土壤呼吸作用时空动态变化及其影响机制研究与展望

测定不同陆地生态系统土壤呼吸速率及其时空波动, 阐明其影响因子, 对于全球碳素平衡预算和全球变化潜在效应估计是最为基本的数据。然而, 有关土壤呼吸作用变异性及其影响因素的知识仍存在局限性, 一些关键的过程和机制还有待阐明。该文综述了近年来土壤呼吸作用时空动态规律、影响机制和模拟方面的研究进展, 指出环境因子和生物因子共同驱动着土壤呼吸作用的时间动态变化; 土壤呼吸作用在不同时间尺度上还具有明显的空间异质性, 这主要是植被覆盖、根系分布、主要的环境因素和土壤特性空间分布的异质性造成的。生物因子是影响土壤呼吸作用时空动态变化的主要因素之一。然而, 目前所使用的土壤呼吸作用经验模型通常利用土壤温度、土壤湿度或者两者的交互作用模拟土壤呼吸作用动态变化, 但没有考虑生物因子的影响, 这可能会导致明显的偏差和错误。因此, 为了精确估算土壤呼吸作用, 必须解决土壤呼吸作用小尺度上的空间变异性; 加强不同时间尺度上生物要素对土壤呼吸作用动态变化的影响研究; 除了气候因子外, 土壤呼吸作用经验模型应该纳入生物因子等其它影响因素作为变量, 用以提高模型模拟的正确性和准确性。     

Do biotic interactions modulate ecosystem functioning along stress gradients? Insights from semi-arid plant and biological soil crust communities

Climate change will exacerbate the degree of abiotic stress experienced by semi-arid ecosystems. While abiotic stress profoundly affects biotic interactions, their potential role as modulators of ecosystem responses to climate change is largely unknown. Using plants and biological soil crusts, we tested the relative importance of facilitative–competitive interactions and other community attributes (cover, species richness and species evenness) as drivers of ecosystem functioning along stress gradients in semi-arid Mediterranean ecosystems. Biotic interactions shifted from facilitation to competition along stress gradients driven by water availability and temperature. These changes were, however, dependent on the spatial scale and the community considered. We found little evidence to suggest that biotic interactions are a major direct influence upon indicators of ecosystem functioning (soil respiration, organic carbon, water-holding capacity, compaction and the activity of enzymes related to the carbon, nitrogen and phosphorus cycles) along stress gradients. However, attributes such as cover and species richness showed a direct effect on ecosystem functioning. Our results do not agree with predictions emphasizing that the importance of plant–plant interactions will be increased under climate change in dry environments, and indicate that reductions in the cover of plant and biological soil crust communities will negatively impact ecosystems under future climatic conditions.     

Factors affecting establishment of a gypsophyte: the case of Lepidium subulatum (Brassicaceae)

The restriction of vascular plants to gypsum-rich soils under arid or semiarid climates has been reported by many authors in different parts of the world. However, factors controlling the presence of gypsophytes on these soils are far from understood. We investigated the establishment of Lepidium subulatum, a gypsophyte, in a nondisturbed semiarid gypsum-soil landscape in central Spain, both from spatial and temporal perspectives. Over 1400 seedlings were tagged, and their growth and survival were monitored for a 2-yr period. Several biotic and abiotic variables were measured to determine the factors controlling the emergence and early survival. These variables included the cover of annual plants, bryophytes, lichens, litter, gypsum crystals, bare fraction and cover of each perennial plant, and several soil properties (gravel, fine gravel, and fine-earth fraction, conductivity, pH, gypsum content, organic matter and penetrometer soil resistance). Our results support the linkage of gypsophily with some physical properties of the surface crust. Seedlings tended to establish on the gypsum surface crust, and their survival was size dependent, probably as a consequence of the necessity of rooting below the surface crust before summer drought arrives. However, once seedlings emerged, a higher survival rate occurred on the alluvial soils of the piedmont-slope boundary where soil crusts are absent or thinner. We conclude that Lepidium subulatum may be considered a refuge model endemic with a distribution range that occupies a reduced fraction of a wider habitat from which it is probably excluded by competition.     

Environmental control of plant species abundance in a microtidal Mediterranean saltmarsh

Question: To what extent are environmental factors the main determinants of species abundance in Mediterranean coastal marshlands? Location: The Llobregat delta, Barcelona, Spain. Methods: Vegetation relevés were performed and a set of water table and soil variables were periodically monitored in 43 sampling points randomly distributed in four marsh areas (sites) along a coastal–inland gradient. A canonical correspondence analysis (CCA) was performed to identify the primary water and soil correlates of species cover, after considering the effect of site and point spatial location. The realized niches of dominant species were modeled through GLMs performed on the first two axes of CCA. Niche overlapping among these species was compared with their coexistence, assessed through pairwise correlations of relative species cover in each sampling point. Results: Water and soil variables explained more of the variation in species' abundance than site and spatial position. Mean water table level, maximum water conductivity and sodium adsorption ratio (SAR), summarized in the two first CCA axes, explained 23.8% of the variability in species' cover. Arthrocnemum fruticosum, Phragmites australis subsp. australis, Juncus acutus, Spartina versicolor and Juncus maritimus dominated the vegetation stands. Niches obtained from GLM response curves showed moderate overlapping among all these species except for A. fruticosum. However, pairwise correlations were mainly negative or non‐significant, indicating low coincidence, and even segregation, between species' cover. Conclusions: The abundance of dominant plants in Mediterranean marshes is only partly explained by the environmental gradients summarized in niche models. The role of other factors such as facilitation or competition between species and random recruitment should be explored.     

Relationships Between Plant Spatial Patterns, Water Infiltration Capacity, and Plant Community Composition in Semi-arid Mediterranean Ecosystems Along Stress Gradients

Water redistribution from bare soil to vegetation patches is a key feature of semi-arid ecosystems, and is responsible for their patchy vegetation patterns. The magnitude of water redistribution depends on the properties of the bare soil (which determine the amount of water run-off) and the capacity of vegetation patches to trap water run-on. We examined the relationships between plant spatial patterns, water infiltration into bare soil, and plant community composition in semi-arid sites with different hydro-physical properties (silty and gypseous soils) in NE Spain. We also studied the effect of two stressors, aridity and grazing, on water infiltration and plant spatial patterns. Our results indicate a negative correlation of bare soil sorptivity (the capacity to absorb water by capillarity) and vegetation aggregation. There was a strong positive correlation between perennial grass cover and the spatial aggregation of vegetation, but aggregation was not associated with positive associations of different plant types. The aggregation of vegetation was positively correlated with species richness and the overall extent of vegetation cover. Grazing reduced water infiltration into silty soils, which are prone to compaction. In contrast, soil crust affected the hydrology of gypseous soils, especially in the most arid sites, where grazing increased infiltration, reducing surface sealing due to breaking of the soil crust. Together, our results suggest that biotic and abiotic factors affect the hydro-physical properties of soils in the semi-arid ecosystems of NE Spain, which is linked to the plant communities through the spatial distribution of plants.     

Factors determining length distribution and abundance of the European eel, Anguilla anguilla, in the River Mondego (Portugal)

1. The distribution and abundance of the European eel, Anguilla anguilla, were investigated in the Mondego River, a strongly modified river in central Portugal. Nine freshwater sites, located below the first impassable obstacle to eel migration, were surveyed for 2 years. The study was conducted monthly during the first year and seasonally during the second year. Fish were caught by electric fishing and, physical and biotic variables potentially influencing eel length distribution and abundance were determined at each sampling session. 2. Canonical correspondence analysis (CCA) was used to explain the relationships between abiotic and biotic habitat variables, and eel length distribution. Spatial variation was strongly associated with distance from the sea, number of obstacles, river width and percentage of instream cover. Depth, river flow, water temperature and cannibalism had weaker effects on the longitudinal distribution, but contributed as explanatory variables for the model. The influence of spatial variables outweighed the importance of temporal variables as predictors in this model. 3. Length distribution changed in space from a dominance of small eels (<100 mm) closer to the sea to larger eels (≥250 mm) in the upper reaches of the river. The smallest length class (eels <100 mm) was strongly associated with wider stretches where instream cover, mainly composed of aquatic submerged macrophytes, was abundant (>75% area coverage). On the contrary, larger eels (≥250 mm) preferred deeper stretches with stronger river flow and less instream cover. 4. The effect of biotic interactions with conspecifics as well as with the non‐native red swamp crayfish Procambarus clarkii, in sites with poor instream cover, modified this general pattern of distribution leading to fewer eels <100 mm at some sites closer to the sea. Therefore, despite the ubiquity and plasticity shown by this species, there were clear ontogenetic variations in habitat use such that the first two canonical axes of a CCA accounted for 58.4% of the spatial variability in size structure.     

GLM versus CCA spatial modeling of plant species distribution

Despite the variety of statistical methods available for static modeling of plant distribution, few studies directly compare methods on a common data set. In this paper, the predictive power of Generalized Linear Models (GLM) versus Canonical Correspondence Analysis (CCA) models of plant distribution in the Spring Mountains of Nevada, USA, are compared. Results show that GLM models give better predictions than CCA models because a species-specific subset of explanatory variables can be selected in GLM, while in CCA, all species are modeled using the same set of composite environmental variables (axes). Although both techniques can be readily ported to a Geographical Information System (GIS), CCA models are more readily implemented for many species at once. Predictions from both techniques rank the species models in the same order of quality; i.e. a species whose distribution is well modeled by GLM is also well modeled by CCA and vice-versa. In both cases, species for which model predictions have the poorest accuracy are either disturbance or fire related, or species for which too few observations were available to calibrate and evaluate the model. Each technique has its advantages and drawbacks. In general GLM will provide better species specific-models, but CCA will provide a broader overview of multiple species, diversity, and plant communities.     

Vegetation-environment relationships of old-growth spruce forest vegetation in Østmarka Nature Reserve, SE Norway, and comparison of three ordination methods

The relationship between vegetation and environmental variables has been studied in 100 sample plots, each 0.25 m², in old-growth spruce forest at Høgkollen, ØOstmarka Nature Reserve, SE Norway. Each sample plot was supplied with measurements of 13 environmental and 5 biotic variables. Parallel application of three ordination techniques, PCA, DCA and LNMDS, resulted in different sample plot configurations. PCA performed poorest due to strong influence of outliers and circumstantial evidence indicated better performance of LNMDS than DCA. Statistical analyses of the relationships between vegetation and ecological data revealed a parallel gradient in soil moisture (decreasing) and canopy closure (increasing) as the most important for differentiation of the vegetation. Species number and field layer cover decreased, while bottom layer cover increased, due to increasing cover of Dicranum majus , with decreasing soil moisture and increasing canopy closure. Constrained canonical correspondence analysis (CCA) was used to partition the variation of the species-sample plot matrix into spatial, environmental and unexplained variation, and combinations. The fraction of unexplained variation was high (80.9 %), most likely due to small sample plot size and short gradient lengths. Most of the explained variation was attributable to environmental factors alone (54.5%). Only 6.3% was shared between environmental and spatial variation, which indicated minor importance of broad-scale and geographically structured environmental variation. Strictly spatial variation constituted 39.3%. However, the spatially structured environmental variation was low, so the causes of spatial variation were likely not to be found among the measured environmental variables.     

Context‐dependent biotic interactions control plant abundance across altitudinal environmental gradients

Many biotic interactions influence community structure, yet most distribution models for plants have focused on plant competition or used only abiotic variables to predict plant abundance. Furthermore, biotic interactions are commonly context‐dependent across abiotic gradients. For example, plant–plant interactions can grade from competition to facilitation over temperature gradients. We used a hierarchical Bayesian framework to predict the abundances of 12 plant species across a mountain landscape and test hypotheses on the context‐dependency of biotic interactions over abiotic gradients. We combined field‐based estimates of six biotic interactions (foliar herbivory and pathogen damage, fungal root colonization, fossorial mammal disturbance, plant cover and plant diversity) with abiotic data on climate and soil depth, nutrients and moisture. All biotic interactions were significantly context‐dependent along temperature gradients. Results supported the stress gradient hypothesis: as abiotic stress increased, the strength or direction of the relationship between biotic variables and plant abundance generally switched from negative (suggesting suppressed plant abundance) to positive (suggesting facilitation/mutualism). For half of the species, plant cover was the best predictor of abundance, suggesting that the prior focus on plant–plant interactions is well‐justified. Explicitly incorporating the context‐dependency of biotic interactions generated novel hypotheses about drivers of plant abundance across abiotic gradients and may improve the accuracy of niche models.     

Spatial patterns of surface soil properties and vegetation in a Mediterranean semi-arid steppe

In arid and semi-arid areas with sparse vegetation cover, the spatial pattern of surface soil properties affects water and nutrient flows, and is a question of considerable interest for understanding degradation processes and establishing adequate management measures. In this study, we investigate the spatial distribution of vegetation and surface soil properties (biological crusts, physical crusts, mosses, rock fragments, earthworm casts, fine root accumulation and below-ground stones) in a semi-arid Stipa tenacissima L. steppe in SE Spain. We applied the combination of spatial analysis by distance indices (SADIE) and geostatistics to assess the spatial pattern of soil properties and vegetation, and correlation analyses to explore how these patterns were related. SADIE analysis detected significant clumped patterns in the spatial distribution of vegetation, mosses, fine root accumulation and below-ground stone content. Contoured SADIE index of clustering maps suggested the presence of patchiness in the distribution of earthworm casts, fine roots, below-ground stone content, mosses and biological crusts. Correlation analyses suggested that spatial pattern of some soil properties such as biological crusts, moss cover, surface rock fragments, physical crusts and fine roots were significantly related with above-ground plant distribution. We discuss the spatial arrangement of surface soil properties and suggest mechanistic explanations for the observed spatial patterns and relationships.     

Biotic interactions boost spatial models of species richness

Biotic interactions are known to affect the composition of species assemblages via several mechanisms, such as competition and facilitation. However, most spatial models of species richness do not explicitly consider inter‐specific interactions. Here, we test whether incorporating biotic interactions into high‐resolution models alters predictions of species richness as hypothesised. We included key biotic variables (cover of three dominant arctic‐alpine plant species) into two methodologically divergent species richness modelling frameworks – stacked species distribution models (SSDM) and macroecological models (MEM) – for three ecologically and evolutionary distinct taxonomic groups (vascular plants, bryophytes and lichens). Predictions from models including biotic interactions were compared to the predictions of models based on climatic and abiotic data only. Including plant–plant interactions consistently and significantly lowered bias in species richness predictions and increased predictive power for independent evaluation data when compared to the conventional climatic and abiotic data based models. Improvements in predictions were constant irrespective of the modelling framework or taxonomic group used. The global biodiversity crisis necessitates accurate predictions of how changes in biotic and abiotic conditions will potentially affect species richness patterns. Here, we demonstrate that models of the spatial distribution of species richness can be improved by incorporating biotic interactions, and thus that these key predictor factors must be accounted for in biodiversity forecasts.     

Does aboveground vegetation composition resemble soil seed bank during succession in specialized vegetation on gypsum soil?

This paper evaluates the aboveground vegetation in relation to the soil seed bank throughout a 60-year succession process following agricultural abandonment in a semi-arid Mediterranean gypsum habitat. There is little information regarding the relationship between these two community components in the context of succession on semi-arid gypsum soils. Aboveground vegetation and the corresponding seed bank of gypsum plant communities were sampled through a chronosequence of 24 abandoned fields. Generalized linear models were used to model seed species richness and density, redundancy analyses to model the effect of time since abandonment and the effect of soil physicochemical parameters on seed bank species composition, and Mantel tests to analyze resemblance between above- and belowground species composition. In this last case, the effect of time since abandonment was controlled using a partial Mantel test. Mantel correlograms using time intervals instead of distances were used to describe the resemblance of above- to belowground species occurrence in different aged fields. No significant variability in seed species richness, seed density, or species composition due to time since abandonment was found. Differences in seed species composition were mainly due to small spatial scale predictors such as slope and soil calcium content. High correlations between species composition in the soil seed bank and the aboveground vegetation were detected during succession. The lack of a significant trend in aboveground species replacement over time was also reflected in seed bank composition. We concluded that the rapid establishment of strict gypsophyte species relied mainly on the long-term persistence of these species in the seed bank.     

Influence of edaphic factors on the spatial structure of inland halophytic communities: a case study in China

Abstract. In order to understand the influence of edaphic factors on the spatial structure of inland halophytic plant communities, a 2.6 km² study site, located on the lower fringe of the alluvial fan of the Hutubi River, in an arid region of China, was sampled and mapped. 105 patches were found to be homogeneous in species composition. Plant species and their coverage were recorded in each patch. 45 patches were randomly selected for the measurement of edaphic variables. A map with quadrat locations and boundaries of patches was digitized into a GIS and related to the vegetation and edaphic data matrices. CCA was used to evaluate the relative importance of edaphic factors in explaining the variation of the species assemblages and to identify the ecological preferences of species. The spatial structure of the communities and the main edaphic factors were analyzed using correlograms, Mantel correlograms and clustering under constraint of spatial contiguity. Gradient analysis showed that there are two distinct vegetation gradients in the study area, one of which is determined mainly by soil moisture (determined by depth to the water table), and the other by soil salinity (determined by electrical conductivity and hydrolytic alkalinity of the first soil layer). However, spatial analyses showed that at the sampling scale the halophytic communities in the study area are structured along one main spatial gradient determined by the water table level. Similar spatial autocorrelation structures between the factors related to the first soil layer and the communities, given our sampling scale, could not be detected. Our results suggest that the relative importance of the effects of different edaphic factors on the spatial structure of halophytic communities is scale-dependent. The partitioning of species variation indicates that in addition to edaphic factors, other factors, such as biotic interactions, may play an important role in structuring these communities.     

Lentic macroinvertebrate assemblage structure along gradients in spatial heterogeneity, habitat size and water chemistry

Littoral zones of small water bodies are spatially heterogeneous habitats, harbouring diverse biotic communities. Despite this apparent heterogeneity, many studies have stressed the importance of water chemistry in determining the structure of littoral macroinvertebrate assemblages. The purpose of this study was to consider the relative importance of several spatial and water chemistry variables in explaining the patterns in the structure of macroinvertebrate assemblages in 21 lentic water bodies in northeastern Finland. Water bodies were selected to represent various habitat conditions ranging from small permanent bog ponds to small forest lakes. According to canonical correspondence analysis (CCA), the most important environmental factors related to assemblage composition were water body area, moss cover, total nitrogen and water hardness. In general, species composition in small bog ponds tended to differ from that in larger lakes with forested shoreline. Total species richness was best explained by a composite variable (PCA) describing physical habitat heterogeneity, species richness being lowest in small bog lakes with simple bottom structure and low amount of aquatic plants. Species numbers in dominant functional feeding groups were related to different environmental factors. Shredder species richness was best explained by a regression model incorporating total nitrogen and the amount of organic matter, both of which were negatively related to the number of shredder species. The number of gatherer species increased with mean substratum particle size. Scraper species richness was negatively affected by the abundance of detritus and positively affected by depth, and a model including both variables explained most of the variation. Variation in the number of predatory species was best explained by a regression model including moss cover and lake area.     

Biotic and abiotic variables show little redundancy in explaining tree species distributions

Abiotic factors such as climate and soil determine the species fundamental niche, which is further constrained by biotic interactions such as interspecific competition. To parameterize this realized niche, species distribution models (SDMs) most often relate species occurrence data to abiotic variables, but few SDM studies include biotic predictors to help explain species distributions. Therefore, most predictions of species distributions under future climates assume implicitly that biotic interactions remain constant or exert only minor influence on large‐scale spatial distributions, which is also largely expected for species with high competitive ability. We examined the extent to which variance explained by SDMs can be attributed to abiotic or biotic predictors and how this depends on species traits. We fit generalized linear models for 11 common tree species in Switzerland using three different sets of predictor variables: biotic, abiotic, and the combination of both sets. We used variance partitioning to estimate the proportion of the variance explained by biotic and abiotic predictors, jointly and independently. Inclusion of biotic predictors improved the SDMs substantially. The joint contribution of biotic and abiotic predictors to explained deviance was relatively small (~9%) compared to the contribution of each predictor set individually (~20% each), indicating that the additional information on the realized niche brought by adding other species as predictors was largely independent of the abiotic (topo‐climatic) predictors. The influence of biotic predictors was relatively high for species preferably growing under low disturbance and low abiotic stress, species with long seed dispersal distances, species with high shade tolerance as juveniles and adults, and species that occur frequently and are dominant across the landscape. The influence of biotic variables on SDM performance indicates that community composition and other local biotic factors or abiotic processes not included in the abiotic predictors strongly influence prediction of species distributions. Improved prediction of species' potential distributions in future climates and communities may assist strategies for sustainable forest management.     

The relative influences of exotic species and environmental factors

Spatial variation in the native fish community of the lower Guadiana basin (southern Iberia) was related to both biotic (abundance of exotic species) and environmental factors using canonical correspondence analysis, CCA. After choosing the best predictors among the environmental and biotic variables, we partitioned the total variation in native species abundances (18 species-size combinations by 44 sampling locations matrix) into that accounted for (1) solely by selected environmental variables, (2) solely by selected biotic variables, (3) by both environmental and biotic variables together, and (4) that unexplained. Of the 22 variables initially considered in the environmental CCA, only RIVER (dummy variable codifying sampling locations belonging to the main river), SALT (dummy variable codifying sampling locations belonging to tributaries that discharge to the brackish Guadiana), substrate heterogeneity, and macrobenthos abundance were selected as best predictors. In the biotic CCA, three species-size combinations were selected from the eight considered: Micropterus salmoides > 150 mm in total length (TL), Lepomis gibbosus > 100 mm in TL and Gambusia holbrooki. The total variation in the native fish community was partitioned into the following components: pure environmental (24.4%), pure biotic (12.4%), shared (9.2%) and unexplained (54.0%). There was a significant influence of exotic fish on native community variation after accounting for the effect of environmental factors. This revised version was published online in July 2006 with corrections to the Cover Date.     

Arbuscular mycorrhizal fungal communities are phylogenetically clustered at small scales

Next-generation sequencing technologies with markers covering the full Glomeromycota phylum were used to uncover phylogenetic community structure of arbuscular mycorrhizal fungi (AMF) associated with Festuca brevipila. The study system was a semi-arid grassland with high plant diversity and a steep environmental gradient in pH, C, N, P and soil water content. The AMF community in roots and rhizosphere soil were analyzed separately and consisted of 74 distinct operational taxonomic units (OTUs) in total. Community-level variance partitioning showed that the role of environmental factors in determining AM species composition was marginal when controlling for spatial autocorrelation at multiple scales. Instead, phylogenetic distance and spatial distance were major correlates of AMF communities: OTUs that were more closely related (and which therefore may have similar traits) were more likely to co-occur. This pattern was insensitive to phylogenetic sampling breadth. Given the minor effects of the environment, we propose that at small scales closely related AMF positively associate through biotic factors such as plant-AMF filtering and interactions within the soil biota.     

Biotic predictors with phenological information improve range estimates for migrating monarch butterflies in Mexico

Although long-standing theory suggests that biotic variables are only relevant at local scales for explaining the patterns of species' distributions, recent studies have demonstrated improvements to species distribution models (SDMs) by incorporating predictor variables informed by biotic interactions. However, some key methodological questions remain, such as which kinds of interactions are permitted to include in these models, how to incorporate the effects of multiple interacting species, and how to account for interactions that may have a temporal dependence. We addressed these questions in an effort to model the distribution of the monarch butterfly Danaus plexippus during its fall migration (September–November) through Mexico, a region with new monitoring data and uncertain range limits even for this well-studied insect. We estimated species richness of selected nectar plants (Asclepias spp.) and roosting trees (various highland species) for use as biotic variables in our models. To account for flowering phenology, we additionally estimated nectar plant richness of flowering species per month. We evaluated three types of models: climatic variables only (abiotic), plant richness estimates only (biotic) and combined (abiotic and biotic). We selected models with AICc and additionally determined if they performed better than random on spatially withheld data. We found that the combined models accounting for phenology performed best for all three months, and better than random for discriminatory ability but not omission rate. These combined models also produced the most ecologically realistic spatial patterns, but the modeled response for nectar plant richness matched ecological predictions for November only. These results represent the first model-based monarch distributional estimates for the Mexican migration route and should provide foundations for future conservation work. More generally, the study demonstrates the potential benefits of using SDM-derived richness estimates and phenological information for biotic factors affecting species distributions.     

Exclusion effects on vegetation characteristics and their correlation to soil factors in the semi-arid rangeland of Mu Us Sandland,China

Exclusion has been applied as a main measure for re-vegetation all over the world.This paper,by comparing the results of year-round exclusion,seasonal exclusion,and non-exclusion,quantified the vegetation variations under three different exclusion measures and their correlation to soil factors.The analysis results for community species component and plant diversity using multi-response permutation procedures (MRPPs)showed that exclusion did change the species component and increase plant diversity remarkably,while the period of exclusion had no significant influence on these two community features.The indicator species analysis and calculation of similarity indices indicated that community for year-round exclusion were becoming xerophytization and unpalatability,and showed highly spatial heterogeneity of plant species distribution,whereas community for seasonal exclusion was under stable non-equilibrium condition.Detrended correspondence analysis (DCA)and detrend canonical correspondence analysis (DCCA)results of relationship between plant species and soil variables demonstrated that soil moisture was a controlling factor for plant species component,microbiotic soil crust cover,soil organic matter,and soil bulk density had significant effects on soil moisture,among which microbiotic soil crust was a leading factor owing to its limitation to rainfall infiltration on the one hand,and its constraints to entrance of herbaceous seeds into soil or to germination of soil seeds on the other hand.As a result of long-term removal of animal grazing,crust kept intact in year-round exclusion community,which was a main reason of community xerophytization.It was also obvious from ordination results that some important environmental factors,such as tempo-spatial change of rainfall and corresponding tempo-spatial change of soil moisture,were neglected during direct gradient analysis.In addition,biodiversity was close related to soil nutrients as well as to soil moisture condition (soil water content and crust cover),and it had positive relation to available N,and negative relation to available P.Higher soil N had advantage to non-leguminous plants growth on nutrition-poor sand land definitely.The impact of P to community component was unclear and should be studied from plant physiology.Further researches on nonequilibrium theory in semi-arid rangeland will provide a scientific and flexible animal development paradigm for being implementing livestock fen-raising and grazing-forbidden policies in China.     

黑河下游地下水波动带地下水与植被动态耦合模拟

采用对数正态分布模型,基于2006年黑河下游的野外实测数据,建立了研究区胡杨和柽柳植被盖度与地下水埋深的模型,并模拟了研究区的潜在植被.结果表明：黑河下游胡杨的最适宜地下水位和平均地下水位分别为2.6和3.6 m,柽柳则分别为2.0和3.0 m;胡杨的高盖度分布区主要集中在河道两侧的区域,而柽柳则可以在研究区的大部分区域以较高的盖度生存,对于研究区当前的地下水埋深而言,柽柳应该是最适宜生存的物种之一;研究区胡杨和柽柳的潜在植被空间分布与现状分布的相似性分别为43.4%和55.6%,导致相似程度不高的主要原因为土壤中存在的石膏盐盘层阻碍了土壤水分的垂直运动.