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Small Lakes Management Plan: Region 5 PowerPoint Presentation
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Small Lakes Management Plan: Region 5

Small Lakes Management Plan: Region 5

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Small Lakes Management Plan: Region 5

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  1. Small Lakes Management Plan: Region 5 Small Lakes Committee Meeting Nov. 22-23, 2007

  2. Overview: SLMP • Part I - Complete inventory of R5 lakes (Kamloops template) • Identify data gaps (lack of assessment wild stocks…) • Identify management challenges: - Water management - Bass

  3. Part II: Management Plan • Part II - Specific management plan (what we’re looking to achieve, quantifiable performance measures, etc.) - Shift in management structure (i.e., manage on an area scale rather than on a lake by lake basis) • Develop 4-5 management “areas” or “zones” - likely base on geographic location • Develop quantifiable performance measures for each “area” - economic (stocked lakes) - management measures (% family, general, trophy) - reference points for effort on wild lakes

  4. Predictive model for stocked lake fisheries in the Cariboo • Regression model approach (GLM) • Similar to a multiple regression - quantify relationship between several independent or predictor variables and a dependent criterion variable

  5. Effort Data • Effort data from aerial boat counts • Included all stocked lakes for which effort data exists since 2000 (69 lakes) • Standardized effort (angler days/ha)

  6. Explanatory Variables • Initial variables: - Sterile - Surface area - Boating restriction - Gear restriction - Stocking rate - Access - Lodge - Campsite - Distance from Kamloops - Biogeoclimatic zone - Bag limit

  7. GLM: Model Function • Conducted GLM using all variables • Ran through AIC procedure - removes variables that are not very influential in explaining variability in angler effort • Repeat above procedure for 100 representative data sets - determine number of times each variable was selected

  8. Variable selection: - Campsite (63/100) - Triploid (53/100) - Gear restriction (53/100) - Surface area (56/100) - Bag limit (58/100) ->high degree of uncertainty of actual influence of these variables in explaining variation in angler effort -> Removed: Campsite, GR, BL, Triploid, and Surface Area variables

  9. Finalized Model • Selected variables: - Access (100/100) - Stocking rate (99/100) - BEC (97/100) - Distance from Kamloops (92/100) - Lodge (83/100) - Boat restriction (75/100) • 65% of variability explained

  10. Lake: Distance from Kamloops = 150 km Stocking rate = 200 fish/ha Factor df log-Coefficient Coefficient Prediction (AD/ha) Intercept 1.17 3.20 3.20 Lodge 1 0.47 1.60 5.13 Access 1 1.25 3.49 17.90 Boat restrict 1 0.85 2.34 41.89 SBSZ (BEC) 7 0.37 1.45 60.64 Stock rate 1 200(0.002) 1.49 90.47 Kamloops 1 150(-0.002) 0.74 67.02 ***All coefficients were significant (P < 0.01)

  11. Benefits of model - Predict results of manipulating different management factors - Detect outliers (lakes that should attract more/less effort given its location and characteristics) ->Identify lakes in need of further work (i.e., biological assessment) - SIMPLE

  12. Current Performance of Stocked Lake Fisheries in Region 5 • Typically measure success in angler days • Need to make economic link -> make most efficient use of minimal resources • Benefit:Cost ratio is common measure of economic efficiency

  13. Economic Benefits • 2000 Survey of Sportfishing in BC (Levey & Williams, 2003) • Provincial average $/AD = 48 • Region 5 average $/AD = 66 (Above average proportion of non-resident angler days in Cariboo region)

  14. Production Costs Production ($) Probable ($) High ($) 2N 3N2N3N2N3N Fry: 0.16 0.184 0.30 0.324 0.46 0.484 FG: 0.12 0.128 0.26 0.264 0.42 0.424 YE: 0.21 0.242 0.35 0.382 0.51 0.542 KO: 0.16 0.184 0.30 0.324 0.46 0.484 CA: 0.73 0.73 0.99 EB: NA 0.206 NA 0.346 NA 0.506

  15. Proposal example: Simon Lake aerator? • Simon Lake: Lodge (No), Access (Yes), Boat restriction (No), BEC (IDFZ), Stocking rate (187/ha), Distance from Kamloops (211km) • Predicted Effort = 10.5 AD/ha • Surface area of Simon Lake = 78.3 ha • Predicted Effort = 10.5 AD/ha * 78.3 ha = 822 ADs • Gross revenue = 822 Ads * $66/AD = $54 252 • Cost of stocking = $4530 • Cost of running an aerator = $5 000 • Net revenue = $54 252 - $4530 - $5 000 = $44 722 • B:C ratio = 54 252/9530 = 5.7:1