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USGS2026

Case report: Observations on expulsions from 20 years of radiotransmitter implantation in adult Burmese pythons

Background Radiotelemetry as a research tool has advanced our understanding of snake behavior and ecology. However, surgical transmitter implantation can lead to health complications for study animals, including expulsion, which may also interfere with research objectives. Two implantation methods include intramuscular and coelomic placements, and we evaluate expulsion rates of transmitters using these methods in Burmese pythons ( Python bivittatus ) in southern Florida. Results From 2005 to 2024, we implanted 305 transmitters in 142 adult Burmese pythons, primarily using intramuscular implantation ( n = 221), then transitioning to include coelomic placement ( n = 84). There were no observations of transmitter-related mortality. Overall, 98.7% of transmitters were retained, with a 1.3% expulsion rate ( n = 4 transmitters). Expelled transmitters were only observed in intramuscularly implanted transmitters from 4 of 13 gravid females. Conclusions We observed no mortality related to transmitter implantation and few instances of transmitter expulsion, indicating that both intramuscular and coelomic implantation techniques are effective for monitoring adult pythons in the wild. However, there is some risk that females may expel transmitters when gravid, and this risk may be reduced when implanting transmitters intracoelomically. Our findings may be useful for studies of other large-bodied snake populations worldwide where radiotransmitter implantation is appropriate and logistically feasible.

Florida↗

USGS2023

Tagger effects in aquatic telemetry: Short-term and delayed impacts of surgery in Atlantic salmon smolts

Objective An assumption of biotelemetry is that animal performance is unaffected by the tagging process and tag burden, yet this assumption is often untested or not thoroughly explored. Our objective was to explore how transmitter implantation procedures influenced Atlantic Salmon Salmo salar smolt survival and migratory performance. Methods We monitored radio-tagged smolts, first in the hatchery and then in a river with a receiver array. We assessed survival and in-river performance in relation to surgeon, surgery duration, processing order, and fish size. Results Mortality was 13.3% during an 8-day hatchery-observation but was higher for fish processed by one of two experienced surgeons (25% vs. 2%). Mortality peaked three days post-surgery and was higher for smaller fish and fish tagged during morning tagging sessions (compared to afternoons). The size effect changed over time, being greatest during the first two days post-surgery, and continuing thereafter at a diminished level. Fish performance once released into a river also differed between surgeons (migration initiation 66% vs. 82%; and to-lake migration success 22% vs 43%), and consistent with hatchery observations, fish tagged in the morning by one surgeon performed poorly once released. Conclusion We highlight immediate and lingering effects of surgical procedures on smolt survival that, if not accounted for, could bias inferences about the study population. Researchers should anticipate tagger effects during study design to ensure potential tagger effects (i.e., surgeon, order tagged, conditions during tagging) are balanced across study groups of interest. Testing for a fixed tagger effect in analyses may not always be adequate because a tagger effect may covary with processing order and fish size and may change over time.

North American Journal of Fisheries Management↗

USGS2017

Use of fish telemetry in rehabilitation planning, management, and monitoring in Areas of Concern in the Laurentian Great Lakes

Freshwater ecosystems provide many ecosystem services; however, they are often degraded as a result of human activity. To address ecosystem degradation in the Laurentian Great Lakes, Canada and the United States of America established the Great Lakes Water Quality Agreement (GLWQA). In 1987, 43 highly polluted and impacted areas were identified under the GLWQA as having one or more of 14 Beneficial Use Impairments (BUIs) to the physical and chemical habitat for fish, wildlife and humans, and were designated as Areas of Concern (AOC). Subnational jurisdictions combined with local stakeholders, with support from federal governments, developed plans to remediate and restore these sites. Biotelemetry (the tracking of animals using electronic tags) provides information on the spatial ecology of fish in the wild relevant to habitat management and stock assessment. Here, seven case studies are presented where biotelemetry data were directly incorporated within the AOC Remedial Action Plan (RAP) process. Specific applications include determining seasonal fish–habitat associations to inform habitat restoration plans, identifying the distribution of pollutant-indicator species to identify exposure risk to contamination sources, informing the development of fish passage facilities to enable fish to access fragmented upstream habitats, and assessing fish use of created or restored habitats. With growing capacity for fish biotelemetry research in the Great Lakes, we discuss the strengths and weaknesses of incorporating biotelemetry into AOC RAP processes to improve the science and practice of restoration and to facilitate the delisting of AOCs.

Great Lakes↗

USGS2014

When to be discrete: The importance of time formulation in understanding animal movement

Animal movement is essential to our understanding of population dynamics, animal behavior, and the impacts of global change. Coupled with high-resolution biotelemetry data, exciting new inferences about animal movement have been facilitated by various specifications of contemporary models. These approaches differ, but most share common themes. One key distinction is whether the underlying movement process is conceptualized in discrete or continuous time. This is perhaps the greatest source of confusion among practitioners, both in terms of implementation and biological interpretation. In general, animal movement occurs in continuous time but we observe it at fixed discrete-time intervals. Thus, continuous time is conceptually and theoretically appealing, but in practice it is perhaps more intuitive to interpret movement in discrete intervals. With an emphasis on state-space models, we explore the differences and similarities between continuous and discrete versions of mechanistic movement models, establish some common terminology, and indicate under which circumstances one form might be preferred over another. Counter to the overly simplistic view that discrete- and continuous-time conceptualizations are merely different means to the same end, we present novel mathematical results revealing hitherto unappreciated consequences of model formulation on inferences about animal movement. Notably, the speed and direction of movement are intrinsically linked in current continuous-time random walk formulations, and this can have important implications when interpreting animal behavior. We illustrate these concepts in the context of state-space models with multiple movement behavior states using northern fur seal ( Callorhinus ursinus ) biotelemetry data.

Movement Ecology↗

USGS2012

Techniques for telemetry transmitter attachment and evaluation of transmitter effects on fish performance: Chapter 4

One assumption of nearly every biotelemetry study is that the tagged animals are representative of the untagged population. That is, that the processes by which study animals are captured, handled, and tagged, as well as the act of carrying a transmitter, will have minimal effect on their behavior and performance. This assumption, commonly stated as a lack of transmitter effects, must be valid if telemetry studies are to describe accurately the movements and behavior of an entire population of interest, rather than only of a subset of that population. Considering the sequence of events necessary to implement telemetry studies (i.e., collection, handling, transmitter attachment), as well as the intrusive nature of many transmitter attachment techniques, it is likely that there will be some effect on the study animals. These potential impacts can range from mild to severe, from transitory to permanent, and may be manifest immediately or not for several days to weeks after tagging. Direct physical impacts can include elevated stress levels, injury, or even death (Knights and Lasee 1996; Jepsen et al. 2001; Lacroix et al. 2004). Interrupted integrity of the scales, mucus, or skin can place fish at increased risk of infection (Mellas and Haynes 1985; Swanberg et al. 1999; Bauer et al. 2005; Harms 2005). Effects on fish behavior include altered buoyancy compensation ability (Gallepp and Magnuson 1972; Fried et al. 1976), reduced swimming performance (McCleave and Stred 1975; Counihan and Frost 1999; Makiguchi and Ueda 2009), reduced feeding, or changes in dominance status (Greenstreet and Morgan 1989; Armstrong and Rawlings 1993; Welch et al. 2007). Changes in behavior such as these can affect a fish’s growth, rate of maturation or migration, or increase its vulnerability to predation. At some level, these transmitter effects will be present in nearly every study using telemetry and if substantial, they can violate the critical assumption that tagged fish are representative of the untagged population.

Book chapter↗

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↗

USGS2012

A history of telemetry in fishery research

Biotelemetry has been defined as “the instrumental technique for gaining and transmitting information from a living organism and its environment to a remote observer” (Slater 1965). Biotelemetry typically utilizes wireless transmission of either an audible signal or electronic data to determine location of a tagged animal. Fisheries researchers use location information to gain a variety of insights into migration, habitat use, behavior, productivity, or survival of fish. Biotelemetry can be divided into two basic categories, acoustic or radio, based on mode of transmission, mechanical or electromagnetic energy, and operating frequency. Most acoustic systems in use today transmit at low frequency, between 30 and 300 kHz, while most radio systems transmit at very high frequency, between 30 and 300 MHz (Sisak and Lotimer 1998). Acoustic telemetry is based on the principals of sonar (sound navigation and ranging), which was developed to detect submarines during World War I. The properties of acoustic systems favor their use in deep waters with high conductivity and low turbulence (Winter 1996). Radio telemetry is based on the principals of wireless radio communication, which were first demonstrated by Nikola Tesla in 1893. Radio systems are best suited in shallow waters with relatively low conductivity but have the added benefit of improved signal detection in turbulent conditions and with aerial antennas. Advances in both technologies have resulted in highly efficient transmitter and receiving systems. Advancements in products used for animal telemetry over the past 50 years have generally followed those in the electronics field (Figure 1). Bell Laboratories1 ushered in the age of digital electronics with the invention of the transistor in 1947 (Mann 2000). Today transistors are common in everyday items such as radios, televisions, hearing aids, computers, cell phones and even MP3 players. Consumer demand for inexpensive small electronic devices with increased functionality has continually driven advancements in the field of electronics. These advancements have subsequently led to improvements in biotelemetry transmitters and receivers such as miniaturization of components, increased battery performance, and more powerful micro-processing.

Book chapter↗

USGS2012

A standard operating procedure for the surgical implantation of transmitters in juvenile salmonids

Biotelemetry is a useful tool to monitor the movements of animals and is widely applied in fisheries research. Radio or acoustic technology can be used, depending on the study design and the environmental conditions in the study area. A broad definition of telemetry also includes the use of Passive Integrated Transponder (PIT) tags, either separately or with a radio or acoustic transmitter. To use telemetry, fish must be equipped with a transmitter. Although there are several attachment procedures available, surgical implantation of transmitters in the abdominal cavity is recognized as the best technique for long-term telemetry studies in general (Stasko and Pincock, 1977; Winter, 1996; Jepsen, 2003), and specifically for juvenile salmonids, Oncorhynchus spp. (Adams and others, 1998a, 1998b; Martinelli and others, 1998; Hall and others, 2009). Studies that use telemetry assume that the processes by which the animals are captured, handled, and tagged, as well as the act of carrying the transmitter, will have minimal effect on their behavior and performance. This assumption, commonly stated as a lack of transmitter effects, must be valid if telemetry studies are to describe accurately the movements and behavior of an entire population of interest, rather than the subset of that population that carries transmitters. This document describes a standard operating procedure (SOP) for surgical implantation of radio or acoustic transmitters in juvenile salmonids. The procedures were developed from a broad base of published information, laboratory experiments, and practical experience in tagging thousands of fish for numerous studies of juvenile salmon movements near Columbia River and Snake River hydroelectric dams. Staff from the Western Fisheries Research Center's Columbia River Research Laboratory (CRRL) frequently have used telemetry studies to evaluate new structures or operations at hydroelectric dams in the Columbia River Basin, and these evaluations typically require large numbers of tagged fish. For example, a study conducted at the dams on the Columbia River and funded by the U.S. Army Corps of Engineers required tagging and monitoring of 40,000 juvenile salmon during a 3-month migration period (Counihan and others, 2006a, 2006b; Perry and others, 2006). To meet the demands of such a large study, the authors and CRRL staff refined the SOP to increase efficiency in the tagging process while maintaining high standards of fish care. The SOP has been used in laboratory and field settings for more than 15 years, and consistently has produced low mortality rates (<1 percent) and transmitter loss rates (<0.01 percent) in the 24-36 hours after tagging. In addition to describing the detailed surgical procedures required for transmitter implantation, this document provides guidance on fish collection, handling and holding, and the release of tagged fish. Although often overlooked, or at least underemphasized, these processes can have a large impact on the outcome of the tagging procedure. Stress associated with the individual steps in handling and tagging can be cumulative and lethal (Maule and others, 1988; Wedemeyer and others, 1990; Portz and others, 2006), so the goal is to provide the best possible fish care at every step in order to manage the overall effect on study fish.

Open-File Report↗

USGS2017

Animal movement: Statistical models for telemetry data

The study of animal movement has always been a key element in ecological science, because it is inherently linked to critical processes that scale from individuals to populations and communities to ecosystems. Rapid improvements in biotelemetry data collection and processing technology have given rise to a variety of statistical methods for characterizing animal movement. The book serves as a comprehensive reference for the types of statistical models used to study individual-based animal movement.

Book↗

USGS2016

Leveraging constraints and biotelemetry data to pinpoint repetitively used spatial features

Satellite telemetry devices collect valuable information concerning the sites visited by animals, including the location of central places like dens, nests, rookeries, or haul‐outs. Existing methods for estimating the location of central places from telemetry data require user‐specified thresholds and ignore common nuances like measurement error. We present a fully model‐based approach for locating central places from telemetry data that accounts for multiple sources of uncertainty and uses all of the available locational data. Our general framework consists of an observation model to account for large telemetry measurement error and animal movement, and a highly flexible mixture model specified using a Dirichlet process to identify the location of central places. We also quantify temporal patterns in central place use by incorporating ancillary behavioral data into the model; however, our framework is also suitable when no such behavioral data exist. We apply the model to a simulated data set as proof of concept. We then illustrate our framework by analyzing an Argos satellite telemetry data set on harbor seals ( Phoca vitulina ) in the Gulf of Alaska, a species that exhibits fidelity to terrestrial haul‐out sites.

Alaska↗

USGS2014

Movement-based estimation and visualization of space use in 3D for wildlife ecology and conservation

Advances in digital biotelemetry technologies are enabling the collection of bigger and more accurate data on the movements of free-ranging wildlife in space and time. Although many biotelemetry devices record 3D location data with x, y , and z coordinates from tracked animals, the third z coordinate is typically not integrated into studies of animal spatial use. Disregarding the vertical component may seriously limit understanding of animal habitat use and niche separation. We present novel movement-based kernel density estimators and computer visualization tools for generating and exploring 3D home ranges based on location data. We use case studies of three wildlife species – giant panda, dugong, and California condor – to demonstrate the ecological insights and conservation management benefits provided by 3D home range estimation and visualization for terrestrial, aquatic, and avian wildlife research.

PLoS ONE↗

USGS2018

Optimizing release strategies: A stepping-stone approach to reintroduction

Evaluation of alternative management strategies enables informed decisions to accelerate species recovery. For reintroductions, post-release survival to reproductive age is a key parameter influencing population growth. Here we trial a ‘stepping-stone’ method to maximize the success of captive-bred animals when the availability of more suitable wild-born release candidates is limited. Our approach makes use of relatively safe and established wild populations to prepare captive-bred individuals for eventual translocation to a final release destination, thus building resilience through establishment of multiple populations over time. We developed a novel multievent model integrating encounter history and biotelemetry data to evaluate reintroduction strategies for the critically endangered Vancouver Island marmot (Marmota vancouverensis). We compared post-release survival of 176 individuals (52 wild-born, 47 captive-bred marmots released directly to destinations, and 77 captive-bred marmots released with a stepping-stone approach). Survival estimates to prime breeding-age (PBA), were then used to quantify expected success of potential release strategies. Our analysis indicates that post-release survival varies by source population and release method, as well as age, season, year, and years since release. Conditional on an objective of maximizing survival to PBA, our results suggest that using wild-born marmots for translocations as often as possible, and stepping-stone captive-bred marmots prior to final release, will result in the best outcomes. There was a 0.86 probability that survival to PBA was greater for captive-bred marmots released as yearlings using a stepping-stone approach (survival to PBA mode = 0.13, 95% CRI = 0.05-0.30) than for captive-bred animals that were directly released to destination sites as one-year-olds (survival to PBA mode = 0.04, 95% CRI = 0.01-0.24). Consequently, the stepping-stone approach yields much higher population establishment or growth potential than previous release strategies that used captive-bred marmots. Optimizing the combination of release candidates, sites, and timing can thereby increase the effectiveness of reintroductions.

British Columbia↗

USGS2023

Whole-lake acoustic telemetry to evaluate survival of stocked juvenile fish

Estimates of juvenile survival are critical for informing population dynamics and the ecology of fish, yet these demographic parameters are difficult to measure. Here, we demonstrate that advances in animal tracking technology provide opportunities to evaluate survival of juvenile tagged fish. We implemented a whole-lake telemetry array in conjunction with small acoustic tags (including tags < 1.0 g) to track the fate of stocked juvenile cisco ( Coregonus artedi ) as part of a native species restoration effort in the Finger Lakes region of New York, USA. We used time-to-event modeling to characterize the survival function of stocked fish, where we infer mortality as the cessation of tag detections. Survival estimates revealed distinct stages of juvenile cisco mortality including high immediate post-release mortality, followed by a period of elevated mortality during an acclimation period. By characterizing mortality over time, the whole-lake biotelemetry effort provided information useful for adapting stocking practices that may improve survival of stocked fish, and ultimately the success of the species reintroduction effort. The combination of acoustic technology and time-to-event modeling to inform fish survival may have wide applicability across waterbodies where receiver arrays can be deployed at scale and where basic assumptions about population closure can be satisfied.

New York↗

USGS1998

Effects of surgically and gastrically implanted radio transmitters on swimming performance and predator avoidance of juvenile chinook salmon ( Oncorhynchus tshawytscha )

Radiotelemetry data are often used to make inferences about an entire study population; therefore, the transmitter attachment method should be the one that least affects the study animal. Juvenile chinook salmon ( Oncorhynchus tshawytscha ) <120 mm in fork length (FL) with either gastrically or surgically implanted transmitters had significantly lower critical swimming speeds than control fish 1 and 19-23 days after tagging. For fish >120 mm FL, fish with gastric implants swam as well as controls 1 day but not 19-23 days after tagging. In contrast, fish with surgical implants swam as well as controls 19-23 days but not 1 day after tagging. During predation trials, fish with gastric or surgical implants were eaten by smallmouth bass ( Micropterus dolomieu ) in significantly greater numbers than controls. We do not recommend implanting transmitters (representing 4.6-10.4% of the fish's body weight) in fish <120 mm FL. Furthermore, surgical implants (representing 2.2-5.6% of the fish's body weight) may be the preferred method for biotelemetry studies of juvenile chinook salmon >120 mm FL.

Canadian Journal of Fisheries and Aquatic Sciences↗

USGS2023

Supervised versus unsupervised approaches to classification of accelerometry data

Sophisticated animal-borne sensor systems are increasingly providing novel insight into how animals behave and move. Despite their widespread use in ecology, the diversity and expanding quality and quantity of data they produce have created a need for robust analytical methods for biological interpretation. Machine learning tools are often used to meet this need. However, their relative effectiveness is not well known and, in the case of unsupervised tools, given that they do not use validation data, their accuracy can be difficult to assess. We evaluated the effectiveness of supervised ( n = 6), semi-supervised ( n = 1), and unsupervised ( n = 2) approaches to analyzing accelerometry data collected from critically endangered California condors ( Gymnogyps californianus ). Unsupervised K-means and EM (expectation–maximization) clustering approaches performed poorly, with adequate classification accuracies of <0.8 but very low values for kappa statistics (range: −0.02 to 0.06). The semi-supervised nearest mean classifier was moderately effective at classification, with an overall classification accuracy of 0.61 but effective classification only of two of the four behavioral classes. Supervised random forest (RF) and k-nearest neighbor (kNN) machine learning models were most effective at classification across all behavior types, with overall accuracies >0.81. Kappa statistics were also highest for RF and kNN, in most cases substantially greater than for other modeling approaches. Unsupervised modeling, which is commonly used for the classification of a priori-defined behaviors in telemetry data, can provide useful information but likely is instead better suited to post hoc definition of generalized behavioral states. This work also shows the potential for substantial variation in classification accuracy among different machine learning approaches and among different metrics of accuracy. As such, when analyzing biotelemetry data, best practices appear to call for the evaluation of several machine learning techniques and several measures of accuracy for each dataset under consideration.

Ecology and Evolution↗