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標題：Wildlife被動聲學記錄器論文：森林景觀的聲學多樣性：與棲息地結(jié)構(gòu)和人為壓力的關(guān)系
Abstract
Understanding how human-dominated landscapes affect biodiversity and ecosystems is essential for effective conservation planning. This work aims to understand the relationship between the acoustic diversity of forested landscapes, and descriptors of habitat structure, composition, and anthropogenic pressure, as well as to identify the characteristic scale at which acoustic community diversity relates to those metrics in central Massachusetts.
Ten passive acoustic recorders were placed within forest areas in central Massachusetts, during the breeding season. Mono audio recordings were collected during the dawn chorus. The relationship between acoustic indices (AI), and core habitat quality, connectivity, vegetation productivity, percent tree cover, human edge, artificial illumination, and traffic noise were assessed.
Significant relationships were found between AI and variables related to habitat structure and human pressure. Sounds related to biota (biophony) and acoustic complexity were positively correlated with core habitat quality, connectivity, and vegetation while negatively correlated with human pressure variables, including nighttime lights, traffic noise, and human edge. AI can therefore act as successful indicators of habitat quality in highly modified landscapes The highest correlations were found at buffers between 1.5 and 3 Km. This response of AI to the broad spatial context and not to the local site characteristics indicate that they can act as robust landscape-scale indicators.
The large characteristic scale indicates that urban planning should consider potential impacts acting at scales beyond site planning. Moreover, conservation planning can benefit from managing the context matrix to support biodiversity, particularly traffic noise and artificial illumination reduction initiatives.
摘要：
了解人類主導的景觀如何影響生物多樣性和生態(tài)系統(tǒng)對于有效的保護規(guī)劃至關(guān)重要。這項工作旨在了解森林景觀的聲學多樣性與棲息地結(jié)構(gòu)、組成和人為壓力的描述符之間的關(guān)系，并確定聲學群落多樣性與馬薩諸塞州中部這些指標相關(guān)的特征尺度。
在繁殖季節(jié)，在馬薩諸塞州中部的森林地區(qū)放置了10臺被動錄音機。黎明合唱時收集了單聲道錄音。評估了聲學指數(shù)（AI）與核心棲息地質(zhì)量、連通性、植被生產(chǎn)力、樹木覆蓋率、人類邊緣、人工照明和交通噪聲之間的關(guān)系。
人工智能與棲息地結(jié)構(gòu)和人類壓力相關(guān)變量之間存在顯著關(guān)系。與生物群（生物聲學）和聲學復雜性相關(guān)的聲音與核心棲息地質(zhì)量、連通性和植被呈正相關(guān)，與人類壓力變量呈負相關(guān)，包括夜間燈光、交通噪音和人類邊緣。因此，人工智能可以作為高度修飾景觀中棲息地質(zhì)量的成功指標。在1.5至3公里的緩沖區(qū)發(fā)現(xiàn)了最高的相關(guān)性。人工智能對廣泛的空間背景而不是當?shù)貓龅靥卣鞯姆磻?yīng)表明，它們可以作為穩(wěn)健的景觀尺度指標。
大的特征尺度表明，城市規(guī)劃應(yīng)考慮在場地規(guī)劃之外的尺度上可能產(chǎn)生的影響。此外，保護規(guī)劃可以從管理背景矩陣中受益，以支持生物多樣性，特別是交通噪音和人工照明減少舉措。
關(guān)鍵詞：Wildlife被動聲學記錄器，聲學追蹤監(jiān)測，野生動物聲學監(jiān)測，聲學分析軟件，野外聲學記錄
