Geology topics

William A. Reiners

Publications and source records attributed to William A. Reiners.

4 recordsLinked to original sources

USGS2016

External influences on ecological theory: Report on organized oral Session 80 at the 100th Anniversary Meeting of the Ecological Society of America

The 100‐year history of the Ecological Society of America spans most of the major advances in the field of ecology, from the “niche” of Grinnell and others, to Lotka and Volterra's models of predation and competition based on the logistic growth equation, to the concept of competitive exclusion developed from experimental ecology, to genetics and evolutionary ecology and all the ramifications and specializations of these topics over the rest of the 20th and into the 21st century. The objective of this session, sponsored by the Historical Records Committee of the ESA, was to explore how ecological concepts have been shaped and changed by influences that are external to the scientific method, such as funding priorities, ideology, politics, personalities, and differences between the ecosystems where influential ecologists developed their ideas. Among the many memorable quotations of the philosopher/poet George Santayana (1863–1952) is the often quoted and misquoted observation, “Those who cannot remember the past are condemned to repeat it.”

Bulletin of the Ecological Society of America↗

USGS2002

Historical and future land use effects on N 2 O and NO emissions using an ensemble modeling approach: Costa Rica's Caribbean lowlands as an example

[1] The humid tropical zone is a major source area for N 2 O and NO emissions to the atmosphere. Local emission rates vary widely with local conditions, particularly land use practices which swiftly change with expanding settlement and changing market conditions. The combination of wide variation in emission rates and rapidly changing land use make regional estimation and future prediction of biogenic trace gas emission particularly difficult. This study estimates contemporary, historical, and future N 2 O and NO emissions from 0.5 million ha of northeastern Costa Rica, a well-documented region in the wet tropics undergoing rapid agricultural development. Estimates were derived by linking spatially distributed environmental data with an ecosystem simulation model in an ensemble estimation approach that incorporates the variance and covariance of spatially distributed driving variables. Results include measures of variance for regional emissions. The formation and aging of pastures from forest provided most of the past temporal change in N 2 O and NO flux in this region; future changes will be controlled by the degree of nitrogen fertilizer application and extent of intensively managed croplands.

Global Biogeochemical Cycles↗

USGS2000

Simulation of nitrous oxide and nitric oxide emissions from tropical primary forests in the Costa Rican Atlantic Zone

Nitrous oxide (N 2 O) and nitric oxide (NO) are important atmospheric trace gases participating in the regulation of global climate and environment. Predictive models on the emissions of N 2 O and NO emissions from soil into the atmosphere are required. We modified the CENTURY model (Soil Sci. Soc. Am. J., 51 (1987) 1173) to simulate the emissions of N 2 O and NO from tropical primary forests in the Atlantic Zone of Costa Rica at a monthly time step. Combined fluxes of N 2 O and NO were simulated as a function of gross N mineralization and water-filled pore space (WFPS). The coefficients for partitioning N 2 O from NO were derived from field measurements (Global Biogeochem. Cycles, 8 (1994) 399). The modified CENTURY was calibrated against observations of carbon stocks in various pools of forest ecosystems of the region, and measured WFPS and emission rates of N 2 O and NO from soil to the atmosphere. WFPS is an important factor regulating nutrient cycling and emissions of N2O and NO from soils making the accuracy of the WFPS prediction central to the modeling process. To do this, we modified the hydrologic submodel and developed a new method for the prediction of WFPS at the monthly scale from daily rainfall information. The new method is based on: (1) the relationship between monthly rainfall and the number of rainfall events, and (2) the relative cumulative frequency distribution of ranked daily rainfall events. The method is generic and should be applicable to other areas. Simulated monthly average WFPS was 0.68±0.02 — identical with the field measurement average of 0.68±0.02 from the annual cycle observed by Keller and Reiners (Global Biogeochem. Cycles, 8 (1994) 399). Simulated fluxes of N 2 O and NO were 52.0±9.4 mg-N m −2 month −1 and 6.5±0.7 mg-N m −2 month −1 , respectively, compared with measured averages of 48.2±11.0 mg-N m −2 month −1 and 7.1±1.1 mg-N m −2 month −1 . The simulated N 2 O/NO ratio was 11.2±1.9 compared with the measured value of 10.9±4.7. WFPS is the dominant determinant of the fraction of gross N mineralization that is emitted from the soil as N 2 O and NO. If WFPS were not limiting during part of the year, this fraction would be 4.2%. With some periods of lower WFPS, the realized fraction is 2.2%. Because of the strong relationships between N 2 O and NO emission rates and rainfall and its derivative, WFPS, these moisture variables can be used to scale up nitrogen trace gas fluxes from sites to larger spatial scales.

Environmental Modelling and Software↗

USGSDate not supplied

Development of stochastic modeling systems using deterministic models and GIS: Principles and a case study in the Atlantic Zone of Costa Rica

The most important requirements for large-area environmental modeling are a tight integration between models and data, and a close match of the spatial scale at which the model is developed with the scale at which the model is to be applied. To better match the scale of data with that of the model, we propose a set of principles for the development of stochastic modeling systems based on linkage of deterministic models with GIS data. For modeling purposes, a region is usually rasterized into cells and the environmental conditions of those cells are specified by ranges or classes using GIS data layers. It is not necessary to simulate each and every GIS cell in the study area because many cells may have similar environmental conditions and can be grouped together to form cohorts. We define a cohort as the assembly of the cells sharing a unique combination of environmental conditions within the study region. Multiple model simulations can be performed for any given cohort. For each simulation, some of the parameter values can be randomly generated within the specified environmental conditions of the cohort according to a certain statistical distribution which, in turn, can be specified by GIS data layers. By this method the variance and covariance of environmental variables in space and time are integrated into the simulation processes with these modeling systems to make full use of the available data and to assess the uncertainties of the simulated results. An integrated simulation system between CENTURY model and GIS was developed to demonstrate the value of the concepts imbedded in stochastic simulation systems for large area studies.

Conference Paper↗