More stories

  • in

    Precision conservation for a changing climate

    The author wishes to thank N. Haan, G. P. Robertson and N. Haddad for their valuable comments. Financial support was provided by USDA/NIFA (awards 2019-67012-29595 and 2015-68007-23133), the US National Science Foundation’s Long-term Ecological Research Program (award 1637653), the US Department of Energy, Office of Science, Office of Biological and Environmental Research (awards DESC0018409 and DE-FC02-07ER64494), and Michigan State University AgBioResearch. More

  • in

    Controversial forestry experiment will be largest-ever in United States

    A clear-cut slope in the Elliott State Forest, Oregon.Credit: Matthew Betts

    Despite lingering tensions among environmentalists and loggers, a plan to launch the largest forestry experiment in the United States — and perhaps the world — last month cleared a major hurdle. Controversially, the study would allow logging in a new research forest, in an attempt to answer a grand question: in a world where wood remains a necessary resource, but biodiversity is declining, what’s the best way to balance timber production with conservation?“We all love wood, and we all need wood,” says Thomas DeLuca, dean of the College of Forestry at Oregon State University (OSU) in Corvallis. “We have to find ways to produce it sustainably, and this project could help us do that.”
    These scientists are setting a forest on fire — and studying it with drones
    If the project — proposed by DeLuca and other researchers at OSU — launches successfully, the newly created Elliott State Research Forest in southwestern Oregon would occupy a roughly 33,000-hectare parcel of land. This would be divided into more than 40 sections, in which scientists would test several forest-management strategies, some including extensive logging. The advisory committee for the project, which comprises environmentalists, hunters, loggers and members of local Indigenous tribes, approved the latest research proposal on 22 April.The plan comes as US President Joe Biden and other international leaders are strengthening commitments to conserve land and biodiversity before a meeting of the United Nations Convention on Biological Diversity later this year. In time, the Elliott research forest could help policymakers to determine how best to define and implement those pledges, says DeLuca.A contested forestFor decades, the land that makes up the Elliott State Forest has been mired in controversy. Logging is big business in the US Pacific Northwest, and this particular state-owned piece of land contains old-growth forest filled with valuable Douglas firs (Pseudotsuga menziesii) and other trees. Other sections have been actively logged and replanted since 1930. It also hosts threatened species such as the spotted owl (Strix occidentalis) and the marbled murrelet (Brachyramphus marmoratus), a seabird that nests in old-growth forests. In 2012, a lawsuit aimed at protecting the marbled murrelet brought commercial logging in the forest to a halt.

    Source: Deanne Carlson, OSU/Oregon Geospatial Enterprise Office; Design: Nature

    The state of Oregon considered various options for the land, before OSU researchers stepped forward with a plan in 2018. Their proposal to convert the property into a research forest would allow logging to resume at a lower level — but in the service of science and conservation, the scientists say. According to the plan, the profit from logging in the Elliott forest — around US$5 million to $7 million annually, says DeLuca — would help to pay for the experiment’s infrastructure and operations.There are dozens of research forests around the globe, including in the United States, and scientists have used them to study everything from ecology and soils to acid rain and the effects of rising atmospheric carbon dioxide levels. But the Elliott research forest would be larger than most of its predecessors, and advocates say that it would provide scientists with the first opportunity to test ecological forestry at such a large scale.A sea change for forestryAs currently designed, the project would leave more than 40% of the forest — a section of old growth that has been regenerating naturally since the area last burnt, a century and a half ago — untouched by logging. In the remaining area, researchers would run a series of replicated experiments, carrying out 4 types of land management across 40 small watersheds. On some plots, selective logging of individual trees would take place across the entire area. On others, clear-cutting would take place on half of the land, with the other half reserved for conservation. Other types of experimental plot would mix these two approaches (see ‘A grand experiment’). To understand the impacts of each management type, scientists would measure a variety of parameters, including levels of carbon in the forest; stream health; and insect, bird and fish diversity.So far, around 20 OSU researchers are involved in the project’s design, but the university hopes eventually to attract more scientists from across the world, who would run their own projects.

    Old-growth areas such as this one would be protected as reserves under a plan to convert the Elliott State Forest into an experimental forest.Credit: Matthew Betts

    The scale and approach of the experiment proposed by OSU would represent a sea change in forestry research, says Sue Baker, a forest ecologist at the University of Tasmania in Hobart, Australia, who is setting up a retrospective study looking at similar questions in Tasmanian forests. “I can’t think of anything similar anywhere in the world where people have been able to manipulate the forest landscape at this scale,” says Baker.More hurdles aheadSince its creation in 1930, the Elliott State Forest has been legally obliged to generate revenue for Oregon’s public schools through logging. Before OSU can take it over, the state must compensate the school fund to the tune of $221 million (the value of the forest); it has so far allocated less than half of that amount.And other hurdles remain. The university must finish a detailed management plan that will lay out rules governing the forest, and it must craft a separate plan for managing threatened and endangered species; this will need to be approved by the US Fish and Wildlife Service.
    How much can forests fight climate change?
    The OSU team has spent the past few years trying to build a broad — and unlikely — coalition for the effort, through public meetings and engagement with local Indigenous tribes, industry, environmentalists and other members of the project’s advisory panel, whose support will be crucial as state leaders weigh their final decision. But tensions haven’t disappeared entirely. Many environmentalists continue to question the logic of clear-cutting forests that absorb and store carbon in the middle of a climate crisis. Rather than perpetuating a long and damaging legacy of clear-cutting, the Elliott forest could be used to pioneer new forestry methods that restore biodiversity and boost carbon storage, says Josh Laughlin, executive director of Cascadia Wildlands, a conservation group based in Eugene, Oregon. “Let’s not make the same mistakes we’ve made over the past 100 years.”Given OSU’s long-standing ties to the timber industry, and controversies surrounding its management of existing research forests, it will also need to overcome scepticism about its role as a land steward, says Bob Van Dyk, a policy director at the Wild Salmon Center, an environmental group based in Portland, Oregon. In 2019, for instance, OSU’s College of Forestry authorized clear-cutting on 6.5 hectares of one of its forests, felling trees that were hundreds of years old.
    When will the Amazon hit a tipping point?
    DeLuca acknowledges that there have been mistakes in the past, but says the university has a solid academic record, and is committed to building a world-class research facility with the Elliott forest. “If we are able to demonstrate practices that accommodate the broadest array of species while still generating timber for meeting human resource needs, we can have a much larger impact,” says DeLuca.Everything will depend on the final management plan, but for now, Van Dyk and other members of the advisory board have unanimously given a provisional green light to the latest proposal. “It’s a good project, and we don’t get many chances to do something that is truly novel and interesting,” he says. More

  • in

    Our radical changes to Earth’s greenery began long ago — with farms, not factories

    A nineteenth-century illustration of a harvest in ancient Greece. Farming intensified around 2000 BC, when the rate of change in Earth’s plant life sped up. Credit: Docutres/Index/Heritage Images/Alamy

    Ecology
    20 May 2021
    Our radical changes to Earth’s greenery began long ago — with farms, not factories

    Humanity’s imprint on plant species and abundance began roughly 4,000 years ago, when agriculture took off.

    Share on Twitter
    Share on Twitter

    Share on Facebook
    Share on Facebook

    Share via E-Mail
    Share via E-Mail

    Human activity began to transform the number and variety of plant species on Earth thousands of years ago, long before the Industrial Revolution, and might have had an even greater impact on vegetation than did the last ice age.Ice entombed much of the planet from roughly 115,000 to some 20,000 years ago. Then, massive glaciers around the world started to retreat and global temperatures rose, resulting in dramatic alterations to Earth’s ecosystems.To investigate how the abundance and composition of global vegetation changed after that thaw, Ondřej Mottl and Suzette Flantua at the University of Bergen in Norway and their colleagues analysed 1,181 fossilized pollen samples from the past 18,000 years. The pollen came from all continents except Antarctica.The researchers found that global vegetation has been transformed, first by the climate changes that accompanied the end of the last glacial period. However, starting about 4,000 years ago, when agriculture intensified, the pace of change in global vegetation accelerated, reaching or exceeding the rate of change at the end of the most recent ice age.

    Science (2021)

    Ecology More

  • in

    Seasonal change is a major driver of soil resistomes at a watershed scale

    1.D’Costa, V. M. et al. Antibiotic resistance is ancient. Nature. 477, 457–461 (2011).PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    2.Allen, H. K. et al. Call of the wild: antibiotic resistance genes in natural environments. Nat. Rev. Microbiol. 8, 251–259 (2010).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    3.Udikovic-Kolic, N., Wichmann, F., Broderick, N. A. & Handelsman, J. Bloom of resident antibiotic-resistant bacteria in soil following manure fertilization. Proc. Natl Acad. Sci. USA. 111, 15202–15207 (2014).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    4.Chen, Q. L. et al. Long-term field application of sewage sludge increases the abundance of antibiotic resistance genes in soil. Environ. Int. 92–93, 1–10 (2016).PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    5.Gillings, M. R. & Stokes, H. W. Are humans increasing bacterial evolvability? Trends Ecol. Evol. 27, 346–352 (2012).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    6.Zhu, Y. G. et al. Diverse and abundant antibiotic resistance genes in Chinese swine farms. Proc. Natl Acad. Sci. USA. 110, 3435–3440 (2013).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    7.Woods, L. C. et al. Horizontal gene transfer potentiates adaptation by reducing selective constraints on the spread of genetic variation. Proc. Natl Acad. Sci. USA. 117, 26868–26875 (2020).8.World Health Organization. Antimicrobial resistance: global report on surveillance. World Health Organization. (2014).9.Forsberg, K. J. et al. The shared antibiotic resistome of soil bacteria and human pathogens. Science. 337, 1107–1111 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    10.Zhu, G. et al. Air pollution could drive global dissemination of antibiotic resistance genes. ISME J. 15, 270–281 (2021).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    11.Xiang, Q. et al. Agricultural activities affect the pattern of the resistome within the phyllosphere microbiome in peri-urban environments. J. Hazard Mater. 382, 121068 (2020).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    12.Wang, F. H. et al. High throughput profiling of antibiotic resistance genes in urban park soils with reclaimed water irrigation. Environ. Sci. Technol. 48, 9079–9085 (2014).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    13.Ding, J. et al. Long-term application of organic fertilization causes the accumulation of antibiotic resistome in earthworm gut microbiota. Environ. Int. 124, 145–152 (2019).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    14.Zhou, S. Y. et al. Phyllosphere of staple crops under pig manure fertilization, a reservoir of antibiotic resistance genes. Environ. Pollut. 252, 227–235 (2019).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    15.Wang, F. H., Qiao, M., Chen, Z., Su, J. Q. & Zhu, Y. G. Antibiotic resistance genes in manure-amended soil and vegetables at harvest. J. Hazard Mater. 299, 215–221 (2015).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    16.Marti, R. et al. Impact of manure fertilization on the abundance of antibiotic-resistant bacteria and frequency of detection of antibiotic resistance genes in soil and on vegetables at harvest. Appl. Environ. Microb. 79, 5701–5709 (2013).CAS 
    Article 

    Google Scholar 
    17.Zhu, Y. G. et al. Continental-scale pollution of estuaries with antibiotic resistance genes. Nat. Microbiol. 2, 16270 (2017).CAS 
    PubMed 
    Article 

    Google Scholar 
    18.Du, S. et al. Large-scale patterns of soil antibiotic resistome in Chinese croplands. Sci. Total Environ. 712, 136418 (2020).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    19.Pruden, A., Pei, R. T., Storteboom, H. & Carlson, K. H. Antibiotic resistance genes as emerging contaminants: studies in northern Colorado. Environ. Sci. Technol. 40, 7445–7450 (2006).CAS 
    PubMed 
    Article 

    Google Scholar 
    20.Bahram, M. et al. Structure and function of the global topsoil microbiome. Nature. 560, 233–237 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    21.Hu, H. W. et al. Diversity of herbaceous plants and bacterial communities regulates soil resistome across forest biomes. Environ. Microbiol. 20, 3186–3200 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    22.Han, X. M. et al. Antibiotic resistance genes and associated bacterial communities in agricultural soils amended with different sources of animal manures. Soil Biol. Biochem. 126, 91–102 (2018).CAS 
    Article 

    Google Scholar 
    23.Hu, H. W. et al. Temporal changes of antibiotic-resistance genes and bacterial communities in two contrasting soils treated with cattle manure. FEMS Microbiol. Ecol. 92, fiv169 (2016).24.Zhang, Y. J. et al. Temporal succession of soil antibiotic resistance genes following application of swine, cattle and poultry manures spiked with or without antibiotics. Environ. Pollut. 231, 1621–1632 (2017).CAS 
    PubMed 
    Article 

    Google Scholar 
    25.Zhou, J. et al. Reproducibility and quantitation of amplicon sequencing-based detection. ISME J. 5, 1303–1313 (2011).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    26.Caporaso, J. G. et al. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods. 7, 335–336 (2010).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    27.Edgar, R. C. Search and clustering orders of magnitude faster than BLAST. Bioinformatics. 26, 2460–2461 (2010).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    28.Wang, Q., Garrity, G. M., Tiedje, J. M. & Cole, J. R. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microb. 73, 5261–5267 (2007).CAS 
    Article 

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

    Google Scholar 
    30.Su, J. Q. et al. Antibiotic resistome and its association with bacterial communities during sewage sludge composting. Environ. Sci. Technol. 49, 7356–7363 (2015).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    31.Ouyang, W. Y., Huang, F. Y., Zhao, Y., Li, H. & Su, J. Q. Increased levels of antibiotic resistance in urban stream of Jiulongjiang River, China. Appl. Microbiol. Biotechnol. 99, 5697–5707 (2015).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    32.Roberts D. W. labdsv: ordination and multivariate analysis for ecology. R package version 1.8-0. 2016. https://CRAN.R-project.org/package=labdsv.33.Oksanen J. et al. Vegan: community ecology package. R package version 2.2-0. 2014. http://CRAN.R-project.org/package=vegan.34.Jiao, S. et al. Soil microbiomes with distinct assemblies through vertical soil profiles drive the cycling of multiple nutrients in reforested ecosystems. Microbiome. 6, 1–13 (2018).35.Sloan, W. T. et al. Quantifying the roles of immigration and chance in shaping prokaryote community structure. Environ Microbiol. 8, 732–740 (2006).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    36.Ning, D., Deng, Y., Tiedje, J. M. & Zhou, J. A general framework for quantitatively assessing ecological stochasticity. Proc. Natl Acad. Sci. USA. 116, 16892–16898 (2019).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    37.De Caceres, M. & Legendre, P. Associations between species and groups of sites: indices and statistical inference. Ecology. 90, 3566–3574 (2009).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    38.Doerks, T., Copley, R. R., Schultz, J., Ponting, C. P. & Bork, P. Systematic identification of novel protein domain families associated with nuclear functions. Genome Res. 12, 47–56 (2002).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    39.Wickham H. ggplot2: elegant graphics for data analysis. (Springer-Verlag, 2009).40.Kassambara A. ggpubr: ‘ggplot2’ based publication ready plots. R package version 0.2. 2018. https://CRAN.R-project.org/package=ggpubr.41.Ahlmann-Eltze C. ggsignif: significance brackets for ‘ggplot2’. R package version 0.4. 0. 2018. https://CRAN.R-project.org/package=ggsignif.42.Zhao, F. K. et al. Soil contamination with antibiotics in a typical peri-urban area in eastern China: seasonal variation, risk assessment, and microbial responses. J. Environ. Sci. (China). 79, 200–212 (2019).Article 

    Google Scholar 
    43.Zhang, Y., Snow, D. D., Parker, D., Zhou, Z. & Li, X. Intracellular and extracellular antimicrobial resistance genes in the sludge of livestock waste management structures. Environ. Sci. Technol. 47, 10206–10213 (2013).CAS 
    PubMed 
    Article 

    Google Scholar 
    44.Mao, D. et al. Persistence of extracellular DNA in river sediment facilitates antibiotic resistance gene propagation. Environ. Sci. Technol. 48, 71–78 (2014).CAS 
    PubMed 
    Article 

    Google Scholar 
    45.Xiang, Q. et al. Spatial and temporal distribution of antibiotic resistomes in a peri-urban area is associated significantly with anthropogenic activities. Environ. Pollut. 235, 525–533 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    46.Forsberg, K. J. et al. Bacterial phylogeny structures soil resistomes across habitats. Nature. 509, 612–616 (2014).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    47.Li, B. et al. Metagenomic and network analysis reveal wide distribution and co-occurrence of environmental antibiotic resistance genes. ISME J. 9, 2490–2502 (2015).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    48.Hu, H. W. et al. Field-based evidence for copper contamination induced changes of antibiotic resistance in agricultural soils. Environ. Microbiol. 18, 3896–3909 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    49.Birgander, J., Rousk, J. & Olsson, P. A. Comparison of fertility and seasonal effects on grassland microbial communities. Soil Biol. Biochem. 76, 80–89 (2014).CAS 
    Article 

    Google Scholar 
    50.Fournier, B. et al. Higher spatial than seasonal variation in floodplain soil eukaryotic microbial communities. Soil Biol. Biochem. 147, 107842 (2020).CAS 
    Article 

    Google Scholar 
    51.Zhang, K., Delgado-Baquerizo, M., Zhu, Y. G. & Chu, H. Space is more important than season when shaping soil microbial communities at a large spatial scale. Msystems. 5, e00783–19 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    52.Ladau, J. & Eloe-Fadrosh, E. A. Spatial, temporal, and phylogenetic scales of microbial ecology. Trends Microbiol. 27, 662–669 (2019).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar  More

  • in

    Germination response to water availability in populations of Festuca pallescens along a Patagonian rainfall gradient based on hydrotime model parameters

    1.Zárate, M. A. & Tripaldi, A. The aeolian system of central Argentina. Aeolian Res. 3, 401–417 (2012).ADS 
    Article 

    Google Scholar 
    2.Chapin III, F. S. Functional role of growth forms in ecosystem and global processes. In Scaling Physiology Process (ed. Ehleringer J. R. & Field C. B.) 287–312. (Elsevier Inc., 1993). https://doi.org/10.1016/C2009-0-03319-4.
    Google Scholar 
    3.Jump, A. S., Mátyás, C. & Peñuelas, J. The altitude-for-latitude disparity in the rangeretractions of woody species. Trends Ecol. Evol. (Amst.) 24, 694–701. https://doi.org/10.1016/j.tree.2009.06.007 (2009).Article 

    Google Scholar 
    4.Donohue, K., Rubio de Casas, R., Burghardt, L., Kovach, K. & Willis, C. G. Germination, postgermination adaptation, and species ecological ranges. Annu. Rev. Ecol. Evol. Syst. 41, 293–319 (2010).Article 

    Google Scholar 
    5.O’Connor, T. Local extinction in perennial grasslands: A life-history approach. Am. Nat. 137, 753–773 (1991).Article 

    Google Scholar 
    6.Rotundo, J. L., Aguiar, M. R. & Benech-Arnold, R. Understanding erratic seedling emergence in perennial grasses using physiological models and field experimentation. Plant Ecol. 216, 143–156 (2015).Article 

    Google Scholar 
    7.Duncan, C., Schultz, N. L., Good, M. K., Lewandrowski, W. & Cook, S. The risk-takers and-avoiders: Germination sensitivity to water stress in an arid zone with unpredictable rainfall. AoB Plants. 11(6), plz066 (2019).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    8.Pendleton, B. & Meyer, S. Habitat-correlated variation in blackbrush (Coleogyne ramosissima: Rosaceae) seed germination response. J. Arid Environ. 59, 229–243 (2004).ADS 
    Article 

    Google Scholar 
    9.Chamorro, D. et al. Germination sensitivity to water stress in four shrubby species across the Mediterranean Basin. Plant Biol. 19(1), 23–31 (2017).PubMed 
    Article 
    CAS 
    PubMed Central 

    Google Scholar 
    10.Bewley, J. D. & Black, M. Seeds. In Seeds. (ed. Bewley, J. D. & Black, M.) 1–33. https://doi.org/10.1007/978-1-4899-1002-8. eBook ISBN978-1-4899-1002-8 (Springer, Boston, MA, 1994).
    Google Scholar 
    11.Bradford, K. J. Water relations in seed germination. In Seed Development and Germination (eds Kigel, J. & Galili, G.) 351–396 (Marcel Dekker Inc, 1995).
    Google Scholar 
    12.Batlla, D. & Benech-Arnold, R. L. The role of fluctuations in soil water content on the regulation of dormancy changes in buried seeds of Polygonum aviculare L. Seed Sci. Res. 16(1), 47–59 (2006).Article 
    CAS 

    Google Scholar 
    13.Luna, B. & Chamorro, D. Germination sensitivity to water stress of eight Cistaceae species from the Western Mediterranean. Seed Sci. Res. 26(2), 101 (2016).Article 

    Google Scholar 
    14.Bradford, K. J. Threshold models applied to seed germination ecology. New Phytol. 165, 338–341 (2005).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    15.Garcia-Huidobro, J., Monteith, J. & Squire, G. Time, temperature and germination of pearl millet (Pennisetum typhoides S. & H.) I. Constant temperature. J. Exp. Bot. 33, 288–296 (1982).Article 

    Google Scholar 
    16.Bradford, K. J. A water relations analysis of seed germination rates. Plant Physiol. 94, 840–849 (1990).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    17.Bradford, K. J. & Still, D. W. Applications of hydrotime analysis in seed testing. Seed Technol. 26(1), 75–85 (2004).
    Google Scholar 
    18.Gummerson, R. J. The effect of constant temperature and osmotic potentials on the germination of sugar beet. J. Exp. Bot. 37, 729–741 (1986).Article 

    Google Scholar 
    19.Bradford, K. J. Applications of hydrothermal time to quantifying and modeling seed germination and dormancy. Weed Sci. 50, 248–260 (2002).Article 
    CAS 

    Google Scholar 
    20.Batlla, D. & Agostinelli, A. M. Thermal regulation of secondary dormancy induction in Polygonum aviculare seeds: A quantitative analysis using the hydrotime model. Seed Sci. Res. 27(3), 231–242 (2017).Article 
    CAS 

    Google Scholar 
    21.Farahinia, P., Sadat-Noori, S. A., Mortazavian, M. M., Soltani, E. & Foghi, B. Hydrotime model analysis of Trachyspermum ammi (L.) Sprague seed germination. J. Appl. Res. Med. Aroma. 5, 88–91 (2017).
    Google Scholar 
    22.Wang, R., Bai, Y. & Tanino, K. Germination of winterfat (Eurotia lanata (Pursh) Moq.) seeds at reduced water potentials: Testing assumptions of hydrothermal time model. Environ. Exp. Bot. 53(1), 49–683 (2005).Article 

    Google Scholar 
    23.Alvarado, V. & Bradford, K. J. A hydrothermal time model explains the cardinal temperatures for seed germination. Plant Cell Environ. 25(8), 1061–1069 (2002).Article 

    Google Scholar 
    24.Bakhshandeh, E. & Gholamhossieni, M. Modelling the effects of water stress and temperature on seed germination of radish and cantaloupe. J. Plant Growth Regul. 38(4), 1402–1411 (2019).Article 
    CAS 

    Google Scholar 
    25.Bakhshandeh, E. & Jamali, M. Population-based threshold models: A reliable tool for describing aged seeds response of rapeseed under salinity and water stress. Environ. Exp. Bot. 176, 104077 (2020).Article 
    CAS 

    Google Scholar 
    26.Leva, P. E. Variación regional de las características agroecológicas y genéticas de Bromus pictus y Poa ligularis en estepas patagónicas (Universidad Nacional de Buenos Aires, 2010).
    Google Scholar 
    27.Palazzesi, L., Barreda, V. & Prieto, A. Análisis evolutivo de la vegetación cenozoica en las provincias de Chubut y Santa Cruz (Argentina) con especial atención en las comunidades herbáceo-arbustivas. Revista del Museo Argentino de Ciencias Naturales nueva serie 5(2), 151–161 (2014).
    Google Scholar 
    28.León, R. J., Bran, D., Collantes, M., Paruelo, J. M. & Soriano, A. Grandes unidades de vegetación de la Patagonia extra andina. Ecol. Austral. 8, 125–144 (1998).
    Google Scholar 
    29.Villalba, R. et al. Large-scale temperature changes across the southern Andes: 20th-century variations in the context of the past 400 years. Clim. Change. 59(1), 177–232 (2003).Article 

    Google Scholar 
    30.Godagnone, R., Bran, D. Inventario integrado de los recursos de la Provincia de Río Negro. (INTA, Argentina, Río Negro, 2009).
    Google Scholar 
    31.Soriano, A. La vegetación del Chubut. Revista Argentina de Agronomía. 17, 30–66 (1950).
    Google Scholar 
    32.Bertiller, M. B. & Coronato, F. Seed bank patterns of Festuca pallescens in semiarid Patagonia (Argentina): A possible limit to bunch reestablishment. Biodivers. Conserv. 3(1), 57–67 (1994).Article 

    Google Scholar 
    33.Defossé, G., Bertiller, M. & Robberecht, R. Germination characteristics of Festuca pallescens, a Patagonian bunchgrass with reclamation potential. Seed Sci. Technol. (Switzerland). 23(3), 715–723 (1995).
    Google Scholar 
    34.Bertiller, M. B., Elissalde, N. O., Rostagno, C. M. & Defossé, G. E. Environmental patterns and plant distribution along a precipitation gradient in western Patagonia. J. Arid Environ. 29, 85–97 (1993).Article 

    Google Scholar 
    35.Bran, D., Ayesa, J., López, C. Regiones ecológicas de Río Negro. Comunicación Técnica No 59. (INTA, EEA Bariloche, 2000).
    Google Scholar 
    36.Oliva, G. et al. Monitoring drylands: The MARAS system. J. Arid Environ. 161, 55–63 (2019).ADS 
    Article 

    Google Scholar 
    37.López, A. S., Marchelli, P., Batlla, D., López, D. R. & Arana, M. V. Seed responses to temperature indicate different germination strategies among Festuca pallescens populations from semi-arid environments in North Patagonia. Agric. For. Meteorol. 272, 81–90 (2019).ADS 
    Article 

    Google Scholar 
    38.Gaitán, J. J. et al. Evaluating the performance of multiple remote sensing indices to predict the spatial variability of ecosystem structure and functioning in Patagonian steppes. Ecol. Indic. 34, 181–191 (2013).Article 

    Google Scholar 
    39.Moore, R. P. Tetrazolium tests for diagnosing causes for seed weaknesses and for predicting and understanding performance. In Proceedings of the Association of Official Seed Analysts. Association of Official Seed Analysts, vol. 56, 70–73. https://www.jstor.org/stable/23432057 (1966).40.Michel, B. E. Evaluation of the water potentials of solutions of polyethylene glycol 8000 both in the absence and presence of other solutes. Plant Physiol. 72(1), 66–70 (1983).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    41.Di Rienzo, J. A., et al. InfoStat versión 2020 & Centro de Transferencia InfoStat. FCA, Universidad Nacional de Córdoba, Argentina. http://www.infostat.com.ar.42.Volis, S., Mendlinger, S. & Ward, D. Adaptive traits of wild barley plants of Mediterranean and desert origin. Oecologia 133(2), 131–138 (2002).ADS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    43.Krichen, K., Mariem, H. B. & Chaieb, M. Ecophysiological requirements on seed germination of a Mediterranean perennial grass (Stipa tenacissima L.) under controlled temperatures and water stress. S. Afr. J. Bot. 94, 210–217 (2014).Article 

    Google Scholar 
    44.Petrů, M. & Tielbörger, K. Germination behaviour of annual plants under changing climatic conditions: Separating local and regional environmental effects. Oecologia 155(4), 717–728 (2008).ADS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    45.Cavallaro, V. et al. Evaluation of variability to drought and saline stress through the germination of different ecotypes of carob (Ceratonia siliqua L.) using a hydrotime model. Ecol. Eng. 95, 557–566 (2016).Article 

    Google Scholar 
    46.Tognetti, P. M., Mazia, N. & Ibáñez, G. Seed local adaptation and seedling plasticity account for Gleditsia triacanthos tree invasion across biomes. Ann. Bot. 124(2), 307–318 (2019).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    47.Allen, P. S., Meyer, S. E. & Khan, M. A. Hydrothermal time as a tool in comparative germination studies. In Seed biology: advances and applications. Proceedings of the Sixth International Workshop on Seeds, Merida, Mexico, 1999. (ed. Black, M., Bradford, J. K. & Vazquez-Ramos, J.) 401–410. https://doi.org/10.1079/9780851994048.0401 (2000).48.Hu, X. W., Fan, Y., Baskin, C. C., Baskin, J. M. & Wang, Y. R. Comparison of the effects of temperature and water potential on seed germination of Fabaceae species from desert and subalpine grassland. Am. J. Bot. 102(5), 649–660 (2015).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    49.Ramírez-Tobías, H., Peña-Valdivia, C., Trejo, C., Aguirre, J. & Vaquera, H. Seed germination of Agave species as influenced by substrate water potential. Biol. Res. 47, 1–9 (2014).Article 
    CAS 

    Google Scholar 
    50.Couso, L. Mecanismos de tolerancia a sequía y sus efectos sobre la habilidad competitiva de pastos de la estepa patagónica (Universidad Nacional de Buenos Aires, 2011).
    Google Scholar 
    51.López, D. R. Una aproximación Estructural-Funcional 1 del Modelo de Estados y Transiciones para el estudio de la dinámica de la vegetación en estepas de Patagonia norte (Universidad Nacional del Comahue, San Carlos de Bariloche, 2011).
    Google Scholar 
    52.Leva, P. E., Aguiar, M. R. & Premoli, A. C. Latitudinal variation of genecological traits in native grasses of Patagonian rangelands. Aust. J. Bot. 61(6), 475–485 (2013).Article 

    Google Scholar 
    53.López, D. R. & Cavallero, L. The role of nurse functional types in seedling recruitment dynamics of alternative states in rangelands. Acta Oecol. 79, 70–80 (2017).ADS 
    Article 

    Google Scholar 
    54.Coronato, F. R. & Bertiller, M. B. Precipitation and landscape related effects on soil moisture in semi-arid rangelands of Patagonia. J. Arid Environ. 34(1), 1–9 (1996).ADS 
    Article 

    Google Scholar 
    55.Coronato, F. R. & Bertiller, B. Climatic controls of soil moisture dynamics in an arid steppe of northern Patagonia, Argentina. Arid Land Res. Manag. 11, 277–288 (1997).
    Google Scholar 
    56.Heber, U., Santarius, K. A. Water stress during freezing. In Water and Plant Life. Ecological Studies (Analysis and Synthesis), vol. 19 (eds. Lange, O. L. et al.) 253–257. https://doi.org/10.1007/978-3-642-66429-8_16 (Springer, Berlin, Heidelberg, 1976).57.López, A. S., López, D. R., Caballe, G., Siffredi, G. L. & Marchelli, P. Local adaptation along a sharp rainfall gradient occurs in a native Patagonian grass, Festuca pallescens, regardless of extensive gene flow. Environ. Exp. Bot. 171, 103933 (2020).Article 
    CAS 

    Google Scholar 
    58.López, A. S., Azpilicueta, M. M., López, D. R., Siffredi, G. L. & Marchelli, P. Phylogenetic relationships and intraspecific diversity of a North Patagonian Fescue: Evidence of differentiation and interspecific introgression at peripheral populations. Folia Geobot. 53, 115–131. https://doi.org/10.1007/s12224-017-9304-1 (2018).Article 

    Google Scholar 
    59.Smith, S., Riley, E., Tiss, J. & Fendenhein, D. Geographical variation in predictive seedling emergence in a perennial desert grass. J. Ecol. 88, 139–149 (2000).Article 

    Google Scholar 
    60.Bohara, H. et al. Influence of poultry litter and biochar on soil water dynamics and nutrient leaching from a very fine sandy loam soil. Soil Tillage Res. 189, 44–51 (2019).Article 

    Google Scholar  More

  • in

    Fivefold higher abundance of ticks (Acari: Ixodida) on the European roe deer (Capreolus capreolus L.) forest than field ecotypes

    1.Lane, R.S. Ekosystemy leśne Kalifornii jako obszary podwyższonego ryzyka zakażenia krętkami boreliozy z Lyme in Vademecum wybranych chorób odzwierzęcych w środowisku leśnym (ed. Skorupski, M., Wierzbicka, A.) 9–22 (Katedra Łowiectwa i Ochrony Lasu. Poznań, Poland, 2012).2.Siuda, K. Kleszcze Polski (Acari: Ixodida). cz. II Systematyka i rozmieszczenie. (Wydawnictwo Naukowe PWN, Warszawa. Poznań, Poland, 1993).3.Piesman, J. & Gern, L. Lyme borreliosis in Europe and North America. Parasitology 129, 191–220. https://doi.org/10.1017/S0031182003004694 (2004).Article 

    Google Scholar 
    4.ECDC. European Centre for Disease Prevention and Control: Second Expert Consultation on Tick-borne Diseases with Emphasis on Lyme Borreliosis and Tick-borne Encephalitis. http://www.ecdc.europa.eu/en/publications/publications/tick-borne-diseases-meeting-report.pdf (2012).5.Welc-Falęciak, R. et al. Co-infection and genetic diversity of tick-borne pathogens in roe deer from Poland. Vector-Borne Zoonotic Dis 13(5), 277–288. https://doi.org/10.1371/journal.pone.000433610.1089/vbz.2012.1136 (2013).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    6.Welc-Falęciak, R. et al. Rickettsiaceae and Anaplasmataceae infections in Ixodes ricinus ticks from urban and natural forested areas of Poland. Parasites Vectors 7, 121. https://doi.org/10.1371/journal.pone.000433610.1186/1756-3305-7-121 (2014).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    7.ECDC. European Centre for Disease Prevention and Control: Lyme Borreliosisin Europe. http://www.ecdc.europa.eu/en/healthtopics/vectors/world-health-day-2014/Documents/factsheet-lyme-borreliosis.pdf (2014).8.Rizzoli, A. et al. Lyme borreliosis in Europe. Euro Surveill. 16(27), 19906. http://www.eurosurveillance.org/ViewArticle.aspx? (2011).9.Burbaite, L. & Csányi, S. Roe deer population and harvest changes in Europe. Est. J. Ecol. 58(3), 169–180. https://doi.org/10.3176/eco.2009.3.02 (2009).Article 

    Google Scholar 
    10.Rizzoli, A., Hauffe, H. C., Tagliapietra, V., Netelerm, M. & Rosà, R. Forest structure and roe deer abundance predict tick-borne encephalitis risk in Italy. PLoS ONE 4(2), e4336. https://doi.org/10.1371/journal.pone.0004336 (2009).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    11.Jaenson, T. G. T., Jaenson, D. G. E., Eisen, L., Petersson, E. & Lindgren, E. Changes in the geographical distribution and abundance of the tick Ixodes ricinus during the past 30 years in Sweden. Parasites Vectors 5, 8 (2012).Article 

    Google Scholar 
    12.Andersen, N. S. et al. Reduction in human Lyme neuroborreliosis associated with a major epidemic among roe deer. Ticks Tick-borne Dis. 9, 379–381. https://doi.org/10.1016/j.ttbdis.2017.12.002 (2018).Article 
    PubMed 

    Google Scholar 
    13.Carpi, G., Cagnacci, F., Neteler, M. & Rizzoli, A. Tick infestation on roe deer in relation to geographic and remotely sensed climatic variables in a tick-borne encephalitis endemic area. Epidemiol. Infect. 136, 1416–1424. https://doi.org/10.1017/S0950268807000039 (2008).CAS 
    Article 
    PubMed 

    Google Scholar 
    14.Zejda, J. & Bauerova, Z. Home range of field roe deer. Acta Sc. Nat. 19, 1–43 (1985).
    Google Scholar 
    15.Cibien, C., Bideau, E., Boisaubert, B. & Maublanc, M. L. Influence of habitat characteristic on winter social organization in field roe deer. Acta Theriol. 34, 219–226 (1989).Article 

    Google Scholar 
    16.Pielowski, Z. Sarna. (Wydawnictwo Świat, Warszawa, Poland, 1999).17.Siuda, K. Kleszcze (Acari: Ixodida) Polski. Część I. Zagadnienia ogólne. (Wydawnictwo Naukowe PWN, Warszawa, Poland, 1991).18.Kamieniarz, R. Struktura krajobrazu rolniczego a funkcjonowanie populacji sarny polnej. Rozprawy naukowe Uniwersytetu Przyrodniczego w Poznaniu, 463. (Poznań, Poland, 2013).19.Kadulski, S. Występowanie stawonogów pasożytniczych na łownych Lagomorpha i Artiodactyla Polski—próba syntezy. Zeszyty Naukowe Uniwersytet Gdański. Rozprawy i monografie. (Wydawnictwo Uniwersytet Gdański. Gdańsk, Poland, 1989).20.Sugar, L. Health status and parasitic infections in three Hungarian populations of roe deer Capreolus capreolus. In Global trends in Wildlife Management. 18th IUGB Congress (ed. Bobek, B., Perzanowski, K. and Regelin, W.L.) 269–271. (Jagiellonian University Kraków, Poland, Wydawnictwo Świat Press, Kraków-Warszawa, Poland, 1991).21.Jędrysiak, D. Stawonogi pasożytnicze sarny europejskiej Capreolus capreolus (L.) z terenów Pojezierzy Południowobałtyckich. PhD thesis, (Uniwersytet Gdański, Gdańsk, Poland, 2006).22.Kiffner, C., Lӧdige, C., Alings, M., Vor, T. & Rühe, F. Abundance estimation of Ixodes ricinus ticks (Acari: Ixodidae) on roe deer (Capreolus capreolus). Exp. Appl. Acarol. 52, 73–84. https://doi.org/10.1007/s10493-010-9341-4 (2010).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    23.Kiffner, C., Lӧdige, C., Alings, M., Vor, T. & Rühe, F. Attachment site selection of ticks on roe deer. Exp. Appl. Acarol. 53, 79–84. https://doi.org/10.1007/s10493-010-9378-4 (2011).CAS 
    Article 
    PubMed 

    Google Scholar 
    24.Tälleklint, L. & Jaenson, T. G. T. Infestation of mammals by Ixodes ricinus ticks (Acari: Ixodidae) in south-central Sweden. Exp. Appl. Acarol. 21, 755–771. https://doi.org/10.1371/journal.pone.000433610.1023/A%3A1018473122070 (1997).Article 
    PubMed 

    Google Scholar 
    25.Vázquez, L. et al. Tick infestation (Acari: Ixodidae) in roe deer (Capreolus capreolus) from northwestern Spain: population dynamics and risk stratification. Exp. Appl. Acarol. 53, 399–409. https://doi.org/10.1371/journal.pone.000433610.1007/s10493-010-9403-7 (2011).Article 
    PubMed 

    Google Scholar 
    26.Adamska, M. Infestation of game animals from north−western Poland by common tick (Ixodes ricinus) (Acari. Ixododa. Ixodidae). Ann. Parasitol. 54(1), 31–36 (2008).
    Google Scholar 
    27.Michalik, J. et al. Roe deer (Capreolus capreolus): important hosts for Ixodes ricinus reproduction in forest ecosystems of the Wielkopolska province, west-central Poland. In Stawonogi. Oddziaływanie na żywiciela (ed. Buczek, A. & Błaszak, C.) 87–91 (Wydawnictwo Akapit Lublin, Poland, 2008).28.Vor, T., Kiffner, C., Hagedorn, P., Nidrig, M. & Rühe, F. Tick burden on European roe deer (Capreolus capreolus). Exp. Appl. Acarol. 51, 405–417. https://doi.org/10.1371/journal.pone.000433610.1007/s10493-010-9337-0 (2010).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    29.Ivanović, I. et al. Hard tick (Acari: Ixodidae) co-infestation of roe deer (Capreolus capreolus Linnaeus, 1758) in vojvodina hunting resort (Serbia). Sci. Pap. Ser. D. Anim Sci LIX, 326–329 (2016).
    Google Scholar 
    30.Dominguez, G. North Spain (Burgos) wild mammals ectoparasites. Parasite 11, 267–272. https://doi.org/10.1051/parasite/2004113267 (2004).CAS 
    Article 
    PubMed 

    Google Scholar 
    31.Liebisch, A.& Walter, G. Untersuchungen von Zecken bei Haus- und Wildtieren in Deutschland. Zum Vorkommen und zur Biologie der Igelzecke (Ixodes hexagonus) und der Fuchszecke (Ixodes canisuga). Deut. Tierärztl. Woch. 93, 447–450 (1986).32.Król, N. et al. Tick burden on European roe deer (Capreolus capreolus) from Saxony, Germany, and detection of tick-borne encephalitis virus in attached ticks. Parasitol. Res. 119, 1387–1392. https://doi.org/10.1016/j.ttbdis.2014.06.007 (2020).Article 
    PubMed 

    Google Scholar 
    33.Plan urządzania lasu dla nadleśnictwa Podanin, obręby: Margonin. Podanin. Na lata 2012–2021. (BULiGL oddz. w Szczecinku, Poland, 2012).34.Dudziński, M. & Dudziński, J. Studium uwarunkowań i kierunków zagospodarowania przestrzennego gminy Czempiń. Załącznik nr 1 do Uchwały Rady Miejskiej. (Czempiń, 2018).35.Rozporządzenia Ministra Środowiska z dnia marca 2005 r. w sprawie określenia okresów polowań na zwierzęta łowne. Dz. U. Nr 48, poz. 459 (2005).36.R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna Ausria (2021). https://www.R-project.org.37.Brooks, M.E. at al.glmmTMB Balances Speed and Flexibility Among Packages for Zero-inflated Generalized Linear Mixed Modeling. The R Journal 9(2), 378–400 https://doi.org/10.32614/RJ-2017-066 (2017)38.Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48. https://doi.org/10.18637/jss.v067.i01 (2015).39.Kuznetsova, A., Brockhoff, P. B. & Christensen, R. H. B. (2017) lmerTest: Tests in Linear Mixed Effects Models. J. Stat. Softw. 82,13. https://doi.org/10.18637/jss.v082.i13 (2017).40.Lenth, R. emmeans: Estimated Marginal Means, aka Least-Squares Means. R package version 1.3.5.1. https://CRAN.R-project.org/package=emmeans (2019). More

  • in

    Contrasting metabolic strategies of two co-occurring deep-sea octocorals

    1.Watling, L., France, S. C., Pante, E. & Simpson, A. Biology of Deep-Water Octocorals. Advances in Marine Biology Vol. 60 (Elsevier, Amsterdam, 2011).
    Google Scholar 
    2.Sánchez, J. A. Diversity and Evolution of Octocoral Animal Forests at Both Sides of Tropical America. in Marine Animal Forests (ed. Rossi, S., Bramanti, L., Gori, A., & Orejas, C) 1–33 (Springer, 2016).3.Rossi, S., Bramanti, L., Gori, A. and Orejas, C. Marine animal forests: the ecology of benthic biodiversity hotspots. 1-1366. (Springer International Publishing, 2017)4.Cairns, S. D. Studies on western Atlantic Octocorallia (Gorgonacea: Primnoidae). Part 8: New records of Primnoidae from the New England and Corner Rise Seamounts. Proceedings of the Biological Society of Washington120(2), 243–263 (2007).5.Freiwald, A. and Roberts, J.M. Cold-water corals and ecosystems. (Springer, 2005)6.Buhl-Mortensen, L. & Buhl-Mortensen, P. Cold Temperate Coral Habitats. in Corals in a Changing World (2018).7.Braga-Henriques, A. et al. Diversity, distribution and spatial structure of the cold-water coral fauna of the Azores (NE Atlantic). Biogeosciences 10, 4009–4036 (2013).ADS 
    Article 

    Google Scholar 
    8.Íris, S., Andre, F., Filipe, M. P., Gui, M. & Marina, C.-S. Census of Octocorallia (Cnidaria: Anthozoa) of the Azores (NE Atlantic) with a nomenclature update. Zootaxa 4550, 451 (2019).PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    9.Tempera, F. et al. Mapping condor seamount seafloor environment and associated biological assemblages (Azores, NE Atlantic). Seafloor Geomorphol. Benthic Habitat https://doi.org/10.1016/B978-0-12-385140-6.00059-1 (2012).Article 

    Google Scholar 
    10.Andrews, A., Stone, R., Lundstrom, C. & DeVogelaere, A. Growth rate and age determination of bamboo corals from the northeastern Pacific Ocean using refined 210Pb dating. Mar. Ecol. Prog. Ser. 397, 173–185 (2009).ADS 
    CAS 
    Article 

    Google Scholar 
    11.Neves, B. D. M., Edinger, E., Layne, G. D. & Wareham, V. E. Decadal longevity and slow growth rates in the deep-water sea pen Halipteris finmarchica (Sars, 1851) (Octocorallia: Pennatulacea): implications for vulnerability and recovery from anthropogenic disturbance. Hydrobiologia 759, 147–170 (2015).CAS 
    Article 

    Google Scholar 
    12.FAO. International guidelines for the management of deep-sea fisheries in the High Seas. (2009).13.OSPAR. Background document for coral gardens, Biodiversity Series, Publication Number: 15486/2010. (2010).14.Kim, K. & Lasker, H. R. Allometry of resource capture in colonial cnidarians and constraints on modular growth. Funct. Ecol. 12, 646–654 (1998).Article 

    Google Scholar 
    15.Gori, A. et al. Effects of food availability on the sexual reproduction and biochemical composition of the Mediterranean gorgonian Paramuricea clavata. J. Exp. Mar. Bio. Ecol. 444, 38–45 (2013).Article 

    Google Scholar 
    16.Coma, R. & Ribes, M. Seasonal energetic constraints in Mediterranean benthic suspension feeders: effects at different levels of ecological organization. Oikos 101, 205–215 (2003).Article 

    Google Scholar 
    17.Nisbet, R. M., Muller, E. B., Lika, K. & Kooijman, S. A. L. M. From molecules to ecosystems through dynamic energy budget models. J. Anim. Ecol. 69, 913–926 (2008).Article 

    Google Scholar 
    18.Sebens, K., Sarà, G. & Nishizaki, M. Energetics, Particle Capture, and Growth Dynamics of Benthic Suspension Feeders. in Marine Animal Forests 813–854 (Springer, 2017).19.Ribes, M., Coma, R. & Gili, J. M. Heterogeneous feeding in benthic suspension feeders: The natural diet and grazing rate of the temperate gorgonian Paramuricea clavata (Cnidaria: Octocorallia) over a year cycle. Mar. Ecol. Prog. Ser. 183, 125–137 (1999).ADS 
    Article 

    Google Scholar 
    20.Orejas, C., Gili, J. M. & Arntz, W. Role of small-plankton communities in the diet of two Antarctic octocorals (Primnoisis antarctica and Primnoella sp.). Mar. Ecol. Prog. Ser. 250, 105–116 (2003).ADS 
    Article 

    Google Scholar 
    21.Ribes, M., Coma, R. & Rossi, S. Natural feeding of the temperate asymbiotic octocoral-gorgonian Leptogorgia sarmentosa (Cnidaria: Octocorallia). Mar. Ecol. Prog. Ser. 254, 141–150 (2003).ADS 
    CAS 
    Article 

    Google Scholar 
    22.Cocito, S. et al. Nutrient acquisition in four Mediterranean gorgonian species. Mar. Ecol. Prog. Ser. 473, 179–188 (2013).ADS 
    CAS 
    Article 

    Google Scholar 
    23.Leal, M. C. et al. Temporal changes in the trophic ecology of the asymbiotic gorgonian Leptogorgia virgulata. Mar. Biol. 161, 2191–2197 (2014).Article 

    Google Scholar 
    24.Fabricius, K. E., Benayahu, Y. & Genin, A. Herbivory in Asymbiotic Soft Corals. Science (80-) 268, 90–92 (1995).ADS 
    CAS 
    Article 

    Google Scholar 
    25.Rossi, S., Ribes, M., Coma, R. & Gili, J. M. Temporal variability in Zooplankton prey capture rate of the passive suspension feeder Leptogorgia sarmentosa (Cnidaria: Octocorallia), a case study. Mar. Biol. 144, 89–99 (2004).Article 

    Google Scholar 
    26.Coma, R., Llorente-Llurba, E., Serrano, E., Gili, J. M. & Ribes, M. Natural heterotrophic feeding by a temperate octocoral with symbiotic zooxanthellae: a contribution to understanding the mechanisms of die-off events. Coral Reefs 34, 549–560 (2015).ADS 
    Article 

    Google Scholar 
    27.Orejas, C., Gili, J., López-González, P. & Arntz, W. Feeding strategies and diet composition of four Antarctic cnidarian species. Polar Biol. 24, 620–627 (2001).Article 

    Google Scholar 
    28.Sherwood, O. A., Jamieson, R. E., Edinger, E. N. & Wareham, V. E. Stable C and N isotopic composition of cold-water corals from the Newfoundland and Labrador continental slope: Examination of trophic, depth and spatial effects . Deep. Res. Part I Oceanogr. Res. Pap. 55, 1392–1402 (2008).ADS 
    CAS 
    Article 

    Google Scholar 
    29.Kiriakoulakis, K. et al. Lipids and nitrogen isotopes of two deep-water corals from the North-East Atlantic: initial results and implications for their nutrition. in Cold-Water Corals and Ecosystems 715–729 (Springer, 2005).30.Naumann, M. S., Tolosa, I., Taviani, M., Grover, R. & Ferrier-Pagès, C. Trophic ecology of two cold-water coral species from the Mediterranean Sea revealed by lipid biomarkers and compound-specific isotope analyses. Coral Reefs 34, 1165–1175 (2015).ADS 
    Article 

    Google Scholar 
    31.Naumann, M. S., Orejas, C., Wild, C. & Ferrier-Pagès, C. First evidence for zooplankton feeding sustaining key physiological processes in a scleractinian cold-water coral. J. Exp. Biol. 214, 3570–3576 (2011).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    32.Sherwood, O. et al. Stable isotopic composition of deep-sea gorgonian corals Primnoa spp.: a new archive of surface processes. Mar. Ecol. Prog. Ser. 301, 135–148 (2005).ADS 
    CAS 
    Article 

    Google Scholar 
    33.Imbs, A. B., Demidkova, D. A. & Dautova, T. N. Lipids and fatty acids of cold-water soft corals and hydrocorals: a comparison with tropical species and implications for coral nutrition. Mar. Biol. 163, 202 (2016).Article 
    CAS 

    Google Scholar 
    34.Salvo, F., Hamoutene, D., Hayes, V. E. W., Edinger, E. N. & Parrish, C. C. Investigation of trophic ecology in Newfoundland cold-water deep-sea corals using lipid class and fatty acid analyses. Coral Reefs 37, 157–171 (2018).ADS 
    Article 

    Google Scholar 
    35.Davies, A. J. et al. Downwelling and deep-water bottom currents as food supply mechanisms to the cold-water coral Lophelia pertusa (Scleractinia) at the Mingulay Reef Complex. Limnol. Oceanogr. 54, 620–629 (2009).ADS 
    Article 

    Google Scholar 
    36.Agusti, S. et al. Ubiquitous healthy diatoms in the deep sea confirm deep carbon injection by the biological pump. Nat. Commun. 6, 1–8 (2015).Article 
    CAS 

    Google Scholar 
    37.Fabricius, K. E., Genin, A. & Benayahu, Y. Flow-dependent herbivory and growth in zoxanthellae-free soft corals. Limnol. Oceanogr. 40, 1290–1301 (1995).ADS 
    Article 

    Google Scholar 
    38.Widdig, A. & Schlichter, D. Phytoplankton: a significant trophic source for soft corals?. Helgol. Mar. Res. 55, 198–211 (2001).ADS 
    Article 

    Google Scholar 
    39.Colaço, A., Giacomello, E., Porteiro, F. & Menezes, G. M. Trophodynamic studies on the Condor seamount (Azores, Portugal, North Atlantic) . Deep. Res. Part II Top. Stud. Oceanogr. 98, 178–189 (2013).ADS 
    Article 

    Google Scholar 
    40.Addamo, A. M. et al. Merging scleractinian genera: the overwhelming genetic similarity between solitary Desmophyllum and colonial Lophelia. BMC Evol. Biol. https://doi.org/10.1186/s12862-016-0654-8 (2016).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    41.Mueller, C. E., Larsson, A. I., Veuger, B., Middelburg, J. J. & van Oevelen, D. Opportunistic feeding on various organic food sources by the cold-water coral Lophelia pertusa. Biogeosciences 11, 123–133 (2014).ADS 
    Article 

    Google Scholar 
    42.Roushdy, H. & Hansen, V. Filtration of phytoplankton by the octocoral Alcyonium digitatum. Nature 190, 649–650 (1961).ADS 
    Article 

    Google Scholar 
    43.Sorokin, Y. Biomass, metabolic rates and feeding of some common reef zoantharians and octocorals. Aust. J. Mar. Freshw. Resour. 42, 729–741 (1991).Article 

    Google Scholar 
    44.Seemann, J. The use of 13C and 15N isotope labeling techniques to assess heterotrophy of corals. J. Exp. Mar. Biol. Ecol. 442, 88–95 (2013).CAS 
    Article 

    Google Scholar 
    45.Orejas, C. et al. The effect of flow speed and food size on the capture efficiency and feeding behaviour of the cold-water coral Lophelia pertusa. J. Exp. Mar. Biol. Ecol. 481, 34–40 (2016).Article 

    Google Scholar 
    46.Carmo, V. et al. Variability of zooplankton communities at Condor seamount and surrounding areas, Azores (NE Atlantic) . Deep. Sea Res. Part II Top. Stud. Oceanogr. 98, 63–74 (2013).ADS 
    Article 

    Google Scholar 
    47.Gori, A., Grover, R., Orejas, C., Sikorski, S. & Ferrier-Pagès, C. Uptake of dissolved free amino acids by four cold-water coral species from the Mediterranean Sea . Deep. Sea Res. Part II Top. Stud. Oceanogr. 99, 42–50 (2014).ADS 
    CAS 
    Article 

    Google Scholar 
    48.Sweetman, A. K. et al. Major impacts of climate change on deep-sea benthic ecosystems. Elementa Science of the Anthropocene vol. 5 (2017).49.Migné, A. & Davoult, D. Experimental nutrition in the soft coral Alcyonium digitatum (Cnidaria: Octocorallia): Removal rate of phytoplankton and zooplankton. Cah. Biol. Mar. 43, 9–16 (2002).
    Google Scholar 
    50.Sebens, K. P. & Koehl, M. A. R. Predation on zooplankton by the benthic anthozoans Alcyonium siderium (Alcyonacea) and Metridium senile (Actiniaria) in the New England subtidal. Mar. Biol. 81, 255–271 (1984).Article 

    Google Scholar 
    51.Gili, J.-M., Coma, R., Orejas, C., López-González, P. & Zabala, M. Are Antarctic suspension-feeding communities different from those elsewhere in the world?. Polar Biol. 24, 473–485 (2001).Article 

    Google Scholar 
    52.Rossi, S. et al. Temporal variation in protein, carbohydrate, and lipid concentrations in Paramuricea clavata (Anthozoa, Octocorallia): evidence for summer-autumn feeding constraints. Mar. Biol. 149, 643–651 (2006).CAS 
    Article 

    Google Scholar 
    53.Coma, R., Ribes, M., Gili, J.-M. & Zabala, M. Seasonality in coastal benthic ecosystems. Trends Ecol. Evol. 15, 448–453 (2000).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    54.Bythell, J. C. & Wild, C. Biology and ecology of coral mucus release. J. Exp. Mar. Biol. Ecol. 408, 88–93 (2011).Article 

    Google Scholar 
    55.Brooke, S., Holmes, M. & Young, C. Sediment tolerance of two different morphotypes of the deep-sea coral Lophelia pertusa from the Gulf of Mexico. Mar. Ecol. Prog. Ser. 390, 137–144 (2009).ADS 
    Article 

    Google Scholar 
    56.Larsson, A. I., van Oevelen, D., Purser, A. & Thomsen, L. Tolerance to long-term exposure of suspended benthic sediments and drill cuttings in the cold-water coral Lophelia pertusa. Mar. Pollut. Bull. 70, 176–188 (2013).CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 
    57.Ragnarsson, S. Á. et al. The impact of anthropogenic activity on cold-water corals. in Marine Animal Forests: The Ecology of Benthic Biodiversity Hotspots 989–1023 (Springer International Publishing, 2017). https://doi.org/10.1007/978-3-319-21012-4_27.58.Rix, L. et al. Coral mucus fuels the sponge loop in warm- and cold-water coral reef ecosystems. Sci. Rep. 6, 18715 (2016).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    59.Lampert, W. Release of dissolved organic carbon by grazing zooplankton. Limnol. Oceanogr. 23, 831–834 (1978).ADS 
    CAS 
    Article 

    Google Scholar 
    60.Moller, E. F. Sloppy feeding in marine copepods: prey-size-dependent production of dissolved organic carbon. J. Plankton Res. 27, 27–35 (2004).Article 
    CAS 

    Google Scholar 
    61.Burton, T., Killen, S. S., Armstrong, J. D. & Metcalfe, N. B. What causes intraspecific variation in resting metabolic rate and what are its ecological consequences?. Proc. R. Soc. B Biol. Sci. 278, 3465–3473 (2011).CAS 
    Article 

    Google Scholar 
    62.Burgess, S. C. et al. Metabolic scaling in modular animals. Invertebr. Biol. 136, 456–472 (2017).Article 

    Google Scholar 
    63.Maier, S. R. et al. Survival under conditions of variable food availability: Resource utilization and storage in the cold-water coral Lophelia pertusa. Limnol. Oceanogr. 64, 1651–1671 (2019).ADS 
    CAS 
    Article 

    Google Scholar 
    64.Okie, J. G. et al. Niche and metabolic principles explain patterns of diversity and distribution: theory and a case study with soil bacterial communities. Proc. R. Soc. B Biol. Sci. 282, 20142630 (2015).Article 

    Google Scholar 
    65.van Oevelen, D. et al. The cold-water coral community as hotspot of carbon cycling on continental margins: a food-web analysis from Rockall Bank (northeast Atlantic). Limnol. Oceanogr. 54, 1829–1844 (2009).ADS 
    Article 

    Google Scholar 
    66.Cathalot, C. et al. Cold-water coral reefs and adjacent sponge grounds: hotspots of benthic respiration and organic carbon cycling in the deep sea. Front. Mar. Sci. 2, 37 (2015).Article 

    Google Scholar 
    67.Coppari, M., Zanella, C. & Rossi, S. The importance of coastal gorgonians in the blue carbon budget. Sci. Rep. 9, 1–12 (2019).CAS 
    Article 

    Google Scholar 
    68.Moller, E. F. & Nielsen, T. G. Production of bacterial substrate by marine copepods: effect of phytoplankton biomass and cell size. J. Plankton Res. 23, 527–536 (2001).Article 

    Google Scholar 
    69.Titelman, J., Riemann, L., Holmfeldt, K. & Nilsen, T. Copepod feeding stimulates bacterioplankton activities in a low phosphorus system. Aquat. Biol. 2, 131–141 (2008).Article 

    Google Scholar 
    70.Violle, C. & Jiang, L. Towards a trait-based quantification of species niche. J. Plant Ecol. 2, 87–93 (2009).Article 

    Google Scholar 
    71.Yesson, C. et al. Global habitat suitability of cold-water octocorals. J. Biogeogr. 39, 1278–1292 (2012).Article 

    Google Scholar 
    72.Kearney, M., Simpson, S. J., Raubenheimer, D. & Helmuth, B. Modelling the ecological niche from functional traits. Philos. Trans. R. Soc. B Biol. Sci. 365, 3469–3483 (2010).Article 

    Google Scholar 
    73.Violle, C. et al. Let the concept of trait be functional!. Oikos 116, 882–892 (2007).Article 

    Google Scholar 
    74.Evans, T. G., Diamond, S. E. & Kelly, M. W. Mechanistic species distribution modelling as a link between physiology and conservation. Conservation Physiology 3, cov056 (2015).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    75.Johnson, J. Y. Description of a new species of flexible coral belonging to the genus Juncella, obtained at Madeira. Proc. Zool. Soc. London 505–506 (1863).76.Weinberg, S. & Grasshoff, M. Gorgonias. El Mar Mediterraneo. Fauna, Flora, Ecologia. II/1. Guia Sistematica y de Identificacion. (Ediciones Omega, 2003).77.Carpine, C. & Grasshoff, M. Les gorgonaires de la Méditerranée. Bull. l’Institut Océanographique 1–140 (1975).78.Brito, A. & Ocaña, O. Corales de las Islas Canarias. (2004).79.Cau, A. et al. Deepwater corals biodiversity along roche du large ecosystems with different habitat complexity along the south Sardinia continental margin (CW Mediterranean Sea). Mar. Biol. 162, 1865–1878 (2015).Article 

    Google Scholar 
    80.Tempera, F. et al. Mapping the Condor seamount seafloor environment and associated biological assemblages (Azores, NE Atlantic). In Seafloor geomorphology as benthic habitat: geohab atlas of seafloor geomorphic features and benthic habitats (eds Harris, P. T. & Baker, E. K.) 807–818 (Elsevier, Amsterdam, 2012).
    Google Scholar 
    81.Santos, M. et al. Phytoplankton variability and oceanographic conditions at Condor seamount, Azores (NE Atlantic) . Deep. Sea Res. Part II Top. Stud. Oceanogr. 98, 52–62 (2013).ADS 
    Article 

    Google Scholar 
    82.Sorokin, Y. I. On the feeding of some scleractinian corals with bacteria and dissolved organic matter. Limnol. Oceanogr. 18, 380–386 (1973).ADS 
    CAS 
    Article 

    Google Scholar 
    83.Maier, S. R. et al. Survival under conditions of variable food availability: Resource utilization and storage in the cold-water coral Lophelia pertusa. Limnol. Oceanogr. https://doi.org/10.1002/lno.11142 (2019).Article 

    Google Scholar 
    84.Zuur, A. F., Ieno, E. N. & Elphick, C. S. A protocol for data exploration to avoid common statistical problems. Methods Ecol. Evol. 1, 3–14 (2010).Article 

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

    Google Scholar 
    86.Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. https://doi.org/10.18637/jss.v067.i01 (2015).Article 

    Google Scholar 
    87.Pinheiro, J., Bates, D., DebRoy, S., Sarkar, D. & R Core Team. nlme: linear and Nonlinear mixed effects models. R package version 3.1–140. (2019). More

  • in

    Don’t forget subterranean ecosystems in climate change agendas

    1.Nat. Clim. Change 9, 491 (2019).2.Arneth, A. et al. Proc. Natl Acad. Sci. USA 117, 30882–30891 (2020).CAS 
    Article 

    Google Scholar 
    3.Dinerstein, E. et al. Sci. Adv. 6, eabb2824 (2020).Article 

    Google Scholar 
    4.Mammola, S. et al. BioScience 69, 641–650 (2019).Article 

    Google Scholar 
    5.Ficetola, G. F., Canedoli, C. & Stoch, F. Conserv. Biol. 33, 214–216 (2019).Article 

    Google Scholar 
    6.Chen, Z. et al. World Karst Aquifer Map (WHYMAP WOKAM) (BGR, IAH, KIT & UNESCO, 2017); https://doi.org/10.25928/b2.21_sfkq-r4067.World Database on Protected Areas (IUCN & UNEP-WCMC, 2016).8.Mammola, S. et al. Anthr. Rev. 6, 98–116 (2019).
    Google Scholar 
    9.Pallarés, S. et al. Anim. Conserv. https://doi.org/10.1111/acv.12654 (2021).10.Castaño-Sánchez, A., Hose, G. C. & Reboleira, A. S. P. Sci. Rep. 10, 12328 (2020).Article 

    Google Scholar 
    11.Taylor, R. G. et al. Nat. Clim. Change 3, 322–329 (2012).Article 

    Google Scholar 
    12.Griebler, C. & Avramov, M. Freshw. Sci. 34, 355–367 (2015).Article 

    Google Scholar 
    13.Gleeson, T., Wada, Y., Bierkens, M. F. P. & van Beek, L. P. H. Nature 488, 197–200 (2012).CAS 
    Article 

    Google Scholar 
    14.Wu, W. Y. et al. Nat. Commun. 11, 3710 (2020).CAS 
    Article 

    Google Scholar 
    15.Famiglietti, J. S. Nat. Clim. Change 4, 945–948 (2014).Article 

    Google Scholar 
    16.Frick, W. F. et al. Ann. N. Y. Acad. Sci. 1469, 5–25 (2020).Article 

    Google Scholar 
    17.Browning, E. et al. Mamm. Rev. https://doi.org/10.1111/mam.12239 (2021).18.Deharveng, L. & Bedos, A. In Cave Ecology 107–172 (Springer, 2019).19.Stein, H. et al. Sci. Rep. 2, 673 (2012).Article 

    Google Scholar 
    20.Culver, D. C. & Holsinger, J. R. Nat. Speleol. Soc. Bull. 54, 79–80 (1992).
    Google Scholar 
    21.Magnabosco, C. et al. Nat. Geosci. 11, 707–717 (2018).CAS 
    Article 

    Google Scholar  More