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.

Environmental DNA provides higher resolution assessment of riverine biodiversity and ecosystem function via spatio-temporal nestedness and turnover partitioning.

Rapidly assessing biodiversity is essential for environmental monitoring; however, traditional approaches are limited in the scope needed for most ecological systems. Environmental DNA (eDNA) based assessment offers enhanced scope for assessing biodiversity, while also increasing sampling efficiency and reducing processing time, compared to traditional methods. Here we investigated the effects of landuse and seasonality on headwater community richness and functional diversity, via spatio-temporal dynamics, using both eDNA and traditional sampling. We found that eDNA provided greater resolution in assessing biodiversity dynamics in time and space, compared to traditional sampling. Community richness was seasonally linked, peaking in spring and summer, with temporal turnover having a greater effect on community composition compared to localized nestedness. Overall, our assessment of ecosystem function shows that community formation is driven by regional resource availability, implying regional management requirements should be considered. Our findings show that eDNA based ecological assessment is a powerful, rapid and effective assessment strategy that enables complex spatio-temporal studies of community diversity and ecosystem function, previously infeasible using traditional methods.

Executing multi-taxa eDNA ecological assessment via traditional metrics and interactive networks.

Current approaches to ecological assessment are limited by the traditional morpho-taxonomic methods presently employed and the inability to meet increasing demands for rapid assessments. Advancements in high throughput sequencing now enable rapid high-resolution ecological assessment using environmental DNA (eDNA). Here we test the ability of using eDNA-based ecological assessment methods against traditional assessment of two key indicator groups (diatoms and macroinvertebrates) and show how eDNA across multiple gene regions (COI, rbcL, 12S and 18S) can be used to infer interactive networks that link to ecological assessment criteria. We compared results between taxonomic and eDNA based assessments and found significant positive associations between macroinvertebrate (p < 0.001 R2 = 0.645) and diatom (p = 0.015, R2 = 0.222) assessment metrics. We further assessed the ability of eDNA based assessment to identify environmentally sensitive genera and found an order of magnitude greater potential for 18S, versus COI or rbcL, to determine environmental filtering of ecologically assessed communities. Lastly, we compared the ability of traditional metrics against co-occurrence network properties of our combined 18S, COI and rbcL indicator genera to infer habitat quality measures currently used by managers. We found that transitivity (network connectivity), linkage density and cohesion were significantly associated with habitat modification scores (HMS), whereas network properties were inconsistent with linking to the habitat quality score (HQS) metric. The incorporation of multi-marker eDNA network assessment opens up a means for finer scale ecological assessment, currently limited using traditional methods. While utilization of eDNA-based assessment is recommended, direct comparisons with traditional approaches are difficult as the methods are intrinsically different and should be treated as such with regards to future research. Overall, our findings show that eDNA can be used for effective ecological assessment while offering a wider range of scope and application compared to traditional assessment methods.

Zones of influence for soil organic matter dynamics: A conceptual framework for data and models.

Soil organic matter (SOM) is an indicator of sustainable land management as stated in the global indicator framework of the United Nations Sustainable Development Goals (SDG Indicator 15.3.1). Improved forecasting of future changes in SOM is needed to support the development of more sustainable land management under a changing climate. Current models fail to reproduce historical trends in SOM both within and during transition between ecosystems. More realistic spatio-temporal SOM dynamics require inclusion of the recent paradigm shift from SOM recalcitrance as an 'intrinsic property' to SOM persistence as an 'ecosystem interaction'. We present a soil profile, or pedon-explicit, ecosystem-scale framework for data and models of SOM distribution and dynamics which can better represent land use transitions. Ecosystem-scale drivers are integrated with pedon-scale processes in two zones of influence. In the upper vegetation zone, SOM is affected primarily by plant inputs (above- and belowground), climate, microbial activity and physical aggregation and is prone to destabilization. In the lower mineral matrix zone, SOM inputs from the vegetation zone are controlled primarily by mineral phase and chemical interactions, resulting in more favourable conditions for SOM persistence. Vegetation zone boundary conditions vary spatially at landscape scales (vegetation cover) and temporally at decadal scales (climate). Mineral matrix zone boundary conditions vary spatially at landscape scales (geology, topography) but change only slowly. The thicknesses of the two zones and their transport connectivity are dynamic and affected by plant cover, land use practices, climate and feedbacks from current SOM stock in each layer. Using this framework, we identify several areas where greater knowledge is needed to advance the emerging paradigm of SOM dynamics-improved representation of plant-derived carbon inputs, contributions of soil biota to SOM storage and effect of dynamic soil structure on SOM storage-and how this can be combined with robust and efficient soil monitoring.

Acidity promotes degradation of multi-species environmental DNA in lotic mesocosms.

Accurate quantification of biodiversity is fundamental to understanding ecosystem function and for environmental assessment. Molecular methods using environmental DNA (eDNA) offer a non-invasive, rapid, and cost-effective alternative to traditional biodiversity assessments, which require high levels of expertise. While eDNA analyses are increasingly being utilized, there remains considerable uncertainty regarding the dynamics of multispecies eDNA, especially in variable systems such as rivers. Here, we utilize four sets of upland stream mesocosms, across an acid-base gradient, to assess the temporal and environmental degradation of multispecies eDNA. Sampling included water column and biofilm sampling over time with eDNA quantified using qPCR. Our findings show that the persistence of lotic multispecies eDNA, sampled from water and biofilm, decays to non-detectable levels within 2 days and that acidic environments accelerate the degradation process. Collectively, the results provide the basis for a predictive framework for the relationship between lotic eDNA degradation dynamics in spatio-temporally dynamic river ecosystems.

Consequences of intensive forest harvesting on the recovery of Swedish lakes from acidification and on critical load exceedances.

Across much of the northern hemisphere, lakes are at risk of re-acidification due to incomplete recovery from historical acidification and pressures associated with more intensive forest biomass harvesting. Critical load (CL) calculations aimed at estimating the amount of pollutants an ecosystem can receive without suffering adverse consequences are dependent on these factors. Here, we present a modelling study of the potential effects of intensified forest harvesting on re-acidification of a set of 3239 Swedish lakes based on scenarios with varying intensities of forest biomass harvest and acid deposition. There is some evidence that forestry would have caused a certain level of acidification even if deposition remained at 1860 levels. We show that all plausible harvest scenarios delay recovery due to increased rates of base cation removal. Scenario results were used to estimate critical loads for the entire population of lakes in Sweden. The forestry intensity included in critical load calculations is a political decision. After scaling calculations to the national level, it was apparent that a high but plausible forest harvest intensity would lead to an increase in the area of CL exceedances and that even after significant reductions in forest harvest intensity, there would still be areas with CL exceedances. Our results show that forest harvest intensity and regional environmental change must be carefully considered in future CL calculations.

Policy Analysis: Valuation of Ecosystem Services in the Southern Appalachian Mountains.

This study estimates the economic value of an increase in ecosystem services attributable to the reduced acidification expected from more stringent air pollution policy. By integrating a detailed biogeochemical model that projects future ecological recovery with economic methods that measure preferences for specific ecological improvements, we estimate the economic value of ecological benefits from new air pollution policies in the Southern Appalachian ecosystem. Our results indicate that these policies generate aggregate benefits of about $3.7 billion, or about $16 per year per household in the region. The study provides currently missing information about the ecological benefits from air pollution policies that is needed to evaluate such policies comprehensively. More broadly, the study also illustrates how integrated biogeochemical and economic assessments of multidimensional ecosystems can evaluate the relative benefits of different policy options that vary by scale and across ecosystem attributes.

Simple models to estimate historical and recent changes of total organic carbon concentrations in lakes.

Quantifying human impacts on the natural environment requires credible reconstructions of reference conditions. Anthropogenic acidification of surface waters is strongly influenced by total organic carbon (TOC) concentrations. Because both the degree of acidification and recovery are dependent on historical TOC concentrations, simple models to estimate changes in surface water TOC between reference conditions (1860) and the present day (2012) are needed. We used visible near infrared spectroscopy (VNIRS) of lake sediments to reconstruct reference condition TOC and long-term monitoring data to predict recent changes. Two empirical models were developed to predict: (i) historical TOC trends between reference conditions (1860) and peak acidification (1980) and (ii) trends in TOC between 1988 and 2012. The models were statistically robust with adj. R(2) of (i) 0.85 and (ii) 0.71, respectively. Models were driven by lake and catchment area, wetlands, historical sulfur deposition and water chemistry. Present day TOC concentrations are similar to VNIRS-reconstructed and modeled reference condition TOC in Swedish lakes. The results are valuable for understanding drivers of TOC changes in lakes and for more credible assessments of reference conditions needed for water management in Europe and elsewhere.

Assessing recovery from acidification of European surface waters in the year 2010: evaluation of projections made with the MAGIC model in 1995.

In 1999 we used the MAGIC (Model of Acidification of Groundwater In Catchments) model to project acidification of acid-sensitive European surface waters in the year 2010, given implementation of the Gothenburg Protocol to the Convention on Long-Range Transboundary Air Pollution (LRTAP). A total of 202 sites in 10 regions in Europe were studied. These forecasts can now be compared with measurements for the year 2010, to give a "ground truth" evaluation of the model. The prerequisite for this test is that the actual sulfur and nitrogen deposition decreased from 1995 to 2010 by the same amount as that used to drive the model forecasts; this was largely the case for sulfur, but less so for nitrogen, and the simulated surface water [NO3(-)] reflected this difference. For most of the sites, predicted surface water recovery from acidification for the year 2010 is very close to the actual recovery observed from measured data, as recovery is predominantly driven by reductions in sulfur deposition. Overall these results show that MAGIC successfully predicts future water chemistry given known changes in acid deposition.

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.

Decreased atmospheric sulfur deposition across the Southeastern U.S.: when will watersheds release stored sulfate?

Emissions of sulfur dioxide (SO2) to the atmosphere lead to atmospheric deposition of sulfate (SO4(2-)), which is the dominant strong acid anion causing acidification of surface waters and soils in the eastern United States. Since passage of the Clean Air Act and its Amendments, atmospheric deposition of SO2 in this region has declined by over 80%, but few corresponding decreases in streamwater SO4(2-) concentrations have been observed in unglaciated watersheds. We calculated SO4(2-) mass balances for 27 forested, unglaciated watersheds from Pennsylvania to Georgia, by using total atmospheric deposition (wet plus dry) as input. Many of these watersheds still retain SO4(2-), unlike their counterparts in the northeastern U.S. and southern Canada. Our analysis showed that many of these watersheds should convert from retaining to releasing SO4(2-) over the next two decades. The specific years when the watersheds crossover from retaining to releasing SO4(2-) correspond to a general geographical pattern of later net watershed release from north to south. The single most important variable that explained the crossover year was the runoff ratio, defined as the ratio of annual mean stream discharge to precipitation. Percent clay content and mean soil depth were secondary factors in predicting crossover year. The conversion of watersheds from net SO4(2-) retention to release anticipates more widespread reductions in streamwater SO4(2-) concentrations in this region.

Modeling past and future acidification of Swedish lakes.

Decades of acid deposition have caused acidification of lakes in Sweden. Here we use data for 3000 lakes to run the acidification model MAGIC and estimate historical and future acidification. The results indicate that beginning in about 1920 a progressively larger number of lakes in Sweden fell into the category of "not naturally acidified" (∆pH > 0.4). The peak in acidification was reached about 1985; since then many lakes have recovered in response to lower levels of acid deposition. Further recovery from acidification will occur by the year 2030 given implementation of agreed legislation for emissions of sulphur (S) and nitrogen (N) in Europe. But the number of catchments with soils being depleted in base cations will increase slightly. MAGIC-reconstructed history of acidification of lakes in Sweden agrees well with information on fish populations. Future acidification of Swedish lakes can be influenced by climate change as well as changes in forest harvest practices.

Target loads of atmospheric sulfur deposition for the protection and recovery of acid-sensitive streams in the Southern Blue Ridge Province.

An important tool in the evaluation of acidification damage to aquatic and terrestrial ecosystems is the critical load (CL), which represents the steady-state level of acidic deposition below which ecological damage would not be expected to occur, according to current scientific understanding. A deposition load intended to be protective of a specified resource condition at a particular point in time is generally called a target load (TL). The CL or TL for protection of aquatic biota is generally based on maintaining surface water acid neutralizing capacity (ANC) at an acceptable level. This study included calibration and application of the watershed model MAGIC (Model of Acidification of Groundwater in Catchments) to estimate the target sulfur (S) deposition load for the protection of aquatic resources at several future points in time in 66 generally acid-sensitive watersheds in the southern Blue Ridge province of North Carolina and two adjoining states. Potential future change in nitrogen leaching is not considered. Estimated TLs for S deposition ranged from zero (ecological objective not attainable by the specified point in time) to values many times greater than current S deposition depending on the selected site, ANC endpoint, and evaluation year. For some sites, one or more of the selected target ANC critical levels (0, 20, 50, 100µeq/L) could not be achieved by the year 2100 even if S deposition was reduced to zero and maintained at that level throughout the simulation. Many of these highly sensitive streams were simulated by the model to have had preindustrial ANC below some of these target values. For other sites, the watershed soils contained sufficiently large buffering capacity that even very high sustained levels of atmospheric S deposition would not reduce stream ANC below common damage thresholds.

Predicting acidification recovery at the Hubbard Brook Experimental Forest, New Hampshire: evaluation of four models.

The performance and prediction uncertainty (owing to parameter and structural uncertainties) of four dynamic watershed acidification models (MAGIC, PnET-BGC, SAFE, and VSD) were assessed by systematically applying them to data from the Hubbard Brook Experimental Forest (HBEF), New Hampshire, where long-term records of precipitation and stream chemistry were available. In order to facilitate systematic evaluation, Monte Carlo simulation was used to randomly generate common model input data sets (n = 10,000) from parameter distributions; input data were subsequently translated among models to retain consistency. The model simulations were objectively calibrated against observed data (streamwater: 1963-2004, soil: 1983). The ensemble of calibrated models was used to assess future response of soil and stream chemistry to reduced sulfur deposition at the HBEF. Although both hindcast (1850-1962) and forecast (2005-2100) predictions were qualitatively similar across the four models, the temporal pattern of key indicators of acidification recovery (stream acid neutralizing capacity and soil base saturation) differed substantially. The range in predictions resulted from differences in model structure and their associated posterior parameter distributions. These differences can be accommodated by employing multiple models (ensemble analysis) but have implications for individual model applications.

Modeling future acidification and fish populations in Norwegian surface waters.

Despite great progress made in the past 25 years, acid deposition continues to cause widespread damage to the environment in Europe and eastern North America. Legislation to limit emissions of sulfur and nitrogen compounds in Europe is now under revision. The most recent protocol was based in part on the critical loads concept. The new protocol may also take into consideration the time delays between dose and response inherent in natural ecosystems. Policy decisions to reduce adverse effects on ecosystems entail a trade-off: quick response will require deeper cuts in emissions and thus higher costs, whereas lower costs with lesser cuts in emissions will give slower response. Acidification of lakes and damage to fish populations in Norway is used as an example. Under current legislation for emission reductions, surface waters will continue to slowly recover, but for many decades lakes in about 18% of Norway will continue to have water quality insufficient to support healthy populations of brown trout and other indicator organisms. Additional emission reductions can speed up the rate and degree of recovery.

Forecasting acidification effects using a Bayesian calibration and uncertainty propagation approach.

We present a statistical framework for model calibration and uncertainty estimation for complex deterministic models. A Bayesian approach is used to combine data from observations, the deterministic model, and prior parameter distributions to obtain forecast distributions. A case study is presented in which the statistical framework is applied using the hydrogeochemical model (MAGIC) for an assessment of recovery from acidification of soils and surface waters at a long-term study site in Norway under different future acid deposition conditions. The water quality parameters are coupled with a simple dose-response model for trout population health. Uncertainties in model output parameters are estimated and forecast results are presented as probability distributions for future water chemistry and as probability distributions of future healthy trout populations. The forecast results are examined for three different scenarios of future acid deposition corresponding to three different emissions control strategies for Europe. Despite the explicit consideration of uncertainties propagated into the future forecasts, there are clear differences among the scenarios. The case study illustrates how inclusion of uncertainties in model predictions can strengthen the inferences drawn from model results in support of decision making and assessments.

Are brook trout streams in western Virginia and Shenandoah National Park recovering from acidification?

Streamwater composition data obtained through periodic sampling of streams that support brook trout (Salvelinus fontinalis) in the mountains of western Virginia were examined for evidence of recovery from acidification during the 1988-2001 period. Measurements of sulfate deposition in precipitation indicate that sulfate deposition in the region declined approximately 40% between 1985 and 2000. While no significant regional trends in acid-base constituents were observed for the set (n = 65) of western Virginia study streams, significant regional trends were observed for a subset (n = 14) of streams in Shenandoah National Park (SNP). For the subset of SNP streams, the median increase in acid-neutralizing capacity (ANC) was 0.168 microequiv L(-1) year(-1) and the median decrease in sulfate concentration was -0.229 microequiv L(-1) year(-1). Although these trends are consistent with recovery from acidification, the degree of apparent recovery is small compared to estimates of historic acidification in SNP streams and much less than observed in other, more northern regions in the United States. Correlation between sulfate concentration trends and current sulfate concentrations in streamwater suggests that recovery from stream acidification in the western Virginia region is determined by sulfur retention processes in watershed soils. A transient increase in nitrate concentrations that occurred among some western Virginia streams following forest defoliation by the gypsy moth (Lymantria dispar) complicates interpretation of the observed patterns of change in acid-base status.

Aggregating Fine-Scale Ecological Knowledge to Model Coarser-Scale Attributes of Ecosystems.

As regional and global scales become more important to ecologists, methods must be developed for the application of existing fine-scale knowledge to predict coarser-scale ecosystem properties. This generally involves some form of model in which fine-scale components are aggregated. This aggregation is necessary to avoid the cumulative error associated with the estimation of a large number of parameters. However, aggregation can itself produce errors that arise because of the variation among the aggregated components. The statistical expectation operator can be used as a rigorous method for translating fine-scale relationships to coarser scales without aggregation errors. Unfortunately this method is too cumbersome to be applied in most cases, and alternative methods must be used. These alternative methods are typically partial corrections for the variation in only a few of the fine-scale attributes. Therefore, for these methods to be effective, the attributes that are the most severe sources of error must be identified a priori. We present a procedure for making these identifications based on a Monte Carlo sampling of the fine-scale attributes. We then present four methods of translating fine-scale knowledge so it can be applied at coarser scales: (1) partial transformations using the expectation operator, (2) moment expansions, (3) partitioning, and (4) calibration. These methods should make it possible to apply the vast store of fine-scale ecological knowledge to model coarser-scale attributes of ecosystems.