States and Transitions in Succession Plant Community Succession

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States and Transitions in Succession

States and Transitions in Succession

Plant Community Succession (Initial Ideas – F. E. Clements) Natural Potential Climax or Potential

Plant Community Succession (Initial Ideas – F. E. Clements) Natural Potential Climax or Potential Natural Community Large Variation Between Years Pioneer/Early Seral Stage Late

Plant Community Succession (Initial Ideas -- Clements) ive s s gre Pro ession infall

Plant Community Succession (Initial Ideas -- Clements) ive s s gre Pro ession infall c ra Suc rage Climax or Potential Natural Community ve ea bov Natural Potential A al ion s s ce Suc ency tend ss e r g o Retr ion ht ug Dro ure s s e g Pr zin Gra Pioneer/Early Seral Stage Late

Example -Succession in the western juniper woodland Grassland after fire Open young juniper Mountain

Example -Succession in the western juniper woodland Grassland after fire Open young juniper Mountain big sagebrush steppe Young multistory juniper Stand initiation juniper Old multistory juniper

Cyclic Patterns creating a “Dynamic Equilibrium” 1979 - Pre-burn 1980 - 1 st year

Cyclic Patterns creating a “Dynamic Equilibrium” 1979 - Pre-burn 1980 - 1 st year after fire 1994 1983 1989

Problems with Succession Model • multiple pathways of succession • multiple stable vegetation types

Problems with Succession Model • multiple pathways of succession • multiple stable vegetation types • no single and certain end-point Two examples of stable states for same ecological site Wyoming big sagebrush/bluebunch wheatgrass steppe near Mtn. Home, ID Wyoming big sagebrush/bluebunch wheatgrass steppe, central Idaho

Problems with Succession Model • multiple pathways of succession • multiple stable vegetation types

Problems with Succession Model • multiple pathways of succession • multiple stable vegetation types • no single and certain end-point State and Transition Models 1989 - Westoby, Walker and Noy-Meir

Focus on States of communities and Transitions between states State A State D State

Focus on States of communities and Transitions between states State A State D State B State C

States and Transitions depend on biotic & abiotic conditions States are relatively stable but

States and Transitions depend on biotic & abiotic conditions States are relatively stable but some states are more stable than others Creosotebush community -this ecological site may have always been creosotebush dominated, or degraded long ago.

States and Transitions depend on biotic & abiotic conditions Juniper Present Low Cheatgrass Risk

States and Transitions depend on biotic & abiotic conditions Juniper Present Low Cheatgrass Risk Higher Elevation Southwestern Idaho Higher Elevation Central Idaho Cheatgrass Risk Lower Elevation Central Idaho States and stability depends on factors such as elevation & climate

Example - Sagebrush Steppe States Grassland Open Sagebrush Depleted Sagebrush Closed Sagebrush Transitions= compositional

Example - Sagebrush Steppe States Grassland Open Sagebrush Depleted Sagebrush Closed Sagebrush Transitions= compositional change resulting in the change in plant community (state) Fire transition Succession transition Improper grazing transition

Sagebrush Steppe State Grassland Open Sagebrush Depleted Sagebrush Closed Sagebrush Threshold Annual Grass Dominated

Sagebrush Steppe State Grassland Open Sagebrush Depleted Sagebrush Closed Sagebrush Threshold Annual Grass Dominated State Grazing reduces likelihood of fire Thresholds = transitions that are nearly irreversible & sometimes unpredictable.

The information required to develop these models: • potential alternative vegetation states on a

The information required to develop these models: • potential alternative vegetation states on a site • potential transitions between states • opportunities to achieve favorable transitions between vegetation states and hazards to avoid unfavorable transitions

Rangeland Ecology and Management Rangelands are Dynamic! • But, dynamic patterns can be describe

Rangeland Ecology and Management Rangelands are Dynamic! • But, dynamic patterns can be describe in state and transition models. • We manage transitions