Effects of Phylogenetic Diversity and Phylogenetic Identity in a Restoration Ecology Experiment



Our understanding of the effects of plant biodiversity on ecosystem function rests in large part on experiments that have disentangled environmental variables from local diversity. Yet phylogenetic diversity (PD) effects can be confounded by phylogenetic identity effects in such experiments if assemblages with low or high PD tend to be dominated by a single clade. We illustrate this problem in a 127-species experiment designed to test the effects of angiosperm PD and trait diversity on tallgrass prairie restoration outcomes. In this experiment, the taxon pool exhibits a phylogenetic bias: if species were randomly assigned to experimental assemblages, low PD plots would frequently be dominated by a single clade (the sunflower or daisy family, Asteraceae). We present a visualization tool for examining phylogenetic experiments for this bias and propose a taxonomically constrained experimental design to reduce the most egregious causes of bias. We then present the experimental design we developed using the constrained approach and summarize initial findings from this large-scale restoration experiment. Entanglement of phylogenetic diversity and phylogenetic identity is an underappreciated and likely widespread challenge for PD experiments, particularly those that draw upon a large number of candidate species. By recognizing, quantifying, and counteracting this bias, researchers can better differentiate the effects of PD per se from phylogenetic identity effects.


Phylogenetic Diversity (PD) Phylogenetic Identity Tallgrass Prairie Prairie Restoration Mean Nearest Taxon Distance (MNTD) 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors are grateful to staff, volunteers, and colleagues too numerous to mention by name at The Morton Arboretum and Chicago Botanic Gardens who made this work possible. Natural resources and facilities staff at the Arboretum—in particular Spencer Campbell, Kurt Dreisilker, and P.J. Smith—were especially instrumental. Donald Waller and colleagues at University of Wisconsin-Madison generously provided access to prepublication trait data for 74 species, supported by US National Science Foundation Award DEB 1046355 to DW and collaborators. Carri LeRoy, Will Pearse, Grégory Sonnier, Daniel Spalink, Donald Waller, and Lindsey Worcester provided valuable comments on an early draft of this manuscript. Collaborators at Pizzo and Associates and Prairie Moon Nursery—in particular Kyle Banas, Jack Pizzo, and Bill Carter—were closely involved in species selection and production and went above and beyond in making room for us in their facilities, even at the busiest of times. Lane Scher took pains to get excellent drone photos of the experiment. This work was supported by US National Science Foundation Awards to ALH (NSF-DEB 1354551) and DJM (NSF-DEB 1354426).

Supplementary material

438199_1_En_10_MOESM1_ESM.pdf (9 kb)
Fig. 10.S1 Plot of mean phylogenetic diversity (PD) of all random 15 species assemblages including each of the species in the experimental design as a function of phylogenetic distinctiveness, ln(w), with species sampling weights a function of w. In an effort to reduce or eliminate the correlation between phylogenetic distinctiveness and mean PD of the plots in which each species occurs, we used w (Box 10.1) as a weight vector in our sampling rather than sampling species with equal probabilities; ln(w) was not utilized because it would result in negative sampling weights. A set of 5 × 105 assemblages of 15 species each were sampled for assemblages ranging from 0 to 1 in exponential and geometric scalings of w. Shown here is the result of using unscaled w as the weight vector, and the effect of all weightings was essentially the same: while the Asteraceae are no longer limited to the lowest PD plots (in fact, the highest mean PD is now occupied by one of the Asteraceae), and the dicots appear to have a sharply reduced correlation between ln(w) and mean PD, the monocots oddly show no reduction in the correlation. We did not use this sampling strategy for the final experiment (PDF 8 kb)
438199_1_En_10_MOESM2_ESM.pdf (9 kb)
Fig. 10.S2 Plot of mean phylogenetic diversity (PD) of all random 15 species assemblages including each of the species in the experiment as a function of phylogenetic distinctiveness, ln(w), including only assemblages in which Asteraceae are constrained to a maximum of three species each. The experiment as planted utilized the original set of 2 × 106 assemblages of 15 species each, limited to just those assemblages in which Asteraceae are constrained to have a maximum of 3 species. The result is a reduced correlation between mean PD and phylogenetic distinctiveness, but not an elimination of this correlation (PDF 8 kb)
438199_1_En_10_MOESM3_ESM.pdf (16 kb)
Fig. 10.S3 Ordinations of species included in experiment in trait space. Ordinations include (a) only species for which all data were present (n = 15 species); (b) species for which a maximum of five data observations were missing (n = 70 species); (c) all species, using both observed and MICE-imputed data; and (d) all species, treating missing data as missing. Ordinations were conducted using nonmetric multidimensional scaling on a Gower distance matrix (PDF 15 kb)
438199_1_En_10_MOESM4_ESM.pdf (13.9 mb)
Fig. 10.S4 Aerial photo of site, end of first year. Photo is oriented with the north to the right; the road on the left side runs along the south edge of the site. (Photo by Lane Scher, 2017-08-02) (PDF 14244 kb)
438199_1_En_10_MOESM5_ESM.xlsx (54 kb)
Table 10.S1 (XLSX 53 kb)
438199_1_En_10_MOESM6_ESM.xlsx (13 kb)
Table 10.S2 (XLSX 12 kb)
438199_1_En_10_MOESM7_ESM.docx (27 kb)
Supplemental Methods (DOCX 27 kb)


  1. Barak RS, Hipp AL, Cavender-Bares J, Pearse WD, Hotchkiss SC, Lynch EA, Callaway JC, Calcote R, Larkin DJ (2015) Taking the long view: integrating recorded, archeological, paleoecological, and evolutionary data into ecological restoration. Int J Plant Sci 177:90–102CrossRefGoogle Scholar
  2. Barak RS, Williams EW, Hipp AL, Bowles ML, Carr GM, Sherman R, Larkin DJ (2017) Restored tallgrass prairies have reduced phylogenetic diversity compared with remnants. J Appl Ecol 54:1080–1090CrossRefGoogle Scholar
  3. Blomberg SP, Garland T Jr, Ives AA (2003) Testing for phylogenetic signal in comparative data: behavioral traits are more labile. Evolution 57:717–745CrossRefPubMedGoogle Scholar
  4. Bowles M, Jones M (2004) Long-term changes in Chicago region prairie vegetation in relation to fire management. CW J 2:7–16Google Scholar
  5. Brudvig LA (2011) The restoration of biodiversity: where has research been and where does it need to go? Am J Bot 98:549–558CrossRefPubMedGoogle Scholar
  6. Cadotte M, Davies TJ (2016) Phylogenies in ecology: a guide to concepts and methods. Princeton University Press, PrincetonCrossRefGoogle Scholar
  7. Cadotte MW, Cavender-Bares J, Tilman D, Oakley TH (2009) Using phylogenetic, functional and trait diversity to understand patterns of plant community productivity. PLoS One 4:e5695CrossRefPubMedPubMedCentralGoogle Scholar
  8. Cavender-Bares J, Cavender N (2011) Phylogenetic structure of plant communities provides guidelines for restoration. In: Greipsson S (ed) Restoration ecology. Jones and Bartlett Learning, LLC, Sudbury/Mississauga/London, pp 119–129Google Scholar
  9. Court FE (2012) Pioneers of ecological restoration: the people and legacy of the University of Wisconsin Arboretum. UW Press, MadisonGoogle Scholar
  10. Faith DP (1992) Conservation evaluation and phylogenetic diversity. Biol Conserv 61:1–10CrossRefGoogle Scholar
  11. Forest F, Grenyer R, Rouget M, Davies T, Cowling R, Faith D, Balmford A, Manning J, Proche S, Bank M et al (2007) Preserving the evolutionary potential of floras in biodiversity hotspots. Nature 445:757–760CrossRefPubMedGoogle Scholar
  12. Gerhold P, Cahill JF, Winter M, Bartish IV, Prinzing A (2015) Phylogenetic patterns are not proxies of community assembly mechanisms (they are far better). Funct Ecol 29:600–614CrossRefGoogle Scholar
  13. Gleason HA (1922) The vegetational history of the middle west. Ann Assoc Am Geogr 12:39–85CrossRefGoogle Scholar
  14. Hansen TF (1997) Stabilizing selection and the comparative analysis of adaptation. Evolution 51:1341–1351CrossRefPubMedGoogle Scholar
  15. Hansen TF, Pienaar J, Orzack SH (2008) A comparative method for studying adaptation to a randomly evolving environment. Evolution 62:1965–1977PubMedGoogle Scholar
  16. Hector A (1998) The effect of diversity on productivity: detecting the role of species complementarity. Oikos 82:597–599CrossRefGoogle Scholar
  17. Hipp AL, Larkin DJ, Barak RS, Bowles ML, Cadotte MW, Jacobi SK, Lonsdorf E, Scharenbroch BC, Williams E, Weiher E (2015) Phylogeny in the Service of Ecological Restoration. Am J Bot 102:647–648CrossRefPubMedGoogle Scholar
  18. Iverson LR (1988) Land-use changes in Illinois, ASA: the influence of landscape attributes on current and historic land use. Landsc Ecol 2:45–61CrossRefGoogle Scholar
  19. Jones MB, Donnelly A (2004) Carbon sequestration in temperate grassland ecosystems and the influence of management, climate and elevated CO2. New Phytol 164:423–439CrossRefGoogle Scholar
  20. Kline VM (1997) Orchards of oak and a sea of grass. In: Packard S, Mutel CF (eds) The Tallgrass restoration handbook: for prairies, savannas, and woodlands. Island Press, Washington, D.C., pp 3–21Google Scholar
  21. Kraft NJB, Ackerly DD (2010) Functional trait and phylogenetic tests of community assembly across spatial scales in an Amazonian forest. Ecol Monogr 80:401–422CrossRefGoogle Scholar
  22. Laliberté E, Legendre P (2010) A distance-based framework for measuring functional diversity from multiple traits. Ecology 91:299–305CrossRefPubMedGoogle Scholar
  23. Larkin DJ, Hipp AL, Kattge J, Prescott W, Tonietto RK, Jacobi SK, Bowles ML (2015) Phylogenetic measures of plant communities show long-term change and impacts of fire management in tallgrass prairie remnants. J Appl Ecol 52:1638–1648CrossRefGoogle Scholar
  24. Lavorel S, Garnier E (2002) Predicting changes in community composition and ecosystem functioning from plant traits: revisiting the holy grail. Funct Ecol 16:545–556CrossRefGoogle Scholar
  25. Leach MK, Givnish TJ (1996) Ecological determinants of species loss in remnant prairies. Science 273:1555–1558CrossRefGoogle Scholar
  26. Li Y, Liu Y, Harris P, Sint H, Murray PJ, Lee MRF, Wu L (2017) Assessment of soil water, carbon and nitrogen cycling in reseeded grassland on the north Wyke farm platform using a process-based model. Sci Total Environ 603:27–37CrossRefPubMedGoogle Scholar
  27. Loreau M (1998) Separating sampling and other effects in biodiversity experiments. Oikos 82:600–602CrossRefGoogle Scholar
  28. Loreau M, Hector A (2001) Partitioning selection and complementarity in biodiversity experiments. Nature 412:72–76CrossRefGoogle Scholar
  29. Montoya D, Rogers L, Memmott J (2012) Emerging perspectives in the restoration of biodiversity-based ecosystem services. Trends Ecol Evol 27:666–672CrossRefPubMedGoogle Scholar
  30. Mouquet N, Devictor V, Meynard CN, Munoz F, Bersier L-F, Chave J, Couteron P, Dalecky A, Fontaine C, Gravel D et al (2012) Ecophylogenetics: advances and perspectives. Biol Rev 87:769–785CrossRefPubMedGoogle Scholar
  31. O’Meara BC, Ané C, Sanderson MJ, Wainwright PC (2006) Testing for different rates of continuous trait evolution using likelihood. Evolution 60:922–933CrossRefPubMedGoogle Scholar
  32. Pagel M (1997) Inferring evolutionary processes from phylogenies. Zool Scr 26:331–348CrossRefGoogle Scholar
  33. Paradis E, Claude J, Strimmer K (2004) APE: analyses of phylogenetics and evolution in R language. Bioinformatics 20:289–290CrossRefGoogle Scholar
  34. Pearse IS, Hipp AL (2009) Phylogenetic and trait similarity to a native species predict herbivory on non-native oaks. Proc Natl Acad Sci 106:18097–18102CrossRefPubMedGoogle Scholar
  35. R Core Team (2016) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna URL Scholar
  36. Revell LJ (2012) Phytools: an R package for phylogenetic comparative biology (and other things). Methods Ecol Evol 3:217–223CrossRefGoogle Scholar
  37. Risser PG (1988) Diversity in and among grasslands. In: Wilson EO, Peter FM (eds) Biodiversity. National Academies Press (US), Washington, D.C, pp 176–180Google Scholar
  38. Rosauer DF, Mooers AO (2013) Nurturing the use of evolutionary diversity in nature conservation. Trends Ecol Evol 28:322–323CrossRefPubMedGoogle Scholar
  39. Soltis DE, Soltis PS, Morgan DR, Swensen SM, Mullin BC, Dowd JM, Martin PG (1995) Chloroplast gene sequence data suggest a single origin of the predisposition for symbiotic nitrogen fixation in angiosperms. Proc Natl Acad Sci U S A 92:2647–2651CrossRefPubMedPubMedCentralGoogle Scholar
  40. Srivastava DS, Cadotte MW, MacDonald AAM, Marushia RG, Mirotchnick N (2012) Phylogenetic diversity and the functioning of ecosystems. Ecol Lett 15:637–648CrossRefPubMedGoogle Scholar
  41. Tilman (1997) Distinguishing between the effects of species diversity and species composition. Oikos 80:185CrossRefGoogle Scholar
  42. Tilman D, Reich PB, Isbell F (2012) Biodiversity impacts ecosystem productivity as much as resources, disturbance, or herbivory. Proc Natl Acad Sci 109: 10394–10397Google Scholar
  43. Tobner CM, Paquette A, Gravel D, Reich PB, Williams LJ, Messier C (2016) Functional identity is the main driver of diversity effects in young tree communities. Ecol Lett 19:638–647CrossRefPubMedGoogle Scholar
  44. van Buuren S, Groothuis-Oudshoorn K (2011) Mice: multivariate imputation by chained equations in R. J Stat Softw 45:1–67CrossRefGoogle Scholar
  45. Verdú M, Gómez-Aparicio L, Valiente-Banuet A (2012) Phylogenetic relatedness as a tool in restoration ecology: a meta-analysis. Proc R Soc B Biol Sci 279:1761–1767CrossRefGoogle Scholar
  46. Weisser WW, Roscher C, Meyer ST, Ebeling A, Luo G, Allan E, Beßler H, Barnard RL, Buchmann N, Buscot F et al (2017) Biodiversity effects on ecosystem functioning in a 15-year grassland experiment: patterns, mechanisms, and open questions. Basic Appl Ecol 23:1–73CrossRefGoogle Scholar
  47. Werner GDA, Cornwell WK, Sprent JI, Kattge J, Kiers ET (2014) A single evolutionary innovation drives the deep evolution of symbiotic N2-fixation in angiosperms. Nat Commun 5:4087CrossRefPubMedPubMedCentralGoogle Scholar
  48. White J (1978) Technical report : Illinois natural areas inventory. Dept. of Landscape Architecture, University of Illinois and Natural Land Institute, UrbanaGoogle Scholar
  49. Wright AJ, de Kroon H, Visser EJW, Buchmann T, Ebeling A, Eisenhauer N, Fischer C, Hildebrandt A, Ravenek J, Roscher C et al (2017) Plants are less negatively affected by flooding when growing in species-rich plant communities. New Phytol 213:645–656CrossRefPubMedGoogle Scholar
  50. Zanne AE, Tank DC, Cornwell WK, Eastman JM, Smith SA, FitzJohn RG, McGlinn DJ, O’Meara BC, Moles AT, Reich PB et al (2014) Three keys to the radiation of angiosperms into freezing environments. Nature 506:89–92CrossRefPubMedGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.The Morton ArboretumLisleUSA
  2. 2.University of Wisconsin – Stevens PointStevens PointUSA
  3. 3.Chicago Botanic GardenGlencoeUSA
  4. 4.University of Illinois – Urbana-ChampaignUrbanaUSA
  5. 5.Cornell UniversityIthacaUSA
  6. 6.University of MinnesotaSt. PaulUSA

Personalised recommendations