Protection of forest ecosystems in the eastern United States from elevated atmospheric deposition of sulfur and nitrogen: A comparison of steady-state and dynamic model results.

Critical loads (CLs) and target loads (TLs) of atmospheric deposition of sulfur (S) and nitrogen (N) specify the thresholds of air pollution above which damage to ecosystems is expected to occur and are used to inform environmental regulation and natural resource management. Model estimates of CL and TL can vary for a given location, and these differences can be important for characterization of ecosystem effects from elevated S and N deposition. Moreover, TLs are used to evaluate associated timeframes of ecosystem recovery. We compared published CLs and TLs based on soil acidity criteria derived from steady-state versus dynamic models for terrestrial ecosystems. We examined the magnitude of differences in the CL/TL results from the two types of models for the same regions in the Eastern U.S. Results showed that CLs/TLs from dynamic models (or from steady state modeling using soil base cation weathering estimates from dynamic models) generally produce a broader range of values of acid-sensitivity, including lower CLs/TLs, as compared with a steady-state approach. Applications of dynamic biogeochemical models capable of developing CLs/TLs are relatively data intensive and typically limited to locations where measured soil and soil solution (or nearby stream water) chemistry are available for model parameterization, calibration, and testing. We recommend that CLs/TLs derived from dynamic models be used, where data permit, as they are likely more accurate and allow for evaluation of time-dependent phenomena and period needed for recovery. However, CLs derived from steady-state models remain a useful tool for understanding broad spatial patterns in soil acid-sensitivity throughout the U.S. Future work should focus on the development of more reliable model input parameters, particularly soil base cation weathering, and the extent to which CLs and TLs at a given location may vary and be altered with anticipated future climate change. In addition, dynamic models could be further developed to estimate CLs/TLs for nutrient N.

The response of stream ecosystems in the Adirondack region of New York to historical and future changes in atmospheric deposition of sulfur and nitrogen.

The present-day acid-base chemistry of surface waters can be directly linked to contemporary observations of acid deposition; however, pre-industrial conditions are key to predicting the potential future recovery of stream ecosystems under decreasing loads of atmospheric sulfur (S) and nitrogen (N) deposition. The integrated biogeochemical model PnET-BGC was applied to 25 forest watersheds that represent a range of acid sensitivity in the Adirondack region of New York, USA to simulate the response of streams to past and future changes in atmospheric S and N deposition, and calculate the target loads of acidity for protecting and restoring stream water quality and ecosystem health. Using measured data, the model was calibrated and applied to simulate soil and stream chemistry at all study sites. Model hindcasts indicate that historically stream water chemistry in the Adirondacks was variable, but inherently sensitive to acid deposition. The median model-simulated acid neutralizing capacity (ANC) of the streams was projected to be 55 µeq L-1 before the advent of anthropogenic acid deposition (~1850), decreasing to minimum values of 10 µeq L-1 around the year 2000. The median simulated ANC increased to 13 µeq L-1 by 2015 in response to decreases in acid deposition that have occurred over recent decades. Model projections suggest that simultaneous decreases in sulfate, nitrate and ammonium deposition are more effective in restoring stream ANC than individual decreases in sulfur or nitrogen deposition. However, the increases in stream ANC per unit equivalent decrease in S deposition is greater compared to decreases in N deposition. Using empirical algorithms, fish community density and biomass are projected to increase under several deposition-control scenarios that coincide with increases in stream ANC. Model projections suggest that even under the most aggressive deposition-reduction scenarios, stream chemistry and fisheries will not fully recover from historical acidification by 2200.

Steady-state sulfur critical loads and exceedances for protection of aquatic ecosystems in the U.S. Southern Appalachian Mountains.

Atmospherically deposited sulfur (S) causes stream water acidification throughout the eastern U.S. Southern Appalachian Mountain (SAM) region. Acidification has been linked with reduced fitness and richness of aquatic species and changes to benthic communities. Maintaining acid-base chemistry that supports native biota depends largely on balancing acidic deposition with the natural resupply of base cations. Stream water acid neutralizing capacity (ANC) is maintained by base cations that mostly originate from weathering of surrounding lithologies. When ambient atmospheric S deposition exceeds the critical load (CL) an ecosystem can tolerate, stream water chemistry may become lethal to biota. This work links statistical predictions of ANC and base cation weathering for streams and watersheds of the SAM region with a steady-state model to estimate CLs and exceedances. Results showed that 20.1% of the total length of study region streams displayed ANC <100 µeq∙L(-1), a level at which effects to biota may be anticipated; most were 4th or lower order streams. Nearly one-third of the stream length within the study region exhibited CLs of S deposition <50 meq∙m(-2)∙yr(-1), which is less than the regional average S deposition of 60 meq∙m(-2)∙yr(-1). Owing to their geologic substrates, relatively high elevation, and cool and moist forested conditions, the percentage of stream length in exceedance was highest for mountain wilderness areas and in national parks, and lowest for privately owned valley bottom land. Exceedance results were summarized by 12-digit hydrologic unit code (subwatershed) for use in developing management goals and policy objectives, and for long-term monitoring.

The spatial pattern of nitrogen cycling in the Adirondack Park, New York.

Maps of canopy nitrogen obtained through analysis of high-resolution, hyperspectral, remotely sensed images now offer a powerful means to make landscape-scale to regional-scale estimates of forest N cycling and net primary production (NPP). Moreover, recent research has suggested that the spatial variability within maps of canopy N may be driven by environmental gradients in such features as historic forest disturbance, temperature, species composition, moisture, geology, and atmospheric N deposition. Using the wide variation in these six features found within the diverse forest ecosystems of the 2.5 million ha Adirondack Park, New York, USA, we examined linkages among environmental gradients and three measures of N cycling collected during the 2003 growing season: (1) field survey of canopy N, (2) field survey of soil C:N, and (3) canopy N measured through analysis of two 185 x 7.5 km Hyperion hyperspectral images. These three measures of N cycling strongly related to forest type but related poorly to all other environmental gradients. Further analysis revealed that the spatial pattern in N cycling appears to have distinct inter- and intraspecific components of variability. The interspecific component, or the proportional contribution of species functional traits to canopy biomass, explained 93% of spatial variability within the field canopy N survey and 37% of variability within the soil C:N survey. Residual analysis revealed that N deposition accounted for an additional 2% of variability in soil C:N, and N deposition and historical forest disturbance accounted for an additional 2.8% of variability in canopy N. Given our finding that 95.8% of the variability in the field canopy N survey could be attributed to variation in the physical environment, our research suggests that remotely sensed maps of canopy N may be useful not only to assess the spatial variability in N cycling and NPP, but also to unravel the relative importance of their multiple controlling factors.