Seismic information transfer in African Elephants - CASE Project

非洲象的地震信息传递地震振动编码的信息：非洲象如何感知地震振动？他们如何使用它们作为信息源和信息传递？这能用于大象保护吗？其他动物是否参与了生物震颤学网络？不断增长的人口，特别是在发展中国家，正日益引发人类与野生动物的冲突。特别是大象，由于农作物遭到掠夺，经常与人类与野生动物的冲突联系在一起，而且还面临着严重的偷猎威胁。结合基于生物震颤学的实验和GPS跟踪提供了一种特别有前途的跨学科方法，可以发现减少人象冲突的新方法，同时增加我们对大象行为和生态学以及大草原生态系统中其他地震相互作用的理解。在典型的行为和生态学研究中，检测和利用穿过基底的振动在很大程度上是一种被忽视的感觉模式（Cocroft et al., 2014）。然而，很多动物都在使用这种振动（Hill & Wessel, 2016; Mortimer 2017），对这种振动的研究被称为生物震颤学。其中包括非洲象，O'Connell-Rodwell（2007）证明大象可以通过地面的次声波振动传递明显的详细信息。具体来说，大象可以区分熟悉和不熟悉的个体发出的警报信号的地震成分。从理论上讲，这些基底振动的衰减速度比可比的空气振动要慢，而且模型表明，大象可以利用地震振动在几公里的距离上进行通信（Mortimer et al., 2018）。重要的是对稀树草原生态系统生物震颤学的理解；大象显然不是唯一能够产生大量地震信号的大型哺乳动物，地震通信已被假设（O'Connell-Rodwell et al., 2001）。具体来说，O'Connell-Rodwell等人（2001）认为黑犀牛可能会利用地震信号组成松散的群体，在夜间协调一致地到达水坑。技术的进步使地震通信的研究更加容易处理，我们建议使用这种方法来更新我们的图像，将大象作为大草原生态系统及其哺乳动物的焦点动物。为此，我们将使用GPS跟踪、生物震颤学技术以及现场观察和实验相结合的方法。GPS跟踪技术提供了对大象空间分布的独特洞察，因此可以远程指示个体之间的互动。对跟踪的雄性大象平行移动数小时但相距数公里的观察表明，它们可能通过地面进行交流（道格拉斯-汉密尔顿和沃尔拉斯未发表的观察）。然而，GPS数据最终证明相互作用的能力将依赖于基于实验和观察相结合的新型生物震颤学技术来证明因果关系（Mortimer et al., 2018）。

Seismic information transfer in African ElephantsInformation encoded in seismic vibrations: How do African elephants perceive seismic vibrations? How do they use them as an information source and for information transfer? Can this be used for elephant conservation? Are other animals participating in biotremology networks?Growing human populations, particularly in developing countries, are increasingly causing human-wildlife conflict. Elephants in particular, are often associated with human-wildlife conflict due to crop raiding and are additionally faced with severe poaching threats.Combining biotremology-based experiments and GPS tracking offers a particularly promising interdisciplinary approach to discover novel ways to reduce human-elephant conflict while at the same time increasing our understanding of elephant behaviour and ecology as well as other seismic interactions in the savannah ecosystem.Detecting and using vibrations that travel through substrates is a largely ignored sensory mode in typical studies of behaviour and ecology (Cocroft et al., 2014). Yet it emerges that such vibrations are used by a wide range of animals (Hill & Wessel, 2016; Mortimer 2017), the study of which is known as biotremology. These include African elephants with O'Connell-Rodwell (2007) demonstrating that elephants can transfer apparently detailed information via infrasonic vibrations through the ground. Specifically, elephants can distinguish between the seismic components of alarm calls generated by familiar and unfamiliar individuals. In theory, these substrate-borne vibrations attenuate less rapidly than comparable air-borne vibrations, and models suggest that elephants can use seismic vibrations to communicate over distances of several kilometres (Mortimer et al., 2018). Importantly for an understanding of biotremology in savannah ecosystems; elephants are apparently not the only large mammals that generate substantial seismic signals for which seismic communication has been hypothesised (O'Connell-Rodwell et al., 2001). Specifically, O'Connell-Rodwell et al. (2001) suggest that black rhino may use seismic signals to form loose groups that coordinate a synchronised arrival at watering holes at night. Advances in technology have made the study of seismic communication more tractable and we propose to use this modus operandi to update our image, using elephants as a focal animal of the savannah ecosystem and its mammals. For this we will use a combination GPS tracking, biotremology techniques, and in-situ observation and experiments.GPS tracking technology provides unique insight into the spatial distribution of elephants and can consequently remotely indicate interactions between individuals. Observations of tracked male elephants moving in parallel over several hours but kilometres apart suggest that they communicate probably via the ground (Douglas-Hamilton and Vollrath unpublished observations). However, the ability of GPS data to conclusively demonstrate interactions will rely on novel biotremology technology to demonstrate cause and effect based on a combination of experiments and observation (Mortimer et al., 2018).