Since the field season of the Hoonah Native Forest Partnership (HNFP) concluded in late October, 2016 there has been a lot of hustle-and-bustle behind the scenes as partners analyze the datasets generated by crews throughout the summer. Three of the key analyses hinge on the use of LiDAR data which was flown over >200,000 acres of the island. One analysis seeks to determine vegetation characteristics based on timber stand characteristics. The other two analyses focus on creating an intrinsic potential model of Pink and Chum Salmon habitat and modeling barriers to fish. Each of these analyses will provide direct information leading to better management of the landscape and rivers.
The goal of the HNFP Vegetation Study is to provide a very detailed map of both forested and non-forested vegetation types for use in timber, fish and wildlife planning as well as to support local residents in their efforts to gather resources for their households and businesses. The methodology being used combines field data collection and aerial photo classification with LiDAR derived vegetation structure and landscape position data. This is the cutting edge of vegetation mapping on planet earth. The use of LiDAR to model vegetation structure and topographic features can dramatically cut the amount of time that traditional methods take to reach the same end. In order for the LiDAR data to be useful, crews surveyed random forest plots (n=111),as well as stratified sampling for non-forest plots (n=208) across the landscape. Forest plots were created from the LiDAR data by combining the openness of the forest structure (open, sparse, gappy, closed) and the height ( short, medium, tall) and a random selection was generated from that. Non-forest plots were selected to cover the range of spectral signatures that occur in four-band orthoimagery acquired for the project area.Plot categories were linked to landscape characteristics that drive plant community dynamics such as elevation, aspect and slope. Because of this stratification across topographic characteristics crews had to survey from sea-level to mountaintops at 3,000 feet. At each plot the crew followed a Forest Service protocol requiring them to identify every species of plant within the plot, as well as its percent composition. They also measured the diameter at breast high (DBH) and height of each tree within the plot.
The data generated by the crew proved to be invaluable to the analysis. Vegetation study leads Conor Reynolds and Bob Christensen are using this analysis to estimate potential for future timber harvest, model deer habitat values under various management scenarios, identify locations to promote blueberry production and estimate future wood availability for salmon habitat maintenance in riparian stands.. This is particularly important in streams where logging occurred up to the river’s edge (before the establishment of the Alaska Forest Practices Act) and large logs are not falling into streams with enough frequency to maintain fish habitat.
“The benefit of the forest inventory to land managers would be that we’ve created a uniform dataset covering the variability of the entire landscape that effectively tells us the size and density of forest cover. This allows for more targeted scheduling of management activities mitigating the negative effects of intermediate stand stages on other resources such as deer and berries.”
— Conor Reynolds
Creating an Intrinsic Potential Model
In order to manage a landscape effectively, it is important to forecast future scenarios and to know the potential of existing habitat. Due to the access difficulties and prohibitive costs associated with conducting extensive on the ground population surveys across large area of rugged southeast Alaska, decision makers are turning toward tools based on remote sensed data for evaluating the associations between salmon populations and their critical freshwater habitat. Bernard Romey, a graduate student, set out to create an intrinsic potential (IP) model that predicted habitat suitability at the landscape level for spawning chum and pink salmon based on LiDAR derived persistent habitat characteristics such as slope and mean annual flow. Previous intrinsic potential models have been created in Oregon for steelhead trout and coho salmon, however, the IP models created through the HNFP will be the first Southeast Alaska specific chum and pink salmon models. They are likely to benefit communities and land managers across the Tongass National Forest.
“Our chum and pink salmon Intrinsic potential models, paired with the NetMap stream network analysis software, are powerful leading-edge GIS-based tools that will allow decision makers a ‘first step’ approach for predicting broad-scale areas of potential high quality salmon spawning habitat.”
— Bernard Romey
Modeling Barriers to Fish
The ability for a salmon to travel upriver to its original spawning ground is truly remarkable, but even their exceptional skill is limit as streams become steeper, skinnier, or laced with barriers. Knowing the upper limit of salmon distribution is important for guiding management decisions to avoid disturbance of spawning habitat and to protect salmon populations. The fine-scale resolution of the LiDAR can be used within the NetMAP toolset to predict the presence of passage barriers such as waterfalls or steep cascades. Crews walked upstream to survey the height and gradient of potential barriers. These data are being used along with Lidar to refine the barrier prediction model and to develop a map of all salmon streams in the region.
A Model for the Future
The products derived from the LiDAR for the Hoonah Native Forest Partnership are an emmense benefit. It is our hope that as future LiDAR projects are flown, that our results and methods may be used in future community forest products looking to streamline the process of collecting forest metrics and modeling habitat.
“The results of the vegetation mapping work we are doing for the HNFP are important because it provides a much higher resolution, and more detailed vegetation map for all private and public lands that surround the community of Hoonah. Consistent, reliable and up-to-date natural resource data in the jurisdictional patchwork of public and private lands that is common in areas surround rural communities in southeast Alaska has simply been non-existant up to this point. Historically, this state of affairs has undermined resource assessments that are best conducted at the watershed scale so we are particularly lucky to have access to this new product for the HNFP.
Furthermore, the additional detail in this vegetation map will support much more strategic, collaborative and cost effective project planning and implementation for timber, fish and wildlife resources. In the end, these results will save land owners and managers money, enhance returns on their investments over time, and integrate improved outcomes for residents and visitors who utilize these lands for hunting, fishing, recreation and entrepreneurial endeavors.”
— Bob Christensen