Abstract

Croplands cover large areas of the globe and contribute significantly to the global carbon cycle. However, like other ecosystems, limited information exists on spatially explicit, ground-based estimates of carbon fluxes. In this study, county-level cropland area and harvest information reported in the U.S. Department of Agriculture (USDA) National Agricultural Statistics Service (NASS) from 1972 to 2001 was utilized to calculate the temporal behavior of net primary production (NPP) for croplands across the United States. Production data for individual crops were converted to estimates of NPP using crop-specific factors. Because NASS does not include all crops of interest during all years, only a crop type in a county estimate was included if the entire time series was complete. Incomplete reporting occurred primarily with hay. Trends in crop area, NPP, and total production (area times NPP) exhibited significant spatial variation. The largest increases in production occurred in the Midwest, Great Plains, and Mississippi River Valley regions. Cropland area exhibited a range of trends from large percent increases in counties across the Great Plains and the West to decreases across the South. Generally, NPP increased in counties throughout the United States and for the country as a whole. It was estimated that total coterminous cropland production increased during 1972–2001 from 0.37 to 0.53 Pg C yr⁻¹, a 40% increase over 1972 values. Since total cropland area changed little during the 30-yr period, production increases were driven primarily by gains in NPP.

Abstract

Over the past two decades, forests in the southeastern United States have undergone dramatic changes as the result of urban sprawl and conversion to intensively managed pine plantations. The Cumberland Plateau, an important ecoregion in the southeastern United States, contains some of the largest remaining tracts of privately owned, native hardwood forest in North America. These ecologically important forests have been undergoing increasingly rapid rates of hardwood-to-pine conversion, much of which has gone undetected by large-scale statewide inventories. Forest conversion in Tennessee's southern Cumberland Plateau provides a case study highlighting the need for interdisciplinary and spatially explicit assessments of the impact and drivers of land-use change at smaller scales. Aerial and satellite imagery were used to create computer-generated maps of land use and forest cover for a 243 000 ha study area within a seven-county region of the southern Cumberland Plateau in Tennessee to track and document patterns of forest change and conversion between 1981 and 2000. The ecological impact of forest harvesting and hardwood-to-pine conversion was evaluated by (i) monitoring aquatic macroinvertebrate diversity, (ii) tracking breeding-bird populations, and (iii) comparing calcium (Ca) stores and cycling in a chronosequence of hardwood to first- and second-rotation loblolly pine (Pinus taeda) plantations. It was found that 14% of native forest cover had been lost since 1981, 74% of which resulted from hardwood-to-pine conversion. It was also found that the rate of conversion to pine doubled from 1997 to 2000. Water quality in streams, as measured by the abundance of critical macroinvertebrates, was significantly lower in recently logged sites than in undisturbed native forest. Surveys of breeding-bird populations showed that pine plantations of several age classes had lower species richness and evenness than did native oak–hickory forests. Despite similar soil concentrations of Ca in native hardwood, mature first-rotation, and early second-rotation pine, changes were found in aboveground Ca storage that suggest substantial system Ca losses that may limit productivity of second-rotation pine or regrowth of oak–hickory forest. As part of the ongoing research on the socioeconomic drivers of land-use change on the Cumberland Plateau, it was found that Tennessee's major forest conservation incentive program only delays forest conversion for a few years while subsidizing landowners who would not have converted their land in the absence of the program. These results demonstrate the need for more detailed and multidisciplinary research conducted at smaller scales so as to enhance the understanding of the impact and drivers of land-use change at larger scales.

Abstract

The spatial distribution of human population on the land surface is a fundamental determinant of land-use impacts on Earth's ecosystems. Census enumerations and satellite-detected night lights provide two complementary, but distinct, representations of human population distribution. Census estimates indicate that 37% of Earth's enumerated land area is populated at densities greater than 1 person per square kilometer. Human populations are strongly clustered within this area. Spatial variations in human population density span more than six orders of magnitude with 50% of the 1990 population occupying less than 3% of the inhabited land area. Temporally stable lighted areas detectable from space provide an independent proxy for the spatial distribution of urban settlements and the intensive land-cover changes that accompany them. These ∼60 000 lighted areas account for less than 2% of inhabited land area, and 50% of this lighted area is associated with the largest 5% of cities and conurbations. Urban land use associated with higher population densities can exert a disproportionate influence on environments both near and distant. The spatial distributions of population density and lighted areas relative to geophysical parameters (continental physiography and climate) highlight some similarities and differences in the relationship of urban and rural land use to different physical environments. The spatial distribution of urban land use is strongly localized with respect to continental physiography (coastal and fluvial proximity and elevation) but much less localized with respect to climatic parameters (annual mean and range of temperature and precipitation). These distributions quantify the extent to which spatially focused development of urban land use, with respect to the physical landscape, influences coastal and riparian ecosystems in particular. If future population distributions follow current patterns, then demographic momentum and increasing rates of urban migration will result in accelerated growth of urban areas in these environments.

Abstract

Increasing atmospheric carbon dioxide concentration and the resulting change in temperature affect vegetation physiologically and structurally. These physiological and structural changes are biospheric feedbacks that may enhance or moderate the impacts due to human-induced land-cover change. It is therefore potentially important to include these biospheric feedbacks in experiments that explore the impact of land-cover change on climate. In this paper, it is shown that the vegetation response to higher carbon dioxide concentrations and warmer temperatures moderates the impacts of historical human-induced land-cover change in Australia. The magnitude of these biospheric feedbacks is explored, and it is shown that including them in climate simulations results in smaller land-cover change impacts on latent heat flux (by about 10–20 W m⁻²) and temperature (by about 0.3°C), irrespective of the direction of change caused initially by land-cover change. Further, the magnitude of the feedback on temperature is nonnegligible and can be comparable, at the regional scale, to temperature changes due to increasing atmospheric carbon dioxide concentrations. It is also shown that the biospheric feedback effects are not limited to areas of human-induced land-cover change. Higher simulated temperatures of about 0.05°–0.15°C were found in regions remote from areas of human-induced changes when these biospheric feedbacks are included. It is concluded therefore that it is necessary to take biospheric feedbacks into account in climate simulations. Excluding these feedbacks may incorrectly assess the impacts due to land-cover change.

Abstract

The goal of this study is to develop and apply a methodology for delineating optimal land-use patterns that minimize peak runoff flow at watershed outlets by coupling a hydrological model and a land-use model. Under the assumption supported in prior research that nonpoint source (NPS) pollution is positively correlated with surface runoff volume, the model then yields land-use patterns that minimize nonpoint source pollution. A hydrological simulation model is developed with a modified and spatially explicit Soil Conservation Service (SCS) curve number method to analyze the geographical impacts of land uses. An optimization algorithm is integrated with the simulation model to evaluate different land-use patterns and their response to rainfall runoff events, and to search for optimal land-use patterns. This approach, applied to the southwestern basin of Lake Erie, Old Woman Creek Watershed (Ohio), yields optimal land-use patterns that reduce the peak runoff rate by 15%–20% under 1-, 2-, 5-, and 10-yr storms, compared to the current land-use pattern. The model results provide site-specific land-use guidelines and identify critical areas for conservation.

Abstract

Relationships between cropland change and presumed determinants were analyzed at scales ranging from 30 to 5100 m using logistic regression. The plot of the odds ratio across the spatial scales indicated that both biophysical and social variables were important in explaining cropland change. In the first period (1984–92), biophysical factors were the dominant factors, while market-related variables were more dominant between 1992 and 1999. Response to changing economic opportunities was the underlying cause of this trend. Policies that would make commercialization of agriculture viable are required in the Volta basin of Ghana.

Abstract

The Gestion Intégrée des Bassins versants à l'aide d'un Système Informatisé (GIBSI), a semidistributed hydrological modeling system, was evaluated for its ability to simulate the impact of deforestation on the hydrological regime of the Famine River watershed (728 km²), a subwatershed of the Chaudière River, Québec, Canada. Annual, spring and summer, and low-water runoff, as well as peak flows, were estimated for both a base-case scenario and a deforestation scenario using 31 annual meteorological series. GIBSI simulated an average increase of annual runoff after clear-cutting of 57% (268 mm) and the proportion of runoff to precipitation increased from 40% to 63%. The average increase in spring runoff was 25%, while in summer it was 138%. For summer low-flow periods, GIBSI simulated an average increase in runoff of 102%. For spring and summer peak-flow rates, hydrographs generated by GIBSI showed that average spring peak flows were increased after deforestation by 26% while summer peak flows were increased by 101%. Differences between spring and summer runoffs as well as peak-flow rates are due to changes in the degree of saturation of the soil and actual evapotranspiration between the two scenarios. Hence, while land-use changes have a substantial impact on summer runoff and low flows, they have little impact on extreme peak-flow events, especially during spring (less than 10% or more than 90% nonexceeding probability). This suggests that land use has a limited role in controlling these extreme events. The simulation results obtained by GIBSI were consistent with those found in the literature. Therefore, GIBSI offers potential as a management tool for investigating prevention and reduction measures of deforestation effects on the hydrological regime of a watershed.

Abstract

The objectives of this study were to quantify land-cover changes. A short-term projection of land-cover distribution in a 2400-ha (1 ha = 10 000 m² ) area of northern Ghana was generated. Landsat Thematic Mapper images acquired in 1984, 1992, and 1999 were used for land-cover mapping, whereas land-cover projections were carried out using transition probability techniques. Remote sensing analyses showed that in the first period (1984–92), the dominant land-cover change process was the expansion of the built-up area (26 ha yr⁻¹) as a result of an increase in demand for housing by the increasing population. Expansion of the built-up area continued at the rate of 35 ha yr⁻¹ in the second period (1992–99), as well as development of peri-urban agriculture (24 ha yr⁻¹) to meet the food demand of the rapidly growing population. Projection of land-cover distribution showed that the built-up area would further increase at the expense of cropland and natural vegetation, covering about 39% of the landscape by 2006. Policy implications of this trend are discussed.

This paper is part of a special theme issue on land use and ecosystems.

Abstract

Long-term (20 yr) river discharge records from 30 of the world’s largest river basins have been used to characterize surface hydrologic flows in relation to net precipitation inputs, ocean climate teleconnections, and human land/water use patterns. This groundwork study is presented as a precedent to distributed simulation modeling of surface hydrologic flows in large river basins. Correlation analysis is used as a screening method to classify river basins into categories based on major controls on discharge, for example, climate, land use, and dams. Comparisons of paired station records at upstream and downstream discharge locations within each major river basin suggest that the discharge signals represented in upstream discharge records are sustained in the downstream station records for nearly two-thirds of the drainage basins selected. River basins that showed the strongest localized climate control over historical discharge records, in terms of correlations with net basinwide precipitation rates, are located mainly in the seasonally warm temperate and tropical latitude zones, as opposed to river basins located mainly in the higher latitude zones (above 45°N). Ocean climate indices such as the Niño1+2 and Niño3+4 correlate highly with historical interannual patterns in monthly river discharge for only four of the selected discharge station records, namely, on the Amazon, Congo (Zaire), Columbia, and Colorado (Arizona) Rivers. Historical patterns of cropland development and irrigated areas may explain the weak climate correlations with interannual patterns in monthly river discharge rates for at least one-third of the major river drainages selected from the historical discharge dataset.

This paper is part of a special theme issue on land use and ecosystems.