Integrating precipitation, grazing, past effects and interactions in long-term vegetation change

- Vegetation change was best explained by including both grazing and precipitation effects.
- Inclusion of lag effects and multi-year averages significantly improved the statistical model.
- A novel interaction between grazing and precipitation also yielded significant results.

Determining the causes of vegetation change in arid and semi-arid environments can be difficult and may involve multiple factors, including disturbance, inter-annual climatic variation, soils, effects from years past and interactions between these factors. Theoretical models describing vegetation change in these systems have generally focused on a single aspect as the primary driver. The integration of these factors into a single model may be what is required to fully understand the drivers of vegetation change in desert systems. To test the contributions of these various factors, we analyzed a long-term (1979-2011) vegetation dataset using multiple linear regression.While precipitation and livestock density were important variables for explaining vegetation change, the consistency with which past effects and interactions significantly improved the models underscores their importance. Past effects were included in every model except for shrub diversity, and included both precipitation and livestock density effects. A novel approach to addressing the interaction between grazing and precipitation was included by dividing precipitation by stocking density. Grass density had a high positive correlation with this metric, while shrub cover had a small negative correlation. These results support the integration of multiple factors to explain vegetation change.