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    Influence of suspended inorganic particles (kaolinite) on eggs and larvae of the pelagic shrimp Lucensosergia lucens

    Uchida, H. & Baba, O. Fishery management and the pooling arrangement in the Sakura ebi fishery in Japan, 175–189. https://www.fao.org/3/a1497e/a1497e16.pdf (2008).Omori, M. The biology of a sergestid shrimp Sergestes lucens Hansen. Bull. Ocean Res. Inst. Univ. Tokyo 4, 1–83 (1969).
    Google Scholar 
    Gurney, R. & Lebour, M. V. Larvae of decapod crustacea. Part VI. The genus Sergestes. Discov. Rep. 20, 1–68 (1940).
    Google Scholar 
    Holthuis, L. B. FAO species catalogue. Vol. 1. Shrimps and prawns of the world. An annotated catalogue of species of interest to fisheries. FAO Fish. Synop. Vol. 125, 1–271 (1980).Omori, M., Ukishima, Y. & Muranaka, F. New record of occurrence of Sergia lucens (Hansen) (Crustacea, Sergestidae) off Tung-kang, Taiwan, with special reference to phylogeny and distribution of the species. J. Oceanogr. Soc. Jpn. 44, 261–267 (1988) (in Japanese with English abstract).Article 

    Google Scholar 
    Isshiki, T. & Tajima, Y. The research of a sergestid shrimp, Sergia lucens (Hansen) in the mouth of Tokyo Bay I. The seasonal distribution of adult and the distribution of eggs. Bull. Kanagawa Pref. Fish. Exp. Stn. 13, 73–78 (1992) (in Japanese with English abstract).
    Google Scholar 
    Lee, D. A., Wu, S. H., Liao, I. C. & Yu, H. P. On three species of commercially important sergestid shrimps (Decapoda: Sergestidae) in the coastal waters of Taiwan. J. Taiwan Fish. Res. Inst. 4, 1–19 (1996) (in Chinese with English abstract).CAS 

    Google Scholar 
    Yinji, L. & Ratana, C. Governing in an uncertain time: The case of Sakura shrimp fishery, Japan. Marit. Stud. 20, 115–126 (2021).Article 

    Google Scholar 
    Isono, R. S., Kita, J. & Setoguma, T. Acute effects of kaolinite suspension on eggs and larvae of some marine teleosts. Comp. Biochem. Physiol. Part C 120, 449–455 (1998).CAS 
    Article 

    Google Scholar 
    Aoki, S. & Oinuma, K. Distribution of clay minerals in surface sediments of Suruga Bay, central Japan. J. Geol. Soc. Jpn. 87(7), 429–438 (1981) (in Japanese with English abstract).Article 

    Google Scholar 
    Nasnodkar, M. R. & Ganapati, N. N. Clay mineralogy and chemistry of mudflat core sediments from Sharavathi and Gurupur estuaries: Source and processes. Indian J. Geo-Mar. Sci. 48(3), 379–388 (2019).
    Google Scholar 
    Capper, N. The effects of suspended sediment on the aquatic organisms Daphnia magna and Pimephales promelas. All Theses. 2. https://tigerprints.clemson.edu/all_theses/2 (2006).Boyd, M. B. et al. Disposal of dredge spoil, problem identification and assessment and research program development. Technical report H-72–8, U.S. army engineer waterways experiment station, CE, Vicksburg, Miss. (1972).McFarland, V. A. & Peddicord, R. K. Lethality of a suspended clay to a diverse selection of marine and estuarine macrofauna. Arch. Environ. Contam. Toxicol. 9, 733–741 (1980).CAS 
    Article 

    Google Scholar 
    Arakawa, H. et al. The influence of suspended particles on larval development in the Manila clam Ruditapes philippinarum. Sci. Postp. 1, e00028. https://doi.org/10.14340/spp.2014.08A0002 (2014).Article 

    Google Scholar 
    Davis, H. C. Effects of turbidity-producing materials in sea water on eggs and larvae of the clam (Venus (Mercenaria) mercenaria). Biol. Bull. 118, 48–54 (1960).Article 

    Google Scholar 
    Tabata, A., Morinaga, T. & Arakawa, H. Influences of concentration, particle-size and kind of inorganic suspended matter on feed caught by Manila clam, Ruditapes philippinarum. La Mer 37, 163–171 (2000).CAS 

    Google Scholar 
    Annisa, Dwiatmoko, M. U., Saismana, U. & Maulanai, R. Characteristics of kaolin clay on Alluvial formation subdistrict mataraman based on physical properties and chemical properties. In MATEC Web of Conferences Vol. 280, 03009. https://doi.org/10.1051/matecconf/201928003009 (2019).Murray, H. H. Structure and composition of clay minerals and their physical and chemical properties. Dev. Clay Sci. 2, 7–31. https://doi.org/10.1016/S1572-4352(06)02002-2 (2006).Article 

    Google Scholar 
    Kumari, N. & Mohan, C. Basics of clay minerals and their characteristic properties. Clay Clay Miner. 1–29 (2021).Lively, J. S., Kaufman, Z. & Carpenter, E. J. Phytoplankton ecology of a barrier island estuary: Great South Bay, New York. Estuar. Coast. Shelf Sci. 16(1), 51–68 (1983).ADS 
    Article 

    Google Scholar 
    Lloyd, D. S. Turbidity as a water quality standard for salmonid habitats in Alaska. N. Am. J. Fish. Manag. 7, 34–45 (1987).Article 

    Google Scholar 
    Kirk, K. L. Effects of suspended clay on Daphnia body growth and fitness. Freshw. Biol. 28, 103–109 (1992).Article 

    Google Scholar 
    McCabe, G. D. & O’Brien, W. J. The effects of suspended silt on feeding and reproduction of Daphnia pulex. Am. Midl. Nat. 110, 324–337 (1983).Article 

    Google Scholar 
    Kirk, K. L. & Gilbert, J. J. Suspended clay and the population dynamics of planktonic Rotifers and Cladocerans. Ecology 71, 1741–1755 (1990).Article 

    Google Scholar 
    Loosanoff, V. L. Effects of turbidity on some larval and adult bivalves. Proc. Gulf. Carib. Fish. Inst. 14, 80–95 (1961).
    Google Scholar 
    Arruda, J. A., Marzolf, G. R. & Faulk, R. T. The role of suspended sediments in the nutrition of zooplankton in turbid reservoirs. Ecology 64, 1225–1235 (1983).Article 

    Google Scholar 
    Kathyayani, S. A., Muralidhar, M., Kumar, T. S. & Alavandi, S. V. Stress quantification in Penaeus vannamei exposed to varying levels of turbidity. J. Coast. Res. 86, 177–183 (2019).CAS 
    Article 

    Google Scholar 
    Wilber, D. H. & Clarke, D. G. Biological effects of suspended sediments: A review of suspended sediment impacts on fish and shellfish with relation to dredging activities in estuaries. N. Am. J. Fish. Manag. 21, 855–875 (2001).Article 

    Google Scholar 
    Lin, H., Charmantier, G., Thuet, P. & Trilles, J. Effects of turbidity on survival, osmoregulation, and gill Na+-K+ ATPase in juvenile shrimp Penaeus japonicus. Mar. Ecol. Prog. Ser. 90, 31–37 (1992).ADS 
    CAS 
    Article 

    Google Scholar 
    Davis, H. C. & Hidu, H. Effects of turbidity-producing substances in sea water on eggs and larvae of three genera of bivalve mollusks. Veliger 11, 316–323 (1969).
    Google Scholar 
    Nimmo, D. R., Hamaker, T. L., Matthews, E. & Young, W. T. The long-term effects of suspended particulates on survival and reproduction of the mysid shrimp, Mysidopsis bahia, in the laboratory. In Proceedings of a Symposium on the Ecological Effects of Environmental Stress, New York, 413–422 (1979).Peddicord, R. & McFarland, V. Effects of suspended dredged material on the commercial crab, Cancer magister. In Proceedings of the Specialty Conference on Dredging and Its Environmental Effects, Mobile, Alabama, 633–644 (1976).Peddicord, R. K. Direct Effects of Suspended Sediments on Aquatic Organisms. Contaminants and Sediments. Volume 1. Fate and Transport, Case Studies, Modeling, Toxicity 501–536 (Ann Arbor Science Publishers, 1980).
    Google Scholar 
    Wakeman, T., Peddicord, R. & Sustar, J. Effects of suspended solids associated with dredging operations on estuarine organisms. In Ocean 75 conference, 431–436 (1975).Gebauer, P., Walter, I. & Anger, K. Effects of substratum and conspecific adults on the metamorphosis of Chasmagnathus granulata (Dana) (Decapoda: Grapsidae) megalopae. J. Exp. Mar. Biol. Ecol. 223, 185–198 (1998).Article 

    Google Scholar 
    Carvalho, L. & Calado, R. Trade-offs between timing of metamorphosis and grow out performance of a marine caridean shrimp juveniles and its relevance for aquaculture. Aquaculture 492, 97–102 (2018).Article 

    Google Scholar 
    Calado, R. et al. The physiological consequences of delaying metamorphosis in the marine ornamental shrimp Lysmata seticaudata and its implications for aquaculture. Aquaculture 546, 737391. https://doi.org/10.1016/j.aquaculture.2021.737391 (2022).Article 

    Google Scholar 
    Murphy, R. C. Factors affecting the distribution of the introduced bivalve, Mercenaria mercenaria, in a California lagoon—The importance of bioturbation. J. Mar. Res. 43, 673–692 (1985).Article 

    Google Scholar 
    Bricelj, V. M. & Malouf, R. E. Influence of algal and suspended sediment concentration on the feeding physiology of the hard clam Mercenaria mercenaria. Mar. Biol. 84, 155–165 (1984).Article 

    Google Scholar 
    Wenger, A. S., Jacob, J. L. & Jones, G. P. Increasing suspended sediment reduces foraging, growth, and condition of a planktivorous damselfish. J. Exp. Mar. Biol. Ecol. 428, 43–48 (2012).Article 

    Google Scholar 
    Robinson, W. E., Wehling, W. E. & Morse, M. P. The effect of suspended clay on feeding and digestive efficiency of the surf clam Spisula solidissima (Dillwyn). J. Exp. Mar. Biol. Ecol. 74, 1–12 (1984).CAS 
    Article 

    Google Scholar 
    Turner, E. J. & Miller, D. C. Behavior and growth of Mercenaria mercenaria during simulated storm events. Mar. Biol. 111, 55–64 (1991).Article 

    Google Scholar 
    Grant, J. & Thorpe, B. Effects of suspended sediment on growth, respiration, and excretion of the soft-shelled clam (Mya arenaria). Can. J. Fish. Aquat. Sci. 48, 1285–1292 (1991).Article 

    Google Scholar 
    Gleason, R. A., Euliss, N. H., Hubbard, D. E. & Duffy, W. G. Effects of sediment load on emergence of aquatic invertebrates and plants from wetland soil egg and seed banks. Wetlands 23, 26–34 (2003).Article 

    Google Scholar 
    Jacek, R., Anna, S. & Miroslaw, S. The effect of lake sediment on the hatching success of Daphnia ephippial eggs. J. Limnol. 75, 597–605 (2016).
    Google Scholar 
    Newcombe, C. P. & McDonald, D. D. Effects of suspended sediment on aquatic ecosystems. N. Am. J. Fish. Manag. 11, 77–82 (1991).Article 

    Google Scholar 
    Chutter, F. M. The effects of silt and sand on the invertebrate fauna of streams and rivers. Hydrobiologia 34, 57–76 (1968).Article 

    Google Scholar 
    Hellawell, J. M. Biological indicators of freshwater pollution and environmental management. In Pollution Monitoring Series (ed. Melanby, K.) https://doi.org/10.1007/978-94-009-4315-5 (1986).Makita, M. & Kondo, M. Rearing of the larvae of Seigia Lucens (Hansen). Bull. Shizuoka Pref. Fish. Exp. Stn. 16, 97–105 (1982) (in Japanese).
    Google Scholar  More

  • in

    Ecosystem size-induced environmental fluctuations affect the temporal dynamics of community assembly mechanisms

    Vellend M. Conceptual synthesis in community ecology. Q Rev Biol. 2010;85:183–206.PubMed 

    Google Scholar 
    Leibold MA. Chase JM Metacommunity Ecology. Levin SA, Horn HS, editors: Princeton University Press, Princeton; 2018.Logue JB, Mouquet N, Peter H, Hillebrand H, Declerck P, Flohre A, et al. Empirical approaches to metacommunities: A review and comparison with theory. Trends Ecol Evol. 2011;26:482–91.PubMed 

    Google Scholar 
    Hanson CA, Fuhrman JA, Horner-Devine MC, Martiny JB. Beyond biogeographic patterns: Processes shaping the microbial landscape. Nat Rev Microbiol. 2012;10:497–506.CAS 
    PubMed 

    Google Scholar 
    Lindström ES, Langenheder S. Local and regional factors influencing bacterial community assembly. Environ Microbiol Rep. 2012;4:1–9.PubMed 

    Google Scholar 
    Langenheder S, Lindström ES. Factors influencing aquatic and terrestrial bacterial community assembly. Environ Microbiol Rep. 2019;11:306–15.PubMed 

    Google Scholar 
    Leibold MA, Holyoak M, Mouquet N, Amarasekare P, Chase JM, Hoopes MF, et al. The metacommunity concept: A framework for multi-scale community ecology. Ecol Lett. 2004;7:601–13.
    Google Scholar 
    Vass M, Langenheder S. The legacy of the past: Effects of historical processes on microbial metacommunities. Aquat Micro Ecol. 2017;79:13–9.
    Google Scholar 
    Fukami T. Historical contingency in community assembly: Integrating niches, species pools, and priority effects. Annu Rev Ecol Evol Syst. 2015;46:1–23.
    Google Scholar 
    Dini-Andreote F, Stegen JC, van Elsas JD, Salles JF. Disentangling mechanisms that mediate the balance between stochastic and deterministic processes in microbial succession. Proc Natl Acad Sci. 2015;112:E1326–32.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Zhang FG, Zhang QG. Patterns in species persistence and biomass production in soil microcosms recovering from a disturbance reject a neutral hypothesis for bacterial community assembly. PLoS One. 2015;10:e0126962.PubMed 
    PubMed Central 

    Google Scholar 
    Zhou J, Deng Y, Zhang P, Xue K, Liang Y, Van Nostrand JD, et al. Stochasticity, succession, and environmental perturbations in a fluidic ecosystem. Proc Natl Acad Sci. 2014;111:E836–45.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ferrenberg S, O’Neill SP, Knelman JE, Todd B, Duggan S, Bradley D, et al. Changes in assembly processes in soil bacterial communities following a wildfire disturbance. ISME J. 2013;7:1102–11.PubMed 
    PubMed Central 

    Google Scholar 
    Jiang L, Morin PJ. Temperature fluctuation facilitates coexistence of competing species in experimental microbial communities. J Anim Ecol. 2007;76:660–8.PubMed 

    Google Scholar 
    Tucker CM, Fukami T. Environmental variability counteracts priority effects to facilitate species coexistence: evidence from nectar microbes. Proc Biol Sci. 2014;281:20132637.PubMed 
    PubMed Central 

    Google Scholar 
    Grainger TN, Letten AD, Gilbert B, Fukami T. Applying modern coexistence theory to priority effects. Proc Natl Acad Sci. 2019;116:6205–10.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Jiang L, Patel SN. Community assembly in the presence of disturbance: A microcosm experiment. Ecology 2008;89:1931–40.PubMed 

    Google Scholar 
    Loeuille N, Leibold MA. Evolution in metacommunities: On the relative importance of species sorting and monopolization in structuring communities. Am Nat. 2008;171:788–99.PubMed 

    Google Scholar 
    Shade A, Jones SE, McMahon KD. The influence of habitat heterogeneity on freshwater bacterial community composition and dynamics. Environ Microbiol. 2008;10:1057–67.CAS 
    PubMed 

    Google Scholar 
    Pereira CL, Araújo MB, Matias MG. Interplay between productivity and regional species pool determines community assembly in aquatic microcosms. Aquat Sci. 2018;80:45.
    Google Scholar 
    Herlemann DP, Labrenz M, Jürgens K, Bertilsson S, Waniek JJ, Andersson AF. Transitions in bacterial communities along the 2000 km salinity gradient of the Baltic Sea. ISME J. 2011;5:1571–9.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Neubauer SC, Piehler MF, Smyth AR, Franklin RB. Saltwater intrusion modifies microbial community structure and decreases denitrification in tidal freshwater marshes. Ecosystems. 2018;22:912–28.
    Google Scholar 
    Rath KM, Fierer N, Murphy DV, Rousk J. Linking bacterial community composition to soil salinity along environmental gradients. ISME J. 2019;13:836–46.CAS 
    PubMed 

    Google Scholar 
    Tang X, Xie G, Shao K, Tian W, Gao G, Qin B. Aquatic bacterial diversity, community composition and assembly in the semi-arid Inner Mongolia Plateau: combined effects of salinity and nutrient levels. Microorganisms. 2021;9:208.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Xia LC, Steele JA, Cram JA, Cardon ZG, Simmons SL, Vallino JJ, et al. Extended local similarity analysis (eLSA) of microbial community and other time series data with replicates. BMC Syst Biol. 2011;5:S15.PubMed 
    PubMed Central 

    Google Scholar 
    Langenheder S, Comte J, Zha Y, Samad MS, Sinclair L, Eiler A, et al. Remnants of marine bacterial communities can be retrieved from deep sediments in lakes of marine origin. Environ Microbiol Rep. 2016;8:479–85.CAS 
    PubMed 

    Google Scholar 
    Comte J, Lindström ES, Eiler A, Langenheder S. Can marine bacteria be recruited from freshwater sources and the air? ISME J. 2014;8:2423–30.PubMed 
    PubMed Central 

    Google Scholar 
    Comte J, Langenheder S, Berga M, Lindström ES. Contribution of different dispersal sources to the metabolic response of lake bacterioplankton following a salinity change. Environ Microbiol. 2017;19:251–60.CAS 
    PubMed 

    Google Scholar 
    Langenheder S, Ragnarsson H. The role of environmental and spatial factors for the composition of aquatic bacterial communities. Ecology 2007;88:2154–61.PubMed 

    Google Scholar 
    del Giorgio PA, Bird DF, Prairie YT, Planas D. Flow cytometric determination of bacterial abundance in lakeplankton with the green nucleid acid stain SYTO 13. Limnol Oceanogr. 1996;41:783–9.
    Google Scholar 
    Blazewicz SJ, Barnard RL, Daly RA, Firestone MK. Evaluating rRNA as an indicator of microbial activity in environmental communities: Limitations and uses. ISME J. 2013;7:2061–8.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Székely AJ, Berga M, Langenheder S. Mechanisms determining the fate of dispersed bacterial communities in new environments. ISME J. 2013;7:61–71.PubMed 

    Google Scholar 
    Apprill A, McNally S, Parsons R, Weber L. Minor revision to V4 region SSU rRNA 806R gene primer greatly increases detection of SAR11 bacterioplankton. Aquat Micro Ecol. 2015;75:129–37.
    Google Scholar 
    Hugerth LW, Wefer HA, Lundin S, Jakobsson HE, Lindberg M, Rodin S, et al. DegePrime, a program for degenerate primer design for broad- taxonomic-range PCR in microbial ecology studies. Appl Environ Microbiol. 2014;80:5116–23.PubMed 
    PubMed Central 

    Google Scholar 
    Martin M. Cutadapt removes adapter sequences from high- throughput sequencing reads. EMBnet J. 2011;17:10–2.
    Google Scholar 
    Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJ, Holmes SP. DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods. 2016;13:581–3.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 2013;41:D590–6.CAS 
    PubMed 

    Google Scholar 
    Chao A, Jost L. Coverage-based rarefaction and extrapolation: standardizing samples by completeness rather than size. Ecology 2012;93:2533–47.PubMed 

    Google Scholar 
    McMurdie PJ, Holmes S. phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS One. 2013;8:e61217.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    R-Core-Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2020.Oksanen J, Blanchet FG, Friendly M, Kindt R, Legendre P, McGlinn D, et al. Vegan: Community Ecology Package. R package version 2.5-7. ed 2020.Bier RL Field and chemistry data from 2016 Fluctuations Project Data sets. In: DiVA, editor. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-3517382016.Noguchi K, Gel YR, Brunner E, Konietschke F. nparLD: An R software package for the nonparametric analysis of longitudinal data in factorial experiments. J Stat Softw. 2012;50:1–23.
    Google Scholar 
    Willis A, Martin BD, Trinh P, Teichman S, Barger K, Bunge J. Breakaway: Species Richness Estimation and Modeling. R package version 4.7.3. ed. 2020.Baselga A, Orme D, Villeger S, De Bortoli J, Leprieur F, Logez M. Betapart: Partitioning beta diversity into turnover and nestedness components. R package version 1.5.2 ed. 2020.Anderson MJ. Permutational multivariate analysis of variance (PERMANOVA). In: Balakrishnan N, Colton T, Everitt B, Piegorsch W, Ruggeri F, Teugels JL, editors. Wiley StatsRef: Statistics Reference Online: John Wiley & Sons, Inc; 2017. p. 1–15.Jabot F, Laroche F, Massol F, Arthaud F, Crabot J, Dubart M, et al. Assessing metacommunity processes through signatures in spatiotemporal turnover of community composition. Ecol Lett. 2020;23:1330–9.PubMed 

    Google Scholar 
    Rosseel Y. Lavaan: An R Package for Structural Equation Modeling. J Stat Softw. 2012;48:1–36.
    Google Scholar 
    Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al. Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13:2498–504.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Assenov Y, Ramirez F, Schelhorn SE, Lengauer T, Albrecht M. Computing topological parameters of biological networks. Bioinformatics 2008;24:282–4.CAS 
    PubMed 

    Google Scholar 
    Drake JA. Community-assembly mechanics and the structure of an experimental species ensemble. Am Nat. 1991;137:1–26.
    Google Scholar 
    Orrock JL, Fletcher RL Jr. Changes in community size affect the outcome of competition. Am Nat. 2005;166:107–11.PubMed 

    Google Scholar 
    Fukami T. Community assembly along a species pool gradient: implications for multiple‐scale patterns of species diversity. Popul Ecol. 2004;46:137–47.
    Google Scholar 
    Lozupone CA, Hamady M, Kelley ST, Knight R. Quantitative and qualitative beta diversity measures lead to different insights into factors that structure microbial communities. Appl Environ Microbiol. 2007;73:1576–85.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Werba JA, Stucy AL, Peralta AL, McCoy MW. Effects of diversity and coalescence of species assemblages on ecosystem function at the margins of an environmental shift. PeerJ. 2020;8:e8608.PubMed 
    PubMed Central 

    Google Scholar 
    Logares R, Brate J, Bertilsson S, Clasen JL, Shalchian-Tabrizi K, Rengefors K. Infrequent marine-freshwater transitions in the microbial world. Trends Microbiol. 2009;17:414–22.CAS 
    PubMed 

    Google Scholar 
    Logares R, Lindström ES, Langenheder S, Logue JB, Paterson H, Laybourn-Parry J, et al. Biogeography of bacterial communities exposed to progressive long-term environmental change. ISME J. 2013;7:937–48.CAS 
    PubMed 

    Google Scholar 
    Muylaert K, Van Der Gucht K, Vloemans N, Meester LD, Gillis M, Vyverman W. Relationship between bacterial community composition and bottom-up versus top-down variables in four eutrophic shallow lakes. Appl Environ Microbiol. 2002;68:4740–50.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Lee AM, Sæther B-E, Engen S. Spatial covariation of competing species in a fluctuating environment. Ecology 2020;101:e02901.PubMed 

    Google Scholar 
    Liu J, Fu B, Yang H, Zhao M, He B, Zhang XH. Phylogenetic shifts of bacterioplankton community composition along the Pearl Estuary: the potential impact of hypoxia and nutrients. Front Microbiol. 2015;6:64.PubMed 
    PubMed Central 

    Google Scholar 
    Guiry MD, Guiry GM. AlgaeBase. World-wide electronic publication: National University of Ireland, Galway; 2022.Shade A, Jones SE, Caporaso JG, Handelsman J, Knight R, Fierer N, et al. Conditionally rare taxa disproportionately contribute to temporal changes in microbial diversity. mBio 2014;5:e01371–14.PubMed 
    PubMed Central 

    Google Scholar 
    Andersson MGI, Berga M, Lindström ES, Langenheder S. The spatial structure of bacterial communities is influenced by historical environmental conditions. Ecology 2014;95:1134–40.PubMed 

    Google Scholar 
    Ai D, Gravel D, Chu C, Wang G. Spatial structures of the environment and of dispersal impact species distribution in competitive metacommunities. PLoS One. 2013;8:e68927.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Maloufi S, Catherine A, Mouillot D, Louvard C, Couté A, Bernard C, et al. Environmental heterogeneity among lakes promotes hyper β-diversity across phytoplankton communities. Freshw Biol. 2016;61:633–45.
    Google Scholar 
    Firkowski CR, Thompson PL, Gonzalez A, Cadotte MW, Fortin M-J. Multi-trophic metacommunity interactions mediate asynchrony and stability in fluctuating environments. Ecol Monogr. n/a:e1484.Lennon JT, Jones SE. Microbial seed banks: The ecological and evolutionary implications of dormancy. Nat Rev Microbiol. 2011;9:119–30.CAS 
    PubMed 

    Google Scholar 
    Knope ML, Forde SE, Fukami T. Evolutionary history, immigration history, and the extent of diversification in community assembly. Front Microbiol. 2011;2:273.PubMed 

    Google Scholar 
    Fukami T. Assembly history interacts with ecosystem size to influence species diversity. Ecology 2004;85:3234–42.
    Google Scholar 
    Orrock JL, Watling JI. Local community size mediates ecological drift and competition in metacommunities. Proc Biol Sci. 2010;277:2185–91.PubMed 
    PubMed Central 

    Google Scholar 
    Chase JM. Community assembly: When should history matter? Oecologia 2003;136:489–98.PubMed 

    Google Scholar 
    Ron R, Fragman-Sapir O, Kadmon R. Dispersal increases ecological selection by increasing effective community size. Proc Natl Acad Sci. 2018;115:11280–5.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Siqueira T, Saito VS, Bini LM, Melo AS, Petsch DK, Landeiro VL, et al. Community size can affect the signals of ecological drift and niche selection on biodiversity. Ecology 2020;101:e03014.PubMed 

    Google Scholar 
    Vass M, Székely AJ, Lindström ES, Langenheder S. Using null models to compare bacterial and microeukaryotic metacommunity assembly under shifting environmental conditions. Sci Rep. 2020;10:2455.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Shen D, Langenheder S, Jürgens K. Dispersal modifies the diversity and composition of active bacterial communities in response to a salinity disturbance. Front Microbiol. 2018;9:2188.PubMed 
    PubMed Central 

    Google Scholar 
    Cunze S, Heydel F, Tackenberg O. Are plant species able to keep pace with the rapidly changing climate? PLoS One. 2013;8:e67909.CAS 
    PubMed 
    PubMed Central 

    Google Scholar  More

  • in

    Feeding ecology of the endangered Asiatic wild dogs (Cuon alpinus) across tropical forests of the Central Indian Landscape

    Floyd, T. J., Mech, L. D. & Jordan, P. A. Relating wolf scat content to prey consumed. J. Wildl. Manag. 42, 528 (1978).Article 

    Google Scholar 
    Ackerman, B. B., Lindzey, F. G. & Hemker, T. P. Cougar food habits in Southern Utah. J. Wildl. Manag. 48, 147 (1984).Article 

    Google Scholar 
    Carbone, C., Mace, G. M., Roberts, S. C. & Macdonald, D. W. Energetic constraints on the diet of terrestrial carnivores. Nature 402, 286–288 (1999).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Klare, U., Kamler, J. F. & Macdonald, D. W. A comparison and critique of different scat-analysis methods for determining carnivore diet: Comparison of scat-analysis methods. Mammal Rev. 41, 294–312 (2011).Article 

    Google Scholar 
    Hatton, I. A. et al. The predator-prey power law: Biomass scaling across terrestrial and aquatic biomes. Science 349, aac6284 (2015).PubMed 
    Article 
    CAS 

    Google Scholar 
    Monterroso, P. et al. Feeding ecological knowledge: The underutilised power of faecal DNA approaches for carnivore diet analysis. Mammal Rev. 49, 97–112 (2019).Article 

    Google Scholar 
    Hayward, M. W., O’Brien, J., Hofmeyr, M. & Kerley, G. I. H. Prey preferences of the African wild dog Lycaon Pictus (Canidae: Carnivora): Ecological requirements for conservation. J. Mammal. 87, 1122–1131 (2006).Article 

    Google Scholar 
    Crawford, K., Mcdonald, R. A. & Bearhop, S. Applications of stable isotope techniques to the ecology of mammals. Mammal Rev. 38, 87–107 (2008).Article 

    Google Scholar 
    Crossey, B., Chimimba, C., du Plessis, C., Ganswindt, A. & Hall, G. African wild dogs ( Lycaon pictus ) show differences in diet composition across landscape types in Kruger National Park, South Africa. J. Mammal. 102, 1211–1221 (2021).Article 

    Google Scholar 
    Ceballos, G. & Ehrlich, P. R. Mammal population losses and the extinction crisis. Science 296, 904–907 (2002).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Treves, A. & Karanth, K. U. Human-carnivore conflict and perspectives on carnivore management worldwide. Conserv. Biol. 17, 1491–1499 (2003).Article 

    Google Scholar 
    Swihart, R. K., Gehring, T. M., Kolozsvary, M. B. & Nupp, T. E. Responses of ‘resistant’ vertebrates to habitat loss and fragmentation: The importance of niche breadth and range boundaries. Divers. Distrib. 9, 1–18 (2003).Article 

    Google Scholar 
    Kamler, J. F. et al. Cuon alpinus. IUCN Red List Threat. Spec. https://doi.org/10.2305/IUCN.UK.2015-4.RLTS.T5953A72477893.en (2015).Article 

    Google Scholar 
    Johnsingh, A. J. T. Distribution and status of dhole Cuon alpinus Pallas, 1811 in South Asia. Mammalia 49, (1985).Acharya, B. B. Dissertation submitted to Saurashtra University, Rajkot, Gujarat, for the award of the Degree of Doctor of Philosophy in Wildlife Science. 133.Sillero-Zubiri, E. C., Hoffmann, M. & Macdonald, D. W. Canids: Foxes, Wolves, Jackals and Dogs. 443.Wolf, C. & Ripple, W. J. Range contractions of the world’s large carnivores. R. Soc. Open Sci. 4, 170052 (2017).ADS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Karanth, K. K., Nichols, J. D., Karanth, K. U., Hines, J. E. & Christensen, N. L. The shrinking ark: Patterns of large mammal extinctions in India. Proc. R. Soc. B Biol. Sci. 277, 1971–1979 (2010).Article 

    Google Scholar 
    Srivathsa, A., Karanth, K. K., Jathanna, D., Kumar, N. S. & Karanth, K. U. On a dhole trail: Examining ecological and anthropogenic correlates of dhole habitat occupancy in the Western Ghats of India. PLoS ONE 9, e98803 (2014).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Newsome, T. M. & Ripple, W. J. A continental scale trophic cascade from wolves through coyotes to foxes. J. Anim. Ecol. 84, 49–59 (2015).PubMed 
    Article 

    Google Scholar 
    Fleming, P. J. S. et al. Roles for the Canidae in food webs reviewed: Where do they fit?. Food Webs 12, 14–34 (2017).Article 

    Google Scholar 
    Van Valkenburgh, B. Iterative evolution of hypercarnivory in canids (Mammalia: Carnivora): Evolutionary interactions among sympatric predators. Paleobiology 17, 340–362 (1991).Article 

    Google Scholar 
    Clements, H. S., Tambling, C. J., Hayward, M. W. & Kerley, G. I. H. An objective approach to determining the weight ranges of prey preferred by and accessible to the five large african carnivores. PLoS ONE 9, e101054 (2014).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Hayward, M. W., Lyngdoh, S. & Habib, B. Diet and prey preferences of dholes ( C uon alpinus ): Dietary competition within A sia’s apex predator guild. J. Zool. 294, 255–266 (2014).Article 

    Google Scholar 
    Srivathsa, A., Sharma, S. & Oli, M. K. Every dog has its prey: Range-wide assessment of links between diet patterns, livestock depredation and human interactions for an endangered carnivore. Sci. Total Environ. 714, 136798 (2020).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Cohen, J. A. Cuon alpinus. Mamm. Spec. https://doi.org/10.2307/3503800 (1978).Article 

    Google Scholar 
    Srivathsa, A., Sharma, S., Singh, P., Punjabi, G. A. & Oli, M. K. A strategic road map for conserving the Endangered dhole Cuon alpinus in India. Mammal Rev. 50, 399–412 (2020).Article 

    Google Scholar 
    Ghaskadbi, P., Nigam, P. & Habib, B. Stranger Danger: Differential response to strangers and neighbors by a social carnivore, the Asiatic wild dog (Cuon alpinus). Behav. Ecol. Sociobiol. 76, 86. https://doi.org/10.1007/s00265-022-03188-4 (2022). Article 

    Google Scholar 
    Ghaskadbi, P., Das, J., Mahadev, V. & Habib, B. First record of mixed species association between dholes and a wolf from Satpura Tiger Reserve, India. Canid Biol. Conserv. 23(4): 15–17. http://www.canids.org/CBC/23/Dhole_wolf_association.pdf (2021).Wachter, B. et al. An advanced method to assess the diet of free-ranging large carnivores based on scats. PLoS ONE 7, e38066 (2012).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Edgaonkar, A. Satpura National Park, India. 135.Borah, J., Deka, K., Dookia, S. & Gupta, R. P. Food habits of dholes (Cuon alpinus) in Satpura Tiger Reserve. Madhya Pradesh, India. 73, 85–88 (2009).
    Google Scholar 
    Karanth, K. U. & Sunquist, M. E. Behavioural correlates of predation by tiger ( Panthera tigris ), leopard ( Panthera pardus ) and dhole ( Cuon alpinus ) in Nagarahole, India. J. Zool. 250, 255–265 (2000).Article 

    Google Scholar 
    Krishna, Y. C., Clyne, P. J., Krishnaswamy, J. & Kumar, N. S. Distributional and ecological review of the four horned antelope. Tetracerus quadricornis. 73, 1–6 (2009).
    Google Scholar 
    Sharma, K., Chundawat, R. S., Van Gruisen, J. & Rahmani, A. R. Understanding the patchy distribution of four-horned antelope Tetracerus quadricornis in a tropical dry deciduous forest in Central India. J. Trop. Ecol. 30, 45–54 (2014).Article 

    Google Scholar 
    Rahman, D. A., Syamsudin, M., Firdaus, A. Y. & Afriandi, H. T. Photographic record of Dholes predating on a young Banteng in southwestern Java, Indonesia. J. Threat. Taxa 13, 20278–20283 (2021).Article 

    Google Scholar 
    Durbin, L. S., Venkataraman, A., Hedges, S. & Dukworth, W. South Asia—south of th e Himalaya (oriental). In Canids: Foxes, Wolves, Jackals and Dogs . Status Survey and Conserva- tion Action Plan. (IUCN Canid Specialist Group, 2004).Bashir, T., Bhattacharya, T., Poudyal, K., Roy, M. & Sathyakumar, S. Precarious status of the Endangered dhole Cuon alpinus in the high elevation Eastern Himalayan habitats of Khangchendzonga Biosphere Reserve, Sikkim, India. Oryx 48, 125–132 (2014).Article 

    Google Scholar 
    Yoshimura, H., Hirata, S. & Kinoshita, K. Plant-eating carnivores: Multispecies analysis on factors influencing the frequency of plant occurrence in obligate carnivores. Ecol. Evol. 11, 10968–10983 (2021).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Snake-in-the-diet-of-Cuon-alpinus-Pallas-1811-in-Kalakad-Mundanthurai-Tiger-Reserve-Tamil-Nadu.pdf.Habib, B. et al. Status of Tigers, Co-Predator and Prey in Tadoba Andhari Tiger Reserve (TATR)— Phase IV Monitoring Report and Report on Collaring of Leopards. (2014). 26 (2015).Habib, B. et al. Status of Tigers, Co-Predator and Prey in Tadoba Andhari Tiger Reserve (TATR) (2015). 62 (2016).Habib, B. et al. Status of Tigers, Co-Predator and Prey in Tadoba Andhari Tiger Reserve (TATR) (2016). 27 (2017).Habib, B. et al. Status of Tigers, Co-Predator and Prey in Tadoba Andhari Tiger Reserve (TATR) (2017). 44 (2018).Habib, B. et al. Status of Tigers, Co-Predator and Prey in Tadoba Andhari Tiger Reserve (TATR) (2018). 41 (2019).Habib, B. et al. Status of Tigers, Co-Predator and Prey in Tadoba Andhari Tiger Reserve (TATR) (2019). 47 https://ntca.gov.in/assets/uploads/Reports/WII/TATR%20Phase%20IV%202019.pdf (2020).Jhala, Y. V., Qureshi, Q. & Nayak, A. K. Status of tigers, co-predators and prey in India 2018. 656 https://ntca.gov.in/assets/uploads/Reports/AITM/Tiger_Status_Report_2018.pdf (2019).Bagchi, S., Goyal, S. P. & Sankar, K. Prey abundance and prey selection by tigers (Panthera tigris) in a semi-arid, dry deciduous forest in western India. J. Zool. 260, 285–290 (2003).Article 

    Google Scholar 
    Woodroffe, R., Lindsey, P. A., Romañach, S. S. & Ranah, S. M. K. African Wild Dogs ( Lycaon pictus ) Can Subsist on Small Prey: Implications for Conservation. J. Mammal. 88, 181–193 (2007).Article 

    Google Scholar 
    Merrill, E. et al. Building a mechanistic understanding of predation with GPS-based movement data. Philos. Trans. R. Soc. B Biol. Sci. 365, 2279–2288 (2010).Article 

    Google Scholar 
    Pitman, R. T., Mulvaney, J., Ramsay, P. M., Jooste, E. & Swanepoel, L. H. Global Positioning System-located kills and faecal samples: A comparison of leopard dietary estimates. J. Zool. 292, 18–24 (2014).Article 

    Google Scholar 
    Jansen, C., Leslie, A. J., Cristescu, B., Teichman, K. J. & Martins, Q. Determining the diet of an African mesocarnivore, the caracal: Scat or GPS cluster analysis?. Wildl. Biol. 2019, wlb.00579 (2019).Article 

    Google Scholar 
    Leighton, G. R. M. et al. An integrated dietary assessment increases feeding event detection in an urban carnivore. Urban Ecosyst. 23, 569–583 (2020).Article 

    Google Scholar 
    Studd, E. K. et al. The Purr-fect Catch: Using accelerometers and audio recorders to document kill rates and hunting behaviour of a small prey specialist. Methods Ecol. Evol. 12, 1277–1287 (2021).Article 

    Google Scholar 
    Bhandari, A., Ghaskadbi, P., Nigam, P. & Habib, B. Dhole pack size variation: Assessing the effect of Prey availability and Apex predator. Ecol. Evol. 11, 4774–4785 (2021).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Hubel, T. Y. et al. Additive opportunistic capture explains group hunting benefits in African wild dogs. Nat. Commun. 7, 11033 (2016).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Parker, D. M., Vyver, D. B. & Bissett, C. The influence of an apex predator introduction on an already established subordinate predator. J. Zool. 313, 224–235 (2021).Article 

    Google Scholar 
    Johnsingh, A. J. T. Prey selection in three large sympatric carnivores in Bandipur. Mammalia 56, (1992).Marucco, F., Pletscher, D. H. & Boitani, L. Accuracy of scat sampling for carnivore diet analysis: Wolves in the Alps as a case study. J. Mammal. 89, 665–673 (2008).Article 

    Google Scholar 
    Martins, Q., Horsnell, W. G. C., Titus, W., Rautenbach, T. & Harris, S. Diet determination of the Cape Mountain leopards using global positioning system location clusters and scat analysis. J. Zool. 283, 81–87 (2011).Article 

    Google Scholar 
    Champion, S. H. G. & Seth, S. K. A Revised Survey of the Forest Types of India (Manager of Publications, 1968).
    Google Scholar 
    Thinley, P. et al. Seasonal diet of dholes (Cuon alpinus) in northwestern Bhutan. Mamm. Biol. 76, 518–520 (2011).Article 

    Google Scholar 
    Modi, S., Habib, B., Ghaskadbi, P., Nigam, P. & Mondol, S. Standardization and validation of a panel of cross-species microsatellites to individually identify the Asiatic wild dog (Cuon alpinus). PeerJ 7, e7453 (2019).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Modi, S., Mondol, S., Nigam, P. & Habib, B. Genetic analyses reveal demographic decline and population differentiation in an endangered social carnivore, Asiatic wild dog. Sci. Rep. 11, 16371 (2021).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Putman, R. J. Facts from faeces. Mammal Rev. 14, 79–97 (1984).Article 

    Google Scholar 
    Kohn, M. H. & Wayne, R. K. Facts from feces revisited. Trends Ecol. Evol. 12, 223–227 (1997).CAS 
    PubMed 
    Article 

    Google Scholar 
    Mukherjee, S., Goyal, S. P. & Chellam, R. Standardisation of scat analysis techniques for leopard (Panthera pardus) in Gir National Park, Western India. Mammalia 58, (1994).Bahuguna, A., Sahajpal, V., Goyal, S. P., Mukherjee, S. & Thakur, V. Species Identification from Guard Hair of Selected Indian Mammals: A Reference Guide. Wildlife Institute of India (Wildlife Institute of India, 2010).
    Google Scholar 
    Leopold, B. D. & Krausman, P. R. Diets of 3 Predators in Big Bend National Park, Texas. J. Wildl. Manag. 50, 290 (1986).Article 

    Google Scholar 
    Van Ballenberghe, V., Erickson, A. W. & Byman, D. Ecology of the Timber Wolf in Northeastern Minnesota. Wildl. Monogr. 3–43 (1975).Ciucci, P., Boitani, L., Pelliccioni, E. R., Rocco, M. & Guy, I. A comparison of scat-analysis methods to assess the diet of the wolf Canis lupus. Wildl. Biol. 2, 37–48 (1996).Article 

    Google Scholar 
    Weaver, J. L. Refining the equation for interpreting prey occurrence in Gray wolf scats. J. Wildl. Manag. 57, 534–538 (1993).Article 

    Google Scholar 
    Chakrabarti, S. et al. Adding constraints to predation through allometric relation of scats to consumption. J. Anim. Ecol. 85, 660–670 (2016).PubMed 
    Article 

    Google Scholar 
    Lumetsberger, T. et al. Re-evaluating models for estimating prey consumption by leopards. J. Zool. 302, 201–210 (2017).Article 

    Google Scholar 
    Jacobs, J. Quantitative measurement of food selection: A modification of the forage ratio and Ivlev’s electivity index. Oecologia 14, 413–417 (1974).ADS 
    PubMed 
    Article 

    Google Scholar 
    Karanth, K. U. & Nichols, J. D. Distribution and Dynamics of Tiger and Prey Populations in Maharashtra, India Final Technical Report (October 2001 to August 2005). (2005).19 LIVESTOCK CENSUS-2012 ALL INDIA REPORT. https://d1wqtxts1xzle7.cloudfront.net/56129012/6ESSJan-6098P-with-cover-page-v2.pdf?Expires=1644491741&Signature=Apc1rT2raxYnUyrRJ64NqOd6oUEpnF2AiRQVPB-9gS2W2TIrOcInF3KnBJVA2dPxzfbIz8ap9IPe-l24mpYs9i8xEZAvsxRVnDhSHT8H9C9fd0voDxyUwl3gUyJgDDzLO-204J95UuopJQw5Df6xTNmTOs5Oiadk0Fkf9Fk-QRVajisuRjzyX2eLmrBH4LyTJFu5irffnKwnluqHl53KoMAQ6nTKi7dlqI4pdFIVCtisXpkSsI44xV1mYX6KC67zmKCZlvjpTxTuHCFV4nmfpgZpPXh4sIOE-0utbwcf5g~UdmRtVVhaXfjZ2iw0gOm7-bIuQILDldPr3OnNUqXbSw__&Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA (2012).The Measurement of Niche Overlap and Some Relatives – Hurlbert – 1978 – Ecology – Wiley Online Library. https://esajournals.onlinelibrary.wiley.com/doi/abs/https://doi.org/10.2307/1936632.Habib, B., Ghaskadbi, P., Khan, S., Hussain, Z. & Nigam, P. Not a cakewalk: Insights into movement of large carnivores in human-dominated landscapes in India. Ecol. Evol. 11, 1653–1666 (2021).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Neu, C. W., Byers, C. R. & Peek, J. M. A technique for analysis of utilization-availability data. J. Wildl. Manag. 38, 541–545 (1974).Article 

    Google Scholar  More

  • in

    Dogs suppress a pivotal function in the food webs of sandy beaches

    Hughes, J. & Macdonald, D. W. A review of the interactions between free-roaming domestic dogs and wildlife. Biol. Cons. 157, 341–351 (2013).Article 

    Google Scholar 
    Doherty, T. S. et al. The global impacts of domestic dogs on threatened vertebrates. Biol. Cons. 210, 56–59 (2017).Article 

    Google Scholar 
    Young, J. K., Olson, K. A., Reading, R. P., Amgalanbaatar, S. & Berger, J. Is wildlife going to the dogs? Impacts of feral and free-roaming dogs on wildlife populations. Bioscience 61, 125–132 (2011).Article 

    Google Scholar 
    Ritchie, E. G., Dickman, C. R., Letnic, M., Vanak, A. T. & Gommper, M. Dogs as predators and trophic regulators. Free-ranging dogs and wildlife conservation, 55–68 (2014).Gompper, M. E. In Free-ranging dogs and wildlife conservation, Oxford University Press (2014).Somaweera, R., Webb, J. K. & Shine, R. It’sa dog-eat-croc world: Dingo predation on the nests of freshwater crocodiles in tropical Australia. Ecol. Res. 26, 957–967 (2011).Article 

    Google Scholar 
    Weston, M. A. & Stankowich, T. In Free-Ranging Dogs and Wildlife Conservation. ME Gompper (ed.) (ed Matthew E Gompper) Ch. 4, 94–113 (Oxford University Press, 2013).Zapata-Ríos, G. & Branch, L. C. Altered activity patterns and reduced abundance of native mammals in sites with feral dogs in the high Andes. Biol. Cons. 193, 9–16 (2016).Article 

    Google Scholar 
    Donadio, E. & Buskirk, S. W. Diet, morphology, and interspecific killing in Carnivora. Am. Nat. 167, 524–536 (2006).PubMed 
    Article 

    Google Scholar 
    Gingold, G., Yom-Tov, Y., Kronfeld-Schor, N. & Geffen, E. Effect of guard dogs on the behavior and reproduction of gazelles in cattle enclosures on the Golan Heights. Anim. Conserv. 12, 155–162 (2009).Article 

    Google Scholar 
    Fernández-Juricic, E. & Tellería, J. L. Effects of human disturbance on spatial and temporal feeding patterns of Blackbird Turdus merula in urban parks in Madrid, Spain. Bird Study 47, 13–21 (2000).Article 

    Google Scholar 
    Vanak, A. T. & Gompper, M. E. Dogs Canis familiaris as carnivores: Their role and function in intraguild competition. Mammal Rev. 39, 265–283 (2009).Article 

    Google Scholar 
    Silva-Rodríguez, E. A. & Sieving, K. E. Domestic dogs shape the landscape-scale distribution of a threatened forest ungulate. Biol. Cons. 150, 103–110 (2012).Article 

    Google Scholar 
    Banks, P. B. & Bryant, J. V. Four-legged friend or foe? Dog walking displaces native birds from natural areas. Biol. Let. 3, 611–613 (2007).Article 

    Google Scholar 
    Langston, R., Liley, D., Murison, G., Woodfield, E. & Clarke, R. What effects do walkers and dogs have on the distribution and productivity of breeding European Nightjar Caprimulgus europaeus?. Ibis 149, 27–36 (2007).Article 

    Google Scholar 
    Lenth, B. E., Knight, R. L. & Brennan, M. E. The effects of dogs on wildlife communities. Nat. Areas J. 28, 218–227 (2008).Article 

    Google Scholar 
    Weston, M. A. & Stankowich, T. Dogs as agents of disturbance. Free-Ranging Dogs and Wildlife Conservation. ME Gompper (ed.), 94–113 (2013).Letnic, M., Ritchie, E. G. & Dickman, C. R. Top predators as biodiversity regulators: The dingo Canis lupus dingo as a case study. Biol. Rev. 87, 390–413 (2012).PubMed 
    Article 

    Google Scholar 
    Maguire, G. S., Miller, K. K. & Weston, M. A. In Impacts of Invasive Species on Coastal Environments 397–412 (Springer, 2019).Cardinale, B. J. et al. Biodiversity loss and its impact on humanity. Nature 486, 59–67 (2012).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Delgado-Baquerizo, M. et al. Microbial diversity drives multifunctionality in terrestrial ecosystems. Nat. Commun. 7, 1–8 (2016).Article 
    CAS 

    Google Scholar 
    Rodriguez, L. F. Can invasive species facilitate native species? Evidence of how, when, and why these impacts occur. Biol. Invasions 8, 927–939 (2006).Article 

    Google Scholar 
    Rosenfeld, J. S. Functional redundancy in ecology and conservation. Oikos 98, 156–162 (2002).Article 

    Google Scholar 
    Díaz, S., Fargione, J., Chapin, F. S. III. & Tilman, D. Biodiversity loss threatens human well-being. PLoS Biol 4, e277 (2006).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Hooper, D. U. et al. A global synthesis reveals biodiversity loss as a major driver of ecosystem change. Nature 486, 105–108 (2012).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Barbier, E. B. et al. The value of estuarine and coastal ecosystem services. Ecol. Monogr. 81, 169–193. https://doi.org/10.1890/10-1510.1 (2011).Article 

    Google Scholar 
    Nel, R. et al. The status of sandy beach science: Past trends, progress, and possible futures. Estuar. Coast. Shelf Sci. 150, 1–10 (2014).ADS 
    Article 

    Google Scholar 
    Schlacher, T. A. et al. Golden opportunities: A horizon scan to expand sandy beach ecology. Estuar. Coast. Shelf Sci. 157, 1–6 (2015).ADS 
    Article 

    Google Scholar 
    Schlacher, T. A. et al. Key ecological function peaks at the land–ocean transition zone when vertebrate scavengers concentrate on ocean beaches. Ecosystems 23, 1–11 (2019).MathSciNet 

    Google Scholar 
    Lockwood, J. L. & Maslo, B. In Coastal Convervation (eds Brooke Maslo & JL Lockwood) 1–10 (Cambridge University Press, 2014).Morin, D. J., Lesmeister, D. B., Nielsen, C. K. & Schauber, E. M. The truth about cats and dogs: Landscape composition and human occupation mediate the distribution and potential impact of non-native carnivores. Glob. Ecol. Conserv. 15, e00413 (2018).Article 

    Google Scholar 
    Cortés, E. I., Navedo, J. G. & Silva-Rodríguez, E. A. Widespread presence of domestic dogs on sandy beaches of Southern Chile. Animals 11, 161 (2021).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Burger, J., Jeitner, C., Clark, K. & Niles, L. J. The effect of human activities on migrant shorebirds: Successful adaptive management. Environ. Conserv. 31, 283–288 (2004).Article 

    Google Scholar 
    Dowling, B. & Weston, M. A. Managing a breeding population of the Hooded Plover Thinornis rubricollis in a high-use recreational environment. Bird Conserv. Int. 9, 255–270 (1999).Article 

    Google Scholar 
    Vanak, A. T. & Gompper, M. E. Interference competition at the landscape level: The effect of free-ranging dogs on a native mesocarnivore. J. Appl. Ecol. 47, 1225–1232 (2010).Article 

    Google Scholar 
    Marzluff, J. M., McGowan, K. J., Donnelly, R. & Knight, R. L. In Avian ecology and conservation in an urbanizing world 331–363 (Springer, 2001).Handler, A., Lonsdorf, E. V. & Ardia, D. R. Evidence for red fox (Vulpes vulpes) exploitation of anthropogenic food sources along an urbanization gradient using stable isotope analysis. Can. J. Zool. 98, 79–87 (2020).Article 

    Google Scholar 
    Prange, S., Gehrt, S. D. & Wiggers, E. P. Demographic factors contributing to high raccoon densities in urban landscapes. The J. Wildlife Manag. 67, 324–333 (2003).Article 

    Google Scholar 
    Méndez, A. et al. Adapting to urban ecosystems: unravelling the foraging ecology of an opportunistic predator living in cities. Urban Ecosyst. 23, 1117–1126 (2020).Article 

    Google Scholar 
    Rees, J., Webb, J., Crowther, M. & Letnic, M. Carrion subsidies provided by fishermen increase predation of beach-nesting bird nests by facultative scavengers. Anim. Conserv. 18, 44–49 (2015).Article 

    Google Scholar 
    Kimber, O. et al. The fox and the beach: Coastal landscape topography and urbanisation predict the distribution of carnivores at the edge of the sea. Glob. Ecol. Conserv. 23, e01071 (2020).Article 

    Google Scholar 
    Ruxton, G. D. & Houston, D. C. Obligate vertebrate scavengers must be large soaring fliers. J. Theor. Biol. 228, 431–436 (2004).ADS 
    MathSciNet 
    PubMed 
    MATH 
    Article 

    Google Scholar 
    Cortés-Avizanda, A., Jovani, R., Donázar, J. A. & Grimm, V. Bird sky networks: How do avian scavengers use social information to find carrion?. Ecology 95, 1799–1808 (2014).PubMed 
    Article 

    Google Scholar 
    Harel, R., Spiegel, O., Getz, W. M. & Nathan, R. Social foraging and individual consistency in following behaviour: Testing the information centre hypothesis in free-ranging vultures. Proc. Royal Soc. B: Biol. Sci. 284, 20162654 (2017).Article 

    Google Scholar 
    Soulsbury, C. D., Iossa, G., Baker, P. J., White, P. C. & Harris, S. Behavioral and spatial analysis of extraterritorial movements in red foxes (Vulpes vulpes). J. Mammal. 92, 190–199 (2011).Article 

    Google Scholar 
    Johnson, C. N. & VanDerWal, J. Evidence that dingoes limit abundance of a mesopredator in eastern Australian forests. J. Appl. Ecol. 46, 641–646 (2009).Article 

    Google Scholar 
    Polis, G. A., Anderson, W. B. & Holt, R. D. Toward an integration of landscape and food web ecology: The dynamics of spatially subsidized food webs. Ann. Rev. Ecol. Syst. 28, 289–316 (1997).Article 

    Google Scholar 
    Barton, P. S., Cunningham, S. A., Lindenmayer, D. B. & Manning, A. D. The role of carrion in maintaining biodiversity and ecological processes in terrestrial ecosystems. Oecologia 171, 761–772 (2013).ADS 
    PubMed 
    Article 

    Google Scholar 
    Schlacher, T. A., Strydom, S. & Connolly, R. M. Multiple scavengers respond rapidly to pulsed carrion resources at the land–ocean interface. Acta Oecologica 48, 7–12 (2013).ADS 
    Article 

    Google Scholar 
    Dunbrack, T. R. & Dunbrack, R. L. Why take your dog on a picnic: presence of a potential predator (Canis lupus familiaris) reverses the outcome of food competition between northwestern crows (Corvus caurinus) and glaucous-winged gulls (Larus glaucescens). Northwest. Nat. 91, 94–98 (2010).Article 

    Google Scholar 
    Jiménez, J. et al. Restoring apex predators can reduce mesopredator abundances. Biol. Cons. 238, 108234 (2019).Article 

    Google Scholar 
    Bhadra, A. et al. The meat of the matter: A rule of thumb for scavenging dogs?. Ethol. Ecol. Evol. 28, 427–440 (2016).Article 

    Google Scholar 
    Turner, K. L., Abernethy, E. F., Conner, L. M., Rhodes, O. E. Jr. & Beasley, J. C. Abiotic and biotic factors modulate carrion fate and vertebrate scavenging communities. Ecology 98, 2413–2424 (2017).PubMed 
    Article 

    Google Scholar 
    Ogada, D., Torchin, M., Kinnaird, M. & Ezenwa, V. Effects of vulture declines on facultative scavengers and potential implications for mammalian disease transmission. Conserv. Biol. 26, 453–460 (2012).CAS 
    PubMed 
    Article 

    Google Scholar 
    O’Bryan, C. J. et al. The contribution of predators and scavengers to human well-being. Nat. Ecol. & Evol. 2, 229–236 (2018).Article 

    Google Scholar 
    Gómez-Serrano, M. Á. Four-legged foes: Dogs disturb nesting plovers more than people do on tourist beaches. Ibis 163, 338–352 (2021).Article 

    Google Scholar 
    Stantial, M., Cohen, J., Darrah, A., Farrell, S. & Maslo, B. The effect of top predator removal on the distribution of a mesocarnivore and nest survival of an endangered shorebird. Avian Conserv. Ecol. https://doi.org/10.5751/ACE-01806-160108 (2021).Article 

    Google Scholar 
    Mahon, P. S. Targeted control of widespread exotic species for biodiversity conservation: The red fox (Vulpes vulpes) in New South Wales, Australia. Ecol. Manag. Restor. 10, S59–S69 (2009).ADS 
    Article 

    Google Scholar 
    Colwell, M. A. In The Population Ecology and Conservation of Charadrius Plovers 127–147 (CRC Press, 2019).Huijbers, C. M. et al. Limited functional redundancy in vertebrate scavenger guilds fails to compensate for the loss of raptors from urbanized sandy beaches. Divers. Distrib. 21, 55–63 (2015).Article 

    Google Scholar 
    Huijbers, C. M., Schlacher, T. A., Schoeman, D. S., Weston, M. A. & Connolly, R. M. Urbanisation alters processing of marine carrion on sandy beaches. Landsc. Urban Plan. 119, 1–8 (2013).Article 

    Google Scholar 
    Meek, P. et al. Recommended guiding principles for reporting on camera trapping research. Biodivers. Conserv. 23, 2321–2343 (2014).Article 

    Google Scholar 
    Kolowski, J. M. & Forrester, T. D. Camera trap placement and the potential for bias due to trails and other features. PLoS ONE 12, e0186679 (2017).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Burton, A. C. et al. Wildlife camera trapping: a review and recommendations for linking surveys to ecological processes. J. Appl. Ecol. 52, 675–685 (2015).Article 

    Google Scholar 
    Selva, N. & Fortuna, M. A. The nested structure of a scavenger community. Proc. Royal Soc. B: Biol. Sci. 274, 1101–1108 (2007).Article 

    Google Scholar 
    Olson, Z. H., Beasley, J. C. & Rhodes, O. E. Jr. Carcass type affects local scavenger guilds more than habitat connectivity. PLoS ONE 11, e0147798 (2016).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Anderson, M. J. Permutation tests for univariate or multivariate analysis of variance and regression. Can. J. Fish. Aquat. Sci. 58, 626–639 (2001).Article 

    Google Scholar 
    Team, R. D. C. R: A language and environment for statistical computing. R Foundation for statistical computing, Vienna, Austria (2013).Dixon, P. VEGAN, a package of R functions for community ecology. J. Veg. Sci. 14, 927–930 (2003).Article 

    Google Scholar 
    Schlacher, T. A. et al. Conservation gone to the dogs: When canids rule the beach in small coastal reserves. Biodivers. Conserv. 24, 493–509 (2015).Article 

    Google Scholar 
    Lewin, W.-C., Freyhof, J., Huckstorf, V., Mehner, T. & Wolter, C. When no catches matter: Coping with zeros in environmental assessments. Ecol. Ind. 10, 572–583 (2010).Article 

    Google Scholar 
    Burnham, K. P. & Anderson, D. R. Model selection and multimodel inference: a practical information-theoretic approach. 488 (Springer Science & Business Media, 2002).Bolker, B. & Team, R. (R package version 0.9, 2010).Barton, K. & Barton, M. K. Package ‘mumin’. Version 1, 439 (2015).Wickham, H., Francois, R., Henry, L. & Müller, K. dplyr: A grammar of data manipulation. R package version 0.4. 3. R Found. Stat. Comput., Vienna. https://CRAN. R-project. org/package= dplyr (2015).Wickham, H., Chang, W. & Wickham, M. H. Package ‘ggplot2’. Create Elegant Data Visualisations Using the Grammar of Graphics. Version 2, 1–189 (2016). More

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    Predictors of psychological stress and behavioural diversity among captive red panda in Indian zoos and their implications for global captive management

    Influence of independent variables on the extent of stereotyped behaviourThe overall level of stereotypy we observed was low, suggesting that the pandas in our study were not seriously stressed. The variables that we found to be correlated with stereotypy are consistent with what we know of pandas’ natural history. Our study reports that variables like logs on the ground, nest, sociality, zoo, tree density, age and tree height used by pandas are the driving force for stereotypy in captive pandas involved in the study.Making the captive environment more naturalistic by integrating enrichment into the enclosure seems to be a promising way of alleviating stress and improving both welfare and reintroduction success41. It also helps to improve reproductive rate and overall health39. Improved health reduces stress and gives greater control over the environment increasing the chances of survival and longevity both in captivity and following release into the wild5. It is generally accepted that enrichment of the captive environment increases animals’ ability to cope with challenges and positive use of the environment reduces or eliminates aberrant behaviour23. Lack of enclosure enrichments and less complex enclosures can cause stereotypy and other atypical behaviours24, while providing enrichment increases the frequency of natural behaviours25 and thereby reduces stress, which in turn decreases stereotypy27. But enrichment needs to be appropriate for the species of animal concerned. Abnormal behaviours are often associated with captive conditions that deviate greatly from the species’ natural environment. Consistent with this argument we found that though dead and fallen logs on the ground are one of the important characteristics of the panda habitats in the wild42,43,44,45, merely providing them in captivity does not ensure the species’ welfare: in fact, stereotypy increased with log density in our study subjects. This could be due to the fact that four individuals that showed more stereotypy were housed in the small barren enclosures with no trees but more logs as a part of enrichment. Without those four individuals, the linear relation between stereotypy and log density was not statistically significant. This clearly suggested that merely providing logs in the small enclosures does not maintain welfare.
    When animals are housed in enclosures designed to resemble their natural habitat by considering their natural history (provision of vegetation, shelter, pool, etc.), there is a reduction or elimination of abnormal patterns of behaviour such as stereotypies, increased fitness and improved health, all of which may influence reproduction25,46,47,48. For many species, nests, shelter or burrows in enclosures will serve as retreat and hiding places, which are essential to cope with environmental stressors10. Gerbils, mice and rabbits have all shown less stereotyped behaviour when retreats are provided9,49,50,51. Such retreats can mitigate the effects of zoo visitors, who can serve as a source of stress for species that rarely interact with humans in the wild. Consistent with these previous results, we found that with provision of nests, the extent of stereotypy decreased in captive pandas. Many species prefer nests both for rearing the young as well as for resting and shelter, and pandas follow this pattern, so providing nests in adequate numbers will supports their natural behaviour as well as provide relief from environmental stressors. Zidar recommends providing one more nest than there are individuals in an enclosure52.Although pandas are an asocial species, our study showed that pandas show more stereotyped behaviour when housed alone than when with another individual or in group. Being a solitary species in the wild might encourage management to house them singly in captivity, but not every activity and habit of species in the wild can be used in captivity. For example, polar bears are also a solitary species, and it was at one time thought best to manage them alone, but it was found that managing them in a social setting reduces stereotypic pacing behaviour53, consistent with this study. Importantly, managers of zoo should note that living in group is greatly influenced by the individuals’ compatibility and hence this should be kept in mind while pairing.Similarly, we found that the presence of trees, and greater mean tree height use by pandas, reduced stereotypy. Pandas’ preferred high elevation habitat is favourable for taller trees20, and Shrestha et al. found that canopy cover was an important factor in habitats for pandas in the wild54. In European zoos, pandas spend 90% of their time off the ground37. Consistent with these previous findings, our study reveals that more and taller trees support natural behaviours in panda. The Central Zoo Authority (CZA) of India enrichment manual recommends taller tree provision in panda enclosures, and again we provide empirical support for its recommendation.We found that with increasing age stereotypy increased in pandas. The older the individuals the more time spent in captivity with its associated risks of stereotypic behaviour. The same trend has been observed in other species: for example in captive bears stereotypic behaviour increased with age55. In another study Asiatic black bear and sun bear showed more stereotypy with age56.Influence of independent variables on behavioural diversityAs noted in the “Introduction” section, in a species like the panda, high daytime behavioural diversity is not necessarily a positive indication of good welfare. However, our comparison of behavioural diversity with stereotypy showed a negative trend (though not significant), suggesting that low behavioural diversity might be associated with poorer welfare.Nonetheless, we found some results that suggested that lower diversity might in fact be associated with a more natural lifestyle. Because of the amount of time that wild pandas spend foraging57 and sleeping or inactive, they cannot show much behavioural diversity, and in our sample of captive individuals, they showed the same trend. For example, behavioural diversity was lower when pandas were provided with more trees in the enclosure. This suggests that when appropriate conditions are maintained in captivity, panda prefer to be inactive during the day, as is consistent with their natural history57. As pandas are essentially arboreal mammals, naturally they also spend most of the time inactive (e.g. sleeping) on the trees57. Indeed, providing larger trees would promote inactive behaviours and hence lower behaviour diversity in captivity, this captures their natural behaviour. This is consistent with our results where increased tree height used by pandas decreased behavioural diversity.We found behavioural diversity was greater when there are more logs in the enclosure. In the Yele Reserve in Sichuan, China, Wei et al. found 107 of 185 panda dropping sites (57.8%) on shrub branches, 49 (26.5%) on fallen logs, and only 29 (15.7%) on the forest floor44. Droppings were found mostly on elevated structures ranging from 1 to 3 m above the forest floor and occasionally on trees over 12 m. Moreover, microhabitats selected by pandas were also characterized by fallen logs and tree stumps42,45. Wei and Zhang mention that to access bamboo leaves easily, pandas usually use some elevated objects, such as shrub branches, fallen logs, or tree stumps to lift their body43. Hence, providing tree logs in the vicinity supports their natural behaviour. But at the same time management should keep in mind that merely providing logs in the enclosure would not guarantee species welfare, as discussed in previous section with respect to stereotypy.Temperature is an important element of microclimate for animals, and influences the activity level of captive animals10. When temperature rises, many species show distress in captivity10. The red panda inhabits low-temperature areas20, so it is unlikely that higher temperatures would support natural behaviours. We found that with increased temperature behavioural diversity decreased in captive pandas. Similarly, we found that pandas showed higher behavioural diversity in the winter season, where temperatures are low as compared to summer season.Studies that have tried to relate behavioural diversity and stereotypy in captive animals have varied in their interpretation; many have found significantly inverse relationships between the two19. In this study our multivariate model suggested that behavioural diversity is negatively influenced by stereotypy in captive pandas, confirming previous research.Other factors associated with variations in behavioural diversity are less easy to identify with welfare, positive or negative. Behavioural diversity also decreases with age of pandas and increases with distance to cage mate, number of visitors and quantum of bamboo provided, though these effects were not significant in the REVS model.Taken together, these results suggest that higher behavioural diversity is not a straightforward indicator of better welfare in all captive animals. The overall non-significant relationship between stereotyped behaviour and diversity we observed could well be the result of a mixture of factors operating in opposite directions. To interpret diversity correctly, it would be helpful to know what level of diversity the species shows in the wild, and such data are rarely available—a limitation of our study as of many others. Although there are dissenting voices58, arguably what matters most both in terms of welfare and in terms of potential reintroduction to the wild, is that a captive animal’s time budget approximates as closely as possible that of a wild animal. It is not diversity as such that is important, but the behaviours that the animal exhibits.Differences between zoosOur study showed that both the extent of stereotyped behaviour and behavioural diversity varied significantly among zoos. However, Zoo 2, an important breeding centre, housed only a female and her two cubs; this may lead to many factors being confounded and is thus a limitation to our study. Captive animals rely on the zoo environment, its routine and husbandry practices to limit their stress levels, and any failure to provide suitable resources will certainly disturb them and lead to distress10. Controlling such variables appropriately will help reduce stress among captive animals, and we can rely to some extent on our knowledge of the species’ natural history to guide us through this challenge. Our study was able to identify some of the factors that are associated with better welfare, but even with these factors taken into account, significant differences among the three zoos remained. These are presumably due to subtler variations in the zoos’ environment or management regimes. Since the panda is endemic to high elevations, we considered whether differences between the elevations of the zoos might be relevant, but the biggest differences were between Zoos 1 and 3, which are at essentially the same elevation.In Zoo 1 pandas showed lower stereotypy and higher behavioural diversity then the other two zoos. Again, these differences may be due to subtle differences between the management regimes in the three zoos; possibilities include keepers’ attitudes and the zoo’s experience in managing pandas. It is notable that Zoo 1 has longer and wider experience in the management of red pandas than the other two zoos, which have joined the captive breeding programme more recently and have fewer animals. Other notable differences were that in Zoo 1, pandas are fed twice a day as compared to the other two zoos where feed is given all at one time (both bamboo and supplementary diet); and that in Zoo 1 the enclosures were of a good size for a small mammal like the red panda, and were well maintained with much natural vegetation. The other two zoos had a large enclosure with poor vegetation (trees and grass), or a small enclosure with a barren floor and no trees at all. Location of the enclosure also needs to be considered: in two of the enclosures at Zoo 3 the sun shone directly on the animals with no shade as such, keeping the temperature higher than would be natural for pandas. Any of these factors could be the reason the pandas performed comparatively well in Zoo 1, and it would be necessary to study a wider (and, therefore, cross-national) sample of zoos holding pandas to identify which of them are the most important. More

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    Rapid evolution of a novel protective symbiont into keystone taxon in Caenorhabditis elegans microbiota

    Samuel, B. S., Rowedder, H., Braendle, C., Félix, M. A. & Ruvkun, G. Caenorhabditis elegans responses to bacteria from its natural habitats. Proc. Natl. Acad. Sci. USA 113, E3941–E3949 (2016).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Oliver, K. M., Smith, A. H. & Russell, J. A. Defensive symbiosis in the real world: Advancing ecological studies of heritable, protective bacteria in aphids and beyond. Funct. Ecol. 28, 341–355 (2014).
    Google Scholar 
    King, K. C. Defensive symbionts. Curr. Biol. 29, R78–R80 (2019).CAS 
    PubMed 

    Google Scholar 
    Foster, K. R., Schluter, J., Coyte, K. Z. & Rakoff-Nahoum, S. The evolution of the host microbiome as an ecosystem on a leash. Nature 548, 43–51 (2017).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ford, S. A., Kao, D., Williams, D. & King, K. C. Microbe-mediated host defence drives the evolution of reduced pathogen virulence. Nat. Commun. 7, 13430 (2016).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Litvak, Y. et al. Commensal Enterobacteriaceae protect against Salmonella colonization through oxygen competition. Cell Host Microbe 25, 128–139 (2019).CAS 
    PubMed 

    Google Scholar 
    Pimentel, A. C., Cesar, C. S., Martins, M. & Cogni, R. The antiviral effects of the symbiont bacteria Wolbachia in insects. Front. Immunol. 11, 626329 (2021).PubMed 
    PubMed Central 

    Google Scholar 
    Becker, M. H., Brucker, R. M., Schwantes, C. R., Harris, R. N. & Minbiole, K. P. C. The bacterially produced metabolite violacein is associated with survival of amphibians infected with a lethal fungus. Appl. Environ. Microbiol. 75, 6635–6638 (2009).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Bates, K. A., Bolton, J. S. & King, K. C. A globally ubiquitous symbiont can drive experimental host evolution. Mol. Ecol. 30, 3882–3892 (2021).CAS 
    PubMed 

    Google Scholar 
    Dahan, D., Preston, G. M., Sealey, J. & King, K. C. Impacts of a novel defensive symbiosis on the nematode host microbiome. BMC Microbiol. 20, 1–10 (2020).
    Google Scholar 
    Banerjee, S., Schlaeppi, K. & van der Heijden, M. G. A. Keystone taxa as drivers of microbiome structure and functioning. Nat. Rev. Microbiol. 16, 567–576 (2018).CAS 
    PubMed 

    Google Scholar 
    Zheng, Y. et al. Exploring biocontrol agents from microbial keystone taxa associated to suppressive soil: A new attempt for a biocontrol strategy. Front. Plant Sci. 12, 655673 (2021).PubMed 
    PubMed Central 

    Google Scholar 
    Tudela, H., Claus, S. P. & Saleh, M. Next generation microbiome research: Identification of keystone species in the metabolic regulation of host-gut microbiota interplay. Front. Cell Dev. Biol. 9, 719072 (2021).PubMed 
    PubMed Central 

    Google Scholar 
    Mateos-Hernández, L. et al. Anti-tick microbiota vaccine impacts Ixodes ricinus performance during feeding. Vaccine 8, 1–21 (2020).
    Google Scholar 
    Mateos-Hernández, L. et al. Anti-microbiota vaccines modulate the tick microbiome in a taxon-specific manner. Front. Immunol. 12, 704621 (2021).PubMed 
    PubMed Central 

    Google Scholar 
    Dirksen, P. et al. The native microbiome of the nematode Caenorhabditis elegans: Gateway to a new host-microbiome model. BMC Biol. 14, 38 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Berg, M. et al. Assembly of the Caenorhabditis elegans gut microbiota from diverse soil microbial environments. ISME J. 10, 1998–2009 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Zhang, F. et al. Caenorhabditis elegans as a model for microbiome research. Front. Microbiol. 8, 485 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    King, K. C. et al. Rapid evolution of microbe-mediated protection against pathogens in a worm host. ISME J. 10, 1915–1924 (2016).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Faust, K. & Raes, J. Microbial interactions: From networks to models. Nat. Rev. Microbiol. 10, 538–550 (2012).CAS 
    PubMed 

    Google Scholar 
    Layeghifard, M., Hwang, D. M. & Guttman, D. S. Disentangling interactions in the microbiome: A network perspective. Trends Microbiol. 25, 217–228 (2017).CAS 
    PubMed 

    Google Scholar 
    Röttjers, L. & Faust, K. From hairballs to hypotheses–biological insights from microbial networks. FEMS Microbiol. Rev. 42, 761–780 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    Agler, M. T. et al. Microbial hub taxa link host and abiotic factors to plant microbiome variation. PLoS Biol. 14, e1002352 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Douglas, G. M. et al. PICRUSt2 for prediction of metagenome functions. Nat. Biotechnol. 38, 685–688 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Hou, Y. et al. Hierarchical microbial functions prediction by graph aggregated embedding. Front. Genet. 11, 608512 (2021).PubMed 
    PubMed Central 

    Google Scholar 
    Montalvo-Katz, S., Huang, H., Appel, M. D., Berg, M. & Shapira, M. Association with soil bacteria enhances p38-dependent infection resistance in Caenorhabditis elegans. Infect. Immun. 81, 514–520 (2013).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Callahan, B. J. et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583 (2016).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Bolyen, E. et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. 7, 852–857 (2019).
    Google Scholar 
    Bokulich, N. A. et al. Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin. Microbiome 6, 1–17 (2018).
    Google Scholar 
    Yarza, P. et al. Uniting the classification of cultured and uncultured bacteria and archaea using 16S rRNA gene sequences. Nat. Rev. Microbiol. 12, 635–645 (2014).CAS 
    PubMed 

    Google Scholar 
    Friedman, J. & Alm, E. J. Inferring correlation networks from genomic survey data. PLoS Comput. Biol. 8, e1002687 (2012).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    RStudio Team. RStudio: Integrated Development for R (RStudio, PBC, 2020).
    Google Scholar 
    Bastian, M., Heymann, S. & Jacomy, M. Gephi: An open-source software for exploring and manipulating networks. Third International AAAI Conference on Weblogs and Social Media (2009).Lhomme, S. NetSwan: Network Strengths and Weaknesses Analysis. R Pack Version (2015).Peschel, S., Müller, C. L., von Mutius, E., Boulesteix, A. L. & Depner, M. NetCoMi: Network construction and comparison for microbiome data in R. Brief Bioinform. 22, bbaa290 (2021).PubMed 

    Google Scholar 
    Kanehisa, M. Goto, S, KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 28, 27–30 (2000).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Tatusov, R. L., Galperin, M. Y., Natale, D. A. & Koonin, E. V. The COG database: A tool for genome-scale analysis of protein functions and evolution. Nucleic Acids Res. 28, 33–36 (2000).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Caspi, R. et al. The MetaCyc database of metabolic pathways and enzymes. Nucleic Acids Res. 46, D633–D639 (2018).CAS 
    PubMed 

    Google Scholar 
    Fernandes, A. D. et al. Unifying the analysis of high-throughput sequencing datasets: Characterizing RNA-seq, 16S rRNA gene sequencing and selective growth experiments by compositional data analysis. Microbiome 2, 15 (2014).PubMed 
    PubMed Central 

    Google Scholar 
    Lin, H. & Peddada, S. D. Analysis of microbial compositions: A review of normalization and differential abundance analysis. npj Biofilms Microbiomes 6, 60 (2020).PubMed 
    PubMed Central 

    Google Scholar 
    Ploner, A. Heatplus: Heatmaps with Row and/or Column Covariates and Colored Clusters. R package version 3.2. (2021).Shannon, C. E. A mathematical theory of communication. Bell Syst. Tech. J. 27, 379–423, 623–656 (1948).Pielou, E. C. The measurement of diversity in different types of biological collections. J. Theor. Biol. 13, 131–144 (1966).ADS 

    Google Scholar 
    Fisher, R. A., Corbet, A. S. & Williams, C. B. The relation between the number of species and the number of individuals in a random sample of an animal population. J. Anim. Ecol. 12, 42 (1943).
    Google Scholar 
    Ford, S. A. & King, K. C. Harnessing the power of defensive microbes: Evolutionary implications in nature and disease control. PLoS Pathog. 12, e1005465 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Gibbons, S. M. Keystone taxa indispensable for microbiome recovery. Nat. Microbiol. 5, 1067–1068 (2020).CAS 
    PubMed 

    Google Scholar 
    Wu-Chuang, A. et al. Thermostable keystone bacteria maintain the functional diversity of the Ixodes scapularis microbiome under heat stress. Microb. Ecol. https://doi.org/10.1007/s00248-021-01929-y (2021).Article 
    PubMed 

    Google Scholar 
    Ford, S. A. & King, K. C. In vivo microbial coevolution favors host protection and plastic downregulation of immunity. Mol. Biol. Evol. 38, 1330–1338 (2021).CAS 
    PubMed 

    Google Scholar 
    Banerjee, S. et al. Agricultural intensification reduces microbial network complexity and the abundance of keystone taxa in roots. ISME J. 13, 1722–1736 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Gao, Q. et al. The microbial network property as a bio-indicator of antibiotic transmission in the environment. Sci. Total Environ. 758, 143712 (2021).ADS 
    CAS 
    PubMed 

    Google Scholar 
    de Vries, F. T. et al. Soil bacterial networks are less stable under drought than fungal networks. Nat. Commun. 9, 3033 (2018).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    de Morais, U. L. A look at the way we look at complex networks’ robustness and resilience. https://arxiv.org/ftp/arxiv/papers/1909/1909.06448.pdf (2017).Carlson, J. M. & Doyle, J. Complexity and robustness. Proc. Natl. Acad. Sci. USA 99, 2538–2545 (2002).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Estrada-Peña, A., Cabezas-Cruz, A. & Obregón, D. Resistance of tick gut microbiome to anti-tick vaccines, pathogen infection and antimicrobial peptides. Pathogens 9, 309 (2020).PubMed Central 

    Google Scholar 
    Neelakanta, G., Sultana, H., Fish, D., Anderson, J. F. & Fikrig, E. Anaplasma phagocytophilum induces Ixodes scapularis ticks to express an antifreeze glycoprotein gene that enhances their survival in the cold. J. Clin. Investig. 120, 3179–3190 (2010).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Dey, A. K., Gel, Y. R. & Poor, H. V. What network motifs tell us about resilience and reliability of complex networks. Proc. Natl. Acad. Sci. USA 116, 19368–19373 (2019).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Nemergut, D. R. et al. Patterns and processes of microbial community assembly. Microbiol. Mol. 77, 342–356 (2013).
    Google Scholar 
    Coyte, K. Z., Rao, C., Rakoff-Nahoum, S. & Foster, K. R. Ecological rules for the assembly of microbiome communities. PLoS Biol. 19, e3001116 (2021).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Coyte, K. Z., Schluter, J. & Foster, K. R. The ecology of the microbiome: Networks, competition, and stability. Science 350, 663–666 (2015).ADS 
    CAS 
    PubMed 

    Google Scholar 
    McLoughlin, K., Schluter, J., Rakoff-Nahoum, S., Smith, A. L. & Foster, K. R. Host selection of microbiota via differential adhesion. Cell Host Microbe 19, 550–559 (2016).CAS 
    PubMed 

    Google Scholar 
    Sheridan, K. J. et al. Ergothioneine biosynthesis and functionality in the opportunistic fungal pathogen, Aspergillus fumigatus. Sci. Rep. 6, 1–17 (2016).
    Google Scholar 
    Rothfork, J. M. et al. Inactivation of a bacterial virulence pheromone by phagocyte-derived oxidants: New role for the NADPH oxidase in host defense. Proc. Natl. Acad. Sci. USA 101, 13867–13872 (2004).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Gaupp, R., Ledala, N. & Somerville, G. A. Staphylococcal response to oxidative stress. Front. Cell. Infect. Microbiol. Microbiol. 2, 33 (2012).
    Google Scholar 
    Matchado, M. S. et al. Network analysis methods for studying microbial communities: A mini review. Comput. Struct. Biotechnol. J. 19, 2687–2698 (2021).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Jiang, D. et al. Microbiome multi-omics network analysis: Statistical considerations, limitations, and opportunities. Front. Genet. 10, 995 (2019).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Gao, C. et al. Co-occurrence networks reveal more complexity than community composition in resistance and resilience of microbial communities. Nat. Commun. 13, 3867 (2022).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Mammeri, M. et al. Cryptosporidium parvum infection depletes butyrate producer bacteria in goat kid microbiome. Front. Microbiol. 16, 548737 (2020).
    Google Scholar 
    Foo, J. L., Ling, H., Lee, Y. S. & Chang, M. W. Microbiome engineering: Current applications and its future. Biotechnol. J. 12, 1600099 (2017).Inda, M. E., Broset, E., Lu, T. K. & de la Fuente-Nunez, C. Emerging frontiers in microbiome engineering. Trends Immunol. 40, 952–973 (2019). More

  • in

    Ecological analysis of Pavlovian fear conditioning in rats

    Watson, J. B. & Morgan, J. J. B. Emotional reactions and psychological experimentation. Am. J. Psychol. 28, 163–174 (1917).Article 

    Google Scholar 
    Watson, J. B. & Rayner, R. Conditioned emotional reactions. J. Exp. Psychol. 3, 1–14 (1920).Article 

    Google Scholar 
    LeDoux, J. Fear and the brain: where have we been, and where are we going. Biol. Psychiatry 44, 1229–1238 (1998).CAS 
    PubMed 
    Article 

    Google Scholar 
    Fendt, M. & Fanselow, M. S. The neuroanatomical and neurochemical basis of conditioned fear. Neurosci. Biobehav. Rev. 23, 743–760 (1999).CAS 
    PubMed 
    Article 

    Google Scholar 
    Maren, S. & Quirk, G. J. Neuronal signalling of fear memory. Nat. Rev. Neurosci. 5, 844–852 (2004).CAS 
    PubMed 
    Article 

    Google Scholar 
    Bouton, M. E., Mineka, S. & Barlow, D. H. A modern learning theory perspective on the etiology of panic disorder. Psychol. Rev. 108, 4–32 (2001).CAS 
    PubMed 
    Article 

    Google Scholar 
    Kim, J. J. & Jung, M. W. Neural circuits and mechanisms involved in Pavlovian fear conditioning: a critical review. Neurosci. Biobehav. Rev. 30, 188–202 (2006).PubMed 
    Article 

    Google Scholar 
    Watson, J. B. Psychology as the behaviorist views it. Psychological Rev. 20, 158–177 (1913).Article 

    Google Scholar 
    Pavlov, I. P. Conditioned Reflexes: An Investigation of the Physiological Activity of the Cerebral Cortex (Oxford University Press, 1927).Guthrie, E. R. Conditioning as a principle of learning. Psychological Rev. 37, 412–428 (1930).Article 

    Google Scholar 
    Kamin, L. J. in Miami Symposium on the Prediction of Behavior (ed. Jones, M. R.) 9–33 (University of Miami Press, 1968).Rescorla, R. A. Probability of shock in the presence and absence of CS in fear conditioning. J. Comp. Physiol. Psychol. 66, 1–5 (1968).CAS 
    PubMed 
    Article 

    Google Scholar 
    Wagner, A. R., Logan, F. A., Haberlandt, K. & Price, T. Stimulus selection in animal discrimination learning. J. Exp. Psychol. 76, 171–180 (1968).CAS 
    PubMed 
    Article 

    Google Scholar 
    Rescorla, R. A. & Wagner, A. R. A Theory of Pavlovian Conditioning: Variations in the Effectiveness of Reinforcement and Nonreinforcement 64–99 (Appleton-Century-Crofts, 1972).Josselyn, S. A. & Tonegawa, S. Memory engrams: recalling the past and imagining the future. Science 367, https://doi.org/10.1126/science.aaw4325 (2020).Tovote, P., Fadok, J. P. & Luthi, A. Neuronal circuits for fear and anxiety. Nat. Rev. Neurosci. 16, 317–331 (2015).CAS 
    PubMed 
    Article 

    Google Scholar 
    Haubensak, W. et al. Genetic dissection of an amygdala microcircuit that gates conditioned fear. Nature 468, 270–276 (2010).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Foa, E. B. & Rothbaum, B. O. Treating the Trauma of Rape: Cognitive Behavioral Therapy for PTSD (Guilford Press, 1998).Butler, A. C., Chapman, J. E., Forman, E. M. & Beck, A. T. The empirical status of cognitive-behavioral therapy: a review of meta-analyses. Clin. Psychol. Rev. 26, 17–31 (2006).PubMed 
    Article 

    Google Scholar 
    Delgado, M. R., Olsson, A. & Phelps, E. A. Extending animal models of fear conditioning to humans. Biol. Psychol. 73, 39–48 (2006).CAS 
    PubMed 
    Article 

    Google Scholar 
    Mahan, A. L. & Ressler, K. J. Fear conditioning, synaptic plasticity and the amygdala: implications for posttraumatic stress disorder. Trends Neurosci. 35, 24–35 (2012).CAS 
    PubMed 
    Article 

    Google Scholar 
    Craske, M. G. et al. What is an anxiety disorder? Focus 9, 20 (2011).
    Google Scholar 
    LeDoux, J. E. The Emotional Brain: the Mysterious Underpinnings of Emotional Life (Simon & Schuster, 1996).Fanselow, M. S. From contextual fear to a dynamic view of memory systems. Trends Cogn. Sci. 14, 7–15 (2010).PubMed 
    Article 

    Google Scholar 
    Lima, S. L. & Dill, L. M. Behavioral decisions made under the risk of predation—a review and prospectus. Can. J. Zool. 68, 619–640 (1990).Article 

    Google Scholar 
    Bednekoff, P. A. Foraging in the Face of Danger 305–329 (University of Chicago Press, 2007).Stephens, D. W. Decision ecology: foraging and the ecology of animal decision making. Cogn. Affect Behav. Neurosci. 8, 475–484 (2008).PubMed 
    Article 

    Google Scholar 
    Beckers, T., Krypotos, A. M., Boddez, Y., Effting, M. & Kindt, M. What’s wrong with fear conditioning? Biol. Psychol. 92, 90–96 (2013).PubMed 
    Article 

    Google Scholar 
    Mobbs, D. & Kim, J. J. Neuroethological studies of fear, anxiety, and risky decision-making in rodents and humans. Curr. Opin. Behav. Sci. 5, 8–15 (2015).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Pellman, B. A. & Kim, J. J. What can ethobehavioral studies tell us about the Brain’s fear system. Trends Neurosci. 39, 420–431 (2016).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Thorndike, E. Biological Lectures from the Marine Laboratory at Woods’ Holl, USA, for 1899. Nature 62, 411 (1900).Bolles, R. C. Species-specific defense reactions and avoidance learning. Psychol. Rev. 77, 32–48 (1970).Choi, J. S. & Kim, J. J. Amygdala regulates risk of predation in rats foraging in a dynamic fear environment. Proc. Natl Acad. Sci. USA 107, 21773–21777 (2010).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Zambetti, P. R., Schuessler, B. P. & Kim, J. J. Sex differences in foraging rats to naturalistic aerial predator stimuli. iScience 16, 442–452 (2019).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Yilmaz, M. & Meister, M. Rapid innate defensive responses of mice to looming visual stimuli. Curr. Biol. 23, 2011–2015 (2013).CAS 
    PubMed 
    Article 

    Google Scholar 
    Papes, F., Logan, D. W. & Stowers, L. The vomeronasal organ mediates interspecies defensive behaviors through detection of protein pheromone homologs. Cell 141, 692–703 (2010).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Tolman, E. C. Cognitive maps in rats and men. Psychol. Rev. 55, 189–208 (1948).CAS 
    PubMed 
    Article 

    Google Scholar 
    Wilensky, A. E., Schafe, G. E. & LeDoux, J. E. The amygdala modulates memory consolidation of fear-motivated inhibitory avoidance learning but not classical fear conditioning. J. Neurosci. 20, 7059–7066 (2000).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Lee, T. & Kim, J. J. Differential effects of cerebellar, amygdalar, and hippocampal lesions on classical eyeblink conditioning in rats. J. Neurosci. 24, 3242–3250 (2004).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Stiedl, O. & Spiess, J. Effect of tone-dependent fear conditioning on heart rate and behavior of C57BL/6N mice. Behav. Neurosci. 111, 703–711 (1997).CAS 
    PubMed 
    Article 

    Google Scholar 
    Guimaraes, F. S., Hellewell, J., Hensman, R., Wang, M. & Deakin, J. F. Characterization of a psychophysiological model of classical fear conditioning in healthy volunteers: influence of gender, instruction, personality and placebo. Psychopharmacology 104, 231–236 (1991).CAS 
    PubMed 
    Article 

    Google Scholar 
    Mackintosh, N. J. The Psychology of Animal Learning (Academic Press, 1974).Bouton, M. E. Learning and Behavior (Sinauer Associates 2007).Sheafor, P. J. “Pseudoconditioned” jaw movements of the rabbit reflect associations conditioned to contextual background cues. J. Exp. Psychol. Anim. Behav. Process 1, 245–260 (1975).CAS 
    PubMed 
    Article 

    Google Scholar 
    Rescorla, R. A. Behavioral studies of Pavlovian conditioning. Annu. Rev. Neurosci. 11, 329–352 (1988).CAS 
    PubMed 
    Article 

    Google Scholar 
    Thompson, R. F. & Krupa, D. J. Organization of memory traces in the mammalian brain. Annu. Rev. Neurosci. 17, 519–549 (1994).CAS 
    PubMed 
    Article 

    Google Scholar 
    Fanselow, M. S. & Wassum, K. M. The origins and organization of vertebrate pavlovian conditioning. Cold Spring Harb. Perspect. Biol. 8, a021717 (2015).PubMed 
    Article 

    Google Scholar 
    Lee, H. J., Berger, S. Y., Stiedl, O., Spiess, J. & Kim, J. J. Post-training injections of catecholaminergic drugs do not modulate fear conditioning in rats and mice. Neurosci. Lett. 303, 123–126 (2001).CAS 
    PubMed 
    Article 

    Google Scholar 
    Palgi, Y., Gelkopf, M. & Berger, R. The inoculating role of previous exposure to potentially traumatic life events on coping with prolonged exposure to rocket attacks: a lifespan perspective. Psychiatry Res. 227, 296–301 (2015).PubMed 
    Article 

    Google Scholar 
    Somer, E. et al. Israeli civilians under heavy bombardment: prediction of the severity of post-traumatic symptoms. Prehosp. Disaster Med. 24, 389–394 (2009).PubMed 
    Article 

    Google Scholar 
    Alexander, B. K., Beyerstein, B. L., Hadaway, P. F. & Coambs, R. B. Effect of early and later colony housing on oral ingestion of morphine in rats. Pharm. Biochem. Behav. 15, 571–576 (1981).CAS 
    Article 

    Google Scholar 
    Gage, S. H. & Sumnall, H. R. Rat Park: how a rat paradise changed the narrative of addiction. Addiction 114, 917–922 (2019).PubMed 
    Article 

    Google Scholar 
    Fanselow, M. S. & Lester, L. S. A Functional Behavioristic Approach to Aversively Motivated Behavior: Predatory Imminence as a Determinant of the Topography of Defensive Behavior 185–212 (Lawrence Erlbaum Associates Inc, 1988).Cain, C. & LeDoux, J. Brain mechanisms of Pavlovian and instrumental aversive conditioning. Handb. Behav. Neurosci. 17, 103–124 (2008).Article 

    Google Scholar 
    Choi, J. S., Cain, C. K. & LeDoux, J. E. The role of amygdala nuclei in the expression of auditory signaled two-way active avoidance in rats. Learn Mem. 17, 139–147 (2014).Article 

    Google Scholar 
    Steimer, T. The biology of fear- and anxiety-related behaviors. Dialogues Clin. Neurosci. 4, 231–249 (2002).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Fanselow, M. S. The role of learning in threat imminence and defensive behaviors. Curr. Opin. Behav. Sci. 24, 44–49 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Fanselow, M. S. Associative vs topographical accounts of the immediate shock freezing deficit in rats—implications for the response selection-rules governing species-specific defensive reactions. Learn. Motiv. 17, 16–39 (1986).Article 

    Google Scholar 
    Landeira-Fernandez, J., DeCola, J. P., Kim, J. J. & Fanselow, M. S. Immediate shock deficit in fear conditioning: effects of shock manipulations. Behav. Neurosci. 120, 873–879 (2006).CAS 
    PubMed 
    Article 

    Google Scholar 
    Hull, C. L. A functional interpretation of the conditioned reflex. Psychol. Rev. 36, 498–511 (1929).Article 

    Google Scholar 
    Lazarus, A. A. Behavior Therapy and Beyond (McGraw-Hill Companies, 1971).Öhman, A. & Mineka, S. Fears, phobias, and preparedness: toward an evolved module of fear and fear learning. Psychol. Rev. 108, 483–522 (2001).PubMed 
    Article 

    Google Scholar 
    Lee, H. & Kim, J. J. Amygdalar NMDA receptors are critical for new fear learning in previously fear-conditioned rats. J. Neurosci. 18, 8444–8454 (1998).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Mathis, A. et al. DeepLabCut: markerless pose estimation of user-defined body parts with deep learning. Nat. Neurosci. 21, 1281–1289 (2018).CAS 
    PubMed 
    Article 

    Google Scholar  More

  • in

    Cell death responses to acute high light mediated by non-photochemical quenching in the dinoflagellate Karenia brevis

    Brand, L. E., Campbell, L. & Bresnan, E. Karenia: The biology and ecology of a toxic genus. Harmful Algae 14, 156–178 (2012).
    Google Scholar 
    Hetland, R. D. & Campbell, L. Convergent blooms of Karenia brevis along the Texas coast. Geophys. Res. Lett. 34, 1–5 (2007).
    Google Scholar 
    Liu, G., Janowitz, G. S. & Kamykowski, D. A biophysical model of population dynamics of the autotrophic dinoflagellate Gymnodinium breve. Mar. Ecol. Prog. Ser. 210, 101–124 (2001).ADS 
    CAS 

    Google Scholar 
    Walsh, J. J. et al. Red tides in the Gulf of Mexico: Where, when, and why?. J. Geophys. Res. 111, C11003 (2006).ADS 

    Google Scholar 
    Bidle, K. D. The molecular ecophysiology of programmed cell death in marine phytoplankton. Ann. Rev. Mar. Sci. 7, 341–375 (2015).PubMed 

    Google Scholar 
    Bidle, K. D. & Bender, S. J. Iron starvation and culture age activate metacaspases and programmed cell death in the marine diatom Thalassiosira pseudonana. Eukaryot. Cell 7, 223–236 (2008).CAS 
    PubMed 

    Google Scholar 
    Bidle, K. D., Haramaty, L., Barcelos, R. J. & Falkowski, P. Viral activation and recruitment of metacaspases in the unicellular coccolithophore, Emiliania huxleyi. Proc. Natl. Acad. Sci. 104, 6049–6054 (2007).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Vardi, A. et al. Programmed cell death of the dinoflagellate Peridinium gatunense is mediated by CO2 limitation and oxidative stress. Curr. Biol. 9, 1061–1064 (1999).CAS 
    PubMed 

    Google Scholar 
    Zuppini, A., Andreoli, C. & Baldan, B. Heat stress: An inducer of programmed cell death in Chlorella saccharophila. Plant Cell Physiol. 48, 1000–1009 (2007).CAS 
    PubMed 

    Google Scholar 
    Britt, A. B. DNA damage and repair in plants. Annu. Rev. Plant Physiol. Plant Mol. Biol. 47, 75–100 (1996).CAS 
    PubMed 

    Google Scholar 
    Jimenez, C. et al. Different ways to die: Cell death modes of the unicellular chlorophyte Dunaliella viridis exposed to various environmental stresses are mediated by the caspase-like activity DEVDase. J. Exp. Bot. 60, 815–828 (2009).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Moharikar, S., D’Souza, J. S., Kulkarni, A. B. & Rao, B. J. Apoptotic-like cell death pathway is induced in unicellular chlorophyte chlamydomonas reinhardtii (Chlorophyceae) cells following UV irradiation: Detection and functional analyses. J. Phycol. 42, 423–433 (2006).CAS 

    Google Scholar 
    Li, Z., Wakao, S., Fischer, B. B. & Niyogi, K. K. Sensing and responding to excess light. Annu. Rev. Plant Biol. 60, 239–260 (2009).CAS 
    PubMed 

    Google Scholar 
    Niyogi, K. K. Photoprotection revisited: Genetic and molecular approaches. Annu. Rev. Plant Physiol. Plant Mol. Biol. 50, 333–359 (1999).CAS 
    PubMed 

    Google Scholar 
    Apel, K. & Hirt, H. Reactive oxygen species: Metabolism, Oxidative Stress, and Signal Transduction. Annu. Rev. Plant Biol. 55, 373–399 (2004).CAS 
    PubMed 

    Google Scholar 
    Müller, P., Li, X. & Niyogi, K. K. Non-photochemical quenching. A response to excess light energy. Plant Physiol. 125, 1558–1566 (2001).PubMed 
    PubMed Central 

    Google Scholar 
    Bidle, K. D. Programmed cell death in unicellular phytoplankton. Curr. Biol. 26, R594–R607 (2016).CAS 
    PubMed 

    Google Scholar 
    McKay, L., Kamykowski, D., Milligan, E., Schaeffer, B. & Sinclair, G. Comparison of swimming speed and photophysiological responses to different external conditions among three Karenia brevis strains. Harmful Algae 5, 623–636 (2006).CAS 

    Google Scholar 
    Miller-Morey, J. S. & Van Dolah, F. M. Differential responses of stress proteins, antioxidant enzymes, and photosynthetic efficiency to physiological stresses in the Florida red tide dinoflagellate, Karenia brevis. Comp. Biochem. Physiol. Part C Toxicol. Pharmacol. 138, 493–505 (2004).
    Google Scholar 
    Tilney, C. L., Shankar, S., Hubbard, K. A. & Corcoran, A. A. Is Karenia brevis really a low-light-adapted species?. Harmful Algae 90, 101709 (2019).CAS 
    PubMed 

    Google Scholar 
    Yuasa, K., Shikata, T., Kuwahara, Y. & Nishiyama, Y. Adverse effects of strong light and nitrogen deficiency on cell viability, photosynthesis, and motility of the red-tide dinoflagellate Karenia mikimotoi. Phycologia 57, 525–533 (2018).CAS 

    Google Scholar 
    Krause, G. H. & Jahns, P. Non-photochemical energy dissipation determined by chlorophyll fluorescence quenching: Characterization and function. In Chlorophyll a Fluorescence 463–495 (Springer, Netherlands, Cham, 2004).
    Google Scholar 
    Evens, T. J. Photophysiological responses of the toxic red-tide dinoflagellate Gymnodinium breve (Dinophyceae) under natural sunlight. J. Plankton Res. 23, 1177–1194 (2001).CAS 

    Google Scholar 
    Heil, C. A. et al. Influence of daylight surface aggregation behavior on nutrient cycling during a Karenia brevis (Davis) G. Hansen & Ø Moestrup bloom: Migration to the surface as a nutrient acquisition strategy. Harmful Algae 38, 86–94 (2014).CAS 

    Google Scholar 
    Errera, R. Response of the Toxic Dinoflagellate Karenia Brevis to Current and Projected Environmental Conditions. (Texas A&M University, PhD dissertation, 2013).Guillard, R. R. L. & Hargraves, P. E. Stichochrysis immobilis is a diatom, not a chrysophyte. Phycologia 32, 234–236 (1993).
    Google Scholar 
    Dingman, J. E. & Lawrence, J. E. Heat-stress-induced programmed cell death in Heterosigma akashiwo (Raphidophyceae). Harmful Algae 16, 108–116 (2012).
    Google Scholar 
    Lin, Q. et al. Differential cellular responses associated with oxidative stress and cell fate decision under nitrate and phosphate limitations in Thalassiosira pseudonana: Comparative proteomics. PLoS ONE 12(9), e0184849 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    Choi, C. J., Brosnahan, M. L., Sehein, T. R., Anderson, D. M. & Erdner, D. L. Insights into the loss factors of phytoplankton blooms: The role of cell mortality in the decline of two inshore Alexandrium blooms. Limnol. Oceanogr. 62, 1742–1753 (2017).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Johnson, J. G., Janech, M. G. & Van Dolah, F. M. Caspase-like activity during aging and cell death in the toxic dinoflagellate Karenia brevis. Harmful Algae 31, 41–53 (2014).CAS 
    PubMed 

    Google Scholar 
    Jauzein, C. & Erdner, D. L. Stress-related responses in Alexandrium tamarense cells exposed to environmental Changes. J. Eukaryot. Microbiol. 60, 526–538 (2013).CAS 
    PubMed 

    Google Scholar 
    Severin, T. & Erdner, D. L. The phytoplankton taxon-dependent oil response and its microbiome: Correlation but not causation. Front. Microbiol. 10, 1–14 (2019).
    Google Scholar 
    Ralph, P. J. & Gademann, R. Rapid light curves: A powerful tool to assess photosynthetic activity. Aquat. Bot. 82, 222–237 (2005).CAS 

    Google Scholar 
    Suzuki, N. & Mittler, R. Reactive oxygen species and temperature stresses: A delicate balance between signaling and destruction. Physiol. Plant. 126, 45–51 (2006).CAS 

    Google Scholar 
    Krause, G. H. & Weis, E. Chlorophyll fluorescence and photosynthesis: The basics. Annu. Rev. Plant Physiol. Plant Mol. Biol. 42, 313–349 (1991).CAS 

    Google Scholar 
    Gechev, T. S. & Hille, J. Hydrogen peroxide as a signal controlling plant programmed cell death. J. Cell Biol. 168, 17–20 (2005).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Miller, G., Suzuki, N., Ciftci-Yilmaz, S. & Mittler, R. Reactive oxygen species homeostasis and signalling during drought and salinity stresses. Plant. Cell Environ. 33, 453–467 (2010).CAS 
    PubMed 

    Google Scholar 
    Purvis, A. C. Role of the alternative oxidase in limiting superoxide production by plant mitochondria. Physiol. Plant. 100, 165–170 (1997).CAS 

    Google Scholar 
    Demmig-Adams, B. & Adams Iii, W. W. Photoprotection and other responses of plants to high light stress. Annu. Rev. Plant Biol. 43, 599–626 (1992).CAS 

    Google Scholar 
    Cui, Y., Zhang, H. & Lin, S. Enhancement of non-photochemical quenching as an adaptive strategy under phosphorus deprivation in the Dinoflagellate Karlodinium veneficum. Front. Microbiol. 8, 1–14 (2017).
    Google Scholar 
    Cassell, R. T., Chen, W., Thomas, S., Liu, L. & Rein, K. S. Brevetoxin, the dinoflagellate neurotoxin, localizes to thylakoid membranes and interacts with the light-harvesting complex II (LHCII) of photosystem II. ChemBioChem 16, 1060–1067 (2015).CAS 
    PubMed 

    Google Scholar 
    Milne, A., Davey, M. S., Worsfold, P. J., Achterberg, E. P. & Taylor, A. R. Real-time detection of reactive oxygen species generation by marine phytoplankton using flow injection-chemiluminescence. Limnol. Oceanogr. Methods 7, 706–715 (2009).CAS 

    Google Scholar 
    Berman-Frank, I. et al. Segregation of nitrogen fixation and oxygenic photosynthesis in the marine cyanobacterium trichodesmium. Science (80-) 294, 1534–1537 (2001).ADS 
    CAS 

    Google Scholar 
    Triantaphylidès, C. et al. Singlet oxygen is the major reactive oxygen species involved in photooxidative damage to plants. Plant Physiol. 148, 960–968 (2008).PubMed 
    PubMed Central 

    Google Scholar 
    Gao, Y. & Erdner, D. L. Dynamics of cell death across growth stages and the diel cycle in the dinoflagellate Karenia brevis. J. Eukaryot. Microbiol. https://doi.org/10.1111/jeu.12874 (2021).Article 
    PubMed 

    Google Scholar 
    Xu, K., Jiang, H., Juneau, P. & Qiu, B. Comparative studies on the photosynthetic responses of three freshwater phytoplankton species to temperature and light regimes. J. Appl. Phycol. 24, 1113–1122 (2012).CAS 

    Google Scholar 
    Yamori, W., Makino, A. & Shikanai, T. A physiological role of cyclic electron transport around photosystem I in sustaining photosynthesis under fluctuating light in rice. Sci. Rep. 6, 20147 (2016).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Berman-Frank, I., Bidle, K. D., Haramaty, L. & Falkowski, P. G. The demise of the marine cyanobacterium, Trichodesmium spp., via an autocatalyzed cell death pathway. Limnol. Oceanogr. 49, 997–1005 (2004).ADS 

    Google Scholar  More