Ecological land survey and soils inventory for Katmai National Park and Preserve, 2016–2017

This study was conducted to inventory, classify, and map soils and vegetation within the ecosystems of Katmai National Park and Preserve (KATM) using an ecological land survey (ELS) approach. The ecosystem classes identified in the ELS effort were mapped across the park, using an archive of Geo-graphic Information System (GIS) and Remote Sensing (RS) datasets pertaining to land cover, topography, surficial geology, and glacial history. The description and mapping of the landform-vegetation-soil relationships identified in the ELS work provides tools to support the design and implementation of future field- and RS-based studies, facilitates further analysis and contextualization of existing data, and will help inform natural resource management decisions. We collected information on the geomorphic, topographic, hydrologic, pedologic, and vegetation characteristics of ecosystems using a dataset of 724 field plots, of which 407 were sampled by ABR, Inc.—Environmental Research and Services (ABR) staff in 2016–2017, and 317 were from existing, ancillary datasets. ABR field plots were located along transects that were selected using a gradient-direct sampling scheme (Austin and Heligers 1989) to collect data for the range of ecological conditions present within KATM, and to provide the data needed to interpret ecosystem and soils development. The field plot dataset encompassed all of the major environmental gradients and landscape histories present in KATM. Individual state-factors (e.g., soil pH, slope aspect) and other ecosystem components (e.g., geomorphic unit, vegetation species composition and structure) were measured or categorized using standard classification systems developed for Alaska. We described and analyzed the hierarchical relationships among the ecosystem components to classify 92 Plot Ecotypes (local-scale ecosystems) that best partitioned the variation in soils, vegetation, and disturbance properties observed at the field plots. From the 92 Plot Ecotypes, we developed classifications of Map Ecotypes and Disturbance Landscapes that could be mapped across the park. Additionally, using an existing surficial geology map for KATM, we developed a map of Generalized Soil Texture by aggregating similar surficial geology classes into a reduced set of classes representing the predominant soil textures in each. We then intersected the Ecotype map with the General-ized Soil Texture Map in a GIS and aggregated combinations of Map Ecotypes with similar soils to derive and map Soil Landscapes and Soil Great Groups. The classification of Great Groups captures information on the soil as a whole, as opposed to the subgroup classification which focuses on the properties of specific horizons (Soil Survey Staff 1999). Of the 724 plots included in the Ecotype analysis, sufficient soils data for classifying soil subgroups was available for 467 plots. Soils from 8 orders of soil taxonomy were encountered during the field sampling: Alfisols (<1% of the mapped area), Andisols (3%), Entisols (45%), Gelisols (<1%), Histosols (12%), Inceptisols (22%), Mollisols (<1%), and Spodosols (16%). Within these 8 Soil Orders, field plots corresponded to a total of 74 Soil Subgroups, the most common of which were Typic Cryaquents, Typic Cryorthents, Histic Cryaquepts, Vitrandic Cryorthents, and Typic Cryofluvents.

High Resolution Apparent Thermal Inertia Mapping on Mars

Thermal inertia, which represents the resistance to change in temperature of the upper few centimeters of the surface, provides information to help understand the surficial geology and recent processes that are potentially still active today. It cannot be directly measured on Mars and is therefore usually modelled. We present a new analytical method based on Apparent Thermal Inertia (ATI), a thermal inertia proxy. Calculating ATI requires readily available input data: temperature, incidence angle, visible dust opacity, and a digital elevation model. Because of the high spatial resolution, the method can be used on sloping terrains, which makes possible thermal mapping using THEMIS in nearly any area of Mars. Comparison with results obtained by other approaches using modeled data shows similarity in flat areas and illustrates the significant influence of slope and aspect on albedo and diurnal temperature differences.

Spatial variability in periglacial terrain conditions, northwestern Canada

&lt;p&gt;Throughout much of northern Canada there is an inadequate knowledge of permafrost and periglacial terrain conditions, which impedes development of climate-resilient northern infrastructure, identification of potential geohazards, decision making regarding resource development, and inferring past and future landscape evolution. Using a land systems approach to better understand formation of landscapes and thaw-sensitive terrains of northern Yukon and northwestern Northwest Territories, we aim to describe the permafrost-related landform-sediment assemblages that exist in the region. Permafrost is continuous in the region, but variations in geology, landscape history, climate, relief, ecology, and other natural processes have produced a diverse range of permafrost conditions and landforms. Using the 875 km-long Dempster and Inuvik-to-Tuktoyaktuk highway corridors (DH-ITH) as a regional transect, and high-resolution satellite imagery, a robust methodology was implemented to identify and digitize (at 1:5000 scale) 8793 landforms (589 km&lt;sup&gt;2&lt;/sup&gt;) within a 10 km-wide corridor (8530 km&lt;sup&gt;2&lt;/sup&gt;) and classify them according to main formational process (hydrological, periglacial, and mass movement). Surficial geology data were extracted from available data sets. Landform densities in all feature classes vary substantially along the transect according to physiographic region and surficial geology. The northern 39% of the corridor is characterized by generally rolling or planar relief, numerous waterbodies (19%), and the remaining land area by mostly morainal (67%), glaciofluvial (12%), lacustrine (7%), and alluvial (7%) deposits. By count, it contains 53% of mapped features and the majority of periglacial (67%) and hydrological (70%) features. In particular, the Tuktoyaktuk Coastlands, Peel Plain, and Mackenzie Delta, contain the greatest density of mapped landforms within the corridor, which cover nearly 23%, 15%, and 15% of the land area of these physiographic regions, respectively. These extents reflect the amount of ground ice and level of permafrost-thaw sensitivity of these regions. In contrast, the physiographic regions of the southern 61% of the study area are characterized by high relative relief, few waterbodies (0.2%), and the land area mainly by colluvial (63%), alluvial (18%), and morainal (14%) deposits. Most mass movement features occur here (85% by count), and are concentrated in the Ogilvie Mountains (n = 1027; 108 km&lt;sup&gt;2&lt;/sup&gt;). This feature inventory provides the basis for developing spatial models of landscape-thaw susceptibility, which can inform risk assessment and improve decision making regarding public safety and environmental management.&lt;/p&gt;

Vertical distribution of excess ice in icy sediments and its statistical estimation from geotechnical data (Tuktoyaktuk Coastlands, Northwest Territories)

&lt;div&gt;Excess ice can be found in the form of massive ice and within icy sediments and is an important variable to quantify as it strongly influences the geomorphic response of landscapes to permafrost thaw. The melting of excess ice in the Western Canadian Arctic has led to thaw subsidence and an increase in the number and size of thaw slumps observed across the Northwest Territories which cause issues to Northern infrastructure and affect fluvial and lacustrine watersheds. The Inuvik-Tuktoyaktuk Highway (ITH) is the first all-weather road to reach the Canadian Arctic Coast and its planning and construction has resulted in a significant cryostratigraphic dataset of 566 boreholes, which forms the basis of this contribution. Although visible ice is often recorded in boreholes, it is not a reliable measure of excess ice content on its own and there is currently no reliable method to estimate the excess ice content of boreholes based on commonly available geotechnical data. In this study, a 16-borehole subset of the ITH dataset for which samples were processed for volumetric excess ice content is used to train a beta regression model that predicts the excess ice content of stratigraphic intervals in the study area based on interval depth, visible ice content, surficial geology, and material types. The resulting predictions are compared to recorded massive ice intervals in the same boreholes and show that excess ice within icy sediments can significantly contribute to potential thaw strain and should be considered alongside massive ice when making thaw strain estimates.&lt;/div&gt;