Biology subjects

Siler, C. D.

Publications and source records attributed to Siler, C. D..

6 recordsLinked to original sources

bioRxiv2026

Exploring the diversity and community structure of the Testudines fecal mycobiome

Most gut microbiome studies have focused on bacteria, leaving a knowledge gap regarding gut associated fungi. We assessed fungal diversity in the gastrointestinal tract of the reptilian order Testudines (turtles and tortoises) using samples from 6 families, 19 genera, and 27 species. A highly diverse community affiliated with 17 phyla and 157 orders was encountered, with four phyla (Neocallimastigomycota, Chytridiomycota, Ascomycota, and Basidiomycota) representing 89.13% of the community. Neocallimastigomycota was identified in host families Testudinidae (land tortoises), Chelidae, Chelydridae, Emydidae, Geoemydidae, and Kinosternidae, with higher relative abundances in Testudinidae (40.18{+/-}37.97%) compared to all other families combined (2.71{+/-}4.04%). Neocallimastigomycota sequences were mostly affiliated with orders Testudinimycetales in the host family Testudinidae and Neocallimastigales in other host families. Chytridiomycota was identified in all host families, but was more ubiquitous and abundant in Kinosternidiae (45.17{+/-}34.12%), and exhibited a high level of variability across samples. Dikarya communities were highly diverse, with 108 orders identified, and, similar to Chytridiomoycota, exhibited a highly stochastic distribution pattern. Representatives of multiple yet-uncultured phyla (Candidatus "Algovoracomycota", "Sedimentomastigomycota", "Tartumycota" and "Cantoromastigomycota") were identified, as well as eight novel orders in Chytridiomycota and Rozellomycota. Deterministic selection shaped community assembly in the host family Testudinidae, while the process was more stochastic in other host families. Distinct community structure was driven by differences in abundance and identity of the Neocallimastigomycota when comparing Testudinidae to. Our results describe a diverse and dynamic fungal community, shaped by the co-occurrence of autochthonous (resident) and transient (allochthonous) members of the gut microbiome. ImportanceFungi are known to inhabit the gastrointestinal tract (GIT) of humans and mammals. However, information on the fungal community in the GIT of reptiles is relatively sparse. We investigated the diversity and community structure of fungi in the reptilian order Testudines. We conducted a culture-independent diversity survey on fecal samples obtained from 27 different host species. We identify representatives of 17 fungal phyla. As well, we demonstrate that the anaerobic gut fungi (phylum Neocallimastigomycota) are not restricted to the family Testudinidae (land tortoises) as previously suggested, but could successfully colonize and inhabit all other testudines families, including those exhibiting a predominantly omnivorous or carnivorous lifestyles. In addition, we expand on the known fungal diversity by identifying additional representatives of multiple recently described yet-uncultured phyla, and describe multiple novel orders and classes within existing phyla. Collectively, this effort adds to the growing body of knowledge of mycobiomes in underexplored animal hosts.

microbiology↗

bioRxiv2024

A hybrid approach to invertebrate biomonitoring using computer vision and DNA metabarcoding

O_LIAutomated invertebrate classification using computer vision has shown significant potential to improve specimen processing efficiency. However, challenges such as invertebrate diversity and morphological similarity among taxa can make it difficult to infer fine-scale taxonomic classifications using computer vision. As a result, many invertebrate computer vision models are forced to make classifications at coarser levels, such as at family or order. C_LIO_LIHere we propose a novel modular method to combine computer vision and bulk DNA metabarcoding specimen processing pipelines to improve the accuracy and taxonomic granularity of individual specimen classifications. To improve specimen classification accuracy, our methods use multimodal fusion models that combine image data with DNA-based assemblage data. To refine the taxonomic granularity of the models classifications, our methods cross-references the classifications with DNA metabarcoding detections from bulk samples. We demonstrated these methods using a continental-scale, invertebrate bycatch dataset collected by the National Ecological Observatory Network. We also introduce the CV.eDNA R package, which aims to assist practitioners looking to implement our methods. C_LIO_LIUsing our methods, we reached a classification accuracy of 79.6% across the 17 taxa using real DNA assemblage data, and 83.6% when the assemblage data was "error-free", resulting in a 2.2% and 6.2% increase in accuracy when compared to a model trained using only images. After cross-referencing with the DNA metabarcoding detections, we improved taxonomic granularity in up to 72.2% of classifications, with up to 5.7% reaching species-level. C_LIO_LIBy providing computer vision models with coincident DNA assemblage data, and refining individual classifications using DNA metabarcoding detections, our methods the potential to greatly expand the capabilities of biological computer vision classifiers. Our methods allow computer vision classifiers to infer taxonomically fine-grained classifications when it would otherwise be difficult or impossible due to challenges of morphologic similarity or data scarcity. These methods are not limited to terrestrial invertebrates and could be applied in any instance where image and DNA metabarcoding data are concurrently collected. C_LI

bioinformatics↗

bioRxiv2021

Embracing imperfection: machine-assisted invertebrate classification in real-world datasets

O_LIDespite growing concerns over the health of global invertebrate diversity, terrestrial invertebrate monitoring efforts remain poorly geographically distributed. Machine-assisted classification has been proposed as a potential solution to quickly gather large amounts of data; however, previous studies have often used unrealistic or idealized datasets to train their models. C_LIO_LIIn this study, we describe a practical methodology for including machine learning in ecological data acquisition pipelines. Here we train and test machine learning algorithms to classify over 56,000 bulk terrestrial invertebrate specimens from morphometric data and contextual metadata. All vouchered specimens were collected in pitfall traps by the National Ecological Observatory Network (NEON) at 27 locations across the United States in 2016. Specimens were photographed, and morphometric data was extracted as feature vectors using ImageJ. Issues stemming from inconsistent taxonomic label specificity were resolved by making classifications at the lowest identified taxonomic level (LITL). Taxa with too few specimens to be included in the training dataset were classified by the model using zero-shot classification. C_LIO_LIWhen classifying specimens that were known and seen by our models, we reached an accuracy of 72.7% using extreme gradient boosting (XGBoost) at the LITL. Models that were trained without contextual metadata underperformed models with contextual metadata by an average of 7.2%. We also classified invertebrate taxa that were unknown to the model using zero-shot classification, with an accuracy of 39.4%, resulting in an overall accuracy of 71.5% across the entire NEON dataset. C_LIO_LIThe general methodology outlined here represents a realistic application of machine learning as a tool for ecological studies. Hierarchical and LITL classifications allow for flexible taxonomic specificity at the input and output layers. These methods also help address the long tail problem of underrepresented taxa missed by machine learning models. Finally, we encourage researchers to consider more than just morphometric data when training their models, as we have shown that the inclusion of contextual metadata can provide significant improvements to accuracy. C_LI

ecology↗

bioRxiv2020

Hidden limbs in the limbless skink Brachymeles lukbani: developmental observations

Reduced limbs and limblessness have evolved independently in many lizard clades. Skinks exhibit a wide range of limb-reduced morphologies, but only some species have been used to study the embryology of limb reduction (i.g., digit reduction in Chalcides and limb reduction in Scelotes). The genus Brachymeles, a Southeast Asian clade of skinks, includes species with a range of limb morphologies, from pentadactyl to functionally as well as structurally limbless species. Adults of the small, snake-like species Brachymeles lukbani show no sign of external limbs in the adult except for small depressions where they might be expected to occur. Embryos of B. lukbani in early stages of development, on the other hand, show a truncated but well-developed limb with a stylopod and a zeugopod, but no signs of an autopod. As development proceeds, the limbs small size persists even while the embryo elongates. These observations are made based on external morphology. We used florescent whole-mount immunofluorescence to visualize the morphology of skeletal elements and muscles within the embryonic limb of B. lukabni. Early stages have a humerus and separated ulna and radius cartilages; associated with these structures are dorsal and ventral muscle masses as those found in the embryos of other limbed species. While the limb remains small, the pectoral girdle grows in proportion to the rest of the body, with well-developed skeletal elements and their associated muscles. In later stages of development, the small limb is still present under the skin but there are few indications of its presence, save for the morphology of the scale covering it. The adult morphology consists of a well-developed pectoral girdle, small humerus, extremely reduced ulna and radius, and well-developed limb musculature connected to the pectoral girdle. These muscles form in association with a developing limb during embryonic stages, a hint that "limbless" lizards that possesses these muscles may have or have had at least transient developing limbs, as we find in B. lukbani. Overall, the observed pattern of ontogenetic reduction, leading to an externally limbless adult in which a limb rudiment is hidden and covered under the trunk skin, is a situation called cryptomelia. The results of this work add to our growing understanding of clade-specific patterns of limb reduction and the convergent evolution of limbless phenotypes through different developmental processes.

evolutionary biology↗

bioRxiv2019

Parachute geckos free fall into synonymy: Gekko phylogeny, and a new subgeneric classification, inferred from thousands of ultraconserved elements

Recent phylogenetic studies of gekkonid lizards have revealed unexpected, widespread paraphyly and polyphyly among genera, unclear generic boundaries, and a tendency towards the nesting of taxa exhibiting specialized, apomorphic morphologies within geographically widespread \"generalist\" clades. This is especially true in the Australasia, where the monophyly of Gekko proper has been questioned with respect to phenotypically ornate flap-legged geckos of the genus Luperosaurus, the Philippine false geckos of the genus Pseudogekko, and even the elaborately \"derived\" parachute geckos of the genus Ptychozoon. Here we employ sequence capture targeting 5060 ultraconserved elements to infer phylogenomic relationships among 42 representative ingroup gekkonine lizard taxa. We analyzed multiple datasets of varying degrees of completeness (10, 50, 75, 95, and 100 percent complete with 4715, 4051, 3376, 2366, and 772 UCEs, respectively) using concatenated maximum likelihood and multispecies coalescent methods. Our sampling scheme was designed to address four persistent systematic questions in this group: (1) Are Luperosaurus and Ptychozoon monophyletic and are any of these named species truly nested within Gekko? (2) Are prior phylogenetic estimates of Sulawesis L. iskandari as sister to Melanesian G. vittatus supported by our genome-scale dataset? (3) Is the high elevation L. gulat of Palawan Island correctly placed within Gekko? (4) And, finally, where do the enigmatic taxa P. rhacophorus and L. browni fall in a higher-level gekkonid phylogeny? We resolve these issues; confirm with strong support some previously inferred findings (placement of Ptychozoon taxa within Gekko; the sister relationship between L. iskandari and G. vittatus); resolve the systematic position of unplaced taxa (L. gulat, and L. browni); and transfer L. iskandari, L. gulat, L. browni, and all members of the genus Ptychozoon to the genus Gekko. Our unexpected and novel systematic inference of the placement of Ptychozoon rhacophorus suggests that this species is not related to Ptychozoon or even Luperosaurus (as previously expected) but may, in fact, be most closely related to several Indochinese species of Gekko. With our final, well-supported topologies, we recognize seven newly defined subgenera to accommodate [~]60 species within the more broadly defined and maximally-inclusive Australasian genus Gekko. The newly defined subgenera will aide taxonomists and systematists in species descriptions by allowing them to only diagnose putatively new species from the most relevant members of the same subgenus, not necessarily the phenotypically variable genus Gekko as a whole, and we argue that it appropriately recognizes geographically circumscribed units (e.g., a new subgenus for a novel clade, entirely endemic to the Philippines) while simultaneously recognizing several of the most systematically controversial, phenotypically distinct, and phylogenetically unique lineages. An added benefit of recognizing the most inclusive definition of Gekko, containing multiple phylogenetically-defined subgenera, is that this practice has the potential to alleviate taxonomic vandalism, if widely adopted, by creating formally available, supraspecific taxa, accompanied by character-based diagnoses and properly assigned type species, such that future, more atomized classifications would necessarily be required to adopt todays subgenera as tomorrows genera under the guidelines of The Code of Zoological Nomenclature. Not only does this simple practice effectively eliminate the nefarious motivation behind taxonomic vandalism, but it also ensures that supraspecific names are created only when accompanied by data, that they are coined with reference to a phylogenetic estimate, and that they explicitly involve appropriate specifiers in the form of type species and, ultimately, type specimens.

zoology↗

bioRxiv2018

The comparative biogeography of geckos challenges predictions from a paradigm of climate-driven vicariant diversification across an island archipelago

A primary goal of biogeography is to understand how large-scale environmental processes, like climate change, affect diversification One often-invoked but seldom tested process is the \"species-pump\" model, in which repeated bouts of co-speciation are driven by oscillating climate-induced habitat connectivity cycles. For example, over the past three million years, the landscape of the Philippine Islands has repeatedly coalesced and fragmented due to sea-level changes associated with glacial cycles. This repeated climate-driven vicariance has been proposed as a model of speciation across evolutionary lineages codistributed throughout the islands. This model predicts speciation times that are temporally clustered around the times when interglacial rises in sea level fragmented the islands. To test this prediction, we collected comparative genomic data from 16 pairs of insular gecko populations. We analyze these data in a full-likelihood, Bayesian model-choice framework to test for shared divergence times among the pairs. Our results provide support against the species-pump model prediction in favor of an alternative interpretation, namely that each pair of gecko populations diverged independently. These results suggest the repeated bouts of climate-driven landscape fragmentation has not been an important mechanism of speciation for gekkonid lizards on the Philippine Islands.

evolutionary biology↗