| 要旨トップ | ESJ71 シンポジウム 一覧 | | 日本生態学会第71回全国大会 (2024年3月、横浜) 講演要旨 ESJ71 Abstract |
シンポジウム S14 3月20日 9:00-12:00 Room D
To meet international biodiversity targets, such as the Kunming-Montreal Global Biodiversity Framework (KM-GBF), monitoring and reporting the status of biodiversity using standardized indicators presents a significant challenge. The Group on Earth Observations Biodiversity Observation Network (GEO BON) has undertaken the development and coordination of Essential Biodiversity Variables (EBVs). These EBVs constitute a set of observable variables for assessing biodiversity and ecosystems, and were designed to facilitate the collection and tracking of changes in biodiversity and ecosystems over time, ensuring the availability of consistent data that can be compared or integrated across regions and countries. Currently, a total of 21 EBVs are listed, covering six categories within the biodiversity hierarchy, from genes to ecosystem scales. This symposium aims to enhance our comprehension of the effectiveness of EBVs in monitoring terrestrial ecosystems and to further explore their contributions to achieving the goals of KM-GBF. Following the introduction the target of this symposium, we will be hosting four speakers who will introduce the latest trends and findings in biodiversity research relating to the EBVs over various scales and methodologies, and will discuss frameworks for biodiversity observation, policy implications, and future prospects.
We will invite a commentator who is a stakeholder of biodiversity-related policy.
[S14-1]
Introduction to the Symposium: What Are Essential Biodiversity Variables, and How Will Those Contribute to Achieving the Goals of the KM-GBF?
[S14-2]
Operationalization of Essential Biodiversity Variables for harmonized biodiversity monitoring – perspectives from Finland and Europe
[S14-3]
Ecosystem phenology and productivity EBVs – case studies on pest species modelling and habitat mapping in Finland
[S14-4]
EBVs at multiple scales – Combining field surveys and remote sensing for forest monitoring
[S14-5]
Predicting and mapping ecosystem services using biodiversity models and remote sensing data