profiling DNA methylation patterns of zebrafish liver associated with parental high dietary arachidonic acid. PLoS ONE 14, e0220934 (2019).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    García-Fernández, P., García-Souto, D., Almansa, E., Morán, P. & Gestal, C. Epigenetic DNA methylation mediating Octopus vulgaris early development: Effect of essential fatty acids enriched diet. Front. Physiol. 8, 1–9 (2017).
    Google Scholar 
    Hearn, J., Pearson, M., Blaxter, M., Wilson, P. J. & Little, T. J. Genome-wide methylation is modified by caloric restriction in Daphnia magna. BMC Genomics 20, 1–11 (2019).
    Google Scholar 
    Palma, A. T., Henríquez, L. A. & Ojeda, F. P. Phytoplanktonic primary production modulated by coastal geomorphology in a highly dynamic environment of central Chile. Rev. Biol. Mar. Oceanogr. 44, 325–334 (2009).
    Google Scholar 
    Faúndez-Báez, P., Morales, C. E. & Arcos, D. Variabilidad espacial y temporal en la hidrografía invernal del sistema de bahías frente a la VIII región (Chile centro-sur). Rev. Chil. Hist. Nat. 74, 817–831 (2001).
    Google Scholar 
    Osma, N. et al. Response of phytoplankton assemblages from naturally acidic coastal ecosystems to elevated pCO2. Front. Mar. Sci. 1, 323 (2020).
    Google Scholar 
    Rebolledo, L. et al. Siliceous productivity changes in Gulf of Ancud sediments (42°S, 72°W), southern Chile, over the last ∼150 years. Cont. Shelf Res. 31, 356–365 (2011).ADS 

    Google Scholar 
    Sun, Y. et al. Genome-wide analysis of DNA methylation in five tissues of Zhikong Scallop, Chlamys farreri. PLoS ONE 9, e86232 (2014).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Bernhardt, J. R., O’Connor, M. I., Sunday, J. M. & Gonzalez, A. Life in fluctuating environments. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 375, 20190454 (2020).PubMed 
    PubMed Central 

    Google Scholar 
    Feinberg, A. P. & Irizarry, R. A. Colloquium Paper: Stochastic epigenetic variation as a driving force of development, evolutionary adaptation, and disease. Proc. Natl. Acad. Sci. USA 107, 1757 (2010).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Tapia, F. J., Largier, J. L., Castillo, M., Wieters, E. A. & Navarrete, S. A. Latitudinal discontinuity in thermal conditions along the nearshore of Central-Northern Chile. PLoS ONE 9, e110841 (2014).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Reyna-López, G. E., Simpson, J. & Ruiz-Herrera, J. Differences in DNA methylation patterns are detectable during the dimorphic transition of fungi by amplification of restriction polymorphisms. Mol. Gen. Genet. 253, 703–710 (1997).PubMed 

    Google Scholar 
    Pérez-Figueroa, A. msap: A tool for the statistical analysis of methylation-sensitive amplified polymorphism data. Mol. Ecol. Resour. 13, 522–527 (2013).PubMed 

    Google Scholar 
    Gu, Z., Eils, R. & Schlesner, M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics 32, 2847–2849 (2016).CAS 
    PubMed 

    Google Scholar 
    Valladares, F., Sanches-Gomez, D. & Zavala, M. A. Quantitative estimation of phenotypic plasticity: Bridging the gap between the evolutionary concept and its ecological applications. J. Ecol. 94, 1103–1116 (2006).
    Google Scholar 
    Excoffier, L., Smouse, P. E. & Quattro, J. M. Analysis of molecular variance inferred from metric distances among DNA haplotypes: Application to human mitochondrial DNA restriction data. Genetics 131, 479–491 (1992).CAS 
    PubMed 
    PubMed Central 

    Google Scholar  More

  • in

    A colonial-nesting seabird shows no heart-rate response to drone-based population surveys

    Ratcliffe, N. et al. A protocol for the aerial survey of penguin colonies using UAVs. J. Unmanned Veh. Syst. 3, 95–101 (2015).
    Google Scholar 
    Albores-Barajas, Y. V. et al. A new use of technology to solve an old problem: Estimating the population size of a burrow nesting seabird. PLoS ONE 13, 1–15 (2018).
    Google Scholar 
    Rush, G. P., Clarke, L. E., Stone, M. & Wood, M. J. Can drones count gulls? Minimal disturbance and semiautomated image processing with an unmanned aerial vehicle for colony-nesting seabirds. Ecol. Evol. 8, 12322–12334 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    Chabot, D., Craik, S. R. & Bird, D. M. Population census of a large Common tern colony with a small unmanned aircraft. PLoS ONE 10, 1–14 (2015).
    Google Scholar 
    McClelland, G. T. W., Bond, A. L., Sardana, A. & Glass, T. Rapid population estimate of a surface-nesting seabird on a remote island using a low-cost unmanned aerial vehicle. Mar. Ornithol. 44, 215–220 (2016).
    Google Scholar 
    Lynch, H. J., White, R., Black, A. D. & Naveen, R. Detection, differentiation, and abundance estimation of penguin species by high-resolution satellite imagery. Polar Biol. 35, 963–968 (2012).
    Google Scholar 
    Fretwell, P. T. et al. An Emperor penguin population estimate: The first global, synoptic survey of a species from space. PLoS ONE 7, e33751 (2012).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Xue, Y., Wang, T. & Skidmore, A. K. Automatic counting of large mammals from very high resolution panchromatic satellite imagery. Remote Sens. 9, 1–16 (2017).
    Google Scholar 
    Laliberte, A. S. & Ripple, W. J. Automated wildlife counts from remotely sensed imagery. Wildl. Soc. Bull. 31, 362–371 (2003).
    Google Scholar 
    Lyons, M. B. et al. Monitoring large and complex wildlife aggregations with drones. Methods Ecol. Evol. 10, 1024–1035 (2019).
    Google Scholar 
    LaRue, M. A., Stapleton, S. & Anderson, M. Feasibility of using high-resolution satellite imagery to assess vertebrate wildlife populations. Conserv. Biol. 31, 213–220 (2017).PubMed 

    Google Scholar 
    Sardà-Palomera, F., Bota, G., Padilla, N., Brotons, L. & Sardà, F. Unmanned aircraft systems to unravel spatial and temporal factors affecting dynamics of colony formation and nesting success in birds. J. Avian Biol. 48, 1273–1280 (2017).
    Google Scholar 
    Schofield, G., Katselidis, K. A., Lilley, M. K. S., Reina, R. D. & Hays, G. C. Detecting elusive aspects of wildlife ecology using drones: New insights on the mating dynamics and operational sex ratios of sea turtles. Funct. Ecol. 31, 2310–2319 (2017).
    Google Scholar 
    Lachman, D., Conway, C., Vierling, K. & Matthews, T. Drones provide a better method to find nests and estimate nest survival for colonial waterbirds: A demonstration with Western grebes. Wetl. Ecol. Manag. 28, 837–845 (2020).
    Google Scholar 
    Torres, L. G., Nieukirk, S. L., Lemos, L. & Chandler, T. E. Drone up! Quantifying whale behavior from a new perspective improves observational capacity. Front. Mar. Sci. 5, 1–14 (2018).
    Google Scholar 
    Jagielski, P. M., Dey, C. J., Gilchrist, H. G., Richardson, E. S. & Semeniuk, C. A. D. Polar bear foraging on common eider eggs: Estimating the energetic consequences of a climate-mediated behavioural shift. Anim. Behav. 171, 63–75 (2021).
    Google Scholar 
    Jagielski, P. M. et al. Polar bears are inefficient predators of seabird eggs. R. Soc. Open Sci. 8, 210391 (2021).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Callaghan, C. T., Brandis, K. J., Lyons, M. B., Ryall, S. & Kingsford, R. T. A comment on the limitations of UAVS in wildlife research—The example of colonial nesting waterbirds. J. Avian Biol. 49, e01825 (2018).
    Google Scholar 
    Brisson-Curadeau, É. et al. Seabird species vary in behavioural response to drone census. Sci. Rep. 7, 1–9 (2017).
    Google Scholar 
    Nowak, M. M., Dziób, K. & Bogawski, P. Unmanned aerial vehicles (UAVs) in environmental biology: A review. Eur. J. Ecol. 4, 56–74 (2019).
    Google Scholar 
    Watts, A. C. et al. Small unmanned aircraft systems for low-altitude aerial surveys. J. Wildl. Manag. 74, 1614–1619 (2010).
    Google Scholar 
    Sasse, D. B. Job-related mortality of wildlife workers in the United States, 1937–2000. Wildl. Soc. Bull. 31, 1015–1020 (2003).
    Google Scholar 
    Carey, M. J. The effects of investigator disturbance on procellariiform seabirds: A review. N. Z. J. Zool. 36, 367–377 (2009).
    Google Scholar 
    Carney, K. M. & Sydeman, W. J. A review of human disturbance effects on nesting colonial waterbirds. Int. J. Waterbird Biol. 22, 68–79 (1999).
    Google Scholar 
    Barber-Meyer, S. M., Kooyman, G. L. & Ponganis, P. J. Estimating the relative abundance of Emperor penguins at inaccessible colonies using satellite imagery. Polar Biol. 30, 1565–1570 (2007).
    Google Scholar 
    Lyons, M. et al. A protocol for using drones to assist monitoring of large breeding bird colonies. EcolEvol https://doi.org/10.32942/osf.io/p9j3f (2019).Article 

    Google Scholar 
    Hodgson, J. C. et al. Drones count wildlife more accurately and precisely than humans. Methods Ecol. Evol. 9, 1160–1167 (2018).
    Google Scholar 
    Hodgson, J. C., Baylis, S. M., Mott, R., Herrod, A. & Clarke, R. H. Precision wildlife monitoring using unmanned aerial vehicles. Sci. Rep. 6, 1–7 (2016).
    Google Scholar 
    Weston, M. A., O’Brien, C., Kostoglou, K. N. & Symonds, M. R. E. Escape responses of terrestrial and aquatic birds to drones: Towards a code of practice to minimize disturbance. J. Appl. Ecol. 57, 777–785 (2020).
    Google Scholar 
    Korczak-Abshire, M. et al. Preliminary study on nesting Adélie penguins disturbance by unmanned aerial vehicles. CCAMLR Sci. 23, 1–16 (2016).
    Google Scholar 
    Mesquita, G. P., Rodríguez-Teijeiro, J. D., Wich, S. A. & Mulero-Pázmány, M. Measuring disturbance at a swift breeding colonies due to the visual aspects of a drone: A quasi-experiment study. Curr. Zool. 41, 259–266 (2020).
    Google Scholar 
    Weimerskirch, H., Prudor, A. & Schull, Q. Flights of drones over sub-Antarctic seabirds show species- and status-specific behavioural and physiological responses. Polar Biol. 41, 259–266 (2018).
    Google Scholar 
    Mulero-Pázmány, M. et al. Unmanned aircraft systems as a new source of disturbance for wildlife: A systematic review. PLoS ONE 12, 1–14 (2017).
    Google Scholar 
    Barnas, A. et al. Evaluating behavioral responses of nesting Lesser snow geese to unmanned aircraft surveys. Ecol. Evol. 8, 1328–1338 (2018).PubMed 

    Google Scholar 
    Ellis-felege, S. N. et al. Nesting Common eiders (Somateria mollissima) show little behavioral response to fixed-wing drone surveys. J. Unmanned Veh. Syst. https://doi.org/10.1139/juvs-2021-0012 (2021).Article 

    Google Scholar 
    Wilson, R. P., Culik, B., Danfeld, R. & Adelung, D. People in Antarctica—how much do Adélie penguins Pygoscelis adeliae care?. Polar Biol. 11, 363–370 (1991).
    Google Scholar 
    Ricklefs, R. E. An analysis of nesting mortality in birds. Smithson. Contrib. Zool. 9, 1–48 (1969).
    Google Scholar 
    Ditmer, M. A. et al. Bears show a physiological but limited behavioral response to unmanned aerial vehicles. Curr. Biol. 25, 2278–2283 (2015).PubMed 

    Google Scholar 
    Ditmer, M. A. et al. Bears habituate to the repeated exposure of a novel stimulus, unmanned aircraft systems. Conserv. Physiol. 6, 1–7 (2018).
    Google Scholar 
    Jaatinen, K., Seltmann, M. W. & Öst, M. Context-dependent stress responses and their connections to fitness in a landscape of fear. J. Zool. 294, 147–153 (2014).
    Google Scholar 
    Seltmann, M. W. et al. Stress responsiveness, age and body condition interactively affect flight initiation distance in breeding female eiders. Anim. Behav. 84, 889–896 (2012).
    Google Scholar 
    Cockrem, J. F. Stress, corticosterone responses and avian personalities. J. Ornithol. 148, S169–S178 (2007).
    Google Scholar 
    Criscuolo, F. Does blood sampling during eider incubation induce nest desertion in the female Common eider Somateria mollissima?. Mar. Ornithol. 29, 47–50 (2001).
    Google Scholar 
    Ellenberg, U., Mattern, T. & Seddon, P. J. Heart rate responses provide an objective evaluation of human disturbance stimuli in breeding birds. Conserv. Physiol. 1, 1–11 (2013).
    Google Scholar 
    DeRose-Wilson, A., Fraser, J. D., Karpanty, S. M. & Hillman, M. D. Effects of overflights on incubating Wilson’s plover behavior and heart rate. J. Wildl. Manag. 79, 1246–1254 (2015).
    Google Scholar 
    de Villiers, M., Bause, M., Giese, M. & Fourie, A. Hardly hard-hearted: Heart rate responses of incubating Northern giant petrels (Macronectes halli) to human disturbance on sub-Antarctic Marion Island. Polar Biol. 29, 717–720 (2006).
    Google Scholar 
    Borneman, T. E., Rose, E. T. & Simons, T. R. Minimal changes in heart rate of incubating American oystercatchers (Haematopus palliatus) in response to human activity. Condor 116, 493–503 (2014).
    Google Scholar 
    Felton, S. K., Pollock, K. H. & Simons, T. R. Response of beach-nesting American oystercatchers to off-road vehicles: An experimental approach reveals physiological nuances and decreased nest attendance. Condor 120, 47–62 (2018).
    Google Scholar 
    Bolduc, F. & Guillemette, M. Human disturbance and nesting success of Common eiders: Interaction between visitors and gulls. Biol. Conserv. 110, 77–83 (2003).
    Google Scholar 
    Hennin, H. L. et al. Plasma mammalian leptin analogue predicts reproductive phenology, but not reproductive output in a capital-income breeding seaduck. Ecol. Evol. 9, 1512–1521 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Culik, B., Adelung, D. & Woakes, A. J. The effect of disturbance on the heart rate and behaviour of Adélie penguins (Pygoscelis adeliae) during the breeding season. In Antarctic Ecosystems. Ecological Change and Conservation (eds Kerry, K. R. & Hempel, G.) 177–182 (Springer, 1990).
    Google Scholar 
    Weimerskirch, H. et al. Heart rate and energy expenditure of incubating Wandering albatrosses: Basal levels, natural variation, and the effects of human disturbance. J. Exp. Biol. 205, 475–483 (2002).PubMed 

    Google Scholar 
    Egan, C. C., Blackwell, B. F., Fernández-Juricic, E. & Klug, P. E. Testing a key assumption of using drones as frightening devices: Do birds perceive drones as risky?. Condor 122, 1–15 (2020).
    Google Scholar 
    McEvoy, J. F., Hall, G. P. & McDonald, P. G. Evaluation of unmanned aerial vehicle shape, flight path and camera type for waterfowl surveys: Disturbance effects and species recognition. PeerJ 4, e1831 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Goebel, M. E. et al. A small unmanned aerial system for estimating abundance and size of Antarctic predators. Polar Biol. 38, 619–630 (2015).
    Google Scholar 
    Bevan, E. et al. Measuring behavioral responses of sea turtles, saltwater crocodiles, and Crested terns to drone disturbance to define ethical operating thresholds. PLoS ONE 13, 4–6 (2018).
    Google Scholar 
    Rümmler, M. C., Mustafa, O., Maercker, J., Peter, H. U. & Esefeld, J. Measuring the influence of unmanned aerial vehicles on Adélie penguins. Polar Biol. 39, 1329–1334 (2016).
    Google Scholar 
    Vas, E., Lescroël, A., Duriez, O., Boguszewski, G. & Grémillet, D. Approaching birds with drones: First experiments and ethical guidelines. Biol. Lett. 11, 20140754 (2015).PubMed 
    PubMed Central 

    Google Scholar 
    Frid, A. & Dill, L. Human-caused disturbance stimuli as a form of predation risk. Ecol. Soc. 6, 11 (2002).
    Google Scholar 
    Forbes, M. R. L., Clark, R. G., Weatherhead, P. J. & Armstrong, T. Risk-taking by female ducks: Intra-and interspecific tests of nest defense theory. Behav. Ecol. Sociobiol. 34, 79–85 (1994).
    Google Scholar 
    Viblanc, V. A., Smith, A. D., Gineste, B., Kauffmann, M. & Groscolas, R. Modulation of heart rate response to acute stressors throughout the breeding season in the King penguin Aptenodytes patagonicus. J. Exp. Biol. 218, 1686–1692 (2015).PubMed 

    Google Scholar 
    Montgomerie, R. D. & Weatherhead, P. J. Risks and rewards of nest defence by parent birds. Q. Rev. Biol. 63, 167–187 (1988).
    Google Scholar 
    Criscuolo, F., Gabrielsen, G. W., Gendner, J.-P. & Maho, Y. L. Body mass regulation during incubation in female Common eiders Somateria mollissima. J. Avian Biol. 33, 83–88 (2002).
    Google Scholar 
    Cyr, N. E., Wikelski, M. & Romero, L. M. Increased energy expenditure but decreased stress responsiveness during molt. Physiol. Biochem. Zool. Ecol. Evol. Approaches 81, 452–462 (2008).
    Google Scholar 
    Kralj-Fišer, S., Scheiber, I. B. R., Kotrschal, K., Weiß, B. M. & Wascher, C. A. F. Glucocorticoids enhance and suppress heart rate and behaviour in time dependent manner in Greylag geese (Anser anser). Physiol. Behav. 100, 394–400 (2010).PubMed 

    Google Scholar 
    Hodgson, J. C. & Koh, L. P. Best practice for minimising unmanned aerial vehicle disturbance to wildlife in biological field research. Curr. Biol. 26, R404–R405 (2016).PubMed 

    Google Scholar 
    Parker, H. & Holm, H. Patterns of nutrient and energy expenditure in female Common eiders nesting in the high Arctic. Auk 107, 660–668 (1990).
    Google Scholar 
    Mehlum, F. Eider Studies in Svalbard Vol. 195 (Norsk Polarinstitutt Skrifter, 1991).
    Google Scholar 
    Markowitz, E. M., Nisbet, M. C., Danylchuk, A. J. & Engelbourg, S. I. What’s that buzzing noise? Public opinion on the use of drones for conservation science. Bioscience 67, 382–385 (2017).
    Google Scholar 
    Legagneux, P. et al. Unpredictable perturbation reduces breeding propensity regardless of pre-laying reproductive readiness in a partial capital breeder. J. Avian Biol. 47, 880–886 (2016).
    Google Scholar 
    Love, O. P., Gilchrist, H. G., Descamps, S., Semeniuk, C. A. D. & Bêty, J. Pre-laying climatic cues can time reproduction to optimally match offspring hatching and ice conditions in an Arctic marine bird. Oecologia 164, 277–286 (2010).ADS 
    PubMed 

    Google Scholar 
    Fast, P. L. F., Gilchrist, H. G. & Clark, R. G. Nest-site materials affect nest-bowl use by Common eiders (Somateria mollissima). Can. J. Zool. 88, 214–218 (2010).
    Google Scholar 
    McKinnon, L., Gilchrist, H. G. & Scribner, K. T. Genetic evidence for kin-based female social structure in Common eiders (Somateria mollissima). Behav. Ecol. 17, 614–621 (2006).
    Google Scholar 
    Descamps, S., Forbes, M. R., Gilchrist, H. G., Love, O. P. & Bêty, J. Avian cholera, post-hatching survival and selection on hatch characteristics in a long-lived bird, the Common eider Somateria mollissima. J. Avian Biol. 42, 39–48 (2011).
    Google Scholar 
    Buttler, E. I. Avian Cholera Among Arctic Breeding Common eiders Somateria mollissima: Temporal Dynamics and the Role of Handling Stress in Reproduction and Survival (Carleton University, 2009).
    Google Scholar 
    Descamps, S., Gilchrist, H. G., Bêty, J., Buttler, E. I. & Forbes, M. R. Costs of reproduction in a long-lived bird: large clutch size is associated with low survival in the presence of a highly virulent disease. Biol. Lett. 5, 278–281 (2009).PubMed 
    PubMed Central 

    Google Scholar 
    Iverson, S. A., Gilchrist, H. G., Smith, P. A., Gaston, A. J. & Forbes, M. R. Longer ice-free seasons increase the risk of nest depredation by Polar bears for colonial breeding birds in the Canadian Arctic. Proc. R. Soc. B Biol. Sci. 281, 20133128 (2014).
    Google Scholar 
    Dey, C. J. et al. Increasing nest predation will be insufficient to maintain Polar bear body condition in the face of sea ice loss. Glob. Change Biol. 23, 1821–1831 (2017).ADS 

    Google Scholar 
    Giese, M., Handsworth, R. & Stephenson, R. Measuring resting heart rates in penguins using an artificial egg. J. Field Ornithol. 70, 49–54 (1999).
    Google Scholar 
    Weller, M. W. A simple field candler for waterfowl eggs. J. Wildl. Manag. 20, 111–113 (1956).
    Google Scholar 
    Barnas, A. F. et al. A standardized protocol for reporting methods when using drones for wildlife research. J. Unmanned Veh. Syst. 8, 89–98 (2020).
    Google Scholar 
    Audacity Team. Audacity(R): Free Audio Editor and Recorder [Computer Application]. Version 2.3.2 retrieved Oct 10th 2019 from https://www.audacityteam.org/ (2019).Nimon, A. J., Schroter, R. C. & Oxenham, R. K. C. Artificial eggs: Measuring heart rate and effects of disturbance in nesting penguins. Physiol. Behav. 60, 1019–1022 (1996).PubMed 

    Google Scholar 
    SAS Institute Inc. SAS® Studio 3.8: User’s Guide (SAS Institute Inc, 2018).
    Google Scholar 
    Burnham, K. P. & Anderson, D. R. Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach (Springer, 2002).MATH 

    Google Scholar 
    Akaike, H. Information theory and an extension of the maximum likelihood principle. In Breakthroughs in Statistics, Volume I, Foundations and Basic Theory (eds Kotz, S. & Johnson, N. L.) 610–624 (Springer, New York, 1998).
    Google Scholar 
    Wickham, H., François, R., Henry, L. & Müller, K. dplyr: A Grammar of Data Manipulation. R package version 0.8.3. https://CRAN.R-project.org/package=dplyr (2015).Grolemund, G. & Wickham, H. Dates and times made easy with lubridate. J. Stat. Softw. 40, 1–25 (2011).
    Google Scholar 
    Hijmans, R. J., Williams, E. & Vennes, C. Geosphere: Spherical Trigonometry. https://CRAN.R-project.org/package=geosphere (2017).Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer, 2016).MATH 

    Google Scholar 
    R Core Team. R: A Language and Environment for Statistical Computing (R Found. Stat. Comput., Vienna, 2017).
    Google Scholar  More

  • in

    Religiosity is associated with greater size, kin density, and geographic dispersal of women’s social networks in Bangladesh

    Lim, C. & Putnam, R. D. Religion, social networks, and life satisfaction. Am. Sociol. Rev. 75, 914–933 (2010).
    Google Scholar 
    Fox, R. Kinship and marriage: an anthropological perspective/by Robin Fox. (1967).Lévi-Strauss, C. The elementary structures of kinship. (Beacon Press, 1969).Murdock, G. P. Social structure. Macmillan 387 (1949).Chapais, B. Primeval kinship: how pair-bonding gave birth to human society. (Harvard University Press, 2009).Walker, R. S. & Hill, K. R. Causes, consequences, and kin bias of human group fissions. Hum. Nat. 25, 465–475 (2014).PubMed 

    Google Scholar 
    Shenk, M. K., Towner, M. C., Voss, E. A. & Alam, N. Consanguineous marriage, kinship ecology, and market transition. Curr. Anthropol. 57, S167–S180 (2016).
    Google Scholar 
    Swann, W. B. Jr., Gómez, A., Seyle, D. C., Morales, J. F. & Huici, C. Identity fusion: The interplay of personal and social identities in extreme group behavior. J. Pers. Soc. Psychol. 96, 995–1011 (2009).PubMed 

    Google Scholar 
    Richerson, P. J. & Boyd, R. Complex societies. Hum. Nat. 10, 253–289 (1999).CAS 
    PubMed 

    Google Scholar 
    Zelinsky, W. The hypothesis of the mobility transition. Geogr. Rev. 61, 219–249 (1971).
    Google Scholar 
    Gurven, M., Jaeggi, A. V., von Rueden, C., Hooper, P. L. & Kaplan, H. Does market integration buffer risk, erode traditional sharing practices and increase inequality? A test among Bolivian forager-farmers. Hum. Ecol. Interdiscip. J. 43, 515–530 (2015).PubMed 
    PubMed Central 

    Google Scholar 
    Godoy, R. A. et al. Do markets worsen economic inequalities? Kuznets in the Bush. Hum. Ecol. 32, 339–364 (2004).
    Google Scholar 
    Kaplan, H. A theory of fertility and parental investment in traditional and modern human societies. Am. J. Phys. Anthropol. 101, 91–135 (1996).
    Google Scholar 
    Duernecker, G. & Vega-Redondo, F. Social Networks and the Process of Globalization. Rev. Econ. Stud. 85, 1716–1751 (2017).MathSciNet 
    MATH 

    Google Scholar 
    Colleran, H. Market integration reduces kin density in women’s ego-networks in rural Poland. Nat. Commun. 11, 266 (2020).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Wilding, R. Families, intimacy and globalization. (Macmillan International Higher Education, 2018).Hackman, J. V. & Kramer, K. L. Kin Ties and market integration in a Yucatec Mayan Village. Soc. Sci. 10, 216 (2021).
    Google Scholar 
    Norenzayan, A. Big gods: How religion transformed cooperation and conflict. (Princeton University Press, 2013).Lauder, W., Mummery, K. & Sharkey, S. Social capital, age and religiosity in people who are lonely. J. Clin. Nurs. 15, 334–340 (2006).PubMed 

    Google Scholar 
    Agate, S. T., Zabriskie, R. B. & Eggett, D. L. Praying, playing, and successful families. Marriage Fam. Rev. 42, 51–75 (2007).
    Google Scholar 
    Day, R. D. et al. Family processes and adolescent religiosity and religious practice: View from the NLSY97. Marriage Fam. Rev. 45, 289–309 (2009).
    Google Scholar 
    Fagan, P. F. Why religion matters even more: The impact of religious practice on social stability. Backgrounder 1992, 1–19 (2006).
    Google Scholar 
    Ellison, C. G. & George, L. K. Religious involvement, social ties, and social support in a Southeastern Community. J. Sci. Study Relig. 33, 46–61 (1994).
    Google Scholar 
    Ellison, C. G. & Xu, X. Religion and families. The Wiley Blackwell companion to the sociology of families 277–299 (2014).Ginges, J., Hansen, I. & Norenzayan, A. Religion and support for suicide attacks. Psychol. Sci. 20, 224–230 (2009).PubMed 

    Google Scholar 
    Lynch, R., Palestis, B. G. & Trivers, R. Religious devotion and extrinsic religiosity affect in-group altruism and out-group hostility oppositely in rural Jamaica. Evol. Psychol. Sci. 3, 335 (2017).
    Google Scholar 
    Walker, R. S. & Bailey, D. H. Marrying kin in small-scale societies. Am. J. Hum. Biol. 26, 384–388 (2014).PubMed 

    Google Scholar 
    Putnam, R. D., Leonardi, R. & Nanetti, R. Y. Making Democracy Work: Civic Traditions in Modern Italy. (Princeton University Press, 1994).Coleman, J. Foundations of Social Theory. (Belknap Press of Harvard University Press, Cambridge, Mass, 1990).Wuthnow, R. The Left Behind: Decline and Rage in Rural America. (Princeton University Press, 2018).Sunstein, C. R. # Republic: Divided democracy in the age of social media. (Princeton University Press, 2018).Putnam, R. D. E Pluribus Unum: Diversity and Community in the Twenty-first Century The 2006 Johan Skytte Prize Lecture. Scan. Polit. Stud. 30, (2007).Putnam, R. Bowling alone: The collapse and revival of American community. (Simon and Schuster, 2000).Olson, M. The Logic of Collective Action: Public Goods and the Theory of Groups, Second printing with new preface and appendix (Harvard Economic Studies). Harvard economic studies, v. 124 (Harvard University Press, 1971).Granovetter, M. S. The strength of weak ties. Am. J. Sociol. (1973).Lynch, R., Lummaa, V. & Panchanathan, K. Integration involves a trade-off between fertility and status for World War II evacuees. Nature Human Behaviour (2019).Beyerlein, K. & Hipp, J. R. Social capital, too much of a good thing? American Religious Traditions and Community Crime. Soc. Forces 84, 995–1013 (2005).
    Google Scholar 
    Lewis, V. A., Macgregor, C. A. & Putnam, R. D. Religion, networks, and neighborliness: The impact of religious social networks on civic engagement. Soc. Sci. Res. 42, 331–346 (2013).PubMed 

    Google Scholar 
    Yu, M. & Stiffman, A. R. Positive family relationships and religious affiliation as mediators between negative environment and illicit drug symptoms in American Indian adolescents. Addict. Behav. 35, 694–699 (2010).PubMed 

    Google Scholar 
    Regnerus, M. D. & Burdette, A. Religious change and adolescent family dynamics. Sociol. Q. 47, 175–194 (2006).
    Google Scholar 
    Marks, L. Religion and family relational health: An overview and conceptual model. J. Relig. Health (2006).Thornton, A. Reciprocal Influences of Family and Religion in a Changing World. J. Marriage Fam. Couns. 47, 381–394 (1985).
    Google Scholar 
    Mahoney, A., Pargament, K. I., Murray-Swank, A. & Murray-Swank, N. Religion and the Sanctification of Family Relationships. Rev. Relig. Res. 44, 220–236 (2003).
    Google Scholar 
    Mahoney, A. Religion in families 1999 to 2009: A relational spirituality framework. J. Marriage Fam. 72, 805–827 (2010).PubMed 
    PubMed Central 

    Google Scholar 
    Ebstyne King, P. & Furrow, J. L. Religion as a resource for positive youth development: religion, social capital, and moral outcomes. Dev. Psychol. 40, 703–713 (2004).PubMed 

    Google Scholar 
    Dudley, M. G. & Kosinski, F. A. Religiosity and marital satisfaction: A research note. Rev. Relig. Res. 32, 78–86 (1990).
    Google Scholar 
    Milevsky, A., Smoot, K., Leh, M. & Ruppe, A. Familial and contextual variables and the nature of sibling relationships in emerging adulthood. Marriage Fam. Rev. 37, 123–141 (2005).
    Google Scholar 
    Galbraith, D. & Shaver, J. H. Religion and Fertility Bibliography. evolutionarydemographyofreligion.Shaver, J. H., Sibley, C. G., Sosis, R., Galbraith, D. & Bulbulia, J. Alloparenting and religious fertility: A test of the religious alloparenting hypothesis. Evol. Hum. Behav. 40, 315–324 (2019).
    Google Scholar 
    Kaufmann, E. Shall the Religious Inherit the Earth?: Demography and Politics in the Twenty-First Century. (Profile Books, 2010).Ebaugh, H. R. & Curry, M. Fictive Kin as social capital in new immigrant communities. Sociol. Perspect. 43, 189–209 (2000).
    Google Scholar 
    Taylor, R. J., Chatters, L. M., Woodward, A. T. & Brown, E. Racial and ethnic differences in extended family, friendship, fictive kin and congregational informal support networks. Fam. Relat. 62, 609–624 (2013).PubMed 
    PubMed Central 

    Google Scholar 
    Durkheim, E. The elementary forms of the religious life. Preprint at (1915).Rappaport, R. A. Ritual and Religion in the Making of Humanity. vol. 110 (Cambridge University Press, 1999).Hastings, O. P. Not a lonely crowd? Social connectedness, religious service attendance, and the spiritual but not religious. Soc. Sci. Res. 57, 63–79 (2016).PubMed 

    Google Scholar 
    Putnam, R. & Campbell, D. E. American grace: How religion is reshaping our civic and political lives. Preprint at (2010).Turke, P. W. Evolution and the demand for children. Popul. Dev. Rev. 15, 61–90 (1989).
    Google Scholar 
    Sear, R. & Coall, D. How much does family matter? Cooperative breeding and the demographic transition. Popul. Dev. Rev. 37, 81–112 (2011).PubMed 

    Google Scholar 
    Jenkins, P. Fertility and Faith: The Demographic Revolution and the Transformation of World Religions. (Baylor University Press, 2020).Rothstein, B. Corruption and social trust: Why the fish rots from the head down. Soc. Res. 80, 1009–1032 (2013).
    Google Scholar 
    Lynch, R, Schaffnit, S. and Shenk, M. OSF preregistration – Does religion help to preserve the density of kin networks often disrupted by globalization? Open Science Framework Registries. https://osf.io/xvyqm/registrations (2020).Alam, N. et al. Health and demographic surveillance system (HDSS) in Matlab, Bangladesh. Int. J. Epidemiol. 46, 809–816 (2017).PubMed 

    Google Scholar 
    Icddr, B. Health and Demographic Surveillance System-Matlab. 2005 Socioeconomic Census (2007).Imf. International Monetary Fund. World Economic Outlook Database. (2016).Razzaque, A., Streatfield, P. K. & Evans, A. Family size and children’s education in Matlab, Bangladesh. J. Biosoc. Sci. 39, 245–256 (2007).PubMed 

    Google Scholar 
    Afsar, R. Unravelling the vicious cycle of recruitment: Labour migration from Bangladesh to the gulf states. http://ilo.org/wcmsp5/groups/public/—ed_norm/—declaration/documents/publication/wcms_106536.pdf (2009).Kabeer, N. Ideas, economics and ‘the sociology of supply’: Explanations for fertility decline in Bangladesh. J. Dev. Stud. 38, 29–70 (2001).
    Google Scholar 
    Novak, J. J. Bangladesh: Reflections on the water. (Indiana University Press, 1993).Shenk, M. K., Towner, M. C., Kress, H. C. & Alam, N. A model comparison approach shows stronger support for economic models of fertility decline. Proc. Natl. Acad. Sci. USA 110, 8045–8050 (2013).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Devine, J., Hinks, T. & Naveed, A. Happiness in Bangladesh: The role of religion and connectedness. J. Happiness Stud. 20, 351–371 (2019).
    Google Scholar 
    Henrich, J. Market incorporation, agricultural change, and sustainability among the Machiguenga Indians of the Peruvian Amazon. Hum. Ecol. 25, 319–351 (1997).
    Google Scholar 
    Lu, F. Integration into the market among indigenous peoples: A cross-cultural perspective from the Ecuadorian Amazon. Curr. Anthropol. 48, 593–602 (2007).
    Google Scholar 
    Bürkner, P.-C. Advanced Bayesian Multilevel Modeling with the R Package brms. arXiv [stat.CO] (2017).Team, R. C. & Others. R: A language and environment for statistical computing. (2013).Lynch, R. Kin_density_and-religiosity. (2021).McElreath, R. Statistical rethinking. (2017).Clarke, M. New kinship, Islam, and the liberal tradition: sexual morality and new reproductive technology in Lebanon. J. R. Anthropol. Inst. 14, 153–169 (2008).
    Google Scholar 
    Swann, W. B. et al. What makes a group worth dying for? Identity fusion fosters perception of familial ties, promoting self-sacrifice. J. Pers. Soc. Psychol. 106, 912–926 (2014).PubMed 

    Google Scholar 
    Benítez, D. M. Bangladesh: Economy Overview and Structural Changes. (2018).Viry, G. Residential mobility and the spatial dispersion of personal networks: Effects on social support. Soc. Networks 34, 59–72 (2012).
    Google Scholar 
    Mok, D., Wellman, B. & Carrasco, J. Does distance matter in the age of the internet?. Urban Stud. 47, 2747–2783 (2010).
    Google Scholar 
    Rivera, M. T., Soderstrom, S. B. & Uzzi, B. Dynamics of dyads in social networks: Assortative, relational, and proximity mechanisms. Annu. Rev. Sociol. 36, 91–115 (2010).
    Google Scholar 
    Pollet, T. V., Roberts, S. G. B. & Dunbar, R. I. M. Going that extra mile: Individuals travel further to maintain face-to-face contact with highly related kin than with less related kin. PLoS ONE 8, e53929 (2013).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Madhavan, S., Clark, S., Araos, M. & Beguy, D. Distance or location? How the geographic distribution of kin networks shapes support given to single mothers in urban Kenya. Geogr. J. 184, 75–88 (2018).
    Google Scholar 
    Curry, O., Roberts, S. G. B. & Dunbar, R. I. M. Altruism in social networks: evidence for a ‘kinship premium’. Br. J. Psychol. 104, 283–295 (2013).PubMed 

    Google Scholar 
    Sullivan, K. & Sullivan, A. Adolescent–parent separation. Dev. Psychol. 16, 93 (1980).
    Google Scholar 
    Roberts, S. G. B. & Dunbar, R. I. M. Communication in social networks: Effects of kinship, network size, and emotional closeness. Pers. Relatsh. 18, 439–452 (2011).
    Google Scholar 
    Shenk, M. K. et al. Social support, nutrition and health among women in rural Bangladesh: complex tradeoffs in allocare, kin proximity and support network size. Philos. Trans. R. Soc. Lond. B Biol. Sci. 376, 207 (2021).Snopkowski, K. & Sear, R. Grandparental help in Indonesia is directed preferentially towards needier descendants: A potential confounder when exploring grandparental influences on child health. Soc. Sci. Med. 128, 105–114 (2015).PubMed 

    Google Scholar 
    Schaffnit, S. B. & Sear, R. Support for new mothers and fertility in the United Kingdom: Not all support is equal in the decision to have a second child. Popul. Stud. 71, 345–361 (2017).
    Google Scholar 
    Boyer, P. The Naturalness of Religious Ideas: A Cognitive Theory of Religion. (University of California Press, 1994).Thomas, M. G. et al. Kinship underlies costly cooperation in Mosuo villages. R Soc Open Sci 5, 171535 (2018).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Maqsood, A. Love as understanding. Am. Ethnol. https://doi.org/10.1111/amet.13000 (2021).Article 

    Google Scholar 
    Schurmann, A. T. & Mahmud, S. Civil society, health, and social exclusion in Bangladesh. J. Health Popul. Nutr. 27, 536–544 (2009).PubMed 
    PubMed Central 

    Google Scholar 
    Haque, M. R., Hasan, M. S., Alam, N., Barkat, S. & Others. Fertility preferences in Bangladesh. in Family Demography in Asia (Edward Elgar Publishing, 2018).Mattison, S. M. Economic impacts of tourism and erosion of the visiting system among the Mosuo of Lugu Lake. Asia Pac. J. Anthropol. 11, 159–176 (2010).
    Google Scholar 
    Mattison, S. M. et al. Context specificity of ‘market integration’ among the matrilineal Mosuo of Southwest China. Curr. Anthropol. 63, 118–124 (2022).
    Google Scholar 
    Uchida, Y., Kitayama, S., Mesquita, B., Reyes, J. A. S. & Morling, B. Is perceived emotional support beneficial? Well-being and health in independent and interdependent cultures. Pers. Soc. Psychol. Bull. 34, 741–754 (2008).PubMed 

    Google Scholar 
    Reblin, M. & Uchino, B. N. Social and emotional support and its implication for health. Curr. Opin. Psychiatry 21, 201–205 (2008).PubMed 
    PubMed Central 

    Google Scholar 
    Inglehart, R. Faith and freedom: Traditional and modern ways to happiness. Int. Differ. Well-being 351, 397 (2010).
    Google Scholar 
    Ferriss, A. L. Religion and the Quality of Life. J. Happiness Stud. 3, 199–215 (2002).
    Google Scholar 
    Greeley, A. & Hout, M. Happiness and lifestyle among conservative Christians. The truth about conservative Christians 1, 150–161 (2006).
    Google Scholar 
    Pilisuk, M. Kinship, social networks, social support and health. Soc. Sci. Med. 12, 273–280 (1978).CAS 
    PubMed 

    Google Scholar 
    Schaffnit, S. B. & Sear, R. Supportive families versus support from families: The decision to have a child in the Netherlands. Demogr. Res. 37, 417–454 (2017).
    Google Scholar 
    Hassan, A., Lawson, D., Schaffnit, S. B., Urassa, M. & Sear, R. Childcare in transition: evidence that patterns of childcare differ by degree of market integration in north-western Tanzania. (2021).https://doi.org/10.31219/osf.io/gtc6kPutnam, R. D. Democracies in Flux: The Evolution of Social Capital in Contemporary Society. (Oxford University Press, 2004). More

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    Phototroph-heterotroph interactions during growth and long-term starvation across Prochlorococcus and Alteromonas diversity

    All Alteromonas strains support long-term survival of Prochlorococcus under N starvationPrevious research showed that Prochlorococcus, and to some extent Synechococcus depend on co-occurring heterotrophic bacteria to survive various types of stress, including nitrogen starvation [33, 34, 42, 43]. At the first encounter between previously axenic Prochlorococcus and Alteromonas (E1), all co-cultures and axenic controls grew exponentially (Fig. 1B, C). However, all axenic cultures showed a rapid and mostly monotonic decrease in fluorescence starting shortly after the cultures stopped growing, reaching levels below the limit of detection after ~20–30 days. None of the axenic Prochlorococcus cultures were able to re-grow when transferred into fresh media after 60 days (Fig. 1C). In contrast, the decline of co-cultures rapidly slowed, and in some cases was interrupted by an extended “plateau” or second growth stage (Fig. 1B). Across multiple experiments, 92% of the co-cultures contained living Prochlorococcus cells for at least 140 days, meaning that they could be revived by transfer into fresh media. Thus, the ability of Alteromonas to support long-term N starvation in Prochlorococcus was conserved in all analyzed strains.Fig. 1: Experimental designs and overview of the dynamics of Prochlorococcus-Alteromonas co-cultures from first encounter and over multiple transfers.A Schematic illustration of the experimental design. One ml from Experiment E1 was transferred into 20 ml fresh media after 100 days, starting experiment E2. Experiment E2 was similarly transferred into fresh media after 140 days, starting experiment E3. Additional experiments replicating these transfers are described in Supplementary Fig. S1. B Overview of the growth curves of the 25 Prochlorococcus-Alteromonas co-cultures over three transfers spanning ~1.2 years (E1, E2 and E3). Results show mean + standard error from biological triplicates, colored by Prochlorococcus strain as in panel D. C Axenic Prochlorococcus grew exponentially in E1 but failed to grow when transferred into fresh media after 60, 100, or 140 days. Axenic Alteromonas cultures were counted after 60 and 100 days, as their growth cannot be monitored sensitively and non-invasively using fluorescence (optical density is low at these cell numbers). D High reproducibility and strain-specific dynamics of the initial contact between Prochlorococcus and Alteromonas strains (E1). Three biological replicates for each mono-culture and co-culture are shown. Note that the Y axis is linear in panels B, C and logarithmic in panel D. Au: arbitrary units.Full size imageIt has previously been shown that Prochlorococcus MIT9313 is initially inhibited by co-culture with Alteromonas HOT1A3, while Prochlorococcus MED4 is not [12, 32]. This “delayed growth” phenotype was observed here too, was specific to MIT9313 (not observed in other Prochlorococcus strains) and occurred with all Alteromonas strains tested (Fig. 1D). MIT9313 belongs to the low-light adapted clade IV (LLIV), which are relatively distant from other Prochlorococcus strains and differ from them in multiple physiological aspects including the structure of their cell wall [44], the use of different (and nitrogen-containing) compatible solutes [45], and the production of multiple peptide secondary metabolites (lanthipeptides, [46, 47]). LLIV cells also have larger genomes, and are predicted to take up a higher diversity of organic compounds such as sugars and amino acids [48]. It is intriguing that specifically this strain, which has higher predicted metabolic and regulatory flexibilities [49], is the only one initially inhibited in co-culture with Alteromonas.Differences in co-culture phenotype are related to Prochlorococcus and not Alteromonas strains and occur primarily during the decline stageWhile co-culture with all Alteromonas strains had a major effect on Prochlorococcus viability after long-term starvation, there was no significant effect of co-culture on traditional metrics of growth such as maximal growth rate, maximal fluorescence, and lag phase (with the exception of the previously described inhibition of MIT9313; Fig. 2A–C). However, a visual inspection of the growth curves suggested subtle yet consistent differences in the shape of the growth curve, and especially the decline phase, between the different Prochlorococcus strains in the co-cultures (Fig. 1D). To test this, we used the growth curves as input for a principal component analysis (PCA), revealing that the growth curves from each Prochlorococcus strain clustered together, regardless of which Alteromonas strain they were co-cultured with (Fig. 2D). The growth curves of all high-light adapted strains (MED4, MIT9312, and MIT0604) were relatively similar, the low-light I strain NATL2A was somewhat distinct, and the low-light IV strain MIT9313 was a clear outlier (Fig. 2D), consistent with this strain being the only one initially inhibited in all co-cultures. Random forest classification supported the observation that the growth curve shapes were affected more by the Prochlorococcus rather than Alteromonas strains, and also confirmed the visual observation that most of the features differentiating between Prochlorococcus strains occurred during culture decline (random forest is a supervised machine learning algorithm explained in more detail in Supplementary Text S2; see also Supplementary Fig. S2). Thus, co-culture with Alteromonas affects the decline stage of Prochlorococcus in co-culture in a way that differs between Prochlorococcus but not Alteromonas strains.Fig. 2: Growth analysis and principal component analysis (PCA) of the growth curves from all co-cultures during 140 days of E1.A Growth rate, B Maximum fluorescence, and C duration of lag phase during experiment E1. Box-plots represent mean and 75th percentile of co-cultures, circles represent measurements of individual cultures of the axenic controls. The only significant difference between axenic and co-cultures is in the length of the lag phase for MIT9313 (Bonferroni corrected ANOVA, p  More

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    Residual levels and dietary intake risk assessment of 11 pesticides in apricots from different ecological planting regions in China

    Chromatographic separation and mass spectrometric optimizationTo obtain the best monitoring conditions for each compound, a 0.5 mg/L mixed standard solution of 11 pesticides was mixed with the mobile phase through a syringe pump and then injected into the mass spectrometer for tuning. The precursor ion of the compound to be tested was determined by the primary mass spectrometry scan under ESI+ and ESI- modes, and then the product ion was scanned by the secondary mass spectrometry. Two groups of ion pairs with the best sensitivity were selected for detection; one group was used for quantification, and another, for qualitative analysis. The optimization results showed high sensitivity of all the 11 pesticides under the ESI+ mode. Among them, abamectin (B1a), β-cypermethrin, deltamethrin, fenpropathrin, and bifenthrin were [M + NH4]+, and other compounds were [M + H]+. MS parameters of 11 pesticides are mentioned in Table S2.Formic acid and ammonium acetate are commonly used reagents to enhance the ionization of target compounds [M + H]+ and [M + NH4]+ under the ESI+ mode, and they can effectively improve the peak pattern, making the peak sharper and more symmetrical; therefore, they need to be added during gradient elution38. To improve work efficiency, it is necessary to separate and complete the monitoring of 11 pesticides in the shortest possible time; therefore, we selected two different types of chromatographic columns (ACQUITY UPLC HSS C18 and ACQUITY UPLC HSS T3) and three different mobile phases (Ι: 0.1% formic acid aqueous solution—ACN, II: 0.05% formic acid aqueous solution—ACN, and III: 0.1% formic acid/5 mmol/L ammonium acetate aqueous solution—ACN) for optimization experiments. We observed that when using the HSS T3 chromatographic column, β-cypermethrin, deltamethrin, fenpropathrin, and bifenthrin did not show a good retention effect under the three mobile phase systems, and there was substantial tailing of the chromatographic peak. The shape of the chromatographic peak and sensitivity of the target compound were used as evaluation indicators. Compared with Ι and II, mobile phase III produced better sensitivity for all target compounds (Fig. 1), with sharper and more symmetrical peaks of β-cypermethrin, deltamethrin, fenpropathrin, and bifenthrin. This may be because the addition of 5 mmol/L ammonium acetate improved the retention performance of the HSS C18 chromatography columns without affecting the ionization efficiency of all target compounds. In summary, we selected the HSS C18 column for chromatographic separation and used 0.1% formic acid/5 mmol/L ammonium acetate aqueous solution—ACN as the mobile phase to further optimize the gradient elution procedure and effectively separate and detect all the target compounds within 8 min.Figure 1When using HSS C18, the peak areas of 11 pesticides in three different mobile phases.Full size imageOptimization of purification materialsThe flesh of apricot contains sugar, protein, calcium, phosphorus, carotene, thiamine, riboflavin, niacin, and vitamin C. Due to these diverse impurities, the analysis of the sample matrix becomes highly complex. Therefore, these impurities need to be removed from the matrix samples before analysis. Currently, PSA, C18, and MWCNTs are widely used to adsorb to the fruit substrate39. PSA has a strong adsorption capacity for metal ions, fatty acids, sugars, and fat-soluble pigments, C18 has a strong adsorption capacity for non-polar impurities (such as fat, sterol, and volatile oil), while MWCNTs have a strong adsorption capacity for pigments, which can effectively remove chlorophyll, lutein, and carotene. However, C18 and MWCNTs can also simultaneously adsorb pesticides, resulting in poor recovery. Nano-ZrO2 has a large specific surface area and good adsorption stability and has recently been used to purify substrates. It can selectively remove fats and pigments from samples compared to conventional C18 fillers.In the current study, different purification materials were combined for the analysis of 11 pesticide residues and to propose the best purification strategy in the pretreatment of apricot samples. As displayed in Fig. 2, the average recovery of 11 pesticides in the apricot was higher using the C18/nano-ZrO2/MWCNTs than other combinations. Nano-ZrO2 showed better adsorption than PSA in purifying fatty acids, organic acids, polar pigments, and sugars in apricot, owing to its larger specific surface area, better adsorption capacity, and stability. To conclude, the combination of 10 mg C18, 30 mg nano-ZrO2, and 5 mg MWCNTs demonstrated the best recovery for 11 pesticides, with recovery in the range of 72% to 114%, at a pesticide spiking level of 0.01 mg/kg. In summary, we finally determined that among the tested combinations, C18/nano-ZrO2/MWCNTs (10 mg/ 30 mg/5 mg) is the best purification combination for the pre-treatment of apricot samples.Figure 2The recoveries of 11 pesticides in apricot matrix under different scavenger combinations (2–1 C18/nano-ZrO2/MWCNTs, 2–2 PSA/C18/MWCNTs, 2–3 nano-ZrO2/PSA/MWCNTs; 0.01 mg/kg, n = 3).Full size imageLinearity, matrix effects, limit of detection and limit of quantificationThe standard curve obtained from the standard working solutions of 11 pesticides and the calibration curve from blank apricot matrix spiked with 11 pesticides showed good linearity (0.001, 0.005, 0.01, 0.05, 0.1, and 0.5 mg/L), with R2 ≥ 0.9959 for all tested samples (Table 1).Table 1 The standard curves, R2 and MEs of 11 pesticides in apricot.Full size tableTo evaluate MEs, the slopes of matching 11 pesticide standards with solvent and apricot matrix were calculated at the same concentration. According to the derived slope of the matrix-matched calibration curve, MEs of 11 pesticides in apricot were between 89 and 113% (Table 1), well within the range of 80% to 120%, indicating that the MEs could be ignored. It also suggests that the current pre-treatment method has a good purification effect and eliminates the matrix effect very well, laying a robust foundation for the subsequent step of quantitative analysis of samples. We next used the standard solution curve to quantify the 11 pesticide residues in apricot.The LOD refers to the minimum concentration or minimum amount of a component to be tested that can be detected from a test sample under a given confidence level by an analytical method. Its physical meaning is the amount of the measured component when the signal is 3 times the standard deviation (S = 3σ) of the reagent blank signal (background signal). Sometimes it also refers to the amount of the measured component corresponding to when the signal is three times the background signal generated by the reagent blank (S = 3 N). The LOQ refers to the minimum amount of the analyte in the sample that can be quantitatively determined, and the determination result should have a certain accuracy40. The LOQ reflects whether the analytical method has the sensitive quantitative detection ability. The LOQ is the lowest validated level with sufficient recovery and precision, which was estimated to be 0.001 mg/L, while the LOD is the lowest calibration level, which was 2 µg/kg, according to SANTE/12,682/2020.Accuracy and precisionIn the matrix, 11 pesticides were spiked at four levels (0.002, 0.02, 0.1, and 1 mg/kg), and for each spiked sample, there were six replicates. The recoveries of 11 pesticides in apricot at all levels ranged between 72 and 119%. The inter- and intra-level relative standard deviations (RSDs, %) of 11 pesticides in apricot were  More