These data are the results of a spatially interpolated integrated population model (SIIPM) fit to count and demographic data collected from populations of Greater Sage-grouse (Centrocercus urophasianus; hereafter, sage-grouse) located in Nevada, U.S.A. during 2013-2021. We used a novel framework, using integrated population models (IPMs), to express demographic relatedness among sampled and unsampled populations using geographic principles of spatial autocorrelation (Shepard, 1968; Tobler, 1970). Specifically, the framework pairs relatively inexpensive population count data with spatially interpolated demographic estimates. When conducted within a Bayesian framework, spatially interpolated demographic parameters can be expressed as probability distributions for unobserved populations. Though novel to the IPM framework, the method is remarkably similar to Tobler’s seminal work on the topic of spatial autocorrelation (Tobler, 1970), which used the Markovian process of human population dynamics to map urban growth over a partially sampled plane. Spatially explicit estimates of survival, recruitment, and finite rate of population change (lambda) represent the 50th percentile of the posterior distribution for each parameter. References cited: Shepard, D. (1968). A two-dimensional interpolation function for irregularly-spaced data. In Proceedings of the 1968 23rd ACM National Conference, ACM 1968. (pp. 517-524). Tobler, W. R. (1970). A Computer Movie Simulating Urban Growth in the Detroit Region. Economic Geography, 46, 234-240. https://doi.org/10.2307/143141