A multi-scale comparison of trait linkages to environmental and spatial variables in fish communities across a large freshwater lake

Species present in communities are affected by the prevailing environmental conditions, and the traits that these species display may be sensitive indicators of community responses to environmental change. However, interpretation of community responses may be confounded by environmental variation at different spatial scales. Using a hierarchical approach, we assessed the spatial and temporal variation of traits in coastal fish communities in Lake Huron over a 5-year time period (2001–2005) in response to biotic and abiotic environmental factors. The association of environmental and spatial variables with trophic, life-history, and thermal traits at two spatial scales (regional basin-scale, local site-scale) was quantified using multivariate statistics and variation partitioning. We defined these two scales (regional, local) on which to measure variation and then applied this measurement framework identically in all 5 study years. With this framework, we found that there was no change in the spatial scales of fish community traits over the course of the study, although there were small inter-annual shifts in the importance of regional basin- and local site-scale variables in determining community trait composition (e.g., life-history, trophic, and thermal). The overriding effects of regional-scale variables may be related to inter-annual variation in average summer temperature. Additionally, drivers of fish community traits were highly variable among study years, with some years dominated by environmental variation and others dominated by spatially structured variation. The influence of spatial factors on trait composition was dynamic, which suggests that spatial patterns in fish communities over large landscapes are transient. Air temperature and vegetation were significant variables in most years, underscoring the importance of future climate change and shoreline development as drivers of fish community structure. Overall, a trait-based hierarchical framework may be a useful conservation tool, as it highlights the multi-scaled interactive effect of variables over a large landscape.     

Abiotic drivers and plant traits explain landscape‐scale patterns in soil microbial communities

The controls on aboveground community composition and diversity have been extensively studied, but our understanding of the drivers of belowground microbial communities is relatively lacking, despite their importance for ecosystem functioning. In this study, we fitted statistical models to explain landscape‐scale variation in soil microbial community composition using data from 180 sites covering a broad range of grassland types, soil and climatic conditions in England. We found that variation in soil microbial communities was explained by abiotic factors like climate, pH and soil properties. Biotic factors, namely community‐weighted means (CWM) of plant functional traits, also explained variation in soil microbial communities. In particular, more bacterial‐dominated microbial communities were associated with exploitative plant traits versus fungal‐dominated communities with resource‐conservative traits, showing that plant functional traits and soil microbial communities are closely related at the landscape scale.     

北方典型沼泽湿地高低土壤水分下植物群落特征

北方沼泽湿地在水源供给、缓解水土流失、遏制草地沙化等方面具有重要作用,明确其植物群落物种组成和多样性特征对提升其生态系统服务功能具有重要意义。目前,在北方地区开展大尺度湿地植被调查的研究仍相对较少。土壤水分是驱动植物群落发展的主导环境因素之一,为了解高低土壤水分背景下湿地植物群落特征差异及关键驱动要素,对我国7个北方典型沼泽湿地的植物群落物种组成及多样性特征进行了调查,分析了植物群落物种组成及多样性特征与环境因子的关系,以及沼泽湿地植物群落内克隆植物的分布特征。研究结果发现不同沼泽湿地的植物群落物种组成和多样性差异显著,但无明显的地带性分布规律,物种分布呈现区域性。群落物种多样性受降水、温度、土壤养分等多种环境因素的共同影响。沼泽湿地高低土壤水分背景下植物群落的物种组成和多样性差异显著,低土壤水分下植物群落物种多样性指数显著高于高土壤水分下植物群落。低土壤水分下物种多样性主要受降水和总氮影响,而高土壤水分下物种多样性主要受温度和总磷的影响。高土壤水分下克隆植物物种数和盖度在沼泽湿地植物中占有较高的比例,表明克隆植物比非克隆植物更适应高土壤水分环境。研究结果表明了7个沼泽湿地植被的区域性...     

Applying ecological site concepts and state‐and‐transition models to a grazed riparian rangeland

Ecological sites and state‐and‐transition models are useful tools for generating and testing hypotheses about drivers of vegetation composition in rangeland systems. These models have been widely implemented in upland rangelands, but comparatively, little attention has been given to developing ecological site concepts for rangeland riparian areas, and additional environmental criteria may be necessary to classify riparian ecological sites. Between 2013 and 2016, fifteen study reaches on five creeks were studied at Tejon Ranch in southern California. Data were collected to describe the relationship between riparian vegetation composition, environmental variables, and livestock management; and to explore the utility of ecological sites and state‐and‐transition models for describing riparian vegetation communities and for creating hypotheses about drivers of vegetation change. Hierarchical cluster analysis was used to classify the environmental and vegetation data (15 stream reaches × 4 years) into two ecological sites and eight community phases that comprised three vegetation states. Classification and regression tree (CART) analysis was used to determine the influence of abiotic site variables, annual precipitation, and cattle activity on vegetation clusters. Channel slope explained the greatest amount of variation in vegetation clusters; however, soil texture, geology, watershed size, and elevation were also selected as important predictors of vegetation composition. The classification tree built with this limited set of abiotic predictor variables explained 90% of the observed vegetation clusters. Cattle grazing and annual precipitation were not linked to qualitative differences in vegetation. Abiotic variables explained almost all of the observed riparian vegetation dynamics—and the divisions in the CART analysis corresponded roughly to the ecological sites—suggesting that ecological sites are well‐suited for understanding and predicting change in this highly variable system. These findings support continued development of riparian ecological site concepts and state‐and‐transition models to aid decision making for conservation and management of rangeland riparian areas.     

Site fertility drives temporal turnover of vegetation at high latitudes

Experimental evidence shows that site fertility is a key modulator underlying plant community changes under climate change. Communities on fertile sites, with species having fast dynamics, have been found to react more strongly to climate change than communities on infertile sites with slow dynamics. However, it is still unclear whether this generally applies to high‐latitude plant communities in natural environments at broad spatial scales. We tested a hypothesis that vegetation of fertile sites experiences greater changes over several decades and thus would be more responsive under contemporary climate change compared to infertile sites that are expected to show more resistance. We resurveyed understorey communities (vascular plants, bryophytes, and lichens) of four infertile and four fertile forest sites along a latitudinal bioclimatic gradient. Sites had remained outside direct human disturbance. We analyzed the magnitude of temporal community turnover, changes in the abundances of plant morphological groups and strategy classes, and changes in species diversity. In agreement with our hypothesis, temporal turnover of communities was consistently greater on fertile sites compared to infertile sites. However, our results suggest that the larger turnover of fertile communities is not primarily related to the direct effects of climatic warming. Furthermore, community changes in both fertile and infertile sites showed remarkable variation in terms of shares of plant functional groups and strategy classes and measures of species diversity. This further emphasizes the essential role of baseline environmental conditions and nonclimatic drivers underlying vegetation changes. Our results show that site fertility is a key determinant of the overall rate of high‐latitude vegetation changes but the composition of plant communities in different ecological contexts is variously impacted by nonclimatic drivers over time.     

Alternative stable states in inherently unstable systems

Alternative stable states are nontransitory states within which communities can exist. However, even highly dynamic communities can be viewed within the framework of stable‐state theory if an appropriate “ecologically relevant” time scale is identified. The ecologically relevant time scale for dynamic systems needs to conform to the amount of time needed for a system's community to complete an entire cycle through its normal range of variation. For some systems, the ecologically relevant period can be relatively short (eg, tidal systems), for others it can be decadal (eg, prairie wetlands). We explore the concept of alternative stable states in unstable systems using the highly dynamic wetland ecosystems of North America's Prairie Pothole Region. The communities in these wetland ecosystems transition through multiple states in response to decadal‐long climate oscillations that cyclically influence ponded‐water depth, permanence, and chemistry. The perspective gained by considering dynamic systems in the context of stable‐state theory allows for an increased understanding of how these systems respond to changing drivers that can push them past tipping points into alternative states. Incorporation of concepts inherent to stable‐state theory has been suggested as a key scientific element upon which to base sustainable environmental management.     

Size distribution of aquatic invertebrates in two prairie wetlands, with and without fish, with implications for community production

1. We compared the size distribution of aquatic invertebrates in two prairie wetlands, one supporting a population of fathead minnows and the other fishless. Both wetlands were sampled in three depth zones on three dates, allowing assessment of temporal and spatial variation.
2. We determined biomass of aquatic invertebrates in 17 log₂ size classes, and used these data to develop normalized size spectra. We also coupled size distributions with an allometric model to estimate relative production at the community level.
3. The composition of the invertebrate communities differed greatly between sites, and invertebrate biomass was higher in nearly all size classes in the fishless wetland. Intercepts of normalized size spectra were significantly different between wetlands, but slopes generally were not, indicating differences in standing-stock biomass but similar size structures between the two invertebrate communities. Higher standing-stock biomass in the fishless wetland resulted in higher relative production per unit area, but similar size distributions resulted in similar mass-specific production (P/B) between wetlands.
4. Our results indicate that invertebrate communities in prairie wetlands may have relatively consistent size structures in spite of large differences in community composition and standing-stock biomass. We hypothesize that the observed differences are because of predation by the minnow population and/or differences in the macrophyte communities between the two sites. However, the relative importance of macrophytes and fish predation in structuring invertebrate communities in prairie wetlands is poorly known.     

A general multi-trait-based framework for studying the effects of biodiversity on ecosystem functioning

Environmental change is as multifaceted as are the species and communities that respond to these changes. Current theoretical approaches to modeling ecosystem response to environmental change often deal only with single environmental drivers or single species traits, simple ecological interactions, and/or steady states, leading to concern about how accurately these approaches will capture future responses to environmental change in real biological systems. To begin addressing this issue, we generalize a previous trait-based framework to incorporate aspects of frequency dependence, functional complementarity, and the dynamics of systems composed of species that are defined by multiple traits that are tied to multiple environmental drivers. The framework is particularly well suited for analyzing the role of temporal environmental fluctuations in maintaining trait variability and the resultant effects on community response to environmental change. Using this framework, we construct simple models to investigate two ecological problems. First, we show how complementary resource use can significantly enhance the nutrient uptake of plant communities through two different mechanisms related to increased productivity (over-yielding) and larger trait variability. Over-yielding is a hallmark of complementarity and increases the total biomass of the community and, thus, the total rate at which nutrients are consumed. Trait variability also increases due to the lower levels of competition associated with complementarity, thus speeding up the rate at which more efficient species emerge as conditions change. Second, we study systems in which multiple environmental drivers act on species defined by multiple, correlated traits. We show that correlations in these systems can increase trait variability within the community and again lead to faster responses to environmental change. The methodological advances provided here will apply to almost any function that relates species traits and environmental drivers to growth, and should prove useful for studying the effects of climate change on the dynamics of biota.     

Predictability in community dynamics

The coupling between community composition and climate change spans a gradient from no lags to strong lags. The no‐lag hypothesis is the foundation of many ecophysiological models, correlative species distribution modelling and climate reconstruction approaches. Simple lag hypotheses have become prominent in disequilibrium ecology, proposing that communities track climate change following a fixed function or with a time delay. However, more complex dynamics are possible and may lead to memory effects and alternate unstable states. We develop graphical and analytic methods for assessing these scenarios and show that these dynamics can appear in even simple models. The overall implications are that (1) complex community dynamics may be common and (2) detailed knowledge of past climate change and community states will often be necessary yet sometimes insufficient to make predictions of a community's future state.     

Land-Use History and Contemporary Management Inform an Ecological Reference Model for Longleaf Pine Woodland Understory Plant Communities

Ecological restoration is frequently guided by reference conditions describing a successfully restored ecosystem; however, the causes and magnitude of ecosystem degradation vary, making simple knowledge of reference conditions insufficient for prioritizing and guiding restoration. Ecological reference models provide further guidance by quantifying reference conditions, as well as conditions at degraded states that deviate from reference conditions. Many reference models remain qualitative, however, limiting their utility. We quantified and evaluated a reference model for southeastern U.S. longleaf pine woodland understory plant communities. We used regression trees to classify 232 longleaf pine woodland sites at three locations along the Atlantic coastal plain based on relationships between understory plant community composition, soils (which broadly structure these communities), and factors associated with understory degradation, including fire frequency, agricultural history, and tree basal area. To understand the spatial generality of this model, we classified all sites together and for each of three study locations separately. Both the regional and location-specific models produced quantifiable degradation gradients–i.e., progressive deviation from conditions at 38 reference sites, based on understory species composition, diversity and total cover, litter depth, and other attributes. Regionally, fire suppression was the most important degrading factor, followed by agricultural history, but at individual locations, agricultural history or tree basal area was most important. At one location, the influence of a degrading factor depended on soil attributes. We suggest that our regional model can help prioritize longleaf pine woodland restoration across our study region; however, due to substantial landscape-to-landscape variation, local management decisions should take into account additional factors (e.g., soil attributes). Our study demonstrates the utility of quantifying degraded states and provides a series of hypotheses for future experimental restoration work. More broadly, our work provides a framework for developing and evaluating reference models that incorporate multiple, interactive anthropogenic drivers of ecosystem degradation.     

Salinity thresholds for understory plants in coastal wetlands

The effects of sea level rise and coastal saltwater intrusion on wetland plants can extend well above the high-tide line due to drought, hurricanes, and groundwater intrusion. Research has examined how coastal salt marsh plant communities respond to increased flooding and salinity, but more inland coastal systems have received less attention. The aim of this study was to identify whether ground layer plants exhibit threshold responses to salinity exposure. We used two vegetation surveys throughout the Albemarle-Pamlico Peninsula (APP) of North Carolina, USA to assess vegetation in a low elevation landscape (≤?3.8 m) experiencing high rates of sea level rise (3–4 mm/year). We examined the primary drivers of community composition change using Non-metric Multidimensional Scaling (NMDS) and used Threshold Indicator Taxa Analysis (TITAN) to detect thresholds of compositional change based on indicator taxa, in response to potential indicators of exposure to saltwater (Na, and the Σ Ca?+?Mg) and elevation. Salinity and elevation explained 64% of the variation in community composition, and we found two salinity thresholds for both soil Na⁺ (265 and 3843 g Na⁺/g) and Ca⁺ +?Mg⁺ (42 and 126 µeq/g) where major changes in community composition occur on the APP. Similar sets of species showed sensitivity to these different metrics of salt exposure. Overall, our results showed that ground layer plants can be used as reliable indicators of salinity thresholds in coastal wetlands. These results can be used for monitoring salt exposure of ecosystems and for identifying areas at risk for undergoing future community shifts.

     

β-多样性的研究：应用多元回归和典范分析研究生态方差的分解

 β-多样性刻画了地理区域中不同地点物种组成的变化,是理解生态系统功能、生物多样性保护和生态系统管理的一个重要概念。该文介绍了如何从群落组成,相关环境和空间数据角度去分析β-多样性。β-多样性可以通过计算每个地点的多样性指数,进而对可能解释点之间差异的因子所作的假设进行检验来研究。也可以将涵盖所有点的群落组成数据表看作是一系列环境和空间变量的函数,进行直接分析。这种分析应用统计方法将多样性指数或群落组成数据表的方差进行关于环境和空间变量的分解。该文对方差分解进行阐述。方差分解是利用环境和空间变量来解释β-多样性的一种方法。β-多样性是生态学家用来比较不同地点或同一地点不同生态群落的一种手段。方差分解就是将群落组成数据表的总方差无偏分解成由各个解释变量所决定的子方差。调整的决定系数提供了针对多元回归和典范冗余分析的无偏估计。 方差分解后,可以对感兴趣的方差解释部分进行显著性检验,同时绘出基于这部分方差解释的预测图。     

Plant diversity in wooded moderate-rich fens across boreal western Canada: an ecoregional perspective

Ecoregions are increasingly being used as a framework for conservation planning. The Mid-Boreal Uplands Ecoregion stretches across Canada from Manitoba to British Columbia. From the perspective of conservation and to understand the dynamics of plant diversity and community composition in a common wetland type, we examined the plant communities and environmental variables in 80 wooded moderate-rich fens within this ecoregion. Regional diversity totalled 273 species, with 86 bryophytes and 187 vascular plants. Total diversity was greatest in Manitoba and decreased in a longitudinal trend west through Saskatchewan and Alberta. This may be related, in part, to orographic precipitation at Manitoba sites and a gradient of growing degree days. Richness of locally rare vascular plants exhibited a clear west to east gradient. Ten species of provincially rare vascular plants were observed across the ecoregion, but without pattern. Ordinations and other analyses revealed distinct plant communities for all three locations, with vascular plant assemblages more discrete than bryophyte assemblages. Bryophyte diversity increased with latitude and longitude, whereas vascular plant diversity decreased. Additionally, elevation, precipitation, surface water alkalinity, water temperature, percent overstory density, and peat organic C played a role in determining species richness and community composition. Overall, species composition and diversity in a single wetland type exhibited continuous change across multiple political jurisdictions at the ecoregion scale. Conservation plans for wetlands at the ecodistrict scale may be preferable.     

Does environmental heterogeneity drive functional trait variation? A test in montane and alpine meadows

While community‐weighted means of plant traits have been linked to mean environmental conditions at large scales, the drivers of trait variation within communities are not well understood. Local environmental heterogeneity (such as microclimate variability), in addition to mean environmental conditions, may decrease the strength of environmental filtering and explain why communities support different amounts of trait variation. Here, we assess two hypotheses: first, that more heterogeneous local environments and second, that less extreme environments, should support a broader range of plant strategies and thus higher trait variation. We quantified drivers of trait variation across a range of environmental conditions and spatial scales ranging from sub‐meter to tens of kilometers in montane and alpine plant communities. We found that, within communities, both environmental heterogeneity and environmental means are drivers of trait variation. However, the importance of each environmental factor varied depending on the trait. Our results indicate that larger‐scale trait–climate linkages that hold across communities also apply at small spatial scales, suggesting that microclimate variation within communities is a key driver of community functional diversity. Microclimatic variation provides a potential mechanism for helping to maintain diversity in local communities and also suggests that small‐scale environmental heterogeneity should be measured as a better predictor of functional diversity.     

Distinct patterns of soil bacterial and fungal community assemblages in subtropical forest ecosystems under warming

Climate change globally affects soil microbial community assembly across ecosystems. However, little is known about the impact of warming on the structure of soil microbial communities or underlying mechanisms that shape microbial community composition in subtropical forest ecosystems. To address this gap, we utilized natural variation in temperature via an altitudinal gradient to simulate ecosystem warming. After 6 years, microbial co-occurrence network complexity increased with warming, and changes in their taxonomic composition were asynchronous, likely due to contrasting community assembly processes. We found that while stochastic processes were drivers of bacterial community composition, warming led to a shift from stochastic to deterministic drivers in dry season. Structural equation modelling highlighted that soil temperature and water content positively influenced soil microbial communities during dry season and negatively during wet season. These results facilitate our understanding of the response of soil microbial communities to climate warming and may improve predictions of ecosystem function of soil microbes in subtropical forests.     

A trait‐based framework for stream algal communities

The use of trait‐based approaches to detect effects of land use and climate change on terrestrial plant and aquatic phytoplankton communities is increasing, but such a framework is still needed for benthic stream algae. Here we present a conceptual framework of morphological, physiological, behavioural and life‐history traits relating to resource acquisition and resistance to disturbance. We tested this approach by assessing the relationships between multiple anthropogenic stressors and algal traits at 43 stream sites. Our “natural experiment” was conducted along gradients of agricultural land‐use intensity (0–95% of the catchment in high‐producing pasture) and hydrological alteration (0–92% streamflow reduction resulting from water abstraction for irrigation) as well as related physicochemical variables (total nitrogen concentration and deposited fine sediment). Strategic choice of study sites meant that agricultural intensity and hydrological alteration were uncorrelated. We studied the relationships of seven traits (with 23 trait categories) to our environmental predictor variables using general linear models and an information‐theoretic model‐selection approach. Life form, nitrogen fixation and spore formation were key traits that showed the strongest relationships with environmental stressors. Overall, FI (farming intensity) exerted stronger effects on algal communities than hydrological alteration. The large‐bodied, non‐attached, filamentous algae that dominated under high farming intensities have limited dispersal abilities but may cope with unfavourable conditions through the formation of spores. Antagonistic interactions between FI and flow reduction were observed for some trait variables, whereas no interactions occurred for nitrogen concentration and fine sediment. Our conceptual framework was well supported by tests of ten specific hypotheses predicting effects of resource supply and disturbance on algal traits. Our study also shows that investigating a fairly comprehensive set of traits can help shed light on the drivers of algal community composition in situations where multiple stressors are operating. Further, to understand non‐linear and non‐additive effects of such drivers, communities need to be studied along multiple gradients of natural variation or anthropogenic stressors.     

Drivers of Collembola assemblages along an altitudinal gradient in northeast China

Altitudinal changes in the diversity of plants and animals have been well documented; however, soil animals received little attention in this context and it is unclear whether their diversity follows general altitudinal distribution patterns. Changbai Mountain is one of few well‐conserved mountain regions comprising natural ecosystems on the Eurasian continent. Here, we present a comprehensive analysis of the diversity and community composition of Collembola along ten altitudinal sites representing five vegetation types from forest to alpine tundra. Among 7834 Collembola individuals, 84 morphospecies were identified. Species richness varied marginally significant with altitude and generally followed a unimodal relationship with altitude. By contrast, the density of Collembola did not change in a consistent way with altitude. Collembola communities changed gradually with altitude, with local habitat‐related factors (soil and litter carbon‐to‐nitrogen ratio, litter carbon content, and soil pH) and climatic variables (precipitation seasonality) identified as major drivers of changes in Collembola community composition. Notably, local habitat‐related factors explained more variation in Collembola assemblages than climatic variables. The results suggest that local habitat‐related factors including precipitation and temperature are the main drivers of changes in Collembola communities with altitude. Specifically, soil and litter carbon‐to‐nitrogen ratio correlated positively with Collembola communities at high altitudes, whereas soil pH correlated positively at low altitudes. This documents that altitudinal gradients provide unique opportunities for identifying factors driving the community composition of not only above‐ but also belowground invertebrates.     

Site History and Edaphic Features Override the Influence of Plant Species on Microbial Communities in Restored Tidal Freshwater Wetlands

Restored wetland soils differ significantly in physical and chemical properties from their natural counterparts even when plant community compositions are similar, but effects of restoration on microbial community composition and function are not well understood. Here, we investigate plant-microbe relationships in restored and natural tidal freshwater wetlands from two subestuaries of the Chesapeake Bay. Soil samples were collected from the root zone of Typha latifolia, Phragmites australis, Peltandra virginica, and Lythrum salicaria. Soil microbial composition was assessed using 454 pyrosequencing, and genes representing bacteria, archaea, denitrification, methanogenesis, and methane oxidation were quantified. Our analysis revealed variation in some functional gene copy numbers between plant species within sites, but intersite comparisons did not reveal consistent plant-microbe trends. We observed more microbial variations between plant species in natural wetlands, where plants have been established for a long period of time. In the largest natural wetland site, sequences putatively matching methanogens accounted for ∼17% of all sequences, and the same wetland had the highest numbers of genes coding for methane coenzyme A reductase (mcrA). Sequences putatively matching aerobic methanotrophic bacteria and anaerobic methane-oxidizing archaea (ANME) were detected in all sites, suggesting that both aerobic and anaerobic methane oxidation are possible in these systems. Our data suggest that site history and edaphic features override the influence of plant species on microbial communities in restored wetlands.     

Studying beta diversity: ecological variation partitioning by multiple regression and canonical analysis

Aims: Beta diversity is the variation in species composition amongsites in a geographic region. Beta diversity is a key conceptfor understanding the functioning of ecosystems, for the conservationof biodiversity and for ecosystem management. The present reportdescribes how to analyse beta diversity from community compositionand associated environmental and spatial data tables. Methods: Beta diversity can be studied by computing diversity indicesfor each site and testing hypotheses about the factors thatmay explain the variation among sites. Alternatively, one cancarry out a direct analysis of the community composition datatable over the study sites, as a function of sets of environmentaland spatial variables. These analyses are carried out by thestatistical method of partitioning the variation of the diversityindices or the community composition data table with respectto environmental and spatial variables. Variation partitioningis briefly described herein. Important findings: Variation partitioning is a method of choice for the interpretationof beta diversity using tables of environmental and spatialvariables. Beta diversity is an interesting ‘currency’for ecologists to compare either different sampling areas ordifferent ecological communities co-occurring in an area. Partitioningmust be based upon unbiased estimates of the variation of thecommunity composition data table that is explained by the varioustables of explanatory variables. The adjusted coefficient ofdetermination provides such an unbiased estimate in both multipleregression and canonical redundancy analysis. After partitioning,one can test the significance of the fractions of interest andplot maps of the fitted values corresponding to these fractions.     

拉萨河流域植物群落的数量分类与排序

青藏高原植物群落空间分异格局是异质生境条件下物种性状、种间相互作用等生态学过程共同作用的结果,对其分析有助于深入理解群落形成与环境因子之间的关系。基于拉萨河流域自然植被样带调查,采用双向指示种分析(TWINSPAN)和典范对应分析(CCA)等方法,探讨了群落的结构组成及影响其结构分异的主导环境因子。结果表明:(1) TWINSPAN数量分类将拉萨河流域草地系统划分成12个群系类型,即圆叶合头菊+唐古拉翠雀花群系;紫花针茅群系;青藏臺草群系;雪层杜鹃+鲜卑花-西藏嵩草群系;高山嵩草群系;小叶金露梅群系;硬叶柳+杯腺柳群系;水栒子+拱枝绣线菊-高山嵩草群系;绢毛蔷薇-冷蒿+白草群系;大果圆柏-垂穗披碱草群系;铺地柏-藏橐吾+高原荨麻群系;醉鱼草+砂生槐群系。12种群系类型包含了较多的植被类型,包括高寒灌丛草甸、高寒灌丛草原、稀树草原、高寒草甸和高寒草原等。(2) CCA排序表明:影响拉萨河流域植物群系分布的主要环境因子是年均温度、海拔和经度和纬度,其次是年均降雨量。(3) TWINSPAN分类与CCA排序结合反映了群系分布格局变异与环境因子之间的关系,可为拉萨河流域草地的保护和可持续利用,以及相关的植被群落研究提供参考。