How much land enrolled in the Conservation Reserve Program is needed to maintain a national pheasant harvest of six million roosters? How much would the pheasant population increase in our county if we doubled the current amount of grassland? Where is the best place to invest our habitat restoration efforts to maximize the number of pheasants that result? When these types of questions are posed to pheasant managers, habitat models are the tools they typically turn to for answers.
More precise and accurate estimation of pheasant population responses to habitat change has been a prominent goal of scientists in recent decades. Pheasant response estimates are based on qualitative or mathematical equations, or models, relating pheasant abundance to varying types, amounts, and/or configurations of habitat, as well as (in some cases) weather and other covariates that can also influence pheasant abundance. Different models require different data inputs depending on, for example, what spatial scale the resulting estimate corresponds to. Some models use state- or county-level habitat data to estimate population abundance at those scales, while others correspond to smaller-scale study areas.
Models are valuable tools, but they have their limitations. The data upon which they are based are often limited to a specific portion of the pheasant range and a relatively narrow time window. The farther removed their application is from the location, time, and spatial scale of model construction, the more caution that must be used when interpreting the model’s outputs. For this reason, there is no one “best” model to rely upon across the pheasant range, and managers must view model results within the context of the larger body of habitat-related literature when making recommendations.
The habitat models below are the ones most commonly referenced by contemporary pheasant managers.
The National Wild Pheasant Conservation Plan model (2013)
The Minnesota Grassland model (Haroldson et al. 2006)
The Iowa County CRP model (Riley 1995)
The Western Range CRP model (Nielson et al. 2008)
The Nebraska Landscape model (Jorgensen et al. 2014)
The Wisconsin Winter Cover model (Gatti and Schneider 2015)