Comparison of Methods for Estimating Bird Abundance and Trends From Historical Count Data

Abstract: The use of bird counts as indices has come under increasing scrutiny because assumptions concerning detection probabilities may not be met, but there also seems to be some resistance to use of model-based approaches to estimating abundance. We used data from the United States Forest Service, Southern Region bird monitoring program to compare several common approaches for estimating annual abundance or indices and population trends from point-count data. We compared indices of abundance estimated as annual means of counts and from a mixed-Poisson model to abundance estimates from a count-removal model with 3 time intervals and a distance model with 3 distance bands. We compared trend estimates calculated from an autoregressive, exponential model fit to annual abundance estimates from the above methods and also by estimating trend directly by treating year as a continuous covariate in the mixed-Poisson model. We produced estimates for 6 forest songbirds based on an average of 621 and 459 points in 2 physiographic areas from 1997 to 2004. There was strong evidence that detection probabilities varied among species and years. Nevertheless, there was good overall agreement across trend estimates from the 5 methods for 9 of 12 comparisons. In 3 of 12 comparisons, however, patterns in detection probabilities potentially confounded interpretation of uncorrected counts. Estimates of detection probabilities differed greatly between removal and distance models, likely because the methods estimated different components of detection probability and the data collection was not optimally designed for either method. Given that detection probabilities often vary among species, years, and observers investigators should address detection probability in their surveys, whether it be by estimation of probability of detection and abundance, estimation of effects of key covariates when modeling count as an index of abundance, or through design-based methods to standardize these effects.     

Geographic patterns of diversification: an example with ectoparasitic insects

On any spatial scale, the species composition of a taxonomic group often departs from a phylogenetically random subset drawn from the pool of species available on a higher scale. Analysis of the uneven representation of related lineages in different assemblages can reveal the action of various forces shaping their diversification. For any assemblage, unequal diversification among lineages can be estimated using diversity skewness, an index of the balance of a phylogenetic tree whose values increase with increasing differences in diversification rates among tree branches. We tested for geographical patterns in the diversity skewness of flea assemblages parasitic on small mammals in 26 distinct geographic localities from the Palaearctic and 15 from the Nearctic. Overall, diversity skewness of the Nearctic flea assemblage was unexpectedly high compared to that of the global flea fauna, whereas that of the Palaearctic did not depart from the expectations of a null model. On a smaller scale, the diversity skewness of local flea assemblages was sometimes lower, sometimes higher, but, in most of the 41 localities, it did not differ significantly from that of random subsets taken from the species pool available on the larger spatial scale (either the world fauna or that of the biogeographical realm, i.e. Palaearctic or Nearctic). More importantly, among Palaearctic assemblages, diversity skewness increased with increasing latitude and/or decreasing mean air temperatures. The different patterns observed in the Palaearctic and Nearctic may be in part due the fact that flea diversification appears to have been more intense in the former than the latter, and to differences between them in relief and glacial history. Temperature‐driven speciation rates may well explain the latitudinal gradient in diversity skewness in the Palaearctic. The results illustrate the action of various biogeographical processes in shaping the uneven differentiation of flea lineages on different spatial scales. © 2008 The Linnean Society of London, Biological Journal of the Linnean Society, 2008, 95 , 807–814.     

Control of emerging infectious diseases using responsive imperfect vaccination and isolation

This paper is concerned with a stochastic model for the spread of an SEIR (susceptible --> exposed (= latent) --> infective --> removed) epidemic among a population partitioned into households, featuring different rates of infection for within and between households. The model incorporates responsive vaccination and isolation policies, based upon the appearance of diagnosed cases in households. Different models for imperfect vaccine response are considered. A threshold parameter R*, which determines whether or not a major epidemic can occur, and the probability of a major epidemic are obtained for different infectious and latent period distributions. Simpler expressions for these quantities are obtained in the limiting case of infinite within-household infection rate. Numerical studies suggest that the choice of infectious period distribution and whether or not latent individuals are vaccine-sensitive have a material influence on the spread of the epidemic, while, for given vaccine efficacy, the choice of vaccine action model is less influential. They also suggest that an effective isolation policy has a more significant impact than vaccination. The results show that R* alone is not sufficient to summarise the potential for an epidemic.     

On global and local critical points of extended contact process on homogeneous trees

We study spatial stochastic epidemic models called households models. The households models have more than two states at each vertex of a graph in contrast to the contact process. We show that, in the households models on trees, two thresholds of infection rates characterize epidemics. The global critical infection rate is defined by epidemic occurrence. However, some households may be eventually disease-free even for infection rates above the global critical infection rate, in as far as they are smaller than the local critical point. Whether the global one is smaller than the local one depends on the graph and the model. We show that, in the households models, the global one is smaller than the local one on homogeneous trees.     

The Ross-Macdonald model in a patchy environment

We generalize to n patches the Ross-Macdonald model which describes the dynamics of malaria. We incorporate in our model the fact that some patches can be vector free. We assume that the hosts can migrate between patches, but not the vectors. The susceptible and infectious individuals have the same dispersal rate. We compute the basic reproduction ratio R(0). We prove that if R(0)1, then the disease-free equilibrium is globally asymptotically stable. When R(0)>1, we prove that there exists a unique endemic equilibrium, which is globally asymptotically stable on the biological domain minus the disease-free equilibrium.     

Seedling interactions in a tropical forest in Panama

Competition is believed to be a central force limiting local diversity and controlling the structure of plant communities. However, it has been proposed that the stressed understory environment limits total understory plant density to such low levels that competitive exclusion cannot be an important factor limiting the local diversity of understory plants. To evaluate the importance of inter-seedling competition, we performed a seedling competition experiment with five shade-tolerant species in a tropical moist forest in Panama. Three-month-old seedlings were transplanted into the forest singly or with their roots intertwined with a single conspecific or heterospecific seedling in all pairwise species combinations. If competition is important, performance (survival, stem height, and number of leaves after one and six years) would be expected to be lowest with a conspecific neighbor and greatest without a neighbor. The experiment was replicated in five 0.24-m² plots at each of 20 sites in tall secondary forest. To test whether seedling performance differed among treatments we fitted linear mixed models (LMM) and generalized linear mixed models (GLMM), treating species identity and microsite (site and plot) as random effects. The five shade-tolerant study species all experienced good establishment with relatively high survival and growth rates. The neighbor treatment consistently affected seedling performance, but the effect was always very small, both in absolute terms and relative to the much stronger species and microsite effects. Seedlings with a conspecific neighbor consistently performed worse than seedlings with a heterospecific neighbor, but having no neighbor generally did not cause superior performance relative to the other treatments. We conclude that direct competitive interactions are relatively unimportant among understory plants in humid tropical forests.     

Geographic variation in Thomas langur (Presbytis thomasi) loud calls

Geographic variation in primate vocalizations has been described at two levels. First, at the level of acoustic variation within the same call type between populations and, second, at the level of presence or absence of certain call types in different populations. Acoustic variation is of interest because there are several factors that can explain this variation, such as gene flow, ecological factors and population density. Here we focus on the first level in a Southeast Asian primate, the Thomas langur. We recorded male loud calls in four populations that differed in their geographic distances from each other and had varying geographic barriers in between them, such as rivers and mountain ranges. The presence of these barriers leads to expectations of loud call variation under the gene flow model, which are examined here. We conducted a principal components analysis to condense the number of acoustic variables. With a subsequent discriminant function analysis on the six principal component scores, we found that the percentage of loud calls that were correctly assigned to a population was relatively high (50.0-76.2%) when three randomly selected loud calls from each male were used. Using the discriminant functions from this analysis to predict population membership of the remainder of the loud calls yielded lower, but still relatively high correct assignment percentages (26.2-66.7%). Analyses to examine the influence of barriers on similarities between populations confirm our expectations. We discuss that differences in loud calls are probably most parsimoniously explained by gene flow (or the lack thereof) between the populations and that future studies of genetic differences are crucial to test this hypothesis.     

Selection of line-transect methods for estimating the density of group-living animals: lessons from the primates

We review the four major contemporary methods for estimating density of group-living animals from line-transect sampling: perpendicular modelling of group centers, perpendicular modelling of center of measurable individuals, strip transects and animal-observer distance. The efficacy of each method is evaluated to produce a simple selection guide. We review the literature and use field data from the Udzungwa Mountains, Tanzania. The review is relevant to all group-living animals; however, examples are drawn from the primates. Perpendicular methods have better mathematical justification than non-perpendicular methods. For perpendicular methods using detection function models, it is preferable to measure group location using center of measurable individuals, as group centers are hard to estimate. The assumptions of detection function models are often broken in poor visibility habitats or with unhabituated animals. Alternatively strip transects may be used where there are reliable data on group spread and/or visibility. Strip transects are also the most practical, along with the animal-observer method; however, the latter lacks mathematical justification. We conclude that there are arguments for continued use of all four methods. In certain situations the use of raw encounter rates may also be considered. The appropriate method is determined by minimizing bias and considering time, resources and field conditions.     

Risk assessment by crow phenotypes in a hybrid zone

Predation is one of the most selective forces in evolution and, thus, predation may select against hybrids in narrow hybrid zones. It may be possible that parental phenotypes and hybrids differ in their responses towards predators or humans. As predation is difficult to observe I used flight-initiation distance (FID) as a metric of risk assessment. FID is a measurable outcome of the trade-off between fleeing and remaining. Here, I tested whether hybrid and parent crow phenotypes (Corvus corone, Corvus cornix) from the hybrid zone in Eastern Germany differ in their FID. Further, I measured many environmental and social variables to control statistically for their influence on FID. I sampled 154 individuals (53 hooded crows, 54 carrion crows, and 48 hybrids) in the hybrid zone in eastern Germany. I calculated a general linear model using a stepwise backward procedure to establish a minimum model containing only significant variables that explained FID in crows. The variable phenotype (hooded, carrion, hybrid) was then added to the model. There were no differences in FID between hybrids and both parental phenotypes types, suggesting similar risk assessment. This suggests that hybrids may behave similarly in their decision to flee as their parent phenotypes, which, in turn, provides no evidence for a selective disadvantage. An additional analysis focusing on pure phenotypic flocks showed that hybrids in pure hybrid flocks had a lower FID than both parental species in pure flocks. This suggests that hybrids in pure hybrid flocks may be at a disadvantage.