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.

The Economics of Threatened Species Conservation: A Review and Analysis

Stabilizing human population size and reducing human-caused impacts on the environment are keys to conserving threatened species (TS). Earth's human population is ~ 7 billion and increasing by ~ 76 million per year. This equates to a human birth-death ratio of 2.35 annually. The 2007 Red List prepared by the International Union for Conservation of Nature and Natural Resources (IUCN) categorized 16,306 species of vertebrates, invertebrates, plants, and other organisms (e.g., lichens, algae) as TS. This is ~ 1 percent of the 1,589,161 species described by IUCN or ~ 0.0033 percent of the believed 5,000,000 total species. Of the IUCN’s described species, vertebrates comprised relatively the most TS listings within respective taxonomic categories (5,742 of 59,811), while invertebrates (2,108 of 1,203,175), plants (8,447 of 297,326), and other species (9 of 28,849) accounted for minor class percentages. Conservation economics comprises microeconomic and macroeconomic principles involving interactions among ecological, environmental, and natural resource economics. A sustainable-growth (steady-state) economy has been posited as instrumental to preserving biological diversity and slowing extinctions in the wild, but few nations endorse this approach. Expanding growth principles characterize most nations' economic policies. To date, statutory fine, captive breeding cost, contingent valuation analysis, hedonic pricing, and travel cost methods are used to value TS in economic research and models. Improved valuation methods of TS are needed for benefit-cost analysis (BCA) of conservation plans. This Chapter provides a review and analysis of: (1) the IUCN status of species, (2) economic principles inherent to sustainable versus growth economies, and (3) methodological issues which hinder effective BCAs of TS conservation.