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At least 1,387 records · Page 77Linked to original sources

Evaluating density-weighted connectivity of black bears (Ursus americanus) in Glacier National Park with spatial capture–recapture models

Background Improved understanding of wildlife population connectivity among protected area networks can support effective planning for the persistence of wildlife populations in the face of land use and climate change. Common approaches to estimating connectivity often rely on small samples of individuals without considering the spatial structure of populations, leading to limited understanding of how individual movement links to demography and population connectivity. Recently developed spatial capture-recapture (SCR) models provide a framework to formally connect inference about individual movement, connectivity, and population density, but few studies have applied this approach to empirical data to support connectivity planning. Methods We used mark-recapture data collected from 924 genetic detections of 598 American black bears ( Ursus americanus ) in 2004 with SCR ecological distance models to simultaneously estimate density, landscape resistance to movement, and population connectivity in Glacier National Park northwest Montana, USA. We estimated density and movement parameters separately for males and females and used model estimates to calculate predicted density-weighted connectivity surfaces. Results Model results indicated that landscape structure influences black bear density and space use in Glacier. The mean density estimate was 16.08 bears/100 km 2 (95% CI 12.52–20.6) for females and 9.27 bears/100 km 2 (95% CI 7.70–11.14) for males. Density increased with forest cover for both sexes. For male black bears, density decreased at higher grizzly bear ( Ursus arctos ) densities. Drainages, valley bottoms, and riparian vegetation decreased estimates of landscape resistance to movement for male and female bears. For males, forest cover also decreased estimated resistance to movement, but a transportation corridor bisecting the study area strongly increased resistance to movement presenting a barrier to connectivity. Conclusions Density-weighed connectivity surfaces highlighted areas important for population connectivity that were distinct from areas with high potential connectivity. For black bears in Glacier and surrounding landscapes, consideration of both vegetation and valley topography could inform the placement of underpasses along the transportation corridor in areas characterized by both high population density and potential connectivity. Our study demonstrates that the SCR ecological distance model can provide biologically realistic, spatially explicit predictions to support movement connectivity planning across large landscapes.

Montana↗

Scale-dependent mechanisms of habitat selection for a migratory passerine: an experimental approach

Habitat selection theory predicts that individuals choose breeding habitats that maximize fitness returns on the basis of indirect environmental cues at multiple spatial scales. We performed a 3-year field experiment to evaluate five alternative hypotheses regarding whether individuals choose breeding territories in heterogeneous landscapes on the basis of (1) shrub cover within a site, (2) forest land-cover pattern surrounding a site, (3) conspecific song cues during prebreeding settlement periods, (4) a combination of these factors, and (5) interactions among these factors. We tested hypotheses with playbacks of conspecific song across a gradient of landscape pattern and shrub density and evaluated changes in territory occupancy patterns in a forest-nesting passerine, the Black-throated Blue Warbler ( Dendroica caerulescens ). Our results support the hypothesis that vegetation structure plays a primary role during presettlement periods in determining occupancy patterns in this species. Further, both occupancy rates and territory turnover were affected by an interaction between local shrub density and amount of forest in the surrounding landscape, but not by interactions between habitat cues and social cues. Although previous studies of this species in unfragmented landscapes found that social postbreeding song cues played a key role in determining territory settlement, our prebreeding playbacks were not associated with territory occupancy or turnover. Our results suggest that in heterogeneous landscapes during spring settlement, vegetation structure may be a more reliable signal of reproductive performance than the physical location of other individuals.

Vermont↗

Wetland selection by breeding and foraging black terns in the Prairie Pothole Region of the United States

We examined wetland selection by the Black Tern (Chlidonias niger), a species that breeds primarily in the prairie pothole region, has experienced population declines, and is difficult to manage because of low site fidelity. To characterize its selection of wetlands in this region, we surveyed 589 wetlands throughout North and South Dakota. We documented breeding at 5% and foraging at 17% of wetlands. We created predictive habitat models with a machine-learning algorithm, Random Forests, to explore the relative role of local wetland characteristics and those of the surrounding landscape and to evaluate which characteristics were important to predicting breeding versus foraging. We also examined area-dependent wetland selection while addressing the passive sampling bias by replacing occurrence of terns in the models with an index of density. Local wetland variables were more important than landscape variables in predictions of occurrence of breeding and foraging. Wetland size was more important to prediction of foraging than of breeding locations, while floating matted vegetation was more important to prediction of breeding than of foraging locations. The amount of seasonal wetland in the landscape was the only landscape variable important to prediction of both foraging and breeding. Models based on a density index indicated that wetland selection by foraging terns may be more area dependent than that by breeding terns. Our study provides some of the first evidence for differential breeding and foraging wetland selection by Black Terns and for a more limited role of landscape effects and area sensitivity than has been previously shown.

Prairie Pothole Region↗

Seed dispersal in fens

Question: How does seed dispersal reduce fen isolation and contribute to biodiversity? Location: European and North American fens. Methods: This paper reviews the literature on seed dispersal to fens. Results: Landscape fragmentation may reduce dispersal opportunities thereby isolating fens and reducing genetic exchange. Species in fragmented wetlands may have lower reproductive success, which can lead to biodiversity loss. While fens may have always been relatively isolated from each other, they have become increasingly fragmented in modern times within agricultural and urban landscapes in both Europe and North America. Dispersal by water, animals and wind has been hampered by changes related to development in landscapes surrounding fens. Because the seeds of certain species are long-lived in the seed bank, frequent episodes of dispersal are not always necessary to maintain the biodiversity of fens. However, of particular concern to restoration is that some dominant species, such as the tussock sedge Carex stricta, may not disperse readily between fens. Conclusions: Knowledge of seed dispersal can be used to maintain and restore the biodiversity of fens in fragmented landscapes. Given that development has fragmented landscapes and that this situation is not likely to change, the dispersal of seeds might be enhanced by moving hay or cattle from fens to damaged sites, or by reestablishing lost hydrological connections. ?? IAVS; Opulus Press.

Conference Paper↗

Scale-dependent factors affecting North American river otter distribution in the midwest

The North American river otter ( Lontra canadensis ) is recovering from near extirpation throughout much of its range. Although reintroductions, trapping regulations and habitat improvements have led to the reestablishment of river otters in the Midwest, little is known about how their distribution is influenced by local- and landscape-scale habitat. We conducted river otter sign surveys from Jan. to Apr. in 2008 and 2009 in eastern Kansas to assess how local- and landscape-scale habitat factors affect river otter occupancy. We surveyed three to nine 400-m stretches of stream and reservoir shorelines for 110 sites and measured local-scale variables ( e.g., stream order, land cover types) within a 100 m buffer of the survey site and landscape-scale variables ( e.g., road density, land cover types) for Hydrological Unit Code 14 watersheds. We then used occupancy models that account for the probability of detection to estimate occupancy as a function of these covariates using Program PRESENCE. The best-fitting model indicated river otter occupancy increased with the proportion of woodland cover and decreased with the proportion of cropland and grassland cover at the local scale. Occupancy also increased with decreased shoreline diversity, waterbody density and stream density at the landscape scale. Occupancy was not affected by land cover or human disturbance at the landscape scale. Understanding the factors and scale important to river otter occurrence will be useful in identifying areas for management and continued restoration.

Kansas↗

A structural equation model analysis of postfire plant diversity in California shrublands

This study investigates patterns of plant diversity following wildfires in fire‐prone shrublands of California, seeks to understand those patterns in terms of both local and landscape factors, and considers the implications for fire management. Ninety study sites were established following extensive wildfires in 1993, and 1000‐m 2 plots were used to sample a variety of parameters. Data on community responses were collected for five years following fire. Structural equation modeling (SEM) was used to relate plant species richness to plant abundance, fire severity, abiotic conditions, within‐plot heterogeneity, stand age, and position in the landscape. Temporal dynamics of average richness response was also modeled. Richness was highest in the first year following fire, indicating postfire enhancement of diversity. A general decline in richness over time was detected, with year‐to‐year variation attributable to annual variations in precipitation. Peak richness in the landscape was found where (1) plant abundance was moderately high, (2) within‐plot heterogeneity was high, (3) soils were moderately low in nitrogen, high in sand content, and with high rock cover, (4) fire severity was low, and (5) stands were young prior to fire. Many of these characteristics were correlated with position in the landscape and associated conditions. We infer from the SEM results that postfire richness in this system is strongly influenced by local conditions and that these conditions are, in turn, predictably related to landscape‐level conditions. For example, we observed that older stands of shrubs were characterized by more severe fires, which were associated with a low recovery of plant cover and low richness. These results may have implications for the use of prescribed fire in this system if these findings extrapolate to prescribed burns as we would expect.

California↗

Introduction to the special issue on “Understanding and predicting change in the coastal ecosystems of the northern Gulf of Mexico”

The coastal region of the northern Gulf of Mexico owes its current landscape structure to an array of tectonic, erosional and depositional, climatic, geochemical, hydrological, ecological, and human processes that have resulted in some of the world's most complex, dynamic, productive, and threatened ecosystems. Catastrophic hurricane landfalls, ongoing subsidence and erosion exacerbated by sea-level rise, disintegration of barrier island chains, and high rates of wetland loss have called attention to the vulnerability of northern Gulf coast ecosystems, habitats, built infrastructure, and economy to natural and anthropogenic threats. The devastating hurricanes of 2005 (Katrina and Rita) motivated the U.S. Geological Survey Coastal and Marine Geology Program and partnering researchers to pursue studies aimed at understanding and predicting landscape change and the associated storm hazard vulnerability of northern Gulf coast region ecosystems and human communities. Attaining this science goal requires increased knowledge of landscape evolution on geologic, historical, and human time scales, and analysis of the implications of such changes in the natural and built components of the landscape for hurricane impact susceptibility. This Special Issue of the Journal of Coastal Research communicates northern Gulf of Mexico research results that (1) improve knowledge of prior climates and depositional environments, (2) assess broad regional ecosystem structure and change over Holocene to human time scales, (3) undertake process studies and change analyses of dynamic landscape components, and (4) integrate framework, climate, variable time and spatial scale mapping, monitoring, and discipline-specific process investigations within interdisciplinary studies.

Journal of Coastal Research↗

Development and application of a coastal change likelihood assessment for the northeast region, Maine to Virginia

Coastal resources are increasingly affected by erosion, extreme weather events, sea level rise, tidal flooding, and other potential hazards related to climate change. These hazards have varying effects on coastal landscapes because of the compounding of geologic, oceanographic, ecologic, and socioeconomic factors that exist at a given location. An assessment framework is introduced in this report that synthesizes existing datasets that cover the variability of the landscape, and hazards that may act on the landscape, to evaluate the likelihood of coastal change along the U.S. coastline on a decadal scale. The pilot study that aided in the development of the framework was run in the northeastern United States (from Maine to Virginia) and consists of datasets derived from a variety of Federal, State, and local sources. First, a decision-tree-based dataset was built that describes the resistance or integrity of the coastal landscape (called the fabric dataset for the purposes of this report) and includes land cover, elevation, slope, long-term (more than 50 years) shoreline change, dune height, and marsh stability data. A second database was generated from coastal hazards, which are divided into event hazards (for example, flooding, wave power, and probability of storm overwash) and persistent or perpetual hazards (for example, relative sea level rise rate, short-term [about 30-year] shoreline erosion rate, and storm recurrence interval). The fabric dataset was then merged with the coastal hazards databases, and a model training dataset made up of hundreds of polygons was generated from these combined data to support machine learning. The pilot study resulted in location-specific, 10-meter-resolution data classified into five raster datasets that include intrinsic characteristics of the coast used to determine the resistance of the landscape to change, the persistent and event hazards that act on the coast, the machine learning output (coastal change likelihood) based on the cumulative effects of the fabric and hazards datasets, and an estimate of the hazard type (event or persistent) that is the most likely to influence coastal change. Final outcomes are intended to be used as a first-order planning tool to determine which areas of the coast are more likely to change in response to future potential coastal hazards and to examine elements and drivers that make change in a location more likely.

Connecticut, Delaware, Maine, Maryland, Massachuse↗

Identifying bird and reptile vulnerabilities to climate change in the southwestern United States

Current and future breeding ranges of 15 bird and 16 reptile species were modeled in the Southwestern United States. Rather than taking a broad-scale, vulnerability-assessment approach, we created a species distribution model (SDM) for each focal species incorporating climatic, landscape, and plant variables. Baseline climate (1940–2009) was characterized with Parameter-elevation Regressions on Independent Slopes Model (PRISM) data and future climate with global-circulation-model data under an A1B emission scenario. Climatic variables included monthly and seasonal temperature and precipitation; landscape variables included terrain ruggedness, soil type, and insolation; and plant variables included trees and shrubs commonly associated with a focal species. Not all species-distribution models contained a plant, but if they did, we included a built-in annual migration rate for more accurate plant-range projections in 2039 or 2099. We conducted a group meta-analysis to (1) determine how influential each variable class was when averaged across all species distribution models (birds or reptiles), and (2) identify the correlation among contemporary (2009) habitat fragmentation and biological attributes and future range projections (2039 or 2099). Projected changes in bird and reptile ranges varied widely among species, with one-third of the ranges predicted to expand and two-thirds predicted to contract. A group meta-analysis indicated that climatic variables were the most influential variable class when averaged across all models for both groups, followed by landscape and plant variables (birds), or plant and landscape variables (reptiles), respectively. The second part of the meta-analysis indicated that numerous contemporary habitat-fragmentation (for example, patch isolation) and biological-attribute (for example, clutch size, longevity) variables were significantly correlated with the magnitude of projected range changes for birds and reptiles. Patch isolation was a significant trans-specific driver of projected bird and reptile ranges, suggesting that strategic actions should focus on restoration and enhancement of habitat at local and regional scales to promote landscape connectivity and conservation of core areas.

Open-File Report↗

Modeling resource selection of bobcats (Lynx rufus) and vertebrate species distributions in Orange County, southern California

For nature reserves in urban settings, wildlife and wildlife habitats may be affected by recreational activities and intensive, adjacent development. Sustaining biodiversity in such reserves is a challenge for land and natural resource managers, but identification of core areas and key resources for wildlife species may help in planning for current and emerging threats. To help identify core areas and resources, we conducted spatial analyses and predictive modeling of vertebrate distributions for a network of nature reserves in densely populated Orange County, California. We primarily focused on bobcats ( Lynx rufus ), a species with a strong association with natural habitat. Bobcat space use has been correlated with broad, simple land-use categories, but relatively little is known about the influence of greater landscape complexity on habitat suitability for bobcats. To examine habitat selection by bobcats, we developed spatial data layers representing environmental factors that might influence this species, and we used previously collected Global Positioning System tracking data for 30 male and 21 female bobcats to indicate bobcat response to complex landscape factors. We examined these inputs using Resource Selection Function (RSF) modeling and developed spatially explicit models of the probability of bobcat use (selection or avoidance) of landscape characteristics. RSF models highlighted the general importance of reserve habitat for bobcats, but suggested that female bobcats were more dependent that male bobcats on habitat within designated reserves. Male bobcats, which range more widely than female bobcats, were associated with undeveloped areas both within and outside reserves. Small areas were present outside reserves that seemed to provide additional suitable habitat or movement areas for bobcats, potentially through restoration, connectivity, or reduced edge effects. Although bobcat RSFs suggested areas of high value to this species and potentially other species, taxa can differ greatly in their resource-selection and spatial requirements. Thus, for several species of reptiles, amphibians, and birds, we adapted species distribution models based on occurrence data to examine the response of other vertebrates to the landscape. To identify potential High-Value Areas (HVAs) for single or multiple species, we then developed a step-wise filtering process that can be applied to a series of spatial data layers. We provide examples of alternative decision models for HVAs that capture different elements of biodiversity and a range of management considerations. As landscape and management challenges change, these spatial layers and decision rules can be adjusted based on new information. Our approach thus establishes a general framework for identifying high-value habitat that can be used for current management decisions and refined in the future, depending on management interests and goals and the availability of suitable quality data or adequate surrogate information.

California↗

Integration of geological remote-sensing techniques in subsurface analysis

Geological remote sensing is defined as the study of the Earth utilizing electromagnetic radiation which is either reflected or emitted from its surface in wavelengths ranging from 0.3 micrometre to 3 metres. The natural surface of the Earth is composed of a diversified combination of surface cover types, and geologists must understand the characteristics of surface cover types to successfully evaluate remotely-sensed data. In some areas landscape surface cover changes throughout the year, and analysis of imagery acquired at different times of year can yield additional geological information. Integration of different scales of analysis allows landscape features to be effectively interpreted. Interpretation of the static elements displayed on imagery is referred to as an image interpretation. Image interpretation is dependent upon: (1) the geologist's understanding of the fundamental aspects of image formation, and (2.) his ability to detect, delineate, and classify image radiometric data; recognize radiometric patterns; and identify landscape surface characteristics as expressed on imagery. A geologic interpretation integrates surface characteristics of the landscape with subsurface geologic relationships. Development of a geologic interpretation from imagery is dependent upon: (1) the geologist's ability to interpret geomorphic processes from their static surface expression as landscape characteristics on imagery, (2) his ability to conceptualize the dynamic processes responsible for the evolution 6f interpreted geologic relationships (his ability to develop geologic models). The integration of geologic remote-sensing techniques in subsurface analysis is illustrated by development of an exploration model for ground water in the Tucson area of Arizona, and by the development of an exploration model for mineralization in southwest Idaho.

Open-File Report↗

The Yellowstone hotspot, Greater Yellowstone ecosystem, and human geography

Active geologic processes associated with the Yellowstone hotspot are fundamental in shaping the landscapes of the greater Yellowstone ecosystem (GYE), a high volcanic plateau flanked by a crescent of still higher mountainous terrain. The processes associated with the Yellowstone hotspot are volcanism, faulting, and uplift and are observed in the geology at the surface. We attribute the driving forces responsible for the northeastward progression of these processes to a thermal plume rising through the Earth’s mantle into the base of the southwest-moving North American plate. This progression began 16 million years ago (Ma) near the Nevada-Oregon border and arrived at Yellowstone about 2 Ma. Before arrival of the hotspot, an older landscape existed, particularly mountains created during the Laramide orogeny about 70–50 Ma and volcanic terrain formed by Absaroka andesitic volcanism mostly between 50–45 Ma. These landscapes were more muted than the present, hotspot-modified landscape because the Laramide-age mountains had worn down and an erosion surface of low relief had developed on the Absaroka volcanic terrain. The Yellowstone Plateau was built by hotspot volcanism of rhyolitic lavas and caldera-forming rhyolite tuffs (ignimbrites). Streams eroding back into the edges of this plateau have created scenic waterfalls and canyons such as the Grand Canyon of the Yellowstone and Lewis Canyon. Rhyolite is poor in plant nutrients and forms sandy, well-drained soils that support the monotonous, fire-adapted lodgepole pine forests of the Yellowstone Plateau. Non-rhyolitic rocks surround this plateau and sustain more varied vegetation, including spruce, fir, and whitebark pine forests broken by grassy meadows. Heat from the hotspot rises upward and drives Yellowstone’s famed geysers, hot springs, and mudpots. These thermal waters are home to specialized, primitive ecosystems, rich in algae and bacteria. The rock alteration associated with hydrothermal systems creates the bright colors of Yellowstone’s Grand Canyon. Basin-and-range-style faulting has accompanied migration of the hotspot to Yellowstone and formed the linear mountains and valleys that occur north and south of the hotspot track, which is the present-day eastern Snake River Plain. High rates of basin-and-range faulting occurred adjacent to the migrating Yellowstone hotspot, creating distinctive landscapes within the GYE such as the Teton Range/Jackson Hole, with characteristic rugged, forested ranges and adjacent flat-floored grassy valleys. The difference in altitude between the mountains and valleys provides a topographic gradient in which vegetation maturation advances with altitude; animal-migration patterns also follow this trend. The valleys provide natural meadows, agricultural land, town sites, and corridors for roads. Uplift of the GYE by as much as 1 km (3,000 ft) during the last 5 million years has resulted in ongoing erosion of deep, steep-walled valleys. Many prominent ecological characteristics of Yellowstone derive from this hotspot-induced uplift, including the moderate- to high- altitude terrain and associated cool temperatures and deep snowfall. Modern and Pleistocene climate and associated vegetation patterns strongly relate to the topography created by the hotspot and its track along the eastern Snake River Plain. Winter air masses from the moist northern Pacific Ocean traverse the topographic low of the Snake River Plain to where orographic rise onto the Yellowstone Plateau and adjacent mountains produces deep snow. A winter precipitation shadow forms on the lee (eastern) sides of the GYE. During Pleistocene glacial times, this moisture conduit provided by the hotspot-track-produced ice-age glaciers that covered the core of the present GYE. These glaciers sculpted bedrock and produced glacial moraines that are both forested and unforested, sand and gravel of ice-marginal streams and outwash gravels that are commonly covered with sagebrush-grassland, and silty lake sediments that are commonly covered by lush grassland such as Hayden Valley. The effects of the Yellowstone hotspot also profoundly shaped the human history in the GYE. Uplift associated with the hotspot elevates the GYE to form the Continental Divide, and streams drain radially outward like spokes from a hub. Inhabitants of the GYE 12,000–10,000 years ago, as well as more recent inhabitants, followed the seasonal green-up of plants and migrating animals up into the mountain areas. During European immigration, people settled around Yellowstone in the lower parts of the drainages and established roads, irrigation systems, and cultural associations. The core Yellowstone highland is too harsh for agriculture and inhospitable to people in the winter. Beyond this core, urban and rural communities exist in valleys and are separated by upland areas. The partitioning inhibits any physical connection of communities, which in turn complicates pursuit of common interests across the whole GYE. Settlements thus geographically isolated evolved as diverse, independent communities

Idaho, Montana, Utah, Wyoming↗

Conditions and processes affecting sand resources at archeological sites in the Colorado River corridor below Glen Canyon Dam, Arizona

This study examined links among fluvial, aeolian, and hillslope geomorphic processes that affect archeological sites and surrounding landscapes in the Colorado River corridor downstream from Glen Canyon Dam, Arizona. We assessed the potential for Colorado River sediment to enhance the preservation of river-corridor archeological resources through aeolian sand deposition or mitigation of gully erosion. By identifying locally prevailing wind directions, locations of modern sandbars, and likely aeolian-transport barriers, we determined that relatively few archeological sites are now ideally situated to receive aeolian sand supply from sandbars deposited by recent controlled floods. Whereas three-fourths of the 358 river-corridor archeological sites we examined include Colorado River sediment as an integral component of their geomorphic context, only 32 sites currently appear to have a high degree of connectivity (coupled interactions) between modern fluvial sandbars and sand-dominated landscapes downwind. This represents a substantial decrease from past decades, as determined by aerial-photograph analysis. Thus, we infer that recent controlled floods have had a limited, and declining, influence on archeological-site preservation. Within the study area, overland-flow (gully) erosion is less severe in sand landscapes with active aeolian sand than in landscapes that lack aeolian transport; gullies terminate more commonly in active sand (sand that is mobile by wind rather than stabilized by biologic soil crust). We infer that these characteristics largely result from aeolian sand transport being an effective gully-limiting and gully-annealing mechanism. Aeolian sand activity in the river corridor varies substantially as a function of reach morphology and dominant wind direction relative to the river-corridor orientation, factors that control accommodation space for river-derived sand and the modern sand supply to aeolian dunes. These attributes, together with an inverse correlation between aeolian sand activity and gully occurrence, define varying degrees of net long-term gully-erosion risk for sediment deposits and associated archeological sites in different regions of the river corridor. Over most of the river corridor, including some of the archeologically richest regions, sand is too inactive with respect to aeolian transport to anneal gullies effectively. At eight selected archeological sites that we studied with high-resolution terrestrial lidar scans for more than a year, sand loss by overland flow (gully erosion) and aeolian deflation generally exceeded deposition, such that erosion dominated over most monitoring intervals—even at four sites with strong connectivity to modern sand supply. The Glen Canyon reach of the river corridor appears especially vulnerable to gully erosion. Among the sites that we monitored in detail, erosion generally dominated over deposition to a greater degree at four Glen Canyon sites with no modern sand supply than at four Marble–Grand Canyon sites with aeolian sand supply from controlled-flood sandbars. Although gross annual-scale erosion rates were similar among the Glen Canyon sites and among the Marble–Grand Canyon sites, a relative lack of depositional processes led to greater net erosion at the Glen Canyon sites. Having found no differences in weather patterns to suggest greater erosive forcing in Glen Canyon, and no conclusively influential differences in the slope or watershed area contributing to gully formation, we attribute the greater erosion at the Glen Canyon sites to a combination of inherent geomorphic context (high terraces that do not receive modern sediment supply) and pronounced effects of postdam sediment-supply limitation. We conclude that most of the river-corridor archeological sites are at elevated risk of net erosion under present dam operations. In the present flow regime, controlled floods do not simulate the magnitude or frequency of natural floods, and are not large enough to deposit sand at elevations that were flooded at annual to decadal intervals in predam time. For archeological sites that depend upon river-derived sand, we infer elevated erosion risk owing to a combination of reduced sand supply (both fluvial and aeolian) through (1) the lower-than-natural flood magnitude, frequency, and sediment supply of the controlled-flooding protocol; (2) reduction of open, dry sand area available for wind redistribution under current normal (nonflood) dam operations, which do not include flows as low as natural seasonal low flows and do include substantial daily flow fluctuations; and (3) impeded aeolian sand entrainment and transport owing to increased riparian vegetation growth in the absence of larger, more-frequent floods. If dam operations were to increase the supply of sand available for windblown transport—for example, through larger floods, sediment augmentation, or increased fluvial sandbar exposure by low flows—and also decrease riparian vegetation, the prevalence of active aeolian sand could increase over time, and the propensity for unmitigated gully erosion could decrease. Although the evolution of river-corridor landscapes and archeological sites has been altered fundamentally by the lack of large, sediment-rich floods (flows on the order of 5,000 m 3 /s), some combination of sediment-rich flows above 1,270 m 3 /s, seasonal flows below 226 m 3 /s, and riparian-vegetation removal might increase the preservation potential for sand-dependent archeological resources in the Colorado River corridor.

Arizona↗

Spatial Distribution of Ground-Water Recharge Estimated with a Water-Budget Method for the Jordan Creek Watershed, Lehigh County, Pennsylvania

This report presents the results of a study by the U.S. Geological Survey, in cooperation with the Pennsylvania Geological Survey, to illustrate a water-budget method for mapping the spatial distribution of ground-water recharge for a 76-square-mile part of the Jordan Creek watershed, northwest of Allentown, in Lehigh County, Pennsylvania. Recharge was estimated by using the Hydrological Evaluation of Landfill Performance (HELP) water-budget model for 577 landscape units in Jordan Creek watershed, delineated on the basis of their soils, land use/land cover, and mean annual precipitation during 1951-2000. The water-budget model routes precipitation falling on each landscape unit to components of evapotranspiration, surface runoff, storage, and vertical percolation (recharge) for a five-layer soil column on a daily basis. The spatial distribution of mean annual recharge during 1951-2000 for each landscape unit was mapped by the use of a geographic information system. Recharge simulated by the water-budget model in Jordan Creek watershed during 1951-2000 averaged 12.3 inches per year and ranged by landscape unit from 0.11 to 17.05 inches per year. Mean annual recharge during 1951-2000 simulated by the water-budget model was most sensitive to changes to input values for precipitation and runoff-curve number. Mean annual recharge values for the crop, forest, pasture, and low-density urban land-use/land-cover classes were similar (11.2 to 12.2 inches per year) but were substantially less for high-density urban (6.8 inches per year), herbaceous wetlands (2.5 inches per year), and forested wetlands (1.3 inches per year). Recharge rates simulated for the crop, forest, pasture, and low-density urban land-cover classes were similar because those land-use/land-cover classes are represented in the model with parameter values that either did not significantly affect simulated recharge or tended to have offsetting effects on recharge. For example, for landscapes with forest land cover, values of runoff-curve number assigned to the model were smaller than for other land-use/land-cover classes (causing more recharge and less runoff), but the maximum depth of evapotranspiration was larger than for other land-use/ land-cover classes because of deeper root penetration in forests (causing more evapotranspiration and less recharge). The smaller simulated recharge for high-density urban and wetland land-use/land-cover classes was caused by the large values of runoff-curve number (greater than 90) assigned to those classes. The large runoff-curve number, however, certainly is not realistic for all wetlands; some wetlands act as areas of ground-water discharge and some as areas of recharge. Simulated mean annual recharge computed by the water-budget model for the 53-square-mile part of the watershed upstream from the streamflow-gaging station near Schnecksville was compared to estimates of recharge and base flow determined by analysis of streamflow records from 1967 to 2000. The mean annual recharge of 12.4 inches per year simulated by the water-budget method for 1967-2000 was less than estimates of mean annual recharge of 19.3 inches per year computed from the RORA computer program and base flow computed by the PART computer program (15.1 inches per year). In theory, the water-budget method provides a practical tool for estimating differences in recharge at local scales of interest, and the watershed- average recharge rate of 12.4 inches per year computed by the method is reasonable. However, the mean annual surface runoff of 4.5 inches per year simulated by the model is unrealistically small. The sum of surface runoff and recharge simulated by the water-budget model (16.9 inches per year) is 7 inches per year less than the streamflow measured at the gaging station near Schnecksville (23.9 inches per year) during 1967-2000, indicating that evapotranspiration is overestimated by the water-budget model by that amount. This discrepancy ca

Scientific Investigations Report↗

A regional classification of the effectiveness of depressional wetlands at mitigating nitrogen transport to surface waters in the Northern Atlantic Coastal Plain

Nitrogen from nonpoint sources contributes to eutrophication, hypoxia, and related ecological degradation in Atlantic Coastal Plain streams and adjacent coastal estuaries such as Chesapeake Bay and Pamlico Sound. Although denitrification in depressional (non-riparian) wetlands common to the Coastal Plain can be a significant landscape sink for nitrogen, the effectiveness of individual wetlands at removing nitrogen varies substantially due to varying hydrogeologic, geochemical, and other landscape conditions, which are often poorly or inconsistently mapped over large areas. A geographic model describing the spatial variability in the likely effectiveness of depressional wetlands in watershed uplands at mitigating nitrogen transport from nonpoint sources to surface waters was constructed for the Northern Atlantic Coastal Plain (NACP), from North Carolina through New Jersey. Geographic and statistical techniques were used to develop the model. Available medium-resolution (1:100,000-scale) stream hydrography was used to define 33,799 individual watershed catchments in the study area. Sixteen landscape metrics relevant to the occurrence of depressional wetlands and their effectiveness as nitrogen sinks were defined for each catchment, based primarily on available topographic and soils data. Cluster analysis was used to aggregate the 33,799 catchments into eight wetland landscape regions (WLRs) based on the value of three principal components computed for the 16 original landscape metrics. Significant differences in topography, soil, and land cover among the eight WLRs demonstrate the effectiveness of the clustering technique. Results were used to interpret the relative likelihood of depressional wetlands in each WLR and their likely effectiveness at mitigating nitrogen transport from upland source areas to surface waters. The potential effectiveness of depressional wetlands at mitigating nitrogen transport varies substantially over different parts of the NACP. Depressional wetlands are common in three WLRs covering 32 percent of the area, and have a relatively high potential to mitigate nitrogen transport from nonpoint sources. Conversely, 37 percent of the study area includes rolling hills with relatively high slope and relief, and little likelihood of depressional wetlands. The remainder of the Coastal Plain includes relatively flat watersheds with moderate to low relative likelihood of nitrogen mitigation. The delineation of WLRs in this model should be useful for targeting wetland conservation or restoration efforts, and for estimating the effects of depressional wetlands on the regional nitrogen budget, but should be considered in light of limitations and assumptions inherent in the model.

Scientific Investigations Report↗

U.S. Geological Survey Karst Interest Group: proceedings, St Petersburg, Florida February 13-16, 2001

Karst and similar landscapes are found in a wide range of biogeographic classes. In the U.S. for example, Everglades, Mammoth Cave, and Hawaii Volcanoes National Parks have little in common - except karst or pseudokarst, and a cultural past (even though these are very different). This diversity of geologic settings makes karst difficult to categorize and work with when designing a national program such as the recent NPS-USGS Geo-Indicators effort. A GIS-based approach with multiple datalayers is the only sane way to understand and convey the many relationships, in X, Y, and Z axes, between component ecosystems and cultural resources within karst and pseudokarst landscapes. Obviously, karst and cultural landscapes cross modern political as well as biogeographic boundaries. Here again, three-dimensional data are the foundation for understanding similar to that in anatomy and physiology: structure and function. In understanding where the most vulnerable 'pressure points' exist within karst landscapes, we can target landscape-scale ecosystem management to greatest effect. USGS and the National Cave and Karst research Institute could play an extremely significant role in cave and karst management on a national scale beyond NPS or other agency boundaries via cooperative management of three-dimensional karst datasets analogous to programs in several states.

Florida↗

Complex vulnerabilities of the water and aquatic carbon cycles to permafrost thaw

The spatial distribution and depth of permafrost are changing in response to warming and landscape disturbance across northern Arctic and boreal regions. This alters the infiltration, flow, surface and subsurface distribution, and hydrologic connectivity of inland waters. Such changes in the water cycle consequently alter the source, transport, and biogeochemical cycling of aquatic carbon (C), its role in the production and emission of greenhouse gases, and C delivery to inland waters and the Arctic Ocean. Responses to permafrost thaw across heterogeneous boreal landscapes will be neither spatially uniform nor synchronous, thus giving rise to expressions of low to medium confidence in predicting hydrologic and aquatic C response despite very high confidence in projections of widespread near-surface permafrost disappearance as described in the 2019 Intergovernmental Panel on Climate Change Special Report on the Ocean and Cryosphere in a Changing Climate: Polar Regions. Here, we describe the state of the science regarding mechanisms and factors that influence aquatic C and hydrologic responses to permafrost thaw. Through synthesis of recent topical field and modeling studies and evaluation of influential landscape characteristics, we present a framework for assessing vulnerabilities of northern permafrost landscapes to specific modes of thaw affecting local to regional hydrology and aquatic C biogeochemistry and transport. Lastly, we discuss scaling challenges relevant to model prediction of these impacts in heterogeneous permafrost landscapes.

Arctic↗

Operationalizing resilience and resistance concepts to address invasive grass-fire cycles

Plant invasions can affect fuel characteristics, fire behavior, and fire regimes resulting in invasive plant-fire cycles and alternative, self-perpetuating states that can be difficult, if not impossible, to reverse. Concepts related to general resilience to disturbance and resistance to invasive plants provide the basis for managing landscapes to increase their capacity to reorganize and adjust following fire, while concepts related to spatial resilience provide the basis for managing landscapes to conserve resources and habitats and maintain connectivity. New, spatially explicit approaches and decision-tools enable managers to understand and evaluate general and spatial resilience to fire and resistance to invasive grasses across large landscapes in arid and semi-arid shrublands and woodlands. These approaches and tools provide the capacity to locate management actions strategically to prevent development of invasive grass-fire cycles and maintain or improve resources and habitats. In this review, we discuss the factors that influence fire regimes, general and spatial resilience to fire, resistance to invasive annual grasses, and thus invasive grass-fire cycles in global arid and semi-arid shrublands and woodlands. The Cold Deserts, Mediterranean Ecoregion, and Warm Deserts of North America are used as model systems to describe how and why resilience to disturbance and resistance to invasive annuals differ over large landscapes. The Cold Deserts are used to illustrate an approach and decision tools for prioritizing areas on the landscape for management actions to prevent development of invasive grass-fire cycles and protect high value resources and habitats and for determining effective management strategies. The concepts and approach herein represent a paradigm shift in the management of these ecosystems, which allows managers to use geospatial tools to identify resilience to disturbance and resistance to invasive plants in order to target conservation and restoration actions where they will provide the greatest benefits.

Frontiers in Ecology and Evolution↗