Opportunity Title:

Development of an Algorithm-based Climate Change Risk Assessment Framework for Near-coastal Species

Research Area:

Climate Change

EPA Lab/Center/Office:

National Health and Environmental Effects Research Laboratory (NHEERL)

Location:

Newport, OR

Duration:

12 months

Brief Summary:

The intern would help develop a climate change risk assessment framework. Areas of focus could include downscaling risks, ocean acidification, or advancing the use of life history traits.

Opportunity Description:

EPA is developing an algorithm-based risk assessment to predict the impacts of climate change on coastal species at regional scales. The overall vulnerability to climate change as well as the specific risks to temperature increases, ocean acidification and sea level rise are predicted from a suite of life history traits integrated with geographic patterns of projected climatic changes and species’ distributions. A data mining/ecoinformatic approach is used, implemented in an online tool CBRAT (www.cbrat.org). The current public version of CBRAT synthesizes the distributional and life history information for all the crabs and rockfish from the Gulf of California through the Beaufort Sea (over 400 species).  The updated public version to be released in early 2017 will incorporate the climate risk assessments for these taxa, and then later in 2017 additional functionalities and taxa (e.g., bivalves) will be added.

Within this risk framework, there are several areas in which an intern could focus, using a data synthesis/analysis and modeling approach. One area is addressing how to downscale the risks generated by CBRAT, which are at an ecoregion scale, to risks at an estuary scale. This could include how to downscale climate projections generated from climate models with resolutions of 10s to 100s of kilometers to the order of a kilometer or less. For example, this could include developing statistical models to predict estuarine water temperature from watershed size, air temperature, ocean temperature near the estuary, precipitation, etc. Another component of downscaling could be how to link predictions of risk at ecoregion scales to specific populations within different types of estuaries. Another potential topic is the development of regional-scale risk assessment approaches for ocean acidification. EPA has a first-cut approach for decapods, but this approach can be refined (e.g., incorporating evolutionary exposure to low pH and/or modifying risk based on the depth distribution of the species) as well as adapted to other taxa. A third potential topic is how to better utilize the biotic traits synthesized in CBRAT to predict vulnerability to climate change or other stressors, such as pollution. An example is that other researchers have developed risk classes based on size, max. life span, fecundity, etc. of fish. We have been capturing similar data for crabs and bivalves but do not have the functions to relate these life history parameters to risk.

Opportunities for Professional Development:

An objective would be for the student, in collaboration with EPA scientists, to produce a first-authored paper by the end of a 12-month internship. The data synthesis and analysis would expose the student to the use of data synthesis and ecoinformatics as an approach to addressing complex, multidisciplinary questions. We would prefer an intern for 12 months, but shorter periods would be acceptable.

Point of Contact or Mentor:

Henry Lee II (lee.henry@epa.gov)