ALBERT

Description: Warming in the Arctic has resulted in changes in the distribution and composition of vegetation communities. Many of these changes are occurring at fine spatial scales and at the level of individual species. Broad-band, coarse-scale remote sensing methods are commonly used to assess vegetation changes in the Arctic, and may not be appropriate for detecting these fine-scale changes; however, the use of hyperspectral, high resolution data for assessing vegetation dynamics remains scarce. The aim of this paper is to assess the ability of field spectroscopy to differentiate among four vegetation communities in the Low Arctic of Alaska. Primary data were collected from the North Slope site of Ivotuk, Alaska (68.49°N, 155.74°W) and analyzed using spectrally resampled hyperspectral narrowbands (HNBs). A two-step sparse partial least squares (SPLS) and linear discriminant analysis (LDA) was used for community separation. Results from Ivotuk were then used to predict community membership at five other sites along the Dalton Highway in Arctic Alaska. Overall classification accuracy at Ivotuk ranged from 84%–94% and from 55%–91% for the Dalton Highway test sites. The results of this study suggest that hyperspectral data acquired at the field level, along with the SPLS and LDA methodology, can be used to successfully discriminate among Arctic tundra vegetation communities in Alaska, and present an improvement over broad-band, coarse-scale methods for community classification.

Description: Abandoned agricultural fields have recently become more abundant in the U.S. and remain susceptible to species invasions after cultivation disturbance. As invasive species become more widespread with increases in anthropogenic activities, we need more effective ways to use limited resources for conservation of native ecosystems. Remote sensing can help us monitor the spread and effects of invasive species, and thus determine the species and locations to target for conservation. To examine this potential, we studied plant communities dominated by exotic invasive plant species in secondary successional fields in northern Virginia using ground-level hyperspectral data. Within these communities, ordination analyses of vegetation surveys revealed differences in species compositions among plots and fields. These differences among communities were also observed in the spectral data. Stepwise multiple linear regression analyses to determine which species influenced the ordination axes revealed that many of the influential species are considered invasive, again underscoring the influence of invasive species on community properties. Stepwise regression analyses also revealed that the most influential wavelengths for discrimination were distributed along the spectral profile from the visible to the near-infrared regions. A discriminant analysis using wavelengths selected with a principal components analysis demonstrated that different plant communities were separable using spectral data. These spectrally observable differences suggest that we can use hyperspectral data to distinguish among invasive-dominated successional plant communities in this region.

Description: Vegetation productivity trends for the Arctic tundra are updated for the 1982–2011 period and examined in the context of land surface temperatures and coastal sea ice. Understanding mechanistic links between vegetation and climate parameters contributes to model advancements that are necessary for improving climate projections. This study employs remote sensing data: Global Inventory Modeling and Mapping Studies (GIMMS) Maximum Normalized Difference Vegetation Index (MaxNDVI), Special Sensor Microwave Imager (SSM/I) sea-ice concentrations, and Advanced Very High Resolution Radiometer (AVHRR) radiometric surface temperatures. Spring sea ice is declining everywhere except in the Bering Sea, while summer open water area is increasing throughout the Arctic. Summer Warmth Index (SWI—sum of degree months above freezing) trends from 1982 to 2011 are positive around Beringia but are negative over Eurasia from the Barents to the Laptev Seas and in parts of northern Canada. Eastern North America continues to show increased summer warmth and a corresponding steady increase in MaxNDVI. Positive MaxNDVI trends from 1982 to 2011 are generally weaker compared to trends from 1982–2008. So to better understand the changing trends, break points in the time series were quantified using the Breakfit algorithm. The most notable break points identify declines in SWI since 2003 in Eurasia and 1998 in Western North America. The Time Integrated NDVI (TI-NDVI, sum of the biweekly growing season values of MaxNDVI) has declined since 2005 in Eurasia, consistent with SWI declines. Summer (June–August) sea level pressure (slp) averages from 1999–2011 were compared to those from 1982–1998 to reveal higher slp over Greenland and the western Arctic and generally lower pressure over the continental Arctic in the recent period. This suggests that the large-scale circulation is likely a key contributor to the cooler temperatures over Eurasia through increased summer cloud cover and warming in Eastern North America from more cloud-free skies.

Description: Remote sensing has become a valuable tool in monitoring arctic environments. The aim of this paper is ground-based hyperspectral characterization of Low Arctic Alaskan tundra communities along four environmental gradients (regional climate, soil pH, toposequence, and soil moisture) that all vary in ground cover, biomass, and dominating plant communities. Field spectroscopy in connection with vegetation analysis was carried out in summer 2012, along the North American Arctic Transect (NAAT). Spectral metrics were extracted, including the averaged reflectance and absorption-related metrics such as absorption depths and area of continuum removal. The spectral metrics were investigated with respect to “greenness”, biomass, vegetation height, and soil moisture regimes. The results show that the surface reflectances of all sites are similar in shape with a reduced near-infrared (NIR) reflectance that is specific for low-growing biomes. The main spectro-radiometric findings are: (i) Southern sites along the climate gradient have taller shrubs and greater overall vegetation biomass, which leads to higher reflectance in the NIR. (ii) Vegetation height and surface wetness are two antagonists that balance each other out with respect to the NIR reflectance along the toposequence and soil moisture gradients. (iii) Moist acidic tundra (MAT) sites have “greener” species, more leaf biomass, and green-colored moss species that lead to higher pigment absorption compared to moist non-acidic tundra (MNT) sites. (iv) MAT and MNT plant community separation via narrowband Normalized Difference Vegetation Index (NDVI) shows the potential of hyperspectral remote sensing applications in the tundra.

Description: The regional controls of biodiversity patterns have been traditionally evaluated using structural and compositional components at the species level, but evaluation of the functional component at the ecosystem level is still scarce. During the last decades, the role of ecosystem functioning in management and conservation has increased. Our aim was to use satellite-derived Ecosystem Functional Types (EFTs, patches of the land-surface with similar carbon gain dynamics) to characterize the regional patterns of ecosystem functional diversity and to evaluate the environmental and human controls that determine EFT richness across natural and human-modified systems in temperate South America. The EFT identification was based on three descriptors of carbon gain dynamics derived from seasonal curves of the MODIS Enhanced Vegetation Index (EVI): annual mean (surrogate of primary production), seasonal coefficient of variation (indicator of seasonality) and date of maximum EVI (descriptor of phenology). As observed for species richness in the southern hemisphere, water availability, not energy, emerged as the main climatic driver of EFT richness in natural areas of temperate South America. In anthropogenic areas, the role of both water and energy decreased and increasing human intervention increased richness at low levels of human influence, but decreased richness at high levels of human influence.