|| 要旨トップ | ESJ69 シンポジウム 一覧 |||日本生態学会第69回全国大会 (2022年3月、福岡) 講演要旨
シンポジウム S20 3月19日 9:00-12:00 Room A, 現地開催/ライブ配信あり
Quantifying biodiversity is among the fundamental challenges in ecology and a range of related disciplines, including community ecology, evolutionary biology, and conservation biology. The growing accumulation of data on ecological communities has broadened our ways to understand and predict the changes in biodiversity across space and time. To make further use of such datasets, researchers have been increasingly motivated to develop new theories and statistical and computational methods.
In this symposium, we share a series of recent advancements in biodiversity theories and methods as well as their applications to real-world data. Specific examples include standardization of diversity metrics, additive partitioning schemes, formal theoretical toolboxes, and dealing with uncertainty and environmental stochasticity. The goal of the symposium is to improve our analytical abilities and stimulate discussion about the spatiotemporal organizations of biodiversity. We believe this symposium will provide a critical step toward preventing and reversing the human-induced biodiversity changes that are currently occurring at unprecedented temporal speeds and spatial extents.
1. In this symposium, held in English, the speakers will try their best to talk slowly and clearly to minimize the potential language barrier.
2. Questions are appreciated and highly encouraged, especially from early-career researchers. We are here to help you.
The iNEXT.beta standardization via rarefaction and extrapolation with beta diversity for spatial and temporal data
Partitioning the extinction and colonization components of beta diversity
A unifying framework for the equilibrium theory of island biogeography and dynamics of biodiversity
Re-creating food webs at the continental scale: statistical uncertainty, data scarcity, and the promises of transfer learning
Predicting coexistence outcomes in natural systems: impacts of demographic uncertainty and environmental variation