Abstract
A recently developed online GIS tool, Nitrogen Critical Loads Assessment by Site (N-CLAS), was used to assess the effects of nitrogen (N) deposition and climate change on 23 tree species of management concern in the northeastern United States. The N-CLAS tool calculates and maps critical loads, target loads, and exceedances across the landscape by linking information on the relationships between N deposition, tree growth and environmental conditions with high resolution geospatial data for species composition and abiotic modifying factors (topography, climate, and soils). Outputs can be customized to capture specific species, locations or applications of interest to land managers.The summary analyses presented here show that most forests in the northeastern United States are at risk of detrimental effects from N deposition, although the extent and magnitude of the risk varies spatially. Eighty-six percent of the forested area in the region (98 M acres) is in exceedance of the critical load. The magnitude of this exceedance is highest (6–8 kg N ha−1 yr−1) in the southwestern part of the study region where N deposition is highest (e.g. North Central Hardwood Forests, Erie Drift Plain, Driftless Area, and Southern Michigan/Northern Indiana Drift Plains ecoregions). The magnitude of exceedance is lowest (1–2 kg N ha−1 yr−1) in the northeastern and northwestern part of the study area where N deposition is lowest (e.g. Acadian Plains and Hills and the Northern Minnesota Wetland ecoregions). White pine (Pinus strobus), quaking aspen (Populus tremuloides), yellow birch (Betula alleghaniensis), northern red oak (Quercus rubra) and bigtooth aspen (Populus grandidentata) are in exceedance of the critical load across large portions of the study area–between 31 and 56 million acres are in exceedance for each species. Red pine (Pinus resinosa), pitch pine (Pinus rigida), and chestnut oak (Quercus montana), which occur over a small geographic extent, are in exceedance of the critical load over 89 to 100 percent of their range.N-CLAS provides land managers easy access to a tool with significant refinement in determining empirical critical loads at a spatial resolution applicable to forest management. This represents an important step towards improving our understanding of the potential risk to forests in the northeastern U.S and linking current state of the science to decision making processes on the ground.
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