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USGS2023

Linking vocal behaviours to habitat structure to create behavioural landscapes

The recent development of animal-borne sensors coupled with location data can provide insights into how individuals modify their behaviour with respect to specific habitat features. Animals can express a diverse array of behaviours as they navigate heterogenous landscapes, yet few studies have specifically evaluated the interaction of behaviours with habitat characteristics. We used a novel broadcast acoustic transmitter to investigate the interaction between vocal behaviours of an endemic Hawaiian thrush, the ʻōmaʻo, Myadestes obscurus , and habitat features across a naturally fragmented forest landscape. Through the development of behavioural landscape models that link specific vocalizations with space use, we found that the use of different vocalization types (calls, songs, whisper songs) were highly variable across the landscape but were associated with distinct habitat features. The likelihood of calls increased in an open lava matrix between forest patches, while whisper songs were more strongly associated with the dense interior areas of forest fragments. In contrast, the rate of ʻōmaʻo vocalizations overall decreased in the open lava matrix, suggesting that ʻōmaʻo may shift behaviours from territory defence to foraging as they transition through different habitats. Our study revealed context-specific changes in behaviour across ʻōmaʻo home ranges, including courtship, aggression and social interactions between individuals. Combining the use of a novel acoustic tool with automated radiotelemetry allowed us to overcome challenges associated with detection and analysis of variation in behaviour and resource selection across a highly heterogeneous landscape that would have been otherwise difficult to impossible.

Hawaii↗

USGS2012

Solute and geothermal flux monitoring using electrical conductivity in the Madison, Firehole, and Gibbon Rivers, Yellowstone National Park

The thermal output from the Yellowstone magma chamber can be estimated from the Cl flux in the major rivers in Yellowstone National Park; and by utilizing continuous discharge and electrical conductivity measurements the Cl flux can be calculated. The relationship between electrical conductivity and concentrations of Cl and other geothermal solutes (Na, SO 4 , F, HCO 3 , SiO 2 , K, Li, B, and As) was quantified at monitoring sites along the Madison, Gibbon, and Firehole Rivers, which receive discharge from some of the largest and most active geothermal areas in Yellowstone. Except for some trace elements, most solutes behave conservatively and the ratios between geothermal solute concentrations are constant in the Madison, Gibbon, and Firehole Rivers. Hence, dissolved concentrations of Cl, Na, SO 4 , F, HCO 3 , SiO 2 , K, Li, Ca, B and As correlate well with conductivity ( R 2 > 0.9 for most solutes) and most exhibit linear trends. The 2011 flux for Cl, SO 4 , F and HCO 3 determined using automated conductivity sensors and discharge data from nearby USGS gaging stations is in good agreement with those of previous years (1983–1994 and 1997–2008) at each of the monitoring sites. Continuous conductivity monitoring provides a cost- and labor-effective alternative to existing protocols whereby flux is estimated through manual collection of numerous water samples and subsequent chemical analysis. Electrical conductivity data also yield insights into a variety of topics of research interest at Yellowstone and elsewhere: (1) Geyser eruptions are easily identified and the solute flux quantified with conductivity data. (2) Short-term heavy rain events can produce conductivity anomalies due to dissolution of efflorescent salts that are temporarily trapped in and around geyser basins during low-flow periods. During a major rain event in October 2010, 180,000 kg of additional solute was measured in the Madison River. (3) The output of thermal water from the Gibbon River appears to have increased by about 0.2%/a in recent years, while the output of thermal water for the Firehole River shows a decrease of about 10% from 1983 to 2011. Confirmation of these trends will require continuing Cl flux monitoring over the coming decades.

Wyoming↗

USGS2005

Buffelgrass (Pennisetum ciliare) land conversion and productivity in the plains of Sonora, Mexico

Bufflelgrass ( Pennisetum ciliare syn. Cenchrus ciliaris ) is an African grass that has been widely introduced in subtropical arid regions of the world to improve rangelands for cattle production. However, it can have a negative effect on the diversity of native plant communities. Buffelgrass was introduced to Sonora, Mexico in the 1970s as a means to bolster the cattle industry. “Desmonte,” the process by which native desert vegetation is removed in preparation for buffelgrass seeding, alters the land surface such that buffelgrass plots are easily detectable from aerial and Landsat satellite images. We estimated the extent of conversion to buffelgrass in a 1,850,000 ha area centered on Hermosillo, from MSS and TM images from 1973, 1983, 1990 and 2000. We then compared the relative above-ground productivity of buffelgrass to native vegetation using Normalized Difference Vegetation Index values (NDVI) from Landsat and Moderate Resolution Imaging Spectrometer (MODIS) satellite sensor systems. Buffelgrass pastures have increased from just 7700 ha in 1973 to over 140,000 ha in 2000. Buffelgrass pastures now cover 8% of the land surface in the study area. Buffelgrass pastures have lower net primary productivity, estimated by MODIS NDVI values, than unconverted desert land. The desmonte process removes trees and shrubs, while the buffelgrass plantings are often sparse, leading to an apparent net loss in net primary production from land conversion. We recommend that the desmonte process be discontinued until its efficacy and safety for native ecosystems can be established, and that a comprehensive plan for preserving biodiversity while accomodating economic development be established for this region of the Sonoran Desert in Mexico.

Sonora↗

USGS2026

Biome-scale spatial patterns of avian abundance reveal proactive conservation opportunities in North American grasslands

North American grassland birds have experienced steeper population declines than any other avian guild, yet conservation efforts remain largely reactive and fragmented. We used nearly four decades of North American Breeding Bird Survey data to identify biome-scale spatial patterns (clustering) of grassland bird abundance for the Great Plains. Our results reveal an ecological core in the north-central Plains where community-level abundance is either increasing by >100% or remains high and stable, providing a strategic roadmap for a “Defend the Core” conservation approach. This approach flips the script from reactive triage centered on isolated population fragments to a proactive strategy of maintaining large-scale ecosystem integrity. Conversely, we found that population losses are more spatially clustered than wins, reflecting the relentless, one-way movement of woody encroachment and agricultural conversion. This asymmetry supports prioritizing intact landscapes, as current restoration rates are often outpaced by the scale of habitat loss. Notably, we found that community-level spatial clustering is a more robust indicator of biome condition than trends of individual flagship species, suggesting that managing for ecosystem integrity provides a more effective multi-species umbrella. Given our results, there is an opportunity for operationalizing a Great Plains Conservation Design that is ecosystem-centric and rooted in the sustainability of the private-land cattle production that maintains these open spaces. By leveraging avian abundance as a biological sensor, managers and producers can deploy a shared vision that matches the spatial scale of the threats, moving from reactive triage to proactive defense of core working grasslands in North America.

Great Plains biome↗

USGS2015

The data quality analyzer: a quality control program for seismic data

The U.S. Geological Survey's Albuquerque Seismological Laboratory (ASL) has several initiatives underway to enhance and track the quality of data produced from ASL seismic stations and to improve communication about data problems to the user community. The Data Quality Analyzer (DQA) is one such development and is designed to characterize seismic station data quality in a quantitative and automated manner. The DQA consists of a metric calculator, a PostgreSQL database, and a Web interface: The metric calculator, SEEDscan, is a Java application that reads and processes miniSEED data and generates metrics based on a configuration file. SEEDscan compares hashes of metadata and data to detect changes in either and performs subsequent recalculations as needed. This ensures that the metric values are up to date and accurate. SEEDscan can be run as a scheduled task or on demand. The PostgreSQL database acts as a central hub where metric values and limited station descriptions are stored at the channel level with one-day granularity. The Web interface dynamically loads station data from the database and allows the user to make requests for time periods of interest, review specific networks and stations, plot metrics as a function of time, and adjust the contribution of various metrics to the overall quality grade of the station. The quantification of data quality is based on the evaluation of various metrics (e.g., timing quality, daily noise levels relative to long-term noise models, and comparisons between broadband data and event synthetics). Users may select which metrics contribute to the assessment and those metrics are aggregated into a “grade” for each station. The DQA is being actively used for station diagnostics and evaluation based on the completed metrics (availability, gap count, timing quality, deviation from a global noise model, deviation from a station noise model, coherence between co-located sensors, and comparison between broadband data and synthetics for earthquakes) on stations in the Global Seismographic Network and Advanced National Seismic System.

Computers & Geosciences↗

USGS2008

Rapid formation of hyperpycnal sediment gravity currents offshore of a semi-arid California river

Observations of sediment dispersal from the Santa Clara River of southern California during two moderately sized river discharge events suggest that river sediment rapidly formed a negatively buoyant (hyperpycnal) bottom plume along the seabed within hours of peak discharge. An array of acoustic and optical sensors were placed at three stations 1 km from the Santa Clara River mouth in 10-m water depth during January-February 2004. These combined observations suggest that fluid mud concentrations of suspended sediment (>10 g/l) and across-shore gravity currents (???5 cm/s) were observed in the lower 20-40 cm of the water column 4-6 h after discharge events. Gravity currents were wave dominated, rather than auto-suspending, and appeared to consist of silt-to-clay sized sediment from the river. Sediment mass balances suggest that 25-50% of the discharged river sediment was transported by these hyperpycnal currents. Sediment settling purely by flocs (???1 mm/s) cannot explain the formation of the observed hyperpycnal plumes, therefore we suggest that some enhanced sediment settling from mixing, convective instabilities, or diverging plumes occurred that would explain the formation of the gravity currents. These combined results provide field evidence that high suspended-sediment concentrations from rivers (>1 g/l) may rapidly form hyperpycnal sediment gravity currents immediately offshore of river mouths, and these pathways can explain a significant portion of the river-margin sediment budget. The fate of this sediment will be strongly influenced by bathymetry, whereas the fate of the remaining sediment will be much more influenced by ocean currents.

Continental Shelf Research↗

USGS2012

Storm-induced inner-continental shelf circulation and sediment transport: Long Bay, South Carolina

Long Bay is a sediment-starved, arcuate embayment located along the US East Coast connecting both South and North Carolina. In this region the rates and pathways of sediment transport are important because they determine the availability of sediments for beach nourishment, seafloor habitat, and navigation. The impact of storms on sediment transport magnitude and direction were investigated during the period October 2003–April 2004 using bottom mounted flow meters, acoustic backscatter sensors and rotary sonars deployed at eight sites offshore of Myrtle Beach, SC, to measure currents, water levels, surface waves, salinity, temperature, suspended sediment concentrations, and bedform morphology. Measurements identify that sediment mobility is caused by waves and wind driven currents from three predominant types of storm patterns that pass through this region: (1) cold fronts, (2) warm fronts and (3) low-pressure storms. The passage of a cold front is accompanied by a rapid change in wind direction from primarily northeastward to southwestward. The passage of a warm front is accompanied by an opposite change in wind direction from mainly southwestward to northeastward. Low-pressure systems passing offshore are accompanied by a change in wind direction from southwestward to southeastward as the offshore storm moves from south to north. During the passage of cold fronts more sediment is transported when winds are northeastward and directed onshore than when the winds are directed offshore, creating a net sediment flux to the north–east. Likewise, even though the warm front has an opposite wind pattern, net sediment flux is typically to the north–east due to the larger fetch when the winds are northeastward and directed onshore. During the passage of low-pressure systems strong winds, waves, and currents to the south are sustained creating a net sediment flux southwestward. During the 3-month deployment a total of 8 cold fronts, 10 warm fronts, and 10 low-pressure systems drove a net sediment flux southwestward. Analysis of a 12-year data record from a local buoy shows an average of 41 cold fronts, 32 warm fronts, and 26 low-pressure systems per year. The culmination of these events would yield a cumulative net inner-continental shelf transport to the south–west, a trend that is further verified by sediment textural analysis and bedform morphology on the inner-continental shelf.

South Carolina↗

USGS2019

Observations of mixing and transport on a steep beach

Surfzone mixing and transport on a sandy, steep (∼1/8 slope), reflective beach at Carmel River State Beach, California, are described for a range of wave and alongshore flow conditions. Depth-limited wave breaking occurred close to the shore due to the steepness of the beach, creating a narrow surf/swash zone (∼10 m wide). Fluorescent Rhodamine dye was released as a slug in the surfzone, and the temporal and spatial evolution was measured using in-situ dye sensors. Dye concentration measured as a function of time reveals sharp fronts that quickly decay resulting in narrow peaks near the dye release, which subsequently broaden and decrease in peak concentration with alongshore distance. The measurements indicate two stages of mixing and transport occur inside the surfzone on the steep beach. 1) In the near-field (<50 m downstream of the dye release location), the dye fully mixed throughout the water column after a few incident waves then continued to disperse in two dimensions, with both advection and diffusion processes being important. 2) In the far-field (>50 m downstream from the dye release location), the mass transport was dominated by advection. The distance to the far-field is much shorter in the alongshore on a steep beach compared with a dissipative beach. Estimates of cross-shore and alongshore diffusion coefficients ( κ x , κ y ) were found to be similar in magnitude within the surfzone. Outside the surfzone in the far-field, the results suggest that the mixing processes are independent of those inside the surfzone. The mixing and transport of material observed on this steep beach are found to be analogous to that previously measured on dissipative beaches, however the diffusion coefficients within and outside the surfzone were found to be smaller on this steep beach.

California↗

USGS2022

Temperature variations in the northern Gulf of Alaska across synoptic to century-long time scales

Surface and subsurface moored buoy, ship-based, remotely sensed, and reanalysis datasets are used to investigate thermal variability of northern Gulf of Alaska (NGA) nearshore, coastal, and offshore waters over synoptic to century-long time scales. NGA sea surface temperature (SST) showed a larger positive trend of 0.22 ± 0.10 °C per decade over 1970–2021 compared to 0.10 ± 0.03 °C per decade over 1900–2021. Over synoptic time scales, SST covariance between two stations is small (<10%) when separation exceeds 100 km, while stations separated by 500 km retain 50% of their co-variability for seasonal and longer fluctuations. Relative to in situ sensor data, remotely sensed SST data has limited accuracy in some NGA settings, capturing 60–70% of the daily SST anomaly in coastal and offshore waters, but often <25% nearshore. North Pacific and NGA leading modes of SST variability leave 25–50% of monthly variance unresolved. Analysis of the 2014–2016 Pacific marine heatwave shows that NGA coastal surface temperatures warmed contemporaneously with offshore waters through 2013, but deep inner shelf waters (200–250 m) exhibited delayed warming. Offshore surface waters cooled from 2014 to 2016, while shelf waters continued to warm from the combined effects of local air-sea and advective heat fluxes. We find that annually averaged Sitka air temperature is a leading predictor (r 2 = 0.37, p < 0.05) for following-year NGA coastal water column temperature. Our results can inform future environmental monitoring designs, assist forward-looking projections of marine conditions, and show the importance of in situ measurements for nearshore studies that require knowledge of thermal conditions over time scales of days and weeks.

Alaska↗

USGS2013

Evapotranspiration and water balance of an anthropogenic coastal desert wetland: responses to fire, inflows and salinities

Evapotranspiration (ET) and other water balance components were estimated for Cienega de Santa Clara, an anthropogenic brackish wetland in the delta of the Colorado River in Mexico. The marsh is in the Biosphere Reserve of the Upper Gulf of California and Delta of the Colorado River, and supports a high abundance and diversity of wildlife. Over 95% of its water supply originates as agricultural drain water from the USA, sent for disposal in Mexico. This study was conducted from 2009 to 2011, before, during and after a trial run of the Yuma Desalting Plant in the USA, which will divert water from the wetland and replace it with brine from the desalting operation. The goal was to estimate the main components in the water budget to be used in creating management scenarios for this marsh. We used a remote sensing algorithm to estimate ET from meteorological data and Enhanced Vegetation Index values from the Moderate Resolution Imaging Spectrometer (MODIS) sensors on the Terra satellite. ET estimates from the MODIS method were then compared to results from a mass balance of water and salt inflows and outflows over the study period. By both methods, mean annual ET estimates ranged from 2.6 to 3.0 mm d −1 , or 50 to 60% of reference ET (ET o ). Water entered at a mean salinity of 2.6 g L −1 TDS and mean salinity in the wetland was 3.73 g L −1 TDS over the 33 month study period. Over an annual cycle, 54% of inflows supported ET while the rest exited the marsh as outflows; however, in winter when ET was low, up to 90% of the inflows exited the marsh. An analysis of ET estimates over the years 2000–2011 showed that annual ET was proportional to the volume of inflows, but was also markedly stimulated by fires. Spring fires in 2006 and 2011 burned off accumulated thatch, resulting in vigorous growth of new leaves and a 30% increase in peak summer ET compared to non-fire years. Following fires, peak summer ET estimates were equal to ET o , while in non-fire years peak ET was equal to only one-half to two-thirds of ET o . Over annual cycles, estimated ET was always lower than ET o , because T. domingensis is dormant in winter and shades the water surface, reducing direct evaporation. Thus, ET of a Typha marsh is likely to be less than an open water surface under most conditions.

Ecological Engineering↗

USGS2013

Vegetation dynamics in response to water inflow rates and fire in a brackish Typha domingensis Pers. marsh in the delta of the Colorado River, Mexico

The Cienega de Santa Clara is a 5600 ha, anthropogenic wetland in the delta of the Colorado River in Mexico. It is the inadvertent creation of the disposal of brackish agricultural waste water from the U.S. into the intertidal zone of the river delta in Mexico, but has become an internationally important wetland for resident and migratory water birds. We used high resolution Quickbird and WorldView-2 images to produce seasonal vegetation maps of the Cienega before, during and after a test run of the Yuma Desalting Plant, which will remove water from the inflow stream and replace it with brine. We also used moderate resolution, 16-day composite NDVI imagery from the Moderate Resolution Imaging Spectrometer (MODIS) sensors on the Terra satellite to determine the main factors controlling green vegetation density over the years 2000–2011. The marsh is dominated by Typha domingensis Pers. with Phragmites australis (Cav.) Trin. Ex Steud. as a sub-dominant species in shallower marsh areas. The most important factor controlling vegetation density was fire. Spring fires in 2006 and 2011 were followed by much more rapid green-up of T. domingensis in late spring and 30% higher peak summer NDVI values compared to non-fire years ( P < 0.001). Fires removed thatch and returned nutrients to the water, resulting in more vigorous vegetation growth compared to non-fire years. The second significant ( P < 0.01) factor controlling NDVI was flow rate of agricultural drain water from the U.S. into the marsh. Reduced summer flows in 2001 due to canal repairs, and in 2010 during the YDP test run, produced the two lowest NDVI values of the time series from 2000 to 2011 ( P < 0.05). Salinity is a further determinant of vegetation dynamics as determined by greenhouse experiments, but was nearly constant over the period 2000–2011, so it was not a significant variable in regression analyses. It is concluded that any reduction in inflow volumes will result in a linear decrease in green foliage density in the marsh.

Ecological Engineering↗

USGS2021

Satellite remote sensing to assess cyanobacterial bloom frequency across the United States at multiple spatial scales

Cyanobacterial blooms can have negative effects on human health and local ecosystems. Field monitoring of cyanobacterial blooms can be costly, but satellite remote sensing has shown utility for more efficient spatial and temporal monitoring across the United States. Here, satellite imagery was used to assess the annual frequency of surface cyanobacterial blooms, defined for each satellite pixel as the percentage of images for that pixel throughout the year exhibiting detectable cyanobacteria . Cyanobacterial frequency was assessed across 2,196 large lakes in 46 states across the continental United States (CONUS) using imagery from the European Space Agency’s Ocean and Land Colour Instrument for the years 2017 through 2019. In 2019, across all satellite pixels considered, annual bloom frequency had a median value of 4% and a maximum value of 100%, the latter indicating that for those satellite pixels, a cyanobacterial bloom was detected by the satellite sensor for every satellite image considered. In addition to annual pixel-scale cyanobacterial frequency, results were summarized at the lake- and state-scales by averaging annual pixel-scale results across each lake and state. For 2019, average annual lake-scale frequencies also had a maximum value of 100%, and Oregon and Ohio had the highest average annual state-scale frequencies at 65% and 52%. Pixel-scale frequency results can assist in identifying portions of a lake that are more prone to cyanobacterial blooms, while lake- and state-scale frequency results can assist in the prioritization of sampling resources and mitigation efforts. Satellite imagery is limited by the presence of snow and ice, as imagery collected in these conditions are quality flagged and discarded. Thus, annual bloom frequencies within nine climate regions were investigated to determine whether missing data biased results in climate regions more prone to snow and ice, given that their annual summaries would be weighted toward the summer months when cyanobacterial blooms tend to occur. Results were unbiased by the time period selected in most climate regions, but a large bias was observed for the Northwest Rockies and Plains climate region. Moderate biases were observed for the Ohio Valley and the Southeast climate regions. Finally, a clustering analysis was used to identify areas of high and low cyanobacterial frequency across CONUS based on average annual lake-scale cyanobacterial frequencies for 2019. Several clusters were identified that transcended state, watershed, and eco-regional boundaries. Combined with additional data, results from the clustering analysis may offer insight regarding large-scale drivers of cyanobacterial blooms.

Ecological Indicators↗

USGS2022

Satellites quantify the spatial extent of cyanobacterial blooms across the United States at multiple scales

Previous studies indicate that cyanobacterial harmful algal bloom (cyanoHAB) frequency, extent, and magnitude have increased globally over the past few decades. However, little quantitative capability is available to assess these metrics of cyanoHABs across broad geographic scales and at regular intervals. Here, the spatial extent was quantified from a cyanobacteria algorithm applied to two European Space Agency satellite platforms—the MEdium Resolution Imaging Spectrometer (MERIS) onboard Envisat and the Ocean and Land Colour Instrument (OLCI) onboard Sentinel-3. CyanoHAB spatial extent was defined for each geographic area as the percentage of valid satellite pixels that exhibited cyanobacteria above the detection limit of the satellite sensor. This study quantified cyanoHAB spatial extent for over 2,000 large lakes and reservoirs across the contiguous United States (CONUS) during two time periods: 2008–2011 via MERIS and 2017–2020 via OLCI when cloud-, ice-, and snow-free imagery was available. Approximately 56% of resolvable lakes were glaciated, 13% were headwater, isolated, or terminal lakes, and the rest were primarily drainage lakes. Results were summarized at national-, regional-, state-, and lake-scales, where regions were defined as nine climate regions which represent climatically consistent states. As measured by satellite, changes in national cyanoHAB extent did have a strong increase of 6.9% from 2017 to 2020 (|Kendall’s tau (τ)| = 0.56; gamma (γ) = 2.87 years), but had negligible change (|τ| = 0.03) from 2008 to 2011. Two of the nine regions had moderate (0.3 ≤ |τ| < 0.5) increases in spatial extent from 2017 to 2020, and eight of nine regions had negligible (|τ| < 0.2) change from 2008 to 2011. Twelve states had a strong or moderate increase from 2017 to 2020 (|τ| ≥ 0.3), while only one state had a moderate increase and two states had a moderate decrease from 2008 to 2011. A decrease, or no change, in cyanoHAB spatial extent did not indicate a lack of issues related to cyanoHABs. Sensitivity results of randomly omitted daily CONUS scenes confirm that even with reduced data availability during a short four-year temporal assessment, the direction and strength of the changes in spatial extent remained consistent. We present the first set of national maps of lake cyanoHAB spatial extent across CONUS and demonstrate an approach for quantifying past and future changes at multiple spatial scales. Results presented here provide water quality managers information regarding current cyanoHAB spatial extent and quantify rates of change.

Ecological Indicators↗

USGS2022

A water quality barometer for Chesapeake Bay: Assessing spatial and temporal patterns using long-term monitoring data

This paper develops a barometer that indexes water quality in the Chesapeake Bay and summarizes quality over spatial regions and temporal periods. The barometer has a basis in risk assessment and hydrology, and is a function of three different metrics of water quality relative to numerical criteria: relative frequency of criterion attainment; magnitude of deviation from a numerical criterion; and duration of criterion attainment. Metrics associated with these features are calculated at the station level, allowing flexibility for simultaneously evaluating multiple stressors, different designated uses, and physical characteristics of the water. The barometer score is then created as a geometric mean of the three metrics. The water quality barometer (WQB) station scores may be spatially aggregated to report habitat scores across a spectrum of spatial resolutions (e.g., management segment, tidal subsystem, or the whole tidal bay). Dissolved oxygen measurements in the Chesapeake Bay collected during summer seasons of 1985 to 2020 are used to evaluate water quality. The WQB score and its bootstrapped confidence interval are reported at the station, segment, tidal subsystem and whole tidal bay levels. Notably, water quality interpreted through application of the WQB with dissolved oxygen concentration data and averaged over the 29-year period of record is good (i.e. protects aquatic living resources) in tributaries such as the James River, Rappahannock River and others; but is not as good in areas such as the Upper Tributaries and the York River. Recent summaries indicate that while the water quality is improving in much of the bay and its tidal tributaries, however, there is an indication of decline in quality in the period 20182020, especially in the upper regions of the Bay. The barometer is designed around using the time series data produced by the Chesapeake Bay Programs annual monitoring strategy; the approach has application to other large water bodies with large scale monitoring programs with extended time series or for integrating information from environmental sensor systems.

Maryland, Virginia↗

USGS2025

Small waterbodies of large conservation concern: Towards an integrated approach to more accurately measuring surface water dynamics

Millions of small waterbodies are dispersed throughout the middle of the North American continent, and billions of dollars have been invested to conserve, restore, and manage these waterbodies in the 20th and 21st centuries. Small waterbody conservation has been supported by different stakeholders aiming at improving water quality, enhancing floodwater storage, and supporting migratory bird breeding habitat. Conservation agencies are using hydrological and biological monitoring, modeling, and mapping to adaptively manage small waterbodies in the face of stressors such as invasive species and climate change. As remote sensing estimates of small waterbody surface water extent have become easier to access, understanding the capabilities and limitations of using remote sensing, especially in areas lacking surface water monitoring, is important for conservation decision making. Here, we used in situ monitoring and process-based hydrological modeling to explore remote sensing accuracy, especially related to waterbody size, emergent aquatic vegetation cover, and climatic conditions. Overall, we found that the accuracy of satellite and aerial imagery surface water mapping approaches vastly decreased for waterbodies smaller than 2 ha. We also found emergent vegetation could be masking surface water in waterbodies larger than 2 ha and that accuracy of some remote sensing estimates may decrease during wetter climatic periods. These results indicate that sensors commonly used for surface water applications alone may not be able to accurately detect small waterbody surface water, which supports the need for combining monitoring and modeling to understand how small waterbodies may respond to future changes in climate and land use.

Minnesota↗

USGS2009

Ultraviolet absorbance as a proxy for total dissolved mercury in streams

Stream water samples were collected over a range of hydrologic and seasonal conditions at three forested watersheds in the northeastern USA. Samples were analyzed for dissolved total mercury (THg d ), DOC concentration and DOC composition, and UV 254 absorbance across the three sites over different seasons and flow conditions. Pooling data from all sites, we found a strong positive correlation of THg d to DOC (r 2 = 0.87), but progressively stronger correlations of THg d with the hydrophobic acid fraction (HPOA) of DOC (r 2 = 0.91) and with UV 254 absorbance (r 2 = 0.92). The strength of the UV 254 absorbance-THg d relationship suggests that optical properties associated with dissolved organic matter may be excellent proxies for THg d concentration in these streams. Ease of sample collection and analysis, the potential application of in-situ optical sensors, and the possibility for intensive monitoring over the hydrograph make this an effective, inexpensive approach to estimate THg d flux in drainage waters.

Environmental Pollution↗

USGS2015

Automated calculation of surface energy fluxes with high-frequency lake buoy data

Lake Heat Flux Analyzer is a program used for calculating the surface energy fluxes in lakes according to established literature methodologies. The program was developed in MATLAB for the rapid analysis of high-frequency data from instrumented lake buoys in support of the emerging field of aquatic sensor network science. To calculate the surface energy fluxes, the program requires a number of input variables, such as air and water temperature, relative humidity, wind speed, and short-wave radiation. Available outputs for Lake Heat Flux Analyzer include the surface fluxes of momentum, sensible heat and latent heat and their corresponding transfer coefficients, incoming and outgoing long-wave radiation. Lake Heat Flux Analyzer is open source and can be used to process data from multiple lakes rapidly. It provides a means of calculating the surface fluxes using a consistent method, thereby facilitating global comparisons of high-frequency data from lake buoys.

Environmental Modelling and Software↗

USGS2008

On developing thermal cave detection techniques for earth, the moon and mars

The purpose of this study is to (1) demonstrate the viability of detecting terrestrial caves at thermal-infrared wavelengths, (2) improve our understanding of terrestrial cave thermal behavior, (3) identify times of day when cave openings have the maximum thermal contrast with the surrounding surface regolith, and (4) further our understanding of how to detect caves on Earth, the Moon and Mars. We monitored the thermal behavior of two caves in the Atacama Desert of northern Chile. Through this work, we identified times when temperature contrasts between entrance and surface were greatest, thus enabling us to suggest optimal overflight times. The largest thermal contrast for both caves occurred during mid-day. One cave demonstrated thermal behavior at the entrance suggestive of cold-trapping, while the second cave demonstrated temperature shifts suggestive of airflow. We also collected thermograms without knowing optimal detection times; these images suggest both caves may also be detectable during off-peak times. We suggest cave detection using thermal remote sensing on Earth and other planetary objects will be limited by (1) capturing imagery in the appropriate thermal wavelength, (2) the size of cave entrance vs. the sensor's spatial resolution, (3) the viewing angle of the platform in relation to the slope trajectory of the cave entrance, (4) the strength of the thermal signal associated with the cave entrance, and (5) the time of day and season of thermal image capture. Through this and other studies, we will begin to identify the range of conditions under which caves are detectable in the thermal infrared and thus improve our detection capabilities of these features on Earth, the Moon and Mars.

Earth and Planetary Science Letters↗