Collaborative Research: Competition for acoustic space as a driver of species diversity in vibrationally-signaling insects

令人震惊的全球昆虫数量下降对生态社区产生了广泛的影响，从鸟类数量减少到生态功能下降。了解环境是如何塑造昆虫多样性的，对于对抗这些迅速下降的昆虫种群至关重要。在这个项目中，研究人员测试了昆虫中的振动交流是否有助于形成这些模式。虽然许多昆虫使用声音进行交流，但绝大多数会唱歌的昆虫(90%)使用的是声音，声音通过植物的茎和叶传递。这些振动信号对领土争端和吸引配偶等过程很重要。然而，如果生活在同一植物上的其他昆虫产生类似的振动信号，这些信号可能会被干扰。研究人员测试了振动信号昆虫群落是否避免了它们的信号重叠。如果是这样，那么振动声空间的这种划分可能会决定哪些昆虫生活在一起。因此，任何影响植被上可以出现多少种不同类型的振动信号的东西，也会直接影响生活在那里的昆虫物种的数量。这项工作的结果可能为昆虫多样性的研究开辟新的途径，突出振动信号在监测昆虫群落方面尚未开发的潜力，并为深入了解人类对植被的影响如何影响昆虫群落提供洞察。除了测试塑造昆虫群落的环境变量的新假说外，该项目还将为不同的学生提供多种培训机会。拟议的工作通过一个新的透镜-振动信号空间来测试声学生态位假说在塑造草原昆虫群落中的作用。对任何给定植物上的振动空间的竞争可能会限制可以共存的振动信号的类型。由于振动信号的物种特异性，因此竞争也应该限制昆虫的多样性。研究人员在不同管理历史和当前做法的草原上生活的昆虫群落中测试了这一新的假设。振动和昆虫将从六个草原上每一片半径为1米的多个地块中收集。研究人员使用从植物身上捕捉微小昆虫振动的压电式记录器，在24-48小时内记录每一块地的振动。然后，他们将立即使用标准化的击网时间段从地块中收集昆虫。将从部分站点进行额外的密集录音，以优化较长期的振动采样策略。研究人员将使用机器学习算法处理振动数据，寻找振动空间分区，将振动声多样性指数与昆虫物种多样性指数进行比较，并开发用于使用振动监测昆虫群落的新工具集。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Alarming worldwide insect declines have widespread effects on ecological communities, ranging from bird population reductions to decreased ecological functioning. Understanding how the environment shapes insect diversity is critical to combat these rapidly declining insect populations. In this project, the researchers test whether vibrational communication in insects contributes to these patterns. While many insects use sound to communicate, the vast majority of singing insects (90%) use sound that travels as tiny vibrations through plant stems and leaves. These vibrational signals are important for processes like territorial disputes and mate attraction. However, the signals may be disrupted if other insects living on the same plant produce similar vibrational signals. The researchers test whether communities of vibrationally signaling insects avoid overlap in their signals. If so, then this partitioning of vibrational acoustic space could shape which insects live together. Thus, anything affecting how many different types of vibrational signals can occur on the vegetation would also directly affect the number of insect species living there. The results of the work could open new avenues of research on insect diversity, highlight the untapped potential of vibrational signals to monitor insect communities, and provide insight into how human impacts on vegetation affects insect communities. In addition to testing a novel hypothesis for the environmental variables shaping insect communities, this project will provide multiple training opportunities for a diversity of students.The proposed work tests the acoustic niche hypothesis in shaping prairie insect communities through a novel lens—vibrational signaling space. Competition for the vibrational space on any given plant can restrict the types of vibrational signals that can coexist. Due to the species-specificity of vibrational signals, competition should therefore also restrict insect diversity. The researchers test this novel hypothesis in insect communities living in prairies with varying management histories and current practices. Vibrations and insects will be collected from multiple 1-m radius plots on each of six prairies. Using piezo recorders that pick up tiny insect vibrations from plants, the researchers will record the vibrations in each plot over 24-48 hours. Then, they will immediately collect insects from the plot using a standardized time period of beat netting. Additional intensive recordings from a subset of sites will be conducted to optimize longer-term vibrational sampling strategies. The researchers will process the vibrational data using machine learning algorithms and look for vibrational space partitioning, compare vibrational acoustic diversity indices to insect species diversity indices, and develop novel toolsets for using vibrations to monitor insect communities.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.