Acute/chronic ratios to estimate chronic toxicity from acute data

Acute toxicity of 25 narcotic compounds to D. magna was determined in this paper. Acute/ Chronic Ratios (ACRs), which are often used to estimate chronic toxicity from acute toxicity data, are discussed based on Quantitative Structure‐Activity Relationships (QSARs) of the compounds between both acute and chronic toxicity data and n‐octanol/water partition coefficients, and an improved equation is derived to estimate chronic toxicity data from acute toxicity data. Application of the improved equation and ACRs is illustrated for D. magna and fathead minnow to estimate chronic toxicity from acute toxicity.     

An animal movement model incorporating home range and habitat selection

Wildlife biologists are often interested in how an animal uses space and the habitat resources within that space. We propose a single model that estimates an animal’s home range and habitat selection parameters within that range while accounting for the inherent autocorrelation in frequently sampled telemetry data. The model is applied to brown bear telemetry data in southeast Alaska. This article is based on a portion of this author’s Ph.D. dissertation completed in 2003 at the University of Iowa.     

Continuous-time correlated random walk model for animal telemetry data

We propose a continuous-time version of the correlated random walk model for animal telemetry data. The continuous-time formulation allows data that have been nonuniformly collected over time to be modeled without subsampling, interpolation, or aggregation to obtain a set of locations uniformly spaced in time. The model is derived from a continuous-time Ornstein-Uhlenbeck velocity process that is integrated to form a location process. The continuous-time model was placed into a state-space framework to allow parameter estimation and location predictions from observed animal locations. Two previously unpublished marine mammal telemetry data sets were analyzed to illustrate use of the model, by-products available from the analysis, and different modifications which are possible. A harbor seal data set was analyzed with a model that incorporates the proportion of each hour spent on land. Also, a northern fur seal pup data set was analyzed with a random drift component to account for directed travel and ocean currents.     

Parental investment, adult sex ratios, and sexual selection in a socially monogamous seabird

Although most birds are monogamous, theory predicts that greater female parental investment and female-biased adult sex ratios will lower the polygyny threshold. This should result in polygynous mating, unless obligate biparental care or the spatial and temporal distribution of fertilizable females constrains a male’s ability to take advantage of a lowered polygyny threshold. Here we present data on the extent of male sexually dimorphic plumage, adult sex ratios and breeding season synchrony in three populations of a socially monogamous seabird, the brown booby Sula leucogaster. For one of these populations, San Pedro Mártir Island, we also present data on differences in male and female parental investment, mortality and probability of pairing. The extent of plumage dimorphism varied among populations. Sex ratios were female biased in all populations. On San Pedro Mártir Island, parental investment was female biased, females failed more often than males to find a mate, but there was no polygyny. We suggest that on San Pedro Mártir: (1) a period of obligate biparental care coupled with a relatively synchronous breeding season constrained the ability of males to take advantage of a high environmental polygamy potential and (2) the resulting socially monogamous mating system, in combination with the female-biased adult sex ratio, caused females to be limited by the availability of males despite their greater parental investment. Received: 18 November 1999 / Accepted: 24 January 2000     

Modified Weibull multi-state models for the analysis of animal carcinogenicity data

The Peto test is the standard method of analysis used in carcinogenicity studies to compare tumor incidence in groups of animals. It assumes that tumors are either instantly fatal or have no effect on mortality and requires a judgement of the lethality of each tumor. To avoid this requirement, parametric multi-state models have been proposed. In addition these allow estimation of tumor onset and mortality rates. This paper considers two such models and presents a modification. It is shown that the modified models provide a better fit to carcinogenicity data and simulated data are used to show that the modified models provide a modest increase in test power relative to the Peto test.     

Secondary sex ratios do not support maternal manipulation: extensive data from laboratory colonies of spiny mice (Muridae: Acomys)

Spiny mice of the genus Acomys (Muridae) represent a very suitable mammalian model for studying factors influencing the secondary sex ratio (SSR). The maternal effort in these rodents is extremely biased in favour of the prenatal period and, therefore, maternal manipulation of the SSR is potentially more advantageous. We studied the SSR in four populations/species of spiny mice kept in family groups consisting of two closely related females, one non-relative male and their descendants. The groups were established from founding animals aged about 3 months (maturing age) and were allowed to breed freely for several months. Each litter was sexed after birth, and relevant data were thoroughly recorded. Altogether, data were collected on 1684 litters: 189 of Acomys sp. from Iran, 203 of A. cilicicus, 875 of A. cahirinus, and 417 of A. dimidiatus. We recorded the sex of 4048 newborns of which 1995 were males and 2053 were females. The overall sex ratio was close to 1:1 (49.2%). Generalized linear mixed models and/or generalized linear models were constructed to evaluate the effect of four life history and eight social variables on the sex ratio. No consistent effects of these variables on the sex ratio were found and, interestingly, none of the variables associated with maternal life history had any effect on the sex ratio. Three factors associated with group composition (i.e. the number of immature males, the number of immature females and the number of breeding females) did have significant effects on the sex ratio, but these effects were not consistent across the studied species. In conclusion, our evaluation of this large dataset revealed that the sex ratio in spiny mice is surprisingly stable.     

Design-based spatial interpolation with data driven selection of the smoothing parameter

Environmental and Ecological Statistics - In the inverse distance weighting interpolation the interpolated, value is a weighted mean of the sampled values, with weights decreasing with the...     

Isotopic ratios of lead in contemporary environmental material from Scotland

Lead emitted into the environment, primarily from the combustion of leaded petrol and industrial activities, retains the isotopic signature of the ore(s) from which it is derived. Leaded petrol, atmospheric particulates and street dust sampled in central Edinburgh between February 1989 and December 1991 had mean²⁰⁶Pb/²⁰⁷Pb ratios of 1.082 ± 0.024, 1.092 ± 0.011 and 1.109 ± 0.016 respectively. These isotope ratios were found to be depleted in²⁰⁶Pb compared with a mean of 1.160 ± 0.012 for tap water in contact with lead pipes and %typical ratios of 1.17–1.19 for British lead ore deposits and coal. Paint, with an observed wide range of 20 Pb²⁰⁷ Pb ratios (1.083–1.183), appears to have significantly influenced house dust and some street dust²⁰⁶Pb²⁰⁷ values. Such overlaps and influences may hinder the quantitative apportionment, via isotope data, of source and route in general population surveys of human exposure to lead.     

Inter-colony movements,at-sea behaviour and foraging in an immature seabird: results from GPS-PPT tracking,radio-tracking and stable isotope analysis

Seabird populations contain large numbers of immatures––in some instances comprising >50% of the fully grown adults in the population. These birds are significant components of marine food webs and may contribute to compensatory recruitment and dispersal, but remain severely understudied. Here, we use GPS-PTTs, radio-tracking and analysis of stable carbon (δ¹³C) and nitrogen (δ¹⁵N) isotopes to investigate the movements and foraging ecology of immature seabirds. Our study focussed on immature northern gannets Morus bassanus aged 2–4 attending non-breeding aggregations alongside a large breeding colony. GPS-PTT tracking of five birds revealed that immatures have the ability to disperse widely during the breeding season, with some individuals potentially prospecting at other colonies. Overall, however, immatures were faithful to the colony of capture. During returns to the focal colony, immatures acted as central place foragers, conducted looping and commuting flights, and analysis of the variance in first-passage time revealed evidence of area-restricted search (ARS) behaviour. In addition, stable carbon (δ¹³C) and nitrogen (δ¹⁵N) isotope analyses indicate that immatures were isotopically segregated from breeders. Our findings provide insights into the foraging, prospecting and dispersal behaviour of immature seabirds, which may have important implications for understanding seabird ecology and conservation.     

Measurement error causes scale-dependent threshold erosion of biological signals in animal movement data.

Recent advances in telemetry technology have created a wealth of tracking data available for many animal species moving over spatial scales from tens of meters to tens of thousands of kilometers. Increasingly, such data sets are being used for quantitative movement analyses aimed at extracting fundamental biological signals such as optimal searching behavior and scale-dependent foraging decisions. We show here that the location error inherent in various tracking technologies reduces the ability to detect patterns of behavior within movements. Our analyses endeavored to set out a series of initial ground rules for ecologists to help ensure that sampling noise is not misinterpreted as a real biological signal. We simulated animal movement tracks using specialized random walks known as Lévy flights at three spatial scales of investigation: 100-km, 10-km, and 1-km maximum daily step lengths. The locations generated in the simulations were then blurred using known error distributions associated with commonly applied tracking methods: the Global Positioning System (GPS), Argos polar-orbiting satellites, and light-level geolocation. Deviations from the idealized Lévy flight pattern were assessed for each track after incrementing levels of location error were applied at each spatial scale, with additional assessments of the effect of error on scale-dependent movement patterns measured using fractal mean dimension and first-passage time (FPT) analyses. The accuracy of parameter estimation (Lévy mu, fractal mean D, and variance in FPT) declined precipitously at threshold errors relative to each spatial scale. At 100-km maximum daily step lengths, error standard deviations of > or = 10 km seriously eroded the biological patterns evident in the simulated tracks, with analogous thresholds at the 10-km and 1-km scales (error SD > or = 1.3 km and 0.07 km, respectively). Temporal subsampling of the simulated tracks maintained some elements of the biological signals depending on error level and spatial scale. Failure to account for large errors relative to the scale of movement can produce substantial biases in the interpretation of movement patterns. This study provides researchers with a framework for understanding the limitations of their data and identifies how temporal subsampling can help to reduce the influence of spatial error on their conclusions.     

Habitat selection models to account for seasonal persistence in radio telemetry data

Models for the analysis of habitat selection data incorporate covariates in an independent multinomial selections model (McCracken et al. 1998) Ramsey and Usner 2003 and an extension of that model to include a persistence parameter (2003). In both cases, all parameters are assumed to be fixed through time. Radio telemetry data collected for habitat selection studies typically consist of animal relocations through time, suggesting the need for an extension to these models. We use a Bayesian approach that allows for the habitat selection probabilities, persistence parameter, or both, to change with season. These extensions are particularly important when movement patterns are expected to differ seasonally and/or when availabilities of habitats change throughout the study period due to weather or migration. We implement and compare the models using radio telemetry data for westslope cutthroat trout in two streams in eastern Oregon.     

Reversed parasite-mediated selection in sticklebacks from eutrophied habitats

Sexual selection is often assumed to increase the viability of populations by increasing the quality of offspring produced. Presently, human-induced environmental changes are altering the process of sexual selection by influencing male–male interactions and female mate choice. Here, we show that increased density of filamentous algae due to eutrophication reverses parasite-mediated selection during reproduction in threespine sticklebacks (Gasterosteus aculeatus). When we manipulated the density of artificial algae in a breeding area in the Baltic Sea, more males nested in dense than in sparse vegetation, but the males in dense vegetation were more parasitized. Interestingly, heavily parasitized males acquired more eggs than less parasitized males in dense vegetation but not in sparse vegetation. The higher probability of reproduction for parasitized males in dense algae growth could be due to impaired visibility relaxing male–male competition or reducing female choosiness. This could favour males in poor condition that often invest more in attracting females than males in good condition. In sparse vegetation, parasitized males may have a lower reproductive success due to intense male–male competition, careful female choice and high predation rate selecting against parasitized males. The results suggest that eutrophication could alter the fraction of the population that reproduces, which could have long-term evolutionary consequences.     

Model selection criteria for overdispersed data and their application to the characterization of a host-parasite relationship

In the statistical modeling of a biological or ecological phenomenon, selecting an optimal model among a collection of candidates is a critical issue. To identify an optimal candidate model, a number of model selection criteria have been developed and investigated based on estimating Kullback’s (Information theory and statistics. Dover, Mineola, 1968) directed or symmetric divergence. Criteria that target the directed divergence include the Akaike (2nd international symposium on information theory. Akadémia Kiadó, Budapest, Hungary, pp 267–281, 1973, IEEE Trans Autom Control AC 19:716–723, 1974) information criterion, AIC, and the “corrected” Akaike information criterion (Hurvich and Tsai in Biometrika 76:297–307, 1989), AICc; criteria that target the symmetric divergence include the Kullback information criterion, KIC, and the “corrected” Kullback information criterion, KICc (Cavanaugh in Stat Probab Lett 42:333–343, 1999; Aust N Z J Stat 46:257–274, 2004). For overdispersed count data, simple modifications of AIC and AICc have been increasingly utilized: specifically, the quasi Akaike information criterion, QAIC, and its corrected version, QAICc (Lebreton et al. in Ecol Monogr 62(1):67–118 1992). In this paper, we propose analogues of QAIC and QAICc based on estimating the symmetric as opposed to the directed divergence: QKIC and QKICc. We evaluate the selection performance of AIC, AICc, QAIC, QAICc, KIC, KICc, QKIC, and QKICc in a simulation study, and illustrate their practical utility in an ecological application. In our application, we use the criteria to formulate statistical models of the tick (Dermacentor variabilis) load on a white-footed mouse (Peromyscus leucopus) in northern Missouri.     

Delimiting synchronous populations from monitoring data

We propose to investigate spatial synchrony in population dynamics from monitoring data. We develop a statistical procedure to delineate populations of sites with synchronous dynamics from short time series. The procedure relies on a new norm, the synchronous total variation norm, which promotes synchrony in the estimation of the sites dynamics. The method is tested on some synthetic data sets and is applied on data from the French breeding bird monitoring program.     

Estimating age-specific hazards from wildlife telemetry data

We illustrate 2 techniques for estimating age-specific hazards with wildlife telemetry data: Siler’s (Ecology 60:750–757, 1979) competing risk model fit using maximum likelihood and a penalized likelihood estimate that only assumes the hazard varies smoothly with age. In most telemetry studies, animals enter at different points in time (and at different ages), leading to data that are left-truncated. In addition, death times may only be known to occur within an interval of time (interval-censoring). Observations may also be right-censored (e.g., due to the end of the study, radio-collar failure, or emigration from the study area). It is important to consider the observation process, since the contribution of each individual’s data to the likelihood will depend on whether data are left-truncated or censored. We estimate age-specific hazards using telemetry data collected in two Phases during a 13-year study of white-tailed deer (Odocoileus virginianus) in northern Minnesota. The hazards estimated from the two methods were similar for the full data set that included 302 adults and 76 neonates (followed since or shortly after birth). However, estimated hazards for early-aged individuals differed considerably for subsets of the data that did not include neonates. We discuss the advantages and disadvantages of these two modeling approaches and also compare the estimators using a short simulation study.     

Functional ANOVA starting from discrete data: an application to air quality data

A nonparametric functional approach is proposed to compare the mean functions of $k$ k samples of curves. In practice, curves data are usually collected in a discrete form and hence they must be pre-processed to use purely functional techniques. However, in the context of $k$ k -sample tests, the pre-processing step can have effects in terms of power reduction. Hall and Van Keilegom (Stat Sin 17:1511–1531, 2007) proposed a methodology to minimizing these effects in the context of tests for the equality of two distribution functions. Their procedure is here extended to the case of $k$ k -sample hypothesis tests. The asymptotic validity of the procedure is established and its finite sample performance is analyzed through Monte Carlo experiments. As an illustration, the method is applied to air quality data collected from several monitoring stations placed at different geographical locations at the center of Spain.     

A new procedure to optimize the selection of groups in a classification tree: Applications for ecological data

Agglomerative cluster analyses encompass many techniques, which have been widely used in various fields of science. In biology, and specifically ecology, datasets are generally highly variable and may contain outliers, which increase the difficulty to identify the number of clusters. Here we present a new criterion to determine statistically the optimal level of partition in a classification tree. The criterion robustness is tested against perturbated data (outliers) using an observation or variable with values randomly generated. The technique, called Random Simulation Test (RST), is tested on (1) the well-known Iris dataset [Fisher, R.A., 1936. The use of multiple measurements in taxonomic problems. Ann. Eugenic. 7, 179–188], (2) simulated data with predetermined numbers of clusters following Milligan and Cooper [Milligan, G.W., Cooper, M.C., 1985. An examination of procedures for determining the number of clusters in a data set. Psychometrika 50, 159–179] and finally (3) is applied on real copepod communities data previously analyzed in Beaugrand et al. [Beaugrand, G., Ibanez, F., Lindley, J.A., Reid, P.C., 2002. Diversity of calanoid copepods in the North Atlantic and adjacent seas: species associations and biogeography. Mar. Ecol. Prog. Ser. 232, 179–195]. The technique is compared to several standard techniques. RST performed generally better than existing algorithms on simulated data and proved to be especially efficient with highly variable datasets.