Abstract
Tools that can monitor biomass and nutritional quality of forage plants are needed to understand how arctic herbivores may respond to the rapidly changing environment at high latitudes. The Normalized Difference Vegetation Index (NDVI) has been widely used to assess changes in abundance and distribution of terrestrial vegetative communities. However, the efficacy of NDVI to measure seasonal changes in biomass and nutritional quality of forage plants in the Arctic remains largely un-evaluated at landscape and fine-scale levels. We modeled the relationships between NDVI and seasonal changes in aboveground biomass and nitrogen concentration in halophytic graminoids, a key food source for arctic-nesting geese. The model was calibrated based on data collected at one site and validated using data from another site. Effects of spatial scale on model accuracy were determined by comparing model predictions between NDVI derived from moderate resolution (250 × 250 m pixels) satellite data and high resolution (20 cm diameter area) handheld spectrometer data. NDVI derived from the handheld spectrometer was a superior estimator (R2 ≥ 0.67) of seasonal changes in aboveground biomass compared to satellite-derived NDVI (R2 ≤ 0.40). The addition of temperature and precipitation variables to the model for biomass improved fit, but provided minor gains in predictive power beyond that of the NDVI-only model. This model, however, was only a moderately accurate estimator of biomass in an ecologically-similar halophytic graminoid wetland located 100 km away, indicating the necessity for site-specific validation. In contrast to assessments of biomass, satellite-derived NDVI was a better estimator for the timing of peak percent of nitrogen than NDVI derived from the handheld spectrometer. We confirmed that the date when NDVI reached 50% of its seasonal maximum was a reasonable approximation of the period of peak spring vegetative green-up and peak percent nitrogen. This study demonstrates the importance of matching the scale of NDVI measurements to the vegetation properties of biomass and nitrogen phenology.
Highlights
Along the approximately 800 km-long Arctic Coastal Plain of Alaska (ACP), a rapid rise in air temperatures over the last half century has been associated with a decreasing ice pack, thawing of the permafrost, and a significant shift in the productivity and species composition of plant communities [1,2,3]
Biomass of C. subspathacea increased as the season progressed, peaking in late July and early August before declining slightly, a pattern generally reflected by plot-level Normalized Difference Vegetation Index (NDVI) values (Figure 2)
We found that NDVI metrics related to the period of rapid spring growth (50% max and max ∆) were generally better indicators of nitrogen phenology than the date of peak NDVI, which is consistent with the idea that plants prioritize growth over structural stability during rapid early-season growth, resulting in low tissue C:N ratios
Summary
Along the approximately 800 km-long Arctic Coastal Plain of Alaska (ACP), a rapid rise in air temperatures over the last half century has been associated with a decreasing ice pack, thawing of the permafrost, and a significant shift in the productivity and species composition of plant communities [1,2,3]. Halophytic graminoid wetlands provide high quality foods that are important for the reproductive success of three migratory avian herbivores on the ACP, lesser snow geese (Chen caerulescens caerulescens; hereafter snow geese), greater white-fronted geese (Anser albifrons frontalis; hereafter white-fronted geese), and black brant (Branta bernicla nigricans; hereafter brant) [7,8] These wetlands contain plants that are high in nitrogen, a critical nutrient for the rapid growth of goslings during the short arctic summers. Satellite-derived NDVI has been used in the Arctic to assess vegetative change in biomass and quality across landscapes and broad-scale communities [18,34,35,36,37,38], but few studies have been validated with concurrent assessments of NDVI and field measurements at landscape and fine-scale levels. We tested the site-specificity of biomass predictions in a validation exercise involving halophytic graminoid wetlands in a similar ecosystem located approximately 100 km from our primary study site
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