Community assembly can change over time following variations in connectivity among habitats. Previous studies have demonstrated the influence of seasonal pulse floods on community structures by facilitating species dispersal, but the effects of short-term flash floods have been poorly investigated. We investigated fish community structures before and after a short-term flood in drainage ditches of paddy fields in the Kita River basin, Japan. The study sites were classified into three connectivity types, “Transient” (connected only during the flood, with a temporally-disappearing vertical gap between drainage ditches and downstream rivers), “Connected” (always connected, without the vertical gap), and “Disconnected” (always not connected, with the vertical gap). The abundance of Misgurnus anguillicaudatus, the only species that dispersed from paddy fields to drainage ditches, increased after the flood irrespective of the connectivity types, although the total abundance of the other species significantly increased after the flood only in the “Transient” sites. The dissimilarity of species composition between the (n-1)-th and n-th surveys at each site was consistently low in the “Connected” and “Disconnected” sites, whereas it rose just after the flood and gradually declined in the “Transient” sites. Species composition was significantly different among the connectivity types, indicating that some fish species need stable connectivity even during the non-flood period. The results showed that the short-term flood facilitated fish dispersal from paddy fields by the increased water discharge and that from downstream rivers by the temporary removal of vertical gap, emphasizing the importance of hydrological connectivity for biodiversity conservation in an agricultural landscape.

The use of artificial intelligence (AI) and machine learning (ML) has significantly enhanced ecological research in Asia by improving data processing, analysis, and pattern extraction. Analyzing 1550 articles, I show an overview of the use of AI and ML for Asian ecological research. Following the last 20 year trend, I found that the topics in Asian ecological research have transitioned from technical perspectives to more applied issues, focusing on biodiversity conservation, climate change, land use change, and societal impacts. Non-Asian countries, on the other hand, have focused more on theoretical understanding and ecological processes. The difference between Asian and non-Asian regions may have emerged due to the ecological challenges faced by Asian countries, such as rapid economic growth, land development, and climate change impacts. In both regions, deep learning related technology has been emerging (e.g. big data collection including image and movement). Within Asia, China has been the Asia-leading country for AI/ML applications followed by Korea, Japan, India, and Iran. The number of computer science education programs for education in China has been increasing 3.5x times faster than that in the U.S., indicating that a nationwide strategy for computer science development is key for ecological science with AI. Overall, the adoption of AI and ML technologies in ecological studies in Asia has propelled the field forward and opened new avenues for innovative research and conservation practices.

Flowering phenology of alpine plant communities and seasonal dynamics of flower visitors have been scarcely studied in the tropical/subtropical alpine regions. We report flowering phenology, flower production, and flower-visiting insects in the alpine site of central Taiwan. Throughout the research period (2017–2018), we recorded flowering phenology of 130 plant species, flower production of 81 species, and 15,127 insects visiting alpine flowers. Most of the alpine plants were visited by dipteran insects and/or hymenopteran insects. The seasonal patterns of flowering were more apparent in bee-visited plants compared to fly-visited plants in which the flowering of bee-visited plants clearly increased as the season progressed. About 63% of flower visitors were dipteran insects (syrphid and non-syrphid flies), and 30% were hymenopteran insects (mostly bumble-bee workers). Although the seasonal trend in fly abundance was less clear between years, bumble-bee abundance consistently increased in the middle to late seasons, reflecting colony development. There was a positive correlation between bee abundance and the number of flowering species of bee-visited plants, but there was no correlation between fly abundance and the number of flowering species of fly-visited plants throughout the season. These results suggest that the flowering phenology of subtropical alpine communities is influenced by the seasonal availability of pollinators. Bumble bees, syrphid flies, and non-syrphid flies had wide ranges of foraging flowers, but their niche overlap was relatively small. Because cold-adapted bumble bees are threatened by climate change in Taiwan, plant–pollinator interactions may be disturbed by global warming.

A subtropical mangrove along the Miyara River in Ishigaki Island, Japan was studied for evaluating the carrying capacity for biomass of the monospecific stands. Rhizophora stylosa and Bruguiera gymnorrhiza were dominant in the downstream area whereas B. gymnorrhiza in the upstream. The stem diameter D, stem height H, fine roots mass were measured and, aboveground biomass AGB, belowground coarse root biomass BGBcoarse were estimated. The AGB, BGBcoarse and fine root mass were estimated as 128.46 Mg ha-1, 31.01 Mg ha-1 and 12.75 Mg ha-1 in the R. stylosa; 269.82 Mg ha-1, 93.68 Mg ha-1 and 11.13 Mg ha-1 in the downstream B. gymnorrhiza; and, 227.94 Mg ha-1, 81.05 Mg ha-1 and 6.35 Mg ha-1 in the upstream B. gymnorrhiza plots, respectively. The AGB did not differ among the plots, meanwhile BGBcoarse was significantly lower and fine root mass was significantly higher in the R. stylosa plots than in the downstream B. gymnorrhiza plots. Significantly lower mean individual phytomass wt specific to tree density  of R. stylosa plots than B. gymnorrhiza plots in the  – wt relationship was found, which denoted the lower carrying capacity for AGB of R. stylosa than that of B. gymnorrhiza. The results rejected our hypothesis that the stressful edaphic conditions, such as high soil salinity and low pH at the downstream, limit biomass and potential canopy height Hmax of mangrove along a river gradient but partly supported another hypothesis that biomass and Hmax differs between different mangrove species at the same edaphic environment.