A predictive model for seasonal pond counts in the United States Prairie Pothole Region using large-scale climate connections

Abstract

The Prairie Pothole Region (PPR), located in central North America, is an important region hydrologically and ecologically. Millions of wetlands, many containing ponds, are located here, and they serve as habitats for various biota and breeding grounds for waterfowl. They also provide carbon sequestration, sediment and nutrient attenuation, and floodwater storage. Land modification and climate change are threatening the PPR, and water and wildlife managers face important conservation decisions due to these threats. We developed predictive, multisite forecasting models using canonical correlation analysis (CCA) for pond counts in the southeast PPR, the portion located within the United States, to aid in these important decisions. These forecast models predict spring (May) and summer (July) pond counts for each region (stratum) of the United States Fish and Wildlife Service's pond and waterfowl surveys using a suite of antecedent, large-scale climate variables and indices including 500 millibar heights, sea surface temperatures (SSTs), and Palmer Drought Severity Index (PDSI). Models were developed to issue forecasts at the start of all preceding months beginning on March 1st. The models were evaluated for their performance in a predictive mode by leave-one-out cross-validation. The models exhibited good performance (R values above 0.6 for May forecasts and 0.4 for July forecasts), with performance increasing as lead time decreased. This simple and versatile modeling approach offers a robust tool for efficient management and sustainability of ecology and natural resources. It demonstrates the ability to use large-scale climate variables to predict a local variable in a skilful way and could serve as an example to develop similar models for use in management and conservation decisions in other regions and sectors of the environment.

Limited shifts in the distribution of migratory bird breeding habitat density in response to future changes in climate

“…Our projections can be continually improved to include additional climate dynamics like relationships developed by Abel et al (2020) that include the response of May ponds to sea surface temperature oscillations and large atmospheric-pressure anomalies. The impact of climate change on increasing the frequency of high-intensity storms could continue the shift from snowmelt-driven wetland hydrology (Shook and Pomeroy 2012) to summer and fall precipitation-driven wetland hydrology that has already been observed in the last 25-years in the southern PPR (McKenna et al 2017).…”

Understanding the Dominant Moisture Sources and Pathways of Summer Precipitation in the Southeast Prairie Pothole Region

“…Another possibility would be to use these large‐scale connections to develop a statistical model for precipitation forecasts at a regional level (e.g., county) similar in design to the forecast model in Abel et al. (2020).…”

“…We used the GHCN station data to determine dates of rain and extreme events during the summers (June, July, August, and September) from 1979‐2017. We defined summer as June‐September because the wet season in the SEPPR begins in spring and extends into September (Abel et al., 2020). We determined the 90th quantile precipitation amount from the subset of days with precipitation for a station.…”

“…Approximately half of the annual precipitation in the SEPPR falls in the summer (Abel et al., 2020; Rosenberry, 2003; Vecchia, 2008). For example, June, July, and August were the first, second, and fourth wettest months, respectively, from 1961‐1990 at the Cottonwood Lake area in North Dakota (Rosenberry, 2003).…”

Assessing the use of climate change information in State Wildlife Action Plans

“…This research was part of a larger project seeking to generate actionable climate information to support wildlife managers and conservation in the north central United States. (c.f., Ballard et al, 2014;Abel et al, 2020;Yocum & Ray, 2019).…”