Emma Brown

Bio: Emma Brown is an academic researcher from National Park Service. The author has contributed to research in topics: Noise pollution & Noise. The author has an hindex of 4, co-authored 5 publications receiving 449 citations.

A synthesis of two decades of research documenting the effects of noise on wildlife

Abstract: Global increases in environmental noise levels – arising from expansion of human populations, transportation networks, and resource extraction – have catalysed a recent surge of research into the effects of noise on wildlife. Synthesising a coherent understanding of the biological consequences of noise from this literature is challenging. Taxonomic groups vary in auditory capabilities. A wide range of noise sources and exposure levels occur, and many kinds of biological responses have been observed, ranging from individual behaviours to changes in ecological communities. Also, noise is one of several environmental effects generated by human activities, so researchers must contend with potentially confounding explanations for biological responses. Nonetheless, it is clear that noise presents diverse threats to species and ecosystems and salient patterns are emerging to help inform future natural resource-management decisions. We conducted a systematic and standardised review of the scientific literature published from 1990 to 2013 on the effects of anthropogenic noise on wildlife, including both terrestrial and aquatic studies. Research to date has concentrated predominantly on European and North American species that rely on vocal communication, with approximately two-thirds of the data set focussing on songbirds and marine mammals. The majority of studies documented effects from noise, including altered vocal behaviour to mitigate masking, reduced abundance in noisy habitats, changes in vigilance and foraging behaviour, and impacts on individual fitness and the structure of ecological communities. This literature survey shows that terrestrial wildlife responses begin at noise levels of approximately 40 dBA, and 20% of papers documented impacts below 50 dBA. Our analysis highlights the utility of existing scientific information concerning the effects of anthropogenic noise on wildlife for predicting potential outcomes of noise exposure and implementing meaningful mitigation measures. Future research directions that would support more comprehensive predictions regarding the magnitude and severity of noise impacts include: broadening taxonomic and geographical scope, exploring interacting stressors, conducting larger-scale studies, testing mitigation approaches, standardising reporting of acoustic metrics, and assessing the biological response to noise-source removal or mitigation. The broad volume of existing information concerning the effects of anthropogenic noise on wildlife offers a valuable resource to assist scientists, industry, and natural-resource managers in predicting potential outcomes of noise exposure.

Using bioacoustics to examine shifts in songbird phenology.

Abstract: Monitoring patterns in biodiversity and phenology have become increasingly important given accelerating levels of anthropogenic change. Long-term monitoring programs have reported earlier occurrence of spring activity, reflecting species response to climate change. Although tracking shifts in spring migration represents a valuable approach to monitoring community-level consequences of climate change, robust long-term observations are challenging and costly. Audio recordings and metrics of bioacoustic activity could provide an effective method for monitoring changes in songbird activity and broader biotic interactions. We used 3 years of spring and fall recordings at six sites in Glacier Bay National Park, Alaska, an area experiencing rapid warming and glacial retreat, to examine the utility of bioacoustics to detect changes in songbird phenology. We calculated the Acoustic Complexity Index (ACI), an algorithm representing an index of bird community complexity. Abrupt changes in ACI values from winter to spring corresponded to spring transition, suggesting that ACI may be an effective, albeit coarse metric to detect the arrival of migrating songbirds. The first peak in ACI shifted from April 16 to April 11 from 2012 to 2014. Changes in ACI were less abrupt in the fall due to weather events, suggesting spring recordings are better suited to indicate phenology. To ensure changes in ACI values were detecting real changes in songbird activity, we explored the relationship between ACI and song of three species: varied thrush (Ixoreus naevius), Pacific wren (Troglodytes pacificus), and ruby-crowned kinglet (Regulus calendula). ACI was positively related to counts of all species, but most markedly with song of the varied thrush, the most common species in our recordings and a known indicator of forest ecosystem health. We conclude that acoustic recordings paired with bioacoustic indices may be a useful method of monitoring shifts in songbird communities due to climate change and other sources of anthropogenic disturbance.

Anthropogenic noise in US national parks – sources and spatial extent

Abstract: T US National Park Service (NPS) was established over a century ago to conserve natural and cultural resources. As the first system of federally protected areas in the world, US national parks have shaped a global standard for protected areas. Since NPS’s inception, the US population has more than tripled, road and aircraft traffic have become widespread, and 80% of the US population now lives in urban areas (Barber et al. 2010). In this context, national parks represent refuges of ecological integrity and provide increasingly important opportunities for people to establish personal connections with natural environments (Miller 2005; Machlis and McNutt 2015). This rapid increase in infrastructure, transportation networks, and human activity has resulted in the widespread distribution of anthropogenic noise (hereafter “noise”), even in the most remote protected areas of the US (Figure 1; Buxton et al. 2017a). At high levels of exposure, noise annoys people and contributes to health problems (Basner et al. 2014). At lower levels of exposure, noise reduces the benefits of experiencing natural sounds, which include increased relaxation, restored attention, improved mood, and reduced stress (Benfield et al. 2014; Abbott et al. 2016). Noise also affects wildlife, masking critical sounds (including incidental signals such as the sound of predators approaching) and increasing perceived risk, causing changes in behavior, physiology, and fitness (reviewed in Shannon et al. [2016]). Moreover, the responses of individual species to noise extend through ecological interactions to alter community structure and ecosystem function (Francis et al. 2012). Despite its known impacts on natural systems, noise is rarely considered alongside other pervasive threats to protected areas (Butchart et al. 2010). Congressional concerns about noise in national parks have been expressed through legislation since 1975, and NPS policy requires the management of noise and conservation of acoustic resources (NPS 2006). Accordingly, NPS has been identifying noise sources, measuring not only how often they are heard but also sound levels at hundreds of sites over the past two decades, resulting in a unique, spatially diverse acoustic dataset. This study is the first comprehensive analysis of all noise sources in national parks across the US. More specifically, we identify the causes of continentalscale patterns of noise exposure (Buxton et al. 2017a) by analyzing the identities and characteristics of noise sources audible in national park units and relating these outputs to landscapescale summaries of acoustic conditions inside national parks. The results document (1) the loudest and most frequent sources of noise and the anthropogenic features associated with them, (2) which of these sources predict landscape levels of noise estimated using geospatial models, and (3) summaries of these noise metrics across different protection categories (ie park type, wilderness areas, and critical habitat of US endangered species). We relate this diagnosis of noise across different park contexts with emerging approaches to mitigate noise pollution, aiming to identify management strategies that preserve or restore natural soundscape experiences for park visitors and wildlife.

On-animal acoustic monitoring provides insight to ungulate foraging behavior

Abstract: Foraging behavior underpins many ecological processes; however, robust assessments of this behavior for free-ranging animals are rare due to limitations to direct observations. We leveraged acoustic monitoring and GPS tracking to assess the factors influencing foraging behavior of mule deer (Odocoileus hemionus). We deployed custom-built acoustic collars with GPS radiocollars on mule deer to measure location-specific foraging. We quantified individual bites and steps taken by deer, and quantified two metrics of foraging behavior: the number of bites taken per step and the number of bites taken per unit time, which relate to foraging intensity and efficiency. We fit statistical models to these metrics to examine the individual, environmental, and anthropogenic factors influencing foraging. Deer in poorer body condition took more bites per step and per minute and foraged for longer irrespective of landscape properties. Other patterns varied seasonally with major changes in deer condition. In December, when deer were in better condition, they took fewer bites per step and more bites per minute. Deer also foraged more intensely and efficiently in areas of greater forage availability and greater movement costs. During March, when deer were in poorer condition, foraging was not influenced by landscape features. Anthropogenic factors weakly structured foraging behavior in December with no relationship in March. Most research on animal foraging is interpreted under the framework of optimal foraging theory. Departures from predictions developed under this framework provide insight to unrecognized factors influencing the evolution of foraging. Our results only conformed to our predictions when deer were in better condition and ecological conditions were declining, suggesting foraging strategies were state-dependent. These results advance our understanding of foraging patterns in wild animals and highlight novel observational approaches for studying animal behavior.

Citation classic - optimal foraging - a selective review of theory and tests

Abstract: Beginning with Emlen (1966) and MacArthur and Pianka (1966) and extending through the last ten years, several authors have sought to predict the foraging behavior of animals by means of mathematical models. These models are very similar,in that they all assume that the fitness of a foraging animal is a function of the efficiency of foraging measured in terms of some "currency" (Schoener, 1971) -usually energy- and that natural selection has resulted in animals that forage so as to maximize this fitness. As a result of these similarities, the models have become known as "optimal foraging models"; and the theory that embodies them, "optimal foraging theory." The situations to which optimal foraging theory has been applied, with the exception of a few recent studies, can be divided into the following four categories: (1) choice by an animal of which food types to eat (i.e., optimal diet); (2) choice of which patch type to feed in (i.e., optimal patch choice); (3) optimal allocation of time to different patches; and (4) optimal patterns and speed of movements. In this review we discuss each of these categories separately, dealing with both the theoretical developments and the data that permit tests of the predictions. The review is selective in the sense that we emphasize studies that either develop testable predictions or that attempt to test predictions in a precise quantitative manner. We also discuss what we see to be some of the future developments in the area of optimal foraging theory and how this theory can be related to other areas of biology. Our general conclusion is that the simple models so far formulated are supported are supported reasonably well by available data and that we are optimistic about the value both now and in the future of optimal foraging theory. We argue, however, that these simple models will requre much modification, espicially to deal with situations that either cannot easily be put into one or another of the above four categories or entail currencies more complicated that just energy.

A Distributed Snow Evolution Modeling System (SnowModel)

Abstract: SnowModel is a spatially distributed snow-evolution modeling system designed for application in landscapes, climates, and conditions where snow occurs. It is an aggregation of four submodels: MicroMet defines meteorological forcing conditions, EnBal calculates surface energy exchanges, SnowPack simulates snow depth and water-equivalent evolution, and SnowTran-3D accounts for snow redistribution by wind. Since each of these submodels was originally developed and tested for nonforested conditions, details describing modifications made to the submodels for forested areas are provided. SnowModel was created to run on grid increments of 1 to 200 m and temporal increments of 10 min to 1 day. It can also be applied using much larger grid increments, if the inherent loss in high-resolution (subgrid) information is acceptable. Simulated processes include snow accumulation; blowing-snow redistribution and sublimation; forest canopy interception, unloading, and sublimation; snow-density evolution; and snowp...

The soundscape of the Anthropocene ocean.

Abstract: Oceans have become substantially noisier since the Industrial Revolution. Shipping, resource exploration, and infrastructure development have increased the anthrophony (sounds generated by human activities), whereas the biophony (sounds of biological origin) has been reduced by hunting, fishing, and habitat degradation. Climate change is affecting geophony (abiotic, natural sounds). Existing evidence shows that anthrophony affects marine animals at multiple levels, including their behavior, physiology, and, in extreme cases, survival. This should prompt management actions to deploy existing solutions to reduce noise levels in the ocean, thereby allowing marine animals to reestablish their use of ocean sound as a central ecological trait in a healthy ocean.

Anthropogenic noise increases fish mortality by predation

Abstract: Noise-generating human activities affect hearing, communication and movement in terrestrial and aquatic animals, but direct evidence for impacts on survival is rare. We examined effects of motorboat noise on post-settlement survival and physiology of a prey fish species and its performance when exposed to predators. Both playback of motorboat noise and direct disturbance by motorboats elevated metabolic rate in Ambon damselfish (Pomacentrus amboinensis), which when stressed by motorboat noise responded less often and less rapidly to simulated predatory strikes. Prey were captured more readily by their natural predator (dusky dottyback, Pseudochromis fuscus) during exposure to motorboat noise compared with ambient conditions, and more than twice as many prey were consumed by the predator in field experiments when motorboats were passing. Our study suggests that a common source of noise in the marine environment has the potential to impact fish demography, highlighting the need to include anthropogenic noise in management plans.

Terrestrial Passive Acoustic Monitoring: Review and Perspectives

Abstract: Passive acoustic monitoring (PAM) is quickly gaining ground in ecological research, following global trends toward automated data collection and big data. Using unattended sound recording, PAM provides tools for long-term and cost-effective biodiversity monitoring. Still, the extent of the potential of this emerging method in terrestrial ecology is unknown. To quantify its application and guide future studies, we conducted a systematic review of terrestrial PAM, covering 460 articles published in 122 journals (1992–2018). During this period, PAM-related studies showed above a fifteenfold rise in publication and covered three developing phases: establishment, expansion, and consolidation. Overall, the research was mostly focused on bats (50%), occurred in northern temperate regions (65%), addressed activity patterns (25%), recorded at night (37%), used nonprogrammable recorders (61%), and performed manual acoustic analysis (58%), although their applications continue to diversify. The future agenda should include addressing the development of standardized procedures, automated analysis, and global initiatives to expand PAM to multiple taxa and regions.