More stories

  • in

    Fungi feed bacteria for biodegradation

    The pesticide hexachlorocyclohexane (HCH) is a toxic and persistent contaminant in the environment. Some bacteria and fungi can degrade HCH and its isomers under laboratory conditions. However, in heterogeneous environments, where many different factors are at play, the biodegradation capacity is challenged by the availability of nutrients to support degraders’ growth. As opposed to bacteria, fungi are more adapted to heterogeneous habitats, and in some cases mycelial fungi can facilitate the transport of organic substrates throughout the mycosphere, increasing their availability to promote bacterial contaminant biodegradation. However, how this occurs is not entirely understood. In this study, Khan et al. demonstrate that mycelial nutrients transferred from nutrient-rich to nutrient-deprived habitats promote co-metabolic degradation of HCH by bacteria. The authors incubated a non-HCH-degrading fungus (Fusarium equiseti K3) and a co-metabolically HCH-degrading bacterium (Sphingobium sp. S8) in a structured model ecosystem. Results from 13C isotope labelling and metaproteomics showed that fungal 13C was incorporated into bacterial proteins responsible for HCH degradation, thus illustrating the importance of synergistic fungal–bacterial interactions for contaminant biodegradation in nutrient-poor environments. More

  • in

    The degree of urbanisation reduces wild bee and butterfly diversity and alters the patterns of flower-visitation in urban dry grasslands

    Sánchez-Bayo, F. & Wyckhuys, K. A. Worldwide decline of the entomofauna: A review of its drivers. Biol. Conserv. 232, 8–27. https://doi.org/10.1016/j.biocon.2019.01.020 (2019).Article 

    Google Scholar 
    van Klink, R. et al. Meta-analysis reveals declines in terrestrial but increases in freshwater insect abundances. Science 368, 417–420. https://doi.org/10.1126/science.aax9931 (2020).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Wagner, D. L. Insect declines in the anthropocene. Annu. Rev. Entomol. 65, 457–480. https://doi.org/10.1146/annurev-ento-011019-025151 (2020).Article 
    CAS 
    PubMed 

    Google Scholar 
    Goulson, D. The insect apocalypse, and why it matters. Curr. Biol. 29, R967–R971. https://doi.org/10.1016/j.cub.2019.06.069 (2019).Article 
    CAS 
    PubMed 

    Google Scholar 
    Cardoso, P. et al. Scientists’ warning to humanity on insect extinctions. Biol. Conserv. 242, 108426. https://doi.org/10.1016/j.biocon.2020.108426 (2020).Article 

    Google Scholar 
    Potts, S. G. et al. Global pollinator declines: Trends, impacts and drivers. Trends Ecol. Evol. 25, 345–353. https://doi.org/10.1016/j.tree.2010.01.007 (2010).Article 
    PubMed 

    Google Scholar 
    Goulson, D., Nicholls, E., Botías, C. & Rotheray, E. L. Bee declines driven by combined stress from parasites, pesticides, and lack of flowers. Science 347, 1255957. https://doi.org/10.1126/science.1255957 (2015).Article 
    CAS 
    PubMed 

    Google Scholar 
    Ollerton, J. Pollinator diversity: Distribution, ecological function, and conservation. Annu. Rev. Ecol. Evol. Syst. 48, 353–376. https://doi.org/10.1146/annurev-ecolsys-110316-022919 (2017).Article 

    Google Scholar 
    Klein, A.-M. et al. Importance of pollinators in changing landscapes for world crops. Proc. Biol. Sci. 274, 303–313. https://doi.org/10.1098/rspb.2006.3721 (2007).Article 
    PubMed 

    Google Scholar 
    Ollerton, J., Winfree, R. & Tarrant, S. How many flowering plants are pollinated by animals?. Oikos 120, 321–326. https://doi.org/10.1111/j.1600-0706.2010.18644.x (2011).Article 

    Google Scholar 
    Ollerton, J., Erenler, H., Edwards, M. & Crockett, R. Pollinator declines. Extinctions of aculeate pollinators in Britain and the role of large-scale agricultural changes. Science 346, 1360–1362. https://doi.org/10.1126/science.1257259 (2014).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Wenzel, A., Grass, I., Belavadi, V. V. & Tscharntke, T. How urbanization is driving pollinator diversity and pollination—A systematic review. Biol. Conserv. 241, 108321. https://doi.org/10.1016/j.biocon.2019.108321 (2020).Article 

    Google Scholar 
    Senapathi, D., Goddard, M. A., Kunin, W. E. & Baldock, K. C. R. Landscape impacts on pollinator communities in temperate systems: Evidence and knowledge gaps. Funct. Ecol. 31, 26–37. https://doi.org/10.1111/1365-2435.12809 (2017).Article 

    Google Scholar 
    Fenoglio, M. S., Rossetti, M. R. & Videla, M. Negative effects of urbanization on terrestrial arthropod communities: A meta-analysis. Glob. Ecol. Biogeogr. 29, 1412–1429. https://doi.org/10.1111/geb.13107 (2020).Article 

    Google Scholar 
    Ives, C. D. et al. Cities are hotspots for threatened species. Glob. Ecol. Biogeogr. 25, 117–126. https://doi.org/10.1111/geb.12404 (2016).Article 

    Google Scholar 
    Soanes, K. & Lentini, P. E. When cities are the last chance for saving species. Front. Ecol. Evol. 17, 225–231. https://doi.org/10.1002/fee.2032 (2019).Article 

    Google Scholar 
    Lynch, L. et al. Changes in land use and land cover along an urban-rural gradient influence floral resource availability. Curr. Landsc. Ecol. Rep. 6, 46–70. https://doi.org/10.1007/s40823-021-00064-1 (2021).Article 

    Google Scholar 
    Hall, D. M. et al. The city as a refuge for insect pollinators. Conserv. Biol. 31, 24–29. https://doi.org/10.1111/cobi.12840 (2017).Article 
    PubMed 

    Google Scholar 
    Buchholz, S. & Egerer, M. H. Functional ecology of wild bees in cities: Towards a better understanding of trait-urbanization relationships. Biodivers. Conserv. 29, 2779–2801. https://doi.org/10.1007/s10531-020-02003-8 (2020).Article 

    Google Scholar 
    Theodorou, P. et al. Urban areas as hotspots for bees and pollination but not a panacea for all insects. Nat. Commun. 11, 576. https://doi.org/10.1038/s41467-020-14496-6 (2020).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Khalifa, S. A. M. et al. Overview of bee pollination and its economic value for crop production. Insects https://doi.org/10.3390/insects12080688 (2021).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Doyle, T. et al. Pollination by hoverflies in the Anthropocene. Proc. Biol. Sci. 287, 20200508. https://doi.org/10.1098/rspb.2020.0508 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Rader, R. et al. Non-bee insects are important contributors to global crop pollination. Proc. Natl. Acad. Sci. USA. 113, 146–151. https://doi.org/10.1073/pnas.1517092112 (2016).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Persson, A. S., Ekroos, J., Olsson, P. & Smith, H. G. Wild bees and hoverflies respond differently to urbanisation, human population density and urban form. Landsc. Urban Plan. 204, 103901. https://doi.org/10.1016/j.landurbplan.2020.103901 (2020).Article 

    Google Scholar 
    Gathof, A. K., Grossmann, A. J., Herrmann, J. & Buchholz, S. Who can pass the urban filter? A multi-taxon approach to disentangle pollinator trait-environmental relationships. Oecologia 199, 165–179. https://doi.org/10.1007/s00442-022-05174-z (2022).Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Baldock, K. C. R. et al. Where is the UK’s pollinator biodiversity? The importance of urban areas for flower-visiting insects. Proc. Biol. Sci. 282, 20142849. https://doi.org/10.1098/rspb.2014.2849 (2015).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ramírez-Restrepo, L. & MacGregor-Fors, I. Butterflies in the city: A review of urban diurnal Lepidoptera. Urban Ecosyst. 20, 171–182. https://doi.org/10.1007/s11252-016-0579-4 (2017).Article 

    Google Scholar 
    Kuussaari, M. et al. Butterfly species’ responses to urbanization: Differing effects of human population density and built-up area. Urban Ecosyst. 24, 515–527. https://doi.org/10.1007/s11252-020-01055-6 (2020).Article 

    Google Scholar 
    Theodorou, P. The effects of urbanisation on ecological interactions. Curr. Opin. Insect. Sci. 52, 100922. https://doi.org/10.1016/j.cois.2022.100922 (2022).Article 
    PubMed 

    Google Scholar 
    Martins, K. T., Gonzalez, A. & Lechowicz, M. J. Patterns of pollinator turnover and increasing diversity associated with urban habitats. Urban Ecosyst. 20, 1359–1371. https://doi.org/10.1007/s11252-017-0688-8 (2017).Article 

    Google Scholar 
    Theodorou, P. et al. The structure of flower visitor networks in relation to pollination across an agricultural to urban gradient. Funct. Ecol. 31, 838–847. https://doi.org/10.1111/1365-2435.12803 (2017).Article 

    Google Scholar 
    Geslin, B., Gauzens, B., Thébault, E. & Dajoz, I. Plant pollinator networks along a gradient of urbanisation. PLoS ONE 8, e63421. https://doi.org/10.1371/journal.pone.0063421 (2013).Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Udy, K. L., Reininghaus, H., Scherber, C. & Tscharntke, T. Plant–pollinator interactions along an urbanization gradient from cities and villages to farmland landscapes. Ecosphere https://doi.org/10.1002/ecs2.3020 (2020).Article 

    Google Scholar 
    Jędrzejewska-Szmek, K. & Zych, M. Flower-visitor and pollen transport networks in a large city: Structure and properties. Arthropod. Plant Interact. 7, 503–516. https://doi.org/10.1007/s11829-013-9274-z (2013).Article 

    Google Scholar 
    von der Lippe, M., Buchholz, S., Hiller, A., Seitz, B. & Kowarik, I. CityScapeLab Berlin: A research platform for untangling urbanization effects on biodiversity. Sustainability 12, 2565. https://doi.org/10.3390/su12062565 (2020).Article 

    Google Scholar 
    Dylewski, Ł, Maćkowiak, Ł & Banaszak-Cibicka, W. Are all urban green spaces a favourable habitat for pollinator communities? Bees, butterflies and hoverflies in different urban green areas. Ecol. Entomol. 44, 678–689. https://doi.org/10.1111/een.12744 (2019).Article 

    Google Scholar 
    Grossmann, A. J., Herrmann, J., Buchholz, S. & Gathof, A. K. Dry grassland within the urban matrix acts as favourable habitat for different pollinators including endangered species. Insect Conserv. Divers. https://doi.org/10.1111/icad.12607 (2022).Article 

    Google Scholar 
    Settele, J., Steiner, R., Feldmann, R. & Hermann, G. Schmetterlinge. Die Tagfalter Deutschlands: 720 Farbfotos. 3rd ed. (2015).Amiet, F. Hymenoptera Apidae, 1. Teil. Allgemeiner Teil, Gattungsschlüssel – Die Gattungen Apis, Bombus und Psithyrus (Centre Suisse de Cartographie de la Faune, 1996).
    Google Scholar 
    Amiet, F., Müller, A. & Neumeyer, R. Apidae 2. Colletes, Dufourea, Hylaeus, Nomia, Nomioides, Rhophitoides, Rophites, Sphecodes, Systropha (Fauna Helvetica, 1999).
    Google Scholar 
    Amiet, F., Herrmann, M., Müller, A. & Neumeyer, R. Apidae 3. Halictus, Lasioglossum (Centre Suisse de Cartographie de la Faune, 2001).
    Google Scholar 
    Amiet, F., Herrmann, M., Müller, A. & Neumeyer, R. Apidae 4. Anthidium, Chelostoma, Coelioxys, Dioxys, Heriades, Lithurgus, Megachile, Osmia, Stelis (Centre Suisse de Cartographie de la Faune, 2004).
    Google Scholar 
    Amiet, F., Herrmann, M., Müller, A. & Neumeyer, R. Apidae 5. Ammobates, Ammobatoides, Anthophora, Biastes, Ceratina, Dasypoda, Epeoloides, Epeolus, Eucera, Macropis, Melecta, Melitta, Nomada, Pasites, Tetralonia, Thyreus, Xylocopa (Centre Suisse de Cartographie de la Faune, 2007).
    Google Scholar 
    Amiet, F., Herrmann, M., Müller, A. & Neumeyer, R. Apidae 6. Andrena, Melliturga, Panurginus, Panurgus (Centre Suisse de Cartographie de la Faune, 2010).
    Google Scholar 
    Gokcezade, J. F., Gereben-Krenn, B.-A., Neumayer, J. & Krenn, H. W. Feldbestimmungsschlüssel für die Hummeln Österreichs, Deutschlands und der Schweiz (Hymenoptera, Apidae). Linzer biologische Beiträge 47, 5–42 (2015).
    Google Scholar 
    Bartsch, H. Tvåvingar: Blomflugor. Diptera: Syrphidae: Syrphinae: denna volym omfattar samtliga nordiska arter (ArtDatabanken Sveriges lantbruksuniversitet, 2009).
    Google Scholar 
    Bartsch, H. Tvåvingar: Blomflugor. Diptera: Syrphidae: Eristalinae & Microdontinae: denna volym omfattar samtliga nordiska arter (ArtDatabanken Sveriges lantbruksuniversitet, 2009).
    Google Scholar 
    Bot, S. & van de Meutter, F. Veldgids zweefvliegen (KNNV Uitgeverij, 2019).
    Google Scholar 
    Jäger, E. J. Rothmaler-Exkursionsflora von Deutschland. Gefäßpflanzen: Grundband 20th edn. (Springer Spektrum, 2011).
    Google Scholar 
    Senate Department for Urban Development and Housing. Berlin Environmental Atlas. 06.01 Actual Use of Built-up Areas/06.02 Inventory of Green and Open Spaces 2010 (2011).Holland, J. D., Bert, D. G. & Fahrig, L. Determining the spatial scale of species’ response to habitat. Bioscience 54, 227. https://doi.org/10.1641/0006-3568(2004)054[0227:DTSSOS]2.0.CO;2 (2004).Article 

    Google Scholar 
    Senate Department for Urban Development and Housing. Berlin Environmental Atlas. 05.08 Biotope Types (2014).Hanski, I. A practical model of metapopulation dynamics. J. Anim. Ecol. 63, 151. https://doi.org/10.2307/5591 (1994).Article 

    Google Scholar 
    Hanski, I. Habitat connectivity, habitat continuity, and metapopulations in dynamic landscapes. Oikos 87, 209. https://doi.org/10.2307/3546736 (1999).Article 

    Google Scholar 
    Senate Department for Urban Development and Housing. Berlin Environmental Atlas. 06.10 Building and Vegetation Heights (2014).Saura, S. & Torné, J. Conefor Sensinode 2.2: A software package for quantifying the importance of habitat patches for landscape connectivity. Environ. Model. Softw. 24, 135–139. https://doi.org/10.1016/j.envsoft.2008.05.005 (2009).Article 

    Google Scholar 
    Saure, C. Rote Liste und Gesamtartenliste der Bienen und Wespen (Hymenoptera part.) von Berlin mit Angaben zu den Ameisen. In Rote Listen der gefährdeten Pflanzen und Tiere von Berlin.Speight, M. C. D. Species Accounts of European Syrphidae (Diptera) (Syrph the Net Publications, 2014).
    Google Scholar 
    Middleton-Welling, J. et al. A new comprehensive trait database of European and Maghreb butterflies, Papilionoidea. Sci. Data 7, 351. https://doi.org/10.1038/s41597-020-00697-7 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Dormann, C. F., Fründ, J., Blüthgen, N. & Gruber, B. Indices, graphs and null models: Analyzing bipartite ecological networks. Open Ecol. J. 2, 7–24. https://doi.org/10.2174/1874213000902010007 (2009).Article 

    Google Scholar 
    Kaiser-Bunbury, C. N. & Blüthgen, N. Integrating network ecology with applied conservation: A synthesis and guide to implementation. AoB Plants https://doi.org/10.1093/aobpla/plv076 (2015).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Almeida-Neto, M., Guimarães, P., Guimarães, P. R., Loyola, R. D. & Ulrich, W. A consistent metric for nestedness analysis in ecological systems: Reconciling concept and measurement. Oikos 117, 1227–1239. https://doi.org/10.1111/J.0030-1299.2008.16644.X (2008).Article 

    Google Scholar 
    Dormann, C. F. & Strauss, R. A method for detecting modules in quantitative bipartite networks. Methods Ecol. Evol. 5, 90–98. https://doi.org/10.1111/2041-210X.12139 (2014).Article 

    Google Scholar 
    Blüthgen, N., Menzel, F. & Blüthgen, N. Measuring specialization in species interaction networks. BMC Ecol. 6, 9. https://doi.org/10.1186/1472-6785-6-9 (2006).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Patefield, W. M. Algorithm AS 159: An efficient method of generating random R × C tables with given row and column totals. J. Appl. Stat. 30, 91. https://doi.org/10.2307/2346669 (1981).Article 
    MATH 

    Google Scholar 
    Stein, K. et al. Plant–pollinator networks in Savannas of Burkina Faso, West Africa. Diversity 13, 1. https://doi.org/10.3390/d13010001 (2021).Article 
    ADS 

    Google Scholar 
    Escobedo-Kenefic, N. et al. Disentangling the effects of local resources, landscape heterogeneity and climatic seasonality on bee diversity and plant–pollinator networks in tropical highlands. Oecologia 194, 333–344. https://doi.org/10.1007/s00442-020-04715-8 (2020).Article 
    ADS 
    PubMed 

    Google Scholar 
    Renaud, E., Baudry, E. & Bessa-Gomes, C. Influence of taxonomic resolution on mutualistic network properties. Ecol. Evol. 10, 3248–3259. https://doi.org/10.1002/ece3.6060 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ropars, L., Dajoz, I., Fontaine, C., Muratet, A. & Geslin, B. Wild pollinator activity negatively related to honey bee colony densities in urban context. PLoS ONE 14, e0222316. https://doi.org/10.1371/journal.pone.0222316 (2019).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Egerer, M. & Kowarik, I. Confronting the modern gordian knot of urban beekeeping. Trends Ecol. Evol. 35, 956–959. https://doi.org/10.1016/j.tree.2020.07.012 (2020).Article 
    PubMed 

    Google Scholar 
    Zuur, A. F., Ieono, E. N., Walker, N., Saveliev, A. A. & Smith, G. M. Mixed Effects Models and Extensions in Ecology with R (Springer, 2009).Book 
    MATH 

    Google Scholar 
    Bartón, K. MuMIn. multi-model inference, R package version 1.42.1 (2018).Paradis, E., Claude, J. & Strimmer, K. APE: Analyses of phylogenetics and evolution in R language. Bioinformatics 20, 289–290. https://doi.org/10.1093/bioinformatics/btg412 (2004).Article 
    CAS 
    PubMed 

    Google Scholar 
    Wood, T. J., Kaplan, I. & Szendrei, Z. Wild bee pollen diets reveal patterns of seasonal foraging resources for honey bees. Front. Ecol. Evol. https://doi.org/10.3389/fevo.2018.00210 (2018).Article 

    Google Scholar 
    Proske, A., Lokatis, S. & Rolff, J. Impact of mowing frequency on arthropod abundance and diversity in urban habitats: A meta-analysis. Urban For Urban Green 76, 127714. https://doi.org/10.1016/j.ufug.2022.127714 (2022).Article 

    Google Scholar 
    Bates, A. J. et al. Changing bee and hoverfly pollinator assemblages along an urban-rural gradient. PLoS ONE 6, e23459. https://doi.org/10.1371/journal.pone.0023459 (2011).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Geslin, B. et al. The proportion of impervious surfaces at the landscape scale structures wild bee assemblages in a densely populated region. Ecol. Evol. 6, 6599–6615. https://doi.org/10.1002/ece3.2374 (2016).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Birdshire, K. R., Carper, A. L. & Briles, C. E. Bee community response to local and landscape factors along an urban-rural gradient. Urban Ecosyst. 23, 689–702. https://doi.org/10.1007/s11252-020-00956-w (2020).Article 

    Google Scholar 
    Goddard, M. A., Benton, T. G. & Dougill, A. J. Beyond the garden fence: Landscape ecology of cities. Trends Ecol. Evol. 25, 202–203. https://doi.org/10.1016/j.tree.2009.12.007 (2010).Article 

    Google Scholar 
    Theodorou, P. et al. Bumble bee colony health and performance vary widely across the urban ecosystem. J. Anim. Ecol. 91, 2135–2148. https://doi.org/10.1111/1365-2656.13797 (2022).Article 
    PubMed 

    Google Scholar 
    Potts, S. G., Vulliamy, B., Dafni, A., Ne’eman, G. & Willmer, P. Linking bees and flowers: How do floral communities structure pollinator communities?. Ecology 84, 2628–2642. https://doi.org/10.1890/02-0136 (2003).Article 

    Google Scholar 
    Ebeling, A., Klein, A.-M., Schumacher, J., Weisser, W. W. & Tscharntke, T. How does plant richness affect pollinator richness and temporal stability of flower visits?. Oikos 117, 1808–1815. https://doi.org/10.1111/j.1600-0706.2008.16819.x (2008).Article 

    Google Scholar 
    Theodorou, P. et al. Urban fragmentation leads to lower floral diversity, with knock-on impacts on bee biodiversity. Sci. Rep. 10, 21756. https://doi.org/10.1038/s41598-020-78736-x (2020).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Potts, S. G. et al. Role of nesting resources in organising diverse bee communities in a Mediterranean landscape. Ecol. Entomol. 30, 78–85. https://doi.org/10.1111/j.0307-6946.2005.00662.x (2005).Article 

    Google Scholar 
    Fründ, J., Linsenmair, K. E. & Blüthgen, N. Pollinator diversity and specialization in relation to flower diversity. Oikos 119, 1581–1590. https://doi.org/10.1111/j.1600-0706.2010.18450.x (2010).Article 

    Google Scholar 
    Fornoff, F. et al. Functional flower traits and their diversity drive pollinator visitation. Oikos 126, 1020–1030. https://doi.org/10.1111/oik.03869 (2017).Article 
    CAS 

    Google Scholar 
    Hofmann, M. M. & Renner, S. S. One-year-old flower strips already support a quarter of a city’s bee species. J. Hymenopt. Res. 75, 87–95. https://doi.org/10.3897/jhr.75.47507 (2020).Article 

    Google Scholar 
    Verboven, H. A., Uyttenbroeck, R., Brys, R. & Hermy, M. Different responses of bees and hoverflies to land use in an urban–rural gradient show the importance of the nature of the rural land use. Landsc. Urban Plan. 126, 31–41. https://doi.org/10.1016/j.landurbplan.2014.02.017 (2014).Article 

    Google Scholar 
    Luder, K., Knop, E. & Menz, M. H. M. Contrasting responses in community structure and phenology of migratory and non-migratory pollinators to urbanization. Divers. Distrib. 24, 919–927. https://doi.org/10.1111/ddi.12735 (2018).Article 

    Google Scholar 
    Merckx, T. & van Dyck, H. Urbanization-driven homogenization is more pronounced and happens at wider spatial scales in nocturnal and mobile flying insects. Glob. Ecol. Biogeogr. 28, 1440–1455. https://doi.org/10.1111/geb.12969 (2019).Article 

    Google Scholar 
    Tzortzakaki, O., Kati, V., Panitsa, M., Tzanatos, E. & Giokas, S. Butterfly diversity along the urbanization gradient in a densely-built Mediterranean city: Land cover is more decisive than resources in structuring communities. Landsc. Urban Plan. 183, 79–87. https://doi.org/10.1016/j.landurbplan.2018.11.007 (2019).Article 

    Google Scholar 
    Krauss, J., Steffan-Dewenter, I. & Tscharntke, T. How does landscape context contribute to effects of habitat fragmentation on diversity and population density of butterflies?. J. Biogeogr. 30, 889–900. https://doi.org/10.1046/j.1365-2699.2003.00878.x (2003).Article 

    Google Scholar 
    Cozzi, G., Müller, C. B. & Krauss, J. How do local habitat management and landscape structure at different spatial scales affect fritillary butterfly distribution on fragmented wetlands?. Landsc. Ecol. 23, 269–283. https://doi.org/10.1007/s10980-007-9178-3 (2008).Article 

    Google Scholar 
    He, M. et al. Effects of landscape and local factors on the diversity of flower-visitor groups under an urbanization gradient, a case study in Wuhan, China. Diversity 14, 208. https://doi.org/10.3390/d14030208 (2022).Article 

    Google Scholar 
    Buchholz, S., Gathof, A. K., Grossmann, A. J., Kowarik, I. & Fischer, L. K. Wild bees in urban grasslands: Urbanisation, functional diversity and species traits. Landsc. Urban Plan. 196, 103731. https://doi.org/10.1016/j.landurbplan.2019.103731 (2020).Article 

    Google Scholar 
    Chapman, R. E. & Bourke, A. F. G. The influence of sociality on the conservation biology of social insects. Ecol. Lett. 4, 650–662. https://doi.org/10.1046/j.1461-0248.2001.00253.x (2001).Article 

    Google Scholar 
    Gaertner, M. et al. Non-native species in urban environments: Patterns, processes, impacts and challenges. Biol. Invasions 19, 3461–3469. https://doi.org/10.1007/s10530-017-1598-7 (2017).Article 

    Google Scholar 
    Kowarik, I. On the role of alien species in urban flora and vegetation. In Urban Ecology. An International Perspective on the Interaction Between Humans and Nature (ed. Marzluff, J. M.) 321–338 (2008).Lorenz, S. & Stark, K. Saving the honeybees in Berlin? A case study of the urban beekeeping boom. Environ. Sociol. 1, 116–126. https://doi.org/10.1080/23251042.2015.1008383 (2015).Article 

    Google Scholar 
    Olesen, J. M., Bascompte, J., Dupont, Y. L. & Jordano, P. The modularity of pollination networks. Proc. Natl. Acad. Sci. USA 104, 19891–19896. https://doi.org/10.1073/pnas.0706375104 (2007).Article 
    ADS 
    PubMed 
    PubMed Central 
    MATH 

    Google Scholar 
    Thébault, E. & Fontaine, C. Stability of ecological communities and the architecture of mutualistic and trophic networks. Science 329, 853–856. https://doi.org/10.1126/science.1188321 (2010).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Dormann, C. F., Fründ, J. & Schaefer, H. M. Identifying causes of patterns in ecological networks: Opportunities and limitations. Annu. Rev. Ecol. Evol. Syst. 48, 559–584. https://doi.org/10.1146/annurev-ecolsys-110316-022928 (2017).Article 

    Google Scholar 
    Tylianakis, J. M., Laliberté, E., Nielsen, A. & Bascompte, J. Conservation of species interaction networks. Biol. Conserv. 143, 2270–2279. https://doi.org/10.1016/j.biocon.2009.12.004 (2010).Article 

    Google Scholar 
    Grilli, J., Rogers, T. & Allesina, S. Modularity and stability in ecological communities. Nat. Commun. 7, 12031. https://doi.org/10.1038/ncomms12031 (2016).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Grass, I., Jauker, B., Steffan-Dewenter, I., Tscharntke, T. & Jauker, F. Past and potential future effects of habitat fragmentation on structure and stability of plant–pollinator and host-parasitoid networks. Nat. Ecol. Evol 2, 1408–1417. https://doi.org/10.1038/s41559-018-0631-2 (2018).Article 
    PubMed 

    Google Scholar 
    Kaiser-Bunbury, C. N. et al. Ecosystem restoration strengthens pollination network resilience and function. Nature 542, 223–227. https://doi.org/10.1038/nature21071 (2017).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Bommarco, R. et al. Dispersal capacity and diet breadth modify the response of wild bees to habitat loss. Proc. Biol. Sci. 277, 2075–2082. https://doi.org/10.1098/rspb.2009.2221 (2010).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Alarcón, R., Waser, N. M. & Ollerton, J. Year-to-year variation in the topology of a plant–pollinator interaction network. Oikos 117, 1796–1807. https://doi.org/10.1111/j.0030-1299.2008.16987.x (2008).Article 

    Google Scholar 
    Dupont, Y. L., Padrón, B., Olesen, J. M. & Petanidou, T. Spatio-temporal variation in the structure of pollination networks. Oikos 118, 1261–1269. https://doi.org/10.1111/j.1600-0706.2009.17594.x (2009).Article 

    Google Scholar 
    Santamaría, S. et al. Landscape effects on pollination networks in Mediterranean gypsum islands. Plant Biol. 20(Suppl 1), 184–194. https://doi.org/10.1111/plb.12602 (2018).Article 
    PubMed 

    Google Scholar  More

  • in

    Balancing the bloom

    Algal blooms that form because of phytoplankton proliferation have key roles in marine ecology and carbon fixation. When the blooms die, most of the fixed carbon is transferred to higher trophic levels, and a small fraction sinks into the deep sea. Viral infection is one of the causes of bloom termination, but its effect on the fate and flow of carbon in the ocean is unknown. In this study, Vincent et al. perform a mesocosm experiment to analyse the bloom dynamics of the coccolithophore microalga Emiliania huxleyi and the impact of viral infection on surrounding bacterial communities and the carbon cycle. The authors observed that viral infection was not only the main cause of phytoplankton mortality, but it also shaped the composition of free-living bacterial and eukaryotic species in the blooms. On viral infection of E. huxleyi, the authors found a comparable biomass of eukaryotic and bacterial heterotrophic recyclers, as well as increased organic and inorganic carbon release that contributed to carbon sinking into the deep ocean. Altogether, these results highlight the impact of viruses on the microbial communities of blooms and the consequences on carbon cycling. More

  • in

    Late Cenozoic cooling restructured global marine plankton communities

    Jonkers, L., Hillebrand, H. & Kucera, M. Global change drives modern plankton communities away from the pre-industrial state. Nature 570, 372–375 (2019).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Barton, A. D., Irwin, A. J., Finkel, Z. V. & Stock, C. A. Anthropogenic climate change drives shift and shuffle in North Atlantic phytoplankton communities. Proc. Natl Acad. Sci. USA 113, 2964–2969 (2016).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Beaugrand, G., Reid, P. C., Ibanez, F., Lindley, J. A. & Edwards, M. Reorganization of North Atlantic marine copepod biodiversity and climate. Science 296, 1692–1694 (2002).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Cheung, W. W., Watson, R. & Pauly, D. Signature of ocean warming in global fisheries catch. Nature 497, 365–368 (2013).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Herbert-Read, J. E. et al. A global horizon scan of issues impacting marine and coastal biodiversity conservation. Nat. Ecol. Evol. 6, 1262–1270 (2022).Article 
    PubMed 

    Google Scholar 
    Yasuhara, M. & Deutsch, C. A. Paleobiology provides glimpses of future ocean. Science 375, 25–26 (2022).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Fenton, I. S. et al. Triton, a new species-level database of Cenozoic planktonic foraminiferal occurrences. Sci. Data 8, 160 (2021).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Strack, A., Jonkers, L., Rillo, M. C., Hillebrand, H. & Kucera, M. Plankton response to global warming is characterized by non-uniform shifts in assemblage composition since the last ice age. Nat. Ecol. Evol. 6, 1871–1880 (2022).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Barnosky, A. D. et al. Has the Earth’s sixth mass extinction already arrived? Nature 471, 51–57 (2011).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Mokany, K. & Ferrier, S. Predicting impacts of climate change on biodiversity: a role for semi‐mechanistic community‐level modelling. Divers. Distrib. 17, 374–380 (2011).Article 

    Google Scholar 
    Pörtner, H.-O. et al. eds IPCC: Climate Change 2022: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (Cambridge Univ. Press, 2022).Pontarp, M. et al. The latitudinal diversity gradient: novel understanding through mechanistic eco-evolutionary models. Trends Ecol. Evol. 34, 211–223 (2019).Article 
    PubMed 

    Google Scholar 
    Schumm, M. et al. Common latitudinal gradients in functional richness and functional evenness across marine and terrestrial systems. Proc. R. Soc. B 286, 20190745 (2019).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Rutherford, S., D’Hondt, S. & Prell, W. Environmental controls on the geographic distribution of zooplankton diversity. Nature 400, 749–753 (1999).Article 
    ADS 
    CAS 

    Google Scholar 
    Worm, B., Lotze, H. K. & Myers, R. A. Predator diversity hotspots in the blue ocean. Proc. Natl Acad. Sci. USA 100, 9884–9888 (2003).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Tittensor, D. P. et al. Global patterns and predictors of marine biodiversity across taxa. Nature 466, 1098–1101 (2010).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Fenton, I. S., Pearson, P. N., Dunkley Jones, T. & Purvis, A. Environmental predictors of diversity in recent planktonic foraminifera as recorded in marine sediments. PLoS ONE 11, e0165522 (2016).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Chaudhary, C., Saeedi, H. & Costello, M. J. Bimodality of latitudinal gradients in marine species richness. Trends Ecol. Evol. 31, 670–676 (2016).Article 
    PubMed 

    Google Scholar 
    Chaudhary, C., Richardson, A. J., Schoeman, D. S. & Costello, M. J. Global warming is causing a more pronounced dip in marine species richness around the equator. Proc. Natl Acad. Sci. USA 118, e2015094118 (2021).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Rillo, M. C., Miller, C. G., Kučera, M. & Ezard, T. H. G. Intraspecific size variation in planktonic foraminifera cannot be consistently predicted by the environment. Ecol. Evol. 10, 11579–11590 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Yasuhara, M. et al. Past and future decline of tropical pelagic biodiversity. Proc. Natl Acad. Sci. USA 117, 12891–12896 (2020).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Thomas, E. Descent into the icehouse. Geology 36, 191–192 (2008).Article 
    ADS 

    Google Scholar 
    Fenton, I. S. et al. The impact of Cenozoic cooling on assemblage diversity in planktonic foraminifera. Phil. Trans. R. Soc. B 371, 20150224 (2016).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Crame, J. A. Early Cenozoic evolution of the latitudinal diversity gradient. Earth Sci. Rev. 202, 103090 (2020).Article 

    Google Scholar 
    Yasuhara, M. et al. Time machine biology. Oceanography 33, 16–28 (2020).Article 

    Google Scholar 
    Alegret, L., Arreguín-Rodríguez, G. J., Trasviña-Moreno, C. A. & Thomas, E. Turnover and stability in the deep sea: benthic foraminifera as tracers of Paleogene global change. Global Planet. Change 196, 103372 (2021).Article 

    Google Scholar 
    Gaskell, D. E. et al. The latitudinal temperature gradient and its climate dependence as inferred from foraminiferal δ18O over the past 95 million years. Proc. Natl Acad. Sci. USA 119, e2111332119 (2022).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Mannion, P. D., Upchurch, P., Benson, R. B. & Goswami, A. The latitudinal biodiversity gradient through deep time. Trends Ecol. Evol. 29, 42–50 (2014).Article 
    PubMed 

    Google Scholar 
    Raja, N. B. & Kiessling, W. Out of the extratropics: the evolution of the latitudinal diversity gradient of Cenozoic marine plankton. Proc. R. Soc. B 288, 20210545 (2021).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Herbert, T. D. et al. Late Miocene global cooling and the rise of modern ecosystems. Nat. Geosci. 9, 843–847 (2016).Article 
    ADS 
    CAS 

    Google Scholar 
    Steinthorsdottir, M. et al. The Miocene: the future of the past. Paleoceanogr. Paleoclimatology 36, e2020PA004037 (2021).Article 

    Google Scholar 
    Brown, R. M., Chalk, T. B., Crocker, A. J., Wilson, P. A. & Foster, G. L. Late Miocene cooling coupled to carbon dioxide with Pleistocene-like climate sensitivity. Nat. Geosci. 15, 664–670 (2022).Article 
    ADS 
    CAS 

    Google Scholar 
    Guillermic, M., Misra, S., Eagle, R. & Tripati, A. Atmospheric CO2 estimates for the Miocene to Pleistocene based on foraminiferal δ11B at Ocean Drilling Program Sites 806 and 807 in the Western Equatorial Pacific. Clim. Past 18, 183–207 (2022).Article 

    Google Scholar 
    Jablonski, D., Roy, K. & Valentine, J. W. Out of the tropics: evolutionary dynamics of the latitudinal diversity gradient. Science 314, 102–106 (2006).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Yasuhara, M., Hunt, G., Dowsett, H. J., Robinson, M. M. & Stoll, D. K. Latitudinal species diversity gradient of marine zooplankton for the last three million years. Ecol. Lett. 15, 1174–1179 (2012).Article 
    PubMed 

    Google Scholar 
    Ezard, T. H. G., Aze, T., Pearson, P. N. & Purvis, A. Interplay between changing climate and species’ ecology drives macroevolutionary dynamics. Science 332, 349–351 (2011).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Peters, S. E., Kelly, D. C. & Fraass, A. J. Oceanographic controls on the diversity and extinction of planktonic foraminifera. Nature 493, 398–401 (2013).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Woodhouse, A. et al. Adaptive ecological niche migration does not negate extinction susceptibility. Sci. Rep. 11, 15411 (2021).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Yasuhara, M., Tittensor, D. P., Hillebrand, H. & Worm, B. Combining marine macroecology and palaeoecology in understanding biodiversity: microfossils as a model. Biol. Rev. 92, 199–215 (2017).Article 
    PubMed 

    Google Scholar 
    Bindoff, N. L. in IPCC Special Report on the Ocean and Cryosphere in a Changing Climate (eds Pörtner, H.-O. et al.) (IPCC, Cambridge Univ. Press, 2019).Aze, T. et al. A phylogeny of Cenozoic macroperforate planktonic foraminifera from fossil data. Biol. Rev. 86, 900–927 (2011).Article 
    PubMed 

    Google Scholar 
    Delmas, E. et al. Analysing ecological networks of species interactions. Biol. Rev. 94, 16–36 (2019).Article 
    PubMed 

    Google Scholar 
    Rojas, A., Calatayud, J., Kowalewski, M., Neuman, M. & Rosvall, M. A multiscale view of the Phanerozoic fossil record reveals the three major biotic transitions. Commun. Biol. 4, 309 (2021).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Swain, A., Devereux, M. & Fagan, W. F. Deciphering trophic interactions in a mid-Cambrian assemblage. iScience 24, 102271 (2021).Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Shaw, J. O. et al. Disentangling ecological and taphonomic signals in ancient food webs. Paleobiology 47, 385–401 (2021).Article 

    Google Scholar 
    Swain, A., Maccracken, S., Fagan, W. & Labandeira, C. Understanding the ecology of host plant–insect herbivore interactions in the fossil record through bipartite networks. Paleobiology 48, 239–260 (2022).Article 

    Google Scholar 
    Poisot, T., Canard, E., Mouquet, N. & Hochberg, M. E. A comparative study of ecological specialization estimators. Methods Ecol. Evol. 3, 537–544 (2012).Article 

    Google Scholar 
    Westerhold, T. et al. An astronomically dated record of Earth’s climate and its predictability over the last 66 million years. Science 369, 1383–1387 (2020).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Boscolo-Galazzo, F. and Crichton, K.A. et al. Temperature controls carbon cycling and biological evolution in the ocean twilight zone. Science 371, 1148–1152 (2021).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Boscolo-Galazzo, F. et al. Late Neogene evolution of modern deep-dwelling plankton. Biogeosciences 19, 743–762 (2022).Article 
    ADS 

    Google Scholar 
    Keller, G. in The Miocene Ocean: Paleoceanography and Biogeography Vol. 163, 177–196 (Geological Society of America, 1985).Holbourn, A. E. et al. Late Miocene climate cooling and intensification of southeast Asian winter monsoon. Nat. Commun. 9, 1584 (2018).Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Willeit, M., Ganopolski, A., Calov, R., Robinson, A. & Maslin, M. The role of CO2 decline for the onset of Northern Hemisphere glaciation. Quat. Sci. Rev. 119, 22–34 (2015).Article 
    ADS 

    Google Scholar 
    Hayashi, T. et al. Latest Pliocene Northern Hemisphere glaciation amplified by intensified Atlantic meridional overturning circulation. Commun. Earth Environ. 1, 25–10 (2020).Article 
    ADS 

    Google Scholar 
    Lam, A. R., Crundwell, M. P., Leckie, R. M., Albanese, J. & Uzel, J. P. Diachroneity rules the mid-latitudes: a test case using late Neogene planktic foraminifera across the Western Pacific. Geosciences 12, 190 (2022).Article 
    ADS 

    Google Scholar 
    Lowery, C. M., Bown, P. R., Fraass, A. J. & Hull, P. M. Ecological response of plankton to environmental change: thresholds for extinction. Annu. Rev. Earth Planet. Sci. 48, 403–429 (2020).Article 
    ADS 
    CAS 

    Google Scholar 
    Rillo, M. C. et al. On the mismatch in the strength of competition among fossil and modern species of planktonic Foraminifera. Global Ecol. Biogeogr. 28, 1866–1878 (2019).Article 

    Google Scholar 
    Poloczanska, E. S. et al. Global imprint of climate change on marine life. Nat. Clim. Change 3, 919–925 (2013).Article 
    ADS 

    Google Scholar 
    Monllor-Hurtado, A., Pennino, M. G. & Sanchez-Lizaso, J. L. Shift in tuna catches due to ocean warming. PLoS ONE 12, e0178196 (2017).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Brook, B. W., Sodhi, N. S. & Bradshaw, C. J. Synergies among extinction drivers under global change. Trends Ecol. Evol. 23, 453–460 (2008).Article 
    PubMed 

    Google Scholar 
    Mora, C. et al. Biotic and human vulnerability to projected changes in ocean biogeochemistry over the 21st century. PLoS Biol. 11, e1001682 (2013).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Renaudie, J., Lazarus, D.B. & Diver, P. NSB (Neptune Sandbox Berlin): an expanded and improved database of marine planktonic microfossil data and deep-sea stratigraphy. Palaeontol. Electron. 23, p.a11 (2020).
    Google Scholar 
    Pearson, P. N. in Atlas of Oligocene Planktonic Foraminifera (eds Wade, B. S. et al) 415–428 (Cushman Foundation of Foraminiferal Research, 2018).Liow, L. H., Skaug, H. J., Ergon, T. & Schweder, T. Global occurrence trajectories of microfossils: environmental volatility and the rise and fall of individual species. Paleobiology 36, 224–252 (2010).Article 

    Google Scholar 
    Lazarus, D., Weinkauf, M. & Diver, P. Pacman profiling: a simple procedure to identify stratigraphic outliers in high-density deep-sea microfossil data. Paleobiology 38, 144–161 (2012).Article 

    Google Scholar 
    Woodhouse, A. et al. Paleoecology and evolutionary response of planktonic foraminifera to the Plio-Pleistocene intensification of Northern Hemisphere glaciations. Preprint at EGUsphere https://doi.org/10.5194/egusphere-2022-844 (2022).Woodhouse, A. et al. Paleoecology and evolutionary response of planktonic foraminifera to the mid-Pliocene Warm Period and Plio-Pleistocene bipolar ice sheet expansion. Biogeosciences 20, 121–139 (2023).Article 
    ADS 

    Google Scholar 
    Dormann, C. F., Fründ, J., Blüthgen, N. & Gruber, B. Indices, graphs and null models: analyzing bipartite ecological networks. Op. Ecol. J. 2, 7–24 (2009).Article 

    Google Scholar 
    Swain, A. et al. Sampling bias and the robustness of ecological metrics for plant-damage-type association networks. Ecology https://doi.org/10.1002/ecy.3922 (2022).Julliard, R., Clavel, J., Devictor, V., Jiguet, F. & Couvet, D. Spatial segregation of specialists and generalists in bird communities. Ecol. Lett. 9, 1237–1244 (2006).Article 
    PubMed 

    Google Scholar 
    Vaughan, I. P. et al. econullnetr: an R package using null models to analyse the structure of ecological networks and identify resource selection. Methods Ecol. Evol. 9, 728–733 (2018).Article 
    MathSciNet 

    Google Scholar  More

  • in

    Effects of moisture and density-dependent interactions on tropical tree diversity

    Gentry, A. H. Changes in plant community diversity and floristic composition on environmental and geographical gradients. Ann. Missouri Bot. Gard. 75, 1–34 (1988).Article 

    Google Scholar 
    Givnish, T. J. On the causes of gradients in tropical tree diversity. J. Ecol. 87, 193–210 (1999).Article 

    Google Scholar 
    Janzen, D. H. Herbivores and the number of tree species in tropical forests. Am. Nat. 104, 501–528 (1970).Article 

    Google Scholar 
    Connell, J. H. in Dynamics of Populations (eds Den Boer, P. J. & Gradwell, G. R.) 298–312 (PUDOC, 1971).Esquivel-Muelbert, A. et al. Seasonal drought limits tree species across the Neotropics. Ecography 40, 618–629 (2017).Article 

    Google Scholar 
    Gillett, J. B. Pest pressure, an underestimated factor in evolution. Syst. Assoc. Publ. 4, 37–46 (1962).
    Google Scholar 
    Engelbrecht, B. M. J. et al. Drought sensitivity shapes species distribution patterns in tropical forests. Nature 447, 80–82 (2007).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Condit, R., Engelbrecht, B. M. J., Pino, D., Pérez, R. & Turner, B. L. Species distributions in response to individual soil nutrients and seasonal drought across a community of tropical trees. Proc. Natl Acad. Sci. USA 110, 5064–5068 (2013).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Allen, C. D. et al. A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests. For. Ecol. Manage. 259, 660–684 (2010).Article 

    Google Scholar 
    Harrison, S., Spasojevic, M. J. & Li, D. Climate and plant community diversity in space and time. Proc. Natl Acad. Sci. USA 117, 4464–4470 (2020).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Milici, V. R., Dalui, D., Mickley, J. G. & Bagchi, R. Responses of plant–pathogen interactions to precipitation: Implications for tropical tree richness in a changing world. J. Ecol. 108, 1800–1809 (2020).Article 

    Google Scholar 
    Mangan, S. A. et al. Negative plant-soil feedback predicts tree-species relative abundance in a tropical forest. Nature 466, 752–755 (2010).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Gripenberg, S. et al. Testing for enemy-mediated density-dependence in the mortality of seedlings: field experiments with five Neotropical tree species. Oikos 123, 185–193 (2014).Article 

    Google Scholar 
    Bagchi, R. et al. Pathogens and insect herbivores drive rainforest plant diversity and composition. Nature 506, 85–88 (2014).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Fricke, E. C., Tewksbury, J. J. & Rogers, H. S. Multiple natural enemies cause distance-dependent mortality at the seed-to-seedling transition. Ecol. Lett. 17, 593–598 (2014).Article 
    PubMed 

    Google Scholar 
    Augspurger, C. K. & Kelly, C. K. Pathogen mortality of tropical tree seedlings: experimental studies of the effects of dispersal distance, seedling density, and light conditions. Oecologia 61, 211–217 (1984).Article 
    ADS 
    PubMed 

    Google Scholar 
    Chen, L. et al. Differential soil fungus accumulation and density dependence of trees in a subtropical forest. Science 366, 124–128 (2019).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Eck, J. L., Stump, S. M., Delavaux, C. S., Mangan, S. A. & Comita, L. S. Evidence of within-species specialization by soil microbes and the implications for plant community diversity. Proc. Natl Acad. Sci. USA 116, 7371–7376 (2019).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kishimoto-Yamada, K. & Itioka, T. How much have we learned about seasonality in tropical insect abundance since Wolda (1988)? Entomol. Sci. 18, 407–419 (2015).Article 

    Google Scholar 
    Huberty, A. F. & Denno, R. F. Plant water stress and its consequences for herbivorous insects: a new synthesis. Ecology 85, 1383–1398 (2004).Article 

    Google Scholar 
    Janzen, D. H. & Hallwachs, W. To us insectometers, it is clear that insect decline in our Costa Rican tropics is real, so let’s be kind to the survivors. Proc. Natl Acad. Sci. USA 118, e2002546117 (2021).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Rodríguez-Castañeda, G. The world and its shades of green: a meta-analysis on trophic cascades across temperature and precipitation gradients. Glob. Ecol. Biogeogr. 22, 118–130 (2013).Article 

    Google Scholar 
    Janzen, D. H. & Schoener, T. W. Differences in insect abundance and diversity between wetter and drier sites during a tropical dry season. Ecology 49, 96–110 (1968).Article 

    Google Scholar 
    Sturrock, R. N. et al. Climate change and forest diseases. Plant Pathol 60, 133–149 (2011).Article 

    Google Scholar 
    Desprez-Loustau, M.-L., Marçais, B., Nageleisen, L.-M., Piou, D. & Vannini, A. Interactive effects of drought and pathogens in forest trees. Ann. For. Sci. 63, 597–612 (2006).Article 

    Google Scholar 
    Swinfield, T., Lewis, O. T., Bagchi, R. & Freckleton, R. P. Consequences of changing rainfall for fungal pathogen-induced mortality in tropical tree seedlings. Ecol. Evol. 2, 1408–1413 (2012).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Jactel, H. et al. Drought effects on damage by forest insects and pathogens: a meta-analysis. Glob. Chang. Biol. 18, 267–276 (2012).Article 
    ADS 

    Google Scholar 
    Maharjan, S. K. et al. Plant functional traits and the distribution of West African rain forest trees along the rainfall gradient. Biotropica 43, 552–561 (2011).Article 

    Google Scholar 
    Klironomos, J. N. Feedback with soil biota contributes to plant rarity and invasiveness in communities. Nature 417, 67–70 (2002).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Petermann, J. S., Fergus, A. J. F., Turnbull, L. A. & Schmid, B. Janzen–Connell effects are widespread and strong enough to maintain diversity in grasslands. Ecology 89, 2399–2406 (2008).Article 
    PubMed 

    Google Scholar 
    Chesson, P. Updates on mechanisms of maintenance of species diversity. J. Ecol. 106, 1773–1794 (2018).Article 

    Google Scholar 
    Barabás, G., Michalska-Smith, M. J. & Allesina, S. The effect of intra- and interspecific competition on coexistence in multispecies communities. Am. Nat. 188, E1–E12 (2016).Article 
    PubMed 

    Google Scholar 
    Lebrija-Trejos, E., Wright, S. J., Hernández, A. & Reich, P. B. Does relatedness matter? Phylogenetic density-dependent survival of seedlings in a tropical forest. Ecology 95, 940–951 (2014).Article 
    PubMed 

    Google Scholar 
    Lebrija-Trejos, E., Reich, P. B., Hernández, A. & Wright, S. J. Species with greater seed mass are more tolerant of conspecific neighbours: a key driver of early survival and future abundances in a tropical forest. Ecol. Lett. 19, 1071–1080 (2016).Article 
    PubMed 

    Google Scholar 
    Green, P. T., Harms, K. E. & Connell, J. H. Nonrandom, diversifying processes are disproportionately strong in the smallest size classes of a tropical forest. Proc. Natl Acad. Sci. USA 111, 18649–18654 (2014).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Comita, L. S. et al. Testing predictions of the Janzen–Connell hypothesis: a meta-analysis of experimental evidence for distance- and density-dependent seed and seedling survival. J. Ecol. 102, 845–856 (2014).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Moles, A. T. & Westoby, M. What do seedlings die from and what are the implications for evolution of seed size? Oikos 106, 193–199 (2004).Article 

    Google Scholar 
    Paine, C. E. T., Harms, K. E., Schnitzer, S. A. & Carson, W. P. Weak competition among tropical tree seedlings: implications for species coexistence. Biotropica 40, 432–440 (2008).Article 

    Google Scholar 
    Weissflog, A., Markesteijn, L., Lewis, O. T., Comita, L. S. & Engelbrecht, B. M. J. Contrasting patterns of insect herbivory and predation pressure across a tropical rainfall gradient. Biotropica 50, 302–311 (2018).Article 

    Google Scholar 
    Brenes-Arguedas, T., Coley, P. D. & Kursar, T. A. Pests vs. drought as determinants of plant distribution along a tropical rainfall gradient. Ecology 90, 1751–1761 (2009).Article 
    PubMed 

    Google Scholar 
    Gaviria, J. & Engelbrecht, B. M. J. Effects of drought, pest pressure and light availability on seedling establishment and growth: their role for distribution of tree species across a tropical rainfall gradient. PLoS ONE 10, e0143955 (2015).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Spear, E. R., Coley, P. D. & Kursar, T. A. Do pathogens limit the distributions of tropical trees across a rainfall gradient? J. Ecol. 103, 165–174 (2015).Article 

    Google Scholar 
    Clark, J. S. et al. The impacts of increasing drought on forest dynamics, structure, and biodiversity in the United States. Glob. Chang. Biol. 22, 2329–2352 (2016).Article 
    ADS 
    PubMed 

    Google Scholar 
    Riutta, T. et al. Experimental evidence for the interacting effects of forest edge, moisture and soil macrofauna on leaf litter decomposition. Soil Biol. Biochem. 49, 124–131 (2012).Article 
    CAS 

    Google Scholar 
    Lebrija-Trejos, E., Pérez-García, E. A., Meave, J. A., Poorter, L. & Bongers, F. Environmental changes during secondary succession in a tropical dry forest in Mexico. J. Trop. Ecol. 27, 477–489 (2011).Article 

    Google Scholar 
    Krishnadas, M. & Comita, L. S. Edge effects on seedling diversity are mediated by impacts of fungi and insects on seedling recruitment but not survival. Front. Glob. Chang. 2, 76 (2019).Article 

    Google Scholar 
    Garcia, R. A., Cabeza, M., Rahbek, C. & Araujo, M. B. Multiple dimensions of climate change and their implications for biodiversity. Science 344, 1247579 (2014).Article 
    PubMed 

    Google Scholar 
    Uriarte, M., Muscarella, R. & Zimmerman, J. K. Environmental heterogeneity and biotic interactions mediate climate impacts on tropical forest regeneration. Glob. Chang. Biol. 24, e692–e704 (2018).Article 
    ADS 
    PubMed 

    Google Scholar 
    Bachelot, B., Kobe, R. K. & Vriesendorp, C. Negative density-dependent mortality varies over time in a wet tropical forest, advantaging rare species, common species, or no species. Oecologia 179, 853–861 (2015).Article 
    ADS 
    PubMed 

    Google Scholar 
    Zhu, Y. et al. Density‐dependent survival varies with species life‐history strategy in a tropical forest. Ecol. Lett. 21, 506–515 (2018).Article 
    CAS 
    PubMed 

    Google Scholar 
    Wright, S. J., Calderón, O., Hernandéz, A. & Muller-Landau, H. C. Annual and spatial variation in seedfall and seedling recruitment in a neotropical forest. Ecology 86, 848–860 (2005).Article 

    Google Scholar 
    Condit, R. Tropical Forest Census Plots https://doi.org/10.1007/978-3-662-03664-8 (Springer, 1998).Kupers, S. J., Wirth, C., Engelbrecht, B. M. J. & Rüger, N. Dry season soil water potential maps of a 50 hectare tropical forest plot on Barro Colorado Island, Panama. Sci. Data 6, 63 (2019).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Garwood, N. C. in The Ecology of a Tropical Forest: Seasonal Rhythms and Long-term Changes (eds Leigh, E. G., Rand, A. S. & Windsor, D. M.) 173–185 (Smithsonian Institution Press, 1982).Jost, L. Entropy and diversity. Oikos 113, 363–375 (2006).Article 

    Google Scholar 
    Burnham, K. P. & Anderson, D. R. Model Selection and Multimodel Inference https://doi.org/10.1007/b97636 (Springer, 2004).Muller-Landau, H. C. et al. Testing metabolic ecology theory for allometric scaling of tree size, growth and mortality in tropical forests. Ecol. Lett. 9, 575–588 (2006).Article 
    PubMed 

    Google Scholar 
    Detto, M., Visser, M. D., Wright, S. J. & Pacala, S. W. Bias in the detection of negative density dependence in plant communities. Ecol. Lett. 22, 1923–1939 (2019).Article 
    PubMed 

    Google Scholar 
    Bolker, B. M. et al. Generalized linear mixed models: a practical guide for ecology and evolution. Trends Ecol. Evol. 24, 127–135 (2009).Article 
    PubMed 

    Google Scholar 
    Barr, D. J., Levy, R., Scheepers, C. & Tily, H. J. Random effects structure for confirmatory hypothesis testing: keep it maximal. J. Mem. Lang. 68, 255–278 (2013).Article 

    Google Scholar 
    Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).Article 

    Google Scholar 
    Bates, D. et al. Package ‘lme4’ Reference Manual https://cran.r-project.org/web/packages/lme4/lme4.pdf (2021).Wilkinson, G. N. & Rogers, C. E. Symbolic description of factorial models for analysis of variance. Appl. Stat. 22, 392 (1973).Article 

    Google Scholar 
    Afshartous, D. & Preston, R. A. Key results of interaction models with centering. J. Stat. Educ. https://doi.org/10.1080/10691898.2011.11889620 (2011).Cohen, J. Statistical Power Analysis for the Behavioral Sciences https://doi.org/10.1016/C2013-0-10517-X (Elsevier, 1977).Steiger, J. H. Tests for comparing elements of a correlation matrix. Psychol. Bull. 87, 245–251 (1980).Article 

    Google Scholar 
    R Core Team. R: A Language and Environment for Statistical Computing https://www.R-project.org/ (2016).Pinheiro, J. et al. nlme: Linear and Nonlinear Mixed Effects Models https://CRAN.R-project.org/package=nlme (2020).Gelman, A. & Hill, J. Data Analysis Using Regression and Multilevel/Hierarchical Models (Cambridge Univ. Press, 2007).Hartig, F. DHARMa: Residual Diagnostics for Hierarchical (Multi-level/Mixed) Regression Models https://CRAN.R-project.org/package=DHARMa (2021).Lebrija-Trejos, E., Wright, S. J. & Hernández, A. Moisture, Density-dependent Interactions, and Tropical Tree Diversity https://figshare.com/s/a4d2dbb2a73b3eb09f9f (2022).Kupers, S. J., Wirth, C., Engelbrecht, B. M. J. & Rüger, N. Dry Season Soil Water Potential Maps of a 50 Hectare Tropical Forest Plot on Barro Colorado Island, Panama https://doi.org/10.6084/m9.figshare.7611005.v1 (2019).Paton, S. Barro Colorado Island, Lutz Catchment, Soil Moisture, Manual https://doi.org/10.25573/data.10042517.v1 (2019). More

  • in

    Genetic monitoring on the world’s first MSC eco-labeled common octopus (O. vulgaris) fishery in western Asturias, Spain

    FAO. El estado mundial de la pesca y la acuicultura 2020 (FAO, 2020).
    Google Scholar 
    Jackson, J. B. C. Historical overfishing and the recent collapse of coastal ecosystems. Science 293, 629–637 (2001).Article 
    CAS 
    PubMed 

    Google Scholar 
    Scheffer, M., Carpenter, S. & de Young, B. Cascading effects of overfishing marine systems. Trends Ecol. Evol. 20, 579–581 (2005).Article 
    PubMed 

    Google Scholar 
    Coll, M., Libralato, S., Tudela, S., Palomera, I. & Pranovi, F. Ecosystem overfishing in the ocean. PLoS ONE 3, e3881 (2008).Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Peterson, M. S. & Lowe, M. R. Implications of cumulative impacts to estuarine and marine habitat quality for fish and invertebrate resources. Rev. Fish. Sci. 17, 505–523 (2009).Article 

    Google Scholar 
    Claudet, J. & Fraschetti, S. Human-driven impacts on marine habitats: A regional meta-analysis in the Mediterranean Sea. Biol. Cons. 143, 2195–2206 (2010).Article 

    Google Scholar 
    Smith, V. H., Tilman, G. D. & Nekola, J. C. Eutrophication: Impacts of excess nutrient inputs on freshwater, marine, and terrestrial ecosystems. Environ. Pollut. 100, 179–196 (1999).Article 
    CAS 
    PubMed 

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

    Google Scholar 
    Doney, S. C. et al. Climate change impacts on marine ecosystems. Ann. Rev. Mar. Sci. 4, 11–37 (2012).Article 
    PubMed 

    Google Scholar 
    Molnar, J. L., Gamboa, R. L., Revenga, C. & Spalding, M. D. Assessing the global threat of invasive species to marine biodiversity. Front. Ecol. Environ. 6, 485–492 (2008).Article 

    Google Scholar 
    Wojnarowska, M., Sołtysik, M. & Prusak, A. Impact of eco-labelling on the implementation of sustainable production and consumption. Environ. Impact Assess. Rev. 86, 106505 (2021).Article 

    Google Scholar 
    Yan, H. F. et al. Overfishing and habitat loss drive range contraction of iconic marine fishes to near extinction. Sci. Adv. 7, 6026 (2021).Article 
    ADS 

    Google Scholar 
    Bastardie, F. et al. Spatial planning for fisheries in the Northern Adriatic: Working toward viable and sustainable fishing. Ecosphere 8, e01696 (2017).Article 

    Google Scholar 
    Arkema, K. K. et al. Integrating fisheries management into sustainable development planning. Ecol. Soc. 24, 0201 (2019).Article 

    Google Scholar 
    Aguión, A. et al. Establishing a governance threshold in small-scale fisheries to achieve sustainability. Ambio. https://doi.org/10.1007/s13280-021-01606-x (2021).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Gudmundsson, E. & Wessells, C. R. Ecolabeling seafood for sustainable production: Implications for fisheries management. Mar. Resour. Econ. 15, 97–113 (2000).Article 

    Google Scholar 
    FAO. Guidelines for the Ecolabelling of Fish and Fishery Products from Marine Capture Fisheries. Revision 1 (FAO, 2009).
    Google Scholar 
    Hilborn, R. & Ovando, D. Reflections on the success of traditional fisheries management. ICES J. Mar. Sci. 71, 1040–1046 (2014).Article 

    Google Scholar 
    Casey, J., Jardim, E. & Martinsohn, J. T. H. The role of genetics in fisheries management under the E.U. common fisheries policy. J. Fish Biol. 89, 2755–2767 (2016).Article 
    CAS 
    PubMed 

    Google Scholar 
    MSC. MSC Fisheries Standard v2.01. https://www.msc.org/docs/default-source/default-document-library/for-business/program-documents/fisheries-program-documents/msc-fisheries-standard-v2-01.pdf?sfvrsn=8ecb3272_9 (2018).Costello, C. et al. Status and solutions for the world’s unassessed fisheries. Science 338, 517–520 (2012).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Hilborn, R. et al. Effective fisheries management instrumental in improving fish stock status. PNAS 117, 2218–2224 (2020).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Worm, B. & Branch, T. A. The future of fish. Trends Ecol. Evol. 27, 594–599 (2012).Article 
    PubMed 

    Google Scholar 
    Palomares, M. L. D. et al. Fishery biomass trends of exploited fish populations in marine ecoregions, climatic zones and ocean basins. Estuar. Coast. Shelf Sci. 243, 106896 (2020).Article 

    Google Scholar 
    Ihssen, P. E. et al. Stock identification: Materials and methods. Can. J. Fish. Aquat. Sci. 38, 1838–1855 (1981).Article 

    Google Scholar 
    Carvalho, G. R. & Hauser, L. Molecular genetics and the stock concept in fisheries. In Molecular Genetics in Fisheries (eds Carvalho, G. R. & Pitcher, T. J.) 55–79 (Springer, 1995).Chapter 

    Google Scholar 
    Worm, B. et al. Rebuilding global fisheries. Science 325, 578–585 (2009).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Gough, C. L. A., Dewar, K. M., Godley, B. J., Zafindranosy, E. & Broderick, A. C. Evidence of overfishing in small-scale fisheries in Madagascar. Front. Mar. Sci. 7, 317 (2020).Article 

    Google Scholar 
    Widjaja, S. et al. Illegal, Unreported and Unregulated Fishing and Associated Drivers 60 (2020).Walters, C. & Martell, S. J. D. Stock assessment needs for sustainable fisheries management. Bull. Mar. Sci. 70, 629–638 (2002).
    Google Scholar 
    Moreira, A. A., Tomás, A. R. G. & Hilsdorf, A. W. S. Evidence for genetic differentiation of Octopus vulgaris (Mollusca, Cephalopoda) fishery populations from the southern coast of Brazil as revealed by microsatellites. J. Exp. Mar. Biol. Ecol. 407, 34–40 (2011).Article 

    Google Scholar 
    Allendorf, F. W., Ryman, N. & Utter, F. M. Genetics and fishery management. In Population Genetics and Fishery Management 1–19 (1987).Oosthuizen, A., Jiwaji, M. & Shaw, P. Genetic analysis of the Octopus vulgaris population on the coast of South Africa. S. Afr. J. Sci. 100, 603–607 (2004).CAS 

    Google Scholar 
    Botsford, L. W., Castilla, J. C. & Peterson, C. H. The management of fisheries and marine ecosystems. Science 277, 509–515 (1997).Article 
    CAS 

    Google Scholar 
    Hilborn, R., Orensanz, J. M. & Parma, A. M. Institutions, incentives and the future of fisheries. Philos. Trans. R. Soc. B Biol. Sci. 360, 47. https://doi.org/10.1098/rstb.2004.1569 (2005).Article 

    Google Scholar 
    Ovenden, J. R., Berry, O., Welch, D. J., Buckworth, R. C. & Dichmont, C. M. Ocean’s eleven: A critical evaluation of the role of population, evolutionary and molecular genetics in the management of wild fisheries. Fish Fish. 16, 125–159 (2015).Article 

    Google Scholar 
    Aguirre-Sarabia, I. et al. Evidence of stock connectivity, hybridization, and misidentification in white anglerfish supports the need of a genetics-informed fisheries management framework. Evol. Appl. 14, 2221 (2021).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Grover, A. & Sharma, P. C. Development and use of molecular markers: Past and present. Crit. Rev. Biotechnol. 36, 290 (2016).Article 
    CAS 
    PubMed 

    Google Scholar 
    Valenzuela-Quiñonez, F. How fisheries management can benefit from genomics? Brief. Funct. Genom. 15, 352–357 (2016).Article 

    Google Scholar 
    Khoufi, W., Jabeur, C. & Bakhrouf, A. Stock assessment of the common octopus (Octopus vulgaris) in Monastir; the Mid-eastern Coast of Tunisia. Int. J. Mar. Sci. 2, 1 (2012).
    Google Scholar 
    Pita, C. et al. Fisheries for common octopus in Europe: Socioeconomic importance and management. Fish. Res. 235, 105820 (2021).Article 

    Google Scholar 
    Melis, R. et al. Genetic population structure and phylogeny of the common octopus Octopus vulgaris Cuvier, 1797 in the western Mediterranean Sea through nuclear and mitochondrial markers. Hydrobiologia 807, 277–296 (2018).Article 
    CAS 

    Google Scholar 
    De Luca, D., Catanese, G., Procaccini, G. & Fiorito, G. Octopus vulgaris (Cuvier, 1797) in the Mediterranean Sea: Genetic diversity and population structure. PLoS ONE 11, e0149496 (2016).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Fernández-Rueda, P. & García-Flórez, L. Octopus vulgaris (Mollusca: Cephalopoda) fishery management assessment in Asturias (north-west Spain). Fish. Res. 83, 351–354 (2007).Article 

    Google Scholar 
    Gobierno del Principado de Asturias. BOPA núm. 233 de 03-XII-2021, Vol. 233 (2021).Roa-Ureta, R. H. et al. Estimation of the spawning stock and recruitment relationship of Octopus vulgaris in Asturias (Bay of Biscay) with generalized depletion models: Implications for the applicability of MSY. ICES J. Mar. Sci. https://doi.org/10.1093/icesjms/fsab113 (2021).Article 

    Google Scholar 
    González, A. F., Macho, G., de Novoa, J. & García, M. Western Asturias Octopus Traps Fishery of Artisanal Cofradías 181 (2015).Sánchez, J. L. F., Fernández Polanco, J. M. & Llorente García, I. Evidence of price premium for MSC-certified products at fishers’ level: The case of the artisanal fleet of common octopus from Asturias (Spain). Mar. Policy 119, 104098 (2020).Article 

    Google Scholar 
    Murphy, J. M., Balguerías, E., Key, L. N. & Boyle, P. R. Microsatellite DNA markers discriminate between two Octopus vulgaris (Cephalopoda: Octopoda) fisheries along the northwest African coast. Bull. Mar. Sci. 71, 545–553 (2002).
    Google Scholar 
    Cabranes, C., Fernandez-Rueda, P. & Martínez, J. L. Genetic structure of Octopus vulgaris around the Iberian Peninsula and Canary Islands as indicated by microsatellite DNA variation. ICES J. Mar. Sci. 65, 12–16 (2008).Article 

    Google Scholar 
    Quinteiro, J., Rodríguez-Castro, J., Rey-Méndez, M. & González-Henríquez, N. Phylogeography of the insular populations of common octopus, Octopus vulgaris Cuvier, 1797, in the Atlantic Macaronesia. PLoS ONE 15, e0230294 (2020).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Greatorex, E. C. et al. Microsatellite markers for investigating population structure in Octopus vulgaris (Mollusca: Cephalopoda). Mol. Ecol. 9, 641–642 (2000).Article 
    CAS 
    PubMed 

    Google Scholar 
    De Luca, D., Catanese, G., Fiorito, G. & Procaccini, G. A new set of pure microsatellite loci in the common octopus Octopus vulgaris Cuvier, 1797 for multiplex PCR assay and their cross-amplification in O. maya Voss & Solís Ramírez, 1966. Conserv. Genet. Resour. 7, 299–301 (2015).Article 

    Google Scholar 
    Zuo, Z., Zheng, X., Liu, C. & Li, Q. Development and characterization of 17 polymorphic microsatellite loci in Octopus vulgaris Cuvier, 1797. Conserv. Genet. Resour. 4, 367–369 (2012).Article 

    Google Scholar 
    Weir, B. S. & Cockerham, C. C. Estimating F-statistics for the analysis of population structure. Evolution 38, 1358 (1984).CAS 
    PubMed 

    Google Scholar 
    Chapuis, M. P. & Estoup, A. Microsatellite null alleles and estimation of population differentiation. Mol. Biol. Evol. 24, 621–631 (2007).Article 
    CAS 
    PubMed 

    Google Scholar 
    Nei, M. & Takezaki, N. Estimation of Genetic Distances and Phylogenetic Trees from DNA Analysis 8 (1983).Do, C. et al. NeEstimator v2: Re-implementation of software for the estimation of contemporary effective population size (Ne) from genetic data. Mol. Ecol. Resour. 14, 209–214 (2014).Article 
    CAS 
    PubMed 

    Google Scholar 
    Waples, R. S. Separating the wheat from the chaff: Patterns of genetic differentiation in high gene flow species. J. Hered. 89, 438–450 (1998).Article 

    Google Scholar 
    Taboada, F. G. & Anadón, R. Patterns of change in sea surface temperature in the North Atlantic during the last three decades: Beyond mean trends. Clim. Change 115, 419–431 (2012).Article 
    ADS 

    Google Scholar 
    Ellegren, H. & Galtier, N. Determinants of genetic diversity. Nat. Rev. Genet. 17, 422–433 (2016).Article 
    CAS 
    PubMed 

    Google Scholar 
    Sinclair, M. & Valdimarsson, G. Responsible Fisheries in the Marine Ecosystem (CABI, 2003).Book 

    Google Scholar 
    Pinsky, M. L. & Palumbi, S. R. Meta-analysis reveals lower genetic diversity in overfished populations. Mol. Ecol. 23, 29–39 (2014).Article 
    PubMed 

    Google Scholar 
    Bradbury, I. R., Laurel, B., Snelgrove, P. V. R., Bentzen, P. & Campana, S. E. Global patterns in marine dispersal estimates: The influence of geography, taxonomic category and life history. Proc. R. Soc. B Biol. Sci. 275, 1803–1809 (2008).Article 

    Google Scholar 
    Waples, R. S. Testing for Hardy-Weinberg proportions: Have we lost the plot? J. Hered. 106, 1–19 (2015).Article 
    PubMed 

    Google Scholar 
    Casu, M. et al. Genetic structure of Octopus vulgaris (Mollusca, Cephalopoda) from the Mediterranean Sea as revealed by a microsatellite locus. Ital. J. Zool. 69, 295–300 (2002).Article 

    Google Scholar 
    Fadhlaoui-Zid, K. et al. Genetic structure of Octopus vulgaris (Cephalopoda, Octopodidae) in the central Mediterranean Sea inferred from the mitochondrial COIII gene. C.R. Biol. 335, 625–636 (2012).Article 
    PubMed 

    Google Scholar 
    Queiroga, H. et al. Oceanographic and behavioural processes affecting invertebrate larval dispersal and supply in the western Iberia upwelling ecosystem. Prog. Oceanogr. 74, 174–191 (2007).Article 
    ADS 

    Google Scholar 
    Mereu, M. et al. Mark–recapture investigation on Octopus vulgaris specimens in an area of the central western Mediterranean Sea. J. Mar. Biol. Assoc. U.K. 95, 131–138 (2015).Article 
    ADS 

    Google Scholar 
    Mereu, M. et al. Movement estimation of Octopus vulgaris Cuvier, 1797 from mark recapture experiment. J. Exp. Mar. Biol. Ecol. 470, 64–69 (2015).Article 

    Google Scholar 
    Roura, Á. et al. Life strategies of cephalopod paralarvae in a coastal upwelling system (NW Iberian Peninsula): Insights from zooplankton community and spatio-temporal analyses. Fish. Oceanogr. 25, 241–258 (2016).Article 

    Google Scholar 
    Moreno, A. et al. Essential habitats for pre-recruit Octopus vulgaris along the Portuguese coast. Fish. Res. 152, 74–85 (2014).Article 
    ADS 

    Google Scholar 
    Chédia, J., Widien, K. & Amina, B. Role of sea surface temperature and rainfall in determining the stock and fishery of the common octopus (Octopus vulgaris, Mollusca, Cephalopoda) in Tunisia. Mar. Ecol. 31, 431–438 (2010).Article 
    ADS 

    Google Scholar 
    Otero, J. et al. Bottom-up control of common octopus Octopus vulgaris in the Galician upwelling system, northeast Atlantic Ocean. Mar. Ecol. Prog. Ser. 362, 181–192 (2008).Article 
    ADS 

    Google Scholar 
    Hedgecock, D. & Pudovkin, A. I. A. I. Sweepstakes reproductive success in highly fecund marine fish and shellfish: A review and commentary. Bull. Mar. Sci. 87, 971–1002 (2011).Article 

    Google Scholar 
    Kalinowski, S. T. & Waples, R. S. Relationship of effective to census size in fluctuating populations. Conserv. Biol. 16, 129–136 (2002).Article 
    PubMed 

    Google Scholar 
    Sonderblohm, C. P., Pereira, J. & Erzini, K. Environmental and fishery-driven dynamics of the common octopus (Octopus vulgaris) based on time-series analyses from leeward Algarve, southern Portugal. ICES J. Mar. Sci. 71, 2231–2241 (2014).Article 

    Google Scholar 
    Sonderblohm, C. P. et al. Participatory assessment of management measures for Octopus vulgaris pot and trap fishery from southern Portugal. Mar. Policy 75, 133–142 (2017).Article 

    Google Scholar 
    Arkhipkin, A. I. et al. Stock assessment and management of cephalopods: Advances and challenges for short-lived fishery resources. ICES J. Mar. Sci. 78, 714–730 (2021).Article 

    Google Scholar 
    Franklin, I. R. Evolutionary change in small populations. In Conservation Biology: An Evolutionary-Ecological Perspective (eds Soulé, M. E. & Wilcox, B. A.) 395 (Sinauer Associates, 1980).
    Google Scholar 
    Slatkin, M. Rare alleles as indicators of gene flow. Evolution 39, 53–65 (1985).Article 
    PubMed 

    Google Scholar 
    Holleley, C. E. & Geerts, P. G. Multiplex manager 1.0: A cross-platform computer program that plans and optimizes multiplex PCR. Biotechniques 46, 511–517 (2009).Article 
    CAS 
    PubMed 

    Google Scholar 
    Van Oosterhout, C., Hutchinson, W. F., Wills, D. P. M. & Shipley, P. MICRO-CHECKER: Software for identifying and correcting genotyping errors in microsatellite data. Mol. Ecol. Notes 4, 535–538 (2004).Article 

    Google Scholar 
    Jombart, T. adegenet: A R package for the multivariate analysis of genetic markers. Bioinformatics 24, 1403–1405 (2008).Article 
    CAS 
    PubMed 

    Google Scholar 
    Paradis, E. Pegas: An R package for population genetics with an integrated-modular approach. Bioinformatics 26, 419–420 (2010).Article 
    CAS 
    PubMed 

    Google Scholar 
    Goudet, J. HIERFSTAT, a package for R to compute and test hierarchical F-statistics. Mol. Ecol. Notes 5, 184–186 (2005).Article 

    Google Scholar 
    Adamack, A. T. & Gruber, B. PopGenReport: Simplifying basic population genetic analyses in R. Methods Ecol. Evol. 5, 384–387 (2014).Article 

    Google Scholar 
    Goudet, J. FSTAT (Version 1.2): A computer program to calculate F-STATISTICS. J. Hered. 86, 485–486 (1995).Article 

    Google Scholar 
    Rice, W. R. Analyzing tables of statistical tests. Evolution 43, 223 (1989).Article 
    PubMed 

    Google Scholar 
    Piry, S., Luikart, G. & Cornuet, J. M. M. Bottleneck: A computer program for detecting recent reductions in the effective population size using allele frequency data. J. Hered. 90, 502–503 (1999).Article 

    Google Scholar 
    Luikart, G., Allendorf, F. W., Cornuet, J.-M.M. & Sherwin, W. B. Distortion of allele frequency distributions provides a test for recent population bottlenecks. J. Hered. https://doi.org/10.1093/jhered/89.3.238 (1998).Article 
    PubMed 

    Google Scholar 
    Pritchard, J. K., Stephens, M. & Donnelly, P. Inference of population structure using multilocus genotype data. Genetics 155, 945–959 (2000).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Besnier, F. & Glover, K. A. ParallelStructure: A R package to distribute parallel runs of the population genetics program STRUCTURE on multi-core computers. PLoS ONE 8, e70651 (2013).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Evanno, G., Regnaut, S. & Goudet, J. Detecting the number of clusters of individuals using the software STRUCTURE: A simulation study. Mol. Ecol. 14, 2611–2620 (2005).Article 
    CAS 
    PubMed 

    Google Scholar 
    Gilbert, K. J. et al. Recommendations for utilizing and reporting population genetic analyses: The reproducibility of genetic clustering using the program structure. Mol. Ecol. https://doi.org/10.1111/j.1365-294X.2012.05754.x (2012).Article 
    PubMed 

    Google Scholar 
    Earl, D. A. & VonHoldt, B. M. Structure harvester: A website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv. Genet. Resour. 4, 359–361 (2012).Article 

    Google Scholar 
    Takezaki, N., Nei, M. & Tamura, K. POPTREEW: Web version of POPTREE for constructing population trees from allele frequency data and computing some other quantities. Mol. Biol. Evol. 31, 1622–1624 (2014).Article 
    CAS 
    PubMed 

    Google Scholar 
    Letunic, I. & Bork, P. Interactive tree of life (iTOL) v5: An online tool for phylogenetic tree display and annotation. Nucleic Acids Res. 49, W293–W296 (2021).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Dray, S. & Dufour, A.-B. The ade4 package: Implementing the duality diagram for ecologists. J. Stat. Softw. 22, 1–20 (2007).Article 

    Google Scholar 
    Slatkin, M. Isolation by distance in equilibrium and non-equilibrium populations. Evolution 47, 264–279 (1993).Article 
    PubMed 

    Google Scholar 
    Cavalli-Sforza, L. L. & Edwards, A. W. F. Phylogenetic analysis. Models and estimation procedures. Am. J. Hum. Genet. 19, 233–257 (1967).CAS 
    PubMed 
    PubMed Central 

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

    Google Scholar 
    Waples, R. S. A generalized approach for estimating effective population size from temporal changes in allele frequency. Genetics 121, 379–391 (1989).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Katsanevakis, S. & Verriopoulos, G. Seasonal population dynamics of Octopus vulgaris in the eastern Mediterranean. ICES J. Mar. Sci. 63, 151–160 (2006).Article 

    Google Scholar 
    Jereb, P. et al. Cephalopod Biology and Fisheries in Europe: II Species Accounts 360 (ICES, 2015).
    Google Scholar  More

  • in

    Seasonal variation in the lipid content of Fraser River Chinook Salmon (Oncorhynchus tshawytscha) and its implications for Southern Resident Killer Whale (Orcinus orca) prey quality

    Caughley, G. Directions in conservation biology. J. Anim. Ecol. 63, 215 (1994).Article 

    Google Scholar 
    Fisheries and Oceans Canada. National recovery strategy for northern and southern resident killer whales (Orcinus orca) in Canada [proposed]. vol. Species at (2018).National Marine Fisheries Service. Recovery Plan for Southern Resident Killer Whales (Orcinus orca). (2008).Barrett-Lennard, L. G. & Ellis, G. M. Population Structure and Genetic Variability in Northeastern Pacific Killer Whales: Towards an Assessment of Population Viability. DFO Can. Sci. Advis. Secr. Res. Deocument 2001/065 65 (2001).DFO. Evaluation of the scientific evidence to inform the probability of effectiveness of mitigation measures in reducing shipping-related noise levels received by southern resident killer whales. CSAS Science Advisory Report vol. 2017/041 (2017).Ross, P. S., Ellis, G. M., Ikonomou, M. G. & Addison, R. F. High PCB concentrations in free-ranging Pacific Killer Whales, Orcinus orca: Effects of age, sex and dietary preference. Mar. Pollut. Bull. 40, 504–515 (2000).Article 
    CAS 

    Google Scholar 
    Ward, E. J., Holmes, E. E. & Balcomb, K. C. Quantifying the effects of prey abundance on killer whale reproduction. J. Appl. Ecol. 46, 632–640 (2009).Article 

    Google Scholar 
    Ford, J. K. B., Ellis, G. M., Olesiuk, P. F. & Balcomb, K. C. Linking killer whale survival and prey abundance: Food limitation in the oceans’ apex predator ?. Biol. Lett. 6, 139–142 (2010).Article 
    PubMed 

    Google Scholar 
    Ford, J. K. B. et al. Dietary specialization in two sympatric populations of killer whales (Orcinus orca) in coastal British Columbia and adjacent waters. Can. J. Zool. 76, 1456–1471 (1998).Article 

    Google Scholar 
    Ford, J. K. B., Ellis, G. M. & Olesiuk, P. F. Linking Prey and Population Dynamics Did Food Limitation Cause Recent Declines of RKW in BC, vol. 3848 (2005).O’Neill, S. M., Ylitalo, G. M. & West, J. E. Energy content of Pacific salmon as prey of northern and southern resident killer whales. Endanger. Species Res. 25, 265–281 (2014).Article 

    Google Scholar 
    Ford, J. K. B. & Ellis, G. M. Selective foraging by fish-eating killer whales Orcinus orca in British Columbia. Mar. Ecol. Prog. Ser. 316, 185–199 (2006).Article 
    ADS 

    Google Scholar 
    Jeffrey, K. M., Côté, I. M., Irvine, J. R. & Reynolds, J. D. Changes in body size of Canadian Pacific salmon over six decades. Can. J. Fish. Aquat. Sci. 74, 191–201 (2017).Article 

    Google Scholar 
    Ohlberger, J., Schindler, D. E., Ward, E. J., Walsworth, T. E. & Essington, T. E. Resurgence of an apex marine predator and the decline in prey body size. Proc. Natl. Acad. Sci. USA https://doi.org/10.1073/pnas.1910930116 (2019).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ohlberger, J., Ward, E. J., Schindler, D. E. & Lewis, B. Demographic changes in Chinook salmon across the Northeast Pacific Ocean. Fish Fish. 19, 533–546 (2018).Article 

    Google Scholar 
    Bigler, B. S., Welch, D. W. & Helle, J. H. A review of size trends among North Pacific salmon (Oncorhynchus spp.). Can. J. Fish. Aquat. Sci. 53, 455–465 (2011).Article 

    Google Scholar 
    Hanson, M. B. et al. Species and stock identification of prey consumed by endangered southern resident killer whales in their summer range. Endanger. Species Res. 11, 69–82 (2010).Article 
    ADS 

    Google Scholar 
    Losee, J. P., Kendall, N. W. & Dufault, A. Changing salmon: An analysis of body mass, abundance, survival, and productivity trends across 45 years in Puget Sound. Fish Fish. 20, 934–951 (2019).Article 

    Google Scholar 
    Riddell, B. et al. Assessment of Status and Factors for Decline of Southern BC Chinook Salmon: Independent Panel’s Report (2013).DFO. Integrated Biological Status of Southern British Columbia Chinook Salmon (Oncorhynchus tshawytscha) Under the Wild Salmon Policy. DFO Can. Sci. Advis. Sec. Sci. Advis. Rep. 2016/042, 15 (2016).
    Google Scholar 
    COSEWIC. COSEWIC assessment and status report on the Chinook Salmon Oncorhynchus tshawytscha, Designatable Units in Southern British Columbia, in Canada. (2019).Pacific Salmon Commission Joint Chinook Technical Committee. Annual Report of Catch and Escapement for 2021. Tcchinook (13)-01 (2021).Quinn, T. P. Behavior and ecology of Pacific Salmon and trout. Fish Fish. 7, 75–76 (2004).
    Google Scholar 
    Brett, J. R. Energetics. In Phsyiological Ecology of Pacific Salmon (eds Groot, C. et al.) 1–68 (UBC Press, 1995).
    Google Scholar 
    Chamberlain, M. W. & Parken, C. Utilizing the Albion test fishery as an in-season predictor of run size of the Fraser River spring and summer age 52 Chinook. DFO Can. Sci. Advis. Sec. Res. Doc. 2012, 42 (2012).
    Google Scholar 
    Schoener, T. W. Theory of feeding strategies. Annu. Rev. Ecol. Syst. 2, 369–404 (1971).Article 

    Google Scholar 
    Williams, R. et al. Competing conservation objectives for predators and prey: Estimating Killer Whale prey requirements for Chinook Salmon. PLoS ONE 6, e26738 (2011).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Courtney, K. R., Falke, J. A., Cox, M. K. & Nichols, J. Energetic status of Alaskan Chinook Salmon: Interpopulation comparisons and predictive modeling using bioelectrical impedance analysis. North Am. J. Fish. Manag. https://doi.org/10.1002/nafm.10398 (2019).Article 

    Google Scholar 
    Pothoven, S. A. et al. Reliability of bioelectrical impedance analysis for estimating whole-fish energy density and percent lipids. Trans. Am. Fish. Soc. 137, 1519–1529 (2008).Article 

    Google Scholar 
    Crossin, G. T. & Hinch, S. G. A Nonlethal, rapid method for assessing the somatic energy content of migrating adult pacific salmon. Trans. Am. Fish. Soc. 134, 184–191 (2005).Article 

    Google Scholar 
    Colt, J. & Shearer, K. D. Evaluation of the Use of the Torry Fish Fatmeter to Non-Lethally Estimate Lipid in Adult Salmon (2001).Hanson, K. C., Ostrand, K. G., Gannam, A. L. & Ostrand, S. L. Comparison and validation of nonlethal techniques for estimating condition in Juvenile Salmonids. Trans. Am. Fish. Soc. 139, 1733–1741 (2010).Article 

    Google Scholar 
    Naughton, G., Caudill, C. & Clabough, T. Migration Behavior and Spawning Success of Spring Chinook Salmon in Fall Creek and the North Fork Middle Fork Willamette River: Relationship Among Fate, Fish Condition, and Environmental Factors, 2011. (2012).Folch, J., Lees, M. & Sloane Stanley, G. A simple method for the isolation and purification of total lipides from animal tissues. J. Biol. Chem. 226, 497–509 (1957).Article 
    CAS 
    PubMed 

    Google Scholar 
    Post, J. R. & Parkinson, E. A. Energy allocation strategy in young fish: Allometry and survival. Ecology 82, 1040–1051 (2001).Article 

    Google Scholar 
    Arrington, D. A., Davidson, B. K., Winemiller, K. O. & Layman, C. A. Influence of life history and seasonal hydrology on lipid storage in three neotropical fish species. J. Fish Biol. 68, 1347–1361 (2006).Article 
    CAS 

    Google Scholar 
    Holty, B. L. & Ciruna, K. A. Conservation units for Pacific Salmon under the Wild Salmon Policy. DFO Can. Sci. Advis. Sec. Res. Doc 2007/070, 350 (2007).
    Google Scholar 
    PSC. Catch and Escapement of Chinook Under Pacific Salmon Commission Jurisdiction, 2001 (PSC, 2002).
    Google Scholar 
    Waples, R. S., Teel, D. J., Myers, J. M. & Marshall, A. R. Life-history divergence in Chinook Salmon: Historic contingency and parallel evolution. Evolution 58, 386–403 (2004).PubMed 

    Google Scholar 
    Beacham, T. D. et al. Pacific rim population structure of chinook salmon as determined from microsatellite analysis. Trans. Am. Fish. Soc. 135, 1604–1621 (2006).Article 
    CAS 

    Google Scholar 
    Crossin, G. T. et al. Energetics and morphology of sockeye salmon: Effects of upriver migratory distance and elevation. J. Fish Biol. 65, 788–810 (2004).Article 

    Google Scholar 
    MacDonald, B. In-Season Forecasting of Fraser Chinook Salmon Using Genetic Stock Identification of Test Fishery Data By (2016).Parken, C. K., Candy, J. R., Irvine, J. R. & Beacham, T. D. Genetic and coded wire tag results combine to allow more-precise management of a complex Chinook salmon aggregate. North Am. J. Fish. Manag. 28, 328–340 (2008).Article 

    Google Scholar 
    Mann, R., Peery, C., Pinson, A. & Anderson, C. Energy use, migration times, and spawning success of adult spring–summer Chinook salmon returning to spawning areas in the South Fork Salmon River in Central Idaho: 2002–2007. Technical report 2009–4 http://www.cnr.uidaho.edu/uiferl/pdfreports/SFS_Tech_Report_2009-4_Final.pdf (2009).Hearsey, J. W. & Kinziger, A. P. Diversity in sympatric chinook salmon runs: Timing, relative fat content and maturation. Environ. Biol. Fishes 98, 413–423 (2015).Article 

    Google Scholar 
    Arimitsu, M. L. et al. Heatwave-induced synchrony within forage fish portfolio disrupts energy flow to top pelagic predators. Glob. Chang. Biol. 27, 1859–1878 (2021).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Lloret-Lloret, E. et al. Small pelagic fish fitness relates to local environmental conditions and trophic variables. Prog. Oceanogr. 202, 102745 (2022).Article 

    Google Scholar 
    Mesa, M. G. & Magie, C. D. Evaluation of energy expenditure in adult spring Chinook salmon migrating upstream in the Columbia River Basin: An assessment based on sequential proximate analysis. River Res. Appl. 22, 1085–1095 (2006).Article 

    Google Scholar 
    Crossin, G. T., Hinch, S. G., Farrell, A. P., Higgs, D. A. & Healey, M. C. Somatic energy of sockeye salmon Oncorhynchus nerka at the onset of upriver migration: A comparison among ocean climate regimes. Fish. Oceanogr. 13, 345–349 (2004).Article 

    Google Scholar 
    Roni, P. & Quinn, T. P. Geographic variation in size and age of North American Chinook salmon. North Am. J. Fish. Manag. 15, 325–345 (1995).Article 

    Google Scholar 
    Hendry, A. P., Berg, O. K., Quinn, T. P. & Condition, T. P. Condition dependence and adaptation-by-time: Breeding date, life history, and energy allocation within a population of salmon. Oikos 85, 499–514 (1999).Article 

    Google Scholar 
    Hanson, M. B. et al. Endangered predators and endangered prey: Seasonal diet of Southern Resident killer whales. PLoS ONE 16, e0247031 (2021).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Weitkamp, L. A. Marine distributions of Chinook Salmon from the West Coast of North America determined by coded wire tag recoveries. Trans. Am. Fish. Soc. 139, 147–170 (2010).Article 

    Google Scholar 
    Shields, M. W., Lindell, J. & Woodruff, J. Declining spring usage of core habitat by endangered fish-eating killer whales reflects decreased availability of their primary prey. Pac. Conserv. Biol. 24, 189–193 (2018).Article 

    Google Scholar 
    Brown, G. S. et al. Pre-COSEWIC review of southern British Columbia Chinook Salmon (Oncorhynchus tshawytscha) conservation units Part I: Background. Can. Sci. Advis. Sec. Res. Doc. 2019/11, 67 (2019).
    Google Scholar 
    NOAA Fisheries West Coast & Washington Department of Fish and Wildlife. Southern Resident Killer Whale Priority Chinook Stocks Report. https://www.westcoast.fisheries.noaa.gov/publications/protected_species/marine_mammals/killer_whales/recovery/srkw_priority_chinook_stocks_conceptual_model_report___list_22june2018.pdf (2018).Chalifour, L. et al. Chinook salmon exhibit long-term rearing and early marine growth in the fraser river, british columbia, a large urban estuary. Can. J. Fish. Aquat. Sci. 78, 539–550 (2021).Article 
    CAS 

    Google Scholar 
    Lamperth, J. S., Quinn, T. P. & Zimmerman, M. S. Levels of stored energy but not marine foraging patterns differentiate seasonal ecotypes of wild and hatchery steelhead (Oncorhynchus mykiss) returning to the Kalama river, Washington. Can. J. Fish. Aquat. Sci. 74, 157–167 (2017).Article 
    CAS 

    Google Scholar 
    Von Biela, V. R. et al. Extreme reduction in nutritional value of a key forage fish during the pacific marine heatwave of 2014–2016. Mar. Ecol. Prog. Ser. 613, 171–182 (2019).Article 
    ADS 

    Google Scholar 
    Healey, M. C. Life history of Chinook Salmon (Oncorhynchus tshawytscha). In Pacific Salmon Life Histories (eds Groot, C. & Margolis, L.) 313–393 (University of British Columbia Press, 1991).
    Google Scholar 
    Freshwater, C. et al. An integrated model of seasonal changes in stock composition and abundance with an application to Chinook salmon. PeerJ 9, 1–27 (2021).Article 

    Google Scholar 
    Couture, F., Oldford, G., Christensen, V., Barrett-lennard, L. & Walters, C. Requirements and availability of prey for northeastern pacific southern resident killer whales. PLoS ONE 17, e0270523 (2022).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    DFO. Government of Canada Takes Action to Address Fraser River Chinook Decline (DFO, 2019).
    Google Scholar 
    Brown, R. F. & Musgrave, M. M. Preliminary Catalogue of Salmon Steams and Escapements of Misson-Harrison Sub District. Fisheries and Marine Service Data Report No. 133 (1979).Manzon, C. I. & Marshall, D. E. Catalogue of salmon streams and spawning escapements of Cariboo subdistrict. Can. Data Rep. Fish. Aquat. Sci. 211, 51 (1980).
    Google Scholar 
    Marshall, D. E. & Manzon, C. I. Catalogue of Salmon Streams and Spawning Escapements of the Prince George Subdistrict (Department of Fisheries and Oceans Fisheries and Marine Services Data Report N0o. 79, 1980).
    Google Scholar 
    Olmsted, W., Whelen, M. & Stewart, R. 1980 Investigations of fall-spawning chinook salmon (Oncorhynchus tshawytscha), Quesnel, blackwater (west road) and cottonwood river drainages, B.C. 34, 131–134 (1981).Brown, R. F., Musgrave, M. M. & Marshall, D. E. Catalogue of salmon streams and spawning escapements for Kamloops sub-district. Fish. Mar. Serv. Data Rep. 151, 226 (1979).
    Google Scholar 
    DFO. Information Document to Assist Development of a Fraser Chinook Management Plan 56 (DFO, 2006).
    Google Scholar 
    Kosakoski, G. T. & Hamilton, R. E. Water Requirements for the Fisheries Resource of the Nicola River, B.C. Can. Manuscr. Rep. Fish. Aquat. Sci. 140 (1982). More

  • in

    An ankylosaur larynx provides insights for bird-like vocalization in non-avian dinosaurs

    Reilly, S. M. & Lauder, G. V. The evolution of tetrapod feeding behavior: kinematic homologies in prey transport. Evolution 44, 1542–1557 (1990).Article 

    Google Scholar 
    Iwasaki, S. Evolution of the structure and function of the vertebrate tongue. J. Anat. 201, 1–13 (2002).Article 

    Google Scholar 
    Fitch, W. T. & Suthers, R. A. In Vertebrate Sound Production and Acoustic Communication (eds Suthers, R. A., Fitch, W. T., Fay, R. R., & Popper, A. N.) 1–18 (Springer, 2016).Carroll, R. L. The Palaeozoic ancestry of salamanders, frogs and caecilians. Zool. J. Linn. Soc. 150, 1–140 (2007).Article 

    Google Scholar 
    Schwenk, K. in Feeding: Form, Function and Evolution in Tetrapod Vertebrates (ed. Schwenk, K.) 175–291 (Academic Press, 2000).Schwenk, K. & Rubega, M. In Physiological and ecological adaptations to feeding in vertebrates, (eds. Starck, M. & Wang, T.) 1–41 (Science Pub. Inc., 2005).Schumacher, G. H. In Biology of the Reptilia, 4 (ed Gans, C.) 101–200 (Academic Press, 1973).Reese, A. M. The laryngeal region of Alligator mississippiensis. Anat. Rec. 92, 273–277 (1945).Article 

    Google Scholar 
    Riede, T., Li, Z., Tokuda, I. & Farmer, C. G. Functional morphology of the Alligator mississippiensis larynx with implications for vocal production. J. Exp. Biol. 218, 991–998 (2015).Article 

    Google Scholar 
    McLelland, J. In Form and Function in Birds, 4 (eds King, A. S. & McLelland, J.) 69–103 (Academic Press, 1989).Homberger, D. G. In The Biology of the Avian Respiratory System (ed Maina, J. N.) 27–97 (Springer, 2017).Fitch, W. T. In Encyclopedia of Language & Linguistics (ed Brown, K.) 115–121 (Elsevier, 2006).Clarke, J. A. et al. Fossil evidence of the avian vocal organ from the Mesozoic. Nature 538, 502–505 (2016).Article 

    Google Scholar 
    Kingsley, E. P. et al. Identity and novelty in the avian syrinx. Proc. Natl Acad. Sci. USA 115, 10209–10217 (2018).Article 
    CAS 

    Google Scholar 
    Riede, T., Thomson, S. L., Titze, I. R. & Goller, F. The evolution of the syrinx: an acoustic theory. PLoS Biol. 17, e2006507 (2019).Nowicki, S. Vocal tract resonances in oscine bird sound production: evidence from birdsongs in a helium atmosphere. Nature 325, 53–55 (1987).Article 
    CAS 

    Google Scholar 
    Hill, R. V. et al. A complex hyobranchial apparatus in a Cretaceous dinosaur and the antiquity of avian paraglossalia. Zool. J. Linn. Soc. 175, 892–909 (2015).Article 

    Google Scholar 
    Li, Z. H., Zhou, Z. H. & Clarke, J. A. Convergent evolution of a mobile bony tongue in flighted dinosaurs and pterosaurs. PLoS One 13, e0198078 (2018).Article 

    Google Scholar 
    Bonaparte, J. F., Novas, F. E. & Coria, R. A. Carnotaurus sastrei Bonaparte, the horned, lightly built carnosaur from the Middle Cretaceous of Patagonia. Contrib. in Sci. Nat. Hist. Mus. L. A. 416, 1–42 (1990).Maryanska, T. Ankylosauridae (Dinosauria) from Mongolia. Palaeontol. Pol. 37, 85–151 (1977).
    Google Scholar 
    Mori, C. A comparative anatomical study on the laryngeal cartilages and laryngeal muscles of birds, and a developmental study on the larynx of the domestic fowl. Acta Med. 27, 2629–2678 (1957).
    Google Scholar 
    Siebenrock, F. Über den Kehlkopf und die Luftröhre der Schildkröten. Sitzungsberichte Der Kais. 108, 581–595 (1899).
    Google Scholar 
    Soley, J. T., Tivane, C. & Crole, M. R. Gross morphology and topographical relationships of the hyobranchial apparatus and laryngeal cartilages in the ostrich (Struthio camelus). Acta Zool. 96, 442–451 (2015).Article 

    Google Scholar 
    Olson, S. L. & Feduccia, A. Presbyornis and the origin of the Anseriformes (Aves: Charadriomorphae). Smithson. Contrib. Zool. 323, 1–24 (1980).Soley, J. T., Tivane, C. & Crole, M. R. A Gross morphology and topographical relationships of the hyobranchial apparatus and laryngeal cartilages in the ostrich (Struthio camelus). Acta Zool. 94, 442–451 (2015).Article 

    Google Scholar 
    Hogg, D. A. Ossification of the laryngeal, tracheal and syringeal cartilages in the domestic fowl. J. Anat. 134, 57–71 (1982).CAS 

    Google Scholar 
    Gaunt, A. S., Stein, R. C. & Gaunt, S. L. Pressure and air flow during distress calls of the starling, Sturnus vulgaris (Aves; Passeriformes). J. Exp. Zool. 183, 241–261 (1973).Article 

    Google Scholar 
    Sacchi, R., Galeotti, P., Fasola, M. & Gerzeli, G. Larynx morphology and sound production in three species of Testudinidae. J. Morphol. 261, 175–183 (2004).Article 

    Google Scholar 
    Titze, I. R. The physics of small-amplitude oscillation of the vocal folds. J. Acoust. Soc. Am. 83, 1536–1552 (1988).Article 
    CAS 

    Google Scholar 
    Russell, A. P., Hood, H. A. & Bauer, A. M. Laryngotracheal and cervical muscular anatomy in the genus Uroplatus (Gekkota: Gekkonidae) in relation to distress call emission. Afr. J. Herpetol. 63, 127–151 (2014).Article 

    Google Scholar 
    Russell, A. P., Rittenhouse, D. R. & Bauer, A. M. Laryngotracheal morphology of Afro‐Madagascan Geckos: a comparative survey. J. Morphol. 245, 241–268 (2000).Article 
    CAS 

    Google Scholar 
    Gans, C. & Maderson, P. F. Sound producing mechanisms in recent reptiles: review and comment. Am. Zool. 13, 1195–1203 (1973).Article 

    Google Scholar 
    Galeotti, P., Sacchi, R., Fasola, M. & Ballasina, D. Do mounting vocalisations in tortoises have a communication function? A comparative analysis. Herpetol. J. 15, 61–71 (2005).
    Google Scholar 
    Fletcher, N. H. Bird song—a quantitative acoustic model. J. Theor. Biol. 135, 455–481 (1988).Article 

    Google Scholar 
    Vergne, A. L., Pritz, M. B. & Mathevon, N. Acoustic communication in crocodilians: from behaviour to brain. Biol. Rev. 84, 391–411 (2009).Article 
    CAS 

    Google Scholar 
    Marler, P. R. & Slabbekoorn, H. Nature’s music: The science of birdsong (Academic Press, San Diego, USA, 2004).White, S. S. In Sisson and Grossman’s The Anatomy of the Domestic Animals. 2 (ed Getty, R.) 1891–1897 (Saunders, Philadelphia, USA 975).Kirchner, J. A. The vertebrate larynx: adaptations and aberrations. Laryngoscope 103, 1197–1201 (1993).Article 
    CAS 

    Google Scholar 
    Mackelprang, R. & Goller, F. Ventilation patterns of the songbird lung/air sac system during different behaviors. J. Exp. Biol. 216, 3611–3619 (2013).
    Google Scholar 
    Brocklehurst, R. J., Schachner, E. R. & Sellers, W. I. Vertebral morphometrics and lung structure in non-avian dinosaurs. R. Soc. Open Sci. 5, 180983 (2018).Article 

    Google Scholar 
    Cerda, I. A., Salgado, L. & Powell, J. E. Extreme postcranial pneumaticity in sauropod dinosaurs from South America. Paläontol. Z. 86, 441–449 (2012).Article 

    Google Scholar 
    Sereno, P. C. et al. Evidence for avian intrathoracic air sacs in a new predatory dinosaur from Argentina. PLoS One 3, e3303 (2008).Chiari, Y., Cahais, V., Galtier, N. & Delsuc, F. Phylogenomic analyses support the position of turtles as the sister group of birds and crocodiles (Archosauria). BMC Biol. 10, 65 (2012).Article 

    Google Scholar  More