Species delimitation in endangered groundwater salamanders: Implications for aquifer management and biodiversity conservation

Devitt, Thomas J.; Wright, April M.; Cannatella, David C.; Hillis, David M.

doi:10.1073/pnas.1815014116

Cited by 100 publications

(108 citation statements)

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“…Central Texas, USA is home to a diverse group of fully-aquatic salamanders in the genus Eurycea, which inhabit spring and aquifer systems (Devitt et al, 2019). The San Marcos salamander (E. nana), is federally threatened and endemic to the headwaters of the San Marcos River (Nelson, 1993), an area with a diverse assemblage of native and introduced predatory fish.…”

Section: Spring-endemic Salamander and The Threat Of Predation By Intmentioning

confidence: 99%

Non-invasive Methods for Measuring and Monitoring Stress Physiology in Imperiled Amphibians

et al. 2019

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Global climate change is negatively impacting global biodiversity and ectothermic vertebrates, with amphibians being the most imperiled vertebrate taxa. Increased mean global atmospheric temperatures, high rates of habitat degradation, and exposure to infectious diseases, such as chytridiomycosis, have contributed to population declines and extinctions of rare and endangered amphibian species. Field-based monitoring of physiological endocrine traits can help determine the sub-lethal effects of environmental stressors and provide early alerts when populations are chronically stressed. Recent advances in amphibian stress endocrinology include the development and use of non-invasive methods to quantify the glucocorticoid, or stress biomarker, corticosterone. Non-invasive methods, such as urinary, skin and buccal swabs, and water-borne hormone monitoring methods (suited for terrestrial and aquatic dwelling species), are available to quantify baseline and short-term physiological stress responses of amphibians under field settings. In this review, we illustrate, by using two case studies of aquatic and terrestrial amphibian species, the applications of non-invasive corticosterone monitoring methods to advance the ecological knowledge and conservation of imperiled amphibian species, discuss the limitations of these methods, and provide future directions for the use of non-invasive hormone monitoring methods. We highlight the use of non-invasive field endocrinology methods to monitor the impacts of environmental stressors on the physiology of amphibians, which can be applied to advance ecological research, conservation, and management of imperiled species.

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Section: Spring-endemic Salamander and The Threat Of Predation By Intmentioning

confidence: 99%

Non-invasive Methods for Measuring and Monitoring Stress Physiology in Imperiled Amphibians

et al. 2019

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“…Despite these limitations, MSC-based analyses can be highly informative about species delimitation, especially when they integrate information from other analyses, and when sampling is adequate to consider potential contact zones and gene flow among connected populations (e.g., Chan et al, 2017;Nieto-Montes de Oca et al, 2017;Devitt et al, 2019). The depth of information from genomic studies can be combined with the breadth of data from better-sampled morphological, ecological, and behavioral studies to produce comprehensive, robust, and stable species delimitation.…”

mentioning

confidence: 99%

Species Delimitation in Herpetology

Hillis

2019

Journal of Herpetology

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124

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“…This approach has been exploited in work that has attracted the attention of biologists (Chifman and Kubatko, 2014;Fernández-Sánchez and Casanellas, 2016), and has allowed a generalization to the multispecies coalescent model and the use of these methods to estimate, not only gene trees, but also species trees (Chifman and Kubatko, 2015). Some of these methods have been implemented in PAUP* (Swofford, 2003), one of the most widely used software packages in phylogenetics, which has opened the use of these tools to the biological community at large and has allowed the application in areas such as biodiversity preservation (Devitt et al, 2019).…”

Section: Consider Nowmentioning

confidence: 99%

Algebraic Statistics in Practice: Applications to Networks

Casanellas

Petrović

Uhler

2020

Annu. Rev. Stat. Appl.

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Algebraic statistics uses tools from algebra (especially from multilinear algebra, commutative algebra and computational algebra), geometry and combinatorics to provide insight into knotty problems in mathematical statistics. In this survey we illustrate this on three problems related to networks, namely network models for relational data, causal structure discovery and phylogenetics. For each problem we give an overview of recent results in algebraic statistics with emphasis on the statistical achievements made possible by these tools and their practical relevance for applications to other scientific disciplines. 1 arXiv:1906.09537v1 [math.ST] 23 Jun 2019 Casanellas, Petrović, Uhler /Algebraic Statistics in Practice 2the nodes of an unknown underlying causal network), and phylogenetics (a particular network structure discovery problem where the underlying network is a tree with latent variables).Section 2 focuses on statistical models for relational data, typical uses of which arise in the social and biological sciences. In these applications, nodes in the network may represent individuals, organizations, proteins, neurons, or brain regions, while links represent observed relationships between the nodes, such as personal or organizational affinities, social/financial relationships, binding between proteins or physical links between brain regions. A key problem in this area is to test whether a proposed statistical model fits the data at hand; such a test typically involves generating a sufficiently large and generic sample of networks from the model and comparing it to the observed network. Perhaps somewhat surprisingly, algorithms for sampling networks with given network statistics for goodness-of-fit testing are often efficiently encoded by algebraic constraints. In Section 2, we outline how techniques from commutative algebra and combinatorics are applied to this problem for several families of network models for which a formal test is otherwise unavailable.In Section 3, we turn to applications where the network structure cannot directly be observed and we only have access to observations on the nodes of the network. Such applications range from data on consumer behavior to click statistics for ads or websites, DNA sequences of related species, gene expression data, etc. The use of such data to gain insight into complex phenomena requires characterizing the relationships among the observed variables. Probabilistic graphical models explicitly capture the statistical relationships between the variables as a network. A good representation of a complex system should not only enable predicting the state of one component given others, but also the effect that local operations have on the global system. This requires causal modeling and making use of interventional data. In Section 3, we discuss the role that algebraic and discrete geometry play in analyzing prominent algorithms for causal structure discovery and in developing the first provably consistent algorithms for causal inference from a mix of observational ...

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Species delimitation in endangered groundwater salamanders: Implications for aquifer management and biodiversity conservation

Cited by 100 publications

References 111 publications

Non-invasive Methods for Measuring and Monitoring Stress Physiology in Imperiled Amphibians

Non-invasive Methods for Measuring and Monitoring Stress Physiology in Imperiled Amphibians

Species Delimitation in Herpetology

Algebraic Statistics in Practice: Applications to Networks

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