Integrating presence-only and detection/non-detection data to estimate distributions and expected abundance of difficult-to-monitor species on a landscape-scale

Estimating species distribution and abundance is foundational to effective management and conservation. Using an integrated species distribution model that combines presence-only data from various sources with detection/non-detection data from structured surveys, we estimated the distribution and expected abundance of difficult-to-monitor mammals of management concern across New York State, namely, coyotes, bobcats, and black bears. Three distinct landscape-scale camera trap surveys provided detection/non-detection data over nine years between 2013-2021, and we augmented those data with incidental records of our focal species from public repositories. We used an inhomogeneous Poisson point process to construct an integrated model that fit both data types simultaneously. We demonstrate a simple application of spatial point density of all species records in the accessed public databases to inform the thinning process to account for unknown spatial sampling in the presence-only data, often..., Landscape-scale structured camera trap surveys
Multiple camera trap surveys spanning nine years documented the occurrence of mammals across much of the state from 2013 – 2021. We conducted winter surveys of the south-central part of the state including the High Allegheny Plateau, the Western Allegheny Plateau, and the Great Lakes ecoregions (Omernik & Griffith, 2014) in 2013 (294 sites), 2014 (608 sites), and 2015 (599 sites). We conducted a second set of large-scale winter camera surveys in the same region in 2019 (584 sites), 2020 (603 sites), and 2021 (601 sites). Winter surveys of the northern part of the state (Northern Appalachians ecoregion), were conducted annually in 2016 (189 sites), 2017 (179 sites), and 2018 (191 sites). All nine winter camera trap surveys from 2013-2021 were leveraged to generate detection/non-detection data for bobcats and coyotes. We additionally conducted summer camera trap surveys for black bears in the High Allegheny Plateau, Western Allegheny Plat..., , # Integrating presence-only and detection/non-detection data to estimate distributions and expected abundance of difficult-to-monitor species on a landscape-scale.

[https://doi.org/10.5061/dryad.ghx3ffbwf](https://doi.org/10.5061/dryad.ghx3ffbwf)

# Summary

These are the data, MCMC samplers, and processing and run scripts for an inhomogeneous Poisson point process model to integrate detection/non-detection data and presence-only data to estimate the expected abundance of species. This model enables the user to integrate these two datatypes by assuming they share the same underlying data-generating process (an inhomogeneous Poisson point process). These models are adapted from Koshkina et al. (2017) [Methods in Ecology and Evolution] but diverge from the original specification to accommodate *t* primary sampling periods (survey years). This model fits temporally varying mean-centered random year effects of all three parameters in the model (detection probability, p, mean expected abund...