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Geology topics

David A. W. Miller

Publications and source records attributed to David A. W. Miller.

14 recordsLinked to original sources
USGS2024

Range-wide salamander densities reveal a key component of terrestrial vertebrate biomass in eastern North American forests

Characterizing the population density of species is a central interest in ecology. Eastern North America is the global hotspot for biodiversity of plethodontid salamanders, an inconspicuous component of terrestrial vertebrate communities, and among the most widespread is the eastern red-backed salamander, Plethodon cinereus . Previous work suggests population densities are high with significant geographic variation, but comparisons among locations are challenged by lack of standardization of methods and failure to accommodate imperfect detection. We present results from a large-scale research network that accounts for detection uncertainty using systematic survey protocols and robust statistical models. We analysed mark–recapture data from 18 study areas across much of the species range. Estimated salamander densities ranged from 1950 to 34 300 salamanders ha −1 , with a median of 9965 salamanders ha −1 . We compared these results to previous estimates for P. cinereus and other abundant terrestrial vertebrates. We demonstrate that overall the biomass of P. cinereus , a secondary consumer, is of similar or greater magnitude to widespread primary consumers such as white-tailed deer ( Odocoileus virginianus ) and Peromyscus mice, and two to three orders of magnitude greater than common secondary consumer species. Our results add empirical evidence that P. cinereus , and amphibians in general, are an outsized component of terrestrial vertebrate communities in temperate ecosystems.

Biology Letters↗
USGS2024

Updated range map of an endangered salamander and congeneric competitor reveals different niche preferences

Estimating distributions for cryptic and highly range-restricted species induces unique challenges for species distribution modeling. In particular, bioclimatic covariates that are typically used to model species ranges at regional and continental scales may not show strong variation at scales of 100s and 10s of meters. This limits both the likelihood and usefulness of correlated occurrence to data typically used in distribution models. Here, we present analyses of species distributions, at 100 × 100 m resolution, for a highly range restricted salamander species (Shenandoah salamander, Plethodon shenandoah ) and a closely related congener (red-backed salamander, Plethodon cinereus ). We combined data across multiple survey types, account for seasonal variation in availability of our target species, and control for repeated surveys at locations– all typical challenges in range-scale monitoring datasets. We fit distribution models using generalized additive models that account for spatial covariates as well as unexplained spatial variation and spatial uncertainty. Our model accommodates different survey protocols using offsets and incorporates temporal variation in detection and availability resulting from survey-specific variation in temperature and precipitation. Our spatial random effect was crucial in identifying small-scale differences in the occurrence of each species and provides cell-specific estimates of uncertainty in the density of salamanders across the range. Counts of both species were seen to increase in the 3 days following a precipitation event. However, P. cinereus were observed even in extremely wet conditions, while surface activity of P. shenandoah was associated with a more narrow range. Our results demonstrate how a flexible analytical approach improves estimates of both distribution and uncertainty, and identify key abiotic relationships, even at small spatial scales and when scales of empirical data are mismatched. While our approach is especially valuable for species with small ranges, controlling for spatial autocorrelation, estimating spatial uncertainty, and incorporating survey-specific information in estimates can improve the reliability of distribution models in general.

Ecology and Evolution↗
USGS2022

A practical guide to understanding and validating complex models using data simulations

Biologists routinely fit novel and complex statistical models to push the limits of our understanding. Examples include, but are not limited to, flexible Bayesian approaches (e.g. BUGS, stan), frequentist and likelihood-based approaches (e.g. packages lme4 ) and machine learning methods. These software and programs afford the user greater control and flexibility in tailoring complex hierarchical models. However, this level of control and flexibility places a higher degree of responsibility on the user to evaluate the robustness of their statistical inference. To determine how often biologists are running model diagnostics on hierarchical models, we reviewed 50 recently published papers in 2021 in the journal Nature Ecology & Evolution , and we found that the majority of published papers did not report any validation of their hierarchical models, making it difficult for the reader to assess the robustness of their inference. This lack of reporting likely stems from a lack of standardized guidance for best practices and standard methods. Here, we provide a guide to understanding and validating complex models using data simulations. To determine how often biologists use data simulation techniques, we also reviewed 50 recently published papers in 2021 in the journal Methods Ecology & Evolution . We found that 78% of the papers that proposed a new estimation technique, package or model used simulations or generated data in some capacity (18 of 23 papers); but very few of those papers (5 of 23 papers) included either a demonstration that the code could recover realistic estimates for a dataset with known parameters or a demonstration of the statistical properties of the approach. To distil the variety of simulations techniques and their uses, we provide a taxonomy of simulation studies based on the intended inference. We also encourage authors to include a basic validation study whenever novel statistical models are used, which in general, is easy to implement. Simulating data helps a researcher gain a deeper understanding of the models and their assumptions and establish the reliability of their estimation approaches. Wider adoption of data simulations by biologists can improve statistical inference, reliability and open science practices.

Methods in Ecology and Evolution↗
USGS2022

Ignoring species availability biases occupancy estimates in single-scale occupancy models

Most applications of single-scale occupancy models do not differentiate between availability and detectability, even though species availability is rarely equal to one. Species availability can be estimated using multi-scale occupancy models; however, for the practical application of multi-scale occupancy models, it can be unclear what a robust sampling design looks like and what the statistical properties of the multi-scale and single-scale occupancy models are when availability is less than one. Using simulations, we explore the following common questions asked by ecologists during the design phase of a field study: (Q1) what is a robust sampling design for the multi-scale occupancy model when there are a priori expectations of parameter estimates? (Q2) what is a robust sampling design when we have no expectations of parameter estimates? and (Q3) can a single-scale occupancy model with a random effects term adequately absorb the extra heterogeneity produced when availability is less than one and provide reliable estimates of occupancy probability? Our results show that there is a tradeoff between the number of sites and surveys needed to achieve a specified level of acceptable error for occupancy estimates using the multi-scale occupancy model. We also document that when species availability is low (<0.40 on the probability scale), then single-scale occupancy models underestimate occupancy by as much as 0.40 on the probability scale, produce overly precise estimates, and provide poor parameter coverage. This pattern was observed when a random effects term was and was not included in the single-scale occupancy model, suggesting that adding a random-effects term does not adequately absorb the extra heterogeneity produced by the availability process. In contrast, when species availability was high (>0.60), single-scale occupancy models performed similarly to the multi-scale occupancy model. Users can further explore our results and sampling designs across a number of different scenarios using the RShiny app https://gdirenzo.shinyapps.io/multi-scale-occ/ . Our results suggest that unaccounted for availability can lead to underestimating species distributions when using single-scale occupancy models, which can have large implications on inference and prediction, especially for those working in the fields of invasion ecology, disease emergence, and species conservation.

Methods in Ecology and Evolution↗
USGS2021

Accommodating the role of site memory in dynamic species distribution models

First-order dynamic occupancy models (FODOMs) are a class of state-space model in which the true state (occurrence) is observed imperfectly. An important assumption of FODOMs is that site dynamics only depend on the current state and that variations in dynamic processes are adequately captured with covariates or random effects. However, it is often difficult to understand and/or measure the covariates that generate ecological data, which are typically spatiotemporally correlated. Consequently, the non-independent error structure of correlated data causes underestimation of parameter uncertainty and poor ecological inference. Here, we extend the FODOM framework with a second-order Markov process to accommodate site memory when covariates are not available. Our modeling framework can be used to make reliable inference about site occupancy, colonization, extinction, turnover, and detection probabilities. We present a series of simulations to illustrate the data requirements and model performance. We then applied our modeling framework to 13 yr of data from an amphibian community in southern Arizona, USA. In this analysis, we found residual temporal autocorrelation of population processes for most species, even after accounting for long-term drought dynamics. Our approach represents a valuable advance in obtaining inference on population dynamics, especially as they relate to metapopulations.

Arizona↗
USGS2021

The influence of species life history and distribution characteristics on species responses to habitat fragmentation in an urban landscape

Fragmentation within urbanized environments often leads to a loss of native species diversity; however, variation exists in responses among-species and among-populations within species. We aimed to identify patterns in species biogeography in an urbanized landscape to understand anthropogenic effects on vertebrate communities and identify species that are more sensitive or resilient to landscape change. We investigated patterns in species richness and species responses to fragmentation in southern Californian small vertebrate communities using multispecies occupancy models and determined factors associated with overall commonness and sensitivity to patch size for 45 small vertebrate species both among and within remaining non-developed patches. In general, smaller patches had fewer species, with amphibian species richness being particularly sensitive to patch size effects. Mammals were generally more common, occurring both in a greater proportion of patches and a higher proportion of the sites within occupied patches. Alternatively, amphibians were generally restricted to larger patches but were more ubiquitous within smaller patches when occupied. Species range size was positively correlated with how common a species was across and within patches, even when controlling for only patches that fell within a species' range. We found sensitivity to patch size was greater for more fecund species and depended on where the patch occurred within a species' range. While all taxa were more likely to occur in patches in the warmer portions of their ranges, amphibians and mammals were more sensitive to fragmentation in these warmer areas as compared to the rest of their ranges. Similarly, amphibians occurred at a smaller proportion of sites within patches in drier portions of their ranges. Mammals occurred at a higher proportion of sites that were also in drier portions of their range while reptiles did not differ in their sensitivity to patch size by range position. We demonstrate that taxonomy, life history, range size and range position can predict commonness and sensitivity of species across this highly fragmented yet biodiverse landscape. The impacts of fragmentation on species communities within an urban landscape depend on scale, with differences emerging among and within species and populations.

California↗
USGS2020

Factors facilitating co-occurrence at the Range Boundary of Shenandoah and Red-backed Salamanders

The transition from species in allopatry to sympatry, i.e., the co-occurrence zone of competing species, allows for investigation of forces structuring range limits and provides evidence of the evolutionary and population responses of competing species, including mechanisms facilitating co-occurrence (e.g., character displacement). The Shenandoah Salamander (Plethodon shenandoah), an endangered plethodontid, is limited to three mountaintops in Shenandoah National Park, Virginia, USA. This species’ distributional limits are attributed to competitive exclusion by the Red-backed Salamander (P. cinereus). Recent work showed range overlap between these species is greater than previously thought, requiring investigation of species morphology, behavior, and demographic measures in single-species and co-occurrence zones that might facilitate such overlap. We analyzed individual characteristics (e.g., life stage, size, color, and microhabitat-use) from two years of transect surveys to see if traits differed within and outside co-occurrence zones. Measures showed species- and zonal-specific differences, but we found limited support for character displacement. Both species were larger when co-occurringin the co-occurrence zone, indicating larger animals might better compete for resources or that symmetric competition restricts dispersal or recruitment processes at the co-occurrence zone. Microhabitat use also differed by species across transects, with Red-backed Salamanders using more rock microhabitats in the co-occurrence zone, potentially due to competition for microclimates that minimize physiological stress. The lack of strong evidence for morphologic, behavioral, or demographic differentiation in situ at the range edge suggests competition may be weaker than previously thought with other factors contributing to the range limits of Shenandoah Salamanders.

Journal of Herpetology↗
USGS2018

Two-species occupancy modeling accounting for species misidentification and nondetection

In occupancy studies, species misidentification can lead to false‐positive detections, which can cause severe estimator biases. Currently, all models that account for false‐positive errors only consider omnibus sources of false detections and are limited to single‐species occupancy. However, false detections for a given species often occur because of the misidentification with another, closely related species. To exploit this explicit source of false‐positive detection error, we develop a two‐species occupancy model that accounts for misidentifications between two species of interest. As with other false‐positive models, identifiability is greatly improved by the availability of unambiguous detections at a subset of site x occasions. Here, we consider the case where some of the field observations can be confirmed using laboratory or other independent identification methods (“confirmatory data”). We performed three simulation studies to (1) assess the model's performance under various realistic scenarios, (2) investigate the influence of the proportion of confirmatory data on estimator accuracy and (3) compare the performance of this two‐species model with that of the single‐species false‐positive model. The model shows good performance under all scenarios, even when only small proportions of detections are confirmed (e.g. 5%). It also clearly outperforms the single‐species model. We illustrate application of this model using a 4‐year dataset on two sympatric species of lungless salamanders: the US federally endangered Shenandoah salamander Plethodon shenandoah , and its presumed competitor, the red‐backed salamander Plethodon cinereus . Occupancy of red‐backed salamanders appeared very stable across the 4 years of study, whereas the Shenandoah salamander displayed substantial turnover in occupancy of forest habitats among years. Given the extent of species misidentification issues in occupancy studies, this modelling approach should help improve the reliability of estimates of species distribution, which is the goal of many studies and monitoring programmes. Further developments, to account for different forms of state uncertainty, can be readily undertaken under our general approach.

Methods in Ecology and Evolution↗
USGS2017

Range position and climate sensitivity: The structure of among-population demographic responses to climatic variation

Species’ distributions will respond to climate change based on the relationship between local demographic processes and climate and how this relationship varies based on range position. A rarely tested demographic prediction is that populations at the extremes of a species’ climate envelope (e.g., populations in areas with the highest mean annual temperature) will be most sensitive to local shifts in climate (i.e., warming). We tested this prediction using a dynamic species distribution model linking demographic rates to variation in temperature and precipitation for wood frogs ( Lithobates sylvaticus ) in North America. Using long-term monitoring data from 746 populations in 27 study areas, we determined how climatic variation affected population growth rates and how these relationships varied with respect to long-term climate. Some models supported the predicted pattern, with negative effects of extreme summer temperatures in hotter areas and positive effects on recruitment for summer water availability in drier areas. We also found evidence of interacting temperature and precipitation influencing population size, such as extreme heat having less of a negative effect in wetter areas. Other results were contrary to predictions, such as positive effects of summer water availability in wetter parts of the range and positive responses to winter warming especially in milder areas. In general, we found wood frogs were more sensitive to changes in temperature or temperature interacting with precipitation than to changes in precipitation alone. Our results suggest that sensitivity to changes in climate cannot be predicted simply by knowing locations within the species’ climate envelope. Many climate processes did not affect population growth rates in the predicted direction based on range position. Processes such as species-interactions, local adaptation, and interactions with the physical landscape likely affect the responses we observed. Our work highlights the need to measure demographic responses to changing climate.

Global Change Biology↗
USGS2016

Large-scale recovery of an endangered amphibian despite ongoing exposure to multiple stressors

Amphibians are one of the most threatened animal groups, with 32% of species at risk for extinction. Given this imperiled status, is the disappearance of a large fraction of the Earth’s amphibians inevitable, or are some declining species more resilient than is generally assumed? We address this question in a species that is emblematic of many declining amphibians, the endangered Sierra Nevada yellow-legged frog ( Rana sierrae ). Based on >7,000 frog surveys conducted across Yosemite National Park over a 20-y period, we show that, after decades of decline and despite ongoing exposure to multiple stressors, including introduced fish, the recently emerged disease chytridiomycosis, and pesticides, R. sierrae abundance increased sevenfold during the study and at a rate of 11% per year. These increases occurred in hundreds of populations throughout Yosemite, providing a rare example of amphibian recovery at an ecologically relevant spatial scale. Results from a laboratory experiment indicate that these increases may be in part because of reduced frog susceptibility to chytridiomycosis. The disappearance of nonnative fish from numerous water bodies after cessation of stocking also contributed to the recovery. The large-scale increases in R. sierrae abundance that we document suggest that, when habitats are relatively intact and stressors are reduced in their importance by active management or species’ adaptive responses, declines of some amphibians may be partially reversible, at least at a regional scale. Other studies conducted over similarly large temporal and spatial scales are critically needed to provide insight and generality about the reversibility of amphibian declines at a global scale.

Proceedings of the National Academy of Sciences of↗
USGS2016

Quantitative evidence for the effects of multiple drivers on continental-scale amphibian declines

Since amphibian declines were first proposed as a global phenomenon over a quarter century ago, the conservation community has made little progress in halting or reversing these trends. The early search for a &ldquo;smoking gun&rdquo; was replaced with the expectation that declines are caused by multiple drivers. While field observations and experiments have identified factors leading to increased local extinction risk, evidence for effects of these drivers is lacking at large spatial scales. Here, we use observations of 389 time-series of 83 species and complexes from 61 study areas across North America to test the effects of 4 of the major hypothesized drivers of declines. While we find that local amphibian populations are being lost from metapopulations at an average rate of 3.79% per year, these declines are not related to any particular threat at the continental scale; likewise the effect of each stressor is variable at regional scales. This result - that exposure to threats varies spatially, and populations vary in their response - provides little generality in the development of conservation strategies. Greater emphasis on local solutions to this globally shared phenomenon is needed.

Scientific Reports↗
USGS2015

Performance of species occurrence estimators when basic assumptions are not met: a test using field data where true occupancy status is known

Populations are rarely censused. Instead, observations are subject to incomplete detection, misclassification and detection heterogeneity that result from human and environmental constraints. Though numerous methods have been developed to deal with observational uncertainty, validation under field conditions is rare because truth is rarely known in these cases. We present the most comprehensive test of occupancy estimation methods to date, using more than 33 000 auditory call observations collected under standard field conditions and where the true occupancy status of sites was known. Basic occupancy estimation approaches were biased when two key assumptions were not met: that no false positives occur and that no unexplained heterogeneity in detection parameters occurs. The greatest bias occurred for dynamic parameters (i.e. local colonization and extinction), and in many cases, the degree of inaccuracy would render results largely useless. We examined three approaches to increase adherence or relax these assumptions: modifying the sampling design, employing estimators that account for false-positive detections and using covariates to account for site-level heterogeneity in both false-negative and false-positive detection probabilities. We demonstrate that bias can be substantially reduced by modifications to sampling methods and by using estimators that simultaneously account for false-positive detections and site-level covariates to explain heterogeneity. Our results demonstrate that even small probabilities of misidentification and among-site detection heterogeneity can have severe effects on estimator reliability if ignored. We challenge researchers to place greater attention on both heterogeneity and false positives when designing and analysing occupancy studies. We provide 9 specific recommendations for the design, implementation and analysis of occupancy studies to better meet this challenge.

Methods in Ecology and Evolution↗
USGS2013

Population size, survival, growth, and movements of Rana sierrae

Based on 2431 captures of 757 individual frogs over a 9-yr period, we found that the population of R. sierrae in one meadow–stream complex in Yosemite National Park ranged from an estimated 45 to 115 adult frogs. Rana sierrae at our relatively low elevation site (2200 m) grew at a fast rate (K = 0.73–0.78), had high overwintering survival rates (44.6–95%), lived a long time (up to 16 yr), and tended to be fairly sedentary during the summer (100% minimum convex polygon annual home ranges of 139 m2) but had low year-to-year site fidelity. Even though the amphibian chytrid fungus (Batrachochytrium dendrobatidis, Bd) has been present in the population for at least 13 yr, there was no clear downward trend as might be expected from reports of R. sierrae population declines associated with Bd or from reports of widespread population decline of R. sierrae throughout its range.

Herpetologica↗