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Impervious surface area (ISA) from the Landsat TM-based NLCD 2001 dataset and land surface temperature (LST) from MODIS averaged over three annual cycles (2003)(2004)(2005) are used in a spatial analysis to assess the urban heat island (UHI) skin temperature amplitude and its relationship to development intensity, size, and ecological setting for 38 of the most populous cities in the continental United States. Development intensity zones based on %ISA are defined for each urban area emanating outward from the urban core to the nonurban rural areas nearby and used to stratify sampling for land surface temperatures and NDVI. Sampling is further constrained by biome and elevation to insure objective intercomparisons between zones and between cities in different biomes permitting the definition of hierarchically ordered zones that are consistent across urban areas in different ecological setting and across scales. We find that ecological context significantly influences the amplitude of summer daytime UHI (urban-rural temperature difference) the largest (8°C average) observed for cities built in biomes dominated by temperate broadleaf and mixed forest. For all cities combined, ISA is the primary driver for increase in temperature explaining 70% of the total variance in LST. On a yearly average, urban areas are substantially warmer than the non-urban fringe by 2.9°C, except for urban areas in biomes with arid and semiarid climates. The average amplitude of the UHI is remarkably asymmetric with a 4.3°C temperature difference in summer and only 1.3°C in winter. In desert environments, the LST's response to ISA presents an uncharacteristic "U-shaped" horizontal gradient decreasing from the urban core to the outskirts of the city and then increasing again in the suburban to the rural zones. UHI's calculated for these cities point to a possible heat sink effect. These observational results show that the urban heat island amplitude both increases with city size and is seasonally asymmetric for a large number of cities across most biomes. The implications are that for urban areas developed within forested ecosystems the summertime UHI can be quite high relative to the wintertime UHI suggesting that the residential energy consumption required for summer cooling is likely to increase with urban growth within those biomes.Published by Elsevier Inc.

The physiological response of terrestrial vegetation when directly exposed to an increase in atmospheric carbon dioxide (CO 2 ) concentration could result in warming over the continents in addition to that due to the conventional CO 2 “greenhouse effect.” Results from a coupled biosphere-atmosphere model (SiB2-GCM) indicate that, for doubled CO 2 conditions, evapotranspiration will drop and air temperature will increase over the tropical continents, amplifying the changes resulting from atmospheric radiative effects. The range of responses in surface air temperature and terrestrial carbon uptake due to increased CO 2 are projected to be inversely related in the tropics year-round and inversely related during the growing season elsewhere.

among islands and regions using nested, mixed-model ANOVA. We screened several potential estimators to find that the Chao 1 procedure provided the most stable values for local species richness. This estimator is the sum of the observed number of species and the quotient a 2 /2b, where a and b equal the number of species represented by one and two colonies, respectively.To analyse the local-regional species richness relationship in each habitat, we used a simple linear regression of the mean local richness per site in a region against habitatspecific regional richness. Linearity is supported by these and supplemental regressions using: (1) log-transformed richness data; (2) local richness standardized to 100 or more colonies per sample 18 ; and (3) the two alternative measures of local species diversity, Fisher's alpha and the Chao 1 estimator of local richness.

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Abstract. This study uses a global terrestrial carbon cycle model (the Carnegie-Ames-Stanford Approach (CASA) model), a satellite-derived map of existing vegetation, and global maps of natural vegetation to estimate the effects of human-induced land cover change on carbon emissions to the atmosphere and net primary production. We derived two maps approximating global land cover that would exist for current climate in the absence of human disturbance of the landscape, using a procedure that minimizes disagreements between maps of existing and natural vegetation that represent artifacts in the data. Similarly, we simulated monthly fields of the Normalized Difference Vegetation Index, required as input to CASA, for the undisturbed land cover case. Model results estimate total carbon losses from human-induced land cover changes of 182 and 199 Pg for the two simulations, compared with an estimate of 124 Pg for total flux between 1850 and 1990 [Houghton, 1999], suggesting that land cover change prior to 1850 accounted for approximately one-third of total carbon emissions from land use change. Estimates of global carbon loss from the two independent methods, the modeling approach used in this paper and the accounting approach of Houghton [1999], are comparable taking into account carbon losses from agricultural expansion prior to 1850 estimated at 48-57 Pg. However, estimates of regional carbon losses vary considerably, notably in temperate midlatitudes where our estimates indicate higher cumulative carbon loss. Overall, land cover changes redu-ced global annual net primary productivity (NPP) by approximately 5%, with large regional variations. High-input agriculture in North America and Europe display higher annual NPP than the natural vegetation that would exist in the absence of cropland. However, NPP has been depleted in localized areas in South Asia and Africa by up to 90%. These results provide initial crude estimates, limited by the spatial resolution of the data sets used as input to the model and by the lack of information about transient changes in land cover. The results suggest that a modeling approach can be used to estimate spatially-explicit effects of land cover change on biosphere-atmosphere interactions.

The sensitivity of global and regional climate to changes in vegetation density is investigated using a coupled biosphere-atmosphere model. The magnitude of the vegetation changes and their spatial distribution are based on natural decadal variability of the normalized difference vegetation index (NDVI). Different scenarios using maximum and minimum vegetation cover were derived from satellite records spanning the period 1982-90. Albedo decreased in the northern latitudes and increased in the Tropics with increased NDVI. The increase in vegetation density revealed that the vegetation's physiological response was constrained by the limits of the available water resources. The difference between the maximum and minimum vegetation scenarios resulted in a 46% increase in absorbed visible solar radiation and a similar increase in gross photosynthetic CO 2 uptake on a global annual basis. This increase caused the canopy transpiration and interception fluxes to increase and reduced those from the soil. The redistribution of the surface energy fluxes substantially reduced the Bowen ratio during the growing season, resulting in cooler and moister near-surface climate, except when soil moisture was limiting. Important effects of increased vegetation on climate are R a cooling of about 1.8 K in the northern latitudes during the growing season and a slight warming during the winter, which is primarily due to the masking of high albedo of snow by a denser canopy; and R a year-round cooling of 0.8 K in the Tropics. These results suggest that increases in vegetation density could partially compensate for parallel increases in greenhouse warming. Increasing vegetation density globally caused both evapotranspiration and precipitation to increase. Evapotranspiration, however, increased more than precipitation, resulting in a global soil-water deficit of about 15%. A spectral analysis on the simulated results showed that changes in the state of vegetation could affect the low-frequency modes of the precipitation distribution and might reduce its low-frequency variability in the Tropics while increasing it in northern latitudes.