Tag Archives: environment

Model anticipates ecological impacts of human responses to climate (Conservation Biology)

A Princeton University research team has created a readily transferable method for conservation planners trying to anticipate how agriculture will be affected by such adaptations. The tested their model by studying wheat and maize production in South Africa. (Image source: WWS)

A Princeton University research team has created a readily transferable method for conservation planners trying to anticipate how agriculture will be affected by such adaptations. The tested their model by studying wheat and maize production in South Africa. (Image source: WWS)

By B. Rose Huber, Woodrow Wilson School of Public and International Affairs

Throughout history, humans have responded to climate.

Take, for example, the Mayans, who, throughout the eighth and 10th centuries, were forced to move away from their major ceremonial centers after a series of multi-year droughts, bringing about agricultural expansion in Mesoamerica, and a clearing of forests. Much later, in the late 20th century, frequent droughts caused the people of Burkina Faso in West Africa to migrate from the dry north to the wetter south where they have transformed forests to croplands and cut the nation’s area of natural vegetation in half.

Such land transformations, while necessary to ensure future crop productivity, can themselves have large ecological impacts, but few studies have examined their effects. To that end, a Princeton University research team has created a model to evaluate how a human response to climate change may alter the agricultural utility of land. The study, featured in Conservation Biology, provides a readily transferable method for conservation planners trying to anticipate how agriculture will be affected by such adaptations.

“Humans can transform an ecosystem much more rapidly and completely than it can be altered by shifting temperature and precipitation patterns,” said Lyndon Estes, lead author and associate research scholar in the Woodrow Wilson School of International and Public Affairs. “This model provides an initial approach for understanding how agricultural land-use might shift under climate change, and therefore which currently natural areas might be converted to farming.”

Under the direction of faculty members Michael Oppenheimer and David Wilcove, both from the Wilson School’s Program in Science, Technology and Policy, and with the help of visiting student research collaborator Lydie-Line Paroz from ETH Zurich and colleagues from several other institutions, Estes studied South Africa, an area projected to be vulnerable to climate change where wheat and maize are the dominant crops.

Before determining how climate change could impact the crops, the team first needed to determine which areas have been or might be farmed for maize and wheat. They created a land-use model based on an area’s potential crop output and simulated how much of each crop was grown from 1979 to 1999 – the two decades for which historical weather data was available. They also calculated the ruggedness of each area of land, which is related to the cost of farming it. Taking all factors into account, the model provides an estimate of whether the land is likely to be profitable or unprofitable for farming.

To investigate any climate-change impacts, the team then examined the production of wheat and maize under 36 different climate-response scenarios. Many possible future climates were taken into account as well as how the crops might respond to rising levels of carbon dioxide. Based on their land-use model, the researchers calculated how the climate-induced productivity changes alter a land’s agricultural utility. In their analysis, they included only conservation lands – current nature reserves and those that South African conservation officials plan to acquire – that contained land suitable for growing one of the two crops either currently or in the future. However, Estes said the model could be adapted to assess whether land under other types of uses (besides conservation) are likely to be profitable or unprofitable for future farming.

They found that most conservation lands currently have low agricultural utility because of their rugged terrain, which makes them difficult to farm, and that they are likely to stay that way under future climate-change scenarios. The researchers did pinpoint several areas that could become more valuable for farming in the future, putting them at greater risk of conversion. However, some areas were predicted to decrease value for farming, which could make them easier to protect and conserve.

“While studying the direct response of species to climatic shifts is important, it’s only one piece of a complicated puzzle. A big part of that puzzle relates to how humans will react, and history suggests you don’t need much to trigger a change in the way land is used that has a fairly long-lasting impact. ” said Estes. “We hope that conservation planners can use this approach to start thinking about human climate change adaptation and how it will affect areas needing protection.”

Other researchers involved in the study include: Lydie-Line Paroz, Swiss Federal Institute of Technology; Bethany A. Bradley, University of Massachusetts; Jonathan Green, STEP; David G. Hole, Conservation International; Stephen Holness, Centre for African Conservation Ecology; and Guy Ziv, University of Leeds.

The work was funded by the Princeton Environmental Institute‘s Grand Challenges Program.

Read the abstract.

Estes LD, Paroz LL, Bradley BA, Green JM, Hole DG, Holness S, Ziv G, Oppenheimer MG, Wilcove DS. Using Changes in Agricultural Utility to Quantify Future Climate-Induced Risk to Conservation Conservation Biology (2013). First published online Dec. 26, 2013.

How will crops fare under climate change? Depends on how you ask (Global Change Biology)

Research image

Mechanistic (top row) and empirical (bottom row) simulations compared recent, or “baseline,” maize production in South Africa (1979-99) to projected future production under climate change (2046-65). While both models showed a reduction in output, the third column shows that the empirical model estimated a widespread yield loss of around 10 percent (in yellow), while the mechanistic model showed several areas of increased production (in green). (Image by Lyndon Estes)

Research image 2

For wheat, the mechanistic model (top row) projected greater wheat yields, while the empirical model (bottom row) suggested that wheat-growing areas would expand by almost 50 percent. (Image by Lyndon Estes)

By Morgan Kelly, Office of Communications

The damage scientists expect climate change to do to crop yields can differ greatly depending on which type of model was used to make those projections, according to research based at Princeton University. The problem is that the most dire scenarios can loom large in the minds of the public and policymakers, yet neither audience is usually aware of how the model itself influenced the outcome, the researchers said.

The report in the journal Global Change Biology is one of the first to compare the agricultural projections generated by empirical models — which rely largely on field observations — to those by mechanistic models, which draw on an understanding of how crop growth and development are affected by the environment. Building on similar studies from ecology, the researchers found yet more evidence that empirical models may show greater losses as a result of climate change, while mechanistic models may be overly optimistic.

The researchers ran an empirical and a mechanistic model to see how maize and wheat crops in South Africa — the world’s ninth largest maize producer, and sub-Saharan Africa’s second largest source of wheat — would fare under climate change in the years 2046 to 2065. Under the hotter, wetter conditions projected by the climate scenarios they used, the empirical model estimated that maize production could drop by 3.6 percent, while wheat output could increase by 6.2 percent. Meanwhile, the mechanistic model calculated that maize and wheat yields might go up by 6.5 and 15.2 percent, respectively.

In addition, the empirical model estimated that suitable land for growing wheat would drop by 10 percent, while the mechanistic model found that it would expand by 9 percent. The empirical model projected a 48 percent expansion in wheat-growing areas, but the mechanistic reported only 20 percent growth. In regions where the two models overlapped, the empirical model showed declining yields while the mechanistic model showed increases. These wheat models were less accurate, but still indicative of the vastly different estimates empirical and mechanistic can produce, the researchers wrote.

Disparities such as these aren’t just a concern for climate-change researchers, said first author Lyndon Estes, an associate research scholar in the Program in Science, Technology and Environmental Policy in Princeton’s Woodrow Wilson School of Public and International Affairs. Impact projections are crucial as people and governments work to understand and address climate change, but it also is important that people understand how they are generated and the biases inherent in them, Estes said. The researchers cite previous studies that suggest climate change will reduce South African maize and wheat yields by 28 to 30 percent — according to empirical studies. Mechanistic models project a more modest 10 to 19 percent loss. What’s a farmer or government minister to believe?

“A yield projection based only on empirical models is likely to show larger yield losses than one made only with mechanistic models. Neither should be considered more right or wrong, but people should be aware of these differences,” Estes said. “People who are interested in climate-change science should be aware of all the sources of uncertainty inherent in projections, and should be aware that scenarios based on a single model — or single class of models — are not accounting for one of the major sources of uncertainty.”

The researchers’ work relates to a broader effort in recent years to examine the biases introduced into climate estimates by the models and data scientists use, Estes said. For instance, a paper posted Aug. 7 by Global Change Biology — and includes second author and 2011 Princeton graduate Ryan Huynh — challenges predictions that higher global temperatures will result in the widespread extinction of cold-blooded forest creatures, particularly lizards. These researchers say that a finer temperature scale than existing projections use suggests that many cold-blooded species would indeed thrive on a hotter Earth.

Scientists are aware of the differences between empirical and mechanistic models, said Estes, who was prompted by a similar comparison that showed an empirical-mechanistic divergence in tree-growth models. Yet, only one empirical-to-mechanistic comparison (of which Estes also was first author) has been published in relation to agriculture — and it didn’t even examine the impact of climate change.

The solution would be to use both model classes so that researchers could identify each class’s biases and correct for it, Estes said. Each model has different strengths and weaknesses that can be complementary when combined.

Simply put, empirical models are built by finding the relationship between observed crop yields and historical environmental conditions, while mechanistic models are built on the physiological understanding of how the plant grows and reproduces in response to a range of conditions. Empirical models, which are simpler and require fewer inputs, are a staple in studying the possible effects of climate change on ecological systems, where the data and knowledge about most species is largely unavailable. Mechanistic models are more common in studying agriculture because there is a much greater wealth of data and knowledge that has accumulated over several thousand years of agricultural development, Estes said.

“These two model classes characterize different portions of the environmental space, or niche, that crops and other species occupy,” Estes said. “Using them together gives us a better sense of the range of uncertainty in the projections and where the errors and limitations are in the data and models. Because the two model classes have such different structures and assumptions, they also can improve our confidence in scenarios where their findings agree.”

Read the abstract.

Estes, Lyndon D., Hein Beukes, Bethany A. Bradley, Stephanie R. Debats, Michael Oppenheimer, Alex C. Ruane, Roland Schulze and Mark Tadross. 2013. Projected climate impacts to South African maize and wheat production in 2055: A comparison of empirical and mechanistic modeling approaches. Global Change Biology. Accepted, unedited article first published online: July 17, 2013. DOI: 10.1111/gcb.12325

The work was funded by the Princeton Environmental Institute‘s Grand Challenges Program.

Spring may come earlier to North American forests (Geophysical Research Letters)

By Catherine Zandonella, Office of the Dean for Research

Trees in the continental U.S. could send out new spring leaves up to 17 days earlier in the coming century than they did before global temperatures started to rise, according to a new study by Princeton University researchers. These climate-driven changes could lead to changes in the composition of northeastern forests and give a boost to their ability to take up carbon dioxide.

Trees play an important role in taking up carbon dioxide from the atmosphere, so researchers led by David Medvigy, assistant professor in Princeton’s department of geosciences, wanted to evaluate predictions of spring budburst — when deciduous trees push out new growth after months of winter dormancy — from models that predict how carbon emissions will impact global temperatures.

The date of budburst affects how much carbon dioxide is taken up each year, yet most climate models have used overly simplistic schemes for representing spring budburst, modeling for example a single species of tree to represent all the trees in a geographic region.

In 2012, the Princeton team published a new model that relied on warming temperatures and the waning number of cold days to predict spring budburst. The model, which was published in the Journal of Geophysical Research, proved accurate when compared to data on actual budburst in the northeastern United States.

In the current paper published online in Geophysical Research Letters, Medvigy and his colleagues tested the model against a broader set of observations collected by the USA National Phenology Network, a nation-wide tree ecology monitoring network consisting of federal agencies, educational institutions and citizen scientists. The team incorporated the 2012 model into predictions of future budburst based on four possible climate scenarios used in planning exercises by the Intergovernmental Panel on Climate Change.

The researchers included Su-Jong Jeong, a postdoctoral research associate in Geosciences, along with Elena Shevliakova, a senior climate modeler, and Sergey Malyshev, a professional specialist, both in the Department of Ecology and Evolutionary Biology and associated with the U.S. National Oceanic and Atmospheric Administration’s Geophysical Fluid Dynamics Laboratory.

The team estimated that, compared to the late 20th century, red maple budburst will occur 8 to 40 days earlier, depending on the part of the country, by the year 2100. They found that the northern parts of the United States will have more pronounced changes than the southern parts, with the largest changes occurring in Maine, New York, Michigan, and Wisconsin.

The researchers also evaluated how warming temperatures could affect the budburst date of different species of tree. They found that budburst shifted to earlier in the year in both early-budding trees such as common aspen (Populus tremuloides) and late-budding trees such as red maple (Acer rubrum), but that the effect was greater in the late-budding trees and that over time the differences in budding dates narrowed.

The researchers noted that early budburst may give deciduous trees, such as oaks and maples, a competitive advantage over evergreen trees such as pines and hemlocks. With deciduous trees growing for longer periods of the year, they may begin to outstrip growth of evergreens, leading to lasting changes in forest make-up.

The researchers further predicted that warming will trigger a speed-up of the spring “greenwave,” or budburst that moves from south to north across the continent during the spring.

The finding is also interesting from the standpoint of future changes in springtime weather, said Medvigy, because budburst causes an abrupt change in how quickly energy, water and pollutants are exchanged between the land and the atmosphere. Once the leaves come out, energy from the sun is increasingly used to evaporate water from the leaves rather than to heat up the surface. This can lead to changes in daily temperature ranges, surface humidity, streamflow, and even nutrient loss from ecosystems, according to Medvigy.

Read the abstract.

Citation:

Jeong, Su-Jong, David Medvigy, Elena Shevliakova, and Sergey Malyshev. 2013. Predicting changes in temperate forest budburst using continental-scale observations and models. Geophysical Research Letters. Article first published online: Jan. 25, 2013. DOI: 10.1029/2012GL054431

This research was supported by award NA08OAR4320752 from the National Oceanic and Atmospheric Administration, U.S. Department of Commerce.

Truths we must tell ourselves to manage climate change (Vanderbilt Law Review)

Climate change is unwelcome news, and the best and worst outcomes consistent with current science are very different, says Princeton University’s Robert Socolow, professor of mechanical and aerospace engineering, in a new review article published in the Vanderbilt Law Review.  There are novel ways the environmental community, in its role as messenger, could tell the story about climate change using greater empathy and candor.  This essay, which was delivered as a keynote address at a symposium held Feb. 24, 2012 at the Vanderbilt Law School, addresses new ways to freshen the conversation.

The era of consciousness of climate change began in 1958 when Charles David Keeling began the first accurate measurements of carbon dioxide in the atmosphere. The seasonal oscillations were unexpected and the annual average has become a new index (the Keeling Curve) of global human impact.

Fifty-four years later, climate change negotiations in the United States and internationally are in paralysis. The current impasse has little social value and a “restart” button is needed. Such a button will be found when those already concerned about climate change become better at telling truths first to themselves and then to the general public. One can begin with acknowledgements that 1) climate change is unwelcome news, a challenge we would rather not have; and 2) the best and worst outcomes consistent with today’s climate change science are very different. Moreover, every nominal energy “solution” to climate change has a dark side and the solution’s proponents are not the ones to be counted upon to identify what can go wrong.

Accordingly, climate change is a problem of risk management requiring balancing the risks of disruption from climate change and the risks of disruption from mitigation and adaptation. Both public and private institutions need to find ways to overcome their reluctance to verify whether intended carbon reduction goals have actually occurred, so that progress can be accurately monitored and learning can occur. Individuals can be helped to become more aware of how their every-day activities create their carbon footprint. Population must reenter the conversation.

There are grounds for optimism. Science has discovered threats fairly early. Many helpful technologies are being developed and deployed. And, our moral compass is in working order, insisting that we care both for those alive today and for the collective future of our species.

Citation: Robert H. Socolow, “Truths We Must Tell Ourselves to Manage Climate Change.” Vanderbilt Law Review, Vol. 65, Number 6, pp. 1455-1478.

Read the full article: http://www.vanderbiltlawreview.org/content/articles/2012/11/Socolow_-65_Vand_L_Rev_1455.pdf