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 earth's 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. Received 12 May 2000; accepted 22 November 2000.     

Two new species of Gomphidius from the Western United States and Eastern Siberia

Study of the genus Gomphidius from recent material from Asia and North America has been carried out using traditional taxonomy combined with molecular systematics. Two new species of Gomphidius (G. borealis and G. pseudoflavipes) are described, one from Eastern Siberia and a second from rarely collected habitats in the Western United States. One taxon has the longest spores reported for the genus and the second species appears to be associated with a Siberian larch.     

Domestic Water Use in the United States: A Life-Cycle Approach

Water and energy are two primary natural resources used by building occupants. A life-cycle assessment (LCA) is performed for water-consuming plumbing fixtures and water-consuming appliances during their operational life for four different building types. Within the cycle studied, water is extracted from the natural environment, subjected to water treatment, pumped to buildings for use, collected for wastewater treatment, and discharged back to the natural environment. Specifically, the impacts of water use, electricity and natural gas generation, energy consumption (for water and wastewater treatment, and for water heating), and the manufacture of water and wastewater treatment chemicals are evaluated both quantitatively and qualitatively on a generalized national level in the United States of America.
It is concluded that water use and consumption within buildings have a much larger impact on resource consumption than the water and wastewater treatment stages of the life cycle. To study this more specifically, the resource consumption of four different building types-an apartment building, a college dormitory, a motel, and an office building-is considered. Of these four building types, the apartment has the highest energy consumption (for water and wastewater treatment, and for water heating) per volume of water used, whereas the office building has the lowest. Similarly, the calculated LCA score for the apartment building is typically greater than those of the other three building types.     

Land Use/Cover Change and the Terrestrial Carbon Cycle in the Asia-Pacific Region

Current atmospheric CO_2 concentrations are the highest on record in the last half a millionyears and are expected to reach between 540 and 970 ppm over the next one hundred years. Thisunprecedented increase is linked to human activities including fossil fuel combustion anddeforestation. The increase in CO_2 concentrations, and to a lesser extent in other greenhouse gases,is linked to changes in climate patterns and variability, and to an average global warming of 0.6℃during the 20th Century (IPCC 2001). Changes in land use and cover are critical controls of the distribution and strength of carbon     

Satellite Evidence of Phenological Differences Between Urbanized and Rural Areas of the Eastern United States Deciduous Broadleaf Forest

We used a 10-year record (1990–99) of composited and cloud-screened reflectances from the Advanced Very High Resolution Radiometer (AVHRR) to test for phenological differences between urban and rural areas in the eastern United States deciduous broadleaf forest (DBF). We hypothesized that well-documented urban heat island effects would be associated with alterations in temperature-sensitive vegetation phenology. Our objectives were thus (a) to investigate possible differences in the start of the growing season (SOS) and end of the growing season (EOS) between the urban and DBF land covers, (b) to investigate related differences in greenness amplitude and fractional cover, and (c) to develop a generalized additive model (GAM) to predict the spatial variation of observed differences. By analyzing individual 1° latitude by 1° longitude blocks, we found that, on average, urbanization is associated with a growing season expansion of 7.6 days. Most of this effect is caused by an earlier SOS in urban areas. In all cases, urban regions had lower fractional cover and greenness amplitude. The GAM model failed to produce a viable model for differences in EOS, probably because it is dominated by photoperiod controls with only a minor temperature impact. SOS differences were predicted with an accuracy of about 2.4 days, with a GAM consisting of smoothed functions of mean annual average temperature, urban fractional cover, and the urban vs DBF greenness amplitude difference. We speculate that evidence of a phenological response to warming indicates that global warming, without reduction in DBF vegetation cover and greenness amplitude, may increase carbon sequestration in mesic deciduous forests. Received 6 June 2001; accepted 23 October 2001.     

Eastern equine encephalitis in the United States, 1971: Past and prologue

During 1971, surveillance for equine encephalitis in the United States was increased due to an epizootic of Venezuelan equine encephalomyelitis. Of 1,982 specimens from 1,551 equines, 76 isolates of eastern equine encephalitis (EEE) virus were recovered from 67 individuals. The virus was isolated from 50/176 brains, 8/74 spleens, 14/1,127 sera, and 4/147 whole bloods from infected equines in 12 of the 31 states bounded by or east of the Mississippi River and in Texas and Iowa; no specimens were received from 9 of these 31 states. Thus, EEE virus was isolated from equines in 12 of 22 of these states. Determinations of antibody to EEE and western equine encephalitis (WEE) viruses indicated a relatively high prevalence of infection with EEE virus in the eastern USA and similarly high prevalence of antibody to WEE virus in the western USA. These data indicate that equine infections with EEE virus in the eastern USA are considerably more common than previous surveillance data have suggested. Increased surveillance and submission of specimens to diagnostic laboratories for diagnosis of EEE virus infections in equines are suggested so that a greater proportion of the thousands of unspecified equine encephalitis cases occurring in the United States each year can be laboratory confirmed.     

Quantifying and Valuing Potential Climate Change Impacts on Coral Reefs in the United States: Comparison of Two Scenarios

The biological and economic values of coral reefs are highly vulnerable to increasing atmospheric and ocean carbon dioxide concentrations. We applied the COMBO simulation model (COral Mortality and Bleaching Output) to three major U.S. locations for shallow water reefs: South Florida, Puerto Rico, and Hawaii. We compared estimates of future coral cover from 2000 to 2100 for a “business as usual” (BAU) greenhouse gas (GHG) emissions scenario with a GHG mitigation policy scenario involving full international participation in reducing GHG emissions. We also calculated the economic value of changes in coral cover using a benefit transfer approach based on published studies of consumers'' recreational values for snorkeling and diving on coral reefs as well as existence values for coral reefs. Our results suggest that a reduced emissions scenario would provide a large benefit to shallow water reefs in Hawaii by delaying or avoiding potential future bleaching events. For Hawaii, reducing emissions is projected to result in an estimated “avoided loss” from 2000 to 2100 of approximately $10.6 billion in recreational use values compared to a BAU scenario. However, reducing emissions is projected to provide only a minor economic benefit in Puerto Rico and South Florida, where sea-surface temperatures are already close to bleaching thresholds and coral cover is projected to drop well below 5% cover under both scenarios by 2050, and below 1% cover under both scenarios by 2100.     

Baseball on the Border: A Tale of Two Laredos

Baseball on the Border:. Tale of Two Laredos. Alan M. Klein. Princeton, NJ: Princeton University Press, 1997.291 pp.     

Effect of Change of Forest Carbon Storage on Net Carbon Dioxide Balance of Wood Use for Energy in Japan

This study analyzed the net carbon dioxide (CO₂) emission reductions between 2005 and 2050 by using wood for energy under various scenarios of forest management and energy conversion technology in Japan, considering both CO₂ emission reductions from replacement of fossil fuels and changes in carbon storage in forests. According to our model, wood production for energy results in a significant reduction of carbon storage levels in forests (by 46% to 77% in 2050 from the 2005 level). Thus, the net CO₂ emission reduction when wood is used for energy becomes drastically smaller. Conventional tree production for energy increases net CO₂ emissions relative to preserving forests, but fast‐growing tree production may reduce net CO₂ emissions more than preserving forests does. When wood from fast‐growing trees is used to generate electricity with gas turbines, displacing natural gas, the net CO₂ emission reduction from the combination of fast‐growing trees and electricity generation with gas turbines is about 58% of the CO₂ emission reduction from electricity generation from gas turbines alone in 2050, and an energy conversion efficiency of around 20% or more is required to obtain net reductions over the entire period until 2050. When wood is used to produce bioethanol, displacing gasoline, net reductions are realized after 2030, provided that heat energy is recovered from residues from ethanol production. These results show the importance of considering the change in carbon storage when estimating the net CO₂ emission reduction effect of the wood use for energy.     

Large-scale Regional Variation in Diatom-water Chemistry Relationships: Rivers of the Eastern United States

We analyzed diatom and water chemistry data collected by The Academy of Natural Sciences from 47 rivers throughout the eastern United States to address several ecological questions. How does the composition of diatom assemblages vary over large regional scales? What are the most important environmental factors affecting assemblage composition and how does their influence vary among regions and with spatial scale? How do distributions and autecological characteristics of individual taxa vary spatially? What are the implications of answers to these questions for use of diatoms as water quality indicators? Data for 186 samples at 116 sites were collected from 1951 to 1991 on moderate- to large-sized rivers ranging from Maine to Texas as part of Academy monitoring and survey programs, most initiated and implemented by Dr. Ruth Patrick. Several sites were highly impaired by point and non-point source pollution. Diatom assemblages grouped into four main categories, based on multivariate analyses. Group membership correlated equally well with intermediate-scale geographic regions and water chemistry: (1) Northeastern US rivers with lower alkalinity and hardness, and pH 6.5–7.8; (2) Primarily dilute coastal plain rivers in the southeastern United States with the lowest average pH (5.5–7.3) of all sites and some with high DOC; (3) Rivers within and west of the Appalachian Mountains, generally having higher pH (>7.5) than those in other regions, but with relatively low chloride concentrations; and (4) Gulf Coast rivers with the highest chloride (>100 mg l^?1), hardness (>250 mg l^?1), and pH of rivers in all the groups. Hardness, pH, alkalinity, and Cl explained most of the variation among diatom assemblages, based on ordination analysis. Factors related to water quality problems, such as BOD, P, NH₄, and turbidity explained much less variability at the eastern US scale, but were more important in the four intermediate-scale regions. Diatom taxa abundance-weighted mean values for water chemistry characteristics varied among the four intermediate-scale regions, often greatly, and in proportion to the average measured values for each region. Design of calibration data sets for development of water quality indicators should account for spatial scale in relation to species dispersal, regional geochemistry and habitat types, and human-influenced water chemistry characteristics.     

Climate change increases risk of plant invasion in the Eastern United States

Invasive plant species threaten native ecosystems, natural resources, and managed lands worldwide. Climate change may increase risk from invasive plant species as favorable climate conditions allow invaders to expand into new ranges. Here, we use bioclimatic envelope modeling to assess current climatic habitat, or lands climatically suitable for invasion, for three of the most dominant and aggressive invasive plants in the southeast United States: kudzu (Pueraria lobata), privet (Ligustrum sinense; L. vulgare), and cogongrass (Imperata cylindrica). We define climatic habitat using both the Maxent and Mahalanobis distance methodologies, and we define the best climatic predictors based on variables that best ‘constrain’ species distributions and variables that ‘release’ the most land area if excluded. We then use an ensemble of 12 atmosphere-ocean general circulation models to project changes in climatic habitat for the three invasive species by 2100. The combined methodologies, predictors, and models produce a robust assessment of invasion risk inclusive of many of the approaches typically used individually to assess climate change impacts. Current invasion risk is widespread in southeastern states for all three species, although cogongrass invasion risk is more restricted to the Gulf Coast. Climate change is likely to enable all three species to greatly expand their ranges. Risk from privet and kudzu expands north into Ohio, Pennsylvania, New York, and New England states by 2100. Risk from cogongrass expands as far north as Kentucky and Virginia. Heightened surveillance and prompt eradication of small pockets of invasion in northern states should be a management priority.     

Learning to Teach in Two Cultures: Japan and the United States

Learning to Teach in Two Cultures: Japan and the United States. Nobuo K. Shimahara and Akira Sakai. New York: Garland Publishing, Inc., 1995. 264 pp.     

Regression Techniques for Examining Land Use/Cover Change: A Case Study of a Mediterranean Landscape

In many areas of the northern Mediterranean Basin the abundance of forest and scrubland vegetation is increasing, commensurate with decreases in agricultural land use(s). Much of the land use/cover change (LUCC) in this region is associated with the marginalization of traditional agricultural practices due to ongoing socioeconomic shifts and subsequent ecological change. Regression-based models of LUCC have two purposes: (i) to aid explanation of the processes driving change and/or (ii) spatial projection of the changes themselves. The independent variables contained in the single ‘best’ regression model (that is, that which minimizes variation in the dependent variable) cannot be inferred as providing the strongest causal relationship with the dependent variable. Here, we examine the utility of hierarchical partitioning and multinomial regression models for, respectively, explanation and prediction of LUCC in EU Special Protection Area 56, ‘Encinares del río Alberche y Cofio’ (SPA 56) near Madrid, Spain. Hierarchical partitioning estimates the contribution of regression model variables, both independently and in conjunction with other variables in a model, to the total variance explained by that model and is a tool to isolate important causal variables. By using hierarchical partitioning we find that the combined effects of factors driving land cover transitions varies with land cover classification, with a coarser classification reducing explained variance in LUCC. We use multinomial logistic regression models solely for projecting change, finding that accuracies of maps produced vary by land cover classification and are influenced by differing spatial resolutions of socioeconomic and biophysical data. When examining LUCC in human-dominated landscapes such as those of the Mediterranean Basin, the availability and analysis of spatial data at scales that match causal processes is vital to the performance of the statistical modelling techniques used here.     

Contributions of Fire Use Study to Land Use/Cover Change Frameworks: Understanding Landscape Change in Agricultural Frontiers

The impact of fire use and hazard in frontier settlement is a critical environmental concern that has been historically overshadowed by deforestation issues- and thus underexamined at local and regional scales by social scientists. Consequently, conceptual frameworks of LUCC change consider fire use as an outcome of land use decisions and neglect the capacity of burning choices to influence these decisions and subsequent land cover change. This paper examines the relationship of settlement, land use, and fire use. It considers recent LUCC frameworks, and then uses household surveys on fire use practices to discuss how the study of fire use can contribute to understanding frontier landscape change. Planting decisions, settlement history, location desires, and burning logistics work in combination to influence burning choices and thus LUCC.     

Forest Cover Estimation in Ireland Using Radar Remote Sensing: A Comparative Analysis of Forest Cover Assessment Methodologies

Quantification of spatial and temporal changes in forest cover is an essential component of forest monitoring programs. Due to its cloud free capability, Synthetic Aperture Radar (SAR) is an ideal source of information on forest dynamics in countries with near-constant cloud-cover. However, few studies have investigated the use of SAR for forest cover estimation in landscapes with highly sparse and fragmented forest cover. In this study, the potential use of L-band SAR for forest cover estimation in two regions (Longford and Sligo) in Ireland is investigated and compared to forest cover estimates derived from three national (Forestry2010, Prime2, National Forest Inventory), one pan-European (Forest Map 2006) and one global forest cover (Global Forest Change) product. Two machine-learning approaches (Random Forests and Extremely Randomised Trees) are evaluated. Both Random Forests and Extremely Randomised Trees classification accuracies were high (98.1–98.5%), with differences between the two classifiers being minimal (<0.5%). Increasing levels of post classification filtering led to a decrease in estimated forest area and an increase in overall accuracy of SAR-derived forest cover maps. All forest cover products were evaluated using an independent validation dataset. For the Longford region, the highest overall accuracy was recorded with the Forestry2010 dataset (97.42%) whereas in Sligo, highest overall accuracy was obtained for the Prime2 dataset (97.43%), although accuracies of SAR-derived forest maps were comparable. Our findings indicate that spaceborne radar could aid inventories in regions with low levels of forest cover in fragmented landscapes. The reduced accuracies observed for the global and pan-continental forest cover maps in comparison to national and SAR-derived forest maps indicate that caution should be exercised when applying these datasets for national reporting.