Geographic Information Systems (GIS) and the Conservation and Use of Plant Genetic Resources Summary of http://www.diva-gis.org/docs/gis_pgr_conservation.pdf 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'. 

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

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

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

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

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)

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)

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

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

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)

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.)

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

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

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

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.

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