Geology topics

Jennifer K. Roach

Publications and source records attributed to Jennifer K. Roach.

6 recordsLinked to original sources

USGS2018

Assessment of Alaska rain-on-snow events using dynamical downscaling

The ice formed by cold-season rainfall or rain on snow (ROS) has striking impacts on the economy and ecology of Alaska. An understanding of the atmospheric drivers of ROS events is required to better predict them and plan for environmental change. The spatially/temporally sparse network of stations in Alaska makes studying such events challenging, and gridded reanalysis or remote sensing products are necessary to fill the gaps. Recently developed dynamically downscaled climate data provide a new suite of high-resolution variables for investigating historical and projected ROS events across all of Alaska from 1979 to 2100. The dynamically downscaled reanalysis data of ERA-Interim replicated the seasonal patterns of ROS events but tended to produce more rain events than in station observations. However, dynamical downscaling reduced the bias toward more rain events in the coarse reanalysis. ROS occurred most frequently over southwestern and southern coastal regions. Extreme events with the heaviest rainfall generally coincided with anomalous high pressure centered to the south/southeast of the locations receiving the event and warm-air advection from the resulting southwesterly wind flow. ROS events were projected to increase in frequency overall and for extremes across most of the region but were expected to decline over southwestern/southern Alaska. Increases in frequency were projected as a result of more frequent winter rainfall, but the number of ROS events may ultimately decline in some areas as a result of temperatures rising above the freezing threshold. These projected changes in ROS can significantly affect wildlife, vegetation, and human activities across the Alaska landscape.

Alaska↗

USGS2015

Climate-induced lake drying causes heterogeneous reductions in waterfowl species richness

Context Lake size has declined on breeding grounds for international populations of waterfowl. Objectives Our objectives were to (1) model the relationship between waterfowl species richness and lake size; (2) use the model and trends in lake size to project historical, contemporary, and future richness at 2500+ lakes; (3) evaluate mechanisms for the species–area relationship (SAR); and (4) identify species most vulnerable to shrinking lakes. Methods Monte Carlo simulations of the richness model were used to generate projections. Correlations between richness and both lake size and habitat diversity were compared to identify mechanisms for the SAR. Patterns of nestedness were used to identify vulnerable species. Results Species richness was greatest at lakes that were larger, closer to rivers, had more wetlands along their perimeters and were within 5 km of a large lake. Average richness per lake was projected to decline by 11 % from 1986 to 2050 but was heterogeneous across sub-regions and lakes. Richness in sub-regions with species-rich lakes was projected to remain stable, while richness in the sub-region with species-poor lakes was projected to decline. Lake size had a greater effect on richness than did habitat diversity, suggesting that large lakes have more species because they provide more habitat but not more habitat types. The vulnerability of species to shrinking lakes was related to species rarity rather than foraging guild. Conclusions Our maps of projected changes in species richness and rank-ordered list of species most vulnerable to shrinking lakes can be used to identify targets for conservation or monitoring.

Landscape Ecology↗

USGS2013

Landscape influences on climate-related lake shrinkage at high latitudes

Climate-related declines in lake area have been identified across circumpolar regions and have been characterized by substantial spatial heterogeneity. An improved understanding of the mechanisms underlying lake area trends is necessary to predict where change is most likely to occur and to identify implications for high latitude reservoirs of carbon. Here, using a population of ca. 2300 lakes with statistically significant increasing and decreasing lake area trends spanning longitudinal and latitudinal gradients of ca. 1000 km in Alaska, we present evidence for a mechanism of lake area decline that involves the loss of surface water to groundwater systems. We show that lakes with significant declines in lake area were more likely to be located: (1) in burned areas; (2) on coarser, well-drained soils; and (3) farther from rivers compared to lakes that were increasing. These results indicate that postfire processes such as permafrost degradation, which also results from a warming climate, may promote lake drainage, particularly in coarse-textured soils and farther from rivers where overland flooding is less likely and downslope flow paths and negative hydraulic gradients between surface water and groundwater systems are more common. Movement of surface water to groundwater systems may lead to a deepening of subsurface flow paths and longer hydraulic residence time which has been linked to increased soil respiration and CO 2 release to the atmosphere. By quantifying relationships between statewide coarse resolution maps of landscape characteristics and spatially heterogeneous responses of lakes to environmental change, we provide a means to identify at-risk lakes and landscapes and plan for a changing climate.

Alaska↗

USGS2013

Spatial heterogeneity in statistical power to detect changes in lake area in Alaskan National Wildlife Refuges

Over the past 50 years, the number and size of high-latitude lakes have decreased throughout many regions; however, individual lake trends have been variable in direction and magnitude. This spatial heterogeneity in lake change makes statistical detection of temporal trends challenging, particularly in small analysis areas where weak trends are difficult to separate from inter- and intra-annual variability. Factors affecting trend detection include inherent variability, trend magnitude, and sample size. In this paper, we investigated how the statistical power to detect average linear trends in lake size of 0.5, 1.0 and 2.0 %/year was affected by the size of the analysis area and the number of years of monitoring in National Wildlife Refuges in Alaska. We estimated power for large (930–4,560 sq km) study areas within refuges and for 2.6, 12.9, and 25.9 sq km cells nested within study areas over temporal extents of 4–50 years. We found that: (1) trends in study areas could be detected within 5–15 years, (2) trends smaller than 2.0 %/year would take >50 years to detect in cells within study areas, and (3) there was substantial spatial variation in the time required to detect change among cells. Power was particularly low in the smallest cells which typically had the fewest lakes. Because small but ecologically meaningful trends may take decades to detect, early establishment of long-term monitoring will enhance power to detect change. Our results have broad applicability and our method is useful for any study involving change detection among variable spatial and temporal extents.

Alaska↗

USGS2012

Comparison of three methods for long-term monitoring of boreal lake area using Landsat TM and ETM+ imagery

Programs to monitor lake area change are becoming increasingly important in high latitude regions, and their development often requires evaluating tradeoffs among different approaches in terms of accuracy of measurement, consistency across multiple users over long time periods, and efficiency. We compared three supervised methods for lake classification from Landsat imagery (density slicing, classification trees, and feature extraction). The accuracy of lake area and number estimates was evaluated relative to high-resolution aerial photography acquired within two days of satellite overpasses. The shortwave infrared band 5 was better at separating surface water from nonwater when used alone than when combined with other spectral bands. The simplest of the three methods, density slicing, performed best overall. The classification tree method resulted in the most omission errors (approx. 2x), feature extraction resulted in the most commission errors (approx. 4x), and density slicing had the least directional bias (approx. half of the lakes with overestimated area and half of the lakes with underestimated area). Feature extraction was the least consistent across training sets (i.e., large standard error among different training sets). Density slicing was the best of the three at classifying small lakes as evidenced by its lower optimal minimum lake size criterion of 5850 m 2 compared with the other methods (8550 m 2 ). Contrary to conventional wisdom, the use of additional spectral bands and a more sophisticated method not only required additional processing effort but also had a cost in terms of the accuracy and consistency of lake classifications.

Canadian Journal of Remote Sensing↗

USGS2011

Mechanisms influencing changes in lake area in Alaskan boreal forest

During the past &sim;50 years, the number and area of lakes have declined in several regions in boreal forests. However, there has been substantial finer-scale heterogeneity; some lakes decreased in area, some showed no trend, and others increased. The objective of this study was to identify the primary mechanisms underlying heterogeneous trends in closed-basin lake area. Eight lake characteristics ( δ 18 O, electrical conductivity, surface : volume index, bank slope, floating mat width, peat depth, thaw depth at shoreline, and thaw depth at the forest boundary) were compared for 15 lake pairs in Alaskan boreal forest where one lake had decreased in area since &sim;1950, and the other had not. Mean differences in characteristics between paired lakes were used to identify the most likely of nine mechanistic scenarios that combined three potential mechanisms for decreasing lake area (talik drainage, surface water evaporation, and terrestrialization) with three potential mechanisms for nondecreasing lake area (subpermafrost groundwater recharge through an open talik, stable permafrost, and thermokarst). A priori expectations of the direction of mean differences between decreasing and nondecreasing paired lakes were generated for each scenario. Decreasing lakes had significantly greater electrical conductivity, greater surface : volume indices, shallower bank slopes, wider floating mats, greater peat depths, and shallower thaw depths at the forest boundary. These results indicated that the most likely scenario was terrestrialization as the mechanism for lake area reduction combined with thermokarst as the mechanism for nondecreasing lake area. Terrestrialization and thermokarst may have been enhanced by recent warming which has both accelerated permafrost thawing and lengthened the growing season, thereby increasing plant growth, floating mat encroachment, transpiration rates, and the accumulation of organic matter in lake basins. The transition to peatlands associated with terrestrialization may provide a transient increase in carbon storage enhancing the role of northern ecosystems as major stores of global carbon.

Alaska↗