一种捕食者与两种猎物：巴塔哥尼亚美洲狮、原驼和绵羊的共存
One predator and two prey: Coexistence of pumas, guanacos and sheep in Patagonia
AI总结：
针对巴塔哥尼亚美洲狮、原驼和绵羊构成的一捕两食生态系统，研究构建并简化方程模型，利用推广三元图和感知器ML分析关键参数对物种共存与灭绝的影响。
摘要：
本研究所考虑的生态系统是一长串历史和生态事件的结果。巴塔哥尼亚的本土动物群由五次重大灭绝事件的幸存者组成，其中尤为引人注目的是美洲狮和原驼，它们是两种最大的本土哺乳动物。除此之外，欧洲移民还将绵羊引入了该生态系统。这三个物种共同构成了一个简单的营养网络，其特征是一种捕食者和两种猎物，全部在巴塔哥尼亚草原内竞争。对牧场主而言，原驼和美洲狮经常被视为对其经济利益的威胁。近几十年来，生物学领域，尤其是生态学，见证了基于方程的模型开发的大幅增长。科学家们感兴趣的是，能够将假设系统化，并深入了解复杂生物系统（例如本研究中呈现的系统）的行为。然而，当人们想要探索参数空间时，模型的非线性本质和大量参数构成了挑战。为了克服这一问题，同时增进对巴塔哥尼亚生态系统的理解，我们首先在以往贡献的基础上构建了一个基于方程的模型，并将其简化为最基本的参数集合。随后，我们引入了两种工具，即三元图的推广和基于感知器的机器学习（ML），以帮助理解系统方程对关键参数的响应。感知器工具使我们能够可视化/解释每个参数对每个物种生存或灭绝的影响。通过三元图的推广，可以在单一图形表示中方便地可视化系统如何响应简化系统方程五个参数的不同组合/变化。
英文摘要：
The ecosystem considered in this study is the outcome of a lengthy sequence of historical and ecological events. Patagonia's indigenous fauna comprises survivors of five significant extinction events, with the notable presence of the puma and the guanaco, two of the largest native mammals. In addition to these, European immigrants introduced sheep into the ecosystem. Together, these three species form a straightforward trophic network, featuring one predator and two prey species, all competing within the Patagonian steppe. For ranchers, guanacos and pumas are frequently perceived as threats to their economic interests. In recent decades, the field of biology, particularly ecology, has witnessed a substantial increase in the development of equation-based models. Scientists are interested in the ability to systematize hypotheses and gain insights into the behavior of complex biological systems, such as the one presented in this study. However, the nonlinear nature and the large number of parameters of models, represent a challenge when one wants to explore the parameter space. To overcome this and, at the same time, improve the understanding of the Patagonia ecosystem, we start by building an equation-based model based on previous contributions, and we reduce it to the essential minimum set of parameters. Then, we introduce two tools, a generalization of ternary graphs and a perceptron based ML, to help understand the response of the system equation to the key parameters. The perceptron tool allows us to visualize/interpret the influence of each parameter on the survival or extinction of each species. Through the generalization of the ternary graph, it was possible to conveniently visualize how the system responds to different combinations/variations of the five parameters of the reduced system equation in a single graphical representation.
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