A geometric morphometric protocol to correct postmortem body arching in fossil fishes

Postmortem body curvature introduces error in fish morphometric data. Compared to living fish, the causes of such body curvature in fossils may be due to additive taphonomic processes that have been widely studied. However, a protocol that helps to correct its effect upon morphometric data remains unexplored. Here, we test two different mathematical approaches (multivariate regression and the so-called 'unbending functions') available to tackle fish geometric morphometric data in two exceptionally preserved gonorynchiformes fossil fishes, Rubiesichthys gregalis and Gordichthys conquensis, from the Las Hoyas deposits (Early Cretaceous, Spain). Although both methods successfully correct body curvature (i.e., removing misleading geometric variation), our results show that traditional approaches applied in living fishes might not be appropriate to fossil ones, because of the additional anatomical alterations. Namely, the best result for 2D fossil fishes is achieved by correcting the arching of the specimens (mathematically "unbending" them). Ultimately, the effect of body curvature on morphometric data is largely taxon independent and morphological diversity mitigates its effect, but size is an important factor to take into account (because larger individuals tend to be less curved).

Is shape in the eye of the beholder? Assessing landmarking error in geometric morphometric analyses on live fish

Geometric morphometrics is widely used to quantify morphological variation between biological specimens, but the fundamental influence of operator bias on data reproducibility is rarely considered, particularly in studies using photographs of live animals taken under field conditions. We examined this using four independent operators that applied an identical landmarking scheme to replicate photographs of 291 live Atlantic salmon (Salmo salar L.) from two rivers. Using repeated measures tests, we found significant inter-operator differences in mean body shape, suggesting that the operators introduced a systematic error despite following the same landmarking scheme. No significant differences were detected when the landmarking process was repeated by the same operator on a random subset of photographs. Importantly, in spite of significant operator bias, small but statistically significant morphological differences between fish from the two rivers were found consistently by all operators. Pairwise tests of angles of vectors of shape change showed that these between-river differences in body shape were analogous across operator datasets, suggesting a general reproducibility of findings obtained by geometric morphometric studies. In contrast, merging landmark data when fish from each river are digitised by different operators had a significant impact on downstream analyses, highlighting an intrinsic risk of bias. Overall, we show that, even when significant inter-operator error is introduced during digitisation, following an identical landmarking scheme can identify morphological differences between populations. This study indicates that operators digitising at least a sub-set of all data groups of interest may be an effective way of mitigating inter-operator error and potentially enabling data sharing.

Phenotypic variation among silverside populations (Atherinopsidae: Atherinella brasiliensis) from distinct environments in Northeastern Brazil

The successful adaptation of populations to a wide range of environments is a central topic in ecology. Based on the assumption that body shape may affect survival, we evaluated to what extent biotic and abiotic factors are capable of inducing morphological changes in Brazilian silverside populations (Atherinella brasiliensis). To reach this goal, we compared 18 morphological traits of specimens from five ecosystems representing three types of environment (estuary, coastal lagoon, reservoir). Populations from estuaries displayed greater anal fin area and greater caudal fin aspect ratio and area. Populations from coastal lagoons had more compressed bodies, larger heads, and slightly broader caudal peduncles. The fish from estuaries and coastal lagoons had longer caudal peduncles, larger pelvic fins and larger eye area. Population from reservoir had more depressed bodies and greater oral protrusion. Food availability explained 31% of the observed ecomorphological patterns. Overall, the morphology of the respective populations was consistent with each type of environment, making it possible to associate phenotypic variation with habitat and feeding patterns, although abiotic factors were more significant than biotic factors. In conclusion, landlocked populations of A. brasiliensis are sustainable and add to current knowledge of phenotypical variability in a species widely distributed along the Western Atlantic coast.

Quantifying nonlinear temporal effects of ethanol preservation on round goby (Neogobius melanostomus) anatomical traits

Geometric morphometrics provides a powerful means of evaluating differences in phenotypic traits among specimens. However, inferences of trait variability can be confounded when measurements are based on preserved samples. We evaluated effects of ethanol preservation on morphology over a 22-week time period for a Laurentian Great Lakes invasive fish, round goby (Neogobius melanostomus, Pallas 1814), using sets of 17 lateral and six dorsal landmarks. We tested whether ethanol preservation affected the magnitude of inter-population variation between individuals collected from lake and river habitats. Generalized least square regression determined that length did not significantly vary through the preservation time series for fish from either population, while mass decreased significantly. Body shape variation was summarized using principal component analysis, which revealed that most preservation-associated changes occurred in the first 14 days. The lateral shape experienced a large magnitude change during the first 24 h in ethanol then only minor changes for the remainder of the study. The dorsal shape began to revert to pre-preservation measurements about 14 days following preservation. Additionally, differences in shape were apparent between the two populations throughout the experiment; however, the magnitude of differences between populations varied depending on whether dorsal or lateral landmarks were considered. Our study demonstrates that tissue responses to ethanol preservation can be more complex than a simple loss of mass, resulting in difficult to predict consequences for geometric morphometric analyses, including variable responses depending on the anatomical region being analyzed.

Measurement error using a SeeMaLab structured light 3D scanner against a Microscribe 3D digitizer

Background

Geometric morphometrics is a powerful approach to capture and quantify morphological shape variation. Both 3D digitizer arms and structured light surface scanners are portable, easy to use, and relatively cheap, which makes these two capturing devices obvious choices for geometric morphometrics. While digitizer arms have been the “gold standard”, benefits of having full 3D models are manifold. We assessed the measurement error and investigate bias associated with the use of an open-source, high-resolution structured light scanner called SeeMaLab against the popular Microscribe 3D digitizer arm.

Methodology

The analyses were based on 22 grey seal (Halichoerus grypus) skulls. 31 fixed anatomical landmarks were annotated both directly using a Microscribe 3D digitizer and on reconstructed 3D digital models created from structured light surface scans. Each skull was scanned twice. Two operators annotated the landmarks, each twice on all the skulls and 3D models, allowing for the investigation of multiple sources of measurement error. We performed multiple Procrustes ANOVAs to compare the two devices in terms of within- and between-operator error, to quantify the measurement error induced by device, to compare between-device error with other sources of variation, and to assess the level of scanning-related error. We investigated the presence of general shape bias due to device and operator.

Results

Similar precision was obtained with both devices. If landmarks that were identified as less clearly defined and thus harder to place were omitted, the scanner pipeline would achieve higher precision than the digitizer. Between-operator error was biased and seemed to be smaller when using the scanner pipeline. There were systematic differences between devices, which was mainly driven by landmarks less clearly defined. The factors device, operator and landmark replica were all statistically significant and of similar size, but were minor sources of total shape variation, compared to the biological variation among grey seal skulls. The scanning-related error was small compared to all other error sources.

Conclusions

As the scanner showed precision similar to the digitizer, a scanner should be used if the advantages of obtaining detailed 3D models of a specimen are desired. To obtain high precision, a pre-study should be conducted to identify difficult landmarks. Due to the observed bias, data from different devices and/or operators should not be combined when the expected biological variation is small, without testing the landmarks for repeatability across platforms and operators. For any study necessitating the combination of landmark measurements from different operators, the scanner pipeline will be better suited. The small scanning-related error indicates that by following the same scanning protocol, different operators can be involved in the scanning process without introducing significant error.

Optimizing digitalization effort in morphometrics

Quantifying phenotypes is a common practice for addressing questions regarding morphological variation. The time dedicated to data acquisition can vary greatly depending on methods and on the required quantity of information. Optimizing digitization effort can be done either by pooling datasets among users, by automatizing data collection, or by reducing the number of measurements. Pooling datasets among users is not without risk since potential errors arising from multiple operators in data acquisition prevent combining morphometric datasets. We present an analytical workflow to estimate within and among operator biases and to assess whether morphometric datasets can be pooled. We show that pooling and sharing data requires careful examination of the errors occurring during data acquisition, that the choice of morphometric approach influences amount of error, and that in some cases pooling data should be avoided. The demonstration is based on a worked example (Sus scrofa teeth) using a combinations of 18 morphometric approaches and datasets for which we identified and quantified several potential sources of errors in the workflow. We show that it is possible to estimate the analytical power of a study using a small subset of data to select the best morphometric protocol and to optimize the number of variables necessary for analysis. In particular, we focus on semi-landmarks, which often produce an inflation of variables in contrast to the number of available observations use in statistical testing. We show how the workflow can be used for optimizing digitization efforts and provide recommendations for best practices in error management.

Comparison of Specimen- and Image-Based Morphometrics for Cisco

Morphometric data from fish are typically generated using one of two methods: direct measurements made on a specimen or extraction of distances from a digital picture. We compared data on 12 morphometrics collected with these two methods on the same collection of Cisco Coregonus artedi from Lake Ontario, North America, to assess the degree of bias in measurements made directly on a specimen- vs. an image-based method. We also assessed the degree of reproducibility within the image-based method by evaluating the amount of variation between different analysts for each morphometric method. Our results indicate specific morphometrics may be more prone to bias across the two methods and between analysts. Four of 12 morphometrics evaluated showed significant deviation from a 1:1 relationship that would be expected if the imaged-based method produced accurate specimen-based measurements. Pelvic fin length and pelvic–anal fin distance had the highest between-analyst variation for image-based landmarks, indicating low reproducibility for these metrics, compared with pectoral fin or total length, which had lower between-analyst variation. Although some morphometric measurements can be accurately obtained with either method, and therefore potentially used interchangeably in studies on Cisco morphology, our findings highlight the importance of considering method bias in morphometric studies that use data collected by different methods.

Testing repeatability, measurement error and species differentiation when using geometric morphometrics on complex shapes: a case study of Patagonian lizards of the genus Liolaemus (Squamata: Liolaemini)

The repeatability of findings is the key factor behind scientific reliability, and the failure to reproduce scientific findings has been termed the ‘replication crisis’. Geometric morphometrics is an established tool in evolutionary biology. However, different operators (and/or different methods) could act as large sources of variation in the data obtained. Here, we investigated inter-operator error in geometric morphometric protocols on complex shapes of Liolaemus lizards, as well as measurement error in three taxa varying in their difficulty of digitalization. We also examined the potential for these protocols to discriminate among complex shapes in closely related species. We found a wide range of inter-operator error, contributing between 19.5% and 60% to the total variation. Moreover, measurement error increased with the complexity of the quantified shape. All protocols were able to discriminate between species, but the use of more landmarks did not imply better performance. We present evidence that complex shapes reduce repeatability, highlighting the need to explore different sources of variation that could lead to such low repeatability. Lastly, we suggest some recommendations to improve the repeatability and reliability of geometric morphometrics results.

Are geometric morphometric analyses replicable? Evaluating landmark measurement error and its impact on extant and fossil Microtus classification

Geometric morphometric analyses are frequently employed to quantify biological shape and shape variation. Despite the popularity of this technique, quantification of measurement error in geometric morphometric datasets and its impact on statistical results is seldom assessed in the literature. Here, we evaluate error on 2D landmark coordinate configurations of the lower first molar of five North American Microtus (vole) species. We acquired data from the same specimens several times to quantify error from four data acquisition sources: specimen presentation, imaging devices, interobserver variation, and intraobserver variation. We then evaluated the impact of those errors on linear discriminant analysis-based classifications of the five species using recent specimens of known species affinity and fossil specimens of unknown species affinity. Results indicate that data acquisition error can be substantial, sometimes explaining >30% of the total variation among datasets. Comparisons of datasets digitized by different individuals exhibit the greatest discrepancies in landmark precision, and comparison of datasets photographed from different presentation angles yields the greatest discrepancies in species classification results. All error sources impact statistical classification to some extent. For example, no two landmark dataset replicates exhibit the same predicted group memberships of recent or fossil specimens. Our findings emphasize the need to mitigate error as much as possible during geometric morphometric data collection. Though the impact of measurement error on statistical fidelity is likely analysis-specific, we recommend that all geometric morphometric studies standardize specimen imaging equipment, specimen presentations (if analyses are 2D), and landmark digitizers to reduce error and subsequent analytical misinterpretations.