The Automatic Ornithologist: A New Website for Predicting Amazonian Bird Species Composition by Locality Mario Cohn-Haft Rolf A. de By Catherine L. Bechtoldt Kleberson J. A. Serique José Laurindo Campos dos Santos

Describe site species composition: 1. Survey/inventory 2. Extrapolation/interpolation: Predictive modeling

Surveys incomplete Time No. species

Predictive bird species occurrence 1. Geographic range 2. Habitat use

Predicting bird species occurrence: 1. Geographic range 2. Habitat use We know this for birds!

Predicting bird species occurrence: 1. Geographic range Ridgely maps in Infonatura (2007) 2. Habitat use Parker database in Stotz et al. (1996) Neotropical Birds

GIS query - Consulta SIG

~1200 spp. Amazônia Brasileira

The Automatic Ornithologist O Ornitólogo Automático

The Automatic Ornithologist O Ornitólogo Automático Bilingual website: On-line GIS platform Linked to avian distribution database Using free software

The Automatic Ornithologist

Data quality?

1. Geographic range Ridgely maps in Infonatura (2007) 2. Habitat use Parker database in Stotz et al. (1996) Neotropical Birds 3. Taxonomy Comitê Brasileiro de Registros Ornitológicos (CBRO)

Data quality? 1. Geographic range Ridgely maps in Infonatura (2007) 2. Habitat use Parker database in Stotz et al. (1996) Neotropical Birds 3. Taxonomy Comitê Brasileiro de Registros Ornitológicos (CBRO)

Data quality? 1. Geographic range Ridgely maps in Infonatura (2007) 2. Habitat use Parker database in Stotz et al. (1996) Neotropical Birds 3. Taxonomy Comitê Brasileiro de Registros Ornitológicos (CBRO)

Data quality? 1. Geographic range Ridgely maps in Infonatura (2007) 2. Habitat use Parker database in Stotz et al. (1996) Neotropical Birds 3. Taxonomy Comitê Brasileiro de Registros Ornitológicos (CBRO)

Black Antbird (Cercomacra serva) Chororó-preto

Spot-backed Antwren (Herpsilochmus dorsimaculatus) Chorozinho-de-costas-manchadas

New data

Spot-backed Antwren (Herpsilochmus dorsimaculatus) Chorozinho-de-costas-manchadas Interfluve model

Who will use? What for?

1. Scientific research

Species richness patterns

Distributional boundaries

Who will use? What for? 1. Scientific research 2. Policy and decision-making

Who will use? What for? 1. Scientific research 2. Policy and decision-making 3. Tourism

Whats next?

1. Distributions based on complex models greater spatial precision probability of occurrence

Whats next? 1. Distributions based on complex models greater spatial precision probability of occurrence 2. Collaborations with other data providers e.g., museum specimen point data 3. Citizen science: user data contribution shared map authorship 4. Expanded geographic coverage international Amazon-wide collaborations

Surveys incomplete Method No. species

Predictive modeling 1. Highly dependent on existing data quality 2. Overestimate (false presences) 3. Underestimate (false absences) 4. Testing depends on surveys