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Beyond traditional ecological restoration on the Colorado Plateau

The Colorado Plateau is one of North America's five major deserts, encompassing 340,000 km 2 of the western U.S., and offering many opportunities for restoration relevant to researchers and land managers in drylands around the globe. The Colorado Plateau is comprised of vast tracts of public land managed by local, state, and federal agencies that oversee a wide range of activities (e.g., mineral and energy extraction, livestock grazing, and recreation). About 75% of the Plateau is managed by federal and tribal agencies and tens of millions of people visit the Plateau's public lands each year. However, even in the face of this diverse use, our knowledge of effective ways to restore Plateau ecosystems remains relatively poor. Further, the multiple agencies on the Plateau have mandates that differ greatly in allowable practices, restoration needs, and desired outcomes. The Colorado Plateau is also expected to undergo ecosystem shifts in the face of climate change, further complicating management decisions and potentially limiting some options while creating others. Here we explore the current state of Colorado Plateau restoration science and underscore key challenges and opportunities for improving our capacity to maintain the myriad of services provided by these desert ecosystems. We highlight past research efforts and future needs related to restoration concepts, including consideration and design of novel ecosystems, mitigation for and adaptation to climate change, use of genetically diverse seed adapted for current and future conditions, and the value of strong multi‐agency and stakeholder collaborations in restoring systems on the Colorado Plateau and beyond.

Colorado Plateau↗

Earthquake shaking and damage to buildings

Ground shaking close to the causative fault of an earthquake is more intense than it was previously believed to be. This raises the possibility that large numbers of buildings and other structures are not sufficiently resistant for the intense levels of shaking that can occur close to the fault. Many structures were built before earthquake codes were adopted; others were built according to codes formulated when less was known about the intensity of near-fault shaking. Although many building types are more resistant than conventional design analyses imply, the margin of safety is difficult to quantify. Many modern structures, such as freeways, have not been subjected to and tested by near-fault shaking in major earthquakes (magnitude 7 or greater). Damage patterns in recent moderate-sized earthquakes occurring in or adjacent to urbanized areas, however, indicate that many structures, including some modern ones designed to meet earthquake code requirements, cannot withstand the severe shaking that can occur close to a fault. It is necessary to review the ground motion assumed and the methods utilized in the design of important existing structures and, if necessary, to strengthen or modify the use of structures that are found to be weak. New structures situated close to active faults should be designed on the basis of ground motion estimates greater than those used in the past. The ultimate balance between risk of earthquake losses and cost for both remedial strengthening and improved earthquake-resistant construction must be decided by the public. Scientists and engineers must inform the public about earthquake shaking and its effect on structures. The exposure to damage from seismic shaking is steadily increasing because of continuing urbanization and the increasing complexity of lifeline systems, such as power, water, transportation, and communication systems. In the near future we should expect additional painful examples of the damage potential of moderate-sized earthquakes in urban areas. Over a longer time span, however, we can significantly reduce the risk to life and property from seismic shaking through better land utilization, improved building codes and construction practices, and at least the gradual replacement of poor buildings by more resistant buildings. Progress toward reducing risk from seismic shaking through better building design is slowed by deficiencies in our knowledge about the nature of damaging ground motion and the failure mechanisms in structures. For example, lacking observational data, seismologists must rely on simplified theoretical and numerical models of the earthquake process to estimate near-fault ground motion, especially for earthquakes as large as magnitude 7 and 8. Because such models have not been adequately tested against data, their reliability is unknown. Engineers lack detailed information about failure processes in structures during an earthquake. Although many structures have been instrumented to measure their response to an earthquake, few records have been obtained from buildings that actually sustained significant structural damage and few structures are properly instrumented to measure all the modes of deformation that are likely to contribute to failure. Moreover, the fact that many structures have withstood ground motion more intense than that assumed in their design indicates that conventional methods of design do not take into account important contributions to earthquake resistance by nonstructural elements and by the ability of structural elements to deform inelastically without necessarily causing failure of the structure. It is fortunate when such reserve resistance exists, but better understanding of the sources of reserve strength is needed to determine how large a margin of safety they confer and how they might be affected by changes in construction practices and materials with time. In the next few years we look forward to significant advances in knowledge and to more effective application of what is already known, largely because of substantial funding of research related to seismic engineering by the National Science Foundation . The increasing number of strong-motion seismographs operating in seismically active regions will likely provide for the first time a number of records of damaging levels of ground motion. Significant effort is being directed toward obtaining near-fault records, although many probable sites of future large earthquakes remain inadequately instrumented, especially outside the conterminous United States. New and more complete information on building response and damage mechanisms will be obtained by improved instrumentation of structures and through laboratory investigations of failure in structures and structural elements. Further developments in computer technology and in computer modeling techniques will permit more realistic simulations of the seismic response of soils and structures that take into account their inelastic behavior and their strain-dependent properties. Earthquake design codes will continually be revised to better utilize existing knowledge concerning the nature of strong ground motion and the dynamic behavior of buildings during earthquakes and to incorporate new knowledge and also experiences gained from future earthquakes. We believe that application of new knowledge, improvements in earthquake-resistant design and construction, and remedial strengthening or replacement of weak existing structures can significantly reduce our current level of exposure to earthquake hazards.

Science↗

How low should we go when warning for earthquakes?

A key goal of earthquake early warning (EEW) systems is to alert populations who may be affected by a particular level of ground shaking so that they can take action to reduce impacts of that shaking, such as injuries, damages to physical infrastructure, or emotional distress. Most EEW systems work by rapidly determining the location and size of an earthquake, estimating shaking levels, and then distributing an alert to potentially affected populations. But EEW systems are limited by how rapidly the size of an earthquake can be determined as well as the details of the earthquake rupture process, the path of the seismic waves, and the alert distribution mechanism. And we are just beginning to understand how people respond to earthquake alerts, often relying on anecdotes. Determining the appropriate shaking intensities for public warnings requires understanding the range of individual and societal responses to earthquake alerts. The decision on when to issue earthquake alerts must balance the technical capabilities and potential outcomes, both desired and undesired, when choosing a ground-motion alerting threshold. Only when benefits outweigh the risks and users are prepared for alerts should they be used to warn the public about the possibility of earthquake shaking.

Science↗

Predictive models for Escherichia coli concentrations at inland lake beaches and relationship of model variables to pathogen detection

Predictive models, based on environmental and water quality variables, have been used to improve the timeliness and accuracy of recreational water quality assessments, but their effectiveness has not been studied in inland waters. Sampling at eight inland recreational lakes in Ohio was done in order to investigate using predictive models for Escherichia coli and to understand the links between E. coli concentrations, predictive variables, and pathogens. Based upon results from 21 beach sites, models were developed for 13 sites, and the most predictive variables were rainfall, wind direction and speed, turbidity, and water temperature. Models were not developed at sites where the E. coli standard was seldom exceeded. Models were validated at nine sites during an independent year. At three sites, the model resulted in increased correct responses, sensitivities, and specificities compared to use of the previous day's E. coli concentration (the current method). Drought conditions during the validation year precluded being able to adequately assess model performance at most of the other sites. Cryptosporidium , adenovirus, eaeA ( E. coli ), ipaH ( Shigella ), and spvC ( Salmonella ) were found in at least 20% of samples collected for pathogens at five sites. The presence or absence of the three bacterial genes was related to some of the model variables but was not consistently related to E. coli concentrations. Predictive models were not effective at all inland lake sites; however, their use at two lakes with high swimmer densities will provide better estimates of public health risk than current methods and will be a valuable resource for beach managers and the public.

Ohio↗

Communication strategy of the U.S. Geological Survey Hawaiian Volcano Observatory during the lava-flow crisis of 2014–2015, Kilauea Volcano, Hawaii

In 2014–2015, a slow-moving pāhoehoe lava flow from the remote Pu‘u ‘Ō‘ō vent on Kīlauea Volcano advanced 20 km into populated areas of the Puna District on the Island of Hawai‘i. The staff of the U.S. Geological Survey’s (USGS) Hawaiian Volcano Observatory (HVO) mobilized their resources to closely monitor the flow and provide up-to-date information to the Hawai‘i County Civil Defense (HCCD) agency, the public, and the news media. Scientists issued formal USGS notifications about the flow and Kīlauea’s two eruptions, prepared maps and annotated photographs, infrared images, and videos for dissemination online, and wrote weekly “Volcano Watch” articles for local newspapers. They also provided regular briefings for federal, state, and county agency representatives, answered questions during near-daily briefings with local and national media, and offered information through an established lecture series and participation in community emergency preparedness fairs. Noteworthy among the communication activities was a series of public meetings organized by the Hawai‘i County mayor’s office and led by the HCCD administrator. The meetings were a regular forum for many HVO scientists to talk directly and frequently with residents, business owners, elected officials, and other stakeholders about their concerns, the evolving status of the eruptions, and the uncertain prognosis of the flow’s advance and extent. The dialogue was essential for HVO staff to describe their observations and insights about the lava flow’s behavior and to gain credibility with the community during the crisis. This experience suggests that personal engagement with people at risk from future lava flows in Hawai‘i and elsewhere in the world will remain a crucial part of an eruption response, even with greater capability to disseminate warnings and information digitally via the Internet.

Hawaii↗

Foreward: Geology Field Trips in and around the U.S. Capital

The first annual meeting of the Geological Society of America (GSA) was held in 1888 in Ithaca, New York (Fairchild, 1932), but official Sections of GSA formed much later. During the spring of 1949, a symposium in Knoxville, Tennessee, on mineral resources of the southeastern United States became the catalyst for the creation of the Southeastern Section of the Geological Society of America (King, 1964), and the first annual meeting of the Southeastern Section was held in 1952 in Roanoke, Virginia (Wilson, 1954). The Northeastern Section formed much later, and its first annual meeting was held in 1966 in Philadelphia, Pennsylvania (Socolow, 1968). At all of these section meetings, field trips have been important venues for geologists and especially students to gather together, examine rocks in the field, and discuss ideas. These field trips have been especially important at combined section meetings because they provide settings for geologists who are experienced in one geographic region to examine and compare the geology of other regions. The first combined meeting of the Southeastern and Northeastern sections occurred in 1976 in Arlington, Virginia. Since then, the Southeastern and Northeastern sections have met together on numerous occasions, including 1982 in Washington, DC; 1991 in Baltimore, Maryland; 2004 in Tysons Corner, Virginia; and 2010 in Baltimore, Maryland. Since the first combined section meeting in 1976, there has been a gradual increase in the role of technology in geology field studies. In fact, during the past several decades there has been an increase in emphasis in our society on the instrumental component of science, the goal of which is operational techniques to do or control things, and a corresponding decrease in emphasis on the natural philosophy component of science, the goal of which is a greater understanding of the natural world (Dear, 2006). The modern education acronym STEM (Science, Technology, Engineering, and Mathematics), for example, is often used as a catch-all term that implies that science and technology are relatively synonymous, and implies that greater technology leads automatically to greater understanding of the natural world. This assumption, however, is not always valid (Dear, 2006), and technology should not be promoted as a substitute for field experiences. Technology can be a tool that leads to greater understanding of the natural world, but not all Science uses technology as a means of providing greater understanding. The benefits of new technologies include: (1) data of greater resolution; and (2) greater efficiency of capturing, storing, and visualizing data. The risks of new technologies include: (1) an overabundance of data, some of which may be of little value; (2) less time available for analysis of data, if geologists become occupied primarily with capturing and storing data; and (3) errors that arise from complacency and the perception that field-checking may not be necessary. In other words, there is a risk that a glut of data and vast amounts of time devoted to the capturing and storing of data may result in a reduced interest and (or) willingness to field-check data. In the spirit of the early GSA section meetings, we feel that there are still enormous advantages to conducting geology field trips in conjunction with traditional meeting presentations and posters. In 2020, with this current combined Southeastern and Northeastern section meeting in Reston, Virginia, we have assembled eight different field trips that cover a wide range of territory in and around the Nation’s capital. These field trip localities include the immediate vicinity of Washington, DC, as well as various locations in nearby areas of Virginia, Maryland, and West Virginia. The physiographic provinces include Mesozoic Rift Basins, the Piedmont, the Blue Ridge, the Valley and Ridge, and the Allegheny Plateau of the Appalachian Basin. The field trip sites exhibit a wide range of igneous, metamorphic, and sedimentary rocks, as well as rocks with a wide range of geologic ages from the Mesoproterozoic to the Holocene. We hope that this guidebook provides new motivation for geologists to examine rocks in the field, to discuss ideas with colleagues in the field, and to avoid becoming complacent. The editors of this volume would like to thank the authors of the different field trip guides, the field trip leaders, and all of the reviewers who made suggestions for improving the field trip manuscripts. The editors would also like to thank Elle Derwent of GSA for her logistical help and guidance regarding the field trips, and April Leo and the staff of the GSA Publications Department for seeing this book through to publication.

Maryland, Virginia, West Virginia↗

Rapid 3-D analysis of rockfalls

Recent fatal and damaging rockfalls in Yosemite National Park indicate the need for rapid response data collection methods to inform public safety and assist with management response. Here we show the use of multiple-platform remote sensing methods to rapidly capture pertinent data needed to inform management and the public following a several large rockfalls from El Capitan cliff in Yosemite Valley, California.

GSA Today↗

Rare earths: Market disruption, innovation, and global supply chains

Rare earths, sometimes called the vitamins of modern materials, captured public attention when their prices increased more than ten-fold in 2010 and 2011. As prices fell between 2011 and 2016, rare earths receded from public view—but less visibly they became a major focus of innovative activity in companies, government laboratories and universities. Geoscientists worked to better understand the resource base and improve our knowledge about mineral deposits that will be mines in the future. Process engineers carried out research that is making primary production and recycling more efficient. Materials scientists and engineers searched for substitutes that will require fewer or no rare earths while providing properties comparable or superior to those of existing materials. As a result, even though global supply chains are not significantly different now than they were before the market disruption, the innovative activity motivated by the disruption likely will have far-reaching, if unpredictable, consequences for supply chains of rare earths in the future.

Environment and Resources↗

Strain accumulation in western United States

This review is principally concerned with recent geodetic strain measurements in western United States undertaken by the US Geological Survey as part of the earthquake studies program and, as a consequence, is heavily biased toward the author's own publications. Most of the publications reporting crustal-strain measurements in western United States prior to about 1968 have been compiled in one volume (National Geodetic Survey 1973), and more recent work (with complete bibliographies) is summarized in three successive quadrennial reports to the International Union of Geodesy and Geophysics (Meade 1971, Savage 1975, Thatcher 1979b). The following conventions are employed in this paper: Strain, a dimensionless quantity, is reported in units of 10 6 Extension is taken as positive. To distinguish between engineering and tensor shear strain, we denote the former by γ and quote the units as μr ad, whereas the latter is denoted by e and given the units of μ strain. Uncertainties in all cases are quoted as ± one standard deviation.

California↗

Whence Orycteropus? The correct authorship and date for the generic name of the aardvark (Mammalia, Tubulidentata, Orycteropodidae)

All else being equal, the principle of priority in zoological taxonomic nomenclature gives precedence to the earliest name for a particular taxon. Determining the origin of some late eighteenth- and early nineteenth-century taxonomic names, however, can be vexing, particularly when the history of a name was never completely documented in contemporary synonymies. The authorship and date for Orycteropus Étienne Geoffroy Saint-Hilaire, 1796: 102, the genus-group name for the African aardvark, Orycteropus afer (Pallas, 1766), has been variously ascribed to at least four authors other than É. Geoffroy Saint-Hilaire. Using digitally imaged publications now available in a variety of internet-accessible libraries, I traced the comprehensive history of the name and show how and, to some extent, why its origin became obscured. É. Geoffroy Saint-Hilaire’s original description was re-published twice, most likely to make the description more widely available. Rather than reinforce his authorship for the name, however, the surprising consequence of the multiple publications was to cast doubt on it.

Bionomina↗

Working toward a National Coordinated Soil Moisture Monitoring Network: Vision, progress, and future directions

Soil moisture is a critical land surface variable, impacting the water, energy, and carbon cycles. While in situ soil moisture monitoring networks are still developing, there is no cohesive strategy or framework to coordinate, integrate, or disseminate these diverse data sources in a synergistic way that can improve our ability to understand climate variability at the national, state, and local levels. Thus, a national strategy is needed to guide network deployment, sustainable network operation, data integration and dissemination, and user-focused product development. The National Coordinated Soil Moisture Monitoring Network (NCSMMN) is a federally led, multi-institution effort that aims to address these needs by capitalizing on existing wide-ranging soil moisture monitoring activities, increasing the utility of observational data, and supporting their strategic application to the full range of decision-making needs. The goals of the NCSMMN are to 1) establish a national “network of networks” that effectively demonstrates data integration and operational coordination of diverse in situ networks; 2) build a community of practice around soil moisture measurement, interpretation, and application—a “network of people” that links data providers, researchers, and the public; and 3) support research and development (R&D) on techniques to merge in situ soil moisture data with remotely sensed and modeled hydrologic data to create user-friendly soil moisture maps and associated tools. The overarching mission of the NCSMMN is to provide coordinated high-quality, nationwide soil moisture information for the public good by supporting applications like drought and flood monitoring, water resource management, agricultural and forestry planning, and fire danger ratings.

Bulletin of the American Meteorological Society↗

Two ensemble approaches for forecasting sulfur dioxide concentrations from Kīlauea volcano

Kīlauea volcano, located on the island of Hawaii, is one of the most active volcanoes in the world. It was in a state of nearly continuous eruption from 1983 to 2018 with copious emissions of sulfur dioxide (SO 2 ) that affected public health, agriculture, and infrastructure over large portions of the island. Since 2010, the University of Hawaiʻi at Mānoa provides publicly available vog forecasts that began in 2010 to aid in the mitigation of volcanic smog (or “vog”) as a hazard. In September 2017, the forecast system began to produce operational ensemble forecasts. The months that preceded Kīlauea’s historic lower east rift zone eruption of 2018 provide an opportunity to evaluate the newly implemented air quality ensemble prediction system and compare it another approach to the generation of ensemble members. One of the two approaches generates perturbations in the wind field while the other perturbs the sulfur dioxide (SO 2 ) emission rate from the volcano. This comparison has implications for the limits of forecast predictability under the particularly dynamic conditions at Kīlauea volcano. We show that for ensemble forecasts of SO 2 generated under these conditions, the uncertainty associated with the SO 2 emission rate approaches that of the uncertainty in the wind field. However, the inclusion of a fluctuating SO 2 emission rate has the potential to improve the prediction of the changes in air quality downwind of the volcano with suitable postprocessing.

Hawaii↗

Quantifying nuisance ground motion thresholds for induced earthquakes

Hazards from induced earthquakes are a growing concern with a need for effective management. One aspect of that concern is the “nuisance” from unexpected ground motions, which have the potential to cause public alarm and discontent. In this article, we borrow earthquake engineering concepts to quantify the chance of building damage states and adapt them to quantify felt thresholds for induced earthquakes in the Central and Eastern United States. We compare binary data of felt or not-felt reports from the “Did You Feel It” database with ShakeMap ground motion intensity measures (IM) for ∼360 earthquakes. We use a Monte Carlo logistic regression to discern the likelihood of perceiving various degrees of felt intensity, given a particular IM. These best-fit nuisance functions are reported in this article and are readily transferable. Of the shaking types considered, we find that peak ground velocity tends to be the best predictor of a felt earthquake. We also find that felt thresholds tended to decrease with increasing earthquake magnitude, after M ∼3.9. We interpret this effect as related to the duration of the event, where events smaller than M 3.9 are perceived as “impulsive” to the human senses. Improved quantification of the nuisance from induced earthquake ground motions could be utilized in management of the public perception of their causal operations. Although aimed at anthropogenic earthquakes, thresholds we derive could be useful in other realms, such as establishing best practices and protocols for earthquake early warning.

Earthquake Spectra↗

The US Geological Survey ground failure product: Near-real-time estimates of earthquake-triggered landslides and liquefaction

Since late 2018, the US Geological Survey (USGS) ground failure (GF) earthquake product has provided publicly available spatial estimates of earthquake-triggered landslide and liquefaction hazards, along with the qualitative hazard and population exposure-based alerts for M > 6 earthquakes worldwide and in near real time (within ∼30 min). Earthquake losses are oftentimes greatly aggravated by the impacts due to ground failure, yet those particular events with dramatic additional losses have not, heretofore, been rapidly identifiable. The GF product now provides situational awareness about the potential extent and severity of ground failure in the crucial time period before direct observations are available. We describe our implementation of the GF product and the lessons learned from the earthquakes that have occurred since the GF product was released. We describe the product design process, the underlying GF models, the methods we have developed for modeling uncertainty, and the development of the alert levels. The GF product has been produced in near real time for 320 events over the 2-year period since its public implementation in late 2018 through early 2021. The majority of these events yielded the lowest level (green) alerts for all ground-failure types, with 25 resulting in elevated hazard or exposure to landslides and 47 for liquefaction. In a qualitative comparison between the GF product alerts and GF occurrence information, we found that the product succeeds at assigning appropriate alert levels in the majority of cases. Based on our experience with the product, we have identified the following priorities for future improvements: (1) refinements of the underlying probabilistic models to incorporate severity and explicitly model the type of landslide/liquefaction; (2) development of models for fatalities and economic losses due to ground failure; and (3) estimation of the impacts of ground failure on infrastructure.

Earthquake Spectra↗

The United States Board on Geographic Names: Standardization or regulation?

The United States Board on Geographic Names was created in 1890 to standardize the use of geographic names on federal maps and documents, and was established in its present form in 1947 by public law. The Board is responsible for geographic name usage and application throughout the federal government and its members must approve a name change or new name before it can be applied to federal maps and publications. To accomplish its mission, the Board has developed principles, policies, and procedures for use in the standardization process. The Board is also responsible legally for the promulgation of standardized names, whether or not these names have ever been controversial, and today this is accomplished by the universal availability of electronic databases for domestic and foreign names. This paper examines the development of Board policies and the implementation of these policies to achieve standardization with a view to relating these policies and activities to questions of standardization or regulation.

Names↗

Variations in community exposure to lahar hazards from multiple volcanoes in Washington State (USA)

Understanding how communities are vulnerable to lahar hazards provides critical input for effective design and implementation of volcano hazard preparedness and mitigation strategies. Past vulnerability assessments have focused largely on hazards posed by a single volcano, even though communities and officials in many parts of the world must plan for and contend with hazards associated with multiple volcanoes. To better understand community vulnerability in regions with multiple volcanic threats, we characterize and compare variations in community exposure to lahar hazards associated with five active volcanoes in Washington State, USA—Mount Baker, Glacier Peak, Mount Rainier, Mount Adams and Mount St. Helens—each having the potential to generate catastrophic lahars that could strike communities tens of kilometers downstream. We use geospatial datasets that represent various population indicators (e.g., land cover, residents, employees, tourists) along with mapped lahar-hazard boundaries at each volcano to determine the distributions of populations within communities that occupy lahar-prone areas. We estimate that Washington lahar-hazard zones collectively contain 191,555 residents, 108,719 employees, 433 public venues that attract visitors, and 354 dependent-care facilities that house individuals that will need assistance to evacuate. We find that population exposure varies considerably across the State both in type (e.g., residential, tourist, employee) and distribution of people (e.g., urban to rural). We develop composite lahar-exposure indices to identify communities most at-risk and communities throughout the State who share common issues of vulnerability to lahar-hazards. We find that although lahars are a regional hazard that will impact communities in different ways there are commonalities in community exposure across multiple volcanoes. Results will aid emergency managers, local officials, and the public in educating at-risk populations and developing preparedness, mitigation, and recovery plans within and across communities.

Washington↗

The global environmental agenda urgently needs a semantic web of knowledge

Progress in key social-ecological challenges of the global environmental agenda (e.g., climate change, biodiversity conservation, Sustainable Development Goals) is hampered by a lack of integration and synthesis of existing scientific evidence. Facing a fast-increasing volume of data, information remains compartmentalized to pre-defined scales and fields, rarely building its way up to collective knowledge. Today's distributed corpus of human intelligence, including the scientific publication system, cannot be exploited with the efficiency needed to meet current evidence synthesis challenges; computer-based intelligence could assist this task. Artificial Intelligence (AI)-based approaches underlain by semantics and machine reasoning offer a constructive way forward, but depend on greater understanding of these technologies by the science and policy communities and coordination of their use. By labelling web-based scientific information to become readable by both humans and computers, machines can search, organize, reuse, combine and synthesize information quickly and in novel ways. Modern open science infrastructure—i.e., public data and model repositories—is a useful starting point, but without shared semantics and common standards for machine actionable data and models, our collective ability to build, grow, and share a collective knowledge base will remain limited. The application of semantic and machine reasoning technologies by a broad community of scientists and decision makers will favour open synthesis to contribute and reuse knowledge and apply it toward decision making.

Environmental Evidence↗

A benchmark for computational analysis of animal behavior, using animal-borne tags

Background Animal-borne sensors (‘bio-loggers’) can record a suite of kinematic and environmental data, which are used to elucidate animal ecophysiology and improve conservation efforts. Machine learning techniques are used for interpreting the large amounts of data recorded by bio-loggers, but there exists no common framework for comparing the different machine learning techniques in this domain. This makes it difficult to, for example, identify patterns in what works well for machine learning-based analysis of bio-logger data. It also makes it difficult to evaluate the effectiveness of novel methods developed by the machine learning community. Methods To address this, we present the Bio-logger Ethogram Benchmark (BEBE), a collection of datasets with behavioral annotations, as well as a modeling task and evaluation metrics. BEBE is to date the largest, most taxonomically diverse, publicly available benchmark of this type, and includes 1654 h of data collected from 149 individuals across nine taxa. Using BEBE, we compare the performance of deep and classical machine learning methods for identifying animal behaviors based on bio-logger data. As an example usage of BEBE, we test an approach based on self-supervised learning. To apply this approach to animal behavior classification, we adapt a deep neural network pre-trained with 700,000 h of data collected from human wrist-worn accelerometers. Results We find that deep neural networks out-perform the classical machine learning methods we tested across all nine datasets in BEBE. We additionally find that the approach based on self-supervised learning out-performs the alternatives we tested, especially in settings when there is a low amount of training data available. Conclusions In light of these results, we are able to make concrete suggestions for designing studies that rely on machine learning to infer behavior from bio-logger data. Therefore, we expect that BEBE will be useful for making similar suggestions in the future, as additional hypotheses about machine learning techniques are tested. Datasets, models, and evaluation code are made publicly available at https://github.com/earthspecies/BEBE , to enable community use of BEBE.

Movement Ecology↗