Approaches to predicting broad-scale regime shifts using changing pattern-process relationships across scales

TitleApproaches to predicting broad-scale regime shifts using changing pattern-process relationships across scales
Publication TypeBook Chapter
Year of Publication2009
AuthorsPeters DC, Bestelmeyer B, Knapp A.K., Herrick JE, H. Monger C, Havstad K
Series EditorMiao S., Carstenn S., Nungesser M.
Book TitleReal World Ecology: Large-scale and long-term case studies and methods
Pagination47-72
CityNew York
Accession NumberJRN00523
ARIS Log Number218478
Keywordsbroad-scale regime, pattern-process
Abstract

Understanding and predicting the occurrence of alternative ecosystem states (i.e., regime shifts) at broad scales is a pressing challenge for ecologists given the scope and nature of global change. In many cases, regime shifts at broad-scales are affected by pattern-process relationships across a range of finer scales. However, experimental and analytical methods to examine state changes, such as from perennial grasslands to woodlands, have not been fully developed. We first define and describe the expansion of woody plants into perennial grasslands. Woody plant encroachment has well-documented consequences for local, regional, and global ecology, and takes several forms, from shrub invasion in arid/semiarid grasslands and arctic ecosystems to tree invasion in mesic and alpine grasslands. We then outline a multi-scale experimental approach to examining the key processes influencing woody plant encroachment from fine to broad scales, and describe the application of this approach to the Jornada Basin Agricultural Research Service-Long Term Ecological Research site as a case study. Several questions can be addressed with this approach, such as: how and under what conditions do dynamics and decisions made at fine scales influence dynamics at broader scales? How and under what conditions do broad-scale dynamics overwhelm fine-scale processes to influence landscape patterns? Finally, we discuss analytical techniques for predicting regime shifts and their associated thresholds.

URLfiles/bibliography/JRN00523.pdf
DOI10.1007/978-0-387-77942-3_3