More stories

  • in

    Iterative evolution of large-bodied hypercarnivory in canids benefits species but not clades

    1.
    Ripple, W. J. et al. Status and ecological effects of the world’s largest carnivores. Science 343, 1–11 (2014).
    Google Scholar 
    2.
    Kruuk, H. The Spotted Hyena: A Study of Predation and Social Behavior (University of Chicago Press, 1972).

    3.
    Carbone, C., Mace, G. M., Roberts, S. C. & Macdonald, D. W. Energetic constraints on the diet of terrestrial carnivores. Nature 402, 286–288 (1999).
    CAS  PubMed  Google Scholar 

    4.
    Carbone, C., Teacher, A. & Rowcliffe, J. M. The costs of carnivory. PLoS Biol. 5, 363–368 (2007).
    CAS  Google Scholar 

    5.
    Van Valkenburgh, B. Deja vu: the evolution of feeding morphologies in the Carnivora. Integr. Comp. Biol. 47, 147–163 (2007).
    PubMed  Google Scholar 

    6.
    MacArthur, R. H. & Pianka, E. R. On optimal use of a patchy environment. Am. Nat. 100, 603–609 (1966).
    Google Scholar 

    7.
    Andersson, M. On optimal predator search. Theor. Popul. Biol. 19, 58–86 (1981).
    Google Scholar 

    8.
    Mukherjee, S. & Heithaus, M. R. Dangerous prey and daring predators: a review. Biol. Rev. 88, 550–563 (2013).
    PubMed  Google Scholar 

    9.
    Brown, C., Balisi, M., Shaw, C. A. & Van Valkenburgh, B. Skeletal trauma reflects hunting behaviour in extinct sabre-tooth cats and dire wolves. Nat. Ecol. Evol. 1, 1–7 (2017).
    Google Scholar 

    10.
    Griffiths, D. Foraging costs and relative prey size. Am. Nat. 116, 743–752 (1980).
    Google Scholar 

    11.
    Fryxell, J. M., Mosser, A., Sinclair, A. R. E. & Packer, C. Group formation stabilizes predator–prey dynamics. Nature 449, 1041–1044 (2007).
    CAS  PubMed  Google Scholar 

    12.
    Binder, W. J., Thompson, E. N. & Van Valkenburgh, B. Temporal variation in tooth fracture among Rancho La Brea dire wolves. J. Vertebr. Paleontol. 22, 423–428 (2002).
    Google Scholar 

    13.
    Binder, W. J. & Van Valkenburgh, B. A comparison of tooth wear and breakage in Rancho La Brea sabertooth cats and dire wolves across time. J. Vertebr. Paleontol. 30, 255–261 (2010).
    Google Scholar 

    14.
    Van Valkenburgh, B. & Hertel, F. Tough times at La Brea: tooth breakage in large carnivores of the late Pleistocene. Science 261, 456–459 (1993).
    Google Scholar 

    15.
    Holekamp, K. E., Smale, L., Berg, R. & Cooper, S. M. Hunting rates and hunting success in the spotted hyena (Crocuta crocuta). J. Zool. 242, 1–15 (1997).
    Google Scholar 

    16.
    Stander, P. E. Cooperative hunting in lions: the role of the individual. Behav. Ecol. Sociobiol. 29, 445–454 (1992).
    Google Scholar 

    17.
    Holliday, J. A. & Steppan, S. J. Evolution of hypercarnivory: the effect of specialization on morphological and taxonomic diversity. Paleobiology 30, 108–128 (2004).
    Google Scholar 

    18.
    Milton, K. The critical role played by animal source foods in human (Homo) evolution. J. Nutr. 133, 3886–3892 (2003).
    Google Scholar 

    19.
    Mealey, S. P. The natural food habits of grizzly bears in Yellowstone National Park, 1973-74. Bears Their Biol. Manag. 4, 281–292 (1980).
    Google Scholar 

    20.
    McNab, B. K. Food habits, energetics, and the population biology of mammals. Am. Nat. 116, 106–124 (1980).
    Google Scholar 

    21.
    Munoz-Garcia, A. & Williams, J. B. Basal metabolic rate in carnivores is associated with diet after controlling for phylogeny. Physiol. Biochem. Zool. 78, 1039–1056 (2005).
    PubMed  Google Scholar 

    22.
    Hoekstra, H. E. & Fagan, W. F. Body size, dispersal ability, and compositional disharmony: the carnivore-dominated fauna of the Kuril Islands. Divers. Distrib. 4, 135–149 (1998).
    Google Scholar 

    23.
    Van Valkenburgh, B. Iterative evolution of hypercarnivory in canids (Mammalia: Carnivora): evolutionary interactions among sympatric predators. Paleobiology 17, 340–362 (1991).
    Google Scholar 

    24.
    Wang, X. Phylogenetic Systematics of the Hesperocyoninae (Carnivora, Canidae). Bulletin of the American Museum of Natural History (American Museum of Natural History, 1994).

    25.
    Wang, X., Tedford, R. H. & Taylor, B. E. Phylogenetic Systematics of the Borophaginae (Carnivora, Canidae). Bulletin of the American Museum of Natural History (American Museum of Natural History, 1999).

    26.
    Tedford, R. H., Wang, X. & Taylor, B. E. Phylogenetic Systematics of the North American fossil Caninae (Carnivora: Canidae). Bulletin of the American Museum of Natural History, Vol. 325 (American Museum of Natural History, 2009).

    27.
    Balisi, M., Casey, C. & Van Valkenburgh, B. Dietary specialization is linked to reduced species durations in North American fossil canids. R. Soc. Open Sci. 5, 1–15 (2018).
    Google Scholar 

    28.
    Van Valkenburgh, B. Major patterns in the history of carnivorous mammals. Annu. Rev. Earth Planet. Sci. 27, 463–493 (1999).
    Google Scholar 

    29.
    Figueirido, B., Martín-Serra, A., Tseng, Z. J. & Janis, C. M. Habitat changes and changing predatory habits in North American fossil canids. Nat. Commun. 6, 1–11 (2015).
    Google Scholar 

    30.
    Silvestro, D., Antonelli, A. A., Salamin, N. & Quental, T. B. The role of clade competition in the diversification of North American canids. Proc. Natl Acad. Sci. USA 112, 8684–8689 (2015).
    CAS  PubMed  Google Scholar 

    31.
    Van Valkenburgh, B., Wang, X. & Damuth, J. Cope’s rule, hypercarnivory, and extinction in North American canids. Science 306, 101–104 (2004).
    PubMed  Google Scholar 

    32.
    Rasmussen, G. S. A., Gusset, M., Courchamp, F. & Macdonald, D. W. Achilles’ heel of sociality revealed by energetic poverty trap in cursorial hunters. Am. Nat. 172, 508–518 (2008).
    PubMed  Google Scholar 

    33.
    Raia, P. et al. Progress to extinction: increased specialisation causes the demise of animal clades. Sci. Rep. 6, 30965 (2016).
    CAS  PubMed  PubMed Central  Google Scholar 

    34.
    Van Valkenburgh, B. Extinction and replacement among predatory mammals in the North American late Eocene and Oligocene: tracking a paleoguild over 12 million years. Hist. Biol. 8, 129–150 (1994).

    35.
    Vermeij, G. J. Biological versatility and earth history. Proc. Natl Acad. Sci. U. S. A. 70, 1936–1938 (1973).
    CAS  PubMed  PubMed Central  Google Scholar 

    36.
    Piras, P. et al. Evolution of the sabertooth mandible: a deadly ecomorphological specialization. Palaeogeogr. Palaeoclimatol. Palaeoecol. 0–1, https://doi.org/10.1016/j.palaeo.2018.01.034 (2018).

    37.
    Palmqvist, P., Martinez-Navarro, B. & Arribas, A. Prey selection by terrestrial carnivores in a lower Pleistocene paleocommunity. Paleobiology 22, 514–534 (1996).
    Google Scholar 

    38.
    Stock, C. Rancho La Brea: A Record of Pleistocene life in California (Natural History Museum of Los Angeles County, 1992).

    39.
    Van Valkenburgh, B., Sacco, T. & Wang, X. Pack hunting in Miocene borophagine dogs: evidence from craniodental morphology and body size. in Bulletin of the American Museum of Natural History 147–162, (American Museum of Natural History, 2003). https://doi.org/10.1206/0003-0090(2003)2792.0.CO;2.

    40.
    Van Valkenburgh, B. & Sacco, T. Sexual dimorphism, social behavior, and intrasexual competition in large Pleistocene carnivorans. J. Vertebr. Paleontol. 22, 164–169 (2002).
    Google Scholar 

    41.
    Carbone, C. et al. Parallels between playbacks and Pleistocene tar seeps suggest sociality in an extinct sabretooth cat, Smilodon. Biol. Lett. 5, 81–85 (2009).
    PubMed  Google Scholar 

    42.
    Van Valkenburgh, B. et al. Sociality in Rancho La Brea Smilodon: arguments favour ‘evidence’ over ‘coincidence’. Biol. Lett. 5, 563–564 (2009).
    PubMed Central  Google Scholar 

    43.
    Creel, S. & Creel, N. M. The African Wild Dog: Behaviour, Ecology and Conservation (Princeton University Press, 2002).

    44.
    Sinclair, A. R. E. & Krebs, C. J. Complex numerical responses to top-down and bottom-up processes in vertebrate populations. Philos. Trans. R. Soc. B Biol. Sci. 357, 1221–1231 (2002).
    CAS  Google Scholar 

    45.
    Rosenzweig, M. L. Net primary productivity of terrestrial communities: prediction from climatological data. Am. Nat. 102, 67–74 (1968).
    Google Scholar 

    46.
    Barnosky, A. D. Distinguishing the effects of the Red Queen and Court Jester on Miocene mammal evolution in the northern Rocky Mountains. J. Vertebr. Paleontol. 21, 172–185 (2001).
    Google Scholar 

    47.
    Smiley, T. M., Hyland, E. G., Cotton, J. M. & Reynolds, R. E. Evidence of early C4 grasses, habitat heterogeneity, and faunal response during the Miocene Climatic Optimum in the Mojave Region. Palaeogeogr. Palaeoclimatol. Palaeoecol. 490, 415–430 (2018).
    Google Scholar 

    48.
    Kohn, M. J. & Fremd, T. J. Miocene tectonics and climate forcing of biodiversity, western United States. Geology 36, 783–786 (2008).
    CAS  Google Scholar 

    49.
    Finarelli, J. A. & Badgley, C. Diversity dynamics of Miocene mammals in relation to the history of tectonism and climate. Proc. R. Soc. B 277, 2721–2726 (2010).
    PubMed  Google Scholar 

    50.
    Payne, J. L., Bush, A. M., Heim, N. A., Knope, M. L. & McCauley, D. J. Ecological selectivity of the emerging mass extinction in the oceans. Science 353, 1284–1286 (2016).
    CAS  PubMed  Google Scholar 

    51.
    Smith, F. A., Smith, R. E. E., Lyons, S. K. & Payne, J. L. Body size downgrading of mammals over the late Quaternary. Science 313, 310–313 (2018).
    Google Scholar 

    52.
    Faurby, S., Silvestro, D., Werdelin, L. & Antonelli, A. A. Brain expansion in early hominins predicts carnivore extinctions in East Africa. Ecol. Lett. https://doi.org/10.1111/ele.13451 (2020).

    53.
    Estes, J. A. et al. Trophic downgrading of planet Earth. Science 333, 301–306 (2011).
    CAS  PubMed  Google Scholar 

    54.
    Wang, X. New material of Osbornodon from the Early Hemingfordian of Nebraska and Florida. in Vertebrate Fossils and Their Context: Contributions in Honor of Richard H.Tedford (ed. Flynn, L. J.) 163–176 (American Museum of Natural History, 2003).

    55.
    Van Valkenburgh, B. Skeletal and dental predictors of body mass in carnivores. in Body Size in Mammalian Paleobiology: Estimation and Biological Implications (eds Damuth, J. & MacFadden, B. J.) 181–206 (Cambridge University Press, 1990).

    56.
    Wang, X. et al. First bone-cracking dog coprolites provide new insight into bone consumption in Borophagus and their unique ecological niche. eLife 7, 1–28 (2018).
    Google Scholar 

    57.
    Van Valkenburgh, B. & Koepfli, K. P. Cranial and dental adaptations to predation in canids. Mamm. Predat. Ser. Symp. Zool. Soc. 65, 15–37 (1993).
    Google Scholar 

    58.
    Slater, G. J. Iterative adaptive radiations of fossil canids show no evidence for diversity-dependent trait evolution. Proc. Natl Acad. Sci. USA 112, 4897–4902 (2015).

    59.
    Carrasco, M. A., Kraatz, B. P., Davis, E. B. & Barnosky, A. D. Miocene Mammal Mapping Project (MIOMAP). http://www.ucmp.berkeley.edu/miomap/ (University of California Museum of Paleontology, 2005).

    60.
    Graham, R. W. & Lundelius, E. L. Jr. FAUNMAP II: New data for North America with a temporal extension for the Blancan, Irvingtonian and early Rancholabrean. FAUNMAP II Database http://ucmp.berkeley.edu/faunmap/ (2010).

    61.
    Bambach, R. K., Knoll, A. H. & Wang, S. C. Origination, extinction, and mass depletions of marine diversity. Paleobiology 30, 522–542 (2004).
    Google Scholar 

    62.
    Woodburne, M. O. (ed.) Late Cretaceous and Cenozoic Mammals of North America: Biostratigraphy and Geochronology. (Columbia University Press, 2004). https://doi.org/10.7312/wood13040.

    63.
    Ellis, A. R., Burchett, W. W., Harrar, S. W. & Bathke, A. C. Nonparametric inference for multivariate data: the R package npmv. J. Stat. Softw. 76, 1–18 (2017).

    64.
    Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B 57, 289–300 (1995).
    Google Scholar 

    65.
    McDonald, J. H. Handbook of Biological Statistics (Sparky House Publishing, 2014).

    66.
    Hunt, G. paleoTS: Analyze Paleontological Time-Series. R package version 0.5.2. https://CRAN.R-project.org/package=paleoTS (2019).

    67.
    Mazerolle, M. J. & Linden, D. AICcmodavg: Model selection and multimodel inference based on (Q)AIC(c). R package version 2.3-0. https://cran.r-project.org/package=AICcmodavg (2019).

    68.
    R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org (2019).

    69.
    Silvestro, D., Salamin, N. & Schnitzler, J. PyRate: a new program to estimate speciation and extinction rates from incomplete fossil data. Methods Ecol. Evol. 5, 1126–1131 (2014).
    Google Scholar 

    70.
    Rambaut, A. et al. Tracer. http://beast.community/tracer (2018).

    71.
    Zachos, J. C., Dickens, G. R. & Zeebe, R. E. An early Cenozoic perspective on greenhouse warming and carbon-cycle dynamics. Nature 451, 279–283 (2008).
    CAS  PubMed  Google Scholar 

    72.
    Balisi, M. & Van Valkenburgh, B. Iterative evolution of large-bodied hypercarnivory in canids benefits species but not clades. Dryad, https://doi.org/10.6071/M3M08P (2020). More

  • in

    Ecological uncertainty favours the diversification of host use in avian brood parasites

    1.
    Levins, R. Evolution in Changing Environments: Some Theoretical Explorations. (Princeton University Press, 1968).
    2.
    Clavel, J., Julliard, R. & Devictor, V. Worldwide decline of specialist species: toward a global functional homogenization? Front. Ecol. Environ. 9, 222–228 (2011).
    Google Scholar 

    3.
    Ducatez, S. Brood parasitism: a good strategy in our changing world? Proc. R. Soc. B: Biol. Sci. 281, 20132404 (2014).
    Google Scholar 

    4.
    Kawecki, T. J. & Ebert, D. Conceptual issues in local adaptation. Ecol. Lett. 7, 1225–1241 (2004).
    Google Scholar 

    5.
    Futuyma, D. J. & Moreno, G. The evolution of ecological specialisation. Annu. Rev. Ecol. Syst. 19, 207–233 (1988).
    Google Scholar 

    6.
    Abrams, P. A., Grover, J. P. & DeAngelis, E. D. L. The prerequisites for and likelihood of generalist‐specialist coexistence. Am. Naturalist 167, 329–342 (2006).
    Google Scholar 

    7.
    Bradshaw, W. E. & Holzapfel, C. M. Evolutionary response to rapid climate change. Science 312, 1477–1478 (2006).
    CAS  PubMed  Google Scholar 

    8.
    Skelly, D. K. et al. Evolutionary responses to climate change. Conserv. Biol. 21, 1353–1355 (2007).
    PubMed  Google Scholar 

    9.
    Norberg, J., Urban, M. C., Vellend, M., Klausmeier, C. A. & Loeuille, N. Eco-evolutionary responses of biodiversity to climate change. Nat. Clim. Change 2, 747–751 (2012).
    Google Scholar 

    10.
    Diffenbaugh, N. S. & Field, C. B. Changes in ecologically critical terrestrial climate conditions. Science 341, 486–492 (2013).
    ADS  CAS  PubMed  Google Scholar 

    11.
    Dunn, R. R., Harris, N. C., Colwell, R. K., Koh, L. P. & Sodhi, N. S. The sixth mass coextinction: are most endangered species parasites and mutualists? Proc. R. Soc. B: Biol. Sci. 276, 3037–3045 (2009).
    Google Scholar 

    12.
    Davies, N. B. Cuckoos, Cowbirds and Other Cheats. (T & A D Poyser, 2000). https://doi.org/10.5040/9781472597472?locatt=label:secondary_bloomsburyCollections.

    13.
    Stoddard, M. C. & Hauber, M. E. Colour, vision and coevolution in avian brood parasitism. Philos. Trans. R. Soc. B: Biol. Sci. 372, 20160339 (2017).
    Google Scholar 

    14.
    Thorogood, R., Spottiswoode, C. N., Portugal, S. J. & Gloag, R. The coevolutionary biology of brood parasitism: a call for integration. Philos. Trans. R. Soc. B: Biol. Sci. 374, 20180190 (2019).
    Google Scholar 

    15.
    Huelsenbeck, J. P., Nielsen, R. & Bollback, J. P. Stochastic mapping of morphological characters. Syst. Biol. 52, 131–158 (2003).
    PubMed  Google Scholar 

    16.
    Johnsgard, P. A. The Avian Brood Parasites: Deception at the Nest. (Oxford University Press, 1997).

    17.
    Soler, M. Avian Brood Parasitism: Behaviour, Ecology, Evolution and Coevolution. (Springer, Berlin Heidelberg, 2017). https://doi.org/10.1007/978-3-319-73138-4.

    18.
    Krüger, O. & Davies, N. B. The evolution of cuckoo parasitism: a comparative analysis. Proc. R. Soc. Lond. Ser. B: Biol. Sci. 269, 375–381 (2002).
    Google Scholar 

    19.
    Hauber, M. E. Interspecific brood parasitism and the evolution of host clutch sizes. Evol. Ecol. Res. 5, 559–570 (2003).
    Google Scholar 

    20.
    Kilner, R. M. The evolution of virulence in brood parasites. Ornithological Sci. 4, 55–64 (2005).
    Google Scholar 

    21.
    Feeney, W. E. et al. Brood parasitism and the evolution of cooperative breeding in birds. Science 342, 1506–1508 (2013).
    ADS  CAS  PubMed  Google Scholar 

    22.
    Medina, I., Langmore, N. E., Lanfear, R. & Kokko, H. The evolution of clutch size in hosts of avian brood parasites. Am. Naturalist 190, E112–E123 (2017).
    Google Scholar 

    23.
    Krüger, O., Sorenson, M. D. & Davies, N. B. Does coevolution promote species richness in parasitic cuckoos? Proc. R. Soc. B: Biol. Sci. 276, 3871–3879 (2009).
    Google Scholar 

    24.
    Krüger, O. & Kolss, M. Modelling the evolution of common cuckoo host-races: speciation or genetic swamping? J. Evolut. Biol. 26, 2447–2457 (2013).
    Google Scholar 

    25.
    Medina, I. & Langmore, N. E. The evolution of host specialisation in avian brood parasites. Ecol. Lett. 19, 1110–1118 (2016).
    PubMed  Google Scholar 

    26.
    Büchi, L. & Vuilleumier, S. Coexistence of specialist and generalist species is shaped by dispersal and environmental factors. Am. Naturalist 183, 612–624 (2014).
    Google Scholar 

    27.
    De Mársico, M. C., Mahler, B., Chomnalez, M., Di Giácomo, A. G. & Reboreda, J. C. Host Use by Generalist and Specialist Brood-Parasitic Cowbirds at Population and Individual Levels. In Advances in the Study of Behavior (ed. Macedo, R.) Ch. 3, Vol. 42, 83–121 (Academic Press, 2010), https://doi.org/10.1016/s0065-3454(10)42003-3.

    28.
    Hopper, K. R. Risk-spreading and bet-hedging in insect population biology. Annu. Rev. Entomol. 44, 535–560 (1999).
    CAS  PubMed  Google Scholar 

    29.
    Farnsworth, G. L. & Simons, T. R. How many baskets? Clutch sizes that maximize annual fecundity of multiple-brooded birds. Auk 118, 973–982 (2001).
    Google Scholar 

    30.
    Starrfelt, J. & Kokko, H. Bet‐hedging—a triple trade‐off between means, variances and correlations. Biol. Rev. 87, 742–755 (2012).
    PubMed  Google Scholar 

    31.
    Rubenstein, D. R. Spatiotemporal environmental variation, risk aversion, and the evolution of cooperative breeding as a bet-hedging strategy. Proc. Natl Acad. Sci. 108, 10816–10822 (2011).
    ADS  CAS  PubMed  Google Scholar 

    32.
    Moskát, C., Barta, Z., Hauber, M. E. & Honza, M. High synchrony of egg laying in common cuckoos (Cuculus canorus) and their great reed warbler (Acrocephalus arundinaceus) hosts. Ethol. Ecol. Evolution 18, 159–167 (2006).
    Google Scholar 

    33.
    Brooker, L. C. & Brooker, M. G. Why are cuckoos host specific? Oikos 57, 301–309 (1990).
    Google Scholar 

    34.
    Botero, C. A., Weissing, F. J., Wright, J. & Rubenstein, D. R. Evolutionary tipping points in the capacity to adapt to environmental change. Proc. Natl Acad. Sci. 112, 184–189 (2015).
    ADS  CAS  PubMed  Google Scholar 

    35.
    Olofsson, H., Ripa, J. & Jonzén, N. Bet-hedging as an evolutionary game: the trade-off between egg size and number. Proc. R. Soc. B: Biol. Sci. 276, 2963–2969 (2009).
    Google Scholar 

    36.
    Akre, K. L. & Johnsen, S. Psychophysics and the evolution of behavior. Trends Ecol. Evolution 29, 291–300 (2014).
    Google Scholar 

    37.
    Botero, C. A., Dor, R., McCain, C. M. & Safran, R. J. Environmental harshness is positively correlated with intraspecific divergence in mammals and birds. Mol. Ecol. 23, 259–268 (2014).
    PubMed  Google Scholar 

    38.
    Poulin, B., Lefebvre, G. & McNeil, R. Tropical avian phenology in relation to abundance and exploitation of food resources. Ecology 73, 2295–2309 (1992).
    Google Scholar 

    39.
    Botero, C. A. & Rubenstein, D. R. Fluctuating environments, sexual selection and the evolution of flexible mate choice in birds. PLoS ONE 7, e32311 (2012).
    ADS  CAS  PubMed  PubMed Central  Google Scholar 

    40.
    Schwinning, S. & Sala, O. E. Hierarchy of responses to resource pulses in arid and semi-arid ecosystems. Oecologia 141, 211–220 (2004).
    ADS  PubMed  Google Scholar 

    41.
    Visser, M. E., Holleman, L. J. M. & Caro, S. P. Temperature has a causal effect on avian timing of reproduction. Proc. R. Soc. B Biol. Sci. 276, 2323–2331 (2009).
    Google Scholar 

    42.
    Nevoux, M., Forcada, J., Barbraud, C., Croxall, J. & Weimerskirch, H. Bet-hedging response to environmental variability, an intraspecific comparison. Ecology 91, 2416–2427 (2010).
    PubMed  Google Scholar 

    43.
    Salaberria, C., Celis, P., López‐Rull, I. & Gil, D. Effects of temperature and nest heat exposure on nestling growth, dehydration and survival in a Mediterranean hole-nesting passerine. Ibis 156, 265–275 (2014).
    Google Scholar 

    44.
    Ospina, E. A., Merrill, L. & Benson, T. J. Incubation temperature impacts nestling growth and survival in an open-cup nesting passerine. Ecol. Evolution 8, 3270–3279 (2018).
    Google Scholar 

    45.
    Nagy, J., Hauber, M. E., Hartley, I. R. & Mainwaring, M. C. Correlated evolution of nest and egg characteristics in birds. Anim. Behav. 158, 211–225 (2019).
    Google Scholar 

    46.
    Martin, T. E. et al. Enclosed nests may provide greater thermal than nest predation benefits compared with open nests across latitudes. Funct. Ecol. 31, 1231–1240 (2017).
    Google Scholar 

    47.
    Turtumøygard, T. & Slagsvold, T. Evolution of brood parasitism in birds: constraints related to prey type. Behaviour 147, 299–317 (2010).
    Google Scholar 

    48.
    Douglas, D. J. T., Newson, S. E., Leech, D. I., Noble, D. G. & Robinson, R. A. How important are climate-induced changes in host availability for population processes in an obligate brood parasite, the European cuckoo? Oikos 119, 1834–1840 (2010).
    Google Scholar 

    49.
    Saino Nicola et al. Climate change effects on migration phenology may mismatch brood parasitic cuckoos and their hosts. Biol. Lett. 5, 539–541 (2009).
    CAS  PubMed  PubMed Central  Google Scholar 

    50.
    Møller, A. P. et al. Rapid change in host use of the common cuckoo Cuculus canorus linked to climate change. Proc. R. Soc. B: Biol. Sci. 278, 733–738 (2011).
    Google Scholar 

    51.
    Koleček, J., Procházka, P., Brlík, V. & Honza, M. Cross-continental test of natal philopatry and habitat-imprinting hypotheses to explain host specificity in an obligate brood parasite. Sci. Nat. 107, 1–8 (2020).
    Google Scholar 

    52.
    Payne, R. B., Payne, L. L., Woods, J. L. & Sorenson, M. D. Imprinting and the origin of parasite–host species associations in brood-parasitic indigobirds, Vidua chalybeata. Anim. Behav. 59, 69–81 (2000).
    CAS  PubMed  Google Scholar 

    53.
    Price, T., Kirkpatrick, M. & Arnold, S. J. Directional selection and the evolution of breeding date in birds. Science 240, 798–799 (1988).
    ADS  CAS  PubMed  Google Scholar 

    54.
    Halupka, L. & Halupka, K. The effect of climate change on the duration of avian breeding seasons: a meta-analysis. Proc. R. Soc. B Biol. Sci. 284, 20171710 (2017).
    Google Scholar 

    55.
    Zink, A. G. & Lyon, B. E. Evolution of conspecific brood parasitism versus cooperative breeding as alternative reproductive tactics. Am. Naturalist 187, 35–47 (2016).
    Google Scholar 

    56.
    Wells, M. T. & Barker, F. K. Big groups attract bad eggs: brood parasitism correlates with but does not cause cooperative breeding. Anim. Behav. 133, 47–56 (2017).
    Google Scholar 

    57.
    Ursino, C. A., De Mársico, M. C., Sued, M., Farall, A. & Reboreda, J. C. Brood parasitism disproportionately increases nest provisioning and helper recruitment in a cooperatively breeding bird. Behav. Ecol. Sociobiol. 65, 2279–2286 (2011).
    Google Scholar 

    58.
    Cockburn, A. Prevalence of different modes of parental care in birds. Proc. R. Soc. B: Biol. Sci. 273, 1375–1383 (2006).
    Google Scholar 

    59.
    Guigueno, M. F. & Sealy, S. G. Nest sanitation in passerine birds: implications for egg rejection in hosts of brood parasites. J. Ornithol. 153, 35–52 (2012).
    Google Scholar 

    60.
    Dunn, P. O. & Winkler, D. W. Changes in timing of breeding and reproductive success in birds. In Effects of Climate Change on Birds. 113–128, (Oxford University Press, 2010) https://doi.org/10.1093/oso/9780198824268.003.0009.

    61.
    Hauber, M. E. Site selection and repeatability in Brown-Headed Cowbird (Molothrus ater) parasitism of Eastern Phoebe (Sayornis phoebe) nests. Can. J. Zool. 79, 1518–1523 (2001).
    Google Scholar 

    62.
    Kilner, R. M. How selfish is a cowbird nestling? Anim. Behav. 66, 569–576 (2003).
    Google Scholar 

    63.
    Lowther, P.E. Brood Parasitism—host Lists. (Field Museum of Natural History, Chicago, IL, 2019) https://www.fieldmuseum.org/blog/brood-parasitism-host-lists.

    64.
    BirdLife International and Handbook of the Birds of the World. Bird species distribution maps of the world. Version 2018.1. http://datazone.birdlife.org/species/requestdis (2018).

    65.
    ORNL DAAC 2018. MODIS and VIIRS Land Products Global Subsetting and Visualization Tool. (ORNL DAAC, Oak Ridge, Tennessee, USA, 2016) https://doi.org/10.3334/ORNLDAAC/1379.

    66.
    Lima-Ribeiro, M. S. et al. EcoClimate: a database of climate data from multiple models for past, present, and future for macroecologists and biogeographers. Biodiversity Informatics 10, https://doi.org/10.17161/bi.v10i0.4955 (2015).

    67.
    Colwell, R. K. Predictability, constancy, and contingency of periodic phenomena. Ecology 55, 1148–1153 (1974).
    Google Scholar 

    68.
    Hadfield, J. D. MCMC methods for multi-response generalized linear mixed models: The MCMCglmm R Package. J. Stat. Softw. 33, 1–22 (2010).
    Google Scholar 

    69.
    Hackett, S. J. et al. A phylogenomic study of birds reveals their evolutionary history. Science 320, 1763–1768 (2008).
    ADS  CAS  PubMed  Google Scholar 

    70.
    Jetz, W., Thomas, G. H., Joy, J. B., Hartmann, K. & Mooers, A. O. The global diversity of birds in space and time. Nature 491, 444–448 (2012).
    ADS  CAS  PubMed  Google Scholar 

    71.
    Millard SP. EnvStats: an R Package for Environmental Statistics. ISBN 978-1-4614-8455-4, (Springer, New York, 2013). http://www.springer.comhttps://doi.org/10.1002/9780470057339.vae043.pub2.

    72.
    Revelle, W. psych: procedures for psychological, psychometric, and personality research. Northwestern University, Evanston, Illinois. R package version 2.0.7, https://CRAN.R-project.org/package=psych (2020).

    73.
    Faith, D. P. Conservation evaluation and phylogenetic diversity. Biol. Conserv. 61, 1–10 (1992).
    Google Scholar 

    74.
    Kembel, S. W. et al. Picante: R tools for integrating phylogenies and ecology. Bioinformatics 26, 1463–1464 (2010).
    CAS  PubMed  Google Scholar  More

  • in

    An excess of niche differences maximizes ecosystem functioning

    Study site and experimental setup
    Our experiment was conducted at the La Hampa field station of the Spanish National Research Council (CSIC) in Seville, Spain (37°16′58.8″ N, 6°03′58.4″ W), 72 m above sea level. The climate is Mediterranean, with mild, wet winters and hot, dry summers. Soils are loamy with pH = 7.74, C/N = 8.70 and organic matter = 1.16% (0–10-cm depth). Precipitation totaled 532 mm during the experiment (September 2014–August 2015), similar to the 50-y average. We used ten common annual plants, which naturally co-occur at the study site, for the experiment. These species cover a wide phylogenetic and functional range and include members of six of the most abundant families in the Mediterranean grasslands of southern Spain (Table 1). Seeds were provided by a local supplier (Semillas silvestres S.L.) from populations located near to our study site. Our experiments were located within an 800 m2 area, which had been previously cleared of all vegetation and which was fenced to prevent mammal herbivory. Landscape fabric was placed between plots to prevent growth of weeds.
    Theoretical background for quantifying niche and fitness differences
    Here we summarize the approach developed in ref. 38 to quantify the stabilizing effect of niche differences and average fitness differences between any pair of species. Both these measures are derived from mathematical models that capture the dynamics of competing annual plant populations with a seed bank19,39. This approach has been used in the past to accurately predict competitive outcomes between annual plant species38. Population growth is described as:

    $$frac{{N_{i,t ,+, 1}}}{{N_{i,t}}},=,left( {1,-,g_i} right)s_i,+,frac{{lambda _ig_i}}{{1,+,alpha _{ii}g_iN_{i,t},+,{mathrm{{Sigma}}}_{j = 1}^{mathrm{S}}alpha _{ij}g_jN_{j,t}}},$$
    (1)

    Where ({textstyle{{N_{i,t + 1}} over {N_{i,t}}}}) is the per capita population growth rate, and Ni,t is the number of individuals (seeds) of species i before germination in the fall of year t. Changes in per capita growth rates depend on the sum of two terms. The first describes the proportion of seeds that do not germinate (1 − gi) but survive in the seed soil bank (si). The second term describes how much the per germinant fecundity, in the absence of competition (λi), is reduced by the germinated density of conspecific (giNi,t) and various heterospecific (left( {{mathrm{{Sigma}}}_{j = 1}^{mathrm{S}}g_jN_{j,t}} right)) neighbors. These neighbor densities are modified by the interaction coefficients describing the per capita effect of species j on species i (αij) and species i on itself (αii).
    Following earlier studies14,38, we define niche differences (1 − ρ) for this model of population dynamics between competing species as:

    $$1,-,rho,=,1,-,sqrt {frac{{alpha _{ij}}}{{alpha _{jj}}}frac{{alpha _{ji}}}{{alpha _{ii}}}} .$$
    (2)

    The stabilizing niche differences reflect the degree to which intraspecific competition exceeds interspecific competition. 1 − ρ is 1 when individuals only compete with conspecifics (i.e., there is no interspecific competition) and it is 0 when individuals compete equally with conspecifics and heterospecifics (i.e., intra and interspecific competition are equal). Niche differences between plant species can arise for instance from differences in light harvesting strategies29,37,38,39, or in soil resource use and shared mutualisms40.
    The average fitness differences between a pair of competitors is ({textstyle{{kappa _j} over {kappa _i}}})38, and its expression is the following:

    $$frac{{kappa _j}}{{kappa _i}},=,frac{{eta _j,-,1}}{{eta _i,-,1}}sqrt {frac{{alpha _{ij}}}{{alpha _{ji}}}frac{{alpha _{ii}}}{{alpha _{jj}}}} .$$
    (3)

    The species with the higher value of ({textstyle{{kappa _j} over {kappa _i}}}) (either species i or species j) is the competitive dominant, and in the absence of niche differences excludes the inferior competitor. This expression shows that ({textstyle{{kappa _j} over {kappa _i}}}) combines two fitness components, the “demographic ratio” (left( {{textstyle{{eta _j – 1} over {eta _i – 1}}}} right)) and the “competitive response ratio” (left( {sqrt {{textstyle{{alpha _{ij}} over {alpha _{ji}}}}{textstyle{{alpha _{ii}} over {alpha _{jj}}}}} } right)). The demographic ratio is a density independent term and describes the degree to which species j has higher annual seed production, per seed lost from the seed bank due to death or germination, than species i

    $$eta _j,=,frac{{lambda _jg_j}}{{1,-,left( {1,-,g_j} right)s_j}}.$$

    The competitive response ratio is a density-dependent term, which describes the degree to which species i is more sensitive to both intra and interspecific competition than species j. Note that the same interaction coefficients defining niche differences are also involved in describing the competitive response ratio, although their arrangement is different. Because of this interdependence, a change in interaction coefficients (( {alpha _{ji}^prime s} )) simultaneously changes both stabilizing niche differences and average fitness differences21.
    With niche differences stabilizing coexistence and average fitness differences promoting competitive exclusion, the condition for coexistence (mutual invasibility) is expressed as14,38:

    $$rho, More

  • in

    Assessment of selected heavy metals and enzyme activity in soils within the zone of influence of various tree species

    1.
    Binggan, W. & Yang, L. A review of heavy metal contaminations in urban soils, urban road dusts and agricultural soils from China. Microchem. J. 94, 99–107. https://doi.org/10.1016/j.microc.2009.09.014 (2010).
    CAS  Article  Google Scholar 
    2.
    Bini, C., Wahsha, M., Fontana, S. & Maleci, L. Effects of heavy metals on morphological characteristic of Taraxacum officinale Web growing on mine soils in NE Italy. J. Geochem. Explor. 123, 101–108. https://doi.org/10.1016/j.geoxplo.2012.07.009 (2012).
    CAS  Article  Google Scholar 

    3.
    Hu, Y., Wang, D., Wei, L., Zhang, X. & Song, B. Bioaccumulation of heavy metals in plant leaves from Yan’an city of the Loess Plateau, China. Ecotox. Environ. Safe 110, 82–88. https://doi.org/10.1016/j.ecoenv.2014.08.021 (2014).
    CAS  Article  Google Scholar 

    4.
    Bartkowiak, A., Lemanowicz, J. & Breza-Borut, B. Evaluation of the content of Zn, Cu, Ni and Pb as well as the enzymatic activity of forest soils exposed to the effect of road traffic pollution. Environ. Sci. Pollut. Res. 24(30), 23893–23902. https://doi.org/10.1007/s11356-017-0013-3 (2017).
    CAS  Article  Google Scholar 

    5.
    Simon, E. et al. Elemental concentrations in deposited dust on leaves along an urbanization gradient. Sci. Total Environ. 490, 514–520. https://doi.org/10.1016/j.scitotenv.2014.05.028 (2014).
    CAS  PubMed  ADS  Article  Google Scholar 

    6.
    Braquinho, C., Serrano, H., Pinto, M. & Martins-Loução, M. Revisiting the plant hyperaccumulation criteria to rare plants and earth abundant elements. Environ. Pollut. 146, 437–443. https://doi.org/10.1016/j.envpol.2006.06.034 (2007).
    CAS  Article  Google Scholar 

    7.
    Remon, E., Bouchardon, J. L., Guédard, M. L., Bessoule, J. J. & Conord, C. Are plants useful as accumulation indicators of metal bioavailability. Environ. Pollut. 175, 1–7. https://doi.org/10.1016/j.envpol.2012.12.015 (2013).
    CAS  PubMed  Article  Google Scholar 

    8.
    Dębska, B., Długosz, J. & Piotrowska-Długosz, A. The impact of a bio-fertilizer on the soil organic matter status and carbon sequestration-results from a field-scale study. J. Soils Sedim. 16(10), 2335–2343. https://doi.org/10.1007/s11368-016-1430-5 (2016).
    CAS  Article  Google Scholar 

    9.
    Serbula, S. M., Miljkovic, D. D., Kovacevic, R. M. & Ilic, A. A. Assessment of airborne heavy metal pollution using plant parts and topsoil. Ecotox. Environ. Safe 76, 209–214. https://doi.org/10.4209/aaqr.2012.06.0153 (2012).
    CAS  Article  Google Scholar 

    10.
    Ugolini, F., Tognetti, R., Raschi, A. & Bacci, A. Quercus ilex L as bioaccumulator for heavy metals in urban areas: Effectiveness of leaf washing with distilled water and considerations on the trees distance from traffic. Urban For. Urban Gree. 12, 576–584. https://doi.org/10.1016/j.ufug.2013.05.007 (2013).
    Article  Google Scholar 

    11.
    Kandziora-Ciupa, M., Nagórska-Socha, A., Ciepał, Ł & Janowicz, I. Heavy metals content and biochemical indicators in birch leaves from polluted and clean areas. Ecol. Chem. Eng. A 22(1), 83–91. https://doi.org/10.2428/ecea.2015.22(1)08 (2015).
    CAS  Article  Google Scholar 

    12.
    Tzvetkova, N. & Petkova, K. Bioaccumulation of heavy metals by the leaves of Robinia pseudoacacia as a bioindicator tree in industrial zones. J. Environ. Biol. 36, 59–63 (2015).
    PubMed  Google Scholar 

    13.
    Nadgórska-Socha, A., Kandziora-Ciupa, M., Trzęsicki, M. & Barczyk, G. Air pollution tolerance index and heavy metal bioaccumulation in selected plant species from urban biotopes. Chemosphere 183, 471–482. https://doi.org/10.1016/j.chemosphere.2017.05.128 (2017).
    CAS  PubMed  ADS  Article  Google Scholar 

    14.
    Baldrian, P. & Šnajdr, J. Lignocellulose-degrading enzymes in soil. In Soil Enzymology (eds Shukla, G. & Varma, A.) 167–186 (Springer, Berlin, 2011).
    Google Scholar 

    15.
    Orczewska, A., Piotrowska, A. & Lemanowicz, J. Soil acid phosphomonoesterase activity end phosphorus forms in ancient and post-agricultural black alder [Alnus glutonosa (L) Gaertn.] woodland. Acta Soc. Bot. Pol. 81(2), 81–86. https://doi.org/10.5586/asbp.2012.013 (2010).
    CAS  Article  Google Scholar 

    16.
    Lemanowicz, J. Dynamics of phosphorus content and the activity of phosphatase in forest soil in the sustained nitrogen compounds emissions zone. Environ. Sci. Pollut. Res. 25(33), 33773–33782. https://doi.org/10.1007/s11356-018-3348-5 (2018).
    CAS  Article  Google Scholar 

    17.
    Bach, C. E. et al. Measuring phenol oxidase and peroxidase activities with pyrogallol, L-DOPA, and ABTS: Effect of assay conditions and soil type. Soil Biol. Biochem. 67, 183–191. https://doi.org/10.1016/j.soilbio.2013.08.022 (2013).
    CAS  Article  Google Scholar 

    18.
    PN-ISO 10390. Chemical and Agricultural Analysis—Determining Soil pH. (Polish Standards Committee, Warszawa, 1997).

    19.
    Crock, J. G. & Severson, R. Four reference soil and rock samples for measuring element availability in the western energy regions. Geochem. Surv. Circ. 841, 1–16 (1980).
    Google Scholar 

    20.
    U.S. EPA. Clean Water Act, Sec. 503, Vol. 58, No. 32. (U.S. Environmental Protection Agency Washington, D.C., 1993).

    21.
    Regulation of the Minister of the Environment dated 1 September 2016 on assessment procedures for the land surface pollution (Journal of Laws, item 1359, September 5, 2016) (in Polish).

    22.
    Obrador, A. et al. Relationships of soil properties with Mn and Zn distribution in acidic soils and their uptake by a barley crop. Geoderma 137(3–4), 432–443. https://doi.org/10.1016/j.geoderma.2006.10.001 (2007).
    CAS  ADS  Article  Google Scholar 

    23.
    Kandeler, E. Enzymes involved in nitrogen metabolism. In Methods in Soil Biology (eds Schinner, F. et al.) 163–184 (Springer, Berlin, 1995).
    Google Scholar 

    24.
    Bartha, R. & Bordeleau, L. Cell-free peroxidases in soil. Soil Biol. Biochem. 1(2), 139–143. https://doi.org/10.1016/0038-0717(69)90004-2 (1969).
    CAS  Article  Google Scholar 

    25.
    USDA. Keys to Soil Taxonomy. Tenth Edition. United States Department of Agriculture, Natural Resources Conservation Service 1–332 (2006).

    26.
    Zehetner, F., Rosenfellner, U., Mentler, A. & Gerzabek, M. H. Distribution of road salt residues, heavy metals and polycyclic aromatic hydrocarbons across a highway-forest interface. Water Air Soil Pollut. 198, 125–132. https://doi.org/10.1007/s11270-008-9831-8 (2009).
    CAS  ADS  Article  Google Scholar 

    27.
    Czubaszek, R. & Bartoszuk, K. Content of selected heavy metals in soils in accordance with its distance from the street and land use. Civil Environ. Eng. 2, 27–34 (2011).
    Google Scholar 

    28.
    Gąsiorek, M., Kowalska, J., Mazurek, R. & Pająk, M. Comprehensive assessment of heavy metal pollution in topsoil of historical urban park on an example of the Planty Park in Krakow (Poland). Chemosphere 179, 148–158. https://doi.org/10.1016/j.chemosphere.2017.03.106 (2017).
    CAS  PubMed  ADS  Article  Google Scholar 

    29.
    Kabata-Pendias, A. & Pendias, P. Trace Elements in Soils and Plants, 3rd edn. (CRC Press, Florida, ISBN 0-8493-1575-1, 2001).

    30.
    Inal, A., Gunes, A., Zhang, F. & Cakmak, I. Peanut/maize intercropping induced change in rhizosphere and nutrient concentration in shoots. Plant Physiol. Biochem. 45, 350–356. https://doi.org/10.1016/j.plaphy.2007.03.016 (2007).
    CAS  PubMed  Article  Google Scholar 

    31.
    Jin, C. W., Zheng, S. J., He, Y. F., Zhou, G. D. & Zhou, Z. H. Lead contamination in tea garden soil and factors affecting its bioavailability. Chemosphere 61(5), 726–732. https://doi.org/10.1016/j.chemosphere.2005.03.053 (2005).
    CAS  PubMed  ADS  Article  Google Scholar 

    32.
    Ashworth, D. J. & Alloway, B. J. Soil mobility of sewage sludge-derived dissolved organic matter, copper, nickel and zinc. Environ. Pollut. 127, 137–144 (2004).
    CAS  PubMed  Article  Google Scholar 

    33.
    Fijałkowski, K., Kacprzak, M., Grobelak, A. & Placek, A. The influence of selected soil parameters on the mobility of heavy metals in soils. Eng. Prot. Environ. 15(1), 81–92 (2012).
    Google Scholar 

    34.
    Lasat, M.M. Phytoextraction of toxic metals. A review of biological mechanisms. J. Environ. Qual. 31, 109–120 (2002).

    35.
    Gonderek, K. & Filipek-Mazur, B. Heavy metal bonding by the soil humus in the soils liable to traffic pollution. Acta Agrophys. 2(4), 759–770 (2003).
    Google Scholar 

    36.
    Lemanowicz, J., Bartkowiak, A. & Breza-Boruta, B. Phosphorus, lead and nickel content and the activity of phosphomonoesterases in soil in the Bydgoska Forest affected by illegal dumping. Sylwan 160(2), 144–152 (2016).
    Google Scholar 

    37.
    Chojnacka, K., Chojnacki, A., Górecka, H. & Górecki, H. Bioavailability of heavy metals from polluted soils to plants. Sci. Total Environ. 337, 175–182. https://doi.org/10.1016/j.scietotenv.2004.06.009 (2005).
    CAS  PubMed  ADS  Article  Google Scholar 

    38.
    Pourkhabbaz, A., Rastin, N., Olbrich, A., Langenfeld-Heyser, R. & Polle, A. Influence of environmental pollution on leaf properties of urban plane trees, Platanus orientalis L. Bull. Environ. Contam. Toxicol. 85, 251–255. https://doi.org/10.1007/s00128-010-0047-4 (2010).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    39.
    Piotrowska, A. & Mazurek, R. Assessment of black locust (Robinia pseudoacacia L) shelterbelt influence on enzymatic activity and some chemical parameters of eutric cambisol. Pol. J. Soil Sci. 42(1), 31–41 (2009).
    CAS  Google Scholar 

    40.
    Sinsabaugh, R. L. Phenol oxidase, peroxidase and organic matter dynamics of soil. Soil Biol. Biochem. 42, 391–404. https://doi.org/10.1016/j.soilbio.2009.10.014 (2010).
    CAS  Article  Google Scholar 

    41.
    Mohsenzadeh, F., Rad, A. C. & Akbari, M. Evaluation of oil removal efficiency and enzymatic activity in some fungal strains for bioremediation of petroleum-polluted soils. Iran. J. Environ. Health Sci. Eng. 9(26), 1–8. https://doi.org/10.1186/1735-2746-9-26 (2012).
    CAS  Article  Google Scholar 

    42.
    Baldrian, P. Distribution of extracellular enzymes in soils: spatial heterogeneity and determining factors at various scales. Soil Sci. Soc. Am. J. 78, 11–18. https://doi.org/10.2136/sssaj2013.04.0155dgs (2014).
    CAS  ADS  Article  Google Scholar 

    43.
    Kotroczo, Z. et al. Soil enzyme activity in response to long-term organic matter manipulation. Soil Biol. Biochem. 70, 237–243. https://doi.org/10.1016/j.soilbio.2013.12.028 (2014).
    CAS  Article  Google Scholar 

    44.
    Błońska, E. Seasonal changeability of enzymatic activity in soils of selected forest sites. Acta Sci. Pol. Silv. Colendar. Rat Ind. Lignar. 9(3–4), 5–15 (2010).

    45.
    Zheng, H. et al. Factors influencing soil enzyme activity in China’s forest ecosystems. Plant Ecol. 219, 31. https://doi.org/10.1007/s11258-017-0775-1 (2018).
    Article  Google Scholar 

    46.
    Yu, X., Liu, X., Zhao, Z., Liu, J. & Zhang, S. Effect of monospecific and mixed sea-buckthorn (Hippophae rhamnoides) plantations on the structure and activity of soil microbial communities. PLoS ONE 10, e0117505. https://doi.org/10.1371/journal.pone.0117505 (2015).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    47.
    Bielińska, E. J., Kołodziej, B. & Sugier, D. Relationship between organic carbon content and the activity of selected enzymes in urban soils under different anthropogenic influence. J. Geochem. Explor. 129, 52–56. https://doi.org/10.1016/j.gexplo.2012.10.019 (2013).
    CAS  Article  Google Scholar 

    48.
    Bollag, J. M., Chen, Ch. M., Sarkar, J. M. & Loll, M. J. Extraction and purification of a peroxidase from soil. Soil Biol. Biochem. 19(1), 61–67. https://doi.org/10.1016/0038-0717(87)90126-X (1987).
    CAS  Article  Google Scholar 

    49.
    Turner, B. L. Variation in pH optima of hydrolytic enzyme activities in tropical rain forest soils. Appl. Environ. Microb. 76, 6485–6493. https://doi.org/10.1128/AEM.00560-10 (2010).
    CAS  Article  Google Scholar  More