1. Improvement of Meadow Stream Health due to Livestock Distribution Efforts K.W. Tate, T.A. Becchetii, C. Battaglia, N.K. McDougald, D.F. Lile, H.A. George, and D.L. Lancaster University of California

2. Grazed streams across CA range from excellent to poor health. What practices are associated with excellent to poor health? Conduct a cross-sectional survey of health and management of grazed stream systems. Grazing – Stream Health

3. Initial Survey of 128 Rangeland Streams Summer of 2000 and 2001. Cross-section of the grazed rangeland stream population. Cascades, Sierra Nevada, and Coast Range. Gradient of stream health and grazing management conditions.

4. Grazing ManagementEPA – CDFG Stream Health Assessment stability fish habitat macroinverts. Overall Health Score 0 – 5poor 6 – 10marginal 11 – 15 suboptimal 16 – 20optimal Off-site water, herding, season, frequency, fencing, etc. Site Characteristics Elevation, channel slope, substrate, watershed disturb., past disturb., etc.

5. Regression analysis – correlate stream health score (0-20) to grazing management variables Analyzed by substrate type: bedrock/boulder, cobble/gravel, fines/alluvial Associations v. Cause-Effect Grazing and Stream Health Associations

6. Grazing – Stream Health Score Correlations: Meadow Streams + Time maintaining off-stream attractants (days/yr). + Herding to reduce time near stream (days/yr). – Cattle density (AU/ac). – Frequency (times/yr).

7. Follow-up Survey of 58 Streams Summer of 2003 and 2004. Collect stream macroinvertebrate assemblages. Meadow streams (Rosgen C and E). Cascades and Sierra Nevada 3,500 and 8,500 ft elevation. Current management in place >10 yr.

8. Macroinvertebrates Integrate stream conditions and disturbance over space and time. EPA – CDF&G protocols –3 transects per 100m reach, d- ring kick-net, 0.25 m2 sample area, 3 minute sample effort ID to genus – species Sub-sample edge and mid stream substrates at 3 transects each stream

9. Site Summary Min.MeanMax. Elevation (ft) 3,4005,9008,500 Pasture / Allotment Area (ac) 80018,000105,000 Herd Size (AU) 10150670 Off-site Attractants (d/yr) 0334 Total Dist. Effort (d/yr) 0941 Substrate Type (% sites) FinesGravelCobble 532720

10. Data Analysis Negative binomial regression (back-step). Count-based data, skewed towards low values, etc. Dependents: –11 macroinvertebrate metrics (11 nbreg models) –no. taxa, no. stoneflies, %EPT, etc. Independents: –Grazing: dist. effort, rest, AUM/ac/yr, freq., etc. –Substrate: fines, gravel, cobble Cluster Variable: stream reach

11. 11 metrics significantly assoc. with total dist. effort (p<0.10). No other grazing variables were significant (p>0.10). Sensitive metrics increased as dist. effort increased. Substrate a major determinant of 10 metrics. Select MetricsDist. Effort (d/yr) Substrate (cobble to fines) No. EPT taxa+ (p=0.01) – (p=0.07) No. Total Taxa+ (p<0.01) – (p=0.02) No. Intolerant Taxa+ (p<0.01) – (p=0.02) % Intolerant Taxa+ (p=0.06) – (p=0.06) % Dominant Taxa– (p=0.03) n.s. (p>0.10)

12. Total livestock distribution effort v. richness for streams with fine, gravel, and cobble substrate.

13. Sensitive metrics decreases with substrate size. Must be accounted for in cross stream comparisons.

14. Distribution effort to reduce time livestock spend near-stream is positively associated with stream health. Relevant to mixed conifer – meadow landscapes, where distribution is inherently a problem. You got to put in the time to see the benefit… Get along little doggie!