Urbanization decreases the extent and variety of leaf herbivory for native canopy tree species Quercus rubra, Quercus alba, and Acer saccharum

Urban environments have species-specific associations with invasive insect herbivores

Urban forests are critically important for providing ecosystem services to rapidly expanding urban populations, but their health is threatened by invasive insect herbivores. To protect urban forests against invasive insects and support future delivery of ecosystem services, we must first understand the factors that affect insect density across urban landscapes. This study explores how a variety of environmental factors that vary across urban habitats influence density of invasive insects. Specifically, we evaluate how vegetational complexity, distance to buildings, impervious surface, canopy temperature, host availability and density of co-occurring herbivores impact three invasive pests of elm trees: the elm leaf beetle (Xanthogaleruca luteola), the elm flea weevil (Orchestes steppensis) and the elm leafminer (Fenusa ulmi). Insect responses to these factors were species-specific, and all environmental factors were associated with density of at least one pest species except for distance to buildings. Elm leafminer density decreased with higher temperatures and was influenced by an interaction between vegetational complexity and impervious surface. Elm flea weevil density increased with greater host availability, and elm leaf beetle density increased with higher temperatures. Both elm leaf beetle and elm flea weevil density decreased with greater leafminer density, suggesting that insect density is mediated by species interactions. These findings can be used to inform urban pest management and tree care efforts, making urban forests more resilient in an era when globalization and climate change make them particularly vulnerable to attack.

An integrated approach for enhancing the overall performance of constructed wetlands in urban areas

Constructed wetlands (CWs) are an important component of the urban matrix and play an essential role in the restoration of urban ecological environments. Although existing studies have mainly focused on the efficiency of technologies for removing pollutants in wastewater, efforts to intensify the overall performance of CWs have not been reported. Here, we propose a novel theoretical scheme for promoting optimal overall performance of CWs through the development of an integrated approach, entailing simulation, evaluation, and optimization strategies for their management. We successfully simulated the water distribution system of the Yanfangdian CW in Beijing, China, applying 42 hydrological parameters within the MIKE 21 software. We further evaluated our simulation results by performing an analytic hierarchy process to calculate performance scores. The back propagation neural network was well trained to quantify the relationship between the hydrological parameters and the overall performance of CW based on its water distribution characteristics and their corresponding scores. Subsequently, a genetic algorithm was applied to determine the hydrological solution. A strategy for optimizing the water level and flow was formulated for improving the ecological, purification and storage performances of the targeted CW along with a flexible strategy for ensuring its proper functioning. Our approach provides a robust and universal platform that can contribute significantly to the advancement of CWs that have a wide range of applications and could be extended to other ecosystems.