BSPP Presidential Meeting 1996Unlocking the Future: Information Technology in Plant Pathology
Systems for computer-based multi-access keys
M J Dallwitz, T A Paine and E J Zurcher
Division of Entomology, CSIRO, GPO Box 1700, Canberra, ACT 2601, Australia.
Computer-based multi-access keys, also known as interactive keys, can offer several advantages over conventional keys:
- A correct identification can be made in spite of errors by the user or in the data.
- Characters can be used, and their values changed, in any order.
- Numeric characters can be used directly, without being divided into ranges.
- The user can express uncertainty by entering more than one state value, or a range of numerical values.
Other desirable features include:
- Advice on the most suitable characters to use at any stage of an identification.
- Character dependencies: certain character values making other characters inapplicable.
- Provision for gaps in the values recorded for integer numeric characters.
- Storing, searching, and displaying free-text information.
- Locating errors which were circumvented by the error-tolerance mechanism.
- Use of probabilities.
- Provision for restricting any operation to subsets of the characters and taxa.
- Glossaries and notes on interpretation of characters.
- Illustrations of characters and taxa.
- Provision for information retrieval.
- Finding the differences and similarities between taxa.
- Finding diagnostic descriptions.
- The ability to handle large data sets efficiently.
- Data sharing with other description-based applications: description writing, generation of conventional keys, and phenetic and cladistic analysis.
It is an inevitable consequence of the flexibility of
interactive keys that much of the strategy involved in carrying
out an identification is left to the user. Good strategies must
be learnt if the keys are to be used to the best advantage.
Peter H Schalk
ETI, University of Amsterdam, Mauritskade 61, 1092 AD Amsterdam, Netherlands. Tel: +31 20 5257239. Fax: +31 20 5257238. E-mail: firstname.lastname@example.org.
The end of this millennium is characterized by an oncoming or perhaps ongoing revolution in the field of information management and fast dissemination by means of the new media. With the large scale introduction of personal computers in the consumer market, the related developments in Information Technology have received an enormous impulse. The possibilities of the compact disk and the Internet have literally erased traditional borders. Information processing and knowledge dissemination have found a new dimension and influenced science and society in an irreversible way.
The demand for readily accessible biological expertise is growing. In the scientific community and in society there is an increasing need for up-to-date information on biological diversity, stimulated in no small way by developments in the context of the Convention on Biological Diversity. In the past, scientific data were mainly for the scientists. Now the information is needed by a far larger group of users for various purposes such as: pure or applied research, industrial processes, nature conservation, biodiversity inventories, policy making, etc. In all these cases the "up-to-date-ness" and validity of the information may be vital.
At the same time the size of the required information sets is growing: we know more, need to update more, and need to check our data against a bigger variety of existing information. Last but not least, we are more in a hurry than ever before. There is an increasing pressure by society to produce and access the latest data fast; both information providers and information users encounter deadlines. This calls for innovative instruments to archive, process and handle our information. Information Technology offers new possibilities.
ETI developed the Linnaeus II software package for biodiversity documentation and species identification. It is a multi-functional system that can be used by scientists on their own PCs to create multimedia biological databases, computer-assisted identification systems and geographic information systems for mapping distributions and biodiversity. Apart from these basic functional parts, supporting modules such as glossaries, literature databases and methodological sections can easily be added. At the same time Linnaeus II presents an electronic publishing tool, allowing fast dissemination of large information systems on CD-ROM or the Internet.
This paper describes in detail the data model and functional aspects of the
Linnaeus II software, and discusses the why and how of ETI's taxonomy
networks: an internal cooperation of specialists to open up the knowledge of
the world's species and document biological diversity in a quality-warranted
Images as a basis for identification
D McL Roberts, G Novarino, G Kennaway & S Hope
Department of Zoology, The Natural History Museum, Cromwell Road, London SW7 5BD, UK.
Identification of a specimen has traditionally relied on it appearance, that is to say visual inspection should reveal sufficient characters to enable the specimen to be identified. This system had shortcomings when applied to very small organisms which, because of their sheer size could not carry sufficient visually accessible characters to allow straightforward identification. The almost universal move towards phylogenetic classification schemes also demonstrated the paucity of characters suitable for establishing relationships between taxonomic groups.
The development of high resolution techniques, particularly the transmission electron microscope, and non-visual methods, particularly molecular biology, has allowed much progress towards defining taxonomic groups, but has also necessitated the observation of difficult or obscure characters. The problem of identification has been greatly helped by the development of multi-access keys (see Dallwitz et al., above).
Some characters, e.g. movement in life or environmental context, have not been used in establishing taxonomic relationships but are almost universally used by those skilled in identification.
Here we will review some practical techniques in microscopy to enhance the
visibility of obscure characters, the use of video and computers to make
other characters accessible, and their use in distance learning. Examples
will be taken from a group generally regarded as "difficult", the
Building models of epidemics to help take decisions
Department of Phytopathology, Agricultural University, POB 8025, 6700 EE Wageningen, Netherlands.
The concern of plant epidemiology is with an understanding, not merely description, of interactions between host and pathogen populations. Based on this understanding it may be possible to make decisions at different levels relating to disease management tactics, strategy and policy. Mathematical modelling, as part of the normal process of scientific inquiry, can contribute both to understanding and to the decision process. Models are used for different purposes: in exploratory analysis; to formalize concepts relating to epidemic processes; and to span biological hierarchies or levels of integration. Examples will be given of how these model types have contributed to decisions in disease management. Most epidemic models attempt to deconstruct an epidemic into component processes and then either identify key processes and their determinants, or to reconstruct an epidemic using computer simulation. Modelling of apple scab (Venturia inaequalis) will be used to illustrate the strengths and weaknesses of different approaches and their contribution to disease management.
A common fallacy is that modelling demands data before it can start. There are many examples of models which have been formulated at an early stage of, and indeed provided the initial stimulus for, an experimental programme. The decisions made by researchers on which directions to follow can be influenced by modelling. In recent years there has been a productive exchange between theoretical models from human/animal epidemiology and plant epidemiology. A fundamental quantity derived in these models (but with antecedents in plant disease) is that of the basic reproductive number. This quantity will be defined and illustrations made of its use for making strategic decisions, in particular in relation to some of the more difficult problems in plant epidemiology: dealing with inter-organismal interactions; combining population dynamic and genetic approaches; integrating different control practices; and quantifying epidemic processes below ground. The availability of powerful computing facilities and the development of numerical algorithms have expanded greatly our abilities to obtain qualitative and quantitative insights into the consequences of different disease management decisions.
SD Garrett (1970) summarized his views on the concepts of inoculum potential in relation to infection and colonization of a substrate, both dealing with 'energy of growth'. These concepts have proved useful for soil-borne pathogens but have not found universal acceptance by epidemiologists because of essential problems in quantification. An energy-based model of soil colonization by a mycoparasite attacking a sclerotium-forming fungus will be outlined. This model bears similarities to the theoretical epidemic models but has physically consistent parameters and derived properties. It may be possible to redefine and operationalize the concept of inoculum potential, and to assess its relevance for decisions in disease management.