Using the Landscape Management System (LMS) James B. McCarter, Kevin W. Zobrist Rural Technology Initiative, University of Washington

Size: px

Start display at page:

Download "Using the Landscape Management System (LMS) James B. McCarter, Kevin W. Zobrist Rural Technology Initiative, University of Washington"

Augustine Andrews
6 years ago
Views:

1 Using the Landscape Management System (LMS) James B. McCarter, Kevin W. Zobrist Rural Technology Initiative, University of Washington

2 Introduction What is LMS? Using LMS Outline Stand Scale Analysis Landscape Scale Analysis Non-spatial landscape analysis Spatial landscape analysis Summary/Conclusions

3 Introduction Management of natural resources is becoming increasingly complex and the production and protection of those resources requires and increasing amount of analysis. Automated processes and development of software can streamline the analysis.

4 What is LMS? The Landscape Management System (LMS) integrates forest inventory, growth models, visualization, and analytical tools into a framework for evaluating stand- and landscape-level management alternatives.

5 What is LMS?

6 LMS Data Requirements Stand level information Site quality variables, age, area Tree inventory information tree list (individual tree data with expansion factors), Need Species, Diameter, and TPA, better to also have Height and Crown ratio Spatial information (for landscape visualization and spatial analysis) Need elevation model (USGS DEM, SDTS, ESRI ASCII Grid converted to PC-Plans DTM format), map of stand boundaries (ERSI shapefile or MOSS file), can add other spatial features (roads, streams, trails, etc)

outputs to Excel, Inventory Wizard, Economatic, Carbon sequestration, Wildlife habitat, etc.

7 LMS has evolved LMS 1.x : Proof of concept that a system could be built to integrate tree list models, visualization, and analytical tools. LMS 2.x : FVS and Organon growth models, visualization (SVS and EnVision), tabular outputs to Excel, Inventory Wizard, Economatic, Carbon sequestration, Wildlife habitat, etc. LMS 3.x : 2005-? Currently in beta, Organon and FVS growth models, 5+ times faster at simulation, visualization (SVS and EnVision), tabular outputs to Excel or Access, Inventory Wizard, larger portfolios possbile.

8 Stand Visualization LMS can easily create stand level visualizations using the Stand Visualization System (SVS, USDA Forest Service). At right is an example of a stand visualization of the inventory for stand BR_TRI in 2000.

the Pack Forest portfolio showing trees,

9 Landscape Visualization LMS can present landscape level visualization using EnVision (USDA Forest Service). At right is an example visualization for the Pack Forest portfolio showing trees, stand boundaries (orange), roads (brown), and streams (blue).

10 LMS Tables LMS can send tabular output to Excel, Access, or text files. Information ranges from raw inventory information to highly summarized information. LMS has a number of different tables available. Additional tables can be added easily.

11 Getting data into LMS LMS 3.0 can import data from a combination of Text, Excel, and Access files. Can be a long and cumbersome process. Import templates are available to streamline the steps. LMS 3.0 Inventory Wizard enter plot data Processes for corporate databases need to be developed

Simplified data input LMS Inventory Wizard The LMS Inventory Wizard provides a simple interface to enter plot level tree inventory data for use with LMS.

12 Simplified data input LMS Inventory Wizard The LMS Inventory Wizard provides a simple interface to enter plot level tree inventory data for use with LMS. Microsoft Access database Includes growth model specific codes Context sensitive help and tutorial Includes field data forms Creates LMS portfolios directly from the database

13 LMS Inventory Wizard Easy to use interface for entering several stands with multiple plots. Can go from plot data to examining alternative management approaches in minutes.

14 Using LMS Stand scale analysis Tabular, graphics, visualization outputs Landscape scale analysis Non-spatial landscape analysis Spatial landscape analysis Visualization GIS

15 Stand Scale Analysis Stand scale is appropriate because it is the traditional organizational unit for implementing management. Evaluate current conditions within a stand Meeting objectives within a single stand Achieving objectives with different stands

16 Evaluate Current Conditions Individual tree information Distributions of tree information Summarized tree information Visualization

17 Individual Tree Information Volume Crown Ratio Dbh (in) CU BF Etc WH STAND WH STAND WH STAND RC STAND DF STAND DF STAND DF STAND DF STAND1 MCU TPA Ht (ft) Species Stand Subset of inventory records for STAND1.

18 Distributions of tree information Diameter distribution for STAND1.

19 Summarized tree information Table 2. Summary statistics for STAND1. Where DBHq=quadratic mean diameter, DBHa=average diameter, TPA=trees per acre, AveHT=average height, TBA=total basal area, SDI=Reineke Stand Density Index, RD=Curtis Relative Density, TVolBF=total board foot volume Species DBHq DBHa TPA AveHt TBA SDI RD TVolBF DF RA RC WH TOTAL

20 Stand visualzation Profile view of STAND1 using Stand Visualization System (McGaughey 1997).

21 Meeting objectives - single stand One stand may provide different outputs based on management scenario. STAND1 no treatment STAND1A thinned STAND1B regeneration harvest

22 Singles stand multiple outcomes Year Stand Oliver SS Standing Volume Cut Volume 2000 STAND1 SE Oliver stand structures, standing volume, and cut volume for STAND1 under different management regimes.. (SI=stand initiation, SE=stem exclusion, UR=understory reinitiation) STAND1 STAND1 STAND1A STAND1A STAND1A STAND1B SE UR SE SE UR SI STAND1B SI STAND1 B SE

23 Meeting objectives - different stands Some stands are more suitable for achieving certain objectives than others. STAND2 is a 50 year old, low site Douglas-fir dominated stand. STAND3 is a young stand recently regenerated, dominated by Douglas-fir

24 Multiple stands multiple outcomes No Treat Thin Harvest & Thin 2000 STAND1 SE SE SI 2025 STAND1 UR UR SE Oliver structural stage classifications for three stands under three different management approaches. (SI=stand initiation, SE=stem exclusion, UR=understory reinitiation STAND1 STAND2 STAND2 STAND2 UR SE SE UR UR SE SE UR UR SE SI SE 2000 STAND3 SI SI SI 2025 STAND3 SE SE SE 2050 STAND3 UR UR UR

25 Landscape Scale Analysis Many management issues must consider changing stand characteristics across multiple stands in an area Non-spatial landscape analysis Spatial landscape analysis

26 Non-spatial landscape analysis Many landscape analyses can be done without the need for details spatial information (proximity not important) Proportional summarization

27 Non-spatial Landscape Analysis Balance of Oliver structures across the example landscape for no treatment scenario (a) and a limited harvesting scenario (b). a b

28 Spatial landscape analysis Many landscape analyses require spatial context (e.g. adjacency and connectivity) Some simple analyses are possible that do not require expensive data collection and GIS work.

29 Spatial Landscape Analysis Example spatial analysis showing number of patches (average patch size [acres]) for Oliver structures. Without treatments the landscape decreases in number and size of younger stand structures as more of the landscape becomes concentrated in the older structures. The Savanna structure is lost without disturbance or treatment OPEN 6 (22) 6 (17) 4 (28) 2 (50) 3 (36) 2 (20) DENSE 5 (35) 4 (22) 4 (30) 4 (28) 4 (21) 3 (21) UNDERSTORY 4 (31) 4 (78) 4 (45) 3 (64) 3 (66) 2 (103) SAVANNA 1 (15) 1 (15) COMPLEX 1 (10) 2 (15) 3 (13) 2 (27) 3 (45)

30 Example landscape visualization using EnVision (Wilson and McGaughey 2000, J. of For. 98:21-27). This visualization requires elevation information, map of stand boundaries, and inventory information for all stands on the landscape. Gray area are harvested or have no data. Landscape visualization

Output is from the FireScoping Tool included with the LMS-FFE Addon.

31 Spatial Landscape Analysis Example showing location of fire risk classes on an landscape in Eastern Washington for 2000 (a) and 2040 (b). Output is from the FireScoping Tool included with the LMS-FFE Addon. These tools are an extensions to LMS that support using FFE-FVS for fire risk analysis. a b

32 Examples of other analyses Fire risk analysis Wildlife habitat modeling Carbon sequestration analysis Economic analysis

Fire Risk Analysis Fire Risk Analysis The fire risk

of the Forest Vegetation Simulator (FVS), the LMS-FFE

present risk conditions as well as to compare the

33 Fire Risk Analysis Fire Risk Analysis The fire risk analysis module includes the Fire and Fuels Extension (FFE) of the Forest Vegetation Simulator (FVS), the LMS-FFE Configuration Tool, the Fire Scoping Report, and the Fire Risk Mapper. Analytical and spatial outputs can be used to evaluate present risk conditions as well as to compare the effectiveness of simulated fire risk reduction treatments across real forested landscapes. Developed by Kevin Ceder and Jim McCarter

Wildlife Habitat Modeling Three approaches to modeling wildlife habitat in LMS are used.

forest structural conditions; and population models provide an estimates of animal

Habitat suitability models are analyzed to assess the tradeoffs in habitat units while

34 Wildlife Habitat Modeling Three approaches to modeling wildlife habitat in LMS are used. Habitat suitability modeling provides an estimate of habitat quality (an index from ) and quantity (i.e. area of the landscape); structure-based habitat models associate particular species with forest structural conditions; and population models provide an estimates of animal density given habitat conditions. Habitat suitability models are analyzed to assess the tradeoffs in habitat units while structure-based habitat models can be used to estimate abundance/shortage of structure types (and by proxy habitat quantities) across large landscapes over time for alternative management approaches. Developed by Kevin Ceder

35 Carbon sequestration analysis A life cycle assessment process has been developed to work with LMS, as an accounting system for forest carbon storage, substitution, and displacement over time under different management alternatives. Management of 32 stand with 5 stands treated in Management of 32 stands with 30 stands intensively managed. Metric Tons Landscape Carbon - Forest, Products, Emissions, Substitution by Component Stem Root Crown Litter Dead Hogfuel Chips Long-Term Harvest Manufacturing Substitution Year Metric Tons Landscape Carbon - Forest, Products, Emissions, Displacement, Substitution by Component Stem Root Crown Litter Dead Chips Long-Term Harvest Manufacturing Displacement Substitution Year Landscape Carbon - Products by Component Hogfuel Chips Long-Term Landscape Carbon - Products by Component Hogfuel Chips Long-Term Metric Tons Metric Tons Year Year

36 Economic Analysis with LMS Economatic is an easy-to-use economic and financial analysis companion for LMS. Economatic takes management simulation data directly from LMS and automatically computes a variety of economic values, including discounted cash flow, equivalent annual annuity, soil expectation value, forest value, and internal rate of return. Users can customize costs, prices, tax rates, and other input parameters. Results are summarized at both the stand and landscape level in a series of tables and charts. Management of 32 stands with 30 stands intensively managed. Total Cash Flow Over Time $2,500,000 $2,000,000 Total Cash Flow $1,500,000 $1,000,000 $500,000 $0 ($500,000) Year Cash Flow Average Developed by Kevin Zobrist, Jeff Comnick, and Jim McCarter

37 Conclusions LMS provides a variety of tools to examine management alternatives at the stand and landscape level Very useful in educational environments Visualizations are powerful communication tools. Other analyses (carbon, financial, wildlife) are becoming increasingly important Getting data in has always been the greatest hurdle

38 LMS available via Web

UNEVEN-AGED MANAGEMENT NORTHWEST CERTIFIED FORESTRY

UNEVEN-AGED MANAGEMENT NORTHWEST CERTIFIED FORESTRY Rolf Gersonde, 6/6/2015 Uneven-aged Management in 90 Minutes 2 Silviculture Background Forest Ecology Management Tools and Stocking Control Multi-aged