1. Geographic Information Systems (GIS) and the Conservation and Use of Plant Genetic Resources
Summary of
DIVA-GIS is a free mapping program, (GIS), that can be used for many different purposes. It is particularly useful for mapping and analyzing biodiversity data, such as the distribution of species, or other 'point-distributions'. 

2. Geographic Information Systems
Said in a simple way: ‘a tool for managing information of any kind according to where it is located’
Main elements:
Data input, verification and editing
Importing digital datasets
Data storage, retrieval and management
Stored as data: vector and raster
Data manipulation and analysis
Bring diverse datasets together, make them compatible and combine and analyze them
Output
Selecting areas or layers for output on a screen

3. Ecogeographic surveying
Source of of information of such survey can be:
Herbarium specimens
Germplasm accessions passport data
Experts
Literature
Field notes
Maps

4. Ecogeographic surveying – main objectives
Identifications of geographic areas which are:
Likely to contain specific desired traits (adaptations), taxa or habitats of interest
Highly diverse (whether environmentally, taxonomically or genetically)
Complementary to each other
Currently missing or under-represented in conservation efforts
Threatened with genetic erosion

5. Output: An example: Distribution of Oryza longistaminata
In southern Africa.
Images, aerial photographs,
satellite imagery, and radar images
combined with other sources of data

6. High diversity areas
Usually begins with dividing the target area into a number of smaller zones e.g. climate zone
Different geometric, political, socio-economic spatial units have been used
More examples: presence/absence of species, measures of diversity based on morphological characters or molecular markers (to calculate the morphological diversity of Capsicum spp)

7. Complementary areas Analyses of diversity
E.g. compare two areas to see if they have the same diversity of taxa or morphotypes
Can allow the diversity measure to be weighted for the distinctness of taxonomic units (thus calculate diversity values, e.g. taxa closely related or not)

8. Under-conserved areas
Identify individual species, species-rich areas and vegetation types that are not represented or underrepresented
To identify ecogeographical gaps in existing ex situ germplasm collection

9. Threatened areas
To predict genetic erosion by documenting and modeling changes of forests, wetlands, different land use types and cropping
Indicators of desertification, soil erosion, increasing outmigration, and appearance of new fields of agriculture into increasingly marginal areas
Can use result to early warning of crop failure and famine in regions of the world
Use sources of remote sensing imagery, agricultural censuses, news report and fieldwork

10. Analyses To map different areas from different datasets
A case study from four separate analyses, from which the results are combined to produce a single map of priority areas for conservation interventions (se next slide)

11. High priority areas for conservation of wild Gossypium in Africa
The methodology involves four separate analyses
Probability of high diversity (localities of 607 herbarium)
Targeting geographical gaps in existing collections
Proximity to roads
Genetic erosion risk assessment (population growth, high density of cattle etc.)

12. GIS technology can contribute with Field work
Field aids
Moisture and temperature maps
Identification of ecogeographic gradients, like slope
Optimal timing of field visits
Rainfall
Surveillance of the state of crops and vegetation over the growing season

13. Design, management and monitoring of in situ reserves
An example of establishing, Masoala National Park in Madagascar using combining maps, satellite imagery, biodiversity surveys and population studies:
Rare and threatened habitats and species
Park should follow features with buffer areas
Park should balance human and wildlife needs

14. Germplasm regeneration and evaluation
To decide what sites are best for which accessions
Climate data and distribution maps for:
Pests
Diseases
Pollinators
Wild relatives
Help to determine unique needs of individual accessions

15. Use of genetic resources GIS can:
Improve quality and quantity of the locality data from collections
Help the genebank curator to complete passportdata (maps and gazetteers, collectors notebook)
Targeting specific areas for evaluation and use, based on the conditions where the accession was collected. E. g. maize that might be adapted to alkaline soils.

16. Prospects
GIS based analysis of data on germplasm accessions add greatly to the value of data
Examples
More frost tolerant potato variety by using climatic data
Climatic data to identify areas where further germplasm collections should be done
Cost–effective of conservation efforts
Facilitate use of germplasm by breeders and others
Still very important:
Solid documentation
Effective management systems
Lots of data to manage