Remote Sensing of Arctic Vegetation: Relations between the NDVI, Spatial Resolution and Vegetation Cover on Boothia Peninsula, Nunavut

Arctic tundra environments are thought to be particularly sensitive to changes in climate, whereby alterations in ecosystem functioning are likely to be expressed through shifts in vegetation phenology, species composition, and net ecosystem productivity (NEP). Remote sensing has shown potential as a tool to quantify and monitor biophysical variables over space and through time. This study explores the relationship between the normalized difference vegetation index (NDVI) and percent-vegetation cover in a tundra environment, where variations in soil moisture, exposed soil, and gravel till have significant influence on spectral response, and hence, on the characterization of vegetation communities. IKONOS multispectral data (4 m spatial resolution) and Landsat 7 ETM+ data (30 m spatial resolution) were collected for a study area in the Lord Lindsay River watershed on Boothia Peninsula, Nunavut. In conjunction with image acquisition, percent cover data were collected for twelve 100 m × 100 m study plots to determine vegetation community composition. Strong correlations were found for NDVI values calculated with surface and satellite sensors, across the sample plots. In addition, results suggest that percent cover is highly correlated with the NDVI, thereby indicating strong potential for modeling percent cover variations over the region. These percent cover variations are closely related to moisture regime, particularly in areas of high moisture (e.g., water-tracks). These results are important given that improved mapping of Arctic vegetation and associated biophysical variables is needed to monitor environmental change.On croit que les environnements de la toundra arctique sont particulièrement sensibles aux changements climatiques, en ce sens que toute altération du fonctionnement de l’écosystème est susceptible d’être exprimée dans le réarrangement de la phénologie de la végétation, de la composition des espèces et de la productivité nette de l’écosystème (PNÉ). La télédétection s’avère un outil efficace de quantification et de surveillance des variables biophysiques dans le temps et dans l’espace. Cette étude explore la relation entre l’indice d’activité végétale et le pourcentage de couverture végétale en milieu de toundra, où les variations propres à l’humidité du sol, au sol exposé et au till de gravier ont une influence considérable sur la réponse spectrale et, par conséquent, sur la caractérisation des communautés végétales. Des données multispectrales IKONOS (résolution spatiale de 4 m) et des données ETM+ de Landsat 7 (résolution spatiale de 30 m) ont été recueillies pour une zone d’étude visée par la ligne de partage des eaux à la hauteur de la rivière Lord Lindsay, dans la péninsule de Boothia, au Nunavut. De concert avec l’acquisition d’images, les données relatives au pourcentage de couverture ont été recueillies pour douze terrains d’étude de 100 m sur 100 m dans le but de déterminer la composition de la communauté végétale. De fortes corrélations ont été dénotées dans le cas des valeurs de l’indice d’activité végétale calculées à l’aide de détecteurs de surface et de détecteurs satellisés et ce, à l’échelle des terrains ayant servi d’échantillon. Par ailleurs, les résultats laissent entendre que le pourcentage de couverture est hautement corrélé avec l’indice d’activité végétale, ce qui indique une forte possibilité de modélisation des variations de pourcentage de couverture dans la région. Ces variations du pourcentage de couverture sont étroitement liées au régime d’humidité, particulièrement dans les régions où l’humidité est élevée (comme les traces d’eau). Ces résultats revêtent de l’importance étant donné qu’il y a lieu d’améliorer le mappage de la végétation arctique et les variables biophysiques connexes afin de surveiller la modification de l’environnement

An Incidence of Multi-Year Sediment Storage on Channel Snowpack in the Canadian High Arctic

During June 2005, we identified the presence of sediment buried within multi-year channel snowpack of a small river located near Cape Bounty, Melville Island, Nunavut (74°55' N, 109°35' W). Photographic evidence indicates that the sediment was deposited during the 2003 season by the initial meltwater flowing on the snowpack, which was dammed by snow upstream of a channel constriction. The resulting pond covered a minimum area of 180 m2 and contained an estimated minimum 27 Mg of sediment. Suspended sediment measurements during the 2003 season indicate that deposition on the snowpack at this location represented 49%–65% of the sediment transport prior to the ponding and emplacement of the sediment on the snow, and approximately 20% of the measured sediment flux for the entire season. Multi-year snow accumulations immediately downstream exhibited similar sediment deposition on snow, but no evidence of multi-year sediment storage was present. By contrast, a similar stream in an adjacent watershed channelized rapidly, with minimal sediment deposition on the snow, and delivered a large pulse of sediment to the downstream lake. These results provide quantitative evidence for the magnitude of sediment storage on snowpack and point to the unique role that snow plays in the fluvial geomorphology of High Arctic watersheds.En juin 2005, nous avons dénoté la présence de sédiment enterré dans une plaque de neige datant de plusieurs années d’une petite rivière située près de cap Bounty, sur l’île Melville, au Nunavut (74°55' N, 109°35' O). D’après des preuves photographiques, le sédiment a été déposé pendant la saison 2003 par l’eau de fusion initiale s’écoulant sur la plaque de neige, qui avait été endiguée par la neige en amont d’un canal confiné. L’étang qui en a découlé recouvrait une aire minimale de 180 m2 et contenait, selon les estimations, au moins 27 Mg de sédiment. Les mesures de sédiment en suspension pendant la saison 2003 indiquent que ce dépôt sur la plaque de neige à cet endroit représentait entre 49 % et 65 % du transport de sédiment avant l’accumulation d’eau et l’emplacement de sédiment sur la neige, et environ 20 % du flux de sédiment mesuré pour toute la saison. Les accumulations de neige de plusieurs années immédiatement en aval comptaient des dépôts de sédiment semblables sur la neige, quoi qu’aucun emmagasinage de sédiment sur plusieurs années n’était présent. Par contraste, un cours d’eau similaire d’un bassin hydrographique adjacent s’est canalisé rapidement, avec peu de dépôts de sédiment sur la neige, puis a laissé une grande quantité de sédiment au lac en aval. Ces résultats fournissent des preuves quantitatives quant à l’ampleur de l’emmagasinage de sédiment sur la plaque de neige et laissent envisager le rôle unique que joue la neige sur la géomorphologie fluviale des bassins hydrographiques de l’Extrême-Arctique

Spatial variability in carbon dioxide exchange processes within wet sedge meadows in the Canadian High Arctic

Wet sedge meadows are the most productive plant communities in the High Arctic. However, the controls on carbon dioxide (CO2) exchange processes within wet sedge communities – and the scale at which they operate – are poorly understood. Here, the factors controlling CO2 exchange of wet sedge meadows experiencing different moisture regimes are examined. Environmental data are used to create predictive models of CO2 exchange on multiple temporal scales. Automated chamber systems recorded CO2 fluxes at 30-minute intervals at wet sedge sites in the Canadian High Arctic from June to August in 2014 and 2015. Static chambers were also deployed over a larger spatial extent in 2014. Our results show that wet sedge communities were strong CO2 sinks during the growing season (−7.67 to −44.36 g C·m−2). CO2 exchange rates in wetter and drier areas within wet sedge meadows differed significantly (Wilcoxon, p<0.001), suggesting that soil moisture regimes within vegetation types influence net CO2 balance. Random Forest models explained a significant amount of the variability in CO2 flux rates over time (R2=0.46 to 0.90). The models showed that the drivers of CO2 exchange in these communities vary temporally. Variable moisture regimes indirectly influenced CO2 fluxes given that they exhibit different vegetation and temperature-response characteristics. We suggest that the response of a single vegetation type to environmental changes may vary depending on microenvironment variability within that community

Arctic Ecological Classifications Derived from Vegetation Community and Satellite Spectral Data

Abstract: As a result of the warming observed at high latitudes, there is significant potential for the balance of ecosystem processes to change, i.e., the balance between carbon sequestration and respiration may be altered, giving rise to the release of soil carbon through elevated ecosystem respiration. Gross ecosystem productivity and ecosystem respiration vary in relation to the pattern of vegetation community type and associated biophysical traits (e.g., percent cover, biomass, chlorophyll concentration, etc.). In an arctic environment where vegetation is highly variable across the landscape, the use of high spatial resolution imagery can assist in discerning complex patterns of vegetation and biophysical variables. The research presented here examines the relationship between ecological and spectral variables in order to generate an ecologically meaningful vegetation classification from high spatial resolution remote sensing data. Our methodology integrates ordination and image classifications techniques for two non-overlapping Arctic sites across a 5 ° latitudinal gradient (approximately 70 ° to 75°N). Ordination techniques were applied to determine the arrangement of sample sites, in relation to environmental variables, followed by cluster analysis to create ecological classes. The derived classes were the

Drivers of soil nitrogen availability and carbon exchange processes in a High Arctic wetland

Increased soil nutrient availability, and associated increases in vegetation productivity, could create a negative feedback between Arctic ecosystems and the climate system, thereby reducing the contribution of Arctic ecosystems to future climate change. To predict whether this feedback will develop, it is important to understand the environmental controls over nutrient cycling in High Arctic ecosystems and their impact on carbon cycling processes. Here, we examined the environmental controls over soil nitrogen availability in a High Arctic wet sedge meadow and how abiotic factors and soil nitrogen influenced carbon dioxide exchange processes. The importance of environmental variables was consistent over the 3 years, but the magnitudes of their effect varied depending on climate conditions. Ammonium availability was higher in warmer years and wetter conditions, while drier areas within the wetland had higher nitrate availability. Carbon uptake was driven by soil moisture, active layer depth, and variability between sampling sites and years (R2 = 0.753), while ecosystem respiration was influenced by nitrogen availability, soil temperature, active layer depth, and sampling year (R2 = 0.848). Considered together, the future carbon dioxide source or sink potential of high latitude wetlands will largely depend on climate-induced changes in moisture and subsequent impacts on nutrient availability

Artificial Neural Network Modeling of High Arctic Phytomass Using Synthetic Aperture Radar and Multispectral Data

Vegetation in the Arctic is often sparse, spatially heterogeneous, and difficult to model. Synthetic Aperture Radar (SAR) has shown some promise in above-ground phytomass estimation at sub-arctic latitudes, but the utility of this type of data is not known in the context of the unique environments of the Canadian High Arctic. In this paper, Artificial Neural Networks (ANNs) were created to model the relationship between variables derived from high resolution multi-incidence angle RADARSAT-2 SAR data and optically-derived (GeoEye-1) Soil Adjusted Vegetation Index (SAVI) values. The modeled SAVI values (i.e., from SAR variables) were then used to create maps of above-ground phytomass across the study area. SAVI model results for individual ecological classes of polar semi-desert, mesic heath, wet sedge, and felsenmeer were reasonable, with r2 values of 0.43, 0.43, 0.30, and 0.59, respectively. When the outputs of these models were combined to analyze the relationship between the model output and SAVI as a group, the r2 value was 0.60, with an 8% normalized root mean square error (% of the total range of phytomass values), a positive indicator of a relationship. The above-ground phytomass model also resulted in a very strong relationship (r2 = 0.87) between SAR-modeled and field-measured phytomass. A positive relationship was also found between optically derived SAVI values and field measured phytomass (r2 = 0.79). These relationships demonstrate the utility of SAR data, compared to using optical data alone, for modeling above-ground phytomass in a high arctic environment possessing relatively low levels of vegetation

Investigating ten years of warming and enhanced snow depth on nutrient availability and greenhouse gas fluxes in a High Arctic ecosystem

ABSTRACTArctic warming and changing precipitation patterns are altering soil nutrient availability and other processes that control the greenhouse gas balance of high-latitude ecosystems. Changes to these biogeochemical processes will ultimately determine whether the Arctic will enhance or dampen future climate change. At the Cape Bounty Arctic Watershed Observatory, a full-factorial International Tundra Experiment site was established in 2008, allowing for the investigation of ten years of experimental warming and increased snow depth on nutrient availability and trace gas exchange in a mesic heath tundra across two growing seasons (2017 and 2018). Plots with open-top chambers (OTCs) had drier soils (p < .1) that released 1.5 times more carbon dioxide (p < .05), and this effect was enhanced in the drier growing season. Increased snow depth delayed the onset of thaw and active layer development (p < .1) and corresponded with greater nitrous oxide release (p < .05). Our results suggest that decreases to soil moisture will lead to an increase in nitrate availability, soil respiration, and nitrous oxide fluxes. Ultimately, these effects may be moderated by the magnitude of future shifts and interactions between climate variability and ecological responses to permafrost thaw

From leaf to canopy: estimation of chlorophyll content using remote sensing to monitor forest conditions

Presented at the Third North American Forest Ecology Workshop, Duluth, Minnesota (USA), 24th-27th June, 2001To develop practical and objective measures of forest condition, the Bioindicators of Forest Condition Project has applied a physiological, remote sensing approach. While stress indicators at the leaf-level exist (e.g., chlorophyll fluorescence, and pigment content), developing reliable indicators at the canopy level is a challenge. Hyperspectral sensors, such as the Compact Airborne Spectrographic Imager (CASI), may be useful in remote detection of vegetation stress effects. In this study, an inverse modeling approach demonstrated the capability of the CASI to map chlorophyll content (root mean square errors ranging from 12.6 to 13.0 mg/cm2) following different silvicultural practices in a tolerant hardwood (Acer saccharum M.) forest. This capability could be readily applicable to operational assessment of forest physiological strain, and in classification of forest condition based on chlorophyll content. The practical significance of developing spectral features related to chlorophyll or other pigments is in identifying whether forests are healthy or stressed (to the point where productivity of the resource may be constrained). A change analysis study was also conducted to evaluate chlorophyll estimation across seasons for a range of sites. Temporal variations in pigment concentrations (e.g. chlorophyll) could provide an objective, earlywarning indicator. The implications of these findings and recommendations for a prototype system to monitor forest condition are presented.Peer reviewe