Uncertainties in the understanding of ecological processes and changes driven by climate and UV-B radiation
This is Section 7.7 of the Arctic Climate Impact Assessment
Lead Author: Terry V. Callaghan; Contributing Authors: Lars Olof Björn, F. Stuart Chapin III,Yuri Chernov,Torben R. Christensen, Brian Huntley, Rolf Ims, Margareta Johansson, Dyanna Jolly Riedlinger, Sven Jonasson, Nadya Matveyeva,Walter Oechel, Nicolai Panikov, Gus Shaver; Consulting Authors: Josef Elster, Heikki Henttonen, Ingibjörg S. Jónsdóttir, Kari Laine, Sibyll Schaphoff, Stephen Sitch, Erja Taulavuori, Kari Taulavuori, Christoph Zöckler
Uncertainties (7.7.1)
Current understanding of ecological processes and changes driven by climate and UV-B radiation is strong in some geographic areas and in some disciplines, but is weak in others. Although the ability to make projections has recently increased dramatically with increased research effort in the Arctic and the introduction of new technologies, current understanding is constrained by various uncertainties. This section focuses on these uncertainties and recommends ways in which they can be reduced.
Uncertainties due to methodologies and conceptual frameworks (7.7.1.1)
Methods of projecting impacts on species and ecosystems
Each method has advantages and strengths and has led to the important and extensive current knowledge base. However, each method also has uncertainties that need to be identified so that methods can be refined and uncertainties quantified.
The use of paleo analogues to infer future changes underrepresents the differences between past changes and those likely to occur in the future due to differences in the starting state of the environment and biota, and the different nature of past and likely future changes. Major differences include anthropogenic effects (e.g., extent of land-use change, current and future stratospheric ozone depletion, and trans-boundary pollution) that are probably unprecedented.
Using geographic analogues can indicate where communities and species should be in a warmer world, but they do not indicate at what rate species can relocate or if new barriers to dispersal such as fragmented habitats will prevent potential distributions from being achieved.
Observations and monitoring provide essential data about changes as they occur, and can be used to test hypotheses and model projections, but they have little predictive power in a time of changing climate during which many biotic responses are nonlinear.
Experiments that simulate future environmental conditions (e.g., CO2 concentrations, UV-B radiation levels, temperature, precipitation, snow depth and duration, etc.) all have artifacts, despite attempts to minimize them. It is difficult in field experiments to include simulations of all likely eventualities: in warming experiments, it is very difficult to identify separate effects of seasonal warming and extreme events because most experiments are small in spatial extent, and are short-term in the context of the life cycles of arctic plants and animals. It is also difficult to identify the complex interactions among all the co-occurring environmental change variables, and ecological processes determined from experiments in one geographic area may not relate sufficiently to other areas because of different ecological conditions and histories.
Indigenous knowledge, although a valuable contributor to current understanding of ecological changes (See Recommendations for future approaches to research and monitoring, below), is more qualitative than quantitative, and often characterized by relatively coarse measures (i.e., monthly and seasonal change rather than daily or weekly). The information available is sometimes limited to phenomena that fall within the cycle of subsistence resource use, and is more likely to be diachronic (long time series of local information) and not synchronic (simultaneously observed). It is often difficult to assign particular environmental changes to individual changes in biota, to determine mechanisms of change, and distinguish climate-related change from other changes occurring in the environment. Indigenous knowledge is variable between and within communities, and interpretation and verification processes are as important as collection and documentation. It is a knowledge system.
Uncertainties can be reduced when information from several methods converges. This chapter accepts all methodologies, knowing their limitations, and qualifies the information presented by the methodologies used to obtain it.
Measuring primary production and controlling factors
Key unknowns about primary productivity in the Arctic include root production and turnover and belowground allocation processes in general, including allocation to mycorrhizae and exudation. Also poorly understood are long-term (multi-year to multi-decade) interactions between the carbon cycle and nutrient cycles, in which relatively slow changes in soil processes and nutrient availability interact with relatively rapid changes in photosynthesis in response to climate change. One major unknown is the control on dispersal, establishment, and rate of change in abundance of species and functional types that are more productive than current arctic species but are not now present or common in arctic vegetation (e.g., trees and tall shrubs).
There are two major approaches to assessing Net Ecosystem Production (NEP): classic biomass weighing and year-round CO2 flux recording, but these approaches are not always compatible. One particular gap in current estimates is the lateral transport of organic carbon (C) from one ecosystem to another. The two methodologies give opposite results when accounting for the input of allochthonous (produced outside) organic matter to a particular ecosystem: CO2 flux measurement gives negative NEP due to increased CO2 emission from soil to atmosphere, while weighing gives a higher accumulation of organic carbon (C) in the soil. In addition, current estimates of buried C released to ecosystems due to thermokarst and soil erosion (Figs. 7.21 and 7.22) are poor.
Difficulties in studying microorganisms
Understanding of microbes that are critically important in many ecosystem processes is limited. Knowledge of microbial diversity and function has been strongly constrained by lack of development in methodology and conceptual frameworks.
Bacteria and even the more advanced microscopic yeast and fungi cannot be characterized by visual observation alone due to their very simple shapes (rods, spheres, filaments). Typically, microbial strains must be cultivated in pure culture to reveal their various functional features, and an appreciable amount of laboratory work is required to differentiate a microbe from close relatives. Only a small fraction of soil microorganisms are able to grow on artificial laboratory media, and less than 1% of the cells observed with a microscope form colonies on the plate.The main reasons for this “Great Plate Count Anomaly”[1] include the metabolic stress of the “famine-to-feast” transition occurring when cells are brought from soil to artificial, nutrientrich media; inadequacy of cultivation conditions compared with the natural environment; and metabiotic interactions/cooperation in natural communities that are broken after cells have been separated by plating[2]. This technical problem has resulted in an underestimation of diversity in natural habitats.
Fortunately, new cultivation approaches are being developed that are helping to overcome this problem[3]. However, it is not presently possible to make a fair comparison between the numbers of species of animals and plants versus bacteria given that these groups are defined differently[4].
Lack of feasible technologies to measure microbial population dynamics in the field has lead to the use of microbial biomass, which is convenient but a poor predictor of productivity and C and nutrient turnover. More sensitive measurements of microbial activity need to be developed for field application.
Incomplete databases
Length of time series of data: Although many long time series of relevant data (e.g., species performance and phenology) exist, most information relates to short time series. This is a particular problem in the Arctic where complex population dynamics (e.g., cycles) need to be understood over periods long enough to allow trends to be separated from underlying natural dynamics. Observations of trace gas emissions also require annual observations over time periods long enough to encompass significant climate variability. Experiments are usually too brief to capture stable responses to environmental manipulations and to avoid artifacts that are disturbance responses. Long time series of data are also necessary in order to identify extreme events and nonlinear system changes.
Geographic coverage and spatial scaling: The ecosystems and environments in the Arctic are surprisingly variable yet generalizations to the circumpolar Arctic are often made from a few plot-level studies. Sometimes, particular experiments (e.g., CO2 concentration and UV-B radiation manipulations) or observations are restricted to a few square meters of tundra at just one or two sites. Uncertainties due to generalizing and scaling up are thus significant. The International Biological Programme (IBP, 19964-74) and the International Tundra experiment (ITEX) are exceptional examples of how standardized experiments and observations can be implemented throughout the Arctic.
Coverage of species and taxa: Chapin F. and Shaver[5] and others have demonstrated the individualistic responses of species to experimental environmental manipulations, including climate, while Dormann and Woodin[6] have shown the inadequacy of the concept of "plant functional types" in generalizing plant responses to such experiments. An approach has to be developed to measure responses of a relevant range of species to changes in climate, and particularly UV-B radiation levels. Plants studied in the UV-B radiation manipulation experiments were generally at their northernmost distributional limits and well adapted to high UV-B radiation levels characteristic of southern parts of their ranges. Greater responses would be expected from species at their southern distributional limits where increased UV-B radiation would exceed levels in the plants' recent "memory".
Some species and taxonomic groups are particularly difficult to study, or have little socioeconomic value, and so are underrepresented in databases. Examples include mosses, lichens, soil fauna and flora, and microorganisms (see Uncertainties due to methodologies and conceptual frameworks above)
Nomenclature and concepts
The restricted use of appropriate language often generates uncertainties.The nomenclature of vegetation and plant community types allows changes in the distribution of these assemblages of species in a changed climate to be modeled, but constrains understanding of changes in the structure of the assemblages that are likely to occur because assemblages of species do not move en bloc. This problem limits understanding of novel future communities[7] and no-analogue communities of the past, and emphasizes the uncertainties due to the inability of quantitative models to project qualitative changes in systems. Similarly, the concept of “line” to denote the limit of species distributions (e.g., treeline) is inadequate to express the gradient of changes from one zone to another that can occur over tens of kilometers.
The concept of “species” is particularly difficult in the context of microorganisms as discussed previously, and even as applied to flowering plants.The traditional view that there are few rare and endemic arctic plant species is challenged by recent studies of the flora of Wrangel Island and Beringia (Table 7.14) but it is not known to what degree plant taxonomy is problematic (although the Pan Arctic Flora project is addressing this problem). Such problems need to be resolved before the impacts of climate change on biodiversity can be assessed.
Uncertainties due to surprises (7.7.1.2)
Perhaps the only certainty in the assessment of impacts of changes in climate and UV radiation levels on terrestrial ecosystems in this chapter is that there will be surprises. By definition, it is difficult to predict surprises. However, the possibility that climate cooling will occur because of a change in thermohaline circulation is potentially the most dramatic surprise that could occur.
Regional cooling
The potential for a negative feedback arising from an increased freshwater flux to the Greenland, Icelandic, and Norwegian seas and the Arctic Basin, leading to a partial or complete shut down of the thermohaline circulation of the global oceans, remains an area of considerable uncertainty (sections 6.8.4 and 9.2.3.4). Such an event would be likely to lead to marked and rapid regional cooling in at least northwest Europe.This region at present enjoys an anomalously warm climate given its latitude (50º–72º N), enabling agriculture to be practiced and substantial settlements maintained at far higher latitudes than in any other arctic or subarctic region. Such cooling would be likely to qualitatively alter terrestrial ecosystems[8] agriculture, and forestry over very large areas of Fennoscandia and Europe.
Mutations
Mutations are projected to occur as a result of increased levels of UV radiation and also as a result of aerosols and volatile chemical mutagens transported to the cool polar atmosphere from the mid- and low latitudes.The direct mutagenic effect is probably not strong, especially if the protecting shielding effects of soil particles and adaptive mechanisms are taken into account. However, possible microbial mutants could lead to epidemic outbreaks that could have profound and unexpected consequences for the Arctic and elsewhere.
Desertification
Several approaches suggest that climate warming will lead to an increase in the productivity of arctic vegetation and long-term net sequestration of CO2. However, the complex interactions among warming, permafrost dynamics, hydrology, precipitation, and soil type are poorly understood. Desertification is a plausible outcome in some areas where scenarios suggest that permafrost will thaw, drainage will increase, temperatures will increase, and precipitation will not increase substantially. In areas of sandy soil and loess deposition, such as parts of eastern Siberia, there is a particular risk of desertification. In the polar deserts, herb barrens, and heaths of northern Greenland, plant productivity is strongly correlated with precipitation and increased evapotranspiration is likely to lead to a similar process[9]. Locally, the impacts of overgrazing and anthropogenic disturbance can accelerate the process. A clear example of the effect of warming and drying on the C balance of Alaskan tundra is provided in Section 7.5 (Uncertainties in the understanding of ecological processes and changes driven by climate and UV-B radiation), and an example of boreal coniferous forest loss in North America is given in Section 14.7.3.1 (Uncertainties in the understanding of ecological processes and changes driven by climate and UV-B radiation). However, the possible wider geographic scale of this process is unknown.
Changes in current distributions of widespread and rare species
Climate change could possibly have counter-intuitive impacts on species distributions. Currently rare arctic plant species, particularly those that are northern outliers of species with more southerly distributions, could possibly expand during initial phases of climate warming.
In contrast, currently widespread species, particularly lichens and mosses, could possibly become more restricted in their abundance during warming. It is necessary to reassess the concept of “threatened species” in the context of climate and UV radiation change (see Section 7.6 (Uncertainties in the understanding of ecological processes and changes driven by climate and UV-B radiation) and Chapter 11 (Uncertainties in the understanding of ecological processes and changes driven by climate and UV-B radiation)).
During the IBP period (late 1960s and early 1970s), tundra research was characterized by extensive field observations but a general lack of modeling capability. Currently, a technological revolution has stimulated model generation and remote sensing of ecosystem change. However, in some cases, validation is insufficient. Models that project NPP at a global or circumpolar level are insufficiently validated, as recent measurements of NPP are rare and restricted to a few localities. The lack of inter-comparison between models and existing observations leads to potential projection errors: modeled displacement of the tundra by the boreal forest contradicts current observations of the southward retreat of the treeline in some areas and the expansion of “pseudotundra” in parts of Russia due to permafrost degradation, paludification, and human activities.
The climate models used to provide future climate scenarios for the ACIA were forced with the B2 emissions scenario (Section 4.4.1 (Uncertainties in the understanding of ecological processes and changes driven by climate and UV-B radiation)), but projections based on the A2 emissions scenario have been used to a limited extent as a plausible alternative (IPCC, 2001; section 1.4.2[10]).The A2 scenario assumes an emphasis on economic development rather than conservation, while the B2 scenario assumes a greater emphasis on environmental concerns: each has considerable uncertainties ([[Section 4.4.1 (Uncertainties in the understanding of ecological processes and changes driven by climate and UV-B radiation)]2]). In this chapter, projections based mainly on the B2 emissions scenario were used to model changes in vegetation and carbon storage. Projections based on the A2 emissions scenario result in higher temperatures for a particular time period than those based on the B2 emissions scenario.The changes projected by models forced with the A2 emissions scenario for the 2041–2060 and 2071–2090 time slices occur 5 to 10 and 10 to 20 years earlier, respectively, compared with projections based on the B2 scenario. Potential impacts on ecosystems would thus occur faster should emissions follow the A2 scenario.
The major implication for ecosystems of a faster rate of temperature change is an increased mismatch between the rate of habitat change and the rate at which species can relocate to occupy new habitats in appropriate climate envelopes.The overall, generalized, difference between projections based on the B2 and A2 emissions scenarios is likely to be an increased risk of disturbance and disease in species that, under projected conditions based on the A2 scenario, cannot relocate quickly enough. Projections based on the A2 scenario also imply an increased mismatch between initial stimulation of soil respiration and longer-term vegetation feedbacks that would reduce C fluxes to the atmosphere.
Recommendations to reduce uncertainties (7.7.2)
Thematic recommendations and justification (7.7.2.1)
This section reviews important thematic topics that require particular research. For each topic, the state of knowledge and important gaps are summarized, and recommendations to fill these gaps are suggested (in italic font).
Mechanisms of species responses to changes in climate and UV-B radiation levels. Changes in microbe, animal, and plant populations are triggered by trends in climate and UV radiation levels exceeding thresholds, and by extreme events, particularly during winter. However, information is uneven and dominated by trends in summer climate. Appropriate scenarios of extreme events are required, as is deployment of long-term experiments simulating extreme events and future winter processes in particular. A better understanding of thresholds relevant to biological processes is also required.
Biodiversity changes. Some groups of species are very likely to be at risk from climate change impacts, and the biodiversity of particular geographic areas such as Beringia are at particular risk. It is not known if currently threatened species might proliferate under future warming, nor which currently widespread species might decrease in abundance. The nature of threats to species, including microbes, must be reassessed using long-term climate and UV-B radiation change simulation experiments.There is also a need to identify and monitor currently widespread species that are likely to decline under climate change, and to redefine conservation and protection in the context of climate and UV radiation change.
Relocation of species. The dominant response of current arctic species to climate change, as in the past, is very likely to be relocation rather than adaptation. Relocation possibilities are very likely to vary according to region and geographic barriers. Some changes are already occurring. However, knowledge of rates of relocation, impact of geographic barriers, and current changes is poor. There is a need to measure and project rates of species migration by combining paleo-ecological information with observations from indigenous knowledge, environmental and biodiversity monitoring, and experimental manipulations of environment and species.
Vegetation zone redistribution. Forest is very likely to replace a significant proportion of the tundra and is very likely to have a great effect on species composition. However, several processes (including land use and permafrost dynamics) are expected to modify the modeled response of vegetation redistribution related to warming. Models of climate, hydrology (permafrost), ecosystems, and land use need to be developed and linked. These models need to be based on improved information about the current boundaries of major vegetation zones, defined and recorded using standardized protocols.
Carbon sinks and sources in the Arctic. Current models suggest that arctic vegetation and active-layer soils will be a sink for C in the long term because of the northward movement of vegetation zones that are more productive than those they displace. Model output needs to be reconciled with observations that tundra areas that are C sources currently exceed those that are C sinks, although the measurements of circumpolar C balance are very incomplete.To what extent disturbance will reduce the C sink strength of the Arctic is also unknown. There is a need to establish long-term, annual C monitoring throughout the Arctic; to develop models capable of scaling ecosystem processes from plot experiments to landscapes; to develop observatories, experiments, and models to relate disturbance such as desertification to C dynamics; and to improve the geographic balance of observations by increasing high-arctic measurements.There is also a need to combine estimates of ecosystem carbon flux with estimates of C flux from thawing permafrost and methane hydrates.
Ultraviolet-B radiation and CO2 impacts. Enhanced CO2 concentrations and UV-B radiation levels have subtle but long term impacts on ecosystem processes that reduce nutrient cycling and have the potential to decrease productivity. However, these are generalizations from very few plot-scale experiments, and it is difficult to understand impacts that include large herbivores and shrubs. There is a need for long-term experiments on CO2 and UV-B radiation effects interacting with climate in a range of arctic ecosystems; short-term experiments stimulating repeated episodes of high UV radiation exposure; long-term experiments that determine the consequences of high CO2 concentrations and UV-B radiation levels for herbivores; and short-term screening trials to identify the sensitivity of a wide range of species, including soil microbes, to current and projected UV-B radiation levels.
Local and regional feedbacks. Displacement of tundra by forest is very likely to lead to a decrease in albedo with a potential for local warming, whereas C sequestration is likely to increase with potential impacts on global concentrations of greenhouse gases. However, the timing of the processes and the balance between the processes are very uncertain. How local factors such as land use, disturbance, tree type, and possible desertification will affect the balance is also uncertain. There is a need for long-term and annual empirical measurements, analysis of past remotely sensed images, and collection of new images together with the development and application of new models that include land use, disturbance, and permafrost dynamics.
Recommendations for future approaches to research and monitoring (7.7.2.2)
No single research or monitoring approach is adequate, and confidence is increased when results from different approaches converge (section 7.7.1.1). Current approaches should be maintained, and new approaches and even paradigms (e.g., when defining “threatened species” and “protected areas”) developed. Some important approaches are highlighted below.Reducing uncertainty by increasing and extending the use of indigenous knowledge
Arctic indigenous peoples retain strong ties to the land through subsistence economies and they are "active participants" in ecosystems[11]. Unlike a scientist, a hunter is not bound in his observations by a project timeline, budget, seasonality, or logistical constraint[12].
Subsistence activities occur on a daily basis, year after year, and throughout the winter period when many scientists are south in home institutions. Indigenous peoples of the Arctic therefore possess a substantial body of knowledge and expertise related to both biological and environmental phenomena. Such local expertise can highlight qualitative changes in the environment and provide pictures of regional variability across the Arctic that are difficult to capture using coarser-scale models.
This chapter presents some of the first efforts at linking western science and flora knowledge to expand the range of approaches that inform this assessment. However, the potential is far greater, including, for example, local-scale expertise, information on climate history, generation of research hypotheses, community monitoring, and community adaptation[13].
Monitoring
Long-term environmental and biological monitoring have been undervalued but are becoming increasingly necessary to detect change, to validate model projections and results from experiments, and to substantiate measurements made from vegetation. Present monitoring programs and initiatives are too scarce and are scattered randomly. Data from the Arctic on many topics are often not based on organized monitoring schemes, are geographically biased, and are not long-term enough to detect changes in species ranges, natural habitats, animal population cycles, vegetation distribution, and C balance. More networks of standardized, long-term monitoring sites are required to better represent environmental and ecosystem variability in the Arctic and particularly sensitive habitats. Because there are interactions among many co-varying environmental variables, monitoring programs should be integrated. Observatories should have the ability to facilitate campaigns to validate output from models or ground-truth observations from remote sensing. There should be collaboration with indigenous and other local peoples' monitoring networks where relevant. It would be advantageous to create a decentralized and distributed, ideally web-based, meta-database from the monitoring and campaign results, including relevant indigenous knowledge.
Monitoring also requires institutions, not necessarily sited in the Arctic, to process remotely sensed data. Much information from satellite and aerial photographs exists already on vegetation change, such as treeline displacement, and on disturbances such as reindeer/caribou overgrazing and insect outbreaks. However, relatively little of this information has been extracted and analyzed.
Monitoring C fluxes has gained increased significance since the signing of the Kyoto Protocol. Past temporal and spatial scales of measurement used to directly measure C flux have been a poor match for the larger scale of Arctic ecosystem modeling and extrapolation. It remains a challenge to determine if flux measurements and model output are complementary. The technological difficulties in extrapolating many non-linear, complex, interacting factors that comprise fluxes at hundreds to thousands of square kilometers over time, space, and levels of biological and environmental organization in the Arctic have been significant[14]. Research is needed to better understand how the complex system behaves at the meter scale related to larger spatial scales that can be efficiently modeled and evaluated at the regional and circumpolar scale. To do this, extensive long-term and year-round eddy covariance sites and other long-term flux sites, including repeated aircraft flux measurements and remote sensing[14], provide the basis for estimating circumpolar net ecosystem CO2exchanges. Currently, the circumpolar Arctic is disproportionately covered by current and recent measurements, with Canadian and high-arctic regions particularly poorly represented.
Long-term and year-round approach to observations and experiments
Many observations and experiments are short term (<5 years) and they are biased toward the summer period often because researchers have commitments to institutions outside the Arctic during winter. However, throughout this assessment it has become clear that long-term and year-round measurements and experiments are essential to understand the slow and complex responses of arctic organisms and ecosystems to climate change.
Long-term (>10 years) observations and experiments are required in order to enable transient responses to be separated from possible equilibrium responses; increase the chances that disturbances, extreme events, and significant interannual variation in ocean are included in the observations; and allow possible thresholds for responses to be experienced.
Year-round observations are necessary to understand the importance of winter processes in determining the survival of arctic species and the function of arctic ecosystems. Such observations are necessary to recognize the projected amplification of climate warming in winter and to redress the current experimental bias toward summer-only warming. For microbes, it is particularly important to understand changes in winter respiration and nutrient mobilization during freeze–thaw events in spring and late autumn.
It is important to improve the appropriateness of the timing of observations and experiments. For example, current information about the impacts of increased UV-B radiation levels is mainly derived from general summer enhancements or filtration of UV-B radiation, although future increases in UV-B radiation levels are likely to be highest in spring and during specific stratospheric ozone depletion events. The frequency of observations should be fitted to the rate of change of the species or processes of interest, for example, decadal measurements may suffice for some variables such as treeline movement.
Increasing the complexity and scale of environmental and ecosystem manipulation experiments
Single-factor manipulation experiments now have limited applicability because it is clear that there are many interactive effects among co-occurring environmental change variables. There is need for well-designed, large, mutifactorial environmental (e.g., climate, UV-B radiation levels, and CO2 concentrations) and ecosystem (e.g., species removal and addition) manipulation experiments that are long-term and seek to understand annual, seasonal, and event-based impacts of changing environments. The complexity of appropriate treatments and timescales is vast and the spatial scale is also a significant challenge, as it is important to have manipulations that can be related to larger plants (e.g., trees, shrubs) and animals (e.g., reindeer/caribou).
Assessing the impacts of cooling on ecosystems
Scenarios of increased permafrost dominate the approaches to projecting responses of ecosystems to future climate. However, cooling in some areas remains a possibility. As the impacts of cooling on terrestrial ecosystems and their services to people are likely to be far more dramatic than the impacts of warming, it is timely to reassess the probabilities of cooling projected by GCMs and the appropriateness of assessing cooling impacts on ecosystems.
Modeling responses of arctic ecosystems to climate and UV-B radiation change and communicating results at appropriate geographic scales
High-resolution models are needed at the landscape scale for a range of landscape types that are projected to experience different future envelopes of climate and UV-B radiation levels. Modeling at the landscape scale will simulate local changes that relate to plot-scale experiments and can be validated by results of experiments and field observations. Visualization of model results presented at the landscape scale will also enhance the understanding of the changes and their implications by local residents and decision-makers. A particular challenge is to provide scenarios for changes in climate and UV-B radiation levels at the scale of tens of meters.
Funding requirements (7.7.2.3)
It is inappropriate here to comment on levels of funding required to fulfill the recommendations discussed above. However, it is appropriate to highlight two essential aspects of funding.
First, current short-term funding is inappropriate to support research into long-term processes such as ecosystem responses to climate change and UV-B radiation impacts. A stable commitment to long-term funding is necessary.
Second, funding possibilities that are restricted to single nations, or at best a few nations, make it extremely difficult to implement coordinated research that covers the variability in ecosystems and projected climate change throughout the circumpolar north, even though the instruments for coordination exist (e.g., within the International Arctic Sciences Committee, the International Council of Scientific Unions, and the International Geosphere–Biosphere Programme). Limitation of international funding possibilities leads to geographic biases and gaps in important information. Circumpolar funding is required so that coordinated projects can operate at geographically appropriate sites over the same time periods.
Chapter 7: Arctic Tundra and Polar Desert Ecosystems
7.1 Introduction (Uncertainties in the understanding of ecological processes and changes driven by climate and UV-B radiation)
7.2 Late-Quaternary changes in arctic terrestrial ecosystems, climate, and ultraviolet radiation levels
7.3 Species responses to changes in climate and ultraviolet-B radiation in the Arctic
7.3.1 Implications of current species distributions for future biotic change
7.3.2 General characteristics of arctic species and their adaptations in the context of changes in climate and ultraviolet-B radiation levels
7.3.3 Phenotypic responses of arctic species to changes in climate and ultraviolet-B radiation
7.3.4 Genetic responses of arctic species to changes in climate and ultraviolet-B radiation levels
7.3.5 Recent and projected changes in arctic species distributions and potential ranges
7.4 Effects of changes in climate and UV radiation levels on structure and function of arctic ecosystems in the short and long term
7.4.1 Ecosystem structure
7.4.2 Ecosystem function
7.5 Effects of climate change on landscape and regional processes and feedbacks to the climate system
7.6 Synthesis: Scenarios of projected changes in the four ACIA regions for 2020, 2050, and 2080
7.7 Uncertainties and recommendations
References
Citation
Committee, I. (2012). Uncertainties in the understanding of ecological processes and changes driven by climate and UV-B radiation. Retrieved from http://editors.eol.org/eoearth/wiki/Uncertainties_in_the_understanding_of_ecological_processes_and_changes_driven_by_climate_and_UV-B_radiation- ↑ Staley J.T. and A. Konopka, 1985. Measurement of in situ activities of nonphotosynthetic microorganisms in aquatic and terrestrial habitats. Annual Review of Microbiology, 39:321–346.
- ↑ Panikov, N.S., 1995. Microbial Growth Kinetics. Chapman & Hall, 378pp.
- ↑ Staley, J.T. and J.J. Gosink, 1999. Poles apart: biodiversity and biogeography of sea ice bacteria. Annual Review of Microbiology, 53:189–215.
- ↑ Staley, J.T., 1997. Biodiversity: Are microbial species threatened? Current Opinion in Biotechnology, 8:340–345.
- ↑ Chapin, F.S. III and G.R. Shaver, 1985a. Individualistic growth response of tundra plant species to environmental manipulations in the field. Ecology, 66:564–576.
- ↑ Dormann, C.F. and S.J. Woodin, 2002. Climate change in the Arctic: using plant functional types in a meta-analysis of field experiments. Functional Ecology, 16:4–17.
- ↑ Chapin, F.S. III and A.M. Starfield, 1997. Time lags and novel ecosystems in response to transient climatic change in Arctic Alaska. Climatic Change, 35:449–461.
- ↑ Fossa, A.M., 2003. Mountain vegetation in the Faroe Islands in a climate change perspective. Ph.D Thesis, University of Lund, 119pp.
- ↑ Heide-Jørgensen, H.S. and I. Johnsen, 1998. Ecosystem vulnerability to climate change in Greenland and the Faroe Islands. Miljønyt, 33:1–266.
- ↑ IPCC, 2001. Climate Change 2001: The Scientific Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change. J.T. Houghton, Y. Ding, D.J. Griggs, M. Noguer, P.J. van der Linden, X. Dai, K. Maskell and C.A. Johnson (eds.). Cambridge University Press, 881pp.
- ↑ Bielawski, E., 1997. Aboriginal participation in global change research in the Northwest Territories of Canada. In: W.C. Oechel, T. Callaghan,T. Gilmanov, J.I. Holten, B. Maxwell, U. Molau and B. Sveinbjornsson (eds.). Global Change and Arctic Terrestrial Ecosystems, pp. 475–483. Springer-Verlag.
- ↑ Krupnik, I., 2000. Native perspectives on climate and sea-ice changes. In: H.P. Huntington (ed.). Impacts of Changes in Sea Ice and other Environmental Parameters in the Arctic. Final Report of the Marine Mammal Commission Workshop, Girdwood, Alaska, 15–17 February 2000, pp. 35–52. Marine Mammal Commission, Maryland.–Riedlinger, D. and F. Berkes, 2001. Contributions of traditional knowledge to understanding climate change in the Canadian Arctic. Polar Record, 37(203):315–328.
- ↑ Riedlinger, D. and F. Berkes, 2001. Op. cit.
- ↑ 14.0 14.1 Oechel, W.C., G.L. Vourlitis, S.J. Hastings, R.P. Ault Jr. and P. Bryant, 1998. The effects of water table manipulation and elevated temperature on the net CO2 flux of wet sedge tundra ecosystems. Global Change Biology, 4:77–90.–Oechel, W.C., G.L. Vourlitis, S.J. Hastings, R.C. Zulueta, L. Hinzman and D. Kane, 2000b. Acclimation of ecosystem CO2 exchange in the Alaskan Arctic in response to decadal climate warming. Nature, 406:978–981.
- ↑ Oechel, W.C., G.L. Vourlitis, J. Verfaillie Jr., T. Crawford, S. Brooks, E. Dumas, A. Hope, D. Stow, B. Boynton, V. Nosov and R. Zulueta, 2000a. A scaling approach for quantifying the net CO2 flux of the Kuparuk River Basin, Alaska. Global Change Biology, 6(S1):160 173.
