Endangered Species, Provincialism, and a Continental Approach to Bird Conservation

I examined lists of endangered species from northeastern and midwestern United States to assess the extent to which they were dominated by species considered rare due to their vulnerability to anthropogenic stressors or, instead, by species whose rarity might be explained otherwise. Northeastern states had longer species lists than midwestern states, and more species associated with locally rare prairie habitats. More species at the edge of their geographic range appeared on lists from the Northeast than the Midwest. About 70% of listed species overall have shown either no significant population trend, or increases, at the continental scale, but wetland and prairie species were frequently listed, consistent with the generally acknowledged, widespread loss of these habitats. Curiously, midwestern states tended to list fewer forest species, despite evidence that forest fragmentation there has had strongly deleterious effects on regional bird populations. Overall, species appear to be listed locally for a variety of reasons not necessarily related to their risk of extinction generally, potentially contributing to inefficient distributions of limited resources to deal effectively with species that legitimately require conservation attention. I advocate a continental perspective when listing species locally, and propose enhanced criteria for characterizing species as endangered at the local level.

An ontological approach to competency management

Competency management is a very important part of a well-functioning organisation. Unfortunately competency descriptions are not uniformly specified nor defined across borders: National, sectorial or organisational, leading to an opaque competency description market with a multitude of competency frameworks and competency benchmarks. An ontology is a formalised description of a domain, which enables automated reasoning engines to be built which by utilising the interrelations between entities can make “intelligent” choices in different situations within the domain. Introducing formalised competency ontologies automated tools, such as skill gap analysis, training suggestion generation, job search and recruitment, can be developed, which compare and contrast different competency descriptions on the semantic level. The major problem with defining a common formalised ontology for competencies is that there are so many viewpoints of competencies and competency frameworks. Work within the TRACE project has focused on finding common trends within different competency frameworks in order to allow an intermediate competency description to be made, which other frameworks can reference. This research has shown that competencies can be divided up into “knowledge”, “skills” and what we call “others”. An ontology has been created based on this with a simple structure of different “kinds” of “knowledges” and “skills” using semantic interrelations to define the basic semantic structure of the ontology. A prototype tool for analysing a skill gap analysis has been developed. Personal profiles can be produced using the tool and a skill gap analysis is performed on a desired competency profile by using an ontologically based inference engine, which is able to list closest fit and possible proficiency gaps