Allen M. Solomon

Bio: Allen M. Solomon is an academic researcher from United States Environmental Protection Agency. The author has contributed to research in topics: Climate change & Carbon cycle. The author has an hindex of 16, co-authored 18 publications receiving 6261 citations. Previous affiliations of Allen M. Solomon include Potsdam Institute for Climate Impact Research.

Carbon pools and flux of global forest ecosystems.

Abstract: Forest systems cover more than 4.1 x 109 hectares of the Earth9s land area. Globally, forest vegetation and soils contain about 1146 petagrams of carbon, with approximately 37 percent of this carbon in low-latitude forests, 14 percent in mid-latitudes, and 49 percent at high latitudes. Over two-thirds of the carbon in forest ecosystems is contained in soils and associated peat deposits. In 1990, deforestation in the low latitudes emitted 1.6 ± 0.4 petagrams of carbon per year, whereas forest area expansion and growth in mid- and high-latitude forest sequestered 0.7 ± 0.2 petagrams of carbon per year, for a net flux to the atmosphere of 0.9 ± 0.4 petagrams of carbon per year. Slowing deforestation, combined with an increase in forestation and other management measures to improve forest ecosystem productivity, could conserve or sequester significant quantities of carbon. Future forest carbon cycling trends attributable to losses and regrowth associated with global climate and land-use change are uncertain. Model projections and some results suggest that forests could be carbon sinks or sources in the future.

A global biome model based on plant physiology and dominance, soil properties and climate

Abstract: A model to predict global patterns in vegetation physiognomy was developed from physiological considera- tions influencing the distributions of different functional types of plant. Primary driving variables are mean coldest- month temperature, annual accumulated temeprature over 5"C, and a drought index incorporating the seasonality of precipitation and the available water capacity of the soil. The model predicts which plant types can occur in a given environment, and selects the potentially dominant types from among them. Biomes arise as combinations of domi- nant types. Global environmental data were supplied as monthly means of temperature, precipitation and sunshine (interpolated to a global 0.5" grid, with a lapse-rate correc-

Forecasting Regional to Global Plant Migration in Response to Climate Change

Abstract: The rate of future climate change is likely to exceed the migration rates of most plant species. The replacement of dominant species by locally rare species may require decades, and extinctions may occur when plant species cannot migrate fast enough to escape the consequences of climate change. Such lags may impair ecosystem services, such as carbon sequestration and clean water production. Thus, to assess global change, simulation of plant migration and local vegetation change by dynamic global vegetation models (DGVMs) is critical, yet fraught with challenges. Global vegetation models cannot simulate all species, necessitating their aggregation into plant functional types (PFTs). Yet most PFTs encompass the full spectrum of migration rates. Migration processes span scales of time and space far beyond what can be confidently simulated in DGVMs. Theories about climate change and migration are limited by inadequate data for key processes at short and long time scales and at small and large spatial scales. These theories must be enhanced to incorporate species-level migration and succession processes into a more comprehensive definition of PFTs.

Tree Mortality in Gap Models: Application to Climate Change

Abstract: Gap models are perhaps the most widely used class of individual-based tree models used in ecology and climate change research. However, most gap model emphasize, in terms of process detail, computer code, and validation effort, tree growth with little attention to the simulation of plant death or mortality. Mortality algorithms have been mostly limited to general relationships because of sparse data on the causal mechanisms of mortality. If gap models are to be used to explore community dynamics under changing climates, the limitations and shortcomings of these mortality algorithms must be identified and the simulation of mortality must be improved. In this paper, we review the treatment of mortality in gap models, evaluate the relationships used to represent mortality in the current generation of gap models, and then assess the prospects for making improvements, especially for applications involving global climate change. Three needs are identified to improve mortality simulations in gap models: (1) process-based empirical analyses are needed to create more climate-sensitive stochastic mortality functions, (2) fundamental research is required to quantify the biophysical relationships between mortality and plant dynamics, and (3) extensive field data are needed to quantify, parameterize, and validate existing and future gap model mortality functions.

Explaining forest composition and biomass across multiple biogeographical regions

Abstract: Current scientific concerns regarding the impacts of global change include the responses of forest composition and biomass to rapid changes in climate, and forest gap models have often been used to address this issue. These models reflect the concept that forest composition and biomass in the absence of large-scale disturbance are explained by competition among species for light and other resources in canopy gaps formed when dominant trees die. Since their intiation 25 yr ago, a wide variety of gap models have been developed that are applicable to different forest ecosystems all over the world. Few gap models, however, have proved to be equally valid over a wide range of environmental conditions, a problem on which our work is focused. We previously developed a gap model that is capable of simulating forest composition and biomass in temperate forests of Europe and eastern North America based on a single model structure. In the present study, we extend the model to simulate individual tree species response to strong moisture seasonality and low temperature seasonality, and we modify the widespread parabolic temperature response function to mimic nonlinear increases in growth with increased temperature up to species-specific optimal values. The resulting gap model, ForClim V2.9, generates realistic projections of tree species composition and biomass across a complex gradient of temperature and moisture in the Pacific Northwest of the United States. The model is evaluated against measured basal area and stand structure data at three elevations of the H. J. Andrews LTER site, yielding satisfactory results. The very same model also provides improved estimates of species composition and stand biomass in eastern North America and central Europe, where it originated. This suggests that the model modifications we introduced are indeed generic. Temperate forests other than those we studied here are characterized by climates that are quite similar to the ones in the three study regions. Therefore we are confident that it is possible to explain forest composition and biomass of all major temperate forests by means of a single hypothesis as embodied in a forest gap model.

A Large and Persistent Carbon Sink in the World’s Forests

Abstract: The terrestrial carbon sink has been large in recent decades, but its size and location remain uncertain. Using forest inventory data and long-term ecosystem carbon studies, we estimate a total forest sink of 2.4 ± 0.4 petagrams of carbon per year (Pg C year–1) globally for 1990 to 2007. We also estimate a source of 1.3 ± 0.7 Pg C year–1 from tropical land-use change, consisting of a gross tropical deforestation emission of 2.9 ± 0.5 Pg C year–1 partially compensated by a carbon sink in tropical forest regrowth of 1.6 ± 0.5 Pg C year–1. Together, the fluxes comprise a net global forest sink of 1.1 ± 0.8 Pg C year–1, with tropical estimates having the largest uncertainties. Our total forest sink estimate is equivalent in magnitude to the terrestrial sink deduced from fossil fuel emissions and land-use change sources minus ocean and atmospheric sinks.

Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful?

Abstract: Modelling strategies for predicting the potential impacts of climate change on the natural distribution of species have often focused on the characterization of a species’ bioclimate envelope. A number of recent critiques have questioned the validity of this approach by pointing to the many factors other than climate that play an important part in determining species distributions and the dynamics of distribution changes. Such factors include biotic interactions, evolutionary change and dispersal ability. This paper reviews and evaluates criticisms of bioclimate envelope models and discusses the implications of these criticisms for the different modelling strategies employed. It is proposed that, although the complexity of the natural system presents fundamental limits to predictive modelling, the bioclimate envelope approach can provide a useful first approximation as to the potentially dramatic impact of climate change on biodiversity. However, it is stressed that the spatial scale at which these models are applied is of fundamental importance, and that model results should not be interpreted without due consideration of the limitations involved. A hierarchical modelling framework is proposed through which some of these limitations can be addressed within a broader, scale-dependent