具有度依赖相互作用的可行物种生态网络
Ecological networks of viable species with degree-dependent interaction
AI总结：
研究将度依赖相互作用强度引入广义随机LV模型，识别出枢纽偏好和枢纽抑制阶段，分析得出阶段边界，发现其会使可行物种网络度-度相关性反向变化，证明度依赖相互作用对塑造物种生存及再现生态网络assortativity值的重要性。
AI中文摘要：
最近由动态平均场理论提出的广义Lotka-Volterra（GLV）框架，能够对大型生态网络进行系统分析。以往研究表明，物种的生存能力取决于其相互作用邻居的数量或“度”。但实际生态群落中相互作用强度与物种度之间存在相关性。为此，我们将度依赖的相互作用强度引入广义随机LV模型。我们识别出两个不同阶段：枢纽偏好阶段，高度连接的物种优先存活；枢纽抑制阶段，它们面临更高灭绝风险。我们分析得出阶段边界。关键的是，这些阶段会导致可行物种网络的度-度相关性或“ assortativity”发生相反变化。最终，我们的发现表明度依赖相互作用不仅是塑造物种生存的基本机制，也是自然再现实际生态网络中广泛观察到的assortativity值的基本机制。
英文摘要：
The generalized Lotka-Volterra (GLV) framework, recently advanced by dynamical mean-field theory, enables the systematic analysis of large ecological networks. When combined with structured interaction topologies, previous studies have shown that the viability of species, defined by having a positive stationary abundance, depends on the number of their interacting neighbors or the "degree." While such model studies usually assume that interaction strengths follow an identical distribution across all connected pairs, real ecological communities often exhibit correlations between interaction strength and a species' degree. To capture this overlooked feature, we introduce degree-dependent interaction strengths into a generalized random LV model. We identify two distinct regimes: a hub-favored phase, where highly connected species survive preferentially, and a hub-suppressed phase, where they face higher extinction risks. We analytically derive the phase boundary where these degree-dependent strengths precisely balance the connectivity effect, leaving all species equally susceptible. Crucially, these phases induce opposing shifts in the degree-degree correlation or "assortativity" of the network of viable species: the hub-favored phase enhances disassortativity by selectively removing the interactions between low-degree species, whereas the hub-suppressed phase reduces it as the interactions involving hub species tend to disappear. Ultimately, our findings demonstrate that degree-dependent interactions are a fundamental mechanism not only for shaping species survival, but for naturally reproducing the wide range of assortativity values observed in real ecological networks.
