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Do genetically-specific tree canopy environments feed back to affect genetically specific leaf decomposition rates?

  • Carri J. LeRoyEmail author
  • Dylan G. Fischer
Regular Article
  • 32 Downloads

Abstract

Aims

In forest ecosystems, trees may have genetically distinct patterns in leaf decomposition. Trees also can have genetically distinct canopy environments which modify temperature, moisture, and microbial communities on the forest floor. The interaction between these factors may result in underexplored interactions between microenvironment and leaf decomposition at the genotype level.

Methods

We compare litter decomposition rates for distinct genotypes of Fremont cottonwood (Populus fremontii) grown in a common garden environment under three different riparian conditions: 1) under a 16-tree stand of the same genotype, 2) under a 16-tree stand of another genotype, and 3) under a 16-tree stand of 16 different genotypes. Genotypes differed in canopy size and phenology.

Results

While genotype exerted a strong effect on decomposition, this effect was most pronounced when litter was decomposed under a self-similar (“home”) canopy. The strongest driver of decomposition rates across all factors (including litter quality and environmental factors) was spring (leaf-out) and fall (leaf-drop) phenology, but responses were variable by genotype.

Conclusions

The influence of genetics on litter decomposition, canopy environment, and tree phenology provides justification for the inclusion of stand-level traits like canopy cover into models of decomposition and complicates the results of studies that rely on litter quality traits alone.

Keywords

Decomposition environment Genes-to-ecosystems Intraspecific variation Home-field advantage Phenology 

Notes

Acknowledgements

We would like to thank The Evergreen State College (Evergreen) for sabbatical funding for DGF, G. Garnett of the U.S. Bureau of Reclamation, and Cibola National Wildlife Refuge staff. We would like to thank T. Whitham, A. Keith, J. Schweitzer, J. Bailey, S. Ferrier, R. Bangert, K. Kennedy, C. Dirks, and G. Wimp. The common garden was supported by NSF DEB-0425908 and NSF DEB-0816675. Undergraduates in the 2014 class, “Advanced Field and Laboratory Biology in Southwest Ecosystems” at Evergreen contributed to data collection.

Author contributions

CJL and DGF conceived, designed, and executed this study and wrote the manuscript together. CJL led decomposition experiment study design, analysis, interpretation, and writing. DGF aided in study design, data collection, statistical analysis, and writing.

References

  1. Araujo PI, Austin AT (2015) A shady business: pine afforestation alters the primary controls on litter decomposition along a precipitation gradient in Patagonia, Argentina. J Ecol 103:1408–1420CrossRefGoogle Scholar
  2. Austin AT, Vivanco L, Gonzalez-Arzac A, Perez LI (2014) There’s no place like home? An exploration of the mechanisms behind plant litter-decomposer affinity in terrestrial ecosystems. New Phytol 204:307–314CrossRefGoogle Scholar
  3. Ayres E, Steltzer H, Simmons BL, Simpson RT, Steinweg JM, Wallenstein MD, Mellor N, Parton WJ, Moore JC, Wall DH (2009) Home-field advantage accelerates leaf litter decomposition in forests. Soil Biol Biochem 41:606–610CrossRefGoogle Scholar
  4. Bailey JK, Bangert RK, Schweitzer JA, Trotter RT III, Shuster SM, Whitham TG (2004) Fractal geometry is heritable in trees. Evolution 58:2100–2102CrossRefGoogle Scholar
  5. Bradshaw HD Jr, Stettler RF (1995) Molecular genetics of growth and development in Populus. IV. Mapping QTLs with large effects on growth, form, and phenology traits in a forest tree. Genetics 139:963–973Google Scholar
  6. Bréda NJ (2003) Ground-based measurements of leaf area index: a review of methods, instruments and current controversies. J Exp Bot 54:2403–2417CrossRefGoogle Scholar
  7. Chomel M, Guittonny-Larchevêque M, DesRochers A, Baldy V (2015) Home field advantage of litter decomposition in pure and mixed plantations under boreal climate. Ecosystems 18:1014–1028CrossRefGoogle Scholar
  8. Cleland EE, Chuine I, Menzel A, Mooney HA, Schwartz MD (2007) Shifting plant phenology in response to global change. Trends Ecol Evol 22:357–365CrossRefGoogle Scholar
  9. Fanin N, Fromin N, Bertrand I (2016) Functional breadth and home-field advantage generate functional differences among soil microbial decomposers. Ecology 97:1023–1037Google Scholar
  10. Fischer DG, Chapman SK, Classen AT, Gehring CA, Grady KC, Schweitzer JA, Whitham TG (2014) Plant genetic effects on soils under climate change. Plant Soil 379:1–19CrossRefGoogle Scholar
  11. Fischer DG, Wimp GM, Hersch-Green E, Bangert RK, LeRoy CJ, Bailey JK, Schweitzer JA, Dirks C, Hart SC, Allan GJ, Whitham TG (2017) Tree genetics strongly affect forest productivity, but intraspecific diversity–productivity relationships do not. Funct Ecol 31:520–529CrossRefGoogle Scholar
  12. Gholz HL, Wedin DA, Smitherman SM, Harmon ME, Parton WJ (2000) Long-term dynamics of pine and hardwood litter in contrasting environments: toward a global model of decomposition. Glob Chang Biol 6:751–765CrossRefGoogle Scholar
  13. Jackrel SL, Wootton JT (2014) Local adaptation of stream communities to intraspecific variation in a terrestrial ecosystem subsidy. Ecology 95:37–43CrossRefGoogle Scholar
  14. Jenny H, Gessel SP, Bingham FT (1949) Comparative study of decomposition rates of organic matter in temperate and tropical regions. Soil Sci 68:419–432CrossRefGoogle Scholar
  15. Joly F-X, Milcu A, Scherer-Lorenzen M, Jean L-K, Bussotti F, Dawud SM, Müller S, Pollastrini M, Raulund-Rasmussen K, Vesterdal L, Hättenschwiler S (2017) Tree species diversity affects decomposition through modified micro-environmental conditions across European forests. New Phytol 214:1281–1293CrossRefGoogle Scholar
  16. Keiser AD, Knoepp JD, Bradford MA (2013) Microbial communities may modify how litter quality affects potential decomposition rates as tree species migrate. Plant Soil 372:167–176CrossRefGoogle Scholar
  17. Kominoski JS, Follstad Shah JJ, Canhoto C, Fischer DG, Giling DP, González E, Griffiths NA, Larrañaga A, LeRoy CJ, Mineau MM, McElarney YR, Shirley SM, Swan CM, Tiegs SD (2013) Forecasting functional implications of global changes in riparian plant communities. Front Ecol Environ 11:423–432CrossRefGoogle Scholar
  18. LeRoy CJ, Whitham TG, Keim P, Marks JC (2006) Plant genes link forests and streams. Ecology 87:255–261CrossRefGoogle Scholar
  19. LeRoy CJ, Whitham TG, Wooley SC, Marks JC (2007) Within-species variation in foliar chemistry influences leaf-litter decomposition in a Utah river. J N Am Benthol Soc 26:426–438CrossRefGoogle Scholar
  20. LeRoy CJ, Wooley SC, Lindroth RL (2012) Genotype and soil nutrient environment influence aspen litter chemistry and in-stream decomposition. Freshw Sci 31:1244–1253CrossRefGoogle Scholar
  21. Lojewski NR, Fischer DG, Bailey JK, Schweitzer JA, Whitham TG, Hart SC (2009) Genetic basis of aboveground productivity in two native Populus species and their hybrids. Tree Physiol 29:1133–1142CrossRefGoogle Scholar
  22. Madritch MD, Lindroth RL (2011) Soil microbial communities adapt to genetic variation in leaf litter inputs. Oikos 120:1696–1704CrossRefGoogle Scholar
  23. Madritch MD, Donaldson JR, Lindroth RL (2006) Genetic identity of Populus tremuloides litter influences decomposition and nutrient release in a mixed forest stand. Ecosystems 9:528–537CrossRefGoogle Scholar
  24. Madritch MD, Greene SL, Lindroth RL (2009) Genetic mosaics of ecosystem functioning across aspen-dominated landscapes. Oecologia 160:119–127CrossRefGoogle Scholar
  25. Pearse IS, Cobb RC, Karban R (2014) The phenology-substrate-match hypothesis explains decomposition rates of evergreen and deciduous oak leaves. J Ecol 102:28–35CrossRefGoogle Scholar
  26. Pugesek BH, Tomer A, von Eye A (2003) Structural equation modeling: applications in ecological and evolutionary biology. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  27. R Core Team (2017) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL: https://www.R-project.org/
  28. Rasband WS (2016) ImageJ. U. S. National Institutes of Health, Bethesda, Maryland, USA, 1997–2016. https://imagej.nih.gov/ij/
  29. Reusch TBH, Hughes AR (2006) The emerging role of genetic diversity for ecosystem functioning: estuarine macrophytes as models. Estuar Coasts 29:159–164CrossRefGoogle Scholar
  30. Rodriguez-Cabal MA, Barrios-Garcia MN, Rudman RM, McKown AD, Sato T, Crutsinger GM (2016) It is about time: genetic variation in the timing of leaf litter inputs influences aquatic ecosystems. Freshw Biol 62:356–365CrossRefGoogle Scholar
  31. Schilling EM, Waring BG, Schilling JS, Powers JS (2016) Forest composition modifies litter dynamics and decomposition in regenerating tropical dry forest. Oecologia 182:287–297CrossRefGoogle Scholar
  32. Schweitzer JA, Bailey JK, Rehill BJ, Martinsen GD, Hart SC, Lindroth RL, Keim P, Whitham TG (2004) Genetically based trait in a dominant tree affects ecosystem processes. Ecol Lett 7:127–134CrossRefGoogle Scholar
  33. Schweitzer JA, Bailey JK, Fischer DG, LeRoy CJ, Lonsdorf EV, Whitham TG, Hart SC (2008) Plant-soil-microorganism interactions: heritable relationship between plant genotype and associated soil microorganisms. Ecology 89:773–781CrossRefGoogle Scholar
  34. Silfver T, Mikola J, Rousi M, Roininen H, Oksanen E (2007) Leaf litter decomposition differs among genotypes in a local Betula pendula population. Oecologia 152:707–714CrossRefGoogle Scholar
  35. USFWS: US Fish and Wildlife Service (2017) Cibola weather station ID CBRA3, Cibola, Arizona. Accessed August 30th, 2017. http://mesowest.utah.edu/cgi-bin/droman/meso_base_dyn.cgi?stn=CBRA3
  36. Veen GF, Freschet GT, Ordonez A, Wardle DA (2015) Litter quality and environmental controls of home-field advantage effects on litter decomposition. Oikos 124:187–195CrossRefGoogle Scholar
  37. Whitham TG, Bailey JK, Schweitzer JA, Shuster SM, Bangert RK, LeRoy CJ, Lonsdorf E, Allan GJ, DiFazio SP, Potts BM, Fischer DG, Gehring CA, Lindroth RL, Marks JC, Hart SC, Wimp GM, Wooley SC (2006) A framework for community and ecosystem genetics: from genes to ecosystems. Nat Rev Genet 7:510–523CrossRefGoogle Scholar
  38. Wu R, Stettler RF (1998) Quantitative genetics of growth and development in Populus. III. Phenotypic plasticity of crown structure and function. Heredity 81:299–310CrossRefGoogle Scholar
  39. Yu Q, Pulkkinen P, Rautio M, Haapanen M, Alen R, Stener LG, Beuker E, Tigerstedt PMA (2001) Genetic control of wood physiochemical properties, growth, and phenology in hybrid aspen clones. Can J For Res 31:1348–1356CrossRefGoogle Scholar
  40. Zhang D, Hui D, Luo Y, Zhou G (2008) Rates of litter decomposition in terrestrial ecosystems: global patterns and controlling factors. J Plant Ecol 1:85–93CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Evergreen Ecosystem Ecology LaboratoryThe Evergreen State CollegeOlympiaUSA

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