BIOMAC participants: Daniel Kissling (PI), Postdocs and MSc students
We live in a world with rapid and unprecedented planetary changes. The ever-increasing consumption by humans and increased demand for energy, land and water, is driving a new geological epoch (the Anthropocene) in which nature and biodiversity are disappearing at an alarming rate. Several global agreements such as the Convention on Biological Diversity (CBD) and the UN 2030 Agenda for Sustainable Development have set policy targets (e.g. the Aichi Biodiversity Targets and the Sustainable Development Goals SDGs) to reduce the current rate of biodiversity loss and to conserve and restore nature and its ecosystem services. However, current efforts are insufficient to achieve these goals.
Enormous challenges therefore remain for detecting and reporting biodiversity change. With our research, we aim to contribute to the quantification and monitoring of global biodiversity change by (1) increasing the digital availability of biodiversity data (e.g. on traits, species interactions), (2) developing Essential Biodiversity Variables (EBVs) as harmonized data products for assessing progress towards national and international policy goals, (3) mapping and analysing ecosystem changes with newly available remote sensing time series, and (4) developing ecoinformatic tools and e-infrastructure that supports the analysis of the increasingly complex, multi-terabyte data sets needed to quantify global biodiversity change. With this work, we contribute to the Group on Earth Observations Biodiversity Observation Network (GEO BON) and the efforts to develop EBVs for quantifying biodiversity change at a global scale.
|Essential Biodiversity Variables (EBVs) allow to quantify spatiotemporal changes in species distributions and population abundances or other aspects of biodiversity. EBVs are part of an information supply chain, conceptually positioned between raw data (i.e. primary data observations) and indicators (i.e. synthetic indices for reporting biodiversity change to policy and management). Figure from Kissling et al. (2018) and Hardisty et al. (2019).|
Please also see our other research themes.