README.md.bak

# OBServ_Models_Open

This repository contains the implementation of two types of pollination supply models[1]:

The folder **Lonsdorf** contains the implementation of the Lonsdorf model[2] in Google Earth Engine.

The folder **Machine Learning** contains the implementation of a machine learning pipeline to predict pollinator visitation rate, using scikit-learn in Python.

# Pipeline for Lonsdorf scores (in preparation)

# Pipeline for machine learning predictions (in preparation)


References:

1) Gimenez-Garcia A, et al. (in preparation) Applicability of simple and reliable pollination supply models from local to global scale.

2) Lonsdorf E, et al. (2009) Modelling pollination services across agricultural landscapes. Annals of Botany 103(9):1589–1600.