Aim: An assessment method that can precisely represent human‐vectored long‐distance dispersals (HVLDD) is currently in need for the effective management of invasive species. Here, we focussed on HVLDD happening along roads and proposed a path‐finding algorithm as a more precise dispersal assessment tool than the most widely used Euclidean distance method by using pine wilt disease (PWD) as a case study.Location: Busan Metropolitan City, Republic of Korea.Methods: A path‐finding algorithm, which calculates distances by considering the spatial distribution of road networks, was tested for its effectiveness in estimating dispersal distances of HVLDD events. To this end, annual HVLDD cases were classified from entire PWD occurrence data from 2016 to 2019, and their dispersal distances were calculated using the path‐finding algorithm and the Euclidean distance method. We constructed potential dispersal ranges based on the occurrence points in 2016, 2017 and 2018 using the respective year's mean dispersal distance for both methods, and their performances in accounting for each subsequent year's HVLDD cases were compared to determine which method calculated more precise distances. The information on which road class contributed more to dispersal occurrences and distances was analysed as well using the proposed algorithm.Results: The potential dispersal ranges of the path‐finding algorithm accounted for more future anthropogenic infection cases than the ones that used the Euclidean distance method, validating its higher functionality. It also revealed that most HVLDDs started and ended on small roads, and large roads constituted the majority of the total dispersal length.Main conclusions: The path‐finding algorithm has proven to be a more effective dispersal assessment method for HVLDD events. It can help design effective control strategies. Thus, we encourage using the path‐finding algorithm for the dispersal assessment of invasive species that move along road networks, and for the development of more powerful HVLDD prediction models.

Urbanization is causing an increase in air pollution leading to serious health issues. However, even though the necessity of its regulation is acknowledged, there are relatively few monitoring sites in the capital metropolitan city of the Republic of Korea. Furthermore, a significant relationship between air pollution and climate variables is expected, thus the prediction of air pollution under climate change should be carefully attended. This study aims to predict and spatialize present and future NO₂ distribution by using existing monitoring sites to overcome deficiency in monitoring. Prediction was conducted through seasonal Land use regression modeling using variables correlated with NO₂ concentration. Variables were selected through two correlation analyses and future pollution was predicted under HadGEM-AO RCP scenarios 4.5 and 8.5. Our results showed a relatively high NO₂ concentration in winter in both present and future predictions, resulting from elevated use of fossil fuels in boilers, and also showed increments of NO₂ pollution due to climate change. The results of this study could strengthen existing air pollution management strategies and mitigation measures for planning concerning future climate change, supporting proper management and control of air pollution.

Context: As cities seek to provide more habitat for wildlife, there may be unintended consequences of increasing tick-borne disease hazards. In the United States, the Northeast is both highly urban and a hotspot for blacklegged ticks (Ixodes scapularis) and tick-borne disease emergence. Though tick-borne disease was once considered a suburban and rural problem, tick-borne hazards in urban landscapes are increasing. Objectives: We hypothesized that multi-scale ecological processes hierarchically contribute to tick-borne hazards across an urbanization gradient. Urban greenspaces with higher functional connectivity to deer movement would have higher deer occupancy at the ‘ecological neighborhood’ scale, resulting in increased blacklegged tick populations and pathogen infection at the scale of within greenspaces. Methods: To evaluate our hypothesis, we used circuit theory methods to model the impact of functional connectivity on deer occupancy, blacklegged tick abundance, and pathogen infected ticks across an urbanization gradient. We sampled nymphal ticks during their peak activity and deployed wildlife cameras to detect deer at 38 greenspaces across New York City and Long Island, NY from 2022 to 2023. Results: We found that functional connectivity significantly predicted deer occupancy with cascading effects on abundance of blacklegged nymphal ticks and Borrelia burgdorferi infection. We novelly identified a threshold of functional connectivity in urban areas necessary for deer occupancy, tick populations, and tick infection with B. burgdorferi, to emerge in urban environments. Conclusions: We recommend targeted tick-borne hazard mitigation along this functional connectivity threshold as part of urban greenspace management plans. Additionally, we highlight the importance of examining multi-scale landscape drivers of host, tick, and pathogen interactions.

Biotope map is a high-resolution ecological information map that reflects environmental and ecological characteristics and values, and can be used as basic data for sustainable urban management. Its utilization for establishment of urban planning is encouraged nationally, but such action has been rarely implemented. In this study, vulnerability assessment in urban thermal environments of Suwon was conducted based on a biotope map. For the vulnerability assessment, 17 indicators for exposure-sensitivity-adaptability were constructed and utilized based on existing studies related to thermal environments such as heat waves and urban heat islands. As a result of the analysis, the regions belonging to the urban biotope showed a higher overall vulnerability than the green biotope regions. Among urban biotope, higher vulnerability was found in manufacturing, residential and commercial areas with high floor-area ratio and impermeable area ratio. In the unit of administrative districts, Paldal-gu, which has the highest ratio of residential and commercial regions, showed the highest overall vulnerability. Thermal vulnerability clearly depended on the distribution of biotope type, even within the same administrative district. In conclusion, an efficient policy and budgeting regarding the thermal environment of urban city should be implemented in consideration of its biotope type and inner driving factor. This study has a meaning in that it could support the establishment of practical and efficient urban and environmental planning to improve thermal environments based on high-resolution biotope map.