More stories

  • in

    Science diplomacy for plant health

    European and Mediterranean Plant Protection Organization (EPPO)-Euphresco, Paris, France
    Baldissera Giovani & Nico Horn

    Austrian Agency for Health and Food Safety (AGES), Institute for Sustainable Plant Production, Vienna, Austria
    Sylvia Blümel

    Food Department, Ministry of Agriculture and Forestry of Finland, Helsinki, Finland
    Ralf Lopian

    Better Border Biosecurity (B3), Plant and Food Research, Christchurch, New Zealand
    David Teulon

    North American Plant Protection Organization (NAPPO), Raleigh, NC, USA
    Stephanie Bloem

    Comite Regional de Sanidad Vegetal del Cono Sur (COSAVE), Dirección de Protección Vegetal, del Servicio Nacional y Sanidad Vegetal y Semillas, Asuncion, Paraguay
    Cristina Galeano Martínez

    Comunidad Andina (CAN), Secretaría General de la Comunidad Andina, Lima, Peru
    Camilo Beltrán Montoya

    Organismo Internacional Regional de Sanidad Agropecuaria (OIRSA), San Salvador, El Salvador
    Carlos Ramon Urias Morales

    Asia and Pacific Plant Protection Commission (APPPC), Bangkok, Thailand
    Sridhar Dharmapuri

    Pacific Plant Protection Organization (PPPO), Pacific Community Land Resources Division, Suva, Fiji
    Visoni Timote

    Near East Plant Protection Organization (NEPPO), Rabat, Morocco
    Mekki Chouibani

    African-Union Interafrican Phytosanitary Council (IAPSC), Yaoundé, Cameroon
    Jean Gérard Mezui M’Ella

    Ministry of Primary Industries (MPI), Wellington, New Zealand
    Veronica Herrera & Aurélie Castinel

    Department of Agriculture, Water and the Environment (DAWE), Canberra, Australian Capital Territory, Australia
    Con Goletsos, Carina Moeller & Ian Naumann

    European Food Safety Authority (EFSA), Parma, Italy
    Giuseppe Stancanelli, Stef Bronzwaer & Sara Tramontini

    Canadian Food Inspection Agency (CFIA), Ottawa, Ontario, Canada
    Philip MacDonald & Loren Matheson

    French Agency for Food, Environmental and Occupational Health and Safety (ANSES), Plant Health Laboratory, Angers, France
    Géraldine Anthoine

    Research Institute for Agriculture, Fisheries and Food (ILVO), Merelbeke, Belgium
    Kris De Jonghe

    Netherlands Food and Consumer Product Safety Authority (NVWA), Wageningen, the Netherlands
    Martijn Schenk

    Julius Kühn Institute (JKI), Braunschweig, Germany
    Silke Steinmöller

    National Institute for Agricultural and Food Research and Technology (INIA), Madrid, Spain
    Elena Rodriguez

    National Institute for Agriculture and Veterinary Research (INIAV), Oeiras, Portugal
    Maria Leonor Cruz

    Plant Biosecurity Research Initiative (PBRI), Hort Innovation, Melbourne, Victoria, Australia
    Jo Luck

    Plant Health Australia (PHA), Deakin, Canberra, Australian Capital Territory, Australia
    Greg Fraser

    International Plant Protection Convention (IPPC), Food and Agriculture Organization of the United Nations, Rome, Italy
    Sarah Brunel, Mirko Montuori, Craig Fedchock & Jingyuan Xia

    Department for Environment, Food & Rural Affairs (DEFRA), London, UK
    Elspeth Steel & Helen Grace Pennington

    Centre for Agriculture and Bioscience International (CABI), Nairobi, Kenya
    Roger Day

    French National Institute for Agricultural Research (INRA), INRA-Montpellier-CBGP, Montferrier-sur-Lez, France
    Jean Pierre Rossi

    B.G. wrote the manuscript. S.B., R.L., D.T., S.B., C.G.M., C.B.M., C.R.U.M., S.D., V.T., N.H., M.C., J.G.M.M., V.H., A.C., C.G., C.M., I.N., G.S., S.B., S.T., P.M.D., L.M., G.A., K.D.J., M.S., S.S., E.R., M.L.C., J.L., G.F., S.B., M.M., C.F., E.S., H.G.P., R.D., J.P.R. and J.X. contributed to the manuscript. More

  • in

    The role of seagrass vegetation and local environmental conditions in shaping benthic bacterial and macroinvertebrate communities in a tropical coastal lagoon

    1.
    Birkeland, C. & Grosenbaugh, D. Ecological interactions between tropical coastal ecosystems. in UNEP Regional Seas Reports and Studies, Vol. 73 (PNUMA, 1985).
    2.
    Moberg, F. & Rönnbäck, P. Ecosystem services of the tropical seascape: interactions, substitutions and restoration. Ocean Coast. Manag.46, 27–46 (2003).
    Google Scholar 

    3.
    Gladstone, W. Conservation and management of tropical coastal ecosystems. In Ecological Connectivity Among Tropical Coastal Ecosystems (ed. Nagelkerken, I.) 565–605 (Springer, Dordrecht, 2009). https://doi.org/10.1007/978-90-481-2406-0_16.
    Google Scholar 

    4.
    Berkström, C. et al. Exploring ‘knowns’ and ‘unknowns’ in tropical seascape connectivity with insights from East African coral reefs. Estuar. Coast. Shelf Sci.107, 1–21 (2012).
    ADS  Google Scholar 

    5.
    Ogden, J. C. The influence of adjacent systems on the structure and function of coral reefs. In Proceedings of the 6th International Coral Reef Symposium, Vol. 1, 123–129 (1988).

    6.
    Nagelkerken, I. et al. Importance of mangroves, seagrass beds and the shallow coral reef as a nursery for important coral reef fishes, using a visual census technique. Estuar. Coast. Shelf Sci.51, 31–44 (2000).
    ADS  Google Scholar 

    7.
    Grober-Dunsmore, R., Pittman, S. J., Caldow, C., Kendall, M. S. & Frazer, T. K. A landscape ecology approach for the study of ecological connectivity across tropical marine seascapes. In Ecological Connectivity Among Tropical Coastal Ecosystems (ed. Nagelkerken, I.) 493–530 (Springer, Dordrecht, 2009). https://doi.org/10.1007/978-90-481-2406-0_14.
    Google Scholar 

    8.
    Hemminga, M. A. & Duarte, C. M. Seagrass ecology (Cambridge University Press, Cambridge, 2000). https://doi.org/10.1017/CBO9780511525551.
    Google Scholar 

    9.
    Short, F., Carruthers, T., Dennison, W. & Waycott, M. Global seagrass distribution and diversity: a bioregional model. J. Exp. Mar. Biol. Ecol.350, 3–20 (2007).
    Google Scholar 

    10.
    Knowles, L. L. & Bell, S. S. The influence of habitat structure in faunal-habitat associations in a Tampa Bay seagrass system Florida. Bull. Mar. Sci.62, 781–794 (1998).
    Google Scholar 

    11.
    Connolly, R. M. & Hindell, J. S. Review of nekton patterns and ecological processes in seagrass landscapes. Estuar. Coast. Shelf Sci.68, 433–444 (2006).
    ADS  Google Scholar 

    12.
    Horinouchi, M. Review of the effects of within-patch scale structural complexity on seagrass fishes. J. Exp. Mar. Biol. Ecol.350, 111–129 (2007).
    Google Scholar 

    13.
    Gacia, E., Duarte, C. M. & Middelburg, J. J. Carbon and nutrient deposition in a Mediterranean seagrass (Posidonia oceanica) meadow. Limnol. Oceanogr.47, 23–32 (2002).
    ADS  CAS  Google Scholar 

    14.
    Hendriks, I. E., Sintes, T., Bouma, T. J. & Duarte, C. M. Experimental assessment and modeling evaluation of the effects of the seagrass Posidonia oceanica on flow and particle trapping. Mar. Ecol. Prog. Ser.356, 163–173 (2008).
    ADS  Google Scholar 

    15.
    Beck, M. W. et al. The identification, conservation, and management of estuarine and marine nurseries for fish and invertebrates: a better understanding of the habitats that serve as nurseries for marine species and the factors that create site-specific variability in nursery quality will improve conservation and management of these areas. AIBS Bull.51, 633–641 (2001).
    Google Scholar 

    16.
    Heck, K. L. Jr., Hays, G. & Orth, R. J. Critical evaluation of the nursery role hypothesis for seagrass meadows. Mar. Ecol. Prog. Ser.253, 123–136 (2003).
    ADS  Google Scholar 

    17.
    Boström, C., Jackson, E. L. & Simenstad, C. A. Seagrass landscapes and their effects on associated fauna: a review. Estuar. Coast. Shelf Sci.68, 383–403 (2006).
    ADS  Google Scholar 

    18.
    Unsworth, R. K. F. & Cullen, L. C. Recognising the necessity for Indo-Pacific seagrass conservation. Conserv. Lett.3, 63–73 (2010).
    Google Scholar 

    19.
    Leopardas, V., Uy, W. & Nakaoka, M. Benthic macrofaunal assemblages in multispecific seagrass meadows of the southern Philippines: variation among vegetation dominated by different seagrass species. J. Exp. Mar. Biol. Ecol.457, 71–80 (2014).
    Google Scholar 

    20.
    Waycott, M. et al. Accelerating loss of seagrasses across the globe threatens coastal ecosystems. PNAS106, 12377–12381 (2009).
    ADS  CAS  PubMed  Google Scholar 

    21.
    Short, F. T. & Wyllie-Echeverria, S. Natural and human-induced disturbance of seagrasses. Environ. Conserv.23, 17–27 (1996).
    Google Scholar 

    22.
    Short, F. T. et al. Extinction risk assessment of the world’s seagrass species. Biol. Conserv.144, 1961–1971 (2011).
    Google Scholar 

    23.
    Duarte, C. M. The future of seagrass meadows. Environ. Conserv.29, 192–206 (2002).
    Google Scholar 

    24.
    Hastings, K., Hesp, P. & Kendrick, G. A. Seagrass loss associated with boat moorings at Rottnest Island, Western Australia. Ocean Coast. Manag.26, 225–246 (1995).
    Google Scholar 

    25.
    Orth, R. J., Luckenbach, M. L., Marion, S. R., Moore, K. A. & Wilcox, D. J. Seagrass recovery in the Delmarva Coastal Bays, USA. Aquat. Bot.84, 26–36 (2006).
    Google Scholar 

    26.
    Ruiz, J. M. & Romero, J. Effects of in situ experimental shading on the Mediterranean seagrass Posidonia oceanica. Mar. Ecol. Prog. Ser.215, 107–120 (2001).
    ADS  Google Scholar 

    27.
    Frost, M. T., Rowden, A. A. & Attrill, M. J. Effect of habitat fragmentation on the macroinvertebrate infaunal communities associated with the seagrass Zostera marina L. Aquat. Conserv. Mar. Freshw. Ecosyst.9, 255–263 (1999).
    Google Scholar 

    28.
    Hovel, K. A. Habitat fragmentation in marine landscapes: relative effects of habitat cover and configuration on juvenile crab survival in California and North Carolina seagrass beds. Biol. Conserv.110, 401–412 (2003).
    Google Scholar 

    29.
    Hovel, K. A. & Lipcius, R. N. Effects of seagrass habitat fragmentation on juvenile blue crab survival and abundance. J. Exp. Mar. Biol. Ecol.271, 75–98 (2002).
    Google Scholar 

    30.
    Thomas, C. D. & Mallorie, H. C. Rarity, species richness and conservation: butterflies of the Atlas Mountains in Morocco. Biol. Conserv.33, 95–117 (1985).
    Google Scholar 

    31.
    Fahrig, L. Effects of habitat fragmentation on biodiversity. Ann. Rev. Ecol. Evol. Syst.34, 487–515 (2003).
    Google Scholar 

    32.
    Fischer, J. & Lindenmayer, D. B. Landscape modification and habitat fragmentation: a synthesis. Glob. Ecol. Biogeogr.16, 265–280 (2007).
    Google Scholar 

    33.
    Link, J. Does food web theory work for marine ecosystems?. Mar. Ecol. Prog. Ser.230, 1–9 (2002).
    ADS  Google Scholar 

    34.
    Peterson, B. J., Thompson, K. R., Cowan, J. H. Jr. & Heck, K. L. Jr. Comparison of predation pressure in temperate and subtropical seagrass habitats based on chronographic tethering. Mar. Ecol. Prog. Ser.224, 77–85 (2001).
    ADS  Google Scholar 

    35.
    Sweatman, J. L., Layman, C. A. & Fourqurean, J. W. Habitat fragmentation has some impacts on aspects of ecosystem functioning in a sub-tropical seagrass bed. Mar. Environ. Res.126, 95–108 (2017).
    CAS  PubMed  Google Scholar 

    36.
    Williams, J. A. et al. Seagrass fragmentation impacts recruitment dynamics of estuarine-dependent fish. J. Exp. Mar. Biol. Ecol.479, 97–105 (2016).
    Google Scholar 

    37.
    Bell, S. S., Brooks, R. A., Robbins, B. D., Fonseca, M. S. & Hall, M. O. Faunal response to fragmentation in seagrass habitats: implications for seagrass conservation. Biol. Conserv.100, 115–123 (2001).
    Google Scholar 

    38.
    McCloskey, R. M. & Unsworth, R. K. F. Decreasing seagrass density negatively influences associated fauna. PeerJ3, e1053 (2015).
    PubMed  PubMed Central  Google Scholar 

    39.
    Ubertini, M. et al. Spatial variability of benthic-pelagic coupling in an estuary ecosystem: consequences for microphytobenthos resuspension phenomenon. PLoS ONE7, e44155 (2012).
    ADS  CAS  PubMed  PubMed Central  Google Scholar 

    40.
    Welsh, D. T. Nitrogen fixation in seagrass meadows: regulation, plant–bacteria interactions and significance to primary productivity. Ecol. Lett.3, 58–71 (2000).
    Google Scholar 

    41.
    Alongi, D. M. The role of bacteria in nutrient recycling in tropical mangrove and other coastal benthic ecosystems. Hydrobiologia285, 19–32 (1994).
    CAS  Google Scholar 

    42.
    Harrison, P. G. Detrital processing in seagrass systems: a review of factors affecting decay rates, remineralization and detritivory. Aquat. Bot.35, 263–288 (1989).
    Google Scholar 

    43.
    Mateo, M. A. & Romero, J. Detritus dynamics in the seagrass Posidonia oceanica: elements for an ecosystem carbon and nutrient budget. Mar. Ecol. Prog. Ser.151, 43–53 (1997).
    ADS  CAS  Google Scholar 

    44.
    Barrón, C., Apostolaki, E. T. & Duarte, C. M. Dissolved organic carbon fluxes by seagrass meadows and macroalgal beds. Front. Mar. Sci.1, 42 (2014).
    Google Scholar 

    45.
    Wetzel, R. G. & Penhale, P. A. Transport of carbon and excretion of dissolved organic carbon by leaves and roots/rhizomes in seagrasses and their epiphytes. Aquat. Bot.6, 149–158 (1979).
    CAS  Google Scholar 

    46.
    Martin, B. C. et al. Low light availability alters root exudation and reduces putative beneficial microorganisms in seagrass roots. Front. Microbiol.8, 2667 (2018).
    PubMed  PubMed Central  Google Scholar 

    47.
    Danovaro, R. Detritus-Bacteria-Meiofauna interactions in a seagrass bed (Posidonia oceanica) of the NW Mediterranean. Mar. Biol.127, 1–13 (1996).
    CAS  Google Scholar 

    48.
    Lohrer, A. M., Thrush, S. F. & Gibbs, M. M. Bioturbators enhance ecosystem function through complex biogeochemical interactions. Nature431, 1092–1095 (2004).
    ADS  CAS  PubMed  Google Scholar 

    49.
    Rosenberg, R. Marine benthic faunal successional stages and related sedimentary activity. Sci. Marina65, 107–119 (2001).
    Google Scholar 

    50.
    Austen, M. C. et al. Biodiversity links above and below the marine sediment–water interface that may influence community stability. Biodivers. Conserv.11, 113–136 (2002).
    Google Scholar 

    51.
    Fanjul, E., Bazterrica, M. C., Escapa, M., Grela, M. A. & Iribarne, O. Impact of crab bioturbation on benthic flux and nitrogen dynamics of Southwest Atlantic intertidal marshes and mudflats. Estuar. Coast. Shelf Sci.92, 629–638 (2011).
    ADS  CAS  Google Scholar 

    52.
    Forster, S. & Graf, G. Impact of irrigation on oxygen flux into the sediment: intermittent pumping by Callianassa subterranea and “piston-pumping” by Lanice conchilega. Mar. Biol.123, 335–346 (1995).
    Google Scholar 

    53.
    Snelgrove, P. V. R. The biodiversity of macrofaunal organisms in marine sediments. Biodivers. Conserv.7, 1123–1132 (1998).
    Google Scholar 

    54.
    Hyndes, G. A. & Lavery, P. S. Does transported seagrass provide an important trophic link in unvegetated, nearshore areas?. Estuar. Coast. Shelf Sci.63, 633–643 (2005).
    ADS  CAS  Google Scholar 

    55.
    Jones, D. A., Ghamrawy, M. & Wahbeh, M. I. Littoral and shallow subtidal environments. In Red Sea (eds Edwards, A. J. & Head, S. M.) 169–193 (Pergamon Press, London, 1987). https://doi.org/10.1016/B978-0-08-028873-4.50014-1.
    Google Scholar 

    56.
    Ruiz-Compean, P. et al. Baseline evaluation of sediment contamination in the shallow coastal areas of Saudi Arabian Red Sea. Mar. Pollut. Bull.123, 205–218 (2017).
    CAS  PubMed  Google Scholar 

    57.
    Bologna, P. A. X. & Heck, K. L. Impact of habitat edges on density and secondary production of seagrass-associated fauna. Estuaries25, 1033–1044 (2002).
    Google Scholar 

    58.
    Calleja, M. L., Al-Otaibi, N. & Morán, X. A. G. Dissolved organic carbon contribution to oxygen respiration in the central Red Sea. Sci. Rep.9, 1–12 (2019).
    CAS  Google Scholar 

    59.
    Stedmon, C. A., Markager, S. & Bro, R. Tracing dissolved organic matter in aquatic environments using a new approach to fluorescence spectroscopy. Mar. Chem.82, 239–254 (2003).
    CAS  Google Scholar 

    60.
    Coble, P. G. Marine optical biogeochemistry: the chemistry of ocean color. Chem. Rev.107, 402–418 (2007).
    ADS  CAS  PubMed  Google Scholar 

    61.
    Gasol, J. M. & Morán, X. A. G. Flow cytometric determination of microbial abundances and its use to obtain indices of community structure and relative activity. In Hydrocarbon and Lipid Microbiology Protocols: Single-Cell and Single-Molecule Methods (eds McGenity, T. J. et al.) 159–1870 (Springer, Berlin, 2015). https://doi.org/10.1007/8623_2015_139.
    Google Scholar 

    62.
    Silva, L. et al. Low abundances but high growth rates of coastal heterotrophic bacteria in the Red Sea. Front. Microbiol.9, 3244 (2019).
    PubMed  PubMed Central  Google Scholar 

    63.
    Leray, M. & Knowlton, N. DNA barcoding and metabarcoding of standardized samples reveal patterns of marine benthic diversity. PNAS112, 2076–2081 (2015).
    ADS  CAS  PubMed  Google Scholar 

    64.
    Klindworth, A. et al. Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. Nucl. Acids Res.41, e1 (2013).
    CAS  PubMed  Google Scholar 

    65.
    Oksanen, J. et al. Vegan: community ecology package. R package version 2.5-2, (2018).

    66.
    R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, Vienna, 2018).

    67.
    Lê, S., Josse, J. & Husson, F. FactoMineR: a package for multivariate analysis. J. Stat. Softw.25, 1–18 (2008).
    Google Scholar 

    68.
    Goslee, S. C. & Urban, D. L. The ecodist package for dissimilarity-based analysis of ecological data. J. Stat. Softw.22, 1–19 (2007).
    Google Scholar 

    69.
    Chen, H. VennDiagram: Generate High-Resolution Venn and Euler Plots (2018).

    70.
    Clarke, K. R. & Gorley, R. N. PRIMER v7: User Manual/Tutorial, PRIMER-E: Plymouth (2015).

    71.
    Callahan, B. J. et al. DADA2: high-resolution sample inference from Illumina amplicon data. Nat. Methods13, 581–583 (2016).
    CAS  PubMed  PubMed Central  Google Scholar 

    72.
    Pruesse, E. et al. SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucl. Acids Res.35, 7188–7196 (2007).
    CAS  PubMed  Google Scholar 

    73.
    McMurdie, P. J. & Holmes, S. phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE8, e61217 (2013).
    ADS  CAS  PubMed  PubMed Central  Google Scholar 

    74.
    Keeley, N., Wood, S. A. & Pochon, X. Development and preliminary validation of a multi-trophic metabarcoding biotic index for monitoring benthic organic enrichment. Ecol. Indic.85, 1044–1057 (2018).
    CAS  Google Scholar 

    75.
    Lobelle, D., Kenyon, E. J., Cook, K. J. & Bull, J. C. Local competition and metapopulation processes drive long-term seagrass-epiphyte population dynamics. PLoS ONE8, e57072 (2013).
    ADS  CAS  PubMed  PubMed Central  Google Scholar 

    76.
    Ávila, E., Yáñez, B. & Vazquez-Maldonado, L. E. Influence of habitat structure and environmental regime on spatial distribution patterns of macroinvertebrate assemblages associated with seagrass beds in a southern Gulf of Mexico coastal lagoon. Mar. Biol. Res.11, 755–764 (2015).
    Google Scholar 

    77.
    Barnes, R. S. K. & Hendy, I. W. Seagrass-associated macrobenthic functional diversity and functional structure along an estuarine gradient. Estuar. Coast. Shelf Sci.164, 233–243 (2015).
    Google Scholar 

    78.
    York, P. H., Hyndes, G. A., Bishop, M. J. & Barnes, R. S. K. Faunal assemblages of seagrass ecosystems. In Seagrasses of Australia: Structure, Ecology and Conservation (eds Larkum, A. W. D. et al.) 541–588 (Springer, Berlin, 2018). https://doi.org/10.1007/978-3-319-71354-0_17.
    Google Scholar 

    79.
    Magni, P., Como, S., Kamijo, A. & Montani, S. Effects of Zostera marina on the patterns of spatial distribution of sediments and macrozoobenthos in the boreal lagoon of Furen (Hokkaido, Japan). Mar. Environ. Res.131, 90–102 (2017).
    CAS  PubMed  Google Scholar 

    80.
    Thomsen, M. S. et al. Secondary foundation species enhance biodiversity. Nat. Ecol. Evol.2, 634 (2018).
    PubMed  Google Scholar 

    81.
    Attrill, M. J., Strong, J. A. & Rowden, A. A. Are macroinvertebrate communities influenced by seagrass structural complexity?. Ecography23, 114–121 (2000).
    Google Scholar 

    82.
    Lee, S. Y., Fong, C. W. & Wu, R. S. S. The effects of seagrass (Zostera japonica) canopy structure on associated fauna: a study using artificial seagrass units and sampling of natural beds. J. Exp. Mar. Biol. Ecol.259, 23–50 (2001).
    PubMed  Google Scholar 

    83.
    Nakamura, Y. & Sano, M. Comparison of invertebrate abundance in a seagrass bed and adjacent coral and sand areas at Amitori Bay, Iriomote Island, Japan. Fish. Sci.71, 543–550 (2005).
    CAS  Google Scholar 

    84.
    Barrio Froján, C. R. S. et al. The importance of bare marine sedimentary habitats for maintaining high polychaete diversity and the implications for the design of marine protected areas. Aquat. Conserv. Mar. Freshw. Ecosyst.19, 748–757 (2009).
    Google Scholar 

    85.
    Barnes, R. S. K. & Barnes, M. K. S. Spatial uniformity of biodiversity is inevitable if the available species are distributed independently of each other. Mar. Ecol. Prog. Ser.516, 263–266 (2014).
    ADS  Google Scholar 

    86.
    Webster, P. J., Rowden, A. A. & Attrill, M. J. Effect of shoot density on the infaunal macro-invertebrate community within a Zostera marina seagrass bed. Estuar. Coast. Shelf Sci.47, 351–357 (1998).
    ADS  Google Scholar 

    87.
    Bowden, D. A., Rowden, A. A. & Attrill, M. J. Effect of patch size and in-patch location on the infaunal macroinvertebrate assemblages of Zostera marina seagrass beds. J. Exp. Mar. Biol. Ecol.259, 133–154 (2001).
    PubMed  Google Scholar 

    88.
    Turner, S. J. et al. Seagrass patches and landscapes: the influence of wind-wave dynamics and hierarchical arrangements of spatial structure on macrofaunal seagrass communities. Estuaries22, 1016–1032 (1999).
    Google Scholar 

    89.
    Tanner, J. E. Edge effects on fauna in fragmented seagrass meadows. Austral Ecol.30, 210–218 (2005).
    Google Scholar 

    90.
    Włodarska-Kowalczuk, M., Jankowska, E., Kotwicki, L. & Balazy, P. Evidence of season-dependency in vegetation effects on macrofauna in temperate seagrass meadows (Baltic Sea). PLoS ONE9, e100788 (2014).
    ADS  PubMed  PubMed Central  Google Scholar 

    91.
    Calleja, M. L., Barrón, C., Hale, J. A., Frazer, T. K. & Duarte, C. M. Light regulation of benthic sulfate reduction rates mediated by seagrass (Thalassia testudinum) metabolism. Estuar. Coasts J ERF29, 1255–1264 (2006).
    CAS  Google Scholar 

    92.
    Barnes, R. S. K. & Barnes, M. K. S. Shore height and differentials between macrobenthic assemblages in vegetated and unvegetated areas of an intertidal sandflat. Estuar. Coast. Shelf Sci.106, 112–120 (2012).
    ADS  Google Scholar 

    93.
    Agawin, N. S. R., Duarte, C. M., Fortes, M. D., Uri, J. S. & Vermaat, J. E. Temporal changes in the abundance, leaf growth and photosynthesis of three co-occurring Philippine seagrasses. J. Exp. Mar. Biol. Ecol.260, 217–239 (2001).
    PubMed  Google Scholar 

    94.
    Pereg, L. L., Lipkin, Y. & Sar, N. Different niches of the Halophila stipulacea seagrass bed harbor distinct populations of nitrogen fixing bacteria. Mar. Biol.119, 327–333 (1994).
    CAS  Google Scholar 

    95.
    Holmer, M., Duarte, C., Boschker, H. & Barrón, C. Carbon cycling and bacterial carbon sources in pristine and impacted Mediterranean seagrass sediments. Aquat. Microb. Ecol.36, 227–237 (2004).
    Google Scholar 

    96.
    Barberá-Cebrián, C., Sánchez-Jerez, P. & Ramos-Esplá, A. Fragmented seagrass habitats on the Mediterranean coast, and distribution and abundance of mysid assemblages. Mar. Biol.141, 405–413 (2002).
    Google Scholar 

    97.
    Ringold, P. Burrowing, root mat density, and the distribution of fiddler crabs in the eastern United States. J. Exp. Mar. Biol. Ecol.36, 11–21 (1979).
    Google Scholar 

    98.
    Ricart, A. M. et al. Variability of sedimentary organic carbon in patchy seagrass landscapes. Mar. Pollut. Bull.100, 476–482 (2015).
    CAS  PubMed  Google Scholar 

    99.
    Samper-Villarreal, J., Lovelock, C. E., Saunders, M. I., Roelfsema, C. & Mumby, P. J. Organic carbon in seagrass sediments is influenced by seagrass canopy complexity, turbidity, wave height, and water depth. Limnol. Oceanogr.61, 938–952 (2016).
    ADS  Google Scholar 

    100.
    Serra, T., Oldham, C. & Colomer, J. Local hydrodynamics at edges of marine canopies under oscillatory flows. PLoS ONE13, e0201737 (2018).
    PubMed  PubMed Central  Google Scholar 

    101.
    Choat, J. H. & Kingett, P. D. The influence of fish predation on the abundance cycles of an algal turf invertebrate fauna. Oecologia54, 88–95 (1982).
    ADS  CAS  PubMed  Google Scholar 

    102.
    Nakamura, Y., Horinouchi, M., Nakai, T. & Sano, M. Food habits of fishes in a seagrass bed on a fringing coral reef at Iriomote Island, southern Japan. Ichthyol. Res.50, 0015–0022 (2003).
    Google Scholar 

    103.
    Eklöf, J. S., de la Torre Castro, M., Adelsköld, L., Jiddawi, N. S. & Kautsky, N. Differences in macrofaunal and seagrass assemblages in seagrass beds with and without seaweed farms. Estuar. Coast. Shelf Sci.63, 385–396 (2005).
    ADS  Google Scholar 

    104.
    Díaz-Cárdenas, C., Patel, B. K. C. & Baena, S. Tistlia consotensisgen. nov., sp. an aerobic, chemoheterotrophic, free-living, nitrogen-fixing alphaproteobacterium, isolated from a Colombian saline spring. Int. J. Syst. Evol. Microbiol.60, 1437–1443 (2010).
    PubMed  Google Scholar 

    105.
    Sun, F. et al. Seagrass (Zostera marina) colonization promotes the accumulation of diazotrophic bacteria and alters the relative abundances of specific bacterial lineages involved in benthic carbon and sulfur cycling. Appl. Environ. Microbiol.81, 6901–6914 (2015).
    CAS  PubMed  PubMed Central  Google Scholar 

    106.
    Brown, S. M. & Jenkins, B. D. Profiling gene expression to distinguish the likely active diazotrophs from a sea of genetic potential in marine sediments. Environ. Microbiol.16, 3128–3142 (2014).
    CAS  PubMed  PubMed Central  Google Scholar 

    107.
    Santos, R., Lirman, D. & Pittman, S. Long-term spatial dynamics in vegetated seascapes: fragmentation and habitat loss in a human-impacted subtropical lagoon. Mar. Ecol.37(1), 200–214. https://doi.org/10.1111/maec.12259 (2015).
    ADS  Article  Google Scholar 

    108.
    Irlandi, E. & Crawford, M. Habitats linkages: the effect of intertidal saltmarshes and adjacent habitats on abundance, movement and growth of an estuarine fish. Oecologia110, 222–230 (1997).
    ADS  CAS  PubMed  Google Scholar 

    109.
    Boström, C., Pittman, S. J., Simenstad, C. & Kneib, R. T. Seascape ecology of coastal biogenic habitats: advances, gaps, and challenges. Mar. Ecol. Prog. Ser.427, 191–218 (2011).
    ADS  Google Scholar 

    110.
    Mumby, P. J. Connectivity of reef fish between mangroves and coral reefs: algorithms for the design of marine reserves at seascape scales. Biol. Conserv.128, 215–222 (2006).
    Google Scholar 

    111.
    Haila, Y. A conceptual genealogy of fragmentation research: from island biogeography to landscape ecology. Ecol. Appl.12, 321–334 (2002).
    Google Scholar 

    112.
    Barnes, R. S. K. Distribution patterns of macrobenthic biodiversity in the intertidal seagrass beds of an estuarine system, and their conservation significance. Biodivers. Conserv.22, 357–372 (2013).
    Google Scholar 

    113.
    Barnes, R. S. K. & Hamylton, S. On the very edge: faunal and functional responses to the interface between benthic seagrass and unvegetated sand assemblages. Mar. Ecol. Prog. Ser.553, 33–48 (2016).
    ADS  Google Scholar  More

  • in

    Effects of short-term manure nitrogen input on soil microbial community structure and diversity in a double-cropping paddy field of southern China

    1.
    Börjesson, G., Menichetti, L., Kirchmann, H. & Kätterer, T. Soil microbial community structure affected by 53 years of nitrogen fertilisation and different organic amendments. Biol. Fertil. Soils48, 245–257 (2012).
    Article  Google Scholar 
    2.
    Cui, J. et al. Carbon and nitrogen recycling from microbial necromass to cope with C: N stoichiometric imbalance by priming. Soil Biol. Biochem.142, 107720 (2020).
    CAS  Article  Google Scholar 

    3.
    Xiao, D. et al. Microbial biomass, metabolic functional diversity, and activity are affected differently by tillage disturbance and maize planting in a typical karst calcareous soil. J. Soil. Sediment.19, 809–821 (2019).
    CAS  Article  Google Scholar 

    4.
    Dangi, S., Gao, S., Duan, Y. H. & Wang, D. Soil microbial community structure affected by biochar and fertilizer sources. Appl. Soil Ecol.150, 103452 (2020).
    Article  Google Scholar 

    5.
    Geisseler, D. & Scow, K. M. Long-term effects of mineral fertilizers on soil microorganisms: a review. Soil Biol. Biochem.75, 54–63 (2014).
    CAS  Article  Google Scholar 

    6.
    Trivedi, P. et al. Soil aggregation and associated microbial communities modify the impact of agricultural management on carbon content. Environ. Microbiol.19, 3070–3086 (2017).
    CAS  Article  Google Scholar 

    7.
    Jia, X., Li, X. D., Zhao, Y. H., Wang, L. & Zhang, C. Y. Soil microbial community structure in the rhizosphere of Robinia pseudoacacia L. seedlings exposed to elevated air temperature and cadmium-contaminated soils for 4 years. Sci. Total Environ.650, 2355–2363 (2019).
    ADS  CAS  Article  Google Scholar 

    8.
    Zhong, W. et al. The effects of mineral fertilizer and organic manure on soil microbial community and diversity. Plant Soil326, 511–522 (2010).
    CAS  Article  Google Scholar 

    9.
    Hartmann, M., Frey, B., Mayer, J., Maeder, P. & Widmer, F. Distinct soil microbial diversity under long-term organic and conventional farming. ISME J.9, 1177–1194 (2015).
    Article  Google Scholar 

    10.
    Francioli, D. et al. Mineral versus organic amendments: microbial community structure, activity and abundance of agriculturally relevant microbes are driven by long-term fertilization strategies. Front. Microbiol.14, 1446 (2016).
    Google Scholar 

    11.
    Wang, Y. et al. Long-term no-tillage and organic input management enhanced the diversity and stability of soil microbial community. Sci. Total Environ.609, 341–347 (2017).
    ADS  CAS  Article  Google Scholar 

    12.
    Treonis, A. M. et al. Effects of organic amendment and tillage on soil microorganisms and microfauna. Appl. Soil Ecol.46, 103–110 (2010).
    Article  Google Scholar 

    13.
    Forge, T. A., Hogue, E. J., Neilsen, G. & Neilsen, D. Organic mulches alter nematode communities, root growth and fluxes of phosphorus in the root zone of apple. Appl. Soil Ecol.39, 15–22 (2008).
    Article  Google Scholar 

    14.
    Ahn, J. et al. Dynamics of bacterial communities in rice field soils as affected by different long-term fertilization practices. J. Microbiol.54, 724–731 (2016).
    CAS  Article  Google Scholar 

    15.
    Zhu, X. C. et al. Soil microbial community and activity are affected by integrated agricultural practices in China. Eur. J. Soil Sci.69, 924–935 (2018).
    Article  Google Scholar 

    16.
    Yang, X. Y., Ren, W. D., Sun, B. H. & Zhang, S. L. Effects of contrasting soil management regimes on total and labile soil organic carbon fractions in a loess soil in China. Geoderma177–178, 49–56 (2012).
    ADS  Article  Google Scholar 

    17.
    Chen, Z. D., Ti, F. S. & Chen, F. Soil aggregates response to tillage and residue management in a double paddy rice soil of the southern China. Nutr. Cycl. Agroecosyst.109, 103–114 (2017).
    Article  Google Scholar 

    18.
    Wei, X., Zhu, Z., Wei, L., Wu, J. & Ge, T. Biogeochemical cycles of key elements in the paddy-rice rhizosphere: microbial mechanisms and coupling processes. Rhizosphere10, 100145 (2019).
    Article  Google Scholar 

    19.
    Tang, H. M. et al. Effects of different soil tillage systems on soil carbon management index under double-cropping rice field in southern China. Agron. J.111, 440–446 (2019).
    CAS  Article  Google Scholar 

    20.
    Tang, H. M. et al. Organic manure managements increases soil microbial community structure and diversity in double-cropping paddy field of southern China. Agric. Ecosyst. Environ. https://doi.org/10.1101/2020.04.08.031609 (2020).
    Article  Google Scholar 

    21.
    Zhao, J. et al. Pyrosequencing reveals contrasting soil bacterial diversity and community structure of two main winter wheat cropping systems in China. Microb. Ecol.67, 443–453 (2014).
    Article  Google Scholar 

    22.
    Wu, J., Joergensen, R. G., Pommerening, B., Chaussod, R. & Brookes, P. C. Measurement of soil microbial biomass by fumigation–extraction-an automated procedure. Soil Biol. Biochem.20, 1167–1169 (1990).
    Article  Google Scholar 

    23.
    Peiffer, J. A. et al. Diversity and heritability of the maize rhizosphere microbiome under field conditions. PNAS110, 6548–6553 (2013).
    ADS  CAS  Article  Google Scholar 

    24.
    Wang, Z. T., Liu, L., Chen, Q., Wen, X. X. & Liao, Y. C. Conservation tillage increases soil bacterial diversity in the dryland of northern China. Agron. Sustain. Dev.36, 28 (2016).
    Article  Google Scholar 

    25.
    Bazzicalupo, A. L., Bálint, M. & Schmitt, I. Comparison of ITS1 and ITS2 rDNA in 454 sequencing of hyper diverse fungal communities. Fungal Ecol.6, 102–109 (2013).
    Article  Google Scholar 

    26.
    Edgar, R. C. Search and clustering orders of magnitude faster than BLAST. Bioinformatics26, 2460–2461 (2010).
    CAS  Article  Google Scholar 

    27.
    SAS. SAS Software of the SAS System for Windows (SAS Institute Inc, Cary, 2008).
    Google Scholar 

    28.
    Blanco-Canqui, H., Ferguson, R. B., Shapiro, C. A., Drijber, R. A. & Walters, D. T. Does inorganic nitrogen fertilization improve soil aggregation? Insights from two long-term tillage experiments. J. Environ. Qual.43, 995–1003 (2014).
    Article  Google Scholar 

    29.
    Neumann, D., Heuer, A., Hemkemeyer, M., Martens, R. & Tebbe, C. C. Response of microbial communities to long-term fertilization depends on their microhabitat. FEMS Microbiol. Ecol.86, 71–84 (2013).
    CAS  Article  Google Scholar 

    30.
    Jenkins, S. N. et al. Taxon specific responses of soil bacteria to the addition of low level C inputs. Soil Biol. Biochem.42, 1624–1631 (2010).
    CAS  Article  Google Scholar 

    31.
    Li, H. et al. Soil bacterial communities of different natural forest types in northeast China. Plant Soil383, 203–216 (2014).
    CAS  Article  Google Scholar 

    32.
    Pascault, N. et al. Stimulation of different functional groups of bacteria by various plant residues as a driver of soil priming effect. Ecosystems16, 810–822 (2013).
    CAS  Article  Google Scholar 

    33.
    He, J. Z., Zheng, Y., Chen, C. R., He, Y. Q. & Zhang, L. M. Microbial composition and diversity of an upland red soil under long-term fertilization treatments as revealed by culture-dependent and culture-independent approaches. J. Soil. Sediment.8, 349–358 (2008).
    CAS  Article  Google Scholar 

    34.
    Paungfoo-lonhienne, C. et al. Nitrogen fertilizer dose alters fungal communities in sugarcane soil and rhizosphere. Sci. Rep.5, 8678 (2015).
    CAS  Article  Google Scholar 

    35.
    Huang, X. M. et al. Changes of soil microbial biomass carbon and community composition through mixing nitrogen-fixing species with Eucalyptus urophylla in subtropical China. Soil Biol. Biochem.73, 42–48 (2014).
    CAS  Article  Google Scholar 

    36.
    Desantis, T. Z. et al. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl. Environ. Microb.72, 5069–5072 (2006).
    CAS  Article  Google Scholar 

    37.
    Iovieno, P., Alfani, A. & Bååth, E. Soil microbial community structure and biomass as affected by Pinus pinea plantation in two mediterranean areas. Appl. Soil Ecol.45, 56–63 (2010).
    Article  Google Scholar  More

  • in

    Colony co-founding in ants is an active process by queens

    1.
    Bourke, A. F. G. & Heinze, J. The ecology of communal breeding: The case of multiple-queen Leptothoracine ants. Philos. Trans. R. Soc. Lond. B Biol. Sci.345, 359–372 (1994).
    ADS  Google Scholar 
    2.
    Bourke, A. F. G. Principles of Social Evolution. Oxford Series in Ecology and Evolution (2011).

    3.
    Cockburn, A. Evolution of helping behavior in cooperatively breeding birds. Annu. Rev. Ecol. Evol. Syst.29, 141–177 (1998).
    Google Scholar 

    4.
    Jennions, M. Cooperative breeding in mammals. Trends Ecol. Evol.9, 89–93 (1994).
    CAS  PubMed  Google Scholar 

    5.
    Lukas, D. & Clutton-Brock, T. Life histories and the evolution of cooperative breeding in mammals. Proc. R. Soc. B279, 4065–4070 (2012).
    PubMed  Google Scholar 

    6.
    Purcell, J. Geographic patterns in the distribution of social systems in terrestrial arthropods. Biol. Rev.86, 475–491 (2011).
    PubMed  Google Scholar 

    7.
    Wong, M. & Balshine, S. The evolution of cooperative breeding in the African cichlid fish, Neolamprologus pulcher. Biol. Rev.86, 511–530 (2011).
    PubMed  Google Scholar 

    8.
    Dugatkin, L. Animal cooperation among unrelated individuals. Naturwissenschaften89, 533–541 (2002).
    ADS  CAS  PubMed  Google Scholar 

    9.
    Emlen, S. The evolution of helping. An ecological constraints model. Am. Nat.119, 29–39 (1982).
    Google Scholar 

    10.
    Nichols, H. J. et al. Food availability shapes patterns of helping effort in a cooperative mongoose. Anim. Behav.83, 1377–1385 (2012).
    Google Scholar 

    11.
    Riehl, C. & Strong, M. J. Stable social relationships between unrelated females increase individual fitness in a cooperative bird. Proc. R. Soc. B285, 20180130 (2018).
    PubMed  Google Scholar 

    12.
    Sharp, S. P., English, S. & Clutton-Brock, T. H. Maternal investment during pregnancy in wild meerkats. Evol. Ecol.27, 1033–1044 (2012).
    Google Scholar 

    13.
    Taborsky, M. Broodcare helpers in the cichlid fish Lamprologus brichardi: Their costs and benefits. Anim. Behav.32, 1236–1252 (1984).
    Google Scholar 

    14.
    Hamilton, W. D. The genetical evolution of social behaviour. J. Theor. Biol.7, 1–52 (1964).
    CAS  PubMed  Google Scholar 

    15.
    Bshary, R. Cooperation between unrelated individuals—a game theoretic approach. In Animal Behaviour: Evolution and Mechanisms (ed. Kappeler, P.) 213–240 (Springer, Berlin, 2010).
    Google Scholar 

    16.
    Dugatkin, L. A. & Mesterton-Gibbons, M. Cooperation among unrelated individuals: Reciprocal altruism, by-product mutualism and group selection in fishes. Biosystems37, 19–30 (1996).
    CAS  PubMed  Google Scholar 

    17.
    Keller, L. Queen Number and Sociality in Insects (Oxford University Press, Oxford, 1993).
    Google Scholar 

    18.
    Matsuura, K., Fujimoto, M., Goka, K. & Nishida, T. Cooperative colony foundation by termite female pairs: Altruism for survivorship in incipient colonies. Anim. Behav.64, 167–173 (2002).
    Google Scholar 

    19.
    Mesterton-Gibbons, M. & Dugatkin, L. A. Cooperation among unrelated individuals: Evolutionary factors. Q. Rev. Biol.67, 267–281 (1992).
    Google Scholar 

    20.
    Bernasconi, G. & Strassmann, J. E. Cooperation among unrelated individuals: The ant foundress case. Trends Ecol. Evol.14, 477–482 (1999).
    CAS  PubMed  Google Scholar 

    21.
    Itô, Y. Behaviour and Social Evolution of Wasps (Oxford University Press, Oxford, 1993).
    Google Scholar 

    22.
    Packer, L. Multiple-foundress associations in sweat bees. In Queen Number and Sociality in Insects (ed. Keller, L.) 215–233 (Oxford University Press, Oxford, 1993).
    Google Scholar 

    23.
    Schwarz, M. P., Bull, N. J. & Hogendoorn, K. Evolution of sociality in the allodapine bees: A review of sex allocation, ecology and evolution. Insectes Soc.45, 349–368 (1998).
    Google Scholar 

    24.
    Shellman-Reeve, J. S. The spectrum of eusociality in termites. In The Evolution of Social Behavior in Insects and Arachnids (eds Choe, J. C. & Crespi, B. J.) 52–93 (Cambridge University Press, Cambridge, 1997).
    Google Scholar 

    25.
    Thorne, B. L. Evolution of eusociality in termites. Annu. Rev. Ecol. Evol. Syst.28, 27–54 (1997).
    Google Scholar 

    26.
    Hölldobler, B. & Wilson, E. O. The Ants (Springer, Berlin, 1990).
    Google Scholar 

    27.
    Schmid-Hempel, P. Parasites in Social Insects (Princeton University Press, Princeton, 1998).
    Google Scholar 

    28.
    Tschinkel, W. R. The Fire Ants (Harvard University Press, Cambridge, 2006).
    Google Scholar 

    29.
    Cole, B. J. The ecological setting of social evolution. In Organization of Insect Societies (eds Gadau, J. & Fewell, J.) 74–104 (Harvard University Press, Cambridge, 2009).
    Google Scholar 

    30.
    Johnson, R. A. Colony founding by pleometrosis in the semi-claustral seed-harvester ant Pogonomyrmex calfornicus (Hymenoptera: Formicidae). Anim. Behav.68, 1189–1200 (2004).
    Google Scholar 

    31.
    Tschinkel, W. R. An experimental study of pleometrotic colony founding in the fire ant, Solenopsis invicta: What is the basis for association?. Behav. Ecol. Sociobiol.43, 247–257 (1998).
    Google Scholar 

    32.
    Jerome, C. A., McInnes, D. A. & Adams, E. S. Group defense by colony-founding queens in the fire ant Solenopsis invicta. Behav. Ecol.9, 301–308 (1998).
    Google Scholar 

    33.
    Helms Cahan, S. & Julian, G. E. Fitness consequences of cooperative colony founding in the desert leaf-cutter ant Acromyrmex versicolor. Behav. Ecol.10, 585–591 (1999).
    Google Scholar 

    34.
    Adams, E. S. & Tschinkel, W. R. Effects of foundress number on brood raids and queen survival in the fire ant Solenopsis invicta. Behav. Ecol. Sociobiol.37, 233–242 (1995).
    Google Scholar 

    35.
    Clark, R. M. & Fewell, J. H. Social dynamics drive selection in cooperative associations of ant queens. Behav. Ecol.25, 117–123 (2014).
    Google Scholar 

    36.
    Offenberg, J., Peng, R. & Nielsen, M. Development rate and brood production in haplo- and pleometrotic colonies of Oecophylla smaragdina. Insectes Soc.59, 307–311 (2012).
    Google Scholar 

    37.
    Rissing, S. W. & Pollock, G. B. An experimental analysis of pleometric advantage in the desert seed-harvester ant Messor pergandei (Hymenoptera; Formicidae). Insectes Soc.38, 205–211 (1991).
    Google Scholar 

    38.
    Sasaki, K., Jibiki, E., Satoh, T. & Obara, Y. Queen phenotype and behaviour during cooperative colony founding in Polyrhachis moesta. Insectes Soc.52, 19–25 (2005).
    Google Scholar 

    39.
    Waloff, N. The effect of the number of queens of the ant Lasius flavus (Fab.) (Hym. Formicidae) on their survival and on the rate of development of the first brood. Insectes Soc.4, 391–408 (1957).
    Google Scholar 

    40.
    Bartz, S. H. & Hölldobler, B. Colony founding in Myrmecocystus mimicus Wheeler (Hymenoptera, Formicidae) and the evolution of foundress associations. Behav. Ecol. Sociobiol10, 137–147 (1982).
    Google Scholar 

    41.
    Helms Cahan, S. Ecological variation across a transition in colony-founding behavior in the ant Messor pergandei. Oecologia129, 629–635 (2001).
    ADS  Google Scholar 

    42.
    Sommer, K. & Hölldobler, B. Colony founding by queen association and determinants of reduction in queen number in the ant Lasius niger. Anim. Behav.50, 287–294 (1995).
    Google Scholar 

    43.
    Tschinkel, W. R. & Howard, D. F. Colony founding by pleometrosis in the fire ant, Solenopsis invicta. Behav. Ecol. Sociobiol12, 103–113 (1983).
    Google Scholar 

    44.
    Herbers, J. M. Nest site limitation and facultative polygyny in the ant Leptothorax longispinosus. Behav. Ecol. Sociobiol19, 115–122 (1986).
    Google Scholar 

    45.
    Nonacs, P. Queen condition and alate density affect pleometrosis in the ant Lasius pallitarsis. Insectes Soc.39, 3–13 (1992).
    Google Scholar 

    46.
    Masoni, A. et al. Pleometrotic colony foundation in the ant Crematogaster scutellaris (Hymenoptera: Formicidae): Better be alone than in bad company. Myrmecol. News25, 51–59 (2016).
    Google Scholar 

    47.
    Sommer, K. & Hölldobler, B. Pleometrosis in Lasius niger. In Biology and Evolution of Social Insects (ed. Billen, J.) 47–50 (Leuven University Press, Leuven, 1992).
    Google Scholar 

    48.
    Pfennig, D. W. Absence of joint nesting advantage in desert seed harvester ants: Evidence from a field experiment. Anim. Behav.49, 567–575 (1995).
    Google Scholar 

    49.
    Tschinkel, W. R. Brood raiding and the population dynamics of founding and incipient colonies of the fire ant Solenopsis invicta. Ecol. Entomol.17, 179–188 (1992).
    Google Scholar 

    50.
    Helms Cahan, S. & Fewell, J. H. Division of labor and the evolution of task sharing in queen associations of the harvester ant Pogonomyrmex californicus. Behav. Ecol. Sociobiol.56, 9–17 (2004).
    Google Scholar 

    51.
    Helmkampf, M., Mikheyev, A. S., Kang, Y., Fewell, J. & Gadau, J. Gene expression and variation in social aggression by queens of the harvester ant Pogonomyrmex californicus. Mol. Ecol.25, 3716–3730 (2016).
    PubMed  Google Scholar 

    52.
    Overson, R. P., Gadau, J., Clark, R. M., Pratt, S. C. & Fewell, J. H. Behavioral transitions with the evolution of cooperative nest founding by harvester ant queens. Behav. Ecol. Sociobiol.68, 21–30 (2014).
    Google Scholar 

    53.
    Shaffer, Z. et al. The foundress’s dilemma: Group selection for cooperation among queens of the harvester ant, Pogonomyrmex californicus. Sci. Rep.6, 29828 (2016).
    ADS  CAS  PubMed  PubMed Central  Google Scholar 

    54.
    Aron, S., Steinhauer, N. & Fournier, D. Influence of queen phenotype, investment and maternity apportionment on the outcome of fights in cooperative foundations of the ant Lasius niger. Anim. Behav.77, 1067–1074 (2009).
    Google Scholar 

    55.
    Brütsch, T., Avril, A. & Chapuisat, M. No evidence for social immunity in co-founding queen associations. Sci. Rep.7, 16262 (2017).
    ADS  PubMed  PubMed Central  Google Scholar 

    56.
    Chérasse, S. & Aron, S. Measuring inotocin receptor gene expression in chronological order in ant queens. Horm. Behav.96, 116–121 (2017).
    PubMed  Google Scholar 

    57.
    Dreier, S. & d’Ettorre, P. Social context predicts recognition systems in ant queens. J. Evol. Biol.22, 644–649 (2009).
    CAS  PubMed  Google Scholar 

    58.
    Holman, L., Dreier, S. & d’Ettorre, P. Selfish strategies and honest signalling: Reproductive conflicts in ant queen associations. Proc. R. Soc. B277, 2007–2015 (2010).
    CAS  PubMed  Google Scholar 

    59.
    Pull, C. D. & Cremer, S. Co-founding ant queens prevent disease by performing prophylactic undertaking behaviour. BMC Evol. Biol.17, 219 (2017).
    PubMed  PubMed Central  Google Scholar 

    60.
    Pull, C. D., Hughes, W. H. O. & Brown, M. J. F. Tolerating an infection: An indirect benefit of co-founding queen associations in the ant Lasius niger. Naturwissenschaften100, 1125–1136 (2013).
    ADS  CAS  PubMed  Google Scholar 

    61.
    Bernasconi, G. & Keller, L. Phenotype and individual investment in cooperative foundress associations of the fire ant, Solenopsis invicta. Behav. Ecol9, 478–485 (1998).
    Google Scholar 

    62.
    Bernasconi, G. & Keller, L. Effect of queen phenotype and social environment on early queen mortality in incipient colonies of the fire ant, Solenopsis invicta. Anim. Behav.57, 371–377 (1999).
    CAS  PubMed  Google Scholar  More

  • in

    Sap flow of Amorpha fruticosa: implications of water use strategy in a semiarid system with secondary salinization

    1.
    Tian, F. Q., Hu, H. C., Zhang, Z. & Hu, H. P. Secondary salinization and evapotranspiration under mulched drip irrigation condition in Tarim River basin of northwestern China. EGU Gen. Assembly Conf. Abstr. 15, EGU2013–8341 (2013).
    2.
    Liu, T. et al. Differentially improved soil microenvironment and seedling growth of Amorpha fruticosa by plastic, sand and straw mulching in a saline wasteland in northwest China. Ecol. Eng.122, 126–134 (2018).
    Article  Google Scholar 

    3.
    Rewald, B., Rachmilevitch, S., McCue, M. D. & Ephrath, J. E. Influence of saline drip-irrigation on fine root and sap-flow densities of two mature olive varieties. Environ. Exp. Bot.72, 107–114 (2011).
    Article  Google Scholar 

    4.
    Wullshleger, S. D., Meinzer, F. C. & Vertessy, R. A. A review of whole-plant water use studies in tree. Tree Physiol.18, 499–512 (1998).
    Article  Google Scholar 

    5.
    Forster, M. A. How significant is nocturnal sap flow?. Tree Physiol.34, 757–765 (2014).
    Article  Google Scholar 

    6.
    Chu, C. R., Hsieh, C. I., Wu, S. Y. & Phillips, N. G. Transient response of sap flow to wind speed. J. Exp. Bot.60, 249–255 (2009).
    CAS  Article  Google Scholar 

    7.
    Ma, C. K. et al. Environmental controls on sap flow in black locust forest in Loess Plateau, China. Sci. Rep.7, 13160 (2017).
    ADS  Article  Google Scholar 

    8.
    Zhao, C. Y., Si, J. H., Feng, Q., Yu, T. F. & Li, P. D. Comparative study of daytime and nighttime sap flow of Populus euphratica. J. Plant Growth Regul.82, 1–10 (2017).
    ADS  Article  Google Scholar 

    9.
    Zhang, Q. Y. et al. Sap flow of black locust in response to short-term drought in southern Loess Plateau of China. Sci. Rep.8, 6222 (2018).
    ADS  Article  Google Scholar 

    10.
    Rosado, B. H. P., Oliveira, R. S., Joly, C. A., Aidar, M. P. M. & Burgess, S. S. O. Diversity in nighttime transpiration behavior of woody species of the Atlantic Rain Forest, Brazil. Agric. For. Meteorol.159, 13–20 (2012).
    ADS  Article  Google Scholar 

    11.
    Doronila, A. I. & Forster, M. A. Performance measurement via sap flow monitoring of three eucalyptus species for mine site and dryland salinity phytoremediation. Int. J. Phytoremediat.17, 101–108 (2015).
    CAS  Article  Google Scholar 

    12.
    Fang, W. W., Lu, N., Zhang, Y., Jiao, L. & Fu, B. J. Responses of nighttime sap flow to atmospheric and soil dryness and its potential roles for shrubs on the Loess Plateau of China. J. Plant Ecol.11, 717–729 (2018).
    Article  Google Scholar 

    13.
    Daley, M. J. & Phillips, N. G. Interspecific variation in nighttime transpiration and stomatal conductance in a mixed New England deciduous forest. Tree Physiol.26, 411–419 (2006).
    Article  Google Scholar 

    14.
    Phillips, N. G., Lewis, J. D., Logan, B. A. & Tissue, D. T. Inter- and intra-specific variation in nocturnal water transport in Eucalyptus. Tree Physiol.30, 586–596 (2010).
    Article  Google Scholar 

    15.
    Caspari, H. W., Green, S. R. & Edwards, W. R. N. Transpiration of well-watered and water-stressed Asian pear trees as determined by lysimetry, heat-pulse, and estimated by a Penman-Monteith model. Agric. For. Meteorol.67, 13–27 (1993).
    ADS  Article  Google Scholar 

    16.
    Pfautsch, S. & Adams, M. A. Water flux of Eucalyptus regnans: Defying summer drought and a record heatwave in 2009. Oecologia172, 317–326 (2013).
    ADS  Article  Google Scholar 

    17.
    Chang, X. X., Zhao, W. Z. & He, Z. B. Radial pattern of sap flow and response to microclimate and soil moisture in Qinghai spruce (Picea crassifolia) in the upper Heihe River Basin of arid northwestern China. Agric. For. Meteorol.187, 14–21 (2014).
    ADS  Article  Google Scholar 

    18.
    Wang, Y. N. et al. Response of the daily transpiration of a larch plantation to variation in potential evaporation, leaf area index and soil moisture. Sci. Rep.9, 4697 (2019).
    ADS  Article  Google Scholar 

    19.
    Prieto, I., Kikvidze, Z. & Pugnaire, F. I. Hydraulic lift: soil processes and transpiration in the Mediterranean leguminous shrub Retama sphaerocarpa (L.) Boiss. Plant Soil329, 447–456 (2010).

    20.
    Shen, Q., Gao, G. Y., Fu, B. J. & Lü, Y. H. Sap flow and water use sources of shelter-belt trees in an arid inland river basin of Northwest China. Ecohydrology8, 1446–1458 (2014).
    Article  Google Scholar 

    21.
    Carter, J. L., Veneklaas, E. J., Colmer, T. D., Eastham, J. & Hatton, T. J. Contrasting water relations of three coastal tree species with different exposure to salinity. Physiol. Plantarum.127, 360–373 (2006).
    CAS  Article  Google Scholar 

    22.
    Ma, J. X., Huang, X., Li, W. H. & Zhu, C. G. Sap flow and trunk maximum daily shrinkage (MDS) measurements for diagnosing water status of Populus euphratica in an inland river basin of Northwest China. Ecohydrology6, 994–1000 (2013).
    CAS  Article  Google Scholar 

    23.
    Zhao, W. Z. & Liu, B. The response of sap flow in shrubs to rainfall pulses in the desert region of China. Agric. For. Meteorol.150, 1297–1306 (2010).
    ADS  Article  Google Scholar 

    24.
    Berbigier, P. et al. Transpiration of a 64-year-old maritime pine stand in Portugal. Oecologia107, 33–42 (1996).
    ADS  Article  Google Scholar 

    25.
    Chen, D. Y., Wang, Y. K., Liu, S. Y., Wei, X. G. & Wang, X. Response of relative sap flow to meteorological factors under different soil moisture conditions in rainfed jujube (Ziziphus jujuba Mil) plantations in semiarid Northwest China. Agric. Water. Manag.136, 23–33 (2014).
    Article  Google Scholar 

    26.
    Shen, Q., Gao, G. Y., Fu, B. J. & Lü, Y. H. Responses of shelterbelt stand transpiration to drought and groundwater variations in an arid inland river basin of Northwest China. J. Hydrol.531, 738–748 (2015).
    ADS  Article  Google Scholar 

    27.
    Sperry, J. S., Alder, N. N. & Eastlack, S. E. The effect of reduced hydraulic conductance on stomatal conductance and xylem cavitation. J. Exp. Bot.44, 1075–1082 (1993).
    Article  Google Scholar 

    28.
    Barbeta, A., Ogaya, R. & Peñuelas, J. Comparative study of diurnal and nocturnal sap flow of Quercus ilex and Phillyrea latifolia in a Mediterranean holm oak forest in Prades (Catalonia, NE Spain). Trees26, 1651–1659 (2013).
    Article  Google Scholar 

    29.
    Knapp, A. K. & Yavitt, J. B. Gas exchange characteristics of Typha latifolia L. from nine sites across North America. Aquat. Bot.49, 203–215 (1995).

    30.
    Wood, S. A. et al. Retraction notice to impacts of fire on forest age and runoff in mountain ash forests. Funct. Plant Biol.35, 483–492 (2008).
    Article  Google Scholar 

    31.
    Pfautsch, S. et al. Diurnal patterns of water use in Eucalyptus victrix indicate pronounced desiccation-rehydration cycles despite unlimited water supply. Tree Physiol.31, 1041–1051 (2011).
    Article  Google Scholar 

    32.
    Wang, Y. B. et al. The characteristics of nocturnal sap flow and stem water recharge pattern in growing season for a Larix principis-rupprechtii plantation. Acta Ecol. Sin.33, 1375–1385 (2013) ((in Chinese with English Abstract)).
    CAS  Article  Google Scholar 

    33.
    Campbell, G. S. & Norman, J. M. An Introduction to Environmental Biophysics. (Springer, New York, 1998). ISBN 978-0-387-94937-6.

    34.
    Granier, A. Evaluation of transpiration in a Douglas-fir stand by means of sap flow measurements. Tree Physiol.3, 309–320 (1987).
    CAS  Article  Google Scholar 

    35.
    Tie, Q., Hu, H. C., Tian, F. Q., Guan, H. D. & Lin, H. Environmental and physiological controls on sap flow in a subhumid mountainous catchment in north China. Agric. For. Meteorol.240–241, 46–57 (2017).
    ADS  Article  Google Scholar 

    36.
    R Core Team. R: A Language and Environment for Statistical Computing. (R Foundation for Statistical Computing, Vienna, 2016). https://www.R-project.org. More

  • in

    Neonicotinoids and decline in bird biodiversity in the United States

    1.
    Brennan, L. A. & Kuvlesky, W. P. North American grassland birds: an unfolding conservation crisis? J. Wildl. Manage. 69, 1–13 (2005).
    Google Scholar 
    2.
    Rice, J. et al. (eds) Summary for Policymakers of the Regional Assessment Report on Biodiversity and Ecosystem Services for the Americas of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES Secretariat, 2018).

    3.
    Rosenberg, K. V. et al. Decline of the North American avifauna. Science 366, 120–124 (2019).
    CAS  Google Scholar 

    4.
    Sauer, J. R., Link, W. A., Fallon, J. E., Pardieck, K. L. & Ziolkowski, D. J. The North American breeding bird survey 1966–2011: summary analysis and species accounts. N. Am. Fauna 79, 1–32 (2013).
    Google Scholar 

    5.
    DiBartolomeis, M., Kegley, S., Mineau, P., Radford, R. & Klein, K. An assessment of acute insecticide toxicity loading (AITL) of chemical pesticides used on agricultural land in the United States. PLoS ONE 14, e0220029 (2019).
    CAS  Google Scholar 

    6.
    Riffell, S., Scognamillo, D. & Burger, L. W. Effects of the conservation reserve program on northern bobwhite and grassland birds. Environ. Monit. Assess. 146, 309–323 (2008).
    Google Scholar 

    7.
    Ay, J. S., Chakir, R., Doyen, L., Jiguet, F. & Leadley, P. Integrated models, scenarios and dynamics of climate, land use and common birds. Clim. Change 126, 13–30 (2014).
    CAS  Google Scholar 

    8.
    Forister, M. L. et al. Increasing neonicotinoid use and the declining butterfly fauna of lowland California. Biol. Lett. 12, 20160475 (2016).
    Google Scholar 

    9.
    Hurley, T. & Mitchell, P. Value of neonicotinoid seed treatments to US soybean farmers. Pest Manage. Sci. 73, 102–112 (2017).
    CAS  Google Scholar 

    10.
    Whitehorn, P. R., O’Connor, S., Wackers, F. L. & Goulson, D. Neonicotinoid pesticide reduces bumble bee colony growth and queen production. Science 336, 351–352 (2012).
    CAS  Google Scholar 

    11.
    Rundlöf, M. et al. Seed coating with a neonicotinoid insecticide negatively affects wild bees. Nature 521, 77–80 (2015).
    Google Scholar 

    12.
    Woodcock, B. A. et al. Country-specific effects of neonicotinoid pesticides on honey bees and wild bees. Science 356, 1393–1395 (2017).
    CAS  Google Scholar 

    13.
    Tsvetkov, N. et al. Chronic exposure to neonicotinoids reduces honey bee health near corn crops. Science 356, 1395–1397 (2017).
    CAS  Google Scholar 

    14.
    Gilburn, A. S. et al. Are neonicotinoid insecticides driving declines of widespread butterflies? PeerJ 3, e1402 (2015).
    Google Scholar 

    15.
    Morrissey, C. A. et al. Neonicotinoid contamination of global surface waters and associated risk to aquatic invertebrates: a review. Environ. Int. 74, 291–303 (2015).
    CAS  Google Scholar 

    16.
    Van Dijk, T. C., Van Staalduinen, M. A. & Van der Sluijs, J. P. Macro-invertebrate decline in surface water polluted with imidacloprid. PLoS ONE 8, e62374 (2013).
    Google Scholar 

    17.
    Mineau, P. & Palmer, C. The Impact of the Nation’s Most Widely Used Insecticides on Birds (American Bird Conservancy, 2013).

    18.
    Cimino, A. M., Boyles, A. L., Thayer, K. A. & Perry, M. J. Effects of neonicotinoid pesticide exposure on human health: a systematic review. Environ. Health Perspect. 125, 155–162 (2016).
    Google Scholar 

    19.
    Hallmann, C. A., Foppen, R. P. B., Van Turnhout, C. A. M., De Kroon, H. & Jongejans, E. Declines in insectivorous birds are associated with high neonicotinoid concentrations. Nature 511, 341–343 (2014).
    CAS  Google Scholar 

    20.
    EFED Section 3 Registration for a Clothianidin and Beta-Cyfluthrin Combination Product for Use on Sugar Beets as a Seed Treatment (USEPA, 2007); https://go.nature.com/32DaXPU

    21.
    Eng, M. L., Stutchbury, B. J. M. & Morrissey, C. A. Imidacloprid and chlorpyrifos insecticides impair migratory ability in a seed-eating songbird. Sci. Rep. 7, 15176 (2017).
    Google Scholar 

    22.
    Eng, M. L., Stutchbury, B. J. M. & Morrissey, C. A. A neonicotinoid insecticide reduces fueling and delays migration in songbirds. Science 365, 1177–1180 (2019).
    CAS  Google Scholar 

    23.
    Pandey, S. P. & Mohanty, B. The neonicotinoid pesticide imidacloprid and the dithiocarbamate fungicide mancozeb disrupt the pituitary–thyroid axis of a wildlife bird. Chemosphere 122, 227–234 (2015).
    CAS  Google Scholar 

    24.
    Hill, A. B. The environment and disease: association or causation? Proc. R. Soc. Med. 58, 295–300 (1965).
    CAS  Google Scholar 

    25.
    Meehan, T. D., Hurlbert, A. H. & Gratton, C. Bird communities in future bioenergy landscapes of the upper Midwest. Proc. Natl Acad. Sci. USA 107, 18533–18538 (2010).
    CAS  Google Scholar 

    26.
    Evans, S. G. & Potts, M. D. Effect of agricultural commodity prices on species abundance of US grassland birds. Environ. Resour. Econ. 62, 549–565 (2015).
    Google Scholar 

    27.
    Illán, J. G. et al. Precipitation and winter temperature predict long-term range-scale abundance changes in western North American birds. Glob. Change Biol. 20, 3351–3364 (2014).
    Google Scholar 

    28.
    Davey, C. M., Chamberlain, D. E., Newson, S. E., Noble, D. G. & Johnston, A. Rise of the generalists: evidence for climate driven homogenization in avian communities. Glob. Ecol. Biogeogr. 21, 568–578 (2012).
    Google Scholar 

    29.
    National Water-Quality Assessment Project—Pesticide National Synthesis Project (USGS, 2018); https://water.usgs.gov/nawqa/pnsp/usage/maps/county-level/

    30.
    Conley, T. G. GMM estimation with cross-sectional dependence. J. Econ. 92, 1–45 (1999).
    Google Scholar 

    31.
    Baker, N. T. & Wesley, W. S. Estimated Annual Agricultural Pesticide Use for Counties of the Conterminous United States, 2008–12 (US Department of the Interior, USGS, 2014).

    32.
    Zeileis, A., Kleiber, C. & Jackman, S. Regression models for count data in R. J. Stat. Softw. 27, 1–25 (2008).
    Google Scholar 

    33.
    Arellano, M. & Bond, S. Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Rev. Econ. Stud. 58, 277–297 (1991).
    Google Scholar 

    34.
    Cresswell, J. E. A meta-analysis of experiments testing the effects of a neonicotinoid insecticide (imidacloprid) on honey bees. Ecotoxicology 20, 149–157 (2011).
    CAS  Google Scholar 

    35.
    Heller, M. Bill aims to ban pesticides harmful to bees. E&E News (21 February 2019); https://www.eenews.net/eenewspm/2019/02/21/stories/1060121799

    36.
    Zeng, G., Chen, M. & Zeng, Z. Risks of neonicotinoid pesticides. Science 340, 1403 (2013).
    CAS  Google Scholar 

    37.
    Grassland Birds (USDA-NRCS, Wildlife Habitat Council, 1999); ftp://ftp-fc.sc.egov.usda.gov/WHMI/WEB/pdf/GRASS1.pdf

    38.
    Hladik, M. L. & Kolpin, D. W. First national-scale reconnaissance of neonicotinoid insecticides in streams across the USA. Environ. Chem. 13, 12–20 (2016).
    CAS  Google Scholar 

    39.
    Loss, S. R., Will, T. & Marra, P. P. Direct mortality of birds from anthropogenic causes. Annu. Rev. Ecol. Evol. Syst. 46, 99–120 (2015).
    Google Scholar 

    40.
    Böcker, T. G. & Finger, R. A meta-analysis on the elasticity of demand for pesticides. J. Agric. Econ. 68, 518–533 (2017).
    Google Scholar 

    41.
    Fernandez-Cornejo, J. & Jans, S. Pest Management in US Agriculture Report No. 717 (USDA ERS, 1999).

    42.
    Commodity Costs and Returns (USDA ERS, 2018); https://www.ers.usda.gov/data-products/commodity-costs-and-returns/

    43.
    Li, Y., Miao, R. & Khanna, M. Effects of ethanol plant proximity and crop prices on land-use change in the United States. Am. J. Agric. Econ. 101, 467–491 (2019).
    Google Scholar 

    44.
    Wang, T. et al. Determinants of motives for land use decisions at the margins of the Corn Belt. Ecol. Econ. 134, 227–237 (2017).
    Google Scholar 

    45.
    Chamberlain, D. E., Fuller, R. J., Bunce, R. G. H., Duckworth, J. C. & Shrubb, M. Changes in the abundance of farmland birds in relation to the timing of agricultural intensification in England and Wales. J. Appl. Ecol. 37, 771–788 (2000).
    Google Scholar 

    46.
    Atkinson, P. W., Buckingham, D. & Morris, A. J. What factors determine where invertebrate-feeding birds forage in dry agricultural grasslands? Ibis 146, 99–107 (2004).
    Google Scholar 

    47.
    Kovács-Hostyánszki, A., Batáry, P., Peach, W. J. & Báldi, A. Effects of fertilizer application on summer usage of cereal fields by farmland birds in central Hungary. Bird Study 58, 330–337 (2011).
    Google Scholar 

    48.
    Stock, J. H. & Yogo, M. in Identification and Inference for Econometric Models: Essays in Honor of Thomas J. Rothenberg (eds Stock, J. H. & Andrews, D. W. K.) 80–108 (Cambridge Univ. Press, 2005).

    49.
    Windmeijer, F. Moment conditions for fixed effects count data models with endogenous regressors. Econ. Lett. 68, 21–24 (2000).
    Google Scholar 

    50.
    Allison, P. D. & Waterman, R. P. Fixed-effects negative binomial regression models. Sociol. Methodol. 32, 247–265 (2002).
    Google Scholar 

    51.
    Guimarães, P. The fixed effects negative binomial model revisited. Econ. Lett. 99, 63–66 (2008).
    Google Scholar 

    52.
    North American Breeding Bird Survey Dataset 1966–2018 (USGS Patuxent Wildlife Research Center, 2018); https://doi.org/10.5066/P9HE8XYJ

    53.
    Peterjohn, B. G. & Sauer, J. R. North American breeding bird survey annual summary 1990–1991. Bird Popul. 1, 52–67 (1993).
    Google Scholar 

    54.
    Smith, A. C., Anne, M., Hudson, R., Downes, C. M. & Francis, C. M. Change points in the population trends of aerial–insectivorous birds in North America: synchronized in time across species and regions. PLoS ONE 10, e013076 (2015).
    Google Scholar 

    55.
    Jost, L. Entropy and diversity. Oikos 113, 363–375 (2006).
    Google Scholar 

    56.
    Fishel, F. Pesticide Toxicity Profile: Neonicotinoid Pesticides (Univ. of Florida, IFAS, 2016); https://edis.ifas.ufl.edu/pi117

    57.
    Cropland Data Layer (USDA-NASS, 2020); http://nassgeodata.gmu.edu/CropScape/

    58.
    Parameter-Elevation Regression on Independent Slopes Model (PRISM) Climate Group (Oregon State Univ., 2018); http://prism.oregonstate.edu

    59.
    Population and Housing Unit Estimates Datasets (US Census Bureau, 2018); https://www.census.gov/programs-surveys/popest/data.html

    60.
    Fertilizer Use and Price (USDA ERS, 2018); https://www.ers.usda.gov/data-products/fertilizer-use-and-price/ More

  • in

    No net insect abundance and diversity declines across US Long Term Ecological Research sites

    1.
    Price, P. W., Denno, R. F., Eubanks, M. D., Finke, D. L. & Kaplan, I. Insect Ecology: Behavior, Populations and Communities (Cambridge Univ. Press, 2011).
    2.
    Watanabe, M. E. Pollination worries rise as honey bees decline. Science 265, 1170–1170 (1994).
    CAS  PubMed  Google Scholar 

    3.
    Soroye, P., Newbold, T. & Kerr, J. Climate change contributes to widespread declines among bumble bees across continents. Science 367, 685–688 (2020).
    CAS  PubMed  Google Scholar 

    4.
    Mathiasson, M. E. & Rehan, S. M. Status changes in the wild bees of north-eastern North America over 125 years revealed through museum specimens. Insect Conserv. Divers. 12, 278–288 (2019).
    Google Scholar 

    5.
    Powney, G. D. Widespread losses of pollinating insects in Britain. Nat. Commun. 10, 1018 (2019).
    PubMed  PubMed Central  Google Scholar 

    6.
    Fox, R. The decline of moths in Great Britain: a review of possible causes. Insect Conserv. Divers. 6, 5–19 (2013).
    Google Scholar 

    7.
    Casey, L. M., Rebelo, H., Rotheray, E. & Goulson, D. Evidence for habitat and climatic specializations driving the long-term distribution trends of UK and Irish bumblebees. Divers. Distrib. 21, 864–875 (2015).
    Google Scholar 

    8.
    Hallmann, C. A. et al. More than 75 percent decline over 27 years in total flying insect biomass in protected areas. PLoS ONE 12, e0185809 (2017).
    PubMed  PubMed Central  Google Scholar 

    9.
    Leather, S. R. “Ecological armageddon”–more evidence for the drastic decline in insect numbers. Ann. Appl. Biol. 172, 1–3 (2018).
    Google Scholar 

    10.
    Habel, J. C., Samways, M. J. & Schmitt, T. Mitigating the precipitous decline of terrestrial European insects: Requirements for a new strategy. Biodivers. Conserv. 28, 1343–1360 (2019).
    Google Scholar 

    11.
    Sánchez-Bayo, F. & Wyckhuys, K. A. G. Worldwide decline of the entomofauna: a review of its drivers. Biol. Conserv. 232, 8–27 (2019).
    Google Scholar 

    12.
    Seibold, S. et al. Arthropod decline in grasslands and forests is associated with drivers at landscape level. Nature 574, 671–674 (2019).
    CAS  PubMed  Google Scholar 

    13.
    Salcido, D. M., Forister, M. L., Garcia Lopez, H. & Dyer, L. A. Loss of dominant caterpillar genera in a protected tropical forest. Sci. Rep. 10, 422 (2020).
    CAS  PubMed  PubMed Central  Google Scholar 

    14.
    Wagner, D. L. Insect declines in the Anthropocene. Annu. Rev. Entomol. 65, 457–480 (2020).
    CAS  PubMed  Google Scholar 

    15.
    Wesner, J. S. et al. Loss of potential aquatic–terrestrial subsidies along the Missouri River floodplain. Ecosystems 23, 111–123 (2020).
    Google Scholar 

    16.
    Wepprich, T., Adrion, J. R., Ries, L., Wiedmann, J. & Haddad, N. M. Butterfly abundance declines over 20 years of systematic monitoring in Ohio, USA. PLoS ONE 14, e0216270 (2019).
    CAS  PubMed  PubMed Central  Google Scholar 

    17.
    Welti, E. A. R., Roeder, K. A., de Beurs, K. M., Joern, A. & Kaspari, M. Nutrient dilution and climate cycles underlie declines in a dominant insect herbivore. Proc. Natl Acad. Sci. USA 117, 7271–7275 (2020).
    CAS  PubMed  Google Scholar 

    18.
    Montgomery, G. A. et al. Is the insect apocalypse upon us? How to find out. Biol. Conserv. 241, 108327 (2020).
    Google Scholar 

    19.
    Saunders, M. E., Janes, J. K. & O’Hanlon, J. C. Moving on from the insect apocalypse narrative: engaging with evidence-based insect conservation. Bioscience 70, 80–89 (2020).
    Google Scholar 

    20.
    Thomas, C. D., Jones, T. H. & Hartley, S. E. “Insectageddon”: a call for more robust data and rigorous analyses. Glob. Change Biol. 25, 1891–1892 (2019).
    Google Scholar 

    21.
    Outhwaite, C. L., Gregory, R. D., Chandler, R. E., Collen, B. & Isaac, N. J. B. Complex long-term biodiversity change among invertebrates, bryophytes and lichens. Nat. Ecol. Evol. 4, 384–392 (2020).
    PubMed  Google Scholar 

    22.
    Macgregor, C. J., Williams, J. H., Bell, J. R. & Thomas, C. D. Moth biomass increases and decreases over 50 years in Britain. Nat. Ecol. Evol. 3, 1645–1649 (2019).
    PubMed  Google Scholar 

    23.
    Gonzalez, A. et al. Estimating local biodiversity change: a critique of papers claiming no net loss of local diversity. Ecology 97, 1949–1960 (2016).
    PubMed  Google Scholar 

    24.
    Vellend, M. et al. Estimates of local biodiversity change over time stand up to scrutiny. Ecology 98, 583–590 (2016).
    Google Scholar 

    25.
    van Klink, R. et al. Meta-analysis reveals declines in terrestrial but increases in freshwater insect abundances. Science 368, 417–420 (2020).
    CAS  PubMed  Google Scholar 

    26.
    Ellis, E. C. Anthropogenic transformation of the terrestrial biosphere. Phil. Trans. R. Soc. A 369, 1010–1035 (2011).
    PubMed  Google Scholar 

    27.
    Vitousek, P. M., Mooney, H. A., Lubchenco, J. & Melillo, J. M. Human domination of Earth’s ecosystems. Science 277, 494–499 (1997).
    CAS  Google Scholar 

    28.
    Kanakidou, M. et al. Past, present, and future atmospheric nitrogen deposition. J. Atmos. Sci. 73, 2039–2047 (2016).
    Google Scholar 

    29.
    Dornelas, M. et al. A balance of winners and losers in the Anthropocene. Ecol. Lett. 22, 847–854 (2019).
    PubMed  Google Scholar 

    30.
    Tylianakis, J. M., Tscharntke, T. & Lewis, O. T. Habitat modification alters the structure of tropical host–parasitoid food webs. Nature 445, 202–205 (2007).
    CAS  PubMed  Google Scholar 

    31.
    Finke, D. L. & Snyder, W. E. Niche partitioning increases resource exploitation by diverse communities. Science 321, 1488–1490 (2008).
    CAS  PubMed  Google Scholar 

    32.
    Crowder, D. W., Northfield, T. D., Strand, M. R. & Snyder, W. E. Organic agriculture promotes evenness and natural pest control. Nature 466, 109–112 (2010).
    CAS  PubMed  Google Scholar 

    33.
    Mack, R. N. et al. Biotic invasions: causes, epidemiology, global consequences, and control. Ecol. Appl. 10, 689–710 (2000).
    Google Scholar 

    34.
    Sikes, D. S. & Raithel, C. J. A review of hypotheses of decline of the endangered American burying beetle (Silphidae: Nicrophorus americanus Olivier). J. Insect Conserv. 6, 103–113 (2002).
    Google Scholar 

    35.
    Harmon, J. P., Stephens, E. & Losey, J. The decline of native coccinellids (Coleoptera: Coccinellidae) in the United States and Canada. J. Insect Conserv. 11, 85–94 (2007).
    Google Scholar 

    36.
    Agrawal, A. A. & Inamine, H. Mechanisms behind the monarch’s decline. Science 360, 1294–1296 (2018).
    CAS  PubMed  Google Scholar 

    37.
    Garibaldi, L. A. et al. Wild pollinators enhance fruit set of crops regardless of honey bee abundance. Science 340, 1608–1611 (2013).
    Google Scholar 

    38.
    Samson, F. & Knopf, F. Prairie conservation in North America. Bioscience 44, 418–421 (1994).
    Google Scholar 

    39.
    Ratajczak, Z. et al. Abrupt change in ecological systems: inference and diagnosis. Trends Ecol. Evol. 33, 513–526 (2018).
    PubMed  Google Scholar 

    40.
    Ives, A. R., Einarsson, Á., Jansen, V. A. A. & Gardarsson, A. High-amplitude fluctuations and alternative dynamical states of midges in Lake Myvatn. Nature 452, 84–87 (2008).
    CAS  PubMed  Google Scholar 

    41.
    Spatiotemporal Design (NEON, National Science Foundation – National Ecological Observatory Network, 2019); https://www.neonscience.org/about/about/spatiotemporal-design

    42.
    North American Butterfly Count Circles (NABA, North American Butterfly Association, 2019); https://www.naba.org/butter_counts.html

    43.
    Burkle, L. A., Marlin, J. C. & Knight, T. M. Plant–pollinator interactions over 120 years: loss of species, co-occurrence, and function. Science 340, 1611–1615 (2013).
    Google Scholar 

    44.
    Harvey, J. A. et al. International scientists formulate a roadmap for insect conservation and recovery. Nat. Ecol. Evol. 4, 174–176 (2020).
    PubMed  Google Scholar 

    45.
    Cardinale, B. J. et al. Biodiversity loss and its impact on humanity. Nature 486, 59–67 (2012).
    CAS  PubMed  Google Scholar 

    46.
    Vellend, M. et al. Global meta-analysis reveals no net change in local-scale plant biodiversity over time. Proc. Natl Acad. Sci. USA 110, 19456–19459 (2013).
    CAS  PubMed  Google Scholar 

    47.
    Dornelas, M. et al. Assemblage time series reveal biodiversity change but not systematic loss. Science 344, 296–299 (2014).
    CAS  Google Scholar 

    48.
    Newbold, T. et al. Global effects of land use on local terrestrial biodiversity. Nature 520, 45–50 (2015).
    CAS  PubMed  Google Scholar 

    49.
    Lagos-Kutz, D. et al. The soybean aphid suction trap network: sampling the aerobiological “soup”. Am. Entomol. 66, 48–55 (2020).
    Google Scholar 

    50.
    R Core Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2019).

    51.
    De Graaf, R. M., Tilghman, N. G. & Anderson, S. H. Foraging guilds of North American birds. Environ. Manag. 9, 493–536 (1985).
    Google Scholar 

    52.
    Ives, A. R., Abbott, K. C. & Ziebarth, N. L. Analysis of ecological time series with ARMA(p, q) models. Ecology 91, 858–871 (2010).
    PubMed  Google Scholar 

    53.
    Breiman, L. Random forests. Mach. Learn. 45, 5–32 (2001).
    Google Scholar 

    54.
    Fick, S. E. & Hijmans, R. J. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37, 4302–4315 (2017).
    Google Scholar 

    55.
    Venter, O. et al. Global terrestrial human footprint maps for 1993 and 2009. Sci. Data 3, 160067 (2016).
    PubMed  PubMed Central  Google Scholar 

    56.
    Halpern, B. S. et al. A global map of human impact on marine ecosystems. Science 319, 948–952 (2008).
    CAS  PubMed  Google Scholar 

    57.
    Cutler, D. R. et al. Random forests for classification in ecology. Ecology 88, 2783–2792 (2007).
    PubMed  Google Scholar 

    58.
    Oksanen, J. et al. vegan: Community Ecology Package. R package version 2.5-4 (2019).

    59.
    Jaccard, P. The distribution of the flora in the alpine zone. N. Phytol. 11, 37–50 (1912).
    Google Scholar 

    60.
    Harrison, S., Ross, S. J. & Lawton, J. H. Beta diversity on geographic gradients in Britain. J. Anim. Ecol. 61, 151–158 (1992).
    Google Scholar 

    61.
    Barwell, L. J., Isaac, N. J. B. & Kunin, W. E. Measuring β-diversity with species abundance data. J. Anim. Ecol. 84, 1112–1122 (2015).
    PubMed  PubMed Central  Google Scholar 

    62.
    Koleff, P., Gaston, K. J. & Lennon, J. J. Measuring beta diversity for presence–absence data. J. Anim. Ecol. 72, 367–382 (2003).
    Google Scholar  More

  • in

    Net benefits to US soy and maize yields from intensifying hourly rainfall

    1.
    Schlenker, W. & Roberts, M. J. Nonlinear temperature effects indicate severe damages to U.S. crop yields under climate change. Proc. Natl Acad. Sci. USA 106, 15594–15598 (2009).
    CAS  Article  Google Scholar 
    2.
    Vogel, E. et al. The effects of climate extremes on global agricultural yields. Environ. Res. Lett. 14, 054010 (2019).
    Article  Google Scholar 

    3.
    Lesk, C., Rowhani, P. & Ramankutty, N. Influence of extreme weather disasters on global crop production. Nature 529, 84–87 (2016).
    CAS  Article  Google Scholar 

    4.
    Troy, T. J., Kipgen, C. & Pal, I. The impact of climate extremes and irrigation on US crop yields. Environ. Res. Lett. 10, 054013 (2015).
    Article  Google Scholar 

    5.
    Lobell, D. B. et al. The critical role of extreme heat for maize production in the United States. Nat. Clim. Change 3, 497–501 (2013).
    Article  Google Scholar 

    6.
    van der Velde, M., Wriedt, G. & Bouraoui, F. Estimating irrigation use and effects on maize yield during the 2003 heatwave in France. Agric. Ecosyst. Environ. 135, 90–97 (2010).
    Article  Google Scholar 

    7.
    Rosenzweig, C., Tubiello, F. N., Goldberg, R., Mills, E. & Bloomfield, J. Increased crop damage in the US from excess precipitation under climate change. Glob. Environ. Change 12, 197–202 (2002).
    Article  Google Scholar 

    8.
    O’Gorman, P. & Schneider, T. The physical basis for increases in precipitation extremes in simulations of 21st-century climate change. Proc. Natl Acad. Sci. USA 106, 14773–14777 (2009).
    Article  Google Scholar 

    9.
    Westra, S. et al. Future changes to the intensity and frequency of short-duration extreme rainfall. Rev. Geophys. 52, 522–555 (2014).
    Article  Google Scholar 

    10.
    Zhu, X. & Troy, T. J. Agriculturally relevant climate extremes and their trends in the world’s major growing regions. Earth’s Future 6, 656–672 (2018).
    Article  Google Scholar 

    11.
    Ray, D. K., Gerber, J. S., Macdonald, G. K. & West, P. C. Climate variation explains a third of global crop yield variability. Nat. Commun. 6, 5989 (2015).
    CAS  Article  Google Scholar 

    12.
    Lobell, D. B. & Field, C. B. Global scale climate–crop yield relationships and the impacts of recent warming. Environ. Res. Lett. 2, 014002 (2007).
    Article  Google Scholar 

    13.
    Urban, D. W., Roberts, M. J., Schlenker, W. & Lobell, D. B. The effects of extremely wet planting conditions on maize and soybean yields. Clim. Change 130, 247–260 (2015).
    CAS  Article  Google Scholar 

    14.
    Li, Y., Guan, K., Schnitkey, G. D., Delucia, E. & Peng, B. Excessive rainfall leads to maize yield loss of a comparable magnitude to extreme drought in the United States. Glob. Change Biol. 25, 2325–2337 (2019).
    Google Scholar 

    15.
    Lobell, D. B. & Burke, M. B. Why are agricultural impacts of climate change so uncertain? The importance of temperature relative to precipitation. Environ. Res. Lett. 3, 034007 (2008).
    Article  Google Scholar 

    16.
    Lobell, D. B. & Gourdji, S. M. The influence of climate change on global crop productivity. Plant Physiol. 160, 1686–1697 (2012).
    CAS  Article  Google Scholar 

    17.
    Palecki, M. A., Angel, J. R. & Hollinger, S. E. Storm precipitation in the United States. Part I: meteorological characteristics. J. Appl. Meteorol. 44, 933–946 (2005).
    Article  Google Scholar 

    18.
    Thorp, J. M. & Scott, B. C. Preliminary calculations of average storm duration and seasonal precipitation rates for the northeast sector of the United States. Atmos. Environ. 16, 1763–1774 (1982).
    Article  Google Scholar 

    19.
    Zhang, W., Villarini, G., Scoccimarro, E. & Vecchi, G. A. Stronger influences of increased CO2 on subdaily precipitation extremes than at the daily scale. Geophys. Res. Lett. 44, 7454–7471 (2017).
    Google Scholar 

    20.
    Lepore, C., Allen, J. T. & Tippett, M. K. Relationships between hourly rainfall intensity and atmospheric variables over the contiguous United States. J. Clim. 29, 3181–3197 (2016).
    Article  Google Scholar 

    21.
    Ashraf, M. & Habib-ur-Rehman. Interactive effects of nitrate and long-term waterlogging on growth, water relations, and gaseous exchange properties of maize (Zea mays L.). Plant Sci. 144, 35–43 (1999).
    CAS  Article  Google Scholar 

    22.
    Martínez-Casasnovas, J. A., Ramos, M. C. & Ribes-Dasi, M. Soil erosion caused by extreme rainfall events: mapping and quantification in agricultural plots from very detailed digital elevation models. Geoderma 105, 125–140 (2002).
    Article  Google Scholar 

    23.
    Meisinger, J. J. & Delgado, J. A. Principles for managing nitrogen leaching. J. Soil Water Conserv. 57, 485–498 (2002).
    Google Scholar 

    24.
    Zahran, H. H. Rhizobium–legume symbiosis and nitrogen fixation under severe conditions and in an arid climate. Microbiol. Mol. Biol. Rev. 63, 968–989 (1999).
    CAS  Article  Google Scholar 

    25.
    Dastane, N. G. Effective Rainfall in Irrigated Agriculture Irrigation and Drainage Paper No. 25 (FAO, 1978).

    26.
    Van Elewijk, L. Stemflow on maize: a stemflow equation and the influence of rainfall intensity on stemflow amount. Soil Technol. 2, 41–48 (1989).
    Article  Google Scholar 

    27.
    Munkvold, G. P. Epidemiology of Fusarium diseases and their mycotoxins in maize ears. Eur. J. Plant Pathol. 109, 705–713 (2003).
    CAS  Article  Google Scholar 

    28.
    Harvell, C. D. et al. Climate warming and disease risks for terrestrial and marine biota. Science 296, 2158–2162 (2002).
    CAS  Article  Google Scholar 

    29.
    Lenderink, G. & Van Meijgaard, E. Increase in hourly precipitation extremes beyond expectations from temperature changes. Nat. Geosci. 1, 511–514 (2008).
    CAS  Article  Google Scholar 

    30.
    Berg, P., Moseley, C. & Haerter, J. O. Strong increase in convective precipitation in response to higher temperatures. Nat. Geosci. 6, 181–185 (2013).
    CAS  Article  Google Scholar 

    31.
    Prein, A. F. et al. The future intensification of hourly precipitation extremes. Nat. Clim. Change 7, 48–52 (2017).
    Article  Google Scholar 

    32.
    Chou, C., Chen, C. A., Tan, P. H. & Chen, K. T. Mechanisms for global warming impacts on precipitation frequency and intensity. J. Clim. 25, 3291–3306 (2012).
    Article  Google Scholar 

    33.
    Kendon, E. J. et al. Heavier summer downpours with climate change revealed by weather forecast resolution model. Nat. Clim. Change 4, 570–576 (2014).
    Article  Google Scholar 

    34.
    Zhao, C. et al. Temperature increase reduces global yields of major crops in four independent estimates. Proc. Natl Acad. Sci. USA 114, 9326–9331 (2017).
    CAS  Article  Google Scholar 

    35.
    de Bruyn, L. P. & de Jager, J. M. A meteorological approach to the identification of drought sensitive periods in field crops. Agric. Meteorol. 19, 35–40 (1978).
    Article  Google Scholar 

    36.
    Lin, Y. GCIP/EOP Surface: Precipitation NCEP/EMC 4KM Gridded Data (GRIB) Stage IV Data (UCAR/NCAR—Earth Obs. Lab., 2011); https://doi.org/10.5065/D6PG1QDD

    37.
    USDA Quickstats (USDA, 2018); http://quickstats.nass.usda.gov

    38.
    Thornton, P. E. et al. Daymet: Daily Surface Weather Data on a 1-km Grid for North America Version 2 (ORNL DAAC, 2016).

    39.
    Butler, E. E. & Huybers, P. Adaptation of US maize to temperature variations. Nat. Clim. Change 3, 68–72 (2013).
    Article  Google Scholar 

    40.
    Krajewski, W. F. & Smith, J. A. Radar hydrology: rainfall estimation. Adv. Water Resour. 25, 1387–1394 (2002).
    Article  Google Scholar 

    41.
    Karl, T., Nicholls, N. & Ghazi, A. Workshop on indices and indicators for climate extremes precipitation. Clim. Change 42, 3–7 (1999).
    Article  Google Scholar 

    42.
    Lau, W. K., Wu, H. & Kim, K. A canonical response of precipitation characteristics to global warming from CMIP5 models. Geophys. Res. Lett. 40, 3163–3169 (2013).
    Article  Google Scholar  More