Relevance of Hydro-Climatic Change Projection and Monitoring for Assessment of Water Cycle Changes in the Arctic

Rapid changes to the Arctic hydrological cycle challenge both our process understanding and our ability to find appropriate adaptation strategies. We have investigated the relevance and accuracy development of climate change projections for assessment of water cycle changes in major Arctic drainage basins. Results show relatively good agreement of climate model projections with observed temperature changes, but high model inaccuracy relative to available observation data for precipitation changes. Direct observations further show systematically larger (smaller) runoff than precipitation increases (decreases). This result is partly attributable to uncertainties and systematic bias in precipitation observations, but still indicates that some of the observed increase in Arctic river runoff is due to water storage changes, for example melting permafrost and/or groundwater storage changes, within the drainage basins. Such causes of runoff change affect sea level, in addition to ocean salinity, and inland water resources, ecosystems, and infrastructure. Process-based hydrological modeling and observations, which can resolve changes in evapotranspiration, and groundwater and permafrost storage at and below river basin scales, are needed in order to accurately interpret and translate climate-driven precipitation changes to changes in freshwater cycling and runoff. In contrast to this need, our results show that the density of Arctic runoff monitoring has become increasingly biased and less relevant by decreasing most and being lowest in river basins with the largest expected climatic changes.     

Seafood from a changing Arctic

We review current knowledge about climate change impacts on Arctic seafood production. Large-scale changes in the Arctic marine food web can be expected for the next 40–100 years. Possible future trajectories under climate change for Arctic capture fisheries anticipate the movement of aquatic species into new waters and changed the dynamics of existing species. Negative consequences are expected for some fish stocks but others like the Barents Sea cod (Gadus morhua) may instead increase. Arctic aquaculture that constitutes about 2% of global farming is mainly made up of Norwegian salmon (Salmo salar) farming. The sector will face many challenges in a warmer future and some of these are already a reality impacting negatively on salmon growth. Other more indirect effects from climate change are more uncertain with respect to impacts on the economic conditions of Arctic aquaculture.     

The missing pieces for better future predictions in subarctic ecosystems: A Torneträsk case study

Arctic and subarctic ecosystems are experiencing substantial changes in hydrology, vegetation, permafrost conditions, and carbon cycling, in response to climatic change and other anthropogenic drivers, and these changes are likely to continue over this century. The total magnitude of these changes results from multiple interactions among these drivers. Field measurements can address the overall responses to different changing drivers, but are less capable of quantifying the interactions among them. Currently, a comprehensive assessment of the drivers of ecosystem changes, and the magnitude of their direct and indirect impacts on subarctic ecosystems, is missing. The Torneträsk area, in the Swedish subarctic, has an unrivalled history of environmental observation over 100 years, and is one of the most studied sites in the Arctic. In this study, we summarize and rank the drivers of ecosystem change in the Torneträsk area, and propose research priorities identified, by expert assessment, to improve predictions of ecosystem changes. The research priorities identified include understanding impacts on ecosystems brought on by altered frequency and intensity of winter warming events, evapotranspiration rates, rainfall, duration of snow cover and lake-ice, changed soil moisture, and droughts. This case study can help us understand the ongoing ecosystem changes occurring in the Torneträsk area, and contribute to improve predictions of future ecosystem changes at a larger scale. This understanding will provide the basis for the future mitigation and adaptation plans needed in a changing climate.Electronic supplementary materialThe online version of this article (10.1007/s13280-020-01381-1) contains supplementary material, which is available to authorized users.     

Responses to projected changes in climate and UV-B at the species level

Environmental manipulation experiments showed that species respond individualistically to each environmental-change variable. The greatest responses of plants were generally to nutrient, particularly nitrogen, addition. Summer warming experiments showed that woody plant responses were dominant and that mosses and lichens became less abundant. Responses to warming were controlled by moisture availability and snow cover. Many invertebrates increased population growth in response to summer warming, as long as desiccation was not induced. CO2 and UV-B enrichment experiments showed that plant and animal responses were small. However, some microorganisms and species of fungi were sensitive to increased UV-B and some intensive mutagenic actions could, perhaps, lead to unexpected epidemic outbreaks. Tundra soil heating, CO2 enrichment and amendment with mineral nutrients generally accelerated microbial activity. Algae are likely to dominate cyanobacteria in milder climates. Expected increases in winter freeze-thaw cycles leading to ice-crust formation are likely to severely reduce winter survival rate and disrupt the population dynamics of many terrestrial animals. A deeper snow cover is likely to restrict access to winter pastures by reindeer/caribou and their ability to flee from predators while any earlier onset of the snow-free period is likely to stimulate increased plant growth. Initial species responses to climate change might occur at the sub-species level: an Arctic plant or animal species with high genetic/racial diversity has proved an ability to adapt to different environmental conditions in the past and is likely to do so also in the future. Indigenous knowledge, air photographs, satellite images and monitoring show that changes in the distributions of some species are already occurring: Arctic vegetation is becoming more shrubby and more productive, there have been recent changes in the ranges of caribou, and "new" species of insects and birds previously associated with areas south of the treeline have been recorded. In contrast, almost all Arctic breeding bird species are declining and models predict further quite dramatic reductions of the populations of tundra birds due to warming. Species-climate response surface models predict potential future ranges of current Arctic species that are often markedly reduced and displaced northwards in response to warming. In contrast, invertebrates and microorganisms are very likely to quickly expand their ranges northwards into the Arctic.     

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

Historically, the function of Arctic ecosystems in terms of cycles of nutrients and carbon has led to low levels of primary production and exchanges of energy, water and greenhouse gases have led to low local and regional cooling. Sequestration of carbon from atmospheric CO2, in extensive, cold organic soils and the high albedo from low, snow-covered vegetation have had impacts on regional climate. However, many aspects of the functioning of Arctic ecosystems are sensitive to changes in climate and its impacts on biodiversity. The current Arctic climate results in slow rates of organic matter decomposition. Arctic ecosystems therefore tend to accumulate organic matter and elements despite low inputs. As a result, soil-available elements like nitrogen and phosphorus are key limitations to increases in carbon fixation and further biomass and organic matter accumulation. Climate warming is expected to increase carbon and element turnover, particularly in soils, which may lead to initial losses of elements but eventual, slow recovery. Individual species and species diversity have clear impacts on element inputs and retention in Arctic ecosystems. Effects of increased CO2 and UV-B on whole ecosystems, on the other hand, are likely to be small although effects on plant tissue chemisty, decomposition and nitrogen fixation may become important in the long-term. Cycling of carbon in trace gas form is mainly as CO2 and CH4. Most carbon loss is in the form of CO2, produced by both plants and soil biota. Carbon emissions as methane from wet and moist tundra ecosystems are about 5% of emissions as CO2 and are responsive to warming in the absence of any other changes. Winter processes and vegetation type also affect CH4 emissions as well as exchanges of energy between biosphere and atmosphere. Arctic ecosystems exhibit the largest seasonal changes in energy exchange of any terrestrial ecosystem because of the large changes in albedo from late winter, when snow reflects most incoming radiation, to summer when the ecosystem absorbs most incoming radiation. Vegetation profoundly influences the water and energy exchange of Arctic ecosystems. Albedo during the period of snow cover declines from tundra to forest tundra to deciduous forest to evergreen forest. Shrubs and trees increase snow depth which in turn increases winter soil temperatures. Future changes in vegetation driven by climate change are therefore, very likely to profoundly alter regional climate.     

Past changes in Arctic terrestrial ecosystems, climate and UV radiation

At the last glacial maximum, vast ice sheets covered many continental areas. The beds of some shallow seas were exposed thereby connecting previously separated landmasses. Although some areas were ice-free and supported a flora and fauna, mean annual temperatures were 10-13 degrees C colder than during the Holocene. Within a few millennia of the glacial maximum, deglaciation started, characterized by a series of climatic fluctuations between about 18,000 and 11,400 years ago. Following the general thermal maximum in the Holocene, there has been a modest overall cooling trend, superimposed upon which have been a series of millennial and centennial fluctuations in climate such as the "Little Ice Age spanning approximately the late 13th to early 19th centuries. Throughout the climatic fluctuations of the last 150,000 years, Arctic ecosystems and biota have been close to their minimum extent within the most recent 10,000 years. They suffered loss of diversity as a result of extinctions during the most recent large-magnitude rapid global warming at the end of the last glacial stage. Consequently, Arctic ecosystems and biota such as large vertebrates are already under pressure and are particularly vulnerable to current and projected future global warming. Evidence from the past indicates that the treeline will very probably advance, perhaps rapidly, into tundra areas, as it did during the early Holocene, reducing the extent of tundra and increasing the risk of species extinction. Species will very probably extend their ranges northwards, displacing Arctic species as in the past. However, unlike the early Holocene, when lower relative sea level allowed a belt of tundra to persist around at least some parts of the Arctic basin when treelines advanced to the present coast, sea level is very likely to rise in future, further restricting the area of tundra and other treeless Arctic ecosystems. The negative response of current Arctic ecosystems to global climatic conditions that are apparently without precedent during the Pleistocene is likely to be considerable, particularly as their exposure to co-occurring environmental changes (such as enhanced levels of UV-B, deposition of nitrogen compounds from the atmosphere, heavy metal and acidic pollution, radioactive contamination, increased habitat fragmentation) is also without precedent.     

The impact of UV-B radiation and ozone on terrestrial vegetation

Although terrestrial vegetation has been exposed to UV-B radiation and ozone over the course of evolutionary history, it is essential to view the effects on vegetation of changing levels of these factors in the context of other features of climate change, such as increasing CO(2) levels and changes in temperature and precipitation patterns. Much of our understanding of the impacts of increased UV-B and ozone levels has come from studies of the effects of each individual factor. While such information may be relevant to a wider understanding of the roles that these factors may play in climate change, experience has shown that the interactions of environmental stresses on vegetation are rarely predictable. A further limitation on the applicability of such information results from the methodologies used for exposing plants to either factor. Much of our information comes from growth chamber, greenhouse or field studies using experimental protocols that made little or no provision for the stochastic nature of the changes in UV-B and ozone levels at the earth's surface, and hence excluded the roles of repair mechanisms. As a result, our knowledge of dose-response relationships under true field conditions is both limited and fragmentary, given the wide range of sensitivities among species and cultivars. Adverse effects of increased levels of either factor on vegetation are qualitatively well established, but the quantitative relationships are far from clear. In both cases, sensitivity varies with stage of plant development. At the population and community levels, differential responses of species to either factor has been shown to result in changes in competitiveness and community structure. At the mechanistic level, ozone generally inhibits photosynthetic gas exchange under both controlled and field conditions, and although UV-B is also inhibitory in some species under controlled conditions, others appear to be indifferent, particularly in the field. Both factors affect metabolism; a common response is increased secondary metabolism leading to the accumulation of phenolic compounds that, in the case of UV-B, offer the leaf cell some protection from radiation. Virtually no information is available about the effects of simultaneous or sequential exposures. Since both increased surface UV-B and ozone exposures have spatial and temporal components, it is important to evaluate the different scenarios that may occur, bearing in mind that elevated daytime ozone levels will attenuate the UV-B reaching the surface to some extent. The experimentation needed to acquire unequivocal effects data that are relevant to field situations must therefore be carried out using technologies and protocols that focus on quantification of the interactions of UV-B and ozone themselves and their interactions with other environmental factors.     

Development of risk-based air quality management strategies under impacts of climate change

Climate change is forecast to adversely affect air quality through perturbations in meteorological conditions, photochemical reactions, and precursor emissions. To protect the environment and human health from air pollution, there is an increasing recognition of the necessity of developing effective air quality management strategies under the impacts of climate change. This paper presents a framework for developing risk-based air quality management strategies that can help policy makers improve their decision-making processes in response to current and future climate change about 30-50 years from now. Development of air quality management strategies under the impacts of climate change is fundamentally a risk assessment and risk management process involving four steps: (1) assessment of the impacts of climate change and associated uncertainties; (2) determination of air quality targets; (3) selections of potential air quality management options; and (4) identification of preferred air quality management strategies that minimize control costs, maximize benefits, or limit the adverse effects of climate change on air quality when considering the scarcity of resources. The main challenge relates to the level of uncertainties associated with climate change forecasts and advancements in future control measures, since they will significantly affect the risk assessment results and development of effective air quality management plans. The concept presented in this paper can help decision makers make appropriate responses to climate change, since it provides an integrated approach for climate risk assessment and management when developing air quality management strategies. Implications: Development of climate-responsive air quality management strategies is fundamentally a risk assessment and risk management process. The risk assessment process includes quantification of climate change impacts on air quality and associated uncertainties. Risk management for air quality under the impacts of climate change includes determination of air quality targets, selections of potential management options, and identification of effective air quality management strategies through decision-making models. The risk-based decision-making framework can also be applied to develop climate-responsive management strategies for the other environmental dimensions and assess costs and benefits of future environmental management policies.     

A reflection on four impactful Ambio papers: The biotic perspective: This article belongs to Ambio’s 50th Anniversary Collection. Theme: Climate change impacts

Climate change represents one of the most pressing societal and scientific challenges of our time. While much of the current research on climate change focuses on future prediction, some of the strongest signals of warming can already be seen in Arctic and alpine areas, where temperatures are rising faster than the global average, and in the oceans, where the combination of rising temperatures and acidification due to increased CO₂ concentrations has had catastrophic consequences for sensitive marine organisms inhabiting coral reefs. The scientific papers highlighted as part of this anniversary issue represent some of the most impactful advances in our understanding of the consequences of anthropogenic climate change. Here, we reflect on the legacy of these papers from the biotic perspective.     

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.     

Arctic Climate Tipping Points

There is widespread concern that anthropogenic global warming will trigger Arctic climate tipping points. The Arctic has a long history of natural, abrupt climate changes, which together with current observations and model projections, can help us to identify which parts of the Arctic climate system might pass future tipping points. Here the climate tipping points are defined, noting that not all of them involve bifurcations leading to irreversible change. Past abrupt climate changes in the Arctic are briefly reviewed. Then, the current behaviour of a range of Arctic systems is summarised. Looking ahead, a range of potential tipping phenomena are described. This leads to a revised and expanded list of potential Arctic climate tipping elements, whose likelihood is assessed, in terms of how much warming will be required to tip them. Finally, the available responses are considered, especially the prospects for avoiding Arctic climate tipping points.     

Modelling tundra vegetation response to recent arctic warming

The Arctic land area has warmed by > 1 °C in the last 30 years and there is evidence that this has led to increased productivity and stature of tundra vegetation and reduced albedo, effecting a positive (amplifying) feedback to climate warming. We applied an individual-based dynamic vegetation model over the Arctic forced by observed climate and atmospheric CO(2) for 1980-2006. Averaged over the study area, the model simulated increases in primary production and leaf area index, and an increasing representation of shrubs and trees in vegetation. The main underlying mechanism was a warming-driven increase in growing season length, enhancing the production of shrubs and trees to the detriment of shaded ground-level vegetation. The simulated vegetation changes were estimated to correspond to a 1.75 % decline in snow-season albedo. Implications for modelling future climate impacts on Arctic ecosystems and for the incorporation of biogeophysical feedback mechanisms in Arctic system models are discussed.     

Effects of changes in climate on landscape and regional processes, and feedbacks to the climate system

Biological and physical processes in the Arctic system operate at various temporal and spatial scales to impact large-scale feedbacks and interactions with the earth system. There are four main potential feedback mechanisms between the impacts of climate change on the Arctic and the global climate system: albedo, greenhouse gas emissions or uptake by ecosystems, greenhouse gas emissions from methane hydrates, and increased freshwater fluxes that could affect the thermohaline circulation. All these feedbacks are controlled to some extent by changes in ecosystem distribution and character and particularly by large-scale movement of vegetation zones. Indications from a few, full annual measurements of CO2 fluxes are that currently the source areas exceed sink areas in geographical distribution. The little available information on CH4 sources indicates that emissions at the landscape level are of great importance for the total greenhouse balance of the circumpolar North. Energy and water balances of Arctic landscapes are also important feedback mechanisms in a changing climate. Increasing density and spatial expansion of vegetation will cause a lowering of the albedo and more energy to be absorbed on the ground. This effect is likely to exceed the negative feedback of increased C sequestration in greater primary productivity resulting from the displacements of areas of polar desert by tundra, and areas of tundra by forest. The degradation of permafrost has complex consequences for trace gas dynamics. In areas of discontinuous permafrost, warming, will lead to a complete loss of the permafrost. Depending on local hydrological conditions this may in turn lead to a wetting or drying of the environment with subsequent implications for greenhouse gas fluxes. Overall, the complex interactions between processes contributing to feedbacks, variability over time and space in these processes, and insufficient data have generated considerable uncertainties in estimating the net effects of climate change on terrestrial feedbacks to the climate system. This uncertainty applies to magnitude, and even direction of some of the feedbacks.     

Simulating uncertainty in climate-pest models with fuzzy numbers

Inputs in climate-pest models are commonly expressed as point estimates ('crisp' numbers), which implies perfect knowledge of the system in study. In reality, however, all model inputs harbor some level of uncertainty. This is particularly true for climate change impact assessments where the inputs (i.e., climate projections) are highly uncertain. In this study, uncertainties in climate projections were expressed as 'fuzzy' numbers; these are uncertain numbers for which one knows that there is a range of possible values and that some values are 'more possible' than others. A generic pest risk model incorporating the combined effects of temperature, soil moisture, and cold stress was implemented in a fuzzy spreadsheet environment and run with three climate scenarios: (1) present climate (control run); (2) crisp climate change; and (3) fuzzy climate change. Under the crisp climate change scenario, winter and summer temperatures and precipitation were altered using best estimates (averaged predictions from the 1995 assessment report of the Intergovernmental Panel on Climate Change [IPCC]). Under the fuzzy scenario, climate changes were expressed as triangular fuzzy numbers, utilizing the extremes (lowest and highest predictions from the IPCC report) in addition to the best estimates. Under each scenario, environmental favorability was calculated for six locations in two geographical regions (Central North America and Southern Europe) with two hypothetical pest species having temperate or mediterranean climate requirements. Simulations with the crisp climate change scenario suggested only minor changes in overall environmental favorability compared with the control run. When simulations were conducted with the fuzzy climate change scenario, however, important changes in environmental favorability emerged, particularly in Southern Europe. In that region, the possibility of considerably increased winter precipitation led to increased values of environmental favorability. However, the simulations also showed that this result harbored a very broad range of possible outcomes. The results support the notion that uncertainty in climate change projections must be reduced before reliable impact assessments can be achieved.     

Transport impacts on atmosphere and climate: Aviation

Aviation alters the composition of the atmosphere globally and can thus drive climate change and ozone depletion. The last major international assessment of these impacts was made by the Intergovernmental Panel on Climate Change (IPCC) in 1999. Here, a comprehensive updated assessment of aviation is provided. Scientific advances since the 1999 assessment have reduced key uncertainties, sharpening the quantitative evaluation, yet the basic conclusions remain the same. The climate impact of aviation is driven by long-term impacts from CO₂ emissions and shorter-term impacts from non-CO₂ emissions and effects, which include the emissions of water vapour, particles and nitrogen oxides (NO_x). The present-day radiative forcing from aviation (2005) is estimated to be 55 mW m^?2 (excluding cirrus cloud enhancement), which represents some 3.5% (range 1.3–10%, 90% likelihood range) of current anthropogenic forcing, or 78 mW m^?2 including cirrus cloud enhancement, representing 4.9% of current forcing (range 2–14%, 90% likelihood range). According to two SRES-compatible scenarios, future forcings may increase by factors of 3–4 over 2000 levels, in 2050. The effects of aviation emissions of CO₂ on global mean surface temperature last for many hundreds of years (in common with other sources), whilst its non-CO₂ effects on temperature last for decades. Much progress has been made in the last ten years on characterizing emissions, although major uncertainties remain over the nature of particles. Emissions of NO_x result in production of ozone, a climate warming gas, and the reduction of ambient methane (a cooling effect) although the overall balance is warming, based upon current understanding. These NO_x emissions from current subsonic aviation do not appear to deplete stratospheric ozone. Despite the progress made on modelling aviation's impacts on tropospheric chemistry, there remains a significant spread in model results. The knowledge of aviation's impacts on cloudiness has also improved: a limited number of studies have demonstrated an increase in cirrus cloud attributable to aviation although the magnitude varies: however, these trend analyses may be impacted by satellite artefacts. The effect of aviation particles on clouds (with and without contrails) may give rise to either a positive forcing or a negative forcing: the modelling and the underlying processes are highly uncertain, although the overall effect of contrails and enhanced cloudiness is considered to be a positive forcing and could be substantial, compared with other effects. The debate over quantification of aviation impacts has also progressed towards studying potential mitigation and the technological and atmospheric tradeoffs. Current studies are still relatively immature and more work is required to determine optimal technological development paths, which is an aspect that atmospheric science has much to contribute. In terms of alternative fuels, liquid hydrogen represents a possibility and may reduce some of aviation's impacts on climate if the fuel is produced in a carbon-neutral way: such fuel is unlikely to be utilized until a ‘hydrogen economy’ develops. The introduction of biofuels as a means of reducing CO₂ impacts represents a future possibility. However, even over and above land-use concerns and greenhouse gas budget issues, aviation fuels require strict adherence to safety standards and thus require extra processing compared with biofuels destined for other sectors, where the uptake of such fuel may be more beneficial in the first instance.     

Modelling Tundra Vegetation Response to Recent Arctic Warming

The Arctic land area has warmed by >1 °C in the last 30 years and there is evidence that this has led to increased productivity and stature of tundra vegetation and reduced albedo, effecting a positive (amplifying) feedback to climate warming. We applied an individual-based dynamic vegetation model over the Arctic forced by observed climate and atmospheric CO₂ for 1980–2006. Averaged over the study area, the model simulated increases in primary production and leaf area index, and an increasing representation of shrubs and trees in vegetation. The main underlying mechanism was a warming-driven increase in growing season length, enhancing the production of shrubs and trees to the detriment of shaded ground-level vegetation. The simulated vegetation changes were estimated to correspond to a 1.75 % decline in snow-season albedo. Implications for modelling future climate impacts on Arctic ecosystems and for the incorporation of biogeophysical feedback mechanisms in Arctic system models are discussed.     

What determines the current presence or absence of permafrost in the Torneträsk region, a sub-arctic landscape in northern Sweden?

In a warming climate, permafrost is likely to be significantly reduced and eventually disappear from the sub-Arctic region. This will affect people at a range of scales, from locally by slumping of buildings and roads, to globally as melting of permafrost will most likely increase the emissions of the powerful greenhouse gas methane, which will further enhance global warming. In order to predict future changes in permafrost, it is crucial to understand what determines the presence or absence of permafrost under current climate conditions, to assess where permafrost is particularly vulnerable to climate change, and to identify where changes are already occurring. The Tornetr?sk region of northern sub-Arctic Sweden is one area where changes in permafrost have been recorded and where permafrost could be particularly vulnerable to any future climate changes. This paper therefore reviews the various physical, biological, and anthropogenic parameters that determine the presence or absence of permafrost in the Tornetr?sk region under current climate conditions, so that we can gain an understanding of its current vulnerability and potential future responses to climate change. A patchy permafrost distribution as found in the Tornetr?sk region is not random, but a consequence of site-specific factors that control the microclimate and hence the surface and subsurface temperature. It is also a product of past as well as current processes. In sub-Arctic areas such as northern Sweden, it is mainly the physical parameters, e.g., topography, soil type, and climate (in particular snow depth), that determine permafrost distribution. Even though humans have been present in the study area for centuries, their impacts on permafrost distribution can more or less be neglected at the catchment level. Because ongoing climate warming is projected to continue and lead to an increased snow cover, the permafrost in the region will most likely disappear within decades, at least at lower elevations.     

An approach for treating the uncertainties in the impact of climate change

Past accumulated data supported by the predictions of climate models suggest that our world is getting warmer. Scientists are trying to construct mathematical models of both climate and crop systems to identify what types of climate changes could constitute a significant risk or benefit for agriculture. However, due to the many uncertainties regarding these models, it is impossible to make unequivocal predictions. At present, almost all the research in this area is carried out without considering the uncertain nature of the problem. The approach outlined here attempts to find a way to deal with the above uncertainty problem. Artificial intelligence techniques are being developed with the aim of performing inferences based on uncertain information. In our method, causal graphs are used for explicit representation of the relationships between climatic factors and yield. Probabilities are used to express the uncertainties associated with these links, and Bayes' theorem is applied to deal with uncertainty reasonings. This approach has the additional advantage of allowing the prediction to be readily updated as results from improved climate and crop models become available. These opportunities are being evaluated initially by using the model for potato growth developed at the Scottish Crop Research Institute.     

Synthesis of effects in four Arctic subregions

An assessment of impacts on Arctic terrestrial ecosystems has emphasized geographical variability in responses of species and ecosystems to environmental change. This variability is usually associated with north-south gradients in climate, biodiversity, vegetation zones, and ecosystem structure and function. It is clear, however, that significant east-west variability in environment, ecosystem structure and function, environmental history, and recent climate variability is also important. Some areas have cooled while others have become warmer. Also, east-west differences between geographical barriers of oceans, archipelagos and mountains have contributed significantly in the past to the ability of species and vegetation zones to relocate in response to climate changes, and they have created the isolation necessary for genetic differentiation of populations and biodiversity hot-spots to occur. These barriers will also affect the ability of species to relocate during projected future warming. To include this east-west variability and also to strike a balance between overgeneralization and overspecialization, the ACIA identified four major sub regions based on large-scale differences in weather and climate-shaping factors. Drawing on information, mostly model output that can be related to the four ACIA subregions, it is evident that geographical barriers to species re-location, particularly the distribution of landmasses and separation by seas, will affect the northwards shift in vegetation zones. The geographical constraints--or facilitation--of northward movement of vegetation zones will affect the future storage and release of carbon, and the exchange of energy and water between biosphere and atmosphere. In addition, differences in the ability of vegetation zones to re-locate will affect the biodiversity associated with each zone while the number of species threatened by climate change varies greatly between subregions with a significant hot-spot in Beringia. Overall, the subregional synthesis demonstrates the difficulty of generalizing projections of responses of ecosystem structure and function, species loss, and biospheric feedbacks to the climate system for the whole Arctic region and implies a need for a far greater understanding of the spatial variability in the responses of terrestrial arctic ecosystems to climate change.