Arctic tundra shrubification can obscure increasing levels of soil erosion in NDVI assessments of land cover derived from satellite imagery

This research was supported by the St Andrews World Leading Scholarship.Monitoring soil erosion in the Arctic tundra is complicated by the highly fragmentated nature of the landscape and the limited spatial resolution of even high-resolution satellite data. The expansion of shrubs across the Arctic has led to substantial changes in vegetation composition that alter the spectral reflectance and directly affect vegetation indices such as the normalized difference vegetation index (NDVI), which is widely applied for environmental monitoring. This change can mask soil erosion if datasets with too coarse spatial resolutions are used, as increases in NDVI driven by shrub expansion can obscure concurrent increases in barren land cover. Here we created land cover maps from a multispectral uncrewed aerial vehicle (UAV) and land cover survey and assessed satellite imagery from PlanetScope, Sentinel-2 and Landsat-8 for several areas in north-eastern Iceland. Additionally, we used a novel application of the Shannon evenness index (SHEI) to evaluate levels of pixel mixing. Our results show that shrub expansion can lead to spectral confusion, which can obscure soil erosion processes and emphasize the importance of considering spatial resolution when monitoring highly fragmented landscapes. We demonstrate that remote sensing data with a resolution < 3 m greatly improves the amount of information captured in an Icelandic tundra environment. The spatial resolution of Landsat data (30 m) is inadequate for environmental monitoring in our study area. We found that the best platform for monitoring tundra land cover is Sentinel-2 when used in combination with multispectral UAV acquisitions for validation. Our study has the potential to improve environmental monitoring capabilities by introducing the use of SHEI to assess pixel mixing and determine optimal spatial resolutions. This approach combined with comparing remote sensing imagery of different spatial and time scales significantly advances our comprehension of land cover changes, including greening and soil degradation, in the Arctic tundra.Publisher PDFPeer reviewe

Environment and Global Climate Change

This module is intended to convey a broad understanding of the nature of climate change and its potential impacts. Students will come to understand the effects of radiation imbalance in the Arctic, fluctuations in albedo, and ecological consequences of decreasing albedo in the Arctic. Upon completion of the module, they will be able to explain: the consequences of decreasing stratospheric ozone, potential hazards of POP's entering Arctic food chains, and the possible impacts of environmental changes on traditional lifestyles in the Arctic. Educational levels: High school, Undergraduate lower division

Geospatial Analysis of Lake and Landscape Interactions within the Toolik Lake Region, North Slope of Alaska

The Arctic region of Alaska is experiencing severe impacts of climate change. The Arctic lakes ecosystems are bound to undergo alterations in its trophic structure and other chemical properties. However, landscape factors controlling the lake influxes were not studied till date. This research has examined the currently existing lake landscape interactions using Remote Sensing and GIS technology. The statistical modeling was carried out using Regression and CART methods. Remote sensing data was applied to derive the required landscape indices. Remote sensing in the Arctic Alaska faces many challenges including persistent cloud cover, low sun angle and limited snow free period. Tundra vegetation types are interspersed and intricate to classify unlike managed forest stands. Therefore, historical studies have remained underachieved with respect thematic accuracies. However, looking at vegetation communities at watershed level and the implementation of expert classification system achieved the accuracies up to 90%. The research has highlighted the probable role of interactions between vegetation root zones, nutrient availability within active zone, as well as importance of permafrost thawing. Multiple regression analyses and Classification Trees were developed to understand relationships between landscape factors with various chemical parameters as well as chlorophyll readings. Spatial properties of Shrubs and Riparian complexes such as complexity of individual patches at watershed level and within proximity of water channels were influential on Chlorophyll production of lakes. Till-age had significant impact on Total Nitrogen contents. Moreover, relatively young tills exhibited significantly positive correlation with concentration of various ions and conductivity of lakes. Similarly, density of patches of Heath complexes was found to be important with respect to Total Phosphorus contents in lakes. All the regression models developed in this study were significant at 95% confidence level. However, the classification trees could not achieve high predictabilities due to limited number of lakes sampled

USING LANDSAT IMAGERY TO EVALUATE LANDSCAPE-LEVEL IMPACTS OF NATURAL GAS FIELD DEVELOPMENT: TAZOVSKY PENNINSULA, RUSSIA, 1984-2007

The Yamburg gas condensate field in northwestern Siberia sits atop the largest natural gas and petroleum basin in the world. Infrastructure related to the extraction and transport of natural gas is both geographically widespread, and has been shown to affect a much larger area than the immediate infrastructural footprint. Because field studies of the environmental impacts of development are often costly or unfeasible given the remoteness of these areas and access restrictions, the use of remote-sensing technologies is a valuable asset for assessing and quantifying disturbance over large areas. Freely available 30 meter resolution Landsat imagery from 1984 to 2007 was employed in this thesis to quantify the effects of natural gas infrastructure on the adjacent tundra using three methods: a landscape fragmentation analysis, mean and change in mean NDVI analyses, and a cross-tabulation analysis. These analyses show that the tundra has become increasingly fragmented during the study period, and that mean NDVI values in areas adjacent to development are lower than those calculated for undisturbed areas. As distance from the infrastructural footprint increases, differences in mean NDVI decrease, approaching undisturbed values at approximately 90 – 150 m. Additionally, analysis of changes in mean NDVI values over time indicate that new infrastructure development has a depressing effect on adjacent NDVI values, while areas that have been consistently developed show a vegetation recovery response evidenced by positive changes in NDVI values when compared to undisturbed areas. Cross-tabulation of the changes in NDVI values between analysis dates indicate that these changes can be attributed to the conversion of vegetated areas to bare ground or water in the case of new development, and conversion from bare ground or water to vegetation in areas that have been consistently developed

Predicting aboveground biomass in Arctic landscapes using very high spatial resolution satellite imagery and field sampling

Remote sensing based biomass estimates in Arctic areas are usually produced using coarse spatial resolution satellite imagery, which is incapable of capturing the fragmented nature of tundra vegetation communities. We mapped aboveground biomass using field sampling and very high spatial resolution (VHSR) satellite images (QuickBird, WorldView-2 and WorldView-3) in four different Arctic tundra or peatland sites with low vegetation located in Russia, Canada, and Finland. We compared site-specific and cross-site empirical regressions. First, we classified species into plant functional types and estimated biomass using easy, non-destructive field measurements (cover, height). Second, we used the cover/height-based biomass as the response variable and used combinations of single bands and vegetation indices in predicting total biomass. We found that plant functional type biomass could be predicted reasonably well in most cases using cover and height as the explanatory variables (adjusted R-2 0.21-0.92), and there was considerable variation in the model fit when the total biomass was predicted with satellite spectra (adjusted R-2 0.33-0.75). There were dissimilarities between cross-site and site-specific regression estimates in satellite spectra based regressions suggesting that the same regression should be used only in areas with similar kinds of vegetation. We discuss the considerable variation in biomass and plant functional type composition within and between different Arctic landscapes and how well this variation can be reproduced using VHSR satellite images. Overall, the usage of VHSR images creates new possibilities but to utilize them to full potential requires similarly more detailed in-situ data related to biomass inventories and other ecosystem change studies and modelling.Peer reviewe

Reactions of shorebirds and passerines to human development in the Russian Arctic under the influence of strict conservation measures

Anthropogenic impact on nesting waders and passerine birds in the Arctic in surroundings of the industrial complex Sabetta, Yamal Peninsula, Russia was studied. A lot of factors associated with human development may affect nesting birds. The human-subsidized predation is considered to be the most significant. Anthropogenic food sources are usually present in human-transformed habitats, as well as additional dens and perch sites. This leads to a higher press of predation. In Sabetta, there are specific conditions causing artificially-limited predation and human-induced disturbance. Finding a large number of nests in close proximity to industrial infrastructure we have suggested that waders (order Charadriiformes) and passerine (order Passeriformes) birds may be tolerant to an urbanized landscape. In the studied industrial habitat, they probably do not reduce the nesting density, thanks to particular advantages of such habitats (drainability and variety of shelters). To test this hypothesis, we performed an analysis of the relationship between the nesting density of the 8 most abundant species of waders and passerines in relation to the degree of habitat transformation. Statistical analysis was carried out using the GLM module of Statsoft Statistica 10. We found a positive relation between nesting density of the Ringed Plover (Charadrius hiaticula) and Snow bunting (Plectrophenax nivalis) and the degree of transformation. Habitat transformation did not significantly affect the White wagtail (Motacilla alba) and Red-throated pipit (Anthus cervinus). The Lapland longspur (Calcarius lapponicus) showed a clear decrease of the nest density in transformed habitats. Last but not least, the Little stint (Calidris minuta), Temminck’s stint (C. temminckii) and Red-necked phalarope (Phalaropus lobatus) completely ignored only artificial habitats, whereas in partially transformed habitats, their mean nesting density was similar to undisturbed natural areas

Species-specific responses to landscape features shaped genomic structure within Alaska galliformes

Aim: Connectivity is vital to the resiliency of populations to environmental change and stochastic events, especially for cold-adapted species as Arctic and alpine tundra habitats retract as the climate warms. We examined the influence of past and current landscapes on genomic connectivity in cold-adapted galliformes as a critical first step to assess the vulnerability of Alaska ptarmigan and grouse to environmental change. We hypothesize that the mosaic of physical features and habitat within Alaska promoted the formation of genetic structure across species. Location: Alaska, United States of America. Taxa: Ptarmigan and Grouse (Galliformes: Tetraoninae). Methods: We collected double digest restriction-site- associated DNA sequence data from six ptarmigan and grouse species (N = 13–145/ species) sampled across multiple ecosystems up to ~10 degrees of latitude. Spatial genomic structure was analysed using methods that reflect different temporal scales: (1) principal components analysis to identify major trends in the distribution of genomic variation; (2) maximum likelihood clustering analyses to test for the presence of multiple genomic groupings; (3) shared co-ancestry analyses to assess contemporary relationships and (4) effective migration surfaces to identify regions that deviate from a null model of isolation by distance. Results: Levels of genomic structure varied across species (ΦST =0.009–0.042). Three general patterns of structure emerged: (1) east-west partition located near the Yukon-Tanana uplands; (2) north-south split coinciding with the Alaska Range and (3) northern group near the Brooks Range. Species-specific patterns were observed; not all landscape features were barriers to gene flow for all ptarmigan and grouse and temporal contrasts were detected at the Brooks Range. Main conclusions: Within Alaska galliformes, patterns of genomic structure coincide with physiographic features and highlight the importance of physical and ecological barriers in shaping how genomic diversity is arrayed across the landscape. Lack of concordance in spatial patterns indicates that species behaviour and habitat affinities play key roles in driving the contrasting patterns of genomic structure

Transition from connected to fragmented vegetation across an environmental gradient: scaling laws in ecotone geometry

A change in the environmental conditions across space—for example, altitude or latitude—can cause significant changes in the density of a vegetation type and, consequently, in spatial connectivity. We use spatially explicit simulations to study the transition from connected to fragmented vegetation. A static (gradient percolation) model is compared to dynamic (gradient contact process) models. Connectivity is characterized from the perspective of various species that use this vegetation type for habitat and differ in dispersal or migration range, that is, “step length” across the landscape. The boundary of connected vegetation delineated by a particular step length is termed the “ hull edge.” We found that for every step length and for every gradient, the hull edge is a fractal with dimension 7/4. The result is the same for different spatial models, suggesting that there are universal laws in ecotone geometry. To demonstrate that the model is applicable to real data, a hull edge of fractal dimension 7/4 is shown on a satellite image of a piñon‐juniper woodland on a hillside. We propose to use the hull edge to define the boundary of a vegetation type unambiguously. This offers a new tool for detecting a shift of the boundary due to a climate change