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Hellgate, Dead Diamond River

Predicting Cold Water Fish Community Presence In New Hampshire for Implementation of Dissolved Oxygen Criteria. By David Neils. Hellgate, Dead Diamond River. Background. CWA requires states to report on status of waters [305(b)/303(d) report]

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Hellgate, Dead Diamond River

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  1. Predicting Cold Water Fish Community Presence In New Hampshire for Implementation of Dissolved Oxygen Criteria By David Neils Hellgate, Dead Diamond River

  2. Background • CWA requires states to report on status of waters [305(b)/303(d) report] • NH DES establishes water quality standards by which to make assessments of water quality (Env-Ws 1700) • Specifically, Env-Ws 1703.07 which outlines NH’s dissolved oxygen criteria: * Period from Oct. 1 – May 14 or June 30 for spring / late hatch fall spawners

  3. Current application of cold water fish spawning area DO criteria • Approximately 10,000 miles of streams • In 2004 305(b)/303(d) equated to 3,189 assessment units • 24 units (<1%) assessed as cold water fish spawning areas using more stringent DO criteria (= 47.5 miles) Current application is restricted to fisheries where field collections of cold water gamefish indicate successful spawning (i.e presence of YOY and/or multiple year classes). Obviously highly accurate, but limited in statewide application.

  4. Biological Community A Biological Community B Environmental Conditions Water-based Climate – cold Physical location – far north Environmental Conditions Terrestrial Climate – warm Physical location – southern hemisphere Community Classification – An alternative approach Basic premise: biological communities are, in part, structured by the physical and chemical environmental conditions in which they live. If distinct biological communities can be identified, then the variables that define them can be defined.

  5. Classifying Stream Fish Communities • Not a new concept – has been widely researched and utilized as tool for grouping similar fish community types • Context for current application is identification of similar community types for purpose of assessing water quality (i.e. cold water fish communities require higher DO levels for natural populations to persist) • Additional application is identification of similar community types for purpose of community condition assessment – biological indices or models built specifically to determine condition of different types of communities

  6. Objectives • To determine if a model could be built that predicts where cold water fish communities occur or should occur • Decide what variables are important in determining the presence or absence of cold water fish communities • Assess the practicality of applying the model’s results statewide

  7. Dataset • NH DES biomonitoring fish collections 1997 – 2003 • Limited to 1st – 4th order streams sampled from June – August • 186 stations included in analysis (eliminated sites known to have significant human disturbance • Broken in calibration (152 sites) and validation (34 sites) datasets • Analysis based on presence / absence occurrence • A minimum of 5 individuals collected at site to be considered “present” Walker Brook, Mason, NH

  8. Identification of target species Need to identify what species define coldwater fish communities (Not “classification” in strict sense) Requirements for target species: • Cold water “specialists” • >30 occurrences in dataset • Known to have statewide distribution • Native to NH Result: Brook Trout (Salvalinus fontinalis) and Slimy Sculpin (Cotus cognatus)

  9. Brook Trout (Salvalinus fontinalis) Habitat (FromScarola):“requires year-round supply of cold, oxygenated water and sufficient areas of gravel on which to spawn. Without these it will not survive” Reproduction: Fall spawner (Oct. – Nov.); eggs develop through winter and larvae (yoy) emerge in early spring. Slimy Sculpin (Cottus cognatus) Habitat: Small rocky bottomed streams; strictly limited to cold water Reproduction: Spring spawner (Apr. - May); eggs develop in 3 – 4 weeks followed by larval emergence.

  10. Requirements • Permanence – Variables that resist change • Good Example: Elevation • Bad Example: Substrate composition • Ease of collection – Variables that can be obtained quickly, accurately • Good Example: Latitude • Bad Example: Flood prone width • Natural range of variability – Variables that are robust • Good Example: Watershed size • Bad Example: Stream bank slope Selection of Predictor Variables Candidate Variables • Latitude – dd.dddd • Longitude – dd.dddd • Elevation – feet • Watershed Area – square miles • Major River Basin – Merrimack, Piscataqua, Saco, Connecticut, Androscoggin • Ecological Drainage Unit (EDU) – Androscoggin, Upper CT, Lower CT, Merrimack/Coastal

  11. Results: Independent Variable Examination * * * Continuous Variables: Variable Means Categorical Variables: EDU: Frequency distribution significantly different than that expected by chance Major River Basin: Frequency distribution significantly different than that expected by chance

  12. CW community present CW community absent WMNF Boundaries Distribution of calibration dataset cold and non-cold water fish communities sampled by NH DES biomonitoring unit 1997 – 2003. • More frequent in north • More frequent at higher elevations • More frequent in smaller watersheds • Less frequent in Merrimack and Coastal areas

  13. Simultaneous Variable Consideration • OK – So 5 of 6 variables are show differences b/t cold and non-cold water fish communities, but how do the variables inter-relate? • We need another analysis tool… • Logistic Regression: yes, I’ll spare you the details • What you need to know: • Each variable is examined for its relative importance (similar to step-wise linear regression) • Regression equation assigns each site a probability (0 – 1) of being a cold (1) or non-cold (0) water fish community based on important variables • Predictive accuracy (i.e. # correct predictions) of model as measure of success

  14. 1 Predict Present P(present) > 0.50 0.8 Individual Point 0.6 Probability of occurrence 0.4 Predict Absent P(present) < 0.50 0.2 Environmental Gradient 0 1 1 + exp (-α – β1X1-.. βiXi) P(present) = Logistic Regression Overview S-shaped predictive curve resulting from Regression Equation

  15. Preliminary Model Results * sig. change w/ 1 df Neither watershed size or drainage basin explained significant portion of variation

  16. Preliminary Model Results Select Model 1 for simplicity – Latitude is the overwhelming predictor of cold water fish community presence / absence. For every 1 degree change in latitude, 14x change in expected fish community type.

  17. Observed Present Observed Absent Predict Present 1 1 Predict Present 0.8 0.8 Errors 0.6 0.6 P(present P(present) Predict Absent Predict Absent 0.4 0.4 Errors 0.2 0.2 0 0 42.5 43 43.5 44 44.5 45 45.5 42.5 43 43.5 44 44.5 45 45.5 Latitude (dd.dddd) Latitude (dd.dddd) Cold Water Fish Community Predictive Regression Equation • Predictive model based solely on latitude • Nearly 80% accurate • P(present) threshold of 0.50 = latitudinal breakpoint @ ~43.7oN

  18. Observed Present Observed Absent 1 Predict Present 1 Predict Present 0.8 0.8 Errors 0.6 0.6 P(present) P(present Predict Absent 0.4 0.4 Predict Absent Errors 0.2 0.2 0 0 42.5 43 43.5 44 44.5 45 45.5 42.5 43 43.5 44 44.5 45 45.5 Latitude (dd.dddd) Latitude (dd.dddd) Exploring Predictive Errors Type I – Reject null hypothesis when it is true For model – predicting CW present when observed absent Minimizing Type I errors is less protective, minimizes chances of applying strict DO std. to non-CW communities Type II - Do not reject null hypothesis when false For model – predicting CW absent when observed present Minimizing Type II errors is more protective (i.e. captures all sites where CW observed present), but run high risk of applying unnecessarily strict standard

  19. Obs - Absent Obs - Present Model Adjustments Probability threshold adjusted to compare results: 1 Few Pink (min. Type I) 0.8 0.6 P(present) 0.4 0.2 Few Yellow (min. Type II) 0 42.5 43 43.5 44 44.5 45 45.5 Latitude (dd.dddd) * Remember above line = predicted present; below line = predicted absent

  20. Final Model Adjustments • Maximum predictive accuracy for validation dataset achieved at 70% probability threshold (72.1%; 25 of 34 sites). • At the 70% threshold model predictions were better than those made by chance. • Inaccurate predictions occurred more frequently at sites observed to have cold water fish communities but predicted to have non-cold cold water fish communities (Type II; 6/15) vs. sites observed to have non-cold water fish communities but predicted to have cold water fish communities (Type I; 3/19). Final Recommendation: Utilize model based on latitude with a 70% probability of occurrence threshold

  21. Reality….Or what the results look like on a map N 43.9850 1 0.8 0.6 1 P(present) = 1+exp[4.395 + 2.641(latitude)] Logistic Regression Function 0.4 0.2 0 42.7 42.9 43.1 43.3 43.5 43.7 43.9 44.1 44.3 44.5 44.7 44.9 45.1 Latitude (dd.dddd)

  22. Non-cold almost twice as high as cold (predicted and observed) • Cold and Non-cold communities above 6.5 pH criteria • Cold higher than non-cold 8.0 mg/L – Instantaneous Minimum 9.5 mg/L – 7-day Mean Minimum Model Prediction Correspondence with Water Quality Data

  23. The model is “conservative” in nature • Additional refinement is suggested • Best professional judgment (better known as common sense) should be included • Models aren’t always right • This is a “first approximation” • Can we agree that all areas predicted as “cold” should be regulated as such

  24. Policy Application / Consideration • Broader implementation of water quality criteria • Potential utilization as regulatory requirement • Trade-off between over vs. under protective criteria • Requires acceptance by regulating entity Technical Application / Consideration • Model improvement requires collection of additional “supplementary” data • Utilization of statewide fish data would be beneficial • Current analysis includes some sites with stocked gamefish • Is there a better way?

  25. An added bonus (or the real reason you might want to know where to find cold water fish communities): David Neils Biomonitoring Program NH Dept. Env. Services 29 Hazen Dr. Concord, NH dneils@des.state.nh.us 603.271.8865

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