東京大学大学院 新領域創成科学研究科 国際協力学専攻

第9回DOIS研究セミナー:Nicholas Friedman 博士(ハンブルク自然史博物館),Jamie Kass 博士(東北大学)


日時:2023年6月1日(木)15:45-17:15
場所:柏キャンパス環境棟7階講義室とZoom

 

講演者1:Nicholas Friedman博士(ハンブルク自然史博物館,キュレーター)
講演タイトル:Evolution across environmental gradients: how birds respond to changes in climate and disturbance

 

講演者2:Jamie Kass博士(東北大学大学院生命科学研究科,准教授)
講演タイトル:Predicting future ecosystem service potential with biodiversity models

 

要旨(講演1)

As environmental conditions change, individuals that are better able to survive and reproduce in the new conditions will contribute more offspring to the next generation. This evolutionary process leads populations to adapt to local conditions, occasionally diverging from their original population and phenotype. Environmental gradients offer a opportunity to study the evolutionary process, how it produces biodiversity over millions of years, and how it affects populations today. Here I describe studies on an environmental gradient in aridity in Australia, and how bird species have adapted to survive and reproduce in some of the world’s most inhospitable deserts. I also describe studies on an environmental gradient in human disturbance in Okinawa, and how human activity affects animal behavior and ecology.

 

要旨(講演2)

Many ecosystem functions and services (EFS) essential for human well-being are in danger of disruption due to environmental change. Pollination, pest control, waste decomposition, and flood attenuation, for example, are dependent upon particular species or functional groups, yet models that predict EFS have typically relied on biophysical variables such as land cover and topography. Considering the strong links between EFS and biodiversity, international consortia that advise on methods for predicting and mapping EFS now advocate strongly for including biodiversity models into workflows, though new methods are still adopted slowly. I will present on several methodological advances in biodiversity modeling and how they can be employed to help improve current and future EFS predictions.