Arctic ice retreating more quickly than computer models project
Arctic sea ice is melting at a significantly faster rate than projected by even the most advanced computer models, a new study concludes. The research, by scientists at the National Center for Atmospheric Research (NCAR) and the University of Colorado's National Snow and Ice Data Center (NSIDC), shows that the Arctic's ice cover is retreating more rapidly than estimated by any of the 18 computer models used by the Intergovernmental Panel on Climate Change (IPCC) in preparing its 2007 assessments.
The study, "Arctic Sea Ice Decline: Faster Than Forecast?" [*abstract] appeared today in the online edition of Geophysical Research Letters. It was led by Julienne Stroeve of the NSIDC and funded by the National Science Foundation, which is NCAR's principal sponsor, and by NASA.
"This suggests that current model projections may in fact provide a conservative estimate of future Arctic change, and that the summer Arctic sea ice may disappear considerably earlier than IPCC projections," says Stroeve.
Thirty years ahead of schedule
The study indicates that, because of the disparity between the computer models and actual observations, the shrinking of summertime ice is about 30 years ahead of the climate model projections. As a result, the Arctic could be seasonally free of sea ice earlier than the IPCC- projected timeframe of any time from 2050 to well beyond 2100.
The authors speculate that the computer models may fail to capture the full impact of increased carbon dioxide and other greenhouse gases in the atmosphere. Whereas the models indicate that about half of the ice loss from 1979 to 2006 was due to increased greenhouse gases, and the other half due to natural variations in the climate system, the new study indicates that greenhouse gases may be playing a significantly greater role:
bioenergy :: biofuels :: energy :: sustainability :: fossil fuels :: climate change :: greenhouse gases :: sea ice :: Arctic ::
There are a number of factors that may lead to the low rates of simulated sea ice loss. Several models overestimate the thickness of the present-day sea ice and the models may also fail to fully capture changes in atmospheric and oceanic circulation that transport heat to polar regions.
March ice
Although the loss of ice for March is far less dramatic than the September loss, the models underestimate it by a wide margin as well. The study concludes that the actual rate of sea ice loss in March, which averaged about 1.8 percent per decade in the 1953 -2006 period, was three times larger than the mean from the computer models. March is typically the month when Arctic sea ice is at its most extensive.
The Arctic is especially sensitive to climate change partly because regions of sea ice, which reflect sunlight back into space and provide a cooling impact, are disappearing. In contrast, darker areas of open water, which are expanding, absorb sunlight and increase temperatures. This feedback loop has played a role in the increasingly rapid loss of ice in recent years, which accelerated to 9.1 percent per decade from 1979 to 2006 according to satellite observations.
Walt Meier, Ted Scambos, and Mark Serreze, all at NSIDC, also co-authored the study.
Image: the graph illustrates the extent to which Arctic sea ice is melting faster than projected by computer models. The dotted line represents the average rate of melting indicated by computer models, with the blue area indicating the spread among the different models (shown as plus/minus one standard deviation). The red line shows the actual rate of Arctic ice loss based on observations. The observations have been particularly accurate since 1979 because of new satellite technology. (Illustration by Steve Deyo, ©UCAR, based on research by NSIDC and NCAR.
More information:
National Center for Atmospheric Research: Arctic Ice Retreating More Quickly Than Computer Models Project - April 30, 2007.
Article continues
The study, "Arctic Sea Ice Decline: Faster Than Forecast?" [*abstract] appeared today in the online edition of Geophysical Research Letters. It was led by Julienne Stroeve of the NSIDC and funded by the National Science Foundation, which is NCAR's principal sponsor, and by NASA.
"While the ice is disappearing faster than the computer models indicate, both observations and the models point in the same direction: the Arctic is losing ice at an increasingly rapid pace and the impact of greenhouse gases is growing." - Marika Holland, NCAR scientist.The authors compared model simulations of past climate with observations by satellites and other instruments. They found that, on average, the models simulated a loss in September ice cover of 2.5 percent per decade from 1953 to 2006. The fastest rate of September retreat in any individual model was 5.4 percent per decade. (September marks the yearly minimum of sea ice in the Arctic.) But newly available data sets, blending early aircraft and ship reports with more recent satellite measurements that are considered more reliable than the earlier records, show that the September ice actually declined at a rate of about 7.8 percent per decade during the 1953-2006 period.
"This suggests that current model projections may in fact provide a conservative estimate of future Arctic change, and that the summer Arctic sea ice may disappear considerably earlier than IPCC projections," says Stroeve.
Thirty years ahead of schedule
The study indicates that, because of the disparity between the computer models and actual observations, the shrinking of summertime ice is about 30 years ahead of the climate model projections. As a result, the Arctic could be seasonally free of sea ice earlier than the IPCC- projected timeframe of any time from 2050 to well beyond 2100.
The authors speculate that the computer models may fail to capture the full impact of increased carbon dioxide and other greenhouse gases in the atmosphere. Whereas the models indicate that about half of the ice loss from 1979 to 2006 was due to increased greenhouse gases, and the other half due to natural variations in the climate system, the new study indicates that greenhouse gases may be playing a significantly greater role:
bioenergy :: biofuels :: energy :: sustainability :: fossil fuels :: climate change :: greenhouse gases :: sea ice :: Arctic ::
There are a number of factors that may lead to the low rates of simulated sea ice loss. Several models overestimate the thickness of the present-day sea ice and the models may also fail to fully capture changes in atmospheric and oceanic circulation that transport heat to polar regions.
March ice
Although the loss of ice for March is far less dramatic than the September loss, the models underestimate it by a wide margin as well. The study concludes that the actual rate of sea ice loss in March, which averaged about 1.8 percent per decade in the 1953 -2006 period, was three times larger than the mean from the computer models. March is typically the month when Arctic sea ice is at its most extensive.
The Arctic is especially sensitive to climate change partly because regions of sea ice, which reflect sunlight back into space and provide a cooling impact, are disappearing. In contrast, darker areas of open water, which are expanding, absorb sunlight and increase temperatures. This feedback loop has played a role in the increasingly rapid loss of ice in recent years, which accelerated to 9.1 percent per decade from 1979 to 2006 according to satellite observations.
Walt Meier, Ted Scambos, and Mark Serreze, all at NSIDC, also co-authored the study.
Image: the graph illustrates the extent to which Arctic sea ice is melting faster than projected by computer models. The dotted line represents the average rate of melting indicated by computer models, with the blue area indicating the spread among the different models (shown as plus/minus one standard deviation). The red line shows the actual rate of Arctic ice loss based on observations. The observations have been particularly accurate since 1979 because of new satellite technology. (Illustration by Steve Deyo, ©UCAR, based on research by NSIDC and NCAR.
More information:
National Center for Atmospheric Research: Arctic Ice Retreating More Quickly Than Computer Models Project - April 30, 2007.
Article continues
Tuesday, May 01, 2007
"Regenerative" farming: recycling and biofuels to reduce environmental impacts
A switch to regenerative agriculture would involve a variety of changes, including reduced use of inorganic fertilizers and more on-farm energy generation from wind and fermentation of biomass into liquid and gaseous biofuels. It would also reduce overcropping and leakage from manure storage that contaminates groundwater. Yet despite similarities, Pearson's concept of regenerative agriculture is distinct from organic farming; for example, regenerative agriculture does rely on chemically treated fertilizer and would exploit robotic systems.
The approach would entail more use of human labor, which is costly, and may reduce output per unit area farmed. But Pearson summarizes studies of organic farming suggesting that price premiums could overcome this disadvantage, and points out that social benefits could be expected. He argues that existing funding programs for farmers could be modified to encourage more regenerative agriculture, and suggests that philanthropists and professional bodies could stimulate its uptake.
Obviously, in a first phase such a model should be strictly limited to the affluent world, where consumers are prepared to and are capable of paying premiums for agricultural products. Without these premiums and philantrophic funding, the model is not viable. What is more, extending such a system to the developing world, where achieving the classic goals of agriculture - increased yields and productivity - are the obvious priority, would be a total disaster for millions of people. Moreover, given that many poor countries are dependent on food imports from the North (because of agricultural subsidies there), a generalisation of the system resulting in higher prices, would be a recipee for global hunger - unless subsidy and trade regimes were to be altered drastically, which is highly unlikely.
Pearson's exploration of a new form of farming is interesting and some elements of it are not incompatible with conventional agriculture (such as using residues for the production of biofuels), but it should be placed in the broader context of development and the global food system and its injustices. Whereas public health considerations, philosophical reflections, ultra-long term 'sustainability', and consumer perceptions may make the case for organic (or something akin to "regenerative") farming in the affluent West, in the developing world the case for conventional agriculture remains extremely strong. Millions in the South need food first, risky 'green' experiments and ideologies may follow, but later.
In his open access article, Pearson sums up eight main reasons for a push towards "regenerative" farming:
biofuels :: energy :: sustainability :: agriculture :: organic :: recycling :: biogas :: bioenergy :: subsidies :: developing world ::
The author warns, however, that several of his arguments may seem contradictory. Indeed, some of them would result in increased food shortages for millions of people in the developing world, if they were to be implemented on a large scale and without creating a framework that should accompany the transition to such a system [some observations by Biopact between brackets]:
Regenerative versus organic systems
With these basic (but seriously inconsistent) starting points in mind, Pearson stresses some major differences between his "regenerative" model and that of ordinary "organic" farming.
Semiclosed systems, here described as “regenerative,” are those designed to minimize external inputs or external impacts of agronomy outside the farm. For example, the extent to which a system can be called regenerative depends on how much the system minimizes its import of fertilizers and pesticides in excess of what will be removed within the grain or other products (e.g., corn stalks, or stover, to be processed into wallboard or car parts) and eliminates unused by-products. The term “regenerative” is proposed because “semiclosed” is cumbersome and unlikely to attract public support (see point 8, above).By contrast, relatively open systems — which, driven by historical reasons or by comparative comparative prices, constitute mainstream agriculture—have progressively reduced labor and recycling on the farm and increased off-farm inputs (and possibly outputs) such as fertilizers, fuel, and pesticides.
Organic systems are those that are certified under a regional or nationally registered scheme. They are examples of semiclosed systems. However, although the concept of a cyclical or regenerative system is the foundation of organic agriculture and is recognized by certification bodies, only the Australian National Standard explicitly mentions closed systems: “A developed organic or biodynamic farm must operate within a closed input system to the maximum extent possible.” Regenerative systems encompass a range of locally adapted “packages” aimed at minimizing inputs, leakiness, and chain distances. They include organically certified agriculture.
However, the generic system (regenerative) is not synonymous with the specific example (organic); there are aspects of organic certification that are irrelevant or unhelpful to maintaining a regenerative ystem (e.g., no chemically treated fertilizer is allowed under any of the organic standards). By contrast, regenerative systems with minimized inputs and nonuseful outputs create opportunities for high-technology initiatives such as information technology and robotics.
Nonetheless, Pearson's overview often cites studies on organic agriculture, as they provide relatively well-defined and independently researched examples of semiclosed or regenerative systems.
Inputs and outputs of various agronomic systems
All agronomic systems are to some extent open; organic systems, which are a relatively low-technology example of regenerative systems, depend on lower levels of externally sourced inputs, some of which come from nonrenewable sources and all of which incur processing and transport energy and cost. Although not currently required, it would be helpful if all certified variants of regenerative systems (e.g., organic, perhaps some LEAF [Linking Environment and Farming]–certified systems) documented or even set limits to the amount or percentage of inputs that are sourced off the farm; this would proactively address contemporary urban concerns such as energy costs and environmental degradation associated with agriculture.
Off-farm inputs are less for regenerative than for open systems, but are seldom zero: Nutrient budget deficits in phosphorus and potassium, and sometimes sulfur, are often identified in organic systems. Soil organic matter routinely increases as systems become more closed. As some recent research indicates, soil quality and health are related to organic matter, with some interesting and perhaps ecologically significant complexities.
For example, Popp and colleagues created a soil quality index involving soil water, organic matter, bulk density, and pH; all of these parameters are affected by organic matter. Further, they showed that the relationship between soil quality and crop production varied with the soil system: On poorer-quality soils, inorganic fertilizer and tillage were used to compensate for soil quality, but as the inherent soil quality became more degraded, inorganic inputs became less and less effective.
The higher level of soil organic matter in semiclosed systems, compared with open systems, creates greater sinks for both carbon (addressing greenhouse warming) and water (addressing the approaching global water shortage). This also creates a soil microbial flora that is more abundant and more diverse.While this is philosophically attractive, given ecologists’quest to maintain biodiversity, Welbaum and colleagues cautiously conclude that it is not clear whether microbial species diversity is critical to soil health or “merely evidence of built-in redundance.”Higher levels of soil organic matter and water in organic systems also produce more earthworms and microarthropods.
With modern molecular biology, it is now opportune to further study soil organisms and their function and management.
Efficiency and costs of regenerative system - only viable with heavy premiums
The energetic efficiency of conventional farming systems compared with more closed systems has been studied through both model farm analyses and modeling. Loake (2001) reviews the energy inputs and outputs, and efficiency, of agronomic systems. Table 1 (Loake 2001, collated from Leach 1976, click to enlarge) illustrates how different the mechanical energetics are for conventional and organic systems.
Loake goes on to estimate daily, seasonal, and annual human energy inputs in organic and conventional farming, concluding that although the regenerative (organic) system is more efficient overall, it relies more on human energy and might thereby create stress. Dalgaard and colleagues, Flessa and colleagues, and others have established, at least over short-term studies or audits, that lower energy use and greater energetic efficiency are commonplace in regenerative (e.g., organic) farming systems, at least where there are no anomalies of infrastructure (for example, the need to use more energy to transport organically certified beets to a processing plant, as there was only one available in the country).
A recent study based on data collected in Pennsylvania for 21 years showed that organic corn farming, although requiring more human labor than did conventional systems, used 30% less energy because it needed less machinery, fertilizer, seeds, herbicides, and transport to the field, albeit using more human labor (Table 1).
Regenerative systems generally require higher on-farm labor than open systems, as evidenced by a survey of 1144 farms in the United Kingdom and Ireland. While this is seen in conventional economics as a disincentive to shift to regenerative systems, the reverse might be argued: Higher labor density (so long as it is economical) maintains or increases social capital and community livelihoods.
Furthermore, the higher labor inputs that characterize organically certified production need not be carried into all forms of regenerative agronomy: The application of fertilizers and pesticides through “precision agriculture,” already employed in large-scale leaky systems, could be deployed to minimize or eliminate waste in semiclosed systems, and the economies of scale and substitution of technology for labor evident in industrial agriculture are equally applicable to regenerative systems.
In the Pennsylvania comparison, corn and soybean yields after a five-year transition were similar in both the conventional and organic systems, and higher in the organic system in drought years. Elsewhere, crop yields in semiclosed systems are reported to be similar to or lower than those of conventional systems. Where weeds are a problem, lower yields, by as much as 38%, occur in semiclosed systems in Europe, in New Zealand, and elsewhere in North America.
In the United Kingdom, Prince Charles’s organically certified farm Highgrove reported wheat yields 50% lower than in neighboring conventional farms. The economic returns for organic systems—a measure of efficiency or productivity that takes account of market worth and not, for example, the costs of externalities — are generally similar to or higher than those for conventional systems. Samples of these are shown in Table 2 (click to enlarge), but the table cannot adequately address the profitability of regenerative systems, for two reasons. First, costs based on organically certified farming are not necessarily applicable to regenerative systems in general.
As explained above, to date scientific comparisons of regenerative systems with conventional systems have been limited to organically certified regenerative systems,with their peculiar constraints that create higher labor costs, partly to avoid synthetic chemicals. From a narrow (on-farm) economic perspective, the financial viability of nonorganic regenerative systems is likely to be greater than that of documented organic systems. This is best demonstrated indirectly: The increasing shift to semiclosed (mostly organic) systems, at a rate of perhaps 10% per year, implies profitability, and price premiums (e.g., for organic fruit and vegetables) are maintained despite this expansion.
The specific case studies in table 2 generally show lower costs of inputs, except for labor (which could be interpreted as a consequence of organic certification, not of semiclosed systems per se). The lower yields common in regenerative systems are sometimes, but not always, offset by these lower costs; they are more than offset by the price premiums that remain common for the outputs. For example, Pimentel and colleagues found net returns for an organic system (based on lower costs for fertilizer and machinery, zero cost for pesticides, and higher labor) similar to those for a conventional system. Although the returns from the organic farm were lower than those from the conventional farm if the labor costs of the farm family operator were fully priced, the organic farm’s profitability was still greater, assuming a premium of 10% or more on the organic produce.
Second, on-farm or whole-farm economic analyses such as those summarized in table 2 do not address the externalities associated with agronomic systems: for example, the costs of manufacturing fertilizer (in money and energy terms) and transporting it to the farm, and the costs of by-products such as excessive fertilizer or pesticides entering the groundwater. Naturally, given that these are difficult to estimate and are subject to many assumptions, to date they have been estimated only at regional or national scales.
Thus, although Table 2 may be instructive, it does not obviate the need to assess the profitability of regenerative systems through an approach that considers costs from start to finish— a whole-of-life-cycle analysis—including off-farm societal as well as on-farm individual costs. This will also identify the leaks in current systems that it would be most advantageous to close.
Considering national energy use, Dalgaard and colleagues estimated how much energy was used in Denmark for current conventional cropping and how much might be used if the country converted to organic farming. For all crops, despite lower yields, the national energy use per unit of crop production was lower, by between 30% and 60% depending on the crop, in the regenerative system. Furthermore, Pretty and colleagues estimated that, because leakage from farmland would be minimal, the negative external cost of agriculture for the United Kingdom would diminish by £1129.5 million, or 75%, if the nation converted completely to organic systems.
Redesigning agronomic systems
There are two approaches to changing agronomic systems: (1) farmer-driven incrementalism and (2) a step change in thinking among farmers, scientists, urban taxpayers and voters, and policymakers. The future design and implementation of agronomic systems does not have to progress linearly from enhancement of conventional technology and thence to open systems with greater use of off-farm inputs.
In an approach that counters the trend toward incremental additions of technology to already open systems, mainstream organizations such as the Agricultural Institute of Canada are promoting agronomic best practices that will make systems more closed. These management changes are relatively simple and can be implemented in the short term, although often they will entail some financial cost. In addition, groups of farmers around the world (e.g., in Denmark, Iowa, Australia) have worked together to eliminate or substantially reduce the negative environmental impacts of their farms.
Pearson believes that moving to regenerative agronomic systems will be the biggest contribution that can be made to the “greening of agriculture”. By contrast,Trewavas has concluded that “when problems with agriculture emerge they usually hinge around poor management not mode of agriculture.” Pearson's view takes account of the negative externalities associated with conventional agriculture, while Trewavas’s conclusion seems based on maximizing the productivity of the internal agronomic systems. In this context of productivity, advocates of increasingly open systems, and critics of semiclosed systems, suggest dire consequences from reducing production per unit of area.
Would this cause more land to be cleared and converted to agriculture to maintain gross food production, or an increasing shortage of food in less affluent countries? Neither is likely. Surplus food production in affluent countries is a problem that distorts world trade and food prices in the less affluent countries, and rising land prices for alternative uses will make it increasingly unattractive to convert land to agriculture. With respect to agricultural production in less developed countries, it has been argued for 10 years that conventional agronomy is depleting soil nutrients and structure, and requirements for expensive inorganic fertilizers and pesticides make agriculture less profitable than it might be if farmers practiced regenerative agronomy. [Biopact note: this is highly disputed in the scientific community - see the African Fertilizer Summit's conclusions.]
Philantrophy to fund the model
Advocacy of, and research into, regenerative systems will require a shift in mind-set. Urban-based voters in the United States are already accustomed to funding programs for farming and farmers, either through taxation or through environmental cooperatives. The next, essential step is to accept the opportunity to create government programs and private philanthropy that leverage change in agronomic systems.
Philanthropy will achieve this directly and through influencing research and government policy. Regenerative agronomy will, of course, require compromises to balance food production and ecosystem services. Economic valuation of ecosystem services may or may not be necessary to obtain the engagement of policymakers.Two aspects of the valuation issue seem relevant here. First, ecosystem services (e.g., provision of, clean water) have two types of value, relating to efficiency (during linear operations) and to safeguarding the system, and its outputs, from catastrophic or nonlinear change. Faber and colleagues describe how trees help avert floods, provide visual appeal, and create preconditions for catastrophic fires to illustrate how they can be valued simultaneously for efficiency and for system maintenance.
In the context of this overview, a regenerative agronomic system might be valued for its, say, long-term creation of grain (through normal market economics) and of soil organic matter (measuring efficiency through carbon credit trading). What value for ecosystem services will ensure that an agronomic system is maintained rather than overcropped, which leads to degraded soil structure and desertification or salinization, as millions of hectares of Australian cropland testify?
To date, estimates of the value of ecological services such as water have worked within the linear system, not considering valuation against catastrophic change. A second issue regarding valuation is whether it is necessary to create a single value that bundles market economics, ecosystem services, and system maintenance. Creating a single value helps attract the attention of politicians, and economists generally argue that the valuation of ecosystems, and choosing among different options for their management, requires enumeration. By contrast, Gatto and De Leo argue that creating a single monetary pricing approach is dangerous, concealing the complexities of decisionmaking. Nonmarket valuation is a point of conflict “both within and outside the profession [of environmental economics]”.
Given the momentum in land-use planning toward participatory decisionmaking, in which trade-offs are achieved mostly through discussion rather than through numerical techniques, it is appropriate to ask whether a thrust in environmental economics toward creating single value systems for market products and environmental services is necessary.
Pearson's paper further investigates the need to design agronomic systems for urban–agronomic mosaics, but this aspect is mainly relevant for heavily industrialised and urbanised societies (in North America and Europe). Technical reflections on different strategies to design new agronomic systems are presented as well.
More information:
Pearson, C. J. "Regenerative, Semiclosed Systems: A Priority for Twenty-First-Century Agriculture", [*.pdf/open access] BioScience, May 2007 / Vol. 57 No. 5, pp. 409-418.
Eurekalert: More recycling on the farm could reduce environmental problems - May 1, 2007.
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posted by Biopact team at 7:47 PM 1 comments links to this post