Critical Loads - Background Information

Forest Service managers directly monitor and use models to measure or estimate the amount of atmospheric deposition occurring on National Forests and how this deposition is affecting forest resources.  Long-term air quality and resource monitoring on and near national forests and Class I areas has helped establish air pollution trends and existing condition of the resources.  Based on these existing conditions, and documented cause and effect relationships, Forest Service Air Specialists and partners have begun to identify critical loads and target loads.

The critical load (CL) is defined as “the quantitative estimate of an exposure to one or more pollutants below which significant harmful effects on specified sensitive elements of the environment are not expected to occur according to present knowledge” (Figure 1).  The critical load is scientifically determined based on expected ecosystem response to a given deposition level.  When critical loads are exceeded, the environmental effects can extend over great distances.  Projected emissions of both sulfur and nitrogen compounds are expected to have continuing negative impacts on forests, and to present serious long-term threats to forest health and productivity in the US, despite decreased sulfur emissions as a result of SO2 abatement legislation.  Critical loads can be used to determine the level of deposition expected to cause harmful ecological effects.  Target loads are based on critical loads, but can include consideration of the timeframe needed to achieve a desired ecosystem condition as well as incorporating policy or management goals; depending on whether or not current critical loads values have been exceeded, a target load can be above or below the critical load.  Defining the critical and target loads for a forest helps resource managers communicate the effects of air pollution on resources to Forest Service decision-makers as well as to air regulators.  This information will also be used to assess how some management activities may exacerbate air pollution related problems or identify areas where mitigation may be an option for resources that have already been negatively affected (see Management Strategy).  This information can be used in a regulatory context when consulting with and advising air regulatory agencies on effects to forest resources resulting from new and existing sources of air pollution.

This web page provides information on:

  1. The CLs concept, and the use of multiple CLs
  2. The approaches for calculating CLs

Information on atmospheric deposition, and negative ecological effects associated with deposition levels in exceedance of critical loads (acidification and nitrogen saturation/eutrophication), can be found by clicking here.  The critical loads section of the portal also hosts a glossary and frequently asked questions.

Critical load is the level of atmospheric deposition below which significant harmful effects on specified sensitive elements of the environment are not expected to occur

Figure 1: This graph visually displays the critical load as the level of deposition below which no harmful ecological effects are experienced.

Critical Load Concept

Critical loads are based on changes to specific biological or chemical indicators.  Critical loads can therefore be developed for a variety of ecosystem responses, including shifts in microscopic aquatic species, increases in invasive grass species, changes in soil chemistry affecting tree growth, and lake and stream acidification to levels that can no longer support fish.  Because different sensitive receptors or species (e.g., forest soils, high elevation lakes, species of lichen) may have varying sensitivities to air pollutant loads, multiple critical loads can be used to describe a variety of impacts along a continuum of increasing deposition for a given location (Figure 2).

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Figure 2: Critical loads correspond to specific effects to sensitive receptors at specific loading rates.  Any one specific effect lies within a cascade of multiple effects along a continuum of loading rates.

In addition, even for the same organism, multiple critical loads may be associated with biological thresholds for different negative effects, such as stunted growth, reduced reproduction, and increased mortality.  Several different threshold levels are therefore included in a critical load assessment.  The policymaker can assess all the critical loads (science-driven ecological thresholds) and select target loads (policy thresholds) based on the level of ecosystem protection desired, economic considerations, and stakeholder input at a given location.

Refer to the documentation surrounding each CL calculation to place the multiple CLs available for your forest into context, and for guidance on interpreting the CLs simultaneously.  For example, empirical CLs for nutrient N are available for many receptors.  In almost all circumstances, lichens and diatoms are more sensitive to the effects of atmospheric deposition than other potential receptors, meaning that they start to experience detrimental effects at lower levels of deposition.  Relying on the critical load for herbaceous vegetation or forest ecosystems would not protect these sensitive species.  A land manager might prefer to rely on the CLs for these sensitive species in order to be protective when it comes to preventing air pollution effects on forest ecosystems.  It is therefore important to consider the full suite of CLs available for your Forest, and to compare these values within the larger framework of management concerns.

Critical Load Approaches

There are three main approaches for calculating critical loads:

  1. Empirical approaches are based on observations of response of an ecosystem or ecosystem receptor (e.g., foliage, lichens, soil) to a given, observed deposition level.  These relationships are developed using dose-response studies or by measuring ecosystem responses to increasing gradients of deposition over space or time.  Empirical critical loads then are calculated for the site where the data were obtained and, generally, they are applied to similar sites where such data are not available.  The nationwide empirical CLs of nutrient nitrogen for ecosystem receptors and responses (fungi, lichens, herbaceous vegetation, forests, nitrate leaching) were calculated using this approach.  More information specific to empirical CLs of nutrient nitrogen for lichens is available in a briefing paper.
  2. Simple mass balance approaches are based on estimating the net loss or accumulation of nutrients based on inputs and outputs of the nutrient of concern (e.g., base cations, nitrogen).  Simple mass balance methods are steady-state models that calculate the critical load of deposition to an ecosystem over the long term.  They are used at sites with moderate to intensive data availability.  The nationwide CLs of acidity for surface waters and nationwide terrestrial CLs of acidity for forested ecosystems were both calculated using this approach.
  3. Dynamic models use a mass balance approach expanded by incorporating internal feedbacks—such as accumulation of N in the system, or exchange of base cations between soil and soil solution from year to year.  Dynamic models can predict time to damage and time to recovery.  Dynamic models are typically used at sites where intensive data are available.

Data availability drives the selection of the type of approach for calculating critical loads.  For sites where little or no data are available, empirical approaches must be based on data from similar or comparable sites.  For sites with a moderate to intensive level of data available, simple mass balance approaches are used.  Most dynamic models may be used only at sites with substantial data that, generally, must range over some period of time.  However, a highly tested dynamic model can be subsequently applied to an adjacent region with more sparse data.  Each type of critical load calculation may yield a different critical load value for the same site because of the different assumptions involved.  Each type of critical load may be calculated for the overall ecosystem or for a particular ecosystem receptor (if data for that receptor are available).

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Empirical approaches (field observation-based)

Empirical critical loads are determined by using literature or field observations of detrimental ecological effect and noting the deposition level at which the effect occurred.  The lowest deposition level at which a response occurs is considered the critical load.  In cases where there is a variation in the level of deposition that causes a given response, a range for the critical load often is reported.  The utility of empirical critical loads is that they can be used to determine the critical load based on the best available information for that ecosystem type when data are not available at a given site.

Advantages of empirical critical loads are simplicity and ease of use (they require no calculation), and applicability over a broad set of conditions.  Empirical critical loads also can be set for different ecosystem types if data are available.  The main conceptual advantage of empirical critical loads is that, under the best circumstances, they link ecosystem response to deposition.  They are particularly useful for setting critical loads for nutrient N, which are difficult to model.

Disadvantages of empirical critical load calculations are primarily due to a lack of quantitative understanding of the empirical observations.  This approach is based on observed cause and effect responses rather than understanding of a process or mechanism.  Thus, it is difficult to be certain of the level of deposition that causes a given response.  Further, since the observations of ecological response to a given deposition level are based on past scenarios, they may not show the breadth of response possible in the future.  For example, if a response is observed at a given deposition level (or fertilization level) after a certain number of years, it is possible that a lower deposition over a longer period of time would cause the same detrimental effect.  This would mean that the empirical critical load was too high.  For example, N deposition of 25 kg/ha/yr (kilograms per hectare per year) for 7 years may cause excess nitrate leaching, and therefore, the critical load would be set at 25 kg/ha/yr.  However, at another site (or even the same site), N deposition of 15 kg/ha/yr for 15 years might cause the same response.

Another pitfall of the empirical approach is that the observed response may be unique to the site at which it was measured (because of particular site history, soil thickness, etc.) and may not be representative of the ecosystem type in general.  In this case if the critical load is too high, then sensitive areas are put at risk.  On the other hand, the critical load might be too low, which would not be of great concern for Class I areas where the mandate is to err on the side of protecting resources.

In Europe, empirical critical loads have been proposed both for acidity and for nutrient N.  In the United States, because of the nonlinear behavior of acid-base processes, and heterogeneity of ecosystems, it is less useful to propose empirical critical loads for acidity.  For nutrient N, however, it is useful to estimate empirical critical loads for different categories of ecosystems.  Assessments on the effects of N deposition on ecosystems have been compiled to generate empirical critical loads for N for ecoregions in the United States (Pardo et al. 2011).  For some ecosystem types where data for calculating critical loads are sparse (e.g., arid ecosystems), it may be advantageous to estimate empirical critical loads based on the best understanding of impacts in those or similar ecosystems elsewhere, rather than to attempt to model them.

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Simple mass balance approaches (steady-state approaches)

Steady-state approaches are based on scientific understanding of ecosystem processes.  These approaches also are called simple mass-balance methods.  They utilize the best available data for estimating the net loss or accumulation in the ecosystem of the nutrient of concern.

The advantage of mass balance equations is that they are scientifically based on the mass balance concept—that if you deplete the ecosystem pool of an essential nutrient, such as base cations, ultimately it will harm the forest.  By contrast, if you have too large a net accumulation of N in the system, it will be detrimental for the forest ecosystem.  The mass balance is based on ecosystem processes and can be applied at different sites, taking into account site condition.

The disadvantages of the mass-balance approach are the requirements for extensive data that are not readily available; considerable uncertainty about the critical thresholds for ecosystem response used; and lack of information about time until the expected ecosystem response or the time frame for recovery.  Further, steady-state models cannot describe any individual site well, as they do not incorporate sufficient detail or include ecosystem processes.

Nonetheless, simple mass-balance models often are considered the best available model for estimation of critical loads across large regions.  These approaches may provide the maximum return for the level of information they require.

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Dynamic Modeling Approaches

Dynamic modeling approaches were developed to address the inability of steady-state models to assess time to ecological damage or time to recovery.  These dynamic models give a more realistic representation of change in an ecosystem by taking into account that response to one change does not occur immediately throughout the whole ecosystem.  Instead, a change in deposition can cause a change in chemistry over some period of time; this change in chemistry causes a subsequent change in biology over time.

The advantages of dynamic models are that they include a more realistic representation of the complexity of ecosystems and that the results allow assessment of the time for a particular ecosystem effect to occur.  Many of the impacts associated with air pollution involve these nonsteady-state conditions; recovery from these impacts also involves nonsteady-state conditions.

The disadvantages of dynamic models are that the models may have very large data requirements, take a fairly long time (and high level of expertise) to apply to a given site, and that some models may describe a particular ecosystem type or site very well, but may not be applicable to a wide variety of sites.  A general difficulty in dynamic modeling is finding the balance between having the model describe a particular system very well (which dynamic models may do, but steady-state models cannot) and having the model be usable at a broad range of sites.  Typically, dynamic models have not been applied over broad areas for terrestrial ecosystems.  Dynamic models may be applied over broad areas with little data, but not without compromising the quality of the results.  In such cases, as in any calculation of critical loads, better quality and finer resolution of input data will yield more accurate results.

Since the critical load concept is essentially a steady-state concept, an appropriate application would be to combine a steady-state estimation of the critical load with a dynamic modeling estimation of time to damage or recovery.  In this case, it is important to ensure that the assumptions and conditions of the dynamic model are consistent with those of the steady-state model.

References

Pardo, LH.  2010.  Approaches for estimating critical loads of N and S deposition for forest ecosystems on U.S. federal lands.  Gen. Tech. Rep. NRS-71.  Newtown Square, PA.  U.S. Department of Agriculture, Forest Service, Northern Research Station. 25 p.

Fenn, ME, KF Lambert, T Blett, DA Burns, LH Pardo, GM Lovett, R Haeuber, DC Evers, CT Driscoll, DS Jeffries. 2011. Setting limits: Using air pollution thresholds to protect and restore U.S. ecosystems. Issues in Ecology 14: 1-21.

Critical Loads - Evaluating the Effects of Airborne Pollutants on Terrestrial and Aquatic Ecosystems.  Critical Loads of Atmospheric Deposition Science Committee of National Atmospheric Deposition Program.  Champaign, IL.

Pardo, LH.  Critical Loads Website. US Forest Service, Northern Research Station.