Will Observation Error and Biases Ruin the Use of Simple Extinction Models?

Abstract: Estimating the risk of extinction for populations of endangered species is an important component of conservation biology. These estimates must be made from data that contain both environmental noise in the year-to-year transitions in population size (so-called "process error"), random errors in sampling, and possible biases in sampling ( both forms of observation errors). To determine how much faith to place in estimated extinction rates, it is important to know how sensitive they are to observation error. We used three simple, commonly employed models of population dynamics to generate simulated population time series. We then combined random observation error or systematic biases with those data, fit models to the time series data, and observed how close the extinction dynamics of the fitted models compared with the dynamics of the underlying models. We found that systematic biases in sampling rarely affected estimates of extinction risk. We also found that even moderate levels of random observation error do not significantly affect extinction estimates except over a small range of process errors, corresponding to the region where extinction risk is most uncertain. With more substantial sampling error, estimates of extinction risk degraded rapidly. Field census techniques for a variety of taxa often involve observation errors within ±32% of actual population sizes. For typical time series used in conservation, therefore, we often may not need to be overly concerned about observation errors as an extra source of imperfection in our estimated extinction rates.     

A survey of antennal responses by five species of coniferophagous bark beetles (Coleoptera: Scolytidae) to bark volatiles of six species of angiosperm trees

Summary. Using Porapak Q traps, we collected the bark volatiles of six angiosperm trees native to British Columbia: black cottonwood, Populus trichocarpa Torr. & A. Gray (Salicaceae), trembling aspen, P. tremuloides Michx. (Salicaceae), paper birch, Betula papyrifera Marsh. (Betulaceae), bigleaf maple, Acer macrophyllum Pursh (Aceraceae), red alder, Alnus rubra Bong. (Betulaceae), and Sitka alder, A. viridis ssp. sinuata (Regel) á. L?ve & D. L?ve (Betulaceae). Utilising coupled gas chromatographic-electroantennographic detection analysis, the captured volatiles were assayed for antennal responses in five species of coniferophagous bark beetles (Coleoptera: Scolytidae), sympatric with most or all of the angiosperm trees: the Douglas-fir beetle, Dendroctonus pseudotsugae Hopkins, the mountain pine beetle, D. ponderosae Hopkins, the spruce beetle, D. rufipennis (Kirby), the western balsam bark beetle, Dryocoetes confusus Swaine, and the pine engraver, Ips pini (Say). The identities of 25 antennally-active compounds were determined by coupled gas chromatographic-mass spectroscopic analysis, and co-chromatographic comparisons with authentic chemicals. The compounds identified were: hexanal, (E)-2-hexenal, (Z)-3-hexen-1-ol, 1-hexanol, heptanal, α-pinene, frontalin, benzaldehyde, β-pinene, 2-hydroxycyclohexanone, 3-carene, limonene, β-phellandrene, benzyl alcohol, (E)-ocimene, salicylaldehyde, conophthorin, guaiacol, nonanal, methyl salicylate, 4-allylanisole, decanal, thymol methyl ether, (E)-nerolidol, and dendrolasin. A number of these compounds are known semiochemicals that are active in the behaviour of other organisms, including bark beetles, suggesting a high degree of semiochemical parsimony. Antennally-active compounds ranged from seven in A. viridis to 17 in P. trichocarpa. The fewest number of compounds (9) were detected by I. pini and the largest number (24) were detected by D. pseudotsugae. Six compounds excited the antennae of all five species of bark beetles. The large number of antennally-active compounds detected in common by numerous bark beetles and present in common in numerous nonhost trees supports the hypothesis of olfaction-based recognition and avoidance of nonhost angiosperm trees during the process of host selection by coniferophagous bark beetles. Received 13 December 1999; accepted 14 March 2000     

Soft intervention technology as a tool for integrated coastal zone management

After introducing soft defence techniques as an alternative to hard defence techniques, the need is emphasized to consider the coastal area as an integral system. By recalling the main driving factors for coastal management: conflict resolution, resilience and sustainability, we logically arrive at the concepts of ecological engineering and ecotechnology, which are increasingly acknowledged as possible solutions to achieve sustainable use of coastal space as a resource. In this context, we refer to the principles of self design and of ecosystem conservation. In order to deal with real situations we are in need of fundamental ‘tools’ for the application of the soft intervention technology approach. We therefore introduce the concept of physiographic units and develop an initial elaboration for a coastal stretch and for coastal wetlands. The latter deserve more attention because of the already established practices of ecotechnology, at least as far as water and soil quality are concerned, but certainly also concerning morphology, especially in the future. We conclude by briefly discussing how activities undertaken in two research projects currently being conducted under the framework of the Marine Science and Technology Program of the Commission of the European Communities are expected to contribute to the concepts introduced here.     

产业与环境：丹麦展望

近20-30年来,很多国家引进了综合性环境保护法律.然而,人们逐渐认识到,在进行具体技术调控的同时,也需要意识上和管理原则上的改变.为帮助各公司在公司层次上减少、评估、监测和控制环境影响,已经开发了各种环境管理技术.本文根据对丹麦公司的一次调查,论述了下列问题:这些技术是如何在工业中采用的?以及发生态度上的变化了吗?     

Modelling the Distribution and Quality of Sand and Gravel Resources in 3D: a Case Study in the Thames Basin,UK

Three-dimensional (3D) models are often utilised to assess the presence of sand and gravel deposits. Expanding these models to provide a better indication of the suitability of the deposit as aggregate for use in construction would be advantageous. This, however, leads to statistical challenges. To be effective, models must be able to reflect the interdependencies between different criteria (e.g. depth to deposit, thickness of deposit, ratio of mineral to waste, proportion of ‘fines’) as well as the inherent uncertainty introduced because models are derived from a limited set of boreholes in a study region. Using legacy borehole data collected during a systematic survey of sand and gravel deposits in the UK, we have developed a 3D model for a 2400 km² region close to Reading, southern England. In developing the model, we have reassessed the borehole grading data to reflect modern extraction criteria and explored the most suitable statistical modelling technique. The additive log-ratio transform and the linear model of coregionalization have been applied, techniques that have been previously used to map soil texture classes in two dimensions, to assess the quality of sand and gravel deposits in the area. The application of these statistical techniques leads to a model which can be used to generate thousands of plausible realisations of the deposit which fully reflect the extent of model uncertainty. The approach offers potential to improve regional-scale mineral planning by providing an enhanced understanding of sand and gravel deposits and the extent to which they meet current extraction criteria.

     

Performance Evaluation of Multiple Groundwater Flow and Nitrate Mass Transport Numerical Models

Environmental Modeling & Assessment - Benchmarking of different numerical models simulating groundwater flow and contaminant mass transport is the aim of the present study, in order to...     

Framing of Geoengineering Affects Support for Climate Change Mitigation

The growing recognition that climate change mitigation alone will be inadequate has led scientists and policymakers to discuss climate geoengineering. An experiment with a US sample found, contrary to previous research, that reading about geoengineering did not reduce conservatives’ skepticism about the existence of anthropogenic climate change. Moreover, depending on how it is framed, geoengineering can reduce support for mitigation among both conservatives and non-conservatives. When geoengineering is framed as a major solution, people worry less about climate change, leading to reduced mitigation support. When framed as disastrous, people perceived geoengineering as riskier, also leading to a decrease in mitigation support. A more moderate framing of geoengineering as a partial solution is less susceptible to moral hazard effects. Overall, results suggest that geoengineering will not lessen political polarization over anthropogenic climate change, and could undercut support for mitigation efforts. Instead, framing geoengineering as a small piece to solving a big puzzle seems to be the best strategy to weaken this potential moral hazard.