Pilot site experiments are being used to help develop long-term adaptive management strategies and identify the social, economic and environmental impacts of forest adaptation options. Through integration of model predictions with local forest management practices, we identified areas where existing tree populations will become vulnerable in the future and areas that will be suitable for planting new species. This analysis has taken place at a series of test sites located in China, Australia and North America. Figure 1: The project study area is highlighted by the red rectangles. Pilot experiment sites (stars) and partners (circles) are also indicated on the map.
Application of niche-based models
Niche-based modelling was applied to the MKRF (Malcolm Knapp Research Forest) pilot site in British Columbia, Canada to project the shift in climate and climate niches for ecosystems and species. This was done using climate change scenarios from the IPCC AR4. These projected changes in bioclimatic envelopes for ecosystems will help generate better forest management strategies to maintain healthy and productive forests in the future.
The application of these models to the pilot sites has provided accurate projections of changes in climate and habitat suitability for the species of interest. Better long-term management planning, and more appropriate species selection for plantations and reforestation efforts can be employed based on the observed changes in the suitable climate niche of the species. This is a valuable tool for forest managers and policy developers to generate long-term strategies that will ensure forests continue to provide ecosystem services and socio-economic benefits.
Application of process-based models
Tools were developed to bridge niche-based model predictions with one or two process-based models. These models were applied to various pilot sites – MKRF, Canada; Fujian site, China; Central Highlands Region, Australia. This allowed us to determine the impacts of climate change on forest ecosystems within these sites, develop adaptation strategies, and produce decision-matrices to rank various management strategies.
Development of recommendations for SFM
There are numerous tools/models used in sustainable forest management (SFM), strategic planning and scenario testing to assist high-level decision-making. We explored the potential implications of these tools/models in the Asia-Pacific to help managers and policy makers make sound SFM decisions under a changing climate. This was done with the expectation that some of these tools will be adopted by other regions to solve local management issues in a cost-effective manner.
Table 1. A summary of modelling tools employed within the pilot sites.
Model | Description | Data input | Output | General Application | Spatial Scale |
Climate Models |
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ClimateAP | A climate model for the Asia-Pacific region | Latitude/longitude, elevation (optional) | 208 seasonal and annual climate variables for a specific location (past, present or future) | Generate climate variables for specific locations for historical years and future | Point locations to regional |
Niche-based Ecological Models |
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Climate niche model | A bioclimate envelope model using the Random Forest (RF) algorithm to model the relationship between climate variables and the presence/absence of a species | Seasonal and annual climate variables from ClimateAP, presence data of the species | Projections of the geographical distribution of the climate niche of a species | Species-specific, climate suitability analysis | Fine to regional |
Process-based Ecological Models |
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FORECAST Climate | A management-oriented, forest growth and ecosystem dynamics model that is an extension of the hybrid forest growth model FORECAST created through the dynamic linkage of FORECAST with the stand-level hydrology model ForWaDy. | Reference daily climate data, forest inventory data, historical growth and yield data, nutrient concentrations in different biomass components | Projections of climate impacts on: long-term forest growth and development, ecosystem carbon storage, water stress, drought-related mortality, litter fall and nutrient cycling rates | Forest productivity, growth and yield, forest carbon dynamics, soil fertility, resource trade-off analysis | Stand, with potential to link to landscapes through analysis units |
TACA-GEM |
Tree and Climate Assessment Model – Germination and Establishment: A mechanistic species distribution model that facilitates an analysis of the response of trees to climate-driven phenological and biophysical variables. It assesses the probability of a species being able to regenerate, grow and survive under a range of climatic and edaphic conditions.
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Daily climate data, forest inventory data | Species regeneration parameters | Species composition, regeneration | Stand, with potential to link to landscapes through analysis units |
TACA-GAP | Tree and Climate Assessment Model – Growth and Productivity: A mechanistic model of species regeneration, which is a combination of TACA-EM and BRIND models used to estimate annual net primary productivity and maximum biomass that a species can achieve under given climate and soil parameters. | Daily climate data, forest inventory data | Species productivity parameters | Species composition, productivity | Stand, with potential to link to landscapes through analysis units |
LANDIS-II | LANDscape Disturbance and Succession: a spatial forest simulation model of ecological processes including succession, seed dispersal, disturbances, and climate change. | Monthly climate data, parameters from TACA models or forest inventory data | A spatial model of species distribution | Species composition, succession | Small to medium landscape |
CBM-CFS3 | An inventory-based forest ecosystem carbon budget model | Forest inventory data | An evaluation of ecosystem carbon storage | Forest carbon dynamics | Stand to regional |
DLM-Ecohydro (BEPS-TerrainLab V2.0) | An eco-hydrological model developed from a dynamic land model | Daily climate data, land surface data | Simulates annual mean temperature, evapotranspiration, soil water storage, surface and subsurface runoff, gross and net primary productivity | Forest hydrology and related biogeochemical processes | Small landscape |
3-PG | Physiological Principles to Predict Growth: A process-based growth model used to explore the biophysical and bio-physiological interactions influencing stand dynamics of a given species | Monthly climate data | Geographic distribution of species under different climate scenarios and stand volume predictions | Forest productivity | Stand to medium landscape |
Model Integration |
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Landscape Summary Tool (LST) | A tool designed in Microsoft Excel to facilitate the calculation of indicators of ecosystem services, including a variable weighting decision approach. Twenty-seven alternative management scenarios were developed using factorial analysis. | Stand-level attribute database from FORECAST Climate output | An indicator matrix of resource trade-off analysis results | A general framework for scaling up stand-level model output, resource trade-off analysis | Small landscape |
Patchworks | A strategic decision model using multiple value trade-off analysis and considering 7 climate related indicators | Model output specified for each indicator (see figure 2) | Quantitative comparison of different management strategies | Forest planning, growth and yield, natural disturbance | Small to medium landscape |
A conceptual framework was then developed to integrate models explored in this study to provide high-level SFM decisions. A summary of this framework is given in Figure 2. Further explanation and results from these modelling tools will be shared once findings are published.
Figure 2. A conceptual flow diagram of the indicator-based decision-support framework.
Publications
Kang, H., Seely, B., Wang, G., Innes, J.L., Zheng, D., Chen, P., Wang, T., and Li, Q. (2014). Evaluating management trade-offs between economic fiber production and ecosystem services in the context of climate change in a Chinese fir dominated forest plantation in Fujian Province. [Manuscript].
Kang, H., Seely, B., Wang, G., Innes, J.L., Zheng, D., Chen, P., Wang, T., and Li, Q. (2014). Simulating the impacts of climate change on growth of Chinese fir plantations in Fujian Province, China. [Manuscript].
Kang, H., Wang, T., Wang, G., Innes, J.L., Zheng, D., Chen, P., Seely, B., and Li, Q. (2014). Application of climate niche approach to project future distribution of Chinese fir and its adaptation strategies under changing climate in Fujian Province. [Manuscript].