W. Daniel Kissling

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I am a quantitative biodiversity scientist with research interests in macroecology, ecoinformatics, biodiversity monitoring, and global change. I am working at the Institute for Biodiversity and Ecosystem Dynamics (IBED) of the University of Amsterdam (UvA), The Netherlands, where I lead the Biogeography & Macroecology (BIOMAC) lab embedded in the Department Theoretical and Computational Ecology (TCE). I am also the scientific coordinator of the Virtual Laboratory & Innovations Center (LW-VLIC) of LifeWatch-ERIC in which we develop workflows, virtual labs and eScience tools for applications in biodiversity and ecosystem research. Additionally, I am leading several tasks and work packages in various national and international, multi-institutional and multi-disciplinary projects, including the biodiversity monitoring demonstration sites in the Netherlands (NIEBA ARISE), the co-design of the future EU-wide biodiversity observation network (EuropaBON), the automation of workflows for generating LiDAR metrics for habitat condition indicators in Natura2000 sites (MAMBO), the modelling of important Arctic bird areas under climate change (NPP project from NWO), and the development of an e-infrastructure for Digital Twins of ecosystems to study and predict how changes in climate and other human-induced pressures affect ecosystems and biodiversity (LTER-LIFE).

My work often bridges from use and compile large ecological and environmental datasets together with ecoinformatic tools to understand, map, model and predict species distributions, trophic interactions, functional traits, ecosystem structure and animal habitats across space and time. I take advantage of recent advances in computing, big data availability, digital sensors, LiDAR, satellite remote sensing and statistical modelling to (1) better understand the broad-scale distribution of life on Earth, and (2) address how biodiversity is changing under past, present and future global change. I am further interested in biodiversity monitoring, the development of virtual research environments (VREs), and in the application of eScience and artificial intelligence (AI) for biodiversity research. I also work on aspects of data science, especially on biodiversity data integration, automation of data streams, high-throughput processing workflows, and the use of remote sensing and digital sensors to measure and monitor biodiversity change. Please see my research pages, my publication list, or the BIOMAC lab homepage for more details.



Call for papers:

Special Issue on "LiDAR Metrics for Habitat Condition Indicators" in the journal Remote Sensing. We are seeking contributions which address how ecological remote sensing research with LiDAR can be used to (1) quantify the role of habitat structure and niche space for the distribution, abundance, and diversity of species, (2) indicate and monitor the dynamics and condition of animal habitats with LiDAR-derived metrics, and (3) challenge or inform habitat management paradigms and practices, e.g. in the context of novel interventions such as re-wilding or ecosystem restoration.