9 resultados para subjective global assessment

em Publishing Network for Geoscientific


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Limited availability of P in soils to crops may be due to deficiency and/or severe P retention. Earlier studies that drew on large soil profile databases have indicated that it is not (yet) feasible to present meaningful values for "plant-available" soil P, obtained according to comparable analytical methods, that may be linked to soil geographical databases derived from 1:5 million scale FAO Digital Soil Map of the World, such as the 5 x 5 arc-minute version of the ISRIC-WISE database. Therefore, an alternative solution for studying possible crop responses to fertilizer-P applied to soils, at a broad scale, was sought. The approach described in this report considers the inherent capacity of soils to retain phosphorus (P retention), in various forms. Main controlling factors of P retention processes, at the broad scale under consideration, are considered to be pH, soil mineralogy, and clay content. First, derived values for these properties were used to rate the inferred capacity for P retention of the component soil units of each map unit (or grid cell) using four classes (i.e., Low, Moderate, High, and Very High). Subsequently, the overall soil phosphorus retention potential was assessed for each mapping unit, taking into account the P-ratings and relative proportion of each component soil unit. Each P retention class has been assigned to a likely fertilizer P recovery fraction, derived from the literature, thereby permitting spatially more detailed, integrated model-based studies of environmental sustainability and agricultural production at the global and continental level (< 1:5 million). Nonetheless, uncertainties remain high; the present analysis provides an approximation of world soil phosphorus retention potential.

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In addition to enhance agricultural productivity, synthetic nitrogen (N) and phosphorous (P) fertilizer application in croplands dramatically altered global nutrient budget, water quality, greenhouse gas balance, and their feedbacks to the climate system. However, due to the lack of geospatial fertilizer input data, current Earth system/land surface modeling studies have to ignore or use over-simplified data (e.g., static, spatially uniform fertilizer use) to characterize agricultural N and P input over decadal or century-long period. We therefore develop a global time-series gridded data of annual synthetic N and P fertilizer use rate in croplands, matched with HYDE 3,2 historical land use maps, at a resolution of 0.5º latitude by longitude during 1900-2013. Our data indicate N and P fertilizer use rates 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) survey of country-level fertilizer input were available. Considering cropland expansion, increase of total fertilizer consumption amount is even larger. Hotspots of agricultural N fertilizer use shifted from the U.S. and Western Europe in the 1960s to East Asia in the early 21st century. P fertilizer input show the similar pattern with additional hotspot in Brazil. We find a global increase of fertilizer N/P ratio by 0.8 g N/g P per decade (p< 0.05) during 1961-2013, which may have important global implication of human impacts on agroecosystem functions in the long run. Our data can serve as one of critical input drivers for regional and global assessment on agricultural productivity, crop yield, agriculture-derived greenhouse gas balance, global nutrient budget, land-to-aquatic nutrient loss, and ecosystem feedback to the climate system.

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Uncertainty information for global leaf area index (LAI) products is important for global modeling studies but usually difficult to systematically obtain at a global scale. Here, we present a new method that cross-validates existing global LAI products and produces consistent uncertainty information. The method is based on a triple collocation error model (TCEM) that assumes errors among LAI products are not correlated. Global monthly absolute and relative uncertainties, in 0.05° spatial resolutions, were generated for MODIS, CYCLOPES, and GLOBCARBON LAI products, with reasonable agreement in terms of spatial patterns and biome types. CYCLOPES shows the lowest absolute and relative uncertainties, followed by GLOBCARBON and MODIS. Grasses, crops, shrubs, and savannas usually have lower uncertainties than forests in association with the relatively larger forest LAI. With their densely vegetated canopies, tropical regions exhibit the highest absolute uncertainties but the lowest relative uncertainties, the latter of which tend to increase with higher latitudes. The estimated uncertainties of CYCLOPES generally meet the quality requirements (± 0.5) proposed by the Global Climate Observing System (GCOS), whereas for MODIS and GLOBCARBON only non-forest biome types have met the requirement. Nevertheless, none of the products seems to be within a relative uncertainty requirements of 20%. Further independent validation and comparative studies are expected to provide a fair assessment of uncertainties derived from TCEM. Overall, the proposed TCEM is straightforward and could be automated for the systematic processing of real time remote sensing observations to provide theoretical uncertainty information for a wider range of land products.

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1. With the global increase in CO2 emissions, there is a pressing need for studies aimed at understanding the effects of ocean acidification on marine ecosystems. Several studies have reported that exposure to CO2 impairs chemosensory responses of juvenile coral reef fishes to predators. Moreover, one recent study pointed to impaired responses of reef fish to auditory cues that indicate risky locations. These studies suggest that altered behaviour following exposure to elevated CO2 is caused by a systemic effect at the neural level. 2. The goal of our experiment was to test whether juvenile damselfish Pomacentrus amboinensis exposed to different levels of CO2 would respond differently to a potential threat, the sight of a large novel coral reef fish, a spiny chromis, Acanthochromis polyancanthus, placed in a watertight bag. 3. Juvenile damselfish exposed to 440 (current day control), 550 or 700 µatm CO2 did not differ in their response to the chromis. However, fish exposed to 850 µatm showed reduced antipredator responses; they failed to show the same reduction in foraging, activity and area use in response to the chromis. Moreover, they moved closer to the chromis and lacked any bobbing behaviour typically displayed by juvenile damselfishes in threatening situations. 4. Our results are the first to suggest that response to visual cues of risk may be impaired by CO2 and provide strong evidence that the multi-sensory effects of CO2 may stem from systematic effects at the neural level.

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This dataset presents the first global fuel map, containing all the parameters required to be input in the Fuel Characteristic Classification System (FCCS). The dataset was developed from different spatial variables, both based on satellite Earth observation products and fuel databases, and is comprised by a global fuelbed map and a database that includes the parameters of each fuelbed that affect fire behavior and effects. A total of 274 fuelbeds were created and parameterized, and can be input into FCCS to obtain fire potentials, surface fire behavior and carbon biomass for each fuelbed. The global fuel dataset can be used for a varied range of applications, including fire danger assessment, fire behavior estimations, fuel consumption calculations and emissions inventories.

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In 2005, the International Ocean Colour Coordinating Group (IOCCG) convened a working group to examine the state of the art in ocean colour data merging, which showed that the research techniques had matured sufficiently for creating long multi-sensor datasets (IOCCG, 2007). As a result, ESA initiated and funded the DUE GlobColour project (http://www.globcolour.info/) to develop a satellite based ocean colour data set to support global carbon-cycle research. It aims to satisfy the scientific requirement for a long (10+ year) time-series of consistently calibrated global ocean colour information with the best possible spatial coverage. This has been achieved by merging data from the three most capable sensors: SeaWiFS on GeoEye's Orbview-2 mission, MODIS on NASA's Aqua mission and MERIS on ESA's ENVISAT mission. In setting up the GlobColour project, three user organisations were invited to help. Their roles are to specify the detailed user requirements, act as a channel to the broader end user community and to provide feedback and assessment of the results. The International Ocean Carbon Coordination Project (IOCCP) based at UNESCO in Paris provides direct access to the carbon cycle modelling community's requirements and to the modellers themselves who will use the final products. The UK Met Office's National Centre for Ocean Forecasting (NCOF) in Exeter, UK, provides an understanding of the requirements of oceanography users, and the IOCCG bring their understanding of the global user needs and valuable advice on best practice within the ocean colour science community. The three year project kicked-off in November 2005 under the leadership of ACRI-ST (France). The first year was a feasibility demonstration phase that was successfully concluded at a user consultation workshop organised by the Laboratoire d'Océanographie de Villefranche, France, in December 2006. Error statistics and inter-sensor biases were quantified by comparison with insitu measurements from moored optical buoys and ship based campaigns, and used as an input to the merging. The second year was dedicated to the production of the time series. In total, more than 25 Tb of input (level 2) data have been ingested and 14 Tb of intermediate and output products created, with 4 Tb of data distributed to the user community. Quality control (QC) is provided through the Diagnostic Data Sets (DDS), which are extracted sub-areas covering locations of in-situ data collection or interesting oceanographic phenomena. This Full Product Set (FPS) covers global daily merged ocean colour products in the time period 1997-2006 and is also freely available for use by the worldwide science community at http://www.globcolour.info/data_access_full_prod_set.html. The GlobColour service distributes global daily, 8-day and monthly data sets at 4.6 km resolution for, chlorophyll-a concentration, normalised water-leaving radiances (412, 443, 490, 510, 531, 555 and 620 nm, 670, 681 and 709 nm), diffuse attenuation coefficient, coloured dissolved and detrital organic materials, total suspended matter or particulate backscattering coefficient, turbidity index, cloud fraction and quality indicators. Error statistics from the initial sensor characterisation are used as an input to the merging methods and propagate through the merging process to provide error estimates for the output merged products. These error estimates are a key component of GlobColour as they are invaluable to the users; particularly the modellers who need them in order to assimilate the ocean colour data into ocean simulations. An intensive phase of validation has been undertaken to assess the quality of the data set. In addition, inter-comparisons between the different merged datasets will help in further refining the techniques used. Both the final products and the quality assessment were presented at a second user consultation in Oslo on 20-22 November 2007 organised by the Norwegian Institute for Water Research (NIVA); presentations are available on the GlobColour WWW site. On request of the ESA Technical Officer for the GlobColour project, the FPS data set was mirrored in the PANGAEA data library.

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A circumpolar representative and consistent wetland map is required for a range of applications ranging from upscaling of carbon fluxes and pools to climate modelling and wildlife habitat assessment. Currently available data sets lack sufficient accuracy and/or thematic detail in many regions of the Arctic. Synthetic aperture radar (SAR) data from satellites have already been shown to be suitable for wetland mapping. Envisat Advanced SAR (ASAR) provides global medium-resolution data which are examined with particular focus on spatial wetness patterns in this study. It was found that winter minimum backscatter values as well as their differences to summer minimum values reflect vegetation physiognomy units of certain wetness regimes. Low winter backscatter values are mostly found in areas vegetated by plant communities typically for wet regions in the tundra biome, due to low roughness and low volume scattering caused by the predominant vegetation. Summer to winter difference backscatter values, which in contrast to the winter values depend almost solely on soil moisture content, show expected higher values for wet regions. While the approach using difference values would seem more reasonable in order to delineate wetness patterns considering its direct link to soil moisture, it was found that a classification of winter minimum backscatter values is more applicable in tundra regions due to its better separability into wetness classes. Previous approaches for wetland detection have investigated the impact of liquid water in the soil on backscatter conditions. In this study the absence of liquid water is utilized. Owing to a lack of comparable regional to circumpolar data with respect to thematic detail, a potential wetland map cannot directly be validated; however, one might claim the validity of such a product by comparison with vegetation maps, which hold some information on the wetness status of certain classes. It was shown that the Envisat ASAR-derived classes are related to wetland classes of conventional vegetation maps, indicating its applicability; 30% of the land area north of the treeline was identified as wetland while conventional maps recorded 1-7%.

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A global sea surface temperature calibration based on the relative abundance of different morphotypes within the coccolithophore genus Gephyrocapsa in Holocene deep-sea sediments is presented. There is evidence suggesting that absolute sea surface temperature for a given location can be calculated from the relative abundance of Gephyrocapsa morphotypes in sediment samples, with a standard error comparable to temperature estimates derived from other temperature proxies such as planktic foraminifera transfer functions. A total of 110 Holocene sediment samples were selected from the Pacific, Indian, and Atlantic Oceans covering a mean sea surface temperature gradient from 13.6° to 29.3°C. Standard multiple linear regression analyses were applied to this data set, linking the relative abundance of Gephyrocapsa morphotypes to sea surface temperature. The best model revealed an r**2 of 0.83 with a standard residual error of 1.78°C for the estimation of mean sea surface temperature. This new proxy provides a unique opportunity for the reconstruction of paleotemperatures with a very small amount of sample material due to the minute size of coccoliths, permitting examination of thinly laminated sediments (e.g., a pinhead of material from laminated sediments for the reconstruction of annual sea surface temperature variations). Such fine-scale resolution is currently not possible with any other proxy. Application of this new paleotemperature proxy may allow new paleoenvironmental interpretations in the late Quaternary period and discrepancies between the different currently used paleotemperature proxies might be resolved.

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This paper provides a method for constructing a new historical global nitrogen fertilizer application map (0.5° × 0.5° resolution) for the period 1961-2010 based on country-specific information from Food and Agriculture Organization statistics (FAOSTAT) and various global datasets. This new map incorporates the fraction of NH+4 (and NONO-3) in N fertilizer inputs by utilizing fertilizer species information in FAOSTAT, in which species can be categorized as NH+4 and/or NO-3-forming N fertilizers. During data processing, we applied a statistical data imputation method for the missing data (19 % of national N fertilizer consumption) in FAOSTAT. The multiple imputation method enabled us to fill gaps in the time-series data using plausible values using covariates information (year, population, GDP, and crop area). After the imputation, we downscaled the national consumption data to a gridded cropland map. Also, we applied the multiple imputation method to the available chemical fertilizer species consumption, allowing for the estimation of the NH+4/NO-3 ratio in national fertilizer consumption. In this study, the synthetic N fertilizer inputs in 2000 showed a general consistency with the existing N fertilizer map (Potter et al., 2010, doi:10.1175/2009EI288.1) in relation to the ranges of N fertilizer inputs. Globally, the estimated N fertilizer inputs based on the sum of filled data increased from 15 Tg-N to 110 Tg-N during 1961-2010. On the other hand, the global NO-3 input started to decline after the late 1980s and the fraction of NO-3 in global N fertilizer decreased consistently from 35 % to 13 % over a 50-year period. NH+4 based fertilizers are dominant in most countries; however, the NH+4/NO-3 ratio in N fertilizer inputs shows clear differences temporally and geographically. This new map can be utilized as an input data to global model studies and bring new insights for the assessment of historical terrestrial N cycling changes.