Accounting for Lack of Independence and Partial Overlap of Observation Zones in Line-Transect Mark-Recapture Distance Sampling

Line-transect mark-recapture distance sampling methods can be used to estimate abundance when at least two observers sight and record distances to detected groups of individuals within the survey area. However, a lack of independence between the observer’s detections will cause biased abundance estimates. Studies are also typically designed such that there is complete overlap of the regions searched by the two observers, but that may not always be possible. Here we detail an intuitive approach for line-transect distance sampling applications based upon logistic regression to account for a potential lack of independence by using the detections of one observer as a covariate in the detection function of the second observer. Partial overlap of the observer survey regions can be addressed by constraining detection probability to equal 0 for the respective observer outside of the overlap zone. We show via simulation that the method provides reliable estimates of abundance and is not affected by random unmodeled heterogeneity in detection probability. The method is illustrated by estimating abundance within the covered region of an aerial line-transect survey for New Zealand’s endemic Hector’s dolphin (Cephalorhynchus hectori hectori) conducted in the austral summer of 2013, the motivating application for this work. Supplementary materials accompanying this paper appear on-line.     

Model-Based Distance Sampling

Conventional distance sampling adopts a mixed approach, using model-based methods for the detection process, and design-based methods to estimate animal abundance in the study region, given estimated probabilities of detection. In recent years, there has been increasing interest in fully model-based methods. Model-based methods are less robust for estimating animal abundance than conventional methods, but offer several advantages: they allow the analyst to explore how animal density varies by habitat or topography; abundance can be estimated for any sub-region of interest; they provide tools for analysing data from designed distance sampling experiments, to assess treatment effects. We develop a common framework for model-based distance sampling, and show how the various model-based methods that have been proposed fit within this framework.     

Analyzing designed experiments in distance sampling

Distance sampling is a survey technique for estimating the abundance or density of wild animal populations. Detection probabilities of animals inherently differ by species, age class, habitats, or sex. By incorporating the change in an observer’s ability to detect a particular class of animals as a function of distance, distance sampling leads to density estimates that are comparable across different species, ages, habitats, sexes, and so on. Increasing interest in evaluating the effects of management practices on animal populations in an experimental context has led to a need for suitable methods of analyzing distance sampling data. We outline a two-stage approach for analyzing distance sampling data from designed experiments, in which a two-step bootstrap is used to quantify precision and identify treatment effects. We illustrate this approach using data from a before—after control-impact experiment designed to assess the effects of large-scale prescribed fire treatments on bird densities in ponderosa pine forests of the southwestern United States.     

Cost-effective abundance estimation of rare animals: Testing performance of small-boat surveys for killer whales in British Columbia

Top predators are often rare, subject to anthropogenic mortality, and possess life-history traits that make them inherently vulnerable to extinction. IUCN criteria recognise populations as Critically Endangered when abundance is <250 mature individuals, but estimating abundance of rare species can be more challenging than for common ones. Cost-effective methods are needed to provide robust abundance estimates. In marine environments, small boats are more widely accessible than large ships for researchers conducting sightings surveys with limited funds, but studies are needed into efficacy of small-boat surveys. This study compares line transect and mark-recapture estimates from small-boat surveys in summer 2004 and 2005 for ‘northern resident’ killer whales in British Columbia to true population size, known from censuses conducted by Fisheries and Oceans Canada. The line transect estimate of 195 animals (95% CI 27-559) used model averaging to incorporate uncertainty in the detection function, while the mark-recapture estimate of 239 animals (CI 154-370) used a simple two-sample Chapman estimator. Both methods produced estimates close to the true population size, which numbered 219 animals in 2004 and 235 in 2006, but both suffered from the small sample sizes and violations of some model assumptions that will vex most pilot studies of rare species. Initial abundance estimates from relatively low-cost surveys can be thought of as hypotheses to be tested as new data are collected. For species of conservation concern, any cost-effective attempt to estimate absolute abundance will assist status assessments, as long as estimates are presented with appropriate caveats.     

Closed mark-recapture models to estimate species richness: An example using data on epigeal spiders

Species richness is a fundamental ecological property. The problem of estimating the number of species is quite similar to that of estimating the population size of a single species. Some authors of mark-recapture statistics have proposed using some of these methods to estimate species richness. This necessitates understanding how the recording probabilities of individuals differ from those of species. In particular, the species of a species pool are likely to exhibit a wide range of recording probabilities. Depending on sampling conditions, temporal or spatial variation in species detection probability may also occur, making model M _th estimators particularly useful. Empirical detection probabilities and estimates of species numbers using three coverage, one point, and two jackknife estimators are presented for series of spatial and temporal trapping occasions of epigeal spiders.     

Genetic structure among earthworms (Lumbricus terrestris L.) from different sampling sites in western Germany based on random amplified polymorphic DNA

Earthworms are being used as bio-indicators to assess terrestrial pollution. However, it is often not known whether their populations possess a uniform genetic structure, which would allow comparison of residues or biological properties of earthworms from different sampling locations. In order to investigate this point, random amplified polymorphic DNA (RAPD) variation was surveyed in earthworms (Lumbricus terrestris) from five different sampling sites in Germany. Forty oligonucleotide RAPD primers (10 base pairs in length) were screened, three of which produced high polymorphic band patterns. A total of 61 DNA fragments were detected in 90 individuals of L. terrestris from five sampling sites with 49 (80.3%) RAPD markers being polymorphic. The genetic similarities within (band sharing rates between 0.756 and 0.795) and among the L. terrestris populations (0.635) were similar even at widely separate locations. Inter-population variation in the RAPD pattern for all five earthworm populations accounted for 37.9% of the total variation, while intra-population variation for three adjacent Saarland populations accounted for only 18.0% of the total variation. Principal component analysis (PCA) and the genetic distances of the populations confirm these results. Twenty-four percent of the genetic distance is caused by geographical isolation as shown by a test for isolation by distance. These results show that L. terrestris fulfils the genetic qualifications for a bio-indicator particularly at closely located sampling sites. However, the results also suggest that earthworm studies of widely separated locations should include genetic characterisation of the earthworm samples.     

Mapping Extent and Change in Surface Mines Within the United States for 2001 to 2006

A complete, spatially explicit dataset illustrating the 21st century mining footprint for the conterminous United States does not exist. To address this need, we developed a semi‐automated procedure to map the country's mining footprint (30‐m pixel) and establish a baseline to monitor changes in mine extent over time. The process uses mine seed points derived from the U.S. Energy Information Administration (EIA), U.S. Geological Survey (USGS) Mineral Resources Data System (MRDS), and USGS National Land Cover Dataset (NLCD) and recodes patches of barren land that meet a “distance to seed” requirement and a patch area requirement before mapping a pixel as mining. Seed points derived from EIA coal points, an edited MRDS point file, and 1992 NLCD mine points were used in three separate efforts using different distance and patch area parameters for each. The three products were then merged to create a 2001 map of moderate‐to‐large mines in the United States, which was subsequently manually edited to reduce omission and commission errors. This process was replicated using NLCD 2006 barren pixels as a base layer to create a 2006 mine map and a 2001–2006 mine change map focusing on areas with surface mine expansion. In 2001, 8,324 km² of surface mines were mapped. The footprint increased to 9,181 km² in 2006, representing a 10·3% increase over 5 years. These methods exhibit merit as a timely approach to generate wall‐to‐wall, spatially explicit maps representing the recent extent of a wide range of surface mining activities across the country. Copyright © 2015 John Wiley & Sons, Ltd.     

Mark-recapture with occasion and individual effects: Abundance estimation through Bayesian model selection in a fixed dimensional parameter space

We present a Bayesian mark-recapture method for explicitly communicating uncertainty about the size of a closed population where capture probabilities vary across both individuals and sampling occasions. Heterogeneity is modeled hierarchically using a continuous logistic-Normal model to specify the capture probabilities for both individuals that are captured on at least one occasion and individuals that are never captured and so remain undetected. Inference about how many undetected individuals to include in the model is accomplished through a Bayesian model selection procedure using MCMC, applied to a product space of possible models for different numbers of undetected individuals. Setting the estimation problem in a fixed dimensional parameter space enables the model selection procedure to be performed using the freely available WinBUGS software. The outcome of inference is a full “posterior” probability distribution for the population size parameter. We demonstrate this method through an example involving real mark-recapture data.     

Predicting Life-History Traits for Female New Zealand Sea Lions, <Emphasis Type="Italic">Phocarctos hookeri</Emphasis>: Integrating Short-Term Mark-Recapture Data and Population Modeling

The trade-off between survival and reproduction by individuals is central to understanding life-history parameters of a species. Few mammal species have life-history information from long-term research. Instead, demographic models are commonly utilized to investigate an individual’s life-history strategy, species dynamics, and population trends. This research investigates age-related survival and reproductive performance of adult female New Zealand (NZ) sea lions (Phocarctos hookeri), using multi-state mark-recapture data from known-age branded individuals over five years. The mark-recapture analysis was integrated with a population model to predict the lifetime reproductive output of female NZ sea lions. The integration of an analysis of short-term datasets with population modeling allows for the prediction of life-history parameters of long lived animals when long-term information is not available. While such approaches involve some caveats, it provides a framework for investigating population dynamics and is preferential to unsubstantiated assumptions. This technique can lead to better design and implementation of conservation management for long lived species.     

Post-fire succession affects abundance and survival but not detectability in a knob-tailed gecko

Altered fire regimes threaten the persistence of many animal species globally, thus understanding how fire affects demographic processes is critical for conservation. Using 2 years of mark-recapture data from the Australian gecko Nephrurus stellatus, we investigated the effect of fire on (i) detectability to reliably measure post-fire changes in abundance, and (ii) survival and reproductive rates to investigate the mechanisms of successional change. Data were collected from two conservation reserves each with three different fire categories based on time since the last fire. “Early”, “medium” and “late” sites had 2–3, 7–9 and 42–48 years since fire, respectively. A robust design modelling framework was used to estimate the effect of fire category on abundance, survival and capture probability while also examining the influence of temperature and behaviour on detectability. Geckos showed trap-shy behaviour and detectability increased significantly with increasing temperature but was not affected by time since fire. Accounting for detectability, geckos were more abundant in the medium than the early sites, and were rare in the late sites. Although trends in survival are more difficult to address with short-term data, our results showed lower monthly survival rates, but higher fecundity in the early than the medium sites. These results were possibly related to successional changes in predation, the thermal environment, and food availability. We demonstrated how mark-recapture analysis can show the causes of animal fire responses while realistically accounting for detectability. Such information is necessary to provide a predictive framework to guide fire management for biodiversity.     

A robust design mark-resight abundance estimator allowing heterogeneity in resighting probabilities

This article introduces the beta-binomial estimator (BBE), a closed-population abundance mark-resight model combining the favorable qualities of maximum likelihood theory and the allowance of individual heterogeneity in sighting probability (p). The model may be parameterized for a robust sampling design consisting of multiple primary sampling occasions where closure need not be met between primary occasions. We applied the model to brown bear data from three study areas in Alaska and compared its performance to the joint hypergeometric estimator (JHE) and Bowden’s estimator (BOWE). BBE estimates suggest heterogeneity levels were non-negligible and discourage the use of JHE for these data. Compared to JHE and BOWE, confidence intervals were considerably shorter for the AIC_c model-averaged BBE. To evaluate the properties of BBE relative to JHE and BOWE when sample sizes are small, simulations were performed with data from three primary occasions generated under both individual heterogeneity and temporal variation in p. All models remained consistent regardless of levels of variation in p. In terms of precision, the AIC_c model-averaged BBE showed advantages over JHE and BOWE when heterogeneity was present and mean sighting probabilities were similar between primary occasions. Based on the conditions examined, BBE is a reliable alternative to JHE or BOWE and provides a framework for further advances in mark-resight abundance estimation.     

Improving Estimates of Abundance by Aggregating Sparse Capture-Recapture Data

Inferences about abundance often are based on unadjusted counts of individuals observed, in part, because of the large amount of data required to generate reliable estimates of abundance. Where capture-recapture data are sparse, aggregating data across multiple sample elements by pooling species, locations, and sampling periods increases the information available for modeling detection probability, a necessary step for estimating abundance reliably. The process of aggregating sample elements involves balancing trade-offs related to the number of aggregated elements; although larger aggregates increase the amount of information available for estimation, they often require more complex models. We describe a heuristic approach for aggregating data for studies with multiple sample elements, use simulated data to evaluate the efficacy of aggregation, and illustrate the approach using data from a field study. Aggregating data systematically improved reliability of model selection and increased accuracy of abundance estimates while still providing estimates of abundance for each original sample unit, an important benefit necessary to maintain the design and sampling structure of a study. Within the framework of capture-recapture sampling, aggregating data improves estimates of abundance and increases the reliability of subsequent inferences made from sparse data. Additional tables and datasets may be found in the online supplements.     

Estimating Disease Prevalence Using Inverse Binomial Pooled Testing

Monitoring populations of hosts as well as insect vectors is an important part of agricultural and public health risk assessment. In applications where pathogen prevalence is likely low, it is common to test pools of subjects for the presence of infection, rather than to test subjects individually. This technique is known as pooled (group) testing. In this paper, we revisit the problem of estimating the population prevalence p from pooled testing, but we consider applications where inverse binomial sampling is used. Our work is unlike previous research in pooled testing, which has largely assumed a binomial model. Inverse sampling is natural to implement when there is a need to report estimates early on in the data collection process and has been used in individual testing applications when disease incidence is low. We consider point and interval estimation procedures for p in this new pooled testing setting, and we use example data sets from the literature to describe and to illustrate our methods.     

Rapid monitoring of species abundance for biodiversity conservation: Consistency and reliability of the MacKinnon lists technique

Effective monitoring of biodiversity for conservation requires information on spatial and temporal variation in species’ abundances. As conservation resources are limited, monitoring methods are required that enable rapid and cost effective data collection. There are many traditional methods of estimating absolute abundance, such as territory mapping and distance sampling. However, these typically require more time, expertise and finances than are available across much of the globe. This is especially so in the tropics, where high species richness, low densities of many species and structurally complex environments also make monitoring particularly challenging. The MacKinnon lists technique is a rapid assessment methodology designed for use in species rich environments. This method is typically used to estimate species richness, but it has also been suggested that it can generate consistent abundance indices, even when observer experience and environmental conditions vary. If this suggestion is correct, the MacKinnon lists method could be used to assess spatial or temporal changes in abundance using diverse survey data. Here, we provide the first detailed assessment of intra- and inter-observer consistency of the Mackinnon List method in generating species abundance indices that could be useful for conservation monitoring purposes. As a case study, we use one of the world’s most diverse avifaunas, that of the forested Bolivian Andes. We show that MacKinnon lists can provide species abundance indices that are consistent between observers of markedly different experience of the focal avifauna (zero to six years), and between assessments carried out in different stages of the breeding season, between which detectability of individuals differed significantly. We believe this is the first time that a biodiversity monitoring method has been demonstrated to produce consistent abundance indices for a highly diverse avian tropical assemblage. We also suggest that the MacKinnon lists methodology has the potential to be a very useful conservation monitoring tool for many taxa in species rich environments, such as the tropics.     

Influence of connectivity, habitat quality and invasive species on egg and larval distributions and local abundance of crucian carp in Japanese agricultural landscapes

The quality of habitat at and around a spawning site, and the availability of movement between spawning and nonspawning habitats are likely to be important determinants for population persistence in a degraded and fragmented landscape. We assessed the influence of habitat connectivity, habitat quality and invasive species for distributions and local abundance of eggs and larvae of crucian carp (Crassius auratus complex, which is listed as “data deficient” on the Japanese Red List) in agricultural landscapes surrounding Lake Mikata, Japan, where drainage ditches and paddy fields are extensively utilised for spawning (lake or river shores are also used). We investigated the presence and abundance of eggs and larvae of crucian carp and habitat components at 146 sites across a range of presumed spawning habitats. Egg presence was affected strongly by connectivity to the lake (watercourse distance from the lake), and egg abundance was significantly influenced by both connectivity and habitat quality. In contrast, larval presence was primarily related to habitat quality. Larval abundance was influenced by connectivity and habitat quality, but the effect of connectivity was relatively low. Furthermore, larval abundance was negatively related to the presence of the invasive species red swamp crayfish (Procambarus craki) and bullfrog (Rana catesbeiana). Our findings indicate that connectivity, habitat quality and the presences of invasive species are crucial in determining suitable spawning and nursery habitats, but their relative importance may vary depending on egg and larval life stages. We suggest that restoring connectivity, improving habitat quality and removal of invasive species could be effective conservation strategies for the declining populations of crucian carp in agricultural landscapes.     

Composite sampling enhances the confidence of soil microarthropod abundance and species richness estimates

The quantification of abundance and species richness of soil microarthropods is most often severely hindered by extraordinary data variability, highly skewed frequency distributions, many extreme and zero counts, and small sample sizes. We developed a composite sampling technique to enhance the confidence of abundance and species richness estimates. Many soil cores (n ≥ 100) are sampled, animals extracted, the extracts pooled, mixed, and subsamples (aliquots) taken. Compared to the standard (separate sampling units), no microarthropods were lost or mechanically damaged during the compositing procedure. The confidence of abundance estimates was substantially greater in the composite than in the standard, although not for taxa of low abundance (< ≈ 10³ ind.m⁻²). Moreover, compositing was the superior technique in estimating species richness. The number of sampling units needed to recover a certain number of species with the composite was 70% of the standard method. We conclude that composite sampling is a promising alternative to the standard technique and may help to increase the generally low confidence of microarthropod field data. Finally, potential limitations of composite plans are discussed: a great number of field cores from an unbiased sampling plan have to be composited; comparisons between composites of unequal size should be avoided; all information on the variation among field cores is lost by compositing; parallel measurements of fauna and other variables in the same cores are not possible.     

西北地区赤霞珠葡萄根际土壤中AM真菌的多样性

对西北地区5个酿酒葡萄赤霞珠（Vitis vinifera L. cv. Cabernet Sauvignon）葡萄园根际土壤060 cm土层的AM真菌空间分布进行了研究。结果表明,葡萄根系可形成丛枝菌根,且侵染率较高,最高达79%; 在西北地区的5个样地中共分离出AM真菌4属22种,其中球囊霉属（Glomus）15种,无梗囊霉属（Acaulospora）4种,盾巨孢囊霉属（Scutellospora）2种,巨孢囊霉属（Gigaspora）1种。5个样地孢子密度大小顺序为: 陕西泾阳（JY）＞山西永济（YJ）＞陕西杨凌（YL）＞宁夏银川（YC）＞甘肃莫高（MG）。各样地葡萄根际土壤中AM真菌种的丰富度不同,陕西泾阳地区最高; 分布于葡萄根际的AM真菌按种类多少排序的属依次是: 球囊霉属无梗囊霉属盾巨孢囊霉属巨孢囊霉属,球囊霉属占据的比例保持着绝对优势; 根内球囊霉、摩西球囊霉、地表球囊霉在不同样地中均为优势菌株,副冠球囊霉,集球囊霉,细凹无梗囊霉是多数样地中的稀有种类。研究表明,葡萄与AM真菌具有良好的共生关系,二者协同进化产生了具有生态环境特异性的菌根真菌多样性; 葡萄根际存在较为丰富的丛枝菌根真菌资源,可供进一步开发利用。     

A six year study of earthworm (Lumbricidae) populations in pasture woodland in southern England shows their responses to soil temperature and soil moisture

There are very few studies on the effects of temporal changes in soil properties on ecosystem engineers in UK soils. This study addresses this lack by presenting earthworm diversity data from a six-year seasonality study comprising 72 monthly samples from the litter and soil of pasture woodland in the New Forest, southern England. These data were analysed in the context of soil moisture and soil temperature, key factors affecting earthworm abundance, and factors likely to be strongly affected by future climate change. The data for the whole period were analysed using non-parametric regression and an additive model used to separate within-year and between-year effects. Seasonal patterns are present for all the common species, generally with a maximum in March and a minimum in September. A majority of the five commonest species show a strong decline in abundance during the two extremely dry periods (2002–2003 and 2006). In sharp contrast, the same species showed a relative increase during the very wet summer and autumn of 2007. There was, however, no significant overall trend in either the climate data or the earthworm species data. The epigeic species, Dendrobaena octaedra, showed the largest decline in the driest months which caused a crash to the point where there were no adults sampled during the four dry summer months of 2003. A second congeneric species, Dendrobaena attemsi, also epigeic, appears to have invaded the woodland during the six year period and is increasing rapidly in abundance. This may indicate the start of a shift in the distribution of the two species, as D. octaedra generally has a northern European distribution and is frost-tolerant, while D. attemsi has a southern European distribution and is more drought-tolerant. In contrast, the very wet summer of 2007 seems to have damped the usual periodic seasonal oscillations in earthworm numbers. Endogeic worm species do not show the D. octaedra seasonal pattern as obviously, probably because these species are able to move more freely through the soil and because they are able to aestivate. These changes are likely to be due to a combination of human movement of earthworms (e.g. D. attemsi) and variations in local climate.     

Snake species distributions and temperate grasslands: A case study from the American tallgrass prairie

Many snake species are declining globally, yet data unavailability in temperate grasslands hinders snake conservation in one of the world’s most endangered biomes. To encourage and inform the conservation of snakes in these regions, I examined snake species diversity and abundance during 2 years of a mark-recapture study at 22 sites located in six American tallgrass prairie preserves in northern Illinois, USA. I emphasized landscape-scale relationships after accounting for covariance with environmental factors at both finer (microhabitat) and broader (regional) scales. A total of 120 snakes representing seven species was captured using drift fence arrays associated with funnel traps and sheet metal cover. The low numbers and diversity of snakes captured, when compared to historic evidence, indicate that since the 1930s Midwestern snake populations have declined. Non-metric multidimensional scaling and Mantel tests demonstrate that differences in snake species composition in remnant and degraded prairies are discernable along gradients of urban and agricultural land cover. However, different patterns of abundance for individual snake species indicate that the relative importance of specific landscape factors differ among species, which has significant conservation implications. Here, I recommend that conservationists use a species-specific approach to manage snake populations. I also stress the need for thorough inventory of snake populations and studies of snake-habitat relationships to advance our understanding of snake ecology and conservation within the little studied temperate grassland habitats of South America and eastern Eurasia.     

Quantifying imperfect detection in an invasive pest fish and the implications for conservation management

In managing non-native species, surveillance programmes aim to minimise the opportunity for invasions to develop from initial introductions through early detection. However, this is dependent on surveillance methods being able to detect species at low levels of abundance to avoid false-negative recordings through imperfect detection. We investigated through field experimentation the ability to detect Pseudorasbora parva, a highly invasive pest fish in Europe, in relation to their known density and sampling method. Secure pond mesocosms of area 100 m² contained P. parva densities from 0.02 to 5.0 m⁻²; each density was in triplicate. These were searched using point sampling electric fishing and deployment of fish traps (non-baited and baited). No fish were captured at densities <0.5 m⁻² using any method and this was considered their detection threshold. Point sample electric fishing was the least effective detection method, producing high proportions of false-negative data even at high fish densities. Baited traps were the most effective detection method. Probability of detection of P. parva was 1.0 for baited traps at all densities >0.5 m⁻², whereas for electric fishing it only exceeded 0.95 at 5.0 m⁻² using high searching effort. These data reveal that small pest fishes such as P. parva may be prone to imperfect detection when at low densities and this is consistent with a number of other invasive species. This indicates the importance of designing surveillance programmes using methods of known statistical power to optimise conservation resource expenditure and enhance management outcomes.