APPENDIX 1. EDT Translation Model We used the EDT model (Mobrand Biometrics 2004) in two different ways in this analysis. The first use of the EDT model was to generate a restoration strategy based on the reach level restoration and preservation prioritization output from EDT (Table A1 and A2). The second use of the EDT model was to evaluate the future landscapes. Using EDT to evaluate future landscapes required a translation between restoration actions and EDT input data (Table A3).

EDT Translation Model

We used the EDT model (Mobrand Biometrics 2004) in two different ways in this analysis. The first use of the EDT model was to generate a restoration strategy based on the reach level restoration and preservation prioritization output from EDT (Table A1 and A2). The second use of the EDT model was to evaluate the future landscapes. Using EDT to evaluate future landscapes required a translation between restoration actions and EDT input data (Table A3).


Table A1. The prioritization system for allocating funds to EDT reaches based on EDT output. Fifty percent of available funds were designated for restoration and 50% for protection. The same reach-level prioritization system was used to allocate funds independently for restoration and for protection.

Basis for Prioritization
Prioritization Notes
EDT model rankings for restoration or protection benefit
Select the reaches with the highest EDT restoration or protection benefit ranking If funds remain after treating all reaches identified as high priority, move to the reaches identified as intermediate priority.
Reach type: Spawning versus non-spawning reaches. Mainstem versus tributary reaches
Start with the spawning reaches. If funds remain after all high priority spawning reaches are treated, move to high priority mainstem reaches
Reach location
Within the high priority spawning (or migration) reaches, select the most upstream reach first.



Table A2. Translation from EDT model output for current conditions within each reach prioritized for restoration or preservation to the EDT watershed management strategy. Fifty percent of the funds were spent on restoration actions. Habitat attributes identified by EDT, by reach, as the most important were “fixed” first. Numbers in each cell represent the prioritization of restoration actions within each row. If there were two habitat attributes that were most limiting, we started with the cheapest problem to fix. All protection funds were spent on riparian protection or restoration. If the current riparian condition was good (as rated by the remotely-sensed riparian model in Table 4), riparian conditions were protected. If the current condition was fair or poor (as rated by the remotely-sensed riparian model in Table 4), riparian conditions were restored.

EDT Habitat Attribute Restoration Actions
Restore Riparian
Decommission Roads
Remove Barriers
Restore for Spawning
Restore Floodplaina
Key Habitat



1
2
Temperature
1




Sediment Load
2
1



Obstructions

1


Habitat Diversity




1
Food
1




Flow
1
2



Chemicals
1b




Channel Stability
1
2



a Only areas that historically had floodplains could be treated with floodplain restoration.
b If the habitat element was chemicals, riparian areas were only treated if the uplands were currently classified as agricultural or urban land-use.


Table A3. Model used to translate conservation actions in management strategies into data in a format ready to be used as inputs by the Ecosystem Diagnosis and Treatment (EDT) model. All actions were subject to 4 constraints: (1) the proportion of each EDT reach affected by a strategy was equal to the proportion of affected SSHIAP reaches comprising an EDT reach; (2) new EDT scores affected by conservation actions were constrained between patient and template scores and trended toward the template; (3) actions only affected scores if there was a potential for change; i.e., patient – template not equal 0; and (4) if >1 actions each changed EDT scores, only the largest was registered if effects were in the same direction but the sum of effects was registered if effects of actions had different directions. Abbreviations used are as follows: p∆ = potential for change; p(reach) = proportion of the EDT reach affected; ↑ = improve score. Conditions: †1 if any part of riparian area was originally urban and at least 50% of the reach is protected/restored; †2 also improve the next downstream reach in the same way; †3 if LWD or PFC function improves.

EDT Attribute
Decommission Roads
Protect or Restore Riparian
Restore Floodplain Connectivity
Restore Spawning Habitat
Bed Scour
Scour Depth is estimated directly from the modeled 2.3 year flood flow as Depth  = 10*sqrt(flood discharge/bankfull width) (from Emmett and Leopold 1965), then converted to EDT ratings.
Embeddedness
↑ score by p(reach) where roads are restored * ∆ in % covered (as estimated based on road density).
↑ score by p(reach) restored.

New score is the p(reach) restored/protected * p∆.
Diel Variation in Flow

↑ score by ½ p(reach) where riparian area was urban * p∆.†1


Fine Sediment Deposited
↑ score by p(reach) where roads are restored * ∆ in % fines (as estimated based on road density)* 1.34.



High Flow
High Flow was calculated as the %∆ in modeled 2.3 year flood flow from historical, and then converted to EDT ratings.
Large Woody Debris Recruited

New score is the p(reach) restored/protected * p∆.†3

New score is the p(reach) restored/protected * p∆.†3
Miscellaneous Toxic Wastes

↑ score by p(reach) where riparian area was urban * p∆.†1


Monthly Max Temperature

New score is the p(reach) restored/protected * p∆.†2


Nutrient Enrichment

↑ score by p(reach) where riparian area was agriculture * p∆.†1


Channel Confinement resulting from hydrological modifications


New score is the p(reach) restored/protected * p∆.

Off-Channel Habitat


↑ score by p(reach) where floodplains were restored * p∆.

Riparian Functions

New score is the p(reach) restored/protected * p∆.
New score is the p(reach) restored/protected * p∆.

Small Cobble- Dominated Habitat



New score is the p(reach) where spawning habitat is restored * p∆.
Turbidity
↑ score by p(reach) where roads are restored * 0.3 * ∆ in road density.
↑ score by p(reach) restored * 0.3.