Remotely sensed solar-induced chlorophyll fluorescence (SIF) is applicable as an indicator of changing photosynthetic activity in terrestrial ecosystems. The vegetation of Borneo has previously been affected by drought and fire during El Niño events. Changes in satellite-based SIF data during an El Niño event in Borneo in 2015 were examined using three satellites-GOSAT, GOME-2, and OCO-2-covering the whole island and its southern and northern areas, respectively. Relationships between environmental factors and vegetation damage, precipitation, fire incidence, vegetation indices, and gross primary production (GPP), which were determined using machine-learning methods, were also examined for the period 2007–2018. SIF tended to be low in dry seasons, even in normal years, possibly because of increased drought stress and/or a higher incidence of fires with less precipitation. During the dry season of 2015, there were significant reductions in SIF in southern Borneo where fires were frequent. Other vegetation indices and GPP were also lower. Serious drought conditions with frequent fires during the El Niño event might have caused ecological degradation throughout Borneo, with a significant decrease in SIF.

　Elevated temperatures during the flowing stage can induce spikelet sterility in rice, posing a major threat to production under climate change. Projecting the impacts and developing effective strategies are critical, but our understanding of regional, seasonal, and long-term trends in rice heat exposure remains limited. Previous studies on spikelet sterility revealed that panicle temperature, estimated using a micrometeorological model and common meteorological factors, serves as a reliable indicator of rice heat exposure. In this study, we employed this model to identify the temporal and spatial variation of panicle temperatures, the differences between panicle and air temperatures (DPAT), and their causes over the past 45 years in Japan. A gridded daily meteorological dataset covering Japan was interpolated at an hourly time step and used as input data of the micrometeorology model for estimating panicle temperatures. Before 2000, estimated panicle temperatures around the heading stage, the most susceptible stage to heat, had rarely exceeded the critical threshold of 33°C, but the heat exposure frequency above this threshold (HEF) has increased almost exponentially in multiple regions since then, increasing the risk of heat-induced sterility. In the unprecedentedly hot summer of 2023, the mean HEF in the Kanto and Chubu regions exceeded 30%. In most regions in Japan, panicles were estimated to be warmer than air, indicating the inadequacy of relying solely on air temperature to gauge rice heat stress. DPAT values showed substantial inter-regional variations in both mean values (from －0.5°C to 3.0°C) and seasonality. Through machine learning and statistical methods, the relationship between DPAT and meteorological factors was characterized, delineating the effects of the meteorological factors on regional and seasonal DPAT variations. Focusing on major high-risk regions, we show that mitigation strategies should be adapted to consider regional characteristics and avoid high panicle temperatures and DPAT conditions during rice heading periods.

　To evaluate suitability for growth of tropical fruits under global warming in Japan, we revealed cold tolerance threshold of subtropical fruit trees by performing field and chamber experiment and developed an extrapolatory method that can predict the cold tolerance of subtropical fruit trees without conducting extensive field experiments. Results of the field experiments estimated cold tolerances of -1.5 and -2°C for ‘Summer Queen’ passion fruit and ‘Sata’ lychee, respectively, and -5, -4.5, and -4°C for ‘Mexicola,’ ‘Bacon,’ and ‘Fuerte,’ avocados, respectively, indicating the dependence of cold tolerance on the variety of the tree species. The cold tolerance obtained from the field experiment was higher than the chamber experiment by 1°C for passion fruit and avocado and 2°C for lychee, which is explained by the difference between air and leaf temperature of field trees caused by radiative cooling on a clear and calm night. Therefore, cold tolerances of passion fruit and avocado can be estimated by adding 1°C to the cold tolerances obtained from the chamber experiment and that of lychee can be estimated by adding 2°C to the cold tolerance obtained from the chamber experiment. Moreover, even for other tree species, which were not consider in this study, the cold tolerance of the trees grown in fields can be estimated based on the results of the chamber experiment and using estimations of the difference between air and leaf temperatures on a clear and calm night.