To a first approximation, the distribution of biodiversity across the Earth can be described in terms of a relatively small number of broad-scale spatial patterns. Although these patterns are increasingly well documented, understanding why they exist constitutes one of the most significant intellectual challenges to ecologists and biogeographers. Theory is, however, developing rapidly, improving in its internal consistency, and more readily subjected to empirical challenge.

Global patterns in biodiversity

Monitoring programmes are being used increasingly to assess spatial and temporal trends of biological diversity, with an emphasis on evaluating the efficiency of management policies. Recent reviews of the existing programmes, with a focus on their design in particular, have highlighted the main weaknesses: the lack of well-articulated objectives and the neglect of different sources of error in the estimation of biological diversity. We review recent developments in methods and designs that aim to integrate sources of error to provide unbiased estimates of change in biological diversity and to suggest the potential causes.

Monitoring of biological diversity in space and time

There is general agreement among scientists that biodiversity is under assault on a global basis and that species are being lost at a greatly enhanced rate. This article examines the role played by biogeographical science in the emergence of conservation guidance and makes the case for the recognition of Conservation Biogeography as a key subfield of conservation biology delimited as: the application of biogeographical principles, theories, and analyses, being those concerned with the distributional dynamics of taxa individually and collectively, to problems concerning the conservation of biodiversity. Conservation biogeography thus encompasses both a substantial body of theory and analysis, and some of the most prominent planning frameworks used in conservation. Considerable advances in conservation guidelines have been made over the last few decades by applying biogeographical methods and principles. Herein we provide a critical review focussed on the sensitivity to assumptions inherent in the applications we examine. In particular, we focus on four inter-related factors: (i) scale dependency (both spatial and temporal); (ii) inadequacies in taxonomic and distributional data (the so-called Linnean and Wallacean shortfalls); (iii) effects of model structure and parameterisation; and (iv) inadequacies of theory. These generic problems are illustrated by reference to studies ranging from the application of historical biogeography, through island biogeography, and complementarity analyses to bioclimatic envelope modelling. There is a great deal of uncertainty inherent in predictive analyses in conservation biogeography and this area in particular presents considerable challenges. Protected area planning frameworks and their resulting map outputs are amongst the most powerful and influential applications within conservation biogeography, and at the global scale are characterised by the production, by a small number of prominent NGOs, of bespoke schemes, which serve both to mobilise funds and channel efforts in a highly targeted fashion. We provide a simple typology of protected area planning frameworks, with particular reference to the global scale, and provide a brief critique of some of their strengths and weaknesses. Finally, we discuss the importance, especially at regional scales, of developing more responsive analyses and models that integrate pattern (the compositionalist approach) and processes (the functionalist approach) such as range collapse and climate change, again noting the sensitivity of outcomes to starting assumptions. We make the case for the greater engagement of the biogeographical community in a programme of evaluation and refinement of all such schemes to test their robustness and their sensitivity to alternative conservation priorities and goals.

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Conservation biogeography: assessment and prospect

Although the uses and merits of terrestrial insects as indicators have been extensively discussed, there is a lack of clear definition, goal directedness and hypothesis testing in studies in the field. In an attempt to redress some of these issues and outline an approach for further studies, three categories of terrestrial insect indicators, corresponding to differences in their application, are proposed, i.e. environmental, ecological and biodiversity indicators. The procedures in terrestrial insect bioindicator studies should start with a clear definition of the study objectives and proposed use of the bioindicator, as well as with a consideration of the scale at which the study is to be carried out. Bioindication studies are conducted at a variety of spatial and temporal scales within the context of earth-system processes, but the objectives of the study will largely determine the scale at which it would be optimally conducted. There is a tendency for studies to be conducted below their space-time scaling functions, giving them apparent predictability. The selection of potential indicator taxa or groups is then based on a priori suitability criteria, the identification of predictive relationships between the indicator and environmental variables and, most importantly, the development and testing of hypotheses according to the correlative patterns found. Finally, recommendations for the use of the indicator in monitoring should be made. Although advocating rigorous, long-term protocols to identify indicators may presently be questionable in the face of the urgency with which conservation decisions have to be made, this approach is critical if bioindicators are to be used with any measurable degree of confidence.

The selection, testing and application of terrestrial insects as bioindicators

Multi-criteria decision analysis in natural resource management: A critical review of methods and new modelling paradigms

http://heather.cs.ucdavis.edu/~matloff/132/Data/ForestCover/BlackardDean.pdf

Comparative accuracies of artificial neural networks and discriminant analysis in predicting forest cover types from cartographic variables

Mapping of biodiversity elements to expose gaps in conservation networks has become a common strategy in nature-reserve design. We review a set of critical assumptions and issues that influence the interpretation and implementation of gap analysis, including: (1) the assumption that a subset of taxa can be used to indicate overall diversity patterns, and (2) the impact of uncertainty and error propagation in reserve design. We focus our review on species diversity patterns and use data from peer-reviewed literature or extant state-level databases to test specific predictions implied by these assumptions. Support for the biodiversity indicator assumption was varied. Patterns of diversity as reflected in species counts, coincidence of hot spots, and representativeness were not generally concordant among different taxa, with the degree of concordance depending on the measure of diversity used, the taxa examined, and the scale of analysis. Simulated errors in predicting the occurrence of individual species indicated that substantial differences in reserve-boundary recommendations could occur when uncertainty is incorporated into the analysis. Furthermore, focusing exclusively on vegetation and species distribution patterns in conservation planning will contribute to reserve-design uncertainty unless the processes behind the patterns are understood. To deal with these issues, reserve planners should base reserve design on the best available, albeit incomplete, data; should attempt to define those ecological circumstances when the indicator assumption is defensible; should incorporate uncertainty explicitly in mapped displays of biodiversity elements; and should simultaneously consider pattern and process in reserve-design problems.

https://www.fs.fed.us/rm/pubs_other/rmrs_1997_flather_c001.pdf

Identifying gaps in conservation networks: of indicators and uncertainty in geographic-based analyses

Comparison of neural networks and discriminant analysis in predicting forest cover types

En foret, plusieurs chemins d'acces existants ne sont pas de simples routes independantes concues pour acceder a un peuplement unique; ils forment plutot un reseau complexe d'embranchements routiers concus pour donner acces a plusieurs peuplements. Les methodes traditionnelles de recherche utilisees pour la localisation optimale de ces reseaux routiers ont ete jusqu'a present presque entierement manuelles. Cette etude developpe et evalue trois strategies de localisation des reseaux routiers forestiers assistee d'un SIRS. Une approche Monte-Carlo fut utilisee pour comparer les solutions generees par chacune de ces strategies avec des solutions optimales creees a partir d'une approche par enumeration complete. Ces analyses ont revele que la technique de solution par evaluation d'embranchement exigeait seulement une fraction du temps et donnait des resultats presque aussi efficaces que ccux obtenus avcc l'enumeration complete. L'evaluation d'embranchement fut donc utilisee pour recreer des reseaux routiers traces aleatoirement a partir de la base de donnees provenant des Forets nationales Roosevelt et Arapaho. Cette etude a demontre que l'evaluation d'embranchement etait capable de recreer des routes similaires aux reseaux routiers existants dans un peu plus de 80% des cas. Ce taux d'agencement relativement eleve signifie que la technique d'evaluation d'embranchement peut s'averer un outil utile pour la conception automatisee de reseaux routiers preliminaires.

Finding optimal routes for networks of harvest site access roads using GIS-based techniques

OBJECTIVE: Several studies have provided prevalence estimates of posttraumatic stress disorder (PTSD) related to the September 11, 2001 (9/11) attacks in broadly affected populations, although without sufficiently addressing qualifying exposures required for assessing PTSD and estimating its prevalence. A premise that people throughout the New York City area were exposed to the attacks on the World Trade Center (WTC) towers and are thus at risk for developing PTSD has important implications for both prevalence estimates and service provision. This premise has not, however, been tested with respect to DSM-IV-TR criteria for PTSD. This study examined associations between geographic distance from the 9/11 attacks on the WTC and reported 9/11 trauma exposures, and the role of specific trauma exposures in the development of PTSD. METHODS: Approximately 3 years after the attacks, 379 surviving employees (102 with direct exposures, including 65 in the towers, and 277 with varied exposures) recruited from 8 affected organizations were interviewed using the Diagnostic Interview Schedule/Disaster Supplement and reassessed at 6 years. The estimated closest geographic distance from the WTC towers during the attacks and specific disaster exposures were compared with the development of 9/11-related PTSD as defined by the Diagnostic and Statistical Manual, Fourth Edition, Text Revision. RESULTS: The direct exposure zone was largely concentrated within a radius of 0.1 mi and completely contained within 0.75 mi of the towers. PTSD symptom criteria at any time after the disaster were met by 35% of people directly exposed to danger, 20% of those exposed only through witnessed experiences, and 35% of those exposed only through a close associate's direct exposure. Outside these exposure groups, few possible sources of exposure were evident among the few who were symptomatic, most of whom had preexisting psychiatric illness. CONCLUSIONS: Exposures deserve careful consideration among widely affected populations after large terrorist attacks when conducting clinical assessments, estimating the magnitude of population PTSD burdens, and projecting needs for specific mental health interventions. Language: en

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Trauma exposure and posttraumatic stress disorder among employees of New York City companies affected by the September 11, 2001 attacks on the World Trade Center.

Denis J. Dean

Papers

Comparative accuracies of artificial neural networks and discriminant analysis in predicting forest cover types from cartographic variables

Identifying gaps in conservation networks: of indicators and uncertainty in geographic-based analyses

Comparison of neural networks and discriminant analysis in predicting forest cover types

Finding optimal routes for networks of harvest site access roads using GIS-based techniques

Trauma exposure and posttraumatic stress disorder among employees of New York City companies affected by the September 11, 2001 attacks on the World Trade Center.