The effects of acorn (Quercus crispula) abundance on the population dynamics of three rodent species (Apodemus speciosus, A. argenteus, and Clethrionomys rufocanus) were analyzed using time series data (1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006). The data were obtained in a forest in northern Hokkaido, Japan, by live trapping rodents and directly counting acorns on the ground. Apodemus speciosus generally increased in abundance following acorn masting. However, the clear effect of acorn abundance was not detected for the other two rodent species. Acorns of Q. crispula contain tannins, which potentially have detrimental effects on herbivores. Apodemus speciosus may reduce the damage caused by acorn tannins with tannin-binding salivary proteins and tannaseproducing bacteria, whereas such physiological tolerance to tannins is not known in the other two rodent species. The differences in the effects of acorns between the three species may be due to differences in their physiological tolerance to tannins.

We analysed the effects of Quercus crispula acorn abundance on the density 44 dependence of the large Japanese wood mouse Apodemus speciosus using time series data (1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007). The data were obtained in a forest in northern Hokkaido, Japan, by live-46 trapping rodents and directly counting acorns on the ground. Acorn abundance in one year clearly influenced the abundance of wood mice in the following year in all models examined 48 based on the Gompertz and Ricker model; in addition, the abundance of wood mice had effects on the population. Acorn abundance influenced the strength of density dependence 50 (intraspecific competition) of the wood mouse population. When the abundance of acorns was high, density dependence was relaxed and as a result the equilibrium density at which the 52 population growth rate decreased to zero became higher. Those effects of acorn abundance were regarded as a nonlinear perturbation effect (sensu Royama 1992). The nonlinearity of 54 density dependence was also detected; higher densities had stronger effects on population growth rates.56

The water chemistry of a stream reflects the biogeochemical processes occurring in upstream forests. Anthropogenic disturbances in forests, such as cutting trees, altering the nitrogen (N) cycle, and increase in N leaching from the soil to streams, potentially cause acidification or eutrophication downstream. In forests with dense understory vegetation, mechanical site preparation following tree cutting is commonly used to improve the early establishment of tree seedlings. In cool‐temperate forests in northern Hokkaido, Japan, dense understory vegetation (mainly comprising Sasa dwarf bamboo) inhibits forest regeneration after tree cutting. Soil scarification is a common site preparation technique for eliminating Sasa bamboo and improving forest regeneration. Long‐term data are useful for examining the temporal changes in stream water chemistry exposed to different specific forest management practices under changing environment (e.g., climate change and atmospheric N deposition). For 14 years (2003–2016), we observed the stream water chemistry in naturally forested watersheds and at one point after the confluence of all streams in Uryu Experimental Forest of Hokkaido University (North Hokkaido Experimental Forests Site of JaLTER) in northern Japan. We also monitored stream discharge, water level and stream water temperature in each watershed. Water samples were collected from the outlets of 10 watersheds. The forest management practice in each watershed includes clear‐cutting, soil scarification in sparse forest with dense understory Sasa, and clear‐cutting and soil scarification followed by soil replacement. Long‐term data in the six unmanaged watersheds are also valuable as a background information to analyze the effect of long‐term climate, environment and vegetation changes on stream water chemistry. The measured water quality data of 1,873 water samples include the ion concentrations (Cl−, NO3−, SO42−, Na+, NH4+, K+, Mg2+, and Ca2+), pH, and electrical conductivity (EC) in the stream water. The range of the concentrations of Cl−, NO3−, SO42−, Mg2+, and Ca2+ in the stream water across all the watersheds throughout the observed periods (minimum to maximum) were 3.35–23.67, 0.01–8.68, 0.83–4.01, 0.45–2.55 and 0.72–6.16 mg L−1, respectively. Similarly, the stream pH and EC ranged from 6.04 to 7.53 and 3.14 to 9.47 mS m−1, respectively. The complete data set for this abstract published in the Data Paper section of the journal is available in electronic format in MetaCat in JaLTER at http://db.cger.nies.go.jp/JaLTER/metacat/metacat/datapaper%202020‐04.1/jalter‐en. [Correction added on 7 September 2020, after first online publication: JaLTER URL has been updated.]