Analysis of long-term (1969-2011) vegetation data from Bodie Hills, CA: Integrating weather, disturbance, lag effects and interactions in vegetation change

Authors: Morris, Christopher; BADIK, KEVIN - University Of Nevada; Weltz, Mark

Submitted to: Government Publication/Report
Publication Type: Government Publication
Publication Acceptance Date: 3/1/2014
Publication Date: 3/28/2014
Citation: Morris, C., Badik, K., Weltz, M.A. 2014. Analysis of long-term (1969-2011) vegetation data from Bodie Hills, CA: Integrating weather, disturbance, lag effects and interactions in vegetation change. Government Publication/Report. 52 p.

Interpretive Summary: Determining the causes of vegetation change in arid and semi-arid environments can be difficult and may involve disturbance, weather, soils, lag effects and the interactions between them. Theoretical ecological models describing vegetation change in these systems have generally focused on one aspect or another as the primary driver. It has been proposed that the ecological models may address different aspects, including temporal scales of the process. Therefore the integration of these factors into a single ecological 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, a long-term (1969-2011) dataset of vegetation cover, density, and diversity taken from permanent plots on four allotments in the Bodie Hills, CA was analyzed. Changes over time were analyzed using ANOVA. Factors associated with changes in measured vegetation characteristics were determined using multiple linear regression. Overall, total vegetation cover increased by approximately 20-35% during the course of the dataset, though values are still lower than comparable “undisturbed” sites. Diversity remained mostly stagnant over the course of the dataset and was well below undisturbed sites. Species composition consisted primarily of grazing-tolerant species. In general, plant metrics were positively correlated with precipitation and negatively correlated with stocking density; although through lag effects and competitive interactions, this pattern was reversed in some cases. Sheep had a more negative effect on grass cover than did cattle. By dividing precipitation by stocking density, a more meaningful interpretation than the 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. Overall, the reduction of grazing has improved range conditions in the Bodie Hills, though conditions have not yet reached those described for comparable “undisturbed” sites.

Technical Abstract: Determining the causes of vegetation change in arid and semi-arid environments can be difficult and may involve disturbance, weather and soil lag effects and the interactions between them. Theoretical ecological models describing vegetation change in these systems have generally focused on one aspect or another as the primary driver. It has been proposed that the ecological models may address different aspects, including temporal scales of the process. Therefore the integration of these factors into a single ecological 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, a long-term (1969-2011) dataset of vegetation cover, density, and diversity taken from permanent plots on four allotments in the Bodie Hills, CA was analyzed. Factors associated with changes in measured vegetation characteristics were determined using multiple linear regression. In general, plant metrics were positively correlated with precipitation and negatively correlated with stocking density; although through lag effects and competitive interactions, this pattern was reversed in some cases with a small effect. Sheep had an increased negative effect on grass cover than did cattle. 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 annual precipitation and cumulative precipitation over the preceding years.