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Title:   Author  item
                                            McCarty, Gregoryitem
                                            Gish, Timothyitem
                                            Daughtry, Craig
  Submitted to: American Society of Agronomy Meetings
                                    Publication Type: Abstract Only
                                    Publication Acceptance Date: 9/10/2001
                                    Publication  Date: N/A
                                    Citation: N/AInterpretive Summary:
                                Technical Abstract: There is substantial need to assess the spatial structure of plant available nitrogen in agricultural ecosystems for implementation of site specific management. Efforts to develop laboratory soil tests to predict nitrogen with mineralization potential as an indicator of available nitrogen for crop growth have had limited success. While the pre-sidedress  nitrate test (PSNT) has shown some promise, it has substantial logistical difficulties that hinders implementation by farmers. The importance of landscape level parameters driving the spatial structure of plant available nitrogen may explain why random point-sample methods fail. An assessment of how landscape influences the spatial distribution of processes governing the nitrogen cycle was conducted at the Beltsville Agricultural Research Center, Beltsville, Maryland. Physical, chemical and biological parameters as well as surface and subsurface topographic features were evaluated in  assessing nitrogen behavior on a watershed scale. The spatial structure of various nitrogen cycling processes was found to be closely linked to surface features such as topographical curvature. These findings suggest that landscape parameters will be a critical driving force in developing nitrogen management models. Such models when used with remotely sensed data for crop nitrogen status could facilitate site specific management of nitrogen for crop production, thus leading to reduced nitrogen loss from agricultural ecosystems.


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