EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Integrating wind energy forecasting and species population models to consider trade offs in a lower carbon future. 

Jay Diffendorfer1, Anthony Lopez2, Wayne Thogmartin3, Trieu Mai2, Bethany Straw4, Brad Udell4, and Asthon Wiens3
Jay Diffendorfer et al.
  • 1United States Geological Survey, Geosciences and Environmental Change Science Center, Denver, United States of America (
  • 2Natural Renewable Energy Laboratory, Golden, CO, United States of America
  • 3United States Geological Survey, Upper Midwest Environmental Science Center, LaCrosse, WI, United States of America
  • 4United States Geological Survey, Fort Collins Science Center, Fort Collins, CO, United States of America

Renewable energy has crossed key technological hurdles related to costs and energy system stability yet impacts to wildlife may present a long-term challenge to the development and operation of renewables.  We describe a number of approaches to address interdisciplinary questions related to enhancing renewable energy development while minimizing unintended consequences to wildlife and habitat.  These approaches range from relatively simple geospatial models and Monte Carlo simulations to more sophisticated integration of spatially explicit techno-economic/physics wind energy forecasting models with bat population models. We present results from demographic models estimating impacts from future wind energy development, how including geographic constraints related to conserving natural capitol and ecosystem services may impact wind energy development and costs, and early work on temporally dynamic integration of energy and population models. We then summarize a few broader ideas on integrated modelling related to ecosystem services and energy systems. 

How to cite: Diffendorfer, J., Lopez, A., Thogmartin, W., Mai, T., Straw, B., Udell, B., and Wiens, A.: Integrating wind energy forecasting and species population models to consider trade offs in a lower carbon future. , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13887,, 2021.