Overview: 2005 Protocol Comparison Test Brett Roper National Aquatic Ecologist, USDA Forest Service (435)

Analysis For Means, STD, CV proc glm data= ***; class stream; model BW = stream; run; To decompose variance proc mixed data=***; classes stream; model BW =; random stream; run; To determine stream means and difference among streams proc mixed data=***; classes stream ; model BW = stream; lsmeans stream /pdiff adjust=tukey; ods output diffs=ppp lsmeans=mmm; ods listing exclude diffs lsmeans; run; %include 'c:\BBRfile\stats\sasmacros\pdmix800.sas'; %pdmix800(ppp,mmm,alpha=0.1,sort=yes); run; No analysis yet to determine significant differences among groups

Proc GLM statement Source DF Squares Mean Square F Value Pr > F Model <.0001 Error Corrected Total R-Square Coeff Var Root MSE grad Mean Proc Mixed statement Covariance Parameter Estimates Cov Parm Estimate Stream Residual

Output of the PDMIX statement for gradient from one group Standard Letter Obs Stream Estimate Error Group 1 Myrtle A 2 Whisky B 3 Indian C 4 Crawfish C 5 WF Lick D 6 Tinker DE 7 Potamus DE 8 Trail EF 9 Big F 10 Crane F 11 Camus F 12 Bridge F

Group 1 = Group What should the results of an aquatic habitat protocol comparison look like?

What is a good attribute For categorization – Very little  Rosgen large classes For status and trend –Minimum S:N of around 2, % stream ≈ 70% (I would prefer S:N of 4 and stream ≈ 80% Coefficient of variation ≈ 20%

Attributes Gradient Bankfull Width Wetted Width Width-to-Depth Sinuosity Entrenchment % Pool Residual Pool Depth %Fines Median Particle Size D 84 Large Wood Large wood volume

Gradient Group 1Group 2Group 3Group 4Group 5Group 6 Mean RMSE CV Stream Error Total S:N %Observer %Stream Groups

Myrtle Crane

Gradient; Results Can be shared? (R 2)

Bankfull Width Group 1Group 2Group 3Group 4Group 5Group 6 Mean RMSE CV Stream Error Total S:N %Observer %Stream Groups

truth GRP 1 GRP 2 GRP 3 GRP 4 GRP 5 GRP 6 truth Group Group Group Group Group Group Correlations among all stream width groups and the truth (remember these are mean values compared to the truth)

Wetted Width Group 2Group 4Group 5Group 7Group 8 Mean RMSE CV Stream Error Total S:N %Observer %Stream Groups 85765

Width to Depth Group 1Group 2Group 3Group 4Group 5Group 6 Mean RMSE CV Stream Error Total S:N %Observer %Stream Groups

Width to Depth Big Crawfish

Sinuosity Group 1Group 2Group 3Group 5 Mean RMSE CV Stream Error Total S:N %Observer %Stream Groups

Entrenchment Group 1Group 2Group 3Group 4Group 6 Mean RMSE CV Stream Error Total S:N %Observer %Stream Groups

Entrenchment Big Crawfish

Percent Pool Group 1Group 2Group 3Group 4Group 5Group 7Group 8 Mean RMSE CV Stream Error Total S:N %Observer %Stream Groups

Myrtle Crane Lets look at Percent Pool

Can data be shared? Some yes Some No. (R 2)

Residual Pool Depth ResPoDepRPD RESIDPDRPDAvgRPDmRPD Group 1Group 2Group 3Group 4Group 5Group 7Group 8 Mean RMSE CV Stream Error Total S:N %Observer %Stream Groups

Median Particle Size (54.4 mm) Group 1Group 2Group 3Group 5Group 7 Mean RMSE CV Stream Error Total S:N %Observer %Stream Groups 44433

D84 (155.1 mm) Group 1Group 2Group 3Group 5Group 7 Mean RMSE CV Stream Error Total S:N %Observer %Stream Groups

% Fines Group 1Group 2Group 3Group 4Group 5Group 6Group 7 Mean RMSE CV Stream Error Total S:N %Observer %Stream Groups

Bank Stability stab2pct100-unstabBNK100-pcterosionPctStab Group 1Group 2Group 4Group 7 Mean RMSE CV Stream Error Total S:N %Observer %Stream Groups 2441

Large Wood >=3m_Cnt1 00mLWD3x30LWDlwdpiece1LWD_L Group 1Group 2Group 3Group 4Group 7Group 8 Mean RMSE CV Stream Error Total S:N %Observer %Stream Groups646425

Large Wood (volume) LWD_Cat1- 2_allLen_Vol100m LWD_Cat1_allLen_ Vol100mVLWDlwdvol1 Group 1Group 2Group 3Group 4 Mean RMSE CV Stream Error Total S:N %Observer %Stream Groups 4431

How I summarized A: S:N >9, stream variability 90%, CV < 20% B: S:N >4, stream variability 80%, CV < 20% C: S:N > 2, Stream variability 70% or CV around 20% D: S:N close to 2, stream variability more than 50%, or CV around 20%. F: Anything lower.

GRP 1 GRP 2 GRP 3 GRP 4 GRP 5 GRP 6 GRP 7 GRP 8 GradientA(1)AABAB BF WidthA(1)AACCB Wetted Width A AA(1) AA WDDFC(1)FFF SinuosityDCA(1) B EntrenchmentFFF(1)F F % PoolFFFBF DA(1) Res Pool DepthAAABA(1) CB D50B(1)CC F F D84BBA(1) B C FinesB(1)FFCBFF Bank StabilityDB A(1) F LWD #A(1)CBB DC LWD VolumeB(1)CFF

Preliminary Observations Some attributes everyone does passable at: gradient, bankfull width, wetted width, residual pool depth. –For these attributes it is likely that cross walks can be determined not only with e ach other but with the truth. Only one attribute that nobody does well at; entrenchment. –Although nobody does well with this one it may not matter since it will only be used for classification; but if that is true why not as a group agree on an AML. For remaining attributes – width to depth, sinousity, % pool, D 50 D 84, fines, bank stability, and large wood volume – some groups have better (more consistent within the group) protocols than others.

Some thoughts on why certain attributes were done better when there was variation in the protocols Ratio things (Sinuosity, width-to-depth, and entrenchment) were done better with laser level. Extensive training resulted in more consistent sediment (fines and particle distributions, and large wood (counts and volume). Pools were best done with a fixed length.

How do we decide what to measure Bankfull width vs wetted width Bankfull width has hydrologic meaning, can be measured if the stream is dry. Not affect by season. Wetted with more consistently measured, is a measure of summer aquatic habitat (nice to know a stream is dry)

What’s next? LiDAR Determine what steps should be taken to standardize protocols. –Continue efforts to develop crosswalks. –Should data quality control recommendations be made. –Seek consensus on the best protocol(s) to use. Determine which attributes provide useful data. Proposal was submitted for BPA funding for follow up work. Publication of the John Day basin protocol test results.

Questions ?