Ecological assessment of vegetation from a nature reserve using regional reference data and indicator scores

A method is presented for ecological assessment of botanical sample data from a nature reserve network. The approach uses regional floristic survey data for a specific biotope as a context for spatial and temporal comparison. Assessments are based upon floristic similarity to reference vegetation types and indicator scores that summarise multivariate plant species data in relation to important environmental gradients. The approach was implemented as a software tool using floristic survey data for soligenous mires in a UK region. Plant community monitoring data were assessed against reference communities from this regional baseline to illustrate the potential advantages of the method. These include; (a) allowing links to be made between multivariate plant species data and measurements of environmental drivers, (b) providing realistic assessments of spatial and temporal differences because comparisons are against typical values of indicator scores for the region, (c) providing the scope for setting realistic criteria for vegetation monitoring.     

Ecological vegetation maps

On ecological vegetation maps, the distribution of vegetation is related to one or more features of the environment. Tolerance, competition, map scales and the environment are discussed with regard to their bearing on the geographical distribution of phytocenoses and their portrayal on maps. There are two types of ecological vegetation maps: those relating the vegetation to one environmental quality, and those with two or more such qualities. The interpretation of ecological vegetation maps is relatively simple when plant communities are related to a single quality of the biotope and difficult but usually more useful when related to several qualities. Perfection is not possible but can be approached asymptotically.     

The use of the land survey record to reconstruct pre-European vegetation patterns in the Darling Downs, Queensland, Australia

The Darling Downs is an extremely arable district in south eastern Queensland that has lost the majority of its native vegetation cover to agriculture. Vegetation references from land survey charts produced during the late 19th and early 20th century aided the reconstruction of the original vegetation patterns in the Darling Downs. Nearly 5000 references to vegetation were located for the study area and formed the basis of a vegetation map. The survey plans contain reference to seventy-three plant names which could generally be aligned to existing species, the majority of which are trees. The surveyors also referred to vegetation structure with terms such as 'open', 'shrubby' and 'dense'. The ambiguous use of some references and the lack of adequate coverage of surveyor's charts for some sections of the study area did not allow for the production of an accurate and comprehensive map using the survey record in isolation. An iterative process evolved where (i) a working map of the vegetation was produced from the survey record; (ii) the map was ground-truthed with existing remnants and ambiguities in surveyors' terminology clarified; (iii) for gaps in the record, hypotheses concerning eradicated vegetation were erected from knowledge of the environmental correlates of existing remnants; and (iv) these hypotheses were tested from areas where the survey record is comprehensive. Some vegetation types cannot be distinguished reliably on the basis of their physical environment and the distinction between these types for mapping was reliant on either the evidence from the survey record or remaining paddock trees. These processes enabled relatively accurate mapping of the pre-European vegetation of the study area at 1:100,000 scale. Comparison of the survey record and the vegetation of existing remnants suggests that overstorey composition and understorey density have changed little during European management within remnants.     

内蒙古主要植被类型与气候因子关系的研究

利用地理信息系统工具,以最新的植被类型图为依据,在统计、建模和空间模拟区域气候因子的基础上,对内蒙古主要植被类型与气候的关系进行了分析,并获得适宜的气候范围。结果表明,内蒙古植被空间分布表现出明显的规律性。一方面,随着距离海洋的远近变化,无论是地带性植被,还是山地垂直带、沙地及低湿地植被,从东向西均反映出地带分异,水分对于这种东西向更替更为重要。另一方面,热量的差异导致纬向上的变化。此外,热量成为     

Ecotope mapping for landscape ecological assessment of habitat and ecosystem

An ecotope (spatial eco-space) map that considers topography and bio-organism-relevant variables emerges as an important basic framework when landscape-scale characteristics for ecosystem management and wildlife conservation are needed. A spatio-geoecological framework based on geographic information systems (GIS) and a vegetation survey were developed for wildlife habitat evaluation of national parks and applied to a representative rugged valley area of Mt. Sorak National Park in Korea. An ecotope map was classified into hundreds of types and dozens of groups by combining biological and geophysical variables. Variables included: forest vegetation type, topographic solar radiation, normalized difference vegetation index (NDVI), elevation, and anthropogenic factors, such as, streams and roads. Layers of GIS variables were produced by field surveys, modeling, satellite images, or digitalization. Vegetation surveys were carried out to identify finer-scale distribution of vegetation types in the rugged valley area. Digital forest vegetation maps from the Forestry Administrator were then modified using the field-surveyed vegetation maps. Topographic solar radiation was predicted with a daily topographic radiation model. The NDVI was calculated from the satellite imagery of a Landsat Thematic Mapper. A digital elevation model (DEM) was used and the other layers were digitized using topographical maps with a scale of 1:25000. The aim of this study is to determine the geoecological factors relating to the spatial pattern of plant community. It was cleared by the spatial pattern of environmental variables and vegetation characteristics by detrended correspondence analysis using plant species and the environmental variables of each plot. The ordination component value of the first axis shows significant regression to some environmental variables. A case study of habitat evaluation was carried out using the resultant ecotope map. The spatial distribution of potential goral habitat and vegetation characteristics were predicted and the impact of human trails on the neighboring vegetation was also examined for restoration planning. The GIS-based framework developed for wildlife habitat evaluation is useful for natural resource management and human activity control in national parks in Korea.     

A vegetation map of The Netherlands,based on the relationship between ecotopes and types of potential natural vegetation

Summary The method of mapping the vegetation on scale 1: 200,000 and the starting points in relation to the potential natural vegetation and ecotopes, are discussed.In view of the planological background of this study, some restrictions have been added to the concept of potential natural vegetation, concerning the period of development and the human influence.The relationship between soil, ground water and vegetation was studied, which resulted in the map of the potential natural vegetation.Each type of potential natural vegetation stands for a series of vegetation types on the same site. Seven main series, with a number of sub-series are distinguished. Within each vegetation series the plant communities have been spread over five groups, according to their structure and naturalness.Ecotopes and ecotope complexes are considered as landscape ecological units. A list of ecotopes was obtained by interpreting topographical maps and by inventory data.The actual vegetation was mapped by estimating the size of the ecotopes within the separate areas. It was expressed in a five figure code for the five groups from the vegetation and ecotopes is combined into the vegetation map of The Netherlands.Interpretation problems, some of them specific for The Netherlands, are discussed and some remarks are made on the necessity of further research.Contribution to the Symposium on Plant Species and Plant Communities, held at Nijmegen, 11–12 November 1976, on the occasion of the 60th birthday of Professor Victor Westhoff.Nomenclature follows Heukels-van Ooststroom, Flora van Nederland, 18e druk, 1975, Wolters-Noordhoff, Groningen; nomenclature of syntaxa follows Westhoff & den Held (1969)     

内蒙古主要植被类型与气候因子关系的研究

利用地理信息系统工具,以最新的植被类型图为依据,在统计、建模和空间模拟区域气候因子的基础上,对内蒙古主要植被类型与气候的关系进行了分析,并获得适宜的气候范围.结果表明,内蒙古植被空间分布表现出明显的规律性.一方面,随着距离海洋的远近变化,无论是地带性植被,还是山地垂直带、沙地及低湿地植被,从东向西均反映出地带分异,水分对于这种东西向更替更为重要.另一方面,热量的差异导致纬向上的变化.此外,热量成为大兴安岭东西两麓发育的林缘草甸、草原、灌丛和低湿地等植被类型空间分布的主导因素.     

Main vegetation types and plant species diversity along an altitudinal gradient of Al Baha region,Saudi Arabia

Plant species composition patterns and vegetation types were investigated along Elevational Gradients in Al Baha region, Saudi Arabia. Sandy plain, wadis, drainage lines, rocky outcrops, hills and fallow lands occur over a wide geographic range encompassing variation in plant species and communities among these different ecological sites. To provide a quantitatively based classification of the vegetation we used Multi Variant Statistical Package (MVSP) software, followed by the re-arrangement of a matrix of the similar plant species in rows and similar sample sites in columns. Plant density and environmental variables were measured and recorded in each quadrat. Two-way indicator species analysis and Canonical Correspondence Analysis (CCA) were used to analyze the relationships between vegetation and environmental variables, while Arc Map was used to analyze the pattern of plant species density. A total of 59 sample plots (25 × 25 m), stratified, randomly-placed relevés were collected in Al Baha region, along a cross section running from south-west to north-west. About 190 plant species belonging to 59 families were recognized. This study showed that these plant species formed 15 vegetation types that primarily correspond mainly to different combinations of elevation, and topography. The study concluded that this research has provided the first quantitative and systematic survey of the vegetation in Al Baha region.     

Comparison of an intuitive mapping classification and numerical classifications of vegetation in south-east Queensland,Australia

Hierarchical agglomerative polythetic clustering of vegetation data for 51 sites from Brian Pastures Research Station, south-east Queensland, Australia, produced site and species groups that supported those formed during a previous intuitive mapping survey. On the basis of floristic composition, these analyses suggested the possible amalgamation of some map units. However, their segregation into separate units was justified on the basis of having distinct photopatterns and physiographic positions in the landscape. The classifications of the trees only (55 species) and woody plants only (115 species) data sets produced site groupings of high similarity to those constructed by the mapping survey. The addition of the herbaceous plants (266 additional species, of which 70% were annual species) tended to dominate the analyses, and produce site groupings that were less similar to the mapping groups. The distribution of many annual species appeared to be independent of the perennial plant species and underlying substrate. In wooded communities, herbaceous plants have only a minor influence on photopattern, which is the primary determinant of the mapping classification. Binary data retained a large percentage of the information contained in the quantitative data. The extra effort of gathering herbaceous data may not be justified for a broad scale mapping project, but is required for comprehensive nature conservation surveys, flora inventory, and vegetation monitoring purposes.     

Influences of the individualistic concept of vegetation on syntaxonomy

The individualistic concept of vegetation is based on three principles: (1) vegetation continuum, (2) ecological and chorological individuality of species and (3) multidimensional variability of vegetation. All principles reflect phenomena existing in nature. The conclusions arising from these principles are these: (1) plant communities (phytocoenoses) are not natural objects (wholes) as such but merely mixtures of plant individuals coexisting on the same site as the result of migration and environmental selection, (2) the classification of vegetation is quite arbitrary if not pseudoscientific, and (3) vegetation phenomena can be reduced to phenomena of plant individuals.The integrated concept of vegetation considers the phytocoenoses as real functional systems (wholes) where plant populations are integrated both by the environment and by interactions among and within plant populations. The principles of the individualistic concept, but not the above conclusions arising from them, are compatible with the integrated concept. Phytocoenoses limit the individualistic performance of species through restriction of ecological amplitudes and shifting of ecological optima (as compared with physiological amplitudes and optima). The individualistic behaviour of species does not exclude the formation of coenological groups of species which form a basis for the classification of vegetation according to floristic-coenological criteria. Under natural conditions, plant communities are usually interconnected by transition zones to form a vegetation continuum. Phenomena of the vegetation continuum do not cause greater difficulties in syntaxonomy than those of polymorphic taxonomic groups in plant taxonomy.     

A performance based consensus approach for predicting spatial extent of the Chinese windmill palm (Trachycarpus fortunei) in New Zealand under climate change

The predicted distribution of the Chinese Windmill Palm (Trachycarpus fortunei) was modelled using several algorithms with inputs consisting of occurrence information and bioclimatic datasets. A global species distribution model was developed and projected into New Zealand to provide a visualization of suitability for the species in current and future conditions. To ensure model robustness, occurrence data was checked for redundancy, spatial auto-correlation and the environmental variables checked for cross-correlation and collinearity. The final maps predicting suitability resulted from ensembling the predictions of all the algorithms. The resulting ensembled maps were weighted based on the evaluation parameters AUC, Kappa and TSS. When reclassified into low, medium and high suitability categories, results show an expansion of high suitability areas accompanied by a reduction of low suitability areas for the species. The centroids of the high suitability areas also exhibit a general movement towards the Southwest under future climate conditions. The range expansion was proportional with the representative values of emission trajectories RCPs (2.5, 4.5, 6.0 and 8.5) used in projecting into future conditions. The movement magnitude and direction of predicted high suitability area centroids for the palm supports the use of the plant as an indicator of climate change.     

The TRM Model of Potential Natural Vegetation in Mountain Forests

Due to advances in spatial modeling and improved availability of digital geodata, traditional mapping of potential natural vegetation (PNV) can be replaced by ecological modeling approaches. We developed a new model to map forest types representing the potential natural forest vegetation in the Bavarian Alps. The TRM model is founded on a three-dimensional system of the ecological gradients temperature (T), soil reaction (R), and soil moisture (M). Within such a “site cube” forest types are defined as homogenous site units that give rise to forest communities with comparable species composition, structure, production and protective functions. The three gradients were modeled using regression algorithms with area-wide, high resolution geodata on climate, relief and soil as predictors and average Ellenberg indicator values for temperature, acidity and moisture of vegetation plots as dependent variables summarizing plant responses to ecological gradients. The resulting predictor-response relationships allowed us to predict gradient positions of each raster cell in the region from geodata layers. The three-dimensional system of gradients was partitioned into 26 forest types, which can be mapped for the whole region. TRM-based units are supplemented by 22 forest types of special sites defined by other ecological factors such as geomorphology, for which individual GIS rules were developed. The application of our model results in an intermediate-scale map of potential natural forest vegetation, which is based on an explicit function of temperature, reaction and moisture and is therefore consistent and repeatable in contrast to traditional PNV maps.     

Vegetation pattern of mountains in West Greenland – a baseline for long-term surveillance of global warming impacts

Background: Steep environmental gradients, coupled with predicted high temperature rises in the Arctic make arctic mountain vegetation highly suitable for surveillance of changes related to global warming. However, guidelines and baselines for such a purpose are widely lacking since arctic mountain vegetation has been little explored.

Aims: We explore options for long-term surveillance on the basis of a detailed analysis of extant plant community patterns and their underlying environmental conditions in the mountainous inland of West Greenland.

Methods: Distribution, abundance and site conditions of vegetation types were analysed, using 664 vegetation samples and detailed vegetation maps in four altitudinal belts.

Results: Most plant communities had a restricted elevation distribution and were confined to special habitats predominantly defined by mesotopography and soil moisture.

Conclusions: Based on the strong linkage to habitat conditions, horizontal and vertical changes of species distribution and vegetation pattern are excellent indicators for inferring underlying environmental changes on three different scales. The recommendations given concerning climate sensitive species and plant communities, ecotones for setting up observation sites as well as stratification of analysis by habitats can be the basis for establishing long-term surveillance programmes on arctic mountain vegetation.     

Plant species composition shifts in the Tatra Mts as a response to environmental change: a resurvey study after 90 years

Mountain vegetation is often considered highly sensitive to climate and land-use changes due to steep environmental gradients determining local plant species composition. In this study we present plant species compositional shifts in the Tatra Mts over the past 90 years and discuss the potential drivers of the changes observed. Using historical vegetation studies of the region from 1927, we resurveyed 76 vegetation plots, recording the vascular flora of each plot using the same methodology as in the original survey. We used an indirect method to quantify plant species compositional shifts and to indicate which environmental gradients could be responsible for these shifts: by calculating shifts in estimated species optima as reflected in shifts in the ecological indicator values of co-occurring species. To find shifts in species composition, focusing on each vegetation type separately, we used ordination (DCA). The species optimum changed significantly for at least one of the tested environmental gradients for 26 of the 95 plant species tested; most of these species changed in terms of the moisture indicator value. We found that the strongest shifts in species composition were in mylonite grassland, snowbed and hygrophilous tall herb communities. Changes in precipitation and increase in temperature were found to most likely drive compositional shifts in vegetation resurveyed. It is likely that the combined effect of climate change and cessation of sheep grazing has driven a species composition shift in granite grasslands communities.     

Defining a Target Map of Native Species Assemblages for Restoration

Vegetation restoration is usually based on predefined species assemblages from large‐scale maps of potential vegetation. However, most restoration plans apply to smaller spatial scales, so a homogeneous species assemblage is usually assigned to the target site. We propose defining species assemblages for restoration by modeling the distribution of individual target species. The example presented here is about postfire restoration, but it can be used in other types of disturbed areas. We surveyed 212 plots in well‐preserved vegetation around the burned area to obtain a list of target species and physical parameters of the plots. The burned area was divided in a grid of 723 squares, 1 ha each, and then characterized according to the same physical parameters. From these data, we modeled the distribution of 23 target species. A target map of predicted species assemblages was built combining species maps. This map largely resembles the native vegetation in terms of species richness per plot, environmental gradients in α‐diversity, spatial variation in β‐diversity, and frequency of species occurrence. Comparison between the target map and the current vegetation (recovery status) indicated that, on average, only half of the potential set of species is already present in each plot. Analysis of the recovery status suggested that both rock outcrops and areas at lower altitude, with gentle slope and deeper soil, recover faster. This illustrates the utility of target maps to outline plots in more need of restoration.     

Regionalizing Indicator Values for Soil Reaction in the Bavarian Alps – from Averages to Multivariate Spectra

We present an approach to produce maps of Ellenberg values for soil reaction (R-value) in the Bavarian Alps. Eleven meaningful environmental predictors covering GIS-derived information on climatic, topographic and soil conditions were used to predict R-values. As dependent variables, Ellenberg indicator values for soil reaction were queried from plot records in the vegetation database WINALPecobase. We used an additive georegression model, which combines complex prediction models and the increased prediction accuracy of a boosting algorithm. In addition to environmental predictors we included spatial effects into the model to account for spatial autocorrelation. As we were particularly interested in the usefulness of averaged R-values for spatial prediction, we applied two different models: (1) a geo-additive regression model that estimates mean R-values and (2) a proportional odds model predicting the probability distribution over R-values 1 to 9. We found meaningful dependencies between the R-value and our predictors. Both models produced the same spatial pattern of predictions. Spatial effects had an impact only in the first model. The main drawback of mean R-values is the oversimplification of complex conditions of soil reaction, which is entailed by averaging and regression to mean values. Therefore, regionalized average indicator values provide only limited information on site-ecological characteristics. Model 1 failed to predict the range and shapes of original indicator spectra precisely. In contrast, the second model provided a more sophisticated picture of soil reaction. To make the multivariate output of model 2 comparable to that of model 1, we propose to plot the distribution in a three-dimensional color-space. In addition, comparison of both models based on a multiple linear regression model resulted in a R ² of 0.93. The proportional odds model is a promising approach also for other indicator values and different regions as well as for other ordinal-scaled ecological parameters.     

Improving predictive mapping in Swiss mire ecosystems through re‐calibration of indicator values

Question: How may Landolt indicator values be re‐calibrated to improve the performance of predictive models? Location: Mires Gross Moos Schwändital (1250 m a.s.l.) in the Prealps, Burgmoos (465 m. a.s.l.) on the Central Plateau and La Burtignière (1000 m a.s.l.) in the Jura, Switzerland. Methods: Habitat distribution models based on high resolution remotely sensed data and vegetation field data are applied to monitor 130 mires. Instead of plant species or communities we used mean indicator values of vegetation records as response variables. To improve the differential power of indicator values for wetland habitat conditions, we calibrated these values using field data. Different methods were tested with our predictive models in three mires to see which calibration method is best in enhancing model performance. To assess the effect of the uneven distribution of vegetation records along environmental gradients, calibrations based on random and evenly distributed samples were compared. As a test of the predictive power of the models we used r² between ground truth and model prediction. This approach is illustrated through an application with nutrient indicator values in the mire La Burtignière. Results: Model performances were not the same for the three mires. The predictive power was better for the nutrient values, soil reaction and humus values than for light and moisture values. 2000 records were sufficient as basis for re‐calibration. Models based on original Landolt indicator values were overall the weakest compared with re‐calibrated values. By comparing the predictive power of Models based on randomly or evenly selected records were about equally predictive. Conclusions: 1. Ahabitat‐specific re‐calibration of the Landolt indicator values enhances the predictive mapping of the Swiss mire ecosystems. 2. The re‐calibration based on weighted averaging gives a better performance than the one based on Gaussian logistic regression. 3. The uneven distribution of indicator values due to the over‐representation of mire habitats does not hamper model performance. 4. 2000 vegetation records are a sufficient basis for an optimal re‐calibration of the vegetation types. An illustration of the method is given by using the soil fertility pattern of the mire La Burtignière.     

Ecological assessment of plant communities by reference to species traits and habitat preferences

Where vegetation is managed for nature conservation, results should be assessed against criteria linked to the objectives of management. An assessment method is presented in which the goal vegetation was defined as a specific biotope limited by a set of biophysical conditions. Vegetation was sampled from field boundary strips intended for the conservation of arable plant communities. Species suited to the specified conditions (suited species) were defined by applying rule sets to a matrix of species with their traits and habitat preferences, compiled from a range of data sources. The proportional contribution of suited species to the total vegetation was calculated for each set of conditions. Scores for each condition (suited species scores) were combined to provide overall comparative site values representing the extent to which the goal vegetation was established. There was close correlation with results of a previous assessment by expert opinion poll. Variation between sites in soil type and cultivation frequency was reflected by differences in individual suited species scores. Ideally, suited species selection would be by traits alone but currently there are insufficient data available. The method is readily applicable to other vegetation types.     

Spatial modelling of ecological indicator values improves predictions of plant distributions in complex landscapes

Ecologically meaningful predictors are often neglected in plant distribution studies, resulting in incomplete niche quantification and low predictive power of species distribution models (SDMs). Because environmental data are rare and expensive to collect, and because their relationship with local climatic and topographic conditions are complex, mapping them over large geographic extents and at high spatial resolution remains a major challenge. Here, we propose to derive environmental data layers by mapping ecological indicator values in space. We combined ~6 million plant occurrences with expert-based plant ecological indicator values (EIVs) of 3600 species in Switzerland. EIVs representing local soil properties (pH, moisture, moisture variability, aeration, humus and nutrients) and climatic conditions (continentality, light) were modelled at 93 m spatial resolution with the Random Forest algorithm and 16 predictors representing meso-climate, land use, topography and geology. Models were evaluated and predictions of EIVs were compared with soil inventory data. We mapped each EIV separately and evaluated EIV importance in explaining the distribution of 500 plant species using SDMs with a set of 30 environmental predictors. Finally, we tested how they improve an ensemble of SDMs compared to a standard set of predictors for ca 60 plant species. All EIV models showed excellent performance (|r| > 0.9) and predictions were correlated reasonably (|r| > 0.4) to soil properties measured in the field. Resulting EIV maps were among the most important predictors in SDMs. Also, in ensemble SDMs overall predictive performance increased, mainly through improved model specificity reducing species range overestimation. Combining large citizen science databases to expert-based EIVs is a powerful and cost–effective approach for generalizing local edaphic and climatic conditions over large areas. Producing ecologically meaningful predictors is a first step for generating better predictions of species distribution which is of main importance for decision makers in conservation and environmental management projects.