Water inputs across a tropical montane landscape in Veracruz,Mexico: synergistic effects of land cover,rain and fog seasonality,and interannual precipitation variability

Land‐cover change can alter the spatiotemporal distribution of water inputs to mountain ecosystems, an important control on land‐surface and land‐atmosphere hydrologic fluxes. In eastern Mexico, we examined the influence of three widespread land‐cover types, montane cloud forest, coffee agroforestry, and cleared areas, on total and net water inputs to soil. Stand structural characteristics, as well as rain, fog, stemflow, and throughfall (water that falls through the canopy) water fluxes were measured across 11 sites during wet and dry seasons from 2005 to 2008. Land‐cover type had a significant effect on annual and seasonal net throughfall (NTF <0=canopy water retention plus canopy evaporation; NTF >0=fog water deposition). Forest canopies retained and/or lost to evaporation (i.e. NTF<0) five‐ to 11‐fold more water than coffee agroforests. Moreover, stemflow was fourfold higher under coffee shade than forest trees. Precipitation seasonality and phenological patterns determined the magnitude of these land‐cover differences, as well as their implications for the hydrologic cycle. Significant negative relationships were found between NTF and tree leaf area index (R²=0.38, P<0.002), NTF and stand basal area (R²=0.664, P<0.002), and stemflow and epiphyte loading (R²=0.414, P<0.001). These findings indicate that leaf and epiphyte surface area reductions associated with forest conversion decrease canopy water retention/evaporation, thereby increasing throughfall and stemflow inputs to soil. Interannual precipitation variability also altered patterns of water redistribution across this landscape. Storms and hurricanes resulted in little difference in forest‐coffee wet season NTF, while El Niño Southern Oscillation was associated with a twofold increase in dry season rain and fog throughfall water deposition. In montane headwater regions, changes in water delivery to canopies and soils may affect infiltration, runoff, and evapotranspiration, with implications for provisioning (e.g. water supply) and regulating (e.g. flood mitigation) ecosystem services.     

A new species of Galearis (Orchidinae: Orchidaceae) from Sichuan,China

A new species, Galearis huanglongensis Q.W.Meng & Y.B.Luo, is described and illustrated. It is similar to Galearis cyclochila (Franch. & Sav.) Soó and Galearis diantha (Schltr.) P.F.Hunt, but differs in having a short spur, two elliptical lateral stigma lobes and distinctly separated bursicles. This new species is known only from the type locality, the Huanglong Valley, Songpan County, western Sichuan, China, growing amongst mosses under alpine shrubs at an elevation of about 3000 m. Based on two years of observations of its population size, the species was categorized as critically endangered CR (B1a, B2a) according to the World Conservation Union (IUCN) Red List Categories and Criteria, Version 3.1. The micromorphology of pollinia and seeds was observed by scanning electron microscopy and compared with that of G. cyclochila and G. diantha. The results supported G. huanglongensis Q.W.Meng & Y.B.Luo as a new species. © 2008 The Linnean Society of London, Botanical Journal of the Linnean Society, 2008, 158 , 689–695.     

Compatible Models of Carbon Content of Individual Trees on a Cunninghamia lanceolata Plantation in Fujian Province,China

We tried to establish compatible carbon content models of individual trees for a Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) plantation from Fujian province in southeast China. In general, compatibility requires that the sum of components equal the whole tree, meaning that the sum of percentages calculated from component equations should equal 100%. Thus, we used multiple approaches to simulate carbon content in boles, branches, foliage leaves, roots and the whole individual trees. The approaches included (i) single optimal fitting (SOF), (ii) nonlinear adjustment in proportion (NAP) and (iii) nonlinear seemingly unrelated regression (NSUR). These approaches were used in combination with variables relating diameter at breast height (D) and tree height (H), such as D, D²H, DH and D&H (where D&H means two separate variables in bivariate model). Power, exponential and polynomial functions were tested as well as a new general function model was proposed by this study. Weighted least squares regression models were employed to eliminate heteroscedasticity. Model performances were evaluated by using mean residuals, residual variance, mean square error and the determination coefficient. The results indicated that models with two dimensional variables (DH, D²H and D&H) were always superior to those with a single variable (D). The D&H variable combination was found to be the most useful predictor. Of all the approaches, SOF could establish a single optimal model separately, but there were deviations in estimating results due to existing incompatibilities, while NAP and NSUR could ensure predictions compatibility. Simultaneously, we found that the new general model had better accuracy than others. In conclusion, we recommend that the new general model be used to estimate carbon content for Chinese fir and considered for other vegetation types as well.