Invasibility framework to predict the early colonization of alien Sonneratia in mangrove: Implications for coastal area management

Abstract

Invasibility, or an ecosystem's susceptibility to invasion, plays a critical role in managing biological invasions but is challenging to quantify due to its dependence on specific ecosystem variables. This limitation restricts the practical application of this concept in the control of alien species. This study aims to simplify invasibility into measurable components and develop an applicable framework to predict early colonization of alien plants within the coastal mangrove ecosystem. We used the unchanneled path length (UPL), a widely applied hydrological connectivity-related indicator, to assess the accessibility of the mangrove. The enhanced vegetation index (EVI), positively correlated with above-ground biomass, was used to evaluate the potential competitive intensity. Firstly, building on existing studies, we developed a four-quadrant concept model integrating the effects of EVI and UPL on the early colonization of the alien species Sonneratia apetala. Our results revealed significant differences in EVI and UPL values between colonized and uncolonized areas, with colonized regions displaying markedly lower values (P < 0.001). Additionally, logistic regression showed a significant negative association between the probability of successful colonization by S. apetala and both indicators (P < 0.001). These results validate the effectiveness of our conceptual model. Furtherly, we identified four key niche opportunities for exotic species in mangrove: mudflats outside the mangrove forest, tidal creeks, canopy gaps, and unmanaged abandoned aquaculture ponds. Overall, this study provides important insight into the ecological processes of alien S. apetala colonization and practical information for management of coastal areas susceptible to invasion. Additionally, it presents a case study on the practical application of the concept of invasibility in the management of alien species.