Mammal fauna in Biodiversity Research Center, Research Institute of Environment,Agriculture and Fisheries, Osaka Prefecture was surveyed using camera traps. The survey period was from April 2018 to December 2022. As a result, eightmammal specieswere identified, including red fox (Vulpes vulpes), a rare species inOsaka Prefecture.Additionally, invasive species such as raccoon (Procyon lotor) and masked palmcivet (Paguma larvata) were also identified. Relative abundance indices (RAI) were high for foxes and cats, especially for spring and winter foxes.

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In the salinity measurements of seawater conducted at this research institute, the number of repeated measurements may increase before determining the final value. To elucidate the causes of the increased number of measurements, we investigated the measurement environment related to temperature and analyzed its relationship with the number of measurements. We employed LiNGAM (Linear Non-Gaussian Acyclic Model) and the PC (Peter and Clark) algorithm, both statistical causal discovery methods, to estimate the causal relationships among factors and constructed a DAG (DirectedAcyclic Graph). The results of the causal discovery revealed that the causal order is temperature →number of measurements.Additionally, it was suggested that reducing the range of water sample temperature and room temperature could be effective in minimizing the number of measurements. That is, stabilizing water sample temperature and room temperature could shorten the measurement time.

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