RESEARCH DATA

This dataset was generated to investigate the effects of experimental warming and nitrogen addition, as well as their interactive effects, on key soil nitrogen mineralization processes, using a natural control (CK) as a reference. Specifically, the dataset focuses on the responses of digestion, ammonification, and nitrification processes under nitrogen addition (N), warming (W), and combined warming and nitrogen addition (W×N) treatments. The underlying hypothesis is that warming and nitrogen inputs alter soil physicochemical conditions and microbially mediated enzyme processes, thereby regulating inorganic nitrogen availability and nitrogen mineralization rates.
The data were obtained from a combination of field manipulation experiments and laboratory incubation experiments. Four treatments were established: natural control (CK), nitrogen addition (N), warming (W), and warming × nitrogen addition (W×N). Soil samples were collected periodically under each treatment. Measurements included soil total nitrogen (TN), ammonium nitrogen (NH₄⁺–N), and nitrate nitrogen (NO₃⁻–N). Based on changes in inorganic nitrogen concentrations before and after incubation, digestion rate, ammonification rate, nitrification rate, and net nitrogen mineralization rate were calculated. In addition, soil enzyme activities related to nitrogen transformation were measured to characterize the microbial potential driving soil nitrogen cycling.
The dataset also includes concurrently measured soil temperature and soil moisture, which were used to characterize environmental conditions under different treatments and to assess their regulatory effects on soil nitrogen mineralization processes. All variables were obtained using consistent sampling, analytical, and quality control procedures. Data are reported in internationally accepted units, and missing or abnormal values are clearly identified in the data files.
This dataset can be used to evaluate the mechanisms underlying soil nitrogen mineralization responses to warming and nitrogen addition under global change scenarios, and it provides a valuable data source for nitrogen cycling model parameterization, multi-factor interaction analyses, and cross-site comparative studies.