Uncovering Spatial Variation in Acoustic Environments Using Sound Mapping

Animals select and use habitats based on environmental features relevant to their ecology and behavior. For animals that use acoustic communication, the sound environment itself may be a critical feature, yet acoustic characteristics are not commonly measured when describing habitats and as a result, how habitats vary acoustically over space and time is poorly known. Such considerations are timely, given worldwide increases in anthropogenic noise combined with rapidly accumulating evidence that noise hampers the ability of animals to detect and interpret natural sounds. Here, we used microphone arrays to record the sound environment in three terrestrial habitats (forest, prairie, and urban) under ambient conditions and during experimental noise introductions. We mapped sound pressure levels (SPLs) over spatial scales relevant to diverse taxa to explore spatial variation in acoustic habitats and to evaluate the number of microphones needed within arrays to capture this variation under both ambient and noisy conditions. Even at small spatial scales and over relatively short time spans, SPLs varied considerably, especially in forest and urban habitats, suggesting that quantifying and mapping acoustic features could improve habitat descriptions. Subset maps based on input from 4, 8, 12 and 16 microphones differed slightly (< 2 dBA/pixel) from those based on full arrays of 24 microphones under ambient conditions across habitats. Map differences were more pronounced with noise introductions, particularly in forests; maps made from only 4-microphones differed more (> 4 dBA/pixel) from full maps than the remaining subset maps, but maps with input from eight microphones resulted in smaller differences. Thus, acoustic environments varied over small spatial scales and variation could be mapped with input from 4–8 microphones. Mapping sound in different environments will improve understanding of acoustic environments and allow us to explore the influence of spatial variation in sound on animal ecology and behavior.动物会依据与其生态及行为相关的环境特征，选择并利用栖息地。对于依赖声学通讯的动物而言，声音环境本身或许是其栖息地的关键特征之一，但在常规的栖息地描述中，声学特征却鲜有被纳入测量范畴；这也导致我们对栖息地声学特征在空间与时间维度上的变化规律认知匮乏。当前，全球范围内人为噪声持续加剧，且越来越多的研究证据表明噪声会干扰动物检测与解读自然声音的能力，因此此类研究的现实意义愈发凸显。本研究中，我们借助麦克风阵列（microphone arrays），在森林、草原与城市三种陆地生境的背景环境条件，以及人工引入噪声的实验场景下，分别录制其声音环境。我们针对与多样生物类群相关的空间尺度，绘制了声压级（sound pressure levels, SPLs）分布图，以此探究声学栖息地的空间变异特征，并评估在背景环境与噪声环境下，麦克风阵列所需的麦克风数量以精准捕捉此类声学变异。即便在较小的空间尺度与相对短暂的时间跨度内，声压级也会出现显著波动，尤以森林与城市生境为甚；这表明量化并绘制声学特征，或可优化栖息地描述的准确性与全面性。在背景环境条件下，基于4、8、12和16个麦克风采集数据生成的子集分布图，与基于24个麦克风的完整阵列生成的分布图之间的差异极小（各生境的差异均小于2 dBA/像素）。而在人工引入噪声后，分布图间的差异更为显著，尤以森林生境为最：仅使用4个麦克风生成的分布图与完整分布图的差异更大（大于4 dBA/像素），其余子集分布图的差异则相对较小；但使用8个麦克风采集数据生成的分布图，其与完整分布图的差异已进一步缩小。综上，声学环境在较小的空间尺度上存在显著变异，且此类变异可通过4~8个麦克风的采集数据进行精准绘制。对不同环境中的声音进行绘图分析，将有助于我们深化对声学环境的认知，并进一步探索声音的空间变异对动物生态与行为的影响。