Susceptibility of Forests in the Northeastern U.S. to Nitrogen and Sulfur Deposition:
Implications for Forest Health
CRITICAL LOADS Nnut
APPROACH
The approach we used to determine acceptable levels of deposition is a
steady-state, ecosystem mass balance for nutrient cations (calcium,
magnesium, and potassium). We calculated the critical load (CL) of S + N
(the level of deposition below which no harmful ecological effects occur for a
forest ecosystem), and the exceedance (the difference between the current
deposition and the CL), which can be used to identify susceptible forest
ecosystems.
DATA USED
Precipitation and climate ClimCalc Model www.pnet.sr.unh.edu/climcalc
Nutrient removal plot biomass measures were used to calculate harvestable
biomass, Tree Chemistry Database values were used for nutrient
concentrations (http://www.hubbardbrook.org/treechem/index.htm)
Mineral weathering The substrate type/clay content method was used to
estimate soil mineral weathering rates. The primary soil series were
determined from digitized county soil survey maps (Soil Survey Geographic
(SSURGO) Database). The Official Soil Series Descriptions were used to
determine minimum, maximum and midpoint values for the required soil
parameters (depth, clay percent, texture, moisture, substrate type). The
midpoint value is the midpoint of the range (max-min). For comparison NSSC
soil pit data (Soil Survey Staff, 2003) were averaged across New England to
generate mean values for the required soil parameters by soil series,
however, because pit data were not available for many areas, these values
are not necessarily representative.
BACKGROUND
Acid deposition is caused by emissions of sulfur (S) and
nitrogen (N) from power plants and vehicles. Although S
emissions have decreased, as a result of SO2 control
programs, projected emissions of acidifying S and N
compounds are expected to have continuing negative
impacts on forest health and productivity. In addition, N
deposition can be harmful to forests beyond these impacts
of acidification, because excess N can lead to N saturation
and plant nutrient imbalances. Nutrient depletion leads to
increases in the susceptibility of forests to climate, pest and
pathogen stress which results in reduced forest health,
reduced growth, increased mortality, and eventual changes
in forest species composition.
CRITICAL LOADS N+S
lpardo@fs.fed.us
EXCEEDANCE Nnut
CL for Acidity
CL S+N = BCdep + BCw – BCu – BCle
(1)
where: BCdep = sum of Ca + Mg + Na+ K deposition rate (eq ha-1 yr-1)
BCw = soil weathering rate of Ca + Mg + K + Na (eq ha-1 yr-1)
BCu = net Ca + Mg + K uptake rate (eq ha-1 yr-1) removed by
harvest or disturbance
BCle = acceptable acid neutralizing capacity (ANC) leaching
rate (eq ha-1 yr-1).
The acceptable ANC leaching rate, BCle, is calculated based on the critical
chemical criteria of no change in base saturation according the NEG/ECP Forest
Mapping Group Protocol (NEG/ECP, 2001). In order to achieve the condition of
no change in base saturation, a BC/Al ratio of 10 (mol/mol) was used.
CL for Nutrient N
CLnut(N) can be expressed as
CLnut(N) = Na + Nu + Nde + Nle
Na-N accumulated in soil
Nu- net N removal via biomass
Nde-N loss via denitrification assumed 0
Nle-accceptable N leaching
The acceptable N leaching rate, Nle, is the maximum acceptable
leaching rate for an ecosystem that is not at N saturation. This leaching
rate is given by
Nle(acc) = Q*[N]crit
(2)
where:
Nle(acc) =acceptable leaching of N
[N]crit =the N concentration in the soil solution above which it
would be considered detrimental to ecosystem or soil
[N]crit was set at 0.2 g N/m3, per the ICP Mapping and Modelling Manual
(http://www.oekodata.com/icpmapping/index.html).
CL Nnut are typically lower than CL S+N, so the CL Nnut was
exceeded for nearly all plots in the Northeast.
High Transparency vs. Exceedance
High Dieback vs. Exceedance
100
70
90
60
% of Trees with High Dieback
OBJECTIVE
To relate measures of forest susceptibility to acid deposition
with indicators of forest health in order to assess the impact
of acid deposition in the northeastern US.
Northern Research Station, USDA Forest Service, Burlington, VT
% of Trees with High Transparency
Linda H. Pardo, Natasha Duarte
80
70
60
50
40
30
20
50
40
30
20
10
10
0
EXCEEDANCE N+S
-6000
-5000
-4000
-3000
-2000
-1000
0
0
1000
2000
Exceedance
-6000
-5000
-4000
-3000
-2000
-1000
0
1000
2000
3000
Exceedance
FOREST HEALTH INDICATORS
CT CL(S+N)
80
80
80
80
60
40
20
0
0
0
0
500
1000
Total number of sites
0
3000
500
1000
17
19
10
10
18
33
37
2
185
713
591 1414
778
NSSC Mean
2000
3000
4000
5000
0
6000
Mid
NSSC Mean
Best Case
MA Exceedance (S+N)
Worst Case
Mid
NSSC Mean
Best Case
ME Exceedance (S+N)
80
60
40
20
-500
0
500
1000
1500
2000
2500
Mid
-1500
-500
Worst Case
NSSC Mean
3000
Best Case
1500
Mid
4000
5000
Worst Case
6000
NSSC Mean
20
0
0
0
500
1000
1500
2000
2500
3000
3500
NSSC Mean
Worst Case
2000
3000
Mid
Worst Case
2000
1000
2000
3000
4000
Mid
Worst Case
NSSC Mean
CL(S+N) Across New England and New York
40
4000
6000
8000
10000
0
12000
0
2000
4000
Worst Case
6000
8000
10000
12000
CL(S+N) (eq/ha/yr)
Mid
Best Case
NSSC Mean
Worst Case
Mid
Best Case
Exceedance of (S+N) across New England and
New York
100
80
60
40
80
60
40
60
40
20
20
0
-2500 -2000 -1500 -1000
-500
0
500
1000
1500
2000
0
-10000
-7500
Best Case
Mid
Worst Case
-5000
-2500
0
2500
5000
7500
0
-10000 -8000
Exceedance ( eq/ha/yr)
Exceedance (eq/ha/yr)
NSSC Mean
Best Case
NSSC Mean
VT Exceedance (S+N)
% Sites
% Sites
1000
Worst Case
0
100
Exceedance (eq/ha/yr)
Best Case
Mid
NSSC Mean
Best Case
20
0
-1000
CL(S+N) (eq/ha/yr)
Mid
Best Case
20
0
4000
Mid
Exceedance (eq/ha/yr)
40
20
80
-1000
2000
60
40
Worst Case
100
RI Exceedance (S+N)
20
1000
60
Best Case
40
0
VT CL(S+N)
60
7000
60
-1000
80
80
-2000
Best Case
CL(S+N) (eq/ha/yr)
Mid
-2000
80
100
-3000
-3000
80
100
-4000
-4000
0
-2000
Exceedance (eq/hay/r)
Worst Case
3000
40
100
NY Exceedance (S+N)
0
-5000
0
-5000
2500
2500
60
100
CL(S+N) (eq/ha/yr)
NSSC Mean
500
2000
20
RI CL(S+N)
100
90
80
70
60
50
40
30
20
10
0
2000
40
Exceedance (eq/ha/yr)
NY CL(S+N)
1000
60
20
0
-2500
3000
1500
NH Exceedance (S+N)
80
40
1000
CL(S+N) (eq/ha/yr)
80
60
500
CL(S+N) (eq/ha/yr)
80
Best Case
% Sites
1000
100
0
Other forest surveys included in this assessment: VMC-FH=Vermont
Monitoring Cooperative Forest Health Plots; NAMP=North American
Maple Program; VT HHS=Vermont Hardwood Health Survey;
NRCS=National Resources Conservation Service soil pits
Worst Case
Exceedance (eq/ha/yr)
4064
0
3500
100
61
103
3000
100
0
-1500 -1000
75
280
Best Case
% Sites
56
2500
100
62
27
Mid
20
35
2000
% Sites
4
Worst Case
1500
CL(S+N) (eq/ha/yr)
CT Exceedance (S+N)
509
VT Additional Research Sites
Total number of sites by state
2500
% Sites
402
99
VT HHS
NRCS
2000
% Sites
22
VT
VMC-FH
NAMP
1500
%Sites
31
552 1012
RI
40
20
% Sites
3
631
NY
40
60
20
% Sites
12
116
NH
% Sites
231
ME
% Sites
FHM (P3 plots)
40
60
20
NSSC Mean
FIA (P2 plots)
60
% Sites
100
% Sites
100
CL(S+N) (eq/ha/yr)
MA
NH CL(S+N)
100
SITE LOCATIONS
CT
ME CL(S+N)
100
0
Site Group
MA CL(S+N)
% Sites
% Sites
According to FIA protocol, the publicly available coordinates for all
New York FIA plots are the geographic center of the county within
which the plot is located (county centroid). Therefore it was not
possible to show spatial patterns within the county. Instead, we
plotted the mean of the county for the entire county, in order to give a
general idea of the larger-scale, regional spatial patterns.
The most susceptible forest ecosystems are in mountainous regions where glacial till and soils are thinnest, and
where atmospheric deposition rates are highest. The cumulative frequency charts (below) show the best case, worst
case and mid scenarios that demonstrate the range in CL and exceedance caused by different estimates of mineral
weathering. The percentage of plots where the CL was exceeded in the mid scenario ranged from 13% in RI to 62%
in NY. Since the weathering rates are based on depth and clay content ranges for the soil series rather than those
measurements on the site, our ability to identify the most sensitive sites is limited. The map (mid scenario; above)
does a better job of identifying general patterns under average conditions than in identifying individual sensitive
sites.
NSSC Mean
Best Case
Mid
Worst Case
-6000
-4000
-2000
0
2000
4000
6000
Exceedance (eq/ha/yr)
NSSC Mean
Best Case
Mid
Worst Case
NSSC Mean
We expected indicators of damage to be higher at sites where
deposition exceeded the CL (exceedance>0), however, we
observed no such pattern for canopy transparency or dieback,
mortality, low density, or moderate-severe decline. This lack of
correlation may reflect that factors other than acid deposition
may be the dominant forces influencing damage at this time. The
main difficulty with the current assessment is that, because the
CL estimates are not based on site soil measurements, they may
not reflect the most sensitive sites’ susceptibility to acid
deposition. CL estimates could be improved with more detailed
plot soils information.
RECOMMENDATIONS FOR FHM SAMPLING/ANALYSIS
• Soil sampling by horizon rather than depth
including depth and bulk density measurements
• Measurement of soil depth to bedrock
• Soil sampling to bedrock or to bottom of rooting zone
• Exchangeable base cation measurement
• Soil mineralogy measurements
Members of the Forest Mapping Working Group Pilot Phase Technical Group
Jean-Christophe Aznar, INRS-ETE University of Quebec
Paul Arp, University of New Brunswick
Bill Breckenridge, Eastern Canadian Provinces Secretariat
Ian DeMerchant, Natural Resources Canada
Natasha Duarte, USDA Forest Service
Guy Fenech, Environment Canada
Wendy Leger, Environment Canada
Eric Miller, Ecosystems Research Group, Ltd.
Heather Morrison, Environment Canada
Rock Ouimet, Forestry Québec, Canadian Co-Chair
Linda H. Pardo, USDA Forest Service
Scott Payne, Department of Forest Resources and AgriFoods
Rheal Poirrier, Eastern Canadian Provinces Secretariat
Sandy Wilmot, Vermont Agency of Natural Resources, US Co-Chair
Collaborators/Funding Agencies
Connecticut Department of Environmental Protection
Joint Conference of New England Governors and Eastern Canadian Premiers
Maine Department of Environmental Protection
New Hampshire Department of Environmental Services, Air Resources Division
Northeastern States for Coordinated Air Use Management
Northern States Research Cooperative
US Environmental Protection Agency
USDA, Forest Health Monitoring Program, Evaluation Monitoring
Vermont Agency of Natural Resources
Acknowledgements:
This project was completed with assistance in assembling data from: Charlie Cogbill; Thomas Frieswyk, USDA
Forest Service; Phil Girton, Vermont Monitoring Cooperative; Eric Miller, Ecosystems Research Group, Ltd.;
Rock Ouimet, Forestry Québec; Judy Rosovsky, Vermont Monitoring Cooperative; and Sandy Wilmot, Vermont
Agency of Natural Resources. Edmund M. Hart, Molly Robin-Abbott, and Bethany Zinni of the USDA Forest
Service assisted with data manipulation.
We are especially indebted to Liz LaPoint, GIS specialist in the USDA Forest Service FIA Program for her
extensive assistance in making these calculations.
For more information on Critical Loads, go to http://www.nrs.fs.fed.us/clean_air_water/clean_water/critical_loads/