Dominique Bachelet

Climate change effects on vegetation distribution and carbon budget in the United States

The Kyoto protocol has focused the attention of the public and policymarkers on the earths carbon (C) budget. Previous estimates of the impacts of vegetation change have been limited to equilibrium “snapshots” that could not capture nonlinear or threshold effects along the trajectory of change. New models have been designed to complement equilibrium models and simulate vegetation succession through time while estimating variability in the C budget and responses to episodic events such as drought and fire. In addition, a plethora of future climate scenarios has been used to produce a bewildering variety of simulated ecological responses. Our objectives were to use an equilibrium model (Mapped Atmosphere–Plant–Soil system, or MAPSS) and a dynamic model (MC1) to (a) simulate changes in potential equilibrium vegetation distribution under historical conditions and across a wide gradient of future temperature changes to look for consistencies and trends among the many future scenarios, (b) simulate time-dependent changes in vegetation distribution and its associated C pools to illustrate the possible trajectories of vegetation change near the high and low ends of the temperature gradient, and (c) analyze the extent of the US area supporting a negative C balance. Both models agree that a moderate increase in temperature produces an increase in vegetation density and carbon sequestration across most of the US with small changes in vegetation types. Large increases in temperature cause losses of C with large shifts in vegetation types. In the western states, particularly southern California, precipitation and thus vegetation density increase and forests expand under all but the hottest scenarios. In the eastern US, particularly the Southeast, forests expand under the more moderate scenarios but decline under more severe climate scenarios, with catastrophic fires potentially causing rapid vegetation conversions from forest to savanna. Both models show that there is a potential for either positive or negative feedbacks to the atmosphere depending on the level of warming in the climate change scenarios.

CLIMATE CHANGE EFFECTS ON VEGETATION DISTRIBUTION, CARBON, AND FIRE IN CALIFORNIA

The objective of this study was to dynamically simulate the response of vegetation distribution, carbon, and fire to the historical climate and to two contrasting scenarios of climate change in California. The results of the simulations for the historical climate compared favorably to independent estimates and observations, but validation of the results was complicated by the lack of land use effects in the model. The response to increasing temperatures under both scenarios was characterized by a shift in dominance from needle-leaved to broad-leaved life-forms and by increases in vegetation productivity, especially in the relatively cool and mesic regions of the state. The simulated response to changes in precipitation were complex, involving not only the effect of changes in soil moisture on vegetation productivity, but also changes in tree-grass competition mediated by fire. Summer months were warmer and persistently dry under both scenarios, so the trends in simulated fire area under both scenarios were primarily a response to changes in vegetation biomass. Total ecosystem carbon increased under both climate scenarios, but the proportions allocated to the wood and grass carbon pools differed. The results of the simulations underscore the potentially large impact of climate change on California eco- systems, and the need for further use and development of dynamic vegetation models using various ensembles of climate change scenarios.

Forest Processes and Global Environmental Change: Predicting the Effects of Individual and Multiple Stressors

G change involves the simultaneous and rapid alteration of several key environmental parameters that control the dynamics of forests. We cannot predict with certainty, through direct experimentation, what the responses of forests to global change will be, because we cannot carry out the multisite, multifactorial experiments required for doing so. The physical extent, complexity, and expense of even single-factor experiments at the scale of the whole ecosystem challenge our abilities, although several such experiments have been successfully undertaken (e.g., DeLucia et al. 1999, Wright and Rasmussen 1998). To inform policy decisions, however, the scientific community can offer an interdisciplinary synthesis of existing information. When this synthesis takes the form of a computer model, quantitative predictions can be made that integrate what has been learned from single-factor experiments. The success of such an approach depends on the quality and completeness of the information base and on the rigor of the modeling effort. The direct and secondary physiological effects of changes in the physical and chemical climate on plants and soils are relatively well known. We also know which primary environmental drivers—precipitation, temperature, and atmospheric concentrations of carbon dioxide (CO2), ozone (O3), and nitrogen (N), for example—are being altered by human activities, and we can directly measure temporal change in these parameters. Despite this relatively rich information base, predictions of future responses of forests to environmental change show significant variation. This is due in part to differences between the models of ecosystem function derived from the existing database and in part to differences in climate scenarios generated by the general circulation models (GCMs) used to predict future climates. Understanding both the trend in predicted futures and the uncertainties surrounding those trends is critical to policy formation. At this time, the major mechanism for determining the degree of uncertainty in predictions is through comparison of results from runs of different models using identical input parameters. The purpose of this article is to review the state of prediction of forest ecosystem response to envisioned changes in the physical and chemical climate. These results are offered as one part of the forest sector analysis of the National Assessment

Simulating the impact of climate change on rice production in Asia and evaluating options for adaptation.

Abstract The likely effects of climate change caused by increasing atmospheric carbon dioxide levels on rice production in Asia were evaluated using two rice crop simulation models, ORYZA1 and SIMRIW, running under ‘fixed-change’ climate scenarios and scenarios predicted for a doubled-CO2 (2 × CO2) atmosphere by the General Fluid Dynamics Laboratory (GFDL), the Goddard Institute of Space Studies (GISS) and the United Kingdom Meteorological Office (UKMO) General Circulation Models. In general, an increase in CO2 level was found to increase yields while increases in temperature reduced yields. Overall rice production in the region was predicted by the ORYZA1 model to change by +6.5, −4.4 and −5.6% under the GFDL, GISS and UKMO 2×CO2 scenarios, respectively, while the corresponding changes predicted by the SIMRIW model were +4.2, −10.4 and −12.8%. The average of these estimates would suggest that rice production in the Asian region may decline by −3.8% under the climate of the next century. Declines in yield were predicted under the GISS and UKMO scenarios for Thailand, Bangladesh, southern China and western India, while increases were predicted for Indonesia, Malaysia, and Taiwan and parts of India and China. Modification of sowing dates at high latitudes, where warmer temperatures allowed a longer growing season, permitted a possible transition from single-cropping to double-cropping at some locations, an adaptation that could potentially have a large positive impact on national rice production in some countries. Planting dates could also be adjusted to avoid high temperatures at the time of flowering which can cause severe spikelet sterility in some varieties, although a delay in planting in some cases may prevent a second crop from being obtained because of high temperatures later in the season. Selection for varieties with a higher tolerance of spikelet fertility to temperature was shown to be capable of restoring yield levels to those predicted for current climates. The use of longer-maturing varieties to take advantage of longer growing seasons at higher latitudes may instead result in lower yields, due to the grain formation and ripening periods being pushed to less favorable conditions later in the season. A better strategy might be to select for shorter-maturing varieties to allow a second crop to be grown in these regions.

GLOBAL POTENTIAL NET PRIMARY PRODUCTION PREDICTED FROM VEGETATION CLASS, PRECIPITATION, AND TEMPERATURE

Net primary production (NPP), the difference between CO2 fixed by photosynthesis and CO2 lost to autotrophic respiration, is one of the most important components of the carbon cycle. Our goal was to develop a simple regression model to estimate global NPP using climate and land cover data. Approximately 5600 global data points with observed mean annual NPP, land cover class, precipitation, and temperature were compiled. Precipitation was better correlated with NPP than temperature, and it explained much more of the variability in mean annual NPP for grass- or shrub-dominated systems (r2 = 0.68) than for tree-dominated systems (r2 = 0.39). For a given precipitation level, tree-dominated systems had significantly higher NPP (approximately 100-150 g C m(-2) yr(-1)) than non-tree-dominated systems. Consequently, previous empirical models developed to predict NPP based on precipitation and temperature (e.g., the Miami model) tended to overestimate NPP for non-tree-dominated systems. Our new model developed at the National Center for Ecological Analysis and Synthesis (the NCEAS model) predicts NPP for tree-dominated systems based on precipitation and temperature; but for non-tree-dominated systems NPP is solely a function of precipitation because including a temperature function increased model error for these systems. Lower NPP in non-tree-dominated systems is likely related to decreased water and nutrient use efficiency and higher nutrient loss rates from more frequent fire disturbances. Late 20th century aboveground and total NPP for global potential native vegetation using the NCEAS model are estimated to be approximately 28 Pg and approximately 46 Pg C/yr, respectively. The NCEAS model estimated an approximately 13% increase in global total NPP for potential vegetation from 1901 to 2000 based on changing precipitation and temperature patterns.

DYNAMIC SIMULATION OF TREE–GRASS INTERACTIONS FOR GLOBAL CHANGE STUDIES

The objective of this study was to simulate dynamically the response of a complex landscape, containing forests, savannas, and grasslands, to potential climate change. Thus, it was essential to simulate accurately the competition for light and water between trees and grasses. Accurate representation of water competition requires simulating the appropriate vertical root distribution and soil water content. The importance of different rooting depths in structuring savannas has long been debated. In simulating this complex landscape, we examined alternative hypotheses of tree and grass vertical root distribution and the importance of fire as a disturbance, as they influence savanna dynamics under historical and changing climates. MC1, a new dynamic vegetation model, was used to estimate the distribution of vegetation and associated carbon and nutrient fluxes for Wind Cave National Park, South Dakota, USA. MC1 consists of three linked modules simulating biogeography, biogeochemistry, and fire disturbance. This new tool allows us to document how changes in rooting patterns may affect production, fire frequency, and whether or not current vegetation types and life-form mixtures can be sustained at the same location or would be replaced by others. Because climate change may intensify resource deficiencies, it will probably affect allocation of resources to roots and their distribution through the soil profile. We manipulated the rooting depth of two life-forms, trees and grasses, that are competing for water. We then assessed the importance of variable rooting depth on eco- system processes and vegetation distribution by running MC1 for historical climate (1895- 1994) and a GCM-simulated future scenario (1995-2094). Deeply rooted trees caused higher tree productivity, lower grass productivity, and longer fire return intervals. When trees were shallowly rooted, grass productivity exceeded that of trees even if total grass biomass was only one-third to one-fourth that of trees. Deeply rooted grasses developed extensive root systems that increased N uptake and the input of litter into soil organic matter pools. Shallowly rooted grasses produced smaller soil carbon pools. Under the climate change scenario, NPP and live biomass increased for grasses and decreased for trees, and total soil organic matter decreased. Changes in the size of biogeochemical pools produced by the climate change scenario were overwhelmed by the range of responses across the four rooting configurations. Deeply rooted grasses grew larger than shallowly rooted ones, and deeply rooted trees outcompeted grasses for resources. In both historical and future scenarios, fire was required for the coexistence of trees and grasses when deep soil water was available to trees. Consistent changes in fire frequency and intensity were simulated during the climate change scenario: more fires occurred because higher temperatures resulted in decreased fuel moisture. Fire also increased in the deeply rooted grass configurations because grass biomass, which serves as a fine fuel source, was relatively high.

Methane emissions from wetland rice areas of Asia

Khalil and Rasmussen (1990) reviewed eleven global methane budgets published between 1978 through 1988. They found that methane emissions from rice paddies ranged from 18 to 280 Tg year−1 which correspond to between 10 and 70% of the total anthropogenic methane emissions. For this paper, we have reviewed and replicated three published techniques to estimate methane emissions from rice paddies. We present the results obtained and we propose to include soil characteristics to revise these estimates. Since 90% of rice production occurs in Asia, we have only focused our study on rice in Asia. The first technique we replicated, uses the Food and Agriculture Organization (FAO)s country statistics and crop calendars to determine the land area under rice cultivation each month. Assuming a constant emission rate, Asian rice fields emit about 82 Tg methane year−1. The second technique we replicated, assumes that methane emissions represent a constant fraction of the net primary production and uses empirical relationships between net primary production and temperature and precipitation records. Asian rice fields then only produce 57 Tg methane year−1. The third technique we replicated, relates methane emissions to rice grain production. It involves the calculation of total organic matter added to rice paddy soils and assumes that a constant fraction is emitted as methane. This leads to an estimate of methane emissions from Asian rice fields of about 63 Tg year−1. We propose to use a classification of rice soils to categorize rice growing locations from potentially methane producing to non-methane producing areas. Using this distinction with any of the three methods we discussed, Asian rice fields emissions are reduced by about 25%.

Matching the multiple scales of conservation with the multiple scales of climate change.

To anticipate the rapidly changing world resulting from global climate change, the projections of climate models must be incorporated into conservation. This requires that the scales of conservation be aligned with the scales of climate-change projections. We considered how conservation has incorporated spatial scale into protecting biodiversity, how the projections of climate-change models vary with scale, and how the two do or do not align. Conservation planners use information about past and current ecological conditions at multiple scales to identify conservation targets and threats and guide conservation actions. Projections of climate change are also made at multiple scales, from global and regional circulation models to projections downscaled to local scales. These downscaled projections carry with them the uncertainties associated with the broad-scale models from which they are derived; thus, their high resolution may be more apparent than real. Conservation at regional or global scales is about establishing priorities and influencing policy. At these scales, the coarseness and uncertainties of global and regional climate models may be less important than what they reveal about possible futures. At the ecoregional scale, the uncertainties associated with downscaling climate models become more critical because the distributions of conservation targets on which plans are founded may shift under future climates. At a local scale, variations in topography and land cover influence local climate, often overriding the projections of broad-scale climate models and increasing uncertainty. Despite the uncertainties, ecologists and conservationists must work with climate-change modelers to focus on the most likely projections. The future will be different from the past and full of surprises; judicious use of model projections at appropriate scales may help us prepare.

Interactions between fire, grazing and climate change at Wind Cave National Park, SD

Projected changes in global climate have important ramifications for the future of national parks and other reserves set aside to conserve ecological uniqueness. We explored potential implications of climatic changes on lifeform distribution and growth at Wind Cave National Park (WCNP), South Dakota, which lies on a climatically determined ecotone between grassland and forest. Fire, promoted by healthy grasslands, is a negative feedback limiting tree development because it kills seedlings and consumes live foliage thus reducing tree growth and survival. Historical records show that fire suppression has enhanced forest expansion. On the other hand, livestock grazing reduces grass biomass and fuel loads thus indirectly reducing fire frequency and enhancing the expansion of forests or woodlands. Natural fires and moderate grazing by native herbivores have maintained the coexistence of trees and grasses but climatic variations affecting the areas water resources can lead to dominance by either lifeform. We used a dynamic vegetation model (DVM) MC1 to simulate the interactions between climatic changes, natural fire regime, and grazing pressure and their impact on the biogeographical and biogeochemical characteristics of the park. We used one future climate projection (HADCM2SUL) which simulates warmer weather by the end of the next century: the temperature increase would constrain the growth of trees that rely on the availability of deep water, favor shrub and grass development and promote a shift from forests to woodlands. Woody encroachment of shrubs in grasslands areas, enhanced by grazing, was only held in check by frequent natural fires in the simulation.

A human-driven decline in global burned area

Burn less, baby, burn less Humans have, and always have had, a major impact on wildfire activity, which is expected to increase in our warming world. Andela et al. use satellite data to show that, unexpectedly, global burned area declined by ∼25% over the past 18 years, despite the influence of climate. The decrease has been largest in savannas and grasslands because of agricultural expansion and intensification. The decline of burned area has consequences for predictions of future changes to the atmosphere, vegetation, and the terrestrial carbon sink. Science, this issue p. 1356 Global burned area has declined by ~25% over the past 18 years. Fire is an essential Earth system process that alters ecosystem and atmospheric composition. Here we assessed long-term fire trends using multiple satellite data sets. We found that global burned area declined by 24.3 ± 8.8% over the past 18 years. The estimated decrease in burned area remained robust after adjusting for precipitation variability and was largest in savannas. Agricultural expansion and intensification were primary drivers of declining fire activity. Fewer and smaller fires reduced aerosol concentrations, modified vegetation structure, and increased the magnitude of the terrestrial carbon sink. Fire models were unable to reproduce the pattern and magnitude of observed declines, suggesting that they may overestimate fire emissions in future projections. Using economic and demographic variables, we developed a conceptual model for predicting fire in human-dominated landscapes.