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.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 modelling analysis engine for spatial and habitat modelling, 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 practising ecologists.

We argue that model selection uncertainty should be fully incorporated into statistical inference whenever estimation is sensitive to model choice and that choice is made with reference to the data. We consider different philosophies for achieving this goal and suggest strategies for data analysis. We illustrate our methods through three examples. The first is a Poisson regression of bird counts in which a choice is to be made between inclusion of one or both of two covariates. The second is a line transect data set for which different models yield substantially different estimates of abundance. The third is a simulated example in which truth is known.

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Summary 0[ Widespread declines in the populations of many British farmland birds have occurred since the early 0869s[ We must understand the causes of these declines to make recommendations about conservation and agricultural management\ and this can be approached by investigating the relationships\ across species\ between abundance and agricultural change[ We describe novel\ quantitative approaches to the interpretation of abundance indices from which reliable inferences about conservation status can be made[ 1[ We calculated farmland Common Birds Census indices for 31 species\ smoothed the series to reveal underlying trends and estimated con_dence intervals for the changes in abundance[ 2[ Between 0857 and 0884\ the abundance of 01 species declined signi_cantly and that of 03 species increased[ 3[ Specialization was the only signi_cant determinant of changes in abundance "of 09 tests against species characteristics#] 02 farmland specialists declined\ on average\ by 29)\ whilst 18 more generalist species underwent an average increase of 12)\ con_rming that farmland birds should engender conservation concern[ 4[ Smoothed abundance curves\ transformed to emphasize trend direction and timing\ were then compared quantitatively to identify whether groups of species had shared common trends[ 5[ Species tended not to be strongly grouped\ but small groups of species with common trends were identi_ed[ Similarities in ecology among grouped species clarify the possible environmental causes of their population trends\ indicating future research priorities[ 6[ The groups identi_ed included] one group consisting of three thrush species Turdus and the skylark Alauda arvensis L[ which all declined from the mid!0869s after being stable previously^one group comprising three trans!Saharan migrant warblers "Sylvidae#\ whose abundance fell in the early 0869s and later increased^and a diverse group of six smoothly increasing species[ 7[ Turning points were identi_ed as where each species| population trend turned signi_cantly\ revealing critical periods during which populations are likely to have been a}ected by environmental change[ 8[ Three collections of downward turning points were found\ including one in the mid!0869s when many farmland bird declines began[ Four other periods each included many upturns[ The groups of turning points should facilitate the identi_cation of environmental changes which have had widespread e}ects[ Management prescriptions can then be designed to reverse or to mirror such key changes and thereby focus conservation e}ort e}ectively[ Key!words] agriculture\ bird populations\ conservation\ environmental change\ turn! ing points[

* Reliable estimates of animal density and abundance are essential for effective wildlife conservation and management. Camera trapping has proven efficient for sampling multiple species, but statistical estimators of density from camera trapping data for species that cannot be individually identified are still in development. * We extend point-transect methods for estimating animal density to accommodate data from camera traps, allowing researchers to exploit existing distance sampling theory and software for designing studies and analysing data. We tested it by simulation, and used it to estimate densities of Maxwell's duikers (Philantomba maxwellii) in Taï National Park, Côte d'Ivoire. * Densities estimated from simulated data were unbiased when we assumed animals were not available for detection during long periods of rest. Estimated duiker densities were higher than recent estimates from line transect surveys, which are believed to underestimate densities of forest ungulates. * We expect these methods to provide an effective means to estimate animal density from camera trapping data and to be applicable in a variety of settings

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Summary1. Accurate and precise estimates of abundance are required for the development of management regimes for deer populations. In woodland areas, indirect dung count methods, such as the clearance plot and standing crop methods, are currently the preferred procedures to estimate deer abundance. The use of line transect methodology is likely to provide a cost-effective alternative to these methods. 2. We outline a methodology based on line transect surveys of deer dung that can be used to obtain deer abundance estimates by geographical block and habitat type. Variance estimation procedures are also described. 3.As an example, we applied the method to estimate sika deer Cervus nippon abundance in south Scotland. Estimates of deer defecation and length of time to dung decay were used to convert pellet group density to deer density by geographical block and habitat type. The results obtained agreed with knowledge from cull and sightings data, and the precision of the estimates was generally high. 4. Relatively high sika deer densities observed in moorland areas up to 300 m from the forest edge indicated the need to encompass those areas in future surveys to avoid an underestimate of deer abundance in the region of interest. 5. It is unlikely that a single method for estimating deer abundance will prove to be better under all circumstances. Direct comparisons between methods are required to evaluate thoroughly the relative merits of each of them. 6. Line transect surveys of dung are becoming a widely used tool to aid management and conservation of a wide range of species. The survey methodology we outline is readily adaptable to other vertebrates that are amenable to dung survey methodology.