Distance software: design and analysis of distance sampling surveys for estimating population size

1. Distance sampling is a widely used technique for estimating the size or density of biological populations. Many distance sampling designs and most analyses use the software Distance. 2. We briefly review distance sampling and its assumptions, outline the history, structure and capabilities of Distance, and provide hints on its use. 3. Good survey design is a crucial prerequisite for obtaining reliable results. Distance has a survey design engine, with a built-in geographic information system, that allows properties of different proposed designs to be examined via simulation, and survey plans to be generated. 4. A first step in analysis of distance sampling data is modeling the probability of detection. Distance contains three increasingly sophisticated analysis engines for this: conventional distance sampling, which models detection probability as a function of distance from the transect and assumes all objects at zero distance are detected; multiple-covariate distance sampling, which allows covariates in addition to distance; and mark–recapture distance sampling, which relaxes the assumption of certain detection at zero distance. 5. All three engines allow estimation of density or abundance, stratified if required, with associated measures of precision calculated either analytically or via the bootstrap. 6. Advanced analysis topics covered include the use of multipliers to allow analysis of indirect surveys (such as dung or nest surveys), the density surface modeling analysis engine for spatial and habitat-modeling, and information about accessing the analysis engines directly from other software. 7. Synthesis and applications. Distance sampling is a key method for producing abundance and density estimates in challenging field conditions. The theory underlying the methods continues to expand to cope with realistic estimation situations. In step with theoretical developments, state-of- the-art software that implements these methods is described that makes the methods accessible to practicing ecologists.

Geographic Variation in Sea Otters, Enhydra lutris

Univariate and multivariate analyses of 20 skull characters of 304 adult sea otters from throughout the geographic range strongly suggest that three subspecies should be recognized. The nominate form, Enhydra lutris lutris, occurs from the Kuril Islands north to the Commander Islands in the western Pacific Ocean. Individuals of E. l. lutris are characterized by large size and wide skulls with short nasal bones. E. 1. nereis is found along the California coast and off San Nicolas Island, where the species recently has been reintroduced from coastal California. Specimens of E. 1. nereis have narrow skulls with a long rostrum and small teeth, and usually lack the characteristic notch in the postorbital region found in most specimens of the other two subspecies. A new subspecies described by Don E. Wilson in this report, occurs throughout the Aleutian Islands and southward in the eastern Pacific to Washington. Specimens of the new subspecies are intermediate in size in most, but not all, characters and have longer mandibles than either of the other two subspecies

Availability and Use of Audiovisual and Electronic Resources by Distance Learning Students in Nigerian Universities: a Case Study of National Open University of Nigeria (NOUN), Ibadan Study Centre

This study investigated the availability and use of audiovisual and electronic resources by distance learning students at the National Open University of Nigeria (NOUN). A questionnaire was administered tothe distance learning students selected across the various departments of the NOUN. The findings revealed that even though NOUN made provision for audiovisual and electronic resources for students' use, a majority of the audiovisual and electronic resources are available through personal provision by the students.The study also revealed regular use of audiovisual and electronic resources by the distance learning students. Constraints on use include poor power supply, poor infrastructure, lack of adequate skill, and high cost of access.

Seasonal Variation in Reception of Fin Whale Calls at Five Geographic Areas in the North Pacific

In late August 1991 scientists at the National Oceanic and Atmospheric Administration’s (NOAA) National Marine Mammal Laboratory (NMML) and Pacific Marine Environmental Laboratory (PMEL) began a pilot study to investigate the capability of hydrophones from the US. Navy’s fixed array system to detect large whales in the North Pacific by passive reception of their calls. PMEL had previously established a direct data link from five bottom-mounted arrays of the Navy SOSUS (Sound Surveillance System), via the Naval Oceanographic Processing Facility (NOPF) at Whidbey Island, Washington, to study low-level seafloor seismicity (Fox et al. 1994). PMEL subsequently provided NMML tapes of SOSUS hydrophone data from which whale calls were analyzed. As in an analogous study conducted in the North Atlantic (Nishimura and Conlon 1994, Clark 1995, Mellinger and Clark 1995), calls attributable to whales were received at each SOSUS site at rates that varied seasonally (Anonymous 1996).

Spatial statistical models that use flow and stream distance

We develop spatial statistical models for stream networks that can estimate relationships between a response variable and other covariates, make predictions at unsampled locations, and predict an average or total for a stream or a stream segment. There have been very few attempts to develop valid spatial covariance models that incorporate flow, stream distance, or both. The application of typical spatial autocovariance functions based on Euclidean distance, such as the spherical covariance model, are not valid when using stream distance. In this paper we develop a large class of valid models that incorporate flow and stream distance by using spatial moving averages. These methods integrate a moving average function, or kernel, against a white noise process. By running the moving average function upstream from a location, we develop models that use flow, and by construction they are valid models based on stream distance. We show that with proper weighting, many of the usual spatial models based on Euclidean distance have a counterpart for stream networks. Using sulfate concentrations from an example data set, the Maryland Biological Stream Survey (MBSS), we show that models using flow may be more appropriate than models that only use stream distance. For the MBSS data set, we use restricted maximum likelihood to fit a valid covariance matrix that uses flow and stream distance, and then we use this covariance matrix to estimate fixed effects and make kriging and block kriging predictions.

A Model-Based Approach for Making Ecological Inference from Distance Sampling Data

We consider a fully model-based approach for the analysis of distance sampling data. Distance sampling has been widely used to estimate abundance (or density) of animals or plants in a spatially explicit study area. There is, however, no readily available method of making statistical inference on the relationships between abundance and environmental covariates. Spatial Poisson process likelihoods can be used to simultaneously estimate detection and intensity parameters by modeling distance sampling data as a thinned spatial point process. A model-based spatial approach to distance sampling data has three main benefits: it allows complex and opportunistic transect designs to be employed, it allows estimation of abundance in small subregions, and it provides a framework to assess the effects of habitat or experimental manipulation on density. We demonstrate the model-based methodology with a small simulation study and analysis of the Dubbo weed data set. In addition, a simple ad hoc method for handling overdispersion is also proposed. The simulation study showed that the model-based approach compared favorably to conventional distance sampling methods for abundance estimation. In addition, the overdispersion correction performed adequately when the number of transects was high. Analysis of the Dubbo data set indicated a transect effect on abundance via Akaike’s information criterion model selection. Further goodness-of-fit analysis, however, indicated some potential confounding of intensity with the detection function.

Landscape-Genetic Analysis of Population Structure in the Texas Gray Fox Oral Rabies Vaccination Zone

In west-central Texas, USA, abatement efforts for the gray fox (Urocyon cinereoargenteus) rabies epizootic illustrate the difficulties inherent in large-scale management of wildlife disease. The rabies epizootic has been managed through a cooperative oral rabies vaccination program (ORV) since 1996. Millions of edible baits containing a rabies vaccine have been distributed annually in a 16-km to 24-km zone around the perimeter of the epizootic, which encompasses a geographic area >4 x 105 km2. The ORV program successfully halted expansion of the epizootic into metropolitan areas but has not achieved the ultimate goal of eradication. Rabies activity in gray fox continues to occur periodically outside the ORV zone, preventing ORV zone contraction and dissipation of the epizootic. We employed a landscape-genetic approach to assess gray fox population structure and dispersal in the affected area, with the aim of assisting rabies management efforts. No unique genetic clusters or population boundaries were detected. Instead, foxes were weakly structured over the entire region in an isolation by distance pattern. Local subpopulations appeared to be genetically non-independent over distances >30 km, implying that long-distance movements or dispersal may have been common in the region. We concluded that gray foxes in west-central Texas have a high potential for long-distance rabies virus trafficking. Thus, a 16-km to 24-km ORV zone may be too narrow to contain the fox rabies epizootic. Continued expansion of the ORV zone, although costly, may be critical to the long-term goal of eliminating the Texas fox rabies virus variant from the United States.

Landscape Genetics of Raccoons (Procyon lotor) Associated with Ridges and Valleys of Pennsylvania: Implications for Oral Rabies Vaccination Programs

Raccoons are the reservoir for the raccoon rabies virus variant in the United States. To combat this threat, oral rabies vaccination (ORV) programs are conducted in many eastern states. To aid in these efforts, the genetic structure of raccoons (Procyon lotor) was assessed in southwestern Pennsylvania to determine if select geographic features (i.e., ridges and valleys) serve as corridors or hindrances to raccoon gene flow (e.g., movement) and, therefore, rabies virus trafficking in this physiographic region. Raccoon DNA samples (n = 185) were collected from one ridge site and two adjacent valleys in southwestern Pennsylvania (Westmoreland, Cambria, Fayette, and Somerset counties). Raccoon genetic structure within and among these study sites was characterized at nine microsatellite loci. Results indicated that there was little population subdivision among any sites sampled. Furthermore, analyses using a model-based clustering approach indicated one essentially panmictic population was present among all the raccoons sampled over a reasonably broad geographic area (e.g., sites up to 36 km apart). However, a signature of isolation by distance was detected, suggesting that widths of ORV zones are critical for success. Combined, these data indicate that geographic features within this landscape influence raccoon gene flow only to a limited extent, suggesting that ridges of this physiographic system will not provide substantial long-term natural barriers to rabies virus trafficking. These results may be of value for future ORV efforts in Pennsylvania and other eastern states with similar landscapes.