273 research outputs found

    Global nitrogen and phosphorus fertilizer use for agriculture production in the past half century: shifted hot spots and nutrient imbalance

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    In addition to enhancing agricultural productivity, synthetic nitrogen (N) and phosphorous (P) fertilizer application in croplands dramatically alters global nutrient budget, water quality, greenhouse gas balance, and their feedback to the climate system. However, due to the lack of geospatial fertilizer input data, current Earth system and land surface modeling studies have to ignore or use oversimplified data (e.g., static, spatially uniform fertilizer use) to characterize agricultural N and P input over decadal or century-long periods. In this study, we therefore develop global time series gridded data of annual synthetic N and P fertilizer use rate in agricultural lands, matched with HYDE 3.2 historical land use maps, at a resolution of 0.5° × 0.5° latitude–longitude during 1961–2013. Our data indicate N and P fertilizer use rates on per unit cropland area increased by approximately 8 times and 3 times, respectively, since the year 1961 when IFA (International Fertilizer Industry Association) and FAO (Food and Agricultural Organization) surveys of country-level fertilizer input became available. Considering cropland expansion, the increase in total fertilizer consumption is even larger. Hotspots of agricultural N fertilizer application shifted from the US and western Europe in the 1960s to eastern Asia in the early 21st century. P fertilizer input shows a similar pattern with an additional current hotspot in Brazil. We found a global increase in fertilizer N∕P ratio by 0.8gNg−1P per decade (p \u3c 0.05) during 1961–2013, which may have an important global implication for human impacts on agroecosystem functions in the long run. Our data can serve as one of critical input drivers for regional and global models to assess the impacts of nutrient enrichment on climate system, water resources, food security, etc. Datasets available at doi:10.1594/PANGAEA.863323

    A dataset of 30-meter annual vegetation phenology indicators (1985–2015) in urban areas of the conterminous United States

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    Fine-resolution satellite observations show great potential for characterizing seasonal and annual dynamics of vegetation phenology in urban domains, from local to regional and global scales. However, most previous studies were conducted using coarse or moderate resolution data, which are inadequate for characterizing the spatiotemporal dynamics of vegetation phenology in urban domains. In this study, we produced an annual vegetation phenology dataset in urban ecosystems for the conterminous United States (US), using all available Landsat images on the Google Earth Engine (GEE) platform. First, we characterized the long-term mean seasonal pattern of phenology indicators of the start of season (SOS) and the end of season (EOS), using a double logistic model. Then, we identified the annual variability of these two phenology indicators by measuring the difference of dates when the vegetation index in a specific year reaches the same magnitude as its long-term mean. The derived phenology indicators agree well with in-situ observations from PhenoCam network and Harvard Forest. Comparing with results derived from the moderate resolution imaging spectroradiometer (MODIS) data, our Landsat derived phenology indicators can provide more spatial details. Also, temporal trends of phenology indicators (e.g., SOS) derived from Landsat and MODIS are consistent overall, but the Landsat derived results from 1985 have a longer temporal span compared to MODIS from 2001. In general, there is a spatially explicit pattern of phenology indicators from the North to the South in cities in the conterminous US, with an overall advanced SOS in the past three decades. The derived phenology product in the US urban domains at the national level is of great use for urban ecology studies for its fine spatial resolution (30 m) and long temporal span (30 years). The data are available at https://doi.org/10.6084/m9.figshare.7685645.v2

    Global gross primary productivity and water use efficiency changes under drought stress

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    Drought can affect the structure, composition and function of terrestrial ecosystems, yet drought impacts and post-drought recovery potentials of different land cover types have not been extensively studied at a global scale. We evaluated drought impacts on gross primary productivity (GPP), evapotranspiration (ET), and water use efficiency (WUE) of different global terrestrial ecosystems, as well as the drought-resilience of each ecosystem type during the period of 2000 to 2011. Using GPP as biome vitality indicator against drought stress, we developed a model to examine ecosystem resilience represented by the length of recovery days (LRD). LRD presented an evident gradient of high (\u3e60 days) in mid-latitude region and low (\u3c60 days) in low (tropical area) and high (boreal area) latitude regions. As average GPP increased, the LRD showed a significantly decreasing trend, indicating readiness to recover after drought, across various land cover types (R 2 = 0.68, p \u3c 0.0001). Moreover, zonal analysis revealed that the most dramatic reduction of the drought-induced GPP was found in the mid-latitude region of the Northern Hemisphere (48% reduction), followed by the low-latitude region of the Southern Hemisphere (13% reduction). In contrast, a slightly enhanced GPP (10%) was evident in the tropical region under drought impact. Additionally, the highest drought-induced reduction of ET was found in the Mediterranean area, followed by Africa. Water use efficiency, however, showed a pattern of decreasing in the Northern Hemisphere and increasing in the Southern Hemisphere. Drought induced reductions of WUE ranged from 0.96% to 27.67% in most of the land cover types, while the increases of WUE found in Evergreen Broadleaf Forest and savanna were about 7.09% and 9.88%, respectively. These increases of GPP and WUE detected during drought periods could either be due to water-stress induced responses or data uncertainties, which require further investigation
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