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The Science of Nature

, 104:55 | Cite as

Estimating the magnitude of morphoscapes: how to measure the morphological component of biodiversity in relation to habitats using geometric morphometrics

  • Diego Fontaneto
  • Martina Panisi
  • Mauro Mandrioli
  • Dario Montardi
  • Maurizio Pavesi
  • Andrea CardiniEmail author
Original Paper

Abstract

Ecological indicators are currently developed to account for the different facets of loss of biological diversity due to direct or indirect effects of human activities. Most ecological indicators include species richness as a metric. Others, such as functional traits and phylogenetic diversity, account for differences in species, even when species richness is the same. Here, we describe and apply a different indicator, called morphoscape dimension, accounting for morphological variability across habitats in a geographical region. We use the case of ground beetles (Coleoptera: Carabidae) in four different habitats in the Po Plain in Northern Italy to exemplify how to quantify the magnitude of the morphological space (i.e. the dimension of the morphoscape) occupied by the species in each habitat using geometric morphometrics. To this aim, we employed a variety of metrics of morphological disparity related to univariate size, and more complex multivariate shape and form. Our ‘proof of concept’ suggests that metrics assessing size and form might largely tend to simply mirror the information provided by species richness, whereas shape morphoscape disparity may be able to account for non-trivial differences in species traits amongst habitats. This is indicated by the woodland morphoscape being on average bigger than that of crops, the most species-rich habitat, despite having almost 20% less species. We conclude suggesting that the analysis of morphoscape dimension has the potential to become a new additional and complimentary tool in the hands of conservation biologists and ecologists to explore and quantify habitat complexity and inform decisions on management and conservation based on a wide set of ecological indicators.

Keywords

Carabidae Disparity Landmarks Procrustes geometric morphometrics Shape 

Notes

Acknowledgements

We are deeply grateful to F. Rigato, F. Melotti, M. Barbieri, M. Coltellacci, M. Gobbi and F.J. Rohlf for their technical and methodological advice on different aspects of the data collection and analysis. We are also grateful to the anonymous reviewers, whose comments greatly helped us to make a much better paper. AC and DF designed the study, and they wrote the paper with the help of MPan and MM. AC did the analyses with the contribution of MPan. DF, MPan, MM, DM, MPav and AC collected the data. This research did not receive any specific grant from funding agencies in the public, commercial or not-for-profit sectors.

References

  1. Ackerly DD, Cornwell WK (2007) A trait-based approach to community assembly: partitioning of species trait values into within-and among-community components. Ecol Lett 10:135–145CrossRefPubMedGoogle Scholar
  2. Adams DC (1999) Methods for shape analysis of landmark data from articulated structures. Evol Ecol Res 1:959–970Google Scholar
  3. Adams DC, Otarola-Castillo E (2013) Geomorph: an R package for the collection and analysis of geometric morphometric shape data. Methods Ecol Evol 4:393–399CrossRefGoogle Scholar
  4. Adams D, Rohlf FJ, Slice D (2013) A field comes of age: geometric morphometrics in the 21st century. Hystrix It J Mammal 24:7–14Google Scholar
  5. Balke M, Schmidt S, Hausmann A, Toussaint EF, Bergsten J, Buffington M, Häuser CL, Kroupa A, Hagedorn G, Riedel A, Polaszek A (2013) Biodiversity into your hands—a call for a virtual global natural history ‘metacollection’. Front Zool 10:55CrossRefPubMedPubMedCentralGoogle Scholar
  6. Barber C, Habel K, Grasman R, Gramacy RB, Stahel A, Sterratt DC (2012) Geometry: mesh generation and surface tesselation. R Package version 0.3–6, URL http://cran.r-project.org/web/packages/geometry/index.html
  7. Barnosky AD (1994) Defining climate’s role in ecosystem evolution: clues from late quaternary mammals. Historical Biol 8:173–190CrossRefGoogle Scholar
  8. Cardinale BJ, Duffy JE, Gonzalez A et al (2012) Biodiversity loss and its impact on humanity. Nature 486:59–67CrossRefPubMedGoogle Scholar
  9. Cardini A (2013) Geometric morphometrics. Encyclopedia of Life Support Systems (EOLSS), Developed under the Auspices of the UNESCO, EOLSS Publishers, Paris, France, URL http://www.eolss.net/
  10. Cardini A (2014) Missing the third dimension in geometric morphometrics: how to assess if 2D images really are a good proxy for 3D structures? Hystrix, It J Mammal 25:73–81Google Scholar
  11. Cardini A (2016) Lost in the other half: improving accuracy in geometric morphometric analyses of one side of bilaterally symmetric structures. Syst Biol 65:1096–1106CrossRefPubMedGoogle Scholar
  12. Cardini A, Seetah K, Barker G (2015) How many specimens do I need? Sampling error in geometric morphometrics: testing the sensitivity of means and variances in simple randomized selection experiments. Zoomorphology 134:149–163CrossRefGoogle Scholar
  13. de Lima RF, Dallimer M, Atkinson PW, Barlow J (2013) Biodiversity and land-use change: understanding the complex responses of an endemic-rich bird assemblage. Divers Distrib 19:411–422CrossRefGoogle Scholar
  14. Di Veroli A, Santoro F, Pallottini M, Selvaggi R, Scardazza F, Cappelletti D, Goretti E (2014) Deformities of chironomid larvae and heavy metal pollution: from laboratory to field studies. Chemosphere 112:9–17CrossRefPubMedGoogle Scholar
  15. Drake AG, Klingenberg CP (2010) Large-scale diversification of skull shape in domestic dogs: disparity and modularity. Am Nat 175:289–301CrossRefPubMedGoogle Scholar
  16. Fithian W, Elith J, Hastie T, Keith DA (2015) Bias correction in species distribution models: pooling survey and collection data for multiple species. Methods Ecol Evol 6:424–438CrossRefPubMedGoogle Scholar
  17. Foote M (1997) The evolution of morphological diversity. Ann Rev Ecol Syst 28:129–152CrossRefGoogle Scholar
  18. Fruciano C (2016) Measurement error in geometric morphometrics. Develop Genes and Evol 3:139–158CrossRefGoogle Scholar
  19. Garamszegi LZ (ed) (2014) Modern phylogenetic comparative methods and their application in evolutionary biology. Concepts and practice. Springer, LondonGoogle Scholar
  20. Gobbi M, Fontaneto D (2008) Biodiversity of ground beetles (Coleoptera: Carabidae) in different habitats of the Italian Po lowland. Agric Ecosyst Environ 127:273–276CrossRefGoogle Scholar
  21. Hammer O, Harper D, Ryan P (2001) PAST: paleontological statistics software package for education and data analysis. Paleontol Electr 4:1–9Google Scholar
  22. Klingenberg CP (2011) MorphoJ: an integrated software package for geometric morphometrics. Molec Ecol Res 11:353–357CrossRefGoogle Scholar
  23. Klingenberg CP (2013) Visualizations in geometric morphometrics: how to read and how to make graphs showing shape changes. Hystrix, It J Mammal 24:15–24Google Scholar
  24. Lajoie G, Vellend M (2015) Understanding context dependence in the contribution of intraspecific variation to community trait–environment matching. Ecology 96:2912–2922CrossRefPubMedGoogle Scholar
  25. Litchman E, Klausmeier CA (2008) Trait-based community ecology of phytoplankton. Ann Rev Ecol Evol Syst 39:615–639CrossRefGoogle Scholar
  26. MacLeod N, Benfield M, Culverhouse P (2010) Time to automate identification. Nature 467:154–155CrossRefPubMedGoogle Scholar
  27. Magurran A (2003) Measuring biological diversity. 2003. Wiley-Blackwell Publishing, 264 ppGoogle Scholar
  28. Maxwell SL, Fuller RA, Brooks TM, Watson JE (2016) Biodiversity: the ravages of guns, nets and bulldozers. Nature 536:143–145CrossRefPubMedGoogle Scholar
  29. McGill BJ, Enquist BJ, Weiher E, Westoby M (2006) Rebuilding community ecology from functional traits. Trends Ecol Evol 21:178–185CrossRefPubMedGoogle Scholar
  30. Mitteroecker P, Gunz P, Windhager S, Schaefer K (2013) A brief review of shape, form, and allometry in geometric morphometrics, with applications to human facial morphology. Hystrix, It J Mammal 24(1):59–66Google Scholar
  31. Mouquet N, Gravel D, Massol F, Calcagno V (2013) Extending the concept of keystone species to communities and ecosystems. Ecol Lett 16:1–8CrossRefPubMedGoogle Scholar
  32. O’Higgins P, Jones N (2006) Morphologika 2.2. Tools for shape analysis. Hull York Medical School, University of York, York. URL https://sites.google.com/site/hymsfme/downloadmorphologica
  33. Odume ON, Palmer CG, Arimoro FO, Mensah PK (2016) Chironomid assemblage structure and morphological response to pollution in an effluent-impacted river, eastern cape, South Africa. Ecol Indic 67:391–402CrossRefGoogle Scholar
  34. Palaniswamy S, Thacker NA, Klingenberg CP (2010) Automatic identification of landmarks in digital images. IET Comput Vis 4:247–260CrossRefGoogle Scholar
  35. Pavoine S, Bonsall MB (2011) Measuring biodiversity to explain community assembly: a unified approach. Biol Rev 86:792–812CrossRefPubMedGoogle Scholar
  36. Pizzo A, Roggero A, Palestrini C et al (2008) Rapid shape divergences between natural and introduced populations of a horned beetle partly mirror divergences between species. Evol Dev 10:166–175CrossRefPubMedGoogle Scholar
  37. R Core Team (2015) R: a language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
  38. Relyea RA (2012) New effects of roundup on amphibians: predators reduce herbicide mortality; herbicides induce antipredator morphology. Ecol Appl 22:634–647CrossRefPubMedGoogle Scholar
  39. Rohlf FJ (2013) NTSYSpc: numerical taxonomy system, ver. 2.3. Setauket. Exeter Publishing, Ltd., New YorkGoogle Scholar
  40. Rohlf FJ (2015) The tps series of software. Hystrix It J Mammal 26(1):9–12Google Scholar
  41. Rohlf FJ, Slice D (1990) Extensions of the Procrustes method for the optimal superimposition of landmarks. Syst Biol 39:40–59Google Scholar
  42. Sasakawa K (2016) Utility of geometric morphometrics for inferring feeding habit from mouthpart morphology in insects: tests with larval Carabidae (Insecta: Coleoptera). Biol J Linn Soc 118:394–409CrossRefGoogle Scholar
  43. Schlager S (2017) Morpho and Rvcg—shape analysis in R. In: Zheng G, Li S, Szekely G (eds.), Statistical shape and deformation analysis, pp. 217–256. Academic PressGoogle Scholar
  44. Schröter D, Cramer W, Leemans R et al (2005) Ecosystem service supply and vulnerability to global change in Europe. Science 310:1333–1337CrossRefPubMedGoogle Scholar
  45. Sfakianakis DG, Renieri E, Kentouri M, Tsatsakis AM (2015) Effect of heavy metals on fish larvae deformities: a review. Environ Res 137:246–255CrossRefPubMedGoogle Scholar
  46. Siefert A, Violle C, Chalmandrier L et al (2015) A global meta-analysis of the relative extent of intraspecific trait variation in plant communities. Ecol Lett 18:1406–1419CrossRefPubMedGoogle Scholar
  47. Sverdrup H, Stjernquist I (eds) (2013) Developing principles and models for sustainable forestry in Sweden (vol. 5). Springer Science & Business MediaGoogle Scholar
  48. Tellería JL, De La Hera I, Perez-Tris J (2013) Morphological variation as a tool for monitoring bird populations: a review. Ardeola 60:191–224CrossRefGoogle Scholar
  49. Vamosi SM (2014) Phylogenetic community ecology as an approach for studying old ideas on competition in the plankton: opportunities and challenges. J Limnol 73(s1):186–192. doi: 10.4081/jlimnol.2014.814
  50. Violle C, Enquist BJ, McGill BJ et al (2012) The return of the variance: intraspecific variability in community ecology. Trends Ecol Evol 27:244–252CrossRefPubMedGoogle Scholar
  51. Viscosi V, Cardini A (2011) Leaf morphology, taxonomy and geometric morphometrics: a simplified protocol for beginners. PLoS One 6:e25630CrossRefPubMedPubMedCentralGoogle Scholar
  52. WWF (2016) The living planet report, 2016. WWF, GlandGoogle Scholar
  53. Zuur AF, Ieno EN, Walker NJ, Saveliev AA, Smith GM (2009) Mixed effects models and extensions in ecology with R. Spring Science and Business Media, New YorkCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.Institute of Ecosystem StudyNational Research Council of ItalyVerbania PallanzaItaly
  2. 2.Departamento de Biologia AnimalFaculdade de Ciências da Universidade de LisboaLisbonPortugal
  3. 3.University of Modena and Reggio EmiliaModenaItaly
  4. 4.Museo Civico di Storia NaturaleMilanItaly
  5. 5.Dipartimento di Scienze Chimiche e GeologicheUniversità di Modena e Reggio EmiliaModenaItaly
  6. 6.School of Anatomy, Physiology and Human BiologyThe University of Western AustraliaCrawleyAustralia

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