Meeting Abstract
Blue crab are an important economic resource in Chesapeake Bay, worth $78 million in 2009 (Chesapeake Bay Foundation). Blue crab are also an important link in the Bay ecosystem and a symbol of the Bay, particularly to local residents and fishermen. Climate change may impact the complex migration and reproduction strategies of blue crab, in particular their distribution and abundance. In this study, we develop a spatially-resolved, agent-based mechanistic blue crab population model. Using this approach, we can approximate observed fluctuations in the population on a monthly timestep, and simulate genetic variation and responses to environmental stimuli on short timescales. The effects of climate change on living resources is difficult to determine reliably via coarse global climate models. Statistical downscaling is increasingly used to apply model output to regional scales relevant to local biological processes. Here, we apply the Quantile Delta Mapping (QDM) bias correction method (Cannon et al. 2015) to Max Planck Institute Earth System Model (MPI-ESM) climate projections at low resolution. We use resulting historical and projected temperature and precipitation estimates as inputs to a Bay water balance model (Muhling et al. 2017). This model predicts surface temperature and salinity, estuarine habitat indicators which we use to drive our blue crab population model. We hope to use this model to show the possible trajectory of blue crab stock under the MPI-ESM-LR climate change scenario. Refining these estimates through updated models is key to informing the management of blue crab in the Chesapeake Bay.
