ARS | Publication request: Grazing systems research: Focusing on the managers-introduction

Submitted to: Society for Range Management Meeting Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: February 1, 2009
Publication Date: February 8, 2009
Citation: Brown, J., Havstad, K.M. 2009. Grazing systems research: Focusing on the managers-introduction [abstract]. 62nd Society for Range Management Annual Meeting. Paper No. 21-1.

Technical Abstract: Translating experimental results into management guidelines or as bases for specific decisions presents a substantial challenge for scientists, advisors and land managers. While inductive reasoning can be a valuable tool in developing general guidelines, particular wholly science-based relationships, taken out of context, may not translate well or may be misleading if improperly applied. For example, substantial effort has been expended on glasshouse, small plot and small paddock scale responses of individual plants, populations and communities to varying frequency and intensity of defoliation and other direct impacts of livestock grazing (trampling, dunging). There is little reason to suspect that these soil and vegetation responses are not scalable to commercial grazing applications if interpreted within the known and applicable bounds of climate and soils. Individual grazing animal attributes discerned experimentally, such as species and community selectivity, forage intake and nutrition related performance (gain/hd, gain/ha) are likewise valid at more extensive scales and generally applicable to policy and management decisions. Properties and relationships that emerge only at commercial scales, such as landscape scale animal distribution and forage selectivity, herd management (genetics, reproduction attributes, hygiene etc), financial management (investment portfolios), and range management (improvements, response to drought) must be investigated, analyzed and interpreted at coarser scales to have meaning. Research and development should clearly identify these variables, their tests and scaleable interpretations to identify their limits of application for management and decision making.