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At least 613 records · Page 34Linked to original sources
USGS2007

Forest dynamics in Oregon landscapes: Evaluation and application of an individual-based model

The FORCLIM model of forest dynamics was tested against field survey data for its ability to simulate basal area and composition of old forests across broad climatic gradients in western Oregon, USA. The model was also tested for its ability to capture successional trends in ecoregions of the west Cascade Range. It was then applied to simulate present and future (1990-2050) forest landscape dynamics of a watershed in the west Cascades. Various regimes of climate change and harvesting in the watershed were considered in the landscape application. The model was able to capture much of the variation in forest basal area and composition in western Oregon even though temperature and precipitation were the only inputs that were varied among simulated sites. The measured decline in total basal area from tall coastal forests eastward to interior steppe was matched by simulations. Changes in simulated forest dominants also approximated those in the actual data. Simulated abundances of a few minor species did not match actual abundances, however. Subsequent projections of climate change and harvest effects in a west Cascades landscape indicated no change in forest dominance as of 2050. Yet, climate-driven shifts in the distributions of some species were projected. The simulation of both stand-replacing and partial-stand disturbances across western Oregon improved agreement between simulated and actual data. Simulations with fire as an agent of partial disturbance suggested that frequent fires of low severity can alter forest composition and structure as much or more than severe fires at historic frequencies. ?? 2007 by the Ecological Society of America.

Ecological Applications↗
USGS2014

Simulating future residential property losses from wildfire in Flathead County, Montana

Wildfire damages to private residences in the United States and elsewhere have increased as a result of expansion of the wildland-urban interface (WUI) and other factors. Understanding this unwelcome trend requires analytical frameworks that simulate how various interacting social, economic, and biophysical factors influence those damages. A methodological framework is developed for simulating expected residential property losses from wildfire [E(RLW)], which is a probabilistic monetary measure of wildfire risk to residential properties in the WUI. E(RLW) is simulated for Flathead County, Montana for five, 10-year subperiods covering the period 2010-2059, under various assumptions about future climate change, economic growth, land use policy, and forest management. Results show statistically significant increases in the spatial extent of WUI properties, the number of residential structures at risk from wildfire, and E(RLW) over the 50-year evaluation period for both the county and smaller subareas (i.e., neighborhoods and parcels). The E(RLW) simulation framework presented here advances the field of wildfire risk assessment by providing a finer-scale tool that incorporates a set of dynamic, interacting processes. The framework can be applied using other scenarios for climate change, economic growth, land use policy, and forest management, and in other areas.

Montana↗
USGS2018

Assessing historical and projected carbon balance of Alaska: A synthesis of results and policy/management implications

We summarize the results of a recent interagency assessment of land carbon dynamics in Alaska, in which carbon dynamics were estimated for all major terrestrial and aquatic ecosystems for the historical period (1950–2009) and a projection period (2010–2099). Between 1950 and 2009, upland and wetland (i.e., terrestrial) ecosystems of the state gained 0.4 Tg C/yr (0.1% of net primary production, NPP), resulting in a cumulative greenhouse gas radiative forcing of 1.68 × 10 −3 W/m 2 . The change in carbon storage is spatially variable with the region of the Northwest Boreal Landscape Conservation Cooperative (LCC) losing carbon because of fire disturbance. The combined carbon transport via various pathways through inland aquatic ecosystems of Alaska was estimated to be 41.3 Tg C/yr (17% of terrestrial NPP). During the projection period (2010–2099), carbon storage of terrestrial ecosystems of Alaska was projected to increase (22.5–70.0 Tg C/yr), primarily because of NPP increases of 10–30% associated with responses to rising atmospheric CO 2 , increased nitrogen cycling, and longer growing seasons. Although carbon emissions to the atmosphere from wildfire and wetland CH 4 were projected to increase for all of the climate projections, the increases in NPP more than compensated for those losses at the statewide level. Carbon dynamics of terrestrial ecosystems continue to warm the climate for four of the six future projections and cool the climate for only one of the projections. The attribution analyses we conducted indicated that the response of NPP in terrestrial ecosystems to rising atmospheric CO 2 (~5% per 100 ppmv CO 2 ) saturates as CO 2 increases (between approximately +150 and +450 ppmv among projections). This response, along with the expectation that permafrost thaw would be much greater and release large quantities of permafrost carbon after 2100, suggests that projected carbon gains in terrestrial ecosystems of Alaska may not be sustained. From a national perspective, inclusion of all of Alaska in greenhouse gas inventory reports would ensure better accounting of the overall greenhouse gas balance of the nation and provide a foundation for considering mitigation activities in areas that are accessible enough to support substantive deployment.

Alaska↗
USGS2015

Rangeland monitoring reveals long-term plant responses to precipitation and grazing at the landscape scale

Managers of rangeland ecosystems require methods to track the condition of natural resources over large areas and long periods of time as they confront climate change and land use intensification. We demonstrate how rangeland monitoring results can be synthesized using ecological site concepts to understand how climate, site factors, and management actions affect long-term vegetation dynamics at the landscape-scale. Forty-six years of rangeland monitoring conducted by the Bureau of Land Management (BLM) on the Colorado Plateau reveals variable responses of plant species cover to cool-season precipitation, land type (ecological site groups), and grazing intensity. Dominant C 3 perennial grasses (Achnatherum hymenoides , Hesperostipa comata) , which are essential to support wildlife and livestock on the Colorado Plateau, had responses to cool-season precipitation that were at least twice as large as the dominant C 4 perennial grass (Pleuraphis jamesii) and woody vegetation. However, these C 3 perennial grass responses to precipitation were reduced by nearly one-third on grassland ecological sites with fine- rather than coarse-textured soils, and there were no detectable C 3 perennial grass responses to precipitation on ecological sites dominated by a dense-growing shrub, Coleogyne ramosissima . Heavy grazing intensity further reduced the responses of C 3 perennial grasses to cool-season precipitation on ecological sites with coarse-textured soils and surprisingly reduced the responses of shrubs as well. By using ecological site groups to assess rangeland condition, we were able to improve our understanding of the long-term relationships between vegetation change and climate, land use, and site characteristics, which has important implications for developing landscape-scale monitoring strategies.

Arizona, Colorado, New Mexico, Utah↗
USGS2019

Modeling spatially and temporally complex range dynamics when detection is imperfect

Species distributions are determined by the interaction of multiple biotic and abiotic factors, which produces complex spatial and temporal patterns of occurrence. As habitats and climate change due to anthropogenic activities, there is a need to develop species distribution models that can quantify these complex range dynamics. In this paper, we develop a dynamic occupancy model that uses a spatial generalized additive model to estimate non-linear spatial variation in occupancy not accounted for by environmental covariates. The model is flexible and can accommodate data from a range of sampling designs that provide information about both occupancy and detection probability. Output from the model can be used to create distribution maps and to estimate indices of temporal range dynamics. We demonstrate the utility of this approach by modeling long-term range dynamics of 10 eastern North American birds using data from the North American Breeding Bird Survey. We anticipate this framework will be particularly useful for modeling species’ distributions over large spatial scales and for quantifying range dynamics over long temporal scales.

Scientific Reports↗
USGS2021

Climatic aridity shapes post-fire interactions between Ceanothus spp. and Douglas-fir (Pseudotsuga menziesii) across the Klamath Mountains

Climate change is leading to increased drought intensity and fire frequency, creating early-successional landscapes with novel disturbance–recovery dynamics. In the Klamath Mountains of northwestern California and southwestern Oregon, early-successional interactions between nitrogen (N)-fixing shrubs ( Ceanothus spp.) and long-lived conifers (Douglas-fir) are especially important determinants of forest development. We sampled post-fire vegetation and soil biogeochemistry in 57 plots along gradients of time since fire (7–28 years) and climatic water deficit (aridity). We found that Ceanothus biomass increased, and Douglas-fir biomass decreased with increasing aridity. High aridity and Ceanothus biomass interacted with lower soil C:N more than either factor alone. Ceanothus biomass was initially high after fire and declined with time, suggesting a large initial pulse of N-fixation that could enhance N availability for establishing Douglas-fir. We conclude that future increases in aridity and wildfire frequency will likely limit post-fire Douglas-fir establishment, though Ceanothus may ameliorate some of these impacts through benefits to microclimate and soils. Results from this study contribute to our understanding of the effects of climate change and wildfires on interspecific interactions and forest dynamics. Management seeking to accelerate forest recovery after high-severity fire should emphasize early-successional conifer establishment while maintaining N-fixing shrubs to enhance soil fertility.

California, Oregon↗
USGS2024

The dynamic feasibility of resisting (R), accepting (A), or directing (D) ecological change

Ecological transformations are occurring as a result of climate change, challenging traditional approaches to land management decision-making. The resist–accept–direct (RAD) framework helps managers consider how to respond to this challenge. We examined how the feasibility of the choices to resist, accept, and direct shifts in complex and dynamic ways through time. We considered 4 distinct types of social feasibility: regulatory, financial, public, and organizational. Our commentary is grounded in literature review and the examples that exist but necessarily has speculative elements because empirical evidence on this newly emerging management strategy is scarce. We expect that resist strategies will become less feasible over time as managers encounter situations where resisting is ecologically, by regulation, financially, or publicly not feasible. Similarly, we expect that as regulatory frameworks increasingly permit their use, if costs decrease, and if the public accepts them, managers will increasingly view accept and direct strategies as more viable options than they do at present. Exploring multiple types of feasibility over time allows consideration of both social and ecological trajectories of change in tandem. Our theorizing suggested that deepening the time horizon of decision-making allows one to think carefully about when one should adopt different approaches and how to combine them over time.

Conservation Biology↗
USGS2021

Investigation of land surface phenology detections in shrublands using multiple scale satellite data

Shrublands occupy about 13% of the global land surface, contain about one-third of the biodiversity, store about half of the global terrestrial carbon, and provide many ecosystem services to a large amount of world's human population and livestock. Because phenology is a sensitive indicator of the response of shrubland ecosystems to climate change, the alteration of ecosystems following species invasions, and the dynamics of shrubland ecosystem function, biodiversity, and carbon budgets, it is critical to monitor and assess phenological dynamics in shrubland ecosystems. However, most current land surface phenology (LSP) products derived from satellite data do not provide phenology detections in some semiarid shrublands where the amplitude of seasonal vegetation greenness is small. Therefore, we investigated the LSP detection using multiple spatial resolution satellite data and examined the impacts of spatial scales and shrubland ecosystem components (shrub and herb cover) on LSP detections over the western United States. Specifically, greenup onset date (GUD) in shrublands was detected from 30 m Harmonized Landsat and Sentinel-2 (HLS) data and 500 m Visible Infrared Imaging Radiometer Suite (VIIRS) data to quantify scale effects. The GUD spatial patterns were explored with 30 m pixel variations in shrubland ecosystem components. The results show that GUD values varied with percent vegetation cover and shifted to earlier dates with increasing vegetation cover, demonstrating that satellite observations were not able to capture greenup onset until a threshold of green vegetation cover is reached. GUD was mostly undetectable from both HLS and VIIRS pixels with vegetation cover less than 10% and became fully detectable with vegetation covers larger than 50%. Similarly, the differences of GUD between HLS and VIIRS detections also decreased with increased vegetation cover. As a result of high shrubland heterogeneity, GUD from 30 m HLS pixels could be partially detected within a 500 m pixel despite GUD being undetectable from VIIRS time series. Moreover, vegetation cover heterogeneity also made it difficult for GUD at 30 m to be aggregated to coarse scales (such as to 500 m VIIRS pixels). These findings have significant implications to the detection and characterization of shrubland LSP responses to environmental and climate changes.

Nevada, Utah↗
USGS2018

Weather-centric rangeland revegetation planning

Invasive annual weeds negatively impact ecosystem services and pose a major conservation threat on semiarid rangelands throughout the western United States. Rehabilitation of these rangelands is challenging due to interannual climate and subseasonal weather variability that impacts seed germination, seedling survival and establishment, annual weed dynamics, wildfire frequency, and soil stability. Rehabilitation and restoration outcomes could be improved by adopting a weather-centric approach that uses the full spectrum of available site-specific weather information from historical observations, seasonal climate forecasts, and climate-change projections. Climate data can be used retrospectively to interpret success or failure of past seedings by describing seasonal and longer-term patterns of environmental variability subsequent to planting. A more detailed evaluation of weather impacts on site conditions may yield more flexible adaptive-management strategies for rangeland restoration and rehabilitation, as well as provide estimates of transition probabilities between desirable and undesirable vegetation states. Skillful seasonal climate forecasts could greatly improve the cost efficiency of management treatments by limiting revegetation activities to time periods where forecasts suggest higher probabilities of successful seedling establishment. Climate-change projections are key to the application of current environmental models for development of mitigation and adaptation strategies and for management practices that require a multidecadal planning horizon. Adoption of new weather technology will require collaboration between land managers and revegetation specialists and modifications to the way we currently plan and conduct rangeland rehabilitation and restoration in the Intermountain West.

Rangeland Ecology and Management↗
USGS2019

The state of the world’s mangrove forests: Past, present, and future

Intertidal mangrove forests are a dynamic ecosystem experiencing rapid changes in extent and habitat quality over geological history, today and into the future. Climate and sea level have drastically altered mangrove distribution since their appearance in the geological record ∼75 million years ago (Mya), through to the Holocene. In contrast, contemporary mangrove dynamics are driven primarily by anthropogenic threats, including pollution, overextraction, and conversion to aquaculture and agriculture. Deforestation rates have declined in the past decade, but the future of mangroves is uncertain; new deforestation frontiers are opening, particularly in Southeast Asia and West Africa, despite international conservation policies and ambitious global targets for rehabilitation. In addition, geological and climatic processes such as sea-level rise that were important over geological history will continue to influence global mangrove distribution in the future. Recommendations are given to reframe mangrove conservation, with a view to improving the state of mangroves in the future.

Annual Review of Environment and Resources↗
USGS2006

Dealing with uncertainty and sensitivity issues in process-based models of carbon and nitrogen cycles in northern forest ecosystems

Many process-based models on carbon (C) and nitrogen (N) cycles have been developed for northern forest ecosystems. These models are widely used to evaluate the long-term decisions in forest management dealing with effects like particulate pollution, productivity and climate change. Regarding climate change, one of the key questions that have sensitive political implications is whether northern forests will sequester atmospheric C or not. Whilst many process-based models have been tested for accuracy by evaluating or validating against observed data, few have dealt with the complexity of the incorporated procedures to estimate uncertainties associated with model predictions or the sensitivity of these predictions to input factors in a systematic, inter-model comparison fashion. In general, models differ in their underlying attempts to match natural complexities with assumed or imposed model structure and process formulations to estimate model parameters, to gather data and to address issues on scope, scale and natural variations. Uncertainties may originate from model structure, estimation of model parameters, data input, representation of natural variation and scaling exercises. Model structure relates to the mathematical representation of the processes modelled and the type of state variables that a model contains. The modelling of partitioning among above- and below-ground C and N pools and the interdependence among these pools remain a major source of uncertainty in model structure and error propagation. Most soil C models use at least three state variables to represent the different types of soil organic matter (SOM). This approach results in creating three artificial SOM pools, assuming that each one contains C compounds with same turnover rate. In reality, SOM consists of many different types of C compounds with widely different turnover rates. Uncertainty in data and parameter estimates are closely linked. Data uncertainties are associated with high variations in estimating forest biomass, productivity and soil organic matter and may be incomplete for model initialization, calibration, validation and sensitivity analysis of generalized predictor models. The scale at which a model is being used also affects the level of uncertainty, as the errors in the prediction of the C and N dynamics differ from the site to the landscape levels and across climatic regions. If the spatial or temporal scale of a model application is changed, additional uncertainty arises from neglecting natural variability in system variables in time and space. Uncertainty issues are also intimately related to model validation and sensitivity analysis. The estimation of uncertainties is needed to inform decision process, in order to detect the possible corridor of development. Uncertainty in this context is an essential measure of quality for stakeholder and decision makers.

Conference Paper↗
USGS2015

Projection of corn production and stover-harvesting impacts on soil organic carbon dynamics in the U.S. Temperate Prairies

Terrestrial carbon sequestration potential is widely considered as a realistic option for mitigating greenhouse gas emissions. However, this potential may be threatened by global changes including climate, land use, and management changes such as increased corn stover harvesting for rising production of cellulosic biofuel. Therefore, it is critical to investigate the dynamics of soil organic carbon (SOC) at regional or global scale. This study simulated the corn production and spatiotemporal changes of SOC in the U.S. Temperate Prairies, which covers over one-third of the U.S. corn acreage, using a biogeochemical model with multiple climate and land-use change projections. The corn production (either grain yield or stover biomass) could reach 88.7–104.7 TgC as of 2050, 70–101% increase when compared to the base year of 2010. A removal of 50% stover at the regional scale could be a reasonable cap in view of maintaining SOC content and soil fertility especially in the beginning years. The projected SOC dynamics indicated that the average carbon sequestration potential across the entire region may vary from 12.7 to 19.6 g C/m 2 /yr (i.e., 6.6–10.2 g TgC/yr). This study not only helps understand SOC dynamics but also provides decision support for sustainable biofuel development.

Iowa, Kansas, Minnesota, Missouri, Nebraska, North↗
USGS2019

Assessing rangeland health under climate variability and change

RANGELAND HEALTH IN A CHANGING WORLD Rangeland health is an integrated metric that describes a complex suite of ecosystem properties and processes as applied to resource management. While the concept of “healthy” landscapes has a long history, the term “rangeland health” was codified in the US in 1994 as part of an effort to move towards a national, data driven, rangeland condition assessment (National Research Council 1994). Rangeland health encompasses the status of both soils and ecological processes as well as the condition of those ecosystems relative to ecological thresholds (e.g. “healthy”, “at-risk”, or “unhealthy"; National Research Council 1994). This latter application ensures that rangeland health assessments not only evaluate the conditions of plants and soils, but also gauge those conditions with respect to known or hypothesized ecological dynamics (Bestelmeyer et al. 2013) for a given set of abiotic constraints (climate, soil, and topographic setting). Thus, an assessment of rangeland health should identify the “degree to which the integrity of the soil and the ecological processes are sustained” (National Research Council 1994, Us Department of Agriculture 1997). Rangeland health attributes and assessment procedures have become widely utilized tools for measuring and monitoring dryland ecosystems, and they may provide valuable perspectives on rangeland response to climate change, although long-term directional change in environmental conditions represents a challenge for traditional rangeland health assessment frameworks.

Book chapter↗
USGS2013

Projected future changes in vegetation in western North America in the 21st century

Rapid and broad-scale forest mortality associated with recent droughts, rising temperature, and insect outbreaks has been observed over western North America (NA). Climate models project additional future warming and increasing drought and water stress for this region. To assess future potential changes in vegetation distributions in western NA, the Community Earth System Model (CESM) coupled with its Dynamic Global Vegetation Model (DGVM) was used under the future A2 emissions scenario. To better span uncertainties in future climate, eight sea surface temperature (SST) projections provided by phase 3 of the Coupled Model Intercomparison Project (CMIP3) were employed as boundary conditions. There is a broad consensus among the simulations, despite differences in the simulated climate trajectories across the ensemble, that about half of the needleleaf evergreen tree coverage (from 24% to 11%) will disappear, coincident with a 14% (from 11% to 25%) increase in shrubs and grasses by the end of the twenty-first century in western NA, with most of the change occurring over the latter half of the twenty-first century. The net impact is a ~6 GtC or about 50% decrease in projected ecosystem carbon storage in this region. The findings suggest a potential for a widespread shift from tree-dominated landscapes to shrub and grass-dominated landscapes in western NA because of future warming and consequent increases in water deficits. These results highlight the need for improved process-based understanding of vegetation dynamics, particularly including mortality and the subsequent incorporation of these mechanisms into earth system models to better quantify the vulnerability of western NA forests under climate change.

Journal of Climate↗
USGS2026

Weathering the ride: Associations of heat, smoke, precipitation, and ozone with bus ridership in Colorado

Weather and climate variability increasingly shape urban travel behavior, yet the short-term temporal dynamics and contextual modifiers of weather-transit relationships remain poorly understood. We analyzed system-wide hourly bus ridership in the Denver metropolitan area from June 2022 through September 2023 using fixed-effects negative binomial distributed lag nonlinear models with lags up to 24 h. Nonlinear exposure-response and lag-response functions were specified for hourly Universal Thermal Climate Index (UTCI) and precipitation, with additional indicators for daily ozone exceedance and wildfire smoke. Models adjust for hour-of-day, day-of-week, and month-year fixed effects, with standard errors clustered by day. Stratified analyses assess heterogeneity by time period, season, fare policy, and shelter availability, with interaction evaluated using Wald tests. Cold thermal stress was associated with the largest, most persistent reductions in ridership, with cumulative declines of −15.7% (95% CI: −26.0%, −4.0%) over 0-24 h. Precipitation was associated with sharp but transient reductions concentrated within 3-6 h (−8.4% to −9.8%), with little evidence of longer-term displacement. Heat associations were weaker and context-dependent, with modest short-run increases, but net same-day declines. Associations varied by time of day and season, were attenuated during the free-fare period, and differed by shelter availability. In contrast, ozone exceedance and wildfire smoke exhibited limited and inconsistent associations, with measurable reductions primarily during morning commute during heavier smoke conditions. Overall, transit ridership is more strongly associated with short-term weather exposure, than with ambient air quality. Fare policy and stop-level infrastructure modify these associations, highlighting actionable strategies to enhance transit resilience under increasing climate variability.

Colorado↗
USGS2013

Validating predictions from climate envelope models

Climate envelope models are a potentially important conservation tool, but their ability to accurately forecast species’ distributional shifts using independent survey data has not been fully evaluated. We created climate envelope models for 12 species of North American breeding birds previously shown to have experienced poleward range shifts. For each species, we evaluated three different approaches to climate envelope modeling that differed in the way they treated climate-induced range expansion and contraction, using random forests and maximum entropy modeling algorithms. All models were calibrated using occurrence data from 1967–1971 (t1) and evaluated using occurrence data from 1998–2002 (t2). Model sensitivity (the ability to correctly classify species presences) was greater using the maximum entropy algorithm than the random forest algorithm. Although sensitivity did not differ significantly among approaches, for many species, sensitivity was maximized using a hybrid approach that assumed range expansion, but not contraction, in t2. Species for which the hybrid approach resulted in the greatest improvement in sensitivity have been reported from more land cover types than species for which there was little difference in sensitivity between hybrid and dynamic approaches, suggesting that habitat generalists may be buffered somewhat against climate-induced range contractions. Specificity (the ability to correctly classify species absences) was maximized using the random forest algorithm and was lowest using the hybrid approach. Overall, our results suggest cautious optimism for the use of climate envelope models to forecast range shifts, but also underscore the importance of considering non-climate drivers of species range limits. The use of alternative climate envelope models that make different assumptions about range expansion and contraction is a new and potentially useful way to help inform our understanding of climate change effects on species.

PLoS ONE↗
USGS2008

The Importance of Uncertainty and Sensitivity Analysis in Process-based Models of Carbon and Nitrogen Cycling in Terrestrial Ecosystems with Particular Emphasis on Forest Ecosystems — Selected Papers from a Workshop Organized by the International Society for Ecological Modelling (ISEM) at the Third Biennal Meeting of the International Environmental Modelling and Software Society (IEMSS) in Burlington, Vermont, USA, August 9-13, 2006

Many process-based models of carbon (C) and nitrogen (N) cycles have been developed for terrestrial ecosystems, including forest ecosystems. They address many basic issues of ecosystems structure and functioning, such as the role of internal feedback in ecosystem dynamics. The critical factor in these phenomena is scale, as these processes operate at scales from the minute (e.g. particulate pollution impacts on trees and other organisms) to the global (e.g. climate change). Research efforts remain important to improve the capability of such models to better represent the dynamics of terrestrial ecosystems, including the C, nutrient, (e.g. N) and water cycles. Existing models are sufficiently well advanced to help decision makers develop sustainable management policies and planning of terrestrial ecosystems, as they make realistic predictions when used appropriately. However, decision makers must be aware of their limitations by having the opportunity to evaluate the uncertainty associated with process-based models ( Smith and Heath, 2001 and Allen et al., 2004 ). The variation in scale of issues currently being addressed by modelling efforts makes the evaluation of uncertainty a daunting task.

Ecological Modelling↗
USGS2006

Terrestrial ice streams-a view from the lobe

The glacial landforms of Minnesota are interpreted as the products of the lobate extensions of ice streams that issued from various ice sheds within the Laurentide Ice Sheet. Low-relief till plains, trough-shaped lowlands, boulder pavements, and streamlined forms make up the subglacial landsystem in Minnesota that is interpreted as having been formed by streaming ice. Extremely uniform tills are created subglacially in a way that remains somewhat mysterious. At the ice margins, thrust moraines and hummocky stagnation topography are more common than single-crested, simple moraines if the ice lobes had repeated advances. Subglacial drainage features are obscure up-ice but are present down-ice in the form of tunnel valleys, eskers, Spooner hills, and associated ice-marginal fans. Ice streaming may occur when basal shear stress is lowered as a result of high subglacial water pressure. Subglacial conditions that allow the retention of water will allow an ice lobe to extend far beyond the ice sheet as long as the ice shed also supports the advance by supplying adequate ice. Even with adequate ice flux, however, the advance of an ice lobe may be terminated, at least temporarily, if the subglacial water is drained, through tunnel valleys or perhaps a permeable substrate. Thrust moraines, and ice stagnation topography will result from sudden drainage. Although climate change is ultimately responsible for the accumulation of ice in the Laurentide Ice Sheet, the asynchronous advances and retreats of the ice lobes in the mid-continent are strongly overprinted by the internal dynamics of individual ice streams as well as the interaction of ice sheds, which obscure the climate signal. ?? 2005 Elsevier B.V. All rights reserved.

Geomorphology↗