More stories

  • in

    Bowhead whales use two foraging strategies in response to fine-scale differences in zooplankton vertical distribution

    1.
    Laidre, K. L., Heide-Jørgensen, M. P., Nielsen, T. G. & Gissel Nielsen, T. Role of the bowhead whale as a predator in West Greenland. Mar. Ecol. Prog. Ser. 346, 285–297 (2007).
    ADS  Article  Google Scholar 
    2.
    Pomerleau, C., Ferguson, S. H. & Walkusz, W. Stomach contents of bowhead whales (Balaena mysticetus) from four locations in the Canadian Arctic. Polar Biol. 34, 615–620 (2011).
    Article  Google Scholar 

    3.
    Pomerleau, C. et al. Prey assemblage isotopic variability as a tool for assessing diet and the spatial distribution of bowhead whale Balaena mysticetus foraging in the Canadian eastern Arctic. Mar. Ecol. Prog. Ser. 469, 161–174 (2012).
    ADS  Article  Google Scholar 

    4.
    Kenney, R. D., Hyman, M. A. M., Owen, R. E., Scott, G. P. & Winn, H. E. Estimation of prey densities required by western North Atlantic right whales. Mar. Mamm. Sci. 2, 1–13 (1986).
    Article  Google Scholar 

    5.
    Baumgartner, M. F. & Tarrant, A. M. The physiology and ecology of diapause in marine copepods. Ann. Rev. Mar. Sci. 9, 387–411 (2017).
    PubMed  Article  Google Scholar 

    6.
    Fortune, S. M., Trites, A. W., Mayo, C. A., Rosen, D. A. S. & Hamilton, P. K. Energetic requirements of North Atlantic right whales and the implications for species recovery. Mar. Ecol. Prog. Ser. 478, 253–272 (2013).
    ADS  Article  Google Scholar 

    7.
    Hays, G. C., Richardson, A. J. & Robinson, C. Climate change and marine plankton. Trends Ecol. Evol. 20, 337–344 (2005).
    PubMed  Article  PubMed Central  Google Scholar 

    8.
    Beaugrand, G., Mackas, D. & Goberville, E. Applying the concept of the ecological niche and a macroecological approach to understand how climate influences zooplankton: advantages, assumptions, limitations and requirements. Prog. Oceanogr. 111, 75–90 (2013).
    ADS  Article  Google Scholar 

    9.
    Beaugrand, G., Reid, P. C., Ibañez, F., Lindley, J. A. & Edwards, M. Reorganization of North Atlantic marine copepod biodiversity and climate. Science 296, 1692–1694 (2002).
    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

    10.
    Beaugrand, G. Decadal changes in climate and ecosystems in the North Atlantic Ocean and adjacent seas. Deep Res. Part II Top. Stud. Oceanogr. 56, 656–673 (2009).
    ADS  Article  Google Scholar 

    11.
    Chust, G. et al. Are Calanus spp. shifting poleward in the North Atlantic? A habitat modelling approach. ICES J. Mar. Sci. 71, 241–253 (2014).
    Article  Google Scholar 

    12.
    Grieve, B. D., Hare, J. A. & Saba, V. S. Projecting the effects of climate change on Calanus finmarchicus distribution within the U.S. Northeast Continental Shelf. Sci. Rep. 7, 6264 (2017).
    ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

    13.
    Feng, Z., Ji, R., Campbell, R. G., Ashjian, C. J. & Zhang, J. Early ice retreat and ocean warming may induce copepod biogeographic boundary shifts in the Arctic Ocean. J. Geophys. Res. Ocean. 121, 6137–6158 (2016).
    ADS  Article  Google Scholar 

    14.
    Feng, Z., Ji, R., Ashjian, C., Campbell, R. & Zhang, J. Biogeographic responses of the copepod Calanus glacialis to a changing Arctic marine environment. Glob. Chang. Biol. 24, e159–e170 (2018).
    ADS  PubMed  Article  PubMed Central  Google Scholar 

    15.
    Kwok, R. et al. Thinning and volume loss of the Arctic Ocean sea ice cover: 2003–2008. J. Geophys. Res. Ocean. 114, 1–16 (2009).
    Article  Google Scholar 

    16.
    Stroeve, J., Holland, M. M., Meier, W., Scambos, T. & Serreze, M. Arctic sea ice decline: Faster than forecast. Geophys. Res. Lett. 34, 1–5 (2007).
    Article  Google Scholar 

    17.
    Notz, D. & Stroeve, J. Observed Arctic sea-ice loss directly follows anthropogenic CO2 emission. Science 354, 747–750 (2016).
    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

    18.
    Pomerleau, C. et al. Spatial patterns in zooplankton communities across the eastern Canadian sub-Arctic and Arctic waters: insights from stable carbon (delta C-13) and nitrogen (delta N-15) isotope ratios. J. Plankton Res. 33, 1779–1792 (2011).
    CAS  Article  Google Scholar 

    19.
    Pomerleau, C., Lesage, V., Winkler, G., Rosenberg, B. & Ferguson, S. H. Contemporary diet of bowhead whales (Balaena mysticetus) from the eastern Canadian Arctic inferred from fatty acid biomarkers. Arctic 67, 84–92 (2014).
    Article  Google Scholar 

    20.
    Heide-Jørgensen, M. P. et al. Large scale sexual segregation of bowhead whales. Endang. Species Res. 13, 73–78 (2010).
    Article  Google Scholar 

    21.
    Heide-Jørgensen, M. P. et al. Winter and spring diving behavior of bowhead whales relative to prey. Anim. Biotelemetry 1, 1–15 (2013).
    Article  Google Scholar 

    22.
    Curry, B., Lee, C. M., Petrie, B., Moritz, R. E. & Kwok, R. Multiyear volume, liquid freshwater, and sea ice transports through Davis Strait, 2004–10. J. Phys. Oceanogr. 44, 1244–1266 (2014).
    ADS  Article  Google Scholar 

    23.
    Pomerleau, C. et al. Mercury and stable isotope cycles in baleen plates are consistent with year-round feeding in two bowhead whale (Balaena mysticetus) populations. Polar Biol. 41, 1881–1893 (2018).
    Article  Google Scholar 

    24.
    Doniol-Valcroze, T. et al. Abundance estimate of the Eastern Canada-West Greenland bowhead whale population based on the 2013 High Arctic Cetacean Survey. (2015).

    25.
    Frasier, T. et al. Abundance estimates of the Eastern Canada-West Greenland bowhead whale (Balaena mysticetus) population based on genetic capture-mark-recapture analyses. (2015).

    26.
    Frasier, T. R. et al. Abundance estimation from genetic mark-recapture data when not all sites are sampled: an example with the bowhead whale. Glob. Ecol. Conserv. 22, e00903 (2020).
    Article  Google Scholar 

    27.
    Dunbar, M. J. Physical oceanographic results of the ‘Calanus’ expeditions in Ungava Bay, Frobisher Bay, Cumberland Sound, Hudson Strait and Northern Hudson Bay, 1949–1955. J. Fish. Res. Board Canada 15, 155–201 (1958).
    Article  Google Scholar 

    28.
    Aitken, A. & Gilbert, R. Holocene nearshore environments and sea-level history in Pangnirtung fjord, Baffin Island, NWT, Canada. Arct. Alp. Res. 21, 34–44 (1989).
    Article  Google Scholar 

    29.
    McMeans, B. C. et al. Seasonal patterns in fatty acids of Calanus hyperboreus (Copepoda, Calanoida) from Cumberland Sound, Baffin Island, Nunavut. Mar. Biol. 159, 1095–1105 (2012).
    CAS  Article  Google Scholar 

    30.
    Bedard, J. M. et al. Outside influences on the water column of Cumberland Sound, Baffin Island. J. Geophys. Res. C Ocean. 120, 5000–5018 (2015).
    ADS  Article  Google Scholar 

    31.
    Tang, C. C. L. et al. The circulation, water masses and sea-ice of Baffin Bay. Prog. Oceanogr. 63, 183–228 (2004).
    ADS  Article  Google Scholar 

    32.
    Falk-Petersen, S., Mayzaud, P., Kattner, G. & Sargent, J. R. Lipids and life strategy of Arctic Calanus. Mar. Biol. Res. 5, 18–39 (2009).
    Article  Google Scholar 

    33.
    Davies, K. T. A., Ryan, A. & Taggart, C. T. Measured and inferred gross energy content in diapausing Calanus spp. in a Scotian shelf basin. J. Plankton Res. 34, 614–625 (2012).
    Article  Google Scholar 

    34.
    Koski, W. R., Davis, R. A., Miller, G. W. & Withrow, D. E. Reproduction. in The bowhead whale (eds. Burns, J. J., Montague, J. J. & Cowles, C. J.) 239–274 (Special Publication Number 2. The Society of Marine Mammalogy, Lawrence, KS, 1993).

    35.
    George, J. C. et al. Inferences from bowhead whale ovarian and pregnancy data: age estimates, length at sexual maturity and ovulation rates. International Whaling Commission Scientific Paper 56 (2004).

    36.
    Higdon, J. W. & Ferguson, S. H. Past, present, and future for bowhead whales (Balaena mysticetus) in northwest Hudson Bay. In A Little Less Arctic: Top Predators in the World’s Largest Northern Inland Sea, Hudson Bay (eds Ferguson, S. H. et al.) 159–177 (Springer, New York, 2010).
    Google Scholar 

    37.
    Liu, H. & Hopcroft, R. R. Growth and development of Pseudocalanus spp. in the northern Gulf of Alaska. J. Plankton Res. 30, 923–935 (2008).
    Article  Google Scholar 

    38.
    DeLorenzo Costa, A., Durbin, E. G. & Mayo, C. A. Variability in the nutritional value of the major copepods in Cape Cod Bay (Massachusetts, USA) with implications for right whales. Mar. Ecol. 27, 109–123 (2006).
    ADS  Article  CAS  Google Scholar 

    39.
    Madsen, S. D., Nielsen, T. G. & Hansen, B. W. Annual population development and production by Calanus finmarchicus, C. glacialisand C. hyperboreus in Disko Bay, western Greenland. Mar. Biol. 139, 75–93 (2001).
    Article  Google Scholar 

    40.
    Reeves, R., Mitchell, E., Mansfield, A. & McLaughlin, M. Distribution and migration of the bowhead whale, Balaena mysticetus, in the Eastern North American. Arctic 36, 60 (1983).
    Article  Google Scholar 

    41.
    Holland, C. A. William penny, 1809–92: Arctic whaling master. Polar Rec. 15, 25–43 (1970).
    Article  Google Scholar 

    42.
    Higdon, J. W. Commercial and subsistence harvests of bowhead whales (Balaena mysticetus) in eastern Canada and West Greenland. J. Cetacean Res. Manag. 11, 185–216 (2010).
    Google Scholar 

    43.
    Diemer, K. M. et al. Marine mammal and seabird summer distribution and abundance in the fjords of northeast Cumberland Sound of Baffin Island, Nunavut, Canada. Polar Biol. 34, 41–48 (2011).
    Article  Google Scholar 

    44.
    Matthews, C. et al. Boat-based surveys for marine mammals and seabirds in Cumberland Sound. Field report. (2012).

    45.
    Baumgartner, M. F., Wenzel, F. W., Lysiak, N. S. J. & Patrician, M. R. North Atlantic right whale foraging ecology and its role in human-caused mortality. Mar. Ecol. Prog. Ser. 581, 165–181 (2017).
    ADS  Article  Google Scholar 

    46.
    Fortune, S. et al. Seasonal diving and foraging behaviour of Eastern Canada-West Greenland bowhead whales. Mar. Ecol. Prog. Ser. 643, 197–217 (2020).
    ADS  Article  Google Scholar 

    47.
    Block, B. A. Physiological ecology in the 21st century: Advancements in biologging science. Integr. Comp. Biol. 45, 305–320 (2005).
    PubMed  Article  PubMed Central  Google Scholar 

    48.
    Hays, G. C. New insights: animal-borne cameras and accelerometers reveal the secret lives of cryptic species. J. Anim. Ecol. 84, 587–589 (2015).
    PubMed  Article  PubMed Central  Google Scholar 

    49.
    Bograd, S. J., Block, B. A., Costa, D. P. & Godley, B. J. Biologging technologies: new tools for conservation. Introduction. Endanger. Species Res. 10, 1–7 (2010).
    Article  Google Scholar 

    50.
    Unstad, K. H. & Tande, K. S. Depth distribution of Calanus finmarchicus and C. glacialis in relation to environmental conditions in the Barents Sea. Polar Res. 10, 409–420 (1991).
    Article  Google Scholar 

    51.
    Hirche, H. J. & Niehoff, B. Reproduction of the Arctic copepod Calanus hyperboreus in the Greenland Sea-field and laboratory observations. Polar Biol. 16, 209–219 (1996).
    Article  Google Scholar 

    52.
    Madsen, S. J., Nielsen, T. G., Tervo, O. M. & Söderkvist, J. Importance of feeding for egg production in Calanus finmarchicus and C. glacialis during the Arctic spring. Mar. Ecol. Prog. Ser. 353, 177–190 (2008).
    ADS  CAS  Article  Google Scholar 

    53.
    Darnis, G. & Fortier, L. Temperature, food and the seasonal vertical migration of key arctic copepods in the thermally stratified Amundsen Gulf (Beaufort Sea, Arctic Ocean) GE. J. Plankton Res. 36, 1092–1108 (2014).
    CAS  Article  Google Scholar 

    54.
    Parent, G. J., Plourde, S. & Turgeon, J. Overlapping size ranges of Calanus spp. off the Canadian Arctic and Atlantic Coasts: impact on species abundances. J. Plankton Res. 33, 1654–1665 (2011).
    CAS  Article  Google Scholar 

    55.
    Hyslop, E. J. Stomach contents analysis—a review of methods and their application. J. Fish Biol. 17, 411–429 (1980).
    Article  Google Scholar 

    56.
    Dunweber, M. et al. Succession and fate of the spring diatom bloom in Disko Bay, western Greenland. Mar. Ecol. Prog. Ser. 419, 11–29 (2010).
    ADS  Article  CAS  Google Scholar 

    57.
    Swalethorp, R. et al. Grazing, egg production, and biochemical evidence of differences in the life strategies of Calanus finmarchicus, C. glacialis and C. hyperboreus in Disko Bay, Western Greenland. Mar. Ecol. Prog. Ser. 429, 125–144 (2011).
    ADS  Article  Google Scholar 

    58.
    Baumgartner, M. F. & Mate, B. R. Summertime foraging ecology of North Atlantic right whales. Mar. Ecol. Prog. Ser. 264, 123–135 (2003).
    ADS  Article  Google Scholar 

    59.
    Hirche, H. J. Long-term experiments on lifespan, reproductive activity and timing of reproduction in the Arctic copepod Calanus hyperboreus. Mar. Biol. 160, 2469–2481 (2013).
    Article  Google Scholar 

    60.
    Visser, A. W. & Jónasdóttir, S. H. Lipids, buoyancy and the seasonal vertical migration of Calanus finmarchicus. Fish. Oceanogr. 8, 100–106 (1999).
    Article  Google Scholar 

    61.
    Scott, C. L., Kwasniewski, S., Falk-Petersen, S. & Sargent, J. R. Lipids and life strategies of Calanus finmarchicus, Calanus glacialis and Calanus hyperboreus in late autumn, Kongsfjorden, Svalbrad. Polar Biol. 23, 510–516 (2000).
    Article  Google Scholar 

    62.
    Heide-Jørgensen, M. P., Laidre, K. L., Logsdon, M. L. & Nielsen, T. G. Springtime coupling between chlorophyll a, sea ice and sea surface temperature in Disko Bay, West Greenland. Prog. Oceanogr. 73, 79–95 (2007).
    ADS  Article  Google Scholar 

    63.
    Baumgartner, M. F. Comparisons of Calanus finmarchicus fifth copepodite abundance estimates from nets and an optical plankton counter. J. Plankton Res. 25, 855–868 (2003).
    Article  Google Scholar 

    64.
    Herman, A. W. Design and calibration of a new optical plankton counter capable of sizing small zooplankton. Deep Sea Res. A 39, 395–415 (1992).
    ADS  Article  Google Scholar 

    65.
    Falk-Petersen, S. et al. Vertical migration in high Arctic waters during autumn 2004. Deep Sea Res. II(55), 2275–2284 (2008).
    ADS  Article  Google Scholar 

    66.
    Baumgartner, M. F., Lysiak, N. S. J., Schuman, C., Urban-Rich, J. & Wenzel, F. W. Diel vertical migration behavior of Calanus finmarchicus and its influence on right and sei whale occurrence. Mar. Ecol. Prog. Ser. 423, 167–184 (2011).
    ADS  Article  Google Scholar 

    67.
    Bollens, S. M. & Frost, B. W. Predator-induced diet vertical migration in a planktonic copepod. J. Plankton Res. 11, 1047–1065 (1989).
    Article  Google Scholar 

    68.
    Hays, G. C. Ontogenetic and seasonal variation in the diel vertical migration of the copepods Metridia lucens and Metridia longa. Limnol. Oceanogr. 40, 1461–1465 (1995).
    ADS  Article  Google Scholar 

    69.
    Huntley, M. & Brooks, E. R. Effects of age and food availability on diel vertical migration of Calanus pacificus. Mar. Biol. 71, 23–31 (1982).
    Article  Google Scholar 

    70.
    Simon, M., Johnson, M. J., Tyack, P. & Madsen, P. T. Behavior and kinematics of continous ram filtration in bowhead wahles (Balaena mysticetus). Proc. R. Soc. Lond. B. 276, 3819–3828 (2009).
    Article  Google Scholar 

    71.
    van der Hoop, J. M. et al. Foraging rates of ram-filtering North Atlantic right whales. Funct. Ecol. 33, 1290–1306 (2019).
    Article  Google Scholar 

    72.
    Goldbogen, J. A. et al. Prey density and distribution drive the three-dimensional foraging strategies of the largest filter feeder. Funct. Ecol. 29, 951–961 (2015).
    Article  Google Scholar 

    73.
    Kooyman, G. L., Wahrenbrock, E. A., Castellini, M. A., Davis, R. W. & Sinnett, E. E. Aerobic and anaerobic metabolism during voluntary diving in Weddell seals: evidence of preferred pathways from blood chemsitry and behavior. J. Comp. Physiol. B 138, 335–346 (1980).
    CAS  Article  Google Scholar 

    74.
    Kooyman, G. L., Castellini, M. A., Davis, R. W. & Maue, R. A. Aerobic diving limits of immature Weddell seals. J. Comp. Physiol. B 151, 171–174 (1983).
    Article  Google Scholar 

    75.
    Dyke, A. S., Hooper, J. & Savelle, J. M. A history of sea ice in the Canadian Arctic archipelago based on postglacial remains of the bowhead whale (Balaena mysticetus). Arctic 49, 235–255 (1996).
    Article  Google Scholar 

    76.
    Baumgartner, M. F., Hammar, T. & Robbins, J. Development and assessment of a new dermal attachment for short-term tagging studies of baleen whales. Methods Ecol. Evol. 6, 289–297 (2015).
    Article  Google Scholar 

    77.
    Reinhart, N. R. et al. Occurrence of killer whale Orcinus orca rake marks on Eastern Canada-West Greenland bowhead whales Balaena mysticetus. Polar Biol. 36, 1133–1146 (2013).
    Article  Google Scholar 

    78.
    Fortune, S. M. E. et al. Evidence of molting and the function of “rock-nosing” behavior in bowhead whales in the eastern Canadian Arctic. PLoS ONE 12, 1–15 (2017).
    MathSciNet  Article  CAS  Google Scholar 

    79.
    Silva, M. A. et al. Assessing performance of Bayesian state-space models fit to argos satellite telemetry locations processed with kalman filtering. PLoS ONE 9, e92277 (2014).
    ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

    80.
    Lowther, A. D., Lydersen, C., Fedak, M. A., Lovell, P. & Kovacs, K. M. The argos-CLS kalman filter: Error structures and state-space modelling relative to fastloc GPS data. PLoS ONE 10, e0124754 (2015).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    81.
    R Development Core Team. R: A Language and Environment for Statistical Computing. R Development Core Team, Vienna (2016). https://doi.org/10.1038/sj.hdy.6800737.

    82.
    Jonsen, I. D., Flemming, J. M. & Myers, R. A. Robust state-space modeling of animal movement data. Ecology 86, 2874–2880 (2005).
    Article  Google Scholar 

    83.
    Jonsen, I. D. et al. State-space models for bio-loggers: a methodological road map. Deep. Res. II(88–89), 34–46 (2013).
    ADS  Google Scholar 

    84.
    Tinbergen, N., Impekoven, M. & Franck, D. An experiment on spacing-out as a defence against predation. Behaviour 28, 307–320 (1967).
    Article  Google Scholar 

    85.
    Kareiva, P. & Odell, G. Swarms of predators exhibit ‘preytaxis’ if individual predators use area-restricted search. Am. Nat. 130, 233–270 (1987).
    Article  Google Scholar 

    86.
    Haskell, D. G. Experiments and a model examining learning in the area-restricted search behavior of ferrets (Mustela putorius furo). Behav. Ecol. 8, 448–455 (1997).
    Article  Google Scholar 

    87.
    Fauchald, P. & Tveraa, T. Using first-passage time in the analysis of area-restricted search and habitat selection. Ecology 84, 282–288 (2003).
    Article  Google Scholar 

    88.
    Anderwald, P. et al. Spatial scale and environmental determinants in minke whale habitat use and foraging. Mar. Ecol. Prog. Ser. 450, 259–274 (2012).
    ADS  Article  Google Scholar 

    89.
    Jonsen, I. D., Myers, R. A. & James, M. C. Identifying leatherback turtle foraging behaviour from satellite telemetry using a switching state-space model. Mar. Ecol. Prog. Ser. 337, 255–264 (2007).
    ADS  Article  Google Scholar 

    90.
    Pinheiro, J. C. & Bates, D. M. Linear mixed-effects models. in Mixed-effects models in S and S-Plus 1–56 (Springer, New York, 2000). https://doi.org/10.1198/tech.2001.s574.

    91.
    Sverdrup, H. U. On conditions for the vernal blooming of phytoplankton. ICES J. Mar. Sci. 18, 287–295 (1953).
    Article  Google Scholar 

    92.
    Thomson, R. E. & Fine, I. V. Estimating mixed layer depth from oceanic profile data. J. Atmos. Ocean. Technol. 20, 319–329 (2003).
    ADS  Article  Google Scholar 

    93.
    Smith, W. O. & Jones, R. M. Vertical mixing, critical depths, and phytoplankton growth in the Ross Sea. ICES J. Mar. Sci. 72, 1952–1960 (2015).
    Article  Google Scholar 

    94.
    Suthers, I. M., Taggart, C. T., Rissik, D. & Baird, M. E. Day and night ichthyoplankton assemblages and zooplankton biomass size spectrum in a deep ocean island wake. Mar. Ecol. Prog. Ser. 322, 225–238 (2006).
    ADS  CAS  Article  Google Scholar 

    95.
    Grainger, E. H. The copepods Calanus glacial is Jaschnov and Calanus finmarchicus (Gunnerus) in Canadian Arctic-Subarctic waters. J. Fish. Res. Board Can. 18, 663–678 (1961).
    Article  Google Scholar 

    96.
    Jaschnov, W. A. Distribution of Calanus Species in the Seas of the Northern Hemisphere. Int. Rev. Hydrobiol. Hydrogr. 55, 197–212 (1970).
    Article  Google Scholar 

    97.
    Hirche, H. J. & Mumm, N. Distribution of dominant copepods in the Nansen Basin, Arctic Ocean, in summer. Deep Sea Res. A 39, 485–505 (1992).
    ADS  Article  Google Scholar 

    98.
    Breteler, W. C. M. K., Fransz, H. G. & Gonzalez, S. R. Growth and development of four calanoid copepod species under experimental and natural conditions. Neth. J. Sea Res. 16, 195–207 (1982).
    Article  Google Scholar  More

  • in

    How Joannites’ economy eradicated primeval forest and created anthroecosystems in medieval Central Europe

    1.
    Carpenter, S. R. & Scheffer, M. Critical transitions and regime shifts in ecosystems: consolidating recent advances. New Models for Ecosystem Dynamics and Restoration 22–32 (2009).
    2.
    Taubert, F. et al. Global patterns of tropical forest fragmentation. Nature 554, 519–522 (2018).
    ADS  CAS  Google Scholar 

    3.
    Geldmann, J., Manica, A., Burgess, N. D., Coad, L. & Balmford, A. A global-level assessment of the effectiveness of protected areas at resisting anthropogenic pressures. Proc. Natl. Acad. Sci. USA 116, 23209–23215 (2019).
    ADS  CAS  Google Scholar 

    4.
    Ellis, E. C. Anthropogenic transformation of the terrestrial biosphere. Philos. Trans. A Math. Phys. Eng. Sci. 369, 1010–1035 (2011).
    ADS  Google Scholar 

    5.
    Stephens, L. et al. Archaeological assessment reveals Earth’s early transformation through land use. Science 365, 897–902 (2019).
    ADS  CAS  Google Scholar 

    6.
    Marchant, R. Archaeological assessment reveals Earth’s early transformation through land use. Science 365, 897–902 (2019).
    ADS  Google Scholar 

    7.
    Kaplan, J. O., Krumhardt, K. M. & Zimmermann, N. The prehistoric and preindustrial deforestation of Europe. Quatern. Sci. Rev. 28, 3016–3034 (2009).
    ADS  Google Scholar 

    8.
    Czerniak, L. & Pyzel, J. Neolithic farmers and the introduction of pottery in the south Baltic. Bericht Römisch-Germanischen Kommission 89, 347–360 (2011).
    Google Scholar 

    9.
    Willis, K. J., Gillson, L. & Brncic, T. M. How, “virgin” is virgin rainforest?. Science 304, 402–403 (2004).
    CAS  Google Scholar 

    10.
    Seddon, A. W. R. What do we mean by regime shift? Distinguishing between extrinsic and intrinsic forcing in paleoecological data. Past Glob. Changes Mag. 25, 94–95 (2017).
    Google Scholar 

    11.
    Loughlin, N. J. D., Gosling, W. D., Mothes, P. & Montoya, E. Ecological consequences of post-Columbian indigenous depopulation in the Andean-Amazonian corridor. Nat. Ecol. Evol. 2, 1233–1236 (2018).
    Google Scholar 

    12.
    Moreno-Mateos, D. et al. Anthropogenic ecosystem disturbance and the recovery debt. Nat. Commun. 8, 14163 (2017).
    ADS  CAS  PubMed  PubMed Central  Google Scholar 

    13.
    Lamentowicz, M. et al. Always on the tipping point—a search for signals of past societies and related peatland ecosystem critical transitions during the last 6500 years in N Poland. Quatern. Sci. Rev. 225, 105954 (2019).
    Google Scholar 

    14.
    Ralska-Jasiewiczowa, M. et al. Late Glacial and Holocene history of vegetation in Poland based on isopollen maps (W. Szafer Institute of Botany, Polish Academy of Sciences, Kraków, 2004).
    Google Scholar 

    15.
    Clifford, M. J. & Booth, R. K. Late-holocene drought and fire drove a widespread change in forest community composition in eastern North America. Holocene 25, 1102–1110 (2015).
    ADS  Google Scholar 

    16.
    Davies, L. J. et al. High-resolution age modelling of peat bogs from northern Alberta, Canada, using pre- and post-bomb 14 C, 210 Pb and historical cryptotephra. Quat. Geochronol. 47, 138–162 (2018).
    Google Scholar 

    17.
    Kołaczek, P., Karpińska-Kołaczek, M., Marcisz, K., Gałka, M. & Lamentowicz, M. Palaeohydrology and the human impact on one of the largest raised bogs complex in the Western Carpathians (Central Europe) during the last two millennia. Holocene 28, 595–608 (2018).
    ADS  Google Scholar 

    18.
    Marcisz, K. et al. Long-term hydrological dynamics and fire history over the last 2000 years in CE Europe reconstructed from a high-resolution peat archive. Quatern. Sci. Rev. 112, 138–152 (2015).
    ADS  Google Scholar 

    19.
    Hildebrandt-Radke, I. & Makohonienko, M. Krajobraz kulturowy Wielkopolski w pradziejach i czasach historycznych: wprowadzenie. Landform Anal. 16, 17–19 (2011).
    Google Scholar 

    20.
    Makohonienko, M. Przyrodnicza historia Gniezna (Homini, Bydgoszcz-Poznań, 2000).
    Google Scholar 

    21.
    Brown, A. & Pluskowski, A. Detecting the environmental impact of the Baltic Crusades on a late-medieval (13th–15th century) frontier landscape: palynological analysis from Malbork Castle and hinterland, Northern Poland. J. Archaeol. Sci. 38, 1957–1966 (2011).
    Google Scholar 

    22.
    Stivrins, N. et al. Palaeoenvironmental evidence for the impact of the crusades on the local and regional environment of medieval (13th-16th century) northern Latvia, eastern Baltic. The Holocene 1–10 (2015).

    23.
    Wacnik, A. et al. Determining the responses of vegetation to natural processes and human impacts in north-eastern Poland during the last millennium: combined pollen, geochemical and historical data. Veg. Hist. Archaeobot. 25, 479–498 (2016).
    Google Scholar 

    24.
    Woodward, C., Shulmeister, J., Larsen, J., Jacobsen, G. E. & Zawadzki, A. Landscape hydrology The hydrological legacy of deforestation on global wetlands. Science 346, 844–847 (2014).

    25.
    Colombaroli, D. & Gavin, D. G. Highly episodic fire and erosion regime over the past 2,000 y in the Siskiyou Mountains, Oregon. Proc. Natl. Acad. Sci. 107, 18909–18914 (2010).
    ADS  CAS  Google Scholar 

    26.
    Bonn, A., Allott, T., Evans, M., Joosten, H. & Stoneman, R. Peatland Restoration and Ecosystem Services: Science, Policy and Practice (Cambridge University Press, Cambridge, 2016).
    Google Scholar 

    27.
    Ireland, A. W. & Booth, R. K. Upland deforestation triggered an ecosystem state-shift in a kettle peatland. J. Ecol. 100, 586–596 (2012).
    Google Scholar 

    28.
    Joosten, H., Tanneberger, F. & Moen, A. Mires and peatlands in Europe “Stuttgart, Germany”, 2017).

    29.
    Swindles, G. T. et al. Widespread drying of European peatlands in recent centuries. Nat. Geosci. 12, 922–928 (2019).
    ADS  CAS  Google Scholar 

    30.
    Marcisz, K., Kołaczek, P., Gałka, M., Diaconu, A.-C. & Lamentowicz, M. Exceptional hydrological stability of a Sphagnum-dominated peatland over the late Holocene. Quatern. Sci. Rev. 231, 106180 (2020).
    Google Scholar 

    31.
    Page, S. E. & Baird, A. J. Peatlands and global change: response and resilience. Annu. Rev. Environ. Resour. 41, 35–57 (2016).
    Google Scholar 

    32.
    Poppick, L. Resilient Peatlands Keep Carbon Bogged Down. Eos 100, (2019).

    33.
    Gorham, E. & Rochefort, L. Peatland restoration: A brief assessment with special reference to Sphagnum bogs. Wetl. Ecol. Manag. 11, 109–119 (2003).
    CAS  Google Scholar 

    34.
    Calder, W. J. & Shuman, B. Detecting past changes in vegetation resilience in the context of a changing climate. Biol. Lett. 15, 20180768 (2019).
    PubMed  PubMed Central  Google Scholar 

    35.
    de Jong, R. et al. in Changing Climates, Earth Systems and Society. Series: International Year of Planet Earth (ed Dodson, J.) 85–121 (Springer, Heidelberg, 2010).

    36.
    Marcinkian, A. Ziemia lubuska w dobie cywilizacji łużyckiej, cz. 2 Zielona Góra, 2010).

    37.
    Urbańska, A. & Kurnatowski, S. in Studia nad początkami i rozplanowaniem miast na środkową Odrą i dolna Warta (województwo zielonogórskie) t. 1: Ziemia Lubuska, Nowa Marchia, Wielkopolska (ed Zdzisław Kaczmarczyk, A. W.) 35–111 Zielona Góra, 1967).

    38.
    Weiss, A. Organizacja diecezji lubuskiej w średniowieczu Lublin, 1970).

    39.
    Labuda, G. Zajęcie Ziemi Lubuskiej przez margrabiów brandenburskicj w połowie XIII wieku. Śląski Kwartalnik Historyczny „Sobótka” 28, 311–322 (1973).

    40.
    Przybył, M. in Cognitioni Gestorum. Studia z dziejów średniowiecza dedykowane Profesorowi Jerzemu Strzelczykowi (eds Sikorski, D. A. & Wyrwa, A. M.) 395–404 Poznań-Warszawa, 2006).

    41.
    Zajchowska, S. in tudia nad początkami i rozplanowaniem miast na środkową Odrą i dolna Warta (województwo zielonogórskie) t. 1: Ziemia Lubuska, Nowa Marchia, Wielkopolska (eds Kaczmarczyk, Z. & Wędzki, A.) 113–126 Zielona Góra, 1967).

    42.
    Wasilkiewicz, K. Templariusze i Joannici w biskupstwie lubuskim (XIII-XVI w.) Gniezno, 2016).

    43.
    Carsten, F. L. Essays in German History (A&C Black, 1985).

    44.
    Piskorski, J. M. Kolonizacja wiejska Pomorza Zachodniego w XIII i w początkach XIV wieku na tle procesów osadniczych w średniowiecznej Europie (Poznańskie Tow, Przyjaciół Nauk, 1990).
    Google Scholar 

    45.
    Chmarzyński, G. Zamek w Łagowie. Pamiętnik Związku Historyków Sztuki i Kultury 1, 55–87 (1948).
    Google Scholar 

    46.
    Lamentowicz, M. & Mitchell, E. A. D. The ecology of testate amoebae (Protists) in Sphagnum in north-western Poland in relation to peatland ecology. Microb. Ecol. 50, 48–63 (2005).
    Google Scholar 

    47.
    van Geel, B. in Tracking environmental change using lake sediments. Volume 3: Terrestrial, Algal and Siliceous Indicators (eds Smol, J. P., Birks, H. J. B. & Last, W. M.) 99–119 (Kluwer Academic Publishers, Dortrecht, 2001).

    48.
    Davies, A. L. Dung fungi as an indicator of large herbivore dynamics in peatlands. Rev. Palaeobot. Palynol. 271, 104108 (2019).
    Google Scholar 

    49.
    Cywa, K. Trees and shrubs used in medieval Poland for making everyday objects. Veg. Hist. Archaeobot. 27, 111–136 (2018).
    Google Scholar 

    50.
    Kurnatowska, Z. & Łosińska, A. in Człowiek a środowisko w środkowym i dolnym Nadodrzu 161–173 Wrocław, 1996).

    51.
    Warner, B. G., Kubiw, H. J. & Hanf, K. I. An anthropogenic cause for quaking mire formation in southwestern Ontario. Nature 340, 380–384 (1989).
    ADS  Google Scholar 

    52.
    Ellis, E. C. et al. Used planet: A global history. Proc. Natl. Acad. Sci. USA 110, 7978–7985 (2013).
    ADS  CAS  Google Scholar 

    53.
    Haldon, J. et al. History meets palaeoscience: Consilience and collaboration in studying past societal responses to environmental change. Proc Natl Acad Sci USA 115, 3210 (2018).
    ADS  CAS  Google Scholar 

    54.
    Czerwiński, S. et al. Znaczenie wspólnych badań historycznych i paleoekologicznych nad wpływem człowieka na środowisko. Przykład ze stanowiska Kazanie we wschodniej Wielkopolsce. Studia Geohistorica 56 (2020).

    55.
    Brown, A. et al. The ecological impact of conquest and colonization on a medieval frontier landscape: combined palynological and geochemical analysis of lake sediments from Radzyń Chełminski, northern Poland. Geoarchaeology 30, 511–527 (2015).
    Google Scholar 

    56.
    Jaroszewicz, B. et al. Białowieża forest—a relic of the high naturalness of European Forests. Forests 10, 849 (2019).

    57.
    Sabatini, F. M. et al. Where are Europe’s last primary forests. Divers. Distrib. 24, 1426–1439 (2018).
    Google Scholar 

    58.
    Ludat, H. Das Lebuser Stiftsregister von 1405. Studien zu den Sozial- und Wirtschaftsverhältnissen im mittleren Oderraum zu Beginn des 15 Wiesbaden, 1965).

    59.
    Zellweger, F. et al. Forest microclimate dynamics drive plant responses to warming. Science 368, 772–775 (2020).
    ADS  CAS  Google Scholar 

    60.
    Hájek, T. in Photosynthesis in Bryophytes and Early Land Plants, Advances in Photosynthesis and Respiration (eds Hanson, D. T. & Rice, S. K.) 233–252 (Springer Science+Business Media, Dordrecht, 2014).

    61.
    Lamentowicz, M., Tobolski, K. & Mitchell, E. A. D. Palaeoecological evidence for anthropogenic acidification of a kettle-hole peatland in northern Poland. The Holocene 17, 1185–1196 (2007).
    ADS  Google Scholar 

    62.
    Słowiński, M. et al. Paleoecological and historical data as an important tool in ecosystem management. J. Environ. Manag. 236, 755–768 (2019).
    Google Scholar 

    63.
    Gorham, E., Janssens, J. A., Wheeler, G. A. & Glaser, P. H. The natural and anthropogenic acidification of peatlands. Effects of atmospheric pollutants on forests, wetlands and agricultural ecosystems. Proc. Toronto, 1985 493–512 (1987).

    64.
    Pawlyta, J. & Lamentowicz, M. in Methods of absolute chronology 10th International conference, Gliwice, Poland, 22–25th April 2010 (2010).

    65.
    Lamentowicz, M. & Obremska, M. A rapid response of testate amoebae and vegetation to inundation of a kettle hole mire. J. Paleolimnol. 43, 499–511 (2010).
    ADS  Google Scholar 

    66.
    Zaccone, C. et al. Highly anomalous accumulation rates of C and N recorded by a relic, free-floating peatland in Central Italy. Sci. Rep. 7, 43040 (2017).
    ADS  CAS  PubMed  PubMed Central  Google Scholar 

    67.
    Korcz, W. Historyczne losy ziem pogranicza lubusko-wielkopolskiego na tle dziejów ziemi lubuskiej. Rocznik Lubuski 40–85 (1966).

    68.
    Ellis, E. C. Ecology in an anthropogenic biosphere. Ecol. Monogr. 85, 287–331 (2015).
    Google Scholar 

    69.
    Bronk Ramsey, C. Radiocarbon calibration and analysis of stratigraphy: the OxCal program. Radiocarbon 37, 425–430 (1995).
    CAS  Google Scholar 

    70.
    Bronk Ramsey, C. Deposition models for chronological records. Quatern. Sci. Rev. 27, 42–60 (2008).
    ADS  Google Scholar 

    71.
    Ramsey, C. B. & Lee, S. Recent and planned developments of the program OxCal. Radiocarbon 55, 720–730 (2013).
    CAS  Google Scholar 

    72.
    Reimer, P. J. et al. Intcal13 and Marine13 radiocarbon age calibration curves 0–50,000 years Cal BP. Radiocarbon 55, 1869–1887 (2013).
    CAS  Google Scholar 

    73.
    Berglund, B. E. & Ralska-Jasiewiczowa, M. in Handbook of Holocene Paleoecology and Paleohydrology (ed Berglund, B. E.) 455–484 (Wiley & Sons Ltd., Chichester-Toronto, 1986).

    74.
    Moore, P. D., Webb, J. A. & Collinson, M. E. Pollen Analysis (Blackwell Scientific Publication, 1991).

    75.
    Beug, H.-J. Leitfaden der Pollenbestimmung für Mitteleuropa und angrenzende Gebiete (Verlag Dr. Friedrich Pfeil, München, 2004).
    Google Scholar 

    76.
    van Geel, B. & Aptroot, A. Fossil ascomycetes in quaternary deposits. Nova Hedwigia 82, 313–329 (2006).
    Google Scholar 

    77.
    Behre, K.-E. The interpretation of anthopogenic indicators in pollen diagrams. Pollen Spores 23, 225–245 (1981).
    Google Scholar 

    78.
    Poska, A., Saarse, L. & Veski, S. Reflections of pre- and early-agrarian human impact in the pollen diagrams of Estonia. Palaeogeogr. Palaeoclimatol. Palaeoecol. 209, 37–50 (2004).
    Google Scholar 

    79.
    Gaillard, M.-J. Pollen methods and studies/archaeological applications. Encyclop. Quatern. Sci. 3, 880–904 (2013).
    Google Scholar 

    80.
    Tinner, W. & Hu, F. S. Size parameters, size-class distribution and area-number relationship of microscopic charcoal: relevance for fire reconstruction. The Holocene 13, 499–505 (2003).
    ADS  Google Scholar 

    81.
    Finsinger, W. & Tinner, W. Minimum count sums for charcoalconcentration estimates in pollen slides: accuracy and potential errors. The Holocene 15, 293–297 (2005).
    ADS  Google Scholar 

    82.
    Davis, M. B. & Deevey, E. S. J. Pollen accumulation rates: estimates from late-glacial sediment of Roger Lake. Science 145, 1293–1295 (1964).
    ADS  CAS  Google Scholar 

    83.
    Feurdean, A. et al. Fire has been an important driver of forest dynamics in the Carpathian Mountains during the Holocene. For. Ecol. Manage. 389, 15–26 (2017).
    Google Scholar 

    84.
    Conedera, M. et al. Reconstructing past fire regimes: methods, applications, and relevance to fire management and conservation. Quatern. Sci. Rev. 28, 555–576 (2009).
    ADS  Google Scholar 

    85.
    Mauquoy, D. & van Geel, B. in Encyclopedia of Quaternary Science (Elsevier, Amsterdam, 2007).

    86.
    Booth, R. K., Lamentowicz, M. & Charman, D. J. Preparation and analysis of testate amoebae in peatland paleoenvironmental studies. Mires Peat 7, 1–7 (2010).
    Google Scholar 

    87.
    Payne, R. J. & Mitchell, E. A. D. How many is enough? Determining optimal count totals for ecological and palaeoecological studies of testate amoebae. J. Paleolimnol. 42, 483–495 (2008).
    Google Scholar 

    88.
    Clarke, K. J. Guide to Identification of Soil Protozoa – Testate Amoebae (Freshwater Biological Association, Ambleside, 2003).
    Google Scholar 

    89.
    Grospietsch, T. Wechseltierchen (Rhizopoden) (Kosmos Verlag, Stuttgart, 1958).
    Google Scholar 

    90.
    Mazei, Y. & Tsyganov, A. N. Freshwater Testate Amoebae (KMK, Moscow, 2006).
    Google Scholar 

    91.
    Ogden, C. G. & Hedley, R. H. An Atlas of Freshwater Testate Amoebae (Oxford University Press, London, 1980).
    Google Scholar 

    92.
    Meisterfeld, R. in The Illustrated Guide to the Protozoa (eds Lee, J. J., Leedale, G. F. & Bradbury, P.) 827–860 (Allen Press, Lawrence, 2001).

    93.
    Meisterfeld, R. in The Illustrated Guide to the Protozoa (eds Lee, J. J., Leedale, G. F. & Bradbury, P.) 1054–1084 (Allen Press, Lawrence, 2001).

    94.
    Siemensma, F. J. Microworld, world of amoeboid organisms. World-wide electronic publication (www.arcella.nl) (Kortenhoef, The Netherlands, 2019).

    95.
    Juggins, S. C2 User guide. Software for ecological and palaeoecological data analysis and visualisation (University of Newcastle, Newcastle upon Tyne, UK, 2003).

    96.
    Grimm, E. C. TILIA/TILIA graph. Version 1.2. (1992).

    97.
    MacAskill, M. R. DataGraph 3.0. J. Stat. Softw. 47, 1–9 (2012).
    Google Scholar 

    98.
    Lara, E., Roussel-Delif, L., Fournier, B., Wilkinson, D. M. & Mitchell, E. A. D. Soil microorganisms behave like macroscopic organisms: patterns in the global distribution of soil euglyphid testate amoebae. J. Biogeogr. 43, 520–532 (2016).
    Google Scholar 

    99.
    Singer, D., Kosakyan, A., Pillonel, A., Mitchell, E. A. D. & Lara, E. Eight species in the Nebela collaris complex: Nebela gimlii (Arcellinida, Hyalospheniidae), a new species described from a Swiss raised bog. Eur. J. Protistol. 51, 79–85 (2015).
    Google Scholar 

    100.
    Dixon, P. VEGAN, a package of R functions for community ecology. J. Veg. Sci. 14, 927–930 (2003).
    Google Scholar 

    101.
    Team R Development Core. R: A language and environment for statistical computing. (2015). More

  • in

    Otolith chemoscape analysis in whiting links fishing grounds to nursery areas

    1.
    Kritzer, J. P. & Sale, P. F. Metapopulation ecology in the sea: From Levins’ model to marine ecology and fisheries science. Fish Fish 5, 131–140 (2004).
    Article  Google Scholar 
    2.
    Mumby, P. J. Connectivity of reef fish between mangroves and coral reefs: algorithms for the design of marine reserves at seascape scales. Biol. Conserv. 128, 215–222 (2006).
    Article  Google Scholar 

    3.
    Laegdsgaard, P. & Johnson, C. Why do juvenile fish utilise mangrove habitats? J. Exp. Mar. Bio. Ecol. https://doi.org/10.1016/S0022-0981(00)00331-2 (2001).
    Article  Google Scholar 

    4.
    Cocheret de la Morinière, E. et al. Ontogenetic dietary changes of coral reef fishes in the mangrove-seagrass-reef continuum: stable isotopes and gut-content analysis. Mar. Ecol. Prog. Ser. https://doi.org/10.3354/meps246279 (2003).
    Article  Google Scholar 

    5.
    Karnauskas, M., Chérubin, L. M. & Paris, C. B. Adaptive significance of the formation of multi-species fish spawning aggregations near submerged capes. PLoS ONE https://doi.org/10.1371/journal.pone.0022067 (2011).
    Article  PubMed  PubMed Central  Google Scholar 

    6.
    Wright, P. J. et al. Integrating the scale of population processes into fisheries management, as illustrated in the sandeel, Ammodytes marinus. ICES J. Mar. Sci. 76, 1453–1463 (2019).
    Article  Google Scholar 

    7.
    Thorrold, S. R., Latkoczy, C., Swart, P. K. & Jones, C. M. Natal homing in a marine fish metapopulation. Science 291, 297–299 (2001).
    CAS  PubMed  Article  Google Scholar 

    8.
    Gillanders, B. M. in Ecological Connectivity among Tropical Coastal Ecosystems (ed. Nagelkerken, I.) 457–492 (Springer Netherlands, 2009).

    9.
    Kincaid, K. & Rose, G. Effects of closing bottom trawling on fisheries, biodiversity, and fishing communities in a boreal marine ecosystem: The Hawke box off Labrador, Canada. Can. J. Fish. Aquat. Sci. 74, 1490–1502 (2017).
    Article  Google Scholar 

    10.
    Le Quesne, W. J. F., Hawkins, S. J. & Shepherd, J. G. A comparison of no-take zones and traditional fishery management tools for managing site-attached species with a mixed larval pool. Fish Fish 8, 181–195 (2007).
    Article  Google Scholar 

    11.
    Horwood, J. W., Nichols, J. H. & Milligan, S. Evaluation of closed areas for fish stock conservation. J. Appl. Ecol. 35, 893–903 (2008).
    Article  Google Scholar 

    12.
    Wright, P. J., Tobin, D., Gibb, F. M. & Gibb, I. M. Assessing nursery contribution to recruitment: Relevance of closed areas to haddock Melanogrammus aeglefinus. Mar. Ecol. Prog. Ser. 400, 221–232 (2010).
    Article  Google Scholar 

    13.
    Lipcius, R. N., Stockhausen, W. T., Eggleston, D. B., Marshall, L. S. & Hickey, B. Hydrodynamic decoupling of recruitment, habitat quality and adult abundance in the Caribbean spiny lobster: Source-sink dynamics? in. Mar. Freshw. Res. 48, 807–815 (1997).
    Article  Google Scholar 

    14.
    McBride, R. S. & Able, K. W. Ecology and fate of butterflyfishes, Chaetodon spp., in the temperate, western North Atlantic. Bull. Mar. Sci. 63, 401–416 (1998).
    Google Scholar 

    15.
    Dahlgren, C. P. et al. Marine nurseries and effective juvenile habitats: Concepts and applications. Mar. Ecol. Prog. Ser. 312, 291–295 (2006).
    Article  Google Scholar 

    16.
    Fogarty, M. J., Fogarty, M. J., Botsford, L. W. & Botsford, L. W. Population connectivity and spatial management of marine fisheries. Oceanography 20, 112–123 (2007).
    Article  Google Scholar 

    17.
    Pickett, G. D., Kelley, D. F. & Pawson, M. G. The patterns of recruitment of sea bass, Dicentrarchus labrax L. from nursery areas in England and Wales and implications for fisheries management. Fish. Res. 68, 329–342 (2004).
    Article  Google Scholar 

    18.
    Walther, B. D. & Thorrold, S. R. Water, not food, contributes the majority of strontium and barium deposited in the otoliths of a marine fish. Mar. Ecol. Prog. Ser. https://doi.org/10.3354/meps311125 (2006).
    Article  Google Scholar 

    19.
    Dorval, E., Jones, C. M., Hannigan, R. & Montfrans, J. van. Relating otolith chemistry to surface water chemistry in a coastal plain estuary. Can. J. Fish. Aquat. Sci. 64, 411–424 (2007).
    CAS  Article  Google Scholar 

    20.
    Thomas, O. R. B., Ganio, K., Roberts, B. R. & Swearer, S. E. Trace element–protein interactions in endolymph from the inner ear of fish: implications for environmental reconstructions using fish otolith chemistry. Metallomics 9, 239–249 (2017).
    CAS  PubMed  Article  Google Scholar 

    21.
    Walther, B. D., Kingsford, M. J., O’Callaghan, M. D. & McCulloch, M. T. Interactive effects of ontogeny, food ration and temperature on elemental incorporation in otoliths of a coral reef fish. Environ. Biol. Fishes 89, 441–451 (2010).
    Article  Google Scholar 

    22.
    Sturrock, A. M. et al. Physiological influences can outweigh environmental signals in otolith microchemistry research. Mar. Ecol. Prog. Ser. 500, 245–264 (2014).
    CAS  Article  Google Scholar 

    23.
    Sturrock, A. M. et al. Quantifying physiological influences on otolith microchemistry. Methods Ecol. Evol. 6, 806–816 (2015).
    Article  Google Scholar 

    24.
    Régnier, T. et al. Otolith chemistry reveals seamount fidelity in a deepwater fish. Deep Sea Res. Part I Oceanogr. Res. Pap. 121, 183–189 (2017).
    Article  Google Scholar 

    25.
    Gillanders, B. M. Temporal and spatial variability in elemental composition of otoliths: implications for determining stock identity and connectivity of populations. Can. J. Fish. Aquat. Sci. 59, 669–679 (2002).
    CAS  Article  Google Scholar 

    26.
    Wright, P. J., Régnier, T., Gibb, F. M., Augley, J. & Devalla, S. Assessing the role of ontogenetic movement in maintaining population structure in fish using otolith microchemistry. Ecol. Evol. 8, 7907–7920 (2018).
    PubMed  PubMed Central  Article  Google Scholar 

    27.
    Wright, P. J., Neat, F. C., Gibb, F. M., Gibb, I. M. & Thordarson, H. Evidence for metapopulation structuring in cod from the west of Scotland and North Sea. J. Fish. Biol. 69, 181–199 (2006).
    CAS  Article  Google Scholar 

    28.
    ICES. Working Group for the Celtic Seas Ecoregion (WGCSE). ICES Scientific Reports 1:29, (ICES, 2019).

    29.
    Tobin, D., Wright, P. J., Gibb, F. M. & Gibb, I. M. The importance of life stage to population connectivity in whiting (Merlangius merlangus) from the northern European shelf. Mar. Biol. 157, 1063–1073 (2010).
    Article  Google Scholar 

    30.
    Burns, N. M., Bailey, D. M. & Wright, P. J. A method to improve fishing selectivity through age targeted fishing using life stage distribution modelling. PLoS ONE https://doi.org/10.1371/journal.pone.0214459 (2019).
    Article  PubMed  PubMed Central  Google Scholar 

    31.
    Symes, D. & Ridgeway, S. Inshore fisheries regulation and management in Scotland; Meeting the challenges of Environmental Integration. Scottish Natural Heritage Commissioned Report F02AA405 (Scottish Natural Heritage and RSPB, 2003).

    32.
    Thygesen, U. H., Pedersen, M. W. & Madsen, H. in Tagging and Tracking of Marine Animals with Electronic Devices. Vol. 9, 23–34 (Springer, 2009).

    33.
    Gillanders, B. M. Connectivity between juvenile and adult fish populations: do adults remain near their recruitment estuaries? Mar. Ecol. Prog. Ser. 240, 215–223 (2002).
    Article  Google Scholar 

    34.
    Elsdon, T. et al. Otolith chemistry to describe movements and life-history parameters of fishes. Oceanogr. Mar. Biol. 46, 297–330 (2008).
    Google Scholar 

    35.
    West, J. B., Bowen, G. J., Dawson, T. E. & Tu, K. P. Isoscapes: Understanding Movement, Pattern, and Process on Earth through Isotope Mapping. (Springer, 2010).

    36.
    Vander Zanden, H. B. et al. Determining origin in a migratory marine vertebrate: A novel method to integrate stable isotopes and satellite tracking. Ecol. Appl. 25, 320–335 (2015).
    PubMed  Article  Google Scholar 

    37.
    Trueman, C. N., MacKenzie, K. M. & St John Glew, K. Stable isotope-based location in a shelf sea setting: accuracy and precision are comparable to light-based location methods. Methods Ecol. Evol. 8, 232–240 (2017).
    Article  Google Scholar 

    38.
    Campana, S. E. & Thorrold, S. R. Otoliths, increments, and elements: keys to a comprehensive understanding of fish populations?. Can. J. Fish. Aquat. Sci. 58, 30–38 (2001).
    Article  Google Scholar 

    39.
    Elsdon, T. S. & Gillanders, B. M. Interactive effects of temperature and salinity on otolith chemistry: challenges for determining environmental histories of fish. Can. J. Fish. Aquat. Sci. 59, 1796–1808 (2002).
    CAS  Article  Google Scholar 

    40.
    Barnes, T. C. & Gillanders, B. M. Combined effects of extrinsic and intrinsic factors on otolith chemistry: Implications for environmental reconstructions. Can. J. Fish. Aquat. Sci. 70, 1159–1166 (2013).
    CAS  Article  Google Scholar 

    41.
    Gibb, F. M., Gibb, I. M. & Wright, P. J. Isolation of Atlantic cod (Gadus morhua) nursery areas. Mar. Biol. 151, 1185–1194 (2007).
    Article  Google Scholar 

    42.
    Higgins, R. M. et al. Multi-disciplinary fingerprints reveal the harvest location of cod Gadus morhua in the Northeast Atlantic. Mar. Ecol. Prog. Ser. 404, 197–206 (2010).
    Article  Google Scholar 

    43.
    Geffen, A. J., Jarvis, K., Thorpe, J. P., Leah, R. T. & Nash, R. D. M. Spatial differences in the trace element concentrations of Irish Sea plaice Pleuronectes platessa and whiting Merlangius merlangus otoliths. J. Sea Res. 50, 247–256 (2003).
    Article  CAS  Google Scholar 

    44.
    Mercier, L. et al. Selecting statistical models and variable combinations for optimal classification using otolith microchemistry. Ecol. Appl. 21, 1352–1364 (2011).
    PubMed  Article  Google Scholar 

    45.
    Balls, P. et al. Ices baseline survey of trace metals in European shelf waters. ICES J. Mar. Sci. https://doi.org/10.1006/jmsc.1993.1047 (1993).
    Article  Google Scholar 

    46.
    IPCS. Barium international programme on chemical safety: environmental health criteria 107. (Environmental Health Criteria, 1990).

    47.
    Balls, P. W. Composition of suspended particulate matter from Scottish coastal waters-geochemical implications for the transport of trace metal contaminants. Sci. Total Environ. https://doi.org/10.1016/0048-9697(86)90021-5 (1986).
    Article  Google Scholar 

    48.
    Muller, F. L. L., Tranter, M. & Balls, P. W. Distribution and transport of chemical constituents in the Clyde Estuary. Estuar. Coast. Shelf Sci. 39, 105–126 (1994).
    CAS  Article  Google Scholar 

    49.
    Gibb, F. M., Régnier, T., Donald, K. & Wright, P. J. Connectivity in the early life history of sandeel inferred from otolith microchemistry. J. Sea Res. 119, 8–16 (2017).
    Article  Google Scholar 

    50.
    Xiao, J., Tagliabracci, V. S., Wen, J., Kim, S. A. & Dixon, J. E. Crystal structure of the Golgi casein kinase. Proc. Natl Acad. Sci. USA 110, 10574–10579 (2013).
    CAS  PubMed  Article  Google Scholar 

    51.
    Liu, Z. et al. Shape-preserving amorphous-to-crystalline transformation of CaCO3 revealed by in situ TEM. Proc. Natl Acad. Sci. USA 117, 3397–3404 (2020).
    CAS  PubMed  Article  Google Scholar 

    52.
    Altenritter, M. E. & Walther, B. D. The Legacy of Hypoxia: tracking carryover effects of low oxygen exposure in a demersal fish using geochemical tracers. Trans. Am. Fish. Soc. https://doi.org/10.1002/tafs.10159 (2019).
    Article  Google Scholar 

    53.
    Forrester, G. E. & Swearer, S. E. Trace elements in otoliths indicate the use of open- coast versus bay nursery habitats by juvenile California halibut. Mar. Ecol. Prog. Ser. 241, 201–213 (2002).
    CAS  Article  Google Scholar 

    54.
    Hamer, P. A. & Jenkins, G. P. Comparison of spatial variation in otolith chemistry of two fish species and relationships with water chemistry and otolith growth. J. Fish. Biol. 71, 1035–1055 (2007).
    CAS  Article  Google Scholar 

    55.
    White, J. W., Standish, J. D., Thorrold, S. R. & Warner, R. R. Markov chain monte carlo methods for assigning larvae to natal sites using natural geochemical tags. Ecol. Appl. 18, 1901–1913 (2008).
    PubMed  Article  Google Scholar 

    56.
    Stanley, R. R. E. et al. Environmentally mediated trends in otolith composition of juvenile Atlantic cod (Gadus morhua). ICES J. Mar. Sci. 72, 2350–2363 (2015).
    Article  Google Scholar 

    57.
    Xu, Q.-S. & Liang, Y.-Z. Monte Carlo cross validation. Chemom. Intell. Lab. Syst. 56, 1–11 (2001).
    CAS  Article  Google Scholar 

    58.
    Baudron, A. R., Serpetti, N., Fallon, N. G., Heymans, J. J. & Fernandes, P. G. Can the common fisheries policy achieve good environmental status in exploited ecosystems: The west of Scotland demersal fisheries example. Fish. Res. 211, 217–230 (2019).
    Article  Google Scholar 

    59.
    Carlucci, R. et al. Nursery areas of red mullet (Mullus barbatus), hake (Merluccius merluccius) and deep-water rose shrimp (Parapenaeus longirostris) in the Eastern-Central Mediterranean Sea. Estuar. Coast. Shelf Sci. 83, 529–538 (2009).
    CAS  Article  Google Scholar 

    60.
    Heath, M. R. et al. Combination of genetics and spatial modelling highlights the sensitivity of cod (Gadus morhua) population diversity in the North Sea to distributions of fishing. ICES J. Mar. Sci. 71, 794–807 (2014).
    Article  Google Scholar 

    61.
    Hunter, A., Speirs, D. C. & Heath, M. R. Fishery-induced changes to age and length dependent maturation schedules of three demersal fish species in the Firth of Clyde. Fish. Res. 170, 14–23 (2015).
    Article  Google Scholar 

    62.
    Phillipson, J. & Symes, D. ‘A sea of troubles’: Brexit and the fisheries question. Mar. Policy 90, 168–173 (2018).
    Article  Google Scholar 

    63.
    Ellis, J. R., Milligan, S. P., Readdy, L., Taylor, N. & Brown, M. J. Spawning and nursery grounds of selected fish species in UK waters. Science Series Technical Report. Vol. 147 (Cefas, 2012).

    64.
    European Commission. Impact assessment of discard policy for specific fisheries. Studies and Pilot Projects for Carrying Out the Common Fisheries Policy No FISH/2006/17. 1–289 (IEEP, 2007).

    65.
    Hufnagl, M., Peck, M. A., Nash, R. D. M., Pohlmann, T. & Rijnsdorp, A. D. Changes in potential North Sea spawning grounds of plaice (Pleuronectes platessa L.) based on early life stage connectivity to nursery habitats. J. Sea Res. 84, 26–39 (2013).
    Article  Google Scholar 

    66.
    Hannesson, R. Zonal attachment of fish stocks and management cooperation. Fish. Res. 140, 149–154 (2013).
    Article  Google Scholar 

    67.
    ICES. Report of the Workshop of National Age Readings Coordinators (WKNARC). (ICES, 2011).

    68.
    Longerich, H. P., Jackson, S. E. & Gunnther, D. Laser ablation inductively coupled plasma mass spectrometery transient signal data acquisition and analyte concentration calculation. J. Anal. Spectrom. 11, 899–904 (1996).
    CAS  Article  Google Scholar 

    69.
    Knick, S. T., Leu, M., Rotenberry, J. T., Hanser, S. E. & Fesenmyer, K. A. Diffuse migratory connectivity in two species of shrubland birds: Evidence from stable isotopes. Oecologia 174, 595–608 (2014).
    PubMed  Article  Google Scholar 

    70.
    Burns, N. M., Hopkins, C. R., Bailey, D. M. & Wright, P. J. Connecting fishing grounds to nursery areas using novel otolith isoscape analysis. [Data Collection] University of Glasgow Enlighten database https://doi.org/10.5525/gla.researchdata.1040 (2020).

    71.
    Burns, N. M. NeilMBurns/Element_chemoscape_geolocation20: Code for Otolith chemoscape analysis in whiting (Version v1.0). Zenodo. https://doi.org/10.5281/zenodo.4088644 (2020). More

  • in

    A dataset of plant and microbial community structure after long-term grazing and mowing in a semiarid steppe

    Site description
    The study site is a typical semiarid grassland representative of the Eurasian steppe17, located in the Xilin River Basin, Inner Mongolia Autonomous Region of China, close to the Inner Mongolia Grassland Ecosystem Research Station (IMGERS, 43°38′ N, 116°42′ E). Mean annual precipitation is 346 mm, with 60–80% of precipitation falling in the growing season (May to September). Mean annual temperature is 0.3 °C, with mean monthly temperatures ranging from −21.6 °C in January to 19.0 °C in July4. The topography at our experimental site consists of two landscape units (i.e. flat block and sloped block), with elevation ranging from 1200 to 1280 m above sea level, and slopes less than 5°18,19. The soil is classified as dark chestnut (Calcic Chernozem, ISSS Working Group RB, 1998) derived from aeolian sediments18,20. The soil substrate is dominated by sandy loam and loamy sand with more than 50% being fine sand and silt21. At the beginning of the experiment, soil organic carbon and total nitrogen contents were higher in the flat block than in the sloped block (Table 1). Plant species richness and above-ground biomass were also greater in the flat block than in the sloped block, although species composition in terms of relative biomass of common species did not differ between the two systems (Table 1). Leymus chinensis (perennial rhizomatous grass) and Stipa grandis (perennial bunchgrass) are the dominant species in the study area, together accounting for more than 70% of community aboveground biomass. Other dominant species include Cleistogenes squarrosa, Agropyron cristatum, Achnatherum sibiricum, and Carex korshinskyi.
    Table 1 Soil and vegetation characteristics in the flat and sloped blocks prior to grazing and mowing interventions.
    Full size table

    Study design
    The experimental area was used for moderate sheep grazing (1.5–3 ewes ha−1 year−1) by local herdsmen until 2003. Afterwards, grass swards recovered for two years before the experiment started20,22. At the end of the growing season in 2004, prior to beginning the experiment, swards in the entire area were cut to 3–5 cm in stubble height23. The experiment was established in June 2005 with split plots in a randomized complete block design (Fig. 1). The study area included two blocks (i.e., flat and sloped blocks), with each block further divided into seven plots. We included flat and sloped blocks because our project was designed to assess the impacts of grazing at spatial scales that are both relevant to land management and that can capture ecosystem and landscape-scale effects of grazing24. It is unrealistic to conduct such a study in an area with no variation in topography. Grazing intensity was randomly assigned to the plots, and each plot was divided into two subplots. The grazing or mowing management regime was randomly assigned into each subplot23. In the grazing regime, there were seven levels of grazing intensity (GI: 0, 1.5, 3.0, 4.5, 6.0, 7.5 and 9.0 sheep ha−1), and sheep grazed in the subplots continuously from June to September each year25. The ungrazed plots (0 sheep ha−1) had no sheep grazing for 12 years. Each subplot was 2 ha, except the subplot with 1.5 sheep ha−1, which was enlarged to 4 ha to ensure a minimum herd of six sheep per subplot. In the mowing regime, mowing was done once a year in the middle of August. Plant and soil microbial community data was collected in late July and early August 2017, after 12 years of grazing and mowing treatments.
    Fig. 1

    Illustration of the grazing experiment design. G: grazing regime, M: mowing regime.

    Full size image

    Plant community surveys
    For each subplot, we randomly laid out ten 1 m × 1 m quadrats at least five meters from the edge of each plot to avoid edge effects. In each quadrat, plant species were identified, and the abundance of each species was counted by bunches (bunchgrasses) or stems (rhizomatous grasses). For each species, five individuals were randomly chosen to measure plant height and the average height of all species was used as plant canopy height. Plant canopy coverage was measured visually.
    Soil sampling
    For each quadrat, three soil cores (3 cm diameter, 10 cm depth) were collected, and soil was passed through a 2 mm sieve to form one composite soil sample per quadrat. Sieved soil was then divided into three subsamples. One subsample was air-dried for the analysis of soil pH, soil organic carbon (SOC), total nitrogen (TN), and total phosphorus (TP). The second fresh subsample was used for the analysis of microbial community structure and microbial biomass. The third subsample was stored at -20 °C prior to being used for microbial sequencing analysis.
    Soil physical and chemical properties
    To evaluate soil compaction, we measured soil hardness by using a Yamanaka-style soil hardness tester (Fujiwara Scientific Co., Japan). Soil moisture content was measured by using 10 g of moist soil that was oven-dried at 105 °C for 24 h. Soil pH was measured in a 1:2.5 soil:water suspension using a pH meter (FE20-FiveEasy, Mettler-Toledo, Switzerland).
    We measured SOC content with the Walkley-black method, soil TN content by the micro-Kjeldahl digestion, followed by colorimetric determination with a 2300 Kjeltec Analyzer Unit, and soil TP content was by the H2SO4-HClO4 fusion method using a 6505 UV spectrophotometer26.
    Soil microbial community structure
    Microbial community structure was assessed using phospholipid fatty acids (PLFAs), as described by Bossio and Scow27. First, lipids were extracted from 10 g of fresh soil using a buffer (CHCL3:CH3OH:K2HPO4 = 1:2:0.8, v:v:v). Second, the fatty acid methyl esters (FAMEs) were separated, quantified and identified using a gas chromatograph system (Agilent 7890, Santa Clara, USA) and a MIDI Sherlock Microbial Identification System (MIDI Inc., Newark, USA). Peak areas were converted to nmol g−1 dry soil using the internal standard, methylnon-adecanoate (C19:0). Third, the specific microbial groups were identified according to their representative markers. Specifically, G+ bacteria correspond to iso-, anteiso- and 10Me-branched PLFAs; G- bacteria correspond to monounsaturated and cyclopropyl PLFAs; arbuscular mycorrhizal fungi (AMF) use 16:1ω5c as representative marker; saprotrophic fungi (SF) use 18:1ω9c, 18:2ω6c and 18:3ω6c as representative markers28,29,30. The 12:0, 14:0, 15:0, 16:0, 17:0, 18:0 PLFAs were general markers present in all microorganisms30,31. Bacterial PLFAs included G+ and G− bacteria PLFAs. Fungal PLFAs included arbuscular mycorrhizal and saprotrophic fungi PLFAs. Total microbial PLFAs were the sum of bacterial, fungal, and general PLFAs.
    Soil microbial biomass carbon (MBC), nitrogen (MBN), and phosphorus (MBP) were measured using the chloroform-extraction method32,33. For MBC and MBN, two fresh soil samples were used for the analysis. One sample was placed in a chloroform steam bath for 24 h and another sample was kept non-fumigated. Then, organic C and total N were extracted by shaking two soil samples in 0.5 M K2SO4 for 1 h and filtering through a Whatman No. 1 filter paper (9 cm in diameter). The filtered extracts were measured with a total organic carbon (TOC) analyzer (Elementar vario TOC, Hanau, Germany). Microbial biomass P was measured using a similar method as for MBC and MBN except that P was extracted by 0.5 M NaHCO3 and then measured with a UV Spectrometer (6505 spectrometer, Jenway, Stone, UK).
    DNA extraction and sequencing
    We mixed ten soil samples of each plot to form one composite sample for DNA extraction and sequencing. Total genomic DNA was extracted from 0.5 g soil using a FastDNA Spin kit (MP Biomedical, Santa Ana, California, USA). The DNA quality was checked by 1% agarose gel electrophoresis and quantity was determined with a NanoDrop 2000 UV-vis spectrophotometer (Thermo Scientific, Wilmington). Bacterial 16 S rRNA genes were amplified with PCR primers 338 F (5′- ACTCCTACGGGAGGCAGCAG-3′) and 806 R (5′-GGACTACHVGGGTWTCTAAT-3′). Fungal internal transcribed spacer (ITS) rRNA genes were amplified with PCR primers ITS1F (5′-CTTGGTCATTTAGAGGAAGTAA-3′) and ITS2 (5′-GCTGCGTTCTTCATCGATGC-3′)34,35. The resulting PCR products were extracted from a 2% agarose gel and further purified using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, USA) and quantified using QuantiFluor™-ST (Promega, USA). Purified amplicons were pooled in equimolar concentrations and paired-end sequenced for high-throughput 16 S rRNA or ITS rRNA gene sequencing on an Illumina Hiseq. 2500 platform (Illumina Inc., USA) according to the standard protocols by Novogene Technology Co., Ltd. Operational taxonomic units (OTUs) were clustered with 97% similarity cut-off using UPARSE (version 7.1 https://drive5.com/uparse/), and chimeric sequences were identified and removed using UCHIME. Silva and Unite databases were used as references for bacteria and fungi, respectively34,35. More

  • in

    Neonicotinoid Clothianidin reduces honey bee immune response and contributes to Varroa mite proliferation

    Impact of Clothianidin on melanization and clotting
    Insects: honey bees used in this study were from Apis mellifera ligustica colonies, maintained in the experimental apiary of the University of Napoli “Federico II”, Department of Agricultural Sciences. Larvae and newly emerged bees used in all the experiments were obtained from brood frames taken from the experimental hives and kept in an incubator at 34 °C, 80% relative humidity for 12 h.
    Implantation experiment: 3rd instar larvae were first fed with 0.05, 0.01 ppm and no Clothianidin, while adults were treated with 20.0, 10.0, 5.0, 2.0 ng/bee and no Clothianidin, as already published4 (5 individuals for each treatment for both larvae and adults). In order to evaluate the encapsulation and melanization index12 a piece of transparent, nylon fluorocarbon coated fishing line (Ø = 0.08 mm; Asso Fishing Line), sterilized under UV light for 24 h, was inserted into the hemocelic cavity on 4th body segment of 5th instar larvae and into the haemocoelic cavity of adults through the membrane between the 3rd and 4th abdominal tergite. After 24 h, the implants were removed and subjected to image analysis, using GIMP version 2.8 (GNU Image Manipulation Program; www.gimp.org). In adult bees the clotting index was also analyzed by evaluating, after 24 h, the healing of a wound generated by piercing the honeybee integument inter-membrane between the 3rd and 4th abdominal tergite, using a sterile entomological needle. The rest of body was immediately stored at –80 °C for the subsequent molecular analysis. The experiment was repeated 3 times.
    Immune genes expression and DWV quantification: in order to assess the relative expression of Amel102 and Dorsal 1A as affected by Clothianidin treatment, two groups of 4th instar larvae (n = 100 per group) received 0.01 ppm of a Clothianidin-treated diet or a clean diet, respectively, as detailed below. After 24 and 72 h from feeding, 15 larvae for each experimental group were sampled and stored at –80 °C for subsequent analysis.
    RNA extraction, DWV quantification and relative gene expression data analysis were performed according to already published protocols12. Briefly, total RNA was isolated from individual honey bees using TRIzol reagent (Thermo Fisher Scientific, Waltham, MA, USA), according to the manufacturer’s instructions. The quantity and the quality of total RNA were assessed using Varioskan Flash spectrophotometer (Thermo Fisher Scientific).
    Differential relative expression of Amel102 and Dorsal 1A was measured by one-step qRT-PCR, using the Power SYBR Green RNA-to-Ct 1-Step Kit (Applied Biosystems, Carlsbad, CA, USA), according to the manufacturer’s instructions. Each reaction was prepared in 20 μL and contained 10 μL qRT-PCR mix 2X, 100 nM of forward and reverse primers, 0.16 μL of 125X RT enzyme mix, DEPC treated water and 50 ng of total RNA. All samples were analyzed in duplicate on a Step One Real Time PCR System (Applied Biosystems). Two reference genes, β-actin and rps5, were used as endogenous control for RNA loading. Relative gene expression data were analyzed using the ∆∆Ct method.
    The quantification of DWV genome copies was performed using the Power SYBR Green RNA-to-Ct 1-Step Kit (Applied Biosystems) as described above. Titers of DWV were determined by relating the Ct values of unknown samples to an established standard curve. The standard curve was established by plotting the logarithm of seven 10-fold dilutions of a starting solution containing 21.9 ng of plasmid DNA pCR II-TOPO (TOPO-TA cloning) with a DWV insert (from 21.9 ng to 21.9 fg), against the corresponding Ct value as the average of three repetitions. The PCR efficiency (E = 107.5%) was calculated based on the slope and coefficient of correlation (R2) of the standard curve, according to the following formula: E = 10(−1/slope) − 1 (slope = −3.155, y-intercept = 41.84, R2 = 0.999). All primers used are shown in Supplementary Table 1.
    Impact of Clothianidin on the reproduction of Varroa destructor
    The artificial diet used for feeding 4th instar larvae (L4) contained D-glucose (9%), D-fructose (9%), yeast extract (2%) and royal jelly (50%)37. Fresh royal jelly was bought from a local supplier. Chemical analysis of royal jelly carried out by the supplier revealed no acaricides, pesticides or antibiotic contaminants. Before use, royal jelly was treated with γ-rays (25 kGy) to eliminate any possible microbial contamination.
    A group of larvae received 0.01 ppm of Clothianidin-treated diet, while another group of larvae (control) received a clean diet. To prepare 100 g of Clothianidin-treated diet, 5 mg of Clothianidin were dissolved into 500 μL of acetone (solution A); then, 100 μL of solution A were diluted in 9900 μL of acetone (solution B); finally, 10 μL of solution B were dissolved in 990 μL of deionised water, which was used for the preparation of the diet.
    After preparing the diet, 3–4 combs containing larvae of different ages were selected from the experimental apiary of the University of Udine, Italy. Fourth instar larvae (L4) were manually collected and transferred into sterile Petri dishes (Ø = 9 cm) containing 15 g of clean or Clothianidin-treated diet. Each Petri dish hosted 15–20 L4, for a total of 80–100 L4 per treatment per replication. Larvae were maintained in Petri dishes for 24 h under controlled conditions (35 °C, 90% R.H., dark).
    Mites were collected from brood cells capped in the preceding 15 h. To this aim, in the afternoon of the day preceding the experiment, when the artificial feeding of larvae was carried out, the capped brood cells of several combs were marked. The following morning, the combs were transferred to the lab and the unmarked cells, that had been capped overnight, were manually unsealed. The combs were then placed in an incubator at 35 °C and 75% R.H., where larvae and mites spontaneously emerged.
    In the meantime, the larvae fed with Clothianidin (or not) that had reached the 5th instar (L5) were cleaned from the larval food and transferred into gelatin capsules (Agar Scientific ltd., Ø = 6.5 mm) with 1 mite38. Infested bees were maintained in a climatic chamber under controlled conditions (35 °C, 75% R.H.) for 12 days until eclosion. From 58 to 77 L5 per experimental group per replicate were infested, for a total of 204 and 210 individuals per experimental group.
    Daily, dead larvae were removed and counted. Upon eclosion, mite mortality and reproduction (i.e. fertility and fecundity) were measured by inspecting, in total, 111 and 120 mite infested honey bees fed or not with Clothianidin during the larval stage, respectively. Once separated from the infesting mite, 28 and 27 newly emerged adult bees in total, fed or not with Clothianidin during the larval stage, respectively, were stored at –80 °C for subsequent analysis aiming at assessing DWV load. The experiment was replicated 3 times.
    Modeling of Varroa population as affected by Clothianidin
    In order to test whether the effect of Clothianidin on Varroa reproduction could account for the higher mite infestation observed in colonies exposed to Clothianidin, under field conditions, we compared the data resulting from a simplified discrete time model of Varroa population with those obtained from the literature13.
    At each time point, our simplified discrete time model calculates Varroa population as follows:

    Varroa mites =Varroa mites + Varroa born − Varroa dead

    Varroa born = (Varroa mites*proportion of mites in brood cells*proportion of mites producing viable offspring)/length of reproducing phase

    Varroa dead = (Varroa mites*proportion of mites in brood cells*mortality of mites in brood cells + Varroa mites*(1 − proportion of mites in brood cells)*mortality of phoretic mites)/length of reproducing phase

    Parameters were derived from published studies20,39, as detailed in the Supplementary Data File. The proportion of treated mites producing viable offspring was calculated according to the results of our experiment (i.e., proportion of treated mites producing viable offspring = proportion of control mites producing viable offspring +23%). Since, the model allowed to estimate the size of Varroa population in treated and control colonies, whereas field studies reported the number of mites on bottom boards13, these latter data were converted into colony infestation according to a standard coefficient derived from literature40.
    The model above was used to follow the number of mites in two experimental groups (treated and control) for the duration of the field experiment that was used as a reference. More details can be found in the Supplementary Data file.
    Statistical analysis
    The statistical tests that were used to assess significance and the relevant data are reported along the corresponding results in the Supplementary Data file. Briefly, data about melanization, encapsulation, clotting, DWV infection level, and gene expression were analyzed by means of non-parametric methods (i.e., Mann–Whitney U tests in case of two samples and Kruskal–Wallis for more), the proportion of reproducing mites in different experimental groups was tested using the Mantel–Haenszel test, clotting in adult bees exposed to different doses of Clothianidin was tested with Spearman’s correlation. If necessary, probabilities were adjusted using the Bonferroni correction. Tests were performed with Excel (version 14.3.5).
    Reporting summary
    Further information on research design is available in the Nature Research Reporting Summary linked to this article. More

  • in

    Correction: A new strategy for membrane-based direct air capture

    Affiliations

    International Institute for Carbon-Neutral Energy Research (WPI-I2CNER), Kyushu University, 744 Motooka, Nishi-ku, Fukuoka, 819-0395, Japan
    Shigenori Fujikawa, Roman Selyanchyn & Toyoki Kunitake

    NanoMembrane Technologies, Inc., 4-1, Kyudai-Shimachi, Nishi-Ku, Fukuoka, 819-0388, Japan
    Shigenori Fujikawa & Toyoki Kunitake

    Department of Chemistry and Biochemistry, Center for Molecular Systems (CMS), Kyushu University, 744 Motooka, Nishiku, Fukuoka, 819-0395, Japan
    Shigenori Fujikawa

    Authors
    Shigenori Fujikawa

    Roman Selyanchyn

    Toyoki Kunitake

    Corresponding author
    Correspondence to Shigenori Fujikawa. More

  • in

    Morphological differentiation across the invasive range in Senecio madagascariensis populations

    1.
    Aïnouche, M. L. et al. Hybridization, polyploidy and invasion: lessons from Spartina (Poaceae). Biol. Invasions 11, 1159–1173 (2009).
    Article  Google Scholar 
    2.
    Hulme, P. E. Trade, transport and trouble: managing invasive species pathways in an era of globalization. J. Appl. Ecol. 46, 10–18 (2009).
    Article  Google Scholar 

    3.
    Baker, H. G. Characteristics and modes of origin of weeds. In The Genetics of Colonizing Species (eds Baker, H. G. & Stebbins, G. L.) 147–168 (Academic Press, New York, 1965).
    Google Scholar 

    4.
    Beest, M. et al. The more the better? The role of polyploidy in facilitating plant invasions. Ann. Bot. 109, 19–45 (2011).
    Article  Google Scholar 

    5.
    Pastorino, M. J., Ghirardi, S., Grosfeld, J., Gallo, L. A. & Puntieri, J. G. Genetic variation in architectural seedling traits of Patagonian cypress natural populations from the extremes of a precipitation range. Ann. For. Sci. 67, 508–508 (2010).
    Article  Google Scholar 

    6.
    Schäfer, M. A. et al. Geographic clines in wing morphology relate to colonization history in New World but not Old World populations of yellow dung flies. Evolution 72, 1629–1644 (2018).
    Article  Google Scholar 

    7.
    Mal, T. K. & Lovett Doust, J. Phenotypic plasticity in vegetative and reproductive traits in an invasive weed, Lythrum salicaria (Lythraceae), in response to soil moisture. Am. J. Bot. 92, 819–825 (2005).
    Article  Google Scholar 

    8.
    Yücedağ, C. & Gailing, O. Morphological and genetic variation within and among four Quercus petraea and Q. robur natural populations. Turk. J. Bot. 37, 619–629 (2013).
    Google Scholar 

    9.
    Kawecki, T. J. & Ebert, D. Conceptual issues in local adaptation. Ecol. Lett. 7, 1225–1241 (2004).
    Article  Google Scholar 

    10.
    Endler, J. A. Natural Selection in the Wild (Princeton University Press, Princeton, 1986).
    Google Scholar 

    11.
    Slatkin, M. Gene flow and the geographic structure of natural populations. Science 236, 787–792 (1987).
    ADS  CAS  Article  Google Scholar 

    12.
    Lenormand, T. Gene flow and the limits to natural selection. Trends Ecol. Evol. 17, 183–189 (2002).
    Article  Google Scholar 

    13.
    Coulleri, J. P. Gene flow and local adaptation: antagonistic forces shape populations of Ilex dumosa (Aquifoliaceae). Bol. Soc. Argent. Bot. 45, 333–342 (2010).
    Google Scholar 

    14.
    Wright, S. Modes of selection. Am. Nat. 90, 5–24 (1956).
    Article  Google Scholar 

    15.
    Sindel, B. M. & Michael, P. W. Seedling emergence and longevity of Senecio madagascariensis Poir. (fireweed) in coastal south-eastern Australia. Plant Prot. Q. 11, 14–19 (1996).
    Google Scholar 

    16.
    Tsutsumi, M. Current and potential distribution of Senecio madagascariensis Poir. (fireweed), an invasive alien plant in Japan. Grassl. Sci. 57, 150–157 (2011).
    Article  Google Scholar 

    17.
    Cabrera, A. L. Compuestas Bonaerenses. Rev. Mus. La Plata 4, 313–315 (1941).
    Google Scholar 

    18.
    Matzenbacher, N. I. & Schneider, A. A. Nota sobre a presença de uma espécie adventícia de Senecio (Asteraceae) no Rio Grande do Sul Brasil. Rev. Brasil. Bioci. 3896, 111–115 (2008).
    Google Scholar 

    19.
    Le Roux, J. J., Wieczorek, A. M., Tran, C. T. & Vorsino, A. E. Disentangling the dynamics of invasive fireweed (Senecio madagascariensis Poir. species complex) in the Hawaiian Islands. Biol. Invasions 12, 2251–2264 (2010).
    Article  Google Scholar 

    20.
    Dematteis, B., Ferrucci, M. S. & Coulleri, J. P. The evolution of dispersal traits based on diaspore features in South American populations of Senecio madagascariensis (Asteraceae). Aust. J. Bot. 67, 358–366 (2019).
    Article  Google Scholar 

    21.
    Ellstrand, N. C. & Schierenbeck, K. A. Hybridization as a stimulus for the evolution of invasiveness in plants?. Proc. Natl. Acad. Sci. 97, 7043–7050 (2000).
    ADS  CAS  Article  Google Scholar 

    22.
    Lee, C. E. Evolutionary genetics of invasive species. Trends Ecol. Evol. 17, 386–391 (2002).
    Article  Google Scholar 

    23.
    Parker, J. D. et al. Do invasive species perform better in their new ranges?. Ecology 94, 985–994 (2013).
    Article  Google Scholar 

    24.
    Rejmánek, M. & Richardson, D. M. What attributes make some plant species more invasive?. Ecology 77, 1655–1661 (1996).
    Article  Google Scholar 

    25.
    Parkhust, D. F. & Loucks, O. L. Optimal life size in relation to environment. J. Ecol. 60, 505–537 (1972).
    Article  Google Scholar 

    26.
    Monty, A. & Mahy, G. Clinal differentiation during invasion: Senecio inaequidens (Asteraceae) along altitudinal gradients in Europe. Oecologia 159, 305–315 (2009).
    ADS  Article  Google Scholar 

    27.
    Kramer, P. J. & Kozlowski, T. T. Physiology of Trees (OUP, Oxford, 1960).
    Google Scholar 

    28.
    Lavergne, S. & Molofsky, J. Increased genetic variation and evolutionary potential drive the success of an invasive grass. Proc. Natl. Acad. Sci. 104, 3883–3888 (2007).
    ADS  CAS  Article  Google Scholar 

    29.
    Walker, L. R., Lodge, S. J., Guzmán-Grajales, S. M. & Fetcher, N. Species specific seedling responses to hurricane disturbance in a Puerto Rican rain forest. Biotropica 35, 472–485 (2003).
    Article  Google Scholar 

    30.
    Durka, W., Bossdorf, O., Prati, D. & Auge, H. Molecular evidence for multiple introductions of garlic mustard (Alliaria petiolata, Brassicaceae) to North America. Mol. Ecol. 14, 1697–1706 (2005).
    Article  Google Scholar 

    31.
    Mäder, G., Castro, L., Bonnato, S. L. & Freitas, L. B. Multiple introductions and gene flow in subtropical South American populations of the fireweed, Senecio madagascariensis (Asteraceae). Genet. Mol. Biol. 39, 135–144 (2016).
    Article  Google Scholar 

    32.
    Di Rienzo, J. A. et al. InfoStat version. Grupo InfoStat, FCA, Universidad Nacional de Córdoba, Argentina. https://www.infostat.com.ar. (2016).

    33.
    Team, R. RStudio: Integrated Development for R. Boston: RStudio, Inc. https://www.Rstudio.com (2015). More

  • in

    Water warming increases aggression in a tropical fish

    1.
    Sih, A., Ferrari, M. C. O. & Harris, D. J. Evolution and behavioural responses to human-induced rapid environmental change. Evol. Appl. 4, 367–387. https://doi.org/10.1111/j.1752-4571.2010.00166.x (2011).
    Article  PubMed  PubMed Central  Google Scholar 
    2.
    Sih, A. Effects of early stress on behavioral syndromes: an integrated adaptive perspective. Neurosci. Biobehav. Rev. 35, 1452–1465. https://doi.org/10.1016/j.neubiorev.2011.03.015 (2011).
    Article  PubMed  Google Scholar 

    3.
    Franks, S. J., Weber, J. J. & Aitken, S. N. Evolutionary and plastic responses to climate change in terrestrial plant populations. Evol. Appl. 7, 123–139. https://doi.org/10.1111/eva.12112 (2014).
    Article  PubMed  Google Scholar 

    4.
    Parmesan, C. Ecological and evolutionary responses to recent climate change. Annu. Rev. Ecol. Evol. Syst. 37, 637–669. https://doi.org/10.1146/annurev.ecolsys.37.091305.110100 (2006).
    Article  Google Scholar 

    5.
    Mulholland, P. J. et al. Effects of climate change on freshwater ecosystems of the south-eastern United States and the Gulf Coast of Mexico. Hydrol. Process. 11, 949–970. https://doi.org/10.1002/(SICI)1099-1085(19970630)11:83.0.CO;2-G (1997).

    6.
    Justić, D., Rabalais, N. N. & Turner, R. E. Coupling between climate variability and coastal eutrophication: evidence and outlook for the northern Gulf of Mexico. J. Sea Res. 54, 25–35. https://doi.org/10.1016/j.seares.2005.02.008 (2005).
    ADS  Article  Google Scholar 

    7.
    Sokolova, I. M. & Lannig, G. Interactive effects of metal pollution and temperature on metabolism in aquatic ectotherms: implications of global climate change. Clim. Res. 37, 181–201. https://doi.org/10.3354/cr00764 (2008).
    Article  Google Scholar 

    8.
    Bradshaw, W. E. & Holzapfel, C. M. Evolutionary response to rapid climate change. Am. Assoc. Adv. Sci. 312, 1477–1478 (2006).
    CAS  Google Scholar 

    9.
    Ghalambor, C. K., Huey, R. B., Martin, P. R., Tewksbury, J. J. & Wang, G. Are mountain passes higher in the tropics? Janzen’s hypothesis revisited. Integr. Comp. Biol. 46, 5–17. https://doi.org/10.1093/icb/icj003 (2006).

    10.
    Huang, S. L., Hao, Y., Mei, Z., Turvey, S. T. & Wang, D. Common pattern of population decline for freshwater cetacean species in deteriorating habitats. Freshw. Biol. 57, 1266–1276. https://doi.org/10.1111/j.1365-2427.2012.02772.x (2012).
    Article  Google Scholar 

    11.
    Matteson, S. W., Mossman, M. J. & Shealer, D. A. Population decline of black terns in Wisconsin: a 30-year perspective. Waterbirds 35, 185–193. https://doi.org/10.1675/063.035.0201 (2012).
    Article  Google Scholar 

    12.
    Blaustein, A. R. & Bancroft, B. A. Amphibian population declines: evolutionary considerations. Bioscience 57, 437–444. https://doi.org/10.1641/B570517 (2007).
    Article  Google Scholar 

    13.
    Taylor, B. M., Houk, P., Russ, G. R. & Choat, J. H. Life histories predict vulnerability to overexploitation in parrotfishes. Coral Reefs 33, 869–878. https://doi.org/10.1111/j.1752-4571.2010.00166.x0 (2014).
    ADS  Article  Google Scholar 

    14.
    Trzcinski, M. K., Mohn, R. & Bowen, W. K. Continued decline of an Atlantic cod population: how important is gray seal predation?. Ecol. Appl. 16, 2276–2292. https://doi.org/10.1111/j.1752-4571.2010.00166.x1 (2006).
    Article  PubMed  Google Scholar 

    15.
    Kovach, R. P. et al. Climate, invasive species and land use drive population dynamics of a cold-water specialist. J. Appl. Ecol. 54, 638–647. https://doi.org/10.1111/j.1752-4571.2010.00166.x2 (2017).
    Article  Google Scholar 

    16.
    Greenlees, M. J., Phillips, B. L. & Shine, R. An invasive species imposes selection on life-history traits of a native frog. Biol. J. Linn. Soc. 100, 329–336. https://doi.org/10.1111/j.1752-4571.2010.00166.x3 (2010).
    Article  Google Scholar 

    17.
    Deutsch, C. A. et al. Impacts of climate warming on terrestrial ectotherms across latitude. Proc. Natl. Acad. Sci. 105, 6668–6672. https://doi.org/10.1111/j.1752-4571.2010.00166.x4 (2008) (arXiv:1408.1149.).
    ADS  Article  PubMed  Google Scholar 

    18.
    Huey, R. B. et al. Predicting organismal vulnerability to climate warming: roles of behaviour, physiology and adaptation. Phil. Trans. R. Soc. B Biol. Sci. 367, 1665–1679. https://doi.org/10.1111/j.1752-4571.2010.00166.x5 (2012).
    Article  Google Scholar 

    19.
    Somero, G. N. The physiology of climate change: how potentials for acclimatization and genetic adaptation will determine ‘winners’ and ‘losers’. J. Exp. Biol. 213, 912–920. https://doi.org/10.1242/jeb.037473 (2010).

    20.
    Hoffman, A. A., Hallas, R. J., Dean, J. A. & Schiffer, M. Low potential for climatic stress adaptation in a rainforest Drosophila species. Science 301, 100–102 (2003).
    ADS  Article  Google Scholar 

    21.
    Martinez, E., Porreca, A. P., Colombo, R. E. & Menze, M. A. Tradeoffs of warm adaptation in aquatic ectotherms: live fast, die young?. Comp. Biochem. Physiol. Part A Mol. Integr. Physiol. 191, 209–215. https://doi.org/10.1111/j.1752-4571.2010.00166.x6 (2016).
    CAS  Article  Google Scholar 

    22.
    Payne, N. L. et al. Temperature dependence of fish performance in the wild: links with species biogeography and physiological thermal tolerance. Funct. Ecol. 30, 903–912. https://doi.org/10.1111/j.1752-4571.2010.00166.x7 (2016).
    Article  Google Scholar 

    23.
    Walsh, S. J., Haney, D. C. & Timmerman, C. M. Variation in thermal tolerance and routine metabolism among spring- and stream-dwelling freshwater sculpins (Teleostei: Cottidae) of the southeastern United States. Ecol. Freshw. Fish 6, 84–94. https://doi.org/10.1111/j.1752-4571.2010.00166.x8 (1997).
    Article  Google Scholar 

    24.
    Strange, K. T., Vokoun, J. C. & Noltie, D. B. Thermal tolerance and growth differences in orangethroat darter (Etheostoma spectabile) from thermally contrasting adjoining streams. Am. Midl. Nat. 148, 120–128. https://doi.org/10.1111/j.1752-4571.2010.00166.x9 (2002).
    Article  Google Scholar 

    25.
    Lemoine, N. P. & Burkepile, D. E. Temperature-induced mismatches between consumption and metabolism reduce consumer fitness. Ecology 93, 2483–2489 (2012).
    Article  Google Scholar 

    26.
    Rall, B. Ö. C., Vucic-Pestic, O., Ehnes, R. B., EmmersoN, M. & Brose, U. Temperature, predator–prey interaction strength and population stability. Glob. Change Biol. 16, 2145–2157. https://doi.org/10.1016/j.neubiorev.2011.03.0150 (2010).
    ADS  Article  Google Scholar 

    27.
    Brodnik, R. M. Impacts of Water Warming on the Physiology and Life-History of a Tropical Freshwater Fish. Master’s thesis, The Ohio State University (2015).

    28.
    O’Reilly, C. M., Alin, S. R., Plisnier, P.-D., Cohen, A. S. & McKee, B. A. Climate change decreases aquatic ecosystem productivity of Lake Tanganika. Afr. Nat. 424, 766–768 (2003).

    29.
    Stenuite, S. et al. Phytoplankton production and growth rate in Lake Tanganyika: evidence of a decline in primary productivity in recent decades. Freshw. Biol. 52, 2226–2239. https://doi.org/10.1016/j.neubiorev.2011.03.0151 (2007).
    CAS  Article  Google Scholar 

    30.
    Verburg, P. & Hecky, R. E. The physics of the warming of Lake Tanganyika by climate change. Limnol. Oceanogr. 54, 2418–2430. https://doi.org/10.1016/j.neubiorev.2011.03.0152 (2009).
    ADS  Article  Google Scholar 

    31.
    Moritz, C. & Agudo, R. The future of species under climate change: resilience or decline?. Science 341, 504–508. https://doi.org/10.1016/j.neubiorev.2011.03.0153 (2013).
    ADS  CAS  Article  PubMed  Google Scholar 

    32.
    Fournier-Level, A. et al. A map of local adaptation in Arabidopsis thaliana. Science 334, 86–89. https://doi.org/10.1016/j.neubiorev.2011.03.0154 (2011).
    ADS  CAS  Article  PubMed  Google Scholar 

    33.
    Biro, P. A., Beckmann, C. & Stamps, J. A. Small within-day increases in temperature affects boldness and alters personality in coral reef fish. Proc. R. Soc. Biol. 277, 71–77 (2010).
    Article  Google Scholar 

    34.
    Kochhann, D., Campos, D. F. & Val, A. L. Experimentally increased temperature and hypoxia affect stability of social hierarchy and metabolism of the Amazonian cichlid Apistogramma agassizii. Comp. Biochem. Physiol. Part A Mol. Integr. Physiol. 190, 54–60. https://doi.org/10.1016/j.neubiorev.2011.03.0155 (2015).
    CAS  Article  Google Scholar 

    35.
    Ratnasabapathi, D., Burns, J. & Souchek, R. Effects of temperature and prior residence on territorial aggression in the convict cichlid Cichlasoma nigrofasciatum. Aggress. Behav. 18, 365–372. https://doi.org/10.1002/1098-2337(1992)18:53.0.CO;2-E (1992).

    36.
    Careau, V. & Garland, T. Jr. Performance, personality, and energetics: correlation, causation, and mechanism. Physiol. Biochem. Zool. 85, 543–571 (2012).
    Article  Google Scholar 

    37.
    Biro, P. A. & Stamps, J. A. Do consistent individual differences in metabolic rate promote consistent individual differences in behavior?. Trends Ecol. Evol. 25, 653–659. https://doi.org/10.1016/j.neubiorev.2011.03.0156 (2010).
    Article  PubMed  Google Scholar 

    38.
    Magurran, A. E. & Seghers, B. H. Variation in schooling and aggression amongst guppy (Poecilia reticulata) populations in Trinidad. Behaviour 118, 214–234 (1991).
    Article  Google Scholar 

    39.
    Kieffer, J. D., Kubacki, M. R., Phelan, F. J., Philipp, D. P. & Tufts, B. L. The effect of catch-and-release angling on the parental care behavior of male smallmouth bass. Trans. Am. Fish. Soc. 124, 70–76. https://doi.org/10.1577/1548-8659(1995)124 More