Rapid urbanization in the Global South places traditional settlements under mounting pressure, threatening cultural heritage and the community institutions that sustain it, directly undermining SDG Targets 11.3 and 11.4. Asset-Based Community Development (ABCD) offers a community-centered alternative to top-down planning but lacks mechanisms to address power asymmetries, intangible asset valuation, and formal governance integration. This study develops an empirically grounded adaptation of the ABCD framework using an abductive analytical approach, combining a two-track literature review (44 core sources, supplemented by foundational pre-2010 works) with field research in two traditional Newar settlements, Thaiba and Badegaun in the Kathmandu Valley, Nepal (February to May 2025). Data collection included 32 semi-structured interviews, 4 focus group discussions, 120 h of observation, and participatory asset mapping, analyzed through iterative abductive coding using MAXQDA. The analysis identifies four interdependent strategies: (1) inclusive participation with temporal and intergenerational safeguards; (2) comprehensive valuation of tangible and intangible cultural assets; (3) hybrid governance arrangements granting communities binding decision-making authority; (4) adaptive learning through institutionalized feedback mechanisms. The resulting framework reconceptualizes heritage from passive cultural relics into productive community capital. Sub-unit variation between the two settlements reveals that institutional governance structure, rather than asset endowment, determines stewardship outcomes: Badegaun's rotating Guthi system sustained governance integration where Thaiba's fragmented permanent-assignment structure could not. By distinguishing symbolic consultation from genuine community control, the study proposes a replicable co-governance model providing municipal policymakers and community practitioners with actionable pathways for implementing SDG 11 and related goals in urbanizing traditional settlements.
Post-productivist transition (PPT) in rural China is well-documented at the structural level, but its micro-level mechanisms remain undertheorized, especially the limited participation of indigenous villagers in amenity provision. This paper addresses that gap by arguing that habitus adaptation is the micro-level mechanism that determines both whether villagers participate in the commercial opportunities PPT creates and how fully they benefit from doing so. Drawing on eight years of ethnographic fieldwork (2016–2024) and interviews with 124 respondents in Gaoshan, a Yao village in Xishuangbanna, Yunnan, we develop a two-level analytical framework. At the first level, field legitimacy and capital profile explain who participates and who does not. At the second, differential depths of habitus adaptation across three practice domains explain variation in participation quality. Adaptation depth is governed by field-side conditions (field legitimacy and legibility) and actor-side conditions (capital profile and field exposure), which together determine the quality and sustainability of participation. The paper provides the first longitudinal, individual-level account of how habitus adaptation unfolds across a village population navigating PPT in tourism.
Rapid urbanization profoundly alters interactions between human societies and natural ecosystems, thereby increasing uncertainty in social–ecological systems (SESs). Understanding the nonlinear responses of SESs to urbanization can help anticipate future risks and guide adaptive regional governance. Taking 296 prefecture-level and larger cities in China as the study area, this study develops an integrated state-structure framework that combines composite state assessment, network analysis, and change-point detection to characterize evolutionary dynamics and identify consensus transition intervals and regime stages along the urbanization gradient. The results show that changes in SES along the urbanization gradient do not follow a linear trajectory of either improvement or degradation. Instead, SESs transition among distinct regime stages through the combined effects of changes in system state and network reorganization. Greater network integration did not consistently correspond to improved system performance. At certain levels of urbanization, greater connectivity coexisted with a lower or declining composite SES state, indicating a mismatch between structural integration and system performance. The joint detection approach identified four consensus transition intervals and five regime stages: coordinated system improvement, continued structural strengthening, marked state deterioration, low-level stabilization, and recovery-oriented optimization. Multi-scenario projections further show that regime trajectories and transition risks vary across urban development scenarios. Cities located near consensus transition intervals or projected to undergo changes in regime-shift types were identified as priority areas for dynamic early warning and adaptive governance. These findings provide a state-structure perspective on urbanization-driven regime shifts in SESs and inform differentiated adaptive governance for sustainable urban development.
This study proposes and operationalizes a new typology based on the relative strength of the regional main center (CBD) and subcenters to classify and track changes in urban spatial structure across around 360 metropolitan areas in the U.S. from 2010 to 2020. Using employment and population data, we first applied spatial statistical techniques to identify CBDs and subcenters across metropolitan areas. We then developed composite CBD and subcenter indices and classified metropolitan areas into four categories for 2010 and 2020: monocentric, balanced polycentric, subcenter-led polycentric, and dispersed. The results show that in 2020, subcenter-led polycentric metropolitan areas emerged as the dominant urban spatial structure, accounting for approximately 43% of all cases. The most notable transition between 2010 and 2020 occurred among balanced polycentric MSAs. Of the 48 metropolitan areas in this category, 20 shifted to a monocentric structure, 8 transitioned to a subcenter-led form, and one transitioned to a dispersed form. Overall, the proposed empirical classification framework provides a replicable approach for systematically classifying and tracking changes in metropolitan spatial structure over time. Also, this framework can support future research on urban form, transportation, and regional development by enabling researchers to systematically evaluate how changes in CBDs and subcenters influence metropolitan spatial structure over time.
