Madygen bryophytes and lycopsids

Moisan, P., S. Voigt, J. W. Schneider & H. Kerp. 2012. New fossil bryophytes from the Triassic Madygen Lagerstätte (SW Kyrgyzstan). Review of Palaeobotany and Palynology 187:29–37. [Abstract]

Recent paper on liverworts and leafy mosses from the Madygen Formation. Adds some new aspects about the Madygen flora which is known for its diversity of seed ferns, lycopsids, horsetails, and cycadophytes whereas (unambiguous) fossils of non-vascular plants, some of them occurring densely packed in shallow lacustrine sediments (and possibly represent submerged plants of the lake margin), have been described for the first time by Moisan and colleagues.

Moisan, P. & S. Voigt. 2013, in press. Lycopsids from the Madygen Lagerstätte (Middle to Late Triassic, Kyrgyzstan, Central Asia). Review of Palaeobotany and Palynology. [Abstract]

Revision of the Madygen lycopsids and of the problematic "Longisquama-appendage-like" foliage Mesenteriophyllum based on materials excavated between 2006 and 2009 whose macromorphological and microscopic epidermal features were studied. Originally described by Sixtel (1961) as a new genus of gymnosperms, Mesenteriophyllum-like plants are now found to belong to different higher lycopsid taxa (Pleuromeiales, Isoetales).

Insect-plant interaction in the Madygen forest

Philippe Moisan, who defended his Ph.D. thesis on floral remains from the Madygen Formation earlier this year, is main author of a recently published paper on ovipostion damage:

Moisan, P., C. C. Labandeira, N. A. Matushkina, T. Wappler, S. Voigt, and H. Kerp (2012): Lycopsid–arthropod associations and odonatopteran oviposition on Triassic herbaceous Isoetites. Palaeogeography, Palaeoclimatology, Palaeoecology 344–345: 6–15. [Link to abstract]

Describes an oviposition damage pattern typical for dragonflies on the quillwort Isoetites which is an unusual thing because lycopsids were not yet known to be hosts of dragonfly egg-laying.

Madygen freshwater sharks made the JVP front page

Fischer, J., S. Voigt, J. W. Schneider, M. Buchwitz & S. Voigt (2011): A selachian freshwater fauna from the Triassic of Kyrgyzstan and its implication for Mesozoic shark nurseries. Journal of Vertebrate Paleontology 31: 937- 953. [Abstract]

Aha: Egg capsules and microvertebrate fossils can be a worthwile study object after all. (Event though Jan Fischer, my fellow grad student at the Geological Institute in Freiberg, had an interview with a critical local newsreporter who doubted that anybody could ever be interested in something like that.)

Jan and colleagues describe chondrichthyan egg capsule fossils from the Madygen Formation and refer them to Palaeoxyris, a capsule type usually assigned to hybodont sharks, and Fayolia, probably produced by xenacanth sharks. These fossils are accompagnied by nearby finds teeth of hybodont shark teeth - most of them are tiny and probably belonged to juveniles of the newly erected species Lonchidion ferganensis.

Oxygen isotope analysis of the teeth and their comparison to hybodont teeth from other localities yields a clear freshwater signal for the Madygen samples, indicating that the shark offspring indeed inhabited a freshwater habitat.

Facial analysis of the sedimentary succession of the Madygen Formation demonstrates the presence of wide-spread shallow and vegetated shore areas during the Middle Triassic which could have functioned as a shark nursery, i.e. a separate and ecologically distinct habitat for juveniles which was not invaded by adult sharks of the same species.

Triassic cicadomorph insects with camouflage

Shcherbakov, D. 2011. New and little-known families of Hemiptera Cicadomorpha from the Triassic of Central Asia – early analogs of treehoppers and planthoppers. Zootaxa 2836: 1-26. [article preview with abstract]

Dmitry Shcherbakov describes twelve new (monotypic) genera and species of cicadomorphs from the Madygen Formation on the basis of some exquisitely preserved fossils and redescribes three others.

He finds homoplastic similarities of the fossil families Saaloscytinidae and Maguviopseidae (newly erected) to leaf hoppers and tree hoppers (Membracoidea) and of Mesojabloniidae to plant hoppers (Fulgoroidea)

Convergent to the extant groups of cicadomorphs the newly described fossil taxa use different means of camouflage, namely bizarrely-shaped tegmina (singular 'tegmen' = anterior cover wings without aerodynamic function), dorsal projections on the thorax and tegmen, well-developed surface sculpture, and (dull) coloration. According to Shcherbakov the specific morphology of the Maguviopseidae and Saaloscytinidae mimicked thorns, bracts, seed-bearing organs, seeds, buds, or leaves, whereas the Mesojabloniidae mimicked rotten wood or bark.

Shcherbakov assumes that predation by tree-living reptiles, such as Sharovipteryx and Longisquama (which are known from the same locality within the Madygen Formation), was an important factor underlying the evolution of elaborate types of camouflage.

As none of these Triassic hoppers appear to have survived for long, Shcherbakov concludes that their extinction was linked to the extinction of the host plants whose plant organs they imitated.

Maths in Paleontology (I): Data

''In every special doctrine of nature only so much science proper can be found as there is mathematics in it.'' - Immanuel Kant, Metaphysical Foundations of Natural Science (1786)

Warningly the maths professor who got the unthankful task to teach us first-semester scientists-to-be some basic basics of his field chose Kant's statement as the first in his first lecture on "higher" maths. However, when I started my studies in geology and paleontology, there was another saying among old school geology teachers: "A bad mathematician makes a good geologist."

Many a fellow student were rather willing to believe in these latter words than in the inconvenient alternative. (I always considered this believe as outdated and I got the feeling that geology as a science might have been shaped not only by the talents of its protagonists but also by their limitations in terms of exactness and rigorousity.)

Luckily you were not necessarily considered as a bad geologist if you were interested in maths and the notion that modern geoscience involves maths and exact methods (e.g. methods of quantitative data analysis, databases, multivariate statistics and geostatistics, geoinformatics and geographic information systems, 3D and 4D modelling, remote sensing) was clearly on the rise. Perhaps from a biologists' point of view this story would be different, but, to tell you the truth, some of the biology-based paleontologists I got to know are not much living on the exact side either.

Apart from microscopy seminars, field, and lab practicals which teach you ways of data acquisition some classes in statistics and data analysis during first semesters of study give you an idea about the structure of data and ways how to sample and how to deal with data in order to find new knowledge, e.g. a relationship between two phenomena previously not considered to be related.

At the very beginning you will learn that there are different types of data used in paleontology and that you have to bring your data into shape for any kind of mathematical analysis tools, i.e. arrange them as a data table such as the following:

Specimen	Class	State of XYZ	No. of UVW	size L [mm]	size M [cm²]
A	a	Aa	2	12.1	234
B	b	B	3	13.3	87
...	...	...	...	...	...
X	x	X	...	...	...

Normally lines of the table represent samples (or groups of samples or taxa) whereas columns may represent various features or measures. Such features may be the belonging to a certain class or category or the presence, absence, or specificity of a feature. Measured values as entries may have a discrete contribution (e.g. natural numbers such as the number of teeth or segments or body chambers) or a continuous distribution (e.g. length, area, angle, temperature measurements).

Various data relevant for paleontologists can be arranged as tables, such as morphological and microstructural data, stable isotope and other geochemical data, geographical, sedimentological, and stratigraphic data, as well as taphonomic and paleoecological data. Some of these data have a special structure and can be referred to one of the following types:


Compositional data...

... add up to 100%. Chemical compositions of fossils or faunal compositions are compositional data:

Community	Trilobites	Brachiopods	Echinoderms	Poriferans	Nautiloids
A	23 [%]	42	17	5	13
B	10	15	5	50	20
...	...	...	...	...	...
X	...	...	...	...	...

These data require careful considerations and a special kind of maths because all variables are (necessarily) correlated and thus an alleged dependence, e.g. of brachiopod and echinoderm abundances, can be obscured by variation in another group.


Spatially or temporally correlated data

‘Spatial correlation’ means that values for data points close to each other are more similar than values of more distant data points – e.g. the faunal composition of an ecosystem from Arizona is rather like that of a Nevada community than that of a Massachusetts community.

Locality	Easting (X)	Northing (Y)	Facies	Archosaurs [%]	Rhynchosaurs [%]
A	5687	0487	lacustrine	23	45
B	6485	0808	fluviatile	34	38
C	6800	1490	fluviatile	40	37
...	...	...	...	...	...

Geostatistics is the usual method to deal with spatially correlated data. Spatial correlation can also occur on much smaller scales, e. g. the shape and size of two skull bones in contact to each other can show a stronger dependence than the shape and size of bones that are more distant to each other.

In paleontology temporal correlation is quite abundant, especially if your study considers different stratigraphic ages or sedimentological field data:

Population	Horizon	Ar/Ar age [Ma]	Facies	δ18O [‰]	Average size [mm]
A	1	210 ± 1	deltaic	-2.0	5.2
B	2a	N/A	distal shelf	1.4	6.4
C	2c	207 ± 2	?	2.1	6.8
D	4	200 ± 1	deltaic	-2.2	6.0

As in stockmarket analytics methods of time series analysis can be applied to interpret temporally correlated data (i.e. time series). Such data may be relevant for your study as they often indicate evolutionary trends (biological evolution in the stricter sense but also evolution of paleoenvironments), cyclic processes with a certain periodicity, and/or they can form the basis for relating contemporaneous processes in the geological past (e.g. stratigraphic correlation of separate sedimentary successions).


Orientation data

For elongated fossils such as conical shells or long bones the orientation of the fossil long axis towards the geographical cordinate system can be measured using a compass (with inclinometer). In a similar way the orientation of bedding planes can be documented. Such measurements are often used for the purpose of deducing the former transport direction of a ancient sediment transport and depostion system (such as a river, delta, or alluvial fan). A data table with orientation data may look like that:

Specimen No.	Description	Length [cm]	Horizon	Azimuth>	Dip
1	long bone	21	1	N 20° E	0°
2	rib	12	1	N 10° W	5°
3	calamite stem	80	2a	N 15° E	0°
...	...	...	...	...	...

“Azimuth” refers to the angle towards north. Orientation data are distributed on a halfsphere. Mean values (e.g. the average orientation of long bones) and other distribution parameters cannot be derived directly from the averaging of orientation angles but vector arithmetics has to be applied.


Cladistic data

Phylogeny on the basis of morphology conventionally involves cladistic methods, especially in the field of vertebrate paleontology which deals with a particular character-rich group that is deemed suitable for cladistic approaches employing certain kinds of analysis software specialized for the calculation of phylogenetic trees (e.g. PAUP, WinClada).

In cladistic datasets lines represent taxa, mostly species or genera of the group of interest, and columns represent characters (ordered by number), i. e. features of the skeleton which are variable among the included taxa:

Taxon	1	2	3	4	5	6	7	8	9	10
A-saurus	0	0	0	0	0	0	1	0	?	0
B-raptor	?	0	1	?	0	0	1	1	0	0
C-onyx	1	1	0	?	-	1	-	1	0	1
D-ops	1	1	2	1	1	1	1	0	1	1
E-mimus	0	-	2	1	1	2	0	0	1	1

One of the main issues in cladistics is the definition of characters and the correct (unbiased) coding of morphological information. You can include qualitative differences ("bone X contacts bone Y but not bone Z" = character state “0”; "bone X contacts bones Y and Z" = character state “1”) and quantitative differences ("length of metatarsal 3 larger than or as large as length of metatarsal 4" = character state "0"; "mt3 is shorter than mt4" = "1"). Sometimes mixed character states like "0 or 1 [but not 2]" occur in a taxon and are coded accordingly.


Missing data...

...occur all the time in paleontology ... either because specimens are not complete enough or because their geological age cannot be exactly determined or because specimens are too rare or valuable to use them for a destructive analysis method or because they are for some reason no longer accessible. "N/A" ("not applicable") or empty entries or question marks often symbolize missing data.


Some introductory literature:

Borradaile, G. J. 2003. Statistics of Earth Science Data. Springer, Berlin, 280 pages. ISBN 3540436030

Swan, A. R. H. and M. Sandilands. 1995. Introduction to geological data analysis. Blackwell, Oxford, 446 pages. ISBN 0632032243

New paper on cycadophytes from Madygen

Moisan, P., S. Voigt, C. Pott, M. Buchwitz, J. Schneider, and H. Kerp. in press. Cycadalean and bennettitalean foliage from the Triassic Madygen Lagerstätte (SW Kyrgyzstan, Central Asia). Review of Palaeobotany and Palynology. [DOI:10.1016/j.revpalbo.2010.11.008]

Philippe Moisan who is doing his Ph.D. in Münster (with paleobotanist Hans Kerp as his supervisor) studies the flora of the Triassic Madygen Fm. In his first paper on that issue he introduces cycadophyte finds collected between 2005 and 2009.

Many of the studied the specimen come from the same succession and locality as Madygenerpeton (there is also a small sketch of the sedimentary profile, see Fig. 2).

One thing I learned from this study was that so-called "xeromorphic features", i.e. plant features that are usually the consequence of an adaptation to aridity, cannot only occur in xerophytes, i.e. in plants adapted to dry environments, but (for other reasons) in hygrophytic and halophytic plants as well.

Indications for aridity, such as desiccation crack horizons or or seasonally drying-out ponds and rivers or wide-spread red bed sediments are lacking in Madygen. Thus, according to Philippe's interpretation, "xeromorphism" in Madygen plants probably served other purposes than the xeromorphism of xerophytes (e.g. "self-cleaning of the leaf surface, regulation of excessive radiation and leaf temperature, mechanical defense against phytophagous insects").