Noise pollution is pervasive in U.S. protected areas Buxton, Rachel T.; McKenna, Megan F.; Mennitt, Daniel ...
Science (American Association for the Advancement of Science),
05/2017, Letnik:
356, Številka:
6337
Journal Article
Recenzirano
Anthropogenic noise threatens ecological systems, including the cultural and biodiversity resources in protected areas. Using continental-scale sound models, we found that anthropogenic noise doubled ...background sound levels in 63% of U.S. protected area units and caused a 10-fold or greater increase in 21%, surpassing levels known to interfere with human visitor experience and disrupt wildlife behavior, fitness, and community composition. Elevated noise was also found in critical habitats of endangered species, with 14% experiencing a 10-fold increase in sound levels. However, protected areas with more stringent regulations had less anthropogenic noise. Our analysis indicates that noise pollution in protected areas is closely linked with transportation, development, and extractive land use, providing insight into where mitigation efforts can be most effective.
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.
Passive acoustic monitoring could be a powerful way to assess biodiversity across large spatial and temporal scales. However, extracting meaningful information from recordings can be prohibitively ...time consuming. Acoustic indices (i.e., a mathematical summary of acoustic energy) offer a relatively rapid method for processing acoustic data and are increasingly used to characterize biological communities. We examined the relationship between acoustic indices and the diversity and abundance of biological sounds in recordings. We reviewed the acoustic-index literature and found that over 60 indices have been applied to a range of objectives with varying success. We used 36 of the most indicative indices to develop a predictive model of the diversity of animal sounds in recordings. Acoustic data were collected at 43 sites in temperate terrestrial and tropical marine habitats across the continental United States. For terrestrial recordings, random-forest models with a suite of acoustic indices as covariates predicted Shannon diversity, richness, and total number of biological sounds with high accuracy (R² ≥ 0.94, mean squared error MSE ≤ 170.2). Among the indices assessed, roughness, acoustic activity, and acoustic richness contributed most to the predictive ability of models. Performance of index models was negatively affected by insect, weather, and anthropogenic sounds. For marine recordings, random-forest models poorly predicted Shannon diversity, richness, and total number of biological sounds (R² ≤ 0.40, MSE ≥ 195). Our results suggest that using a combination of relevant acoustic indices in a flexible model can accurately predict the diversity of biological sounds in temperate terrestrial acoustic recordings. Thus, acoustic approaches could be an important contribution to biodiversity monitoring in some habitats. El monitoreo acústico pasivo podría ser una manera poderosa de evaluar la biodiversidad en escalas temporales y espaciales grandes. Sin embargo, la extracción de información significativa a partir de grabaciones puede ser inasequible y requerir de mucho tiempo. Los índices acústicos (es decir, un resumen matemático de la energía acústica) proporcionan un método relativamente rápido para procesar los datos acústicos y cada vez se usan más para caracterizar las comunidades biológicas. Examinamos la relación entre los índices acústicos y la diversidad y abundancia de sonidos biológicos en las grabaciones. Revisamos la bibliografía sobre el índice de acústica y encontramos que más de 60 índices han sido aplicados a una gama de objetivos con éxito variante. Usamos 36 de los índices más indicativos para desarrollar un modelo predictivo de la diversidad de sonidos de animales en las grabaciones. Se recolectaron datos acústicos en 43 sitios en habitats terrestres templados y marinos tropicales en todos los Estados Unidos continentales. Para las grabaciones terrestres, los modelos de bosques aleatorios junto con un juego de índices acústicos como covariantes predijeron la diversidad de Shannon, la riqueza y el número total de sonidos biológicos con una certeza elevada (R² ≥ 0.94, error medio al cuadrado MSE ≤ 170.2). Entre los índices que se evaluaron, la desigualdad, la actividad acústica y la riqueza acústica fueron los que más contribuyeron a la habilidad predictiva de los modelos. El desempeño de los modelos de índices fue afectado negativamente por sonidos de insectos, del clima y de origen humano. Para las grabaciones marinas, los modelos de bosque aleatorio predijeron pobremente la diversidad de Shannon, la riqueza y el número total de sonidos biológicos (R² ≤ 0.40, MSE ≥ 195). Nuestros resultados sugieren que el uso de una combinación de índices acústicos relevantes dentro de un modelo flexible puede predecir con exactitud la diversidad de los sonidos biológicos en un registro acústico de un habitat terrestre templado. Así, las estrategias acústicas podrían ser una contribución importante para el monitoreo de la biodiversidad en algunos habitats. 被动的声音监测可以跨越较大的时空尺度有效地评估生物多祥性。然而，从录音中提取有意义的信息可 能会非常耗时。声学指标（即对声能的数学总结) 提供了一种相对快速地处理声学数据的方法，正越来越多地 被用于描述生物群落的特征。我们检验了声学指标与录音中生物声音的多祥性和丰度之间的关系。通过对声学 指标文献的综述，我们找到了超过 60 个用于不同目的的声学指标，成效不一。我们选用了 36 个最具指示性的 指标，以建立录音中动物声音多祥性的预测模型。声学数据来自美国大陆的温带陆地和热带海洋生境的 43 个 位点。在陆地的录音中，含有一系列声学指标作为协变量的随机森林模型可以精准地预测香农多样性、丰富度 和生物声音的总数 (R² ≥ 0.94，平均方差 MSE ≤ 170.2)。在我们评估的指标中，声音的粗糖度、活动性和丰富 度对模型预测能力贡献最大。指数模型的效果会受到昆虫、天气和人类活动声音的负面影响。对于海洋录音来 说，随机森林模型对香农多祥性、丰富度和生物声音总数的预测结果不佳(R² ≤ 0.40, MSE ≥ 195) 。我们的结 果表明，在模型中灵活运用相关声学指标的组合可以准确预测温带陆地生态系统录音的生物声音多祥性。因此， 声学方法可以为某些生境的生物多祥性监测做出重要贡献。
Low-frequency ocean ambient noise is dominated by noise from commercial ships, yet understanding how individual ships contribute deserves further investigation. This study develops and evaluates ...statistical models of container ship noise in relation to design characteristics, operational conditions, and oceanographic settings. Five-hundred ship passages and nineteen covariates were used to build generalized additive models. Opportunistic acoustic measurements of ships transiting offshore California were collected using seafloor acoustic recorders. A 5-10 dB range in broadband source level was found for ships depending on the transit conditions. For a ship recorded multiple times traveling at different speeds, cumulative noise was lowest at 8 knots, 65% reduction in operational speed. Models with highest predictive power, in order of selection, included ship speed, size, and time of year. Uncertainty in source depth and propagation affected model fit. These results provide insight on the conditions that produce higher levels of underwater noise from container ships.
Mid-frequency military (1–10 kHz) sonars have been associated with lethal mass strandings of deep-diving toothed whales, but the effects on endangered baleen whale species are virtually unknown. ...Here, we used controlled exposure experiments with simulated military sonar and other mid-frequency sounds to measure behavioural responses of tagged blue whales (Balaenoptera musculus) in feeding areas within the Southern California Bight. Despite using source levels orders of magnitude below some operational military systems, our results demonstrate that mid-frequency sound can significantly affect blue whale behaviour, especially during deep feeding modes. When a response occurred, behavioural changes varied widely from cessation of deep feeding to increased swimming speed and directed travel away from the sound source. The variability of these behavioural responses was largely influenced by a complex interaction of behavioural state, the type of mid-frequency sound and received sound level. Sonar-induced disruption of feeding and displacement from high-quality prey patches could have significant and previously undocumented impacts on baleen whale foraging ecology, individual fitness and population health.
For many marine organisms, especially large whales that cannot be studied in laboratory settings, our ability to obtain basic behavioral and physiological data is limited, because these organisms ...occupy offshore habitats and spend a majority of their time underwater. A class of multisensor, suction-cup-attached archival tags has revolutionized the study of large baleen whales, particularly with respect to the predatory strategies used by these gigantic bulk filter feeders to exploit abundant oceanic resources. By integrating these data with those from other disciplines, researchers have uncovered a diverse and extraordinary set of underwater behaviors, ranging from acrobatic diving maneuvers to extreme feeding events during which whales engulf volumes of prey-laden water that are much larger than their own body. This research framework not only improves our knowledge of the individual performance and behavior of these keystone predators but also informs our ability to understand the dynamics of complex marine ecosystems.
Global expansion of human activities is associated with the introduction of novel stimuli, such as anthropogenic noise, artificial lights and chemical agents. Progress in documenting the ecological ...effects of sensory pollutants is weakened by sparse knowledge of the mechanisms underlying these effects. This severely limits our capacity to devise mitigation measures. Here, we integrate knowledge of animal sensory ecology, physiology and life history to articulate three perceptual mechanisms-masking, distracting and misleading-that clearly explain how and why anthropogenic sensory pollutants impact organisms. We then link these three mechanisms to ecological consequences and discuss their implications for conservation. We argue that this framework can reveal the presence of 'sensory danger zones', hotspots of conservation concern where sensory pollutants overlap in space and time with an organism's activity, and foster development of strategic interventions to mitigate the impact of sensory pollutants. Future research that applies this framework will provide critical insight to preserve the natural sensory world.
Behavior represents animals’ primary means of responding to environmental variation and adapting to rapid environmental change.Many animals’ presence, let alone behavior, is highly cryptic to human ...observers, presenting a significant barrier in both theoretical and applied behavioral ecology.Bioacoustic signals not only reveal animals’ presence, but also encode detailed information about the behaviors in which they are engaging.The study of behavioral bioacoustics has emerged to decipher the context and function of animal sounds and to apply this comprehension to understanding animal behavior across ecological scales and levels of biological organization.Growing capacity for behavioral bioacoustics represents a profound opportunity to understand animal behavior and steward rapidly changing ecosystems in the Anthropocene.
Interpreting sound gives powerful insight into the health of ecosystems. Beyond detecting the presence of wildlife, bioacoustic signals can reveal their behavior. However, behavioral bioacoustic information is underused because identifying the function and context of animals’ sounds remains challenging. A growing acoustic toolbox is allowing researchers to begin decoding bioacoustic signals by linking individual and population-level sensing. Yet, studies integrating acoustic tools for behavioral insight across levels of biological organization remain scarce. We aim to catalyze the emerging field of behavioral bioacoustics by synthesizing recent successes and rising analytical, logistical, and ethical challenges. Because behavior typically represents animals’ first response to environmental change, we posit that behavioral bioacoustics will provide theoretical and applied insights into animals’ adaptations to global change.
Interpreting sound gives powerful insight into the health of ecosystems. Beyond detecting the presence of wildlife, bioacoustic signals can reveal their behavior. However, behavioral bioacoustic information is underused because identifying the function and context of animals’ sounds remains challenging. A growing acoustic toolbox is allowing researchers to begin decoding bioacoustic signals by linking individual and population-level sensing. Yet, studies integrating acoustic tools for behavioral insight across levels of biological organization remain scarce. We aim to catalyze the emerging field of behavioral bioacoustics by synthesizing recent successes and rising analytical, logistical, and ethical challenges. Because behavior typically represents animals’ first response to environmental change, we posit that behavioral bioacoustics will provide theoretical and applied insights into animals’ adaptations to global change.
Matching the timing of life‐history transitions with ecosystem phenology is critical for the survival of many species, especially those undertaking long‐distance migrations. As a result, whether and ...how migratory populations adjust timing of life‐history transitions in response to environmental variability are important questions in ecology and conservation. Yet the flexibility and drivers of life‐history transitions remain largely untested for migratory marine populations, which contend with the unique spatiotemporal dynamics and sensory conditions found in marine ecosystems.
Here, using an acoustic signature of blue whales’ regional population‐level transition from foraging to breeding migration, we document significant interannual flexibility in the timing of this life‐history transition (spanning roughly 4 months) over a continuous 6‐year study period.
We further show that variability in the timing of this transition follows the oceanographic phenology of blue whales’ foraging habitat, with a later transition from foraging to breeding migration occurring in years with an earlier onset, later peak and greater accumulation of biological productivity.
These findings indicate that blue whales delay the transition from foraging to southward migration in years of the highest and most persistent biological productivity, consistent with the hypothesis that this population maximizes energy intake on foraging grounds rather than departing towards breeding grounds as soon as sufficient energy reserves are accumulated.
The use of flexible cues (e.g. foraging conditions and long‐distance acoustic signals) in timing a major life‐history transition may be key to the persistence of this endangered population facing the pressures of rapid environmental change. Furthermore, these results extend theoretical understanding of the flexibility and drivers of population‐level migration to a relatively solitary marine migrant.
Read the free Plain Language Summary for this article on the Journal blog.
Read the free Plain Language Summary for this article on the Journal blog.
Linking individual and population scales is fundamental to many concepts in ecology 1, including migration 2, 3. This behavior is a critical 4 yet increasingly threatened 5 part of the life history ...of diverse organisms. Research on migratory behavior is constrained by observational scale 2, limiting ecological understanding and precise management of migratory populations in expansive, inaccessible marine ecosystems 6. This knowledge gap is magnified for dispersed oceanic predators such as endangered blue whales (Balaenoptera musculus). As capital breeders, blue whales migrate vast distances annually between foraging and breeding grounds, and their population fitness depends on synchrony of migration with phenology of prey populations 7, 8. Despite previous studies of individual-level blue whale vocal behavior via bio-logging 9, 10 and population-level acoustic presence via passive acoustic monitoring 11, detection of the life history transition from foraging to migration remains challenging. Here, we integrate direct high-resolution measures of individual behavior and continuous broad-scale acoustic monitoring of regional song production (Figure 1A) to identify an acoustic signature of the transition from foraging to migration in the Northeast Pacific population. We find that foraging blue whales sing primarily at night, whereas migratory whales sing primarily during the day. The ability to acoustically detect population-level transitions in behavior provides a tool to more comprehensively study the life history, fitness, and plasticity of population behavior in a dispersed, capital breeding population. Real-time detection of this behavioral signal can also inform dynamic management efforts 12 to mitigate anthropogenic threats to this endangered population 13, 14).
•Acoustic monitoring reveals patterns in population-level blue whale song production•Tag-derived metrics provide behavioral context for distinct diel patterns in song•When integrated, tag and acoustic metrics reveal an acoustic signature of migration•Key to discerning timing, plasticity, and drivers of a dispersed migration
Oestreich et al. integrate long-term acoustic monitoring and tag-derived metrics to identify an acoustic signature of blue whales’ transition from foraging to migration. This finding links individual and population-level behavior in a highly dispersed population and is central to discerning timing, plasticity, and drivers of blue whale migration.
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