Bird and mammal species composition in distinct geographic regions and their relationships with environmental factors across multiple spatial scales

Global patters of species distributions and their underlying mechanisms are a major question in ecology, and the need for multi‐scale analyses has been recognized. Previous studies recognized climate, topography, habitat heterogeneity and disturbance as important variables affecting such patterns. Here we report on analyses of species composition – environment relationships among different taxonomic groups in two continents, and the components of such relationships, in the contiguous USA and Australia. We used partial Canonical Correspondence Analysis of occurrence records of mammals and breeding birds from the Global Biodiversity Information Facility, to quantify relationships between species composition and environmental variables in remote geographic regions at multiple spatial scales, with extents ranging from 10⁵ to 10⁷ km² and sampling grids from 10 to 10,000 km². We evaluated the concept that two elements contribute to the impact of environmental variables on composition: the strength of species' affinity to an environmental variable, and the amount of variance in the variable. To disentangle these two elements, we analyzed correlations between resulting trends and the amount of variance contained in different environmental variables to isolate the mechanisms behind the observed relationships. We found that climate and land use‐land cover are responsible for most explained variance in species composition, regardless of scale, taxonomic group and geographic region. However, the amount of variance in species composition attributed to land use / land cover (LULC) was closely related to the amount of intrinsic variability in LULC in the USA, but not in Australia, while the effect of climate on species composition was negatively correlated to the variability found in the climatic variables. The low variance in climate, compared to LULC, suggests that species in both taxonomic groups have strong affinity to climate, thus it has a strong effect on species distribution and community composition, while the opposite is true for LULC.     

Impact of ecological redundancy on the performance of machine learning classifiers in vegetation mapping

Vegetation maps are models of the real vegetation patterns and are considered important tools in conservation and management planning. Maps created through traditional methods can be expensive and time‐consuming, thus, new more efficient approaches are needed. The prediction of vegetation patterns using machine learning shows promise, but many factors may impact on its performance. One important factor is the nature of the vegetation–environment relationship assessed and ecological redundancy. We used two datasets with known ecological redundancy levels (strength of the vegetation–environment relationship) to evaluate the performance of four machine learning (ML) classifiers (classification trees, random forests, support vector machines, and nearest neighbor). These models used climatic and soil variables as environmental predictors with pretreatment of the datasets (principal component analysis and feature selection) and involved three spatial scales. We show that the ML classifiers produced more reliable results in regions where the vegetation–environment relationship is stronger as opposed to regions characterized by redundant vegetation patterns. The pretreatment of datasets and reduction in prediction scale had a substantial influence on the predictive performance of the classifiers. The use of ML classifiers to create potential vegetation maps shows promise as a more efficient way of vegetation modeling. The difference in performance between areas with poorly versus well‐structured vegetation–environment relationships shows that some level of understanding of the ecology of the target region is required prior to their application. Even in areas with poorly structured vegetation–environment relationships, it is possible to improve classifier performance by either pretreating the dataset or reducing the spatial scale of the predictions.     

Vegetation of Barton Peninsula in the neighbourhood of King Sejong Station (King George Island,maritime Antarctic)

Plant communities were studied on Barton Peninsula around King Sejong Station on King George Island, maritime Antarctic. The objective of this study was to document the occurrence and distribution of plant assemblages to provide the bases for monitoring the effects of environmental changes and human impact on the vegetation of this area. Approximately 47% of the investigated area was covered by vegetation. Crustose lichens showed the highest mean cover (21%) among vegetation components. The total mean cover of the four dominant taxa, together with the other three major subdominant components, i.e., Usnea spp., Andreaea spp. and Sanionia georgico-uncinata, was 78.2% of the total cover of all the species. Lichen cover and species diversity increased with altitude and the time of exposure from snow. Lichens contributed substantially more to the increased species density and diversity than did bryophytes. Ten plant communities were recognized within the study area. All of them belong to the Antarctic cryptogam tundra formation; they were grouped into four subformations: fruticose lichen and moss cushion subformation, crustose lichen subformation, moss carpet subformation and moss hummock subformation. The moss turf subformation was not found on this region. The Antarctic herb tundra formation was also not found; however, the populations of both Antarctic vascular plants have rapidly expanded around Barton Peninsula in recent years, which may allow development of the Antarctic herb tundra formation in the future.     

Hotspots of uncertainty in land‐use and land‐cover change projections: a global‐scale model comparison

Model‐based global projections of future land‐use and land‐cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms of quantity and allocation of projected changes, which can severely impact the results of environmental assessments. In this study, we identify hotspots of uncertainty, based on 43 simulations from 11 global‐scale LULC change models representing a wide range of assumptions of future biophysical and socioeconomic conditions. We attribute components of uncertainty to input data, model structure, scenario storyline and a residual term, based on a regression analysis and analysis of variance. From this diverse set of models and scenarios, we find that the uncertainty varies, depending on the region and the LULC type under consideration. Hotspots of uncertainty appear mainly at the edges of globally important biomes (e.g., boreal and tropical forests). Our results indicate that an important source of uncertainty in forest and pasture areas originates from different input data applied in the models. Cropland, in contrast, is more consistent among the starting conditions, while variation in the projections gradually increases over time due to diverse scenario assumptions and different modeling approaches. Comparisons at the grid cell level indicate that disagreement is mainly related to LULC type definitions and the individual model allocation schemes. We conclude that improving the quality and consistency of observational data utilized in the modeling process and improving the allocation mechanisms of LULC change models remain important challenges. Current LULC representation in environmental assessments might miss the uncertainty arising from the diversity of LULC change modeling approaches, and many studies ignore the uncertainty in LULC projections in assessments of LULC change impacts on climate, water resources or biodiversity.     

晋北地区土地利用覆被格局的演变与模拟

区域土地利用覆被变化及未来发展情景对区域土地管理和可持续发展具有重要意义。以地处农牧交错带、土地利用覆被变化剧烈的晋北地区为研究区,获取其2010、2015年的土地利用覆被(Land use/land cover,LULC)数据,选取高程、人口、经济、气温、降水等9种影响因素作为驱动因子,采用CLUE-S模型拟合研究区2015年的土地覆被格局并判断拟合精度,在此基础上,分别设置了3种社会经济发展情景,模拟这些情景下研究区2020年的土地利用覆被格局演变。结果表明:1)晋北地区土地利用覆被以耕地、林地和草地为主,各类型土地主要呈西北斜向的条带状分布;2)Logistic回归模型可以很好地提取LULC与驱动因子之间的关系,反映不同的驱动因素对不同的土地利用类型分布格局的影响效果及程度;3)CLUE-S模型在晋北地区土地利用覆被格局的拟合上有较好的精度,模拟Kappa系数值达0.89,表明该模型能够很好地模拟晋北地区的土地利用覆被;4)情景模拟结果表明,研究区生态保护情景(c)下的土地利用覆被格局明显优于维持现状情景(a)和经济优先情景(b),建议在未来土地开发利用过程中,应当减缓工矿用地增...     

Landscape composition and configuration in the central highlands of Ethiopia

Landscape dynamics are common phenomenon in the human‐dominated environments whereby it can be observed that the composition and configuration between landscape elements change over time. This dynamism brings about habitat loss and fragmentation that can greatly alter ecosystem services at patch, class, and landscape levels. We conducted a study to examine composition and configuration of forested landscape in the central highlands of Ethiopia using satellite images of over a period of four decades, and FRAGSTAT raster dataset was used to analyze fragmentation. Our result showed five land use/land cover (LULC) types in the study area. Cultivated land and settlement land increased at the expense of forestland, shrubland, and grassland. Fragmentation analysis showed the number of patches increased for all LULC types, indicating the level of fragmentation and interspersion. Juxtaposition increased for shrubland, grassland, and cultivated lands and decreased for settlement and forestland resulting in the fragmentation and isolation of patches. The study of LULC along with fragmentation at the landscape level can help improve our understanding of the pace at which conversion of landscape elements is happening and the impacts on ecosystem services as studies of LULC are courser in nature and would not show how each land use is reducing in size, proximity and shape among other things that determine ecosystem services. Such type of studies in rural landscapes are very vital to consider appropriate land management policies for the landscape level by taking into account the interaction between each element for sustainable development. We recommend land managers, conservationists, and land owners for observing the roles of each patch in the matrix to maximize the benefits than focusing on a single element.     

Factors controlling the spatial species richness pattern of four groups of terrestrial vertebrates in an area between two different biogeographic regions in northern Spain

Aim To examine the influence of environmental variables on species richness patterns of amphibians, reptiles, mammals and birds and to assess the general usefulness of regional atlases of fauna. Location Navarra (10,421 km²) is located in the north of the Iberian Peninsula, in a territory shared by Mediterranean and Eurosiberian biogeographic regions. Important ecological patterns, climate, topography and land‐cover vary significantly from north to south. Methods Maps of vertebrate distribution and climatological and environmental data bases were used in a geographic information systems framework. Generalized additive models and partial regression analysis were used as statistical tools to differentiate (A) the purely spatial fraction, (B) the spatially structured environmental fraction and (C) the purely environmental fraction. In this way, we can evaluate the explanatory capacity of each variable, avoiding false correlations and assessing true causality. Final models were obtained through a stepwise procedure. Results Energy‐related features of climate, aridity and land‐cover variables show significant correlation with the species richness of reptiles, mammals and birds. Mammals and birds exhibit a spatial pattern correlated with variables such as aridity index and vegetation land‐cover. However, the high values of the spatially structured environmental fraction B and the low values of the purely environmental fraction A suggest that these predictor variables have a limited causal relationship with species richness for these vertebrate groups. An increment in land‐cover diversity is correlated with an increment of specific richness in reptiles, mammals and birds. No variables were found to be statistically correlated with amphibian species richness. Main conclusions Although aridity and land‐cover are the best predictor variables, their causal relationship with species richness must be considered with caution. Historical factors exhibiting a similar spatial pattern may be considered equally important in explaining the patterns of species richness. Also, land‐cover diversity appears as an important factor for maintaining biological diversity. Partial regression analysis has proved a useful technique in dealing with spatial autocorrelation. These results highlight the usefulness of coarsely sampled data and cartography at regional scales to predict and explain species richness patterns for mammals and birds. The accuracy of models appears to be related to the range perception of each group and the scale of the information.     

The relationship between species richness and standing crop in wetlands: the importance of scale

One of the few important empirical generalizations regarding herbaceous plant systems has been the demonstration that species richness is related to standing crop with maximum richness occurring at moderate levels of standing crop. This relationship is normally demonstrated by comparing among vegetation types (i.e., vegetation with different dominants). We undertook this study to test whether the species richness-standing crop relationship was evident at a finer-grained level of organization, the within vegetation type level. Fifteen wetland sites were sampled in eastern Canada and species richness and standing crop determined in each of 224 0.25 m² quadrats. Each site was relatively homogeneous in terms of the dominant species present and were therefore categorized as single vegetation types. However, as a group, the sites comprised a wide range of vegetation types.A second order polynomial regression indicated a significant bitonic relationship between species richness and standing crop at the among-vegetation types scale, that is, when all 15 sites were combined. At the within-vegetation type level, however, no significant relationships were observed (p>0.05). The results indicate that the model of species richness proposed by Grime has predictive power at a coarse-grained level of organization, among vegetation types, but does not survive the transition to a finer-grained level of organization, the within vegetation type level. Therefore, the higher level processes which structure species richness patterns among vegetation types are not the same processes which determine richness patterns within a vegetation type.     

Quantifying relationships between land‐use gradients and structural and functional indicators of stream ecological integrity

1. Modification of natural landscapes and land‐use intensification are global phenomena that can result in a range of differing pressures on lotic ecosystems. We analysed national‐scale databases to quantify the relationship between three land uses (indigenous vegetation, urbanisation and agriculture) and indicators of stream ecological integrity. Boosted regression tree modelling was used to test the response of 14 indicators belonging to four groups – water quality (at 578 sites), benthic invertebrates (at 2666 sites), fish (at 6858 sites) and ecosystem processes (at 156 sites). Our aims were to characterise the ecological response curves of selected functional and structural metrics in relation to three land uses, examine the environmental moderators of these relationships and quantify the relative utility of metrics as indicators of stream ecological integrity. 2. The strongest indicators of land‐use effects were nitrate + nitrite, delta‐15 nitrogen value (δ¹⁵N) of primary consumers and the Macroinvertebrate Community Index (a biotic index of organic pollution), while the weakest overall indicators were gross primary productivity, benthic invertebrate richness and fish richness. All indicators declined in response to removal of indigenous vegetation and urbanisation, while variable responses to agricultural intensity were observed for some indicators. 3. The response curves for several indicators suggested distinct thresholds in response to urbanisation and agriculture, specifically at 10% impervious cover and at 0.1 g m^?3 nitrogen concentration, respectively. 4. Water quality and ecosystem process indicators were influenced by a combination of temperature, slope and flow variables, whereas for macroinvertebrate indicators, catchment rainfall, segment slope and temperature were significant environmental predictor variables. Downstream variables (e.g. distance to the coast) were significant in explaining residual variation in fish indicators, not surprisingly given the preponderance of diadromous fish species in New Zealand waterways. The inclusion of continuous environmental variables used to develop a stream typology improved model performance more than the inclusion of stream type alone. 5. Our results reaffirm the importance of accounting for underlying spatial variation in the environment when quantifying relationships between land use and the ecological integrity of streams. Of distinctive interest, however, were the contrasting and complementary responses of different indicators of stream integrity to land use, suggesting that multiple indicators are required to identify land‐use impact thresholds, develop environmental standards and assign ecological scores for reporting purposes.     

Impacts of land cover changes on climate trends in Jiangxi province China

Land-use/land-cover (LULC) change is an important climatic force, and is also affected by climate change. In the present study, we aimed to assess the regional scale impact of LULC on climate change using Jiangxi Province, China, as a case study. To obtain reliable climate trends, we applied the standard normal homogeneity test (SNHT) to surface air temperature and precipitation data for the period 1951–1999. We also compared the temperature trends computed from Global Historical Climatology Network (GHCN) datasets and from our analysis. To examine the regional impacts of land surface types on surface air temperature and precipitation change integrating regional topography, we used the observation minus reanalysis (OMR) method. Precipitation series were found to be homogeneous. Comparison of GHCN and our analysis on adjusted temperatures indicated that the resulting climate trends varied slightly from dataset to dataset. OMR trends associated with surface vegetation types revealed a strong surface warming response to land barrenness and weak warming response to land greenness. A total of 81.1 % of the surface warming over vegetation index areas (0–0.2) was attributed to surface vegetation type change and regional topography. The contribution of surface vegetation type change decreases as land cover greenness increases. The OMR precipitation trend has a weak dependence on surface vegetation type change. We suggest that LULC integrating regional topography should be considered as a force in regional climate modeling.     

Environmental relationships of floristic variation in the alpine vegetation of southeast Australia

Abstract. Australian alpine vegetation is confined to the southeast of the continent and the island of Tasmania. It exhibits strong geographic patterns of floristic variation. These patterns have been attributed to variation in edaphic conditions resulting from geographic variation in substrate, climate and glacial history. This edaphic hypothesis is tested using floristic and environmental data from 166 quadrats distributed throughout the floristic and geographic range of Australian alpine vegetation. Environmental vector fitting in three-dimensional ordination space, the number of significant environmental differences between all pairs of 17 floristic groups and overall statistical analyses of the environmental differences between communities suggest a primacy of climatic variables over edaphic variables in explaining the broad patterns of floristic variation. Continentality, summer warmth, summer rainfall and winter cold all provide a better statistical explanation of floristic variation than the most explanatory of the edaphic variables, extractable P. The environmental variables that best discriminate the groups at each dichotomy of the divisive classification of the floristic data are largely climatic at the upper two levels, with edaphic, topographic and biotic variables being generally more important than climatic variables at the lower levels. Many of the edaphic variables that were most important in discriminating dichotomous groups were relatively insignificant in the broader analyses, suggesting that it is important to partition large data sets for environment/floristic analyses. The results of such partitioning show that the environmental factors most important in influencing floristic variation in alpine vegetation in Australia vary by location and geographic scale.     

Assessing the long-term impact of land-use and land-cover changes on soil erosion in Ethiopia’s Chemoga Basin using the RUSLE model

Soil erosion is one of the primary causes of environmental degradation worldwide. The Chemoga Basin—the highlands region in northwestern Ethiopia—has experienced accelerated soil erosion due to changes in land-use and land-cover (LULC) in recent decades. The Revised Universal Soil Loss Equation (RUSLE) model was used to quantify the impact of LULC changes on soil loss in the study area. Satellite images from 1987 and 2017 were used to characterize the spatial patterns of LULC changes. All RUSLE factors were mapped on a 30?m ×?30 m grid to reflect the natural and environmental conditions of the study area. An expansion of agricultural lands occurred between 1987 and 2017, while the area of natural vegetation cover such as woodlands and grasslands declined. Forest cover has recovered in recent years as a result of afforestation and eucalyptus plantations. Reflecting LULC changes, the total soil loss in the study area was estimated at 2,087,894 t year^–1 in 1987, which increased to 2,112,093 t year^–1 in 2017. Agricultural lands accounted for 89.3% and 90.1% of the total soil loss in 1987 and 2017, respectively. The results showed that slope gradient and elevation are important factors in agricultural land conversion, and thereby influence soil erosion. An understanding of the impact of LULC changes on soil erosion potential is crucial for establishing government policy and action plans to conserve natural resources in erosion-prone areas of the Ethiopian highlands.

     

Effects of bird species-level environmental preference on landscape-level richness-heterogeneity relationships

The niche-based argument that species are filtered from environments in which they cannot sustain viable populations is the basis of the Richness-Heterogeneity Relationship (RHR). However, the multi-dimensionality of niches suggests that the RHR may take different shapes along different environmental axes, with potential confounding effects if filtering along the axes is not equally strong. Here, we explore how different structural and landscape variables drive the RHR as the accumulative outcome of environmental preferences at the species-level while considering the intercorrelation between heterogeneity levels along three niche axes. We used occurrence data of avifauna from 226 sites situated along a grassland-to-woodland gradient in a Midwestern USA study area. In each site, we quantified horizontal (habitat cover type), vertical (vegetation height structure), and spatial (habitat configuration) heterogeneity and explored the shape of the observed RHR at the landscape scale, as well as the correlations among heterogeneity levels at different axes. We then fitted species distribution models to environmental variables from the three axes separately and compared the stacked probabilities of occurrences of all species to the observed species richness. We found that predictions of richness patterns improved when more than one heterogeneity axis was included in RHR models, and that habitat suitability along different axes is not equally strong. Furthermore, a unimodal RHR along the vegetation height axis, which the species distribution models revealed to be a weak predictor for most species, may arise through intercorrelation with heterogeneity along the two other axes, along which we recorded stronger signals of environmental preference at the species level. Our results emphasize the importance of selecting relevant niche axes in studies of species richness patterns because ultimately, these patterns reflect the various environmental preferences of individual species.     

How does forest landscape structure explain tree species richness in a Mediterranean context?

Although the strong relationship between vegetation and climatic factors is widely accepted, other landscape composition and configuration characteristics could be significantly related with vegetation diversity patterns at different scales. Variation partitioning was conducted in order to analyse to what degree forest landscape structure, compared to other spatial and environmental factors, explained forest tree species richness in 278 UTM 10 × 10 km cells in the Mediterranean region of Catalonia (NE Spain). Tree species richness variation was decomposed through linear regression into three groups of explanatory variables: forest landscape (composition and configuration), environmental (topography and climate) and spatial variables. Additionally, the forest landscape characteristics which significantly contributed to explain richness variation were identified through a multiple regression model. About 60% of tree species richness variation was explained by the whole set of variables, while their joint effects explained nearly 28%. Forest landscape variables were those with a greater pure explanatory power for tree species richness (about 15% of total variation), much larger than the pure effect of environmental or spatial variables (about 2% each). Forest canopy cover, forest area and land cover diversity were the most significant composition variables in the regression model. Landscape configuration metrics had a minor effect on forest tree species richness, with the exception of some shape complexity indices, as indicators of land use intensity and edge effects. Our results highlight the importance of considering the forest landscape structure in order to understand the distribution of vegetation diversity in strongly human-modified regions like the Mediterranean.     

基于多源遥感信息融合的广东省土地利用分类方法——以雷州半岛为例

准确高效的获取土地利用信息对生态环境评价非常重要。广东省地处华南热带和亚热带季风气候区,经济作物种类繁多,土地覆盖破碎,为土地利用精确分类带来很大不确定性,而常年多云雨的天气也为有效光学影像的获取带来困难。为提高土地覆盖分类精度,以雷州半岛为实验区,综合应用Landsat-TM/ETM、多时相HJ光学影像,以及X波段Terra SAR数据,通过分析不同地物类型在光谱、极化以及多时相特征上的差别,对原始图像进行特征提取。在此基础上融合多源遥感信息的地物特征运用面向对象土地覆盖分类方法获取研究区高精度的土地利用信息。结果显示这一方法能有效提高土地覆盖利用信息获取精度,为研究生态环境变化提供更准确的数据支持。     

Are there any differences between taxa groups having distinct ecological traits based on their responses to environmental factors?

The aim of this study was to explore the differences between taxa groups with different ecological strategies for persistence, regarding their responses to environmental factors and seasonal variation. We studied the relationship between the seasonal patterns and habitat attributes of the Ephemeroptera, Plecoptera, Trichoptera (EPT) and the Colepotera, Heteroptera (CH) assemblages. Sampling was carried out in May, July and October of 2009. Samples were taken according to the AQEM protocol at 10 stream sections in the Mecsek Mountains. Based on multivariate analyses (RDA, pRDA), distinctive differences were found between the EPT and the CH taxa groups regarding their response to local chemical variables and variables describing the riparian vegetation. The measured environmental variables had a higher relative influence on the distribution patterns of EPT and CH assemblages than spatial variation of species patterns. The physical structure of aquatic habitats, including the type of bedrock, had greater effects on CH than EPT patterns, whereas the structure of riparian vegetation was more important for EPT than CH. Average density and average taxon richness of EPT were seasonally variable, but CH assemblages were not.     

Patterns and gradients of diversity in South Patagonian ombrotrophic peat bogs

Many north‐hemispherical mires seemingly untouched by drainage and cultivation are influenced by a diffuse sum of man‐made environmental changes, such as atmospherical nitrogen deposition that mask general patterns in species richness and functional group responses along resource gradients. To obtain insights into natural diversity‐environment relationships, we studied the vegetation and the peat chemistry of pristine bog ecosystems in southern Patagonia along a west–east transect across the Andes. The studied bog ecosystems covered a floristic gradient from hyperoceanic blanket bogs dominated by cushion building vascular plants via a transitional mixed type to Sphagnum‐dominated raised bogs east of the mountain range. To test the influence of resource availability on diversity patterns, species richness and functional groups were related to environmental variables by calculating general regression models and generalized additive models. Species richness showed strong linear correlations to peat chemical features and the general regression model resulted in three major environmental variables (water level, total nitrogen, NH₄Cl soluble calcium), altogether explaining 76% of variance. Functional group response illustrated a clear separation along environmental gradients. Mosses dominated at the low end of a nitrogen gradient, whereas cushion plants had their optimum at intermediate levels, and graminoids dominated at high nitrogen contents. Further shifts were related to NH₄Cl soluble calcium and water level. The models documented partly non‐linear relationships between functional group response and trophical peat properties. Within the three bog types, the calculated models differed remarkably illustrating the scale‐dependency of the explanatory factors. Our findings confirmed several general patterns of species richness and functional shifts along resource gradients in a surprisingly clear way and underpin the significance of undisturbed peatlands as reference systems for testing of ecological theory and for conservation and ecological restoration in landscapes with strong human impact.     

贡湖湾退圩还湖区水位高程下植被分布格局与土壤特征

为揭示水陆交错带水位高程下植被分布格局、多样性指数和土壤特征的变化,于2015年10月对贡湖湾湿地北部生态修复区不同水位高程下植物群落组成和土壤特征进行调查,结果表明:整个研究区有165种植物,隶属65科、142属,多为多年生植物且受人为影响严重;随水位高程增加,植物群落R、H、D、J呈现逐渐递增趋势,具体表现为常年水淹区G1季节性水淹区G2水淹区G3;土壤容重及机械组成中粉、黏粒含量随水位高程升高而增加;随土壤营养物渐增其植物群落多样性增加,多样性和优势度指数与土壤全氮(TN和有机质(OM)负相关。OM含量呈"V"型先减后增分布;TN呈逐渐增多的趋势;速效钾(EP)含量无明显波动,约为13.50 mg/kg;有效磷(AP)含量先减少后基本不变;4个多样性指数间正相关;TN与OM显著正相关(R~2=0.533);OM与EP负相关(R~2=-0.144;TN与丰富度、多样性、优势度正相关;AP与4个多样性指数均正相关;pH值与4个多样性指数负相关;回归分析可见,TN和OM是影响植物群落多样性的关键因子。科学的植被管理、全面调控土壤营养盐含量有助于水陆交错带植被恢复。     

Environmental factors and community dynamics at the southernmost part of the North American Graminetum – I. On the contribution of climatic factors to temporal variation in species composition

Compositional patterns of vegetation and their relationship to temporal and spatial environmental variation, with emphasis on climatic factors, were investigated in plant communities located in the southernmost portion of the North American Graminetum, in central México. Data from 353 samples, obtained in four ecologically contrasting plant communities during 11 years, were analyzed by partial canonical correspondence analysis. Eight climatic variables and eighteen covariables (seventeen edaphic and one resource management) were included in the ordination. A relationship between floristic change and weather variation, once covariables effects were fitted, was examined. Despite a strong contrast in ecological conditions among study sites, a set of four climatic variables was finally found in which each variable contributed independently and statistically (P < 0.01) to the total variance in the vegetation data. Thus, environmental variables other than climatic could not conceal the important role of weather as a mediator of floristic change through time. Summer precipitation and summer maximum temperature showed the highest correlations with the first two species axes, 0.77 and –0.39, respectively. Contribution of these two climatic variables to variance in the vegetation data explained by environmental variables was approximately 81%. Annual species were abundant during rainy years, while abundance of perennial grasses and shrubs showed no clear relationship to weather variation. This study explicitly probes the important role of rain patterns in shaping structure and composition of semiarid communities and considers how other environmental factors can affect plant communities at the southernmost part of the North American Graminetum.     

Vegetation‐environment relationships in Atlantic European calcareous grasslands

Abstract. The relationship between vegetation and environment was investigated for calcareous grasslands in a region in the west of Spain, France, Britain and Ireland defined by climatic criteria. Vegetation was sampled using objective methods and data collected on soils, land cover, location and management. Climate data were obtained from an available database. Examination of the first axis of vegetation variation as defined by Detrended Correspondence Analysis (DCA) showed a gradient from the Irish and British samples to those from France. The Spanish samples formed a separate group on the second axis. The species composition along the gradients is discussed. Correlations between the vegetation gradients and environmental variables were determined. The strongest correlations with the first DCA axis were for temperature, latitude, soil organic matter, grazing and land cover. The second DCA axis was highly correlated with rainfall, altitude and land cover. The third and fourth DCA axes were more difficult to interpret but appeared to be related to land cover. The results indicate that climate factors are important at this scale, but should not be considered in isolation and that factors relating to land cover and management should also be taken into account.