Spatial sampling bias in the Neotoma paleoecological archives affects species paleo-distribution models

The ability to infer paleo-distributions with limited knowledge of absence makes species distribution modeling (SDM) a useful tool for exploring paleobiogeographic questions. Spatial sampling bias is a known issue when modeling extant species. Here we quantify the spatial sampling bias in a North American packrat midden archive and explore its impact on estimating paleo-distributions. We test whether (1) spatial sampling bias inherent in this macrofossil record can influence estimates of paleo-distributions, (2) this bias can alter the ability to measure shifts in distributions and climatic niche breadth from the Northgrippian subdivision of the Holocene (8.3 ka - 4.2 ka) to present day (1950-2000 yr), and (3) bias correction methods can improve estimates of paleo-distributions and analyses of range shifts and niche breadth. We estimate spatial sampling bias for the mid-Holocene period with a three-stage statistical model, each representing a hypothesized source of bias: fossil site availability, preservation and accessibility. This approach enables the use of SDM to evaluate three separate paleo-distributions calibrated on the packrat midden archive: those without bias correction (σ-naïve), those created with a standard method (σ-standard), and those created with a novel alternative (σ-modeled) incorporating the three-stage model of bias. We find that paleo-distributions modeled for the mid-Holocene without bias correction (σ-naïve) provided poor estimates of hindcast paleo-distributions, and that the σ-modeled correction method improved paleo-distributions for our six species with, on average, 50% higher overlap to hindcast distributions than σ-naïve paleo-distributions (σ-standard results fell between σ-naïve and σ-modeled).