Monitoring to detect change on rangelands: physical, social, and economic/policy drivers

TitleMonitoring to detect change on rangelands: physical, social, and economic/policy drivers
Publication TypeJournal Article
Year of Publication2004
AuthorsBrown J., Havstad K
JournalAfrican Journal of Range and Forage Science
Date PublishedOctober 1, 2004
ARIS Log Number159425
Keywordsbiological, communities, drivers, environmental, monitoring
AbstractEnvironmental 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 public values. It is difficult to identify the impact of specific drivers on specific properties at specific times since drivers seldom operate independently, at similar scales, or in isolation from other drivers. Impacts of some drivers, especially nonecological, may not be quantifiable. Yet, any interest in understanding how systems will respond to specific drivers, such as grazing management practices, requires monitoring of system dynamics and pertinent environmental drivers at appropriate scales. For example, risk assessments, adaptive management analyses, or management by hypothesis 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 stressors. Though our abilities to generate accurate predictions are currently limited, conceptual models of system response to drivers are improving. Continued incorporation and refinement of understanding and monitoring effects and interactions of different drivers will contribute to improvements in these predictive capacities. It is important to remember we are developing monitoring systems for the future, as well as for today.