Cathy J. Wilson

Arctic Landscapes in Transition: Responses to Thawing Permafrost

Observations indicate that over the past several decades, geomorphic processes in the Arctic have been changing or intensifying. Coastal erosion, which currently supplies most of the sediment and carbon to the Arctic Ocean [Rachold et al., 2000], may have doubled since 1955 [Mars and Houseknecht, 2007]. Further inland, expansion of channel networks [Toniolo et al., 2009] and increased river bank erosion [Costard et al., 2007] have been attributed to warming. Lakes, ponds, and wetlands appear to be more dynamic, growing in some areas, shrinking in others, and changing distribution across lowland regions [e.g., Smith et al., 2005]. On the Arctic coastal plain, recent degradation of frozen ground previously stable for thousands of years suggests 10–30% of lowland and tundra landscapes may be affected by even modest warming [Jorgenson et al., 2006]. In headwater regions, hillslope soil erosion and landslides are increasing [e.g., Gooseff et al., 2009].

Quantifying and relating land-surface and subsurface variability in permafrost environments using LiDAR and surface geophysical datasets

The value of remote sensing and surface geophysical data for characterizing the spatial variability and relationships between land-surface and subsurface properties was explored in an Alaska (USA) coastal plain ecosystem. At this site, a nested suite of measurements was collected within a region where the land surface was dominated by polygons, including: LiDAR data; ground-penetrating radar, electromagnetic, and electrical-resistance tomography data; active-layer depth, soil temperature, soil-moisture content, soil texture, soil carbon and nitrogen content; and pore-fluid cations. LiDAR data were used to extract geomorphic metrics, which potentially indicate drainage potential. Geophysical data were used to characterize active-layer depth, soil-moisture content, and permafrost variability. Cluster analysis of the LiDAR and geophysical attributes revealed the presence of three spatial zones, which had unique distributions of geomorphic, hydrological, thermal, and geochemical properties. The correspondence between the LiDAR-based geomorphic zonation and the geophysics-based active-layer and permafrost zonation highlights the significant linkage between these ecosystem compartments. This study suggests the potential of combining LiDAR and surface geophysical measurements for providing high-resolution information about land-surface and subsurface properties as well as their spatial variations and linkages, all of which are important for quantifying terrestrial-ecosystem evolution and feedbacks to climate.ResuméLa portée de la télédétection et des données géophysique de surface pour caractériser la variabilité spatiale et les relations entre la surface du terrain et les propriétés de la subsurface a été étudiée sous tous ses aspects dans l’écosystème de la plaine côtière d’Alaska (USA). Dans cette région, sur un site où la surface du sol est dominée par des polygones, une série de données se recoupant a été collectée, incluant : données LiDAR; géoradar, tomographie électromagnétique et résistivité; profondeur de la couche aquifère, température, teneur en humidité, texture, teneur en carbone et en azote du sol; et cations du fluide des pores. Les données Lidar ont été utilisées pour établir les cotes géomorphiques, qui peuvent indiquer un drainage potentiel. Des données géophysiques ont été utilisées pour déterminer la profondeur de la couche aquifère, la teneur en humidité du sol, et la variabilité du pergélisol. L’analyse par agglomérat des données LiDAR et des attributs géophysiques ont révélé la présence de trois zones spatiales ayant une distribution similaire des propriétés géomorphiques, hydrogéologiques, thermales et géochimiques. La correspondance entre la zonation géomorphique basée sur LiDAR, la couche aquifère selon la géophysique et la zonation permafrost, met en lumière la relation significative entre ces compartiments de l’écosystème. Cette étude montre le potentiel d’une combinaison des mesures LiDAR et des mesures géophysiques de surface pour fournir une information haute résolution sur les propriétés de surface et de subsurface du sol aussi bien que sur leur variations spatiales et liens, toutes étant importantes pour quantifier l’évolution de l’écosystème terrestre et les réponses au climat.ResumenSe exploró el valor de los sensores remotos y de los datos geofísicos de superficie para caracterizar la variabilidad espacial y las relaciones entre la superficie y las propiedades subsuperficiales en un ecosistema de planicie costera en Alaska (EEUU). En este sitio, un conjunto anidado de medidas fue colectado dentro de una región donde la superficie estaba dominada por polígonos, incluyendo: datos LiDAR; datos de radar, electromagnéticos, y tomografías de resistividad eléctrica; profundidad de la capa activa, temperatura del suelo, contenido de humedad del suelo, textura del suelo, contenido de carbono y nitrógeno en suelo; y cationes del fluido de poros. Los datos LiDAR fueron usados para extraer los indicadores geomórficos, que posiblemente indican un drenaje potencial. Los datos geofísicos fueron para caracterizar la profundidad de la capa activa, el contenido de humedad del suelo y la variabilidad del permafrost. En análisis de cluster de los LiDAR y los atributos geofísicos revelaron la presencia espacial de tres zonas, que tenían una única distribución de propiedades geomórficas, hidrológicas, térmicas y geoquímicas. La correspondencia entre la zonación geomórfica basada en LiDAR y la capa activa basada en geofísica y la zonación del permafrost destaca la vinculación significativa entre estos compartimentos del ecosistema. Este estudio sugiere el potencial de la combinación LiDAR y las mediciones geofísicas de superficie para proveer información de alta resolución acerca de las propiedades de la superficie y de la subsuperficie así como su variación espacial y su articulación, todos los cuales son importantes para cuantificar la evolución del ecosistema terrestre y las reacciones con el clima.摘要用来描述地表和地下性质的空间变异性和两者之间的关系的遥感和地面地球物理数据已在阿拉斯加(美国)的一个沿海平原生态系统进行了探讨。在本次研究场地的一个表面呈多边形的区域收集到了一套测量数据,包括激光雷达数据;探地雷达数据,电磁和电阻断层扫描数据;活性层深度,土壤温度,土壤水气含量,土壤质地,土壤碳和氮的含量;以及孔隙流体阳离子数据。激光雷达数据用来提取地貌指标,这可能指示出潜在的排泄。地球物理数据用来刻画活性层的深度,土壤水气含量和永久冻土的变化特征。通过对激光雷达和地球物理数据属性的聚类分析发现了三个在地形,水文,热和地球化学性质分布上存在异常的空间区域。基于激光雷达测量的地貌分区与基于地球物理数据的活性层和永久冻土分区之间的对应关系突出了这些生态系统分区间的紧密联系。本次研究表明可以通过结合激光雷达和地表地球物理测量来为地表和地下的性质以及它们在空间上的变化和关系提供高分辨率的信息,所有这些对于量化陆地生态系统的演化和对气候变化的反应都是非常重要的。ResumoNum ecossistema da planície costeira do Alaska (EUA) foi explorado o valor da deteção remota e de dados de geofísica de superfície para caracterizar a variabilidade espacial e as relações entre propriedades da superfície do terreno e da subsuperfície. Neste local, inserido numa região onde o terreno superficial é dominado por polígonos, foi recolhido um conjunto agregado de medições, incluindo: dados de LiDAR; dados de geoadar, eletromagnéticos e de tomografia de resistência elétrica; profundidade da camada ativa, temperatura do solo, teor de água no solo, textura do solo, teor de carbono e azoto no solo; e catiões no fluido poroso. Os dados LiDAR foram usados para extrair dimensões geomórficas que potencialmente indicam o potencial de drenagem. Os dados geofísicos foram usados para caracterizar a profundidade da camada ativa, o teor de humidade no solo e a variabilidade no permafrost. A análise grupal de atributos LiDAR e geofísicos revelou a presença de três zonas espaciais que tinham distribuições únicas de propriedades geomórficas, hidrológicas, térmicas e geoquímicas. A correspondência entre o zonamento geomórfico baseado no LiDAR e a zonação da camada activa baseada na geofísica e do permafrost, demonstra a significativa conexão entre estes compartimentos do ecossistema. Este estudo sugere o potencial da combinação de medições de LiDAR e de geofísica de superfície para fornecer informação de alta resolução acerca das propriedades da superfície do terreno e da subsuperfície, assim como sobre as variações espaciais e conexões, sendo todas elas importantes para a quantificação da evolução do ecossistema terrestre e as retroações com o clima.

Effects of logging and fire on runoff and erosion on highly erodible granitic soils in Tasmania

A set of rainfall simulator experiments was carried out in a logged forest in Tasmania, Australia, to quantify the impact of logging and fire on runoff and soil loss. A large, portable rainfall simulator was developed for the experiments to help overcome problems associated with spatially varying hydraulic and erosion properties of the soil. Simulated rainfall events with intensities of approximately 35, 75, and 150 mm h−1 were applied to four 300 m2 plots with different levels of surface disturbance: severely burnt, logged and burnt with high mechanical disturbance, logged with low mechanical disturbance, and undisturbed. The experiments indicated that the amount of runoff and soil loss from the plots depended on the type and degree of disturbance to the natural biotic crust developed on this soil. Erodibility per unit runoff was greatest on the severely burnt plot; but runoff on the mechanically disturbed site was so great that it produced the highest total sediment yield on an event basis. Runoff production was similar on the three plots where the natural biotic crust was largely intact and was low relative to the plot with high mechanical disturbance. Total sediment yield was typically higher on logged plots than on unlogged plots.

Toward a Mechanistic Modeling of Nitrogen Limitation on Vegetation Dynamics

Nitrogen is a dominant regulator of vegetation dynamics, net primary production, and terrestrial carbon cycles; however, most ecosystem models use a rather simplistic relationship between leaf nitrogen content and photosynthetic capacity. Such an approach does not consider how patterns of nitrogen allocation may change with differences in light intensity, growing-season temperature and CO2 concentration. To account for this known variability in nitrogen-photosynthesis relationships, we develop a mechanistic nitrogen allocation model based on a trade-off of nitrogen allocated between growth and storage, and an optimization of nitrogen allocated among light capture, electron transport, carboxylation, and respiration. The developed model is able to predict the acclimation of photosynthetic capacity to changes in CO2 concentration, temperature, and radiation when evaluated against published data of Vc,max (maximum carboxylation rate) and Jmax (maximum electron transport rate). A sensitivity analysis of the model for herbaceous plants, deciduous and evergreen trees implies that elevated CO2 concentrations lead to lower allocation of nitrogen to carboxylation but higher allocation to storage. Higher growing-season temperatures cause lower allocation of nitrogen to carboxylation, due to higher nitrogen requirements for light capture pigments and for storage. Lower levels of radiation have a much stronger effect on allocation of nitrogen to carboxylation for herbaceous plants than for trees, resulting from higher nitrogen requirements for light capture for herbaceous plants. As far as we know, this is the first model of complete nitrogen allocation that simultaneously considers nitrogen allocation to light capture, electron transport, carboxylation, respiration and storage, and the responses of each to altered environmental conditions. We expect this model could potentially improve our confidence in simulations of carbon-nitrogen interactions and the vegetation feedbacks to climate in Earth system models.

Extrapolating active layer thickness measurements across Arctic polygonal terrain using LiDAR and NDVI data sets.

Landscape attributes that vary with microtopography, such as active layer thickness (ALT), are labor intensive and difficult to document effectively through in situ methods at kilometer spatial extents, thus rendering remotely sensed methods desirable. Spatially explicit estimates of ALT can provide critically needed data for parameterization, initialization, and evaluation of Arctic terrestrial models. In this work, we demonstrate a new approach using high-resolution remotely sensed data for estimating centimeter-scale ALT in a 5 km2 area of ice-wedge polygon terrain in Barrow, Alaska. We use a simple regression-based, machine learning data-fusion algorithm that uses topographic and spectral metrics derived from multisensor data (LiDAR and WorldView-2) to estimate ALT (2 m spatial resolution) across the study area. Comparison of the ALT estimates with ground-based measurements, indicates the accuracy (r2 = 0.76, RMSE ±4.4 cm) of the approach. While it is generally accepted that broad climatic variability associated with increasing air temperature will govern the regional averages of ALT, consistent with prior studies, our findings using high-resolution LiDAR and WorldView-2 data, show that smaller-scale variability in ALT is controlled by local eco-hydro-geomorphic factors. This work demonstrates a path forward for mapping ALT at high spatial resolution and across sufficiently large regions for improved understanding and predictions of coupled dynamics among permafrost, hydrology, and land-surface processes from readily available remote sensing data.

Modeling challenges for predicting hydrologic response to degrading permafrost

The fate of the approximately 1,700 billion metric tons of carbon (Tarnocai et al. 2009) currently frozen in permafrost affected regions of the Arctic and subarctic is highly uncertain (IPCC 2007), primarily because of the potential for topographic evolution and resulting drainage network reorganization as permafrost degrades and massive ground ice contained in ice-rich permafrost soils melts. Computer modeling is a key tool in untangling these complex feedbacks to understand the evolution of the Arctic and subarctic landscapes and the potential feedbacks with the global climate system. Some of the challenges associated with modeling the hydrologic system in and around degrading permafrost are discussed in this essay. Modeling requirements depend very strongly on the spatial resolution of the model. Two different classes can be identified, depending on whether microtopography is explicitly resolved or incorporated into the model through a subgrid parameterization. The focus here is on the computational challenges associated with microtopography-resolving models using hydrologic response of polygon mires as an example. In such microtopography-resolving models, horizontal grid spacing on the order of 0.25mwould typically be required. Although highand low-centered ice wedge polygons have been identified as important controls on Arctic surface hydrology (e.g. Liljedahl et al. 2012) and evolution from lowto highcentered polygon landscapes is expected as Arctic temperatures increase (Jorgenson et al. 2006), as far as we are aware, there is no existing computer code that represents the full range of processes required to model the co-evolution of surface topography, active layer, and permafrost at the microtopography-resolving scale. For microtopography-resolving models of hydrology in permafrost landscapes, it is convenient to partition the large number of coupled processes into four critical sets: subsurface thermal/hydrology, surface thermal processes, mechanical deformation, and overland flow processes. However, it is important to recognize that the partitioning is somewhat arbitrary and that multiple tightly coupled processes exist within each set.

Antibody Responses to Acinetobacter spp. and Pseudomonas aeruginosa in Multiple Sclerosis: Prospects for Diagnosis Using the Myelin-Acinetobacter-Neurofilament Antibody Index

ABSTRACT Antibody responses to Acinetobacter (five strains),Pseudomonas aeruginosa, Escherichia coli, myelin basic protein (MBP), and neurofilaments were measured in sera from 26 multiple sclerosis (MS) patients, 20 patients with cerebrovascular accidents (CVA), 10 patients with viral encephalitis, and 25 healthy blood donors. In MS patients, elevated levels of antibodies against all strains of Acinetobacter tested were present, as well as antibodies against P. aeruginosa, MBP, and neurofilaments, but not antibodies toE. coli, compared to the CVA group and controls. The myelin-Acinetobacter-neurofilament antibody index appears to distinguish MS patients from patients with CVAs or healthy controls. The relevance of such antibodies to the neuropathology of MS requires further evaluation.

Microtopographic and depth controls on active layer chemistry in Arctic polygonal ground

Polygonal ground is a signature characteristic of Arctic lowlands, and carbon release from permafrost thaw can alter feedbacks to Arctic ecosystems and climate. This study describes the first comprehensive spatial examination of active layer biogeochemistry that extends across high- and low-centered, ice wedge polygons, their features, and with depth. Water chemistry measurements of 54 analytes were made on surface and active layer pore waters collected near Barrow, Alaska, USA. Significant differences were observed between high- and low-centered polygons suggesting that polygon types may be useful for landscape-scale geochemical classification. However, differences were found for polygon features (centers and troughs) for analytes that were not significant for polygon type, suggesting that finer-scale features affect biogeochemistry differently from polygon types. Depth variations were also significant, demonstrating important multidimensional aspects of polygonal ground biogeochemistry. These results have major implications for understanding how polygonal ground ecosystems function, and how they may respond to future change.

A water balance approach to assessing the hydrologic buffering potential of an alluvial fan

The hydrologic connectivity of a catchment determines the efficiency with which runoff is moved through the catchment and hence opportunities for runoff storage. Potential storages include valley floors and alluvial fans. Monitoring results from a small alluvial fan indicate that alluvial fans can be significant hydrologic buffers. Between 20% and 100% of surface runoff delivered to the study fan from a 26-ha catchment was slowed and/or stored during the monitored events. Interevent differences in buffering response are attributed to antecedent moisture conditions. In one event, when catchment conditions were very wet, only 20% of incoming runoff was absorbed by the fan. Under dry conditions, smaller proportions of total rainfall were delivered to the fan head as surface runoff, of which >60% was absorbed by the fan. Because sediment storages can modify surface runoff delivery, because of their distinctive morphologic and sedimentologic properties, it is suggested that their distribution through a catchment will influence catchment hydrologic connectivity hence runoff and sediment delivery through catchments.

Comparison of SAR techniques for luminescence dating of sediments derived from volcanic tuff

Abstract In this investigation we evaluate several proposed optically stimulated luminescence single-aliquot regeneration (OSL SAR) procedures to determine which technique has the greatest potential to yield accurate ages for samples collected from tuff-derived alluvial sediments within the narrow, sharply incised canyon systems of the Pajarito Plateau of northern New Mexico. The SAR data collection methods evaluated are: infrared-stimulated luminescence (IRSL), post-IR blue-OSL, IRSL with TL annealing cycles on polymineral fine-grains, and blue-OSL on quartz fine sand. A single-grain laser luminescence (SGLL) procedure for quartz sand is also evaluated. Age estimates obtained from these methods are compared with radiocarbon, soil PDI (profile development index), and IRSL multi-aliquot additive dose (MAAD) age constraints. Our results indicate that the modal D e of quartz sand SGLL dose distributions yield ages that are consistent with radiocarbon and PDI age constraints for the tuff derived sediments in this investigation and appears to be the most promising method for studies in this area. Additionally, two fine-grained polymineral methods, IRSL SAR and traditional IRSL MAAD, produced ages that were generally in agreement with the SGLL ages and with available 14 C and PDI age constraints. At the present stage of research, we advocate using quartz sand SGLL in conjunction with IRSL SAR or even IRSL MAAD for polymineral fine-grains to provide the most robust and reliable luminescence age data sets for tuff-derived sediments.