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Bird rarity in terra-firme forest: reality or imperfect detection?

Bird rarity in terra-firme forest: reality or imperfect detection?. Marconi Campos Cerqueira Gonçalo Ferraz, Claudeir Vargas, Christian Borges, Thiago Vernucci, Angela Midori, Marcelo Santos, Monica Ribas, Mario Conh-Haft. Fotos:Erik Johnson.

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Bird rarity in terra-firme forest: reality or imperfect detection?

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  1. Bird rarity in terra-firme forest: reality or imperfect detection? Marconi Campos Cerqueira Gonçalo Ferraz, Claudeir Vargas, Christian Borges, Thiago Vernucci, Angela Midori, Marcelo Santos, Monica Ribas, Mario Conh-Haft Fotos:Erik Johnson

  2. “Rare species play such a central role in conservation biology that the discipline has been defined as the science of scarcity and diversity “Soulé, 1986 • Hypothesis: - The ornithologist`s perception of commonness and rarity reflect the truth about forest patch occupancy by birds. • Conservation implications: - some common species may be mistakenly classified as rare.

  3. Rarity as occupancy : • Proportion of occupied sites, or occupancy, instead of abundance. • Positive interspecific correlation between occupancy and abundance – not only obvious but well documented (Gaston and Blackburn 1999) • Locally abundant species tend to occupy more places than rare ones. -

  4. Fiuí fiu fiitri

  5. Detection is not perfect ? ? ?

  6. Ovenbirds Trogons Woodcreepers Jacamars Puffbirds

  7. Antwrens Antshrikes Wrens Antthrushes Vireos

  8. Study area

  9. Methodology • 2 weeks of survey: • 1st week – Ten trained researches make 3-minute point counts in ten different trails simultaneously. • 660 point counts • 1980 min of observation • 330 km collective walk • 2nd week- playback of 16 species` songs in one more visit per point by one observer.

  10. Improve and measure observer skills • Prior training in the field • Memory training with ‘electronic flashcards’ • Memory retention test -> observer score • Observer score as covariate of detection

  11. Analysis • Parameter estimation(Occupancy and detection) Maximum likelihood • Hypothesis testing Models selection AIC the model with lowest AIC value provides the most parsimonious and best approximation of information contained in the data1 1(Burnham e Anderson 1998)

  12. Detection probabilities Example: Bucco tamatia p(playback+time) Naive estimate = 0,25 Estimated occupancy = 0,38 ±0.09

  13. Time of the day × detection (given presence)

  14. Observer score × detection (given presence)

  15. Playback ×detection (given presence)

  16. Occupancy for 20 species – final estimate

  17. So… are the birders getting it?

  18. So… are the birders getting it?

  19. Rarity team Sure they are getting it!

  20. Apoio

  21. Obrigado,thanks! marconi_cerqueira@yahoo.com.br

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