Assessing conservation priorities: the African Vertebrates Databank (AVD)

Istituto di Ecologia ApplicataVia L.Spallanzani, 3200161 Rome ITALYemail: iea@mclink.it

Luigi BoitaniDept. Animal Biology, University of Rome

Participating Institutions

• IUCN/SSC• Conservation International - CABS• Natural History Museum – London• University of Cambridge• Natural History Museum – Copenhagen• Birdlife International• Istituto di Ecologia Applicata• University of Rome

Project goals

• Produce a continental scale conservation tool for African vertebrates

• This major goal is achieved by:– building a data bank on African vertebrates with the

aim of providing the raw data for future applications and analyses on conservation options and priorities

– modeling actual and potential species distribution

Conservation Needs• Broad scale planning (eventually global)

– Metapopulation approach– Identification of core areas and corridors– ….

which implies– Detailed knowledge on actual species distribution– Extensive data on species ecology and biology– Spatially explicit predicting tools

GIS modeling

Cost effective approach Maximizes the information obtainable from

the few data sets available Updateable distributions Repeatable approach

Three (four) pieces of information

Species Extent of Occurrence Environmental variables Species-environment relationship

+ Validation data set and procedures

Other projects with similar approach:

• African Mammal Databank (1999)• Ecological Network for the Italian

Vertebrates (current)• Asian Mammal Databank (submitted to the

EU)

Distribution modeling

• AVD integrates two (maybe three) levels:– "Blotch" distribution– Categorical-Discrete distributions obtained

through a deterministic approach based on GIS overlay procedures

and maybe– Probabilistic-Continuous distribution models

based on statistically supported GIS overlay procedures.

“Blotch” distribution

Extent of Occurence of the CheetahAcinonyx jubatus

certainpossible

Categorical Discrete Model

Area of Occupancy of the CheetahAcinonyx jubatus

Probabilistic Continuous Model

Suitability surface for the CheetahAcinonyx jubatus

Categorical Discrete ModelValidation

• The AMD project was validated with field work carried out in four selected countries in Africa

•Botswana, Cameroon, Morocco, Uganda• 427 plots were allocated at random within the four

countries• The presence/absence of each species at each of the

predetermined points was verified by:•direct observation•in loco collection of publications and scientific reports•interviews with local experts/authorities/inhabitants

• In each country a team composed by a researcher from a local Institution and one IEA staff member carried out the field work

Categorical Discrete ModelValidation

Validation parameters

Valid plots = all plots falling inside the Extent of Occurrence + all other plots in which the species was found during field work

Index of Accordance = Percentage of valid plots in accordance with the Categorical Discrete model

Categorical Discrete ModelValidation

• The AVD limited budget resources will prevent direct field work

• Similar scheme will be implemented using known species locations from bibliography

Categorical Discrete ModelProducts

suitable moderately suitable unsuitable TotalOCCURRENCE km2 % km2 % km2 % km2 %

certain 4 736 158 49 3 741 586 39 1 041 932 11 9 519 676 98

possible 46 130 0 63 110 1 61 065 1 170 305 2

Total 4 782 288 49 3 804 696 39 1 102 997 11 9 689 981 100

Surfaces and percentage of each suitability class within the Extent of Occurrence of the cheetah (Acinonyx jubatus)

Categorical Discrete ModelProducts

Number Patches(NP)

Mean Patch Size(MPS)km2

Patch Size SD(PSSD)

km2

Largest PatchIndex (LPI)

%

Mean ShapeIndex (MSI)

Area-WeightedMean Shape

Index (AWMSI)

suitable 3 569 1 348 40 385 18.73 1.26 24.17

moderately suitable 4 425 873 18 920 10.94 1.33 19.1

Total AO 614 14 127 309 897 88.53 1.25 20.87

Fragmentation indexes of the Area of Occupancy (all suitable and moderately suitable areas) of the cheetah (Acinoyx jubatus)

Categorical Discrete ModelProducts

Efficacy of protected areas for the speciesVulnerable (VU: A1d+2d,C1) as A. jubatusEndangered (EN: C2a, D1) as A. j. hencki NW African cheetah

Management tools

• The different types of distribution models produced can be included in management tools of increasing information content:– Blotch distribution

• hot spots identification• effectiveness of protected areas

– Categorical Discrete Distribution Model• population fragmentation • management strategies for conservation

– Probabilistic Continuous Distribution Model• metapopulation PVA• corridors identification

Mammals biodiversity hotspots281 species of large mammals

Mammals biodiversity hotspots281 species of large mammals

AMD Products• a printed volume containing for each of the 281 species:

• Taxonomic notes• IUCN threat category• Available ecological information• Bibliography• Extent of Occurrence (“Blotch”)• Categorical Discrete Model• Probabilistic Continuous Model• Comments and conservation issues

• set of 10 CD-ROM with the digital version of all the above information

• web site with all data sets:– www.gisbau.uniroma1.it/amd

AVD: where we are ?• Mammals:

– Rodents– Bats– Insectivores– Others…

• Birds• Amphibians• Herps

– Snakes– Lizards– Others ?

• Fishes ??

Why modeling? And how• Purpose of distribution maps

– ….– …. conservation: maps must be current and at the appropriate

resolution/scale for each taxon• Maps ARE models !!• Increasing distribution information:

– Points (if qualified: date, accuracy, species biology) (good for transformation into blotches and/or for inductive modeling and/or for model validation)

– Polygons (if qualified)– Grids (if all cells are qualified)– Models (if validated)