蝙蝠研究
2019_從聲音性狀探討氣溫變異對臺灣蝙蝠群落組成的影響_陳冠伃
出版年份：2019
研究生：陳冠伃
分類：碩士論文
題目：從聲音性狀探討氣溫變異對臺灣蝙蝠群落組成的影響
Title：Effect of temperature variability on the trait-based community assembly of bats in Taiwan
摘要：
氣候變異會威脅生態系運作及造成生物多樣性的損失，例如溫度變異會影響物種個體、物種關係及群落結構。生物群落的性狀多樣性可以反映該群落提供的生態系統服務及功能，因此性狀多樣性可作為相關系統服務及功能的指標。為了解不同時間尺度下的溫度變異會如何影響生物群落及其性狀組成，本研究利用台灣森林性蝙蝠的回聲定位叫聲性狀，測試以下三個假說。1)環境過濾假說（Environmental filtering）:氣溫變異為環境的篩選因子，篩選出擁有特定性狀值的物種。根據此假說，我預期氣溫變異越大，該群落的性狀值所佔的性狀空間(trait space)會越小。2)競爭假說（Competition）:在不穩定的環境下，物種間的競爭平衡趨向不穩定，因此我預期溫度變異越大，群落的種間競爭壓力越小，造成物種性狀的分化越不明顯。3)氣候變異假說（Climate variability hypothesis）:生存於氣候變異大的物種會有較寬的環境棲位或忍受範圍，因此我預期溫度變異越大，該群落的物種性狀範圍會越大。本研究在臺灣八個地點設置超音波錄音機收集蝙蝠叫聲，並將所有叫聲分類成七大類，以計算三種功能性狀值（群落層級的功能豐富度、功能分散度及物種層級的功能豐富度）。結果顯示，在日間變異尺度下，群落層級的功能性狀豐富度與溫度變異成負相關，支持環境過濾假說；且功能性狀分散度與溫度變異成負相關，支持競爭假說。但在月間變異尺度下，功能性狀分散度與溫度變異成正相關，不支持競爭假說。本研究不支持氣候變異假說，因為在月內及月間變異尺度下，物種層級的功能性狀豐富度與溫度變異成負相關，代表物種的性狀範圍隨溫度變異增加而縮小。綜合以上結果，本研究顯示功能性狀可以幫助我們了解氣候變異會如何影響生物群落的組成，另外，本研究也彰顯出考量不同時間尺度對於探討群落組成的重要性。
Abstract：
While climate change is threatening various communities, pioneering studies suggest that temperature variability potentially affects species, species interactions, and community composition. To understand how species coexist under different temporal scales of temperature variability, I used the echolocation trait composition of bat communities in Taiwan as a case to test community assembly hypotheses built upon environmental filtering and competition. First, I hypothesized that temperature variability would act as an environmental filter only allowing species with certain traits to filter through, and that larger temperature variability would act as a stronger filter. Therefore, I predicted that the trait space occupied in a community would decrease with increasing temperature variability . Second, I hypothesized that large temperature variability would lead to an unstable competitive equilibrium and promote species coexistence. Therefore, I predicted that large temperature variability would reduce niche differentiation, thus resulting in a spreading distribution of trait values in a community. Third, the temperature variability hypothesis states that temperature variability could select for the species with a broader niche (trait value), which allows species to endure environmental fluctuation. Therefore, I predicted that large temperature variability would select species with a broad niche, leading to a large trait space occupied by a species. To test the three hypotheses, I labelled bat echolocation calls in the long-term ultrasonic recordings collected at eight sites across Taiwan and measured their traits using trait-calculating function modified from the seewave in R. I then calculated three functional diversity indices (community-level functional richness, functional dispersion and species-level functional richness) from the traits, along with the daily, monthly, and inter-monthly temperature variability from the eight sites. To test the predictions, I used linear models and multiple models to investigate the correlation between functional indices and temperature variability. This study had three main findings: 1) A negative correlation existed between daily temperature variability and the community-level trait space, suggesting that daily temperature variability acted as an environmental filter limiting the range of trait values in a community; 2) Daily temperature variability correlated negatively with functional dispersion, suggesting that daily temperature variability could change the competition pattern of bat communities. However, inter-monthly temperature variability correlated positively with functional dispersion, suggesting that increasing temporal scale (from daily to inter-monthly) in temperature variability may intensify bat competition; 3) A negative correlation existed between monthly / inter-monthly temperature variability and the species-level functional richness, suggesting that increasing monthly and inter-monthly temperature variability would reduce the trait space of species. Overall, this study demonstrates that trait-based approaches can help us understand how climate change affects community composition through different mechanisms. Moreover, this study highlights the importance of considering the underlying mechanisms for community assembly at different temporal scales.