Long-term modelling of nitrogen turnover and critical loads in a forested catchment using the INCA model

Many forest ecosystems in Central Europe have reached the status of N saturation due to chronically high N deposition. In consequence, the NO₃ leaching into ground- and surface waters is often substantial. Critical loads have been defined to abate the negative consequences of the NO₃ leaching such as soil acidification and nutrient losses. The steady state mass balance method is normally used to calculate critical loads for N deposition in forest ecosystems. However, the steady state mass balance approach is limited because it does not take into account hydrology and the time until the steady state is reached. The aim of this study was to test the suitability of another approach: the dynamic model INCA (Integrated Nitrogen Model for European Catchments). Long-term effects of changing N deposition and critical loads for N were simulated using INCA for the Lehstenbach spruce catchment (Fichtelgebirge, NE Bavaria, Germany) under different hydrological conditions. <br>Long-term scenarios of either increasing or decreasing N deposition indicated that, in this catchment, the response of nitrate concentrations in runoff to changing N deposition is buffered by a large groundwater reservoir. The critical load simulated by the INCA model with respect to a nitrate concentration of 0.4 mg N l^–1 as threshold value in runoff was 9.7 kg N ha^–1yr^–1 compared to 10 kg ha^–1yr^–1 for the steady state model. Under conditions of lower precipitation (520 mm) the resulting critical load was 7.7 kg N ha^–1yr^–1 , suggesting the necessity to account for different hydrological conditions when calculating critical loads. The INCA model seems to be suitable to calculate critical loads for N in forested catchments under varying hydrological conditions e.g. as a consequence of climate change.</p> <p style='line-height: 20px;'><b>Keywords: </b>forest ecosystem, N saturation, critical load, modelling, long-term scenario, nitrate leaching, critical loads reduction, INCA</p

Long-term modelling of nitrogen turnover and critical loads in a forested catchment using the INCA model

International audienceMany forest ecosystems in Central Europe have reached the status of N saturation due to chronically high N deposition. In consequence, the NO3 leaching into ground- and surface waters is often substantial. Critical loads have been defined to abate the negative consequences of the NO3 leaching such as soil acidification and nutrient losses. The steady state mass balance method is normally used to calculate critical loads for N deposition in forest ecosystems. However, the steady state mass balance approach is limited because it does not take into account hydrology and the time until the steady state is reached. The aim of this study was to test the suitability of another approach: the dynamic model INCA (Integrated Nitrogen Model for European Catchments). Long-term effects of changing N deposition and critical loads for N were simulated using INCA for the Lehstenbach spruce catchment (Fichtelgebirge, NE Bavaria, Germany) under different hydrological conditions. Long-term scenarios of either increasing or decreasing N deposition indicated that, in this catchment, the response of nitrate concentrations in runoff to changing N deposition is buffered by a large groundwater reservoir. The critical load simulated by the INCA model with respect to a nitrate concentration of 0.4 mg N l?1 as threshold value in runoff was 9.7 kg N ha?1yr?1 compared to 10 kg ha?1yr?1 for the steady state model. Under conditions of lower precipitation (520 mm) the resulting critical load was 7.7 kg N ha?1yr?1 , suggesting the necessity to account for different hydrological conditions when calculating critical loads. The INCA model seems to be suitable to calculate critical loads for N in forested catchments under varying hydrological conditions e.g. as a consequence of climate change. Keywords: forest ecosystem, N saturation, critical load, modelling, long-term scenario, nitrate leaching, critical loads reduction, INCA</p

Comparative simulation of the nitrogen dynamics using the INCA model and a neural network analysis: implications for improved nitrogen modelling

International audienceContinuing deposition of nitrogen in forested catchments affects stream and groundwater quality. However, the dependence of nitrogen dynamics on climatic and hydrological boundary conditions is still poorly understood. These dynamics have been investigated by applying the process-oriented Integrated Nitrogen in CAtchments (INCA) model and an artificial neural network to the data set from the forested Steinkreuz catchment in South Germany. The data comprise daily values of precipitation, air temperature and discharge of the catchment runoff. The INCA model simulated the mean nitrate concentration in the stream as well as seasonal fluctuations but it underestimated the short-term variance of the observed stream water nitrate concentration, especially the pronounced concentration peaks in late summer. In contrast, the artificial neural network matched the short-term dynamics using non-linear regressions with stream discharge and air temperature data. The results provide strong evidence that the short-term dynamics of stream nitrate concentration during storm-flow were generated in the riparian zone, which is less than 1% of the catchment area, and is not considered explicitly in the INCA model. The concentration peaks have little effect on the catchment's nitrogen budget and the shallow groundwater data suggest that the short-term hydrological dynamics also govern groundwater recharge in the upland parts of the catchment. This substantial underestimate by the INCA model parameterisation is balanced by a corresponding underestimate of denitrification in clayey layers of the deeper aquifer. A better understanding of these processes is necessary to improve long-term risk assessments. Keywords: catchment, runoff, nitrogen, INCA, artificial neural network, flushin

N fluxes in two nitrogen saturated forested catchments in Germany: dynamics and modelling with INCA

International audienceThe N cycle in forests of the temperate zone in Europe has been changed substantially by the impact of atmospheric N deposition. Here, the fluxes and concentrations of mineral N in throughfall, soil solution and runoff in two German catchments, receiving high N inputs are investigated to test the applicability of an Integrated Nitrogen Model for European Catchments (INCA) to small forested catchments. The Lehstenbach catchment (419 ha) is located in the German Fichtelgebirge (NO Bavaria, 690-871 m asl.) and is stocked with Norway spruce (Picea abies (L.) Karst.) of different ages. The Steinkreuz catchment (55 ha) with European beech (Fagus sylvatica L.) as the dominant tree species is located in the Steigerwald (NW Bavaria, 400-460 m asl.). The mean annual N fluxes with throughfall were slightly higher at the Lehstenbach (24.6 kg N ha-1) than at the Steinkreuz (20.4 kg N ha-1). In both catchments the N fluxes in the soil are dominated by NO3. At Lehstenbach, the N output with seepage at 90 cm soil depth was similar to the N flux with throughfall. At Steinkreuz more than 50 % of the N deposited was retained in the upper soil horizons. In both catchments, the NO3 fluxes with runoff were lower than those with seepage. The average annual NO3 concentrations in runoff in both catchments were between 0.7 to 1.4 mg NO3-N L-1 and no temporal trend was observed. The N budgets at the catchment scale indicated similar amounts of N retention (Lehstenbach: 19 kg N ha-1yr-1 ; Steinkreuz: 17 kg N ha-1yr-1). The parameter settings of the INCA model were simplified to reduce the model complexity. In both catchments, the NO3 concentrations and fluxes in runoff were matched well by the model. The seasonal patterns with lower NO3 runoff concentrations in summer at the Lehstenbach catchment were replicated. INCA underestimated the increased N3 concentrations during short periods of rewetting in late autumn at the Steinkreuz catchment. The model will be a helpful tool for the calculation of "critical loads" for the N deposition in Central European forests including different hydrological regimes. Keywords: forest ecosystem, modelling, N budgets, N saturation, NO3 leaching, water quality, INCA</p

N fluxes in two nitrogen saturated forested catchments in Germany: dynamics and modelling with INCA

The N cycle in forests of the temperate zone in Europe has been changed substantially by the impact of atmospheric N deposition. Here, the fluxes and concentrations of mineral N in throughfall, soil solution and runoff in two German catchments, receiving high N inputs are investigated to test the applicability of an Integrated Nitrogen Model for European Catchments (INCA) to small forested catchments. The Lehstenbach catchment (419 ha) is located in the German Fichtelgebirge (NO Bavaria, 690-871 m asl.) and is stocked with Norway spruce <i>(Picea abies</i> (L.) Karst.) of different ages. The Steinkreuz catchment (55 ha) with European beech <i>(Fagus sylvatica</i> L.) as the dominant tree species is located in the Steigerwald (NW Bavaria, 400-460 m asl.). The mean annual N fluxes with throughfall were slightly higher at the Lehstenbach (24.6 kg N ha^-1) than at the Steinkreuz (20.4 kg N ha^-1). In both catchments the N fluxes in the soil are dominated by NO₃. At Lehstenbach, the N output with seepage at 90 cm soil depth was similar to the N flux with throughfall. At Steinkreuz more than 50 % of the N deposited was retained in the upper soil horizons. In both catchments, the NO₃ fluxes with runoff were lower than those with seepage. The average annual NO₃ concentrations in runoff in both catchments were between 0.7 to 1.4 mg NO₃-N L^-1 and no temporal trend was observed. The N budgets at the catchment scale indicated similar amounts of N retention (Lehstenbach: 19 kg N ha^-1yr^-1 ; Steinkreuz: 17 kg N ha^-1yr^-1). The parameter settings of the INCA model were simplified to reduce the model complexity. In both catchments, the NO₃ concentrations and fluxes in runoff were matched well by the model. The seasonal patterns with lower NO₃ runoff concentrations in summer at the Lehstenbach catchment were replicated. INCA underestimated the increased N₃ concentrations during short periods of rewetting in late autumn at the Steinkreuz catchment. The model will be a helpful tool for the calculation of âcritical loadsâ? for the N deposition in Central European forests including different hydrological regimes.</p> <p style='line-height: 20px;'><b>Keywords: </b>forest ecosystem, modelling, N budgets, N saturation, NO₃ leaching, water quality, INCA</p

Comparative simulation of the nitrogen dynamics using the INCA model and a neural network analysis: implications for improved nitrogen modelling

Continuing deposition of nitrogen in forested catchments affects stream and groundwater quality. However, the dependence of nitrogen dynamics on climatic and hydrological boundary conditions is still poorly understood. These dynamics have been investigated by applying the process-oriented Integrated Nitrogen in CAtchments (INCA) model and an artificial neural network to the data set from the forested Steinkreuz catchment in South Germany. The data comprise daily values of precipitation, air temperature and discharge of the catchment runoff. The INCA model simulated the mean nitrate concentration in the stream as well as seasonal fluctuations but it underestimated the short-term variance of the observed stream water nitrate concentration, especially the pronounced concentration peaks in late summer. In contrast, the artificial neural network matched the short-term dynamics using non-linear regressions with stream discharge and air temperature data. The results provide strong evidence that the short-term dynamics of stream nitrate concentration during storm-flow were generated in the riparian zone, which is less than 1% of the catchment area, and is not considered explicitly in the INCA model. The concentration peaks have little effect on the catchment’s nitrogen budget and the shallow groundwater data suggest that the short-term hydrological dynamics also govern groundwater recharge in the upland parts of the catchment. This substantial underestimate by the INCA model parameterisation is balanced by a corresponding underestimate of denitrification in clayey layers of the deeper aquifer. A better understanding of these processes is necessary to improve long-term risk assessments.</p> <p style='line-height: 20px;'><b>Keywords: </b>catchment, runoff, nitrogen, INCA, artificial neural network, flushin

Expression of HOXB2, a retinoic acid signaling target in pancreatic cancer and pancreatic intraepithelial neoplasia

Purpose: Despite significant progress in understanding the molecular pathology of pancreatic cancer and its precursor lesion: pancreatic intraepithelial neoplasia (PanIN), there remain no molecules with proven clinical utility as prognostic or therapeutic markers. Here, we used oligonucleotide microarrays to interrogate mRNA expression of pancreatic cancer tissue and normal pancreas to identify novel molecular pathways dysregulated in the development and progression of pancreatic cancer. Experimental Design: RNA was hybridized to Affymetrix Genechip HG-U133 oligonucleotide microarrays. A relational database integrating data from publicly available resources was created to identify candidate genes potentially relevant to pancreatic cancer. The protein expression of one candidate, homeobox B2 (HOXB2), in PanIN and pancreatic cancer was assessed using immunohistochemistry. Results: We identified aberrant expression of several components of the retinoic acid (RA) signaling pathway (RARa, MUC4, Id-1, MMP9, uPAR, HB-EGF, HOXB6, and HOXB2), many of which are known to be aberrantly expressed in pancreatic cancer and Pan IN. HOXB2, a downstream target of RA, was up-regulated 6.7-fold in pancreatic cancer compared with normal pancreas. Immunohistochemistry revealed ectopic expression of HOXB2 in 15% of early Pan IN lesions and 48 of 128 (38%) pancreatic cancer specimens. Expression of HOXB2 was associated with nonresectable tumors and was an independent predictor of poor survival in resected tumors. Conclusions: We identified aberrant expression of RA signaling components in pancreatic cancer, including HOXB2, which was expressed in a proportion of PanIN lesions. Ectopic expression of HOXB2 was associated with a poor prognosis for all patients with pancreatic cancer and was an independent predictor of survival in patients who underwent resection