Q17b – C. Frizzle

What landscape level ecosystem goods and service indicators can be developed with airborne LiDAR data?

The impact of forest management on ecosystems is a growing concern, which imposes increased reporting of environmental impacts. Forest industries are looking for accurate wood yield predictions, but this is tied to targets on environmental indicators, like those found in forest certifications. Quantifying ecological services (ES) is one way to guide forest management activities to reach acceptable trade-offs between forest resource extraction and the impacts of related activities. ES are the benefits that humans derive directly or indirectly from ecological functions. Forests provide ES in many ways, but the most important one for forest industries is wood production. Other ES need to be quantified to monitor the sustainable use of forest: fresh water, water regulation, water purification, erosion regulation, natural hazard protection, wildlife habitat support, etc. Output variables from hydrological models are used to quantify water-related ES, but they are complex to derive. On the other hand, proxies, like land cover and land use, may be used to map ES, however, they can introduce errors or biases. Many of the available spatial layers may not provide the map accuracy required for strategic planning of forest activities. Since LiDAR can be used to produce high spatial resolution DEMs and to infer 3D structural characteristics of vegetation, this study aims to quantify how LiDAR can increase the precision and accuracy of ES maps at the landscape level. First, this project will create function indicators from LiDAR to map forest, water and wildlife ES at the spatio-temporal resolution suitable for forest management (see figure1).


Figure 1. Function indicators from LiDAR derived spatial information (ALS : Airborne Laser Scan ; FI : Function indicator)

Second, a mapping method will be developed to map each of the three ES. Thirdly, trade-offs, synergy or loss between forest, water and wildlife ES will be assessed. To make sure water-related function indicators are efficient for ES mapping, the results will be evaluated with the output of a SWAT model (see figure 2).


Figure 2. Indicator evaluation with hydrological model (+L : with LiDAR ; ES : Ecological Services ; SWAT : Soil and Water Assessment Tool ; CC : Climate change ; BMP : Best management practices)

Two different sites will be studied: the Harry’s River Watershed (HRW) in Newfoundland and the au Saumon River Watershed (SRW) in Quebec (see figure 3). While ES in HRW show little disturbance, human impacts are greater in the SRW. Therefore, the relative scale of ES in these two contrasted watersheds will be closer to an absolute scale that is more relevant and transferrable to other studies.

Figure 3. Localization of the two study sites