The systematics of ammonoids are complicated by their large degree of intra-specific variation, which complicates a stable validation of species. Aegocrioceras is a heteromorph ammonite from the Lower Saxony Basin in the Hauterivian Boreal, and a prime example of a genus with an unstable internal systematic and external relationship to other ammonoids. Here, we use quantitative morphometrics on Aegocrioceras species from an assemblage collected in the clay pit Resse (north-west Germany) to evaluate the systematics and phylogeny of this Cretaceous genus. We simplify the systematic of the genus into the three entities A. bicarinatum [m]/A. semicinctum [M] complex (which potentially contains A. quadratum as well), A. raricostatum and A. spathi. The most likely phylogeny coincides very well with the stratigraphic record of the species and implies anagenetic adaptations in A. raricostatum and A. spathi after the origin of the species. Aegocrioceras most likely derived from warm-water adapted Tethyan Crioceratites species, and Boreal Crioceratites are potentially warm-water adapted descendants of the cold-water adapted Aegocrioceras but may alternatively represent renewed Tethyan invasions. Our data imply that Aegocrioceras’ success against incumbent ammonites in the Boreal was rooted in abiotic change (Court Jester) processes due to its high adaptability, while selection within the Aegocrioceras clade was more likely based on biotic interaction (Red Queen) processes.

General abbreviations for morphological parameters

[m]/[M], small/large antidimorphs (i.e. microconch and macroconch); wh, whorl height; wi, whorl interspace; uw, umbilical width; dm, conch diameter; ARI, absolute rib index; RDW, ribs per demi-whorl; WER, whorl expansion rate; WHER, whorl height expansion rate; UWI, umbilical width index; WII, whorl interspace index.

Fossil material

The material was collected from the clay pit Resse, 10 km north of Hanover (north-west Germany), located at 52° 28′ 47.64″ N and 9° 38′ 6.96″ E. All specimens were collected from calcareous concretions, ensuring their 3D-preservation, and are deposited in the Naturalis Biodiversity Centre in Leiden, The Netherlands and the Landesamt für Bergbau, Energie und Geologie (LBEG), Geozentrum Hanover, Germany. The clay pit sediments cover the latest early Hauterivian Aegocrioceras beds, dated to belong to the nannofossil zones BC 8b–8c (Möller & Mutterlose 2014). The Aegocrioceras beds have been dated by Möller & Mutterlose (2014) using the index fossils Cruciellipsis cuvillieri (132.87 Ma) and Lithraphidites bollii (133.53 Ma). Absolute ages are here based on the Geological Time Scale 2012 (Gradstein et al. 2012). This implies that the Aegocrioceras beds comprise c.600 kyrs (Mutterlose 1992). The clay pit Resse was situated firmly in the middle of the Lower Saxony Basin during Hauterivian times, c.50 km away from the Pompeckj Swell to the north and the Rhenish Massif to the south (Möller & Mutterlose 2014, fig. 1). The sediment profile is comprised of an interlayering between thick claystone layers and thinner (10–20 cm), more calcareous layers which contain brown-greyish concretions; each calcareous layer comprises c.60 kyrs (Möller & Mutterlose 2014).

A total of 320 specimens of Aegocrioceras spp. from seven different beds of the clay pit Resse have been analysed for this work, comprised of the following species: 167 specimens of Aegocrioceras bicarinatum [m], 37 specimens of Aegocrioceras semicinctum [M], 9 specimens of Aegocrioceras quadratum, 49 specimens of Aegocrioceras raricostatum and 58 specimens of Aegocrioceras spathi. Species designation followed Rawson (1975).

We also extracted morphological data from the depiction of the type specimen of Aegocrioceras densiradiatum from Rawson (1975, pl. 6, fig. 2). In addition, we extracted morphometric data from single specimens of closely related Boreal species from published images, depicting their type specimens/only described specimens or specimens with an ‘average’ morphology. These include the Valanginian Juddiceras curvicosta from Kemper & Wiedenroth (1987, p. 353, pl. 9, fig. 2), the Valanginian Crioceratites sp. from Kemper & van der Burgh (1992, pl. 30, fig. 1), and the upper Hauterivian Crioceratites seeleyi (p. 272, fig. 11I) and Emericiceras wermbteri (p. 272, fig. 11A) from Mutterlose & Wiedenroth (2009).

Morphometric data extraction and preparation

For all specimens, we extracted morphological data of the conch using the software CONCH v. 1.0 (Hoffmann et al. 2019a, b). The following measurements were taken at radial angles of every 45°, starting at 0° in the adult stage of the conch, and numbered consecutively: (1) The whorl height (wh); (2) the whorl interspace (wi; i.e. the height of the gap between consecutive whorls); (3) the umbilical width (uw); (4) the conch diameter (dm); (5) the absolute rib indices ARI₂₀ and ARI₄₀, which are the number of ribs in a circle of 20 or 40 mm diameter around the measurement point (De Baets et al. 2009) and (6) the number of ribs per demi-whorl index (RDW), which is the number of ribs on the 180°-section of the conch toward the juvenile stage. From these raw parameters, we calculated the following derived parameters for every measurement point i: (1) The whorl expansion rate WER_i = [dm_i/(dm_i − (wh_i + wi_i))]² (Korn 2000); (2) the whorl-height expansion rate WHER_i = (wh_i/wh_i+4)² (Korn & Vöhringer 2004); (3) the umbilical width index UWI_i = uw_i/dm_i (Korn & Vöhringer 2004) and (4) the whorl interspace index WII_i = wi_i/wh_i (De Baets et al. 2009).

Because the ammonoid conchs were often only preserved as fragments and, thus, missed parts of the shell, a method to make measurements homologous and thus comparable was needed. For this, we applied the superimposition procedure described by Hoffmann et al. (2019a). In this procedure, all specimens are aligned via rotation in 45°-steps to the largest specimen until the closest possible fit between their respective radial angle–diameter curves is reached. The radial angles of the superimposed specimens are then adjusted according to the degree of rotation, so that measurements that show the same radial angle represent morphologically homologous measurements in all specimens.

Data analysis

All data have been analysed using R v. 4.0.2 (R Core Team 2020). We developed a method to re-describe the morphological data in a comparable way between all specimens, including the entire preserved ontogeny. We did this by fitting ordinary least-squares linear regression or non-linear regression models to the parameters, with radial angle (deg) as independent variable. The model for every parameter P took either of the two forms P = m × deg + b or P = m × e^b × deg (the decision of whether to fit a linear or an exponential model was made via visual examination of the plotted parameters). For either model, we extracted three values to describe the Aegocrioceras morphology throughout its ontogeny: (1) The intercept parameter m, which gives a representative indication of the normalized size of the respective parameter (representative for the adult stage); (2) the slope parameter b, which can be interpreted as the ontogenetic trajectory of the parameter, indicating to what degree it changes during the life of the individual and (3) the inverse coefficient of determination 1−R² of the model, which indicates the individual variation of the parameter throughout ontogeny. These model parameters had been centred at zero and scaled to unit variance before ensuing analyses to ensure their comparability. We used the Greedy Wilks algorithm (Mardia et al. 1979) with a λ-level of 0.05, as implemented in the R-package ‘klaR’ v. 0.6-15 (Weihs et al. 2005), to identify the most important model parameters for a separation between Aegocrioceras species. The thus identified parameters were used for the construction of a phenetic tree for all species based on the Euclidean distances, using the R-package ‘ape’ v. 5.4-1 (Paradis et al. 2004). Tree generation was performed using the balanced FastME algorithm (Desper & Gascuel 2002). For the Aegocrioceras species, we included morphological variation for the phylogram reconstruction. For this, 999 random trees were generated where the morphological parameters for each species were allowed to vary around the mean morphology following a Gaussian distribution with the standard deviation estimated from the measured data. These random trees were then used to calculate a consensus tree based on the Robinson–Foulds distance (Robinson & Foulds 1981), with the phylogeny based on the average morphology as a starting point, using the R-package ‘phytools’ v. 0.7-47 (Revell 2012).

References

DE BAETS, K., KLUG, C. and KORN, D. 2009. Anetoceratinae (Ammonoidea, Early Devonian) from the Eifel and Harz mountains (Germany), with a revision of their genera. Neues Jahrbuch für Geologie und Paläontologie – Abhandlungen, 252 (3), 361–376.

DESPER, R. and GASCUEL, O. 2002. Fast and accurate phylogeny reconstruction algorithms based on the minimum-evolution principle. 357–374. In GUIGÓ, R. and GUSFIELD, D. (eds). Algorithms in Bioinformatics: Second International Workshop, WABI 2002 Rome, Italy, September 17–21, 2002 Proceedings. Lecture Notes in Computer Science, Vol. 2452. Springer-Verlag, Berlin, Heidelberg, 554 pp.

GRADSTEIN, F., OGG, J., SCHMITZ, M. and OGG, G. 2012. The Geologic Time Scale 2012. Elsevier, Oxford, Amsterdam, Waltham, 1176 pp.

HOFFMANN, R., WEINKAUF, M. F. G., WIEDENROTH, K., GOEDDERTZ, P. and DE BAETS, K. 2019a. Morphological disparity and ontogeny of the endemic heteromorph ammonite genus Aegocrioceras (Early Cretaceous, Hauterivian, NW-Germany). Palaeogeography, Palaeoclimatology, Palaeoecology, 520, 1–17.

HOFFMANN, R., WEINKAUF, M. F. G., WIEDENROTH, K., GOEDDERTZ, P. and DE BAETS, K. 2019b. CONCH – Ammonoid Morphometric Software. Figshare. https://doi.org/10.6084/m9.figshare.6287255.v1

KEMPER, E. and VAN DER BURGH, J. 1992. Die tiefe Unterkreide im Vechte–Dinkel-Gebiet (westliches Niedersächsisches Becken), mit einem paläobotanischen Beitrag von J. van der Burgh. Losser, Stichting het Staringmonument, 95 pp.

KEMPER, E. and WIEDENROTH, K. 1987. Klima und Tier-Migrationen am Beispiel der frühkretazischen Ammoniten Nordwestdeutschlands. 315–363. In KEMPER, E. and BATTEN, D. J. (eds). Das Klima der Kreidezeit – Mit Beiträgen zur Klima-Analyse der Kreide. Geologisches Jahrbuch Reihe A, Vol. 96. Schweizerbart Science Publishers, Stuttgart, 399 pp.

KORN, D. 2000. Morphospace occupation of ammonoids over the Devonian–Carboniferous boundary. Paläontologische Zeitschrift, 74, 247–257.

KORN, D. and VÖHRINGER, E. 2004. Allometric growth and intraspecific variability in the basal Carboniferous ammonoid Gattendorfia crassa Schmidt, 1924. Paläontologische Zeitschrift, 78 (2), 425–432.

MARDIA, K. V., KENT, J. T. and BIBBY, J. M. 1979. Multivariate Analysis. Probability and Mathematical Statistics. Academic Press, Michigan, 521 pp.

MÖLLER, C. and MUTTERLOSE, J. 2014. Middle Hauterivian biostratigraphy and palaeoceanography of the Lower Saxony Basin (northwest Germany). Zeitschrift der Deutschen Gesellschaft für Geowissenschaften, 165 (4), 501–520.

MUTTERLOSE, J. 1992. Biostratigraphy and palaeobiogeography of Early Cretaceous calcareous nannofossils. Cretaceous Research, 13 (2), 167–189.

MUTTERLOSE, J. and WIEDENROTH, K. 2009. Neue Tagesaufschlüsse der Unter-Kreide (Hauterive–Unter-Apt) im Großraum Hannover–Braunschweig: Stratigraphie und Faunenführung. Berliner paläobiologische Abhandlungen, 10, 257–288.

PARADIS, E., CLAUDE, J. and STRIMMER, K. 2004. APE: Analyses of phylogenetics and evolution in R language. Bioinformatics, 20 (2), 289–290.

RAWSON, P. F. 1975. Lower Cretaceous ammonites from north-east England: The Hauterivian heteromorph Aegocrioceras. Bulletin of the British Museum (Natural History) – Geology, 26 (4), 129–159.

R CORE TEAM 2020. R: A Language and Environment for Statistical Computing. Version 4.0.2. R Foundation for Statistical Computing.

REVELL, L. J. 2012. phytools: An R package for phylogenetic comparative biology (and other things). Methods in Ecology and Evolution, 3 (2), 217–223.

ROBINSON, D. F. and FOULDS, L. R. 1981. Comparison of phylogenetic trees. Mathematical Biosciences, 53 (1–2), 131–147.

WEIHS, C., LIGGES, U., LUEBKE, K. and RAABE, N. 2005. klaR analyzing German business cycles. 335–343. In BAIER, D., DECKER, R. and SCHMIDT-THIEME, L. (eds). Data Analysis and Decision Support. Studies in Classification, Data Analysis, and Knowledge Organization. Springer-Verlag, Berlin, Heidelberg, 352 pp.

All these information are also included in README.txt to aid reusability of the data.

Weinkauf_2021_Aegocrioceras_AppendixS1.pdf

.pdf file

This file contains additional analytical results that are complementing the results presented in the manuscript.

1. A description of the superimposition procedures and results illustrating the superimposition success.
2. A depiction of the ARI40 data trajectories between species.
3. The unrooted phylogenies.
4. A metric multidimensional scaling to compare our consensus tree with the random trees.
5. A comparison for different phylogenetic tree rootings.
6. Phenotypic reconstructions of remaining conch character traits not presented in the manuscript.

Weinkauf_2021_Aegocrioceras_CollectionNumbers.xlsx

.xlsx file

This file contains the collection numbers of specimens used in this study in the Naturalis Biodiversity Centre in Leiden, The Netherlands and the Landesamt für Bergbau, Energie und Geologie (LBEG), Geozentrum Hanover, Germany.

Weinkauf_2021_Aegocrioceras_Morphology_Resse.csv

Comma-separated .txt file

This file contains extracted morphometric data of Aegocrioceras spp. from the clay pit Resse.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Weinkauf_2021_Aegocrioceras_Morphology_TypeSpecimens.csv

Comma-separated .txt file

This file contains extracted morphometric data of the type specimen of Aegocrioceras densiradiatum, as depicted in Rawson (1975).

 

 

 

 

 

 

 

 

 

 

 

 

References

RAWSON, P. F. 1975. Lower Cretaceous ammonites from north-east England: The Hauterivian heteromorph Aegocrioceras. Bulletin of the British Museum (Natural History) – Geology, 26 (4), 129–159.

Weinkauf_2021_Aegocrioceras_Morphology_Outgroup.csv

Comma-separated .txt file

This file contains extracted morphometric data of ammonoid from literature images to serve as outgroups.

 

 

 

 

 

 

 

 

 

 

 

 

References

KEMPER, E. and VAN DER BURGH, J. 1992. Die tiefe Unterkreide im Vechte–Dinkel-Gebiet (westliches Niedersächsisches Becken), mit einem paläobotanischen Beitrag von J. van der Burgh. Losser, Stichting het Staringmonument, 95 pp.

KEMPER, E. and WIEDENROTH, K. 1987. Klima und Tier-Migrationen am Beispiel der frühkretazischen Ammoniten Nordwestdeutschlands. 315–363. In KEMPER, E. and BATTEN, D. J. (eds). Das Klima der Kreidezeit – Mit Beiträgen zur Klima-Analyse der Kreide. Geologisches Jahrbuch Reihe A, Vol. 96. Schweizerbart Science Publishers, Stuttgart, 399 pp.

MUTTERLOSE, J. and WIEDENROTH, K. 2009. Neue Tagesaufschlüsse der Unter-Kreide (Hauterive–Unter-Apt) im Großraum Hannover–Braunschweig: Stratigraphie und Faunenführung. Berliner paläobiologische Abhandlungen, 10, 257–288.

Weinkauf_2021_Aegocrioceras_Morphology_Mutterlose.csv

Comma-separated .txt file

This file contains extracted morphometric data of two misidentified Aegocrioceras-species from literature images.

 

 

 

 

 

 

 

 

 

 

 

 

References

MUTTERLOSE, J. and WIEDENROTH, K. 2009. Neue Tagesaufschlüsse der Unter-Kreide (Hauterive–Unter-Apt) im Großraum Hannover–Braunschweig: Stratigraphie und Faunenführung. Berliner paläobiologische Abhandlungen, 10, 257–288.

Weinkauf_2021_Aegocrioceras_SimpleTree.tree

Phylogenetic tree in Newick format

This file contains our phylogenetic tree (unrooted) of Aegocrioceras and related species. It is based on the simple mean morphology of Aegocrioceras specimens and was calculated using the FastME algorithm (Desper & Gascuel 2002).

References

DESPER, R. and GASCUEL, O. 2002. Fast and accurate phylogeny reconstruction algorithms based on the minimum-evolution principle. 357–374. In GUIGÓ, R. and GUSFIELD, D. (eds). Algorithms in Bioinformatics: Second International Workshop, WABI 2002 Rome, Italy, September 17–21, 2002 Proceedings. Lecture Notes in Computer Science, Vol. 2452. Springer-Verlag, Berlin, Heidelberg, 554 pp.

Weinkauf_2021_Aegocrioceras_ConsensusTree.tree

Phylogenetic tree in Newick format

This file contains our phylogenetic tree (unrooted) of Aegocrioceras and related species. It is a consensus tree from 999 random trees (calculated using the FastME algorithm, Desper & Gascuel 2002) where the morphology within each Aegocrioceras-species was allowed to vary around the mean morphology following a Gaussian distribution, with the standard deviation estimated from the data. The consensus tree was calculated based on the Robinson-Foulds distance (Robinson & Foulds 1981), and the base tree (Weinkauf_2021_Aegocrioceras_SimpleTree.tree) was used as the starting point.

References

DESPER, R. and GASCUEL, O. 2002. Fast and accurate phylogeny reconstruction algorithms based on the minimum-evolution principle. 357–374. In GUIGÓ, R. and GUSFIELD, D. (eds). Algorithms in Bioinformatics: Second International Workshop, WABI 2002 Rome, Italy, September 17–21, 2002 Proceedings. Lecture Notes in Computer Science, Vol. 2452. Springer-Verlag, Berlin, Heidelberg, 554 pp.

ROBINSON, D. F. and FOULDS, L. R. 1981. Comparison of phylogenetic trees. Mathematical Biosciences, 53 (1–2), 131–147.

Weinkauf_2021_Aegocrioceras_Rawson1975Tree.tree

Phylogenetic tree in Newick format

This file contains a phylogenetic tree (unrooted) of Aegocrioceras created by Rawson (1975) based on the stratigraphic distribution of species in the Speeton clays (UK).

References

RAWSON, P. F. 1975. Lower Cretaceous ammonites from north-east England: The Hauterivian heteromorph Aegocrioceras. Bulletin of the British Museum (Natural History) – Geology, 26 (4), 129–159.