Biodiversity Information Systems: Designing a www-based spatial
information system
David Pereira Jerez
Departamento de Proyectos y Planificación Rural
Universidad Politécnica de Madrid
Abstract
We present an information system prototype oriented to store biodiversity spatial information.
The system is fed and requested using www. It allows incorporation of information from
different sources and methods making it accessible to public, extending the number of
potential users and providing a valuable conservation policies tool.
The system is developed using a wide approach considering information needs fulfilling
biodiversity, conservation and sustainable development policies demands, to provide a
database structure and a new user-based approach. We also take into account current
biodiversity and geographical information metadata standardisation processes and actually we
are testing the system using several Spanish endangered steppe birds.
Besides some information lacks we also observe important dispersion and heterogeneity
limiting information utility. Usually basic information is needed (presence, density,
abundance, population size, richness, habitat, evolution, determinant factors) that is not
scientific production result but gross input (census) or intermediate products. Therefore it
doesn't exist sufficient available information or clear incentives to share or standardise it. The
way to involucrate scientific community in this kind of project is to incorporate a scientific
distributed work system. We'll incentive information input if scientists can use prototype as a
more complete database and analysis software. That is what we identify information needs at
this level (usually with more severe quality restrictions) and biodiversity spatial analysis
methods.
More users also help to justify system existence and maintenance. Therefore the system
permits other uses like consulting services depending on biodiversity related information
(EIA, SEA, landscape planning, sustainable development planning). Finally, request
possibilities by Internet guarantee a quick and wide public access useful as a tool in
sensitisation and education about biodiversity conservation problems.
Introduction
Over the last decades, a growing number of biological conservation initiatives have been
developed according with population worry about species conservation and generalised lost of
habitat quality. Biodiversity information is always a central point of these schemes but, while
information needs are always marked as a relevant objective at any conservation policy, some
practical problems are addressed and sometimes, available information grows slower than
policy expectations and requirements.
Until 1994 the most important conservation tool, the IUCN conservation status categories, is
based on expert qualitative opinion. However, in 1994, IUCN conservation status categories
were modified, changing a qualitative expert evaluation for a quantitative rules set (IUCN;
1994, 1996). This change promotes quantitative analysis of biodiversity conservation and
both regional and national initiatives to supply data needed. Thus, population size, area of
occupancy and population trends must be known for all biological species with any kind of
threat. As a global initiative one of the biggest problems is information standardisation and
classification at all levels, beginning with taxonomic databases.
According with its bio-geographical position, Spain has a specific problem in this field. It has
149 species catalogued as endangered species, 5 as sensitive to habitat modification, 9 as
vulnerable and 363 as with special interest (Ministerio de Medio Ambiente, 1.999). In
addition we have a great number of locally rare species, endemic species and others regionally
protected. Therefore one of the most important research objectives is to provide biodiversity
information about rare species status and conservation. Universities and research centres
develop research programs with endangered species especially at regional levels but
coordination and standardisation efforts are still too poor.
Information technologies can play an important role but some difficulties exist regarding
scientific methods and efforts. Independently of any institutional initiative this work begun as
a conceptual reflection about biodiversity information standardisation, public access and the
way to involucrate scientific community in the process. This paper discusses some
implications for information systems design process and how we broach the problem.
Information needs
The first step of BIS design process is to identify information needs. In this case we have been
working both at international and national levels analysing documents from IUCN (IUCN
1994, 1996), Subsidiary Body of Scientific, Technical and Technological Advice (SBSTTA,
1996, 1997) dependent form Biological Diversity Convection and Species Survival
Commission (SSC, 1997, 1999) dependent from IUCN. We consider also Spanish
Environment Ministry documents (Ministerio de Medio Ambiente, 1996, 1999) for Spanish
national biodiversity information priorities.
IUCN new red list categories (IUCN, 1994, 1996) are the best example of biodiversity
information requirements at both policy and technical level. These criteria rules sets are
mainly quantitative and must be achieved for all species under some threat. Most vertebrate
species must be evaluated using it at both global and regional level.
The UICN categories, ordered from higher to lower extinction risk, are: extinct, extinct in the
wild, critically endangered, endangered, vulnerable, minor risk, data insufficient and non
evaluated. Minor Risk categories are divided in three subcategories: Conservation dependent,
Near Threatened and Least Concern. Table 1 shows the quantitative criteria for threatened
categories.
Category
Critically Endangered
Endangered
Vulnerable
Criteria
1) 80% population observed, estimated, projected or suspected
reduction in 10 years or 3 generations
2) Extent of occurrence estimated to be less than 100 km2 or area of
occupancy estimated to be less than 10 km2 and estimates indicating
severe fragmentation, a single population, continue decline or
extreme fluctuations
3) Population estimated to number less than 250 mature individuals
and either an estimated continuing decline of at least 25% within 3
years or one generation, a continuing decline with severe
fragmentation or a single population
4) Population estimated to number less than 50 mature individuals
5) Quantitative analysis showing the probability of extinction in the
wild is at least 50% within 10 years or 3 generations
1) The same criteria with decline of at least 50%
2) The same with extent of occupancy less than 5.000 km2 or area of
occupancy lest than 500 km2.
3) The same with population less than 2.500 mature individuals
4) The same with population less than 250 mature individuals
5) The same with probability of extinction at least 20% within 20
years or 5 generations
1) The same criteria with decline of at least 20%
2) The same with extent of occupancy less than 20.000 km2 or area
of occupancy lest than 2.000 km2.
3) The same with population less than 10.000 mature individuals
4) Population less than 1.000 mature individuals, area of occupancy
less than 100 km2 less than five locations
5) The same with probability of extinction at least 10% within 100
years
Table 1. IUCN categories quantitative criteria
IUCN categories were designed to be applied at a global label, but can be used at a regional
levels with two exceptions: 1) A new category, Regionally Extinct, can be used when all
reproductive individuals have disappeared; 2) the category Extinct in the Wild should be used
only if specie are regionally extinct but extant in cultivation, in captivity or as a naturalised
population (SSC, 1997). A logical consequence of this possibility is quantitative criteria
transposition to national categories based usually on expert opinion.
More information needs can be founded in documents developing environmental indicators
and environmental accounting systems. This point of view is extent calling for information
concerning with biodiversity condition but also biodiversity threads causes and management
measures effectiveness. This is strongly related with Biodiversity Convention mandates
(figure 2).
Figure 2. Relationship between state-pressure-response indicators and Convention on
Biological Diversity articles (SBSTTA, 1996, 1997)
The development and use of indicators can be a key focal point in capacity-building efforts,
whereby the entire data and information infrastructure and decision-support mechanisms are
energised to deliver policy-relevant information (SBSTTA, 1996).
Information needs are divided into direct data resulting from biodiversity monitoring and
aggregated data resulting from direct data analysis. According to IUCN rule set, Spanish
National Biodiversity Conservation Strategy (Ministerio de Medio Ambiente, 1999) and other
technical documents from SBTTA and SSC. Tables 3 and 4 summarise the main information
needed in both cases.
Data type
Reference data
Observations
Data for cataloguing information
Presence
Presence or absence in a specific spatial
unit
Number of individuals of a specific
subpopulation
Subpopulation size
Abundance/density
Any relationship between subpopulation
size and subpopulation area of occupancy
Abundance indexes cab be used as a
relative measures without absolute
reference to subpopulation size
(1) Dependent from taxon
Database fields
Census Code
Taxon
Date
Author and/or Working Team
Presence Geographical coordinates
Number of individuals or other
species dependent unit.
Subpopulation limits geographical
coordinates
Subpopulation limits geographical
coordinates
Subpopulation size
Abundance index (1)
Table 3. Direct information needs
Data type
Population size
Observations
The total number of individuals of the taxon
assessed (SSC, 1999)
Extension of occupancy Extent of occurrence is defined as the area
contained within the shortest continuous
imaginary boundary that can be drawn to
encompass all the known, inferred or
projected sites of present occurrence of a
taxon, excluding cases of vagrancy. This
measure may exclude discontinuities or
disjunctions within the overall distributions
of taxa (e.g., large areas of obviously
unsuitable habitat)
Area of occupancy
Area of occupancy is defined as the area
within its 'extent of occurrence' (see
definition below) which is occupied by a
taxon
Trend
Differences between observations at several
moments
(2) Working scale is dependent from taxon
Database fields
Subpopulation size
Abundance index
Presence geographical
coordinates
Presence geographical
coordinates (2)
Population size
Date
Table 4. Aggregated information needs
Other information like reproductive status or habitat depends strongly on species or species
groups. Despite some common basic data (see tables above), data can be adapted to different
species groups using specific classification methods. For steppe birds we are configuring as
basic data New Spanish Reproductive Bird Atlas template consisting in some qualitative
categories for reproductive status. This is an official initiative conducted by Spanish
Environment Ministry and Spanish Ornithological Society at national level and restricted to
this kind of bird.
General System Structure
BIS structure is divided in two subsystems:
 The first one conduces data entry and scientific work with original data. This
subsystem standardises basic information and stores it in a another database
 The second one permits users to query database showing data reports and maps.
Figure 5 shows subsystem principal components. Red text represents main tasks: data
configuration, data input, and data query. Circles represent relational databases. Yellow
databases are knowledge base stored at the information system and white databases are user
data storage databases. User specific methods and templates can be stored and marked as
private methods.
Figure 5. BIS general structure
Some database tables are common to both subsystems because they store and codify general
reference information as taxonomic, authors and teams or bibliographic information. All
tables have relationships between them to permit scientists (first subsystem) and professionals
(advanced data in second subsystem) to find:
 Authors and teams working with specific species
 Bibliography related with specie conservation state and biology
BIS data input and scientific work subsystem is designed to manage data input and data
standardisation. Three database groups store knowledge information regarding census
techniques and inference and standardisation methods.
Figure 6 is an example of user action - software responses chains. Similar processes are being
developed for data treatment, filter and debugging, statistical analysis, inferential of new data
and standardisation. Several methods can be used and more can be added to system.
Figure 6. User action - software responses chains
The BIS data query subsystem collects standardised basic species information and aggregated
results. Processed information is stored at the same time at several geographic scales to
facilitate and to improve database query. Lowest scales are used for general purposes and
public access but information referred to 1x1 km grid is reserved to scientific and professional
uses.
Www-based design
Biodiversity database can be queried through Internet. For this purpose the information
system has a WWW interface of html pages designed for both data input and query results
reading. Upgrade work can be performed using data forms and templates, however an html
page reload is required for each small update, retrieval or calculation operation (input of a
new record, query modify, mathematics operation, etc). With a large amount of data, data
input can be a quite slow operation with few possibilities to correct errors.
To resolve this problem BIS has an alternative way of data input. By this way, the user can
work off-line and therefore data entry is independent from network speed, performance or
reloads. Users only have to work on-line when they want to update or query database
information. BIS provides a Visual Basic application connected to a local database and is
capable of synchronising information between local and external databases, updating external
data and transferring information. Information stored at local and external databases is shown
at the same time and user can work while external database data is downloading. When the
user decides to update the information, a Visual Basic application prepares html pages to send
them as data form. Figure 7 shows both working methods:
Figure 7. Alternate systems of distributed work at BIS
All data stored in each session can be updated at the external database in a single operation
and therefore it results in a faster process. Other advantages of this distributed structure are:
 Greater interface possibilities using Windows software rather than html pages,
especially when the user repeats several times the same action, copies and pastes
tabular data, or fills different cells with the same data.
 User stores his own information in a local database
The role of Geographical Information: Spatial variables
Biodiversity information always has a strong spatial component. BIS data query subsystem
information is always georeferenced. Thus BIS spatial component has a very important role
inside the system. Most part of data queries reports maps as a result or tables with columns
dedicated to spatial information, therefore data input subsystem must be capable to acquire,
manage and store spatial reference for information.
Figure 8. Spatial information functions, databases and formats
Another important role of spatial information is data spatial inference. Usually field data are
samples and must be interpolated using habitat, land-cover or bio-geographical datasheets.
Users can utilise their own coverages adapted to census methods and species significant
variables but the system utilises Corine-LandCover categories as reference units. The main
purpose is to provide an easy way to interchange information among different methods.
Users point of view: scientific and professional work and public access
Figure 9 shows the hierarchical access structure for main kind of users and access policy. This
structure reflects user functions and interests. Free access is provided to basic data at
appropriated scale to prevent conservation problems, advanced quality information is
provided for professional use and finally full access is possible to scientific and
administration purposes.
Figure 9. User system utilisation
Public access
Internet possibilities for communication and providing public access are well known.
Therefore, like other WWW-based designs BIS could be good for public information. Data
availability is restricted to gross scale to prevent conservation problems such as illegal
harvesting. Data input or finest queries requires authorisation.
Consulting and professional use
Other uses such as consulting services require data availability at finest scales. BIS can
provide it but it is designed to control and monitor data access and use to prevent abuse.
Biodiversity information system as scientific work and research tool
Despite data input BIS data input and scientific work subsystem can be used as a scientific
and research tool. This kind of use is based on three components:
 BIS stores multiple census and inference methods and other new techniques can be
added to database by scientists. Therefore BIS is useful software to scientific data
management.
 Through BIS, scientists can access crude data from census provided by other
working groups. Thus more basic data is available for analysis. Usually it is
precedent from different regions.
 Uncertainty management and decision-making according with uncertainty level
Data available for endangered species is often very poor and a great deal of current research is
devoted to developing methods to incorporate and quantify the uncertainty in the data
(Colyvan; Burgman; et al, 1999). Thus BIS provides some uncertainty treatment. Data is
divided into six categories according to its uncertainty level:
 Direct quantitative observation data
 Inferred data with statistic uncertainty estimation
 Direct qualitative observation data with expert uncertainty estimation
 Inferred data with qualitative expert uncertainty estimation
 Direct qualitative data without uncertainty estimation
 Inferred data without uncertainty estimation
If BIS finds some divergences among data from different sources it selects lower uncertainty
level data. Higher uncertainty level data is marked as possibly wrong. For some purposes
(scientific and professional work) the user can select only data with fixed uncertainty level.
References
Colyvan, M., Burgman, M. A., Todd, C. R., Akçakaya, H. R. & Boek, C., “The treatment of
uncertainty and the structure of the IUCN threatened categories”. Biological Conservation Vol 89, PP.
245-249, 1999
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IUCN, Red list of threatened animals, Gland Switzerland, IUCN, 1996
Ministerio de Medio Ambiente, Sistema español de indicadores ambientales: subáreas de
biodiversidad y bosque, Madrid, Dirección General de Calidad Ambiental, 1996
Ministerio de Medio Ambiente, Estrategia Española para la conservación de la Biodiversidad,
Madrid, Dirección General de Calidad Ambiental Madrid, 1996
Species Survival Commission, Draft Guidelines for the application of IUCN red list criteria at
national and regional levels, http://www.iucn.org/themes/ssc/guidelines.htm, 1997
Species Survival Commission, IUCN red list criteria review provisional report. Draft of the proposed
changes and recommendations, IUCN/SSC Criteria Review Working Group,
http://www.iucn.org/themes/ssc/provisional.htm, 1999
Subsidiary Body of Scientific, Technical and Technological Advice (SBSTTA), Indicators for
assessing the effectiveness of measures taken under the convention. Montreal, Canada, SBSTTA
second meeting, 2 to 6 September, Doc SBSTTA/2/04, 1996
Subsidiary Body of Scientific, Technical and Technological Advice (SBSTTA), Recommendations for
a core set of indicators of biological diversity, Montreal, Canada, SBSTTA third meeting, 1 to 5
September, Doc SBSTTA/3/13, 1997