Currently, PoPS users are responsible for obtaining raw weather data to calibrate PoPS. Below are some resources for weather data:
During calibration of a case study for PoPS, all raw temperature and precipitation values are first converted to indices ranging from 0 to 1 to describe their impact on a species’ ability to survive and reproduce; the transformations, tailored for each species, are saved in the PoPS database.
Due to the modular nature of PoPS, weather components can be turned on or off. For example, a case study of Sudden Oak Death (SOD) used a polynomial function to convert daily Daymet (Thornton et al. 2017) temperature and a threshold of 2.5 mm to convert daily Daymet precipitation into weekly weather coefficients ranging from 0 to 1 (Meentemeyer et al. 2011).
In contrast, a case study of Spotted Lanternfly (SLF) used a step function to convert daily Daymet temperature into a monthly coefficient ranging from 0 to 1. Because SLF spread does not depend on precipitation, that component of the model was turned off.