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Evaluation of SWIR crop residue bands for the Landsat Next mission

This research reports the findings of a Landsat Next expert review panel that evaluated the use of narrow shortwave infrared (SWIR) reflectance bands to measure ligno-cellulose absorption features centered near 2100 and 2300 nm, with the objective of measuring and mapping non-photosynthetic vegetation (NPV), crop residue cover, and the adoption of conservation tillage practices within agricultural landscapes. Results could also apply to detection of NPV in pasture, grazing lands, and non-agricultural settings. Currently, there are no satellite data sources that provide narrowband or hyperspectral SWIR imagery at sufficient volume to map NPV at a regional scale. The Landsat Next mission, currently under design and expected to launch in the late 2020’s, provides the opportunity for achieving increased SWIR sampling and spectral resolution with the adoption of new sensor technology. This study employed hyperspectral data collected from 916 agricultural field locations with varying fractional NPV, fractional green vegetation, and surface moisture contents. These spectra were processed to generate narrow bands with centers at 2040, 2100, 2210, 2260, and 2230 nm, at various bandwidths, that were subsequently used to derive 13 NPV spectral indices from each spectrum. For crop residues with minimal green vegetation cover, two-band indices derived from 2210 and 2260 nm bands were top performers for measuring NPV (R 2 = 0.81, RMSE = 0.13) using bandwidths of 30 to 50 nm, and the addition of a third band at 2100 nm increased resistance to atmospheric correction residuals and improved mission continuity with Landsat 8 Operational Land Imager Band 7. For prediction of NPV over a full range of green vegetation cover, the Cellulose Absorption Index, derived from 2040, 2100, and 2210 nm bands, was top performer (R 2 = 0.77, RMSE = 0.17), but required a narrow (≤20 nm) bandwidth at 2040 nm to avoid interference from atmospheric carbon dioxide absorption. In comparison, broadband NPV indices utilizing Landsat 8 bands centered at 1610 and 2200 nm performed poorly in measuring fractional NPV (R 2 = 0.44), with significantly increased interference from green vegetation.

Remote Sensing↗

Integration of vegetation classification with land cover mapping: Lessons from regional mapping efforts in the Americas

Aims : Natural resource management and biodiversity conservation rely on inventories of vegetation that span multiple management or political jurisdictions. However, while remote sensing data and analytical tools have enabled production of maps at increasing spatial resolution and reliability, there are limited examples where national or continental-scaled maps are produced to represent vegetation at high thematic detail. We illustrate two examples that have bridged the gap between traditional land cover mapping and modern vegetation classification. Study area : Our two case studies include national ( USA ) and continental (North and South America) vegetation and land cover mapping. These studies span conditions from subpolar to tropical latitudes of the Americas. Methods : Both case studies used a supervised modeling approach with the International Vegetation Classification ( IVC ) to produce maps that provide for greater thematic detail. Georeferenced locations for these vegetation types are used by machine learning algorithms to train a predictive model and generate a distribution map. Results : The USA LANDFIRE (Landscape Fire and Resource Management Planning Tools Project) case study illustrates how a history of vegetation-based classification and availability of key inputs can come together to generate standard map products covering more than 9.8 million km 2 that are unsurpassed anywhere in the world in terms of spatial and thematic resolution. That being said, it also remains clear that mapping at the thematic resolution of the IVC Group and finer resolution require very large and spatially balanced inputs of georeferenced samples. Even with extensive prior data collection efforts, these remain a key limitation. The NatureServe effort for the Americas - encompassing 22% of the global land surface - demonstrates methods and outputs suitable for worldwide application at continental scales. Conclusions : Continued collection of input data used in the case studies could enable mapping at these spatial and thematic resolutions around the globe.

Vegetation Classification and Survey↗

Physiography, geology, and land cover of four watersheds in eastern Puerto Rico: Chapter A in Water quality and landscape processes of four watersheds in eastern Puerto Rico

Four watersheds with differing geology and land cover in eastern Puerto Rico have been studied on a long-term basis by the U.S. Geological Survey to evaluate water, energy, and biogeochemical budgets. These watersheds are typical of tropical, island-arc settings found in many parts of the world. Two watersheds are located on coarse-grained granitic rocks that weather to quartz- and clay-rich, sandy soils, and two are located on fine-grained volcanic rocks and volcaniclastic sedimentary rocks that weather to quartz-poor, fine-grained soils. For each bedrock type, one watershed is covered with mature forest, and the other watershed, like most of Puerto Rico, has transformed from relatively undisturbed pre-European forest to intensive agriculture in the 19th and early 20th centuries, and further to ongoing reforestation that began in the middle of the 20th century. The comparison of water chemistry and hydrology in these watersheds allows an evaluation of the effects of land-use history and geology on hydrologic regimes and erosion rates. This chapter describes the physiography, geology, and land cover of the four watersheds and provides background information for the remaining chapters in this volume.

Professional Paper↗

Impacts of vehicles on natural terrain at seven sites in the San Francisco Bay area

The impacts of off-road vehicles on vegetation and soil were investigated at seven representative sites in the San Francisco Bay area. Plant cover of grass and chaparral (with shrubs to 4 m tall) have been stripped by the two- and four-wheel vehicles in use. Impacts on loamy soils include increased surface strength (as much as 275 bars), increased bulk density (averaging 18%) to depths of 90 cm or more, reduction of soil moisture by an average 43% to 30 cm depths, greatly reduced infiltration, extension of the diurnal temperature range by as much as 12??C, and reduction of organic carbon by an average 33% in exposed soils. Very sandy soils respond similarly to vehicular use except that moisture is increased and surface strength of beach sand is decreased. These physical and chemical impacts reduce the land's capability of restoring its vegetative cover, which in turn adversely affects animal populations. Both the loss of plant cover and the physical changes caused by vehicles promote erosion. Measured soil and substrate losses from vehicular use zones range from 7 to 1180 kg/m2. The estimated erosion rate of the Chabot Park site exceeds the rate of erosion considered a serious problem by a factor 30, it exceeds United States Soil Conservation Service tolerance values by a factor of 46, and it exceeds average San Francisco Bay area erosion rates by a factor of 17. The resulting soil losses are effectively permanent. Neither the increased sediment yield nor the increased runoff is accomodated on the sites of use, and both are causing adverse effects to neighboring properties. ?? 1978 Springer-Verlag New York Inc.

Environmental Geology↗

Fire rehabilitation effectiveness: a chronosequence approach for the Great Basin

Federal land management agencies have invested heavily in seeding vegetation for emergency stabilization and rehabilitation (ES&R) of non-forested lands. ES&R projects are implemented to reduce post-fire dominance of non-native annual grasses, minimize probability of recurrent fire, quickly recover lost habitat for sensitive species, and ultimately result in plant communities with desirable characteristics including resistance to invasive species and resilience or ability to recover following disturbance. Land managers lack scientific evidence to verify whether seeding non-forested lands achieves their desired long-term ES&R objectives. The overall objective of our investigation is to determine if ES&R projects increase perennial plant cover, improve community composition, decrease invasive annual plant cover and result in a more desirable fuel structure relative to no treatment following fires while potentially providing habitat for Greater Sage-Grouse, a species of management concern. In addition, we provide the locations and baseline vegetation data for further studies relating to ES&R project impacts. We examined effects of seeding treatments (drill and broadcast) vs. no seeding on biotic and abiotic (bare ground and litter) variables for the dominant climate regimes and ecological types within the Great Basin. We attempted to determine seeding effectiveness to provide desired plant species cover while restricting non-native annual grass cover relative to post-treatment precipitation, post-treatment grazing level and time-since-seeding. Seedings were randomly sampled from all known post-fire seedings that occurred in the four-state area of Idaho, Nevada, Oregon and Utah. Sampling locations were stratified by major land resource area, precipitation, and loam-dominated soils to ensure an adequate spread of locations to provide inference of our findings to similar lands throughout the Great Basin. Nearly 100 sites were located that contained an ES&R project. Of these sites, 61 were seeded by using a drill, 27 were broadcast aerially, and 12 had a combination of both. We randomly sampled three burned and seeded, burned and unseeded, and unburned and unseeded locations in the vicinity of the fire, each within the same ecological site. We measured foliar cover of all plant functional groups (perennial or annual, shrub, grass, forb, native or introduced), biological soil crusts, and abiotic (bare soil and litter) variables using the line-point intercept protocol. Fuel loads and horizontal fuel continuity were measured. We applied linear mixed models to response variables (cover and density of plant groups) relative to the dependent variables (seeding treatments and precipitation/temperature relationships. Post-fire strengths with native perennial grasses or shrubs in mixes did not increase density or cover of these groups significantly relative to unseeded, burned areas. Seeded non-native perennial grasses and the shrub Bassia prostrata were effective in providing more cover in aerial and drill seedings. Seeded non-native perennial grass cover increased with increased annual precipitation regardless of seeding type. Seeding native shrubs, particularly Artemisia tridentata, did not significantly increase shrub cover in burned areas. Cover of undesirable non-native annual grasses was lower in drill seedings relative to unseeded areas but only at higher elevations. Seeding effectiveness after wildfire is unpredictable in drier, low elevation environments, and our findings indicate management objectives are more likely met when focusing efforts on higher elevation or higher precipitation locations where establishment of perennial grasses is more likely. On sites where potential for invasion and dominance of non-native annuals is high, such as lower and drier sites, intensive methods of restoration that include invasive plant control before seeding may be required. Where establishment of native perennial plants is the goal, managers might consider using native-only seed mixtures, because we found that the non-native perennials typically used in Great Basin restoration efforts are selected for their competitive nature and may reduce establishment of less competitive native species. Although we attempted to include information on livestock grazing history after seedings, we were unable to extract sufficient data from files to address this topic that may play an additional role in understanding native plant abundance post-fire seeding. Evaluation of drill and aerial seeding effects on fuel characteristics focused on two metrics that are standard inputs for fire behavior models, fuel load and fuel continuity. Fuel loads were evaluated separately for total fuel load biomass, and the individual components that sum to total biomass, namely herbaceous, shrub, shrub:herbaceous ratio, litter, 10-hour, and 100-hour fuel biomasses. Fuel continuity was evaluated using the following cover categories, total, annual grass, annual forb, perennial forb perennial grass, shrub, litter, vegetative interspace, and perennial interspace. Drill seeding did not affect fuel loads, except to reduce 10-hour fuels, probably due to mechanical destruction of dead and down fuels by the drill seeding equipment. Drill seeding did affect fuel continuity, specifically decreasing total plant cover by increasing perennial grass cover which suppressed annual grass and litter production resulting in a net decrease in continuity, but only at the elevations above approximately 1500m. Aerial seeding had no effect on any fuel load or fuel continuity category. For the Greater Sage-Grouse habitat study, we developed multi-scale empirical models of sage-grouse occupancy in 211 randomly located plots within a 40 million ha portion of the species’ range. We then used these models to predict sage-grouse habitat quality at 101 ES&R seeding projects. We compared conditions at restoration sites to published habitat guidelines. Sage-grouse occupancy was positively related to plot- and landscape-level dwarf sagebrush (Artemisia arbuscula, A. nova, A. tripartita) and big sagebrush steppe, and negatively associated with non-native grass and human development. The predicted probability of sage-grouse occupancy at treated plots was low on average (0.07–0.09) and was not significantly different from burned areas that had not been treated. Restoration was more often successful at higher elevation sites with low annual temperatures, high spring precipitation, and high plant diversity. No plots seeded after fire (n=313) met all overstory guidelines for breeding habitats, but approximately 50% met understory guidelines, particularly for perennial grasses. This trend was similar for summer habitat. Ninety-eight percent of treated plots did not meet winter habitat guidelines. Restoration actions in burned areas did not increase the probability of meeting most guideline criteria. The probability of meeting guidelines was influenced by a latitudinal gradient, local climate, and topography. Post-fire seeding treatments in Great Basin sagebrush shrublands generally have not created high quality habitat for sage-grouse. Understory conditions are more likely to be adequate than those of overstory, but in unfavorable climates, establishing forbs and reducing cheatgrass dominance is unlikely. Reestablishing sagebrush cover will require more than 20 years using the restoration methods of the past two decades. Given current fire frequencies and restoration capabilities, protection of landscapes containing a mix of dwarf sagebrush and big sagebrush steppe, minimal human development, and low non-native plant cover may provide the best opportunity for conservation of sage-grouse habitats. Our database of ES&R locations has used the Land Treatment Digital Library to archive data and location information regarding our study (see Pilliod and Welty 2013). This has contributed to two additional studies. One examined the potential spread of Bassia prostrata (aka Kochia prostrata; forage kochia) from ES&R project locations (Gray and Muir 2013). The second used remote sensing to determine the phenology of vegetation green-up on post-fire seeded sites (Sankey et al. 2013).

California;Idaho;Oregon;Utah↗

Relation of Environmental characteristics to the composition of aquatic assemblages along a gradient of urban land use in New Jersey, 1996-98

Community data from 36 watersheds were used to evaluate the response of fish, invertebrate, and algal assemblages in New Jersey streams to environmental characteristics along a gradient of urban land use that ranged from 3 to 96 percent. Aquatic assemblages were sampled at 36 sites during 1996-98, and more than 400 environmental attributes at multiple spatial scales were summarized. Data matrices were reduced to 43, 170, and 103 species of fish, invertebrates, and algae, respectively, by means of a predetermined joint frequency and relative abundance approach. White sucker (Catostomus commersoni) and Tessellated darter (Etheostoma olmstedi) were the most abundant fishes, accounting for more than 20 and 17 percent, respectively, of the mean abundance. Net-spinning caddisflies (Hydropsychidae) were the most commonly occurring benthic invertebrates and were found at all but one of the 36 sampling sites. Blue-green (for example, Calothrix sp. and Oscillatoria sp.) and green (for example, Protoderma viride) algae were the most widely distrib-uted algae; however, more than 81 percent of the algal taxa collected were diatoms. Principal-component and correlation analyses were used to reduce the dimensionality of the environmental data. Multiple linear regression analysis of extracted ordination axes then was used to develop models that expressed effects of increasing urban land use on the structure of aquatic assemblages. Significant environmental variables identified by using multiple linear regression analysis then were included in a direct gradient analysis. Partial canonical correspondence analysis of relativized abundance data was used to restrict further the effects of residual natural variability, and to identify relations among the environmental variables and the structure of fish, invertebrate, and algal assemblages along an urban land-use gradient. Results of this approach, combined with the results of the multiple linear regression analyses, were used to identify human population density (311-37,594 persons/km2), amount and type of impervious surface cover (0.12-1,350 km2), nutrient concentrations (for example, 0.01-0.29 mg/L of phosphorus), hydrologic instability (for example, 100-8,955 ft3/s for 2-year peak flow), the amount of forest and wetlands in a basin (0.01-6.25 km2), and substrate quality (0-87 percent cobble substrate) as variables that are highly correlated with aquatic-assemblage structure. Species distributions in ordination space clearly indicate that tolerant species are more abundant in the streams impaired by urbanization and sensitive taxa are more closely associated with the least impaired basins. The distinct differences in aquatic assemblages along the urban land-use gradient demonstrate the deleterious effects of urbanization on assemblage structure and indicate that conserving landscape attributes that mitigate anthropogenic influences (for example, stormwater-management practices emphasizing infiltration and preservation of existing forests, wetlands, and riparian corridors) will help to maintain the relative abundance of sensitive taxa. Complementary multiple linear regression models indicate that aquatic community indices were correlated with many of the anthropogenic factors that were found to be significant along the urban land-use gradient. These indices appear to be effective in differentiating the moderately and severely impaired streams from the minimally impaired streams. Evaluation of disturbance thresholds for aquatic assemblages indicates that moderate to severe impairment is detectable in New Jersey streams when impervious surface cover in the drainage basin reaches approximately 18 percent.

Water-Resources Investigations Report↗

Unravelling the influence of landscape alteration from flow alteration on benthic macroinvertebrate assemblage response in the Delaware River Basin

Quantifying the effects of streamflow alteration on assemblage response is central to understanding the role humans play in shaping aquatic environments. These changes represent a level of complexity that impedes developing quantitative links between flow and ecological response because stream hydrology is strongly intertwined with natural and anthropogenic factors. Better management outcomes require disentangling these linkages. Benthic macroinvertebrate data were combined with GIS-derived natural and anthropogenic basin characteristics to identify factors associated with changes in flow processes and assemblage characteristics. Models linking streamflow metrics and macroinvertebrate response at basin and subregion scales were developed using boosted regression tree (BRT) analysis. Basin-scale BRT analyses revealed that links between macroinvertebrate response and flow metrics were often obscured, whereas more homogeneous subregions were better able to discern relations with flow. Urban land cover was the primary factor accounting for changes in flow characteristics. Elevation, land cover, and high flow frequency were the principal variables driving changes in assemblage structure within subregions. Assemblage metrics and traits were equally useful for building response models and were affected similarly by streamflow alteration. Results indicate that response models should be developed based on upland and coastal subregions. However, when defining subregions, care should be taken to maintain data sufficiency. Developing practical flow-protection standards that support a balance between human water requirements and ecological integrity requires models that reduce uncertainty and identify management-relevant drivers. However, effective management often differs by location and models developed at the subregion level may be more applicable to management and stakeholder interests.

Delaware, New Jersey, New York, Pennsylvania↗

Examining change detection approaches for tropical mangrove monitoring

This study evaluated the effectiveness of different band combinations and classifiers (unsupervised, supervised, object-oriented nearest neighbor, and object-oriented decision rule) for quantifying mangrove forest change using multitemporal Landsat data. A discriminant analysis using spectra of different vegetation types determined that bands 2 (0.52 to 0.6 μm), 5 (1.55 to 1.75 μm), and 7 (2.08 to 2.35 μm) were the most effective bands for differentiating mangrove forests from surrounding land cover types. A ranking of thirty-six change maps, produced by comparing the classification accuracy of twelve change detection approaches, was used. The object-based Nearest Neighbor classifier produced the highest mean overall accuracy (84 percent) regardless of band combinations. The automated decision rule-based approach (mean overall accuracy of 88 percent) as well as a composite of bands 2, 5, and 7 used with the unsupervised classifier and the same composite or all band difference with the object-oriented Nearest Neighbor classifier were the most effective approaches.

Photogrammetric Engineering and Remote Sensing↗

Ground-water vulnerability to nitrate contamination in the mid-atlantic region

The U.S. Environmental Protection Agency?s (USEPA) Regional Vulnerability Assessment (ReVA) Program has developed a set of statistical tools to support regional-scale, integrated ecological risk-assessment studies. One of these tools, developed by the U.S. Geological Survey (USGS), is used with available water-quality data obtained from USGS National Water-Quality Assessment (NAWQA) and other studies in association with land cover, geology, soils, and other geographic data to develop logistic-regression equations that predict the vulnerability of ground water to nitrate concentrations exceeding specified thresholds in the Mid-Atlantic Region. The models were developed and applied to produce spatial probability maps showing the likelihood of elevated concentrations of nitrate in the region. These maps can be used to identify areas that currently are at risk and help identify areas where ground water has been affected by human activities. This information can be used by regional and local water managers to protect water supplies and identify land-use planning solutions and monitoring programs in these vulnerable areas.

Fact Sheet↗

Assessing roadway contributions to stormwater flows, concentrations, and loads with the StreamStats application

The Oregon Department of Transportation (ODOT) and other state departments of transportation need quantitative information about the percentages of different land cover categories above any given stream crossing in the state to assess and address roadway contributions to water-quality impairments and resulting total maximum daily loads. The U.S. Geological Survey, in cooperation with ODOT and the FHWA, added roadway and land cover information to the online StreamStats application to facilitate analysis of stormwater runoff contributions from different land covers. Analysis of 25 delineated basins with drainage areas of about 100 mi2 indicates the diversity of land covers in the Willamette Valley, Oregon. On average, agricultural, developed, and undeveloped land covers comprise 15%, 2.3%, and 82% of these basin areas. On average, these basins contained about 10 mi of state highways and 222 mi of non-state roads. The Stochastic Empirical Loading and Dilution Model was used with available water-quality data to simulate long-term yields of total phosphorus from highways, non-highway roadways, and agricultural, developed, and undeveloped areas. These yields were applied to land cover areas obtained from StreamStats for the Willamette River above Wilsonville, Oregon. This analysis indicated that highway yields were larger than yields from other land covers because highway runoff concentrations were higher than other land covers and the highway is fully impervious. However, the total highway area was a fraction of the other land covers. Accordingly, highway runoff mitigation measures can be effective for managing water quality locally, they may have limited effect on achieving basin-wide stormwater reduction goals.

Transportation Research Record↗

Evaluating the ability of regional models to predict local avian abundance

Spatial modeling over broad scales can potentially direct conservation efforts to areas with high species-specific abundances. We examined the performance of regional models for predicting bird abundance at spatial scales typically addressed in conservation planning. Specifically, we used point count data on wood thrush (Hylocichla mustelina) and blue-winged warbler (Vermivora cyanoptera) from 2 time periods (1995-1998 and 2006-2007) to evaluate the ability of regional models derived via Bayesian hierarchical techniques to predict bird abundance. We developed models for each species within Bird Conservation Region (BCR) 23 in the upper midwestern United States at 800-ha, 8,000-ha, and approximately 80,000-ha scales. We obtained count data from the Breeding Bird Survey and land cover data from the National Land Cover Dataset (1992). We evaluated predictions from the best models, as defined by an information-theoretic criterion, using point count data collected within an ecological subregion of BCR 23 at 131 count stations in the 1990s and again in 2006-2007. Competing (Deviance Information Criteria <5) blue-winged warbler models accounted for 67% of the variability and suggested positive associations with forest edge and proportion of forest at the 8,000-ha scale, and negative associations with forest patch area (800 ha) and wetness (800 ha and 80,000 ha). The regional model performed best for blue-winged warbler predicted abundances from point counts conducted in Iowa during 1995-1996 ( r s = 0.57; P = 0.14), the survey period that most closely aligned with the time period of data used for regional model construction. Wood thrush models exhibited positive correlations with point count data for all survey areas and years combined ( r s = 0.58, P &le; 0.001). In comparison, blue-winged warbler models performed worse as time increased between the point count surveys and vintage of the model building data ( r s = 0.03, P = 0.92 for Iowa and r s = 0.13, P = 0.51 for all areas, 2006-2007), likely related to the ephemeral nature of their preferred early successional habitat. Species abundance and sensitivity to changing habitat conditions seems to be an important factor in determining the predictive ability of regional models. Hierarchical models can be a useful tool for concentrating efforts at the scale of management units and should be one of many tools used by land managers, but we caution that the utility of such models may decrease over time for species preferring relatively ephemeral habitats if model inputs are not updated accordingly.

Journal of Wildlife Management↗

Ecological influence and pathways of land use in sagebrush

Land use in sagebrush (Artemisia spp.) landscapes influences all sage-grouse (Centrocer-cus spp.) populations in western North America. Croplands and the network of irrigation canals cover 230,000 km2 and indirectly influence up to 77% of the Sage-Grouse Conservation Area and 73% of sagebrush land cover by subsidizing synanthropic predators on sage-grouse. Urbanization and the demands of human population growth have created an extensive network of con-necting infrastructure that is expanding its influence on sagebrush landscapes. Over 2,500 km 2 are now covered by interstate highways and paved roads; when secondary roads are included, 15% of the Sage-Grouse Conservation Area and 5% of existing sagebrush habitats are 2.5 km from roads. Density of secondary roads often exceeds 5 km/km 2 , resulting in widespread motorized access for recreation, creating extensive travel corridors for management actions and resource development, subsidizing predators adapted to human presence, and facilitating spread of exotic or invasive plants. Sagebrush lands also are being used for their wilderness and recreation values, including off highway vehicle use. Approximately 12,000,000 animal use months (AUM amount of forage to support one livestock unit per month) are permitted for grazing livestock on public lands in the western states. Direct effects of grazing on sage-grouse populations or sagebrush landscapes are not possible to assess from current data. However, management of lands grazed by livestock has influenced sagebrush ecosystems by vegetation treatments to increase forage and reduce sagebrush and other plant species unpalatable to livestock. Fences (2 km/km 2 in some regions), roads, and water developments to manage livestock movements further modify the landscape. Oil and gas development influences 8% of the sagebrush habitats with the highest intensities occurring in the eastern range of sage-grouse; 20% of the sagebrush distribution is indirectly influenced in the Great Plains, Wyoming Basin, and Colorado Plateau SMZs. Energy development physically removes habitat to construct well pads, roads, power lines, and pipelines; indirect effects include habitat fragmentation, soil disturbance, and facilitation of exotic plant and animal spread. More recent development of alternative energy, such as wind and geothermal, creates infrastructure in new regions of the sage-grouse distribution. Land use will continue to be a dominant stressor on sage-brush systems; its individual and cumulative effects will challenge long-term conservation of sage-grouse populations.

Book chapter↗

Prominence of the tropics in the recent rise of global nitrogen pollution

Nitrogen (N) pollution is shaped by multiple processes, the combined effects of which remain uncertain, particularly in the tropics. We use a global land biosphere model to analyze historical terrestrial-freshwater N budgets, considering the effects of anthropogenic N inputs, atmospheric CO2, land use, and climate. We estimate that globally, land currently sequesters 11 (10–13)% of annual N inputs. Some river basins, however, sequester >50% of their N inputs, buffering coastal waters against eutrophication and society against greenhouse gas-induced warming. Other basins, releasing >25% more than they receive, are mostly located in the tropics, where recent deforestation, agricultural intensification, and/or exports of land N storage can create large N pollution sources. The tropics produce 56 ± 6% of global land N pollution despite covering only 34% of global land area and receiving far lower amounts of fertilizers than the extratropics. Tropical land use should thus be thoroughly considered in managing global N pollution.

Nature Communications↗

Runoff response to directional land cover change across reference basins in the conterminous United States

Land cover change plays a critical role in influencing hydrological responses. Change in land cover has impacted runoff across basins with substantial human interference; however, the impacts in basins with minimal human interference have been studied less. In this study, we investigated the impacts of directional land cover changes (forest to/from combined grassland and shrubland) in runoff coefficient (RC; ratio of runoff to precipitation) and runoff volume across 603 low human interference reference basins in the conterminous United States (CONUS). The results indicate basins with significant ( p <0.05) increasing trends in runoff and RC were across the northeast and northwest regions of CONUS, and basins with decreasing trends were in the southern CONUS region. A unit percent increase in basin area from grassland and shrubland to forest was associated with a ∼4% decrease in RC across basins with decreasing RC trends. Similarly, a unit percent increase in basin area from forest to a combined grassland and shrubland was associated with a ∼1% increase in RC across increasing RC trend basins. Runoff volume was decreased (increased) by ∼25 × 10 6 m 3 yr −1 (∼9 × 10 6 m 3 yr −1 ) across basins with decreasing (increasing) trends in runoff and RC. When relating runoff volume with the area of directional land cover changes, each 1 km 2 increase in area from grassland and shrubland to forest resulted in a decrease of ∼530,000 m 3 runoff volume across basins with decreasing trends. In contrast, each 1 km 2 increase in area from forest to grassland and shrubland increased runoff volume by ∼200,000 m 3 across increasing trend basins. Basins in the southern region of CONUS were more impacted by runoff parameters (RC and runoff volume) from directional land cover changes than basins in the northern region. The findings of this study are useful for planning and managing water availability for sustainable and adaptive water resources management at regional scales.

Advances in Water Resources↗

Resolving small-scale forest snow patterns using an energy-balance snow model with a 1-layer canopy

Modelling spatiotemporal dynamics of snow in forests is challenging, as involved processes are strongly dependent on small-scale canopy properties. In this study, we explore how local canopy structure information can be integrated in a medium-complexity energy-balance snow model to replicate observed snow patterns at very high spatial resolutions. Snow depth distributions simulated with the Flexible Snow Model (FSM2) were tested against extensive experimental data acquired in discontinuous subalpine forest stands in Eastern Switzerland over three winters. While the default canopy implementation in FSM2 fails to capture the observed snow depth variability, performance is considerably improved when local canopy cover fraction and hemispherical sky view fraction are additionally accounted for (30% reduction in RMSE). However, realistic snow depth distribution patterns throughout the season are only achieved if effective temperatures of near and distant canopy elements are discerned, and if a mechanism to mimic preferential deposition of snow in canopy gaps is included. We demonstrate that by diversifying the canopy structure input in order to reflect respective portions of the canopy relevant to different processes, even a simple model based on widely used process parametrizations and canopy metrics can be applied for high-resolution simulations of the sub-canopy snow cover with just a few modifications. The presented approaches could be implemented in commonly used land surface models, allowing upscaling experiments and development of sub-grid parametrizations without necessitating complex high-resolution models.

Water Resources Research↗

Intra-urban variations in land surface phenology in a semi-arid environment

Urban vegetation is growing in importance as cities use 'green infrastructure' to mitigate the impacts of climate change, reduce extreme heat, and improve human health and comfort. However, due to the heterogeneity of city landscapes, urban vegetation experiences a diverse range of environmental conditions, potentially leading to differences in growing season timing and length within cities. Here, we investigate physical drivers of urban land surface phenology and timing within a semi-arid city (Denver, CO, USA) using four years (2018–2021) of remotely sensed vegetation indices, modelled air temperature, and land cover datasets. Within the metropolitan region study area, satellite-based vegetation index measurements indicate that growing season length is variable on sub-neighborhood spatial scales. This variability is largely due to differences in the timing of fall senescence, as opposed to early season growth. Areas with substantial fractions of irrigated land cover tend to remain greener for longer, while unirrigated and cooler areas are correlated with an earlier end to the growing season (up to ∼two months shorter). These findings complement those from non-arid cities where surface and air temperature are the dominant environmental control on phenological timing. Results here indicate the importance of soil moisture for phenology in semi-arid regions and suggest unique semi-arid urban growing season dynamics and temperature-vegetation feedbacks. These interactions have implications for water, heat, and vegetation management strategies to maximize ecosystem services in water-limited environments.

Colorado↗

Areas contributing recharge to production wells and effects of climate change on the groundwater system in the Chipuxet River and Chickasheen Brook Basins, Rhode Island

The Chipuxet River and Chickasheen Brook Basins in southern Rhode Island are an important water resource for public and domestic supply, irrigation, recreation, and aquatic habitat. The U.S. Geological Survey, in cooperation with the Rhode Island Department of Health, began a study in 2012 as part of an effort to protect the source of water to six large-capacity production wells that supply drinking water and to increase understanding of how climate change might affect the water resources in the basins. Soil-water-balance and groundwater-flow models were developed to delineate the areas contributing recharge to the wells and to quantify the hydrologic response to climate change. Surficial deposits of glacial origin ranging from a few feet to more than 200 feet thick overlie bedrock in the 24.4-square mile study area. These deposits comprise a complex and productive aquifer system. Simulated areas contributing recharge to the production wells covered a total area of 0.63 square miles for average well withdrawal rates from 2007 through 2011 (total rate of 583 gallons per minute). Simulated areas contributing recharge for the maximum well pumping capacities (total rate of 3,700 gallons per minute) covered a total area of 2.55 square miles. Most simulated areas contributing recharge extend upgradient of the wells to morainal and upland till deposits and to groundwater divides. Some simulated areas contributing recharge include small, isolated areas remote from the wells. Relatively short groundwater traveltimes from recharging locations to discharging wells indicated that the wells are vulnerable to contamination from land-surface activities; median traveltimes ranged from 3.5 to 8.6 years for the production wells examined, and 57 to 91 percent of the traveltimes were 10 years or less. Land cover in the areas contributing recharge includes a substantial amount of urban and agriculture land use for five wells adjacent to the Chipuxet River; for one well adjacent to a tributary stream, land use is less developed. The calibrated groundwater-flow model provided a single, best representation of the areas contributing recharge to a production well. The parameter variance-covariance matrix from model calibration was used to create parameter sets that reflect the uncertainty of the parameter estimates and the correlation among parameters to evaluate the uncertainty associated with the predicted contributing areas to the wells. A Monte Carlo analysis led to contributing areas expressed as a probability distribution that differed from a single deterministic contributing area. Because of the effects of parameter uncertainty, the size of the probabilistic contributing areas for both average and maximum pumping rates was larger than the size of the deterministic contributing areas for the wells. Thus, some areas not in the deterministic contributing area might actually be in the contributing area, including additional areas of urban and agricultural land use that has the potential to contaminate groundwater. Additional areas that might be in the contributing area included recharge originating near the pumping wells that have relatively short groundwater-flow paths and traveltimes. At the maximum pumping rates, areas associated with low probabilities extended long distances along groundwater divides in the uplands remote from the wells. Climate projections for the Chipuxet River and Chickasheen Brook Basins from downscaled output from general circulation models indicate that mean annual temperature might increase by 4.7 degrees Fahrenheit and 8.0 degrees Fahrenheit by the late 21st century (2070&ndash;99) compared with the late 20th century (1970&ndash;99) under scenarios of lower and higher emissions of greenhouse gases, respectively. By the late 21st century, winter and spring precipitation is projected to increase by 12 to 17 percent, summer precipitation to increase by about the same as mean annual precipitation (8 percent), and fall precipitation to decrease by 5 percent for both emission scenarios compared with the late 20th century. Soil-water-balance simulations indicate that, although precipitation is expected to increase in three seasons, only in winter do precipitation increases exceed actual evapotranspiration increases. Recharge is projected to decrease in fall and generally change little in spring and summer. By the late 21st century, winter recharge is expected to increase by 13 percent for the lower emissions scenario and by 15 percent for the higher emissions scenario. In fall, recharge is projected to diminish by 13 percent for the lower emissions scenario and by 24 percent for the higher emissions scenario. Although recharge is projected to change seasonally in the 21st century, mean annual recharge changes minimally. Soil moisture is projected to decrease in the 21st century from spring through fall because of increases in potential evapotranspiration, and in fall because of decreases in precipitation in addition to increases in potential evapotranspiration. By the late 21st century, soil moisture for the lower emissions scenario is expected to decrease by 11 percent in summer and 15 percent in fall, and for the higher emissions scenario, decrease by 23 percent for both seasons. These decreases in soil moisture during the growing season might have implications for agriculture in the study area. Predicted changes in the magnitude and seasonal distribution of recharge in the 21st century increase simulated base flows and groundwater levels in the winter months for both emission scenarios, but because of less recharge in the fall and less or about the same recharge in the preceding months of spring and summer, base flows and groundwater levels in the fall months decrease for both emission scenarios. October has the largest base flow and groundwater level decreases. By the late 21st century, base flows at the Chipuxet River in October are projected to decrease by 9 percent for the lower emissions scenario and 18 percent for the higher emissions scenario. For a headwater stream in the upland till with shorter groundwater-flow paths and lower storage properties in its drainage area, base flows in October are projected to diminish by 28 percent and 42 percent for the lower and higher emissions scenarios by the late 21st century. Groundwater level changes in the uplands show substantial decreases in fall, but because of the large storage capacity of stratified deposits, water levels change minimally in the valley. By the late 21st century, water levels in large areas of upland till deposits in October are projected to decrease by up to 2 feet for the lower emissions scenario, whereas large areas decrease by up to 5 feet, with small areas with decreases of as much as 10 feet, for the higher emissions scenario. For both emission scenarios, additional areas of till go dry in fall compared with the late 20th century. Thus projected changes in recharge in the 21st century might extend low flows and low water levels for the year later in fall and there might be more intermittent headwater streams compared with the late 20th century with corresponding implications to aquatic habitat. Finally, the size and location of the simulated areas contributing recharge to the production wells are minimally affected by climate change because mean annual recharge, which is used to determine the contributing areas to the production wells, is projected to change little in the 21st century.

Rhode Island↗

Characterizing land surface phenology and exotic annual grasses in dryland ecosystems using Landsat and Sentinel-2 data in harmony

Invasive annual grasses, such as cheatgrass (Bromus tectorum L.), have proliferated in dryland ecosystems of the western United States, promoting increased fire activity and reduced biodiversity that can be detrimental to socio-environmental systems. Monitoring exotic annual grass cover and dynamics over large areas requires the use of remote sensing that can support early detection and rapid response initiatives. However, few studies have leveraged remote sensing technologies and computing frameworks capable of providing rangeland managers with maps of exotic annual grass cover at relatively high spatiotemporal resolutions and near real-time latencies. Here, we developed a system for automated mapping of invasive annual grass (%) cover using in situ observations, harmonized Landsat and Sentinel-2 (HLS) data, maps of biophysical variables, and machine learning techniques. A robust and automated cloud, cloud shadow, water, and snow/ice masking procedure (mean overall accuracy >81%) was implemented using time-series outlier detection and data mining techniques prior to spatiotemporal interpolation of HLS data via regression tree models (r = 0.94; mean absolute error (MAE) = 0.02). Weekly, cloud-free normalized difference vegetation index (NDVI) image composites (2016–2018) were used to construct a suite of spectral and phenological metrics (e.g., start and end of season dates), consistent with information derived from Moderate Resolution Image Spectroradiometer (MODIS) data. These metrics were incorporated into a data mining framework that accurately (r = 0.83; MAE = 11) modeled and mapped exotic annual grass (%) cover throughout dryland ecosystems in the western United States at a native, 30-m spatial resolution. Our results show that inclusion of weekly HLS time-series data and derived indicators improves our ability to map exotic annual grass cover, as compared to distribution models that use MODIS products or monthly, seasonal, or annual HLS composites as primary inputs. This research fills a critical gap in our ability to effectively assess, manage, and monitor drylands by providing a framework that allows for an accurate and timely depiction of land surface phenology and exotic annual grass cover at spatial and temporal resolutions that are meaningful to local resource managers.

California, Idaho, Nevada, Oregon↗

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