Wildlife Vulnerability Scenarios 

CENTRO DE INVESTIGACIONES EN BIODIVERSIDAD Y RECURSOS GENÉTICOS CIEBREG-COLCIENCIAS
JAGUAR CONSERVATION PROGRAM. WILDLIFE CONSERVATION SOCIETY-MESOAMERICAN PROGRAM
TROPICAL AGRICULTURAL CENTRE FOR RESEARCH AND HIGHER EDUCATION (CATIE-COSTA RICA)
GRUPO DE INVESTIGACIÓN EN HIDROCIENCIAS FACULTAD DE INGENIERÍA. PONTIFICIA UNIVERSIDAD JAVERIANA

CENTRO DE INVESTIGACIONES EN BIODIVERSIDAD Y RECURSOS GENÉTICOS CIEBREG
PONTIFICIA UNIVERSIDAD JAVERIANA

Radiotelemetry, explicit spatial modelling using cellular automata

Wildlife conservation and management inside and outside Regional Protected Areas System in order to obtain Biodiversity goods and services to human communities

Establish Conservation Units (CU) in the areas adjacent to the Ucumarí Regional Park (PRU) and the Flora and Fauna Sanctuary Otún Quimbaya (SFFOQ), integrating historical and evolutionary ecology within conservation biology in a spatial and conceptual vulnerability scenarios model.
1)Identify amphibian and lizard adaptations within an historical-phylogenetic approach.
2)Identify endemic species and areas of endemism based on amphibians and lizards.
3)Identify mammal habitat quality, inside and outside the protected areas.
4)Predict the production systems effects scenarios on biodiversity (patterns and processes based on historical and evolutionary ecology).

Determination of CUs will be based on the risk factors which affect the relationship between the protected areas and the surrounding productive areas.
The proposal constitutes explicit spatial modeling based on cellular automata which incorporate information from:
1) Identification of endemism and / or historical relationships between groups of amphibian and reptile species, based on the hypothesis that the taxon history of a given area of endemism must be equal for any of its biotic components.
2) Determination of mammal habitat quality, assuming that the abundance and distribution of this group is dependant upon habitat characteristics, (Mackey & Lindenmayer 2001).
3) Characterization of the current productive systems in the area, accounting for natural resources exploitation by humans.

This methodology will integrate the ecological (historical and evolutionary habitat quality maps), and socioeconomic variables (social maps) using a series of transition rules within a spatial and temporal model (Peck 2001, Carter & Finn 1999, Low et al. 1999). Habitat quality maps and social maps will be elaborated for the study area using Geographic Information System programs (GIS) and will be calibrated using geostatistics unsupervised (Jimenez 2003, 2001) and supervised classifications (Savitsky 1998a,b,c).

Fuzzy logic and decision trees will be used to establish relationships between measured variables and criteria inside cellular automata (Chen, 2004). A dynamic simulation model will then be developed using the Multi Agent System analysis and cellular automata (Bousquet & Lepage 2004, Bandini et al. 2001). During calibration the model will aim to optimize the number of rules, some rules may change, others disappear and new ones may appear. Optimum mathematical algorithms will be employed to overcome combination criteria (in the proposal 211). Through these operations the number of combinations most suited to the model will emerge (simulated annealing, Obregón com pers, Fragala & Obregón 2002, Obregón et. al 2002). The aforementioned relationships may be observed as dynamic maps where some habitats will augment, others decrease and some disappear through time, with the corresponding biodiversity consequences. Those analyses could be conducted based on spatial pattern quantification using fractal analysis and multiple resolution moving windows (Chen, 2004).

Habitat Quality Maps, Social Maps, Vulnerability Scenarios Analysis Model