Data from: A cost of being amicable in a hibernating marmot

Amicable social interactions can enhance fitness in many species, have negligible consequences for some, and reduce fitness in others. For yellow-bellied marmots (Marmota flaviventris), a facultatively social rodent species with demonstrable costs of social relationships during the active season, the effects of sociality on overwinter survival have yet to be fully investigated. Here, we explored how summer social interactions, quantified as social network attributes, influenced marmot survival during hibernation. Using social data collected from 2002 to 2012 on free-living yellow-bellied marmots, we calculated eight social network measures (in-degree, out-degree, in-closeness, out-closeness, in-strength, out-strength, embeddedness, and clustering coefficient) for both affiliative and agonistic interactions. We performed a principle component analysis to reduce those attributes to three affiliative (connectedness, strength, and clustering) and four agonistic (submissiveness, bullying, strength, and clustering) components. Then, we fitted a generalized linear mixed model to explain variation in overwinter survival as a function of these social components, along with body mass, sex, age, weather conditions, hibernation group size, and hibernation group composition. We found that individuals with stronger amicable relationships were more likely to die during hibernation. This suggests that social relationships, even affiliative ones, need not be beneficial; for yellow-bellied marmots, they can even be fatal.

友好的社会互动可提升诸多物种的适合度，对部分物种无显著影响，却会降低另一些物种的适合度。对于黄腹旱獭（*Marmota flaviventris*）这种兼性社会性啮齿类而言，已有研究证实其在活动季的社会关系存在显性代价，但社会性对其越冬存活率的影响尚未得到充分探究。本研究旨在探究以社会网络属性量化的夏季社会互动如何影响旱獭冬眠期间的存活率。我们利用2002年至2012年间收集的野生黄腹旱獭社会互动数据，针对亲和互动与对抗互动分别计算了8项社会网络指标：入度（in-degree）、出度（out-degree）、入接近中心性（in-closeness）、出接近中心性（out-closeness）、入强度（in-strength）、出强度（out-strength）、嵌入性（embeddedness）与聚类系数（clustering coefficient）。随后我们开展主成分分析，将上述指标降维为3个亲和性主成分（连接性、强度与聚类性）与4个对抗性主成分（顺从性、欺凌行为、强度与聚类性）。随后我们构建广义线性混合模型，以这些社会主成分为核心自变量，结合体重、性别、年龄、气象条件、冬眠群体规模与冬眠群体组成，对越冬存活率的变异进行解释。研究结果显示，拥有更强亲和社会关系的个体在冬眠期间的死亡风险更高。这表明社会关系（即便为亲和性社会关系）未必总能带来益处；对黄腹旱獭而言，此类关系甚至可能是致命的。