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Christopher Potter, Pusheng Zhang, Steven Klooster, Vanessa Genovese, Shashi Shekhar, and Vipin Kumar

. Piechota , J. A. Dracup , and T. A. McMaho . 1998 . El Niño-Southern Oscillation and Australian rainfall, stream flow, and drought—Links and potential for forecasting. J. Hydrol. 204 : 138 – 149 . Clark , M. P. , M. C. Serreze , and G. J. McCabe . 2001 . Historical effects of El Niño and La Niña events on the seasonal evolution of the montane snowpack in the Columbia and Colorado River Basins. Water Resour. Res. 37 : 741 – 758 . Coe , M. T. 2000 . Modeling terrestrial

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Martin-Pierre Lavigne, Alain N. Rousseau, Richard Turcotte, Anne-Marie Laroche, Jean-Pierre Fortin, and Jean-Pierre Villeneuve

simulation models and a spatial and attribute database. The objective of this study is to characterize the ability of GIBSI to simulate the impact of deforestation on the hydrological regime of the Famine River watershed (728 km 2 ), a subwatershed of the Chaudière River (6682 km 2 ), by analyzing annual runoff, seasonal runoff, low-water runoff, and peak flows. 2. Background 2.1. Annual runoff Studies on the impact of deforestation on annual runoff are numerous. Plamondon ( Plamondon, 1993 ) observed

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Gemma T. Narisma and Andrew J. Pitman

and CO 2 concentration are a decrease in the stomatal conductance ( g s ) and an increase in the LAI or other biomass, respectively. These effects may lead to contrasting feedbacks on climate, specifically on temperature ( Betts et al., 1997 ; Betts et al., 2000 ). The decrease in g s tends to decrease transpiration, affecting the energy partitioning by decreasing evaporation and increasing sensible heat, potentially leading to warming. Henderson-Sellers et al. ( Henderson-Sellers et al., 1995

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Ademola K. Braimoh and Paul L. G. Vlek

partition the effects of quantity and location errors in the model at each scale ( Pontius, 2000 ). These were kappa for location ( κ loc ) and kappa for quantity ( κ q ). 4. Results and discussion 4.1. Relationships at the basic Landsat TM scale Logistic regression results for the two periods are presented in Table 2 . For the basic 30-m Landsat TM resolution (scale 1), the likelihood of conversion to cropland increased by more than 4 times in the zone where the rainfall was equal to or more than 100

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Christopher Small

. This schematic diagram does not account for the important effects of the seasonal phase of temperature and precipitation cycles, soil properties, and other factors that influence the distribution of biomes. 5. Discussion The modern human habitat can be quantified as distributions of population density and lighted area within geophysical parameter spaces. Conventional maps of population distribution clearly show the distinction between sparsely and densely inhabited regions at global scales but do

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