Ensemble Modeling of the Baltic Sea Ecosystem to Provide Scenarios for Management

We present a multi-model ensemble study for the Baltic Sea, and investigate the combined impact of changing climate, external nutrient supply, and fisheries on the marine ecosystem. The applied regional climate system model contains state-of-the-art component models for the atmosphere, sea ice, ocean, land surface, terrestrial and marine biogeochemistry, and marine food-web. Time-dependent scenario simulations for the period 1960–2100 are performed and uncertainties of future projections are estimated. In addition, reconstructions since 1850 are carried out to evaluate the models sensitivity to external stressors on long time scales. Information from scenario simulations are used to support decision-makers and stakeholders and to raise awareness of climate change, environmental problems, and possible abatement strategies among the general public using geovisualization. It is concluded that the study results are relevant for the Baltic Sea Action Plan of the Helsinki Commission.     

Uncertainties and recommendations

An assessment of the impacts of changes in climate and UV-B radiation on Arctic terrestrial ecosystems, made within the Arctic Climate Impacts Assessment (ACIA), highlighted the profound implications of projected warming in particular for future ecosystem services, biodiversity and feedbacks to climate. However, although our current understanding of ecological processes and changes driven by climate and UV-B is strong in some geographical areas and in some disciplines, it is weak in others. Even though recently the strength of our predictions has increased dramatically with increased research effort in the Arctic and the introduction of new technologies, our current understanding is still constrained by various uncertainties. The assessment is based on a range of approaches that each have uncertainties, and on data sets that are often far from complete. Uncertainties arise from methodologies and conceptual frameworks, from unpredictable surprises, from lack of validation of models, and from the use of particular scenarios, rather than predictions, of future greenhouse gas emissions and climates. Recommendations to reduce the uncertainties are wide-ranging and relate to all disciplines within the assessment. However, a repeated theme is the critical importance of achieving an adequate spatial and long-term coverage of experiments, observations and monitoring of environmental changes and their impacts throughout the sparsely populated and remote region that is the Arctic.     

Use of historical assessment for evaluation of process-based model projections of future environmental change: Lake acidification in the Adirondack mountains, New York, USA

Because of the considerable uncertainties associated with modeling complex ecosystem processes, it is essential that every effort be made to test model performance prior to relying on model projections for assessment of future surface water chemical response to environmental perturbation. Unfortunately, long-term chemical data with which to validate model performance are seldom available. The authors present here an evaluation of historical acidification of lake waters in the northeastern United States, and compare historical changes in a set of lakes to hindcasts from the same watershed model (MAGIC) used to estimate future changes in response to acidic deposition. The historical analyses and comparisons with MAGIC model hindcasts and forecasts of acid-base response demonstrate that the acidic and low-ANC lakes in this region are responsive to strong acid inputs. However, the model estimates suggest lakewater chemistry is more responsive to atmospheric inputs of sulfur than do the estimates based on paleolimnological historical analyses. A 'weight-of-evidence approach' that incorporates all available sources of information regarding acid-base response provides a more reasonable estimate of future change than an approach based on model projections alone. The results of these analyses have important implications for predicting future surface water chemical change in response to acidic deposition, establishing critical loads of atmospheric pollutants, and other environmental assessment activities where natural variation often exceeds the trends under investigation (high noise-to-signal ratio). Under these conditions, it is particularly important to evaluate future model projections in light of historical trends data.     

Assessing and managing freshwater ecosystems vulnerable to environmental change

Freshwater ecosystems are important for global biodiversity and provide essential ecosystem services. There is consensus in the scientific literature that freshwater ecosystems are vulnerable to the impacts of environmental change, which may trigger irreversible regime shifts upon which biodiversity and ecosystem services may be lost. There are profound uncertainties regarding the management and assessment of the vulnerability of freshwater ecosystems to environmental change. Quantitative approaches are needed to reduce this uncertainty. We describe available statistical and modeling approaches along with case studies that demonstrate how resilience theory can be applied to aid decision-making in natural resources management. We highlight especially how long-term monitoring efforts combined with ecological theory can provide a novel nexus between ecological impact assessment and management, and the quantification of systemic vulnerability and thus the resilience of ecosystems to environmental change.     

Effects on the structure of Arctic ecosystems in the short- and long-term perspectives

Species individualistic responses to warming and increased UV-B radiation are moderated by the responses of neighbors within communities, and trophic interactions within ecosystems. All of these responses lead to changes in ecosystem structure. Experimental manipulation of environmental factors expected to change at high latitudes showed that summer warming of tundra vegetation has generally led to smaller changes than fertilizer addition. Some of the factors manipulated have strong effects on the structure of Arctic ecosystems but the effects vary regionally, with the greatest response of plant and invertebrate communities being observed at the coldest locations. Arctic invertebrate communities are very likely to respond rapidly to warming whereas microbial biomass and nutrient stocks are more stable. Experimentally enhanced UV-B radiation altered the community composition of gram-negative bacteria and fungi, but not that of plants. Increased plant productivity due to warmer summers may dominate food-web dynamics. Trophic interactions of tundra and sub-Arctic forest plant-based food webs are centered on a few dominant animal species which often have cyclic population fluctuations that lead to extremely high peak abundances in some years. Population cycles of small rodents and insect defoliators such as the autumn moth affect the structure and diversity of tundra and forest-tundra vegetation and the viability of a number of specialist predators and parasites. Ice crusting in warmer winters is likely to reduce the accessibility of plant food to lemmings, while deep snow may protect them from snow-surface predators. In Fennoscandia, there is evidence already for a pronounced shift in small rodent community structure and dynamics that have resulted in a decline of predators that specialize in feeding on small rodents. Climate is also likely to alter the role of insect pests in the birch forest system: warmer winters may increase survival of eggs and expand the range of the insects. Insects that harass reindeer in the summer are also likely to become more widespread, abundant and active during warmer summers while refuges for reindeer/caribou on glaciers and late snow patches will probably disappear.     

Meteorological Considerations in Air Quality Planning

Results from dispersion models which are routinely used for regulatory purposes do not reflect the uncertainties which are Inherent In the input data. To remedy this, a formula for propagating measurement uncertainties of emission rate, wind speed, wind direction, horizontal dispersion parameter, vertical dispersion parameter, effective emission height, and mixing depth is derived for EPA’s Industrial Source Complex Short Term (ISCST) Gaussian dispersion model for the simple case of a single stack-type source and nonbuoyant plume. Values for the uncertainties of the input variables are chosen and used to calculate ambient concentration uncertainties. These calculated uncertainties are compared with the standard deviation of ambient concentrations calculated from 2500 input data sets for each of four stability classes and three downwind distances, which were randomly altered to simulate the effects of measurement uncertainty. The calculated uncertainties do not differ significantly from the standard deviations of the randomized calculations for input data uncertainties as high as 30 percent and Stability Classes A-C. The calculated uncertainties overestimate the actual uncertainty of model calculations for input data uncertainties greater than 20 percent for Stability Class D.     

Impact of Climate Change on Fish Population Dynamics in the Baltic Sea: A Dynamical Downscaling Investigation

Understanding how climate change, exploitation and eutrophication will affect populations and ecosystems of the Baltic Sea can be facilitated with models which realistically combine these forcings into common frameworks. Here, we evaluate sensitivity of fish recruitment and population dynamics to past and future environmental forcings provided by three ocean-biogeochemical models of the Baltic Sea. Modeled temperature explained nearly as much variability in reproductive success of sprat (Sprattus sprattus; Clupeidae) as measured temperatures during 1973-2005, and both the spawner biomass and the temperature have influenced recruitment for at least 50 years. The three Baltic Sea models estimate relatively similar developments (increases) in biomass and fishery yield during twenty-first century climate change (ca. 28 % range among models). However, this uncertainty is exceeded by the one associated with the fish population model, and by the source of global climate data used by regional models. Knowledge of processes and biases could reduce these uncertainties.     

The re-imagining of a framework for agricultural land use: A pathway for integrating agricultural practices into ecosystem services,planetary boundaries and sustainable development goals: This article belongs to Ambio’s 50th Anniversary Collection. Theme: Agricultural land use

This paper reflects on the legacy of the Ambio papers by Sombroek et al. (1993), Turner et al. (1994), and Brussaard et al. (1997) on the study of agricultural land use and its impacts on global carbon storage and nutrient dynamics. The papers were published at a time of transition in ecology that involved the integration of humans as components of ecosystems, the formulation of the ecosystem services, and emergence of sustainability science. The papers offered new frameworks to studying agricultural land use across multiple scales in a way that captured causality from interacting components of the system. Each paper argued for more comprehensive data sets; foreseeing the power of network-based science, the potential of molecular technologies to assess biodiversity, and advances in remote sensing. The papers have contributed both conceptual framings and methodological approaches to an ongoing movement to identify a pathway to study agricultural land use and environmental change that fit within the concepts of ecosystem services, planetary boundaries and sustainable development goals.     

Characterization of the effluents from a Municipal Solid Waste incinerator plant and of their environmental impact

An easy approach for the evaluation of the environmental impact of a Municipal Solid Waste (MSW) incinerator plant is described. In order to perform this study, selected chemical pollutants were monitored both in the plant emissions and in the waste to be burnt. The composition of waste was also determined. A mathematical model was worked out for the estimation of the ground deposition fluxes. A first validation of the model for the case studied was drawn by comparing the simulation values with data obtained on real soil samples.     

On the uncertainty and confidence in decision support tools (DSTs) with insights from the Baltic Sea ecosystem

Ecosystems around the world are increasingly exposed to multiple, often interacting human activities, leading to pressures and possibly environmental state changes. Decision support tools (DSTs) can assist environmental managers and policy makers to evaluate the current status of ecosystems (i.e. assessment tools) and the consequences of alternative policies or management scenarios (i.e. planning tools) to make the best possible decision based on prevailing knowledge and uncertainties. However, to be confident in DST outcomes it is imperative that known sources of uncertainty such as sampling and measurement error, model structure, and parameter use are quantified, documented, and addressed throughout the DST set-up, calibration, and validation processes. Here we provide a brief overview of the main sources of uncertainty and methods currently available to quantify uncertainty in DST input and output. We then review 42 existing DSTs that were designed to manage anthropogenic pressures in the Baltic Sea to summarise how and what sources of uncertainties were addressed within planning and assessment tools. Based on our findings, we recommend future DST development to adhere to good modelling practise principles, and to better document and communicate uncertainty among stakeholders.Electronic supplementary materialThe online version of this article (doi:10.1007/s13280-020-01385-x) contains supplementary material, which is available to authorized users.     

Economy-wide material flow indicators in the Czech Republic: trends, decoupling analysis and uncertainties

Material and energy flows (together with human appropriation of land) are considered the key cause of environmental problems. This paper describes the application of economy-wide material flow accounting and analysis to the economy of the Czech Republic for 1990-2002. The results show a decrease of material intensity and decoupling of the economic growth from environmental pressure. The second part of the paper treats an important issue of uncertainties related to economy-wide material flow indicators in the Czech Republic. The results point out that the high uncertainties related to some material flow indicators may be an obstacle to their applicability.     

Scientific activities of Euro Chlor in monitoring and assessing naturally and man-made organohalogens

In this paper a review of the scientific activities and research programmes carried out by Euro Chlor, the European Federation of chlor-alkali producers is presented according to two main axes: marine risk assessments with statistical analysis of monitoring data, temporal trends of emission levels and environmental concentrations. The methodology applied in each field is briefly presented and then illustrated by several practical examples. As a large part of the uncertainties in assessing the risk of a chemical to a given species or ecosystem often comes from the difficulty in evaluating the exposure level, Euro Chlor has chosen to use a monitoring approach, the exposure level being estimated from a statistical analysis of measured concentrations levels in water and sediment from rivers, estuaries and coastal areas. As the modelling approach often used by the authorities to estimate the predicted environmental concentration value is starting from roughly estimated emission levels, Euro Chlor collated emissions data from about 80 production plants in order to reduce the uncertainty associated with the default values introduced in the modelling approach.A brief review of the European emission levels for chlorinated organic substances is given as well as the temporal trends of both emission and environmental levels. A methodology to quantify the trends in measured concentrations at local and regional scales is briefly described. The observed decreasing trends demonstrate the continuous progress made by the Euro Chlor member companies in protecting the environment.Finally, the problems linked to the simultaneous presence in the environment of naturally and man-made chlorinated substances are briefly reviewed. To stimulate further research in the field, two key questions are raised which have not yet found a satisfactory answer: how to quantify natural background levels and how to quantify global persistence in the environment?     

Representative boreal forest habitats in northern Europe,and a revised model for ecosystem management and biodiversity conservation

The natural range of variation of ecosystems provides reference conditions for sustainable management and biodiversity conservation. We review how the understanding of natural reference conditions of boreal forests in northern Europe has changed from earlier perceptions of even-aged dynamics driven by stand-replacing disturbances towards current understanding highlighting the role of non-stand-replacing disturbances and the resultant complex forest dynamics and structures. We show how earlier views and conceptual models of forest disturbance dynamics, including the influential ASIO model, provide estimates of reference conditions that are outside the natural range of variation. Based on a research synthesis, we present a revised forest reference model incorporating the observed complexity of ecosystem dynamics and the prevalence of old forests. Finally, we outline a management model and demonstrate its use in forest ecosystem management and show how regional conservation area needs can be estimated. We conclude that attaining favourable conservation status in northern Europe’s boreal forests requires increasing emphasis on ecosystem management and conservation for old forest characteristics.Electronic supplementary materialThe online version of this article (10.1007/s13280-020-01444-3) contains supplementary material, which is available to authorized users.     

Atmospheric composition change: Climate–Chemistry interactions

Chemically active climate compounds are either primary compounds like methane (CH₄), removed by oxidation in the atmosphere, or secondary compounds like ozone (O₃), sulfate and organic aerosols, both formed and removed in the atmosphere. Man-induced climate–chemistry interaction is a two-way process: Emissions of pollutants change the atmospheric composition contributing to climate change through the aforementioned climate components, and climate change, through changes in temperature, dynamics, the hydrological cycle, atmospheric stability, and biosphere-atmosphere interactions, affects the atmospheric composition and oxidation processes in the troposphere. Here we present progress in our understanding of processes of importance for climate–chemistry interactions, and their contributions to changes in atmospheric composition and climate forcing. A key factor is the oxidation potential involving compounds like O₃ and the hydroxyl radical (OH). Reported studies represent both current and future changes. Reported results include new estimates of radiative forcing based on extensive model studies of chemically active climate compounds like O₃, and of particles inducing both direct and indirect effects. Through EU projects like ACCENT, QUANTIFY, and the AeroCom project, extensive studies on regional and sector-wise differences in the impact on atmospheric distribution are performed. Studies have shown that land-based emissions have a different effect on climate than ship and aircraft emissions, and different measures are needed to reduce the climate impact. Several areas where climate change can affect the tropospheric oxidation process and the chemical composition are identified. This can take place through enhanced stratospheric–tropospheric exchange of ozone, more frequent periods with stable conditions favoring pollution build up over industrial areas, enhanced temperature induced biogenic emissions, methane releases from permafrost thawing, and enhanced concentration through reduced biospheric uptake. During the last 5–10 years, new observational data have been made available and used for model validation and the study of atmospheric processes. Although there are significant uncertainties in the modeling of composition changes, access to new observational data has improved modeling capability. Emission scenarios for the coming decades have a large uncertainty range, in particular with respect to regional trends, leading to a significant uncertainty range in estimated regional composition changes and climate impact.     

Projecting Climate Change Effects on Forest Net Primary Productivity in Subtropical Louisiana,USA

This study projected responses of forest net primary productivity (NPP) to three climate change scenarios at a resolution of 5 km × 5 km across the state of Louisiana, USA. In addition, we assessed uncertainties associated with the NPP projection at the grid and state levels. Climate data of the scenarios were derived from Community Climate System Model outputs. Changes in annual NPP between 2000 and 2050 were projected with the forest ecosystem model PnET-II. Results showed that forest productivity would increase under climate change scenarios A1B and A2, but with scenario B1, it would peak during 2011–2020 and then decline. The projected average NPP under B1 over the years from 2000 to 2050 was significantly different from those under A1B and A2. Forest NPP appeared to be primarily a function of temperature, not precipitation. Uncertainties of the NPP projection were due to large spatial resolution of the climate variables. Overall, this study suggested that in order to project effects of climate change on forest ecosystem at regional level, modeling uncertainties could be reduced by increasing the spatial resolution of the climate projections.     

Modeling assessment of air emission flux of mercury from soils in terrestrial landscape components: model tests and sensitivities

The abilities of a screening-level model to predict variations in elemental mercury (Hg0) air emissions from soils in terrestrial landscapes are examined by comparing simulation results to published observational data and by performing sensitivity analyses. Despite uncertainties and simplifications, the model results obtained offer some degree of confidence in the model's joint ability to relate readily available environmental parameters to airborne emissions of Hg predicted by coupling simple atmospheric and soil parameters with Hg cycling and transport algorithms. The model reasonably predicted the observational data in the considered data sets except for one site for which significant uncertainty was associated with model input data. Predictions are consistent with many trends observed in the field studies; better predictions were obtained for nonvegetated systems (relative errors between 0.4 and 9.7%) than for shaded-soil landscapes (relative errors between 2.3 and 27%). The model reflected field data showing that daily average emission rates of Hg0, formed by the reduction of Hg(II), are primarily controlled by changes in solar radiation, soil moisture, temperature, and, to a lesser extent, wind conditions. The model may have potential use in several preliminary studies to characterize trends of airborne Hg emitted from terrestrial sources to the atmosphere.     

Uncertainties and novel prospects in the study of the soil carbon dynamics

Establishment of the Kyoto Protocol has resulted in an effort to look towards living biomass and soils for carbon sequestration. In order for carbon credits to be meaningful, sustained carbon sequestration for decades or longer is required. It has been speculated that improved land management could result in sequestration of a substantial amount of carbon in soils within several decades and therefore can be an important option in reducing atmospheric CO2 concentration. However, evaluation of soil carbon sources and sinks is difficult because the dynamics of soil carbon storage and release is complex and still not well understood. There has been rapid development of quantitative techniques over the past two decades for measuring the component fluxes of the global carbon cycle and for studying the soil carbon cycle. Most significant development in the soil carbon cycle study is the application of accelerator mass spectrometry (AMS) in radiocarbon measurements. This has made it possible to unravel rates of carbon cycling in soils, by studying natural levels of radiocarbon in soil organic matter and soil CO2. Despite the advances in the study of the soil carbon cycle in the recent decades, tremendous uncertainties exist in the sizes and turnover times of soil carbon pools. The uncertainties result from lack of standard methods and incomplete understanding of soil organic carbon dynamics, compounded by natural variability in soil carbon and carbon isotopic content even within the same ecosystem. Many fundamental questions concerning the dynamics of the soil carbon cycle have yet to be answered. This paper reviews and synthesizes the isotopic approaches to the study of the soil carbon cycle. We will focus on uncertainties and limitations associated with these approaches and point out areas where more research is needed to improve our understanding of this important component of the global carbon cycle.     

Predictive modeling of effects under global change

The status of computer simulation models from around the world for evaluating the possible ecological, environmental, and societal consequences of global change is presented in this paper. In addition, a brief synopsis of the state of the science of these impacts is included. Issues considered include future changes in climate and patterns of land use for societal needs. Models discussed relate to vegetation (e.g. crop), soil, bio-geochemistry, water, and wildlife responses to conventional, forecasted changes in temperature and precipitation. Also described are models of these responses, alone and interactively, to increased CO(2), other air pollutants and UV-B radiation, as the state of the science allows. Further, models of land-use change are included. Additionally, global multiple sector models of environment, natural resources, human population dynamics, economics, energy, and political relations are reviewed for integrated impact assessment. To the extent available, information on computer software and hardware requirements is presented for the various models. The paper concludes with comments about using these technologies as they relate to ecological risk assessment for policy decision analysis. Such an effort is hampered by considerable uncertainties with the output of existing models, because of the uncertainties associated with input data and the definitions of their dose-response relationships. The concluding suggestions point the direction for new developments in modeling and analyses that are needed for the 21st century.     

The carbon budget of Canadian forests: a sensitivity analysis of changes in disturbance regimes, growth rates, and decomposition rates

Ecosystem responses to climate changes will affect the exchange of carbon (C) with the atmosphere, thus providing feedback for future climate response. We have developed a C budget model of Canadian forests and forest sector activities and used sensitivity analysis runs with changes in productivity, decomposition, and disturbance regimes to assess the sensitivity of the Canadian forest sector C budget over the next century. The model operates on data derived from Canada's National Forest Biomass Inventory, from the Oak Ridge National Laboratory global soil C data base, and from Canadian data bases that document areas annually disturbed by fire, insects, and harvesting. It simulates the dynamics of biomass and soil C pools (including detritus and coarse woody debris) as they are affected by growth, decomposition, and disturbances. For the reference run of the model, we assumed unchanging climate and disturbance regimes. Under these conditions, total ecosystem C increased by 2 Gt C (2.3%) over the 100-year simulation period. In the sensitivity analysis, we explored the effects of changes in the area annually disturbed by fire and insect-induced stand mortality (-60 to +300%), growth rates (-10 to +20%), decomposition rates (-10 to +25%), and combined changes in growth and decomposition rates. In every model run, the change of total ecosystem C relative to the reference run was less than 10%. Combined changes to growth and decomposition rates yielded very small deviations from the results of the reference run (-0.8 to +1.2%). Because disturbance regime changes affect forest age-class structure as well as forest dynamics, they are expected to affect C budgets strongly. Total ecosystem C, however, is slightly more sensitive to changes in growth and decomposition parameters than to changes in disturbance regimes. Although the sensitivity analysis results suggest that C budgets are little affected by the range of parameter changes implemented here, we must emphasize that our sensitivity analyses do not account for potentially important processes, such as regeneration failure or the shifts in forest distribution.     

A fuzzy logic expert system for evaluating policy progress towards sustainability goals

Evaluating progress towards environmental sustainability goals can be difficult due to a lack of measurable benchmarks and insufficient or uncertain data. Marine settings are particularly challenging, as stakeholders and objectives tend to be less well defined and ecosystem components have high natural variability and are difficult to observe directly. Fuzzy logic expert systems are useful analytical frameworks to evaluate such systems, and we develop such a model here to formally evaluate progress towards sustainability targets based on diverse sets of indicators. Evaluation criteria include recent (since policy enactment) and historical (from earliest known state) change, type of indicators (state, benefit, pressure, response), time span and spatial scope, and the suitability of an indicator in reflecting progress toward a specific objective. A key aspect of the framework is that all assumptions are transparent and modifiable to fit different social and ecological contexts. We test the method by evaluating progress towards four Aichi Biodiversity Targets in Canadian oceans, including quantitative progress scores, information gaps, and the sensitivity of results to model and data assumptions. For Canadian marine systems, national protection plans and biodiversity awareness show good progress, but species and ecosystem states overall do not show strong improvement. Well-defined goals are vital for successful policy implementation, as ambiguity allows for conflicting potential indicators, which in natural systems increases uncertainty in progress evaluations. Importantly, our framework can be easily adapted to assess progress towards policy goals with different themes, globally or in specific regions.