1International Center for Climate and Global Change Research and School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL 36849, USA
2Research Center for Eco-Environmental Sciences, State Key Laboratory of Urban and Regional Ecology, Chinese Academy of Sciences, Beijing 100085, China
3Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
4Statistics Division, Food and Agriculture Organization of the United Nations, Via Terme di Caracalla, Rome, Italy
5College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China
6School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
7Department of Ecosystem Science and Sustainability, Colorado State University, Fort Collins, CO 80523, USA
8Department of Soil and Crop Sciences, Colorado State University, Fort Collins, CO 80523, USA
9Biogeochemical Cycle Modeling and Analysis Section, Earth System Division, National Institute for Environmental Studies 16-2, Onogawa, Tsukuba, 305-8506, Japan
10Forest Ecosystems and Society, Oregon State University, Corvallis, OR 97330, USA
11Department of Natural Resource Ecology and Management, Oklahoma State University, Stillwater, OK 74078, USA
12International Food Policy Research Institute (IFPRI), 1201 Eye Street, NW, Washington, DC 20005, USA
13Department of Environment, Geology, and Natural Resources, Ball State University, Muncie, IN 47306, USA
1International Center for Climate and Global Change Research and School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL 36849, USA
2Research Center for Eco-Environmental Sciences, State Key Laboratory of Urban and Regional Ecology, Chinese Academy of Sciences, Beijing 100085, China
3Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
4Statistics Division, Food and Agriculture Organization of the United Nations, Via Terme di Caracalla, Rome, Italy
5College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China
6School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
7Department of Ecosystem Science and Sustainability, Colorado State University, Fort Collins, CO 80523, USA
8Department of Soil and Crop Sciences, Colorado State University, Fort Collins, CO 80523, USA
9Biogeochemical Cycle Modeling and Analysis Section, Earth System Division, National Institute for Environmental Studies 16-2, Onogawa, Tsukuba, 305-8506, Japan
10Forest Ecosystems and Society, Oregon State University, Corvallis, OR 97330, USA
11Department of Natural Resource Ecology and Management, Oklahoma State University, Stillwater, OK 74078, USA
12International Food Policy Research Institute (IFPRI), 1201 Eye Street, NW, Washington, DC 20005, USA
13Department of Environment, Geology, and Natural Resources, Ball State University, Muncie, IN 47306, USA
Received: 11 Mar 2022 – Discussion started: 01 Jun 2022
Abstract. Excessive anthropogenic nitrogen (N) inputs to the biosphere have disrupted the global nitrogen cycle. To better quantify the spatial and temporal patterns of anthropogenic N enrichments, assess their impacts on the biogeochemical cycles of the planet and other living organisms, and improve nitrogen use efficiency (NUE) for sustainable development, we have developed a comprehensive and synthetic dataset for reconstructing the History of anthropogenic N inputs (HaNi) to the terrestrial biosphere. The HaNi dataset takes advantage of different data sources in a spatiotemporally consistent way to generate a set of high-resolution gridded N input products from the preindustrial to present (1860–2019). The HaNi dataset includes annual rates of synthetic N fertilizer, manure application/deposition, and atmospheric N deposition in cropland, pasture, and rangeland at a spatial resolution of 5-arcmin. Specifically, the N inputs are categorized, according to the N forms and land uses, as ten types: 1) NH4+-N fertilizer applied to cropland, 2) NO3-N fertilizer applied to cropland, 3) NH4+-N fertilizer applied to pasture, 4) NO3-N fertilizer applied to pasture, 5) manure N application on cropland, 6) manure N application on pasture, 7) manure N deposition on pasture, 8) manure N deposition on rangeland, 9) NHx-N deposition, and 10) NOy-N deposition. The total anthropogenic N (TN) inputs to global terrestrial ecosystems increased from 29.05 Tg N yr-1 in the 1860s to 267.23 Tg N yr-1 in the 2010s, with the dominant N source changing from atmospheric N deposition (before the 1900s) to manure N (the 1910s–2000s), and to synthetic fertilizer in the 2010s. The proportion of synthetic NH4+-N fertilizer increased from 64 % in the 1960s to 90 % in the 2010s, while synthetic NO3-N fertilizer decreased from 36 % in the 1960s to 10 % in the 2010s. Hotspots of TN inputs shifted from Europe and North America to East and South Asia during the 1960s-2010s. Such spatial and temporal dynamics captured by the HaNi dataset are expected to facilitate a comprehensive assessment of the coupled human-earth system and address a variety of social welfare issues, such as climate-biosphere feedback, air pollution, water quality, and biodiversity.
This study is a very impressive work that comprehensively reconstructs the History of anthropogenic N inputs to the terrestrial biosphere, especially with consistent temporal coverage, spatial resolution, and spatial allocation. This work is beneficial for a comprehensive assessment of the coupled human-earth system and addresses a variety of social welfare issues, including climate-biosphere feedback, air pollution, water quality, and biodiversity. Although uncertainties and limitations occur in this global N input dataset, I think this work has taken a big step forward anyway. This paper is reasonably well written. I fully support the submission of this paper with minor revisions. The detailed comments are as follows:
Line 200, the subtitle is not quite correct, since in this part you also describe the method for N fertilizer use in the pasture.
Line 210-241 Does the method of spatializing manure application in pasture differ from that in Xu et al. (2019)? Can you explain where the improvements are made? I must be understanding something wrong, otherwise, I can't figure out why the ratios of the two methods are exactly opposite. What’s the definition of Napp_c,y, and how to get the value of Napp_c,y. In addition, the GNprod_c,y you get should be adjusted and compared with the national-level application amounts from the FAOSTAT database.
Line 224, the reference of Dong et al., 2006 can not be found in the reference list. Please check throughout the manuscript.
Line 247-248. The method you used for spatializing manure deposition in pasture and rangeland is similar to the method for manure deposition to pasture in Xu et al., not the manure application method.
Line 255-256, what’s the full name of SSP585 and TRENDY. A full name is required on the first occurrence. Please check throughout the manuscript.
Line 280-282, when manure N and atmospheric N deposition accounted for 37% and 24% of N inputs refer to which year? The sentence is not very clear and easy to cause ambiguity. Please rephrase it.
You might cite and compare with the recent work of Wang et al. (published in National Science Review, 7: 441-452, 2020), which developed crop-specific N fertilizer inputs applied to cropland from 1961-2014.
Nitrogen is one of the critical nutrients for life growth. Evaluating the Nitrogen inputs change due to human activities is necessary for nutrient management and pollution control. In this study, we generated a historical dataset of Nitrogen input to land at global scale. This dataset consists of Nitrogen fertilizer, manure, atmospheric deposition inputs to cropland, pasture, and rangeland at high resolution from 1860 to 2019.
Nitrogen is one of the critical nutrients for life growth. Evaluating the Nitrogen inputs change...
