Urban forest ecosystems, the structure, and functions therein are subjected to anthropogenic disturbances. Native and sensitive species from those forests might be lost due to such disturbances. At the same time, supplemented anthropogenic resources might create opportunities for exotic and invasive species. Although invasive species are considered one of the major threats to the urban biodiversity and ecosystems, the research on invasion dynamics in the Himalayas has primarily focused on the impacts of invasion on forest structure and productivity. This study aims to understand the influence of forest structure and anthropogenic factors in invasion success that are poorly covered in the existing literature. We selected 11 urban forest patches for the study considering the presence-absence of selected invasive species and structural attributes. We used Principal Component Analysis (PCA) to reduce co-linearity in the covariates and generalized linear mixed effects model (GLMM) to identify the factors affecting invasion success. We found that forest structural attributes, namely, tree diameter, height and canopy cover, and anthropogenic disturbances regulate invasion success in urban forests. This implies that maintaining urban forest structural attributes, especially the stands with large-sized trees, is essential to control invasion in the context of urbanization.
In this article, we study the electricity time‐of‐use (TOU) tariff for an electricity company with stochastic demand. The electricity company offers the flat rate (FR) and TOU tariffs to customers. Under the FR tariff, the customer pays a flat price for electricity consumption in both the peak and non‐peak periods. Under the TOU tariff, the customer pays a high price for electricity consumption in the peak period and a low price for electricity consumption in the non‐peak period. The electricity company uses two technologies, namely the base‐load and peak‐load technologies, to generate electricity. We derive the optimal capacity investment and pricing decisions for the electricity company. Furthermore, we use real data from a case study to validate the results and derive insights for implementing the TOU tariff. We show that in almost all the cases, the electricity company needs less capacity for both technologies under the TOU tariff than under the FR tariff, even though the expected demand in the non‐peak period increases. In addition, except for some extreme cases, there is essentially no signicant reduction in the total demand of the two periods, although the TOU tariff can reduce the demand in the peak period. Under the price‐cap regulation, the customer may pay a lower price on average under the TOU tariff than under the FR tariff. We conduct an extensive numerical study to assess the impacts of the model parameters on the optimal solutions and the robustness of the analytical results, and generate managerial implications of the research findings. 相似文献
