Distributions of invasive species are commonly predicted with species distribution models that build upon the statistical relationships between observed species presence data and climate data. We used field observations, climate station data, and Maximum Entropy species distribution models for 13 invasive plant species in the United States, and then compared the models with inputs from a General Circulation Model (hereafter GCM-based models) and a downscaled Regional Climate Model (hereafter, RCM-based models). We also compared species distributions based on either GCM-based or RCM-based models for the present (1990–1999) to the future (2046–2055).
RCM-based species distribution models replicated observed distributions remarkably better than GCM-based models for all invasive species under the current climate. This was shown for the presence locations of the species, and by using four common statistical metrics to compare modeled distributions. For two widespread invasive taxa (Bromus tectorum or cheatgrass, and Tamarix spp. or tamarisk), GCM-based models failed miserably to reproduce observed species distributions. In contrast, RCM-based species distribution models closely matched observations. Future species distributions may be significantly affected by using GCM-based inputs. Because invasive plants species often show high resilience and low rates of local extinction, RCM-based species distribution models may perform better than GCM-based species distribution models for planning containment programs for invasive species.
Natural layered rocks subjected to layer-parallel extension typically develop an array of opening-mode fractures with a remarkably regular spacing. This spacing often scales with layer thickness, and it decreases as extension increases until fracture saturation is reached. To increase the understanding of how these opening-mode fractures form in layered rocks, a series of 2D numerical simulations are performed to investigate the infilling process of fractures subjected to different driving forces. Numerical results illustrate that any one of the following could be considered as a driving force behind the propagation of infilling fractures: thermal effect, internal fluid pressure, direct extension loading, or pure compressive loading. Fracture spacing initially decreases with loading process, and at a certain ratio of fracture spacing to layer thickness, no new fractures nucleate (saturated). Both an increase in the opening of the infilled fractures and interface delamination are observed as mechanisms that accommodate additional strain. Interface debonding stops the transition of stress from the neighboring layers to the embedded central layer, which may preclude further infilling of new fractures. Whatever the driving force is, a large overburden stress and a large elastic contrast between the stiff and soft layers (referred to as a central or fractured layer and the top and bottom layers) are key factors favoring the development of tensile stress around the infilled fractures in the models. Fracture spacing is expected to decrease with increasing overburden stress. Numerical results highlight the fracturing process developed in heterogeneous and layered sedimentary rocks which provides supplementary information on the stress distribution and failure-induced stress redistribution., It also shows, in detail, the propagation of the fracture zone and the interaction of the fractures, which are impossible to observe in field and are difficult to consider with static stress analysis approaches.
China has experienced urbanization at an unprecedented rate over the past decades. Against this background, this paper demonstrates the multi-level spatiotemporal urban sprawl process from 1983 to 2007 on the perspective of urban agglomeration with a case study in Southern Jiangsu. Based on a combination of eight rounds of satellite images from 1983 to 2007, the presented results suggest the following three main findings: (1) At the prefecture-city level, the urban sprawl in Southern Jiangsu has presented significantly divergent growth patterns, with more than half of this vast growth occurring in the Suzhou prefecture-level city. (2) At the county level, clear spatial differentiations exist in the direction of the urban sprawl. The centroids of all county seats in the Suzhou and Wuxi prefecture-level cities have an eastward tendency (Shanghai oriented), while those of the county seats in the Changzhou prefecture-level city tend to be westward (Nanjing oriented). (3) At the township level, two convergent groups have gradually formed over time; namely, the low density urban zone in the western hilly land and the high density urban zone around the three central downtown areas. The urban areas close to urban cores tend to merge, showing a high-density convergent growth pattern, as do the western and southwestern townships in Southern Jiangsu, showing a low-density convergent growth pattern. All of these findings may be valuable for researchers and local authorities in providing reference for regional coordinated growth, environmental management, and urban planning decision-making.
Crop models are robust tools for simulating the impact of climate change on rice development and production, but are usually designed for specific stations and varieties. This study focuses on a more adaptable model called Simulation Model for Rice-Weather Relations (SIMRIW). The model was calibrated and validated in major rice production regions over China, and the parameters that most affect the model’s output were determined in sensitivity analyses. These sensitive parameters were estimated in different ecological zones. The simulated results of single and double rice cropping systems in different ecological zones were then compared. The accuracy of SIMRIW was found to depend on a few crucial parameters. Using optimized parameters, SIMRIW properly simulated the rice phenology and yield in single and double cropping systems in different ecological zones. Some of the parameters were largely dependent on ecological zone and rice type, and may reflect the different climate conditions and rice varieties among ecological zones.
Spatially explicit simulation of land use change is the basis for estimating the effects of land use and cover change on energy fluxes, ecology and the environment. At the pixel level, logistic regression is one of the most common approaches used in spatially explicit land use allocation models to determine the relationship between land use and its causal factors in driving land use change, and thereby to evaluate land use suitability. However, these models have a drawback in that they do not determine/allocate land use based on the direct relationship between land use change and its driving factors. Consequently, a multinomial logistic regression method was introduced to address this flaw, and thereby, judge the suitability of a type of land use in any given pixel in a case study area of the Jiangxi Province, China. A comparison of the two regression methods indicated that the proportion of correctly allocated pixels using multinomial logistic regression was 92.98%, which was 8.47% higher than that obtained using logistic regression. Paired t-test results also showed that pixels were more clearly distinguished by multinomial logistic regression than by logistic regression. In conclusion, multinomial logistic regression is a more efficient and accurate method for the spatial allocation of land use changes. The application of this method in future land use change studies may improve the accuracy of predicting the effects of land use and cover change on energy fluxes, ecology, and environment.
Although many of the first-generation Digital Earth systems have proven to be quite useful for the modeling and visualization of geospatial objects relevant to the Earth’s surface and near-surface, they were not designed for the purpose of modeling and application in geological or atmospheric space. There is a pressing need for a new Digital Earth system that can process geospatial information with full dimensionality. In this paper, we present a new Digital Earth system, termed SolidEarth, as an alternative virtual globe for the modeling and visualization of the whole Earth space including its surface, interior, and exterior space. SolidEarth consists of four functional components: modeling in geographical space, modeling in geological space, modeling in atmospheric space, and, integrated visualization and analysis. SolidEarth has a comprehensive treatment to the third spatial dimension and a series of sophisticated 3D spatial analysis functions. Therefore, it is well-suited to the volumetric representation and visual analysis of the inner/outer spheres in Earth space. SolidEarth can be used in a number of fields such as geoscience research and education, the construction of Digital Earth applications, and other professional practices of Earth science.
The accurate radiocarbon dating of loess-soil sequences plays an essential role in the reconstruction of the environmental and climatic changes in continental settings during the last glaciation and Holocene. However, our knowledge about the reliability of radiocarbon ages of various fractions of soil and loess samples is still insufficient. Here, we present our study results on radiocarbon ages based on bulk organic matter, humin fraction, and carbonate of samples collected from a loess-paleosol section in the western Chinese Loess Plateau. We compare these observations with the optically stimulated luminescence ages and charcoal radiocarbon ages to evaluate the reliability of these fractions. We observed that the radiocarbon ages of humin fraction are very close to those of charcoal and are consistent with the optically stimulated luminescence ages within the experimental errors. We observed a significant deviation in the radiocarbon ages of carbonate and bulk organic matter from those of charcoal and optically stimulated luminescence ages, likely due to the dilution of these fractions during the pedogenetic process. Our results reveal that, except for charcoal, the humin fraction may yield reliable 14C ages for the Chinese loess-soil sequence.
The Dongjiang River, one of the tributaries of the Pearl River, serves as the critical water source for Guangdong Province and the District of Hong Kong in China. In this study, the change trend and change points of flow at three main gaging stations in the Dongjiang River were analyzed using the nonparametric Mann-Kendall test and Pettitt-Mann-Whitney change-point statistics. Flow regime changes in the Dongjiang River were quantified by using both the Indicators of Hydrologic Alteration (IHA) parameters and eco-statistics, such as ecosurplus and ecodeficit. It was found that the change trend for annual median flow in the Dongjiang River increased over the past 60 years, with the major change occurring sometime between 1970 and 1974. IHA analyses showed that the magnitude of monthly flow decreased during the flood period, but increased greatly during the dry period. The median date of the one-day minimum flow moved ahead, and the duration of low pulse for the Dongjiang River was reduced significantly because of reservoir construction and operations. The IHA-based Dundee Hydrological Regime Alteration Method analysis indicated that all three stations have experienced a moderate risk of impact since 1974. The eco-statistical analyses showed that the majority of the flows appeared to be ecosurplus at all three locations after 1974, while flows with less than 30%, or higher exceedance probability, had ecodeficit in the summer flood period due to heavy reservoir operations.
Analyses results of total peatland area changes in the southern Altay Mountain region over the past 20 years are discussed in this paper. These analyses were based on remote sensing (RS) and geographical information system (GIS) studies. Possible control methods are evaluated by comparing these results to other regional records and climate data. The area of the peatland zones was calculated by overlaying a peatland layer of Landsat TM (Thematic Map) image constructed by using supervised classification with a layer of slope based on a digital elevation model (DEM). The results show that slope layer is crucial to improving the accuracy of peatland extracted from TM images. The peatland area of the Altay Mountains increased from 931.5 km2 in 1990 to 977.7 km2 in 2010. This trend is consistent with the climate change in this region, due in part to increasing temperatures and precipitation, suggesting possible climate controls on peatland expansion. The increase in the peatland area in the Altay Mountains over the last 20 years has been influenced by the westerlies. Alternatively, changes in the largest highland peatland area of the Zoige Basin, located in the eastern Tibetan Plateau have been influenced by the intensity of the Asian summer monsoons. In addition to increased temperatures, decreased precipitation in the Zoige Basin and increased precipitation in the Altay Mountains, due to varied patterns of atmospheric circulation, are the probable causes for driving the change differences in these two peatland areas.
Testate amoebae are sensitive indicators of substrate moisture in peatlands. Over the last decades, they have been studied to reconstruct hydrological changes since the Holocene. However, these studies have been geographically restricted to North America and Europe. We conducted the first investigation of testate amoebae on the largest continental fresh water wetland in the Sanjiang Plain, China. The objectives of this study were to provide baseline data on the ecology of testate amoebae in the peatlands of Northeast China and to assess the potential of using them as environmental indicators in this ecosystem. We examined modern testate amoeba assemblages and species-environmental relationships at 46 microsites within 5 waterlogged depressions. The environmental parameters measured included: depth to water table, pH, and loss on ignition. The results showed that the dominant species were Trinema complanatum type, Euglypha rotunda type, Euglypha strigosa type, and Centropyxis cassis type. Redundancy analysis demonstrates that water table depth has the most important effect on testate amoeba assemblages, explaining 16.7% (p=0.002) of the total variance. pH was not a statistically significant factor for testate amoeba assemblages. Weighted averaging and weighted averaging partial least squares models were used to build transfer functions for depth to water table. The best performing transfer function was generated by the weighted averaging partial least squares model with an r2LOSO of 0.62 and RMSEPLOSO of 6.96 cm. Results indicate that testate amoebae in waterlogged depression peatland have the potential to be used as indicators for hydrological changes and for palaeohydrologic reconstructions in the Sanjiang Plain.
Changes in the levels of biogenic silica (BSi%) in lake sediments have been widely used in order to study lake productivity and palaeoclimatic changes. However, the provenance of biogenic silica (BSi) needs to be investigated for each lake, especially for large lakes, as does the relationship between levels of BSi and relevant environmental factors. In this study, we measured the percentage of BSi contained in lake sediments, river sediments, and surface soils within the the Lake Qinghai catchment, and compared the quantities and shapes of diatoms and phytoliths before and after the extraction processes. The results suggest that BSi in lake sediments is primarily derived from endogenous diatoms; therefore, BSi levels can be used to reflect the changes in primary productivity within the lake. Further comparisons showed that on long-term timescales, the variations in BSi% are generally consistent with those in total organic carbon (TOC) and grain size, reflecting the dominant impacts of precipitation on primary productivity in Lake Qinghai. On short-term timescales, however, the relationship between BSi% and TOC and that between BSi% and grain size are not clear or stable. For example, BSi% sometimes covaried with grain size, but it was sometimes out of phase with or even inversely related to grain size. We speculate that both climate and environmental processes, such as the dilution effect, influence short-term BSi% and its related environmental significance. As a result, BSi% should be used selectively as an indicator of climatic changes on different time scales.
Environmental influences upon energy balance in areas of different vegetation types (i.e., forest at Kog-Ma in Thailand and at Yakutsk in Russia, grassland at Amdo in Chinese Tibet and at Arvaikheer in Mongolia, and mixed farmland at Tak in Thailand) in the GEWEX Asian Monsoon Experiment were investigated. The sites we investigated are geographically and climatologically different; and consequently had quite large variations in temperature (T), water vapor pressure deficit (VPD), soil moisture (SM), and precipitation (PPT). During May–October, the net radiation flux (R n) (in W·m–2) was 406.21 at Tak, 365.57 at Kog-Ma, 390.97 at Amdo, 316.65 at Arvaikheer, and 287.10 at Yakutsk. During the growing period, the R n partitioned into latent heat flux (λE/R n) was greater than that partitioned into sensible heat flux (H/R n) at Tak and at Kog-Ma. In contrast, λE/R n was lower than H/R n at Arvaikheer, H/R n was less than λE/R n between DOY 149 and DOY 270 at Amdo, and between DOY 165 and DOY 235 at Yakutsk. The R n partitioned into ground heat flux was generally less than 0.15. The short-wave albedo was 0.12, 0.18, and 0.20 at the forest, mixed land, and grass sites, respectively.
At an hourly scale, energy partitions had no correlation with environmental factors, based on average summer half-hourly values. At a seasonal scale energy partitions were linearly correlated (usually p<0.05) with T, VPD, and SM. The λE/R n increased with increases in SM, T, and VPD at forest areas. At mixed farmlands, λE/R n generally had positive correlations with SM, T, and VPD, but was restrained at extremely high values of VPD and T. At grasslands, λE/R n was enhanced with increases of SM and T, but was decreased with VPD.
An improved synchronous fluorimetric method for the determination of dissolved organic matter in cave drip water, by adding ascorbic acid, is described. The method is based on the redox reaction between ascorbic acid and the electron-withdrawing constituents in dissolved organic matter. The results show that adding ascorbic acid can quench the minor peaks, at 200–300 nm, but does not affect the intensity of the main peaks at 300–500 nm. In addition, adding ascorbic acid can maintain relatively high and constant fluorescence intensity over a wide pH range (9–4).
The canopy light extinction coefficient (K) is a key factor in affecting ecosystem carbon, water, and energy processes. However, K is assumed as a constant in most biogeochemical models owing to lack of in-site measurements at diverse terrestrial ecosystems. In this study, by compiling data of K measured at 88 terrestrial ecosystems, we investigated the spatiotemporal variations of this index across main ecosystem types, including grassland, cropland, shrubland, broadleaf forest, and needleleaf forest. Our results indicated that the average K of all biome types during whole growing season was 0.56. However, this value in the peak growing season was 0.49, indicating a certain degree of seasonal variation. In addition, large variations in K exist within and among the plant functional types. Cropland had the highest value of K (0.62), followed by broadleaf forest (0.59), shrubland (0.56), grassland (0.50), and needleleaf forest (0.45). No significant spatial correlation was found between K and the major environmental factors, i.e., mean annual precipitation, mean annual temperature , and leaf area index (LAI). Intra-annually, significant negative correlations between K and seasonal changes in LAI were found in the natural ecosystems. In cropland, however, the temporal relationship was site-specific. The ecosystem type specific values of K and its temporal relationship with LAI observed in this study may contribute to improved modeling of global biogeochemical cycles.
A Bayesian optimal estimation (OE) retrieval technique was used to retreive aerosol optical depth (AOD), aerosol single scattering albedo (SSA), and an asymmetry factor (g) at seven ultraviolet wavelengths, along with total column ozone (TOC), from the measurements of the UltraViolet Multifilter Rotating Shadowband Radiometer (UV-MFRSR) deployed at the Southern Great Plains (SGP) site during March through November in 2009. The OE technique specifies appropriate error covariance matrices and optimizes a forward model (Tropospheric ultraviolet radiative transfer model, TUV), and thus provides a supplemental method for use across the network of the Department of Agriculture UV-B Monitoring and Research Program (USDA UVMRP) for the retrieval of aerosol properties and TOC with reasonable accuracy in the UV spectral range under various atmospheric conditions. In order to assess the accuracy of the OE technique, we compared the AOD retreivals from this method with those from Beer’s Law and the AErosol RObotic Network (AERONET) AOD product. We also examine the OE retrieved TOC in comparison with the TOC from the U.S. Department of Agriculture UV-B Monitoring and Research Program (USDA UVMRP) and the Ozone Monitoring Instrument (OMI) satellite data. The scatterplots of the estimated AOD from the OE method agree well with those derived from Beer’s law and the collocated AERONET AOD product, showing high values of correlation coefficients, generally 0.98 and 0.99, and large slopes, ranging from 0.95 to 1.0, as well as small offsets, less than 0.02 especially at 368 nm. The comparison of TOC retrievals also indicates the promising accuracy of the OE method in that the standard deviations of the difference between the OE derived TOC and other TOC products are about 5 to 6 Dobson Units (DU). Validation of the OE retrievals on these selected dates suggested that the OE technique has its merits and can serve as a supplemental tool in further analyzing UVMRP data.
Microwave Humidity Sounders (MHS) onboard NOAA-15, -16, -17, -18, -19, and EUMETSAT MetOp-A/B satellites provide radiance measurements at a single polarization state at any of five observed frequencies. The Microwave Humidity Sounder (MWHS) onboard the FengYun-3 (FY-3) satellite has a unique instrument design that provides dual polarization measurements at 150 GHz. In this study, the MWHS polarization signal was investigated using observed and modeled data. It is shown that the quasi-polarization brightness temperatures at 150 GHz display a scan angle dependent bias. Under calm ocean conditions, the polarization difference at 150 GHz becomes non-negligible when the scan angle varies from 10° to 45° and reaches a maximum when the scan angle is about 30°. Also, the polarization state is sensitive to surface parameters such as surface wind speed. Under clear-sky conditions, the differences between horizontal and vertical polarization states at 150 GHz increase with decreasing surface wind speed. Therefore, the polarization signals from the cross-track scanning microwave measurements at window channels contain useful information about surface parameters. In addition, the availability of dual polarization measurements allows a one-to-one conversion from antenna brightness temperature to sensor brightness temperature if a cross-polarization spill-over exists.