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

Authors: Weltz, Mark; MORRIS, CHRISTO - Oregon State University; BADIK, KEVIN - University Of Nevada; MORRIS, LESLEY - Oregon State University

Submitted to: Journal of Arid Environments
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/3/2015
Publication Date: 1/15/2016
Citation: Weltz, M.A., Morris, C., Badik, K.J., Morris, L.R. 2016. Integrating precipitation, grazing, past effects and interactions in long-term vegetation change. Journal of Arid Environments. 124:111-117.

Interpretive Summary: Determining the causes of vegetation change in arid and semi-arid environments can be difficult and may involve multiple factors, including disturbance, weather, soils, lag effects and the various interactions between these factors. Theoretical models describing vegetation change in these systems have generally focused on a single aspect as the primary driver. It has been proposed that the competing models may address different aspects of the process, especially temporal scales. Therefore 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 (1969-2011) dataset of vegetation cover, density, and diversity taken from permanent plots on four allotments in the Bodie Hills, CA. Factors associated with changes in measured vegetation characteristics were determined using multiple linear regression. While precipitation and livestock density were important variables for explaining vegetation change, the consistency with which lag effects and interactions significantly improved the models underscores their importance. Lag effects were included in every model except one. Lag effects also resulted in some negative correlations with precipitation through competitive interactions between growth forms. A novel approach to addressing the interaction between grazing pressure and precipitation was included and yielded significant results. By dividing precipitation by stocking density, a more meaningful interpretation than a traditional interaction was possible. Grass density had a high positive correlation with this approach, while shrub cover had a small negative correlation. These results highlight the importance of adjusting stocking rates based on precipitation accumulated over several years.

Technical Abstract: Determining the causes of vegetation change in arid and semi-arid environments can be difficult and may involve multiple factors, including disturbance, weather, soils, lag effects and the various interactions between these factors. Theoretical models describing vegetation change in these systems have generally focused on a single aspect as the primary driver. It has been proposed that the competing models may address different aspects of the process, especially temporal scales. Therefore 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 (1969-2011) dataset of vegetation cover, density, and diversity taken from permanent plots on four allotments in the Bodie Hills, CA. Factors associated with changes in measured vegetation characteristics were determined using multiple linear regressions. While precipitation and livestock density were important variables for explaining vegetation change, the consistency with which lag effects and interactions significantly improved the models underscores their importance. Lag effects were included in every model except one. Lag effects also resulted in some negative correlations with precipitation through competitive interactions between growth forms. A novel approach to addressing the interaction between grazing pressure and precipitation was included and yielded significant results. By dividing precipitation by stocking density, a more meaningful interpretation than a traditional interaction was possible. Grass density had a high positive correlation with this metric, while shrub cover had a small negative correlation. These results highlight the importance of adjusting stocking rates based on precipitation accumulated over several years.