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Winter storms produce major problems for society, and the key responsible factor is often the varying types of precipitation. The objective of this study is to better understand the formation of different types of winter precipitation (freezing rain, ice pellets, snow, slush, wet snow and refrozen wet snow) within the varying and interacting environmental conditions in many winter storms. To address this issue, a one‐dimensional cloud model utilizing a double‐moment bulk microphysics scheme has been developed. Temperature and moisture profiles favorable for the formation of different winter precipitation types were varied in a systematic manner in an environment where snow is falling continuously through a temperature inversion. The ensuing precipitation evolved as a result of the variations in atmospheric temperature and moisture arising from phase changes such as melting and freezing. This study underlines the often complex manner through which different precipitation types form. It also demonstrates that the formation of semimelted particles can have a profound effect on the evolution of precipitation types aloft and at the surface. Furthermore, some types of precipitation only form within a narrow range of environmental conditions.

ABSTRACT The relationship between plant diversity and animal diversity on a broadscale and its mechanisms are uncertain. In this study, we explored this relationship and its possible mechanisms using data from 186 nature reserves across China on species richness of vascular plants and terrestrial vertebrates, and climatic and topographical variables. We found significant positive correlations between species richness in almost all taxa of vascular plants and terrestrial vertebrates. Multiple regression analyses indicated that plant richness was a significant predictor of richness patterns for terrestrial vertebrates (except birds), suggesting that a causal association may exist between plant diversity and vertebrate diversity in China. The mechanisms for the relationships between species richness of plants and animals are probably dependent on vertebrate groups. For mammals (endothermic vertebrates), this relationship probably represents the integrated effects of plants on animals through trophic links (i.e. providing foods) and non‐trophic interactions (i.e. supplying habitats), whereas for amphibians and reptiles (ectothermic vertebrates), this may be a result of the non‐trophic links, such as the effects of plants on the resources that amphibians and reptiles require.

Explaining species richness patterns over broad geographic scales is a central issue of biogeography and macroecology. In this study, we took spatial autocorrelation into account and used terrestrial vertebrate species richness data from 211 nature reserves, together with climatic and topographical variables and reserve area, to explain terrestrial vertebrate species richness patterns in China and to test two climatically based hypotheses for animals. Our results demonstrated that species richness patterns of different terrestrial vertebrate taxa were predicted by the environmental variables used, in a decreasing order, as reptiles (56.5%), followed by amphibians (51.8%), mammals (42%), and birds (19%). The endothermic vertebrates (mammals and birds) were closely correlated with net primary productivity (NPP), which supports the productivity hypothesis, whereas the ectothermic vertebrates (amphibians and reptiles) were strongly associated with both water and energy variables but weakly with NPP, which supports the physiologically based ambient climate hypothesis. The differences in the dependence of endothermic and ectothermic vertebrates on productivity or ambient climate may be due in part to their different thermoregulatory mechanisms. Consistent with earlier studies, mammals were strongly and positively related to geomorphologic heterogeneity, measured by elevation range, implying that the protection of mountains may be especially important in conserving mammalian diversity.

ABSTRACT Aim  To document the patterns of fish species richness and their possible causes in China's lakes at regional and national scales. Location  Lakes across China. Methods  We compiled data of fish species richness, limnological characteristics and climatic variables for 109 lakes across five regions of China: East region, Northeast region, Southwest region, North‐Northwest region, and the Tibetan Plateau. Correlation analyses, regression models and a general linear model were used to explore the patterns of fish species richness. Results  At the national scale, lake altitude, energy availability (potential evapotranspiration, PET) and lake area explained 79.6% of the total variation of the lake fish species richness. The determinants of the fish richness pattern varied among physiographic regions. Lake area was the strongest predictor of fish species richness in the East and Southwest lakes, accounting for 22.2% and 82.9% of the variation, respectively. Annual PET explained 68.7% of the variation of fish richness in the Northeast lakes. Maximum depth, mineralization degree, and lake area explained 45.5% of the fish variation in the lakes of the North‐Northwest region. On the Tibetan Plateau, lake altitude was the first predictor variable, interpreting 32.2% of the variation. Main conclusions  Lake altitude was the most important factor explaining the variation of fish species richness across China's lakes, and accounted for 74.5% of the variation. This may stem in part from the fact that the lakes investigated in our study span the largest altitudinal range anywhere in the world. The effects of the lake altitude on fish species richness can be separated into direct and indirect aspects due to its collinearity with PET. We also found that the fish diversity and its determinants were scale‐dependent. Fish species richness was probably energy‐determined in the cold region, while it was best predicted by the lake area in the relatively geologically old region. The independent variables we used only explained a small fraction of the variations in the lake fish species richness in East China and the Tibetan Plateau, which may be due to the effects of human activity and historical events, respectively.

Abstract Viewed within a historical context, Asia has experienced dramatic land transformations, and currently more than 50% of Asian land area is under agriculture. The consequences of this transformation are manifold. Southeast Asia has the highest deforestation rate of any major tropical region. Many of the world's large rivers and lakes in Asia have been heavily degraded. About 11 of 19 world megacities with more than 10 million inhabitants are in Asia. These land use activities have resulted in substantial negative ecological consequences, including increased anthropogenic CO 2 emissions, deteriorated air and water quality, alteration of regional climate, an increase of disease and a loss of biodiversity. Although land use occurs at the local level, it has the potential to cause ecological impact across local, regional and global scales. Reducing the negative environmental impacts of land use change while maintaining economic viability and social acceptability is an major challenge for most developing countries in Asia.

Process-based carbon dynamic models are rarely validated against traditional forest growth and yield data and are difficult to use as a practical tool for forest management. To bridge the gap between empirical and process-based models, a simulation using a hybrid model of TRIPLEX1.0 was performed for the forest growth and yield of the boreal forest ecosystem in the Lake Abitibi Model Forest in northeastern Ontario. The model was tested using field measurements, forest inventory data, and the normal yield table. The model simulations of tree height and diameter at breast height (DBH) showed a good agreement with measurements for black spruce (Picea mariana (Mill.) BSP), jack pine (Pinus banksiana Lamb.), and trembling aspen (Populus tremuloides Michx.). The coefficients of determination (R 2 ) between simulated values and permanent sample plot measurements were 0.92 for height and 0.95 for DBH. At the landscape scale, model predictions were compared with forest inventory data and the normal yield table. The R 2 ranged from 0.73 to 0.89 for tree height and from 0.72 to 0.85 for DBH. The simulated basal area is consistent with the normal yield table. The R 2 for basal area ranged from 0.82 to 0.96 for black spruce, jack pine, and trembling aspen for each site class. This study demonstrated the feasibility of testing the performance of the process-based carbon dynamic model using traditional forest growth and yield data and the ability of the TRIPLEX1.0 model for predicting growth and yield variables. The current work also introduces a means to test model accuracy and its prediction of forest stand variables to provide a complement to empirical growth and yield models for forest management practices, as well as for investigating climate change impacts on forest growth and yield in regions without sufficient established permanent sample plots and remote areas without suitable field measurements.

Abstract The role and impact that boundary layer and shallow cumulus clouds have on the medium-range forecast of a large-scale weather system is discussed in this study. A mesoscale version of the Global Environmental Multiscale (GEM) atmospheric model is used to produce a 5-day numerical forecast of a midlatitude large-scale weather system that occurred over the Pacific Ocean during February 2003. In this version of GEM, four different schemes are used to represent (i) boundary layer clouds (including stratus, stratocumulus, and small cumulus clouds), (ii) shallow cumulus clouds (overshooting cumulus), (iii) deep convection, and (iv) nonconvective clouds. Two of these schemes, that is, the so-called MoisTKE and Kuo Transient schemes for boundary layer and overshooting cumulus clouds, respectively, have been recently introduced in GEM and are described in more detail. The results show that GEM, with this new cloud package, is able to represent the wide variety of clouds observed in association with the large-scale weather system. In particular, it is found that the Kuo Transient scheme is mostly responsible for the shallow/intermediate cumulus clouds in the rear portion of the large-scale system, whereas MoisTKE produces the low-level stratocumulus clouds ahead of the system. Several diagnostics for the rear portion of the system reveal that the role of MoisTKE is mainly to increase the vertical transport (diffusion) associated with the boundary layer clouds, while Kuo Transient is acting in a manner more consistent with convective stabilization. As a consequence, MoisTKE is not able to remove the low-level shallow cloud layer that is incorrectly produced by the GEM nonconvective condensation scheme. Kuo Transient, in contrast, led to a significant reduction of these nonconvective clouds, in better agreement with satellite observations. This improved representation of stratocumulus and cumulus clouds does not have a large impact on the overall sea level pressure patterns of the large-scale weather system. Precipitation in the rear portion of the system, however, is found to be smoother when MoisTKE is used, and significantly less when the Kuo Transient scheme is switched on.

Abstract A total of 11,612 black spruce trees were measured from permanent sample plots across the boreal and central regions of Ontario and were used to fit the well-known Chapman-Richards growth model at provincial, regional, and ecoregional scales. The results suggest that the height-diameter relationships of black spruce vary with different geographic regions and scales. There were significant variations in height-diameter relationships for black spruce between boreal and central regions as well as among some of the seven ecoregions. The ecoregion-based height-diameter models presented here will provide more accurate predictions for tree height and, consequently, tree volume than these models developed at both provincial and regional scales. Furthermore, the heterogeneity of tree species should be considered in developing and applying ecoregion-based height-diameter models for predicting local tree height.

Individual-tree models of five-year basal area growth were developed for jack pine (Pinus banksiana Lamb.) and black spruce (Picea mariana (Mill.) BSP) in northern Ontario. Tree growth data were collected from long-term permanent plots of pure and mixed stands of the two species. The models were fitted using mixed model methods due to correlated remeasurements of tree growth over time. Since the data covered a wide range of stand ages, stand conditions and tree sizes, serious heterogeneous variances existed in the data. Therefore, the coefficients of the final models were obtained using weighted regression techniques. The models for the two species were evaluated across 4-cm diameter classes using independent data. The results indicated (1) the models of jack pine and black spruce produced similar prediction errors and biases for intermediate-sized trees (1228 cm in tree diameter), (2) both models yielded relatively large errors and biases for larger trees (> 28 cm) than those for smaller trees, and (3) the jack pine model produced much larger errors and biases for small-sized trees (< 12 cm) than did the black spruce model. Key words: mixed models, repeated measures, model validation