綜合本研究的結果，建議進行長期聲景監測前，前測是必要的過程，以決 定整體聲景最佳的錄音取樣方法。前測錄音建議進行 24 小時連續錄音取 樣 7 日以上，且包含各棲地樣點。接著計算適合的聲音指數或 BI 指數進 行量化，並設計多種子取樣的錄音方法，可參考本研究在錄音頻度與錄音 覆蓋率為基礎下設計的 16 種取樣方法。再利用本研究的重複取樣分析方 法進行分析，唯須注意 bootstrapping 每次取樣的日數應與前測總日數一 致，所得的最佳錄音覆蓋率是單一季節中的結果，應用在整年監測應將覆 蓋率提高。
如果是需要進行特定聲景的長期監測時，前測也是必要的過程。針對特定 季節的聲景時，所得的最佳錄音覆蓋率即可直接使用；如果是特定聲音群 集的聲景時，可挑選適合的時間區間後，再進行取樣方法的分析。如果沒 有前測的規劃時，則可依研究目的、棲地、季節、聲音群集等資訊參考本 研究的結果，與研究本身錄音、分析與儲存工具的資源做最佳的調整。需 注意的是，本研究的結果與建議是以六種聲音指數的五種每日百分位數為 分析基礎，不一定適用於其他時間尺度、其他聲音指數或其他統計值，因 此，可以根據研究需要便在前測做適當的調整與計算，將能更符合後續聲 景資料收集的需求。整體而言，避免過低的錄音覆蓋率 (6.7%以下)，且 監測目標為跨季節聲景或單一聲音群集聲景時，需使用較高的錄音覆蓋 率。
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第伍章 結論
聲景的組成包含生物、環境與人造音，從聲音的角度提供監測生物多樣性的 另一種方法，已有許多研究證實聲景資訊可應用於生物多樣性的監測與保 育。然而，目前尚未有長期聲景監測錄音取樣方法的研究，不但各研究的錄 音取樣方法不一致，更無法確認哪些取樣資料能完整地反應聲景。本研究在 臺灣北部三種棲地樣點，收集每日完整錄音與整年間隔錄音資料，透過 6 種聲音指數各 5 個百分位數量化聲景特徵，以檢測 6 種錄音覆蓋率下的 16 種錄音頻度(每日完整錄音)與 6 種錄音頻度(整年間隔錄音)之聲景代表性。
結果發現，錄音覆蓋率降低會使錄音取樣的聲景代表性降低，錄音頻度在各 聲景間的影響並不一致，整體聲景適合低頻度，聲音群集聲景適合高頻度。
此外，單一季節相較跨季節能使用較低的錄音覆蓋率達到相近的聲景代表 性，但單一聲音群集相較跨群集則需要更高的錄音覆蓋率方能達到相近的聲 景代表性。本研究建議，使用聲音指數評估長期聲景監測取樣方法時，越高 的錄音覆蓋率原則上越具聲景代表性，但為有效利用資源，可考量進行前 測，找出符合一個地區的研究或管理目標之最佳錄音覆蓋率。在這樣的前測 中，須特別考量季節的影響，因為單一季節的前測資料可能會低估跨季節聲 景監測所需之錄音覆蓋率。本研究利用聲音指數量化聲景特徵以評估不同錄 音取樣方法的代表性，並對未來長期且自動排程錄音的聲景監測工作提供具 體的建議。
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