Advertisement

Polar Biology

, Volume 41, Issue 8, pp 1531–1545 | Cite as

The detritus-based microbial-invertebrate food web contributes disproportionately to carbon and nitrogen cycling in the Arctic

  • Amanda M. Koltz
  • Ashley Asmus
  • Laura Gough
  • Yamina Pressler
  • John C. Moore
Original Paper

Abstract

The Arctic is the world’s largest reservoir of soil organic carbon and understanding biogeochemical cycling in this region is critical due to the potential feedbacks on climate. However, our knowledge of carbon (C) and nitrogen (N) cycling in the Arctic is incomplete, as studies have focused on plants, detritus, and microbes but largely ignored their consumers. Here we construct a comprehensive Arctic food web based on functional groups of microbes (e.g., bacteria and fungi), protozoa, and invertebrates (community hereafter referred to as the invertebrate food web) residing in the soil, on the soil surface and within the plant canopy from an area of moist acidic tundra in northern Alaska. We used an energetic food web modeling framework to estimate C flow through the food web and group-specific rates of C and N cycling. We found that 99.6% of C processed by the invertebrate food web is derived from detrital resources (aka ‘brown’ energy channel), while 0.06% comes from the consumption of live plants (aka ‘green’ energy channel). This pattern is primarily driven by fungi, fungivorous invertebrates, and their predators within the soil and surface-dwelling communities (aka the fungal energy channel). Similarly, >99% of direct invertebrate contributions to C and N cycling originate from soil- and surface-dwelling microbes and their immediate consumers. Our findings demonstrate that invertebrates from within the fungal energy channel are major drivers of C and N cycling and that changes to their structure and composition are likely to impact nutrient dynamics within tundra ecosystems.

Keywords

Food web structure Energetic food web model Nutrient cycling C mineralization N mineralization Invertebrate Arctic Tundra 

Notes

Acknowledgements

We thank Gaius R. Shaver, Jim Laundre, and the Arctic LTER for support and coordinating transportation to the study area. We are also grateful to Greg Selby and Rod Simpson for assisting with the sampling and processing of soil samples and Sarah Meierotto, Kiki Contreras, Kathryn Daly, and PolarTREC teacher Nell Kemp for assistance processing the aboveground arthropod samples. Logistic support was provided by Toolik Field Station, University of Alaska, Fairbanks, USA and CH2MHILL; Fig. 1 was generated by the Toolik GIS Office. Funding for this research was provided by the U.S. National Science Foundation (OPP-0908602, 0909507, 0909441, and DEB 1026843 and 1210704), CREOi, and the National Geographic Committee for Research and Exploration.

Supplementary material

300_2017_2201_MOESM1_ESM.pdf (89 kb)
Supplementary material 1 (PDF 89 kb). Taxon rarefaction curve for surface and canopy communities sampled in July 2013 near Toolik Lake, Alaska. A total of 33 taxa were sampled; Estimates of extrapolated species richness suggest that the surface and canopy community actually contains 40 ± 7.1 taxa, indicating that we were able to capture roughly 82.5% of the aboveground arthropod community with our sampling methods and at this level of taxonomic resolution
300_2017_2201_MOESM2_ESM.pdf (42 kb)
Supplementary material 2 (PDF 41 kb) Designations of functional feeding and trophic groups for all arthropod families sampled from canopy and surface habitats. Trophic groups were used in reporting the biomass and trophic structure of each habitat type (see main text; Fig. 2) and functional feeding groups were used in the energetics-based food web model (Fig. 3; Online Resource 3)
300_2017_2201_MOESM3_ESM.xls (45 kb)
Supplementary material 3 (XLS 45 kb) Parameters used to initialize the energetics-based food web model and the simulated C flow rates between all consumer functional feeding groups within the invertebrate tundra food web. Included are estimates of the C:N ratio, death rate (DR), assimilation efficiency (AE), production efficiency (PE), and biomass (mean and standard deviation) for each functional feeding group. We assumed that detritus, diatoms, lichen, moss, live plant biomass (roots, vascular plants, pollen), and blood were not limiting resources and thus assigned theoretical values of 2,500,000 g C m−2 to detritus, 300,000 mg C m−2 to diatoms, and 300 mg C m−2 to all others. Estimates of C flow rates (mg C m−2 year−1) are from the complete (sampled) food web with assigned feeding preferences (see methods in main text). Zeroes denote no consumptive relationship between groups. Cross-habitat feeding relationships (e.g., between soil- and surface-dwelling organisms or surface- and canopy-dwelling organisms) are indicated by boldface type
300_2017_2201_MOESM4_ESM.xlsx (25 kb)
Supplementary material 4 (XLSX 25 kb). Summarized model results from the complete, sampled food web and all food web manipulations. Food web manipulations included not specifying feeding preferences and removing each sampled functional feeding group from the network, one at a time, while holding the rest of the food web constant. The results shown here are the mean and standard errors from 1000 model runs for each food web configuration. Estimates for total C flow and all rates of organic and inorganic C and N cycling are for the entire food web and expressed in mg C or N m−2 year−1. S-min is a measure of stability, estimated by determining the value of ‘s’ needed to ensure that the real parts of all the eigenvalues of the matrix are negative (e.g., Moore and Hunt 1988; de Ruiter et al. 1995; Rooney et al. 2006; Moore and deRuiter 2012). An s-min value of one indicates that the diagonal strength ensuring stability of the food web is dependent solely on the specific death rates of the functional groups. Hence low s-min values (s-min ≤ 1) indicate more stable food webs relative to those with high s-min (s-min ≥ 1)
300_2017_2201_MOESM5_ESM.pdf (1.4 mb)
Supplementary material 5 (PDF 1410 kb). Differences in the role of the invertebrate community in C consumption and cycling rates of organic and inorganic C and N between the complete, sampled food web versus those without feeding preferences or with individual functional feeding groups excluded (see “Methods” in main text)

References

  1. Andrés P et al (2016) Soil food web stability in response to grazing in a semi-arid prairie: the importance of soil textural heterogeneity. Soil Biol Biochem 97:131–143. doi: 10.1016/j.soilbio.2016.02.014 Google Scholar
  2. Baermann G (1917) Eine eifache Methode Zur Auffindung con Anklyostomum (Nematoden) larvel in Erdproben Geneesk. Tijdschrift woor Nederlands Indie 57:131–137Google Scholar
  3. Bardgett RD, Wardle DA (2010) Aboveground-belowground linkages: biotic interactions, ecosystem processes, and global change. Oxford University Press, Oxford. doi: 10.1111/j.1442-9993.2012.02405.x Google Scholar
  4. Barrio IC et al (2017) Background invertebrate herbivory on dwarf birch (Betula glandulosa-nana complex) increases with temperature and precipitation across the tundra biome. Polar Biol. doi: 10.1007/s00300-017-2139-7 Google Scholar
  5. Birkhofer K, Wise DH, Scheu S (2008) Subsidy from the detrital food web, but not microhabitat complexity, affects the role of generalist predators in an aboveground herbivore food web. Oikos 117:494–500. doi: 10.1111/j.0030-1299.2008.16361.x Google Scholar
  6. Bliss LC, Matveyeva NN (1992) Circumpolar arctic vegetation. In: Chapin FS III, Reynolds JF, Shaver GR, Svoboda J (eds) Arctic ecosystems in a changing climate: an ecophysiological perspective. Academic Press, San Diego, pp 59–89Google Scholar
  7. Bloem J (1995) Fluorescent staining of microbes for total direct counts. In: Akkermans ADL, van Elsas JD, De Bruijn F (eds) Molecular microbial ecology manual. Springer, Netherlands, pp 367–378Google Scholar
  8. Boelman NT et al (2015) Greater shrub dominance alters breeding habitat and food resources for migratory songbirds in Alaskan arctic tundra. Glob Change Biol 21:1508–1520. doi: 10.1111/gcb.12761 Google Scholar
  9. Bokhorst S, Huiskes A, Convey P, Van Bodegom PM, Aerts R (2008) Climate change effects on soil arthropod communities from the Falkland Islands and the Maritime Antarctic. Soil Biol Biochem 40:1547–1556Google Scholar
  10. Bolduc E et al (2013) Terrestrial arthropod abundance and phenology in the Canadian Arctic: modelling resource availability for Arctic-nesting insectivorous birds. Can Entomol 145:155–170. doi: 10.4039/tce.2013.4 Google Scholar
  11. Bolker BM (2008) Ecological models and data in R. Princeton University Press, PrincetonGoogle Scholar
  12. Bret-Harte MS et al (2013) The response of Arctic vegetation and soils following an unusually severe tundra fire. Philos Trans Royal Soc B. doi: 10.1098/rstb.2012.0490 Google Scholar
  13. Briand F (1983) Environmental Control of Food Web Structure. Ecol 64(2):253–263Google Scholar
  14. Clein JS, Schimel JP (1995) Microbial activity of tundra and taiga soils at sub-zero temperatures. Soil Biol Biochem 27:1231–1234Google Scholar
  15. Coleman D, Andrews R, Ellis J, Singh J (1976) Energy flow and partitioning in selected man-managed and natural ecosystems Agro-ecosystems 3:45–54Google Scholar
  16. Coleman DC, Crossley D, Hendrix PF (2004) Fundamentals of soil ecology. Academic press, CambridgeGoogle Scholar
  17. Convey P, Block W, Peat HJ (2003) Soil arthropods as indicators of water stress in Antarctic terrestrial habitats? Glob Change Biol 9:1718–1730Google Scholar
  18. Coulson SJ et al (1996) Effects of experimental temperature elevation on high-arctic soil microarthropod populations. Polar Biol 16:147–153. doi: 10.1007/BF02390435 Google Scholar
  19. Crotty FV, Adl SM, Blackshaw RP, Murray PJ (2012) Using stable isotopes to differentiate trophic feeding channels within soil food webs. J Eukaryot Microbiol 59:520–526PubMedGoogle Scholar
  20. Crowther TW et al. (2016) Quantifying global soil carbon losses in response to warming. Nature 540:104–108 doi: 10.1038/nature20150. http://www.nature.com/nature/journal/v540/n7631/abs/nature20150.html—supplementary-information
  21. Csardi G, Nepusz T (2006) The igraph software package for complex network research. InterJournal Complex Syst 1695:1–9Google Scholar
  22. Culler LE, Ayres MP, Virginia RA (2015) In a warmer Arctic, mosquitoes avoid increased mortality from predators by growing faster. Proc Royal Soc B. doi: 10.1098/rspb.2015.1549 Google Scholar
  23. Curry JP (1986) Above-ground arthropod fauna of four swedish cropping systems and its role in carbon and nitrogen cycling. J Appl Ecol 23:853–870. doi: 10.2307/2403939 Google Scholar
  24. Dale VH et al (2001) Climate change and forest disturbances. BioScience 51:723–734. doi:10.1641/0006-3568(2001)051[0723:CCAFD]2.0.CO;2Google Scholar
  25. Danks HV (1992) Arctic Insects as Indicators of Environmental Change. Arctic 1992(45):159–166. doi: 10.14430/arctic1389 Google Scholar
  26. Darbyshire J, Wheatley R, Greaves M, Inkson R (1974) A rapid micromethod for estimating bacterial and protozoan populations in soil. Revue d’Ecologie et de Biologie du Sol 11:465–475Google Scholar
  27. Day TA, Ruhland CT, Strauss SL, Park JH, Krieg ML, Krna MA, Bryant DM (2009) Response of plants and the dominant microarthropod, Cryptopygus antarcticus, to warming and contrasting precipitation regimes in Antarctic tundra. Global Change Biol 15:1640–1651Google Scholar
  28. de Ruiter PC, Neutel A-M, Moore JC (1994) Modelling food webs and nutrient cycling in agro-ecosystems. Trends Ecol Evol 9:378–383. doi: 10.1016/0169-5347(94)90059-0 PubMedGoogle Scholar
  29. de Ruiter PC, Neutel A-M, Moore JC (1995) Energetics, patterns of interaction strengths, and stability in real ecosystems. Science 269:1257PubMedGoogle Scholar
  30. Detling JK (1988) Grasslands and savannas: regulation of energy flow and nutrient cycling by herbivores. In: Pomeroy LR, Alberts JJ (eds) Concepts of ecosystem ecology. Springer, Berlin, pp 131–148Google Scholar
  31. Doles J (2000) A survey of soil biota in the arctic tundra and their role in mediating terrestrial nutrient cycling. University of Northern Colorado, GreeleyGoogle Scholar
  32. Dreyer J, Townsend PA, Iii JCH, Hoekman D, Vander Zanden MJ, Gratton C (2015) Quantifying aquatic insect deposition from lake to land. Ecology 96:499–509. doi: 10.1890/14-0704.1 PubMedGoogle Scholar
  33. EPA US (2013) Most probably number (MPN) calculator version 2.0. In: User and system installation and administration manual. Environmental protection agency, Washington D.C., U.S., pp. 1–43Google Scholar
  34. Frey SD, Elliott ET, Paustian K (1999) Bacterial and fungal abundance and biomass in conventional and no-tillage agroecosystems along two climatic gradients. Soil Biol Biochem 31:573–585. doi: 10.1016/S0038-0717(98)00161-8 Google Scholar
  35. Gauthier G, Bêty J, Giroux J-F, Rochefort L (2004) Trophic interactions in a high arctic snow goose colony. Integr Comp Biol 44:119–129. doi: 10.1093/icb/44.2.119 PubMedGoogle Scholar
  36. Gelfgren M (2010) The importance of litter for interactions between terrestrial plants and invertebrates. Umea Universitet, UmeaGoogle Scholar
  37. Gough L, Moore JC, Shaver GR, Simpson RT, Johnson DR (2012) Above- and belowground responses of arctic tundra ecosystems to altered soil nutrients and mammalian herbivory. Ecology 93:1683–1694. doi: 10.1890/11-1631.1 PubMedGoogle Scholar
  38. Gruner DS (2003) Regressions of length and width to predict arthropod biomass in the Hawaiian Islands. Pac Sci 57:325–336Google Scholar
  39. Harte J, Rawa A, Price V (1996) Effects of manipulated soil microclimate on mesofaunal biomass and diversity. Soil Biol Biochem 28:313–322Google Scholar
  40. Haukioja E (1981) Invertebrate herbivory at tundra sites Tundra ecosystems: a comparative analysis. Cambridge Univ Press, Cambridge, pp 547–555Google Scholar
  41. Hinzman L et al (2005) Evidence and implications of recent climate change in Northern Alaska and other arctic regions. Climatic Change 72:251–298. doi: 10.1007/s10584-005-5352-2 Google Scholar
  42. Hobbie JE et al (2003) Climate forcing at the arctic LTER site. In: Greenland D (ed) Climate variability and ecosystem response at long-term ecological research (LTER) Sites. Oxford University Press, New York, pp 74–91Google Scholar
  43. Hódar JA (1997) The use of regression equations for estimation of prey length and biomass in diet studies of insectivore vertebrates. Miscel·lània Zoològica 20:1–10Google Scholar
  44. Hodkinson ID, Webb N, Bale J, Block W, Coulson S, Strathdee A (1998) Global change and Arctic ecosystems: conclusions and predictions from experiments with terrestrial invertebrates on Spitsbergen. Arctic Alpine Res 30:306–313Google Scholar
  45. Hoekman D et al (2016) Design for mosquito abundance, diversity, and phenology sampling within the national ecological observatory network. Ecosphere 7:e01320. doi: 10.1002/ecs2.1320 Google Scholar
  46. Høye T, Forchhammer M (2008) Phenology of high-arctic arthropods: effects of climate on spatial, seasonal and inter-annual variation Adv. Ecol Res 40:299–324Google Scholar
  47. Huitu O, Koivula M, Korpimäki E, Klemola T, Norrdahl K (2003) Winter food supply limits growth of northern vole populations in the absence of predation. Ecology 84:2108–2118Google Scholar
  48. Hunt HW et al (1987) The detrital food web in a shortgrass prairie. Biol Fertil Soils 3:57–68. doi: 10.1007/bf00260580 Google Scholar
  49. Ingham ER, Klein DA (1984) Soil fungi: relationships between hyphal activity and staining with fluorescein diacetate. Soil Biol Biochem 16:273–278. doi: 10.1016/0038-0717(84)90014-2 Google Scholar
  50. Jandt RR, Miller EA, Yokel DA, Bret-Harte MS, Mack MC, Kolden CA (2012) Findings of Anaktuvuk River fire recovery study. US Bureau of Land Management, FairbanksGoogle Scholar
  51. Jepsen JU, Hagen SB, Ims RA, Yoccoz NG (2008) Climate change and outbreaks of the geometrids Operophtera brumata and Epirrita autumnata in subarctic birch forest: evidence of a recent outbreak range expansion. J Anim Ecol 77:257–264. doi: 10.1111/j.1365-2656.2007.01339.x PubMedGoogle Scholar
  52. Jepsen JU, Kapari L, Hagen SB, Schott T, Vindstad OPL, Nilssen AC, Ims RA (2011) Rapid northwards expansion of a forest insect pest attributed to spring phenology matching with sub-Arctic birch. Glob Change Biol 17:2071–2083. doi: 10.1111/j.1365-2486.2010.02370.x Google Scholar
  53. Kaspari M, Yanoviak SP (2009) Biogeochemistry and the structure of tropical brown food webs. Ecology 90:3342–3351. doi: 10.1890/08-1795.1 PubMedGoogle Scholar
  54. Kaukonen M et al (2013) Moth herbivory enhances resource turnover in subarctic mountain birch forests? Ecology 94:267–272. doi: 10.1890/12-0917.1 PubMedGoogle Scholar
  55. Laperriere AJ, Lent PC (1977) Caribou feeding sites in relation to snow characteristics in Northeastern Alaska. Arctic 30:101–108Google Scholar
  56. Legagneux P et al (2012) Disentangling trophic relationships in a High Arctic tundra ecosystem through food web modeling. Ecology 93:1707–1716. doi: 10.1890/11-1973.1 PubMedGoogle Scholar
  57. Lund M, Raundrup K, Westergaard-Nielsen A, López-Blanco E, Nymand J, Aastrup P (2017) Larval outbreaks in West Greenland: instant and subsequent effects on tundra ecosystem productivity and CO2 exchange. Ambio 46:26–38. doi: 10.1007/s13280-016-0863-9 PubMedPubMedCentralGoogle Scholar
  58. Lundgren R, Olesen JM (2005) The Dense and highly connected world of Greenland’s plants and their pollinators Arctic. Antarctic Alpine Res 37:514–520. doi:10.1657/1523-0430(2005)037[0514:TDAHCW]2.0.CO;2Google Scholar
  59. MacLean SF Jr (1983) Life cycles and the distribution of psyllids (Homoptera) in arctic and subarctic Alaska. Oikos 40:445–451Google Scholar
  60. Marshall SA (2006) Insects: their natural history and diversity: with a photographic guide to insects of eastern North America. Firefly Books Buffalo, New YorkGoogle Scholar
  61. May RM (1972) Will a large complex system be stable? Nature 238:413–414PubMedGoogle Scholar
  62. Moore JC, deRuiter PC (2012) Energetic food webs: an analysis of real and model ecosystems. Oxford University Press, OxfordGoogle Scholar
  63. Moore JC, William Hunt H (1988) Resource compartmentation and the stability of real ecosystems. Nature 333:261–263Google Scholar
  64. Moore JC, Walter DE, Hunt HW (1988) Arthropod regulation of micro- and mesobiota in below-ground detrital food webs. Annu Rev Entomol 33:419–435. doi: 10.1146/annurev.en.33.010188.002223 Google Scholar
  65. Moore JC, Tripp BB, Simpson RT, Coleman DC (2000) Springtails in the classroom: collembola as model organisms for inquiry-based laboratories. Am Biol Teacher 62:512–519Google Scholar
  66. Moore JC, McCann K, Setälä H, De Ruiter PC (2003) Top-down is bottom-up: does predation in the rhizosphere regulate aboveground dynamics? Ecology 84:846–857. doi:10.1890/0012-9658(2003)084[0846:TIBDPI]2.0.CO;2Google Scholar
  67. Moore JC et al (2004) Detritus, trophic dynamics and biodiversity. Ecol Lett 7:584–600. doi: 10.1111/j.1461-0248.2004.00606.x Google Scholar
  68. Mosbacher JB, Kristensen DK, Michelsen A, Stelvig M, Schmidt NM (2016) Quantifying Muskox plant biomass removal and spatial relocation of nitrogen in a high Arctic Tundra ecosystem Arctic. Antarctic Alpine Res 48:229–240. doi: 10.1657/AAAR0015-034 Google Scholar
  69. Myers-Smith IH et al (2011) Shrub expansion in tundra ecosystems: dynamics, impacts and research priorities. Environ Res Lett 6:045509Google Scholar
  70. Neutel A-M, Heesterbeek JA, de Ruiter PC (2002) Stability in real food webs: weak links in long loops. Science 296:1120–1123PubMedGoogle Scholar
  71. Nielsen UN, Wall DH (2013) The future of soil invertebrate communities in polar regions: different climate change responses in the Arctic and Antarctic? Ecol Lett 16:409–419. doi: 10.1111/ele.12058 PubMedGoogle Scholar
  72. Oksanen L, Fretwell SD, Arruda J, Niemela P (1981) Exploitation ecosystems in gradients of primary productivity. Am Nat 118:240–261Google Scholar
  73. Pedersen C, Post E (2008) Interactions between herbivory and warming in aboveground biomass production of arctic vegetation. BMC Ecol. doi: 10.1186/1472-6785-8-17 PubMedPubMedCentralGoogle Scholar
  74. Pérez JH et al (2016) Nestling growth rates in relation to food abundance and weather in the Arctic. Auk 133:261–272. doi: 10.1642/AUK-15-111.1 Google Scholar
  75. Polis GA, Holt RD (1992) Intraguild predation: the dynamics of complex trophic interactions. Trends Ecol Evol 7:151–154PubMedGoogle Scholar
  76. Rich ME, Gough L, Boelman NT (2013) Arctic arthropod assemblages in habitats of differing shrub dominance. Ecography 36:994–1003. doi: 10.1111/j.1600-0587.2012.00078.x Google Scholar
  77. Rooney N, McCann K, Gellner G, Moore JC (2006) Structural asymmetry and the stability of diverse food webs. Nature 442:265–269. http://www.nature.com/nature/journal/v442/n7100/suppinfo/nature04887_S1.html
  78. Roslin T, Wirta H, Hopkins T, Hardwick B, Várkonyi G (2013) Indirect Interactions in the High Arctic. PLoS ONE 8:e67367. doi: 10.1371/journal.pone.0067367 PubMedPubMedCentralGoogle Scholar
  79. Ryan JK (1977) Synthesis of energy flows and population dynamics of Truelove Lowland invertebrates [Insects, protozoa, nematodes]. In: Bliss LC (ed) Truelove Lowland, Devon Island, Canada: a High Arctic Ecosystem. The University of Alberta Press, Edmonton, pp 325–346Google Scholar
  80. Sabo JL, Bastow JL, Power ME (2002) Length–mass relationships for adult aquatic and terrestrial invertebrates in a California watershed. J North Am Benthol Soc 21:336–343. doi: 10.2307/1468420 Google Scholar
  81. Sample BE, Cooper RJ, Greer RD, Whitmore RC (1993) Estimation of insect biomass by length and width. Am Midland Nat 129:234–240. doi: 10.2307/2426503 Google Scholar
  82. Scheu S (2001) Plants and generalist predators as links between the below-ground and above-ground system. Basic Appl Ecol 2:3–13. doi: 10.1078/1439-1791-00031 Google Scholar
  83. Schmidt ND, Kucera C (1973) Arthropod food chain energetics in a Missouri tall grass prairie. University of Missouri, ColumbiaGoogle Scholar
  84. Schmitz OJ (2008a) Effects of predator hunting mode on grassland ecosystem function. Science 319:952–954. doi: 10.1126/science.1152355 PubMedGoogle Scholar
  85. Schmitz OJ (2008b) Herbivory from individuals to ecosystems Annual Review of Ecology. Evol Syst 39:133–152Google Scholar
  86. Schuur EAG et al (2008) Vulnerability of permafrost carbon to climate change: implications for the global carbon cycle. Bioscience 58:701–714. doi: 10.1641/b580807 Google Scholar
  87. Shaver GR, Chapin FS (1991) Production: biomass relationships and element cycling in contrasting arctic vegetation types. Ecol Monogr 61:1–31. doi: 10.2307/1942997 Google Scholar
  88. Sistla SA, Moore JC, Simpson RT, Gough L, Shaver GR, Schimel JP (2013) Long-term warming restructures Arctic tundra without changing net soil carbon storage. Nature 497:615–618 doi: 10.1038/nature12129. http://www.nature.com/nature/journal/v497/n7451/abs/nature12129.html - supplementary-information
  89. Sjögersten S, van der Wal R, Woodin S (2012) Impacts of grazing and climate warming on C pools and decomposition rates in arctic environments. Ecosystems 15:349–362. doi: 10.1007/s10021-011-9514-y Google Scholar
  90. Soja AJ et al (2007) Climate-induced boreal forest change: predictions versus current observations. Global Planet Change 56:274–296. doi: 10.1016/j.gloplacha.2006.07.028 Google Scholar
  91. Søvik G, Leinaas HP, Ims RA, Solhøy T (2003) Population dynamics and life history of the oribatid mite Ameronothrus lineatus (Acari, Oribatida) on the high arctic archipelago of Svalbard. Pedobiologia 47:257–271. doi: 10.1078/0031-4056-00189 Google Scholar
  92. Stoyan D, Kushka V (2001) On animal abundance estimation based on pitfall traps. Biom J 43:45–52Google Scholar
  93. Strathdee A, Bale J (1998) Life on the edge: insect ecology in arctic environments. Annu Rev Entomol 43:85–106PubMedGoogle Scholar
  94. Summerhayes VS, Elton CS (1923) Bear Island. J Ecol 11:216–233. doi: 10.2307/2255864 Google Scholar
  95. Suzuki S, Kitayama K, S-i Aiba, Takyu M, Kikuzawa K (2013) Annual leaf loss caused by folivorous insects in tropical rain forests on Mt. Kinabalu, Borneo. J For Res 18:353–360. doi: 10.1007/s10310-012-0356-z Google Scholar
  96. Tiusanen M, Hebert PDN, Schmidt NM, Roslin T (2016) One fly to rule them all—muscid flies are the key pollinators in the Arctic. Proc Royal Soc B. doi: 10.1098/rspb.2016.1271 Google Scholar
  97. Triplehorn CA, Johnson NF (2005) Borror and DeLong’s Introduction to the Study of Insects, 7th edn. Thomson Brooks/Cole, BelmontGoogle Scholar
  98. Tsiafouli MA, Kallimanis AS, Katana E, Stamou GP (2005) &, Sgardelis SP. Responses of soil microarthropods to experimental short-term manipulations of soil moisture Applied Soil Ecology 29:17–26Google Scholar
  99. van Straalen NM, Verhoef HA (1997) The development of a bioindicator system for soil acidity based on arthropod pH preferences. J Appl Ecol 34:217–232. doi: 10.2307/2404860 Google Scholar
  100. Verhoef HA, Selm AJV (1983) Distribution and population dynamics of collembola in relation to soil moisture holarctic. Ecology 6:387–394. doi: 10.2307/3682436 Google Scholar
  101. Volney WJA, Fleming RA (2000) Climate change and impacts of boreal forest insects agriculture. Ecosyst Environ 82:283–294. doi: 10.1016/S0167-8809(00)00232-2 Google Scholar
  102. Wardle DA (2002) Communities and ecosystems: linking the aboveground and belowground components, vol 34. Princeton University Press, PrincetonGoogle Scholar
  103. Whitfield D (1972) Systems analysis Devon Island IBP project, high Arctic ecosystem Dept Botany. Univ Alberta, Edmonton, pp 392–409Google Scholar
  104. Wirta HK et al (2015a) Exposing the structure of an Arctic food web. Ecol Evol 5:3842–3856. doi: 10.1002/ece3.1647 PubMedPubMedCentralGoogle Scholar
  105. Wirta HK, Weingartner E, Hambäck PA, Roslin T (2015b) Extensive niche overlap among the dominant arthropod predators of the High Arctic. Basic Appl Ecol 16:86–92. doi: 10.1016/j.baae.2014.11.003 Google Scholar
  106. Wolf A, Kozlov M, Callaghan T (2008) Impact of non-outbreak insect damage on vegetation in northern Europe will be greater than expected during a changing climate. Climatic Change 87:91–106. doi: 10.1007/s10584-007-9340-6 Google Scholar
  107. Wyant KA, Draney ML, Moore JC (2011) Epigeal Spider (Araneae) Communities in Moist Acidic and Dry Heath Tundra at Toolik Lake, Alaska. Arctic Antarctic Alpine Res 43:301–312. doi: 10.1657/1938-4246-43.2.301 Google Scholar
  108. Zettel J (2000) Alpine Collembola - adaptations and strategies for survival in harsh environments Zool-Anal. Complex Syst 102:73–89Google Scholar
  109. Zou K, Thébault E, Lacroix G, Barot S (2016) Interactions between the green and brown food web determine ecosystem functioning. Funct Ecol 30:1454–1465. doi: 10.1111/1365-2435.12626 Google Scholar

Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Amanda M. Koltz
    • 1
  • Ashley Asmus
    • 2
  • Laura Gough
    • 3
  • Yamina Pressler
    • 4
  • John C. Moore
    • 4
    • 5
  1. 1.Department of BiologyWashington University in St. LouisSt. LouisUSA
  2. 2.Department of BiologyUniversity of Texas at ArlingtonArlingtonUSA
  3. 3.Department of Biological SciencesTowson UniversityTowsonUSA
  4. 4.Natural Resource Ecology LaboratoryColorado State UniversityFt. CollinsUSA
  5. 5.Department of Ecosystem Science and SustainabilityColorado State UniversityFt. CollinsUSA

Personalised recommendations