Modeling Conservation Priorities in Veracruz, Mexico

1. Modeling Conservation Priorities in Veracruz, Mexico Jeff Malone

2. The Problem • Designation of conservation and protection usually based on factors such as: • Historical significance • Recreational use • Scenic beauty • Protection of wetlands, forests, watersheds • Biodiversity is usually NOT taken into account

3. The Solution • Efforts to ID gaps in biodiversity protection • Map predictions of species distribution • Compare to protected areas • For example… Long Tailed Sabrewing

4. Northeastern Mexico Case Study • Species distribution modeling of preservation systems • For 19 bird and mammal species • Distributions were modeled • Gaps in protection identified Possible solution developed for enhancing protection of species Red-Crowned Parrot

6. Methodology • 2 types of data used • Species distribution data • Environmental attribute data (in raster GIS architecture) • Species selected have primary native habitat in Veracruz, Mexico • Selection as well as distributional data based on literature and observations Bearded Wood Partridge

8. Methodology Continued • Thematic geographic layers used to define environmental variables • Combined to create single image file • Then for each species distribution point, the values for each geographic layer were extracted Crimson- Collared Grosbeak

9. Methodology Continued • Those values from the geographic layers were used to create a 6-dimensional box • Its limits represent the defining criteria for species distribution • Used to select pixels in study area meeting same criteria Mexican Black Agouti

10. Also known as a ‘parallelepiped’

11. Methodology Continued • The 6 layers a filtered through a decision rule • To produce a predicted distribution map • Which was plausibility tested based on field knowledge • 6 species were overestimated in the literature • Areas of overestimation were set to zero in the GIS distribution maps Tawny-Collared Nightjar

12. Decision Rule Filtering

13. Methodology Continued • Final Step: optimal reserve system was identified based on predicted distributions • Buffer was created around each predicted distributional pixel • All buffered species maps were summed to create a map of species richness • More species in an area, higher conservation priority • Species present were removed, summed remaining species maps to ID next conservation priority

14. Black dots = known presence Dark gray = predicted location Light gray = apparent overestimations

15. Methodology Continued • For comparison, existing protected areas were evaluated the same way • Each protected area evaluated for species richness Mexican Sheartail

16. Results • Existing preserves buffered to 100,000 ha • Raster GIS overlay operation used to compare protected areas to species richness • Of 19 species, 12 are found in currently protected areas Dwarf Jay

18. Results Continued • Identified reserve system ignoring current one • 16 species in 4 reserves, all 19 in 7 reserves • But cannot ignore/scrap current preserves • Alternative is to complement existing preserves with unprotected species • By adding 5 of the potential preserves from optimal model, all 19 native species could be protected • More plausible to take a hybrid approach Altamira Yellowthroat

19. Black dots = existing preserves Dark gray = potential new preserves (1,3,5,6 and 7 combined would protect all 19 species)