### Improving Precision in Multiple Covariate Distance Sampling: A Case Study with Whales in Alaska

, 2006

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This is to certify that I have examined this copy of a doctoral dissertation by

### 1 Point transect sampling with traps or lures 2 3 4 5 6 7 8

"... 1. The ability to monitor abundance of animal populations is becoming increasingly important, in light of growing concerns over the loss of biodiversity through anthropogenic changes. A widely-used tool for such monitoring is distance sampling, in which distances of detected animals from a line or p ..."

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1. The ability to monitor abundance of animal populations is becoming increasingly important, in light of growing concerns over the loss of biodiversity through anthropogenic changes. A widely-used tool for such monitoring is distance sampling, in which distances of detected animals from a line or point are modelled, to estimate detectability and hence abundance. Nevertheless, many species still prove problematic to survey. We develop two extensions to point transect sampling that potentially allow abundance to be estimated of a number of species from diverse taxa for which good survey methods have not previously been available. 2. For each method, the primary survey comprises a random sample of points, or more usually a systematic grid of points, through the region of interest. Animals are lured to a point, or trapped at a point, and the number of animals observed at each point is recorded. A separate study is conducted on a subset of animals, to record whether they

### METHODS RESULTS ESTIMATING ANIMAL ABUNDANCE ………………………………………..……3

, 2008

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### REVIEW 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 andmost analyses use the softwareDistance. 2. We briefly review distance sampling and its assumptions, outline the history, structure and capabilities of Distan ..."

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1. Distance sampling is a widely used technique for estimating the size or density of biological populations.Many distance sampling designs andmost analyses use the softwareDistance. 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 pro-posed designs to be examined via simulation, and survey plans to be generated. 4. A first step in analysis of distance sampling data is modelling 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.

### Distance sampling

"... Distance sampling is a widely used group of closely related methods for estimating the density and/or abundance of biological populations. The main methods are line-transect sampling and point-transect sampling (also called variable circular plot sam-pling). These have been used successfully in a ve ..."

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Distance sampling is a widely used group of closely related methods for estimating the density and/or abundance of biological populations. The main methods are line-transect sampling and point-transect sampling (also called variable circular plot sam-pling). These have been used successfully in a very diverse array of taxa, including trees, shrubs and herbs, insects, amphibians, reptiles, birds, fish, and marine and land mammals. In both cases, the basic idea is the same. One or more observers perform a standardized survey along a randomly located set of lines or points, searching for objects of interest (usually animals or clusters of animals). For each object detected, they record the distance from the line or point to the object. Not all the objects will be detected, but a fundamental assumption of the basic methods is that all objects that are actually on the line or point are detected. Intuitively, one would expect that objects become harder to detect with increasing distance from the line or point, resulting in fewer detections with increasing distance. The key to dis-tance sampling analyses is to fit a detection function to the observed distances, and use this fitted function to estimate the proportion of objects missed during the survey. From here, we can readily obtain point and interval estimates for the density and abundance of objects in the survey area. The basic methods (sometimes called standard or conventional distance sampling) are described in detail in Ref. 1, which is an updated version of Ref. 2. Various extensions and more advanced methods are considered in Ref. 3. Free software, Distance [4], provides for the design and analysis of distance sampling surveys, imple-menting the methods described in Ref. 1 and many of those in Ref. 3. Distance sampling is an extension of quadrat-based sampling methods. Two forms of quadrat sam-pling are strip transects, in which one or more observers move along a line, counting all objects within a predetermined distance of the line, and point

### Journal of Applied Ecology doi: 10.1111/j.1365-2664.2009.01737.x REVIEW 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 Dis ..."

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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 modelling 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.

### doi:10.1017/S0959270908000294 Printed in the United Kingdom Estimating bird abundance: making methods work

"... In many bird monitoring surveys, no attempt is made to estimate bird densities or abundance. Instead, counts of one form or another are made, and these are assumed to correlate with bird density. Unless complete counts on sample plots are feasible, this approach can easily lead to false conclusions, ..."

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In many bird monitoring surveys, no attempt is made to estimate bird densities or abundance. Instead, counts of one form or another are made, and these are assumed to correlate with bird density. Unless complete counts on sample plots are feasible, this approach can easily lead to false conclusions, because detectability of birds varies by species, habitat, observer and many other factors. Trends in time of counts often reflect trends in detectability, rather than trends in abundance. Conclusions are further compromised when surveys are conducted at unrepresentative sites. We consider how to avoid these problems. We give a brief description of distance sampling methods, which allow detectability to be estimated. We consider strategies to ease their implementation, to enhance their reliability, to adapt the methods for difficult species, and to deal with circumstances in which representative sampling is problematic. We also consider some of the common problems encountered, and suggest solutions.