Empirical Modeling of Atmospheric Deposition in Mountainous Landscapes

Abstract

Abstract. Atmospheric deposition has long been recognized as an important source of pollutants and nutrients to ecosystems. The need for reliable, spatially explicit estimates of total atmospheric deposition (wet þ dry þ cloud) is central, not only to air pollution effects researchers, but also for calculation of input-output budgets, and to decision makers faced with the challenge of assessing the efficacy of policy initiatives related to deposition. Although atmospheric deposition continues to represent a critical environmental and scientific issue, current estimates of total deposition have large uncertainties, particularly across heterogeneous landscapes such as montane regions.We developed an empirical modeling approach that predicts total deposition as a function of landscape features. We measured indices of total deposition to the landscapes of Acadia (121 km 2 ) and Great Smoky Mountains (2074 km 2 ) National Parks (USA). Using ;300-400 point measurements and corresponding landscape variables at each park, we constructed a statistical (general linear) model relating the deposition index to landscape variables measured in the field. The deposition indices ranged over an order of magnitude, and in response to vegetation type and elevation, which together explained ;40% of the variation in deposition. Then, using the independent landscape variables available in GIS data layers, we created a GIS-relevant statistical nitrogen (N) and sulfur (S) deposition model (LandMod). We applied this model to create park-wide maps of total deposition that were scaled to wet and dry deposition data from the closest national network monitoring stations. The resultant deposition maps showed high spatial heterogeneity and a four-to sixfold variation in ''hot spots'' and ''cold spots'' of N and S deposition ranging from 3 to 31 kg NÁha À1 Áyr À1 and from 5 to 42 kg SÁha À1 ÁyrÀ1 across these park landscapes. Area-weighted deposition was found to be up to 70% greater than NADP plus CASTNET monitoring-station estimates together. Modelvalidation results suggest that the model slightly overestimates deposition for deciduous and coniferous forests at low elevation and underestimates deposition for high-elevation coniferous forests. The spatially explicit deposition estimates derived from LandMod are an improvement over what is currently available. Future research should test LandMod in other mountainous environments and refine it to account for (currently) unexplained variation in deposition.

Changes in alpine vegetation over 21 years: Are patterns across a heterogeneous landscape consistent with predictions?

“…Many alpine plant species are strongly limited by snowpack and moisture availability (Engler et al 2011), with warming effects translating to stronger or weaker water limitation depending on the timing and amount of snowpack (Pauli et al 2012). Alpine systems also can experience high levels of nitrogen (N) deposition (Baron et al 2000, Williams and Tonnessen 2000, Weathers et al 2006) and changes in land use associated with grazing (Quetier et al 2007). N deposition can interact with warming to influence elevational advance (Bobbink et al 2010, Smith et al 2012.…”

High elevation watersheds in the southern Appalachians: Indicators of sensitivity to acidic deposition and the potential for restoration through liming

“…In some forest ecosystems the Oa-horizon plays an important role in nutrient availability with many tree roots occupying that layer (Perala and Alban, 1982; Rauland-Rasmussen and Vejre, 1995; Joergensen et al, 2009). The Oa-horizon has been examined as a surrogate for total deposition, as it represents the accumulation of all mineral input sources, litterfall, root turnover, and fungal activity, as well as wet and dry deposition (Weathers et al, 2006;Joergensen et al, 2009). In our study, O-horizon Al concentrations and C:N ratios had a positive relationship with stream Ca:Al molar ratio; however, increasing O-horizon total N concentrations resulted in declining stream ANC.…”

“…Patterns of atmospheric S and N deposition in mountainous terrain varies across landscapes and is related to rainfall amount, the presence of clouds and fog, elevation, forest edges, aspect, and vegetation composition (Weathers et al, 2000;Sullivan et al, 2007) with an estimated a 4-6-fold range in spatial variability (Weathers et al, 2006). Within the southern Appalachian Mountains high elevation sites receive higher rainfall (Swift et al, 1988) and greater inputs of nutrient and pollutant deposition (Swank, 1988;Swank and Vose, 1997;Sullivan et al, 2007) than low elevation sites.…”

Measuring atmospheric nutrient deposition to inland waters: Evaluation of direct methods

“…In spite of their growing importance (Weathers et al 2006), direct estimates of dry and wet atmospheric deposition of nitrogen (N) and phosphorous (P) are difficult to obtain owing to analytical problems and limitations (Krupa 2002). This limitation has led to an increase in studies of atmospheric nutrient deposition via complex and costly sampling methods (Krupa 2002) and empirical (Weathers et al 2006) and physical (Pryor et al 2007) modeling.…”

“…This limitation has led to an increase in studies of atmospheric nutrient deposition via complex and costly sampling methods (Krupa 2002) and empirical (Weathers et al 2006) and physical (Pryor et al 2007) modeling. Models must be verified against real measurements, however, so it is still necessary to understand and overcome the sources of error and variability of direct measurements of nutrient deposition.…”