Hybrid poplar in Saskatchewan: Projected long-term productivity and N dynamics using the FORECAST model

Transcription

1 Hybrid poplar in Saskatchewan: Projected long-term productivity and N dynamics using the FORECAST model Clive Welham (clive.welham@ubc.ca) 1 Hamish Kimmins (hamish.kimmins@ubc.ca) 1 Ken Van Rees (ken.vanrees@usask.ca) 2 Brad Seely (brad.seely@ubc.ca) 1 1 Forest Ecosystem Management Simulation Group University of British Columbia Vancouver, BC Canada V6T 1Z4 2 Department of Soil Science University of Saskatchewan Saskatoon, SK Canada S7N 5A8

2 Overview Why modeling? The FORECAST model Study area and objectives Management practices simulated Simulation results and conclusions Future activities and developments

3 Why Modeling???? Because we cannot wait for the long-term results of long-term studies Because the future is uncertain and what we need is tools for scenario, risk and value tradeoff analysis Field experiments cannot provide the critical longterm empirical data needed in a timely fashion Field experiments should be designed to compliment modeling for calibration and validation

4 FORECAST Stand-level, multi-value (timber and non-timber) ecosystem management A management oriented, ecosystem-level, multi-value modeling framework

5 M anagement and other events which can be simulated: forestry and agroforestry Site preparation Planting / Regeneration Weed control Stocking control Pruning Intermediate harvests Final harvests Utilization level Fertilization Nurse crops Alternating or mixed species Rotation length Seedling size and quality Wildfire / broadcast burn Insect defoliation Wildlife browsing Organic waste recycling Clearcutting / patch cut Uniform partial harvesting - e.g. shelterwood, seedtree

6 Stand-level, multi-value (timber and non-timber) ecosystem management 2. FORECAST Stand A management oriented, ecosystem-level, multi-value modeling framework Uses the hybrid simulation approach: experience + understanding

7 Core ecosystem processes represented in FORECAST ESM Maximum potential foliage biomass set by moisture FOLIAGE NITROGEN CONTENT AVAILABLE LIGHT 1. Plant growth and carbon allocation PHOTOSYNTHETIC EFFICIENCY 2. Light limitation 3. Nutrient limitation AVAILABLE SOIL MOISTURE NET PRIMARY PRODUCTION AVAILABLE SOIL NUTRIENTS 4. Moisture limitation ALLOCATION 5. Competition for resources ROOTS STEMS FOLIAGE

8 Summary of Nutrient Cycling Over A Rotation Short rotation Long rotation Clearcut Time

9 Patterns of Nutrient Availability, Uptake Demand and Internal Cycling % of Production Below Above Ground Ground

10 File structure of FORECAST Input files TREEDATA PLANTDATA BRYODATA SOILDATA SETUP Programs TREEGROW PLANTGROW BRYOGROW SOILS Output files TREEPLOT PLANTPLOT BRYOPLOT SOILPLOT ECOSYSTEM SIMULATION TREETRND ECODATA PLANTTRND ECOSYSTM BYROTRND ECOSTATE ENDSTATE SOILTRND INITSTATE OUTPUT ASSESSMENT GRAPHICAL OUTPUT TABULAR OUTPUT MGMT ECOSYSECONOM ECONOM ENERGYCARBON

11 FORECAST Stand-level, multi-value (timber and non-timber) ecosystem management A management oriented, ecosystem-level, multi-value modeling framework Uses the hybrid simulation approach: experience + understanding Major focus: sustainability of a variety of values under alternative management strategies for changing/uncertain futures

12 Forestry is about people - values, needs, desires - and sustaining the ecosystems on which these are dependent Wood Non-wood products Water Wildlife Aesthetics Biological conservation Recreation Employment Spiritual values Environmental protection Ecosystem processes Economics - wealth creation Energy - fuel

13 FORECAST Non-spatial ecosystem management stand model Visualization software stand and landscape POSSIBLE FOREST FUTURES: watershed landscape management model LLEMS: complex cutblock simulator LLEMS Local Landscape Ecosystem Management Simulator FORCEE: Individual tree, complex stand model Trees Ecotone Open * Is this a clearcut? * What will the future forest species composition be? * How will Douglas-fir compete with western hemlock? * Will shade tolerant hardwoods be able to grow?

14 DECISION SUPPORT SYSTEM: Modelling Framework Projection Forest-level Timber Supply Model (ATLAS) Interpretation Wildlife Habitat Supply Model (SimFor) Polygon- Based Raster- Based Stand-level Model (FORECAST) Merchantable Volume Snags (>25cm dbh) Ecosystem C Storage Early Seral Shrub Cover (%) Visualization Software

15 Study area Cool summers, cold winters Mean daily July temp. 16 C Mean daily Jan. temp. -18 C Mean annual precip mm Mean May-Sept. precip. 280 mm Meadow Lake Last spring frost mid June First fall frost mid August White spruce/aspen on med. to good soils Jack pine on poor sandy soils

16 Culbert (poor) OM 70 t/ha. N 4000 kg/ha Cubbons (rich) OM 160 t/ha. N 7000 kg/ha The field sites

17 Objectives To calibrate FORECAST for poplar on the study sites To compare model predictions with field data To explore with the model the effects of weed control and fertilizer on poplar growth To assess the economic performance of these treatments To examine carbon budgets and possible climate change effects

18 Simulated weed management Intensive weed management: Included both pre-planting and post-planting weed control Minimal weed management: Only pre-planting weed control was applied

19 Simulated fertilizer treatments Four alternative treatments were simulated: no fertilizer (F0), and fertilizer applied at a rate of 100 kg N ha -1 in year 2 (F2), year 7 (F7) or year 12 (F12) after plantation establishment

20 Simulation design 2 sites (poor and rich) x 2 weed control measures (pre- and post- planting, and pre-planting planting only) x 4 fertilizer timings (F0, F2, F7, and F12) = 16 treatment combinations

21 Simulated plantation management Hybrid poplar were established from 25 cm rooted cuttings at 3 x 3 m (1111 sph) Grown for 20 years then harvested 98% of stemwood, 95% of branches, 90% of roots, and 5% of leaves were removed at harvest A total of five consecutive 20-year rotations was simulated. The same management regime was applied in each rotation.

22 Results 1: Validation study site data Average height (m) Stand age (y) Projected height growth was similar to empirical measures in two plantations but not a third.

23 Results: Validation data from other sites Average height (m) RichWCF7 PoorNoWCF0 PoorWCF Stand age (y) Early height growth in rooted cuttings may not be a reliable indicator of site productivity over a rotation

24 Stemwood biomass (Mg/ha) Poor site Pre- and post-planting Pre-planting only RichWCF Results: weed control simulations Stemwood production was always negatively affected by the weed competition that resulted from using only pre- planting weed control. 50 Rich site The effect was more severe on the poor than on the rich site. Stemwood biomass (Mg/ha) Simulation year

25 Tree available N or N Leaching loss (kg/ha) Pre- and post-planting weed control Tree available N RichWCF 7 Results: weed control simulations Poor site, no fertilizer Off-site losses of N were considerably reduced when weeds were present Leaching loss Leaching loss Tree available N or N Leaching loss (kg/ha) Pre-planting weed control only PoorNoWCF0 Tree available N Simulation year

26 Results: stemwood production (A) Post-planting weed control Conclusions F2 a /F0 b F7 c /F0 F12 d /F0 Rotation Poor Rich Poor Rich Poor Rich Fertilization always increased stemwood production compared to no fertilizer (B) Pre-planting weed control only Rotation Poor F2/F0 Rich Poor F7/F0 Rich Poor F12/F0 Rich Fertilization was more beneficial to stemwood production when weed control was limited to pre-planting planting only

27 General conclusion Ecologically, the relative benefit of fertilizer in hybrid poplar depends upon the nutrient status of the site, the weed control strategy, and the particular rotation

28 Further developments: Economic Conclusions to date: analysis 1. The rotation age that maximizes MAI can be very different from that which maximizes economic return 2. Net present value (NPV) is maximized using pre- planting weed control combined with fertilization; post-planting planting weed control is uneconomical 3. A management regime that maximizes NPV in one rotation will likely not be the same regime that maximizes NPV in the subsequent rotation (each rotation must be considered sequentially)

29 Further developments: Economic Work in progress: analysis Short-term: The economic returns from timber production and carbon sequestration Long-term: Optimal allocation between competing uses, (sawlogs, biofuel, and pulp), non-use values (carbon credits, soil protection), and their hybrids (agroforestry)

30 Future work: climate change The FORECAST simulations are based upon average climatic conditions, and significant deviations from climatic norms are not presently reflected in model output. Severe drought conditions in 2002 depressed both survival and growth in the poplar planted that year, but this was not represented in the simulations. Climate change and moisture effects are currently being added to FORECAST