全球木本植物叶片硅钙生态化学计量学特征

ABSTRACTAim The objectives of this study were to determine the relationships between climatic factors and litterfall in coniferous and broadleaf forests in Eurasia and to explore the difference in litterfall between coniferous and broadleaf forests as related to climate at a continental scale.Location We have used data from across Eurasia.Methods The relationships between litterfall and climatic factors were examined using linear regression analysis of a compilation of published data from coniferous and broadleaf forests in Eurasia.Results The relationships between litterfall and climatic factors show that in the temperate, subtropical, and tropical areas, broadleaf forests had higher litterfall than coniferous ones, whilst the opposite was found for boreal forests. Combining all climatic zones, a multiple regression analysis using annual mean temperature (T) and annual precipitation (P) as independent variables gave an adjusted R2 () of 0.272 for total litterfall in coniferous forests (n = 199, P < 0.001), 0.498 for broadleaf litterfall (n = 240, P < 0.001), and 0.535 for combined coniferous and broadleaf litterfall (n = 439, P < 0.001). The linear models for broadleaf stands have significantly higher coefficients for T and P than those for coniferous ones but the intercepts were similar. Thus, litterfall in broadleaf forests increased faster with T and P than that in coniferous forests. Further, a transformation of temperature and precipitation to relative units showed that a relative‐unit change in T had a larger impact than P on total litterfall in broadleaf forests. The results indicate that at a continental scale, climatic controls over litterfall differ between coniferous and broadleaf forests.Conclusions A relative unit change in annual mean temperature has a greater effect on litterfall compared to the same change in annual precipitation across the Eurasian forests. Further, the higher response to T for broadleaf forests indicates a difference in climate control between coniferous and broadleaf forests at a continental scale, and consequently different litterfall responses to climate change.

Root:shoot ratios across China’s forests: Forest type and climatic effects

Understanding the relationship between the spatial distribution of precipitation and crop yields on large scales (i.e., county, state, regional) while accounting for the spatial non-stationarity can help managers to better evaluate the long-term trends in agricultural productivity to make better assessments in food security, policy decisions, resource assessments, land and water resources enhancement, and management decisions. A relatively new technique, geographically weighted regression (GWR), has the ability to account for spatial non-stationarity with space. While its application is growing in other scientific disciplines (i.e., social sciences), the application of this new technique in agricultural settings has not been practiced. The geographic information system (GIS), along with two different statistical techniques [GWR and conventional ordinary least square regression (OLS)], was utilized to analyze the relationships between various precipitation categories and irrigated and rainfed maize and soybean yields for all 93 counties in Nebraska from 1996 to 2008. Precipitation was spatially interpolated in ArcGIS using a spline interpolation technique with zonal statistics. Both measured and GWR- and OLS-predicted yields were correlated to spatially interpolated annual (January 1 to December 31), seasonal (May 1 to September 30), and monthly (May, June, July, August, and September) precipitation for each county. Statewide average annual precipitation in Nebraska from 1996 to 2008 was 564 mm, with a maximum of 762 mm and minimum of 300 mm. Mean precipitation decreased gradually from May to September during the growing season. County average yields followed the same temporal trends as precipitation. When the OLS regression model was used, there was a general trend of linear correlation between observed yield and long-term average mean annual total precipitation with a varying coefficient of determination (R2). For rainfed crops, 67% of the variability in mean yield was explained by the mean annual precipitation. About 23% and 17% of the variability in mean yield was explained by mean annual precipitation for irrigated maize and soybean, respectively. However, the performance of the GWR technique in predicting the yields from spatially interpolated precipitation for irrigated and rainfed maize and soybean was significantly better than the performance of the OLS model. For both rainfed maize and soybean, 77% to 80% of the variation in yield was explained by the mean annual precipitation alone. For irrigated crops, 42% of the variation in the yield was explained by the mean annual precipitation. For rainfed crops, there was a strong correlation between seasonal precipitation and yield, with R2 values of 0.73 and 0.76 for maize and soybean, respectively. The mean annual total precipitation was a better predictor of rainfed maize yield than rainfed soybean yield. On a statewide average, July precipitation as a predictor had the greatest correlation with yields of both maize and soybean. June, July, and August precipitation had greater impact on maize yield than on soybean under rainfed conditions due to more sensitivity of maize to water stress than soybean. For irrigated yields, July precipitation had more impact on soybean yield than on maize. The performance of the GWR technique was superior to the OLS model in analyzing the relationship between yield and precipitation. The superiority of the GWR technique to OLS is mainly due to its ability to account for the impact of spatial non-stationarity on the precipitation vs. yield relationships.

Knowledge of soil organic matter (SOM) dynamics following deforestation or reforestation is essential for evaluating carbon (C) budgets and cycle at regional or global scales. Worldwide land-use changes involving conversion of vegetation with different photosynthetic pathways (e.g. C3 and C4 ) offer a unique opportunity to quantify SOM decomposition rate and its response to climatic conditions using stable isotope techniques. We synthesized the results from 131 sites (including 87 deforestation observations and 44 reforestation observations) which were compiled from 36 published papers in the literatures as well as our observations in China's Qinling Mountains. Based on the 13 C natural abundance analysis, we evaluated the dynamics of new and old C in top soil (0-20cm) following land-use change and analyzed the relationships between soil organic C (SOC) decomposition rates and climatic factors. We found that SOC decomposition rates increased significantly with mean annual temperature and precipitation in the reforestation sites, and they were not related to any climatic factor in deforestation sites. The mean annual temperature explained 56% of variation in SOC decomposition rates by exponential model (y=0.0014e0.1395x ) in the reforestation sites. The proportion of new soil C increased following deforestation and reforestation, whereas the old soil C showed an opposite trend. The proportion of new soil C exceeded the proportion of old soil C after 45.4years' reforestation and 43.4years' deforestation, respectively. The rates of new soil C accumulation increased significantly with mean annual precipitation and temperature in the reforestation sites, yet only significantly increased with mean annual precipitation in the deforestation sites. Overall, our study provides evidence that SOC decomposition rates vary with temperature and precipitation, and thereby implies that global warming may accelerate SOM decomposition.

Eggs of Aedes triseriatus mosquitoes are stimulated to hatch when inundated with water, but only a small fraction of eggs from the same batch will hatch for any given stimulus. Similar hatching or germination patterns are observed in desert plants, copepods, rotifers, insects, and many other species. Bet hedging theory suggests that parents stagger offspring emergence into vulnerable life history stages in order to avoid catastrophic reproductive failures. For Ae. triseriatus, a treehole breeding mosquito, immediate hatching of an entire clutch leaves all of the parent's progeny vulnerable to extinction in the event of a severe drought. Natural selection has likely favored parents that pursued a bet hedging strategy where the risk of reproductive failure is distributed over time. Considering treehole mosquitoes, bet hedging theory could be used to predict that hatch delay would be positively correlated with the likelihood of drought. To test this prediction, we collected Ae. triseriatus from habitats that varied widely in mean annual precipitation and exposed them to several hatch stimuli in the laboratory. Here we report that, as predicted, Ae. triseriatus eggs from high precipitation regions showed less hatch delay than areas of low precipitation. This strategy probably allows Ae. triseriatus to cope with the wide variety of climatic conditions that it faces in its extensive geographical range.

The infiltration of streamflow is potential recharge to alluvial-basin aquifers at or near mountain fronts in southern New Mexico. Data for 13 streamflow-gaging stations were used to determine a relation between mean annual stream- flow and basin and climatic conditions. Regression analysis was used to develop an equation that can be used to estimate mean annual streamflow on the basis of drainage areas and mean annual precipi- tation. The average standard error of estimate for this equation is 46 percent. Regression analysis also was used to develop an equation to estimate mean annual streamflow on the basis of active- channel width. Measurements of the width of active channels were determined for 6 of the 13 gaging stations. The average standard error of estimate for this relation is 29 percent. Stream- flow estimates made using a regression equation based on channel geometry are considered more reliable than estimates made from an equation based on regional relations of basin and climatic conditions. The sample size used to develop these relations was small, however, and the reported standard error of estimate may not represent that of the entire population. Active-channel-width measurements were made at 23 ungaged sites along the Rio Grande upstream from Elephant Butte Reservoir. Data for additional sites would be needed for a more comprehensive assessment of mean annual streamflow in southern New Mexico.

This study analyzes the changes in the surface area of each forest cover, based on temperature data analysis and satellite imagery as the basic methods for the impact assessment of climate change on regional units. Furthermore, future changes in the forest cover are predicted using the double exponential smoothing method. The results of the study have shown an overall increase in annual mean temperature in the studied region since 1990, and an especially increased rate in winter and autumn compared to other seasons. The multi-temporal analysis of the changes in the forest cover using satellite images showed a large decrease of coniferous forests, and a continual increase in deciduous forests and mixed forests. Such changes are attributed to the increase in annual mean temperature of the studied regions. The analysis of changes in the surface area of each forest cover using the statistical data displayed similar tendencies as that of the forest cover categorizing results from the satellite images. Accordingly, rapid changes in forest cover following the increase of temperature in the studied regions could be expected. The results of the study of the forest cover surface using the double exponential smoothing method predict a continual decrease in coniferous forests until 2050. On the contrary, deciduous forests and mixed forests are predicted to show continually increasing tendencies. Deciduous forests have been predicted to increase the most in the future. With these results, the data on forest cover can be usefully applied as the main index for climate change. Further qualitative results are expected to be deduced from these data in the future, compared to the analyses of the relationship between tree species of forest and climate factors.

ABSTRACTAim Senesced‐leaf litter plays an important role in the functioning of terrestrial ecosystems. While green‐leaf nutrients have been reported to be affected by climatic factors at the global scale, the global patterns of senesced‐leaf nutrients are not well understood.Location Global.Methods Here, bringing together a global dataset of senesced‐leaf N and P spanning 1253 observations and 638 plant species at 365 sites and of associated mean climatic indices, we describe the world‐wide trends in senesced‐leaf N and P and their stoichiometric ratios.Results Concentration of senesced‐leaf N was highest in tropical forests, intermediate in boreal, temperate, and mediterranean forests and grasslands, and lowest in tundra, whereas P concentration was highest in grasslands, lowest in tropical forests and intermediate in other ecosystems. Tropical forests had the highest N : P and C : P ratios in senesced leaves. When all data were pooled, N concentration significantly increased, but senesced‐leaf P concentration decreased with increasing mean annual temperature (MAT) and mean annual precipitation (MAP). The N : P and C : P ratios also increased with MAT and MAP, but C : N ratios decreased. Plant functional type (PFT), i.e. life‐form (grass, herb, shrub or tree), phylogeny (angiosperm versus gymnosperm) and leaf habit (deciduous versus evergreen), affected senesced‐leaf N, P, N : P, C : N and C : P with a ranking of senesced‐leaf N from high to low: forbs ≈ shrubs ≈ trees > grasses, while the ranking of P was forbs ≈ shrubs ≈ trees < grasses. The climatic trends of senesced‐leaf N and P and their stoichiometric ratios were similar between PFTs.Main conclusions Globally, senesced‐leaf N and P concentrations differed among ecosystem types, from tropical forest to tundra. Differences were significantly related to global climate variables such as MAT and MAP and also related to plant functional types. These results at the global scale suggest that nutrient feedback to soil through leaf senescence depends on both the climatic conditions and the plant composition of an ecosystem.

The influence of climate on landscape evolution in natural settings remains debated. Here, we focus on tropical hotspot volcanic islands because they exhibit relatively uniform lithology and experience significant precipitation and climate gradients. Furthermore, intermittent volcanic flows effectively “reset” the landscape that begins to evolve post-eruption. Thus, we can constrain initial conditions by reconstructing the initial geometry of radiometrically dated volcanic flows. We constrain landscape evolution through time in several volcanic islands with strong climate gradients to assess the role of climate on incision. We perform topographic reconstructions to calculate long-term basin-averaged erosion rates in two islands of the Réunion hotspot (Réunion, Mauritius) and compile published erosion rates on Réunion and Kaua’i (Hawaii hotspot). We define the time since incision started as the age of the surface incised lava flow. To calibrate incision parameters on all three islands, we use the stream power model and apply a data-driven Bayesian approach to obtain the erodibility, K, the drainage area exponent, m, and the slope exponent, n. We also calculate a normalized erodibility index, Kn, using n = 1 to directly compare results among the different study sites. Erosion rates of Réunion Island range from 9.9 ± 0.5 mm/yr to 5.2 x 10-3 ± 2 x 10-4 mm/yr and erosion rates in Mauritius Island range from 6.5 x 10-2 ± 8 x 10-3 mm/yr to 5.1 x 10-3 ± 4 x 10-4 mm/yr. Incision efficiency seems to decrease with time since incision started from 63 ka to ~300 ka and then does not vary significantly with time since incision started from ~300 ka to 4300 ka. This is likely due to the covariation between the age of volcanism repaving and precipitation rates on Réunion, which is related to the configuration of the island’s two volcanoes – the active Piton de la Fournaise located on the windward side and the dormant Piton des Neiges on the center and leeward side. Our empirical calibration of the stream power law shows high dispersion in n and Kn on each individual island. m ranges from 0.2 to 2.9, and Kn ranges from 2.3 x 10-7 to 9.8 x 10-4 m1-2m/yr. For Réunion, we identify a positive trend between mean annual precipitation and erosion rates, and between mean annual precipitation and Kn, for low to moderate erosion rates (

Climate dependence of feldspar weathering in shale soils along a latitudinal gradient

Corrigendum

Abiotic factors vary along altitudinal gradients, and this may influence plant morphology, physiology and function. This study aimed to test the hypothesis that leaf δ13C—a common proxy for water use efficiency—was indirectly influenced by morphological adjustments with changing climatic factors along an altitudinal gradient on Mount Kenya. We sampled leaves of Dendrosenecio keniensis and Lobelia gregoriana using seventy‐two 10 × 10 m plots situated every 100 m starting from 3600 to 4300 m. We determined leaf δ13C using stable isotope mass spectrometry. We also quantified the following morphological factors; leaf area, leaf mass per area, specific leaf area and leaf thickness. Climate data included mean annual temperature and precipitation, diurnal temperature range and water vapor pressure. Our results revealed that there was a leaf δ13C enrichment of 1.76 ‰ km−1 and 1.62 ‰ km−1 with altitude for D. keniensis and L. gregoriana, respectively. Leaf δ13C was enrichment by 0.01 ‰ mm−1 with mean annual precipitation along the altitude gradient for D. keniensis and 0.02 ‰ mm−1 for L. gregoriana. D. keniensis and L. gregoriana have high‐water use efficiency, an adaptation for surviving near freezing alpine temperatures and high‐diurnal range. Leaf δ13C exhibited a depletion of −0.37 ‰ per °C increase of mean annual temperature along the altitude gradient for D. keniensis and −0.34 ‰ per °C increase for L. gregoriana. Our results also showed a negative relationship between pCO2 and leaf δ13C and positive relationship between pCO2 and ∆13C for both species. Low temperatures led to the increase in leaf thickness and specific leaf area for these two species, factors that influenced leaf δ13C and ∆13C.Abstract in Chinese is available with online material.

Atmospheric deposition and above-ground cycling of sulfur (S) were evaluated in adjacent deciduous and coniferous forests at the Panola Mountain Research Watershed (PMRW), Georgia, U.S.A. Total atmospheric S deposition (wet plus dry) was 12.9 and 12.7 kg ha-1 yr-1 for the deciduous and coniferous forests, respectively, from October 1987 through November 1989. Dry deposition contributes more than 40% to the total atmospheric S deposition, and SO2 is the major source (∼55%) of total dry S deposition. Dry deposition to these canopies is similar to regional estimates suggesting that 60-km proximity to emission sources does not noticeably impact dry deposition at PMRW. Below-canopy S fluxes (throughfall plus stemflow) in each forest are 37% higher annually in the deciduous forest than in the coniferous forest. An excess in below-canopy S flux in the deciduous forest is attributed to leaching and higher dry deposition than in the coniferous forest. Total S deposition to the forest floor by throughfall, stemflow and litterfall was 2.4 and 2.8 times higher in the deciduous and coniferous forests, respectively, than annual S growth requirement for foliage and wood. Although S deposition exceeds growth requirement, more than 95% of the total atmospheric S deposition was retained by the watershed in 1988 and 1989. The S retention at PMRW is primarily due to SO42- adsorption by iron oxides and hydroxides in watershed soils. The S content in white oak and loblolly pine boles have increased more than 200% in the last 20 yr, possibly reflecting increases in emissions.

BackgroundForest above-ground biomass (AGB) accumulation is widely considered an important tool for mitigating climate change. However, the general pattern of forest AGB accumulation associated with age and climate gradients across various forest functional types at a global scale have remained unclear. In this study, we compiled a global AGB data set and applied a Bayesian statistical model to reveal the age-related dynamics of forest AGB accumulation, and to quantify the effects of mean annual temperature and annual precipitation on the initial AGB accumulation rate and on the saturated AGB characterizing the limit to AGB accumulation.ResultsThe results of the study suggest that mean annual temperature has a significant positive effect on the initial AGB accumulation rate in needleleaf evergreen forest, and a negative effect in broadleaf deciduous forest; whereas annual precipitation has a positive effect in broadleaf deciduous forest, and negative effect in broadleaf evergreen forest. The positive effect of mean annual temperature on the saturated AGB in broadleaf evergreen forest is greater than in broadleaf deciduous forest; annual precipitation has a greater negative effect on the saturated AGB in deciduous forests than in evergreen forests. Additionally, the difference of AGB accumulation rate across four forest functional types is closely correlated with the forest development stage at a given climate.ConclusionsThe contrasting responses of AGB accumulation rate to mean annual temperature and precipitation across four forest functional types emphasizes the importance of incorporating the complexity of forest types into the models which are used in planning climate change mitigation. This study also highlights the high potential for further AGB growth in existing evergreen forests.

The investigation of relationship between rural settlement density, size, spatial distribution and its geophysical parameters of China using Landsat TM images