Plant community-specific greening patterns predict population size increases in a temperate herbivore

Climate change driven impacts on vegetation productivity have been shown to drive mammalian herbivore population dynamics in arctic and alpine environments. However, there is less evidence for temperate systems. To address this, we examined the contribution of increasing plant biomass in different vegetation communities (measured by NDVI, normalised difference vegetation index) and winter weather on the observed long-term upward trend in the population of the Soay sheep of Hirta, St Kilda, UK. We found that biomass had increased in all vegetation communities present and done so increased fastest in vegetation types preferred by the sheep. Specifically, those communities with high Specific Leaf Area and Ellenberg’s N, low Leaf Dry Matter Content. Peak summer NDVI and either winter average wind speed or winter North Atlantic Oscillation data added to the variance explained by a simple density dependence model of yearly sheep population growth rates. The highest explanatory power was found..., Please see the paper for details. The work described combined whole population census data, meteorological data, and Landsat NDVI data for different vegetation types., , # Data from: Plant community-specific greening patterns predict population size increases in a temperate herbivore

[https://doi.org/10.5061/dryad.ttdz08m72](https://doi.org/10.5061/dryad.ttdz08m72)

## Description of the data and file structure

The data used in the analysis is a mixture of remote sensing data (Landsat NDVI), meteorological data from weather stations at the study site and from the nearest long-term station, whole island population counts of the Soay sheep on Hirta, vegetation maps, vegetation composition data and plant trait data from databases.

### Files and variables

If using the data from the Soay Sheep Project [meteorological data or sheep population data] it is advised that you contact the authors as the project data is continually being added to and checked. The files here are only appropriate for use with this particular analysis. 

1\. Prediction of Hirta weather prior to installation of weather stations 

WeatherAnalysis.R

WeatherForAnalysis.csv

\[Column h...