PARENT SESSION
Symposium #16: Thresholds and non-linear responses in ecosystems: Understanding, sustaining, and restoring complex rangelands.
Sponsored by ESA Rangeland Ecology Section
Organized by: D.D. Breshears and J. Herrick.
Wednesday, August 8, 2001. 1:00 PM to 5:00 PM. Lecture Hall
Landscape characteristics can define disturbance response thresholds in arid and semiarid ecosystems: Three case studies.
BELNAP, J1, REID, R2, 1 2
ABSTRACT- Human influence on ecosystem structure and function can be immediate and apparent (e.g., logging) or subtle and long-term (e.g., nutrient cycling). In arid regions, human impacts are often the subtle, long-lasting variety, and recovery can be linear or threshold-driven, depending on landscape characteristics. 1. Biological soil crusts (BSCs) are a critical component of arid ecosystems. Globally, the resistance and resilience of BSCs to disturbance is dependent on landscape characteristics (e.g., soil, climate). Generally, BSCs have low resistance to disturbance, with some exceptions (e.g., heavily-weathered soils). Resilience to disturbance is dependent on rainfall, soil stability and disturbance regime. Some components recover linearly, while other components, or the same components in different regions, recover non-linearly. A global model will be presented; 2. Resistance to Bromus invasion in arid lands can be defined by landscape characteristics (e.g., landscape position, soil chemistry). We will discuss how these factors determine whether an area will be invaded; 3. In east Africa, pastoralists create nutrient hotspots when they abandon old livestock corrals, leaving behind a nutrient signal for up to a century. In more arid systems, these hotspots can lift tree regeneration above a survival threshold and can initiate a transition from open grassland into wooded savanna. Rainfall and soil fertility determine how bright these spots appear on landscapes and how likely they will create non-linear effects cascading through the structure of these systems.
KEY WORDS: Nutrient cycles, Non-linear response, Disturbance, Human influence