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    PISCOeo_pm, a reference evapotranspiration gridded database based on FAO Penman-Monteith in Peru

    Allen, R. G. et al. Crop evapotranspiration-guidelines for computing crop water requirements-FAO irrigation and drainage paper 56. FAO, Rome 300, D05109 http://www.fao.org/docrep/X0490E/X0490E00.htm (1998).
    Google Scholar 
    Trenberth, K. E., Fasullo, J. T. & Kiehl, J. Earth’s global energy budget. Bulletin of the American Meteorological Society 90, 311–324, https://doi.org/10.1175/2008BAMS2634.1 (2009).ADS 
    Article 

    Google Scholar 
    Wang, K. & Dickinson, R. E. A review of global terrestrial evapotranspiration: Observation, modeling, climatology, and climatic variability. Reviews of Geophysics 50, https://doi.org/10.1029/2011RG000373 (2012).Liu, W. Evaluating remotely sensed monthly evapotranspiration against water balance estimates at basin scale in the Tibetan Plateau. Hydrology Research 49, 1977–1990, https://doi.org/10.2166/nh.2018.008 (2018).Article 

    Google Scholar 
    Valipour, M., Bateni, S. M., Gholami Sefidkouhi, M. A., Raeini-Sarjaz, M. & Singh, V. P. Complexity of forces driving trend of reference evapotranspiration and signals of climate change. Atmosphere 11, 1081, https://doi.org/10.1007/s41748-021-00252-3 (2020).ADS 
    Article 

    Google Scholar 
    Anwar, S. A., Mamadou, O., Diallo, I. & Sylla, M. B. On the influence of vegetation cover changes and vegetation-runoff systems on the simulated summer potential evapotranspiration of Tropical Africa using RegCM4. Earth Systems and Environment 5, 883–897, https://doi.org/10.3390/atmos11101081 (2021).ADS 
    Article 

    Google Scholar 
    Tomas-Burguera, M., Vicente-Serrano, S. M., Beguera, S., Reig, F. & Latorre, B. Reference crop evapotranspiration database in Spain (1961–2014). Earth System Science Data 11, 1917–1930, https://doi.org/10.5194/essd-11-1917-2019 (2019).ADS 
    Article 

    Google Scholar 
    Córdova, M., Carrillo-Rojas, G., Crespo, P., Wilcox, B. & Célleri, R. Evaluation of the Penman-Monteith (FAO 56 PM) Method for Calculating Reference Evapotranspiration Using Limited Data. Mountain Research and Development 35, 230–239, https://doi.org/10.1659/MRD-JOURNAL-D-14-0024.1 (2015).Article 

    Google Scholar 
    Valle Júnior, L. C. G. d. et al. Evaluation of FAO-56 procedures for estimating reference evapotranspiration using missing climatic data for a Brazilian tropical savanna. Water 13, 1763, https://doi.org/10.3390/w13131763 (2021).Article 

    Google Scholar 
    Djaman, K., Irmak, S. & Futakuchi, K. Daily reference evapotranspiration estimation under limited data in Eastern Africa. Journal of Irrigation and Drainage Engineering 143, 06016015, https://doi.org/10.1061/(ASCE)IR.1943-4774.0001154 (2017).Article 

    Google Scholar 
    Čadro, S., Uzunović, M., Žurovec, J. & Žurovec, O. Validation and calibration of various reference evapotranspiration alternative methods under the climate conditions of Bosnia and Herzegovina. International Soil and Water Conservation Research 5, 309–324, https://doi.org/10.1016/j.iswcr.2017.07.002 (2017).Article 

    Google Scholar 
    Vicente-Serrano, S. M. et al. Recent changes in monthly surface air temperature over Peru, 1964–2014. International Journal of Climatology 38, 283–306, https://doi.org/10.1002/joc.5176 (2018).ADS 
    Article 

    Google Scholar 
    Huerta, A., Aybar, C. & Lavado-Casimiro, W. PISCO temperatura versión 1.1 (PISCOt v1. 1). Lima, Peru: National Meteorology and Hydrology Service of Peru (SENAMHI) https://iridl.ldeo.columbia.edu/SOURCES/.SENAMHI/.HSR/.PISCO/.Temp/ (2018).Lavado Casimiro, W. S., Labat, D., Guyot, J. L. & Ardoin-Bardin, S. Assessment of climate change impacts on the hydrology of the Peruvian Amazon–Andes basin. Hydrological Processes 25, 3721–3734, https://doi.org/10.1002/hyp.8097 (2011).ADS 
    Article 

    Google Scholar 
    Rau, P. et al. Assessing multidecadal runoff (1970–2010) using regional hydrological modelling under data and water scarcity conditions in Peruvian Pacific catchments. Hydrological Processes 33, 20–35, https://doi.org/10.1002/hyp.13318 (2019).ADS 
    Article 

    Google Scholar 
    Olsson, T. et al. Downscaling climate projections for the Peruvian coastal Chancay-Huaral basin to support river discharge modeling with WEAP. Journal of Hydrology: Regional Studies 13, 26–42, https://doi.org/10.1016/j.ejrh.2017.05.011 (2017).Article 

    Google Scholar 
    Lavado-Casimiro, W., Lhomme, J. P., Labat, D. & Loup, J. Estimating reference evapotranspiration (FAO 56 Penman Monteith) with limited climatic data in the Peruvian Amazon-Andes basin. Revista Peruana Geo-Atmosferica 4, 31–43 (2015).
    Google Scholar 
    Hargreaves, G. H. & Samani, Z. A. Reference crop evapotranspiration from temperature. Applied engineering in agriculture 1, 96–99, https://doi.org/10.13031/2013.26773 (1985).Article 

    Google Scholar 
    Laqui, W. et al. Can artificial neural networks estimate potential evapotranspiration in Peruvian highlands? Modeling Earth Systems and Environment 5, 1911–1924, https://doi.org/10.1007/s40808-019-00647-2 (2019).Article 

    Google Scholar 
    Baigorria, G. A., Villegas, E. B., Trebejo, I., Carlos, J. F. & Quiroz, R. Atmospheric transmissivity: distribution and empirical estimation around the central Andes. International Journal of Climatology 24, 1121–1136, https://doi.org/10.1002/joc.1060 (2004).ADS 
    Article 

    Google Scholar 
    Huerta, A. PISCO potential evapotranspiration, https://iridl.ldeo.columbia.edu/SOURCES/.SENAMHI/.HSR/.PISCO/.PET/.Oudin, L., Michel, C. & Anctil, F. Which potential evapotranspiration input for a lumped rainfall-runoff model?: Part 1—can rainfall-runoff models effectively handle detailed potential evapotranspiration inputs? Journal of Hydrology 303, 275–289, https://doi.org/10.1016/j.jhydrol.2004.08.025 (2005).ADS 
    Article 

    Google Scholar 
    Xiang, K., Li, Y., Horton, R. & Feng, H. Similarity and difference of potential evapotranspiration and reference crop evapotranspiration – a review. Agricultural Water Management 232, 106043, https://doi.org/10.1016/j.agwat.2020.106043 (2020).Article 

    Google Scholar 
    Harris, I., Osborn, T. J., Jones, P. & Lister, D. Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset. Scientific data 7, 1–18, https://doi.org/10.1038/s41597-020-0453-3 (2020).Article 

    Google Scholar 
    Abatzoglou, J. T., Dobrowski, S. Z., Parks, S. A. & Hegewisch, K. C. TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015. Scientific data 5, 1–12, https://doi.org/10.1038/sdata.2017.191 (2018).Article 

    Google Scholar 
    Kalnay, E. et al. The NCEP/NCAR 40-year reanalysis project. Bulletin of the American Meteorological Society 77, 437–472, 10.1175/1520-0477(1996)077  2.0.CO;2 (1996).Hersbach, H. et al. The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society 146, 1999–2049, https://doi.org/10.1002/qj.3803 (2020).ADS 
    Article 

    Google Scholar 
    Muñoz Sabater, J. et al. ERA5-Land: a state-of-the-art global reanalysis dataset for land applications. Earth System Science Data 13, 4349–4383, https://doi.org/10.5194/essd-13-4349-2021 (2021).ADS 
    Article 

    Google Scholar 
    Aybar, C. et al. Construction of a high-resolution gridded rainfall dataset for Peru from 1981 to the present day. Hydrological Sciences Journal 65, 770–785, https://doi.org/10.1080/02626667.2019.1649411 (2020).Article 

    Google Scholar 
    Llauca, H., Lavado-Casimiro, W., Montesinos, C., Santini, W. & Rau, P. PISCO_HyM_GR2M: A model of monthly water balance in Peru (1981–2020). Water 13, 1048, https://doi.org/10.3390/w13081048 (2021).Article 

    Google Scholar 
    Gubler, S. et al. The influence of station density on climate data homogenization. International Journal of Climatology 37, 4670–4683, https://doi.org/10.1002/joc.5114 (2017).ADS 
    Article 

    Google Scholar 
    Hunziker, S. et al. Identifying, attributing, and overcoming common data quality issues of manned station observations. International Journal of Climatology 37, 4131–4145, https://doi.org/10.1002/joc.5037 (2017).ADS 
    Article 

    Google Scholar 
    Hunziker, S. et al. Effects of undetected data quality issues on climatological analyses. Climate of the Past 14, 1–20, https://doi.org/10.5194/cp-14-1-2018 (2018).ADS 
    Article 

    Google Scholar 
    Paredes, P., Pereira, L., Almorox, J. & Darouich, H. Reference grass evapotranspiration with reduced data sets: Parameterization of the FAO Penman-Monteith temperature approach and the Hargeaves-Samani equation using local climatic variables. Agricultural Water Management 240, 106210, https://doi.org/10.1016/j.agwat.2020.106210 (2020).Article 

    Google Scholar 
    Irmak, S., Kabenge, I., Skaggs, K. E. & Mutiibwa, D. Trend and magnitude of changes in climate variables and reference evapotranspiration over 116-yr period in the Platte River Basin, central Nebraska–USA. Journal of Hydrology 420, 228–244, https://doi.org/10.1016/j.jhydrol.2011.12.006 (2012).ADS 
    Article 

    Google Scholar 
    Tomas-Burguera, M., Vicente-Serrano, S. M., Grimalt, M. & Beguera, S. Accuracy of reference evapotranspiration (ETo) estimates under data scarcity scenarios in the Iberian Peninsula. Agricultural water management 182, 103–116, https://doi.org/10.1016/j.agwat.2016.12.013 (2017).Article 

    Google Scholar 
    Mardikis, M., Kalivas, D. & Kollias, V. Comparison of interpolation methods for the prediction of reference evapotranspiration—an application in Greece. Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) 19, 251–278, https://doi.org/10.1007/s11269-005-3179-2 (2005).Article 

    Google Scholar 
    McVicar, T. R. et al. Spatially distributing monthly reference evapotranspiration and pan evaporation considering topographic influences. Journal of Hydrology 338, 196–220, https://doi.org/10.1016/j.jhydrol.2007.02.018 (2007).ADS 
    Article 

    Google Scholar 
    Robinson, E. L., Blyth, E. M., Clark, D. B., Finch, J. & Rudd, A. C. Trends in atmospheric evaporative demand in Great Britain using high-resolution meteorological data. Hydrology and Earth System Sciences 21, 1189–1224, https://doi.org/10.5194/hess-21-1189-2017 (2017).ADS 
    Article 

    Google Scholar 
    Mohammadi, B. & Moazenzadeh, R. Performance analysis of daily global solar radiation models in Peru by regression analysis. Atmosphere 12, https://doi.org/10.3390/atmos12030389 (2021).Vicente-Serrano, S. M., Beguería, S., López-Moreno, J. I., García-Vera, M. A. & Stepanek, P. A complete daily precipitation database for northeast Spain: reconstruction, quality control, and homogeneity. International Journal of Climatology 30, 1146–1163, https://doi.org/10.1002/joc.1850 (2010).ADS 
    Article 

    Google Scholar 
    Lanzante, J. R. Resistant, robust and non-parametric techniques for the analysis of climate data: Theory and examples, including applications to historical radiosonde station data. International Journal of Climatology: A Journal of the Royal Meteorological Society 16, 1197–1226, 10.1002/(SICI)1097-0088(199611)16:11 < 1197::AID-JOC89 > 3.0.CO;2-L (1996).ADS 
    Article 

    Google Scholar 
    Wood, W. H., Marshall, S. J., Whitehead, T. L. & Fargey, S. E. Daily temperature records from a mesonet in the foothills of the Canadian Rocky Mountains, 2005–2010. Earth System Science Data 10, 595–607, https://doi.org/10.5194/essd-10-595-2018 (2018).ADS 
    Article 

    Google Scholar 
    Guentchev, G., Barsugli, J. J. & Eischeid, J. Homogeneity of gridded precipitation datasets for the Colorado River basin. Journal of Applied Meteorology and Climatology 49, 2404–2415, https://doi.org/10.1175/2010JAMC2484.1 (2010).ADS 
    Article 

    Google Scholar 
    Oyler, J. W., Ballantyne, A., Jencso, K., Sweet, M. & Running, S. W. Creating a topoclimatic daily air temperature dataset for the conterminous United States using homogenized station data and remotely sensed land skin temperature. International Journal of Climatology 35, 2258–2279, https://doi.org/10.1002/joc.4127 (2015).ADS 
    Article 

    Google Scholar 
    McAfee, S. A., McCabe, G. J., Gray, S. T. & Pederson, G. T. Changing station coverage impacts temperature trends in the Upper Colorado River basin. International Journal of Climatology 39, 1517–1538, https://doi.org/10.1002/joc.5898 (2019).ADS 
    Article 

    Google Scholar 
    Beguería, S., Vicente-Serrano, S. M., Tomás-Burguera, M. & Maneta, M. Bias in the variance of gridded data sets leads to misleading conclusions about changes in climate variability. International Journal of Climatology 36, 3413–3422, https://doi.org/10.1002/joc.4561 (2016).ADS 
    Article 

    Google Scholar 
    Thevakaran, A. & Sonnadara, D. Estimating missing daily temperature extremes in Jaffna, Sri Lanka. Theoretical and applied climatology 132, 145–152, https://doi.org/10.1007/s00704-017-2082-0 (2018).ADS 
    Article 

    Google Scholar 
    Hubbard, K. Spatial variability of daily weather variables in the high plains of the USA. Agricultural and Forest Meteorology 68, 29–41, https://doi.org/10.1016/0168-1923(94)90067-1 (1994).ADS 
    Article 

    Google Scholar 
    Camargo, M. B. & Hubbard, K. G. Spatial and temporal variability of daily weather variables in sub-humid and semi-arid areas of the United States high plains. Agricultural and forest meteorology 93, 141–148, https://doi.org/10.1016/S0168-1923(98)00122-1 (1999).ADS 
    Article 

    Google Scholar 
    Brugnara, Y., Good, E., Squintu, A. A., van der Schrier, G. & Brönnimann, S. The EUSTACE global land station daily air temperature dataset. Geoscience Data Journal 6, 189–204, https://doi.org/10.5285/7925ded722d743fa8259a93acc7073f2 (2019).ADS 
    Article 

    Google Scholar 
    Gonzalez-Hidalgo, J. C., Peña-Angulo, D., Brunetti, M. & Cortesi, N. MOTEDAS: a new monthly temperature database for mainland Spain and the trend in temperature (1951–2010). International Journal of Climatology 35, 4444–4463, https://doi.org/10.1002/joc.4298 (2015).ADS 
    Article 

    Google Scholar 
    Gudmundsson, L., Bremnes, J. B., Haugen, J. E. & Engen-Skaugen, T. Technical note: Downscaling RCM precipitation to the station scale using statistical transformations – a comparison of methods. Hydrology and Earth System Sciences 16, 3383–3390, https://doi.org/10.5194/hess-16-3383-2012 (2012).ADS 
    Article 

    Google Scholar 
    Stanley, T., Kirschbaum, D. B., Huffman, G. J. & Adler, R. F. Approximating long-term statistics early in the global precipitation measurement era. Earth Interactions 21, 1–10, https://doi.org/10.1175/EI-D-16-0025.1 (2017).Article 

    Google Scholar 
    Haimberger, L. Homogenization of radiosonde temperature time series using innovation statistics. Journal of Climate 20, 1377–1403, https://doi.org/10.1175/JCLI4050.1 (2007).ADS 
    Article 

    Google Scholar 
    Menne, M. J. & Williams, C. N. Homogenization of temperature series via pairwise comparisons. Journal of Climate 22, 1700–1717, https://doi.org/10.1175/2008JCLI2263.1 (2009).ADS 
    Article 

    Google Scholar 
    Vincent, L. A., Zhang, X., Bonsal, B. R. & Hogg, W. D. Homogenization of daily temperatures over Canada. Journal of Climate 15, 1322–1334, 10.1175/1520-0442(2002)015 < 1322:HODTOC > 2.0.CO;2 (2002).ADS 
    Article 

    Google Scholar 
    Jin, M. & Dickinson, R. E. Land surface skin temperature climatology: Benefitting from the strengths of satellite observations. Environmental Research Letters 5, 044004, https://doi.org/10.1088/1748-9326/5/4/044004 (2010).ADS 
    Article 

    Google Scholar 
    Wan, Z., Hook, S. & Hulley, G. MOD11A2 MODIS/Terra land surface temperature/emissivity 8-day l3 global 1 km SIN grid v006. NASA EOSDIS Land Processes DAAC 10, https://doi.org/10.5067/MODIS/MOD11A2.006 (2015).Wilson, A. M. & Jetz, W. Remotely sensed high-resolution global cloud dynamics for predicting ecosystem and biodiversity distributions. PLoS biology 14, e1002415, https://doi.org/10.1371/journal.pbio.1002415 (2016).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Danielson, J. J. & Gesch, D. B. Global multi-resolution terrain elevation data 2010 (GMTED2010) (US Department of the Interior, US Geological Survey Washington, DC, USA, 2011).Holden, Z. A., Abatzoglou, J. T., Luce, C. H. & Baggett, L. S. Empirical downscaling of daily minimum air temperature at very fine resolutions in complex terrain. Agricultural and Forest Meteorology 151, 1066–1073, https://doi.org/10.1016/j.agrformet.2011.03.011 (2011).ADS 
    Article 

    Google Scholar 
    Fick, S. E. & Hijmans, R. J. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. International journal of climatology 37, 4302–4315, https://doi.org/10.1002/joc.5086 (2017).ADS 
    Article 

    Google Scholar 
    Willmott, C. J. & Robeson, S. M. Climatologically aided interpolation (CAI) of terrestrial air temperature. International Journal of Climatology 15, 221–229, https://doi.org/10.1002/joc.3370150207 (1995).ADS 
    Article 

    Google Scholar 
    Hunter, R. D. & Meentemeyer, R. K. Climatologically aided mapping of daily precipitation and temperature. Journal of Applied Meteorology 44, 1501–1510, https://doi.org/10.1175/JAM2295.1 (2005).ADS 
    Article 

    Google Scholar 
    Parmentier, B. et al. Using multi-timescale methods and satellite-derived land surface temperature for the interpolation of daily maximum air temperature in Oregon. International Journal of Climatology 35, 3862–3878, https://doi.org/10.1002/joc.4251 (2015).ADS 
    Article 

    Google Scholar 
    Hengl, T., Heuvelink, G. B. & Rossiter, D. G. About regression-kriging: From equations to case studies. Computers & Geosciences 33, 1301–1315, https://doi.org/10.1016/j.cageo.2007.05.001. Spatial Analysis (2007).Sun, X.-L., Yang, Q., Wang, H.-L. & Wu, Y.-J. Can regression determination, nugget-to-sill ratio and sampling spacing determine relative performance of regression kriging over ordinary kriging? CATENA 181, 104092, https://doi.org/10.1016/j.catena.2019.104092 (2019).Article 

    Google Scholar 
    Trajkovic, S. & Gocic, M. Evaluation of three wind speed approaches in temperature-based ET 0 equations: a case study in Serbia. Arabian Journal of Geosciences 14, 1–8, https://doi.org/10.1007/s12517-020-06331-5 (2021).Article 

    Google Scholar 
    Fotheringham, A. S., Brunsdon, C. & Charlton, M. Geographically weighted regression: the analysis of spatially varying relationships (John Wiley & Sons, 2003).Comber, A. et al. A route map for successful applications of geographically weighted regression. Geographical Analysis https://doi.org/10.1111/gean.12316 (2021).Li, X., Zhou, Y., Asrar, G. R. & Zhu, Z. Developing a 1 km resolution daily air temperature dataset for urban and surrounding areas in the conterminous United States. Remote Sensing of Environment 215, 74–84, https://doi.org/10.1016/j.rse.2018.05.034 (2018).ADS 
    Article 

    Google Scholar 
    Wu, J., Zhong, B., Tian, S., Yang, A. & Wu, J. Downscaling of urban land surface temperature based on multi-factor geographically weighted regression. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 12, 2897–2911, https://doi.org/10.1109/JSTARS.2019.2919936 (2019).ADS 
    Article 

    Google Scholar 
    Zhang, G., Zhu, S., Zhang, N., Zhang, G. & Xu, Y. Downscaling hourly air temperature of WRF simulations over complex topography: A case study of Chongli District in Hebei Province, China. Journal of Geophysical Research: Atmospheres 127, e2021JD035542, https://doi.org/10.1029/2021JD035542 (2022).ADS 
    Article 

    Google Scholar 
    Callañaupa Gutierrez, S. et al. Seasonal variability of daily evapotranspiration and energy fluxes in the Central Andes of Peru using eddy covariance techniques and empirical methods. Atmospheric Research 261, 105760, https://doi.org/10.1016/j.atmosres.2021.105760 (2021).Article 

    Google Scholar 
    Zotarelli, L., Dukes, M. D., Romero, C. C., Migliaccio, K. W. & Morgan, K. T. Step by step calculation of the Penman-Monteith Evapotranspiration (FAO-56 Method). Institute of Food and Agricultural Sciences. University of Florida https://edis.ifas.ufl.edu/pdf/AE/AE45900.pdf (2010).Huerta, A. PISCOeo_pm, a reference evapotranspiration gridded database based on FAO Penman-Monteith in Peru. figshare https://doi.org/10.6084/m9.figshare.c.5633182.v3 (2021).Willmott, C. J., Robeson, S. M. & Matsuura, K. A refined index of model performance. International Journal of climatology 32, 2088–2094, https://doi.org/10.1002/joc.2419 (2012).ADS 
    Article 

    Google Scholar 
    Legates, D. R. & McCabe, G. J. A refined index of model performance: a rejoinder. International Journal of Climatology 33, 1053–1056, https://doi.org/10.1002/joc.3487 (2013).ADS 
    Article 

    Google Scholar 
    Durre, I., Menne, M. J., Gleason, B. E., Houston, T. G. & Vose, R. S. Comprehensive automated quality assurance of daily surface observations. Journal of Applied Meteorology and Climatology 49, 1615–1633, https://doi.org/10.1175/2010JAMC2375.1 (2010).ADS 
    Article 

    Google Scholar 
    Huerta, A. & Lavado-Casimiro, W. Atlas de Zonas Áridas del Perú: una evaluación presente y futura (Servicio Nacional de Meteorología e Hidrología del Perú, Lima, Perú, 2021).Singer, M. B. et al. Hourly potential evapotranspiration at 0.1° resolution for the global land surface from 1981-present. Scientific Data 8, 1–13, https://doi.org/10.1038/s41597-021-01003-9 (2021).Article 

    Google Scholar 
    Pelosi, A. & Chirico, G. Regional assessment of daily reference evapotranspiration: Can ground observations be replaced by blending ERA5-Land meteorological reanalysis and CM-SAF satellite-based radiation data? Agricultural Water Management 258, 107169, https://doi.org/10.1016/j.agwat.2021.107169 (2021).Article 

    Google Scholar 
    McCuen, R. H. A sensitivity and error analysis cf procedures used for estimating evaporation. JAWRA Journal of the American Water Resources Association 10, 486–497, https://doi.org/10.1111/j.1752-1688.1974.tb00590.x (1974).ADS 
    Article 

    Google Scholar 
    Coleman, G. & DeCoursey, D. G. Sensitivity and model variance analysis applied to some evaporation and evapotranspiration models. Water Resources Research 12, 873–879, https://doi.org/10.1029/WR012i005p00873 (1976).ADS 
    Article 

    Google Scholar 
    Beven, K. A sensitivity analysis of the Penman-Monteith actual evapotranspiration estimates. Journal of Hydrology 44, 169–190, https://doi.org/10.1016/0022-1694(79)90130-6 (1979).ADS 
    Article 

    Google Scholar 
    Hupet, F. & Vanclooster, M. Effect of the sampling frequency of meteorological variables on the estimation of the reference evapotranspiration. Journal of Hydrology 243, 192–204, https://doi.org/10.1016/S0022-1694(00)00413-3 (2001).ADS 
    Article 

    Google Scholar 
    Ali, M. et al. Sensitivity of Penman–Monteith estimates of reference evapotranspiration to errors in input climatic data. Journal of Agrometeorology 11, 1–8, https://journal.agrimetassociation.org/index.php/jam/article/view/1214 (2009).
    Google Scholar 
    Field, C. B., Jackson, R. B. & Mooney, H. A. Stomatal responses to increased CO2: implications from the plant to the global scale. Plant, Cell & Environment 18, 1214–1225, https://doi.org/10.1111/j.1365-3040.1995.tb00630.x (1995).Article 

    Google Scholar 
    Roderick, M. L., Greve, P. & Farquhar, G. D. On the assessment of aridity with changes in atmospheric CO2. Water Resources Research 51, 5450–5463, https://doi.org/10.1002/2015WR017031 (2015).ADS 
    CAS 
    Article 

    Google Scholar 
    Swann, A. L., Hoffman, F. M., Koven, C. D. & Randerson, J. T. Plant responses to increasing CO2 reduce estimates of climate impacts on drought severity. Proceedings of the National Academy of Sciences 113, 10019–10024, https://doi.org/10.1073/pnas.1604581113 (2016).ADS 
    CAS 
    Article 

    Google Scholar 
    Milly, P. C. & Dunne, K. A. Potential evapotranspiration and continental drying. Nature Climate Change 6, 946–949, https://doi.org/10.1038/nclimate3046 (2016).ADS 
    Article 

    Google Scholar 
    Greve, P., Roderick, M. L. & Seneviratne, S. I. Simulated changes in aridity from the last glacial maximum to 4xCO2. Environmental Research Letters 12, 114021, https://doi.org/10.1088/1748-9326/aa89a3 (2017).ADS 
    CAS 
    Article 

    Google Scholar 
    Scheff, J. Drought indices, drought impacts, CO2, and warming: a historical and geologic perspective. Current Climate Change Reports 4, 202–209, https://doi.org/10.1007/s40641-018-0094-1 (2018).Article 

    Google Scholar 
    Swann, A. L. Plants and drought in a changing climate. Current Climate Change Reports 4, 192–201, https://doi.org/10.1007/s40641-018-0097-y (2018).Article 

    Google Scholar 
    Lemordant, L., Gentine, P., Swann, A. S., Cook, B. I. & Scheff, J. Critical impact of vegetation physiology on the continental hydrologic cycle in response to increasing CO2. Proceedings of the National Academy of Sciences 115, 4093–4098, https://doi.org/10.1073/pnas.1720712115 (2018).ADS 
    CAS 
    Article 

    Google Scholar 
    Yang, Y., Roderick, M. L., Zhang, S., McVicar, T. R. & Donohue, R. J. Hydrologic implications of vegetation response to elevated CO2 in climate projections. Nature Climate Change 9, 44–48, https://doi.org/10.1038/s41558-018-0361-0 (2019).ADS 
    CAS 
    Article 

    Google Scholar 
    Greve, P., Roderick, M., Ukkola, A. & Wada, Y. The aridity index under global warming. Environmental Research Letters 14, 124006, https://doi.org/10.1088/1748-9326/ab5046 (2019).ADS 
    CAS 
    Article 

    Google Scholar 
    Huerta, A. & Gutierrez, L. PISCOeo_pm. figshare https://doi.org/10.6084/m9.figshare.19686738.v1 (2022). More

  • in

    Comparative metagenomics reveals expanded insights into intra- and interspecific variation among wild bee microbiomes

    Engel, M. S. A new interpretation of the oldest fossil bee (Hymenoptera: Apidae). Am. Mus. Novit. 3296, 1–11 (2000).Article 

    Google Scholar 
    Michener, C. D. The Bees of the World 2nd edn, (John Hopkins University Press, 2007).Klein, A. M. et al. Importance of pollinators in changing landscapes for world crops. Proc. R. Soc. B. 274, 303–313 (2007).PubMed 
    Article 

    Google Scholar 
    Fürst, M., McMahon, D. P., Osborne, J. L., Paxton, R. J. & Brown, M. J. F. Disease associations between honeybees and bumblebees as a threat to wild pollinators. Nature 506, 364–366 (2014).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    McMahon, D. P., Wilfert, L., Paxton, R. J. & Brown, M. J. F. Emerging viruses in bees: from molecules to ecology. Adv. Virus Res. 101, 251–291 (2015).Article 

    Google Scholar 
    Koch, H., Abrol, D. P., Li, J. & Schmid-Hempel, P. Diversity of evolutionary patterns of bacterial gut associates of corbiculate bees. Mol. Ecol. 22, 2028–2044 (2013).CAS 
    PubMed 
    Article 

    Google Scholar 
    McFrederick, Q. S. et al. Environment or kin: whence do bees obtain acidophilic bacteria? Mol. Ecol. 21, 1754–1768 (2012).PubMed 
    Article 

    Google Scholar 
    McFrederick, Q. S., Wcislo, W. T., Hout, M. C. & Mueller, U. G. Host species and developmental stage, but not host social structure, affects bacterial community structure in social polymorphic bees. FEMS Microbiol. Ecol. 88, 398–406 (2014).CAS 
    PubMed 
    Article 

    Google Scholar 
    McFrederick, Q. S. et al. Flowers and wild megachilid bees share microbes. Microb. Ecol. 73, 188–200 (2017).PubMed 
    Article 

    Google Scholar 
    Jones, J. C. et al. The gut microbiome is associated with behavioural task in honey bees. Insectes Sociaux 65, 419–429 (2018).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Kristensen, T. N., Schonherz, A., Rohde, P. D., Sorensen, J. G. & Loeschcke, V. Strong experimental support for the hologenome hypothesis revealed from Drosophila melanogaster selection lines. bioRxiv https://doi.org/10.1101/2021.09.09.459587 (2021)Bovo, S., Utzeri, V. J., Ribani, A., Cabbri, R. & Fontanesi, L. Shotgun sequencing of honey DNA can describe honey bee derived environmental signatures and the honey bee hologenome complexity. Sci. Rep. 10, 1–17 (2020).Article 
    CAS 

    Google Scholar 
    Dharampal, P. S., Carlson, C., Currie, C. R. & Steffan, S. A. Pollen-borne microbes shape bee fitness. Proc. R. Soc. B. 286, 20182894 (2019).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Graystock, P., Rehan, S. M. & McFrederick, Q. S. Hunting for healthy microbiomes: determining the core microbiomes of Ceratina, Megalopta, and Apis bees and how they associate with microbes in bee collected pollen. Conserv. Genet. 18, 701–711 (2017).Article 

    Google Scholar 
    Engel, P. et al. The bee microbiome: impact on bee health and model for evolution and ecology of host-microbe interactions. MBio 7, e02164–15 (2016).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Voulgari-Kokota, A., McFrederick, Q. S., Steffan-Dewenter, I. & Keller, A. Drivers, diversity, and functions of the solitary-bee microbiota. Trends Microbiol 27, 1034–1044 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    Rothman, J. A., Leger, L., Graystock, P., Russell, K. & McFrederick, Q. S. The bumble bee microbiome increases survival of bees exposed to selenate toxicity. Environ. Microbiol. 21, 3417–3429 (2019).CAS 
    Article 

    Google Scholar 
    Engel, P., Martinson, V. G. & Moran, N. A. Functional diversity within the simple gut microbiota of the honey bee. PNAS 109, 11002–11007 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Engel, P. & Moran, N. A. Functional and evolutionary insights into the simple yet specific gut microbiota of the honey bee from metagenomic analysis. Gut Microbes 4, 60–65 (2013).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Kwong, W. K. et al. Dynamic microbiome evolution in social bees. Sci. Adv. 3, e1600513 (2017).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Breeze, T. D., Bailey, A. P., Balcombe, K. G. & Potts, S. G. Pollination services in the UK: How important are honeybees? Agric. Ecosyst. Environ. 142, 137–143 (2011).Article 

    Google Scholar 
    Dharampal, P. S., Hetherington, M. C. & Steffan, S. A. Microbes make the meal: oligolectic bees require microbes within their host pollen to thrive. Ecol. Entomol. 45, 1418–1427 (2020).Article 

    Google Scholar 
    Keller, A. et al. (More than) hitchhikers through the network: the shared microbiome of bees and flowers. Curr. Opin. Insect 44, 8–15 (2021).Article 

    Google Scholar 
    Hugenholtz, P. & Tyson, G. W. Metagenomics. Nature 455, 481–483 (2008).CAS 
    PubMed 
    Article 

    Google Scholar 
    Galbraith, D. A. et al. Investigating the viral ecology of global bee communities with high- throughput metagenomics. Sci. Rep. 8, 8879 (2018).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Regan, T. et al. Characterisation of the British honey bee metagenome. Nat. Commun. 9, 1–13 (2018).CAS 
    Article 

    Google Scholar 
    Bovo, S. et al. Shotgun metagenomics of honey DNA: Evaluation of a methodological approach to describe a multi-kingdom honey bee derived environmental DNA signature. PLOS ONE 13, e0205575 (2018).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Schoonvaere, K. et al. Unbiased RNA shotgun metagenomics in social and solitary wild bees detects associations with eukaryote parasites and new viruses. PLOS ONE 11, e0168456 (2016).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Cox-Foster, D. L. et al. A metagenomic survey of microbes in honey bee colony collapse disorder. Science 318, 283–287 (2007).CAS 
    PubMed 
    Article 

    Google Scholar 
    Rehan, S. M., Leys, R. & Schwarz, M. P. A mid-cretaceous origin of sociality in xylocopine bees with only two origins of true worker castes. PLOS ONE 7, e34690 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Rehan, S. M. Small carpenter bees (Ceratina). Encyclopedia of Social Insects (ed Chris, S.) (Springer, 2020).Sakagami, S. F. & Maeta, Y. Multifemale nests and rudimentary castes in the normally solitary bee Ceratina japonica (Hymenoptera: Xylocopinae). J. Kans. Entomol. 57, 639–656 (1984).
    Google Scholar 
    Huisken, J. L., Shell, W. A., Pare, H. K. & Rehan, S. M. The influence of social environment on cooperating and conflict in an incipiently social bee, Ceratina calcarata. Behav. Ecol. 75, 74 (2021).Article 

    Google Scholar 
    Rehan, S. M., Glastad, K. M., Lawson, S. P. & Hunt, B. G. The genome and methylome of a subsocial small carpenter bee, Ceratina calcarata. GBE 8, 1401–1410 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Rehan, S. M. et al. Conserved genes underlie phenotypic plasticity in an incipiently social bee. GBE 10, 2749–2758 (2018).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Arsenault, S. V., Hunt, B. G. & Rehan, S. M. The effect of maternal care on gene expression and DNA methylation in a subsocial bee. Nat. Commun. 9, 3468 (2018).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Shell, W. A. et al. Sociality sculpts similar patterns of molecular evolution in two independently evolved lineages of eusocial bees. Comms. Biol. 4, 1–9 (2021).Article 
    CAS 

    Google Scholar 
    Dew, R. M., McFrederick, Q. S. & Rehan, S. M. Diverse diets with consistent core microbiome in wild bee pollen provisions. Insects 11, 49 (2020).Article 

    Google Scholar 
    Lawson, S. P., Kennedy, K. & Rehan, S. M. Pollen composition significantly impacts development and survival of the native small carpenter bee, Ceratina calcarata. Ecol. Entomol. 46, 232–239 (2021).Article 

    Google Scholar 
    Oppenheimer, R. L., Shell, W. A. & Rehan, S. M. Phylogeography and population genetics of the Australian small carpenter bee, Ceratina australensis. Biol. J. Linn. Soc. 124, 747–755 (2018).Article 

    Google Scholar 
    McFrederick, Q. S. & Rehan, S. M. Wild bee pollen usage and microbial communities co- vary across landscapes. Microb. Ecol. 77, 513–522 (2018).PubMed 
    Article 
    CAS 

    Google Scholar 
    Rehan, S. M., Richards, M. H. & Schwarz, M. P. Sociality in the Australian small carpenter bee Ceratina (Neoceratina) australensis. Insectes Sociaux 57, 403–412 (2010).Article 

    Google Scholar 
    Harpur, B. A. & Rehan, S. M. Connecting social polymorphism to single nucleotide polymorphism: population genomics of the small carpenter bee, Ceratina australensis. Biol. J. Linn. Soc. 132, 945–954 (2021).Article 

    Google Scholar 
    Neu, A. T., Allen, E. E. & Roy, K. Defining and quantifying the core microbiome: challenges and prospects. PNAS 118, e2104429118 (2021).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Lawson, S. P., Ciaccio, K. N. & Rehan, S. M. Maternal manipulation of pollen provisions affects worker production in a small carpenter bee. Behav. Ecol. 70, 1891–1900 (2016).Article 

    Google Scholar 
    Ganeshprasad, D. N., Jani, K., Shouche, Y. S. & Sneharani, A. H. Gut bacterial inhabitants of open nested honey bee, Apis florea. Preprint at https://assets.researchsquare.com/files/rs-225332/v1/ddf21abe-2456-4f45-af61-4ba3e81d16e7.pdf?c=1641312753 (2021).Rothman, J. A., Cox-Foster, D. L., Andrikopoulos, C. & McFrederick, Q. S. Diet breadth affects bacterial identity but not diversity in the pollen provisions of closely related polylectic and oligolectic bees. Insects 11, 1–13 (2020).Article 

    Google Scholar 
    Cohen, H., McFrederick, Q. S. & Philpott, S. M. Environment shapes the microbiome of the blue orchard bee, Osmia lignaria. Microb. Ecol. 80, 897–907 (2020).PubMed 
    Article 

    Google Scholar 
    Dew, R. M., Rehan, S. M. & Schwarz, M. P. Biogeography and demography of an Australian native bee Ceratina australensis (Hymenoptera: Apidae) since the last glacial maximum. J. Hymenopt. Res. 49, 25–41 (2016).Article 

    Google Scholar 
    Pinto-Tomás, A. A. et al. Symbiotic nitrogen fixation in the fungus gardens of leaf-cutter ants. Science 326, 1120–1123 (2009).PubMed 
    Article 
    CAS 

    Google Scholar 
    Walterson, A. M. & Stavrinides, J. Pantoea insights into a highly versatile and diverse genus within the Enterobacteriaceae. FEMS Microbiol. Rev. 39, 968–984 (2015).CAS 
    PubMed 
    Article 

    Google Scholar 
    Scheiner, R., Strauß, S., Thamm, M., Farré-Armengol, G. & Junker, R. R. The bacterium Pantoea ananatis modifies behavioral responses to sugar solutions in honeybees. Insects 11, 692 (2020).PubMed Central 
    Article 

    Google Scholar 
    Leonhardt, S. D. & Kaltenpoth, M. Microbial communities of three sympatric Australian stingless bee species. Plos ONE 9, e105718 (2014).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Bailey, L. & Ball, B. V. Honey Bee Pathology (Academic Press, 1991).Tham, V. L. Isolation of Streptococcus pluton from the larvae of European honey bees in Australia. Aust. Vet. J. 54, 406–407 (1978).CAS 
    PubMed 
    Article 

    Google Scholar 
    Bowman, J. The genus Flavobacterium. Prokaryotes 7, 481–531 (2006).
    Google Scholar 
    Voordouw, G. The genus Desulovibrio: The centennial. Appl. Environ. Microbiol. 61, 2813–2819 (1995).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Singaravelen, N., Nee’man, G., Inbar, M. & Izhaki, I. Feeding responses of free-flying honeybees to secondary compounds mimicking floral nectars. J. Chem. Ecol. 31, 2791–2804 (2005).Article 
    CAS 

    Google Scholar 
    Baracchi, D., Marples, A., Jenkins, A. J., Leitch, A. R. & Chittka, L. Nicotine in floral nectar pharmacologically influences bumblebee learning of floral features. Sci. Rep. 7, 1951 (2017).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Adler, L. S. & Irwin, R. E. Ecological costs and benefits of defenses in nectar. Ecology 86, 2968–2978 (2005).Article 

    Google Scholar 
    Bally, J. et al. Nicotiana paulineana, a new Australian species in Nicotiana section Suaveolentes. Aust. Syst. Bot. 34, 477–484 (2021).Article 

    Google Scholar 
    Coenye, T. & Vandamme, P. Diversity and significance of Burkholderia species occupying diverse ecology niches. Environ. Microbiol. 5, 719–729 (2003).CAS 
    PubMed 
    Article 

    Google Scholar 
    Levy, A., Merritt, A. J., Aravena-Roman, M., Hodge, M. M. & Inglis, T. J. J. Expanded range of Burkholderia species in Australia. Am. J. Trop. Med. Hyg. 78, 599–604 (2008).CAS 
    PubMed 
    Article 

    Google Scholar 
    Kaltenpoth, M. & Flórez, L. V. Versatile and dynamic symbioses between insects and Burkholderia bacteria. Annu. Rev. Entomol. 65, 145–170 (2019).PubMed 
    Article 
    CAS 

    Google Scholar 
    Foley, K., Fazio, G., Jensen, A. B. & Hughes, W. O. H. Nutritional limitation and resistance to opportunistic Aspergillus parasites in honey bee larvae. J. Invertebr. Pathol. 111, 68–73 (2012).PubMed 
    Article 

    Google Scholar 
    Yoder, J. A. et al. Fungicide contamination reduces beneficial fungi in bee bread based on an area-wide field study in honey bee, Apis mellifera, colonies. J. Toxicol. Environ. Health Part A 76, 587–600 (2013).CAS 
    Article 

    Google Scholar 
    Yun, J.-H., Jung, M.-J., Kim, P. S. & Bae, J.-W. Social status shapes the bacterial and fungal gut communities of the honey bee. Sci. Rep. 8, 1–11 (2018).
    Google Scholar 
    Dew, R. M., Silva, D. P. & Rehan, S. M. Range expansion of an already widespread bee under climate change. GECCO 17, e00584 (2019).
    Google Scholar 
    Cambra, M., Capote, N. & Myrta, A. & Llácer, G. Plum pox virus and the estimated costs associated with sharka disease. EPPO Bull. 36, 202–204 (2006).Article 

    Google Scholar 
    Roberts, J. M. K., Ireland, K. B., Tay, W. T. & Paini, D. Honey bee-assisted surveillance for early plant virus detection. Ann. Appl. Biol. 173, 285–293 (2018).CAS 
    Article 

    Google Scholar 
    Elliott, B. et al. Pollen diets and niche overlap of honey bees and native bees in protected areas. BAAE 50, 169–180 (2021).
    Google Scholar 
    Porrini, C. et al. Use of honey bees as bioindicators of environmental pollution in Italy. in Honey bees: estimating the environmental impact of chemicals (eds Devillers, J. & Pham-Delegue, M.-H.) (Taylor & Francis Press, 2002).Kennedy, P., Higginson, A. D., Radford, A. N. & Sumner, S. Altruism in a volatile world. Nature 555, 359–362 (2018).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Rubin, B. E. R., Sanders, J. G., Turner, K. M., Pierce, N. E. & Kocher, S. D. Social behaviour in bees influences the abundance of Sodalis (Enterobacteriaceae) symbionts. R. Soc. Open Sci. 5, 180369 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Mohr, K. I. & Tebbe, C. C. Diversity and phylotype consistency of bacteria in the guts of three bee species (Apoidea) at an oilseed rape field. Environ. Microbiol. 8, 258–272 (2006).CAS 
    PubMed 
    Article 

    Google Scholar 
    Raymann, K. & Moran, N. A. The role of the gut microbiome in health and disease of adult honey bee workers. Curr. Opin. Insect Sci. 26, 97–104 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Amin, F. A. Z. et al. Probiotic properties of Bacillus strains isolated from stingless bee (Heterotrigona itama) honey collected across Malaysia. Int. J. Envrion. Res. Public Health 17, 1–15 (2020).
    Google Scholar 
    Takeshita, K. & Kikuchi, Y. Riptortus pedestris and Burkholderia symbiont: an ideal model system for insect-microbe symbiotic associations. Res. Microbiol. 168, 175–187 (2017).PubMed 
    Article 

    Google Scholar 
    Martinson, V. G. et al. A simple and distinctive microbiota associated with honey bees and bumble bees. Mol. Ecol. 20, 619–628 (2011).PubMed 
    Article 

    Google Scholar 
    D’Alvise, P. et al. The impact of winter feed type on intestinal microbiota and parasites in honey bees. Apidologie 49, 252–264 (2018).Article 
    CAS 

    Google Scholar 
    Wang, L. et al. Dynamic changes of gut microbial communities of bumble bee queens through important life stages. mSystems 4, e00631–19 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Kapheim, K. M., Johnson, M. M. & Jolley, M. Composition and acquisition of the microbiome in solitary, ground-nesting alkali bees. Sci. Rep. 11, 2993 (2021).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Abdelazez, A. et al. Potential benefits of Lactobacillus plantarum as probiotic and its advantages in human health and industrial applications: A review. Adv. Environ. Biol. 12, 16–27 (2018).CAS 

    Google Scholar 
    Frese, S. A. et al. The evolution of host specialization in the vertebrate gut symbiont Lactobacillus reuteri. PLoS Genet 7, e1001314 (2011).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Duar, R. M. et al. Lifestyles in transition: evolution and natural history of the genus Lactobacillus. FEMS Microbiol. Rev. 41, S27–S48 (2017).PubMed 
    Article 

    Google Scholar 
    Tejerina, M. R., Cabana, M. J. & Benitez-Ahrendts, M. R. Strains of Lactobacillus spp. reduce chalkbrood in Apis mellifera. J. Invertebr. Pathol. 178, 107521 (2021).CAS 
    PubMed 
    Article 

    Google Scholar 
    Vásquez, A. et al. Symbionts as major modulators of insect health: Lactic acid bacteria and honeybees. PLOS ONE 7, e33188 (2012).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Voulgari-Kokota, A., Steffan-Dewenter, I. & Keller, A. Susceptibility of red mason bee larvae to bacterial threats due to microbiome exchange with imported pollen provisions. Insects 11, 1–14 (2020).Article 

    Google Scholar 
    Steffan, S. A. et al. Omnivory in bees: Elevated trophic positions among all major bee families. Am. Nat. 194, 414–421 (2019).PubMed 
    Article 

    Google Scholar 
    Hurst, P. S. Social biology of Exoneurella tridentata, an allodapine bee with morphological castes and perennial colonies. Unpublished D. Phil. Thesis (Flinders University, 2001).Chalita, M. et al. Improved metagenomic taxonomic profiling using a curated core gene- based bacterial database reveals unrecognized species in the genus Streptococcus. Pathogens 9, 204 (2021).Article 

    Google Scholar 
    Rehan, S. M. & Toth, A. L. Climbing the social ladder: molecular evolution of sociality. Trends Ecol. Evol. 30, 426–433 (2015).PubMed 
    Article 

    Google Scholar 
    Shell, W. A. & Rehan, S. M. Behavioral and genetic mechanisms of social evolution: insights from incipiently and facultatively social bees. Apidologie 49, 13–30 (2018).CAS 
    Article 

    Google Scholar 
    Kirby, K. S. Isolation and characterization of ribosomal ribonucleic acid. Biochem. J. 96, 266–269 (1956).Article 

    Google Scholar 
    Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 1754–1760 (2019).Article 
    CAS 

    Google Scholar 
    Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Tsilimigras, M. C. B. & Fodor, A. A. Compositional data analysis of the microbiome: fundamentals, tools, and challenges. Ann. Epidemiol. 26, 330–335 (2016).PubMed 
    Article 

    Google Scholar 
    Wood, D. E., Lu, J. & Langmead, B. Improved metagenomic analysis with Kraken 2. Genome Biol. 20, 257 (2019).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Nurk, S., Meleshko, D., Korobeynikov, A. & Pevzner, P. A. metaSPAdes: a new versatile metagenomic assembler. Genome Res 27, 824–834 (2017).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    Altschul, S. F. et al. Basic local alignment search tool. J. Mol. Biol. 215, 403–410 (1990).CAS 
    PubMed 
    Article 

    Google Scholar 
    Oksanen, J. et al. Package ‘vegan’. Community Ecology package, version 2, 1–295 (2013).Hammer, Ø., Harper, D. A. T. & Ryan, P. D. PAST: Paleontological statistics software package for education and data analysis. Palaeontol. Electron. 4, 9 (2001).
    Google Scholar 
    Buchfink, B., Xie, C. & Huson, D. H. Fast and sensitive protein alignment using DIAMOND. Nat. Methods 12, 59–60 (2015).CAS 
    PubMed 
    Article 

    Google Scholar 
    Mina, R., Haixu, T. & Yuzhen, Y. FragGeneScan: predicting genes in short and error-prone reads. Nucleic Acids Res. 38, e191 (2010).Article 
    CAS 

    Google Scholar 
    Kanehisa, M., Sato, Y. & Morishima, K. BlastKOALA and GhostKOALA: KEGG tools for functional characterization of genome and metagenome sequences. J. Mol. Biol. 428, 726–731 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    Huerta-Cepas, J. et al. Fast genome-wide functional annotation through orthology assignment by eggNOG-mapper. Mol. Biol. Evol. 34, 2115–2122 (2017).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 1–21 (2014).Article 
    CAS 

    Google Scholar 
    Langfelder, P. & Horvath, S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinf 9, 599 (2008).Article 
    CAS 

    Google Scholar 
    Langfelder, P. & Horvath, S. Tutorials for the WGCNA package. https://horvath.genetics.ucla.edu/html/CoexpressionNetwork/Rpackages/WGCNA/Tutorials/ (2016).Liaw, A. & Wiener, M. Classification and regression by randomForest. R. N. 2, 18–22 (2002).
    Google Scholar 
    Kuhn, M. Building predictive models in R using the caret package. J. Stat. Softw. 28, 1–26 (2008).Article 

    Google Scholar 
    Paluszynska, A. Structure mining and knowledge extraction from random forest with applications to The Cancer Genome Atlas project. Master’s Thesis (University of Warsaw, 2017). More

  • in

    SEM/EDX analysis of stomach contents of a sea slug snacking on a polluted seafloor reveal microplastics as a component of its diet

    Derraik, J. G. The pollution of the marine environment by plastic debris: A review. Mar. Pollut. Bull. 44(9), 842–852 (2002).CAS 
    PubMed 

    Google Scholar 
    Gregory, M. R. Environmental implications of plastic debris in marine settings—Entanglement, ingestion, smothering, hangers-on, hitch-hiking and alien invasions. Philos. Trans. R. Soc. B Biol. Sci. 364(1526), 2013–2025 (2009).
    Google Scholar 
    Claessens, M., Van Cauwenberghe, L., Vandegehuchte, M. B. & Janssen, C. R. New techniques for the detection of microplastics in sediments and field collected organisms. Mar. Pollut. Bull. 70(1–2), 227–233 (2013).CAS 
    PubMed 

    Google Scholar 
    Auta, H. S., Emenike, C. U. & Fauziah, S. H. Distribution and importance of microplastics in the marine environment: A review of the sources, fate, effects, and potential solutions. Environ. Int. 102, 165–176 (2017).CAS 
    PubMed 

    Google Scholar 
    Zobkov, M. B. & Esiukova, E. E. Microplastics in a Marine Environment: Review of Methods for Sampling, Processing, and Analyzing Microplastics in Water, Bottom Sediments, and Coastal Deposits (2018).Coyle, R., Hardiman, G. & O’Driscoll, K. Microplastics in the marine environment: A review of their sources, distribution processes, uptake and exchange in ecosystems. Case Stud. Chem. Environ. Eng. 2, 100010 (2020).
    Google Scholar 
    Barnes, D. K., Galgani, F., Thompson, R. C. & Barlaz, M. Accumulation and fragmentation of plastic debris in global environments. Philos. Trans. R. Soc. Lond. B Biol. Sci. 364, 1985–1998 (2009).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    GESAMP. Sources, Fate and Effects of Microplastics in the Marine Environment: Part 2 of a Global Assessment. A Report to Inform the Second United Nations Environment Assembly, 220 (Joint Group of Experts on the Scientific Aspects of Marine Environmental Protection, 2016).
    Google Scholar 
    Kroon, F. J., Motti, C. E., Jensen, L. H. & Berry, K. L. Classification of marine microdebris: A review and case study on fish from the Great Barrier Reef, Australia. Sci. Rep. 8(1), 1–15. https://doi.org/10.1038/s41598-018-34590-6 (2018).CAS 
    Article 

    Google Scholar 
    Cole, M., Lindeque, P., Halsband, C. & Galloway, T. Microplastics as contaminants in the marine environment: A review. Mar. Pollut. Bull. 62(12), 2588–2597 (2011).CAS 
    PubMed 

    Google Scholar 
    Cole, M. A novel method for preparing microplastic fibers. Sci. Rep. 6(1), 1–7. https://doi.org/10.1038/srep34519 (2016).CAS 
    Article 

    Google Scholar 
    Costa, M. et al. On the importance of size of plastic fragments and pellets on the strandline: A snapshot of a Brazilian beach. Environ. Monit. Assess. 168, 299–304 (2010).PubMed 

    Google Scholar 
    Kershaw, P. J. et al. (eds) GESAMP Guidelines or the Monitoring and Assessment of Plastic Litter and Microplastics in the Ocean, Rep. Stud. GESAMP No. 99 130 (IMO/FAO/UNESCO-IOC/UNIDO/WMO/IAEA/UN/UNEP/UNDP/ISA Joint Group of Experts on the Scientific Aspects of Marine Environmental Protection, 2019).
    Google Scholar 
    Lusher, A. L., Welden, N. A., Sobral, P. & Cole, M. Sampling, isolating and identifying microplastics ingested by fish and invertebrates. Anal. Methods 9, 1346 (2017).
    Google Scholar 
    Lusher, A., Bråte, I. L. N., Hurley, R., Iversen, K. & Olsen, M. Testing of Methodology for Measuring Microplastics in Blue Mussels (Mytilus spp) and Sediments, and Recommendations for Future Monitoring of Microplastics (R & D-project) (2017).Laist, D. W. Impacts of marine debris: Entanglement of marine life in marine debris including a comprehensive list of species with entanglement and ingestion records. In Marine debris, 99–139 (Springer, 1997).Denuncio, P. et al. Plastic ingestion in Franciscana dolphins, Pontoporia blainvillei (Gervais and d’Orbigny, 1844), from Argentina. Mar. Pollut. Bull. 62(8), 1836–1841 (2011).CAS 
    PubMed 

    Google Scholar 
    Do Sul, J. A. I., Santos, I. R., Friedrich, A. C., Matthiensen, A. & Fillmann, G. Plastic pollution at a sea turtle conservation area in NE Brazil: Contrasting developed and undeveloped beaches. Estuar. Coasts 34(4), 814–823 (2011).
    Google Scholar 
    Lazar, B. & Gračan, R. Ingestion of marine debris by loggerhead sea turtles, Caretta caretta, in the Adriatic Sea. Mar. Pollut. Bull. 62(1), 43–47 (2011).CAS 
    PubMed 

    Google Scholar 
    Poppi, L. et al. Post-mortem investigations on a leatherback turtle Dermochelys coriacea stranded along the Northern Adriatic coastline. Dis. Aquat. Org. 100(1), 71–76 (2012).
    Google Scholar 
    Van Franeker, J. A. et al. Monitoring plastic ingestion by the northern fulmar Fulmarus glacialis in the North Sea. Environ. Pollut. 159(10), 2609–2615 (2011).PubMed 

    Google Scholar 
    Betts, K. Why Small Plastic Particles May Pose a Big Problem in the Oceans 8995–8995 (ACS Publications, 2008).
    Google Scholar 
    Cefas, L. Programme 8: Bass gillnet selectivity. Fish. Sci. 09 (2008).Priscilla, V., Sedayu, A. & Patria, M. P. Microplastic abundance in the water, seagrass, and sea hare Dolabella auricularia in Pramuka Island, Seribu Islands, Jakarta Bay, Indonesia. J. Phys. Conf. Ser. 1402, 033073. https://doi.org/10.1088/1742-6596/1402/3/033073 (2019).Article 

    Google Scholar 
    Graham, E. R. & Thompson, J. T. Deposit-and suspension-feeding sea cucumbers (Echinodermata) ingest plastic fragments. J. Exp. Mar. Biol. Ecol. 368(1), 22–29 (2009).
    Google Scholar 
    Thompson, R. C. et al. Lost at sea: Where is all the plastic? Science 304(5672), 838–838 (2004).CAS 
    PubMed 

    Google Scholar 
    Hämer, J., Gutow, L., Köhler, A. & Saborowski, R. Fate of microplastics in the marine isopod Idotea emarginata. Environ. Sci. Technol. 48(22), 13451–13458 (2014).ADS 
    PubMed 

    Google Scholar 
    Setälä, O., Fleming-Lehtinen, V. & Lehtiniemi, M. Ingestion and transfer of microplastics in the planktonic food web. Environ. Pollut. 185, 77–83 (2014).PubMed 

    Google Scholar 
    Cole, M. et al. Microplastics alter the properties and sinking rates of zooplankton faecal pellets. Environ. Sci. Technol. 50(6), 3239–3246 (2016).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Gutow, L., Eckerlebe, A., Giménez, L. & Saborowski, R. Experimental evaluation of seaweeds as a vector for microplastics into marine food webs. Environ. Sci. Technol. 50(2), 915–923 (2016).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Naji, A., Nuri, M. & Vethaak, A. D. Microplastics contamination in molluscs from the northern part of the Persian Gulf. Environ. Pollut. 235, 113–120 (2018).CAS 
    PubMed 

    Google Scholar 
    Ding, J. et al. Detection of microplastics in local marine organisms using a multi-technology system. Anal. Methods 11(1), 78–87 (2019).CAS 

    Google Scholar 
    Gniadek, M. & Dąbrowska, A. The marine nano-and microplastics characterisation by SEM-EDX: The potential of the method in comparison with various physical and chemical approaches. Mar. Pollut. Bull. 148, 210–216 (2019).CAS 
    PubMed 

    Google Scholar 
    Dąbrowska, A. A roadmap for a plastisphere. Mar. Pollut. Bull. 167, 112322 (2021).PubMed 

    Google Scholar 
    Ebere, E. C. & Ngozi, V. E. Microplastics, an emerging concern: A review of analytical techniques for detecting and quantifying microplatics. Anal. Methods Environ. Chem. J. 2(2), 13–30 (2019).
    Google Scholar 
    Mariano, S., Tacconi, S., Fidaleo, M., Rossi, M. & Dini, L. Micro and nanoplastics identification: Classic methods and innovative detection techniques. Front. Toxicol. https://doi.org/10.3389/ftox.2021.636640 (2021).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ferrante, M. et al. Microplastics in fillets of Mediterranean seafood. A risk assessment study. Environ. Res. 204, 112247 (2022).CAS 
    PubMed 

    Google Scholar 
    Li, J. et al. Characterization, source, and retention of microplastic in sandy beaches and mangrove wetlands of the Qinzhou Bay, China. Mar. Pollut. Bull. 136, 401–406 (2018).CAS 
    PubMed 

    Google Scholar 
    Liu, J. et al. Pollution characteristics of microplastics in mollusks from the coastal Area of Yantai. China. Bull. Environ. Contamin. Toxicol. 107, 1–7 (2021).
    Google Scholar 
    Tarjuelo, I., Posada, D., Crandall, K., Pascual, M. & Turon, X. Cryptic species of Clavelina (Ascidiacea) in two different habitats: Harbours and rocky littoral zones in the northwestern Mediterranean. Mar. Biol. 139(3), 455–462 (2001).
    Google Scholar 
    Brunetti, R. & Mastrototaro, F. Botrylloides pizoni, a new species of Botryllinae (Ascidiacea) from the Mediterranean Sea R. Zootaxa 3258(1), 28–36 (2012).
    Google Scholar 
    Beli, E. et al. The zoogeography of extant rhabdopleurid hemichordates (Pterobranchia: Graptolithina), with a new species from the Mediterranean Sea. Invertebr. Syst. 32(1), 100–110 (2018).
    Google Scholar 
    Chimienti, G., Angeletti, L., Furfaro, G., Canese, S. & Taviani, M. Habitat, morphology and trophism of Tritonia callogorgiae sp. nov., a large nudibranch inhabiting Callogorgia verticillata forests in the Mediterranean Sea. Deep Sea Res. I Oceanogr. Res. Pap. 165, 103364 (2020).
    Google Scholar 
    Furfaro, G. & Mariottini, P. A new Dondice Marcus Er. 1958 (Gastropoda: Nudibranchia) from the Mediterranean Sea reveals interesting insights into the phylogenetic history of a group of Facelinidae taxa. Zootaxa 4731(1), 1–22. https://doi.org/10.11646/zootaxa.4731.1.1 (2020).Article 

    Google Scholar 
    Cózar, A. et al. Plastic accumulation in the Mediterranean Sea. PLoS ONE 10(4), e0121762. https://doi.org/10.1371/journal.pone.0121762 (2015).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Sharma, S., Sharma, V. & Chatterjee, S. Microplastics in the Mediterranean Sea: Sources, pollution intensity, sea health, and regulatory policies. Front. Mar. Sci. 8, 634934. https://doi.org/10.3389/fmars.2021.634934 (2021).Article 

    Google Scholar 
    Pinardi, N. & Masetti, E. Variability of the large scale general circulation of the Mediterranean Sea from observations and modelling: A review. Palaeogeogr. Palaeoclimatol. Palaeoecol. 158(3–4), 153–173 (2000).
    Google Scholar 
    Suaria, G. et al. The Mediterranean Plastic soup: Synthetic polymers in Mediterranean surface waters. Sci. Rep. 6(1), 1–10 (2016).
    Google Scholar 
    Vianello, A. et al. Microplastic particles in sediments of Lagoon of Venice, Italy: First observations on occurrence, spatial patterns and identification. Estuar. Coast. Shelf. Sci. 130, 54–61. https://doi.org/10.1016/j.ecss.2013.03.022 (2013).ADS 
    CAS 
    Article 

    Google Scholar 
    Parenzan, P. Il Mar Piccolo di Taranto. Ciem. Comm. Taranto (1984).Cavallo, R. A. & Stabili, L. Presence of vibrios in seawater and Mytilus galloprovincialis (Lam.) from the Mar Piccolo of Taranto (Ionian Sea). Water Res. 36(15), 3719–3726 (2002).CAS 
    PubMed 

    Google Scholar 
    Cardellicchio, N. et al. Organic pollutants (PAHs, PCBs) in sediments from the Mar Piccolo in Taranto (Ionian Sea, Southern Italy). Mar. Pollut. Bull. 55(10–12), 451–458 (2007).CAS 
    PubMed 

    Google Scholar 
    Cardellicchio, N., Annicchiarico, C., Di Leo, A., Giandomenico, S. & Spada, L. The Mar Piccolo of Taranto: An interesting marine ecosystem for the environmental problems studies. Environ. Sci. Pollut. Res. 23(13), 12495–12501 (2016).
    Google Scholar 
    Tursi, A. et al. Mega-litter and remediation: The case of Mar Piccolo of Taranto (Ionian Sea). Rendiconti Lincei. Sci. Fisiche e Nat. 29(4), 817–824 (2018).
    Google Scholar 
    Mastrototaro, F. et al. Benthic diversity of the soft bottoms in a semi-enclosed basin of the Mediterranean Sea. Marine Biological Association of the United Kingdom. J. Mar. Biol. Assoc. U.K. 88(2), 247 (2008).
    Google Scholar 
    Li, J. et al. Using mussel as a global bioindicator of coastal microplastic pollution. Environ. Pollut. 244, 522–533 (2019).CAS 
    PubMed 

    Google Scholar 
    Corami, F. et al. Evidence of small microplastics (< 100 μm) ingestion by Pacific oysters (Crassostrea gigas): A novel method of extraction, purification, and analysis using Micro-FTIR. Mar. Pollut. Bull. 160, 111606 (2020).CAS  PubMed  Google Scholar  De-la-Torre, G. E., Apaza-Vargas, D. M. & Santillán, L. L. Microplastic ingestion and feeding ecology in three intertidal mollusk species from Lima, Peru. Rev. Biol. Mar. Oceanogr. 55(2), 167–171 (2020). Google Scholar  Jiang, Y. et al. A review of microplastic pollution in seawater, sediments and organisms of the Chinese coastal and marginal seas. Chemosphere 286, 131677 (2021).ADS  PubMed  Google Scholar  Haszprunar, G. The heterobranchia—A new concept of the phylogeny of the higher Gastropoda. J. Zool. Syst. Evol. Res. 23(1), 15–37 (1985). Google Scholar  Wägele, H., Klussmann-Kolb, A., Vonnemann, V. & Medina, M. Heterobranchia I: The Opisthobranchia. In Phylogeny and Evolution of the Mollusca (eds Ponder, W. F. & Lindberg, D.) 385–408 (University of California Press, 2008). Google Scholar  Prkic, J. et al. First record of Calma gobioophaga Calado and Urgorri, 2002 (Gastropoda: Nudibranchia) in the Mediterranean Sea. Mediterr. Mar. Sci. 15(2), 423–428 (2014). Google Scholar  Furfaro, G., Trainito, E., De Lorenzi, F., Fantin, M. & Doneddu, M. Tritonia nilsodhneri Marcus Ev., 1983 (Gastropoda, Heterobranchia, Tritoniidae): First records for the Adriatic Sea and new data on ecology and distribution of Mediterranean populations. Acta Adriat. 58, 2 (2017). Google Scholar  Thompson, T. E. Studies on ontogeny of Tritonia hombergi Cuvier (Gastropoda: Opisthobranchia). Philos. Trans. R. Soc. Lond. B 245, 171–218. https://doi.org/10.1098/rstb.1962.0009 (1962).ADS  Article  Google Scholar  Cattaneo-Vietti, R., Angelini, S. & Bavestrello, G. Skin and gut spicules in Discodoris atromaculata (Bergh, 1880) (Mollusca: Nudibranchia). Bollettino Malacol. 28, 173–180 (1993). Google Scholar  Cattaneo-Vietti, R., Angelini, S., Gaggero, L. & Lucchetti, G. Mineral composition of nudibranch spicules. J. Molluscan Stud. 61(3), 331–337. https://doi.org/10.1093/mollus/61.3.331 (1995).Article  Google Scholar  Garese, A., García-Matucheski, S., Acuña, F. H. & Muniain, C. Feeding behavior of Spurilla sp. (Mollusca: Opisthobranchia) with a description of the kleptocnidae sequestered from its sea anemone prey. Zool. Stud. 51(7), 905–912 (2012).CAS  Google Scholar  Braga, T. et al. Bursatella leachii from Mar Menor as a source of bioactive molecules: Preliminary evaluation of the nutritional profile, in vitro biological activities and fatty acids contents. J. Aquat. Food Prod. Technol. 26(10), 1337–1350 (2017).CAS  Google Scholar  Willis, T. J. et al. Kleptopredation: A mechanism to facilitate planktivory in a benthic mollusc. Biol. Let. 13, 20170447. https://doi.org/10.1098/rsbl.2017.0447 (2017).Article  Google Scholar  Goodheart, J. A. et al. Comparative morphology and evolution of the cnidosac in Cladobranchia (Gastropoda: Heterobranchia: Nudibranchia). Front. Zool. 15(1), 1–18. https://doi.org/10.1186/s12983-018-0289-2 (2018).CAS  Article  Google Scholar  Marin, A. & Ros, J. Chemical defenses in Sacoglossan Opisthobranchs: Taxonomic trends and evolutive implications. Sci. Mar. 67(Suppl. 1), 227–241 (2004). Google Scholar  Wägele, H., Ballestero, M. & Avila, C. Defensive glandular structures in opisthobranch molluscs—From histology to ecology. Oceanogr. Mar. Biol. Annu. Rev. 44, 197–276 (2006). Google Scholar  Pavlik, J. R. Antipredatory defensive roles of natural products from marine invertebrates. In Handbook of Marine Natural Products Vol. 12 (eds Fattorusso, E. et al.) 677–710 (Springer, 2012). Google Scholar  Avila, C., Nuñez-Pons, L. & Moles, J. From the tropics to the poles chemical defense strategies in sea slugs (Mollusca: Heterobranchia). In Chemical Ecology: The Ecological Impact of Marine Natural Products (eds Puglisi, M. P. & Becerro, M. A.) 93 (CRC Press, 2018). Google Scholar  Capper, A., Tibbetts, I. R., O’Neil, J. M. & Shaw, G. R. The fate of Lyngbya majuscula toxins in three potential consumers. J. Chem. Ecol. 31(7), 1595–1606 (2005).CAS  PubMed  Google Scholar  Dean, L. J. & Prinsep, M. R. The chemistry and chemical ecology of nudibranchs. Nat. Prod. Rep. 34(12), 1359–1390 (2017).CAS  PubMed  Google Scholar  Simmons, T. L., Andrianasolo, E., McPhail, K., Flatt, P. & Gerwick, W. H. Marine natural products as anticancer drugs. Mol. Cancer Ther. 4(2), 333–342 (2005).CAS  PubMed  Google Scholar  Klussmann-Kolb, A. Phylogeny of the Aplysiidae (Gastropoda, Opisthobranchia) with new aspects of the evolution of seahares. Zool. Scr. 33, 439–462 (2004). Google Scholar  Willan, R. C. Phylogenetic systematics of the Notaspidea (Opisthobranchia) with reappraisal of families and genera. Am. Malacol. Bull. 5, 215–241 (1987). Google Scholar  Medina, M. & Walsh, P. J. Molecular systematics of the order Anaspidea based on mitochondrial DNA sequences (12S, 16S, and COI). Mol. Phylogenet. Evol. 15, 41–58 (2000).CAS  PubMed  Google Scholar  Furfaro, G., De Matteo, S., Mariottini, P. & Giacobbe, S. Ecological notes of the alien species Godiva quadricolor (Gastropoda: Nudibranchia) occurring in Faro Lake (Italy). J. Nat. Hist. 52(11–12), 645–657 (2018). Google Scholar  Appleton, D. R., Sewell, M. A., Berridge, M. V. & Copp, B. R. A new biologically active malyngamide from a New Zealand collection of the sea hare Bursatella leachii. J. Nat. Prod. 65(4), 630–631 (2002).CAS  PubMed  Google Scholar  Rajaganapathi, J., Kathiresan, K. & Singh, T. P. Purification of anti-HIV protein from purple fluid of the sea hare Bursatella leachii de Blainville. Mar. Biotechnol. 4(5), 447–453 (2002).CAS  Google Scholar  Suntornchashwej, S., Chaichit, N., Isobe, M. & Suwanborirux, K. Hectochlorin and morpholine derivatives from the Thai Sea Hare, Bursatella leachii. J. Nat. Prod. 68(6), 951–955 (2005).CAS  PubMed  Google Scholar  Dhahri, M. et al. Extraction, characterization, and anticoagulant activity of a sulfated polysaccharide from Bursatella leachii viscera. ACS Omega 5(24), 14786–14795 (2020).CAS  PubMed  PubMed Central  Google Scholar  Clarke, C. L. The population dynamics and feeding preferences of Bursatella leachii (Opisthobranchia: Anaspidea) in northeast Queensland, Australia. Rec. West. Austral. Museum Suppl. 69, 11–21 (2006). Google Scholar  Blainville, H. M. D. de. Bursatella, p. 138, in: Dictionnaire des Sciences Naturelles (F. Cuvier, ed.), Vol. 5, Supplément. Levrault, Strasbourg & Le Normant, Paris (1817).Trainito, E. & Doneddu, M. Nudibranchi del Mediterraneo 2nd edn, 192 (Il Castello, 2014). Google Scholar  Zbyszewski, M., Corcoran, P. L. & Hockin, A. Comparison of the distribution and degradation of plastic debris along shorelines of the Great Lakes, North America. J. Great Lakes Res. 40(2), 288–299 (2014).CAS  Google Scholar  Wang, Z. M., Wagner, J., Ghosal, S., Bedi, G. & Wall, S. SEM/EDS and optical microscopy analyses of microplastics in ocean trawl and fish guts. Sci. Total Environ. 603, 616–626 (2017).ADS  PubMed  Google Scholar  Gewert, B., Plassmann, M. & MacLeod, M. Pathways for degradation of plastic polymers floating in the marine environment. Environ. Sci. Process. Impacts 17, 1513–1521 (2015).CAS  PubMed  Google Scholar  Gewert, B., Plassmann, M., Sandblom, O. & MacLeod, M. Identification of chain scission products released to water by plastic exposed to ultraviolet light. Environ. Sci. Technol. Lett. 5, 272–276 (2018).CAS  Google Scholar  Lang, M. et al. Fenton aging significantly affects the heavy metal adsorption capacity of polystyrene microplastics. Sci. Total Environ. 722, 137762 (2020).ADS  CAS  PubMed  Google Scholar  Ding, L., Mao, R., Ma, S., Guo, X. & Zhu, L. High temperature depended on the ageing mechanism of microplastics under different environmental conditions and its effect on the distribution of organic pollutants. Water Res. 174, 115634 (2020).CAS  PubMed  Google Scholar  Wang, F. et al. The influence of polyethylene microplastics on pesticide residue and degradation in the aquatic environment. J. Hazard. Mater. 394, 122517 (2020).CAS  PubMed  Google Scholar  Ouyang, Z. et al. The aging behavior of polyvinyl chloride microplastics promoted by UV-activated persulfate process. J. Hazard. Mater. 424, 127461 (2022).CAS  PubMed  Google Scholar  Dehaut, A. et al. Microplastics in seafood: Benchmark protocol for their extraction and characterization. Environ. Pollut. 215, 223–233 (2016).CAS  PubMed  Google Scholar  Besley, A., Vijver, M. G., Behrens, P. & Bosker, T. A standardized method for sampling and extraction methods for quantifying microplastics in beach sand. Mar. Pollut. Bull. 114(1), 77–83 (2017).CAS  PubMed  Google Scholar  Karami, A. et al. A high-performance protocol for extraction of microplastics in fish. Sci. Total Environ. 578, 485–494 (2017).ADS  CAS  PubMed  Google Scholar  Caron, A. G. et al. Ingestion of microplastic debris by green sea turtles (Chelonia mydas) in the Great Barrier Reef: Validation of a sequential extraction protocol. Mar. Pollut. Bull. 127, 743–751 (2018).CAS  PubMed  Google Scholar  Piarulli, S. et al. Microplastic in wild populations of the omnivorous crab Carcinus aestuarii: A review and a regional-scale test of extraction methods, including microfibres. Environ. Pollut. 251, 117–127 (2019).CAS  PubMed  Google Scholar  Pfohl, P. et al. Microplastic extraction protocols can impact the polymer structure. Microplast. Nanoplast. 1(1), 1–13 (2021). Google Scholar  Qiu, Q. et al. Extraction, enumeration and identification methods for monitoring microplastics in the environment. Estuar. Coast. Shelf Sci. 176, 102–109 (2016).ADS  CAS  Google Scholar  Lusher, A. L., Munno, K., Hermabessiere, L. & Carr, S. Isolation and extraction of microplastics from environmental samples: An evaluation of practical approaches and recommendations for further harmonization. Appl. Spectrosc. 74(9), 1049–1065 (2020).ADS  CAS  PubMed  Google Scholar  Bellasi, A., Binda, G., Pozzi, A., Boldrocchi, G. & Bettinetti, R. The extraction of microplastics from sediments: An overview of existing methods and the proposal of a new and green alternative. Chemosphere 278, 130357 (2021).ADS  CAS  PubMed  Google Scholar  Essa, A. M. & Khallaf, M. K. Antimicrobial potential of consolidation polymers loaded with biological copper nanoparticles. BMC Microbiol. 16(1), 1–8 (2016). Google Scholar  Etcheverry, M., Ferreira, M. L., Capiati, N. J., Pegoretti, A. & Barbosa, S. E. Strengthening of polypropylene–glass fiber interface by direct metallocenic polymerization of propylene onto the fibers. Compos. A Appl. Sci. Manuf. 39(12), 1915–1923 (2008). Google Scholar  Ivanič, A., Kravanja, G., Kidess, W., Rudolf, R. & Lubej, S. The influences of moisture on the mechanical, morphological and thermogravimetric properties of mineral wool made from basalt glass fibers. Materials 13(10), 2392 (2020).ADS  PubMed Central  Google Scholar  Kavad, B. V., Pandey, A. B., Tadavi, M. V. & Jakharia, H. C. A review paper on effects of drilling on glass fiber reinforced plastic. Procedia Technol. 14, 457–464 (2014). Google Scholar  Alsayed, S. H., Al-Salloum, Y. A. & Almusallam, T. H. Performance of glass fiber reinforced plastic bars as a reinforcing material for concrete structures. Compos. B Eng. 31(6–7), 555–567 (2000). Google Scholar  Fries, E. et al. Identification of polymer types and additives in marine microplastic particles using pyrolysis-GC/MS and scanning electron microscopy. Environ. Sci. Process Impacts 15(10), 1949–1956 (2013).CAS  PubMed  Google Scholar  Turner, A. & Filella, M. The influence of additives on the fate of plastics in the marine environment, exemplified with barium sulphate. Mar. Pollut. Bull. 158, 111352 (2020).CAS  PubMed  Google Scholar  Barathi, M., Kumar, A. S. K. & Rajesh, N. Efficacy of novel Al–Zr impregnated cellulose adsorbent prepared using microwave irradiation for the facile defluoridation of water. J. Environ. Chem. Eng. 1(4), 1325–1335 (2013).CAS  Google Scholar  Bahsis, L. et al. Cellulose-copper as bio-supported recyclable catalyst for the clickable azide-alkyne [3+2] cycloaddition reaction in water. Int. J. Biol. Macromol. 119, 849–856 (2018).CAS  PubMed  Google Scholar  Ibrahim, N. A., Eid, B. M., Abd El-Aziz, E., Abou Elmaaty, T. M. & Ramadan, S. M. Multifunctional cellulose-containing fabrics using modified finishing formulations. RSC Adv. 7(53), 33219–33230 (2017).ADS  CAS  Google Scholar  Van, H. T., Le Sy, H., Nguyen, T. M. L. & Nguyen, D. K. Application of Mussell-derived biosorbent to remove NH 4+ from aqueous solution: Equilibrium and Kinetics. SN Appl. Sci. 3(4), 1–12 (2021). Google Scholar  Lakshmanna, B. et al. Data on Molluscan Shells in parts of Nellore Coast, southeast coast of India. Data Brief 16, 705–712 (2018).CAS  PubMed  Google Scholar  Taylor, P. D., Vinn, O., Kudryavtsev, A. & Schopf, J. W. Raman spectroscopic study of the mineral composition of cirratulid tubes (Annelida, Polychaeta). J. Struct. Biol. 171(3), 402–405 (2010).CAS  PubMed  Google Scholar  Schröder, V. et al. Micromorphological details and identification of chitinous wall structures in Rapana venosa (Gastropoda, Mollusca) egg capsules. Sci. Rep. 10(1), 1–13 (2020). Google Scholar  Ngamniyom, A., Wongroj, W., Karnchaisri, K. & Siriwattanarat, R. Ophidascaris baylisi (Nematoda: Ascarididae): Scanning electron microscopic study of the adult surface with ultrastructure and chemical composition analysis of eggshells. Sci. Technol. Asia 26, 189–198 (2021). Google Scholar  Fabra, M. et al. The plastic Trojan horse: Biofilms increase microplastic uptake in marine filter feeders impacting microbial transfer and organism health. Sci. Total Environ. 797, 149217 (2021).ADS  CAS  PubMed  Google Scholar  Jacquin, J. et al. Microbial ecotoxicology of marine plastic debris: A review on colonization and biodegradation by the “Plastisphere”. Front. Microbiol. 10, 865 (2019).PubMed  PubMed Central  Google Scholar  More

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    Reply to: Evidence confirms an anthropic origin of Amazonian Dark Earths

    Lombardo et al. argue that, if our hypothesis is correct, ADEs should be continuous rather than patchy. However, alluvium deposition can be a patchy process and the distribution of large and small ADE patches can be predicted regionally based on fluvial geomorphology. For example, 89% of all known ADEs have been predictively mapped using elevation, distance to bluff, and geological provenance as the key predictors (with a false negative rate of 6.5% and a false positive rate of 4.7%)10. Predicted areas include small and large ADE patches, up to several square kilometres in size, and indicate that ADEs cover ~154,000 km2 mostly in central and western Amazonia. This may seem to be a very large area ( >3% of the Amazon basin) but it is only a fraction of the projections found in some of the most cited anthropogenic theory literature11. Assuming the same excess fertility observed at our site, the creation of those ADEs would have required a prohibitive amount of biomass burning, in areas 800–1680 times larger (Fig. 1), which is inconsistent with the centralised small-scale deposition proposed by Lombardo et al. In this regional scenario, it remains unclear how many Amazons would have been needed to build the already-mapped ADEs.Lombardo et al. centre their opinion on settlements in other parts of the Amazon basin, under different socioecological and geomorphological contexts, and where the data we have developed are not available for comparison. Their narrative conflates the Brazilian lowland with other regions, such as the Llanos de Moxos and other systems in the Bolivian-Peruvian foreland basins, where older archeological sites occur. Their comments about the mineral composition of ADEs appear to contradict recent discoveries (made by some of their co-authors)12 which show that some oxides found at our ADE site bear “no relationship to anthropogenic activity” because “their sources are attributed to the weathering of micas, feldspars, mafic minerals (pyroxene), and sodic plagioclase” that are not found locally. To explain the inconsistency between those findings and the current theory of ADE formation, Macedo et al. argue that “sediment depositions in floodplain soils” that “are not related to human occupation” should be considered. That suggestion is consistent with our data which indicate deposition of exogenous materials to the site prior to the invention of agriculture in central Amazonia.Our study area is on a Tertiary terrace, and we acknowledge in our paper that it lies above the modern 100-year flood height for Manaus. However, significant Pleistocene and Holocene tectonic activity and river aggradation/degradation demonstrably affected the flood height over time. A complex neotectonic history has affected terrace elevations, nutrient deposition, and remobilisation, as well as flood heights and aggradation, resulting in higher base levels that were many metres above flood waters today in past millennia13,14,15. In addition, rivers transported and dispersed sediments from the Andes to the lowland, which were re-mobilised, and re-deposited in patchy patterns, from floodplains several times between 20 and 5 thousand years ago16,17,18. Such mineral inputs by past avulsion events may have occurred earlier in the Quaternary and remain as a relict soil where it has not subsequently eroded19. The older weathered sediments on the upper terraces lining the river look nothing like recent alluvium and the distribution of elements and their assemblages at our site are consistent with alluvial deposits in other sites. This process is explained in studies cited by Lombardo et al. (e.g., Pupim et al.), which note several periods of river aggradation, that support our hypothesis.As explained in our original paper, our data do not preclude a more recent human effect on the local landscape. The wisdom of indigenous populations, manifested in the application of waste materials to agricultural sites (since at least the late Holocene), may have further enriched ADEs or countered their natural degradation. Recent studies12, 16, 17, which post-date the studies that Lombardo et al. cite to argue against a geogenic influence, reveal a dynamic neotectonic history and support our hypothesis. Thus, the extent to which other ADE sites originated from depositional processes should be investigated based on evidence that goes beyond those presented by Lombardo et al. More

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    Biotic induction and microbial ecological dynamics of Oceanic Anoxic Event 2

    The biotic induction of OAE-2The rapid proliferation of select microbial communities at 427.54 mcd likely represents a pre-OAE biotic perturbation (pre-OAE BP) presaging the protracted period of widespread marine deoxygenation during OAE-2, and progressive deoxygenation predating the +CIE7 (Fig. 4). At the beginning of the pre-OAE BP (427.54 mcd), abruptly elevated tetrapyrroles and crenarchaeol concentrations signify an abrupt increase in primary production by photoautotrophs and chemoautotrophs residing above the chemocline. Increased volumes of precipitating biogenic snow concordantly consumed oxygen, expanding the preexisting OMZ as anaerobic bacteria thrived based on accelerated obGDGTs synthesis. Euxinia did not penetrate the photic zone at the outset of the productivity bloom as isorenieratane was not detected and heightened rates of microbial sulfate reduction were seemingly transient, inferred from the DAGEs profile, and limited to pre-OAE BP initiation. The lack of a well-stratified water column, evinced by absent to low concentrations of halophilic archaeal lipids (i.e., extended archaeols), relatively low rates of microbial sulfate reduction, and a dense oxygenic microbial plate likely precluded the development of PZE initially.Establishing a definitive causal mechanism for the pre-OAE BP is difficult, but the concomitance of LIP activity with the productivity spike is intriguing. Application of a linear sedimentation rate from OAE-2 to the pre-OAE BP interval following previous works6,7 approximated the pre-OAE BP occurring 220 ± 4 kyr before OAE-2, lasting for ~100 kyr (427.54–426.88 mcd; see Estimating the duration of the pre-OAE BP in Supplementary Information for rationale and calculation). Significantly, this was roughly coincident with the onset of LIP activity (~200–300 kyr before OAE-2) inferred from marine osmium isotope stratigraphy27. Similarities in the modern planktonic community response, such as elevated productivity and compositional changes, between the 2018 Kilauea eruption28 and the pre-OAE BP reinforce inference of a potential magmatic trigger for this event (see Evidence for LIP trigger of the pre-OAE biotic perturbation in Supplementary Information for additional details).A constant, yet overall lower, nutrient and trace metal inventory6 (Fig. S4) combined with a redox-driven shift in fixed N species (from NO3− to NH4+)15, potentially leading to a fixed N shortage29 via intensified denitrification and annamox reactions30, were probable culprits in the failure to sustain prolific rates of primary production beyond 100 kyr at the Demerara Rise. The gradual decline in biomass production, indicated by decreasing tetrapyrrole and crenarchaeol profiles (Fig. 4), was accompanied by a notable shift in deep water communities. Sulfate-reducing bacteria exerted increasing predominance over methanogenic archaea, a trend coeval with the primary productivity spike and extending well into the OAE (Fig. 3). A collapse of autotrophic communities to pre-perturbation levels was concordant with the progressive shoaling of H2S-laden waters. Continued vertical migration of the chemocline intruded the photic zone, producing PZE that enabled anoxygenic photosynthesis by Chlorobiaceae (Fig. 4). Unlike the overall oscillatory character of PZE throughout the studied section, this protracted phase of PZE was sustained until the onset of OAE-2 (426.43–426.00 mcd, Figs. 3 and 4) and is approximately contemporaneous with a thallium (Tl) isotope excursion7 (426.40–426.30 mcd).The positive Tl isotope excursion represents the progressive expansion of bottom water anoxia predating OAE-2 by 43 ± 11 kyr6,7. However, evidence for a causal mechanism of pre-OAE deoxygenation remains indeterminate. Our comprehensive biomarker inventory provides an interpreted sequence of events culminating in the regional to global expansion of anoxia predating OAE-2. A protracted phase of enhanced primary productivity began ~220 ± 4 kyr prior to OAE-2, increasing localized production and export of organic carbon at Demerara Rise. Similar productivity spikes likely occurred in settings of comparable paleogeographic configuration (e.g., equatorial, continental margins/shelves), seeding the oceans with fixed carbon. Continued scavenging of marine oxygen via organic carbon remineralization resulted in OMZ expansion locally, and likely initiated oxygen drawdown in much of the proto-North Atlantic Ocean. Stratigraphic records of sulfur isotopes of pyrite (δ34Spyrite) from the proto-North Atlantic and Tethys Oceans11 validate the areal extrapolation of our interpretations. A gradual decline in δ34Spyrite values at Demerara Rise begins at 427.50 mcd, nearly identical to the onset of the pre-OAE BP (427.54 mcd, Fig. 4). Correlation of δ34Spyrite in a global transect (Western Interior Seaway, proto-North Atlantic, Tethys) revealed consistent behavior in δ34Spyrite prior to the +CIE, indicating increasingly expansive marine deoxygenation on a global scale11. Over ~100 kyr, increased regional biomass production induced pervasive marine anoxia, inhibiting Mn-oxide formation, producing the observed positive Tl isotope excursion, and ultimately, the globally observed +CIE reflecting enhanced organic carbon burial signaling the onset of OAE-2. Thus, the local biotic signal recorded at ODP Site 1258 underlines the crucial role the Demerara Rise, and similar undocumented settings, served in initiating deoxygenation of the global ocean.Microbial ecological dynamics during and after OAE-2Changes in microbial community compositions during OAE-2 were apparent, signified by a shift in the normalized total biomarker pool (Fig. 3) and variations in the absolute concentrations of individual biomarkers (Fig. 4). In general, OAE-2 was defined by an expansion and diversification of intermediate and deep water communities (426.00–423.07 mcd), followed by a period of instability leading to the termination of the OAE (423.07–422.00 mcd). Photo- and chemoautotrophs residing above the chemocline were adversely affected, evinced by relatively low, invariant tetrapyrrole and crenarchaeol profiles (Fig. 4). Based on these observations, we divided OAE-2 into two periods defined by contrasting paleoenvironmental conditions modulating the microbial inhabitants of Demerara Rise.The first period of OAE-2 (426.00–423.07 mcd, Fig. 4) was marked by the intrusion of a euxinic OMZ into the photic zone. Elevated, yet fluctuating isorenieratane concentrations suggest relatively persistent PZE of varying vertical extent, in agreement with previous investigations using biomarkers and nitrogen isotopes at nearby sites12,13,31. During this interval, microbial sulfate reduction was likely active as DAGEs continually increased, aligning with estimates of expanded seafloor euxinia32. The co-occurrence of abundant extended archaeols and isorenieratane intimates the role that density stratification served in maintaining the protracted PZE of OAE-2, substantiating concurrent findings based on neodymium33 and oxygen isotopes34. Vertical nutrient advection via upwelling35 led to preferential exposure to expanding intermediate water communities tolerant to sulfidic conditions in the OMZ. Scavenging of a potentially limited fixed N inventory30, depleted in NO3− and predominated by NH4+[ 15,29, and inhibition of efficient nutrient transfer by pronounced density stratification likely induced severe N deficiency in surface water communities, explaining the relatively muted productivity of oxygenic photoautotrophs (i.e., tetrapyrroles) and chemoautotrophs (i.e., crenarchaeol) observed (Fig. 4). The concentration and predominant utilization of fixed N in the OMZ led to the proliferation and diversification of intermediate and deep water microbial taxa, while a shoaling chemocline led to increased nutrient (i.e., fixed N) competition between photoautotrophs and retreating Thaumarchaeota as highlighted by our biomarker inventory and the nitrogen isotopic record31. These findings challenge previous interpretations of highly productive, predominantly eukaryotic primary producers reliant on the upwelling of isotopically depleted NH4+ during OAE-215. Instead, the decline of C30-17-nor-DPEP (Fig. S5; Supplementary Data 3), a source-specific tetrapyrrole diagenetically derived from algal chlorophyll-c36, and reconstructed water column conditions during OAE-2 indirectly support a rise in cyanobacteria, diazotrophs able to fix N2, in oxygenated, nutrient-depleted shallow waters. Increased cyanobacterial contribution is further supported by C and N stable isotopes16,37, as well as the prominence of potentially phylum-specific biomarkers across OAE-2 (e.g., 2-methylhopanoids6,14).Fig. 5: Contrasting biogeochemical conditions between the pre-OAE BP and OAE-2.a, b Microbial ecology and water column conditions during the pre-OAE BP, reflecting high primary production of organic carbon (a) and OAE-2, characterized by relatively lower organic carbon production, but substantially enhanced biomass preservation (b). c, d Averaged fractional abundances of individual biomarkers throughout the pre-OAE BP (c) and OAE-2 (d). Biomarker source organisms are abbreviated as follows: phytoplankton (P), ammonia oxidizing archaea (AOA), sulfur oxidizing bacteria (SOB), unknown anaerobic bacteria (UAB), sulfate reducing bacteria (SRB), halophilic archaea (HA), methanogenic archaea (MA).Full size imageA reversal from the formerly outlined conditions typified the second period of OAE-2 (423.07–421.99 mcd, Fig. 4). Destabilization of the stratified water column and reduced production of H2S led to deepening and contraction of the euxinic OMZ. The observed decline in halophilic archaea, coincident with an overall decline in Chlorobiaceae populations, is roughly coeval with positive neodymium isotopic excursions observed across the proto-North Atlantic33 attributed to the enhanced latitudinal commingling of proto-North Atlantic water masses38. Although detrimental to sustained PZE, the persistence of a well-developed anaerobic bacterial community (i.e., obGDGTs) suggests the lasting presence of a non-euxinic OMZ despite improved bottom water circulation. A premature recovery of the chemoautotrophic Thaumarchaeota, inhabiting the base of the photic zone, relative to the shallower dwelling obligately oxygenic phototrophs (Fig. 3) likely reflects reduced toxicity associated with retreating euxinic waters, lessened resource competition with [primarily] Chlorobiaceae, and a competitive advantage tied to preferential exposure to upwelled nutrients and tolerance to low O2 conditions.The termination of OAE-2 was marked by the temporary re-establishment of microbial community compositions mirroring those observed prior to the pre-OAE BP (Figs. 3 and 4). Contraction of the OMZ led to a deep chemocline, with PZE restricted to the basal photic zone as the production of reduced sulfide species diminished. The Thaumarchaeota continued the recovery initiated towards the latter half of OAE-2, accompanied by the rebounding oxygenic photoautotrophs. However, the recovery of shallow autotrophic communities was halted by an episode of PZE (421.19–421.04 mcd) based on abrupt increases in isorenieratane concentrations (Fig. 4). Temporary development of pronounced density stratification likely facilitated the accumulation of H2S in the lower to intermediate photic zone, producing the short-lived PZE episode. Interestingly, covariant responses observed in additional biomarker profiles (e.g., obGDGTs) to PZE during OAE-2 were not evident across this post-OAE interval, possibly due to the transient nature of PZE at this time. For example, the initial increase in isorenieratane concentrations at the onset of OAE-2 was not immediately accompanied by shifts in other biomarker classes (e.g., obGDGTs; Fig. 4), suggesting frequent recurrences of PZE may be required to illicit a major microbial ecological response as observed later during the OAE. Still, this brief episode of post-OAE PZE (421.19–421.04 mcd) coincides with a positive organic carbon isotope excursion9 (Fig. S5), trace metal drawdown6 (Fig. S4), and minor positive Tl isotope excursion7 at the Demerara Rise. Prior study7 tentatively attributed this interval to enhanced carbon burial during a post-OAE deoxygenation event of smaller magnitude, with subsequent work revealing continued pyrite burial post-OAE 211. Our biomarker inventory revealed some environmental consistencies (e.g., PZE) between this interval and OAE-2, but the overall biotic response to this post-OAE geochemical perturbation was relatively subdued and requires additional sampling and investigation to properly constrain.Broader implicationsThe recognition of the pre-OAE BP and evolving water column conditions at Demerara Rise highlights additional complexities of a dynamic ocean relevant to interpretations of OAE-2 and the +CIE. Enhanced, sustained, and widespread carbon burial is required to produce the +CIE used to define OAE-28,10. Still, the principal forcing, productivity or preservation, remains enigmatic as evidence for the former mounts12,39.Based on the tetrapyrrole profiles (Fig. 4) primary production was greatest during the pre-OAE BP and relatively muted throughout OAE-2 at Demerara Rise, assuming minimal alteration to the genetic tetrapyrrole stratigraphic signal. Biomass preservation was presumedly enhanced during OAE-2 through sulfurization11, as the OMZ transitioned from anoxic to euxinic and penetrated the photic zone, yet low tetrapyrrole concentrations persist. Previous work noted a similar discrepancy between preservation potential and porphyrin abundance, postulating a paucity of trace metals to chelate with the free-base porphyrins induced poor preservation as desulfurization did not reveal additional porphyrin content16. However, both the pre-OAE BP and OAE-2 were characterized by relatively depleted trace metal inventories6 (Fig. S4), yet exhibit contrasting tetrapyrrole profiles, suggesting relative changes in primary production were the predominate control on the stratigraphic distribution of tetrapyrroles across the studied interval at the Demerara Rise. The strong covariance between tetrapyrrole and crenarchaeol concentrations reinforces the interpretation tetrapyrroles faithfully reflect primary production (Fig. S6). Crenarchaeol, a biosynthetic product of chemoautotrophic archaea (Thaumarchaeota) comprising up to 20% of all archaea and bacteria in the modern ocean40, is structurally distinct from the tetrapyrroles making it likely that diagenetic alteration of the two biomarkers is not consistent in rate or form. Thus, the positive correlation between key proxies for major contributors to primary production, the photoautotrophs and chemoautotrophs, minimizes concern for the integrity of the biotic signal at Demerara Rise (see Tetrapyrroles as a record of primary production in Supplementary Information for additional details).These findings provide direct evidence for a causal mechanism resulting in both the Tl isotope excursion and +CIE as previously described. It is highly probable the pre-OAE BP was not exclusive to the Demerara Rise based on the immense and presently unconstrained organic carbon burial required to produce the +CIE10. Further characterization of comparable localities to Demerara Rise may reveal similar high productivity events, as primed, highly productive settings likely capitalized on exogenous nutrient delivery via efficient upwelling to the photic zone prior to stratification during OAE-2. Hence, OAE-2 and the +CIE were not coincident with heightened surface water productivity relative to the pre-OAE BP at the Demerara Rise. Rather, antecedent increases in primary production locally facilitated the initiation of the OAE as a mechanism to consume marine oxygen and subsequently enhance organic carbon preservation globally. This highlights how OAE-2, and perhaps other OAEs in the geologic record, were not instantaneously induced but rather a gradual transition stemming from sustained forcing(s). In addition, the occurrence of the pre-OAE BP well before the established onset of OAE-2 reveals how fluctuations in primary production can be linked to marine deoxygenation but may not necessarily be concurrent. As shown here, OAE-2 at the Demerara Rise was preceded by elevated primary production that progressively attenuated towards event onset. While the hallmark features of an OAE are well-established, further identification and refinement of trends preceding widespread anoxia in the past will improve our understanding of how marine deoxygenation develops, as well as our ability to assess planetary health today.A shift from a productivity- to preservation-dominant system during OAE-2 at Demerara Rise, and possibly similar paleogeographic settings experiencing the pre-OAE BP, facilitated substantial organic carbon burial producing the +CIE. Distinct shifts in water column chemistry and structure from the pre-OAE BP to OAE-2 imparted considerable changes on microbial life, which altered the primary driver governing biomass sequestration (Fig. 5). Yet, both intervals reveal relatively comparable carbonate-corrected total organic carbon values6 (Fig. S5), signifying enhanced preservation as a critical component of organic carbon burial during OAE-2 at Demerara Rise. Consequently, this work suggests that sustained increases in primary production prior to OAE-2 initiated and regulated pre-OAE deoxygenation, resulting in a progressive shift to preservation as the primary control on organic carbon accumulation in sediments. Expanding euxinia and attendant changes to biogeochemical cycling adversely affected primary producers while simultaneously enhancing organic matter preservation via sulfurization11. Flourishment of Thaumarchaeota in oligotrophic settings in the modern open ocean41, and lack thereof during OAE-2 based on diminished crenarchaeol concentrations, underscores the scarcity of bioessential elements (e.g., fixed N) caused by microbial utilization of electron acceptors further down the redox ladder due to intensified marine anoxia, ultimately limiting primary production. The switch from a productivity to preservation model, reconstructed using biomarkers (Fig. 5) and initially suggested based on drawdown of the trace metal inventory6, was also concomitant with relative warming4. Simulated projections of the marine microbial response to continued global warming in the future revealed similar biotic trends (e.g., decreased primary productivity) to warming-induced oceanographic changes42 (e.g., intensified stratification) observed during OAE-2. Thus, an abundance of proxy- and model-based results paired with conceptual evidence suggest relatively low production and enhanced preservation of organic carbon throughout OAE-2 at the equatorial Demerara Rise.The pre-OAE BP may foreshadow greater regional trends observed during OAE-2. Equatorial upwelling centers, like Demerara Rise, are spatially restricted and represent regions of already high primary production before OAE-2. Climatic shifts concurrent with OAE-2 may have produced favorable conditions for elevated primary productivity in regions unable to capitalize on or exposed to allochthonous nutrient delivery prior to the +CIE. While the pre-OAE BP offers a causal mechanism for the Tl isotope excursion and +CIE initiation, areal expansion of organic carbon preservation and production is necessary to sustain enhanced organic carbon burial for the duration of the +CIE.Continued development of preexisting proxies is critical to extract and clarify current understandings of major climatic events in Earth history. Although reliant on excellent preservation of the microbial signal, the analytical and interpretative approach used here enables simultaneous examination of a wide array of biomarkers, producing a more holistic reconstruction of oceanographic changes inferred from microbial ecological variations spanning the surface to the sediment. This is timely, as investigations of the sedimentary archives become increasingly valuable analogs to understand the response of modern oceans to natural and anthropogenic forcings. Similarities between the pre-OAE BP and modern, climate-driven marine deoxygenation are concerning, while particular attention to preexisting highly productive settings may hold the key to forecasting the geologically rapid transition to a global OAE. Even though natural processes are currently beyond our control, stifling anthropogenic catalysts of climate change may decelerate the unfortunate, progressive suitability of OAEs as climate analogs in the future. More

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    Population dynamics of synanthropic rodents after a chemical and infrastructural intervention in an urban low-income community

    Panti-May, J. A. et al. A two-year ecological study of Norway rats (Rattus norvegicus) in a Brazilian Urban Slum. PLoS ONE 11(3), 1–12. https://doi.org/10.1371/journal.pone.0152511 (2016).CAS 
    Article 

    Google Scholar 
    Himsworth, C. G. et al. A mixed methods approach to exploring the relationship between Norway rat (Rattus norvegicus) abundance and features of the urban environment in an inner-city neighborhood of Vancouver, Canada. PLoS ONE 9(5), 97776. https://doi.org/10.1371/journal.pone.0097776 (2014).ADS 
    CAS 
    Article 

    Google Scholar 
    Lambert, M. S., Quy, R. J., Smith, R. H. & Cowan, D. P. The effect of habitat management on home-range size and survival of rural Norway rat populations. J. Appl. Ecol. 45(6), 1753–1761. https://doi.org/10.1111/j.1365-2664.2008.01543.x (2008).Article 

    Google Scholar 
    Meerburg, B. G., Singleton, G. R. & Kijlstra, A. Rodent-borne diseases and their risks for public health (Vol. 7828). https://doi.org/10.1080/10408410902989837 (2009)Buckle, A. & Smith, R. Rodent Pests and Their Control 2nd edn. (CABI Press, Wallingford, 2015).Book 

    Google Scholar 
    Byers, K. A., Lee, M. J., Patrick, D. M. & Himsworth, C. G. Rats about town: A systematic review of rat movement in urban ecosystems. Front. Ecol. Evol. 7, 1–12. https://doi.org/10.3389/fevo.2019.00013 (2019).Article 

    Google Scholar 
    Carvalho-Pereira, T. et al. The helminth community of a population of Rattus norvegicus from an urban Brazilian slum and the threat of zoonotic diseases. Parasitology 145(6), 797–806. https://doi.org/10.1017/S0031182017001755 (2018).Article 
    PubMed 

    Google Scholar 
    Costa, F. et al. Patterns in Leptospira shedding in Norway rats (Rattus norvegicus) from Brazilian slum communities at high risk of disease transmission. PLoS Negl. Trop. Dis. 9(6), 1–14. https://doi.org/10.1371/journal.pntd.0003819 (2015).CAS 
    Article 

    Google Scholar 
    Parsons, M. H. et al. Rats and the COVID-19 pandemic: Early data on the global emergence of rats in response to social distancing. MedRxiv https://doi.org/10.1101/2020.07.05.20146779 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Awoniyi, A. M. et al. Effect of chemical and sanitary intervention on rat sightings in urban communities of New Providence, the Bahamas. SN Appl. Sci. 3, 495. https://doi.org/10.1007/s42452-021-04459-x (2021).CAS 
    Article 

    Google Scholar 
    Costa, F. et al. Influence of household rat infestation on leptospira transmission in the urban slum environment. PLoS Negl. Trop. Dis. 8(12), 3338. https://doi.org/10.1371/journal.pntd.0003338 (2014).Article 

    Google Scholar 
    Khalil, H. et al. Poverty, sanitation, and Leptospira transmission pathways in residents from four Brazilian slums. PLoS Negl. Trop. Dis. 15(3), 1–15. https://doi.org/10.1371/journal.pntd.0009256 (2021).Article 

    Google Scholar 
    Zeppelini, C. G. et al. Demographic drivers of Norway rat populations from urban slums in Brazil. Urban Ecosyst. https://doi.org/10.1007/s11252-020-01075-2 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    United Nations -UN. World Urbanization Prospects: The 2018 Revision. https://www.un.org/development/desa/en/news/population/2018-revision-of-world-urbanization-prospects.html. Accessed 24 Dec 2020 (2018)United Nations UN-SDG. Sustainable Development Goals: Make cities and human settlements inclusive, safe, resilient and sustainable. https://unstats.un.org/sdgs/report/2019/goal-11/#:~:text=The%20absolute%20number%20of%20people,Southern%20Asia%20(227%20million). Accessed 24 Dec 2020 (2018)Russell, J. C., Towns, D. R. & Clout, M. N. Review of rat invasion biology: Implications for island biosecurity. Sci. Conserv. 286, 1–53 (2008).
    Google Scholar 
    Minter, A. et al. Optimal control of rat-borne leptospirosis in an urban environment. Front. Ecol. Evol. 7, 1–10. https://doi.org/10.3389/fevo.2019.00209 (2019).ADS 
    Article 

    Google Scholar 
    Mathur, R. P. Effectiveness of various rodent control measures in cereal crops and plantations in India. In: Leirs H. and Schockaert E. ed. Proceedings of the International Workshop on Rodent Biology and Integrated Pest Management in Africa, 21-25 October 1996, Morogoro, Tanzania. Belg. J. Zool. 127(supplement 1), 137–144 (1997).
    Google Scholar 
    Pascal, M., Siorat, F., Lorvelec, O., Yésou, P. & Simberloff, D. A pleasing consequence of Norway rat eradication : Two shrew species recover. Divers. Distrib. 11, 193–198. https://doi.org/10.1111/j.1366-9516.2005.00137.x (2005).Article 

    Google Scholar 
    Singleton, G. R., Hinds, L. & Leirs, H. Ecologically-based management of rodent pests. Australian Centre for International Agricultural Research, (ACIAR Monograph 59), 494. (1999)Sullivan, L. M. Roof rat control around homes and other structures. Cooper. Extens. Bull. AZ 1280, 1–6 (2002).
    Google Scholar 
    Childs, J. E. Size-dependent predation on rats (Rattus norvegicus) by house cats (Felis catus) in an urban setting. J. Mammol. 67(1), 196–199 (1986).Article 

    Google Scholar 
    Davis, D. E. The characteristics of rat populations. Quart. Rev. Biol. 28, 373–401. https://doi.org/10.1086/399860 (1953).CAS 
    Article 
    PubMed 

    Google Scholar 
    Glass, G. E. et al. Trophic garnishes: Cat-Rat interactions in an urban environment. PLoS ONE 4(6), e5794. https://doi.org/10.1371/journal.pone.0005794 (2009).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Lenton, G. M. Biological control of rats by owls in oil palm and other plantations. Biotrop Spec. Publ. 12, 87–94 (1980).
    Google Scholar 
    Smith, R. H. & Meyer, A. N. Rodent controlmethods: Non-chemical and non-lethal chemical, with special reference to food stores. In Rodent Pests and Their Control 2nd edn (eds Buckle, A. & Smith, R.) 81–101 (CABI International, 2015) (ISBN-13: 978-1-84593-817-8).
    Google Scholar 
    Oyedele, D. T., Sah, S. A. M., Kairuddin, L. & Ibrahim, W. M. M. W. Range measurement and a habitat suitability map for the Norway rat in a highly developed urban environment. Trop. Life Sci. Res. 26(2), 27–44 (2015).PubMed 
    PubMed Central 

    Google Scholar 
    Hansen, N., Hughes, N. K., Bryom, A. E. & Banks, P. B. Population recovery of alien black rats Rattus rattus: A test of reinvasion theory. Austral Ecol. 45, 291–304. https://doi.org/10.1111/aec.12855 (2020).Article 

    Google Scholar 
    Awoniyi, A. M. et al. Using Rhodamine B to assess the movement of small mammals in an urban slum. Methods Ecol. Evol. 12(11), 2234–2242. https://doi.org/10.1111/2041-210X.13693 (2021).Article 

    Google Scholar 
    Glass, G. E., Klein, S. L., Norris, D. E. & Gardner, L. C. Multiple paternity in urban Norway rats: Extended ranging for mates. Vector-Borne Zoonotic Dis. 16(5), 342–248. https://doi.org/10.1089/vbz.2015.1816 (2016).Article 
    PubMed 

    Google Scholar 
    Buckle, A. P. & Eason, C. T. Rodent control methods: Chemical. In Rodent Pests and Their Control 2nd edn (eds Buckle, A. & Smith, R.) 81–101 (CABI International, Wallingford, 2015) (ISBN-13: 978-1-84593-817-8).Chapter 

    Google Scholar 
    de Masi, E., Pedro, J. V. & Maria, T. P. Evaluation on the effectiveness of actions for controlling infestation by rodents in Campo Limpo region, São Paulo Municipality, Brazil Access details: Access Details: [subscription number 913003116]. Int. J. Environ. Health Res. 19(4), 291–304. https://doi.org/10.1080/09603120802592723 (2009).Article 
    PubMed 

    Google Scholar 
    Lambropoulos, A. S. et al. Rodent control in urban areas—An interdisciplinary approach. J. Environ. Health 61, 12–17 (1999).
    Google Scholar 
    Reis, R. B. et al. Impact of environment and social gradient on Leptospira infection in urban slums. PLoS Negl. Trop. Dis. 2(4), 11–18. https://doi.org/10.1371/journal.pntd.0000228 (2008).MathSciNet 
    Article 

    Google Scholar 
    Instituto Brasileiro de Geografia e Estatistica (IBGE). Accessed 15 November 2019 (2010)CDC. Integrated pest management: conducting urban rodent surveys. Centers for Disease Control and Prevention-Atlanta: US Department of Health and Human Services (2006)Hacker, K. P. et al. A comparative assessment of track plates to quantify fine scale variations in the relative abundance of Norway rats in urban slums. Urban Ecosyst. 19(2), 561–575. https://doi.org/10.1007/s11252-015-0519-8 (2016).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Eyre, M. T. et al. A multivariate geostatistical framework for combining multiple indices of abundance for disease vectors and reservoirs: A case study of rattiness in a low-income urban Brazilian community: A multivariate geostatistical framework for combining multiple ind. J. R. Soc. Interface 17(170), 1–21. https://doi.org/10.1098/rsif.2020.0398 (2020).Article 

    Google Scholar 
    Bursac, Z., Gauss, C. H., Williams, D. K. & Hosmer, D. W. Purposeful selection of variables in logistic regression. Source Code Biol. Med. 8, 1–8. https://doi.org/10.1186/1751-0473-3-17 (2008).Article 

    Google Scholar 
    Burnham, K. P. & Anderson, D. R. Model selection and multimodel inference: A practical information-theoretic approach (Springer, 2002).MATH 

    Google Scholar 
    R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org (2019).Bates, D., Maechler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67(1), 1–48. https://doi.org/10.18637/jss.v067.i01 (2015).Article 

    Google Scholar 
    Barton, K. MuMIn: Multi-Model Inference. R package version 1.43.17. https://CRAN.R-project.org/package=MuMIn (2020)Kassambara A. ggpubr: ‘ggplot2’ Based Publication Ready Plots. R package version 0.4.0. https://CRAN.R-project.org/package=ggpubr (2020)Richardson, J. L. et al. Using fine-scale spatial genetics of Norway rats to improve control efforts and reduce leptospirosis risk in urban slum environments. Evol. Appl. 10(4), 323–337. https://doi.org/10.1111/eva.12449 (2017).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Santos, N. D. J., Sousa, E., Reis, M. G., Ko, A. I. & Costa, F. Rat infestation associated with environmental deficiencies in an urban slum community with high risk of leptospirosis. Cad. Saúde Pública 33(2), 1–13. https://doi.org/10.1590/0102-311X00132115 (2017).CAS 
    Article 

    Google Scholar 
    Murray, M. H. & Sanchez, C. A. Urban rat exposure to anticoagulant rodenticides and zoonotic infection risk. Biol. Lett. 17, 20210311. https://doi.org/10.1098/rsbl.2021.0311 (2021).CAS 
    Article 
    PubMed 

    Google Scholar 
    Parsons, M. H., Banks, P. B., Deutsch, M. A., Corrigan, R. F. & Munshi-South, J. Trends in urban rat ecology: A framework to define the prevailing knowledge gaps and incentives for academia, pest management professionals (PMPs) and public health agencies to participate. J. Urban Ecol. 3(1), 1–8. https://doi.org/10.1093/jue/jux005 (2017).Article 

    Google Scholar 
    Costa, F. et al. Household rat infestation in urban slum populations: Development and validation of a predictive score for leptospirosis Household rat infestation in urban slum populations: Development and validation of a predictive score for leptospirosis. PLoS Negl. Trop. Dis. 15(3), 9154. https://doi.org/10.1371/journal.pntd.0009154 (2021).Article 

    Google Scholar 
    Mwanjabe, P. S. & Leirs, H. An early warning system for IPM-based rodent control in smallholder farming systems in Tanzania. In: Leirs, H., & Schockaert, E., ed., Proceedings of the International Workshop on Rodent Biology and Integrated Pest Management in Africa, 21-25 October 1996, Morogoro, Tanzania. Belg. J. Zool. 127(supplement 1), 4–58 (1997).
    Google Scholar 
    Richards, C. G. J. R. & Buckle, A. P. Towards integrated rodent pest management at the village level. In Control of Mammal Pests (eds Richards, C. G. J. R. & Ku, T. Y.) 293–312 (Taylor and Francis, 1987).
    Google Scholar 
    Masi, E. Socioeconomic and environmental risk factors for urban rodent infestation in Sao Paulo, Brazil. J. Pest Sci. 83(3), 231–241. https://doi.org/10.1007/s10340-010-0290-9 (2010).Article 

    Google Scholar 
    Brooks, J. E. Methods of sewer rat control. In Proceedings of the 1st Vertebrate Pest Conference. https://digitalcommons.unl.edu/vpcone/17. Accessed 20 August 2021 (1962) More

  • in

    Expected contraction in the distribution ranges of demersal fish of high economic value in the Mediterranean and European Seas

    Gattuso, J.-P. et al. Ocean solutions to address climate change and its effects on marine ecosystems. Front. Mar. Sci. 5, 337 (2018).Article 

    Google Scholar 
    Pauly, D. The gill-oxygen limitation theory (GOLT) and its critics. Sci. Adv. 7, 6050 (2021).Article 
    ADS 
    CAS 

    Google Scholar 
    Miller, D. D., Ota, Y., Sumaila, U. R., Cisneros-Montemayor, A. M. & Cheung, W. W. L. Adaptation strategies to climate change in marine systems. Glob. Change Biol. 24, e1–e14 (2018).Article 
    ADS 

    Google Scholar 
    Chan, F. T. et al. Climate change opens new frontiers for marine species in the Arctic: Current trends and future invasion risks. Glob. Change Biol. 25, 25–38 (2019).Article 
    ADS 

    Google Scholar 
    Cheung, W. W. L. et al. Structural uncertainty in projecting global fisheries catches under climate change. Ecol. Model. 325, 57–66 (2016).CAS 
    Article 

    Google Scholar 
    Pita, I., Mouillot, D., Moullec, F. & Shin, Y. Contrasted patterns in climate change risk for Mediterranean fisheries. Glob. Change Biol. 27, 5920–5933 (2021).Article 

    Google Scholar 
    Tacon, A. G. J. & Metian, M. Fishing for aquaculture: Non-food use of small pelagic forage fish—a global perspective. Rev. Fish. Sci. 17, 305–317 (2009).Article 

    Google Scholar 
    Coll, M., Pennino, M. G., Steenbeek, J., Sole, J. & Bellido, J. M. Predicting marine species distributions: Complementarity of food-web and Bayesian hierarchical modelling approaches. Ecol. Model. 405, 86–101 (2019).Article 

    Google Scholar 
    Schickele, A. et al. Improving predictions of invasive fish ranges combining functional and ecological traits with environmental suitability under climate change scenarios. Glob. Change Biol. 27, 6086–6102 (2021).Article 

    Google Scholar 
    Lejeusne, C., Chevaldonné, P., Pergent-Martini, C., Boudouresque, C. F. & Pérez, T. Climate change effects on a miniature ocean: The highly diverse, highly impacted Mediterranean Sea. Trends Ecol. Evol. 25, 250–260 (2010).PubMed 
    Article 

    Google Scholar 
    Cramer, W. et al. Climate change and interconnected risks to sustainable development in the Mediterranean. Nat. Clim. Change 8, 972–980 (2018).Article 
    ADS 

    Google Scholar 
    FAO. The State of Mediterranean and Black Sea Fisheries 2020—At a glance. 20 (2020).McGinty, N., Barton, A. D., Finkel, Z. V., Johns, D. G. & Irwin, A. J. Niche conservation in copepods between ocean basins. Ecography https://doi.org/10.1111/ecog.05690 (2021).Article 

    Google Scholar 
    Dormann, C. F. et al. Biotic interactions in species distribution modelling: 10 questions to guide interpretation and avoid false conclusions. Glob. Ecol. Biogeogr. 27, 1004–1016 (2018).Article 

    Google Scholar 
    Hannemann, H., Willis, K. J. & Macias-Fauria, M. The devil is in the detail: unstable response functions in species distribution models challenge bulk ensemble modelling: Unstable response functions in SDMs. Glob. Ecol. Biogeogr. 25, 26–35 (2016).Article 

    Google Scholar 
    Beaugrand, G. et al. Prediction of unprecedented biological shifts in the global ocean. Nat. Clim. Chang. 9, 237–243 (2019).Article 
    ADS 

    Google Scholar 
    Lasram, B. R. et al. An open-source framework to model present and future marine species distributions at local scale. Ecol. Inform. 59, 101130 (2020).Article 

    Google Scholar 
    Araújo, M. B. et al. Standards for distribution models in biodiversity assessments. Sci. Adv. 5, 4858 (2019).Article 
    ADS 

    Google Scholar 
    Schickele, A. et al. European small pelagic fish distribution under global change scenarios. Fish Fish 22, 212–225 (2021).Article 

    Google Scholar 
    Duarte, R., Azevedo, M., Landa, J. & Pereda, P. Reproduction of angler®sh (Lophius budegassa Spinola and Lophius piscatorius Linnaeus) from the Atlantic Iberian coast. Fish. Res. 13, 2 (2001).
    Google Scholar 
    Nunes, P., Svensson, L. & Markandya, A. Handbook on the Economics and Management of Sustainable Oceans (Edward Elgar Publishing, 2017).Book 

    Google Scholar 
    Schickele, A. et al. Modelling European small pelagic fish distribution: Methodological insights. Ecol. Model. 416, 108902 (2020).Article 

    Google Scholar 
    Cheung, W. W. L., Jones, M. C., Reygondeau, G. & Frölicher, T. L. Opportunities for climate-risk reduction through effective fisheries management. Glob. Change Biol. 24, 5149–5163 (2018).Article 
    ADS 

    Google Scholar 
    Bossier, S. et al. The Baltic Sea Atlantis: An integrated end-to-end modelling framework evaluating ecosystem-wide effects of human-induced pressures. PLoS ONE 13, e0199168 (2018).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Dahlke, F. T., Wohlrab, S., Butzin, M. & Pörtner, H.-O. Thermal bottlenecks in the life cycle define climate vulnerability of fish. Science 369, 65–70 (2020).CAS 
    PubMed 
    Article 
    ADS 

    Google Scholar 
    Valle, C., Bayle-Sempere, J. T., Dempster, T., Sanchez-Jerez, P. & Giménez-Casalduero, F. Temporal variability of wild fish assemblages associated with a sea-cage fish farm in the south-western Mediterranean Sea. Estuar. Coast. Shelf Sci. 72, 299–307 (2007).Article 
    ADS 

    Google Scholar 
    Madurell, T., Cartes, J. E. & Labropoulou, M. Changes in the structure of fish assemblages in a bathyal site of the Ionian Sea (eastern Mediterranean). Fish. Res. 66, 245–260 (2004).Article 

    Google Scholar 
    Volkoff, H. & Rønnestad, I. Effects of temperature on feeding and digestive processes in fish. Temperature 7, 307–320 (2020).Article 

    Google Scholar 
    Rutterford, L. A. et al. Future fish distributions constrained by depth in warming seas. Nat. Clim. Change 5, 569–573 (2015).Article 
    ADS 

    Google Scholar 
    Pauly, D. & Christensen, V. Primary production required to sustain global fisheries. Nature 374, 255–257 (1995).CAS 
    Article 
    ADS 

    Google Scholar 
    Conti, L. & Scardi, M. Fisheries yield and primary productivity in large marine ecosystems. Mar. Ecol. Prog. Ser. 410, 233–244 (2010).Article 
    ADS 

    Google Scholar 
    Chérif, M. et al. Food and feeding habits of the red mullet, Mullus barbatus (Actinopterygii: Perciformes: Mullidae), off the northern Tunisian coast (central Mediterranean). Acta Icth et Piscat 41, 109–116 (2011).Article 

    Google Scholar 
    Mellon-Duval, C. et al. Trophic ecology of the European hake in the Gulf of Lions, northwestern Mediterranean Sea. Sci. Mar. 81, 7 (2017).Article 

    Google Scholar 
    Steingrund, P. & Gaard, E. Relationship between phytoplankton production and cod production on the Faroe Shelf. ICES J. Mar. Sci. 62, 163–176 (2005).Article 

    Google Scholar 
    Friedland, K. D. et al. Pathways between primary production and fisheries yields of large marine ecosystems. PLoS ONE 7, e28945 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 
    ADS 

    Google Scholar 
    Frederiksen, M., Edwards, M., Richardson, A. J., Halliday, N. C. & Wanless, S. From plankton to top predators: Bottom-up control of a marine food web across four trophic levels. J. Anim. Ecol. 75, 1259–1268 (2006).PubMed 
    Article 

    Google Scholar 
    Vasilakopoulos, P., Raitsos, D. E., Tzanatos, E. & Maravelias, C. D. Resilience and regime shifts in a marine biodiversity hotspot. Sci. Rep. 7, 13647 (2017).PubMed 
    PubMed Central 
    Article 
    ADS 
    CAS 

    Google Scholar 
    Issifu, I., Alava, J. J., Lam, V. W. Y. & Sumaila, U. R. Impact of ocean warming, overfishing and mercury on European fisheries: A risk assessment and policy solution framework. Front. Mar. Sci. 8, 770805 (2022).Article 

    Google Scholar 
    Lima, A. R. A. et al. Forecasting shifts in habitat suitability across the distribution range of a temperate small pelagic fish under different scenarios of climate change. Sci. Total Environ. 804, 150167 (2022).CAS 
    PubMed 
    Article 
    ADS 

    Google Scholar 
    Sumaila, U. R. et al. Benefits of the Paris Agreement to ocean life, economies, and people. Sci. Adv. 5, 3855 (2019).Article 
    ADS 

    Google Scholar 
    Holsman, K. K. et al. Ecosystem-based fisheries management forestalls climate-driven collapse. Nat. Commun. 11, 4579 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 
    ADS 

    Google Scholar 
    Sumaila, U. R. & Tai, T. C. End overfishing and increase the resilience of the ocean to climate change. Front. Mar. Sci. 7, 523 (2020).Article 

    Google Scholar 
    Lindegren, M. & Brander, K. Adapting fisheries and their management to climate change: A review of concepts, tools, frameworks, and current progress toward implementation. Rev. Fish. Sci. Aquacult. 26, 400–415 (2018).Article 

    Google Scholar 
    Demirel, N., Zengin, M. & Ulman, A. First large-scale eastern mediterranean and black sea stock assessment reveals a dramatic decline. Front. Mar. Sci. 7, 103 (2020).Article 

    Google Scholar 
    Weiss, C. V. C. et al. Climate change effects on marine renewable energy resources and environmental conditions for offshore aquaculture in Europe. ICES J. Mar. Sci. 77, 3168–3182 (2020).Article 

    Google Scholar 
    Cascarano, M. C. et al. Mediterranean aquaculture in a changing climate: temperature effects on pathogens and diseases of three farmed fish species. Pathogens 10, 1205 (2021).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Kleitou, P. et al. Fishery reforms for the management of non-indigenous species. J. Environ. Manag. 280, 111690 (2021).Article 

    Google Scholar 
    Hamida, B.-B. & O, Ben Hadj Hamida N, Chaouch H, Missaoui H,. Allometry, condition factor and growth of the swimming blue crab Portunus segnis in the Gulf of Gabes, Southeastern Tunisia (Central Mediterranean). Medit. Mar. Sci. 20, 566 (2019).Article 

    Google Scholar 
    Wisz, M. S. et al. Reply to ‘Sources of uncertainties in cod distribution models’. Nat. Clim. Change 5, 790–791 (2015).Article 
    ADS 

    Google Scholar 
    Kramer-Schadt, S. et al. The importance of correcting for sampling bias in MaxEnt species distribution models. Divers. Distrib. 19, 1366–1379 (2013).Article 

    Google Scholar 
    Buisson, L., Thuiller, W., Casajus, N., Lek, S. & Grenouillet, G. Uncertainty in ensemble forecasting of species distribution. Glob. Change Biol. 16, 1145–1157 (2010).Article 
    ADS 

    Google Scholar 
    Hao, T., Elith, J., Lahoz-Monfort, J. J. & Guillera-Arroita, G. Testing whether ensemble modelling is advantageous for maximising predictive performance of species distribution models. Ecography 43, 549–558 (2020).Article 

    Google Scholar 
    Thuiller, W., Damie, G., Robin, E., Frank, F.Biomod2: Ensemble Platform for Species Distribution Modeling (2016).Stolar, J. & Nielsen, S. E. Accounting for spatially biased sampling effort in presence-only species distribution modelling. Divers. Distrib. 21, 595–608 (2015).Article 

    Google Scholar 
    Stockwell, D. The GARP modelling system: Problems and solutions to automated spatial prediction. Int. J. Geogr. Inf. Sci. 13, 143–158 (1999).Article 

    Google Scholar 
    Cornwell, W. K., Schwilk, D. W. & Ackerly, D. D. A trait-based test for habitat filtering: Convex hull volume. Ecology 87(6), 1465–1471 (2003).Article 

    Google Scholar 
    Hengl, T., Sierdsema, H., Radović, A. & Dilo, A. Spatial prediction of species’ distributions from occurrence-only records: Combining point pattern analysis ENFA and regression-kriging. Ecol. Modell. 220, 3499–3511 (2009).Article 

    Google Scholar 
    Faillettaz, R., Beaugrand, G., Goberville, E. & Kirby, R. R. Atlantic Multidecadal Oscillations drive the basin-scale distribution of Atlantic bluefin tuna. Sci. Adv. 5, eaar6993 (2019).Lavoie, D., Lambert, N. & Gilbert, D. Projections of future trends in biogeochemical conditions in the northwest Atlantic using CMIP5 earth system models. Atmos. Ocean 57, 18–40 (2019).CAS 
    Article 

    Google Scholar 
    Taylor, K. E. Summarizing multiple aspects of model performance in a single diagram. J. Geophys. Res. 106, 7183–7192 (2001).Article 
    ADS 

    Google Scholar 
    Cristofari, R. et al. Climate-driven range shifts of the king penguin in a fragmented ecosystem. Nat. Clim. Change 8, 245–251 (2018).Article 
    ADS 

    Google Scholar 
    Zeller, D. et al. Still catching attention: Sea Around Us reconstructed global catch data, their spatial expression and public accessibility. Mar. Policy 70, 145–152 (2016).Article 

    Google Scholar 
    GBIF.org (27 May 2020) GBIF Occurrence Download https://doi.org/10.15468/dl.2crvdpGBIF.org (7 June 2020) GBIF Occurrence Download https://doi.org/10.15468/dl.y8ujd7GBIF.org (7 June 2020) GBIF Occurrence Download https://doi.org/10.15468/dl.hs8py7GBIF.org (7 June 2020) GBIF Occurrence Download https://doi.org/10.15468/dl.kqwq3aGBIF.org (14 July 2020) GBIF Occurrence Download https://doi.org/10.15468/dl.raka7jGBIF.org (14 July 2020) GBIF Occurrence Download https://doi.org/10.15468/dl.fwbk43GBIF.org (30 July 2020) GBIF Occurrence Download https://doi.org/10.15468/dl.845mcwGBIF.org (30 July 2020) GBIF Occurrence Download https://doi.org/10.15468/dl.wdavbrGBIF.org (11 September 2020) GBIF Occurrence Download https://doi.org/10.15468/dl.ucuavw More

  • in

    A polar bear paleogenome reveals extensive ancient gene flow from polar bears into brown bears

    Hewitt, G. The genetic legacy of the Quaternary ice ages. Nature 405, 907–913 (2000).CAS 
    Article 
    PubMed 

    Google Scholar 
    Muhlfeld, C. C. et al. Invasive hybridization in a threatened species is accelerated by climate change. Nat. Clim. Change 4, 620–624 (2014).Article 

    Google Scholar 
    Taylor, S. A. et al. Climate-mediated movement of an avian hybrid zone. Curr. Biol. 24, 671–676 (2014).CAS 
    Article 
    PubMed 

    Google Scholar 
    Cahill, J. A. et al. Genomic evidence of widespread admixture from polar bears into brown bears during the last ice age. Mol. Biol. Evol. 35, 1120–1129 (2018).CAS 
    Article 
    PubMed 

    Google Scholar 
    Mao, Y., Economo, E. P. & Satoh, N. The roles of introgression and climate change in the rise to dominance of Acropora corals. Curr. Biol. 28, 3373–3382.e5 (2018).CAS 
    Article 
    PubMed 

    Google Scholar 
    Vianna, J. A. et al. Genome-wide analyses reveal drivers of penguin diversification. Proc. Natl Acad. Sci. USA 117, 22303–22310 (2020).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Racimo, F., Sankararaman, S., Nielsen, R. & Huerta-Sánchez, E. Evidence for archaic adaptive introgression in humans. Nat. Rev. Genet. 16, 359–371 (2015).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    McKelvey, K. S. et al. Patterns of hybridization among cutthroat trout and rainbow trout in northern Rocky Mountain streams. Ecol. Evol. 6, 688–706 (2016).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kim, B. Y., Huber, C. D. & Lohmueller, K. E. Deleterious variation shapes the genomic landscape of introgression. PLoS Genet. 14, e1007741 (2018).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Wu, D.-D. et al. Pervasive introgression facilitated domestication and adaptation in the Bos species complex. Nat. Ecol. Evol. 2, 1139–1145 (2018).Article 
    PubMed 

    Google Scholar 
    Wang, M.-S. et al. Ancient hybridization with an unknown population facilitated high-altitude adaptation of canids. Mol. Biol. Evol. 37, 2616–2629 (2020).CAS 
    Article 
    PubMed 

    Google Scholar 
    Meier, J. I. et al. Ancient hybridization fuels rapid cichlid fish adaptive radiations. Nat. Commun. 8, 14363 (2017).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Haig, S. M., Mullins, T. D., Forsman, E. D., Trail, P. W. & Wennerberg, L. I. V. Genetic identification of spotted owls, barred owls, and their hybrids: legal implications of hybrid identity. Conserv. Biol. 18, 1347–1357 (2004).Article 

    Google Scholar 
    vonHoldt, B. M. et al. Whole-genome sequence analysis shows that two endemic species of North American wolf are admixtures of the coyote and gray wolf. Sci. Adv. 2, e1501714 (2016).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Liu, S. et al. Population genomics reveal recent speciation and rapid evolutionary adaptation in polar bears. Cell 157, 785–794 (2014).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kumar, V. et al. The evolutionary history of bears is characterized by gene flow across species. Sci. Rep. 7, 46487 (2017).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Preuß, A., Gansloßer, U., Purschke, G. & Magiera, U. Bear-hybrids: behaviour and phenotype. Zool. Gart. 78, 204–220 (2009).Article 

    Google Scholar 
    Cahill, J. A. et al. Genomic evidence for island population conversion resolves conflicting theories of polar bear evolution. PLoS Genet. 9, e1003345 (2013).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Cahill, J. A. et al. Genomic evidence of geographically widespread effect of gene flow from polar bears into brown bears. Mol. Ecol. 24, 1205–1217 (2015).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Pongracz, J. D., Paetkau, D., Branigan, M. & Richardson, E. Recent hybridization between a polar bear and grizzly bears in the Canadian Arctic. Arctic 70, 151–160 (2017).Article 

    Google Scholar 
    Pugach, I., Matveyev, R., Wollstein, A., Kayser, M. & Stoneking, M. Dating the age of admixture via wavelet transform analysis of genome-wide data. Genome Biol. 12, R19 (2011).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Farquharson, L. et al. Alaskan marine transgressions record out-of-phase Arctic Ocean glaciation during the last interglacial. Geology 46, 783–786 (2018).Article 

    Google Scholar 
    Kapp, J. D., Green, R. E. & Shapiro, B. A fast and efficient single-stranded genomic library preparation method optimized for ancient DNA. J. Hered. 112, 241–249 (2021).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Briggs, A. W. et al. Patterns of damage in genomic DNA sequences from a Neandertal. Proc. Natl Acad. Sci. USA 104, 14616–14621 (2007).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Li, H. & Durbin, R. Inference of human population history from individual whole-genome sequences. Nature 475, 493–496 (2011).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Fu, Q. et al. Genome sequence of a 45,000-year-old modern human from western Siberia. Nature 514, 445–449 (2014).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Schiffels, S. & Durbin, R. Inferring human population size and separation history from multiple genome sequences. Nat. Genet. 46, 919–925 (2014).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Pease, J. B. & Hahn, M. W. Detection and polarization of introgression in a five-taxon phylogeny. Syst. Biol. 64, 651–662 (2015).CAS 
    Article 
    PubMed 

    Google Scholar 
    Barlow, A. et al. Middle Pleistocene genome calibrates a revised evolutionary history of extinct cave bears. Curr. Biol. 31, 1771–1779.e7 (2021).CAS 
    Article 
    PubMed 

    Google Scholar 
    Barlow, A. et al. Partial genomic survival of cave bears in living brown bears. Nat. Ecol. Evol. 2, 1563–1570 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Wang, K., Mathieson, I., O’Connell, J. & Schiffels, S. Tracking human population structure through time from whole genome sequences. PLoS Genet. 16, e1008552 (2020).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Polyak, L. et al. History of sea ice in the Arctic. Quat. Sci. Rev. 29, 1757–1778 (2010).Article 

    Google Scholar 
    Dutton, A. et al. Sea-level rise due to polar ice-sheet mass loss during past warm periods. Science 349, aaa4019 (2015).CAS 
    Article 
    PubMed 

    Google Scholar 
    Salonen, J. S. et al. Abrupt high-latitude climate events and decoupled seasonal trends during the Eemian. Nat. Commun. 9, 2851 (2018).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Guarino, M.-V. et al. Sea-ice-free Arctic during the Last Interglacial supports fast future loss. Nat. Clim. Change 10, 928–932 (2020).Article 

    Google Scholar 
    Rode, K. D., Robbins, C. T., Nelson, L. & Amstrup, S. C. Can polar bears use terrestrial foods to offset lost ice-based hunting opportunities? Front. Ecol. Environ. 13, 138–145 (2015).Article 

    Google Scholar 
    Laidre, K. L., Stirling, I., Estes, J. A., Kochnev, A. & Roberts, J. Historical and potential future importance of large whales as food for polar bears. Front. Ecol. Environ. 16, 515–524 (2018).Article 

    Google Scholar 
    Miller, S., Wilder, J. & Wilson, R. R. Polar bear–grizzly bear interactions during the autumn open-water period in Alaska. J. Mammal. 96, 1317–1325 (2015).Article 

    Google Scholar 
    Steyaert, S. M. J. G., Endrestøl, A., Hackländer, K., Swenson, J. E. & Zedrosser, A. The mating system of the brown bear Ursus arctos. Mamm. Rev. 42, 12–34 (2012).Article 

    Google Scholar 
    Stirling, I., Spencer, C. & Andriashek, D. Behavior and activity budgets of wild breeding polar bears (Ursus maritimus). Mar. Mamm. Sci. 32, 13–37 (2016).Article 

    Google Scholar 
    Méheust, M., Stein, R., Fahl, K. & Gersonde, R. Sea-ice variability in the subarctic North Pacific and adjacent Bering Sea during the past 25 ka: new insights from IP25 and Uk′37 proxy records. Arktos 4, 1–19 (2018).Article 

    Google Scholar 
    Brigham-Grette, J. & Hopkins, D. M. Emergent marine record and paleoclimate of the last interglaciation along the northwest Alaskan coast. Quat. Res. 43, 159–173 (1995).Article 

    Google Scholar 
    Boessenkool, S. et al. Combining bleach and mild predigestion improves ancient DNA recovery from bones. Mol. Ecol. Resour. 17, 742–751 (2017).CAS 
    Article 
    PubMed 

    Google Scholar 
    Dabney, J. et al. Complete mitochondrial genome sequence of a Middle Pleistocene cave bear reconstructed from ultrashort DNA fragments. Proc. Natl Acad. Sci. USA 110, 15758–15763 (2013).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Meyer, M. & Kircher, M. Illumina sequencing library preparation for highly multiplexed target capture and sequencing. Cold Spring Harb. Protoc. 2010, pdb.prot5448 (2010).Article 
    PubMed 

    Google Scholar 
    Kircher, M., Sawyer, S. & Meyer, M. Double indexing overcomes inaccuracies in multiplex sequencing on the Illumina platform. Nucleic Acids Res. 40, e3 (2012).CAS 
    Article 
    PubMed 

    Google Scholar 
    Rohland, N. & Reich, D. Cost-effective, high-throughput DNA sequencing libraries for multiplexed target capture. Genome Res. 22, 939–946 (2012).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Li, H. & Durbin, R. Fast and accurate long-read alignment with Burrows–Wheeler transform. Bioinformatics 26, 589–595 (2010).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Jónsson, H., Ginolhac, A., Schubert, M., Johnson, P. L. F. & Orlando, L. mapDamage2.0: fast approximate Bayesian estimates of ancient DNA damage parameters. Bioinformatics 29, 1682–1684 (2013).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Prüfer, K. snpAD: an ancient DNA genotype caller. Bioinformatics 34, 4165–4171 (2018).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Green, R. E. et al. A complete Neandertal mitochondrial genome sequence determined by high-throughput sequencing. Cell 134, 416–426 (2008).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Li, H. Aligning sequence reads, clone sequences and assembly contigs with BWA–MEM. Preprint at https://doi.org/10.48550/arXiv.1303.3997 (2013).McKenna, A. et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kumar, S., Stecher, G., Peterson, D. & Tamura, K. MEGA-CC: computing core of molecular evolutionary genetics analysis program for automated and iterative data analysis. Bioinformatics 28, 2685–2686 (2012).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kumar, S., Stecher, G. & Tamura, K. MEGA7: Molecular Evolutionary Genetics Analysis version 7.0 for bigger datasets. Mol. Biol. Evol. 33, 1870–1874 (2016).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Vihtakari, M. PlotSvalbard: User Manual. Github https://mikkovihtakari.github.io/PlotSvalbard/articles/PlotSvalbard.html (2020).Yu, G., Smith, D. K., Zhu, H., Guan, Y. & Lam, T. T. ggtree: an R package for visualization and annotation of phylogenetic trees with their covariates and other associated data. Methods Ecol. Evol. 8, 28–36 (2017).Article 

    Google Scholar 
    Yu, G. Using ggtree to visualize data on tree-like structures. Curr. Protoc. Bioinformatics 69, e96 (2020).Article 
    PubMed 

    Google Scholar 
    Yu, G., Lam, T. T., Zhu, H. & Guan, Y. Two methods for mapping and visualizing associated data on phylogeny using ggtree. Mol. Biol. Evol. 35, 3041–3043 (2018).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Wang, L.-G. et al. Treeio: an R package for phylogenetic tree input and output with richly annotated and associated data. Mol. Biol. Evol. 37, 599–603 (2020).CAS 
    Article 
    PubMed 

    Google Scholar 
    Lindqvist, C. et al. Complete mitochondrial genome of a Pleistocene jawbone unveils the origin of polar bear. Proc. Natl Acad. Sci. USA 107, 5053–5057 (2010).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Edgar, R. C. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 32, 1792–1797 (2004).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Stamatakis, A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30, 1312–1313 (2014).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Browning, B. L. & Browning, S. R. Genotype imputation with millions of reference samples. Am. J. Hum. Genet. 98, 116–126 (2016).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kelleher, J., Etheridge, A. M. & McVean, G. Efficient coalescent simulation and genealogical analysis for large sample sizes. PLoS Comput. Biol. 12, e1004842 (2016).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Palkopoulou, E. et al. Complete genomes reveal signatures of demographic and genetic declines in the woolly mammoth. Curr. Biol. 25, 1395–1400 (2015).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Green, R. E. et al. A draft sequence of the Neandertal genome. Science 328, 710–722 (2010).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Patterson, N. et al. Ancient admixture in human history. Genetics 192, 1065–1093 (2012).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Vershinina, A. O. et al. Ancient horse genomes reveal the timing and extent of dispersals across the Bering Land Bridge. Mol. Ecol. 30, 6144–6161 (2021).Article 
    PubMed 

    Google Scholar 
    Chen, L., Wolf, A. B., Fu, W., Li, L. & Akey, J. M. Identifying and interpreting apparent Neanderthal ancestry in African individuals. Cell 180, 677–687.e16 (2020).CAS 
    Article 
    PubMed 

    Google Scholar 
    Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Lisiecki, L. E. & Raymo, M. E. A Pliocene-Pleistocene stack of 57 globally distributed benthic δ18O records. Paleoceanography 20, PA1003 (2005).
    Google Scholar  More