The duration of residence approach to a dynamic stochastic model of internal migration: A test of the axiom of cumulative inertia

Abstract

The data presented indicate a definite trend that tends to support the axiom of cumulative inertia. The probabilities of movement decline by increasing duration of residence for each year. Not only is information on duration of residence an important element in any study of migration, but it also provides a necessary modification for the Markov chain approach to migration probabilities. Future studies of the mathematical model will require data that will satisfy the criteria stipulated in this paper and will be of sufficient quantity to assure reliable within‐cell probabilities of movement.     

Site occupancy models with heterogeneous detection probabilities

Models for estimating the probability of occurrence of a species in the presence of imperfect detection are important in many ecological disciplines. In these "site occupancy" models, the possibility of heterogeneity in detection probabilities among sites must be considered because variation in abundance (and other factors) among sampled sites induces variation in detection probability (p). In this article, I develop occurrence probability models that allow for heterogeneous detection probabilities by considering several common classes of mixture distributions for p. For any mixing distribution, the likelihood has the general form of a zero-inflated binomial mixture for which inference based upon integrated likelihood is straightforward. A recent paper by Link demonstrates that in closed population models used for estimating population size, different classes of mixture distributions are indistinguishable from data, yet can produce very different inferences about population size. I demonstrate that this problem can also arise in models for estimating site occupancy in the presence of heterogeneous detection probabilities. The implications of this are discussed in the context of an application to avian survey data and the development of animal monitoring programs.     

Is there a star tree paradox?

Concerns have been raised that posterior probabilities on phylogenetic trees can be unreliable when the true tree is unresolved or has very short internal branches, because existing methods for Bayesian phylogenetic analysis do not explicitly evaluate unresolved trees. Two recent papers have proposed that evaluating only resolved trees results in a "star tree paradox": when the true tree is unresolved or close to it, posterior probabilities were predicted to become increasingly unpredictable as sequence length grows, resulting in inflated confidence in one resolved tree or another and an increasing risk of false-positive inferences. Here we show that this is not the case; existing Bayesian methods do not lead to an inflation of statistical confidence, provided the evolutionary model is correct and uninformative priors are assumed. Posterior probabilities do not become increasingly unpredictable with increasing sequence length, and they exhibit conservative type I error rates, leading to a low rate of false-positive inferences. With infinite data, posterior probabilities give equal support for all resolved trees, and the rate of false inferences falls to zero. We conclude that there is no star tree paradox caused by not sampling unresolved trees.     

Fitting probability distributions to animal movement trajectories: using artificial neural networks to link distance, resources, and memory

Animal movement paths are often thought of as a confluence of behavioral processes and landscape patterns. Yet it has proven difficult to develop frameworks for analyzing animal movement that can test these interactions. Here we describe a novel method for fitting movement models to data that can incorporate diverse aspects of landscapes and behavior. Using data from five elk (Cervus canadensis) reintroduced to central Ontario, we employed artificial neural networks to estimate movement probability kernels as functions of three landscape-behavioral processes. These consisted of measures of the animals' response to the physical spatial structure of the landscape, the spatial variability in resources, and memory of previously visited locations. The results support the view that animal movement results from interactions among elements of landscape structure and behavior, motivating context-dependent movement probabilities, rather than from successive realizations of static distributions, as some traditional models of movement and resource selection assume. Flexible, nonlinear models may thus prove useful in understanding the mechanisms controlling animal movement patterns.     

Effect of search method and age class on mark-recapture parameter estimation in a population of red-backed salamanders

Mark-recapture methods are generally considered to more accurately reflect population trends than count data, which is especially important for indicator species. Terrestrial salamanders are often used as indicators of forest ecosystem health and may be monitored through diurnal cover object searches or nocturnal activity searches. Our goal was to determine whether search method affected encounter probabilities, whether these probabilities differed between age classes, and whether the inclusion of search method in mark-recapture models affected abundance estimates. We used program MARK to analyze 3 years of red-backed salamander (Plethodon cinereus) mark-recapture data using Pollock’s robust design taken from a 144 m² plot. Initial encounter probabilities during night searches were consistently greater than during diurnal cover object searches. As a result, inclusion of search method in models sometimes affected abundance estimates. There was no difference between adult and juvenile encounter probabilities nor were abundance estimates affected by inclusion of age class, but there was yearly variation in the juvenile abundance estimates. For these reasons, we recommend that sampling of terrestrial salamanders include nocturnal activity searches and be conducted over multiple years. Monitoring programs of other species should take into account whether the selected search method(s) may be more likely to sample different subsets of the population of interest and how this may restrict their inferences.     

脊髓灰质炎病毒各代表株壳蛋白二级结构及亲水概率的电子计算机预测

本文用脊髓灰质炎病毒3个型6个强弱代表株壳蛋白一级结构,借助电子计算机预测和计算出病毒壳蛋白的二级结构和亲水概率。     

Testing the consistency of wildlife data types before combining them: the case of camera traps and telemetry

Wildlife data gathered by different monitoring techniques are often combined to estimate animal density. However, methods to check whether different types of data provide consistent information (i.e., can information from one data type be used to predict responses in the other?) before combining them are lacking. We used generalized linear models and generalized linear mixed-effects models to relate camera trap probabilities for marked animals to independent space use from telemetry relocations using 2 years of data for fishers (Pekania pennanti) as a case study. We evaluated (1) camera trap efficacy by estimating how camera detection probabilities are related to nearby telemetry relocations and (2) whether home range utilization density estimated from telemetry data adequately predicts camera detection probabilities, which would indicate consistency of the two data types. The number of telemetry relocations within 250 and 500 m from camera traps predicted detection probability well. For the same number of relocations, females were more likely to be detected during the first year. During the second year, all fishers were more likely to be detected during the fall/winter season. Models predicting camera detection probability and photo counts solely from telemetry utilization density had the best or nearly best Akaike Information Criterion (AIC), suggesting that telemetry and camera traps provide consistent information on space use. Given the same utilization density, males were more likely to be photo-captured due to larger home ranges and higher movement rates. Although methods that combine data types (spatially explicit capture–recapture) make simple assumptions about home range shapes, it is reasonable to conclude that in our case, camera trap data do reflect space use in a manner consistent with telemetry data. However, differences between the 2 years of data suggest that camera efficacy is not fully consistent across ecological conditions and make the case for integrating other sources of space-use data.     

Match probabilities in a finite, subdivided population

We generalize a recently introduced graphical framework to compute the probability that haplotypes or genotypes of two individuals drawn from a finite, subdivided population match. As in the previous work, we assume an infinite-alleles model. We focus on the case of a population divided into two subpopulations, but the underlying framework can be applied to a general model of population subdivision. We examine the effect of population subdivision on the match probabilities and the accuracy of the product rule which approximates multi-locus match probabilities as a product of one-locus match probabilities. We quantify the deviation from predictions of the product rule by R, the ratio of the multi-locus match probability to the product of the one-locus match probabilities. We carry out the computation for two loci and find that ignoring subdivision can lead to underestimation of the match probabilities if the population under consideration actually has subdivision structure and the individuals originate from the same subpopulation. On the other hand, under a given model of population subdivision, we find that the ratio R for two loci is only slightly greater than 1 for a large range of symmetric and asymmetric migration rates. Keeping in mind that the infinite-alleles model is not the appropriate mutation model for STR loci, we conclude that, for two loci and biologically reasonable parameter values, population subdivision may lead to results that disfavor innocent suspects because of an increase in identity-by-descent in finite populations. On the other hand, for the same range of parameters, population subdivision does not lead to a substantial increase in linkage disequilibrium between loci. Those results are consistent with established practice.     

A stochastic repair—misrepair model for the effects of radiation on cells

The purpose of this paper is to present a stochastic model for effects of radiation on cells. The model includes provisions for lethal effects and for transformation to malignant status. Empirical findings indicate the presence of some repair mechanism in the cells, and a way to incorporate this idea into the model is discussed. Comparisons of the derived survival and transformation probabilities with actual data are favorable. The interpretation of the estimated values leads to questions to be investigated by the experimenters.Supported in part by the Graduate Research Board, University of Maryland     

Effects of branch length uncertainty on Bayesian posterior probabilities for phylogenetic hypotheses

In Bayesian phylogenetics, confidence in evolutionary relationships is expressed as posterior probability--the probability that a tree or clade is true given the data, evolutionary model, and prior assumptions about model parameters. Model parameters, such as branch lengths, are never known in advance; Bayesian methods incorporate this uncertainty by integrating over a range of plausible values given an assumed prior probability distribution for each parameter. Little is known about the effects of integrating over branch length uncertainty on posterior probabilities when different priors are assumed. Here, we show that integrating over uncertainty using a wide range of typical prior assumptions strongly affects posterior probabilities, causing them to deviate from those that would be inferred if branch lengths were known in advance; only when there is no uncertainty to integrate over does the average posterior probability of a group of trees accurately predict the proportion of correct trees in the group. The pattern of branch lengths on the true tree determines whether integrating over uncertainty pushes posterior probabilities upward or downward. The magnitude of the effect depends on the specific prior distributions used and the length of the sequences analyzed. Under realistic conditions, however, even extraordinarily long sequences are not enough to prevent frequent inference of incorrect clades with strong support. We found that across a range of conditions, diffuse priors--either flat or exponential distributions with moderate to large means--provide more reliable inferences than small-mean exponential priors. An empirical Bayes approach that fixes branch lengths at their maximum likelihood estimates yields posterior probabilities that more closely match those that would be inferred if the true branch lengths were known in advance and reduces the rate of strongly supported false inferences compared with fully Bayesian integration.     

Towards the automated detection and occupancy estimation of primates using passive acoustic monitoring

Recent advancements in technology have made possible the use of novel, cost-efficient biomonitoring techniques which facilitate monitoring animal populations at larger spatial and temporal scales. Here, we investigated using passive acoustic monitoring (PAM) for wild primate populations living in the forest of Taï National Park, Côte d’Ivoire. We assessed the potential of using a customized algorithm for the automated detection of multiple primate species to obtain reliable estimates of species occurrence from acoustic data. First, we applied the algorithm on continuous rainforest recordings collected using autonomous recording units (ARUs) to detect and classify three sound signals: chimpanzee buttress drumming, and the loud calls of the diana and king colobus monkey. Using an occupancy modelling approach we then investigated to what extent the automated, probabilistic output needs to be listened to, and thus manually cleaned, by a human expert, to approach occupancy probabilities derived from ARU data fully verified by a human. To do this we explored the robustness of occupancy probability estimates by simulating ARU datasets with various degrees of cleaning for false positives and false negative detections. We further validated the approach by comparing it to data collected by human observers on point transects located within the same study area. Our study demonstrates that occurrence estimates from ARU data, combined with automated processing methods such as our algorithm, can provide results comparable to data collected by humans and require less effort. We show that occupancy probabilities are quite robust to cleaning effort, particularly when occurrence is high, and suggest that for some species even naïve occupancy, as derived from ARU data without any cleaning, could provide a quick and reliable indicator to guide monitoring efforts. We found detection probabilities to be most influenced by time of day for chimpanzee drums while temperature and, likely, poaching pressure, affected detection of diana monkey loud calls. None of the covariates investigated appeared to have strongly affected king colobus loud call detection. Finally, we conclude that the semi-automated approach presented here could be used as an early-warning system for poaching activity and suggest additional techniques for improving its performance.     

A rapid conditional enumeration haplotyping method in pedigrees

Haplotyping in pedigrees provides valuable information for genetic studies (e.g., linkage analysis and association study). In order to identify a set of haplotype configurations with the highest likelihoods for a large pedigree with a large number of linked loci, in our previous work, we proposed a conditional enumeration haplotyping method which sets a threshold for the conditional probabilities of the possible ordered genotypes at every unordered individual-marker to delete some ordered genotypes with low conditional probabilities and then eliminate some haplotype configurations with low likelihoods. In this article we present a rapid haplotyping algorithm based on a modification of our previous method by setting an additional threshold for the ratio of the conditional probability of a haplotype configuration to the largest conditional probability of all haplotype configurations in order to eliminate those configurations with relatively low conditional probabilities. The new algorithm is much more efficient than our previous method and the widely used software SimWalk2.     

Estimating Detection Probabilities from Sign of Collared Peccary

ABSTRACT Determining presence or absence of collared peccaries (Pecari tajacu) from surveys of sign (tracks and feces) requires information on whether animals in sample units are detected. We estimated detection probabilities of collared peccary from sign surveys using occupancy models. Because it was unlikely that residence status of collared peccary in sampling units remained the same over a survey season, which is a primary assumption of occupancy models, we first determined the time interval for which to pool data. We then examined the influence of rainfall and peccary abundance on detection probabilities. We placed 90 sign stations (25-m-diam circular plots) throughout Chaparral Wildlife Management Area, south Texas, USA. We surveyed plots weekly for the presence or non-presence of collared peccary during 2 11-week sampling seasons in spring and fall 2003. We examined sign data weekly and we pooled the data in intervals from 2 weeks to 5 weeks. Estimates of detection probabilities increased from 1 week to 3 weeks of pooled data and leveled off thereafter. We needed a 3-week time interval to meet the assumption of unchanging residence status. Using sign data pooled in 3-week increments, detection probabilities were influenced by areas that differed in peccary abundance, but they were not influenced by rainfall. Estimates of detection probabilities ranged from 0.43 to 0.77 for 3-week time intervals. Sign surveys and occupancy modeling of data can be used to measure spatial patterns of collared peccary in south Texas as long as multiple 3-week time intervals are sampled.     

Models for analysing species’ presence/absence data at two time points

Species’ presence/absence at two time points is a very common form of ecological data. It is the simplest type of longitudinal study and has fundamental applications in ecological succession, environmental monitoring, and climate change scenarios. Despite its widespread commonality the use of statistical regression to analyse such data has been wanting. We propose the use of the bivariate odds-ratio model to analyse these data. Seldomly used in ecology, it is argued as being suitable, especially within a constrained ordination framework. In particular, this paper presents the constrained ordination-odds ratio framework as a potentially important key in understanding the underlying processes of niche theory dynamics, e.g., local extinction and colonization probabilities can be described in terms of it. Some of the mathematical and statistical challenges associated with more ambitious extensions are highlighted. As examples, with an underlying Poisson abundance model, a complementary log-log link for the marginal probabilities is shown to be more appropriate. We then develop this model based on the zero-inflated Poisson distribution since excess absences relative to a Poisson distribution is frequent in practice. Two vegetation data sets are used for illustrative purposes.     

Estimating migratory connectivity of birds when re‐encounter probabilities are heterogeneous

Understanding the biology and conducting effective conservation of migratory species requires an understanding of migratory connectivity – the geographic linkages of populations between stages of the annual cycle. Unfortunately, for most species, we are lacking such information. The North American Bird Banding Laboratory (BBL) houses an extensive database of marking, recaptures and recoveries, and such data could provide migratory connectivity information for many species. To date, however, few species have been analyzed for migratory connectivity largely because heterogeneous re‐encounter probabilities make interpretation problematic. We accounted for regional variation in re‐encounter probabilities by borrowing information across species and by using effort covariates on recapture and recovery probabilities in a multistate capture–recapture and recovery model. The effort covariates were derived from recaptures and recoveries of species within the same regions. We estimated the migratory connectivity for three tern species breeding in North America and over‐wintering in the tropics, common (Sterna hirundo), roseate (Sterna dougallii), and Caspian terns (Hydroprogne caspia). For western breeding terns, model‐derived estimates of migratory connectivity differed considerably from those derived directly from the proportions of re‐encounters. Conversely, for eastern breeding terns, estimates were merely refined by the inclusion of re‐encounter probabilities. In general, eastern breeding terns were strongly connected to eastern South America, and western breeding terns were strongly linked to the more western parts of the nonbreeding range under both models. Through simulation, we found this approach is likely useful for many species in the BBL database, although precision improved with higher re‐encounter probabilities and stronger migratory connectivity. We describe an approach to deal with the inherent biases in BBL banding and re‐encounter data to demonstrate that this large dataset is a valuable source of information about the migratory connectivity of the birds of North America.     

CAPTURE-RECAPTURE ANALYSIS FOR ESTIMATING MANATEE REPRODUCTIVE RATES

Modeling the life history of the endangered Florida manatee ( Trichechus manatus latirostris ) is an important step toward understanding its population dynamics and predicting its response to management actions. We developed a multi-state markresighting model for data collected under Pollock's robust design. This model estimates breeding probability conditional on a female's breeding state in the previous year; assumes sighting probability depends on breeding state; and corrects for misclassification of a cow with first-year calf, by estimating conditional sighting probability for the calf. The model is also appropriate for estimating survival and unconditional breeding probabilities when the study area is closed to temporary emigration across years. We applied this model to photo-identification data for the Northwest and Atlantic Coast populations of manatees, for years 1982–2000. With rare exceptions, manatees do not reproduce in two consecutive years. For those without a first-year calf in the previous year, the best-fitting model included constant probabilities of producing a calf for the Northwest (0.43, SE = 0.057) and Atlantic (0.38, SE = 0.045) populations. The approach we present to adjust for misclassification of breeding state could be applicable to a large number of marine mammal populations.     

Protein probabilities in shotgun proteomics: evaluating different estimation methods using a semi-random sampling model

The calculation of protein probabilities is one of the most intractable problems in large-scale proteomic research. Current available estimating methods, for example, ProteinProphet, PROT_PROBE, Poisson model and two-peptide hits, employ different models trying to resolve this problem. Until now, no efficient method is used for comparative evaluation of the above methods in large-scale datasets. In order to evaluate these various methods, we developed a semi-random sampling model to simulate large-scale proteomic data. In this model, the identified peptides were sampled from the designed proteins and their cross-correlation scores were simulated according to the results from reverse database searching. The simulated result of 18 control proteins was consistent with the experimental one, demonstrating the efficiency of our model. According to the simulated results of human liver sample, ProteinProphet returned slightly higher probabilities and lower specificity than real cases. PROT_PROBE was a more efficient method with higher specificity. Predicted results from a Poisson model roughly coincide with real datasets, and the method of two-peptide hits seems solid but imprecise. However, the probabilities of identified proteins are strongly correlated with several experimental factors including spectra number, database size and protein abundance distribution.     

Movement,site fidelity and connectivity in a top marine predator,the killer whale

Movement, site fidelity and connectivity have important consequences for the evolution of population structure and therefore the conservation and management of a species. In this study photographs of naturally marked killer whales collected from sites across the Northeast Atlantic are used to estimate fidelity to sampling locations and movement between locations, expressed as transition probabilities, pt, using maximum likelihood methods. High transition probabilities suggest there is high inter-annual site fidelity to all locations, and large-scale movement between the spawning and wintering grounds of both Norwegian and Iceland stocks of Atlantic herring. There was no evidence of movement between the Norwegian herring grounds and Icelandic herring grounds, or between the mackerel fishing grounds and the herring fishing grounds. Thus the movement of predictable and abundant prey resources can lead to intrinsic isolation in this species We also find movement between the Northern Isles, Scotland and East Iceland. An association network indicates that killer whales predating seals around the Northern Isles, Scotland are linked to the community of killer whales that follow the Icelandic summer-spawning herring. This adds support to existing evidence of a broad niche width in some populations.     

Movements and source–sink dynamics of a Masai giraffe metapopulation

Spatial variation in habitat quality and anthropogenic factors, as well as social structure, can lead to spatially structured populations of animals. Demographic approaches can be used to improve our understanding of the dynamics of spatially structured populations and help identify subpopulations critical for the long-term persistence of regional metapopulations. We provide a regional metapopulation analysis to inform conservation management for Masai giraffes (Giraffa camelopardalis tippelskirchi) in five subpopulations defined by land management designations. We used data from an individual-based mark–recapture study to estimate subpopulation sizes, subpopulation growth rates, and movement probabilities among subpopulations. We assessed the source–sink structure of the study population by calculating source–sink statistics, and we created a female-based matrix metapopulation model composed of all subpopulations to examine how variation in demographic components of survival, reproduction, and movement affected metapopulation growth rate. Movement data indicated no subpopulation was completely isolated, but movement probabilities varied among subpopulations. Source–sink statistics and net flow of individuals indicated three subpopulations were sources, while two subpopulations were sinks. We found areas with higher wildlife protection efforts and fewer anthropogenic impacts were sources, and less-protected areas were identified as sinks. Our results highlight the importance of identifying source–sink dynamics among subpopulations for effective conservation planning and emphasize how protected areas can play an important role in sustaining metapopulations.