Generalization of a state-transition model to address degradation of Ecuador's tropical dry forest at a regional scale

Understanding how chronic disturbance leads to forest degradation across an entire ecosystem is necessary to avoid the loss of ecological integrity at scale. In poorly studied ecosystems, expert-based models can help conceptualize the primary drivers and consequences of degradation. Drawing on knowledge from local ecologists and land managers ("experts"), we assessed whether a local state-and-transition model (STM) could be generalized to support management of Ecuador's seasonally dry tropical forest (SDTF) at a regional scale. The objectives of this study were to: (i) examine whether socioecological drivers across this ecosystem generate distinct states and transitions, (ii) determine which restoration actions are most effective at reversing degradation, and (iii) identify vegetation attributes that can serve as indicators of forest states. Although the human pressures identified as the main drivers of degradation differed between provinces, experts consistently recognized the same five forest states and four transitions in all three provinces. This suggests that forest degradation follows a similar pattern throughout the region and is more a consequence of indirect effects of forest structure loss like water stress than direct impacts on forest species. Expert responses about recovery pathways were highly variable, revealing ambiguity as to which restoration practices are most effective for each forest state. Tree density and canopy height were singled out as the vegetation attributes that best distinguish between states and thus could serve as effective indicators of degradation. These results enabled the development of a general STM to support forest management, research, and restoration throughout Ecuador's SDTF.