Linking distribution and return‐on‐investment models to optimize woody management for prairie grouse in Nebraska

Abstract

Grasslands in Nebraska, USA, face threats from agricultural conversion, urban development, and woody encroachment, all of which negatively affect prairie grouse ( Tympanuchus spp.) populations. To optimize conservation planning, Nebraska wildlife agencies developed probabilistic area‐based surveys for greater prairie‐chicken ( T. cupido ) and sharp‐tailed grouse ( T. phasianellus ) to sample landscapes across a range of environmental conditions. This design improves historical surveys and enables the development of distribution models that quantitatively define habitat associations and support scenario‐based conservation planning. Using survey data collected during 2020–2022, we modeled prairie grouse occurrence and abundance as functions of land cover, topography, and climate using Bayesian logistic and zero‐inflated negative binomial models with regularized horseshoe priors. We then conducted a maximum potential return‐on‐investment analysis of woody cover treatments, assuming sustained treatment success, relative to projected impacts of woody encroachment on prairie grouse populations by 2050. Among modeled associations were a positive association with grasslands having low woody cover and a negative association with grasslands having high woody cover. Across the 3‐year period, median estimated annual populations were 142,380 for greater prairie‐chicken (range of 95% CIs across years = 68,821–277,615) and 64,154 for sharp‐tailed grouse (range of 95% CIs across years = 27,550–146,559). Under projected woody encroachment, mean predicted population declines were 10% for greater prairie‐chicken (range of 95% CIs = 7–14%) and 6% for sharp‐tailed grouse (range of 95% CIs = 5–7%). Areas with high prairie grouse density and low treatment costs in 2021, and high projected woody encroachment and population loss by 2050, offered the greatest return on investment for woody management. Return on investment was greatest in the northwestern Shortgrass Prairie ecoregion (northwestern Nebraska) for sharp‐tailed grouse and the eastern Sandhills ecoregion (central Nebraska) for both species. These models underscore the value of evidence‐based, quantitative approaches for prioritizing conservation actions on working lands. Scenario‐based modeling could be extended to guide other treatments, such as optimizing restoration (e.g., Conservation Reserve Program) or incentivizing grassland persistence in areas with predicted climate resilience.