Phylogenetic, ecological and intraindividual variability patterns in grass phytolith shape
Language English Country Great Britain, England Media print
Document type Journal Article
PubMed
34849559
PubMed Central
PMC8835630
DOI
10.1093/aob/mcab143
PII: 6446111
Knihovny.cz E-resources
- Keywords
- Paleoecology, Pooideae, geometric morphometrics, grass phylogeny, phytoliths, semi-landmarks,
- MeSH
- Biological Evolution MeSH
- Phylogeny MeSH
- Poaceae * genetics MeSH
- Silicon Dioxide MeSH
- Fossils * MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Silicon Dioxide MeSH
BACKGROUND AND AIMS: Grass silica short cell (GSSC) phytoliths appear to be the most reliable source of fossil evidence for tracking the evolutionary history and paleoecology of grasses. In recent years, modern techniques that quantitatively assess phytolith shape variation have widened opportunities for the classification of grass fossil phytoliths. However, phylogenetic, ecological and intraindividual variability patterns in phytolith shape remain largely unexplored. METHODS: The full range of intraindividual phytolith shape variation [3650 two-dimensional (2-D) outlines] from 73 extant grass species, 48 genera, 18 tribes and eight subfamilies (particularly Pooideae) was analysed using geometric morphometric analysis based on semi-landmarks spanning phytolith outlines. KEY RESULTS: The 2-D phytolith shape is mainly driven by deep-time diversification of grass subfamilies. There is distinct phytolith shape variation in early-diverging lineages of Pooideae (Meliceae, Stipeae). The amount of intraindividual variation in phytolith shape varies among species, resulting in a remarkable pattern across grass phylogeny. CONCLUSIONS: The phylogenetic pattern in phytolith shape was successfully revealed by applying geometric morphometrics to 2-D phytolith shape outlines, strengthening the potential of phytoliths to track the evolutionary history and paleoecology of grasses. Geometric morphometrics of 2-D phytolith shape is an excellent tool for analysis requiring large numbers of phytolith outlines, making it useful for quantitative palaeoecological reconstruction.
Institute of Archaeology Czech Academy of Sciences Letenská 4 CZ 11801 Praha 1 Czech Republic
Institute of Botany Academy of Science of the Czech Republic CZ 252 43 Průhonice Czech Republic
See more in PubMed
Adams DC, Collyer ML, Kaliontzopoulou A, Balken E. 2021. Geomorph: software for geometric morphometric analyses. R package version 3.3.2.
Allard G, Nelson CJ, Pallardy SG. 1991. Shade effects on growth of tall fescue: I. Leaf anatomy and dry matter partitioning. Crop Science 31: 163–167.
Alexandre A, Meunier JD, Lézine AM, Vincens A, Schwartz D. 1997. Phytoliths: indicators of grassland dynamics during the late Holocene in intertropical Africa. Palaeogeography, Palaeoclimatology, Palaeoecology 136: 213–229.
Ball TB, Davis A, Evett RR, et al. . 2016. Morphometric analysis of phytoliths: recommendations towards standardization from the International Committee for Phytolith Morphometrics. Journal of Archaeological Science 68: 106– 111.
Barboni D, Bremond L, Bonnefille R. 2007. Comparative study of modern phytolith assemblages from inter-tropical Africa. Palaeogeography, Palaeoclimatology, Palaeoecology 246: 454–470.
Bookstein FL. 1989. Principal warps: thin-plate splines and the decomposition of deformations. IEEE Transactions in Pattern Analysis and Machine Intelligence 11: 567–585.
Bookstein FL. 1997. Landmark methods for forms without landmarks: morphometrics of group differences in outline shape. Medical Image Analysis 1: 225–243. PubMed
Bouchenak-Khelladi Y, Verboom GA, Savolainen V, Hodkinson TR. 2010. Biogeography of the grasses (Poaceae): a phylogenetic approach to reveal evolutionary history in geographical space and geological time. Botanical Journal of the Linnean Society 162: 543–557.
Bremond L, Alexandre A, Hély C, Guiot J. 2005. A phytolith index as a proxy of tree cover density in tropical areas: calibration with Leaf Area Index along a forest–savanna transect in southeastern Cameroon. Global and Planetary Change 45: 277–293.
Cai Z, Ge S. 2017. Machine learning algorithms improve the power of phytolith analysis: a case study of the tribe Oryzeae (Poaceae). Journal of Systematics and Evolution 55: 377–384.
Diester-Haass L, Schrader HJ, Thiede J. 1973. Sedimentological and paleoclimatological investigations of two pelagic ooze cores off Cape Barbas, North-West Africa. Meteor Forshungergebnisse 16: 19–66.
Dryden IL., Mardia KV. 2016. Statistical shape analysis, with applications in R, 2nd edn. Chichester, UK: Wiley.
Dunn RE, Le TY, Strömberg CA. 2015. Light environment and epidermal cell morphology in grasses. International Journal of Plant Sciences 176: 832–847.
Edwards EJ, Smith SA. 2010. Phylogenetic analyses reveal the shady history of C4 grasses. Proceedings of the National Academy of Sciences, USA 107: 2532–2537. PubMed PMC
Evett RR, Cuthrell RQ. 2016. A conceptual framework for a computer-assisted, morphometric-based phytolith analysis and classification system. Journal of Archaeological Science 68: 70–78.
Fahmy AG. 2008. Diversity of lobate phytoliths in grass leaves from the Sahel region, West Tropical Africa: Tribe Paniceae. Plant Systematics and Evolution 270: 1– 23.
Fredlund GG, Tieszen LT. 1994. Modern phytolith assemblages from the North American great plains. Journal of Biogeography 21: 321–335.
Gallego L, Distel RA. 2004. Phytolith assemblages in grasses native to central Argentina. Annals of Botany 94: 865–874. PubMed PMC
Gallaher TJ, Akbar SZ, Klahs PC, et al. . 2020. 3D shape analysis of grass silica short cell phytoliths: a new method for fossil classification and analysis of shape evolution. New Phytologist 228: 376–392. PubMed
Gibson DJ. 2009. Grasses and grassland ecology. Oxford: Oxford University Press.
Gunz P, Mitteroecker P. 2013. Semilandmarks: a method for quantifying curves and surfaces. Hystrix, the Italian Journal of Mammalogy 24: 103–109.
Hammer Ø, Harper DAT, Ryan PD. 2001. PAST: paleontological statistics software package for education and data analysis. Palaeontologia Electronica 4: 9.
Hošková K, Pokorná A, Neustupa J, Pokorný P. 2021. Inter- and intraspecific variation in grass phytolith shape and size: a geometric morphometrics perspective. Annals of Botany 127: 191–201. PubMed PMC
International Committee for Phytolith Taxonomy (ICPT). 2019. International code for phytolith nomenclature (ICPN) 2.0. Annals of Botany 124: 189–199. PubMed PMC
Jacobs BF, Kingston JD, Jacobs LL. 1999. The origin of grass-dominated ecosystems. Annals of the Missouri Botanical Garden 86: 590–643.
Jin Y, Qian H. 2019. V. PhyloMaker: an R package that can generate very large phylogenies for vascular plants. Ecography 42: 1353–1359. PubMed PMC
Klingenberg CP. 2011. MorphoJ: an integrated software package for geometric morphometrics. Molecular Ecology Resources 11: 353–357. PubMed
Klingenberg CP. 2013. Visualization in geometric morphometrics: how to read and how to make graphs showing shape changes. Hystrix, the Italian Journal of Mammalogy 24: 15–24.
Klingenberg CP. 2015. Analyzing fluctuating asymmetry with geometric morphometrics: concepts, methods, and applications. Symmetry 7: 843–934.
Knapp AK, Gilliam FS. 1985. Response of Andropogon gerardii (Poaceae) to fire-induced high vs. low irradiance environments in tallgrass prairie: leaf structure and photosynthetic pigments. American Journal of Botany 72:1668–1671.
Kumar S, Milstein Y, Brami Y, Elbaum M, Elbaum R. 2017. Mechanism of silica deposition in sorghum silica cells. New Phytologist 213: 791–798. PubMed
Lu H, Liu KB. 2003. Morphological variations of lobate phytoliths from grasses in China and the south-eastern United States. Diversity and Distributions 9: 73–87.
Mander L, Li M, Mio W, Fowlkes CC, Punyasena SW. 2013. Classification of grass pollen through the quantitative analysis of surface ornamentation and texture. Proceedings of the Royal Society B: Biological Sciences 280: 1–7. PubMed PMC
Metcalfe CR. 1960. Anatomy of the monocotyledons. I. Gramineae. Oxford: Clarendon Press.
Mitteroecker P, Bookstein F. 2011. Linear discrimination, ordination, and the visualization of selection gradients in modern morphometrics. Evolutionary Biology 38: 100–114.
Mulholland SC. 1989. Phytolith shape frequencies in North Dakota grasses: a comparison to general patterns. Journal of Archaeological Science 16: 489–511.
Mulholland SC, Rapp G Jr. 1992. A morphological classification of grass silica bodies. In: Rapp G Jr, Mulholland SC, eds. Phytolith systematics: emerging issues. Advances in archaeological and museum science, Vol. 1. Boston, MA: Springer, 65–89.
Neumann K, Fahmy AG, Müller-Scheeßel N, Schmidt M. 2017. Taxonomic, ecological and palaeoecological significance of leaf phytoliths in West African grasses. Quaternary International 434: 15–32.
Neustupa J. 2013. Patterns of symmetric and asymmetric morphological variation in unicellular green microalgae of the genus Micrasterias (Desmidiales, Viridiplantae). Fottea 13: 53–63.
Neustupa J, Woodard K. 2021. Male sterility significantly elevates shape variation and fluctuating asymmetry of zygomorphic corolla in gynodioecious Glechoma hederacea (Lamiaceae). AoB Plants 13: plab013. PubMed PMC
Novello A, Barboni D, Berti-Equille L, Mazur JC, Poilecot P, Vignaud P. 2012. Phytolith signal of aquatic plants and soils in Chad, Central Africa. Review of Palaeobotany and Palynology 178: 43– 58.
Oksanen J, Blanchet FG, Friendly M, et al. . 2019. vegan: community ecology package. R package version 2.5-6.
Orme D, Freckleton R, Thomas G, et al. . 2018. caper: comparative analyses of phylogenetics and evolution in R. R package version 1.0.1.
Pérez R, De Ciurana J, Riba C. 2006. The characterization and specification of functional requirements and geometric tolerances in design. Journal of Engineering Design 17: 311–324.
Piperno DR. 2006. Phytoliths: a comprehensive guide for archaeologists and paleoecologists. Lanham, MD: Altamira Press.
Piperno DR, Pearsall DM. 1998. The silica bodies of tropical American grasses: morphology, taxonomy, and implications for grass systematics and fossil phytolith identification. Smithsonian Contributions to Botany 85: 1–40.
Polly PD, Motz GJ. 2016. Patterns and processes in morphospace: geometric morphometrics of three-dimensional objects. The Paleontological Society Papers 22: 71–99.
Prasad V, Strömberg CA, Alimohammadian H, Sahni A. 2005. Dinosaur coprolites and the early evolution of grasses and grazers. Science 310: 1177–1180. PubMed
Prasad V, Strömberg CAE, Leaché AD, et al. . 2011. Late Cretaceous origin of the rice tribe provides evidence for early diversification in Poaceae. Nature Communications 2: 1–9. PubMed
R Core Team. 2020. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing.
Revell LJ. 2012. phytools: an R package for phylogenetic comparative biology (and other things). Methods in Ecology and Evolution 3: 217–223.
Rohlf FJ. 2015. The tps series of software. Hystrix, the Italian Journal of Mammalogy 26: 9–12.
Romaschenko K, Peterson PM, Soreng RJ, Futorna O, Susanna A. 2011. Phylogenetics of Piptatherum s. l. (Poaceae: Stipeae): evidence for a new genus, Piptatheropsis, and resurrection of Patis. Taxon 60: 703–1716.
Romaschenko K, Peterson PM, Soreng RJ, Garcia-Jacas N, Futorna O, Susanna A. 2012. Systematics and evolution of the needle grasses (Poaceae: Pooideae: Stipeae) based on analysis of multiple chloroplast loci, ITS, and lemma micromorphology. Taxon 61: 18–44.
Rovner I, Russ JC. 1992. Darwin and design in phytolith systematics: morphometric methods for mitigating redundancy. In: Mulholland SC, Rapp G, eds. Phytolith systematics: emerging issues. Advances in archaeological and museum science, Vol. 1. Boston, MA: Springer, 253–276
Rudall PJ, Prychid CJ, Gregory T. 2014. Epidermal patterning and silica phytoliths in grasses: an evolutionary history. Botanical Review 80: 59–71.
Russ JC, Rovner I. 1989. Stereological identification of opal phytolith populations from wild and cultivated Zea. American Antiquity 54: 784–792.
Savriama Y. 2018. A step-by-step guide for geometric morphometrics of floral symmetry. Frontiers in Plant Science 9: 1433. PubMed PMC
Savriama Y, Klingenberg CP. 2011. Beyond bilateral symmetry: geometric morphometric methods for any type of symmetry. BMC Evolutionary Biology 11: 280. PubMed PMC
Savriama Y, Gómez JM, Perfectti F, Klingenberg CP. 2012. Geometric morphometrics of corolla shape: dissecting components of symmetric and asymmetric variation in Erysimum mediohispanicum (Brassicaceae). New Phytologist 196: 945–954. PubMed
Savriama Y, Neustupa J, Klingenberg CP. 2010. Geometric morphometrics of symmetry and allometry in Micrasterias rotata (Zygnemophyceae, Viridiplantae). Nova Hedwigia 136: 43–54.
Schaefer K, Lauc T, Mitteroecker P, Gunz P, Bookstein FL. 2006. Dental arch asymmetry in an isolated Adriatic community. American Journal of Physical Anthropology 129: 132–142. PubMed
Schubert M, Grønvold L, Sandve SR, Hvidsten TR, Fjellheim S. 2019a. Evolution of cold acclimation and its role in niche transition in the temperate grass subfamily Pooideae. Plant Physiology 180: 404–419. PubMed PMC
Schubert M, Marcussen T, Meseguer AS, Fjellheim S. 2019b. The grass subfamily Pooideae: Cretaceous–Palaeocene origin and climate-driven Cenozoic diversification. Global Ecology and Biogeography 28: 1168–1182.
Silantyeva M, Solomonova M, Speranskaja N, Blinnikov MS. 2018. Phytoliths of temperate forest–steppe: a case study from the Altay, Russia. Review of Palaeobotany and Palynology 250: 1–15.
Smith SA, Brown JW. 2018. Constructing a broadly inclusive seed plant phylogeny. American Journal of Botany 105: 302–314. PubMed
Soreng RJ, Peterson PM, Romaschenko K, et al. . 2015. A worldwide phylogenetic classification of the Poaceae (Gramineae). Journal of Systematics and Evolution 53: 117–137.
Soreng RJ, Peterson PM, Romaschenko K, et al. . 2017. A worldwide phylogenetic classification of the Poaceae (Gramineae) II: an update and a comparison of two 2015 classifications. Journal of Systematics and Evolution 55: 259–290.
Strömberg CAE. 2005. Decoupled taxonomic radiation and ecological expansion of open-habitat grasses in the Cenozoic of North America. Proceedings of the National Academy of Sciences, USA 102: 11980–11984. PubMed PMC
Strömberg CAE. 2009. Methodological concerns for analysis of phytolith assemblages: does count size matter? Quaternary International 193: 124–140.
Strömberg CAE. 2011. Evolution of grasses and grassland ecosystems. Annual Review of Earth and Planetary Sciences 39: 517–544.
Strömberg CAE, Dunn RE, Crifò C, Harris EB. 2018. Phytoliths in paleoecology: analytical considerations, current use, and future directions. In: Croft DA, Su DF, Simpson SW, eds. Methods in paleoecology: reconstructing cenozoic terrestrial environments and ecological communities. Cham, Switzerland: Springer, 235–287.
Thomasson JR. 1978. Epidermal patterns of the lemma in some fossil and living grasses and their phylogenetic significance. Science 199: 975–977. PubMed
Thomasson JR. 1987. Late Miocene plants from northeastern Nebraska. Journal of Paleontology 61: 1065–1079.
Twiss PC. 1992. Predicted world distribution of C3 and C4 grass phytoliths. In: Rapp G Jr, Mulholland SC, eds. Phytolith systematics: emerging issues. Advances in archaeological and museum science, Vol. 1. Boston, MA: Springer, 113–128.
Twiss PC, Suess E, Smith RM. 1969. Morphological classification of grass phytoliths. Soil Science Society of America Proceedings 33: 109–115.
Yost CL, Ivory SJ, Deino AL, Rabideaux NM, Kingston JD, Cohen AS. 2021. Phytoliths, pollen, and microcharcoal from the Baringo Basin, Kenya reveal savanna dynamics during the Plio-Pleistocene transition. Palaeogeography, Palaeoclimatology, Palaeoecology 570: 109779.
Zelditch ML, Swiderski DL, Sheets DH. 2012. Geometric morphometrics for biologists: a primer, 2nd edn. London: Academic Press.