More stories

  • in

    Flow patterns in circular fish tanks and its relations with flow rate and nozzle features

    Rotational velocityFigure 3 shows the effect of flow rate, nozzle diameter and number of nozzles on the rotational velocity of water in a circular tank. The results indicate that the rotational velocity increases with increasing flow rates and deceasing nozzle diameter. It could be seen that, the rotational velocity decreased from 10.1 to 5.0 cm s−1, when the nozzle diameter increased from 10 to 20 mm, respectively for 5 nozzles used, and it decreased from 5.1 to 4.0 cm s−1, when the nozzle diameter increased from 10 to 15 mm, respectively, for 10 nozzles used with 5 m3 h−1 flow rate. At 15 m3 h−1, the rotational velocity was decreased from 23.5 to 17.5, 12.0 to 7.5, 10.0 to 6.9, 7.6 to 4.7 and 5.9 to 4.0 cm s−1 when the nozzle diameter increased from 10 to 20 mm, respectively, for 5, 10, 15, 20 and 25 nozzles, respectively. The results also indicate that when the nozzle diameter increased from 20 to 25 mm, the rotational velocity decreased from 19.0 to 16.5, 12.0 to 10.0 and 7.1 to 5.5 cm s−1 for 3, 6 and 9 nozzles, respectively, with 15 m3 h−1 flow rate.Figure 3Effect of flow rate, nozzle diameter and number of nozzles on the rotational velocity of water in a circular tank.Full size imageAt 30 m3 h−1 flow rate, the highest value of the rotational velocity was 33.5 cm s−1 was found for 5 nozzles and 10 mm nozzle diameter. While, the lowest value of the rotational velocity was 7.3 cm s−1 was found for 25 nozzles and 25 mm nozzle diameter. At 45 m3 h−1 flow rate, the rotational velocity ranged from 11.0 to 49.9 cm s−1 for all treatments under study.At 60 m3 h−1 flow rate, the rotational velocity deceased from 61.0 to 50.1, 47.7 to 34.0, 36.3 to 23.0, 23.5 to 17.5, 21.0 to 15.0 and 17.0 to 11.5 cm s−1 when the nozzle diameter increased from 10 to 20 mm, respectively at 5, 10, 15, 20, 25 and 30 number of nozzles. The results also indicate that, when the nozzle diameter increased from 20 to 25 mm, the rotational velocity decreased from 56.0 to 47.0, 43.0 to 33.0, 27.0 to 22.0 and 19.0 to 16.5 cm s−1 at 3, 6, 9 and 12 nozzles, respectively.At 75 m3 h−1 flow rate, the rotational velocity deceased from 60.9 to 49.1, 48.4 to 38.0, 39.0 to 30, 31.8 to 23.0, 23.5 to 17.5 and 22.0 to 15.0 cm s−1 when the nozzle diameter increased from 10 to 20 mm, respectively for 5, 10, 15, 20, 25 and 30 nozzles, respectively. The results also indicate that, when the nozzle diameter increased from 20 to 25 mm, the rotational velocity decreased from 50.48 to 43.0 to 38.5, 33.0 to 27.5 and 23.5 to 22.0 cm s−1 for 3, 6, 9 and 12 nozzles, respectively.The results also indicate that the highest values of the rotational velocities were 10.1, 23.5, 33.5, 49.9, 60.9 and 61.0 cm s−1 were found for 5 nozzles and 10 mm nozzle diameter at 5, 15, 30, 45, 60 and 75 m3 h−1 flow rate, respectively. While, the lowest values of the rotational velocities were 4.0, 7.5 and 11.5 cm s−1 for 25 nozzles and 15 mm nozzle diameter at 5, 15 and 30 m3 h−1 flow rate, respectively. They were 11.5 and 15 cm s−1 were found for 30 nozzles and 15 mm nozzle diameter at 60 and 75 m3 h−1 flow rate, respectively. The velocity of water obtained seemed to be in the recommended range of safe and proper velocity for fish according to12. Due to it is effective compromise to allow heavy solids settle rapidly, yet sufficiently fast to create “good” hydraulics. Timmons and Youngs18 mentioned that the water velocity needed to maintain self-cleaning properties ranges from 3 to 40 cm s−1 varying greatly according to the physical properties of the biosolids. When fish swims at lower speed than its optimal, a large amount of energy will be used for higher spontaneous activity such as aggression. In contrast, when fish swim at higher speed than optimal, they become stressful, unstable, increase lactate production and fatigue6.Multiple regression analysis was carried out to obtain a relationship between the rotational velocity of water as dependent variable and different both of flow rate and nozzle diameter as independent variables. The best fit for this relationship with coefficient of determination of 0.95 and an error of 1.06% is in the following form:-$$ RV = 6.97 + 0.41Q – 0.19Dquad {text{R}}^{{2}} = 0.95 $$
    (3)
    where RV is the rotational velocity of water, cm s−1, Q is the water flow rate, m3 h−1, D is the nozzle diameter, mm.This equation could be applied in the range of 5 to 75 m3 h−1 water flow rate and from 10 to 25 mm of nozzle diameter.Impulse force of waterFigure 4 shows the effect of flow rate, diameter and number of nozzles on the impulse force of water in a circular tank. The results indicate that the impulse force of water increases with increasing flow rates and deceasing nozzle diameter and number of nozzles. It could be seen that, the impulse force of water decreased from 5.1 to 1.7 N, when the number of nozzles increased from 5 to 15, respectively at 10 nozzle diameter, and it decreased from 2.3 to 1.2 N, when the number of nozzles increased from 5 to 10, respectively, at 15 diameter nozzle with 5 m3 h−1 flow rate. At 15 m3 h−1, the impulse force of water was decreased from 84.7 to 9.4 N when the number of nozzles increased from 5 to 30, respectively 10 mm diameter nozzle. The results also indicate that when the number of nozzles increased from 5 to 25, the impulse force of water decreased from 14.8 to 1.4 N at 15 mm nozzle diameter, respectively, and it decreased from 9.5 to 1.9 and 5.3 to 1.3 N at 20 and 25 mm, respectively, when the number of nozzles increased from 3 to 9.Figure 4Effect of flow rate, nozzle diameter and number of nozzles on the impulse force of water in a circular tank.Full size imageAt 30 m3 h−1 flow rate, the impulse force of water deceased from 84.7 to 46.9, 56.9 to 14.8, 28.5 to 5.3, 14.9 to 3.0 and 11.8 to 2.2 N when the nozzle diameter increased from 10 to 15 mm, respectively at 5, 10, 15, 20 and 25 nozzles. The results also indicate that, when the nozzle diameter increased from 20 to 25 mm, the impulse force of water decreased from 21.4 to 14.9, 14.8 to 5.4, 5.3 to 2.2 and 2.3 to 1.9 N for 3, 6, 9 and 12 nozzles, respectively.At 45 m3 h−1 flow rate, the impulse force of water was ranged from 2.1 to 111.2 N for all treatments under this study. Also, at 60 m3 h−1 flow rate, the impulse force of water ranged from 5.1 to 151.3 N for all treatments under this study. At 75 m3 h−1 flow rate, the highest value of the impulse force of water 211.2 N was found for 5 numbers of nozzles and 10 mm nozzle diameter, respectively. While, the lowest value of the impulse force of water was 9.1 N was found for 12 nozzles and 25 mm nozzle diameter, respectively.The results also indicate that the highest value of the impulse force of water 211.2 N was found for 5 nozzles and 10 mm nozzle diameter at 75 m3 h−1 flow rate, respectively. While, the lowest value of the impulse force of water was 1.2 N was found for 10 nozzles and 15 mm nozzle diameter at 5 m3 h−1 flow rate, respectively.The results indicated that, the relationship between the rotational velocity and impulse force of water is linear relationship at the same treatments. When the rotational velocity increased from 10.7 to 37.6, 8.1 to 28.8, 10.2 to 36.0 and 11.0 to 31.9 cm s−1, the impulse force of water increased from 3.1 to 106.6, 1.8 to 31.1, 1.3 to 32.5 and 1.4 to 22.8 N, respectively, at the same treatments. The trend of these results agreed with those obtained by19.Multiple regression analysis was carried out to obtain a relationship between the impulse force of water as dependent variable and different both of flow rate and nozzle diameter as independent variables. The best fit for this relationship with coefficient of determination of 0.88 and an error of 2.13% is in the following form:-$$ F_{i} = 38.18 + 0.67Q – 2.35Dquad {text{R}}^{{2}} = 0.88 $$
    (4)
    This equation could be applied in the range of 5 to 75 m3 h−1 water flow rate and from 10 to 25 mm of nozzle diameter.Average velocity of waterFigure 5 shows the effect of flow rate, diameter and number of nozzles on the average velocity of water in a circular tank. The results indicate that the average velocity of water increases with increasing flow rates and deceasing nozzle diameter and number of nozzles. It could be seen that, the average velocity of water decreased from 3.32 to 1.59 cm s−1, when the number of nozzles increased from 5 to 15, respectively at 10 nozzle diameter, and it decreased from 1.13 to 1.07 cm s−1, when the number of nozzles increased from 5 to 10, respectively, at 15 diameter nozzle with 5 m3 h−1 flow rate. At 15 m3 h−1, the average velocity of water was decreased from 12.03 to 4.33 cm s−1 when the number of nozzles increased from 5 to 30, respectively 10 mm diameter nozzle. The results also indicate that when the number of nozzles increased from 5 to 25, the average velocity of water decreased from 6.93 to 2.89 cm s−1 at 15 mm nozzle diameter, respectively, and it decreased from 7.55 to 4.00 and 4.89 to 2.95 cm s−1 at 20 and 25 mm, respectively, when the number of nozzles increased from 3 to 9.Figure 5Effect of flow rate, nozzle diameter and number of nozzles on the average velocity of water in a circular tank.Full size imageAt 30 m3 h−1 flow rate, the highest value of the average velocity of water 18.51 cm s−1 was found for 5 nozzles and 10 mm nozzle diameter. While, the lowest value of the average velocity of water was 4.65 cm s−1 was found for 12 nozzles and 25 mm nozzle diameter. At 45 m3 h−1 flow rate, the average velocity of water ranged from 6.66 to 23.26 for all treatments under study, also, at 60 m3 h−1 flow rate, the average velocity of water ranged from 9.23 to 34.82 for all treatments under study. At 75 m3 h−1 flow rate, the average velocity of water ranged from 10.00 to 48.76 for all treatment of this study.The results also indicate that the highest value of the average velocity of water 48.76 cm s−1 was found for 5 nozzles and 10 mm nozzle diameter at 75 m3 h−1 flow rate, respectively. While, the lowest value of the average velocity of water was 1.07 cm s−1 was found for 10 nozzles and 15 mm nozzle diameter at 5 m3 h−1 flow rate, respectively. These results agreed with those obtained by18,20. Fish distribution in the circular tank is influenced by the heterogeneity of water velocity in the area between inlet flow and the center of the tank9. Fish distribution in the circular tank is mostly concentrated in the area between high and low velocity area. The high velocity area will be avoided by most fishes as it requires high swimming energy, while dead volumes (low velocity area) are unfavorable condition for fish (low DO and higher metabolites accumulation)21.Multiple regression analysis was carried out to obtain a relationship between the average velocity of water as dependent variable and different both of flow rate and nozzle diameter as independent variables. The best fit for this relationship with coefficient of determination of 0.91 and an error of 1.48% is in the following form:$$ V_{avg} = 6.53 + 0.26Q – 0.37Dquad {text{R}}^{{2}} = 0.91 $$
    (5)
    This equation could be applied in the range of 5 to 75 m3 h−1 water flow rate and from 10 to 25 mm of nozzle diameter. More

  • in

    Multidecadal, continent-level analysis indicates agricultural practices impact wheat aphid loads more than climate change

    El Bilali, H., Callenius, C., Strassner, C. & Probst, L. Food and nutrition security and sustainability transitions in food systems. Food Energy Secur 8, e00154 (2019).Article 

    Google Scholar 
    De Raymond, A. B. & Goulet, F. Science, technology and food security: An introduction. Sci. Technol. Soc. 25, 7–18 (2020).Article 

    Google Scholar 
    Wang, C. et al. Occurrence of crop pests and diseases has largely increased in China since 1970. Nat. Food 3, 57–65 (2022).Article 

    Google Scholar 
    Deutsch, C. A. et al. Increase in crop losses to insect pests in a warming climate. Science 361, 916–919 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    Verger, P. J. P. & Boobis, A. R. Reevaluate pesticides for food security and safety. Science 341, 717–718 (2013).CAS 
    PubMed 
    Article 

    Google Scholar 
    Humann‐Guilleminot, S. et al. A nation‐wide survey of neonicotinoid insecticides in agricultural land with implications for agri‐environment schemes. J. Appl. Ecol. 56, 1502–1514 (2019).Article 
    CAS 

    Google Scholar 
    Haynes, K. J., Allstadt, A. J. & Klimetzek, D. Forest defoliator outbreaks under climate change: Effects on the frequency and severity of outbreaks of five pine insect pests. Glob. Change Biol. 20, 2004–2018 (2014).Article 

    Google Scholar 
    Sheppard, L., Bell, J. R., Harrington, R. & Reuman, D. C. Changes in large-scale climate alter spatial synchrony of aphid pests. Nat. Clim. Change 6, 610–613 (2016).Article 

    Google Scholar 
    Skendžić, S. et al. The impact of climate change on agricultural insect pests. Insects 12, 440 (2021).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    WASDE. World Agricultural Supply and Demand Estimates 1554–9089 (World Agricultural Outlook Board, 2012).FAOSTAT. Food and agriculture organisation of the United Nations. http://faostat.fao.org/ (2018).Bellard, C. et al. Impacts of climate change on the future of biodiversity. Ecol. Lett. 15, 365–377 (2012).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Bebber, D. P. Range-expanding pests and pathogens in a warming world. Annu. Rev. Phytopathol. 53, 335–356 (2015).CAS 
    PubMed 
    Article 

    Google Scholar 
    Jactel, H., Koricheva, J. & Castagneyrol, B. Responses of forest insect pests to climate change: Not so simple. Curr. Opin. Insect Sci. 35, 103–108 (2019).PubMed 
    Article 

    Google Scholar 
    Stephane, A. P., Derocles, D. H., Lunt Sophie, C. F. & Moss., B. Climate warming alters the structure of farmland tritrophic ecological networks and reduces crop yield. Mol. Ecol. 27, 4931–4946 (2018).Article 

    Google Scholar 
    Nechols, J. R. The potential impact of climate change on non-target risks from imported generalist natural enemies and on biological control. Bio. Control 66, 37–44 (2021).
    Google Scholar 
    Tian, B. et al. Elevated temperature reduces wheat grain yield by increasing pests and decreasing soil mutualists. Pest Manag. Sci. 75, 466–475 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    Lehmann, P. et al. Complex responses of global insect pests to climate warming. Front. Ecol. Environ. 18, 141–150 (2020).Article 

    Google Scholar 
    Zhao, F., Zhang, W., Hoffmann, A. A. & Ma, C. Night warming on hot days produces novel impacts on development, survival, and reproduction in a small arthropod. J. Anim. Ecol. 83, 769–778 (2014).PubMed 
    Article 

    Google Scholar 
    Marini, L. et al. Climate drivers of bark beetle outbreak dynamics in Norway spruce forests. Ecography 40, 1426–1435 (2017).Article 

    Google Scholar 
    Bale, J. S. et al. Herbivory in global climate change research: Direct effects of rising temperature on insect herbivores. Glob. Change Biol. 8, 1–16 (2002).Article 

    Google Scholar 
    Jamieson, M. A., Trowbridge, A. M., Raffa, K. F. & Lindroth, R. L. Consequences of climate warming and altered precipitation patterns for plant-insect and multitrophic interactions. Plant Physiol. 160, 1719–1727 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Gagic, V. et al. Better outcomes for pest pressure, insecticide use, and yield in less intensive agricultural landscapes. Proc. Natl Acad. Sci. USA 118, 1–6 (2021).Article 
    CAS 

    Google Scholar 
    Paredes, D. et al. Landscape simplification increases vineyard pest outbreaks and insecticide use. Ecol. Lett. 24, 73–83 (2021).PubMed 
    Article 

    Google Scholar 
    Brattsten, L. B., Holyoke, C. W., Leeper, J. R. & Raffa, K. F. Insecticide resistance: Challenge to pest management and basic research. Science 231, 1255–1260 (1986).CAS 
    PubMed 
    Article 

    Google Scholar 
    Haddi, K. et al. Rethinking biorational insecticides for pest management: Unintended effects and consequences. Pest Manag. Sci. 76, 2286–2293 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    Gould, F., Brown, Z. S. & Kuzma, J. Wicked evolution: Can we address the sociobiological dilemma of pesticide resistance? Science 360, 728–732 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    Wei, N. et al. Transcriptome analysis and identification of insecticide tolerance-related genes after exposure to insecticide in Sitobion avenae. Genes 1012, 951 (2019).Article 
    CAS 

    Google Scholar 
    Gong, X. et al. Feasibility of reinforced post-endogenous denitrification coupling with synchronous nitritation, denitrification and phosphorus removal for high-nitrate sewage treatment using limited carbon source in municipal wastewater. Chemosphere 269, 128687 (2021).CAS 
    PubMed 
    Article 

    Google Scholar 
    Tilman, D. et al. Agricultural sustainability and intensive production practices. Nature 418, 671–677 (2002).CAS 
    PubMed 
    Article 

    Google Scholar 
    Geiger, F. et al. Persistent negative effects of pesticides on biodiversity and biological control potential on European farmland. Basic Appl. Ecol. 11, 97–105 (2010).CAS 
    Article 

    Google Scholar 
    Muneret, L. et al. Evidence that organic farming promotes pest control. Nat. Sustain 1, 361–368 (2018).Article 

    Google Scholar 
    Lu, Y. et al. Widespread adoption of Bt cotton and insecticide decrease promotes biocontrol services. Nature 487, 362–365 (2012).CAS 
    PubMed 
    Article 

    Google Scholar 
    Chaplin‐Kramer, R., O’Rourke, M. E., Blitzer, E. J. & Kremen, C. A meta‐analysis of crop pest and natural enemy response to landscape complexity. Ecol. Lett. 14, 922–932 (2011).PubMed 
    Article 

    Google Scholar 
    Baillod, A. B., Tscharntke, T., Clough, Y. & Batary, P. Landscape‐scale interactions of spatial and temporal cropland heterogeneity drive biological control of cereal aphids. J. Appl. Ecol. 54, 1804–1813 (2017).Article 

    Google Scholar 
    Gagic, V. et al. Combined effects of agrochemicals and ecosystem services on crop yield across Europe. Ecol. Lett. 20, 1427–1436 (2017).PubMed 
    Article 

    Google Scholar 
    Zhang, W. et al. Multidecadal, county-level analysis of the effects of land use, Bt cotton, and weather on cotton pests in China. Proc. Natl Acad. Sci. USA 115, 700–7709 (2018).
    Google Scholar 
    Horgan, F. G. et al. Population development of rice black bug, Scotinophara latiuscula (Breddin), under varying nitrogen in a field experiment. Entomol. Gen. 37, 19–33 (2018).Article 

    Google Scholar 
    Butler, J., Garratt, M., & Leather, S. Fertilisers and insect herbivores: A meta‐analysis. Ann. Appl. Biol. 161, 223–233 (2012).Article 

    Google Scholar 
    Aqueel, M. A. et al. Effect of plant nutrition on aphid size, prey consumption, and life history characteristics of green lacewing. Insect Sci. 21, 74–82 (2014).PubMed 
    Article 

    Google Scholar 
    Benton, T. G., Vickery, J. A. & Wilson, J. D. Farmland biodiversity: Is habitat heterogeneity the key? Trends Ecol. Evol. 18, 182–188 (2003).Article 

    Google Scholar 
    Winqvist, C. et al. Mixed effects of organic farming and landscape complexity on farmland biodiversity and biological control potential across Europe. J. Appl. Ecol. 48, 570–579 (2011).Article 

    Google Scholar 
    Tscharntke, T. et al. Landscape perspectives on agricultural intensification and biodiversity-ecosystem service management. Ecol. Lett. 8, 857–874 (2005).Article 

    Google Scholar 
    Meehan, T. D., Werling, B. P., Landis, D. A. & Gratton, C. Agricultural landscape simplification and insecticide use in the Midwestern United States. Proc. Natl Acad. Sci. USA 108, 11500–11505 (2011).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Macfadyen, S. et al. Do differences in food web structure between organic and conventional farms affect the ecosystem service of pest control? Ecol. Lett. 12, 229–238 (2009).PubMed 
    Article 

    Google Scholar 
    Liu, J., Ning, J., Kuang, W. & Xu, X. Spatio-temporal patterns and characteristics of land-use change in China during 2010-2015. J. Geogr. Sci. 73, 789–802 (2018).
    Google Scholar 
    Ma, C., Ma, G. & Zhao, F. Impact of global warming on cereal aphids. Chin. J. Appl. Entomol. 51, 1435–1443 (2014).
    Google Scholar 
    Han, Z. et al. Effects of simulated climate warming on the population dynamics of Sitobion avenae (Fabricius) and its parasitoids in wheat fields. Pest Manag. Sci. 75, 3252–3259 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    Meisner, M. H., Harmon, J. P. & Ives, A. R. Temperature effects on long‐term population dynamics in a parasitoid-host system. Ecol. Monogr. 84, 457–476 (2014).Article 

    Google Scholar 
    Xiao, H. et al. Exposure to mild temperatures decreases overwintering larval survival and post-diapause reproductive potential in the rice stem borer Chilo suppressalis. J. Pest Sci. 90, 117–125 (2017).Article 

    Google Scholar 
    Senior, V. L. et al. Phenological responses in a sycamore-aphid-parasitoid system and consequences for aphid population dynamics: A 20 year case study. Glob. Change Biol. 26, 2814–2828 (2020).Article 

    Google Scholar 
    Chiu, M. C., Chen, Y. H. & Kuo, M. H. The effect of experimental warming on a low‐latitude aphid, Myzus varians. Entomol. Exp. Appl. 142, 216–222 (2012).Article 

    Google Scholar 
    Adler, L. S., De Valpine, P., Harte, J. & Call, J. Effects of long-term experimental warming on aphid density in the field. J. Kans. Entomol. Soc. 80, 156–169 (2007).Article 

    Google Scholar 
    Clement, S. L., Husebye, D. S. & Eigenbrode, S. D. Aphid Biodiversity under Environmental Change 107–129 (Springer, 2010).Van der Putten, W. H., Macel, M. & Visser, M. E. Predicting species distribution and abundance responses to climate change: why it is essential to include biotic interactions across trophic levels. Philos. T. Roy. Soc. B. 365, 2025–2034 (2010).Article 

    Google Scholar 
    Evans, E. W. Multitrophic interactions among plants, aphids, alternate prey and shared natural enemies—a review. Eur. J. Entomol. 105, 369–380 (2013).Article 

    Google Scholar 
    Sigsgaard, L. A survey of aphids and aphid parasitoids in cereal fields in Denmark, and the parasitoids’ role in biological control. J. Appl. Entomol. 126, 101–107 (2002).Article 

    Google Scholar 
    Diehl, E., Sereda, E., Wolters, V. & Birkhofer, K. Effects of predator specialization, host plant and climate on biological control of aphids by natural enemies: a meta‐analysis. J. Appl. Ecol. 50, 262–270 (2013).Article 

    Google Scholar 
    Hopper, K. R. et al. Natural enemy impact on the abundance of Diuraphis noxia (Homoptera: Aphididae) in wheat in Southern France. Environ. Entomol. 24, 402–408 (1995).Article 

    Google Scholar 
    Latham, D. R. & Mills, N. J. Quantifying aphid predation: The mealy plum aphid Hyalopterus pruni in California as a case study. J. Appl. Ecol. 47, 200–208 (2010).Article 

    Google Scholar 
    Östman, Ö., Ekbom, B. & Bengtsson, J. Yield increase attributable to aphid predation by ground-living polyphagous natural enemies in spring barley in Sweden. Ecol. Econ. 45, 149–158 (2003).Article 

    Google Scholar 
    Snyder, W. E. & Ives, A. R. Interactions between specialist and generalist natural enemies: Parasitoids, predators, and pea aphid control. Ecology 84, 91–107 (2003).Article 

    Google Scholar 
    Freier, B., Triltsch, H., Möwes, M. & Moll, E. The potential of predators in natural control of aphids in wheat: results of a ten-year field study in two German landscapes. Biocontrology 52, 775–788 (2007).Article 

    Google Scholar 
    Barczak, T., Dębek-Jankowska, A. & Bennewicz, J. Primary parasitoid and hyperparasitoid guilds (Hymenoptera) of grain aphid (Sitobion avenae F.) in northern Poland. Arch. Biol. Sci. 66, 1141–1148 (2014).Article 

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

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

    Google Scholar 
    Zhang, W., Jiang, F. & Ou, J. Global pesticide consumption and pollution: With China as a focus. P. Intern. Acad. Ecol. Environ. Sci. 1, 125–144 (2011).CAS 

    Google Scholar 
    El-Wakeil, N., Gaafar, N., Sallam, A. & Volkmar, C. Side Effects of Insecticides on Natural Enemies and Possibility of their Integration in Plant Protection Strategies. Insecticides: Development of Safer and More Effective Technologies Agricultural and Biological Sciences (ed Trdan, S.) 1–56 (Intech Open Access Publisher, 2013).Peshin, R. & Dhawan, A. K. Integrated Pest Management: Innovation-Development Process (Springer Science & Business Media, 2009).Jia, B., Hong, S., Zhang, Y. & Cao, Y. Toxicity and safety of 12 insecticides to Diadegma semiclausum. J. Shanxi Agric. Sci. 43, 999–1002 (2015).
    Google Scholar 
    Emery, S. E. et al. High agricultural intensity at the landscape scale benefits pests, but low intensity practices at the local scale can mitigate these effects. Agric. Ecosyst. Environ. 306, 107199 (2021).Article 

    Google Scholar 
    Aqueel, M. A. & Leather, S. R. Effect of nitrogen fertilizer on the growth and survival of Rhopalosiphum padi (L.) and Sitobion avenae (F.)(Homoptera: Aphididae) on different wheat cultivars. Crop. Prot. 30, 216–221 (2011).Article 

    Google Scholar 
    Gao, J., Guo, H. J., Sun, Y. C. & Ge, F. Juvenile hormone mediates the positive effects of nitrogen fertilization on weight and reproduction in pea aphid. Pest Manag. Sci. 74, 2511–2519 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    Barnett, K. L. & Facey, S. L. Grasslands, invertebrates, and precipitation: A review of the effects of climate change. Front. Plant. Sci. 7, 1196 (2016).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Yu, X. et al. Engineering plants for aphid resistance: Current status and future perspectives. Theor. Appl. Genet. 127, 2065–2083 (2014).CAS 
    PubMed 
    Article 

    Google Scholar 
    Martin, E. A. et al. The interplay of landscape composition and configuration: New pathways to manage functional biodiversity and agroecosystem services across Europe. Ecol. Lett. 22, 1083–1094 (2019).PubMed 
    Article 

    Google Scholar 
    Steckel, J. et al. Landscape composition and configuration differently affect trap-nesting bees, wasps and their antagonists. Biol. Conserv. 172, 56–64 (2014).Article 

    Google Scholar 
    Lu, Y. H. et al. Major ecosystems in China: Dynamics and challenges for sustainable management. Environ. Manag. 48, 13–27 (2011).Article 

    Google Scholar 
    Wood, G. A. et al. Real-time measures of canopy size as a basis for spatially varying nitroge applications to winter wheat sown at different seed rates. Biosyst. Eng. 84, 513–531 (2003).Article 

    Google Scholar 
    NOAA. https://www.ncdc.noaa.gov/cdo-web/ (2018).WORLD BANK GROUP. https://climateknowledgeportal.worldbank.org/download-data (2018). More

  • in

    Strategic planning to mitigate mining impacts on protected areas in the Brazilian Amazon

    Adams, V. M., Iacona, G. D. & Possingham, H. P. Weighing the benefits of expanding protected areas versus managing existing ones. Nat. Sustain. 2, 404–411 (2019).Article 

    Google Scholar 
    Blicharska, M. et al. Biodiversity’s contributions to sustainable development. Nat. Sustain. 2, 1083–1093 (2019).Article 

    Google Scholar 
    Hanson, J. O. et al. Global conservation of species’ niches. Nature 580, 232–234 (2020).CAS 
    Article 

    Google Scholar 
    Sonter, L. J., Barrett, D. J., Soares-filho, B. S. & Moran, C. J. Global demand for steel drives extensive land-use change in Brazil’ s Iron Quadrangle. Glob. Environ. Change 26, 63–72 (2014).Article 

    Google Scholar 
    Siqueira-Gay, J., Soares-Filho, B., Sánchez, L. E., Oviedo, A. & Sonter, L. J. Proposed legislation to mine Brazil’s Indigenous lands will threaten Amazon forests and their valuable ecosystem services. One Earth 3, 356–362 (2020).Article 

    Google Scholar 
    El Bizri, H. R., Macedo, J. C. B. M., Plaglia, A. P. & Morcatty, T. Q. Mining undermining Brazil’s environment. Science 353, 2–3 (2016).Article 

    Google Scholar 
    Ferreira, J. et al. Brazil’s environmental leadership at risk. Science 346, 706–707 (2014).CAS 
    Article 

    Google Scholar 
    Rudke, A. P. et al. Impact of mining activities on areas of environmental protection in the southwest of the Amazon: a GIS- and remote sensing-based assessment. J. Environ. Manage. 263, 110392 (2020).Article 

    Google Scholar 
    Naughton-Treves, L. & Holland, M. B. Losing ground in protected areas? Science 364, 832–833 (2019).CAS 
    Article 

    Google Scholar 
    Kroner, R. E. G. et al. The uncertain future of protected lands and waters. Science 364, 881–886 (2019).Article 
    CAS 

    Google Scholar 
    Pack, S. M. et al. Protected area downgrading, downsizing, and degazettement (PADDD) in the Amazon. Biol. Conserv. 197, 32–39 (2016).Article 

    Google Scholar 
    PADDDtracker.org Data Release Version 2.0 (Conservation International and World Wildlife Fund, 2019); https://doi.org/10.5281/zenodo.3371733Bebbington, A. J., Humphreys, D., Aileen, L., Rogan, J. & Agrawal, S. Resource extraction and infrastructure threaten forest cover and community rights. Proc. Natl Acad. Sci. USA 115, 13164–13173 (2018).CAS 
    Article 

    Google Scholar 
    Paiva, P. F. P. R. et al. Deforestation in protect areas in the Amazon: a threat to biodiversity. Biodivers. Conserv. 29, 19–38 (2020).Article 

    Google Scholar 
    Boldy, R., Santini, T., Annandale, M., Erskine, P. D. & Sonter, L. J. Understanding the impacts of mining on ecosystem services through a systematic review. Extr. Ind. Soc. https://doi.org/10.1016/j.exis.2020.12.005 (2020).Murguía, D. I., Bringezu, S. & Schaldach, R. Global direct pressures on biodiversity by large-scale metal mining: spatial distribution and implications for conservation. J. Environ. Manage. 180, 409–420 (2016).Article 

    Google Scholar 
    Kobayashi, H., Watando, H. & Kakimoto, M. A global extent site-level analysis of land cover and protected area overlap with mining activities as an indicator of biodiversity pressure. J. Clean. Prod. 84, 459–468 (2014).Article 

    Google Scholar 
    Craig, M. D., White, D. A., Stokes, V. L. & Prince, J. Can postmining revegetation create habitat for a threatened mammal? Ecol. Manage. Restor. 18, 149–155 (2017).Article 

    Google Scholar 
    Sonter, L. J. et al. Mining drives extensive deforestation in the Brazilian Amazon. Nat. Commun. 8, 1013 (2017).Article 
    CAS 

    Google Scholar 
    Siqueira-Gay, J., Sonter, L. J. & Sánchez, L. E. Exploring potential impacts of mining on forest loss and fragmentation within a biodiverse region of Brazil’s northeastern Amazon. Resour. Policy 67, 101662 (2020).Article 

    Google Scholar 
    Siqueira-Gay, J. & Sánchez, L. E. Keep the Amazon niobium in the ground. Environ. Sci. Policy 111, 1–6 (2020).CAS 
    Article 

    Google Scholar 
    Mascia, M. B. & Pailler, S. Protected area downgrading, downsizing, and degazettement (PADDD) and its conservation implications. Conserv. Lett. 4, 9–20 (2011).Article 

    Google Scholar 
    Raiter, K. G., Possingham, H. P., Prober, S. M. & Hobbs, R. J. Under the radar: mitigating enigmatic ecological impacts. Trends Ecol. Evol. 29, 635–644 (2014).Article 

    Google Scholar 
    Whitehead, A. L., Kujala, H. & Wintle, B. A. Dealing with cumulative biodiversity impacts in strategic environmental assessment: a new frontier for conservation planning. Conserv. Lett. 10, 195–204 (2017).Article 

    Google Scholar 
    Jenner, N. Making Mining ‘Forest-Smart’: Executive Summary Report (World Bank, 2019); http://documents.worldbank.org/curated/en/369711560319906622/Making-Mining-Forest-Smart-Executive-Summary-ReportRenca: Situação legal dos direitos minerários da reserva nacional do cobre (WWF, 2017).Soares-Filho, B. S., Cerqueira, G. C. & Pennachin, C. L. DINAMICA—a stochastic cellular automata model designed to simulate the landscape dynamics in an Amazonian colonization frontier. Ecol. Modell. 154, 217–235 (2002).Article 

    Google Scholar 
    Strand, J. et al. Spatially explicit valuation of the Brazilian Amazon forest’s ecosystem services. Nat. Sustain. 1, 657–664 (2018).Article 

    Google Scholar 
    Barber, C. P., Cochrane, M. A., Souza, C. M. & Laurance, W. F. Roads, deforestation, and the mitigating effect of protected areas in the Amazon. Biol. Conserv. 177, 203–209 (2014).Article 

    Google Scholar 
    Rorato, A. C. et al. Brazilian Amazon Indigenous peoples threatened by mining bill. Environ. Res. Lett. 15, 1040a3 (2020).Article 

    Google Scholar 
    Villén-Pérez, S., Anaya-Valenzuela, L., Conrado da Cruz, D. & Fearnside, P. M. Mining threatens isolated Indigenous peoples in the Brazilian Amazon. Glob. Environ. Change 72, (2022).Siqueira-Gay, J. & Sánchez, L. E. The outbreak of illegal gold mining in the Brazilian Amazon boosts deforestation. Reg. Environ. Change 21, 28 (2021).Article 

    Google Scholar 
    Sonter, L. J., Dade, M. C., Watson, J. E. M. & Valenta, R. K. Renewable energy production will exacerbate mining threats to biodiversity. Nat. Commun. 11, 4174 (2020).CAS 
    Article 

    Google Scholar 
    Tallis, H., Kennedy, C. M., Ruckelshaus, M., Goldstein, J. & Kiesecker, J. M. Mitigation for one & all: an integrated framework for mitigation of development impacts on biodiversity and ecosystem services. Environ. Impact Assess. Rev. 55, 21–34 (2015).Article 

    Google Scholar 
    Bull, J. W. et al. Quantifying the “avoided” biodiversity impacts associated with economic development. Front. Ecol. Environ. https://doi.org/10.1002/fee.2496 (2022).Gastauer, M. et al. Mine land rehabilitation: modern ecological approaches for more sustainable mining. J. Clean. Prod. 172, 1409–1422 (2018).Article 

    Google Scholar 
    Souza, B. A., Rosa, J. C. S., Siqueira-Gay, J. & Sánchez, L. E. Mitigating impacts on ecosystem services requires more than biodiversity offsets. Land Use Policy 105, 105393 (2021).Article 

    Google Scholar 
    Ritter, C. D. et al. Environmental impact assessment in Brazilian Amazonia: challenges and prospects to assess biodiversity. Biol. Conserv. 206, 161–168 (2017).Article 

    Google Scholar 
    Good Practice Handbook: Cumulative Impact Assessment and Management, Guidance for the Private Sector in Emerging Markets (IFC, 2013).Gunn, J. H. & Noble, B. F. Integrating cumulative effects in regional strategic environmental assessment frameworks: lessons from practice. J. Environ. Assess. Policy Manage. 11, 267–290 (2009).Article 

    Google Scholar 
    Ferrante, L. & Fearnside, P. M. The Amazon’ s road to deforestation. Science 20, 20–22 (2020).
    Google Scholar 
    Runge, C. A., Tulloch, A. I. T., Gordon, A. & Rhodes, J. R. Quantifying the conservation gains from shared access to linear infrastructure. Conserv. Biol. 31, 1428–1438 (2017).Article 

    Google Scholar 
    Kiesecker, J. M., Copeland, H., Pocewicz, A. & McKenney, B. Development by design: blending landscape-level planning with the mitigation hierarchy. Front. Ecol. Environ. 8, 261–266 (2010).Article 

    Google Scholar 
    Heiner, M. et al. Moving from reactive to proactive development planning to conserve Indigenous community and biodiversity values. Environ. Impact Assess. Rev. 74, 1–13 (2019).Article 

    Google Scholar 
    Pfaff, A., Robalino, J., Herrera, D. & Sandoval, C. Protected areas’ impacts on Brazilian Amazon deforestation: examining conservation–development interactions to inform planning. PLoS ONE 10, 1–17 (2015).Article 
    CAS 

    Google Scholar 
    Almeida, C. A. et al. High spatial resolution land use and land cover mapping of the Brazilian Legal Amazon in 2008 using Landsat-5 / TM and MODIS data. Acta Amazon. 46, 291–302 (2008).Article 

    Google Scholar 
    Asner, G. P. & Tupayachi, R. Accelerated losses of protected forests from gold mining in the Peruvian Amazon. Environ. Res. Lett. 12, 094004 (2016).Article 

    Google Scholar 
    Boham-Carter, G. F. Geographic Information Systems for Geoscientists: Modelling with GIS (Elsevier, 1994).Soares-Filho, B., Rodrigues, H. & Follador, M. A hybrid analytical–heuristic method for calibrating land-use change models. Environ. Model. Softw. 43, 80–87 (2013).Article 

    Google Scholar 
    INPE. TerraClass https://www.terraclass.gov.br/geoportal-aml/ (2021).INPE. Slope http://www.dsr.inpe.br/topodata/acesso.php (2020).Ministério do Meio Ambiente (MMA). Conservation units http://mapas.mma.gov.br/i3geo/datadownload.htm (2022).Fundação Nacional do Índio (FUNAI). Indigenous lands http://www.funai.gov.br/index.php/shape (2021).Leite-Filho, A., Soares-filho, B. S., Davis, J. & Rodrigues, H. Dinamica EGO Guidebook (Centro de Sensoriamento Remoto, UFMG, 2020).Serviço Geológico do Brasil. Mineral deposits https://geosgb.cprm.gov.br/ (2020).Soares-Filho, B. et al. Simulating the response of land-cover changes to road paving and governance along a major Amazon highway: the Santarém-Cuiabá corridor. Glob. Change Biol. 10, 745–764 (2004).Article 

    Google Scholar 
    Centro de Sensoriamento Remoto. Biodiversity https://csr.ufmg.br/amazones/biodiversity/ (2021).Fahrig, L. Ecological responses to habitat fragmentation per se. Annu. Rev. Ecol. Evol. Syst. 48, 1–23 (2017).Pardini, R., de Bueno, A. A., Gardner, T. A., Prado, P. I. & Metzger, J. P. Beyond the fragmentation threshold hypothesis: regime shifts in biodiversity across fragmented landscapes. PLoS ONE 5, e13666 (2010).Montibeller, B., Kmoch, A., Virro, H., Mander, Ü. & Uuemaa, E. Increasing fragmentation of forest cover in Brazil’s Legal Amazon from 2001 to 2017. Sci. Rep. 10, 5803 (2020).CAS 
    Article 

    Google Scholar 
    Cabral, A. I. R., Saito, C., Pereira, H. & Laques, A. E. Deforestation pattern dynamics in protected areas of the Brazilian Legal Amazon using remote sensing data. Appl. Geogr. 100, 101–115 (2018).Article 

    Google Scholar 
    Colson, F., Bogaert, J. & Ceulemans, R. Fragmentation in the Legal Amazon, Brazil: can landscape metrics indicate agricultural policy differences? Ecol. Indic. 11, 1467–1471 (2011).Article 

    Google Scholar 
    Monmonier, M. S. Measures of pattern complexity for choroplethic maps. Am. Cartogr. 1, 159–169 (1974).Article 

    Google Scholar 
    Werner, T. T. et al. Global-scale remote sensing of mine areas and analysis of factors explaining their extent. Glob. Environ. Change 60, 102007 (2020).Article 

    Google Scholar 
    Soares-Filho, B. et al. Roads, http://maps.csr.ufmg.br/ (2016). More

  • in

    Increased incompatibility of heterologous algal symbionts under thermal stress in the cnidarian-dinoflagellate model Aiptasia

    Sylvan, J. How to protect a coral reef: the public trust doctrine and the law of the sea recommended citation. Sustain. Dev. Law Policy 7, 12 (2006).
    Google Scholar 
    LaJeunesse, T. C. et al. Systematic revision of symbiodiniaceae highlights the antiquity and diversity of coral endosymbionts. Curr. Biol. 28, 2570–2580.e6 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    Kopp, C. et al. Highly dynamic cellular-level response of symbiotic coral to a sudden increase in environmental nitrogen. mBio 4, e00052–13 (2013).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Muscatine, L. The role of symbiotic algae in carbon and energy flux in reef corals. Coral Reef. 25, 75–87 (1990).
    Google Scholar 
    Dubinsky, Z. & Stambler, N. Coral reefs: an ecosystem in transition. (Springer, 2011).Wiedenmann, J. et al. Nutrient enrichment can increase the susceptibility of reef corals to bleaching. https://doi.org/10.1038/NCLIMATE1661 (2012).Suggett, D. J., Warner, M. E. & Leggat, W. Symbiotic dinoflagellate functional diversity mediates coral survival under ecological crisis. Trends Ecol. Evolution 32, 735–745 (2017).Article 

    Google Scholar 
    Morris, L. A., Voolstra, C. R., Quigley, K. M., Bourne, D. G. & Bay, L. K. Nutrient availability and metabolism affect the stability of coral–symbiodiniaceae symbioses. Trends Microbiol. 27, 678–689 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    Lehnert, E. M. et al. Extensive differences in gene expression between symbiotic and aposymbiotic cnidarians. G3 (Bethesda) 4, 277–95 (2014).CAS 
    Article 

    Google Scholar 
    Dubinsky, Z. & Berman-Frank, I. Uncoupling primary production from population growth in photosynthesizing organisms in aquatic ecosystems. in. Aquat. Sci. 63, 4–17 (2001).CAS 
    Article 

    Google Scholar 
    Burriesci, M. S., Raab, T. K. & Pringle, J. R. Evidence that glucose is the major transferred metabolite in dinoflagellate–cnidarian symbiosis. J. Exp. Biol. 215, 3467–3477 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Davy, S. K., Allemand, D. & Weis, V. M. Cell biology of cnidarian-dinoflagellate symbiosis. Microbiol. Mol. Biol. Rev. 76, 229–61 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Rädecker, N., Pogoreutz, C., Voolstra, C. R., Wiedenmann, J. & Wild, C. Nitrogen cycling in corals: the key to understanding holobiont functioning? Trends Microbiol. 23, 490–497 (2015).PubMed 
    Article 
    CAS 

    Google Scholar 
    Cui, G. et al. Host-dependent nitrogen recycling as a mechanism of symbiont control in Aiptasia. PLOS Genet. 15, e1008189 (2019).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Rädecker, N. et al. Heat stress destabilizes symbiotic nutrient cycling in corals. Proc. Natl Acad. Sci. USA 118, https://doi.org/10.1073/pnas.2022653118 (2021).Weis, V. M. Cellular mechanisms of Cnidarian bleaching: stress causes the collapse of symbiosis. J. Exp. Biol. 211, 3059–3066 (2008).CAS 
    PubMed 
    Article 

    Google Scholar 
    Wooldridge, S. A. Breakdown of the coral-algae symbiosis: towards formalising a linkage between warm-water bleaching thresholds and the growth rate of the intracellular zooxanthellae. Biogeosciences Discuss. 9, 8111–8139 (2012).
    Google Scholar 
    Cziesielski, M. J., Schmidt‐Roach, S. & Aranda, M. The past, present, and future of coral heat stress studies. Ecol. Evol. https://doi.org/10.1002/ece3.5576 (2019).Leggat, W. et al. Differential responses of the coral host and their algal symbiont to thermal stress. PLoS ONE 6, e26687 (2011).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Pinzón, J. H. et al. Whole transcriptome analysis reveals changes in expression of immune-related genes during and after bleaching in a reef-building coral. R. Soc. Open Sci. 2, 140214 (2015).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Ziegler, M., Seneca, F. O., Yum, L. K., Palumbi, S. R. & Voolstra, C. R. Bacterial community dynamics are linked to patterns of coral heat tolerance. Nat. Commun. 8, 14213 (2017).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Bang, C. et al. Metaorganisms in extreme environments: do microbes play a role in organismal adaptation? Zoology 127, 1–19 (2018).PubMed 
    Article 

    Google Scholar 
    Berkelmans, R. & van Oppen, M. J. H. The role of zooxanthellae in the thermal tolerance of corals: a “nugget of hope” for coral reefs in an era of climate change. Proc. Biol. Sci./R. Soc. 273, 2305–12 (2006).
    Google Scholar 
    Sampayo, E. M., Ridgway, T., Bongaerts, P. & Hoegh-Guldberg, O. Bleaching susceptibility and mortality of corals are determined by fine-scale differences in symbiont type. Proc. Natl Acad. Sci. 105, 10444–10449 (2008).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Howells, E. J. et al. Coral thermal tolerance shaped by local adaptation of photosymbionts. Nat. Clim. Change https://doi.org/10.1038/nclimate1330 (2011).Cziesielski, M. J. et al. Multi-omics analysis of thermal stress response in a zooxanthellate cnidarian reveals the importance of associating with thermotolerant symbionts. Proc. Biol. Sci. 285, 20172654 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    Baker, A. C., Starger, C. J., McClanahan, T. R. & Glynn, P. W. Corals’ adaptive response to climate change. Nature 430, 741–741 (2004).CAS 
    PubMed 
    Article 

    Google Scholar 
    Thornhill, D. J., LaJeunesse, T. C., Kemp, D. W., Fitt, W. K. & Schmidt, G. W. Multi-year, seasonal genotypic surveys of coral-algal symbioses reveal prevalent stability or post-bleaching reversion. Mar. Biol. 148, 711–722 (2006).Article 

    Google Scholar 
    Palumbi, S. R., Barshis, D. J., Traylor-Knowles, N. & Bay, R. A. Mechanisms of reef coral resistance to environmental stress,making its relative ability to acclimate or adapt extremely important to the to future climate change. Science 344, 895–898 (2014).CAS 
    PubMed 
    Article 

    Google Scholar 
    Herrera, M. et al. Temperature transcends partner specificity in the symbiosis establishment of a cnidarian. ISME J. 15, 141–153 (2021).CAS 
    PubMed 
    Article 

    Google Scholar 
    Howells, E. J. et al. Corals in the hottest reefs in the world exhibit symbiont fidelity not flexibility. Mol. Ecol. 29, 899–911 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    Hume, B. C. C., Mejia-Restrepo, A., Voolstra, C. R. & Berumen, M. L. Fine-scale delineation of Symbiodiniaceae genotypes on a previously bleached central Red Sea reef system demonstrates a prevalence of coral host-specific associations. Coral Reefs 1–19 https://doi.org/10.1007/s00338-020-01917-7 (2020).Perez, S. F., Cook, C. B. & Brooks, W. R. The role of symbiotic dinoflagellates in the temperature-induced bleaching response of the subtropical sea anemone Aiptasia pallida. J. Exp. Mar. Biol. Ecol. 256, 1–14 (2001).CAS 
    PubMed 
    Article 

    Google Scholar 
    Mieog, J. C. et al. The roles and interactions of symbiont, host and environment in defining coral fitness. PLoS ONE 4, e6364 (2009).Cantin, N. E., van Oppen, M. J. H., Willis, B. L., Mieog, J. C. & Negri, A. P. Juvenile corals can acquire more carbon from high-performance algal symbionts. Coral Reefs 28, 405–414 (2009).Article 

    Google Scholar 
    Herrera, M. et al. Unfamiliar partnerships limit cnidarian holobiont acclimation to warming. Glob. Change Biol. 26, 5539–5553 (2020).Article 

    Google Scholar 
    LaJeunesse, T. et al. Closely related Symbiodinium spp. differ in relative dominance in coral reef host communities across environmental, latitudinal and biogeographic gradients. Mar. Ecol. Prog. Ser. 284, 147–161 (2004).Article 

    Google Scholar 
    Parkinson, J. E. & Baums, I. B. The extended phenotypes of marine symbioses: ecological and evolutionary consequences of intraspecific genetic diversity in coral-algal associations. Front. Microbiol. 5, 445 (2014).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Coffroth, M. A., Poland, D. M., Petrou, E. L., Brazeau, D. A. & Holmberg, J. C. Environmental symbiont acquisition may not be the solution to warming seas for reef-building corals. PLoS ONE 5, e13258 (2010).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Bellantuono, A. J., Granados-Cifuentes, C., Miller, D. J., Hoegh-Guldberg, O. & Rodriguez-Lanetty, M. Coral thermal tolerance: tuning gene expression to resist thermal stress. PLoS ONE 7, e50685 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Sunagawa, S. et al. Generation and analysis of transcriptomic resources for a model system on the rise: the sea anemone Aiptasia pallida and its dinoflagellate endosymbiont. BMC Genomics 10, 258 (2009).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Baumgarten, S. et al. The genome of Aiptasia, a sea anemone model for coral symbiosis. Proc. Natl Acad. Sci. 112, 201513318 (2015).
    Google Scholar 
    Matthews, J. L. et al. Menthol-induced bleaching rapidly and effectively provides experimental aposymbiotic sea anemones (Aiptasia sp.) for symbiosis investigations. J. Exp. Biol. jeb.128934 https://doi.org/10.1242/JEB.128934 (2015).Kenkel, C. D. et al. Evidence for a host role in thermotolerance divergence between populations of the mustard hill coral (Porites astreoides) from different reef environments. Mol. Ecol. 22, 4335–4348 (2013).CAS 
    PubMed 
    Article 

    Google Scholar 
    Polato, N. R., Altman, N. S. & Baums, I. B. Variation in the transcriptional response of threatened coral larvae to elevated temperatures. Mol. Ecol. 22, 1366–1382 (2013).CAS 
    PubMed 
    Article 

    Google Scholar 
    DeSalvo, M., Sunagawa, S., Voolstra, C. R. & Medina, M. Transcriptomic resonses to heat stress and bleaching in the elkhorn coral Acropora palmata. Mar. Ecol. Prog. Ser. 402, 97–113 (2010).CAS 
    Article 

    Google Scholar 
    Maor-Landaw, K. & Levy, O. Gene expression profiles during short-term heat stress; branching vs. massive Scleractinian corals of the Red Sea. PeerJ 4, e1814 (2016).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Yamamoto, K. et al. Control of the heat stress-induced alternative splicing of a subset of genes by hnRNP K. Genes Cells 21, 1006–1014 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    Seneca, F. O. & Palumbi, S. R. The role of transcriptome resilience in resistance of corals to bleaching. Mol. Ecol. 24, 1467–1484 (2015).PubMed 
    Article 

    Google Scholar 
    Meyer, E. & Weis, V. M. Study of cnidarian-algal symbiosis in the “omics” age. Biol. Bull. 223, 44–65 (2012).CAS 
    PubMed 
    Article 

    Google Scholar 
    Oakley, C. A. et al. Thermal shock induces host proteostasis disruption and endoplasmic reticulum stress in the model symbiotic Cnidarian Aiptasia. J. Proteome Res. 16, 2121–2134 (2017).CAS 
    PubMed 
    Article 

    Google Scholar 
    Robbart, M. L., Peckol, P., Scordilis, S. P., Curran, H. A. & Brown-Saracino, J. Population recovery and differential heat shock protein expression for the corals Agaricia agaricites and A-tenuifolia in Belize. Mar. Ecol. Prog. Ser. 283, 151–160 (2004).Article 

    Google Scholar 
    Barshis, D. J. et al. Genomic basis for coral resilience to climate change. Proc. Natl Acad. Sci. 110, 1387–1392 (2013).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Traylor-Knowles, N., Rose, N. H. & Palumbi, S. R. The cell specificity of gene expression in the response to heat stress in corals. J. Exp. Biol. 220, 1837–1845 (2017).PubMed 

    Google Scholar 
    Benchimol, S. p53-dependent pathways of apoptosis. Cell Death Differ. 8, 1049–1051 (2001).CAS 
    PubMed 
    Article 

    Google Scholar 
    Moya, A. et al. Functional conservation of the apoptotic machinery from coral to man: The diverse and complex Bcl-2 and caspase repertoires of Acropora millepora. BMC Genomics 17, 62 (2016).Elmore, S. Apoptosis: a review of programmed cell death. Toxicol. Pathol. 35, 495–516 (2007).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Karim, W., Nakaema, S. & Hidaka, M. Temperature effects on the growth rates and photosynthetic activities of symbiodinium cells. J. Mar. Sci. Eng. 3, 368–381 (2015).Article 

    Google Scholar 
    Cunning, R. & Baker, A. C. Excess algal symbionts increase the susceptibility of reef corals to bleaching. Nat. Clim. Change 3, 259–262 (2013).Article 

    Google Scholar 
    Rehman, A. U. et al. Symbiodinium sp. cells produce light-induced intra- and extracellular singlet oxygen, which mediates photodamage of the photosynthetic apparatus and has the potential to interact with the animal host in coral symbiosis. N. Phytologist 212, 472–484 (2016).CAS 
    Article 

    Google Scholar 
    Lesser, K. B. & Garcia, F. A. Association between polycystic ovary syndrome and glucose intolerance during pregnancy. J. Matern. Fetal Med. 6, 303–307 (1997).CAS 
    PubMed 
    Article 

    Google Scholar 
    Dunn, S. R., Schnitzler, C. E. & Weis, V. M. Apoptosis and autophagy as mechanisms of dinoflagellate symbiont release during cnidarian bleaching: every which way you lose. Proc. R. Soc. Lond. B: Biol. Sci. 274, 3079–3085 (2007).
    Google Scholar 
    DeSalvo, M. K. et al. Coral host transcriptomic states are correlated with Symbiodinium genotypes. Mol. Ecol. 19, 1174–1186 (2010).CAS 
    PubMed 
    Article 

    Google Scholar 
    Levin, R. A. et al. Engineering strategies to decode and enhance the genomes of coral symbionts. Front. Microbiol. https://doi.org/10.3389/fmicb.2017.01220 (2017).Yuyama, I., Ishikawa, M., Nozawa, M., Yoshida, M. & Ikeo, K. Transcriptomic changes with increasing algal symbiont reveal the detailed process underlying establishment of coral-algal symbiosis. Sci. Rep. 8, 16802 (2018).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Sproles, A. E. et al. Sub-cellular imaging shows reduced photosynthetic carbon and increased nitrogen assimilation by the non-native endosymbiont Durusdinium trenchii in the model cnidarian Aiptasia. Environ. Microbiol. 22, 3741–3753 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    Rädecker, N. et al. Using Aiptasia as a model to study metabolic interactions in Cnidarian-Symbiodinium symbioses. Front. Physiol. 9, 214 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Falkowski, P. G., Dubinsky, Z., Muscatine, L. & McCloskey, L. Population control in symbiotic corals. BioScience 43, 606–611 (1993).Article 

    Google Scholar 
    Wang & Douglas. Nitrogen recycling or nitrogen conservation in an alga-invertebrate symbiosis? J. Exp. Biol. 201, 2445–53 (1998).Loram, J. E., Trapido-Rosenthal, H. G. & Douglas, A. E. Functional significance of genetically different symbiotic algae Symbiodinium in a coral reef symbiosis. Mol. Ecol. 16, 4849–4857 (2007).CAS 
    PubMed 
    Article 

    Google Scholar 
    Karako-Lampert, S. et al. Transcriptome analysis of the scleractinian coral Stylophora pistillata. PLoS One 9, e88615 (2014).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Hillyer, K. E., Tumanov, S., Villas-Bôas, S. & Davy, S. K. Metabolite profiling of symbiont and host during thermal stress and bleaching in a model cnidarian-dinoflagellate symbiosis. J. Exp. Biol. 219, 516–27 (2016).PubMed 

    Google Scholar 
    Bertucci, A., Forêt, S., Ball, E. E. & Miller, D. J. Transcriptomic differences between day and night in Acropora millepora provide new insights into metabolite exchange and light-enhanced calcification in corals. Mol. Ecol. 24, 4489–4504 (2015).CAS 
    PubMed 
    Article 

    Google Scholar 
    Matthews, J. L. et al. Optimal nutrient exchange and immune responses operate in partner specificity in the cnidarian-dinoflagellate symbiosis. Proc. Natl Acad. Sci. 114, 13194–13199 (2017).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Lin, M.-F., Takahashi, S., Forêt, S., Davy, S. K. & Miller, D. J. Transcriptomic analyses highlight the likely metabolic consequences of colonization of a cnidarian host by native or non-native Symbiodinium species. Biol. Open 8, bio038281 (2019).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Medrano, E., Merselis, D. G., Bellantuono, A. J. & Rodriguez-Lanetty, M. Proteomic Basis of Symbiosis: A Heterologous Partner Fails to Duplicate Homologous Colonization in a Novel Cnidarian– Symbiodiniaceae Mutualism. Front. Microbiol. 10, 1153 (2019).Schoepf, V., Stat, M., Falter, J. L. & McCulloch, M. T. Limits to the thermal tolerance of corals adapted to a highly fluctuating, naturally extreme temperature environment. Sci. Rep. 5, 17639 (2015).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Xiang, T., Hambleton, E. A., DeNofrio, J. C., Pringle, J. R. & Grossman, A. R. Isolation of clonal axenic strains of the symbiotic dinoflagellate Symbiodinium and their growth and host specificity1. J. Phycol. 49, 447–458 (2013).CAS 
    PubMed 
    Article 

    Google Scholar 
    Bray, N. L., Pimentel, H., Melsted, P. & Pachter, L. Near-optimal probabilistic RNA-seq quantification. Nat. Biotechnol. 34, 525–527 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    Pimentel, H., Bray, N. L., Puente, S., Melsted, P. & Pachter, L. Differential analysis of RNA-seq incorporating quantification uncertainty. Nat. Methods 14, 687–690 (2017).CAS 
    PubMed 
    Article 

    Google Scholar  More

  • in

    RNA viromes from terrestrial sites across China expand environmental viral diversity

    Shi, M. et al. Redefining the invertebrate RNA virosphere. Nature 540, 539–543 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    Zhang, Y.-Z., Shi, M. & Holmes, E. C. Using metagenomics to characterize an expanding virosphere. Cell 172, 1168–1172 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    Li, C.-X. et al. Unprecedented genomic diversity of RNA viruses in arthropods reveals the ancestry of negative-sense RNA viruses. eLife 4, e05378 (2015).PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Starr, E. P., Nuccio, E. E., Pett-Ridge, J., Banfield, J. F. & Firestone, M. K. Metatranscriptomic reconstruction reveals RNA viruses with the potential to shape carbon cycling in soil. Proc. Natl Acad. Sci. USA 116, 25900–25908 (2019).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Wolf, Y. I. et al. Doubling of the known set of RNA viruses by metagenomic analysis of an aquatic virome. Nat. Microbiol. 5, 1262–1270 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Zayed, A. A. et al. Cryptic and abundant marine viruses at the evolutionary origins of Earth’s RNA virome. Science 376, 156–162 (2022).CAS 
    PubMed 
    Article 

    Google Scholar 
    Simmonds, P. et al. Virus taxonomy in the age of metagenomics. Nat. Rev. Microbiol. 15, 161–168 (2017).CAS 
    PubMed 
    Article 

    Google Scholar 
    Trubl, G., Hyman, P., Roux, S. & Abedon, S. T. Coming-of-age characterization of soil viruses: a user’s guide to virus isolation, detection within metagenomes, and viromics. Soil Syst. 4, 23 (2020).CAS 
    Article 

    Google Scholar 
    Jin, M. et al. Diversities and potential biogeochemical impacts of mangrove soil viruses. Microbiome 7, 58 (2019).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Trubl, G. et al. Soil viruses are underexplored players in ecosystem carbon processing. mSystems 3, e00076-18 (2018).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Steward, G. F. et al. Are we missing half of the viruses in the ocean? ISME J. 7, 672–679 (2013).CAS 
    PubMed 
    Article 

    Google Scholar 
    Paul, K. I., Scott Black, A. & Conyers, M. K. in Advances in Agronomy. Sparks, D.L., Vol. 78 187–214 (Elsevier, 2003).Urayama, S., Takaki, Y. & Nunoura, T. FLDS: a comprehensive dsRNA sequencing method for intracellular RNA virus surveillance. Microbes Environ. 31, 33–40 (2016).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Armbrust, E. V. The life of diatoms in the world’s oceans. Nature 459, 185–192 (2009).CAS 
    PubMed 
    Article 

    Google Scholar 
    Wu, W., Jin, Y., Bai, F. & Jin, S. in Molecular Medical Microbiology. Tang, Y.W., Liu, D., Schwartzman, J., Sussman, M., Poxton, I., 753–767 (Elsevier, 2015).Cooney, S., O’Brien, S., Iversen, C. & Fanning, S. in Encyclopedia of Food Safety. Motarjemi, Y., 433–441 (Elsevier, 2014).Geoghegan, J. L. et al. Hidden diversity and evolution of viruses in market fish. Virus Evol. 4, vey031 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Lauber, C. et al. Deciphering the origin and evolution of hepatitis B viruses by means of a family of non-enveloped fish viruses. Cell Host Microbe 22, 387–399.e6 (2017).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Shi, M., Zhang, Y.-Z. & Holmes, E. C. Meta-transcriptomics and the evolutionary biology of RNA viruses. Virus Res. 243, 83–90 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    Turnbull, O. M. H. et al. Meta-transcriptomic identification of divergent Amnoonviridae in Fish. Viruses 12, 1254 (2020).CAS 
    PubMed Central 
    Article 

    Google Scholar 
    Bauermann, F. V., Hause, B., Buysse, A. R., Joshi, L. R. & Diel, D. G. Identification and genetic characterization of a porcine hepe-astrovirus (bastrovirus) in the United States. Arch. Virol. 164, 2321–2326 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    Oude Munnink, B. B. et al. A novel astrovirus-like RNA virus detected in human stool. Virus Evol. 2, vew005 (2016).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Williamson, K. E. et al. Estimates of viral abundance in soils are strongly influenced by extraction and enumeration methods. Biol. Fertil. Soils 49, 857–869 (2013).Article 

    Google Scholar 
    Wang, C., Liu, D. & Bai, E. Decreasing soil microbial diversity is associated with decreasing microbial biomass under nitrogen addition. Soil Biol. Biochem. 120, 126–133 (2018).CAS 
    Article 

    Google Scholar 
    Wang, Q. et al. Effects of nitrogen and phosphorus inputs on soil bacterial abundance, diversity, and community composition in Chinese fir plantations. Front. Microbiol. 9, 1543 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Payne, S. in Viruses. Payne, S., 219–226 (Elsevier, 2017).Hillman, B. I. & Cai, G. The family Narnaviridae. Adv. Virus Res. 86, 149–176 (2013).PubMed 
    Article 

    Google Scholar 
    Wolf, Y. I. et al. Origins and evolution of the global RNA virome. mBio 9, e02329-18 (2018).PubMed 
    PubMed Central 
    Article 

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

    Google Scholar 
    Li, D., Liu, C.-M., Luo, R., Sadakane, K. & Lam, T.-W. MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics 31, 1674–1676 (2015).CAS 
    PubMed 
    Article 

    Google Scholar 
    Wu, F. et al. A new coronavirus associated with human respiratory disease in China. Nature 579, 265–269 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Buchfink, B., Xie, C. & Huson, D. H. Fast and sensitive protein alignment using DIAMOND. Nat. Methods 12, 59–60 (2015).CAS 
    PubMed 
    Article 

    Google Scholar 
    Katoh, K. & Standley, D. M. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol. Biol. Evol. 30, 772–780 (2013).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Capella-Gutierrez, S., Silla-Martinez, J. M. & Gabaldon, T. trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics 25, 1972–1973 (2009).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Nguyen, L.-T., Schmidt, H. A., von Haeseler, A. & Minh, B. Q. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol. Biol. Evol. 32, 268–274 (2015).CAS 
    PubMed 
    Article 

    Google Scholar 
    Paradis, E. & Schliep, K. ape 5.0: an environment for modern phylogenetics and evolutionary analysis in R. Bioinformatics 35, 526–528 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    Yu, G., Smith, D. K., Zhu, H., Guan, Y. & Lam, T. T. ggtree: an R package for visualization and annotation of phylogenetic trees with their covariates and other associated data. Methods Ecol. Evol. 8, 28–36 (2017).Article 

    Google Scholar 
    Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Nayfach, S. et al. CheckV assesses the quality and completeness of metagenome-assembled viral genomes. Nat. Biotechnol. 39, 578–585 (2021).CAS 
    PubMed 
    Article 

    Google Scholar 
    Almagro Armenteros, J. J. et al. SignalP 5.0 improves signal peptide predictions using deep neural networks. Nat. Biotechnol. 37, 420–423 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    Krogh, A., Larsson, B., von Heijne, G. & Sonnhammer, E. L. L. Predicting transmembrane protein topology with a hidden markov model: application to complete genomes. J. Mol. Biol. 305, 567–580 (2001).CAS 
    PubMed 
    Article 

    Google Scholar 
    Gupta, R., Jung, E. & Brunak, S. NetNGlyc 1.0 Server (2017). DTU Health Tech. http://www.cbs.dtu.dk/services/NetNGlyc/Mirdita, M. et al. Uniclust databases of clustered and deeply annotated protein sequences and alignments. Nucleic Acids Res. 45, D170–D176 (2017).CAS 
    PubMed 
    Article 

    Google Scholar 
    Remmert, M., Biegert, A., Hauser, A. & Söding, J. HHblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment. Nat. Methods 9, 173–175 (2012).CAS 
    Article 

    Google Scholar 
    Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596 (2012).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Li, H. A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data. Bioinformatics 27, 2987–2993 (2011).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Lagkouvardos, I., Fischer, S., Kumar, N. & Clavel, T. Rhea: a transparent and modular R pipeline for microbial profiling based on 16S rRNA gene amplicons. PeerJ 5, e2836 (2017).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    McLeod, A., Xu, C. & Lai, Y. Package ‘bestglm’. CRAN. (2020).Fu, L., Niu, B., Zhu, Z., Wu, S. & Li, W. CD-HIT: accelerated for clustering the next-generation sequencing data. Bioinformatics 28, 3150–3152 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar  More

  • in

    Stable isotopes unveil one millennium of domestic cat paleoecology in Europe

    Turner, D. & Bateson, P. (eds) The Domestic Cat: The Biology of Its Behaviour (Cambridge Univ. Press, 2000).
    Google Scholar 
    Bradshaw, J. W. S., Goodwin, D., Legrand-Defrétin, V. & Nott, H. M. R. Food selection by the domestic cat, an obligate carnivore. Comp. Biochem. Physiol. A Physiol. 114, 205–209 (1996).CAS 
    PubMed 
    Article 

    Google Scholar 
    Trouwborst, A., McCormack, P. C. & Martínez Camacho, E. Domestic cats and their impacts on biodiversity: A blind spot in the application of nature conservation law. People Nat. 2, 235–250 (2020).Article 

    Google Scholar 
    Crowley, S. L., Cecchetti, M. & McDonald, R. A. Our wild companions: Domestic cats in the anthropocene. Trends Ecol. Evol. 35, 477–483 (2020).PubMed 
    Article 

    Google Scholar 
    Driscoll, C. A. et al. The Near Eastern origin of cat domestication. Science 317, 519–523 (2007).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Van Neer, W., Linseele, V., Friedman, R. & De Cupere, B. More evidence for cat taming at the Predynastic elite cemetery of Hierakonpolis (Upper Egypt). J. Archaeol. Sci. 45, 103–111 (2014).Article 

    Google Scholar 
    Ottoni, C. et al. The palaeogenetics of cat dispersal in the ancient world. Nat. Ecol. Evol. 1, 0139 (2017).Article 

    Google Scholar 
    Baca, M. et al. Human-mediated dispersal of cats in the Neolithic Central Europe. Heredity 121, 557–563 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Vigne, J. The beginning of cat domestication in East and West Asia. Doc. Archaeobiol. 15, 343–354 (2019).
    Google Scholar 
    Krajcarz, M. et al. Ancestors of domestic cats in Neolithic Central Europe: Isotopic evidence of a synanthropic diet. Proc. Natl. Acad. Sci. USA 117, 17710–17719 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Piontek, A. M. et al. Analysis of cat diet across an urbanisation gradient. Urban Ecosyst. 24, 59–69 (2021).Article 

    Google Scholar 
    Medina, F. M. et al. A global review of the impacts of invasive cats on island endangered vertebrates. Glob. Chang. Biol. 17, 3503–3510 (2011).ADS 
    Article 

    Google Scholar 
    Moseby, K. E., Peacock, D. E. & Read, J. L. Catastrophic cat predation: A call for predator profiling in wildlife protection programs. Biol. Conserv. 191, 331–340 (2015).Article 

    Google Scholar 
    Loss, S. R., Will, T. & Marra, P. P. The impact of free-ranging domestic cats on wildlife of the United States. Nat. Commun. 4, 1396 (2013).ADS 
    PubMed 
    Article 
    CAS 

    Google Scholar 
    Beaumont, M. et al. Genetic diversity and introgression in the Scottish wildcat. Mol. Ecol. 10, 319–336 (2001).CAS 
    PubMed 
    Article 

    Google Scholar 
    Beugin, M. P. et al. Hybridization between Felis silvestris silvestris and Felis silvestris catus in two contrasted environments in France. Ecol. Evol. 10, 263–276 (2020).PubMed 
    Article 

    Google Scholar 
    Biró, Z., Lanszki, J., Szemethy, L., Heltai, M. & Randi, E. Feeding habits of feral domestic cats (Felis catus), wild cats (Felis silvestris) and their hybrids: Trophic niche overlap among cat groups in Hungary. J. Zool. 266, 187–196 (2005).Article 

    Google Scholar 
    Széles, G. L., Purger, J. J., Molnár, T. & Lanszki, J. Comparative analysis of the diet of feral and house cats and wildcat in Europe. Mammal. Res. 63, 43–53 (2018).Article 

    Google Scholar 
    Ottoni, C. & Van Neer, W. The dispersal of the domestic cat paleogenetic and zooarcheological evidence. Near East. Archaeol. 83, 38–45 (2020).Article 

    Google Scholar 
    Bitz-Thorsen, J. & Gotfredsen, A. B. Domestic cats (Felis catus) in Denmark have increased significantly in size since the Viking Age. Danish J. Archaeol. 7, 241–254 (2018).Article 

    Google Scholar 
    Faure, E. & Kitchener, A. C. An archaeological and historical review of the relationships between felids and people. Anthrozoos 22, 221–238 (2009).Article 

    Google Scholar 
    von den Driesch, A. Kulturgeschichte der Hauskatze. In Krankheiten der Katze, Bd. 1 (eds Schmidt, V. & Horzinek, M. C.) 17–40 (Fischer, 1992).
    Google Scholar 
    Głażewska, I. & Kijewski, T. A new view on the European feline population from mtDNA analysis in Polish domestic cats. Forensic Sci. Int. Genet. 27, 116–122 (2017).PubMed 
    Article 
    CAS 

    Google Scholar 
    Cucchi, T. et al. Tracking the Near Eastern origins and European dispersal of the western house mouse. Sci. Rep. 10, 8276 (2020).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Van Klinken, G. J., Richards, M. P. & Hedges, B. E. M. An overview of causes for stable isotopic variations in past European human populations: environmental, ecophysiological, and cultural effects. In Biogeochemical Approaches to Paleodietary Analysis (eds Ambrose, S. & Katzenberg, M.) 39–63 (Kluwer Academic Publishers, 2002). https://doi.org/10.1007/0-306-47194-9_3.Chapter 

    Google Scholar 
    Drucker, D. G., Bridault, A., Hobson, K. A., Szuma, E. & Bocherens, H. Can carbon-13 in large herbivores reflect the canopy effect in temperate and boreal ecosystems? Evidence from modern and ancient ungulates. Palaeogeogr. Palaeoclimatol. Palaeoecol. 266, 69–82 (2008).Article 

    Google Scholar 
    Koch, P. L. Isotopic study of the biology of modern and fossil vertebrates. In Stable Isotopes in Ecology and Environmental Science (eds Michener, R. & Lajtha, K.) 99–154 (Blackwell Publishing Ltd, 2007). https://doi.org/10.1002/9780470691854.ch5.Chapter 

    Google Scholar 
    Hofman-Kamińska, E. et al. Foraging habitats and niche partitioning of European large herbivores during the holocene—Insights from 3D dental microwear texture analysis. Palaeogeogr. Palaeoclimatol. Palaeoecol. 506, 183–195 (2018).Article 

    Google Scholar 
    Bocherens, H., Hofman-Kamińska, E., Drucker, D. G., Schmölcke, U. & Kowalczyk, R. European bison as a refugee species? Evidence from isotopic data on Early Holocene bison and other large herbivores in northern Europe. PLoS ONE 10, 1–19 (2015).Article 
    CAS 

    Google Scholar 
    Hu, Y. et al. Earliest evidence for commensal processes of cat domestication. Proc. Natl. Acad. Sci. USA. 111, 116–120 (2014).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Haruda, A. F. et al. The earliest domestic cat on the Silk Road. Sci. Rep. 10, 11241 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Meckstroth, A. M., Miles, A. K. & Chandra, S. Diets of introduced predators using stable isotopes and stomach contents. J. Wildl. Manag. 71, 2387–2392 (2007).Article 

    Google Scholar 
    McDonald, B. W. et al. High variability within pet foods prevents the identification of native species in pet cats’ diets using isotopic evaluation. PeerJ 8, e8337 (2020).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Maeda, T., Nakashita, R., Shionosaki, K., Yamada, F. & Watari, Y. Predation on endangered species by human-subsidized domestic cats on Tokunoshima Island. Sci. Rep. 9, 16200 (2019).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Stewart, G. R., Aidar, M. P. M., Joly, C. A. & Schmidt, S. Impact of point source pollution on nitrogen isotope signatures (δ15N) of vegetation in SE Brazil. Oecologia 131, 468–472 (2002).ADS 
    PubMed 
    Article 

    Google Scholar 
    Graven, H., Keeling, R. F. & Rogelj, J. Changes to carbon isotopes in atmospheric CO2 over the industrial era and into the future. Glob. Biogeochem. Cycles 34, 1–21 (2020).Article 
    CAS 

    Google Scholar 
    DeNiro, M. J. Postmortem preservation and alteration of in vivo bone collagen isotope ratios in relation to palaeodietary reconstruction. Nature 317, 806–809 (1985).ADS 
    CAS 
    Article 

    Google Scholar 
    Linderholm, A. & Kjellström, A. Stable isotope analysis of a medieval skeletal sample indicative of systemic disease from Sigtuna Sweden. J. Archaeol. Sci. 38, 925–933 (2011).Article 

    Google Scholar 
    Webb, E. C. et al. Compound-specific amino acid isotopic proxies for distinguishing between terrestrial and aquatic resource consumption. Archaeol. Anthropol. Sci. 10, 1–18 (2018).Article 

    Google Scholar 
    Müldner, G. & Richards, M. P. Stable isotope evidence for 1500 years of human diet at the city of York, UK. Am. J. Phys. Anthropol. 133, 682–697 (2007).PubMed 
    Article 

    Google Scholar 
    Müldner, G. & Richards, M. P. Fast or feast: Reconstructing diet in later medieval England by stable isotope analysis. J. Archaeol. Sci. 32, 39–48 (2005).Article 

    Google Scholar 
    van der Sluis, L. G., Hollund, H. I., Kars, H., Sandvik, P. U. & Denham, S. D. A palaeodietary investigation of a multi-period churchyard in Stavanger, Norway, using stable isotope analysis (C, N, H, S) on bone collagen. J. Archaeol. Sci. Rep. 9, 120–133 (2016).
    Google Scholar 
    Polet, C. & Katzenberg, M. A. Reconstruction of the diet in a mediaeval monastic community from the coast of Belgium. J. Archaeol. Sci. 30, 525–533 (2003).Article 

    Google Scholar 
    Kosiba, S. B., Tykot, R. H. & Carlsson, D. Stable isotopes as indicators of change in the food procurement and food preference of Viking Age and Early Christian populations on Gotland (Sweden). J. Anthropol. Archaeol. 26, 394–411 (2007).Article 

    Google Scholar 
    Olsen, K. C. et al. Isotopic anthropology of rural German medieval diet: Intra- and inter-population variability. Archaeol. Anthropol. Sci. 10, 1053–1065 (2018).Article 

    Google Scholar 
    Benevolo, L. The European City (Blackwell Publishers, 1993).
    Google Scholar 
    Barrett, J. et al. Detecting the medieval cod trade: A new method and first results. J. Archaeol. Sci. 35, 850–861 (2008).Article 

    Google Scholar 
    Barrett, J. H. et al. Interpreting the expansion of sea fishing in medieval Europe using stable isotope analysis of archaeological cod bones. J. Archaeol. Sci. 38, 1516–1524 (2011).Article 

    Google Scholar 
    Bogaard, A., Heaton, T. H. E., Poulton, P. & Merbach, I. The impact of manuring on nitrogen isotope ratios in cereals: Archaeological implications for reconstruction of diet and crop management practices. J. Archaeol. Sci. 34, 335–343 (2007).Article 

    Google Scholar 
    Heaton, T. H. E. Spatial, species, and temporal variations in the 13C/12C ratios of C3 plants: Implications for palaeodiet studies. J. Archaeol. Sci. 26, 637–649 (1999).Article 

    Google Scholar 
    Bogaard, A. et al. Crop manuring and intensive land management by Europe’s first farmers. Proc. Natl. Acad. Sci. USA. 110, 12589–12594 (2013).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Styring, A. K. et al. Refining human palaeodietary reconstruction using amino acid δ15N values of plants, animals and humans. J. Archaeol. Sci. 53, 504–515 (2015).CAS 
    Article 

    Google Scholar 
    Guiry, E. Complexities of stable carbon and nitrogen isotope biogeochemistry in ancient freshwater ecosystems: Implications for the study of past subsistence and environmental change. Front. Ecol. Evol. 7, 313 (2019).Article 

    Google Scholar 
    Fuller, B. T., Müldner, G., Van Neer, W., Ervynck, A. & Richards, M. P. Carbon and nitrogen stable isotope ratio analysis of freshwater, brackish and marine fish from Belgian archaeological sites (1st and 2nd millennium AD). J. Anal. At. Spectrom. 27, 807–820 (2012).CAS 
    Article 

    Google Scholar 
    Robson, H. K. et al. Carbon and nitrogen stable isotope values in freshwater, brackish and marine fish bone collagen from Mesolithic and Neolithic sites in central and northern Europe. Environ. Archaeol. 21, 105–118 (2016).Article 

    Google Scholar 
    Hobson, K. A., Piatt, J. F. & Pitocchelli, J. Using stable isotopes to determine seabird trophic relationships. J. Anim. Ecol. 63, 786–798 (1994).Article 

    Google Scholar 
    Guiry, E. & Buckley, M. Urban rats have less variable, higher protein diets. Proc. R. Soc. B Biol. Sci. 285, 20181441 (2018).Article 
    CAS 

    Google Scholar 
    Bicknell, A. W. J. et al. Stable isotopes reveal the importance of seabirds and marine foods in the diet of St Kilda field mice. Sci. Rep. 10, 1–12 (2020).Article 
    CAS 

    Google Scholar 
    Hoffmann, R. C. Medieval fishing. In Working with Water in Medieval Europe. Technology and Resource-Use (ed. Squatriti, P.) 331–393 (Brill, 2000).
    Google Scholar 
    Gillies, C. & Clout, M. The prey of domestic cats (Felis catus) in two suburbs of Auckland City, New Zealand. J. Zool. 259, 309–315 (2003).Article 

    Google Scholar 
    Brickner-Braun, I., Geffen, E. & Yom-Tov, Y. The domestic cat as a predator of Israeli wildlife. Isr. J. Ecol. Evol. 53, 129–142 (2007).Article 

    Google Scholar 
    Flockhart, D. T. T., Norris, D. R. & Coe, J. B. Predicting free-roaming cat population densities in urban areas. Anim. Conserv. 19, 472–483 (2016).Article 

    Google Scholar 
    Castañeda, I., Zarzoso-Lacoste, D. & Bonnaud, E. Feeding behaviour of red fox and domestic cat populations in suburban areas in the south of Paris. Urban Ecosyst. 23, 731–743 (2020).Article 

    Google Scholar 
    Zhu, Y., Siegwolf, R. T. W., Durka, W. & Körner, C. Phylogenetically balanced evidence for structural and carbon isotope responses in plants along elevational gradients. Oecologia 162, 853–863 (2010).ADS 
    PubMed 
    Article 

    Google Scholar 
    Männel, T. T., Auerswald, K. & Schnyder, H. Altitudinal gradients of grassland carbon and nitrogen isotope composition are recorded in the hair of grazers. Glob. Ecol. Biogeogr. 16, 583–592 (2007).Article 

    Google Scholar 
    Pińska, K. & Badura, M. Warunki przyrodnicze i dieta roślinna mieszkańców Pucka w późnym średniowieczu. In Puck – kultura materialna małego miasta w późnym średniowieczu (ed. Starski, M.) 517 (Uniwersytet Warszawski, 2017).
    Google Scholar 
    Lefebvre, A. et al. Morphology of estuarine bedforms, Weser Estuary, Germany. Earth Surf. Process. Landforms 47, 242–256 (2022).ADS 
    Article 

    Google Scholar 
    Bischop, D. & Von der Küchelmann, H. C. Küche in den Graben – Bremens Stadtgraben und die Essgewohnheiten seiner Anwohner an der Wende zur Frühen Neuzeit. In Lebensmittel im Mittelalter und in der frühen Neuzeit. Erzeugung, Verarbeitung, Versorgung. Beiträge des 16. Kolloquiums des Arbeitskreises zur archäologischen Erforschung des mittelalterlichen Handwerks, Soester Beiträge zur Archäologie 15 (ed. Melzer, W.) 137–151 (Mocker und Jahn, 2018).
    Google Scholar 
    Elmshäuser, K. & Pordzik, V. V. Lachsgarnen, Tomen und Kumpanen – Die älteste Bremer Fischeramtsrolle. Bremisches Jahrb. 98, 13–72 (2019).
    Google Scholar 
    Küchelmann, H. C. Viel Butter bei wenig Fisch. Zwei Fischknochenkomplexe des 12.–13. Jahrhunderts aus der Bremer Altstadt. In Grenzen überwinden. Archäologie zwischen Disziplin und Disziplinen. Festschrift für Uta Halle zum 65. Geburtstag, Internationale Archäologie Studia Honoraria 40 (eds Kahlow, S. et al.) 413–426 (Verlag Marie Leidorf GmbH, 2021).
    Google Scholar 
    Schwarcz, H. P. & Schoeninger, M. J. Stable isotope analyses in human nutritional ecology. Am. J. Phys. Anthropol. 34, 283–321 (1991).Article 

    Google Scholar 
    Wallace, M. et al. Stable carbon isotope analysis as a direct means of inferring crop water status and water management practices. World Archaeol. 45, 388–409 (2013).Article 

    Google Scholar 
    van der Merwe, N. J. & Medina, E. The canopy effect, carbon isotope ratios and foodwebs in amazonia. J. Archaeol. Sci. 18, 249–259 (1991).Article 

    Google Scholar 
    Ervynck, A. Orant, pugnant, laborant. The diet of the three orders in the feudal society of medieval north-western Europe. In Behaviour Behind Bones. The Zooarchaeology of Ritual, Religion, Status and Identity (eds O’Day, S. J. et al.) 215–223 (Oxbow Books, 2004).
    Google Scholar 
    von den Driesch, A. A guide to the measurement of animal bones from archaeological sites. Peabody Museum Bull. 1, 1–137 (1976).
    Google Scholar 
    O’Connor, T. P. Wild or domestic? Biometric variation in the cat Felis silvestris Schreber. Int. J. Osteoarchaeol. 17, 581–595 (2007).Article 

    Google Scholar 
    Kratochvíl, Z. Schadelkriterien der Wild- und Hauskatze (Felis silvestris silvestris Schreber 1777 und Felis s. f. catus L. 1758). Acta Sci. Nat. Brno 7, 1–50 (1973).
    Google Scholar 
    Kratochvíl, Z. Das Postkranialskelett der Wild- und Hauskatze (Felis silvestris und F. lybica f. catus). Acta Sci. Nat. Brno 10, 1–43 (1976).
    Google Scholar 
    Dyce, K. M., Sack, W. O. & Wensing, C. J. G. Textbook of Veterinary Anatomy (Saunders/Elsevier, 2010).
    Google Scholar 
    Krajcarz, M. et al. On the trail of the oldest domestic cat in Poland. An insight from morphometry, ancient DNA and radiocarbon dating. Int. J. Osteoarchaeol. 26, 912–919 (2016).Article 

    Google Scholar 
    Bronk Ramsey, C. Radiocarbon calibration and analysis of stratigraphy: The OxCal program. Radiocarbon 37, 425–430 (1995).CAS 
    Article 

    Google Scholar 
    Bronk Ramsey, C., Dee, M., Lee, S., Nakagawa, T. & Staff, R. Developments in the calibration and modeling of radiocarbon dates. Radiocarbon 52, 953–961 (2010).Article 

    Google Scholar 
    Ferreira, J. P., Leitão, I., Santos-Reis, M. & Revilla, E. Human-related factors regulate the spatial ecology of domestic cats in sensitive areas for conservation. PLoS ONE 6, e25970 (2011).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Pirie, T. J., Thomas, R. L. & Fellowes, M. D. E. Pet cats (Felis catus) from urban boundaries use different habitats, have larger home ranges and kill more prey than cats from the suburbs. Landsc. Urban Plan. 220, 104338 (2022).Article 

    Google Scholar 
    Bocherens, H. et al. Paleobiological implications of the isotopic signatures (13C, 15N) of fossil mammal collagen in Scladina cave (Sclayn, Belgium). Quat. Res. 48, 370–380 (1997).Article 

    Google Scholar 
    Longin, R. New method of collagen extraction for radiocarbon dating. Nature 230, 241–242 (1971).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Boudin, M., Boeckx, P., Vandenabeele, P. & Van Strydonck, M. Improved radiocarbon dating of contaminated protein-containing archaeological samples via cross-flow nanofiltrated amino acids. Rapid Commun. Mass Spectrom. 27, 2039–2050 (2013).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Wojcieszak, M., Van Den Brande, T., Ligovich, G. & Boudin, M. Pretreatment protocols performed at the Royal Institute for Cultural Heritage (RICH) prior to AMS 14C measurements. Radiocarbon 62, e14–e24 (2020).Article 

    Google Scholar 
    Hammer, Ø. PAST. PAleontological Statistics. Version 4.05 Reference manual (Natural History Museum University of Oslo, 2021).
    Google Scholar 
    Hammer, Ø., Harper, D. A. T. & Ryan, P. D. PAST: Paleontological statistics software package for education and data analysis. Palaeontol. Electron. 4, 1–9 (2001).
    Google Scholar 
    Rohland, N., Glocke, I., Aximu-Petri, A. & Meyer, M. Extraction of highly degraded DNA from ancient bones, teeth and sediments for high-throughput sequencing. Nat. Protoc. 13, 2447–2461 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    Nguyen, L. T., Schmidt, H. A., Von Haeseler, A. & Minh, B. Q. IQ-TREE: A fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol. Biol. Evol. 32, 268–274 (2015).CAS 
    PubMed 
    Article 

    Google Scholar  More

  • in

    Using metabarcoding and droplet digital PCR to investigate drivers of historical shifts in cyanobacteria from six contrasting lakes

    Paerl, H. W. & Huisman, J. Climate change: a catalyst for global expansion of harmful cyanobacterial blooms. Environ. Microbiol. Rep. 1, 27–37 (2009).CAS 
    PubMed 
    Article 

    Google Scholar 
    Paerl, H. W. & Paul, V. J. Climate change: links to global expansion of harmful cyanobacteria. Water Res. 46, 1349–1363 (2012).CAS 
    PubMed 
    Article 

    Google Scholar 
    Huisman, J. et al. Cyanobacterial blooms. Nat. Rev. Microbiol. 16, 471 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    Reissig, M., Trochine, C., Queimaliños, C., Balseiro, E. & Modenutti, B. Impact of fish introduction on planktonic food webs in lakes of the Patagonian Plateau. Biol. Conserv. 132, 437–447 (2006).Article 

    Google Scholar 
    Britton, J. R., Davies, G. D. & Harrod, C. Trophic interactions and consequent impacts of the invasive fish Pseudorasbora parva in a native aquatic foodweb: a field investigation in the UK. Biol. Invasions 12, 1533–1542 (2010).Article 

    Google Scholar 
    Beaulieu, M., Pick, F. & Gregory-Eaves, I. Nutrients and water temperature are significant predictors of cyanobacterial biomass in a 1147 lakes data set. Limnol. Oceanogr. 58, 1736–1746 (2013).ADS 
    CAS 
    Article 

    Google Scholar 
    O’Neil, J. M., Davis, T. W., Burford, M. A. & Gobler, C. J. The rise of harmful cyanobacteria blooms: the potential roles of eutrophication and climate change. Harmful Algae 14, 313–334 (2012).Article 
    CAS 

    Google Scholar 
    Paerl, H. W. & Huisman, J. Blooms like it hot. Science 320, 57–58 (2008).CAS 
    PubMed 
    Article 

    Google Scholar 
    Toxic Cyanobacteria in Water: A Guide to Their Public Health Consequences, Monitoring, and Management. (E & FN Spon, 1999).Sukenik, A., Quesada, A. & Salmaso, N. Global expansion of toxic and non-toxic cyanobacteria: effect on ecosystem functioning. Biodivers. Conserv. 24, 889–908 (2015).Article 

    Google Scholar 
    Ibelings, B. W., Bormans, M., Fastner, J. & Visser, P. M. CYANOCOST special issue on cyanobacterial blooms: synopsis—a critical review of the management options for their prevention, control and mitigation. Aquat. Ecol. 50, 595–605 (2016).CAS 
    Article 

    Google Scholar 
    Paerl, H. W. Mitigating harmful cyanobacterial blooms in a human- and climatically-impacted world. Life 4, 988–1012 (2014).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Rastogi, R. P., Madamwar, D. & Incharoensakdi, A. Bloom dynamics of cyanobacteria and their toxins: environmental health impacts and mitigation strategies. Front. Microbiol. https://doi.org/10.3389/fmicb.2015.01254 (2015).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ewing, H. A. et al. “New” cyanobacterial blooms are not new: two centuries of lake production are related to ice cover and land use. Ecosphere 11, e03170 (2020).Article 

    Google Scholar 
    McGlone, M. S. & Wilmshurst, J. M. Dating initial Maori environmental impact in New Zealand. Quat. Int. 59, 5–16 (1999).Article 

    Google Scholar 
    Brooking, A. P. D. of H. T. & Brooking, T. The History of New Zealand. (Greenwood Publishing Group, 2004).Wilmshurst, J. M., Anderson, A. J., Higham, T. F. G. & Worthy, T. H. Dating the late prehistoric dispersal of Polynesians to New Zealand using the commensal Pacific rat. PNAS 105, 7676–7680 (2008).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    McGlone, M. S. The Polynesian settlement of New Zealand in relation to environmental and biotic changes. N. Z. J. Ecol. 12, 115–129 (1989).
    Google Scholar 
    McGlone, M. S. Polynesian deforestation of New Zealand: a preliminary synthesis. Archaeol. Ocean. 18, 11–25 (1983).Article 

    Google Scholar 
    McWethy, D. B. et al. Rapid landscape transformation in South Island, New Zealand, following initial Polynesian settlement. PNAS 107, 21343–21348 (2010).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    McWethy, D. B., Wilmshurst, J. M., Whitlock, C., Wood, J. R. & McGlone, M. S. A high-resolution chronology of rapid forest transitions following Polynesian arrival in New Zealand. PLoS ONE 9, e111328 (2014).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Star, P. New Zealand environmental history: a question of attitudes. Environ. Hist. Camb. 9, 463–475 (2003).Article 

    Google Scholar 
    Clark, A. H. The Invasion of New Zealand by Plants, People, and Animals (Rutgers University Press, 1949).
    Google Scholar 
    Wilmshurst, J. M. Human effects on the environment: European impact. Te Ara: The Encyclopedia of New Zealand https://teara.govt.nz/en/human-effects-on-the-environment/page-3 (2007).Smol, J. P. The ratio of diatom frustules to chrysophycean statospores: a useful paleolimnological index. Hydrobiologia 123, 199–208 (1985).Article 

    Google Scholar 
    Rees, A. B. H., Cwynar, L. C. & Cranston, P. S. Midges (Chironomidae, Ceratopogonidae, Chaoboridae) as a temperature proxy: a training set from Tasmania, Australia. J. Paleolimnol. 40, 1159–1178 (2008).ADS 
    Article 

    Google Scholar 
    Epp, L. S., Stoof, K. R., Trauth, M. H. & Tiedemann, R. Historical genetics on a sediment core from a Kenyan lake: intraspecific genotype turnover in a tropical rotifer is related to past environmental changes. J. Paleolimnol. 43, 939–954 (2010).ADS 
    Article 

    Google Scholar 
    Buchaca, T. et al. Rapid ecological shift following piscivorous fish introduction to increasingly eutrophic and warmer Lake Furnas (Azores Archipelago, Portugal): a paleoecological approach. Ecosystems 14, 458–477 (2011).CAS 
    Article 

    Google Scholar 
    Cristescu, M. E. & Hebert, P. D. N. Uses and misuses of environmental DNA in biodiversity science and conservation. Annu. Rev. Ecol. Evol. Syst. 49, 209–230 (2018).Article 

    Google Scholar 
    Giguet-Covex, C. et al. Long livestock farming history and human landscape shaping revealed by lake sediment DNA. Nat. Commun. 5, 3211 (2014).ADS 
    PubMed 
    Article 
    CAS 

    Google Scholar 
    Alsos, I. G. et al. Plant DNA metabarcoding of lake sediments: how does it represent the contemporary vegetation. PLoS ONE 13, e0195403 (2018).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Nelson-Chorney, H. T. et al. Environmental DNA in lake sediment reveals biogeography of native genetic diversity. Front. Ecol. Environ. 17, 313–318 (2019).
    Google Scholar 
    Capo, E. et al. Lake sedimentary DNA research on past terrestrial and aquatic biodiversity: overview and recommendations. Quaternary 4, 6 (2021).Article 

    Google Scholar 
    Shokralla, S., Spall, J. L., Gibson, J. F. & Hajibabaei, M. Next-generation sequencing technologies for environmental DNA research. Mol. Ecol. 21, 1794–1805 (2012).CAS 
    PubMed 
    Article 

    Google Scholar 
    Taberlet, P., Coissac, E., Pompanon, F., Brochmann, C. & Willerslev, E. Towards next-generation biodiversity assessment using DNA metabarcoding. Mol. Ecol. 21, 2045–2050 (2012).CAS 
    PubMed 
    Article 

    Google Scholar 
    Thomsen, P. F. & Willerslev, E. Environmental DNA: an emerging tool in conservation for monitoring past and present biodiversity. Biol. Conserv. 183, 4–18 (2015).Article 

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

    Google Scholar 
    Monchamp, M.-E., Walser, J.-C., Pomati, F. & Spaak, P. Sedimentary DNA reveals cyanobacterial community diversity over 200 years in two perialpine lakes. Appl. Environ. Microbiol. 82, 6472–6482 (2016).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Pal, S., Gregory-Eaves, I. & Pick, F. R. Temporal trends in cyanobacteria revealed through DNA and pigment analyses of temperate lake sediment cores. J. Paleolimnol. 54, 87–101 (2015).ADS 
    Article 

    Google Scholar 
    Dodsworth, W. Temporal Trends in Cyanobacteria Through Paleo-Genetic Analyses. (Université d’Ottawa/University of Ottawa, 2020). https://doi.org/10.20381/ruor-24401.Rinta-Kanto, J. M. et al. The diversity and distribution of toxigenic Microcystis spp. in present day and archived pelagic and sediment samples from Lake Erie. Harmful Algae 8, 385–394 (2009).CAS 
    Article 

    Google Scholar 
    Zastepa, A. et al. Reconstructing a long-term record of microcystins from the analysis of lake sediments. Sci. Total Environ. 579, 893–901 (2017).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Schallenberg, M. et al. Ecosystem services of lakes. In Ecosystem Services in New Zealand (ed. Dymond, J.) 23 (Manaaki Whenua Press, 2013).
    Google Scholar 
    Ministry for the Environment & Ausseil, A.-G. Our freshwater 2020. www.mfe.govt.nz (2020).Takiwa—Map Page. https://lernz.takiwa.co/map.Leathwick, J. et al. Freshwater ecosystems of New Zealand (FENZ) geodatabase. Users guide. (2010).Cochrane, L. Reconstructing Ecological Change, Catchment Disturbance, and Anthropogenic Impact over the last 3000 years at Lake Pounui, Wairarapa, New Zealand. (2017).Burns, C. W. & Mitchell, S. F. Seasonal succession and vertical distribution of phytoplankton in Lake Hayes and Lake Johnson, South Island, New Zealand. N. Z. J. Mar. Freshw. Res. 8, 167–209 (1974).Article 

    Google Scholar 
    Lawa. Land, Air, Water Aotearoa (LAWA) https://www.lawa.org.nz/ (2018).Bunny, T., Perrie, A., Milne, J. & Keenan, L. Lake water quality in the Ruamāhanga Whaitua. 17 (2014).McKinnon, M. Volcanic Plateau region: The lure of trout. Te Ara—The Encyclopedia of New Zealand https://teara.govt.nz/en/volcanic-plateau-region/page-8 (2015).Burns, C. W. & Mitchell, S. F. Seasonal succession and vertical distribution of zooplankton in Lake Hayes and Lake Johnson. N. Z. J. Mar. Freshw. Res. 14, 189–204 (1980).Article 

    Google Scholar 
    Schallenberg, M. & Schallenberg, L. Lake Hayes restoration and monitoring plan. 55 https://a234f952-dbf2-444e-983e-ef311d984ee7.filesusr.com/ugd/c1b10b_d2993ed023cd4bdbac7eef71a89c2de7.pdf (2017).NIWA. NIWA https://niwa.co.nz/.Mackereth, F. J. H. A portable core sampler for lake deposits. Limnol. Oceanogr. 3, 181–191 (1958).ADS 
    Article 

    Google Scholar 
    Howarth, J. D., Fitzsimons, S. J., Norris, R. J. & Jacobsen, G. E. Lake sediments record cycles of sediment flux driven by large earthquakes on the Alpine fault, New Zealand. Geology 40, 1091–1094 (2012).ADS 
    CAS 
    Article 

    Google Scholar 
    Trodahl, M. I., Rees, A. B. H., Newnham, R. M. & Vandergoes, M. J. Late Holocene geomorphic history of Lake Wairarapa, North Island, New Zealand. N. Z. J. Geol. Geophys. 59, 330–340 (2016).CAS 
    Article 

    Google Scholar 
    Khan, S., Puddick, J., Burns, C. W., Closs, G. & Schallenberg, M. Palaeolimnological evaluation of historical nutrient and food web contributions to the eutrophication of two monomictic lakes. Submitted for Journal Publication (2022).Rinta-Kanto, J. M. et al. Quantification of toxic Microcystis spp. during the 2003 and 2004 blooms in Western Lake Erie using quantitative real-time PCR. Environ. Sci. Technol. 39, 4198–4205 (2005).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Nübel, U., Garcia-Pichel, F. & Muyzer, G. PCR primers to amplify 16S rRNA genes from cyanobacteria. Appl. Environ. Microbiol. 63, 3327–3332 (1997).ADS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    R Core Team. R: A Language and Environment for Statistical Computing. (R Foundation for Statistical Computing, 2020).RStudio Team. RStudio: Integrated Development for R. RStudio, PBC, Boston, MA. (2020).Wickham, H. et al. Welcome to the Tidyverse. J. Open Sour. Softw. 4, 1686 (2019).ADS 
    Article 

    Google Scholar 
    Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer-Verlag, 2016).MATH 
    Book 

    Google Scholar 
    Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.journal 17, 10–12 (2011).Article 

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

    Google Scholar 
    Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596 (2013).CAS 
    PubMed 
    Article 

    Google Scholar 
    Yilmaz, P. et al. The SILVA and “all-species living tree project (LTP)” taxonomic frameworks. Nucleic Acids Res. 42, D643–D648 (2013).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Glöckner, F. O. et al. 25 years of serving the community with ribosomal RNA gene reference databases and tools. J. Biotechnol. 261, 169–176 (2017).PubMed 
    Article 
    CAS 

    Google Scholar 
    McMurdie, P. J. & Holmes, S. phyloseq: an R Package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE 8, e61217 (2013).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Oksanen, J. et al. vegan: Community Ecology Package. R package version 2.5–6. 2019. (2019).Williams, P. A. & Cameron, E. K. Creating gardens: the diversity and progression of European plant introductions. In Biological Invasions in New Zealand Vol. 186 (eds Allen, R. B. & Lee, W. G.) 33–47 (Springer-Verlag, 2006).Chapter 

    Google Scholar 
    Simpson, G. L. Modelling palaeoecological time series using generalised additive models. Front. Ecol. Evol. https://doi.org/10.3389/fevo.2018.00149 (2018).Article 

    Google Scholar 
    Chen, H. & Boutros, P. C. VennDiagram: a package for the generation of highly-customizable Venn and Euler diagrams in R. BMC Bioinform. 12, 35 (2011).Article 

    Google Scholar 
    Juggins, S. rioja: analysis of quaternary science data. (2020).de Vries, A. & Ripley, B. D. ggdendro: create dendrograms and tree diagrams using ‘ggplot2’. (2022).Anderson, M. J. A new method for non-parametric multivariate analysis of variance. Austral Ecol. 26, 32–46 (2001).
    Google Scholar 
    Anderson, M. J. Distance-based tests for homogeneity of multivariate dispersions. Biometrics 62, 245–253 (2006).MathSciNet 
    PubMed 
    MATH 
    Article 

    Google Scholar 
    Soo, R. M. et al. An expanded genomic representation of the phylum Cyanobacteria. Genome Biol. Evol. 6, 1031–1045 (2014).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    MacKeigan, P. W. et al. Comparing microscopy and DNA metabarcoding techniques for identifying cyanobacteria assemblages across hundreds of lakes. Harmful Algae 113, 102187 (2022).CAS 
    PubMed 
    Article 

    Google Scholar 
    Wood, S. A. et al. Trophic state and geographic gradients influence planktonic cyanobacterial diversity and distribution in New Zealand lakes. FEMS Microbiol. Ecol. https://doi.org/10.1093/femsec/fiw234 (2017).Article 
    PubMed 

    Google Scholar 
    Becker, S., Richl, P. & Ernst, A. Seasonal and habitat-related distribution pattern of Synechococcus genotypes in Lake Constance. FEMS Microbiol. Ecol. 62, 64–77 (2007).CAS 
    PubMed 
    Article 

    Google Scholar 
    Sánchez-Baracaldo, P., Handley, B. A. & Hayes, P. K. Picocyanobacterial community structure of freshwater lakes and the Baltic Sea revealed by phylogenetic analyses and clade-specific quantitative PCR. Microbiology (Reading) 154, 3347–3357 (2008).Article 
    CAS 

    Google Scholar 
    Pilon, S. et al. Contrasting histories of microcystin-producing cyanobacteria in two temperate lakes as inferred from quantitative sediment DNA analyses. Lake Reserv. Manag. 35, 102–117 (2019).CAS 
    Article 

    Google Scholar 
    Queenstown’s Pioneering Beginnings. https://www.queenstownnz.co.nz/stories/post/queenstowns-pioneer-beginnings/ (2017).Fish, G. R. A limnological study of four lakes near Rotorua. N. Z. J. Mar. Freshw. Res. 4, 165–194 (1970).Article 

    Google Scholar 
    Lake Rotoehu—Lakes Water Quality Society. https://lakeswaterquality.co.nz/lake-rotoehu/.Bay of Plenty Regional Council, Rotorua District Council, & Te Arawa Lakes Trust. Lake Rotoehu Action Plan. 61 http://www.rotorualakes.co.nz/vdb/document/76 (2007).Hobbs, W. O. et al. Using a lake sediment record to infer the long-term history of cyanobacteria and the recent rise of an anatoxin producing Dolichospermum sp.. Harmful Algae 101, 101971 (2021).CAS 
    PubMed 
    Article 

    Google Scholar 
    de la Escalera, G. M., Antoniades, D., Bonilla, S. & Piccini, C. Application of ancient DNA to the reconstruction of past microbial assemblages and for the detection of toxic cyanobacteria in subtropical freshwater ecosystems. Mol. Ecol. 23, 5791–5802 (2014).Article 
    CAS 

    Google Scholar 
    Retrolens—Historical Imagery Resource. https://retrolens.co.nz/.Strayer, D. L. Alien species in fresh waters: ecological effects, interactions with other stressors, and prospects for the future. Freshw. Biol. 55, 152–174 (2010).Article 

    Google Scholar 
    Hall, S. R. & Mills, E. L. Exotic species in large lakes of the world. Aquat. Ecosyst. Health Manag. 3, 105–135 (2000).Article 

    Google Scholar 
    Gehrke, P. C. & Harris, J. H. The role of fish in cyanobacterial blooms in Australia. Mar. Freshw. Res. 45, 905–915 (1994).Article 

    Google Scholar 
    Burns, C. W. & Schallenberg, M. Impacts of nutrients and zooplankton on the microbial food web of an ultra-oligotrophic lake. J. Plankton Res. 20, 1501–1525 (1998).Article 

    Google Scholar 
    Rowe, D. K. & Schallenberg, M. Food webs in lakes. In Freshwaters of New Zealand (ed. Harding, J. S.) 23 (Wellington, N.Z.: New Zealand Hydrological Society, 2004).Gliwicz, Z. M. & Pijanowska, J. The role of predation in zooplankton succession. In Plankton Ecology: Succession in Plankton Communities (ed. Sommer, U.) 253–296 (Springer, 1989).Chapter 

    Google Scholar 
    Vanni, M. J. & Findlay, D. L. Trophic cascades and phytoplankton community structure. Ecology 71, 921–937 (1990).Article 

    Google Scholar 
    Smith, K. F. & Lester, P. J. Trophic interactions promote dominance by cyanobacteria (Anabaena spp.) in the pelagic zone of lower Karori reservoir, Wellington, New Zealand. N. Z. J. Mar. Freshw. Res. 41, 143–155 (2007).Article 

    Google Scholar 
    Smith, K. F. & Lester, P. J. Cyanobacterial blooms appear to be driven by top-down rather than bottom-up effects in the Lower Karori Reservoir (Wellington, New Zealand). N. Z. J. Mar. Freshw. Res. 40, 53–63 (2006).CAS 
    Article 

    Google Scholar 
    Caroppo, C. Ecology and biodiversity of picoplanktonic cyanobacteria in coastal and brackish environments. Biodivers. Conserv. 24, 949–971 (2015).Article 

    Google Scholar 
    Pulina, S. et al. Picophytoplankton seasonal dynamics and interactions with environmental variables in three Mediterranean coastal lagoons. Estuaries Coasts 40, 469–478 (2017).CAS 
    Article 

    Google Scholar 
    Callieri, C. Picophytoplankton in freshwater ecosystems: the importance of small-sized phototrophs. Freshw. Rev. 1, 1–28 (2008).Article 

    Google Scholar 
    Keefer, D. K. Investigating landslides caused by earthquakes: a historical review. Surv. Geophys. 23, 473–510 (2002).ADS 
    Article 

    Google Scholar 
    Fan, X. et al. Earthquake-induced chains of geologic hazards: patterns, mechanisms, and impacts. Rev. Geophys. 57, 421–503 (2019).ADS 
    Article 

    Google Scholar 
    Manighetti, I. et al. Repeated giant earthquakes on the Wairarapa fault, New Zealand, revealed by Lidar-based paleoseismology. Sci. Rep. 10, 2124 (2020).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    McSaveney, E. Historic earthquakes: the 1942 Wairarapa earthquakes. Te Ara Encyclopedia of New Zealand https://teara.govt.nz/en/historic-earthquakes/page-9 (2006).New Zealand’s environmental reporting series: our atmosphere and climate. (Ministry for the Environment & Stats NZ, 2020).Beng, K. C. & Corlett, R. T. Applications of environmental DNA (eDNA) in ecology and conservation: opportunities, challenges and prospects. Biodivers. Conserv. 29, 2089–2121 (2020).Article 

    Google Scholar 
    Freeland, J. R. The importance of molecular markers and primer design when characterizing biodiversity from environmental DNA. Genome https://doi.org/10.1139/gen-2016-0100 (2016).Article 
    PubMed 

    Google Scholar 
    Barnes, M. A. et al. Environmental conditions influence eDNA persistence in aquatic systems. Environ. Sci. Technol. 48, 1819–1827 (2014).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Barnes, M. A. et al. Environmental conditions influence eDNA particle size distribution in aquatic systems. Environmental DNA https://doi.org/10.1002/edn3.160 (2020).Article 

    Google Scholar 
    Corinaldesi, C., Beolchini, F. & Dell’anno, A. Damage and degradation rates of extracellular DNA in marine sediments: implications for the preservation of gene sequences. Mol. Ecol. 17, 3939–3951 (2008).CAS 
    PubMed 
    Article 

    Google Scholar 
    Eichmiller, J. J., Best, S. E. & Sorensen, P. W. Effects of temperature and trophic state on degradation of environmental DNA in lake water. Environ. Sci. Technol. 50, 1859–1867 (2016).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Strickler, K. M., Fremier, A. K. & Goldberg, C. S. Quantifying effects of UV-B, temperature, and pH on eDNA degradation in aquatic microcosms. Biol. Conserv. 183, 85–92 (2015).Article 

    Google Scholar 
    Seymour, M. et al. Acidity promotes degradation of multi-species environmental DNA in lotic mesocosms. Commun. Biol. https://doi.org/10.1038/s42003-017-0005-3 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Dommain, R. et al. The challenges of reconstructing tropical biodiversity with sedimentary ancient DNA: a 2200-year-long metagenomic record from Bwindi Impenetrable Forest, Uganda. Front. Ecol. Evol. https://doi.org/10.3389/fevo.2020.00218 (2020).Article 

    Google Scholar 
    Jöhnk, K. D. et al. Summer heatwaves promote blooms of harmful cyanobacteria. Glob. Change Biol. 14, 495–512 (2008).ADS 
    Article 

    Google Scholar 
    Sogin, M. L. et al. Microbial diversity in the deep sea and the underexplored “rare biosphere”. PNAS 103, 12115–12120 (2006).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar  More

  • in

    Deep-sea infauna with calcified exoskeletons imaged in situ using a new 3D acoustic coring system (A-core-2000)

    Joos, F., Plattner, G. K., Stocker, T. F., Marchal, O. & Schmittner, A. Global warming and marine carbon cycle feedbacks on future atmospheric CO2. Science 284(5413), 464–467 (1999).ADS 
    CAS 
    Article 

    Google Scholar 
    Smith, K. L. et al. Climate, carbon cycling, and deep-ocean ecosystems. Proc. Nat. Acad. Sci USA 106, 19211–19218 (2009).ADS 
    CAS 
    Article 

    Google Scholar 
    Ramirez-Llodra, E. et al. Man and the last great wilderness: Human impact on the deep sea. PLoS ONE 6, e22588 (2011).ADS 
    CAS 
    Article 

    Google Scholar 
    Pham, C. K. et al. Marine litter distribution and density in European Seas, from the shelves to deep basins. PLoS ONE 9, e95839 (2014).ADS 
    Article 

    Google Scholar 
    Angel, M. What is the deep sea? In Deep-sea fishes (eds Randall, D. & Farrell, A.) 1–41 (Academic Publishing, 1997).
    Google Scholar 
    Smith, C. R., De Leo, F. C., Bernardino, A. F., Sweetman, A. K. & Arbizu, P. M. Abyssal food limitation, ecosystem structure and climate change. Trends Ecol. Evol. 23, 518–528 (2008).Article 

    Google Scholar 
    Thurber, A. R. et al. Ecosystem function and services provided by the deep sea. Biogeosciences 11, 3941–3963 (2014).ADS 
    Article 

    Google Scholar 
    Solan, M. et al. Extinction and ecosystem function in the marine benthos. Science 306(5699), 1177–1180 (2004).ADS 
    CAS 
    Article 

    Google Scholar 
    Danise, S., Twitchett, R. J., Little, C. T. & Clemence, M. E. The impact of global warming and anoxia on marine benthic community dynamics: An example from the Toarcian (Early Jurassic). PLoS ONE 8(2), e56255 (2013).ADS 
    CAS 
    Article 

    Google Scholar 
    Nomaki, H. et al. In situ experimental evidences for responses of abyssal benthic biota to shifts in phytodetritus compositions linked to global climate change. Glob. Chang. Biol. 27, 6139–6155 (2021).Article 

    Google Scholar 
    Viehman, H. A. & Zydlewski, G. B. Fish interactions with a commercial-scale tidal energy device in the natural environment. Estuaries Coast 38(1), 241–252 (2015).Article 

    Google Scholar 
    Danovaro, R. et al. Implementing and innovating marine monitoring approaches for assessing marine environmental status. Front. Mar. Sci. 3, 213 (2016).Article 

    Google Scholar 
    Mizuno, K. et al. An efficient coral survey method based on a large-scale 3-D structure model obtained by Speedy Sea Scanner and U-Net segmentation. Sci. Rep. 10(1), 12416. https://doi.org/10.1038/s41598-020-69400-5 (2020).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Eleftheriou, A., & Moore, D. C. (2013). Macrofauna techniques. Methods for the study of marine benthos, 175–251.Solan, M. et al. In situ quantification of bioturbation using time lapse fluorescent sediment profile imaging (f SPI), luminophore tracers and model simulation. Mar. Ecol. Prog. Ser. 271, 1–12 (2004).ADS 
    Article 

    Google Scholar 
    Hale, R. et al. High-resolution computed tomography reconstructions of invertebrate burrow systems. Sci. Data 2(1), 1–5 (2015).Article 

    Google Scholar 
    Plets, R. M. et al. The use of a high-resolution 3D Chirp sub-bottom profiler for the reconstruction of the shallow water archaeological site of the Grace Dieu (1439), River Hamble, UK. J. Archaeol. Sci. 36(2), 408–418 (2009).Article 

    Google Scholar 
    Mizuno, K. et al. Automatic non-destructive three-dimensional acoustic coring system for in situ detection of aquatic plant root under the water bottom. Case Stud. Nondestruct. Test. Evaluat. 5, 1–8 (2016).CAS 
    Article 

    Google Scholar 
    Suganuma, H., Mizuno, K. & Asada, A. Application of wavelet shrinkage to acoustic imaging of buried asari clams using high-frequency ultrasound. J. Appl. Phys. 57(7S1), 07LG08 (2018).Article 

    Google Scholar 
    Dorgan, K. M. et al. Impacts of simulated infaunal activities on acoustic wave propagation in marine sediments. J. Acoust. Soc. Am. 147(2), 812–823 (2020).ADS 
    Article 

    Google Scholar 
    Mizuno, K., Cristini, P., Komatitsch, D. & Capdeville, Y. Numerical and experimental study of wave propagation in water-saturated granular media using effective method theories and a full-wave numerical simulation. IEEE J. Ocean. Eng. 45(3), 772–785 (2020).ADS 
    Article 

    Google Scholar 
    Schulze, I. et al. Laboratory measurements to image endobenthos and bioturbation with a high-frequency 3D seismic lander. Geosciences 11(12), 508 (2021).ADS 
    Article 

    Google Scholar 
    Hashimoto, J. et al. Deep-sea communities dominated by the giant clam, Calyptogena soyoae, along the slope foot of Hatsushima Island, Sagami Bay, central Japan. Palaeogeogr. Palaeoclimatol. Palaeoecol. 71(12), 179–192 (1989).Article 

    Google Scholar 
    Fujikura, K., Hashimoto, J. & Okutani, T. Estimated population densities of megafauna in two chemosynthesisbased communities: A cold seep in Sagami Bay and a hydrothermal vent in the Okinawa Trough. Benthos. Res. 57(1), 21–30 (2002).Article 

    Google Scholar 
    Childress, J. J. & Girguis, P. R. The metabolic demands of endosymbiotic chemoautotrophic metabolism on host physiological capacities. J. Exp. Biol. 214(2), 312–325 (2011).CAS 
    Article 

    Google Scholar 
    Okuba, K. (2021). Basic study on sonar system development for exploring infaunal bivalves. Master thesis, GSFS, The University of Tokyo (in Japanese).Stoll, R. D. & Bryan, G. M. Wave attenuation in saturated sediments. The J. Acoust. Soc. Am. 47(5B), 1440–1447 (1970).ADS 
    Article 

    Google Scholar 
    Schwartz, L. & Plona, T. J. Ultrasonic propagation in close-packed disordered suspensions. J. Appl. Phys. 55(11), 3971–3977 (1984).ADS 
    Article 

    Google Scholar 
    Seike, K., Shirai, K. & Murakami-Sugihara, N. Using tsunami deposits to determine the maximum depth of benthic burrowing. PLoS ONE 12(8), e0182753. https://doi.org/10.1371/journal.pone.0182753 (2017).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar  More