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Enzymatic and detrital influences on the structure, function, and dynamics of spatially-explicit model ecosystems

Abstract

We developed agent-based models patterned after the equation-based models developed by Schimel and Weintraub (Soil Biol Biochem 35:549–563, 2003) to explore the influence of microbial-derived extracellular enzymes on carbon (C) dynamics. The models featured spatial arrangements of detritus as either randomly-spaced particles (rain) or as root-like structures (root), detritus input intervals (continuous vs. pulsed) and rates (0–5,000 units in 500 unit intervals), trophic structures (presence or absence of predators preying on microbes), and extracellular enzymes with different half-lives (1, 10, 100, and 1,000 time steps). We studied how these features affected C dynamics and model persistence (no extinctions). Models without predators were more likely to persist than those with predators, and their C dynamics could be explained with energetics-based arguments. When predators were present, two of the four model configurations—root-continuous and rain-pulsed—were more likely to persist. The root-continuous models were more likely to persist at lower detritus input rates (500–3,500 units), while the rain-pulsed models were more likely to persist at intermediate detritus input rates (2,000–3,500 units). For both these model configurations, shorter extracellular enzyme half-lives increased the likelihood of persistence. Consistent with the results of Schimel and Weintraub (Soil Biol Biochem 35:549–563, 2003), C dynamics was governed by extracellular enzyme production activity and loss. Our results demonstrated that extracellular enzyme control of C dynamics depends on the spatial arrangement of resources, the input rate and input intervals of detritus and trophic structure.

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References

  • Acosta-Martínez V, Zobeck TM, Gill TE, Kennedy AC (2003) Enzyme activities and microbial community structure in semiarid agricultural soils. Biol Fertil Soils 38:216–227

    Article  Google Scholar 

  • Allison SD (2005) Cheaters, diffusion and nutrients constrain decomposition by microbial enzymes in spatially structured environments. Ecol Lett 8:626–635

    Article  Google Scholar 

  • Allison SD, Wallenstein MD, Bradford MA (2010) Soil-carbon response to warming dependent on microbial physiology. Nat Geosci 3:336–340

    Article  Google Scholar 

  • Amin BAZ, Chabbert B, Moorhead D, Bertand I (2013) Impact of fine litter chemistry on lignocellulolytic enzyme efficiency during decomposition of maize leaf and root in soil. Biogeochemistry. doi:10.1007/s10533-013-9856-y

    Google Scholar 

  • Axelrod R (2006) Agent-based modeling as a bridge between disciplines. In: Tesfatsion L, Judd KL (eds) Agent based computational economics, vol 2., Handbook of computational economicsNorth-Holland, Amsterdam, pp 1565–1584

    Google Scholar 

  • Bonabeau E (2002) Agent-based modeling: methods and techniques for simulating human systems. Proc Natl Acad Sci 99:7280–7287

    Article  Google Scholar 

  • Bratbak G (1985) Bacterial biovolume and biomass estimates. Appl Environ Microbiol 49:1488–1493

    Google Scholar 

  • Callaway DS, Hastings A (2002) Consumer movement through differentially subsidized habitats creates a spatial food web with unexpected results. Ecol Lett 5:329–332

    Article  Google Scholar 

  • Cambier C, Bousso M, Masse D, Perrier E (2007) A new, offer versus demand, modeling approach to assess the impact of micro-organisms spatio-temporal population dynamics on soil organic matter decomposition rates. Ecol Model 209:301–313

    Article  Google Scholar 

  • Carpenter SR, Kitchell JF, Hodgson JR, Cochran PA, Elser JJ, Elser MM, Lodge DM, Kretchmer D, He X, von Ende CN (1987) Regulation of lake primary productivity by food web structure. Ecology 68:1863–1876

    Article  Google Scholar 

  • Clarholm M (1985) Interactions of bacteria, protozoa and plants leading to mineralization of soil nitrogen. Soil Biol Biochem 17:181–187

    Google Scholar 

  • Clark JR, Daines SJ, Lenton TM, Watson AJ, Williams HTP (2011) Individual-based modeling of adaptation in marine microbial populations using genetically defined physiological parameters. Ecol Model 222:3823–3837

    Article  Google Scholar 

  • Coleman DC, Reid CPP, Cole CV (1983) Biological strategies of nutrient cycling in soil systems. In: Anderson JM, Rayner ADM, Walton DWH (eds) Invertebrate-microbial interactions. Cambridge University Press, Cambridge, England, pp 35–58

  • Collins SL, Sinsabaugh RL, Crenshaw C, Green L, Porras-Alfaro A, Stursova M, Zeglin LH (2008) Pulse dynamics and microbial processes in aridland ecosystems. J Ecol 96:413–420

    Article  Google Scholar 

  • Darbyshire JF, Wheatley RE, Greaves MP, Inkson RHE (1974) Rapid micromethod for estimating bacterial and protozoan populations in Soil. Revue d’Ecologie et de Biologie du Sol 11:465–475

    Google Scholar 

  • DeAngelis DL (1975) Stability and connectance in food web models. Ecology 56:238–243

    Google Scholar 

  • De Bruyn AMH, McCann KS, Moore JC, Strong DR (2007) An energetic framework for trophic control. In: Rooney N, McCann KS, Noakes DLG (eds) From energetics to ecosystems: the dynamics and structure of ecological systems. Springer, Dordrecht, pp 65–85

    Google Scholar 

  • de Ruiter PC, Van Veen JA, Moore JC, Brussaard L, Hunt HW (1993) Calculation of nitrogen mineralization in soil food webs. Plant Soil 157:263–273

    Article  Google Scholar 

  • de Ruiter PC, Neutel A, Moore JC (1995) Energetics, patterns of interaction strengths, and stability in real ecosystems. Science 269:1257–1260

    Article  Google Scholar 

  • DeAngelis DL (1992) Dynamics of nutrient cycling and food webs. Chapman and Hall, London

    Book  Google Scholar 

  • DeAngelis DL (1995) Equilibrium and nonequilibrium concepts in ecological models. Encyclop Environ Biol 1:687–695

    Google Scholar 

  • DeAngelis DL, Waterhouse JC (1987) Equilibrium and nonequilibrium concepts in ecological models. Ecol Monogr 57:1–21

    Article  Google Scholar 

  • Duffy KJ, Cummings PT, Ford RM (1995) Random walk calculations for bacterial migration in porous media. Biophys J 68:800–806

    Article  Google Scholar 

  • Folse HJ, Allison SD (2012) Cooperation, competition, and coalitions in enzyme-producing microbes: social evolution and nutrient depolymerization rates. Front Microbiol 3:1–10

    Article  Google Scholar 

  • Frey SD, Knorr M, Parrent JL, Simpson RT (2004) Chronic nitrogen enrichment affects the structure and function of the soil microbial community in temperate hardwood and pine forests. For Ecol Manage 196:159–171

    Article  Google Scholar 

  • Gras A, Ginovart M, Portell X, Baveye PC (2010) Individual-based modeling of carbon and nitrogen dynamics in soils: parameterization and sensitivity analysis of abiotic components. Soil Sci 175:363–374

    Article  Google Scholar 

  • Griffiths BS (1994) Microbial-feeding nematodes and protozoa in soil: their effects on microbial activity and nitrogen mineralization in decomposition hotspots and the rhizosphere. Plant Soil 164:25–33

    Article  Google Scholar 

  • Grimm V, Berger U, Bastiansen F, Eliassen S, Ginot V, Giske J, Goss-Custard J, Grand T, Heinz S, Huse G, Huth A, Jepsen JU, Jørgensen C, Mooij WM, Müller B, Pe’er G, Piou C, Railsback SF, Robbins AM, Robbins MM, Rossmanith E, Rüger N, Strand E, Souissi S, Stillman RA, Vabø R, Visser U, DeAngelis DL (2006) A standard protocol for describing individual-based and agent-based models. Ecol Model 198:115–126

    Article  Google Scholar 

  • Grimm V, Berger U, DeAngelis DL, Polhill JG, Giske J, Railsback SF (2010) The ODD protocol: a review and first update. Ecol Model 221:2760–2768

    Article  Google Scholar 

  • Hagen EM, McCluney KE, Wyant KA, Soykan CU, Keller AC, Luttermose KC, Holmes EJ, Moore JC, Sabo JL (2012) A meta-analysis of the effects of detritus on primary producers and consumers in marine, freshwater and terrestrial ecosystems. Oikos 121:1507–1515

    Article  Google Scholar 

  • Hairston NG Jr, Hairston NG Sr (1993) Cause-effect relationships in energy flow, trophic structure, and interspecific interactions. Am Nat 142:379–411

    Article  Google Scholar 

  • Hairston NG, Smith FE, Slobodkin LB (1960) Community structure, population control, and competition. Am Nat 94:421–425

    Article  Google Scholar 

  • Hastings A (2012) Temporally varying resources amplify the importance of resource input in ecological populations. Biol Lett 8:1067–1069

    Article  Google Scholar 

  • Hellweger FL, Bucci V (2009) A bunch of tiny individuals—individual-based modeling of microbes. Ecol Model 220:8–22

    Article  Google Scholar 

  • Hilbert DW, Swift DM, Detling JK, Dyer MI (1981) Relative growth rates and the grazing optimization hypothesis. Oecologia 51:14–18

    Article  Google Scholar 

  • Huffaker CB (1958) Experimental studies on predation: dispersion factors and predator–prey oscillations. Hilgardia 27:795–834

    Google Scholar 

  • Hunt HW, Coleman DC, Ingham ER, Ingham RE, Elliott ET, Moore JC, Rose SL, Reid CPP, Morley CR (1987) The detrital food web in a shortgrass prairie. Biol Fertil Soil 3:57–68

    Google Scholar 

  • Hutchinson GE (1959) Homage to Santa Rosalia or why are there so many kinds of animals? Am Nat 93:145–159

    Article  Google Scholar 

  • Ingham RE, Trofymow JA, Ingham ER, Coleman DC (1985) Interaction of bacteria, fungi, and their nematode grazers: effects on nutrient cycling and plant growth. Ecol Monogr 55:119–140

    Google Scholar 

  • Jones SE, Lennon JT (2010) Dormancy contributes to the maintenance of microbial biodiversity. Proc Natl Acad Sci USA 107:5881–5886

    Article  Google Scholar 

  • Kourtev PS, Ehrenfeld JG, Häggblom M (2002) Exotic plant species alter the microbial community structure and function in the soil. Ecology 83:3152–3166

    Article  Google Scholar 

  • Kreft J-U, Plugge CM, Grimm V, Prats C, Leveau JHJ, Banitz T, Baines S, Clark J, Ros A, Klapper I, Topping CJ, Field AJ, Schuler A, Litchman E, Hellweger FL (2013) Mighty small: observing and modeling individual microbes becomes big science. Proc Natl Acad Sci USA 110:18027–18028

    Article  Google Scholar 

  • Lardon LA, Merkey BV, Martins S, Dötsch A, Picloreanu C, Kreft J-U, Smets BF (2011) iDynoMiCS: next-generation individual-based modeling of biofilms. Environ Microbiol 13(9):2416–2434. doi:10.1111/j.1462-2920.2011.02414.x

    Article  Google Scholar 

  • Lennon JT, Jones SE (2011) Microbial seed banks: the ecological and evolutionary implications of dormancy. Nat Rev 9:119–130

    Google Scholar 

  • Masse D, Cambier C, Brauman A, Sall S, Assigbetse K, Chotte JL (2007) MIOR: an individual-based model for simulating the spatial patterns of soil organic matter microbial decomposition. Eur J Soil Sci 58:1127–1135

    Article  Google Scholar 

  • May RM (1976) Simple mathematical models with very complicated dynamics. Nature 261:459–467

    Google Scholar 

  • McCann K, Hastings A, Strong D (1998) Trophic cascades and trophic trickles in pelagic food webs. Proc Royal Soc London B 265:205–209

    Article  Google Scholar 

  • Moore JC (1988) Influence of soil microarthropods on belowground symbiotic and non-symbiotic mutualisms. Interactions between soil inhabiting invertebrates and microorganisms in relation to plant growth. Agric Ecosyst Environ 24:147–159

    Article  Google Scholar 

  • Moore JC, de Ruiter PC (2012) Energetic food webs: an analysis of real and model ecosystems. Oxford University Press, Oxford

    Book  Google Scholar 

  • Moore JC, de Ruiter PC, Hunt HW (1993) The influence of productivity on the stability of real and model ecosystems. Science 261:906–908

    Google Scholar 

  • Moore JC, Walter DE, Hunt HW (1988) Arthropod regulation of micro-and mesobiota in belowground detrital food webs. Annu Rev Entomol 33:419–439

    Article  Google Scholar 

  • Moore JC, McCann K, Setälä H, de Ruiter PC (2003) Top-down is bottom-up: does predation in the rhizosphere regulate aboveground production? Ecology 84:846–857

    Article  Google Scholar 

  • Moore JC, Berlow EL, Coleman DC, de Ruiter PC, Dong Q, Hastings A, Collins-Johnson N, McCann KS, Melville K, Morin PJ, Nadelhoffer K, Rosemond AD, Post DM, Sabo JL, Scow KM, Vanni MJ, Wall D (2004) Detritus, trophic dynamics, and biodiversity. Ecol Lett 7:584–600

    Article  Google Scholar 

  • Moorhead DL, Lashermes G, Sinsabaugh RL (2012) A theoretical model of C- and N-acquiring extracellular enzyme activities, which balances microbial demands during decomposition. Soil Biol Biochem 53:133–141

    Article  Google Scholar 

  • Norton JM, Smith JL, Firestone MK (1990) Carbon flow in the rhizosphere of ponderosa pine seedlings. Soil Biol Biochem 22:449–455

    Article  Google Scholar 

  • Oksanen L, Fretwell SD, Arruda J, Niemelä P (1981) Exploitation ecosystems in gradients of primary productivity. Am Nat 118:240–261

    Article  Google Scholar 

  • Parton WJ, Schimel DS, Cole CV, Ojima DS (1987) Analysis of factors controlling soil organic matter levels in great plains grasslands. Soil Sci Soc Am J 51:1173–1179

    Google Scholar 

  • Polis GA, Strong DR (1996) Food web complexity and community dynamics. Am Nat 147:183–846

    Google Scholar 

  • Railsback SP, Grimm V (2012) Agent-based and individual-based modeling: a practical introduction. Princeton University Press, Princeton

    Google Scholar 

  • Resat H, Bailey V, McCue LA, Konopka A (2012) Modeling microbial dynamics in heterogeneous environments: growth on soil carbon sources. Microb Ecol 63:883–897

    Article  Google Scholar 

  • Rooney N, McCann K, Moore JC (2008) A metabolic theory for food webs on the landscape. Ecol Lett 11:867–881

    Article  Google Scholar 

  • Rosenzweig ML (1971) Paradox of enrichment: destabilization of exploitative ecosystems in ecological time. Science 171:385–387

    Google Scholar 

  • Schimel JP, Bennett J (2004) Nitrogen mineralization: challenges of a changing paradigm. Ecology 85:591–602

    Article  Google Scholar 

  • Schimel JP, Weintraub MN (2003) The implications of extracellular enzymes activity on microbial carbon and nitrogen limitation in soil: a theoretical model. Soil Biol Biochem 35:549–563

    Article  Google Scholar 

  • Schlesinger WH (1997) Biogeochemistry: an analysis of global change. Academic Press, San Diego

    Google Scholar 

  • Shurin JB, Gruner DS, Hillbrand H (2006) All wet or dried up? Real differences between aquatic and terrestrial food webs. Proc Royal Soc B 273:1–9

    Article  Google Scholar 

  • Strong DR (1992) Are trophic cascades all wet? Differentiation and donor-control in speciose ecosystems. Ecology 73:747–754

    Article  Google Scholar 

  • Swift MJ, Heal OW, Anderson JM (1979) Studies in ecology. In: Decomposition in terrestrial ecosystems, vol 5. University of California Press, Berkeley/Los Angeles, p 372

  • Treseder KK, Balser TC, Bradford MA, Brodie EL, Dubinsky EA, Eviner VT, Hofmockel KS, Lennon JT, Levine UR, MacGregor BJ, Pett-Ridge J, Waldrop WP (2012) Integrating microbial ecology into ecosystem models: challenges and priorities. Biogeochemistry 109:7–18

    Article  Google Scholar 

  • Wall DW, Moore JC (1999) Interactions underground: soil biodiversity, mutualism and ecosystem processes. Bioscience 49:109–117

    Article  Google Scholar 

  • Wallenstein MD, Weintraub MN (2008) Emerging tools for measuring and modeling the in situ activity of soil extracellular enzymes. Soil Biol Biochem 40:2098–2106

    Article  Google Scholar 

  • Wang G, Post WM, Mayes MA (2013) Development of microbial-enzyme-mediated decomposition model parameters through steady-state and dynamic analyses. Ecol Appl 23:255–272

    Article  Google Scholar 

  • Wiens J (1984) On understanding a nonequilibrium world: myth and reality in community patterns and processes. In: Strong DR, Simberloff D, Abele LG, Thistle AB (eds) Ecological communities: conceptual issues and evidences. Princeton University Press, Princeton, pp 439–457

    Google Scholar 

  • Wilensky U (1999) NetLogo. Center for connected learning and computer-based modeling. Northwestern University, Evanston. http//ccl.northwestern.edu/NetLogo/

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Acknowledgments

We thank Matthew Wallenstein, Mary Stromberger, Richard Dick, and Colin Bell for organizing the workshop, presenters and participants at the workshop for their insights, guidance and discussion, and the anonymous reviewers for their comments. Funding for this research was provided by grants from the US National Science Foundation (OPP-0425606, DEB-0423385, DEB-0840869, ARC-0909441, DEB-0919383).

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Correspondence to John C. Moore.

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Moore, J.C., Boone, R.B., Koyama, A. et al. Enzymatic and detrital influences on the structure, function, and dynamics of spatially-explicit model ecosystems. Biogeochemistry 117, 205–227 (2014). https://doi.org/10.1007/s10533-013-9932-3

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  • DOI: https://doi.org/10.1007/s10533-013-9932-3

Keywords

  • Agent-based model
  • Enzymes
  • Soil food web
  • Spatial distribution
  • Trophic structure