Abstract
Ecosystem maps are foundational tools that support multi-disciplinary study design and applications including wildlife habitat assessment, monitoring and Earth-system modeling. Here, we present continuous-field cover maps for tundra plant functional types (PFTs) across ~125,000 km2 of Alaska’s North Slope at 30-m resolution. To develop maps, we collected a field-based training dataset using a point-intercept sampling method at 225 plots spanning bioclimatic and geomorphic gradients. We stratified vegetation by nine PFTs (e.g., low deciduous shrub, dwarf evergreen shrub, sedge, lichen) and summarized measurements of the PFTs, open water, bare ground and litter using the cover metrics total cover (areal cover including the understory) and top cover (uppermost canopy or ground cover). We then developed 73 spectral predictors derived from Landsat satellite observations (surface reflectance composites for ~15-day periods from May–August) and five gridded environmental predictors (e.g., summer temperature, climatological snow-free date) to model cover of PFTs using the random forest data-mining algorithm. Model performance tended to be best for canopy-forming PFTs, particularly deciduous shrubs. Our assessment of predictor importance indicated that models for low-statured PFTs were improved through the use of seasonal composites from early and late in the growing season, particularly when similar PFTs were aggregated together (e.g., total deciduous shrub, herbaceous). Continuous-field maps have many advantages over traditional thematic maps, and the methods described here are well-suited to support periodic map updates in tandem with future field and Landsat observations.
Highlights
Quantitative measurements of vegetation and environmental covariates support the classification and mapping of terrestrial ecosystems
Spectral Predictors: Landsat Seasonal Composites For analysis, we summarized the cover data by species, aggregated to plant functional types (PFTs) using two cover metriWcse: (c1o)mtoptaillecdovcearl,ibthraetepde,rcaetnmt oosfpshamerpiclaellpyoicnotrsreacttwedhicahndspepcrieecsisbioelnontgerinraginto caoPrrFeTctoedccu(Lrr1eTd), Landsat Surface Reflectance High Level Data Products [40] derived from Landsat 4–5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper (ETM+) and Landsat 8 Operational Land Imager (OLI) observations between 15 May and 31 August 1999–2015
The field measurements and resultant PFT cover maps indicated moderate to high cover values for low deciduous shrubs, dwarf evergreen shrubs, sedges, bryophytes and lichens for most of the mapping area, while tall deciduous shrubs, dwarf deciduous shrubs, grasses and forbs typically occurred at very low cover values except in specific landscape settings (Table 4)
Summary
Quantitative measurements of vegetation and environmental covariates support the classification and mapping of terrestrial ecosystems. Most Arctic ecosystem mapping efforts to date have applied categorical classifications, such as vegetation or land cover types, using raster analysis [1,2,3,4,5] or visual photo-interpretation [6,7]. Categorical vegetation maps have limitations for long-term monitoring because changes in vegetation properties over time are more likely to involve shifts within the range of variability of a given map class, rather than a transition from one class to another. A more precise approach is to quantitatively map the cover of vegetation within biophysically-meaningful strata, such as plant functional types (PFTs) [8,9]; to date, quantitative or “continuous field” vegetation mapping efforts have mainly focused on forest ecosystems [10]
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