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SUMMARY:Towards Global Maps of Anthropogenic Threats to Biodiversity and T
 heir Contributions to Species Extinctions - Emilio Luz-Ricca\, University 
 of Cambridge
DTSTART:20250321T130000Z
DTEND:20250321T140000Z
UID:TALK225559@talks.cam.ac.uk
CONTACT:114742
DESCRIPTION:*Abstract*\n\nSpecies extinctions are primarily driven by loss
  of habitat\, which is relatively easy to monitor by satellite remote sens
 ing\; other anthropogenic threats to biodiversity\, like hunting\, are muc
 h more difficult to observe directly. My PhD project draws on local studie
 s which capture the population effect of some anthropogenic threat\, scali
 ng these results using machine learning and remote sensing. In this talk\,
  I will discuss my first attempt at this through quantifying species-speci
 fic responses to hunting pressure. I find that machine learning methods ca
 n offer marked improvements over (linear) statistical models\, which are c
 ommonly used in ecology\, but model validation must be done carefully to p
 roperly contextualise predictive performance. I will preview my plans for 
 integrating these hunting pressure models with the LIFE biodiversity metri
 c framework to express pressure in terms of extinction risk. If there is t
 ime\, I will also discuss future plans for my PhD.\n\n*Bio*\n\nEmilio is a
  PhD student in the Department of Zoology at the University of Cambridge i
 n the Conservation Science Group and the Energy and Environment Group. He 
 is supervised by Andrew Balmford\, with co-supervision from Anil Madhavape
 ddy and Tom Swinfield. He is also part of the AI for Environmental Risks C
 entre for Doctoral Training\, a researcher at the Cambridge Centre for Car
 bon Credits\, and a member of Churchill College. His research focuses on t
 he uses of predictive modeling for biodiversity conservation\, with an emp
 hasis on quantifying species-specific responses to human disturbance.
LOCATION:FS07\, William Gates Building. Zoom link: https://cl-cam-ac-uk.zo
 om.us/j/4361570789?pwd=Nkl2T3ZLaTZwRm05bzRTOUUxY3Q4QT09&from=addon 
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