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Geology topics

Robert M. Dorazio

Publications and source records attributed to Robert M. Dorazio.

At least 19 recordsLinked to original sources
USGS2019

Environmental DNA sampling reveals high occupancy rates of invasive Burmese pythons at wading bird breeding aggregations in the central Everglades

The Burmese python ( Python bivittatus ) is now established as a breeding population throughout south Florida, USA. However, the extent of the invasion, and the ecological impacts of this novel apex predator on animal communities are incompletely known, in large part because Burmese pythons (hereafter “pythons”) are extremely cryptic and there has been no efficient way to detect them. Pythons are recently confirmed nest predators of long-legged wading bird breeding colonies (orders Ciconiiformes and Pelecaniformes). Pythons can consume large quantities of prey and may not be recognized as predators by wading birds, therefore they could be a particular threat to colonies. To quantify python occupancy rates at tree islands where wading birds breed, we utilized environmental DNA (eDNA) analysis—a genetic tool which detects shed DNA in water samples and provides high detection probabilities. We fitted multi-scale Bayesian occupancy models to test the prediction that pythons occupy islands with wading bird colonies at higher rates compared to representative control islands containing no breeding birds. Our results suggest that pythons are widely distributed across the central Everglades in proximity to active wading bird colonies. In support of our prediction that pythons are attracted to colonies, site-level python eDNA occupancy rates were higher at wading bird colonies (ψ = 0.88, 95% credible interval [0.59–1.00]) than at the control islands (ψ = 0.42 [0.16–0.80]) in April through June (n = 15 colony-control pairs). We found our water temperature proxy (time of day) to be informative of detection probability, in accordance with other studies demonstrating an effect of temperature on eDNA degradation in occupied samples. Individual sample concentrations ranged from 0.26 to 38.29 copies/μL and we generally detected higher concentrations of python eDNA in colony sites. Continued monitoring of wading bird colonies is warranted to determine the effect pythons are having on populations and investigate putative management activities.

Florida↗
USGS2016

Detection limits of quantitative and digital PCR assays and their influence in presence-absence surveys of environmental DNA

A set of universal guidelines is needed to determine the limit of detection (LOD) in PCR-based analyses of low concentration DNA. In particular, environmental DNA (eDNA) studies require sensitive and reliable methods to detect rare and cryptic species through shed genetic material in environmental samples. Current strategies for assessing detection limits of eDNA are either too stringent or subjective, possibly resulting in biased estimates of species’ presence. Here, a conservative LOD analysis grounded in analytical chemistry is proposed to correct for overestimated DNA concentrations predominantly caused by the concentration plateau, a nonlinear relationship between expected and measured DNA concentrations. We have used statistical criteria to establish formal mathematical models for both quantitative and droplet digital PCR. To assess the method, a new Grass Carp ( Ctenopharyngodon idella ) TaqMan assay was developed and tested on both PCR platforms using eDNA in water samples. The LOD adjustment reduced Grass Carp occupancy and detection estimates while increasing uncertainty – indicating that caution needs to be applied to eDNA data without LOD correction. Compared to quantitative PCR, digital PCR had higher occurrence estimates due to increased sensitivity and dilution of inhibitors at low concentrations. Without accurate LOD correction, species occurrence and detection probabilities based on eDNA estimates are prone to a source of bias that cannot be reduced by an increase in sample size or PCR replicates. Other applications also could benefit from a standardized LOD such as GMO food analysis, and forensic and clinical diagnostics.

Molecular Ecology Resources↗
USGS2015

Estimating the effects of habitat and biological interactions in an avian community

We used repeated sightings of individual birds encountered in community-level surveys to investigate the relative roles of habitat and biological interactions in determining the distribution and abundance of each species. To analyze these data, we developed a multispecies N-mixture model that allowed estimation of both positive and negative correlations between abundances of different species while also estimating the effects of habitat and the effects of errors in detection of each species. Using a combination of single- and multispecies N-mixture modeling, we examined for each species whether our measures of habitat were sufficient to account for the variation in encounter histories of individual birds or whether other habitat variables or interactions with other species needed to be considered. In the community that we studied, habitat appeared to be more influential than biological interactions in determining the distribution and abundance of most avian species. Our results lend support to the hypothesis that abundances of forest specialists are negatively affected by forest fragmentation. Our results also suggest that many species were associated with particular types of vegetation as measured by structural attributes of the forests. The abundances of 6 of the 73 species observed in our study were strongly correlated. These species included large birds (American Crow and Red-winged Blackbird) that forage on the ground in open habitats and small birds (Red-eyed Vireo, House Wren, Hooded Warbler, and Prairie Warbler) that are associated with dense shrub cover. Species abundances were positively correlated within each size group and negatively correlated between groups. Except for the American Crow, which preys on eggs and nestlings of small song birds, none of the other 5 species is known to display direct interactions, so we suspect that the correlations may have been associated with species-specific responses to habitat components not adequately measured by our covariates.

Connecticut↗
USGS2015

Environmental DNA (eDNA) sampling improves occurrence and detection estimates of invasive Burmese pythons

Environmental DNA (eDNA) methods are used to detect DNA that is shed into the aquatic environment by cryptic or low density species. Applied in eDNA studies, occupancy models can be used to estimate occurrence and detection probabilities and thereby account for imperfect detection. However, occupancy terminology has been applied inconsistently in eDNA studies, and many have calculated occurrence probabilities while not considering the effects of imperfect detection. Low detection of invasive giant constrictors using visual surveys and traps has hampered the estimation of occupancy and detection estimates needed for population management in southern Florida, USA. Giant constrictor snakes pose a threat to native species and the ecological restoration of the Florida Everglades. To assist with detection, we developed species-specific eDNA assays using quantitative PCR (qPCR) for the Burmese python ( Python molurus bivittatus ), Northern African python ( P . sebae ), boa constrictor ( Boa constrictor ), and the green ( Eunectes murinus ) and yellow anaconda ( E . notaeus ). Burmese pythons, Northern African pythons, and boa constrictors are established and reproducing, while the green and yellow anaconda have the potential to become established. We validated the python and boa constrictor assays using laboratory trials and tested all species in 21 field locations distributed in eight southern Florida regions. Burmese python eDNA was detected in 37 of 63 field sampling events; however, the other species were not detected. Although eDNA was heterogeneously distributed in the environment, occupancy models were able to provide the first estimates of detection probabilities, which were greater than 91%. Burmese python eDNA was detected along the leading northern edge of the known population boundary. The development of informative detection tools and eDNA occupancy models can improve conservation efforts in southern Florida and support more extensive studies of invasive constrictors. Generic sampling design and terminology are proposed to standardize and clarify interpretations of eDNA-based occupancy models.

Florida↗
USGS2014

Accounting for imperfect detection and survey bias in statistical analysis of presence-only data

Aim During the past decade ecologists have attempted to estimate the parameters of species distribution models by combining locations of species presence observed in opportunistic surveys with spatially referenced covariates of occurrence. Several statistical models have been proposed for the analysis of presence-only data, but these models have largely ignored the effects of imperfect detection and survey bias. In this paper I describe a model-based approach for the analysis of presence-only data that accounts for errors in the detection of individuals and for biased selection of survey locations. Innovation I develop a hierarchical, statistical model that allows presence-only data to be analysed in conjunction with data acquired independently in planned surveys. One component of the model specifies the spatial distribution of individuals within a bounded, geographic region as a realization of a spatial point process. A second component of the model specifies two kinds of observations, the detection of individuals encountered during opportunistic surveys and the detection of individuals encountered during planned surveys. Main conclusions Using mathematical proof and simulation-based comparisons, I demonstrate that biases induced by errors in detection or biased selection of survey locations can be reduced or eliminated by using the hierarchical model to analyse presence-only data in conjunction with counts observed in planned surveys. I show that a relatively small number of high-quality data (from planned surveys) can be used to leverage the information in presence-only observations, which usually have broad spatial coverage but may not be informative of both occurrence and detectability of individuals. Because a variety of sampling protocols can be used in planned surveys, this approach to the analysis of presence-only data is widely applicable. In addition, since the point-process model is formulated at the level of an individual, it can be extended to account for biological interactions between individuals and temporal changes in their spatial distributions.

Global Ecology and Biogeography↗
USGS2014

Estimating abundances of interacting species using morphological traits, foraging guilds, and habitat

We developed a statistical model to estimate the abundances of potentially interacting species encountered while conducting point-count surveys at a set of ecologically relevant locations - as in a metacommunity of species. In the model we assume that abundances of species with similar traits (e.g., body size) are potentially correlated and that these correlations, when present, may exist among all species or only among functionally related species (such as members of the same foraging guild). We also assume that species-specific abundances vary among locations owing to systematic and stochastic sources of heterogeneity. For example, if abundances differ among locations due to differences in habitat, then measures of habitat may be included in the model as covariates. Naturally, the quantitative effects of these covariates are assumed to differ among species. Our model also accounts for the effects of detectability on the observed counts of each species. This aspect of the model is especially important for rare or uncommon species that may be difficult to detect in community-level surveys. Estimating the detectability of each species requires sampling locations to be surveyed repeatedly using different observers or different visits of a single observer. As an illustration, we fitted models to species-specific counts of birds obtained while sampling an avian community during the breeding season. In the analysis we examined whether species abundances appeared to be correlated due to similarities in morphological measures (body mass, beak length, tarsus length, wing length, tail length) and whether these correlations existed among all species or only among species of the same foraging guild. We also used the model to estimate the effects of forested area on species abundances and the effects of sound power output (as measured by body size) on species detection probabilities.

PLoS ONE↗
USGS2014

Tailoring point counts for inference about avian density: dealing with nondetection and availability

Point counts are commonly used for bird surveys, but interpretation is ambiguous unless there is an accounting for the imperfect detection of individuals. We show how repeated point counts, supplemented by observation distances, can account for two aspects of the counting process: (1) detection of birds conditional on being available for observation and (2) the availability of birds for detection given presence. We propose a hierarchical model that permits the radius in which birds are available for detection to vary with forest stand age (or other relevant habitat features), so that the number of birds available at each location is described by a Poisson-gamma mixture. Conditional on availability, the number of birds detected at each location is modeled by a beta-binomial distribution. We fit this model to repeated point count data of Florida scrub-jays and found evidence that the area in which birds were available for detection decreased with increasing stand age. Estimated density was 0.083 (95%CI: 0.060–0.113) scrub-jays/ha. Point counts of birds have a number of appealing features. Based on our findings, however, an accounting for both components of the counting process may be necessary to ensure that abundance estimates are comparable across time and space. Our approach could easily be adapted to other species and habitats.

Natural Resource Modeling↗
USGS2013

Bayes and empirical Bayes estimators of abundance and density from spatial capture-recapture data

In capture-recapture and mark-resight surveys, movements of individuals both within and between sampling periods can alter the susceptibility of individuals to detection over the region of sampling. In these circumstances spatially explicit capture-recapture (SECR) models, which incorporate the observed locations of individuals, allow population density and abundance to be estimated while accounting for differences in detectability of individuals. In this paper I propose two Bayesian SECR models, one for the analysis of recaptures observed in trapping arrays and another for the analysis of recaptures observed in area searches. In formulating these models I used distinct submodels to specify the distribution of individual home-range centers and the observable recaptures associated with these individuals. This separation of ecological and observational processes allowed me to derive a formal connection between Bayes and empirical Bayes estimators of population abundance that has not been established previously. I showed that this connection applies to every Poisson point-process model of SECR data and provides theoretical support for a previously proposed estimator of abundance based on recaptures in trapping arrays. To illustrate results of both classical and Bayesian methods of analysis, I compared Bayes and empirical Bayes esimates of abundance and density using recaptures from simulated and real populations of animals. Real populations included two iconic datasets: recaptures of tigers detected in camera-trap surveys and recaptures of lizards detected in area-search surveys. In the datasets I analyzed, classical and Bayesian methods provided similar – and often identical – inferences, which is not surprising given the sample sizes and the noninformative priors used in the analyses.

PLoS ONE↗
USGS2013

Too risky to settle: avian community structure changes in response to perceived predation risk on adults and offspring

Predation risk is widely hypothesized as an important force structuring communities, but this potential force is rarely tested experimentally, particularly in terrestrial vertebrate communities. How animals respond to predation risk is generally considered predictable from species life-history and natural-history traits, but rigorous tests of these predictions remain scarce. We report on a large-scale playback experiment with a forest bird community that addresses two questions: (i) does perceived predation risk shape the richness and composition of a breeding bird community? And (ii) can species life-history and natural-history traits predict prey community responses to different types of predation risk? On 9 ha plots, we manipulated cues of three avian predators that preferentially prey on either adult birds or offspring, or both, throughout the breeding season. We found that increased perception of predation risk led to generally negative responses in the abundance, occurrence and/or detection probability of most prey species, which in turn reduced the species richness and shifted the composition of the breeding bird community. Species-level responses were largely predicted from the key natural-history trait of body size, but we did not find support for the life-history theory prediction of the relationship between species' slow/fast life-history strategy and their response to predation risk.

Florida↗
USGS2013

Estimating abundance while accounting for rarity, correlated behavior, and other sources of variation in counts

The class of N-mixture models allows abundance to be estimated from repeated, point count surveys while adjusting for imperfect detection of individuals. We developed an extension of N-mixture models to account for two commonly observed phenomena in point count surveys: rarity and lack of independence induced by unmeasurable sources of variation in the detectability of individuals. Rarity increases the number of locations with zero detections in excess of those expected under simple models of abundance (e.g., Poisson or negative binomial). Correlated behavior of individuals and other phenomena, though difficult to measure, increases the variation in detection probabilities among surveys. Our extension of N-mixture models includes a hurdle model of abundance and a beta-binomial model of detectability that accounts for additional (extra-binomial) sources of variation in detections among surveys. As an illustration, we fit this model to repeated point counts of the West Indian manatee, which was observed in a pilot study using aerial surveys. Our extension of N-mixture models provides increased flexibility. The effects of different sets of covariates may be estimated for the probability of occurrence of a species, for its mean abundance at occupied locations, and for its detectability.

Ecology↗
USGS2012

Predicting the geographic distribution of a species from presence-only data subject to detection errors

Several models have been developed to predict the geographic distribution of a species by combining measurements of covariates of occurrence at locations where the species is known to be present with measurements of the same covariates at other locations where species occurrence status (presence or absence) is unknown. In the absence of species detection errors, spatial point-process models and binary-regression models for case-augmented surveys provide consistent estimators of a species’ geographic distribution without prior knowledge of species prevalence. In addition, these regression models can be modified to produce estimators of species abundance that are asymptotically equivalent to those of the spatial point-process models. However, if species presence locations are subject to detection errors, neither class of models provides a consistent estimator of covariate effects unless the covariates of species abundance are distinct and independently distributed from the covariates of species detection probability. These analytical results are illustrated using simulation studies of data sets that contain a wide range of presence-only sample sizes. Analyses of presence-only data of three avian species observed in a survey of landbirds in western Montana and northern Idaho are compared with site-occupancy analyses of detections and nondetections of these species.

Biometrics↗
USGS2012

A two-phase sampling design for increasing detections of rare species in occupancy surveys

1. Occupancy estimation is a commonly used tool in ecological studies owing to the ease at which data can be collected and the large spatial extent that can be covered. One major obstacle to using an occupancy-based approach is the complications associated with designing and implementing an efficient survey. These logistical challenges become magnified when working with rare species when effort can be wasted in areas with none or very few individuals. 2. Here, we develop a two-phase sampling approach that mitigates these problems by using a design that places more effort in areas with higher predicted probability of occurrence. We compare our new sampling design to traditional single-season occupancy estimation under a range of conditions and population characteristics. We develop an intuitive measure of predictive error to compare the two approaches and use simulations to assess the relative accuracy of each approach. 3. Our two-phase approach exhibited lower predictive error rates compared to the traditional single-season approach in highly spatially correlated environments. The difference was greatest when detection probability was high (0·75) regardless of the habitat or sample size. When the true occupancy rate was below 0·4 (0·05-0·4), we found that allocating 25% of the sample to the first phase resulted in the lowest error rates. 4. In the majority of scenarios, the two-phase approach showed lower error rates compared to the traditional single-season approach suggesting our new approach is fairly robust to a broad range of conditions and design factors and merits use under a wide variety of settings. 5. Synthesis and applications. Conservation and management of rare species are a challenging task facing natural resource managers. It is critical for studies involving rare species to efficiently allocate effort and resources as they are usually of a finite nature. We believe our approach provides a framework for optimal allocation of effort while maximizing the information content of the data in an attempt to provide the highest conservation value per unit of effort.

Methods in Ecology and Evolution↗
USGS2012

A sampling design and model for estimating abundance of Nile crocodiles while accounting for heterogeneity of detectability of multiple observers

As part of the development of a management program for Nile crocodiles in Lake Nasser, Egypt, we used a dependent double-observer sampling protocol with multiple observers to compute estimates of population size. To analyze the data, we developed a hierarchical model that allowed us to assess variation in detection probabilities among observers and survey dates, as well as account for variation in crocodile abundance among sites and habitats. We conducted surveys from July 2008-June 2009 in 15 areas of Lake Nasser that were representative of 3 main habitat categories. During these surveys, we sampled 1,086 km of lake shore wherein we detected 386 crocodiles. Analysis of the data revealed significant variability in both inter- and intra-observer detection probabilities. Our raw encounter rate was 0.355 crocodiles/km. When we accounted for observer effects and habitat, we estimated a surface population abundance of 2,581 (2,239-2,987, 95% credible intervals) crocodiles in Lake Nasser. Our results underscore the importance of well-trained, experienced monitoring personnel in order to decrease heterogeneity in intra-observer detection probability and to better detect changes in the population based on survey indices. This study will assist the Egyptian government establish a monitoring program as an integral part of future crocodile harvest activities in Lake Nasser

Lake Nasser↗
USGS2011

No evidence of interference competition among the invasive feral pig and two native peccary species in a Neotropical wetland

In South America, the invasive feral pig ( Sus scrofa Linnaeus) has become established in Argentina, Uruguay, Paraguay and in a wide range within Brazil, along the southern half of the Atlantic Forest, in the cerrado (savanna) and in the Pantanal wetland. The geographical ranges of the two most common South American native peccary ( Tayassu pecari Link and Pecari tajacu Linnaeus) overlap almost entirely, and the feral pig now co-occurs with them in several areas. Because feral pig, white-lipped and collared peccary are considered ecological equivalents, there has been much speculation about possible competitive interactions among them (Desbiez et al. 2009, Sicuro & Oliveira 2002).

Journal of Tropical Ecology↗
USGS2011

Estimating occupancy dynamics in an anuran assemblage from Louisiana, USA

Effective monitoring programs are designed to track changes in the distribution, occurrence, and abundance of species. We developed an extension of Royle and Kéry's (2007) single species model to estimate simultaneously temporal changes in probabilities of detection, occupancy, colonization, extinction, and species turnover using data on calling anuran amphibians, collected from 2002 to 2006 in the Lower Mississippi Alluvial Valley of Louisiana, USA. During our 5-year study, estimates of occurrence probabilities declined for all 12 species detected. These declines occurred primarily in conjunction with variation in estimates of local extinction probabilities (cajun chorus frog [ Pseudacris fouquettei ], spring peeper [ P. crucifer ], northern cricket frog [ Acris crepitans ], Cope's gray treefrog [ Hyla chrysoscelis ], green treefrog [ H. cinerea ], squirrel treefrog [ H. squirella ], southern leopard frog [ Lithobates sphenocephalus ], bronze frog [ L. clamitans ], American bullfrog [ L. catesbeianus ], and Fowler's toad [ Anaxyrus fowleri ]). For 2 species (eastern narrowmouthed toad [ Gastrophryne carolinensis ] and Gulf Coast toad [ Incilius nebulifer ]), declines in occupancy appeared to be a consequence of both increased local extinction and decreased colonization events. The eastern narrow-mouthed toad experienced a 2.5-fold increase in estimates of occupancy in 2004, possibly because of the high amount of rainfall received during that year, along with a decrease in extinction and increase in colonization of new sites between 2003 and 2004. Our model can be incorporated into monitoring programs to estimate simultaneously the occupancy dynamics for multiple species that show similar responses to ecological conditions. It will likely be an important asset for those monitoring programs that employ the same methods to sample assemblages of ecologically similar species, including those that are rare. By combining information from multiple species to decrease the variance on estimates of individual species, our results are advantageous compared to single-species models. This feature enables managers and researchers to use an entire community, rather than just one species, as an ecological indicator in monitoring programs.

Louisiana↗
USGS2011

Occupancy and abundance of wintering birds in a dynamic agricultural landscape

Assessing wildlife management action requires monitoring populations, and abundance often is the parameter monitored. Recent methodological advances have enabled estimation of mean abundance within a habitat using presence–absence or count data obtained via repeated visits to a sample of sites. These methods assume populations are closed and intuitively assume habitats within sites change little during a field season. However, many habitats are highly variable over short periods. We developed a variation of existing occupancy and abundance models that allows for extreme spatio‐temporal differences in habitat, and resulting changes in wildlife abundance, among sites and among visits to a site within a field season. We conducted our study in sugarcane habitat within the Everglades Agricultural Area southeast of Lake Okeechobee in south Florida. We counted wintering birds, primarily passerines, within 245 sites usually 5 times at each site during December 2006–March 2007. We estimated occupancy and mean abundance of birds in 6 vegetation states during the sugarcane harvest and allowed these parameters to vary temporally or spatially within a vegetation state. Occupancy and mean abundance of the common yellowthroat ( Geothlypis trichas ) was affected by structure of sugarcane and uncultivated edge vegetation (occupancy = 1.00 [ = 0.96–1.00] and mean abundance = 7.9 [ = 3.2–19.5] in tall sugarcane with tall edge vegetation versus 0.20 [ = 0.04–0.71] and 0.22 [ = 0.04–1.2], respectively, in short sugarcane with short edge vegetation in one half of the study area). Occupancy and mean abundance of palm warblers ( Dendroica palmarum ) were constant (occupancy = 1.00, = 0.69–1.00; mean abundance = 18, = 1–270). Our model may enable wildlife managers to assess rigorously effects of future edge habitat management on avian distribution and abundance within agricultural landscapes during winter or the breeding season. The model may also help wildlife managers make similar management decisions involving other dynamic habitats such as wetlands, prairies, and even forested areas if forest management or fires occur during the field season.

Florida↗
USGS2010

Parameter-expanded data augmentation for Bayesian analysis of capture-recapture models

Data augmentation (DA) is a flexible tool for analyzing closed and open population models of capture-recapture data, especially models which include sources of hetereogeneity among individuals. The essential concept underlying DA, as we use the term, is based on adding "observations" to create a dataset composed of a known number of individuals. This new (augmented) dataset, which includes the unknown number of individuals N in the population, is then analyzed using a new model that includes a reformulation of the parameter N in the conventional model of the observed (unaugmented) data. In the context of capture-recapture models, we add a set of "all zero" encounter histories which are not, in practice, observable. The model of the augmented dataset is a zero-inflated version of either a binomial or a multinomial base model. Thus, our use of DA provides a general approach for analyzing both closed and open population models of all types. In doing so, this approach provides a unified framework for the analysis of a huge range of models that are treated as unrelated "black boxes" and named procedures in the classical literature. As a practical matter, analysis of the augmented dataset by MCMC is greatly simplified compared to other methods that require specialized algorithms. For example, complex capture-recapture models of an augmented dataset can be fitted with popular MCMC software packages (WinBUGS or JAGS) by providing a concise statement of the model's assumptions that usually involves only a few lines of pseudocode. In this paper, we review the basic technical concepts of data augmentation, and we provide examples of analyses of closed-population models ( M 0, M h , distance sampling, and spatial capture-recapture models) and open-population models (Jolly-Seber) with individual effects.

Journal of Ornithology↗