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Performance-Based Forest Land Management (some implications). Don Reimer D.R. systems inc., Nanaimo, B.C. Key Features of PBFM. Forecast of future expectations resource inventories projection system(s) model(s) & assumptions Measurements of achievements monitoring systems
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Performance-Based Forest Land Management(some implications) Don Reimer D.R. systems inc., Nanaimo, B.C.
Key Features of PBFM • Forecast of future expectations • resource inventories • projection system(s) • model(s) & assumptions • Measurements of achievements • monitoring systems • reporting systems • Adaptive Management Process • continuous improvement
Features of PBFM Data • The data you have is not the data you want • The data you want is not the data you need • The data you need you cannot get • The data you can get you cannot afford
HCP Scope and Timetable • Project took 2 years to complete (1994 - 1996) and involved a project team of 15-20 scientists and analysts. • Project used a “multi-disciplinary, science-team approach” to defining habitats and habitat management objectives • The science team based their work on the substantial amount of work done by Plum Creek previously on spotted owl habitat and spotted owl activity patterns as well as published work done by other gov’t and industrial researchers and biologists on the relevant endangered species present. • The Cascades HCP included habitat considerations for all 285 vertebrate species which were thought to be found on Plum Creek’s land base. These species were grouped in guilds/lifeforms. Habitat requirements and habitat definitions were established for the lifeforms by the science team. • All scenarios and analyses were based upon a spatially-explicit modeling approach. All resource inventories, resource constraints, land management operating rules, and habitat requirements were entered into a common, multi-layer GIS database. • D.R. systems inc. did all of the modeling and business and spatial analyses associated with the project.
Land Ownership (acres) Plum Creek 169,200 Forest Service 201,800 State & Private 41,100 Lakes 6,800 Total Project 418,900 Featured Species Northern Spotted Owl Marbled Murrelet Gray Wolf Grizzly Bear 281 Other Species
Stand Structures Seedling/Sapling Dispersal Forest Old Growth
Quantitative Monitoring Program QMP Objective Improve and/or verify the accuracy of information being used for HCP monitoring to foster confidence in the information for the users (PC) and the reviewers (Services and the general public) Development of QMP - Improved Inventory Stand Level Cruise Criteria Established % to Cruise by Stand Type Established Frequency by Stand Type Verification Site Index / Age Stand Structure Growth Monitoring
Quantitative Monitoring ProgramStand-level cruising criteria HCP Commitment “Accelerate Inventory Schedule to Obtain More Precise Information” Cruising Status 1996 2,978 acres 1997 28,334 acres
Tracking habitats for 285+ species Terrestrial Monitoring Overview Habitat parameter Species Verification • spotted owl • marbled murrelet • grizzly bear/gray wolf • goshawk • snags • down wood • understory vegetation • resident birds • stream amphibians • snag/recruitment tree retention
Aquatic Habitat and Resource Monitoring Watershed Analysis Landscape-Wide Habitat Conditions Biotic Integrity Stream Temperature
Annual Reporting % Plum Creek Lands . Actual . Proj. 1/1/97 1/1/981/1/992001 Spotted Owl Habitat Nesting, Roosting & Foraging 20 18 16 16 Foraging & Dispersal 17 16 17 14 Total 37 34 33 30 Stand Structures Stand Initiation 3 4 4 9 Shrub & Sapling 7 5 8 9 Young Forest 36 36 34 34 Pole Timber 7 9 10 7 Dispersal Forest 15 16 17 13 Mature Forest 19 17 16 16 Managed Old Growth 3 3 2 3 Old Growth 2 2 1 1 Non Forested 8 8 8 8 Total 100 100 100 100
Annual Reporting % Total HCP Acres . Actual .Proj Lifeform HabitatArea1/1/971/1/981/1/992001 2 Frogs, Salamanders RHA 71 71 72 71 3 Turtles, Ducks RHA 71 71 72 71 4 Goats, Falcons Talus 60 59 58 57 5 Elk, Hares Edge 88 88 88 89 6 Warblers, Porcupines RHA 62 61 60 62 7 Sparrows, Thrushes RHA 73 75 75 74 8 Flycatchers HCP 70 69 70 67 9 Waxwings, Grosbeaks RHA 68 70 66 71 10 Squirrels, Tanagers HCP 68 68 67 62 11 Hawks, Vireos HCP 69 70 69 66 12 Herons, Osprey RHA 54 56 58 55 13 Woodpeckers HCP 61 61 58 54 13a Lewis’ Woodpecker HCP 53 53 50 47 14 Bats, Owls HCP 66 65 64 63 14a Vaux’s Swift, Fisher HCP 32 30 28 27 15 (Young) Shrews HCP 46 45 46 52 15 (Middle) Bears HCP 22 25 27 20 15 (Late) Voles HCP 24 22 19 20 16 Otters, Beavers RHA 71 71 72 71
Changes in Land Mgmt • As we address other resource objectives we are dramatically changing how we manage the landbase.
RHAs / Inner Gorge 100 ft Jade Creek 200 ft Bam Bam
Talus Slope Cedar View North Slope
200 ft RHA Silverback After Before Cabin Creek
Wetlands G-Bear Buffer Bear Clean Landscape Diversity Flyover Helicopter
Inner Gorge / Talus Slope Real Tree Tree Line
Five-Year Reporting Issues • Changes to the landbase (large-scale trades with the USFS and some smaller sales to special interest groups). Resulted in a net loss of 40,000 acres in Plum Creek ownership • Big push on forest inventory - lots of new samples • Change from mgmt blocks to forest cover polygons
Five-Year Reporting Issues - cont. • Changes to habitat definitions • Changes to the reporting expectations • Required reporting precision levels • Model versions (upgrades over time)
Landbase Changes • Net loss was 40,000 acres but trade involved over 90,000 acres • Much of the high quality, older seral habitat was traded away • The USFS lands received by Plum Creek had poor inventory data
Forest Inventory Changes • HCP required dramatic improvement in %-age of cruised stands - ranked by seral stage • USFS lands had to be re-cruised (25% of new net landbase)
Habitat Definition Changes • Switched from management blocks to forest cover polygons • Had to change habitat definitions to match biologists’ map calls on habitat
Reporting Expectations • PC and the agencies had independently agreed to +/- 10% error in habitat statistics • Focus was on owl habitat and older seral stages (error +/- 0.5% on NRF!) • Reduction in landbase dramatically affected the range of allowable error (as low as +/- 0.2% error on NRF!) • Over time PC and agencies wanted the same numbers across all 45 years
Modeling Changes Upgrades • Software upgrades themselves were not a problem. But proving there were no effects with each upgrade was a problem due to all other changes. • Switch to forest cover polygons • Continual upgrades of forest inventory • Changes to habitat definitions • Drawn out land exchange process
What Have we Re-Learned (supposedly we already know this) • Never underestimate the power of senior management on both sides to create an impossible situation • It is absolutely critical that all data components in the DSS be design compatible • There never is enough money to do it right
What Have we Really Learned • Our current concepts and designs for forest inventory no longer are adequate • Growth and Yield forecasting has to go to stand tables (or tree lists) • We have to pay attention to underlying statistical rules and use them in establishing decision rules for all habitats. • Risk and Liability are not the same thing
What Have we Really Learned • Our so-called monitoring systems only indirectly are affecting results -- and the effects are relatively minimal to date • The big effects, even on lands which have not changed hands, have been inventory data changes and inventory data management issues • In the near-term, we have to devise improved methods to link habitat and environmental goals to broad-based inventory systems. In the long-term?
What Have we Really Learned • Between decision-makers and monitoring agencies we CANNOT handle changes in forecasts. • Decision makers do not like increases in habitat over original established/approved forecasts • Agency staff do not like decreases in habitat over original forecasts
What Have we Really Learned • Risk and Liability are very different concepts - this is critical when dealing with PBFM issues. • We tend to design inventories and other sampling systems from the viewpoint of risk • Liabilities may be linked to degrees of risk - but are often based upon an assumption that there exists a reasonable avoidance of risk.