Estimating the population size of the Sanje mangabey (Cercocebus sanjei) using acoustic distance sampling

The Sanje mangabey (Cercocebus sanjei) is endemic to the Udzungwa Mountains, Tanzania, and is classified as Endangered due to its putatively declining population size, habitat degradation and fragmentation. Previous population size estimates have ranged from 1,350 to 3,500 individuals, with the last direct survey being conducted 15 years before the present study. Previous estimates are now thought to have underestimated the population due to a limited knowledge of group and habitat size, nonsystematic approaches and the use of visual methods that are not suitable for surveying the Sanje mangabey with its semi-terrestrial and elusive behaviors. We used an acoustic survey method with observers recording the distinctive “whoop-gobble” vocalization produced by mangabeys and point transect distance sampling to model a detection function and estimate abundance. Twenty-eight surveys were conducted throughout the two forests where Sanje mangabeys are found: Mwanihana forest in the Udzungwa Mountains National Park (n = 13), and the Uzungwa Scarp Nature Reserve (n = 15). Group density was found to be significantly lower in the relatively unprotected Uzungwa Scarp forest (0.15 groups/km²; 95% CI: 0.08–0.27) compared to the well-protected Mwanihana forest (0.29 groups/km²; 95% CI: 0.19–0.43; p = .03). We estimate that there are 1,712 (95% CI: 1,141–2,567) individuals in Mwanihana and 1,455 (95% CI: 783–2,702) in the Uzungwa Scarp, resulting in a total population size of 3,167 (95% CI: 2,181–4,596) individuals. The difference in group density between sites is likely a result of the differing protection status and levels of enforcement between the forests, suggesting that protection of the Uzungwa Scarp should be increased to encourage recovery of the population, and reduce the threat of degradation and hunting. Our results contribute to the reassessment of the species' IUCN Red List status and informing management and conservation action planning.     

Estimating density of ant nests using distance sampling

The quantification of ant nest densities is a useful but challenging task given the group’s high abundance and diversity of nesting sites. We present a new application of a distance-sampling method which follows standard distance analytical procedures, but introduces a sampling innovation that is particularly useful for ants; instead of having an observer look for ants we let ants find a bait station and measure the distances covered between nest and station. We test this method by estimating the density of epigaeic ant nests in an Amazon tropical forest site near Manaus, Brazil. We distributed 220 baits of canned sardine mixed with cassava flour among 10, 210-m long transects in old-growth upland forest. Forty-five minutes after baiting, we followed the ants’ trails and measured the linear distance between the bait and each nest’s entrance. We then used the freely available program DISTANCE to estimate the number of nests per unit area while accounting for the effect of distance on the probability that a colony will find a bait. There were found 38 species nesting in 287 different colonies, with an estimated 2.66 nests/m². This estimate fell within the 95 % confidence bounds of nest density predicted for a similar number of species based on a literature survey of ant species richness and nest density. Our sampling solution, however, takes less than 30 % of the time used by conventional sampling approaches for a similar area, with the advantage that it produces not only a point estimate but also a quantification of uncertainty about density.     

Estimating the global distribution of field size using crowdsourcing

There is an increasing evidence that smallholder farms contribute substantially to food production globally, yet spatially explicit data on agricultural field sizes are currently lacking. Automated field size delineation using remote sensing or the estimation of average farm size at subnational level using census data are two approaches that have been used. However, both have limitations, for example, automatic field size delineation using remote sensing has not yet been implemented at a global scale while the spatial resolution is very coarse when using census data. This paper demonstrates a unique approach to quantifying and mapping agricultural field size globally using crowdsourcing. A campaign was run in June 2017, where participants were asked to visually interpret very high resolution satellite imagery from Google Maps and Bing using the Geo‐Wiki application. During the campaign, participants collected field size data for 130 K unique locations around the globe. Using this sample, we have produced the most accurate global field size map to date and estimated the percentage of different field sizes, ranging from very small to very large, in agricultural areas at global, continental, and national levels. The results show that smallholder farms occupy up to 40% of agricultural areas globally, which means that, potentially, there are many more smallholder farms in comparison with the two different current global estimates of 12% and 24%. The global field size map and the crowdsourced data set are openly available and can be used for integrated assessment modeling, comparative studies of agricultural dynamics across different contexts, for training and validation of remote sensing field size delineation, and potential contributions to the Sustainable Development Goal of Ending hunger, achieve food security and improved nutrition and promote sustainable agriculture.     

Multi-list methods using incomplete lists in closed populations

Multi-list methods have become a common application of capture-recapture methodology to estimate the size of human populations, and have been successfully applied to estimating prevalence of diabetes, human immunodeficiency virus (HIV), and drug abuse. A key assumption in multi-list methods is that individuals have a unique "tag" that allows them to be matched across all lists. This article develops multi-list methodology that relaxes the assumption of a single tag common to all lists. Estimates are found using estimating functions. An example illustrates its application for estimating the prevalence of diabetes, and a simulation study investigates conditions under which the methodology is robust to different list and population sizes.     

Estimating hybridization in the presence of coalescence using phylogenetic intraspecific sampling

Background

Recent research has indicated a positive association between rates of molecular evolution and diversification in a number of taxa. However debate continues concerning the universality and cause of this relationship. Here, we present the first systematic investigation of this relationship within the mammals. We use phylogenetically independent sister-pair comparisons to test for a relationship between substitution rates and clade size at a number of taxonomic levels. Total, non-synonymous and synonymous substitution rates were estimated from mitochondrial and nuclear DNA sequences.

Results

We found no evidence for an association between clade size and substitution rates in mammals, for either the nuclear or the mitochondrial sequences. We found significant associations between body size and substitution rates, as previously reported.

Conclusions

Our results present a contrast to previous research, which has reported significant positive associations between substitution rates and diversification for birds, angiosperms and reptiles. There are three possible reasons for the differences between the observed results in mammals versus other clades. First, there may be no link between substitution rates and diversification in mammals. Second, this link may exist, but may be much weaker in mammals than in other clades. Third, the link between substitution rates and diversification may exist in mammals, but may be confounded by other variables.     

Estimating the size at maturity in field populations of Daphnia (Cladocera)

• 1 Two methods for estimating the average body size at the onset of reproduction were applied to populations of Daphnia hyalina. The first, ‘average maturation size’, assesses maturity by the relative length of abdominal processes of Daphnia; the second, ‘size at first reproduction’ (SFR), calculates the size class in which 50% of the maximum proportion of egg-bearing females is reached.
• 2 The influence of environmental factors on the expression of the difference in length between the first and the second abdominal process was tested in the laboratory. Neither temperature nor chemical cues from predators affected the difference in length, but the processes were indistinguishable at very low food concentrations.
• 3 During one season, D. hyalina exhibited pronounced changes in fecundity, proportion of egg-bearing adults and SFR. The pattern obtained by the two methods was similar in many cases, although maturation size estimated by the first method was slightly smaller than SFR obtained by the second method. Neither method gave reliable results during times of starvation (clear-water phase).

     

Estimating asymptotic size using the largest individuals per sample

Summary Estimates of asymptotic size are especially useful for comparative studies of taxonomic groups in which animals mature at small sizes relative to their final asymptotic sizes. The largest individuals per sample can provide reasonable estimates of asymptotic size if three conditions are met: 1) at least some adults in a population are near their final asymptotic size, 2) samples of a reasonable size are likely to contain a largest individual that is near the average asymptotic size for the members of its sex, and 3) the coefficient of variation in asymptotic size is small for the members of each sex. In the current study, we show that all three of these conditions are met for one species of Anolis lizards (A. limifrons). For a series of samples from the genus Anolis, the largest individual per sample produces estimates of asymptotic size that are virtually identical to those produced by fitting field data on growth rates to nonlinear growth equations. These results suggest that the largest individual method can provide reasonable estimates of asymptotic size for the members of this genus, and imply that this method may also be useful for estimating asymptotic sizes in other taxa that satisfy the criteria listed above.     

Robust estimation of population size in closed animal populations from capture-recapture experiments

In this paper the problem of finding robust estimators of population size in closed K-sample capture-recapture experiments is considered. Particular attention is paid to models where heterogeneity of capture probabilities is allowed. First, a general estimation procedure is given which does not depend on any assumptions about the form of the distribution of capture probabilities. This is followed by a detailed discussion of the usefulness of the generalized jackknife technique to reduce bias. Numerical comparisons of the bias and variance of various estimators are given. Finally, a general discussion is given with several recommendations on estimators to be used in practice.     

Estimating the size of the HIV epidemic by using mortality data

Evidence that more people are dying as a result of HIV infection than is reflected by the number of deaths among reported cases meeting the WHO definition of AIDS is derived from mortality data. Ninety-five causes of death likely to be associated with HIV infection were selected. Standardized mortality ratios due to these causes increased for single men aged 15-54 years from 100 in 1984 to 118 in 1987. The age, sex, marital status, temporal and geographic distribution of these excess deaths suggest that they are HIV-associated. It is estimated that 58% of excess deaths due to HIV-related causes were among cases reported to the CDSC AIDS Surveillance Programme in 1987. Some of these deaths may have been among HIV-positive people who did not meet the WHO definition at the time of death. There is a need for surveillance to be extended to include HIV-positive people who die before meeting the WHO definition if the full extent of the HIV epidemic is to be identified.     

Estimating sampling bias when using electrofishing to catch stone loach

Point abundance sampling, using electrofishing, for stone loach Barbatula barbatula in two habitats, riffle and pool, showed that there was no difference in density between the two habitats. The density of fish increased significantly (1·8 fold; P  < 0·001) when the substratum of small cobbles (128–256 mm) was removed and electrofishing repeated.     

Estimating major gene effects with partial information using Gibbs sampling

A method for estimating major gene effects using Gibbs sampling to infer genotype of individuals with unknown values, was compared with a standard mixed-model analysis. The purpose of this study was to evaluate the effect of including information of individuals with unknown genotypes on the estimates and their error variances (Ve) of the single-gene effects. When genotypes were known for all the individuals, results using the Gibbs method (GS) were similar to those obtained with the mixed model (MM). In the absence of selection, when information from individuals with unknown genotypes was included, GS yielded unbiased estimates of the major gene effects while reducing the Ve associated with them. This reduction in Ve depended on the gene frequency and mode of action of the major locus. For the additive effect, the reduction in Ve ranged from 29 to 69% of the total reduction which would have been obtained if all individuals had had a known genotype. Similarly the reduction in Ve found for the dominance effect ranged from 12 to 58%. Estimates using GS generally had small detectable biases when the polygenic heritability used in the analysis was inflated or estimated simultaneously. However, the benefit of using information from individuals with unknown genotypes was still maintained when comparing the mean square error of the estimates using either GS or MM when genotypes are only known for a subset of the population. When the population has been under selection, the use of Gibbs sampling to incorporate information of individuals without genotypes reduced substantially the bias and mean square error found for MM analysis on partial data. Nevertheless, there was some bias detected using Gibbs sampling. The gene frequency of the major gene in the base population was also well estimated despite its change over generations due to selection.     

Estimating the prevalence of infections in vector populations using pools of samples

Several statistical methods have been proposed for estimating the infection prevalence based on pooled samples, but these methods generally presume the application of perfect diagnostic tests, which in practice do not exist. To optimize prevalence estimation based on pooled samples, currently available and new statistical models were described and compared. Three groups were tested: (a) Frequentist models, (b) Monte Carlo Markov‐Chain (MCMC) Bayesian models, and (c) Exact Bayesian Computation (EBC) models. Simulated data allowed the comparison of the models, including testing the performance under complex situations such as imperfect tests with a sensitivity varying according to the pool weight. In addition, all models were applied to data derived from the literature, to demonstrate the influence of the model on real‐prevalence estimates. All models were implemented in the freely available R and OpenBUGS software and are presented in Appendix S1. Bayesian models can flexibly take into account the imperfect sensitivity and specificity of the diagnostic test (as well as the influence of pool‐related or external variables) and are therefore the method of choice for calculating population prevalence based on pooled samples. However, when using such complex models, very precise information on test characteristics is needed, which may in general not be available.     

Estimating biomass of submersed vegetation using a simple rake sampling technique

We evaluated the use of a simple rake sampling technique for predicting the biomass of submersed aquatic vegetation. Vegetation sampled from impounded areas of the Mississippi River using a rake sampling technique, was compared with vegetation harvested from 0.33-m² quadrats. The resulting data were used to model the relationship between rake indices and vegetation biomass (total and for individual species). We constructed linear regression models using log-transformed biomass data for sites sampled in 1999 and 2000. Data collected in 2001 were used to validate the resulting models. The coefficient of determination (R ²) for predicting total biomass was 0.82 and ranged from 0.59 (Potamogeton pectinatus) to 0.89 (Ceratophyllum demersum) for individual species. Application of the model to estimate total submersed aquatic vegetation is illustrated using data collected independent of this study. The accuracy and precision of the models tested indicate that the rake method data may be used to predict total vegetation biomass and biomass of selected species; however, the method should be tested in other regions, in other plant communities, and on other species. Handling editor: S. M. Thomaz     

Estimating the parameters of the incompletely penetrant single locus model using multiple populations

A method involving the comparison of two or more populations is suggested as a means of obtaining a unique solution to the parameters of the incompletely penetrant single locus model. The proposed method allows a test of the assumptions of the model when three or more populations are compared. Equations that allow the inclusion of data on twin concordance rates and/or the proportion of affected children given neither, one or both parents affected are also given. Finally, some implications of fitting the model are discussed in terms of genetic counseling, residual environmental variance and the concept of heritability as applied to dichotomous traits.     

Investigating the accessibility of the closed domain conformation of citrate synthase using essential dynamics sampling

A molecular dynamics study of pig heart citrate synthase is presented that aims to directly address the question of whether, for this enzyme, the ligand-induced closed domain conformation is accessible to the open unliganded enzyme. The approach utilises the technique of essential dynamics sampling, which is used in two modes. In exploring mode, the enzyme is encouraged to explore domain conformations it might not normally sample in free molecular dynamics simulation. In targeting mode, the enzyme is encouraged to adopt the domain conformation of a target structure. Using both modes extensively, it has been found that when the enzyme is prepared from a crystallographic open-domain structure and is in the unliganded state, it is unable to adopt the crystallographic closed-domain conformation of the liganded enzyme. Likewise, when the enzyme is prepared from the crystallographic closed liganded conformation with the ligands removed, it is unable to adopt the crystallographic open domain conformation. Structural investigations point to a common structural difference that is the source of this energy barrier; namely, the shift of alpha-helix 328-341 along its own axis relative to the large domain. Without this shift, the domains are unable to close or open fully. The charged substrate, oxaloacetate, binds near the base of this helix in the large domain and the interaction of Arg329 at the base of the helix with oxaloacetate is one that is consistent with the shift of this helix in going from the crystallographic open to closed structure. Therefore, the results suggest that without the substrate the enzyme remains in a partially open conformation ready to receive the substrate. In this way, the efficiency of the enzyme should be increased over one that is closed part of the time, with its binding site inaccessible to the substrate.