Assessing forest disturbances for carbon modeling : building the bridge between activity data and carbon budget modeling

Detailed observations of natural and anthropogenic disturbances that alter the forest structure and the distribution of carbon are essential to estimate changes in forest carbon sinks and sources. Remote sensing is one of the primary sources to provide observations of land cover and land-cover change for carbon studies and other ecological applications due to its ability to monitor the Earth’s surface on a regular and continuous basis. However, observations of change are often not attributed directly to an underlying disturbance type and are not well validated, especially in tropical areas. The overall objectives of this thesis are to 1) assess forest disturbances (natural and anthropogenic) and derive activity data for carbon budget modeling, and 2) estimate the impact of different activity data on the terrestrial carbon balance for REDD+ in Mexican tropical forests. To do so, a novel Multi-Source, Multi-Scale Disturbance (MS-D) assessment method was developed to: 1) characterize natural and anthropogenic forest disturbances; 2) obtain land-cover change observations; and 3) attribute land-cover changes to their most likely disturbance driver. Spatially-explicit layers of major disturbance types were generated in annual time steps for carbon modeling across the Yucatan Peninsula from 2005 to 2010. Using geospatial techniques and regression-tree analysis the MS-D approach successfully attributed 86% of land-cover changes derived from the MODIS satellite imagery to their underlying disturbance cause, creating synergies between remote-sensing products, forest inventory and ancillary datasets. Four remote-sensing products derived from Landsat and MODIS satellites were then compiled, providing inputs of activity data for carbon modeling with the CBM-CFS3. Two map sequences were generated for each product, with and without attributing land-cover changes to disturbance type with the MS-D approach. Annual carbon fluxes were simulated to compare the impact of: 1) spatial resolution, 2) temporal resolution, and 3) attribution/non-attribution of land-cover changes by disturbance type on carbon flux estimates. The results clearly demonstrated that different choices of satellite imagery and attribution of changes to disturbance types change the estimated carbon balance. This study provides an integral cost-effective approach to derive activity data for carbon modeling, and support policy and decision-making for forest monitoring and REDD+.Forestry, Faculty ofGraduat

Choice of satellite imagery and attribution of changes to disturbance type strongly affects forest carbon balance estimates

Background: Remote sensing products can provide regular and consistent observations of the Earth´s surface to monitor and understand the condition and change of forest ecosystems and to inform estimates of terrestrial carbon dynamics. Yet, challenges remain to select the appropriate satellite data source for ecosystem carbon monitoring. In this study we examine the impacts of three attributes of four remote sensing products derived from Landsat, Landsat-SPOT, and MODIS satellite imagery on estimates of greenhouse gas emissions and removals: (1) the spatial resolution (30 vs. 250 m), (2) the temporal resolution (annual vs. multi-year observations), and (3) the attribution of forest cover changes to disturbance types using supplementary data. Results With a spatially-explicit version of the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3), we produced annual estimates of carbon fluxes from 2002 to 2010 over a 3.2 million ha forested region in the Yucatan Peninsula, Mexico. The cumulative carbon balance for the 9-year period differed by 30.7 million MgC (112.5 million Mg CO2e) among the four remote sensing products used. The cumulative difference between scenarios with and without attribution of disturbance types was over 5 million Mg C for a single Landsat scene. Conclusions Uncertainty arising from activity data (rates of land-cover changes) can be reduced by, in order of priority, increasing spatial resolution from 250 to 30 m, obtaining annual observations of forest disturbances, and by attributing land-cover changes by disturbance type. Even missing a single year in the land-cover observations can lead to substantial errors in ecosystems with rapid forest regrowth, such as the Yucatan Peninsula.Forestry, Faculty ofNon UBCForest Resources Management, Department ofReviewedFacult

A systems approach to assess climate change mitigation options in landscapes of the United States forest sector

Abstract Background United States forests can contribute to national strategies for greenhouse gas reductions. The objective of this work was to evaluate forest sector climate change mitigation scenarios from 2018 to 2050 by applying a systems-based approach that accounts for net emissions across four interdependent components: (1) forest ecosystem, (2) land-use change, (3) harvested wood products, and (4) substitution benefits from using wood products and bioenergy. We assessed a range of land management and harvested wood product scenarios for two case studies in the U.S: coastal South Carolina and Northern Wisconsin. We integrated forest inventory and remotely-sensed disturbance data within a modelling framework consisting of a growth-and-yield driven ecosystem carbon model; a harvested wood products model that estimates emissions from commodity production, use and post-consumer treatment; and displacement factors to estimate avoided fossil fuel emissions. We estimated biophysical mitigation potential by comparing net emissions from land management and harvested wood products scenarios with a baseline (‘business as usual’) scenario. Results Baseline scenario results showed that the strength of the ecosystem carbon sink has been decreasing in the two sites due to age-related productivity declines and deforestation. Mitigation activities have the potential to lessen or delay the further reduction in the carbon sink. Results of the mitigation analysis indicated that scenarios reducing net forest area loss were most effective in South Carolina, while extending harvest rotations and increasing longer-lived wood products were most effective in Wisconsin. Scenarios aimed at increasing bioenergy use either increased or reduced net emissions within the 32-year analysis timeframe. Conclusions It is critical to apply a systems approach to comprehensively assess net emissions from forest sector climate change mitigation scenarios. Although some scenarios produced a benefit by displacing emissions from fossil fuel energy or by substituting wood products for other materials, these benefits can be outweighed by increased carbon emissions in the forest or product systems. Maintaining forests as forests, extending rotations, and shifting commodities to longer-lived products had the strongest mitigation benefits over several decades. Carbon cycle impacts of bioenergy depend on timeframe, feedstocks, and alternative uses of biomass, and cannot be assumed carbon neutral