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      Predicting the Occurrence of Cave-Inhabiting Fauna Based on Features of the Earth Surface Environment

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          Abstract

          One of the most challenging fauna to study in situ is the obligate cave fauna because of the difficulty of sampling. Cave-limited species display patchy and restricted distributions, but it is often unclear whether the observed distribution is a sampling artifact or a true restriction in range. Further, the drivers of the distribution could be local environmental conditions, such as cave humidity, or they could be associated with surface features that are surrogates for cave conditions. If surface features can be used to predict the distribution of important cave taxa, then conservation management is more easily obtained. We examined the hypothesis that the presence of major faunal groups of cave obligate species could be predicted based on features of the earth surface. Georeferenced records of cave obligate amphipods, crayfish, fish, isopods, beetles, millipedes, pseudoscorpions, spiders, and springtails within the area of Appalachian Landscape Conservation Cooperative in the eastern United States (Illinois to Virginia and New York to Alabama) were assigned to 20 x 20 km grid cells. Habitat suitability for these faunal groups was modeled using logistic regression with twenty predictor variables within each grid cell, such as percent karst, soil features, temperature, precipitation, and elevation. Models successfully predicted the presence of a group greater than 65% of the time (mean = 88%) for the presence of single grid cell endemics, and for all faunal groups except pseudoscorpions. The most common predictor variables were latitude, percent karst, and the standard deviation of the Topographic Position Index (TPI), a measure of landscape rugosity within each grid cell. The overall success of these models points to a number of important connections between the surface and cave environments, and some of these, especially soil features and topographic variability, suggest new research directions. These models should prove to be useful tools in predicting the presence of species in understudied areas.

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          Most cited references 4

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          Climate Change and the Future of California's Endemic Flora

          The flora of California, a global biodiversity hotspot, includes 2387 endemic plant taxa. With anticipated climate change, we project that up to 66% will experience >80% reductions in range size within a century. These results are comparable with other studies of fewer species or just samples of a region's endemics. Projected reductions depend on the magnitude of future emissions and on the ability of species to disperse from their current locations. California's varied terrain could cause species to move in very different directions, breaking up present-day floras. However, our projections also identify regions where species undergoing severe range reductions may persist. Protecting these potential future refugia and facilitating species dispersal will be essential to maintain biodiversity in the face of climate change.
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            Evidence for repeated loss of selective constraint in rhodopsin of amblyopsid cavefishes (Teleostei: Amblyopsidae).

            The genetic mechanisms underlying regressive evolution-the degeneration or loss of a derived trait--are largely unknown, particularly for complex structures such as eyes in cave organisms. In several eyeless animals, the visual photoreceptor rhodopsin appears to have retained functional amino acid sequences. Hypotheses to explain apparent maintenance of function include weak selection for retention of light-sensing abilities and its pleiotropic roles in circadian rhythms and thermotaxis. In contrast, we show that there has been repeated loss of functional constraint of rhodopsin in amblyopsid cavefishes, as at least three cave lineages have independently accumulated unique loss-of-function mutations over the last 10.3 Mya. Although several cave lineages still possess functional rhodopsin, they exhibit increased rates of nonsynonymous mutations that have greater effect on the structure and function of rhodopsin compared to those in surface lineages. These results indicate that functionality of rhodopsin has been repeatedly lost in amblyopsid cavefishes. The presence of a functional copy of rhodopsin in some cave lineages is likely explained by stochastic accumulation of mutations following recent subterranean colonization. © 2012 The Author(s). Evolution© 2012 The Society for the Study of Evolution.
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              Making more out of sparse data: hierarchical modeling of species communities.

              Community ecologists and conservation biologists often work with data that are too sparse for achieving reliable inference with species-specific approaches. Here we explore the idea of combining species-specific models into a single hierarchical model. The community component of the model seeks for shared patterns in how the species respond to environmental covariates. We illustrate the modeling framework in the context of logistic regression and presence-absence data, but a similar hierarchical structure could also be used in many other types of applications. We first use simulated data to illustrate that the community component can improve parameterization of species-specific models especially for rare species, for which the data would be too sparse to be informative alone. We then apply the community model to real data on 500 diatom species to show that it has much greater predictive power than a collection of independent species-specific models. We use the modeling approach to show that roughly one-third of distance decay in community similarity can be explained by two variables characterizing water quality, rare species typically preferring nutrient-poor waters with high pH, and common species showing a more general pattern of resource use.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                17 August 2016
                2016
                : 11
                : 8
                Affiliations
                [1 ]Departments of Biology and of Statistics, University of Florida, Gainesville, Florida, and MCC Statistical Consulting LLC, Gainesville, Florida, United States of America
                [2 ]U. S. Geological Survey, Reston, Virginia, United States of America
                [3 ]Illinois Natural History Survey, Prairie Research Institute, University of Illinois at Urbana-Champaign, Champaign, Illinois, United States of America
                [4 ]U. S. Geological Survey, Leetown Science Center, Kearneysville, West Virginia, United States of America
                [5 ]Department of Biology, The University of the South, Sewanee, Tennessee, United States of America
                [6 ]Department of Environmental Science, American University, Washington, District of Columbia, United States of America
                University of New England, AUSTRALIA
                Author notes

                Competing Interests: The affiliation of Mary C Christman with the commercial company MCC Statistical Consulting LLC does not alter the authors' adherence to PLOS ONE policies on data and materials.

                • Conceived and designed the experiments: MCC DCC.

                • Performed the experiments: DHD MLN DJW KSZ DCC.

                • Analyzed the data: MCC JAY.

                • Contributed reagents/materials/analysis tools: DHD DJW JAY MCC KSZ MLN.

                • Wrote the paper: DCC.

                ‡ These authors also contributed equally to this work.

                Article
                PONE-D-15-56001
                10.1371/journal.pone.0160408
                4988700
                27532611

                This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

                Page count
                Figures: 5, Tables: 3, Pages: 19
                Product
                Funding
                Funded by: Wildlife Management Institute through Appalachian Land Conservation Cooperative
                Award ID: ALCC2013-04
                Award Recipient :
                This work was supported by the Wildlife Management Institute through the Appalachian Land Conservation Cooperative (ALCC 2013-4) to DCC. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. One author (MCC) is employed by a commercial company, MCC Statistical Consulting LCC. The funder provided support in the form of salaries for an author [MCC], but did not have any additional role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific role of this author is articulated in the ‘author contributions’ section.
                Categories
                Research Article
                Earth Sciences
                Geomorphology
                Topography
                Landforms
                Caves
                Earth Sciences
                Geomorphology
                Topography
                Landforms
                Plateaus
                Earth Sciences
                Geomorphology
                Topography
                Karst Features
                Earth Sciences
                Geography
                Cartography
                Latitude
                Biology and Life Sciences
                Organisms
                Animals
                Invertebrates
                Arthropoda
                Crustaceans
                Isopods
                Biology and Life Sciences
                Organisms
                Animals
                Invertebrates
                Arthropoda
                Crustaceans
                Crayfish
                Biology and Life Sciences
                Organisms
                Animals
                Invertebrates
                Arthropoda
                Insects
                Beetles
                Ecology and Environmental Sciences
                Conservation Science
                Custom metadata
                Except for cave locations, all relevent data are in the paper and supporting information. Cave location information is not public information due to the sensitivity of the information, data sharing agreements, as well as restrictions under the Federal Cave Resources Protection Act of 1988. Persons wishing to access the cave location data should contact Matthew L. Niemiller, Illinois Natural History Survey, University of Illinois Urbana- Champaign, 1816 Oak Street, Champaignk IL 61820 Email: cavemander17@ 123456gmail.com .

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