Hierarchical multi-scale occupancy estimation for monitoring wildlife populations

Occupancy estimation is an effective analytic framework, but requires repeated surveys of a sample unit to estimate the probability of detection. Detection rates can be estimated from spatially replicated rather than temporally replicated surveys, but this may violate the closure assumption and result in biased estimates of occupancy. We present a new application of a multi-scale occupancy model that permits the simultaneous use of presence–absence data collected at 2 spatial scales and uses a removal design to estimate the probability of detection. Occupancy at the small scale corresponds to local territory occupancy, whereas occupancy at the large scale corresponds to regional occupancy of the sample units. Small-scale occupancy also corresponds to a spatial availability or coverage parameter where a species may be unavailable for sampling at a fraction of the survey stations. We applied the multi-scale occupancy model to a hierarchical sample design for 2 bird species in the Black Hills National Forest: brown creeper (Certhia americana) and lark sparrow (Chondestes grammacus). Our application of the multi-scale occupancy model is particularly well suited for hierarchical sample designs, such as spatially replicated survey stations within sample units that are typical of avian monitoring programs. The model appropriately accounts for the non-independence of the spatially replicated survey stations, addresses the closure assumption for the spatially replicated survey stations, and is useful for decomposing the observation process into detection and availability parameters. This analytic approach is likely to be useful for monitoring at local and regional scales, modeling multi-scale habitat relationships, and estimating population state variables for rare species of conservation concern. © 2011 The Wildlife Society.     

Evaluation of non-lethal gut microbiome sampling methods in a passerine bird

Gut microbial communities play critical roles in the biological functions of their host, such as mediating nutrient absorption, digesting food components the host cannot, and offering protection against enteric pathogens. Extensive research on gut microbial communities has been conducted on mammals, including humans and rodents, but much less work has been done in birds. Furthermore, much of the research on host–microbe interactions make use of faecal samples and rectal/cloacal swabs as a proxy for intestinal samples, which can be difficult to obtain directly. However, little is known about the overlap between the microbial communities of the gut, faeces and swabs, which limits interpretability of results based on faecal samples and swabs. To address this gap in knowledge, we compared the microbiome from five sample types – proventriculus, small intestine, large intestine, cloacal swabs and faeces – across individual Zebra Finches Taeniopygia guttata housed in constant conditions with a standardized diet. We compared diversity and community composition through 16S rRNA gene sequencing. Our results show that microbial communities from both cloacal swabs and faeces were distinct from proventriculus and small intestinal samples, but generally indistinguishable from large intestinal samples, indicating that these non-lethal samples may be useful proxies for large intestinal bacterial communities. Gaining insight into non-invasive sampling techniques for passerines has implications for studies of gut microbial diversity and abundance in wild bird populations. Furthermore, reliable non-lethal sampling is necessary for experiments where repeated sampling is required.     

Effects of sampling and sub-sampling variation using the STAR-AQEM sampling protocol on the precision of macroinvertebrate metrics

As part of the extensive field sampling programme within the European Union STAR project, replicate macroinvertebrate samples were taken using the STAR-AQEM sampling method at each of 2–13 sites of varying ecological quality within each of 15 stream types spread over 12 countries throughout Europe. The STAR-AQEM method requires the sub-sampling and taxonomic identification of at least one-sixth of the sample and at least 700 individuals. Replicate sub-samples were also taken at most of these sites. Sub-sampling effects caused more than 50% of the overall variance between replicate samples values for 12 of the 27 macroinvertebrate metrics analysed and was generally greatest for metrics that depend on the number of taxa present. The sampling precision of each metric was estimated by the overall replicate sampling variance as a percentage P_samp of the total variance in metric values within a stream type. Average over all stream types, the three Saprobic indices had the lowest percentage sampling variances with median values of only 3–6%. Most of the metrics had typical replicate sampling variances of 8–18% of the total variability within a stream type; this gives rise to estimated rates of mis-classifying sites to ecological status class of between 22 and 55% with an average of about 40%. This suggests that the precision of such metrics based on the STAR-AQEM method is only sufficient to indicate gross changes in the ecological status of sites, but there will be considerable uncertainty in the assignment of sites to adjacent status classes. These estimates can be used to provide information on the effects of STAR-AQEM sampling variation on the expected uncertainty in multi-metric assessments of the ecological status of sites in the same or similar stream types, where only one sample has been taken at a point in time and thus there is no replication.     

Properties of a nonparametric test for early comparison of treatments in clinical trials in the presence of surrogate endpoints

A nonparametric test is derived for comparing treatments with respect to the final endpoint in clinical trials in which the final endpoint has been observed for a random subset of patients, but results are available for a surrogate endpoint for a larger sample of patients. The test is an adaptation of the Wilcoxon-Mann-Whitney two-sample test, with an adjustment that involves a comparison of the ranks of the surrogate endpoints between patients with and without final endpoints. The validity of the test depends on the assumption that the patients with final endpoints represent a random sample of the patients registered in the study. This assumption is viable in trials in which the final endpoint is evaluated at a "landmark" timepoint in the patients' natural history. A small sample simulation study demonstrates that the test has a size that is close to the nominal value for all configurations evaluated. When compared with the conventional test based only on the final endpoints, the new test delivers substantial increases in power only when the surrogate endpoint is highly correlated with the true endpoint. Our research indicates that, in the absence of modeling assumptions, auxiliary information derived from surrogate endpoints can provide significant additional information only under special circumstances.     

Estimation of the individual number entering each development stage in an insect population

A method for estimating the number entering each development stage from data obtained by regular sampling through one generation of an insect population was described. This method is consisted of the following two procedures: The provisional estimates are calculated on the assumption that each stage has a common mortality in a sampling interval. Then these estimates are corrected on another assumption that the mortality is different in each stage but constant during a stage. The result of testing its validity with two laboratory populations of the common cabbage butterfly, Pieris rapae crucivora, showed the availability of the present method.     

A practical sampling design for acoustic surveys of bats

Acoustic surveys are widely used for describing bat occurrence and activity patterns and are increasingly important for addressing concerns for habitat management, wind energy, and disease on bat populations. Designing these surveys presents unique challenges, particularly when a probabilistic sample is required for drawing inference to unsampled areas. Sampling frame errors and other logistical constraints often require survey sites to be dropped from the sample and new sites added. Maintaining spatial balance and representativeness of the sample when these changes are made can be problematic. Spatially balanced sampling designs recently developed to support aquatic surveys along rivers provide solutions to a number of practical challenges faced by bat researchers and allow for sample site additions and deletions, support unequal-probability selection of sites, and provide an approximately unbiased local neighborhood-weighted variance estimator that is efficient for spatially structured populations such as is typical for bats. We implemented a spatially balanced design to survey canyon bat (Parastrellus hesperus) activity along a stream network. The spatially balanced design accommodated typical logistical challenges and yielded a 25% smaller estimated standard error for the mean activity level than the usual simple random sampling estimator. Spatially balanced designs have broad application to bat research and monitoring programs and will improve studies relying on model-based inference (e.g., occupancy models) by providing flexibility and protection against violations of the independence assumption, even if design-based estimators are not used. Our approach is scalable and can be used for pre- and post-construction surveys along wind turbine arrays and for regional monitoring programs. © 2011 The Wildlife Society.     

New bioreactor-coupled rapid stopped-flow sampling technique for measurements of metabolite dynamics on a subsecond time scale

Knowledge of concentrations of intracellular metabolites is important for quantitative analysis of metabolic networks. As far as the very fast response of intracellular metabolites in the millisecond range is concerned, the frequently used pulse technique shows an inherent limitation. The time span between the disturbance and the first sample is constrained by the time necessary to obtain a homogeneous distribution of the pertubation within the bioreactor. For determination of rapid changes, a novel sampling technique based on the stopped-flow method has been developed. A continuous stream of biosuspension leaving the bioreactor is being mixed with a glucose solution in a turbulent mixing chamber. Through computer-aided activation of sequentially positioned three-way valves, different residence times and thus reaction times can be verified. The application of this new sampling method is illustrated with examples including measurements of adenine nucleotides and glucose-6-phosphate in Saccharomyces cerevisiae as well as measurements related to the PTS system in Escherichia coli.     

Breath air analysis and its use as a biomarker in biological monitoring of occupational and environmental exposure to chemical agents

The analysis of exhaled air has several advantages since it is a noninvasive method applicable to a large number of toxic agents, in addition to being a simpler matrix than those of other biological samples such as urine and blood. However, it presents some challenges, such as the necessity of a more sensitive sampling procedure, since the chemical substances eliminated through exhaled air are unchanged in form, not being metabolized, and exhaled compounds are present at extremely low concentrations, i.e. in the nanomolar range. To improve the sensitivity and precision of measurement of the concentration of these substances in exhaled air, the sample usually has to be concentrated before assay by gas chromatography. To this end, the use of the solid-phase microextraction (SPME) technique has been proposed as an efficient sampling method. This paper presents a revision of breath analysis as a biomarker for occupational and environmental exposure to chemicals. The sampling methods and the potential use of SPME for determining chemical substances in exhaled air are discussed.     

Investigation of hydrodynamic focusing in a microfluidic coulter counter device

The Coulter technique enables rapid analysis of particles or cells suspended in a fluid stream. In this technique, the cells are suspended in an electrically conductive solution, which is hydrodynamically focused by nonconducting sheath flows. The cells produce a characteristic voltage signal when they interrupt an electrical path. The population and size of the cells can be obtained through analyzing the voltage signal. In a microfluidic Coulter counter device, the hydrodynamic focusing technique is used to position the conducting sample stream and the cells and also to separate close cells to generate distinct signals for each cell and avoid signal jam. The performance of hydrodynamic focusing depends on the relative flow ratio between the sample stream and sheath stream. We use a numerical approach to study the hydrodynamic focusing in a microfluidic Coulter counter device. In this approach, the flow field is described by solving the incompressible Navier-Stokes equations. The sample stream concentration is modeled by an advection-diffusion equation. The motion of the cells is governed by the Newton-Euler equations of motion. Particle motion through the flow field is handled using an overlapping grid technique. A numerical model for studying a microfluidic Coulter counter has been validated. Using the model, the impact of relative flow rate on the performance of hydrodynamic focusing was studied. Our numerical results show that the position of the sample stream can be controlled by adjusting the relative flow rate. Our simulations also show that particles can be focused into the stream and initially close particles can be separated by the hydrodynamic focusing. From our study, we conclude that hydrodynamic focusing provides an effective way to control the position of the sample stream and cells and it also can be used to separate cells to avoid signal jam.     

Significance testing for correlated binary outcome data

Multiple logistic regression is a commonly used multivariate technique for analyzing data with a binary outcome. One assumption needed for this method of analysis is the independence of outcome for all sample points in a data set. In ophthalmologic data and other types of correlated binary data, this assumption is often grossly violated and the validity of the technique becomes an issue. A technique has been developed (Rosner, 1984) that utilizes a polychotomous logistic regression model to allow one to look at multiple exposure variables in the context of a correlated binary data structure. This model is an extension of the beta-binomial model, which has been widely used to model correlated binary data when no covariates are present. In this paper, a relationship is developed between the two techniques, whereby it is shown that use of ordinary logistic regression in the presence of correlated binary data can result in true significance levels that are considerably larger than nominal levels in frequently encountered situations. This relationship is explored in detail in the case of a single dichotomous exposure variable. In this case, the appropriate test statistic can be expressed as an adjusted chi-square statistic based on the 2 X 2 contingency table relating exposure to outcome. The test statistic is easily computed as a function of the ordinary chi-square statistic and the correlation between eyes (or more generally between cluster members) for outcome and exposure, respectively. This generalizes some previous results obtained by Koval and Donner (1987, in Festschrift for V. M. Joshi, I. B. MacNeill (ed.), Vol. V, 199-224.(ABSTRACT TRUNCATED AT 250 WORDS)     

Temporal stability and rates of post‐depositional change in geochemical signatures of brown trout Salmo trutta scales

This study investigates temporal stability in the scale microchemistry of brown trout Salmo trutta in feeder streams of a large heterogeneous lake catchment and rates of change after migration into the lake. Laser‐ablation inductively coupled plasma mass spectrometry was used to quantify the elemental concentrations of Na, Mg, Mn, Cu, Zn, Ba and Sr in archived (1997–2002) scales of juvenile S. trutta collected from six major feeder streams of Lough Mask, County Mayo, Ireland. Water‐element Ca ratios within these streams were determined for the fish sampling period and for a later period (2013–2015). Salmo trutta scale Sr and Ba concentrations were significantly (P < 0·05) correlated with stream water sample Sr:Ca and Ba:Ca ratios respectively from both periods, indicating multi‐annual stability in scale and water‐elemental signatures. Discriminant analysis of scale chemistries correctly classified 91% of sampled juvenile S. trutta to their stream of origin using a cross‐validated classification model. This model was used to test whether assumed post‐depositional change in scale element concentrations reduced correct natal stream classification of S. trutta in successive years after migration into Lough Mask. Fish residing in the lake for 1–3 years could be reliably classified to their most likely natal stream, but the probability of correct classification diminished strongly with longer lake residence. Use of scale chemistry to identify natal streams of lake S. trutta should focus on recent migrants, but may not require contemporary water chemistry data.     

Small Sample Comparison of Modified Chi‐Square Test Statistics for Survey Data

The problem of categorial data analysis in survey sampling arises because of non‐independence of sample elements of the sample obtained through imposed sampling design. In this article the performance of modified χ² statistic for testing independence of attributes have been evaluated for small sample sizes with the help of log‐linear models with respect to its achieved level of significance for fixed nominal level at 5%, through simulation technique. It hase been observed that the perfiormance of these test statistics depends on average and coefficient of variation of eigen values of design effect matrix. The first order corrected statistic is able to capture the effect of sampling design to a great extent but the performance of second order corrected statistic is much better. Further, these modified χ² test statistics were applied to a real survey data and their performance were evaluated with respect to their achievied level of significance.     

Standardized sampling plan for Aphis gossypii based on the cotton cultivar,plant phenology and crop size

A standardized sampling plan is the starting point for developing a decision‐making system for pest control. Aphis gossypii (Hemiptera: Aphididae) is a destructive sap‐feeding pest on cotton worldwide. However, research addressing cotton cultivar, plant phenology and field size with the aim of developing a sampling plan for A. gossypii has not been done. Therefore, in this study, we developed a standardized sampling for A. gossypii as a function of these factors. To accomplish this, A. gossypii densities in four experimental cotton cultivars were sampled weekly during year one to determine the ideal aphid characteristic to sample (by individual or colony). During year one and two, A. gossypii densities were sampled weekly in the same cultivars to determine sampling unit, sampling technique and the number of samples for an A. gossypii sampling plan. Using the sample number determined, the sampling time was recorded for cotton field size of 1, 5, 10, 50, 100 and 150 ha in order to estimate the sampling cost. In cotton, the count of individuals was the best characteristic for the assessment of A. gossypii. Leaves of the most apical branches for the vegetative and reproductive cotton plant stage were the best sampling units. The best sampling technique was direct counting. The cotton cultivar did not affect the development of the sampling plan. The A. gossypii sampling plan involved the evaluation of 58 samples per zone and required 20 min (<0.35 min/sample) for the evaluation of these samples. However, the walking time between samples was the main factor responsible for the total sampling time and cost in cotton fields, and this factor strongly depends on the size of the cotton field.     

Sampling Hubbell's neutral theory of biodiversity

In the context of neutral theories of community ecology, a novel genealogy‐based framework has recently furnished an analytic extension of Ewens’ sampling multivariate abundance distribution, which also applies to a random sample from a local community. Here, instead of taking a multivariate approach, we further develop the sampling theory of Hubbell's neutral spatially implicit theory and derive simple abundance distributions for a random sample both from a local community and a metacommunity. Our result is given in terms of the average number of species with a given abundance in any randomly extracted sample. Contrary to what has been widely assumed, a random sample from a metacommunity is not fully described by the Fisher log‐series, but by a new distribution. This new sample distribution matches the log‐series expectation at high biodiversity values (θ > 1) but clearly departs from it for species‐poor metacommunities (θ < 1). Our theoretical framework should be helpful in the better assessment of diversity and testing of the neutral theory by using abundance data.     

Response of macroinvertebrates and water quality to long-term decrease in organic pollution in some Estonian streams during 1990–1998

A survey was started in 1990 of the benthic macroinvertebrate community and water quality in some Estonian streams affected by organic pollution, especially the spreading of slurry on fields. The study was expanded during 1991–1998 to involve 47 sampling sites. Long-term dependence was tested using the SAS/GLM contrast statement. All biological indices used (BMWP-ASPT, number of ASPT scoring families (N_ASPT), Danish Fauna Index, Belgian Biotic Index, EPT-index) were significantly related to the degree of organic pollution. Compared with the reference sites, the test sites revealed significantly lower water quality: higher BOD₇, total P and NH₄; lower pH and all hydrobiological indices. Season and stream size at the sampling site (expressed in km from the stream source) had significant effects on both hydrochemical and hydrobiological variables. On the contrary, discharge and precipitation had no significant influence on the studied water quality indicators, with the exception of pH in a few cases. At the same time, all but three variables for the reference and the test sites were different at the beginning of the sampling period; this difference remained only for a few sensitive indices such as ASPT and Danish Fauna Index at the end of the period, indicating general improvement in the environment.     

Ontogenetic Sequence Analysis: using parsimony to characterize developmental sequences and sequence polymorphism

Ontogenetic sequences are a pervasive aspect of development and are used extensively by biologists for intra- and interspecific comparisons. A tacit assumption behind most such analyses is that sequence is largely invariant within a species. However, recent embryological and experimental work emphasizes that ontogenetic sequences can be variable and that sequence polymorphism may be far more prevalent than is generally realized. We present a method that uses parsimony algorithms to map hierarchic developmental patterns that capture variability within a sample. This technique for discovering and formalizing sequences is called the "Ontogenetic Sequence Analysis" (OSA). Results of OSA include formalized diagrams of reticulating networks, describe all most parsimonious sequences, and can be used to develop statistics and metrics for comparison of both intraspecific and interspecific sequence variation. The method is tested with examples of human postnatal skeletal ossification, comprising a time-calibrated data set of human hand and wrist epiphyseal unions, and a longitudinal data set of human wrist ossification. Results illustrate the validity of the method for discovering sequence patterns and for predicting morphologies not represented in analytic samples. OSA demonstrates the potential and challenges of incorporating ontogenetic sequences of morphological information into evolutionary analyses.     

Spatial sampling bias and model complexity in stream‐based species distribution models: A case study of Paddlefish (Polyodon spathula) in the Arkansas River basin,USA

Leveraging existing presence records and geospatial datasets, species distribution modeling has been widely applied to informing species conservation and restoration efforts. Maxent is one of the most popular modeling algorithms, yet recent research has demonstrated Maxent models are vulnerable to prediction errors related to spatial sampling bias and model complexity. Despite elevated rates of biodiversity imperilment in stream ecosystems, the application of Maxent models to stream networks has lagged, as has the availability of tools to address potential sources of error and calculate model evaluation metrics when modeling in nonraster environments (such as stream networks). Herein, we use Maxent and customized R code to estimate the potential distribution of paddlefish (Polyodon spathula) at a stream‐segment level within the Arkansas River basin, USA, while accounting for potential spatial sampling bias and model complexity. Filtering the presence data appeared to adequately remove an eastward, large‐river sampling bias that was evident within the unfiltered presence dataset. In particular, our novel riverscape filter provided a repeatable means of obtaining a relatively even coverage of presence data among watersheds and streams of varying sizes. The greatest differences in estimated distributions were observed among models constructed with default versus AIC_C‐selected parameterization. Although all models had similarly high performance and evaluation metrics, the AIC_C‐selected models were more inclusive of westward‐situated and smaller, headwater streams. Overall, our results solidified the importance of accounting for model complexity and spatial sampling bias in SDMs constructed within stream networks and provided a roadmap for future paddlefish restoration efforts in the study area.     

Longitudinal distribution of Trichoptera in the Loire River (France): simple ordination methods and community structure

The longitudinal distribution of Trichoptera at 37 sampling sites along 800 km of the Loire River (France) was analyzed in order to better understand large-scale changes in community structure occurring on a stream continuum. Different simple ordination methods — centered PCA and Correspondence Analysis — were performed to investigate these changes. Both analyses showed that a major change occurs in the community in the upper reaches of the Loire River between the Serre de la Fare and Vorey sampling sites with the appearance of Hydropsyche contubernalis and H. Exocellata. Even though other changes in community structure could exist, revealed either by Correspondence Analysis at the first sampling sites (crenal), or by PCA at sampling sites influenced by dams, this Trichoptera community appears to be stable enough in the latter part of the Loire River with the addition of a few species, Hydropsyche bulgaromanorum, Ecnomus tenellus and E. deceptor, rather than changes in species. The results are discussed in the light of different concepts in stream ecology, and the validity of such data analyses to describe some community patterns.     

Sampling strategies for estimating brook trout effective population size

The influence of sampling strategy on estimates of effective population size (N _e ) from single-sample genetic methods has not been rigorously examined, though these methods are increasingly used. For headwater salmonids, spatially close kin association among age-0 individuals suggests that sampling strategy (number of individuals and location from which they are collected) will influence estimates of N _e through family representation effects. We collected age-0 brook trout by completely sampling three headwater habitat patches, and used microsatellite data and empirically parameterized simulations to test the effects of different combinations of sample size (S = 25, 50, 75, 100, 150, or 200) and number of equally-spaced sample starting locations (SL = 1, 2, 3, 4, or random) on estimates of mean family size and effective number of breeders (N _b ). Both S and SL had a strong influence on estimates of mean family size and [^(N)]_b , \hat{N}_{b} , however the strength of the effects varied among habitat patches that varied in family spatial distributions. The sampling strategy that resulted in an optimal balance between precise estimates of N _b and sampling effort regardless of family structure occurred with S = 75 and SL = 3. This strategy limited bias by ensuring samples contained individuals from a high proportion of available families while providing a large enough sample size for precise estimates. Because this sampling effort performed well for populations that vary in family structure, it should provide a generally applicable approach for genetic monitoring of iteroparous headwater stream fishes that have overlapping generations.     

A comparison of nonlethal sampling methods for amphibian gut microbiome analyses

Noninvasive sampling methods for studying intestinal microbiomes are widely applied in studies of endangered species and in those conducting temporal monitoring during manipulative experiments. Although existing studies show that noninvasive sampling methods among different taxa vary in their accuracy, no studies have yet been published comparing nonlethal sampling methods in adult amphibians. In this study, we compare microbiomes from two noninvasive sample types (faeces and cloacal swabs) to that of the large intestine in adult cane toads, Rhinella marina. We use 16S rRNA gene sequencing to investigate how microbial communities change along the digestive tract and which nonlethal sampling method better represents large intestinal microbiota. We found that cane toads' intestinal microbiota was dominated by Bacteroidetes, Proteobacteria and Firmicutes and, interestingly, we also saw a high proportion of Fusobacteria, which has previously been associated with marine species and changes in frog immunity. The large and small intestine of cane toads had a similar microbial composition, but the large intestine showed higher diversity. Our results indicate that cloacal swabs were more similar to large intestine samples than were faecal samples, and small intestine samples were significantly different from both nonlethal sample types. Our study provides valuable information for future investigations of the cane toad gut microbiome and validates the use of cloacal swabs as a nonlethal method to study changes in the large intestine microbiome. These data provide insights for future studies requiring nonlethal sampling of amphibian gut microbiota.