Mapping mountain vegetation using species distribution modeling,image‐based texture analysis,and object‐based classification

Objective: The objective of this study was to map vegetation composition across a 24 000 ha watershed. Location: The study was conducted on the western slope of the Sierra Nevada mountain range of California, USA. Methods: Automated image segmentation was used to delineate image objects representing vegetation patches of similar physiognomy and structure. Image objects were classified using a decision tree and data sources extracted from individual species distribution models, Landsat spectral data, and life form cover estimates derived from aerial image‐based texture variables. Results: A total of 12 plant communities were mapped with an overall accuracy of 75% and a χ‐value of 0.69. Species distribution model inputs improved map accuracy by approximately 15% over maps derived solely from image data. Automated mapping of existing vegetation distributions, based solely on predictive distribution model results, proved to be more accurate than mapping based on Landsat data, and equivalent in accuracy to mapping based on all image data sources. Conclusions: Results highlight the importance of terrain, edaphic, and bioclimatic variables when mapping vegetation communities in complex terrain. Mapping errors stemmed from the lack of spectral discernability between vegetation classes, and the inability to account for the confounding effects of land use history and disturbance within a static distribution modeling framework.     

Geomorphological disturbance affects ecological driving forces and plant turnover along an altitudinal stress gradient on alpine slopes

The altitudinal gradient is considered as a stress gradient for plant species because the development and fitness of plant communities tend to decrease as a result of the extreme environmental conditions present at high elevations. Abiotic factors are predicted to be the primary filter for species assemblage in high alpine areas, influencing biotic interactions through both competition for resources and positive interactions among species. We hypothesised that the relative importance of the ecological driving forces that affect the biotic interactions within plant communities changes along an elevation gradient on alpine debris slopes. We used multiple gradient analyses of 180 vegetation plots along an altitudinal range from ~1,600 to 2,600 m and single 100 m-bands in the Adamello-Presanella Group (Central Alps) to investigate our hypothesis; we measured multiple environmental variables related to different ecological driving forces. Our results illustrate that resource limitations at higher elevations affect not only the shift from competition to facilitation among species. A geomorphological disturbance regime along alpine slopes favours the resilience of the high-altitude species within topographic/geomorphological traps. An understanding of the ecological driving forces and positive interactions as a function of altitude may clarify the mechanisms underlying plant responses to present and future environmental changes.     

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。     

Broad-scale adaptive genetic variation in alpine plants is driven by temperature and precipitation

Identifying adaptive genetic variation is a challenging task, in particular in non-model species for which genomic information is still limited or absent. Here, we studied distribution patterns of amplified fragment length polymorphisms (AFLPs) in response to environmental variation, in 13 alpine plant species consistently sampled across the entire European Alps. Multiple linear regressions were performed between AFLP allele frequencies per site as dependent variables and two categories of independent variables, namely Moran's eigenvector map MEM variables (to account for spatial and unaccounted environmental variation, and historical demographic processes) and environmental variables. These associations allowed the identification of 153 loci of ecological relevance. Univariate regressions between allele frequency and each environmental factor further showed that loci of ecological relevance were mainly correlated with MEM variables. We found that precipitation and temperature were the best environmental predictors, whereas topographic factors were rarely involved in environmental associations. Climatic factors, subject to rapid variation as a result of the current global warming, are known to strongly influence the fate of alpine plants. Our study shows, for the first time for a large number of species, that the same environmental variables are drivers of plant adaptation at the scale of a whole biome, here the European Alps.     

采用广义加法模型整合数字高程模型和遥感数据进行植被分布预测

为了采用广义加法模型整合数字高程模型和遥感数据进行植被分布的预测, 并探索耦合环境变量和遥感数据作为预测变量是否能够有效地提高植被分布预测的精度, 选择海拔、坡度、至黄河最近距离、至海岸线最近距离, 以及从SPOT5遥感影像中提取的光谱变量作为预测变量, 采用广义加法模型整合环境变量和光谱变量, 建立植被分布预测模型。研究设置3种建模情景(以环境变量作为预测变量, 以光谱变量作为预测变量, 综合使用环境变量与光谱变量作为预测变量)对黄河三角洲的优势植被类型的分布进行了预测, 并对预测结果采用偏差分析、受试者工作特征曲线和野外采样点对比等3种方法进行了验证。结果表明: (1)基于广义加法模型的植被分布预测方法具有一定的实用性, 可以较为准确地预测植被的分布; 盖度较高的植被类型预测精度较高, 盖度较低的植被类型预测精度较低, 植物群落结构的特点是出现这些差异的主要原因; 综合使用环境变量和光谱变量作为预测变量的模型, 预测精度高于单独以环境变量或者光谱变量作为预测变量的模型。(2)环境变量、光谱变量大多被选入模型, 二者均对植被分布预测有重要的作用; 同一预测变量在不同植被类型的预测模型中的贡献不同, 这与植被的光谱、环境特征差异有关; 同一预测变量在不同的建模情景下对模型的贡献不同, 环境变量与光谱变量的耦合效应可能是导致预测变量对模型的贡献出现变化的原因。     

藏北高原草地群落的数量分类与排序

采用TWINSPAN数量分类和DCA、CCA排序的方法,对藏北高原草地29个样点进行统计分析。结果显示:(1)TWINSPAN数量分类将藏北高寒草地群落划分成10种类型。(2)样点DCA排序第一轴基本反映了水分环境梯度,第二轴基本反映了热量梯度。(3)TWINSPAN分类所划分的各群落在DCA排序图上都有各自的分布范围和界限,说明DCA排序能较好的反应各优势群落与其环境资源之间的关系。(4)样点CCA排序表明,影响群落分布的首要环境因子是水分因子(年均降水量)和空间因子(经度),其次是热量因子(年均温度),CCA排序进一步阐明了群落分布决定于水分和温度等环境因子,并间接验证了TWINSPAN的分类结果。(5)物种CCA排序和TWINSPAN分类结果表明:植物群落中物种的分布格局与植物群落类型的分布格局存在一定的相似性。     

Modelling plant species distribution in alpine grasslands using airborne imaging spectroscopy

Remote sensing using airborne imaging spectroscopy (AIS) is known to retrieve fundamental optical properties of ecosystems. However, the value of these properties for predicting plant species distribution remains unclear. Here, we assess whether such data can add value to topographic variables for predicting plant distributions in French and Swiss alpine grasslands. We fitted statistical models with high spectral and spatial resolution reflectance data and tested four optical indices sensitive to leaf chlorophyll content, leaf water content and leaf area index. We found moderate added-value of AIS data for predicting alpine plant species distribution. Contrary to expectations, differences between species distribution models (SDMs) were not linked to their local abundance or phylogenetic/functional similarity. Moreover, spectral signatures of species were found to be partly site-specific. We discuss current limits of AIS-based SDMs, highlighting issues of scale and informational content of AIS data.     

Importance of soil nutrients in the distribution of forest communities on a large geographical scale

Aim Soil nutrient content plays a key role in plant growth through mineral nutrition and toxicity. Its impact on plant species and community distribution is studied on a large geographical scale through surrogates like topography or geology. We investigated the importance of soil pH and C:N ratio, as direct nutritional gradients, to determine, with climatic factors, the spatial distribution of plant communities over large territories. Location We studied the distribution of six beech habitats of the NATURA 2000 network throughout France (550,000 km²). Methods Models were calibrated with 2108 floristic plots classified in the NATURA 2000 system and including climatic and topographic variables and soil nutritional measurements carried out in a laboratory. Logistic regression was used to model habitat distribution according to environmental variables. Climatic layers, a digital elevation model and maps of soil pH and nitrogen content, created using plant indicator values and large floristic databases, were used to map the sites suitable for beech communities. Distribution models were evaluated with an independent set of 2091 phytosociological plots. Results pH and nitrogen supply were the key distribution drivers for four of the six beech communities on a national scale. Their use in the distribution models distinguished within homogeneous climatic territories a gradient of nutritional conditions from acidic areas, suitable for nutrient‐poor beech communities, to calcareous areas suitable for nutrient‐rich ones. Predicted maps of beech habitats fit the spatial distribution of validation plots. Main conclusions Soil pH and nitrogen supply strongly improve predictions of forest community distribution carried out with climatic variables on a broad geographical scale. They allow delineation of areas with nutritional conditions suitable for each community, as well as the realization of predictive high‐resolution maps over large areas useful for sustainable and conservation management. Nomenclature Tutin & Heywood (2001 ) Flora Europaea. Cambridge University Press, Cambridge.     

Vegetation composition and its relationship with the environment in mallines of north Patagonia,Argentina

“Mallines” are characteristic Patagonian wet meadows. The objectives of this study were to describe plant community composition in the main mallines in northern Patagonia and to determine the influence of selected environmental variables on the distribution of vegetation. Fifty-two sites were selected for vegetation surveys and measurements of water table (WT) depth, soil pH, electric conductivity (EC), and mean annual precipitation. We performed cluster analysis for vegetation classification and correspondence analysis (CA) and canonical correspondence analysis (CCA) for vegetation ordination. Plant composition was mostly related to both environmental variables and longitude and that it was not possible to disentangle the two (i.e. the vegetation was spatially structured). We defined three plant communities that differed along two main environmental gradients. The main gradient operates on a regional scale and is determined, from west to east, by a decrease in mean annual precipitation and an increase in the depth of the WT, soil pH, and EC. The secondary gradient operates on a site scale and is determined by topographic features inside the mallín and their influence on the hydrological regime (increasing moisture from the border towards the center). This second gradient allowed us to distinguish two plant communities, one of wet characteristics in the centers of the mallín, and another of mesic characteristics along the borders of the mallín.     

Satellite surface reflectance improves habitat distribution mapping: a case study on heath and shrub formations in the Cantabrian Mountains (NW Spain)

Aim We aim to map the distribution of four heath and shrub formations constituting habitats of high conservation priority in Europe, whose occurrence is strongly dependent on human activities. Specifically, we assess whether the use of LANDSAT data in habitat distribution modelling may account for land use management, allowing accurate mapping of real distribution patterns. In particular, we explore whether reflectance values may be a better alternative to other remote sensing data traditionally used in modelling approaches (i.e. spectral vegetation indices and classified land cover maps). Finally, we test whether modelling performance is affected by the ecological traits of the dominant species of the target formations. Location Cantabrian Mountains (NW Spain). Methods We generated maps for the four formations (two specialists vs. two generalists) using MaxEnt. First, we ran the models with environmental predictors only (topography, climate, lithology and human disturbances). Then, we compared the advantages of including, in turn, different data derived from LANDSAT imagery: reflectance values (corresponding to different wavelength channels of the multispectral image), a spectral index and a land cover map. We assessed changes in explanatory power and also in the formation’s predicted distribution patterns. Results Formations dominated by specialist species were accurately mapped on a base of environmental variables only, whereas those dominated by generalists were overpredicted. Average mean temperature, southness and distance to urban areas were the variables contributing most in predictions of environmental models. LANDSAT channels increased the accuracy of all models, but mainly those for formations dominated by generalist species. They showed advantages against other remote sensing data traditionally used in modelling approaches. Main conclusions Habitat distribution models allowed accurate mapping of heath and shrub formations. The use of reflectance values as predictors improved the accuracy of the models, particularly for formations dominated by generalist species, supplying environmental information that was otherwise unavailable.     

陕西子午岭生态因素对植物群落的影响

为探讨生境对植被格局分布的影响,对黄土高原马栏林区60块样地进行植被学调查的基础上,采用17个环境指标刻画植物群落的空间位置、地形和土壤特征;利用双向指示种分析(TWINSPAN)划分了该区不同演替阶段的植物群落类型;利用前向选择法(forward selection)及Monte Carlo检验对不同演替阶段植物群落物种组成影响显著(p＜0.05)的环境因子进行筛选;利用去势典范对应分析(DCCA)排序方法分析不同演替阶段植物群落分布格局与环境的关系;利用偏典范对应分析(partial CCA)定量分离环境、空间及其交互作用对植被格局总体变异的影响.结果表明:(1)马栏林区的植物群落可划分为13个类型,分别属于4个不同的演替阶段;(2)对演替初期阶段群落影响显著的环境因子是土壤含盐量和碱解氮,对演替过渡阶段群落影响显著的环境因子是海拔和腐殖质厚度,对演替亚顶级阶段群落影响显著的因子是海拔、坡向、枯落物厚度、腐殖质厚度和pH值,而对演替顶级阶段群落分异影响显著的因子是海拔、坡向、pH值和速效磷;(3)不同演替阶段群落的生态学特性和分布规律与环境空间的生态梯度格局吻合较好;(4)随着演替的进行,环境因子单独对植物群落的影响越来越大,而样地位置单独作用和样地位置与环境因子的交互作用之和越来越小.     

长白山北坡木本植物分布与环境关系的典范对应分析

 在长白山北坡海拔700～2 600 m的坡面上,海拔每上升100 m设立一个样点,共计20个样点。调查每个样点中木本植物的生态重要值,并计测样点内包括气候、土壤、林冠郁闭度在内的13个环境因子。应用CANOCO3.12软件对获得的数据进行了典范对应分析(CCA),应用CANODRAW3.0作出了种类     

Eco-Floristic studies of native plants of the Beer Hills along the Indus River in the districts Haripur and Abbottabad,Pakistan

The present study was conducted to elaborate vegetation composition structure to analyze role of edaphic and topographic factors on plant species distribution and community formation during 2013–14. A mixture of quadrat and transect methods were used. The size of quadrat for trees shrubs and herbs were 10 × 5, 5 × 2, 1 × 1 meter square respectively. Different phytosociological attribute were measured at each station. Primary results reported 123 plant species belong to 46 families. Asteraceae and Lamiaceae were dominant families with 8 species each. PCORD version 5 were used for Cluster and Two Way Cluster Analyses that initiated 4 plant communities within elevation range of 529–700 m from sea level. Indicator species analyses (ISA) were used to identify indicator species of each community. CANOCO Software (version 4.5) was used to measure the influence of edaphic and topographic variables on species composition, diversity and community formation. Whereas Canonical Correspondence Analysis (CCA) was used to measure the effect of environmental variables which showed elevation and aspect were the stronger environmental variable among topographic and CaCO₃ contents, electric conductivity, soil pH were the stronger edaphic factors in determination of vegetation and communities of the Bheer Hills. Grazing pressure was one of the main anthropogenic factors in this regard.     

Environment‐driven changes in diversity of riparian plant communities along a mountain river

The study of changes in species richness and composition along rivers has focused on large spatial scales. It has been ignored that in different sections of the river (high mountain area, middle zone, and mouth of the river) the specific environmental conditions can generate different longitudinal patterns of the species richness and composition. In this study, we determine whether species richness and composition of the riparian plant communities change along a mountain river and whether these changes are related to environmental variables. We expect an increase in species richness and turnover along the river, that the upstream communities would be a subset of the downstream communities, and that such would be related to edaphic and hydrologic conditions. To test this, we sampled three strata of the riparian vegetation (upper: individuals with <1 cm of ND, middle: individuals with >1 cm of ND, low: individuals with >1 m tall) in a set of 15 sites that we place along a mountain river. Additionally, we recorded topographic, hydrological, morphological, and soil variables. We performed correlation analyzes to determine whether changes in species richness and turnover were related to increased distance to the origin of the river. Also, we obtained the nestedness and evaluated the importance of environmental variables with GLM, LASSO regression, and CCA. With the increase in distance, the species richness decreases in the upper stratum, but not in the middle and the low stratum (although the highest values were observed near the origin of the river), the turnover increase in all strata and the upstream communities were not a subset of the downstream communities. The changes in species richness and composition were related to topographic (altitude), hydrological (flow), and edaphic (conductivity and pH) variables. Our results indicate that at small spatial scales the patterns of richness and composition differ from what has been found at larger spatial scales and that these patterns are associated with environmental changes in the strong altitude gradients of mountain rivers.     

丹江口水库水滨带植物群落空间分布及环境解释

探讨了环境因素对丹江口水库(南水北调中线水源地)水滨带植物群落空间分布的影响。通过对水滨带植物群落和环境因素的实地调查,用双向指示种分析(TWINSPAN)对201个水滨带植物群落进行分类;结合地形、土壤和水文因素用除趋势典范对应分析法(DCCA)分析环境因素对水滨带植物群落的影响;并对环境因素的解释能力进行定量分离。结果表明:(1)水滨带植物群落包括7种类型,分别是萹蓄群落、苘麻群落、细叶水芹+狗牙根群落、狗牙根群落、响叶杨-狗牙根群落、杜梨-白刺花-狗牙根群落和侧柏-牡荆-三穗苔草群落;(2)海拔和水淹影响对水滨带植物群落空间分布具有主导作用。海拔升高,水淹影响减弱,植物群落呈现由草本植物群落向木本植物群落变化的格局;(3)土壤因素的解释能力大于地形因素,水文因素的解释能力最小。各类环境因素之间存在交互作用,地形、水文和土壤因素三者间的交互作用最大,地形和土壤因素之间的交互作用最小。环境因素共解释水滨带植物群落空间分布的21.99%,未解释部分为78.01%。结果证明环境对植被的解释能力是由植被的复杂程度决定的,植被越复杂,环境的解释能力越低。     

拉萨河谷草地群落的数量分类与排序

采用TWINSPAN数量分类和DCA、CCA排序的方法,对拉萨河谷草地23个样点进行统计分析。结果显示:(1)TWINSPAN数量分类将拉萨河谷草地群落划分成8种类型,拉萨河谷的草地群落分布呈现明显的垂直地带性分布格局。(2)TWINSPAN分类所划分的各群落在DCA排序图上都有各自的分布范围和界限,说明DCA排序能较好的反应各群落与其环境资源之间的关系,同时,TWINSPAN的分类结果也在排序图上得到较好的印证。(3)样点DCA排序的第一轴基本反映了海拔高度的变化梯度,第二轴基本反映了坡向的变化。(4)样点CCA排序表明,影响群落分布的主要环境因子是海拔,其次是坡向。CCA排序进一步阐明了拉萨河谷草地群落分布决定于海拔和坡向等环境因子,并间接验证了TWINSPAN的分类结果。(5)物种CCA排序和TWINSPAN分类结果表明:植物群落中物种的分布格局与植物群落类型的分布格局存在一定的相似性,物种的分布格局在很大程度上影响着群落的分布格局。     

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.     

Species richness and species composition of fungal communities associated with cellulose decomposition at different altitudes on the Tibetan Plateau

Aims The aims of this study were to compare the fungal communities developing on cotton strips at three different altitudes on the Tibetan Plateau and to assess the environmental variables influencing them.Methods Cotton strips that had been buried in soil for a year were sampled at three sites at different altitudes (4500, 4950 and 5200 m) located on a southeast-facing slope on the Nyainqentanglha Mountains near Damxung. The fungi on the cotton strips were isolated using a modified washing method. The decomposition abilities and colony growth properties of the major species cultured in pure-culture conditions were investigated and compared. Canonical correspondence analysis (CCA) was used to evaluate the relationships between fungal community composition and environmental variables (altitude, soil depth, soil water content [SWC], plant root mass and gravel content).Important findings A total of 24 species were isolated from the cotton strips, and 12 species occurred frequently and were regarded as major species. The number of fungal species was lower at the 4950-m altitude site than at the other two sites, indicating that not only altitude but also other factors affected the number of species present. All of the major species were able to decompose the cotton strips. In the CCA ordination, automatic forward selection revealed that altitude, SWC and plant root mass significantly affected fungal species composition. Our results suggest that species number and the composition of cellulolytic fungal communities are highly correlated with environmental variables as well as altitude in the alpine meadow on the Tibetan Plateau.     

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.