Skip to main content
ARS Home » Plains Area » Las Cruces, New Mexico » Range Management Research » Research » Publications at this Location » Publication #145570
Title: ENVIRONMENTAL DRIVERS AND MONITORING OF RANGELANDS

Author
item Havstad, Kris
item BROWN, JOEL - USDA-NRCS

Submitted to: International Rangeland Congress
Publication Type: Abstract Only
Publication Acceptance Date: 12/1/2002
Publication Date: 8/1/2003
Citation: HAVSTAD, K.M., BROWN, J.R. ENVIRONMENTAL DRIVERS AND MONITORING OF RANGELANDS. INTERNATIONAL RANGELAND CONGRESS. 2003.

Interpretive Summary:

Technical Abstract: Environmental drivers are factors that cause measurable changes in properties of biological communities. Examples of drivers can include environmental factors such as rainfall variability and available soil nitrogen, management factors such as livestock grazing practices and prescribed burning, government factors such as tax laws and environmental policies, and societal factors such as attitudes regarding property rights and prevailing public values. It is difficult to identify the impact of specific drivers on specific properties at specific times since drivers seldom operate independently or singularly. Impacts of some drivers, especially non-ecological, may not be readily quantifiable. Yet, any interest in understanding how systems will respond to specific drivers, such as a grazing management practice, requires monitoring of system dynamics and pertinent environmental drivers. For example, risk assessments and adaptive management analyses both require understanding linkages between environmental drivers and various management options on ecological properties of managed systems. Any type of predictive management strategy for proposing future options would require an understanding of biological responses to environmental drivers. Though our abilities to generate accurate predictions are currently limited, conceptual models of system responses to drivers are improving. Continued incorporation and refinement of our understanding and monitoring effects and interactions of different drivers will contribute to improvements in these predictive capacities. It is important to remember that we are developing monitoring systems for the future, as well as for today.