SEARCH · Geology Reports

Results for “Drones”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2Linked to original sources

USGS2021

Point clouds of bridge generated by terrestrial laser scanner and images via Structure from Motion technique: Comparison study

A collection of points representing an object in space is commonly called a point cloud. There are several techniques for collecting point clouds. This research is focused on a comparison study of two approaches: (1) collecting point clouds with a surveying grade terrestrial laser scanner (TLS) and (2) generating point clouds from drone-taken still images by utilizing Structure-from-Motion (SFM) technique. The paper's main objective is to compare the generated point clouds to each other and show the advantages and disadvantages of both techniques for structural health monitoring of bridges. To achieve the goal of the paper, we selected a pedestrian bridge for a comparison study. For simplicity, the study was limited to a single-span bridge. The bridge we studied is a composite steel and reinforced concrete (RC) bridge with a curved deck. A terrestrial laser scanner was used to scan the bridge from several positions, and point clouds were registered based on point-cloud to point-cloud matching. No targets were used during the collection of the point clouds by the laser scanner. In addition, still images of both bridges were taken by a drone. Based on a quantitative comparison of the results, the paper discusses the pros and cons of both approaches.

California↗

USGS2014

Estimating movement and survival rates of a small saltwater fish using autonomous antenna receiver arrays and passive integrated transponder tags

We evaluated the performance of small (12.5 mm long) passive integrated transponder (PIT) tags and custom detection antennas for obtaining fine-scale movement and demographic data of mummichog Fundulus heteroclitus in a salt marsh creek. Apparent survival and detection probability were estimated using a Cormack Jolly Seber (CJS) model fitted to detection data collected by an array of 3 vertical antennas from November 2010 to March 2011 and by a single horizontal antenna from April to August 2011. Movement of mummichogs was monitored during the period when the array of vertical antennas was used. Antenna performance was examined in situ using tags placed in wooden dowels (drones) and in live mummichogs. Of the 44 tagged fish, 42 were resighted over the 9 mo monitoring period. The in situ detection probabilities of the drone and live mummichogs were high (~80-100%) when the ambient water depth was less than ~0.8 m. Upstream and downstream movement of mummichogs was related to hourly water depth and direction of tidal current in a way that maximized time periods over which mummichogs utilized the intertidal vegetated marsh. Apparent survival was lower during periods of colder water temperatures in December 2010 and early January 2011 (median estimate of daily apparent survival = 0.979) than during other periods of the study (median estimate of daily apparent survival = 0.992). During late fall and winter, temperature had a positive effect on the CJS detection probability of a tagged mummichog, likely due to greater fish activity over warmer periods. During the spring and summer, this pattern reversed possibly due to mummichogs having reduced activity during the hottest periods. This study demonstrates the utility of PIT tags and continuously operating autonomous detection systems for tracking fish at fine temporal scales, and improving estimates of demographic parameters in salt marsh creeks that are difficult or impractical to sample with active fishing gear.

Marine Ecology Progress Series↗

USGS2021

Exploring local riverbank sediment controls on the occurrence of preferential groundwater discharge points

Groundwater discharge to rivers takes many forms, including preferential groundwater discharge points (PDPs) along riverbanks that are exposed at low flows, with multi-scale impacts on aquatic habitat and water quality. The physical controls on the spatial distribution of PDPs along riverbanks are not well-defined, rendering their prediction and representation in models challenging. To investigate the local riverbank sediment controls on PDP occurrence, we tested drone-based and handheld thermal infrared to efficiently map PDP locations along two mainstem rivers. Early in the study, we found drone imaging was better suited to locating tributary and stormwater inflows, which created relatively large water surface thermal anomalies in winter, compared to PDPs that often occurred at the sub-meter scale and beneath riparian tree canopy. Therefore, we primarily used handheld thermal infrared imaging from watercraft to map PDPs and larger seepage faces along 12-km of the fifth-order Housatonic River in Massachusetts, USA and 26-km of the Farmington River in Connecticut, USA. Overall, we mapped 31 riverbank PDPs along the Housatonic reach that meanders through lower permeability soils, and 104 PDPs along the Farmington reach that cuts through sandier sediments. Riverbank soil parameters extracted at PDP locations from the Soil Survey Geographic (SSURGO) database did not differ substantially from average bank soils along either reach, although the Farmington riverbank soils were on average 5× more permeable than Housatonic riverbank soils, likely contributing to the higher observed prevalence of PDPs. Dissolved oxygen measured in discharge water at these same PDPs varied widely, but showed no relation to measured sand, clay, or organic matter content in surficial soils indicating a lack of substantial near-surface aerobic reaction. The PDP locations were investigated for the presence of secondary bank structures, and commonly co-occurred with riparian tree root masses indicating the importance of localized physical controls on the spatial distribution of riverbank PDPs.

Connecticut↗

USGS2026

Surface detection probability of leatherback turtles at the Rio de La Plata and its Maritime Front: Implications for density estimates

The Río de la Plata and its Maritime Front (RLPMF) serve as a key, seasonal feeding area for leatherback sea turtles ( Dermochelys coriacea ) in the Southwestern Atlantic Ocean. While leatherback turtles can be frequently observed in these waters, there is little data on regional abundances and relative densities, which hinders threat assessments and the development of effective conservation strategies. Consequently, given that in this region parameters needed for in-water leatherback turtle density estimates have not been previously published, the objective of this study was to investigate the surface availability bias, g(0). This parameter requires region-specific considerations for factors like aggregation behaviour and environmental conditions. To address these gaps, our study assessed leatherback turtle aggregations in the RLPMF using satellite tag data and direct drone observations. Through satellite tracking, surfacing behaviour data of six leatherback turtles, g(0) was estimated to be 0.3183. This analysis represents the first of its kind in the region, providing an important contribution to sea turtle conservation studies. It enables substantial progress in characterising surface time, which is essential for understanding leatherback diving and surface behaviour in the region and for improving relative density estimates in the Southwestern Atlantic Ocean. Furthermore, this contribution represents a resource for planning more effective conservation strategies to mitigate threats and promote population recovery.

Río de la Plata and its Maritime Front↗

USGS2022

Democratizing macroecology: Integrating unoccupied aerial systems with the National Ecological Observatory Network

Macroecology research seeks to understand ecological phenomena with causes and consequences that accumulate, interact, and emerge across scales spanning several orders of magnitude. Broad-extent, fine-grain information (i.e., high spatial resolution data over large areas) is needed to adequately capture these cross-scale phenomena, but these data have historically been costly to acquire and process. Unoccupied aerial systems (UAS or drones carrying a sensor payload) and the National Ecological Observatory Network (NEON) make the broad-extent, fine-grain observational domain more accessible to researchers by lowering costs and reducing the need for highly specialized equipment. Integration of these tools can further democratize macroecological research, as their strengths and weaknesses are complementary. However, using these tools for macroecology can be challenging because mental models are lacking, thus requiring large up-front investments in time, energy, and creativity to become proficient. This challenge inspired a working group of UAS-using academic ecologists, NEON professionals, imaging scientists, remote sensing specialists, and aeronautical engineers at the 2019 NEON Science Summit in Boulder, Colorado, to synthesize current knowledge on how to use UAS with NEON in a mental model for an intended audience of ecologists new to these tools. Specifically, we provide (1) a collection of core principles for collecting high-quality UAS data for NEON integration and (2) a case study illustrating a sample workflow for processing UAS data into meaningful ecological information and integrating it with NEON data collected on the ground—with the Terrestrial Observation System—and remotely—from the Airborne Observation Platform. With this mental model, we advance the democratization of macroecology by making a key observational domain—the broad-extent, fine-grain domain—more accessible via NEON/UAS integration.

Ecosphere↗

USGS2016

Unmanned aircraft systems in wildlife research: Current and future applications of a transformative technology

Unmanned aircraft systems (UAS) – also called unmanned aerial vehicles (UAVs) or drones – are an emerging tool that may provide a safer, more cost-effective, and quieter alternative to traditional research methods. We review examples where UAS have been used to document wildlife abundance, behavior, and habitat, and illustrate the strengths and weaknesses of this technology with two case studies. We summarize research on behavioral responses of wildlife to UAS, and discuss the need to understand how recreational and commercial applications of this technology could disturb certain species. Currently, the widespread implementation of UAS by scientists is limited by flight range, regulatory frameworks, and a lack of validation. UAS are most effective when used to examine smaller areas close to their launch sites, whereas manned aircraft are recommended for surveying greater distances. The growing demand for UAS in research and industry is driving rapid regulatory and technological progress, which in turn will make them more accessible and effective as analytical tools.

Frontiers in Ecology and the Environment↗

USGS2023

Expansive, positive changes to fish habitat diversity following the formation of a valley plug in a degraded desert river

Widespread hydrologic alterations have simplified in-stream habitats in rivers globally, driving population declines and extirpations of many native fishes. Here, we examine how rapid geomorphic change in a historically degraded desert river has influenced habitat diversification and ecosystem persistence. In 2010, a large reach of the degraded and simplified lower San Rafael River (SRR), Utah, was impacted by the formation of a valley plug and began to shift from a homogenous, single-thread channel to a complex, multi-threaded riverscape. We combined field measurements and drone-collected imagery to document changes in fish habitat due to the valley plug. Our results demonstrate that in 2021, the affected reach was more diverse than any other stream reach along the SRR, containing 641% more diverse habitat (e.g., pools, riffles, and backwaters) than what was measured in 2015. The plug reach also retained water for periods beyond what was expected during seasonal drying, with the total extent of inundation within the riverscape increasing by over 2800%. Since the formation of the valley plug, riparian habitat has increased by 230% and channel networks have expanded to more than 50 distinct channels throughout the zone of influence. Our results provide evidence of successful self-restoration in a formerly highly degraded reach of desert river, and encourage new methods of desert river restoration. We aim to inform the use of large-scale, disruptive restoration actions like intentional channel occlusions, with the goal of mitigating the impacts of simplification and increasing habitat persistence in the face of exacerbated aridity in the desert Southwest.

Utah↗

USGS2025

Applications of unoccupied aerial systems (UAS) in landscape ecology: A review of recent research, challenges and emerging opportunities

Context Unoccupied aerial systems/vehicles (UAS/UAV, a.k.a. drones) have become an increasingly popular tool for ecological research. But much of the recent research is concerned with developing mapping and detection approaches, with few studies attempting to link UAS data to ecosystem processes and function. Landscape ecologists have long used high resolution imagery and spatial analyses to address ecological questions and are therefore uniquely positioned to advance UAS research for ecological applications. Objectives The review objectives are to: (1) provide background on how UAS are used in landscape ecological studies, (2) identify major advancements and research gaps, and (3) discuss ways to better facilitate the use of UAS in landscape ecology research. Methods We conducted a systematic review based on PRISMA guidelines using key search terms that are unique to landscape ecology research. We reviewed only papers that applied UAS data to investigate questions about ecological patterns, processes, or function. Results We summarize metadata from 161 papers that fit our review criteria. We highlight and discuss major research themes and applications, sensors and data collection techniques, image processing, feature extraction and spatial analysis, image fusion and satellite scaling, and open data and software. Conclusion We observed a diversity of UAS methods, applications, and creative spatial modeling and analysis approaches. Key aspects of UAS research in landscape ecology include modeling wildlife micro-habitats, scaling of ecosystem functions, landscape and geomorphic change detection, integrating UAS with historical aerial and satellite imagery, and novel applications of spatial statistics.

Landscape Ecology↗

USGS2026

Advances and applications of Unoccupied Aerial Systems (UAS) research in landscape ecology

Landscape ecologists have long depended on satellite and aerial remote sensing to address questions about landscape pattern and process, structure, and change (Foody 2023 ). Unoccupied aerial systems/vehicles (UAS/UAV, a.k.a. drones) technology is becoming an increasingly popular research tool in environmental sciences allowing scientists to generate low-cost, high-quality, and high-resolution imagery on demand that can be tailored to specific research questions. While satellite data are of a fixed resolution and temporal interval, UAS offer researchers control and flexibility to design studies and collect data at resolutions and scales that provide ecologically relevant information at finer spatial resolutions (e.g., < 30 cm) than what is currently available from satellite platforms (typically > 3m), thus helping capture objects such as individual plant canopies, micro-topography, and individual animals. Unlike satellites with fixed orbits, UAS can be deployed at more optimal temporal frequencies for ecological monitoring. We organized the special collection “Advances and Applications of Unoccupied Aerial Systems (UAS) Research in Landscape Ecology” to showcase the many ways that UAS tools and technologies are currently applied to advance landscape ecological research. When we announced the collection in 2023, only 11 papers published in the journal Landscape Ecology used UAS data, which was a notably small number compared to many other general ecology, environmental science and remote sensing journals. In an attempt to understand why UAS were not more widely used in landscape ecology and provide possible solutions, we published a review article (Villarreal et al. 2025) that identified the challenges, knowledge gaps, and obstacles for the adoption of UAS technologies in landscape ecology research. The main issues we identified include: (1) an abundance of UAS methods papers in the existing literature, with comparatively few studies demonstrating how UAS can be applied to address ecological questions; (2) a perceived scale mismatch between the geographic extent of UAS data collection (local) compared to larger study areas (landscapes) and a need to design robust scaling approaches to connect fine-scale UAS data with broader ecological patterns; and (3) a need for improved integration of UAS data with other commonly used remote sensing datasets including historical high resolution aerial imagery. Additionally, researchers new to UAS remote sensing may be discouraged or overwhelmed by the general lack of scientific consensus and standardized protocols for typical tasks such as data collection, vegetation classification, and change detection, as well as restrictive and/or confusing policy, regulatory, and legal issues surrounding UAS operations (Villarreal et al. 2025).

Landscape Ecology↗

USGS2022

Manatee population traits elucidated through photo-identification

Data on the demography and distribution of wildlife populations are important for informing conservation and management decisions; however, determination of life history traits and population trends often are elusive. All four extant species in the order Sirenia are deemed vulnerable to extinction; therefore, determining the demography and distribution for populations worldwide is crucial. Aerial surveys, radio-tagging and tracking, genetic sampling and analyses, health assessments, carcass examination, and photographic documentation are all techniques used to study sirenian populations. A 40 +-year computer-aided catalog of images and demography data collected on Florida manatees enables searches of individuals by descriptions of feature (scar) types and has enabled estimates of annual survival and reproductive rates, documented extra-limital movements, and advanced modeling designs. Photography is discussed as a method for the documentation of unique and acquired features specifically on Florida manatees. By means of these features, individual Florida manatees have been re-identified as far from their established range as Cape Cod, Massachusetts, Houston, Texas, and in Cuba, The Bahamas, and Mexico. The length of gestation (11–13 months) and calf dependency (1–3 years), and potential longevity in the wild (> 50 years), have been verified. To meet the challenge of an increasing number of images collected with the advent of digital photography, there has been an increasing interest and potential for new techniques to assist with individual identification. Several researchers are utilizing drones and artificial intelligence to find, photograph, and streamline the individual identification of sirenians as well as other marine mammal species. New techniques have potential to simplify the photographic identification of Florida manatees. Photographic documentation could be a model for demographic and distribution research of sirenian populations outside of Florida and as a tool to monitor the viability of sirenian populations, particularly as threats emerge due to anthropogenic pressures and global climate change.

Mammalian Biology↗

USGS2019

Return flows from beaver ponds enhance floodplain-to-river metals exchange in alluvial mountain catchments

River to floodplain hydrologic connectivity is strongly enhanced by beaver- ( Castor canadensis ) engineered channel water diversions. The hydroecological impacts are wide ranging and generally positive, however, the hydrogeochemical characteristics of beaver-induced flowpaths have not been thoroughly examined. Using a suite of complementary ground- and drone-based heat tracing and remote sensing methodology we characterized the physical template of beaver-induced floodplain exchange for two alluvial mountain streams near Crested Butte, Colorado, USA. A flowpath-oriented perspective to water quality sampling allowed characterization of the chemical evolution of channel water diverted through floodplain beaver ponds and ultimately back to the channel in ‘beaver pond return flows’. Subsurface return flow seepages were universally suboxic, while ponds and surface return flows showed a range of oxygen concentration due to in-situ photosynthesis and atmospheric mixing. Median concentrations of reduced metals: manganese (Mn), iron (Fe), aluminum (Al), and arsenic (As) were substantially higher along beaver-induced flowpaths than in geologically controlled seepages and upstream main channel locations. The areal footprint of reduced return seepage flowpaths were imaged with surface electromagnetic methods, indicating extensive zones of high-conductivity shallow groundwater flowing back toward the main channels and emerging at relatively warm bank seepage zones observed with infrared. Multiple-depth redox dynamics within one focused seepage zone showed coupled variation over time, likely driven by observed changes in seepage rate that may be controlled by pond stage. High-resolution times series of dissolved Mn and Fe collected downstream of the beaver-impacted reaches demonstrated seasonal dynamics in mixed river metal concentrations. Al time series concentrations showed proportional change to Fe at the smaller stream location, indicating chemically reduced flowpaths were sourcing Al to the channel. Overall our results indicated beaver-induced floodplain exchanges create important, and perhaps dominant, transport pathways for floodplain metals by expanding chemically-reduced zones paired with strong advective exchange.

Colorado↗

USGS2022

Microcontinent breakup and links to possible plate boundary reorganization in the northern Gulf of California, México

Faults on microcontinents record the dynamic evolution of plate boundaries. However, most microcontinents are submarine and difficult to study. Here, we show that the southern part of the Isla Ángel de la Guarda (IAG) microcontinent, in the northern Gulf of California rift, is densely faulted by a late Quaternary-active normal fault zone. To characterize the onshore kinematics of this Almeja fault zone, we integrated remote fault mapping using high-resolution satellite- and drone-based topography with neotectonic field-mapping. We produced 13 luminescence ages from sediment deposits offset or impounded by faults to constrain the timing of fault offsets. We found that north-striking normal faults in the Almeja fault zone continue offshore to the south and likely into the nascent North Salsipuedes basin southwest of IAG. Late Pleistocene and Holocene luminescence ages indicate that the most recent onshore fault activity occurred in the last ∼50 kyr. These observations suggest that the North Salsipuedes basin is kinematically linked with and continues onshore as the active Almeja fault zone. We suggest that fragmentation of the evolving IAG microcontinent may not yet be complete and that the Pacific-North America plate boundary is either not fully localized onto the Ballenas transform fault and Lower Delfin pull-apart basin or is in the initial stage of a plate boundary reorganization.

Gulf of California↗

USGS2022

Probing the upper end of intracontinental earthquake magnitude: A prehistoric example from the Dzhungarian and Lepsy faults of Kazakhstan

The study of surface ruptures is key to understanding the earthquake occurrence of faults especially in the absence of historical events. We present a detailed analysis of geomorphic displacements along the Dzhungarian Fault, which straddles the border of China and Kazakhstan. We use digital elevation models derived from structure-from-motion analysis of Pléiades satellite imagery and drone imagery from specific field sites to measure surface offsets. We provide direct age constraints from alluvial terraces displaced by faulting and indirect dating from morphological analysis of the scarps. We find that the southern 250 km of the fault likely ruptured in a single event in the last 4000 years, with displacements of 10-15 m, and potentially up to 20 m at one site. We infer that this Dzhungarian rupture is likely linked with a previously identified paleo-earthquake rupture on the Lepsy Fault through a system of splays in the intervening highlands. Though there are remaining uncertainties regarding consistency in age constraints between the two fault ruptures, the majority of sites along the two faults are consistent with a most recent event 2000-4000 years ago. Rupture on the Dzhungarian fault alone is likely to have exceeded Mw 8, and the combined Lepsy-Dzhungarian rupture may have been up to Mw 8.4. Despite being at the upper end of known or inferred continental earthquake magnitudes, our proposed scenario combining the 375 km of the Dzhungarian and Lepsy ruptures yields a slip-to-length ratio consistent with global averages and so do other historical intra-continental earthquakes in Central Asia.

Dzhungarian fault, Lepsy fault, Tien Shan↗

USGS2021

Volatile metal emissions from volcanic degassing and lava–seawater interactions at Kīlauea Volcano, Hawai’i

Volcanoes represent one of the largest natural sources of metals to the Earth’s surface. Emissions of these metals can have important impacts on the biosphere as pollutants or nutrients. Here we use ground- and drone-based direct measurements to compare the gas and particulate chemistry of the magmatic and lava–seawater interaction (laze) plumes from the 2018 eruption of Kīlauea, Hawai’i. We find that the magmatic plume contains abundant volatile metals and metalloids whereas the laze plume is further enriched in copper and seawater components, like chlorine, with volatile metals also elevated above seawater concentrations. Speciation modelling of magmatic gas mixtures highlights the importance of the S 2− ligand in highly volatile metal/metalloid degassing at the magmatic vent. In contrast, volatile metal enrichments in the laze plume can be explained by affinity for chloride complexation during late-stage degassing of distal lavas, which is potentially facilitated by the HCl gas formed as seawater boils.

Hawaii↗

USGS2019

Precision mapping of snail habitat provides a powerful indicator of human schistosomiasis transmission

Recently, the World Health Organization recognized that efforts to interrupt schistosomiasis transmission through mass drug administration have been ineffective in some regions; one of their new recommended strategies for global schistosomiasis control emphasizes targeting the freshwater snails that transmit schistosome parasites. We sought to identify robust indicators that would enable precision targeting of these snails. At the site of the world’s largest recorded schistosomiasis epidemic—the Lower Senegal River Basin in Senegal—intensive sampling revealed positive relationships between intermediate host snails (abundance, density, and prevalence) and human urogenital schistosomiasis reinfection (prevalence and intensity in schoolchildren after drug administration). However, we also found that snail distributions were so patchy in space and time that obtaining useful data required effort that exceeds what is feasible in standard monitoring and control campaigns. Instead, we identified several environmental proxies that were more effective than snail variables for predicting human infection: the area covered by suitable snail habitat (i.e., floating, nonemergent vegetation), the percent cover by suitable snail habitat, and size of the water contact area. Unlike snail surveys, which require hundreds of person-hours per site to conduct, habitat coverage and site area can be quickly estimated with drone or satellite imagery. This, in turn, makes possible large-scale, high-resolution estimation of human urogenital schistosomiasis risk to support targeting of both mass drug administration and snail control efforts.

PNAS↗

USGS2026

Rain interacts with directional wind to cause nest failures within breeding colonies of Western and Clark's Grebes

Western Grebe ( Aechmophorus occidentalis ) and Clark's Grebe ( Aechmophorus clarkii ) populations have declined across their range, and they are species of high conservation concern. Cascade Reservoir in central Idaho supports one of the largest breeding colonies of Aechmophorus grebes in North America (and the largest in Idaho), but few offspring are produced from the colony in most years. Low fecundity and little natal recruitment may be the proximate cause of Aechmophorus grebe population declines, but the ultimate cause of low recruitment is not known. One hypothesis for the low fecundity at Cascade Reservoir (and at other grebe colonies in the region) is that waves on freshwater breeding lakes inundate nests and cause pairs to abandon their nests. We tested that hypothesis by examining whether nest survival was negatively associated with changes in daily water level, daily peak wind speed and daily peak wind direction (i.e. winds that push water into the breeding colony). We also included daily mean temperature and daily total precipitation to evaluate a more general hypothesis that weather events caused nest failures. We used aerial imagery obtained from repeated drone flights to create encounter histories for 3888 Aechmophorus grebe nests to then estimate daily nest survival and evaluate whether daily water level, daily peak wind speed and daily peak wind direction (as predicted by the wind-driven wave hypothesis) were important causes of nest failure relative to other factors that commonly affect daily nest survival in birds. Nesting success was alarmingly low and we found some support for the wave inundation hypothesis; the results suggest that nesting attempts are more likely to fail on days with precipitation combined with winds blowing into the colony. Our results are the first to show that wind and precipitation affect the nest fate of Aechmophorus grebes.

Idaho↗

USGS2020

Using the Lomb-Scargle method for wave statistics from gappy time series

Sandwich Town Neck Beach in Sandwich, MA, has experienced substantial erosion and has been the subject of efforts by the town and private landowners to limit the sand loss. Erosion has been particularly dramatic in the past five years with the loss of dwellings. Sandwich's nourishment efforts presented a unique opportunity for scientists at the U.S. Geological Survey Woods Hole Coastal and Marine Science Center to monitor beach morphology and to test new technologies and techniques such as geo-referenced drone imaging. Two bottom lander deployments were performed in Cape Cod Bay at a location that was key to model the fate of waves at Sandwich Town Neck Beach and to support the study of beach morphological evolution. The study period was after the town nourished the beach and during a time when several intense winter storms reshaped the beach and removed much of the nourished sand. A TRDI Workhorse Sentinel V ADCP was used for both deployments. For wave bursts, the instruments collected 2048 samples at 2 Hz every hour. The first deployment during the winter of 2016 returned good quality data. The second deployment during the following winter had gaps throughout the time series from a wiring problem in the external battery pack. The timing of the gaps was random, the duration approximately 100 s. While most of the bursts started at the top of each hour, many had 1-3 gaps within. Time series data with random gaps are problematic for computing spectral density, and thus, wave statistics. This kind of situation is familiar in other scientific disciplines such as astrophysics [1], where techniques exist to find stationary signals in sparse data. One of these methods is the Lomb-Scargle technique for computing periodograms. The most useful feature of the Lomb-Scargle (LS) method is that it allows the spectral analysis of incomplete records, without having to manipulate the record to extrapolate from or replace missing data. We compared the effectiveness of LS against common methods of averaging Fourier transforms such as a simple un-windowed Fast Fourier transform (FFT), Welch's method, and TRDI's Wavesmon software; methods that are commonly used in oceanography for non-gappy data. Synthetic data series that have been artificially modified to introduce gaps were used to evaluate the performance of each method. The LS approach was able to recover spectral density even with several 100-s gaps present. The method was applied here to the gappy and non-gappy data from both Sandwich deployments, and wave statistics were obtained and compared to the wave-buoy data. LS was used to process data that contains gaps that was rejected by Wavesmon, which was approximately 39% of the dataset. Significant wave height and peak period from LS compared well with buoy data. Mean period computed on gappy data using LS produced values biased low, compared with other methods when gaps were filled with the mean value. The LS technique has potential to uncover low-frequency signals such as infragravity waves from gappy records where the non-gappy segments are not long enough to resolve them. It has potential to unlock new information from older data sets.

Massachusetts↗

USGS2022

Using piecewise regression to identify biological phenomena in biotelemetry datasets

1. Technological advances in the field of animal tracking have greatly expanded the potential to remotely monitor animals, opening the door to exploring how animals shift their behavior over time or respond to external stimuli. A wide variety of animal-borne sensors can provide information on an animal’s location, movement characteristics, external environmental conditions, and internal physiological status. 2. Here, we demonstrate how piecewise regression can be used to identify the presence and timing of potential shifts in a variety of biological responses using GPS telemetry and other biologging data streams. Different biological latent states can be inferred by partitioning a time-series into multiple segments based on changes in modeled responses (e.g., their mean, variance, trend, degree of autocorrelation) and specifying a unique model structure for each interval. 3. We provide six example applications highlighting a variety of taxonomic species, data streams, timescales and biological phenomena. These examples include a short-term behavioural response (flee and return) by a trumpeter swan Cygnus buccinator following a GPS collar deployment; remote identification of parturition based on movements by a pregnant moose Alces alces ; a physiological response (spike in heart-rate) in a black bear Ursus americanus to a stressful stimulus(presence of a drone); a mortality event of a trumpeter swan signalled by changes in collar temperature and overall dynamic body acceleration; an unsupervised method for identifying the onset, return, duration and staging use of sandhill crane Antigone canadensis migration; and estimation of the transition between incubation and brood-rearing (i.e. hatching) for a breeding trumpeter swan. 4. We implement analyses using the MCP package in R, which provides functionality for specifying and fitting a wide variety of user-defined model structures in a Bayesian framework and methods for assessing and comparing models using information criteria and cross-validation measures.

Journal of Animal Ecology↗