Biodiversity and Climate Modeling Workshop Series: Overview, Recommendations, and Conclusions
Dates
Publication Date
2019-02-04
Summary
In 1969, researchers developed the first global circulation model (Ruttiman 2006); however, it was not until 2014 that modelers first attempted a global ecosystem and biodiversity model that included human pressures (i.e., the Madingley Model) (Harfoot et al. 2014). Other large-scale models of biodiversity exist, such as GLOBIO (Alkemade et al. 2009), but to date there are no well accepted global biodiversity models similar to global circulation models that can help guide global biodiversity policy development and targets. The lack of global biodiversity models compared to the extensive array of general circulation models provides a unique opportunity for climate, ecosystem, and biodiversity modeling experts to determine similarities [...]
Summary
In 1969, researchers developed the first global circulation model (Ruttiman 2006); however, it was not until 2014 that modelers first attempted a global ecosystem and biodiversity model that included human pressures (i.e., the Madingley Model) (Harfoot et al. 2014). Other large-scale models of biodiversity exist, such as GLOBIO (Alkemade et al. 2009), but to date there are no well accepted global biodiversity models similar to global circulation models that can help guide global biodiversity policy development and targets. The lack of global biodiversity models compared to the extensive array of general circulation models provides a unique opportunity for climate, ecosystem, and biodiversity modeling experts to determine similarities and differences in modeling approaches to inform development of integrated global biodiversity modeling approaches.
More accurate and comprehensive biodiversity models are needed to understand how countries individually and as a whole are progressing towards the internationally defined targets (e.g., Aichi Biodiversity Targets and Sustainable Development Goals) to inform global biodiversity conservation, monitoring, and sustainable use (Tittensor 2014). In addition, the scenarios and modeling summary from the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES) identified a need for better assessment of biodiversity models and progress towards more global models. Collaborative approaches between the biodiversity and global climate modeling communities can provide information to advance biodiversity models and improve each community’s approaches to forecasting change. Collaboration can also help tighten the linkages between biodiversity and climate and land-use models as climate change and other anthropogenic stressors continue to threaten biodiversity and its ecosystem services.
To address the need for improved large-scale biodiversity models, experts in biodiversity and climate modeling and remote sensing fields came together via a series of in-person workshops and virtual discussions. Our goals were to 1) identify strategies (both qualitative and quantitative) from climate models to be applied to large-scale biodiversity models, 2) to explore NASA and other remote sensing products to assist in global biodiversity modeling efforts and 3) to address and build on gaps and data needs to inform development of GEOBON Essential Biodiversity Variables (EBV) and tracking and development of the next generation of Aichi Biodiversity Targets and Sustainable Development Goals.
The first in-person meeting was held in June 2017 with 20 in-person and remote participants in Reston, VA and a second in-person meeting in February 2018 with 18 in-person and remote participants in Tucson, AZ to address these objectives. Participants came from national and international academic institutions, government agencies, and non-governmental organizations and were from various stages in their careers. The workshop series resulted in three main outcomes, including a list of lessons learned and recommendations from those with expertise in climate modeling to address goal 1 above, a framework for assessment and refinement of diverse biodiversity models using remote sensing tools to address goal 1, 2, and 3 above, and lastly the development of a meta-conceptual biodiversity model to inform future model development and needs. Below is a detailed overview highlighting recommendations and outcomes of the workshop series.
