Data from: Reliable species distributions are obtainable with sparse, patchy and biased data by leveraging over species and data types ...

• Main Authors: Peel, Samantha L., Hill, Nicole A., Foster, Scott D., Wotherspoon, Simon J., Ghiglione, Claudio, Schiaparelli, Stefano
• Format: Dataset
• Language: English
• Published: Dryad 2019
• Subjects: Southern Ocean Mollusca; presence‐absence data; sampling bias; presence‐only data; Poisson point processes; Southern Ocean
• Online Access: https://dx.doi.org/10.5061/dryad.2226v8m; https://datadryad.org/stash/dataset/doi:10.5061/dryad.2226v8m

1. New methods for species distribution models (SDMs) utilise presence‐absence (PA) data to correct the sampling bias of presence‐only (PO) data in a spatial point process setting. These have been shown to improve species estimates when both data sets are large and dense. However, is a PA data set that is smaller and patchier than hitherto examined able to do the same? Furthermore, when both data sets are relatively small, is there enough information contained within them to produce a useful estimate of species’ distributions? These attributes are common in many applications. 2. A stochastic simulation was conducted to assess the ability of a pooled data SDM to estimate the distribution of species from increasingly sparser and patchier data sets. The simulated data sets were varied by changing the number of presence‐absence sample locations, the degree of patchiness of these locations, the number of PO observations, and the level of sampling bias within the PO observations. The performance of the pooled data ... : Species ListSpecies list for Dryad.csv ...