Forestry heritage tourism can spread the ecological concept of harmonious coexistence between humans and nature, and it is a nature-based solution to climate change. However, how tourists are guided to form an emotional identity and how their attention to climate change issues can be stimulated continuously remain unclear. Therefore, in this study, we selected the Wuyi Mountain Forestry Heritage Site as our study site and employed PLS-SEM to analyze the responses of 384 tourists, thereby examining the underlying mechanism linking their perceptions of climate change to carbon offset behaviors within forestry heritage sites. The results showed the following: Perceptions of climate change had a positive and significant impact on carbon offset behavior (β = 0.310, p < 0.001), ecological identity had a positive and significant impact on carbon offset behavior (β = 0.375, p < 0.001), and the sense of environmental responsibility had a positive and significant impact on carbon offset behavior (β = 0.226, p < 0.01). At the same time, ecological identity and environmental responsibility play an intermediary role, and the impact of climate change perception on the carbon offset behavior of tourists at forestry heritage sites is moderated by tourists’ health attitudes. In addition, gender, age, and educational background have an impact on the process of carbon-offsetting behavior development at forestry heritage sites. This research further clarifies the internal logic of tourists’ carbon offset behavior in the context of heritage tourism, helps to enrich the theoretical system of Nbs and heritage tourism research, and provides a feasible reference for the realization of the SDGs.

National modern agricultural industrial parks are the core carriers for promoting agricultural modernization. Clarifying their spatial differentiation patterns is of great significance for revealing the efficiency of resource allocation and promoting coordinated regional development. Based on the data from 338 national modern agricultural industrial parks in China, this study uses methods such as the nearest neighbor index, Voronoi spatial statistics, and spatial autocorrelation to identify their spatial distribution characteristics, and adopts the XGBoost–SHAP model to explore the nonlinear effects of driving factors. The research found the following: (1) The parks exhibit a distinct “sparse west–concentrated middle–dense east” agglomeration pattern aligned with China’s Hu Huanyong Line agro–economic divide. (2) At the municipal level, four high-density cores emerged in central-eastern regions with “dual hot spots–gradient diffusion” characteristics. (3) Farmers’ professional cooperatives and transportation accessibility are the most consistent fundamental driving elements, reflecting the transition of the development momentum of contemporary agriculture from “resource dependency” to “circulation dependence.” Heterogeneity analysis shows elevation, cooperatives and rural income differentially drive agglomeration across regions, with elevation constituting a universal constraint. (4) While regional development and mechanization show adaptive synergy, excessive urbanization generates a distinct “non–agriculturalization” crowding–out effect on agricultural development.