Conceptualizing and communicating management effects on forest water quality

We present a framework for evaluating and communicating effects of human activity on water quality in managed forests. The framework is based on the following processes: atmospheric deposition, weathering, accumulation, recirculation and flux. Impairments to water quality are characterized in terms of their extent, longevity and frequency. Impacts are communicated using a “traffic lights” metaphor for characterizing severity of water quality impairments arising from forestry and other anthropogenic pressures. The most serious impairments to water quality in managed boreal forests include (i) forestry activities causing excessive sediment mobilization and extirpation of aquatic species and (ii) other anthropogenic pressures caused by long-range transport of mercury and acidifying pollutants. The framework and tool presented here can help evaluate, summarize and communicate the most important issues in circumstances where land management and other anthropogenic pressures combine to impair water quality and may also assist in implementing the “polluter pays” principle.     

Nitrogen dynamics in managed boreal forests: Recent advances and future research directions

Nitrogen (N) availability plays multiple roles in the boreal landscape, as a limiting nutrient to forest growth, determinant of terrestrial biodiversity, and agent of eutrophication in aquatic ecosystems. We review existing research on forest N dynamics in northern landscapes and address the effects of management and environmental change on internal cycling and export. Current research foci include resolving the nutritional importance of different N forms to trees and establishing how tree–mycorrhizal relationships influence N limitation. In addition, understanding how forest responses to external N inputs are mediated by above- and belowground ecosystem compartments remains an important challenge. Finally, forestry generates a mosaic of successional patches in managed forest landscapes, with differing levels of N input, biological demand, and hydrological loss. The balance among these processes influences the temporal patterns of stream water chemistry and the long-term viability of forest growth. Ultimately, managing forests to keep pace with increasing demands for biomass production, while minimizing environmental degradation, will require multi-scale and interdisciplinary perspectives on landscape N dynamics.     

Consequences of nitrate leaching following stem-only harvesting of Swedish forests are dependent on spatial scale

Short-term increases in soil solution nitrate (NO₃⁻) concentration are often observed after forest harvest, even in N-limited systems. We model NO₃⁻ leaching below the rooting zone as a function of site productivity. Using national forest inventories and published estimates of N attenuation in rivers and the riparian zone, we estimate effects of stem-only harvesting on NO₃⁻ leaching to groundwater, surface waters and the marine environment. Stem-only harvesting is a minor contributor to NO₃⁻ pollution of Swedish waters. Effects in surface waters are rapidly diluted downstream, but can be locally important for shallow well-waters as well as for the total amount of N reaching the sea. Harvesting adds approximately 8 Gg NO₃-N to soil waters in Sweden, with local concentrations up to 7 mg NO₃-N l⁻¹. Of that, ∼3.3 Gg reaches the marine environment. This is ∼3% of the overall Swedish N load to the Baltic.     

Assessment of Uncertainty in Long-Term Mass Balances for Acidification Assessments: A MAGIC Model Exercise

Long-term (1860–2010) catchment mass balance calculations rely on models and assumptions which are sources of uncertainty in acidification assessments. In this article, we report on an application of MAGIC to model acidification at the four Swedish IM forested catchments that have been subject to differing degrees of acidification stress. Uncertainties in the modeled mass balances were mainly associated with the deposition scenario and assumptions about sulfate adsorption and soil mass. Estimated base cation (BC) release rates (weathering) varied in a relatively narrow range of 47–62 or 42–47 meq m⁻² year⁻¹, depending on assumptions made about soil cation exchange capacity and base saturation. By varying aluminum solubility or introducing a dynamic weathering feedback that allowed BC release to increase at more acidic pHs, a systematic effect on predicted changes in acid neutralizing capacity (ΔANC ca. 10–41 μeq l⁻¹) and pH (ca. ΔpH = 0.1–0.6) at all sites was observed. More robust projections of future changes in pH and ANC are dependent on reducing uncertainties in BC release rates, the timing, and extent of natural acidification through BC uptake by plants, temporal changes in soil element pools, and fluxes of Al between compartments.     

Riparian Zone Influence on Stream Water Dissolved Organic Carbon Concentrations at the Swedish Integrated Monitoring Sites

Short-term variability in stream water dissolved organic carbon (DOC) concentrations is controlled by hydrology, climate and atmospheric deposition. Using the Riparian flow-concentration Integration Model (RIM), we evaluated factors controlling stream water DOC in the Swedish Integrated Monitoring (IM) catchments by separating out hydrological effects on stream DOC dynamics. Model residuals were correlated with climate and deposition-related drivers. DOC was most strongly correlated to water flow in the northern catchment (Gammtratten). The southern Aneboda and Kindla catchments had pronounced seasonal DOC signals, which correlated weakly to flow. DOC concentrations at Gårdsjön increased, potentially in response to declining acid deposition. Soil temperature correlated strongly with model residuals at all sites. Incorporating soil temperature in RIM improved model performance substantially (20–62% lower median absolute error). According to the simulations, the RIM conceptualization of riparian processes explains between 36% (Kindla) and 61% (Aneboda) of the DOC dynamics at the IM sites.     

A classification and regression tree model of controls on dissolved inorganic nitrogen leaching from European forests

Often, there is a non-linear relationship between atmospheric dissolved inorganic nitrogen (DIN) input and DIN leaching that is poorly captured by existing models. We present the first application of the non-parametric classification and regression tree approach to evaluate the key environmental drivers controlling DIN leaching from European forests. DIN leaching was classified as low (<3), medium (3-15) or high (>15 kg N ha⁻¹ year⁻¹) at 215 sites across Europe. The analysis identified throughfall NO₃⁻ deposition, acid deposition, hydrology, soil type, the carbon content of the soil, and the legacy of historic N deposition as the dominant drivers of DIN leaching for these forests. Ninety four percent of sites were successfully classified into the appropriate leaching category. This approach shows promise for understanding complex ecosystem responses to a wide range of anthropogenic stressors as well as an improved method for identifying risk and targeting pollution mitigation strategies in forest ecosystems.     

The role of biogeochemical hotspots,landscape heterogeneity,and hydrological connectivity for minimizing forestry effects on water quality

Protecting water quality in forested regions is increasingly important as pressures from land-use, long-range transport of air pollutants, and climate change intensify. Maintaining forest industry without jeopardizing sustainability of surface water quality therefore requires new tools and approaches. Here, we show how forest management can be optimized by incorporating landscape sensitivity and hydrological connectivity into a framework that promotes the protection of water quality. We discuss how this approach can be operationalized into a hydromapping tool to support forestry operations that minimize water quality impacts. We specifically focus on how hydromapping can be used to support three fundamental aspects of land management planning including how to (i) locate areas where different forestry practices can be conducted with minimal water quality impact; (ii) guide the off-road driving of forestry machines to minimize soil damage; and (iii) optimize the design of riparian buffer zones. While this work has a boreal perspective, these concepts and approaches have broad-scale applicability.     

The Swedish monitoring of surface waters: 50 years of adaptive monitoring

For more than 50 years, scientific insights from surface water monitoring have supported Swedish evidence-based environmental management. Efforts to understand and control eutrophication in the 1960s led to construction of wastewater treatment plants with phosphorus retention, while acid rain research in the 1970s contributed to international legislation curbing emissions. By the 1990s, long-time series were being used to infer climate effects on surface water chemistry and biology. Monitoring data play a key role in implementing the EU Water Framework Directive and other legislation and have been used to show beneficial effects of agricultural management on Baltic Sea eutrophication. The Swedish experience demonstrates that well-designed and financially supported surface water monitoring can be used to understand and manage a range of stressors and societal concerns. Using scientifically sound adaptive monitoring principles to balance continuity and change has ensured long-time series and the capability to address new questions over time.     

Is the Water Footprint an Appropriate Tool for Forestry and Forest Products: The Fennoscandian Case

The water footprint by the Water Footprint Network (WF) is an ambitious tool for measuring human appropriation and promoting sustainable use of fresh water. Using recent case studies and examples from water-abundant Fennoscandia, we consider whether it is an appropriate tool for evaluating the water use of forestry and forest-based products. We show that aggregating catchment level water consumption over a product life cycle does not consider fresh water as a renewable resource and is inconsistent with the principles of the hydrologic cycle. Currently, the WF assumes that all evapotranspiration (ET) from forests is a human appropriation of water although ET from managed forests in Fennoscandia is indistinguishable from that of unmanaged forests. We suggest that ET should not be included in the water footprint of rain-fed forestry and forest-based products. Tools for sustainable water management should always contextualize water use and water impacts with local water availability and environmental sensitivity.     

Statistical models for evaluating suspected artefacts in long-term environmental monitoring data

Long-term water quality monitoring is of high value for environmental management as well as for research. Artificial level shifts in time series due to method improvements, flaws in laboratory practices or changes in laboratory are a common limitation for analysis, which, however, are often ignored. Statistical estimation of such artefacts is complicated by the simultaneous existence of trends, seasonal variation and effects of other influencing factors, such as weather conditions. Here, we investigate the performance of generalised additive mixed models (GAMM) to simultaneously identify one or more artefacts associated with artificial level shifts, longitudinal effects related to temporal trends and seasonal variation, as well as to model the serial correlation structure of the data. In the same model, it is possible to estimate separate residual variances for different periods so as to identify if artefacts not only influence the mean level but also the dispersion of a series. Even with an appropriate statistical methodology, it is difficult to quantify artificial level shifts and make appropriate adjustments to the time series. The underlying temporal structure of the series is especially important. As long as there is no prominent underlying trend in the series, the shift estimates are rather stable and show less variation. If an artificial shift occurs during a slower downward or upward tendency, it is difficult to separate these two effects and shift estimates can be both biased and have large variation. In the case of a change in method or laboratory, we show that conducting the analyses with both methods in parallel strongly improves estimates of artefact effects on the time series, even if certain problems remain. Due to the difficulties of estimating artificial level shifts, posterior adjustment is problematic and can lead to time series that no longer can be used for trend analysis or other analysis based on the longitudinal structure of the series. Before carrying out a change in analytic method or laboratory, it should be considered if this is absolutely necessary. If changes cannot be avoided, the analysis of the two methods considered, or the two laboratories contracted, should be run in parallel for a considerable period of time so as to enable a good assessment of changes introduced to the data series.