title: A Bayesian approach for temporally scaling climate for modeling ecological systems.
abstract: With climate change becoming more of concern, many ecologists are including climate variables in their system and statistical models. The Standardized Precipitation Evapotranspiration Index (SPEI) is a drought index that has potential advantages in modeling ecological response variables, including a flexible computation of the index over different timescales. However, little development has been made in terms of the choice of timescale for SPEI. We developed a Bayesian modeling approach for estimating the timescale for SPEI and demonstrated its use in modeling wetland hydrologic dynamics in two different eras (i.e., historical [pre-1970] and contemporary [post-2003]). Our goal was to determine whether differences in climate between the two eras could explain changes in the amount of water in wetlands. Our results showed that wetland water surface areas tended to be larger in wetter conditions, but also changed less in response to climate fluctuations in the contemporary era. We also found that the average timescale parameter was greater in the historical period, compared with the contemporary period. We were not able to determine whether this shift in timescale was due to a change in the timing of wet-dry periods or whether it was due to changes in the way wetlands responded to climate. Our results suggest that perhaps some interaction between climate and hydrologic response may be at work, and further analysis is needed to determine which has a stronger influence. Despite this, we suggest that our modeling approach enabled us to estimate the relevant timescale for SPEI and make inferences from those estimates. Likewise, our approach provides a mechanism for using prior information with future data to assess whether these patterns may continue over time. We suggest that ecologists consider using temporally scalable climate indices in conjunction with Bayesian analysis for assessing the role of climate in ecological systems.
authors.affiliation: U.S. Geological Survey Northern Prairie Wildlife Research Center 8711 37th Street Jamestown North Dakota 58401.
authors.forename: Max
authors.initials: M
authors.lastname: Post van der Burg
authors.affiliation: U.S. Geological Survey Northern Prairie Wildlife Research Center 8711 37th Street Jamestown North Dakota 58401.
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Anteau
authors.affiliation: U.S. Geological Survey Northern Prairie Wildlife Research Center South Dakota State University 8711 37th 5 St SE Jamestown North Dakota 58401; Present address: A105 Russell Labs The Nature Conservancy Center for Science and Public Policy 1510 E Fort Lowell Rd Tucson AZ 85719.
authors.forename: Lisa A
authors.initials: LA
authors.lastname: McCauley
authors.affiliation: U.S. Geological Survey Northern Prairie Wildlife Research Center 8711 37th Street Jamestown North Dakota 58401.
authors.forename: Mark T
authors.initials: MT
authors.lastname: Wiltermuth
keywords: Bayesian hierarchical models; Prairie Pothole Region; Standardized Precipitation Evapotranspiration Index; drought indices; hydrology; semipermanent wetlands