1. Heterogeneity in Pasture Systems of Different Diversity: Implications for Management Fernando R. Vizcarra 1, Paul T. Greenway 2, and Santiago A. Utsumi 3. 1 Undergraduate student of Animal Bio-health, Alabama A&M University, Normal, AL 35758; 2 Research technician and 3 Assistant professor of Animal Science, W.K. Kellogg Biological Station, Michigan State University, Hickory Corners, MI 49060. Introduction and Background. Treatments: Two pasture systems of different plant species diversity, high diversity (HD: 7 species) and low diversity (LD: 2 species). A total of 8 paddocks (1 ha each), 4 of HD and 4 of LD were used. Grazing management: Pastures were rotationally grazed by lactating dairy cows managed on a voluntary milking system at very high stocking rate (4.4 cows/ha). Mapping: Interpolation techniques using ArcGis software were used to model the spatial pattern of pre- and post-grazing pasture biomass (Kg DM/ha) as well as pasture utilization (%). Maps of utilization, were created by calculation of the biomass that disappeared during grazing in relation to the pre-grazing biomass measured before grazing Analysis: Pasture heterogeneity in height and biomass across spatial scales was analyzed by global and local autocorrelation analysis using ArcGis software. ANOVA for a CRD, using mixed models (SAS V 9.3) was used to compare heterogeneity between pasture diversity treatments (High vs Low), grazing stages (Pregrazing, postgrazing and grazing utilization) and spatial scales (5 to 120 m). Conclusions Acknowledgements: Results Maintaining heterogeneity rather than homogeneity of grazed pasture could lead into management approaches that can simultaneously support both, biological diversity and agricultural production. However, retaining desirable resource heterogeneity can be increasingly challenging if the grazing selectivity by animals is cannot be manipulated or managed correctly. Hypothesis The authors would like to thank the W. K. Kellogg Biological Station and the KBS Dairy Farm Staff, including but not limited to Howard Straub and Brook Wilke, for their assistance and for allowing research on their pastures. This research was partially funded by MSU-AgBioResearch. Fernando Vizcarra was supported by an REU-NSF grant funding to MSU-KBS. Materials & Methods References Objective Significant differences in patch utilization were detected between HD and LD pastures (P < 0.0001). High patch biomass contrast in LD pastures favored the utilization of patches with lower biomass (i.e. selection for forage quality), whereas low biomass contrast in HD pastures favored the utilization of patches with higher biomass (i.e. selection towards intake-rate maximization). Figure 1. ATV with C-Dax Pasture Meter Figure 4. Grazing utilization of patches with high, medium and low pregrazing biomass in pasture systems of A) high or B) Low diversity. 1)The immediate effect of grazing on pasture heterogeneity depends on the selective response of grazing animals to the preexisting spatial pattern of vegetation. 2)The magnitude of spatial heterogeneity affected in intensively grazed pastures depends on the level of diversity and forage contrast between patches. Examine differences in spatial variability of biomass in pasture systems of high or low diversity to understand how animal grazing can be manipulated to alter pasture heterogeneity. Figure 2. Maps showing the spatial variability of pasture Maps properly illustrated differences in spatial variability of pasture. The LD pastures had greater pregrazing average biomass (2437 vs. 1988± 160% kg DM/ha) and variability (25% vs 17%±2%) than HD pastures. Postgrazing biomass was also higher (1512 vs 1193±104% kg DM/ha) and more variable (33% vs 23%±2%) for LD than HD. Pasture utilization was uneven and highly affected by the spatial variability of pasture biomass. Figure 3. Results of autocorrelation analysis showing spatial variability of pasture Spatial variability of biomass was affected by a significant (P 50 m). Greater variability of post-grazing biomass and utilization of biomass was found in the LD at the patch and site level. A significant spatial scale effect (P < 0.0001) was detected on pasture biomass in the two diversity treatments and the 3 grazing stages. Measurement: C-Dax Pasture Meter (Figure 1) was used to collected site –specific measurement of pasture height and biomass. By riding through several transects in a paddock, the meter collected pasture data every 2.7 m. Geospatial pasture data was downloaded remotely and transferred into a GIS data base for spatial analyses. Pre-grazing Utilization,% Post-grazing High average biomass High patch heterogeneity High average biomass High patch heterogeneity Utilization focused on patches with greater biomass Utilization focused on patches with lower biomass Low average biomass Low patch heterogeneity Low average biomass Low patch heterogeneity Grazing management Pasture allocation Forage allowance Grazing management Pasture allocation Forage allowance Increase in spatial heterogeneity Decrease in spatial heterogeneity Pre-grazing Utilization,% Post-grazing High Diversity Treatment Low Diversity Treatment Figure 6. Flow chart explaining differences in biomass utilization and pasture heterogeneity The immediate effects of grazing on spatial heterogeneity depend on previous grazing, the pre-existing spatial variation of the pasture and the level of plant diversity. The spatial variability of biomass before and after grazing and grazing utilization was different between HD and LD treatments. At scales lower than 50 m, the LD pastures were subject to greater spatial variability of biomass and grazing utilization than HD pastures. Average biomass and biomass variability among patches was greater in LD than HD pastures. Grazing utilization was greater in patches of low biomass in LD pastures and in patches of high biomass in HD pastures. Our research rises new challenging questions regarding spatial-dependent plant-animal interactions and the creation and maintenance of resource heterogeneity in intensively managed grazing systems. Adler, P.B., D.A. Raff and W.K. Lauenroth. 2001. The effect of grazing on the spatial heterogeneity of vegetation. Oecologia, 128:465-479. Parsons, A., and B. Dumont. 2003. Spatial heterogeneity and grazing processes. Animal Research, 52: 161-179. Lawrence, H., I. Yule, and R. Murray. 2007. Pasture Monitoring Technologies. New Zealand Centre for Precision Agriculture, Massey University. Figure 5. Example of pregrazing (left) and postgrazing (right) pasture spatial variability Kg DM/Ha