The Minshan mountain region of China is a focal point for giant panda conservation. Here, we use graph-theoretic methods and social-economic-natural complex ecosystem theory to analyze and assess giant panda habitat stressors and their interactions. We selected twelve stressors spanning tourism, agriculture, mining, hydropower and the collection of timber, fuel wood and Chinese medicinal plants for our analysis. We found that 47% of stressor combinations directly interacted with each other, and that 89% of interactions between stressors had aggravating effects. There was a strong linkage component K＝{ (TD); (RB); (MI); (HPL); (AP); (AD); (SR); (TH); (FC)}, suggesting that stressors from tourism and tourist site construction, hydropower engineering, transportation, road construction, agriculture and farming, and fuel wood collection are likely to create additional impacts on giant panda habitat through interactions with other stressors. Given these findings, these eight stressors are the most significant factors threatening giant panda habitat across the Minshan Mountains. Our study demonstrates that graph-theoretic methods are useful tools in simplifying reticular interactions amongst various giant panda habitat stressors, and identifying key stressors upon which management plans can be designed.