Indicators of nitrate in wetland surface and soil-waters: interactions of vegetation and environmental factors

This paper describes a new bio-indicator method for assessing wetland ecosystem health: as such, the study is particularly relevant to current legislation such as the EU Water Framework Directive, which provides a baseline of the current status Of Surface waters. Seven wetland sites were monitored across northern Britain, with model construction data for predicting, eco-hydroloplical relationships collected from five sites during 1999, Two new sites and one repeat site were monitored during 2000 to provide model test data. The main growing season for the vegetation, and hence the sampling period, was May-August during both years. Seasonal mean concentrations of nitrate (NO3-) in surface and soil water samples during 1999 ranged from 0.01 to 14.07 mg N 1(-1), with a mean value of 1.01 mg N 1(-1). During 2000, concentrations ranged from trace level (<0.01 m- N 1(-1)) to 9.43 mg N 1(-1), with a mean of 2.73 mg N 1(.)(-1) Surface and soil-water nitrate concentrations did not influence plant species composition significantly across representative tall herb fen and mire communities. Predictive relationships were found between nitrate concentrations and structural characteristics of the wetland vegetation, and a model was developed which predicted nitrate concentrations from measures of plant diversity, canopy structure and density of reproductive structures. Two further models, which predicted stem density and density of reproductive structures respectively, utilised nitrate concentration as one of the independent predictor variables. Where appropriate, the models were tested using data collected during 2000. This approach is complementary to species-based monitoring, representing a useful and simple too] to assess ecological status in target wetland systems and has potential for bio-indication purposes.

Land degradation and vegetation distribution in Chott El Beida wetland, Algeria

The aim of this study is to explore the environmental factors that determine plant Community distribution in northeast Algeria. This paper provides a quantitative analysis of the vegetation-environment relationships for a study site in the Cholt El Beida wetland, a RAMSAR site in Setif, Algeria. Sixty vegetation plots were sampled and analysed using TWINSPAN and Detrended Correspondence Analysis (DCA) in order to identify the principal vegetation communities and determine the environmental gradients associated with these. 127 species belonging to 41 families and 114 genera were recorded. Six of the recorded species were endemic representing 4.7% of the total species. The richest families were Compositae, Gramineae, Cruciferae and Chenopodiaceae. Therophytes and hemicryptophytes were the most frequent life forms. the Mediterranean floristic element is dominant and is represented by 39 species. The samples were classified into four main community types. The principal DCA axes represent gradients of soil salinity, moisture and anthropogenic pressure. The use of classification in combination with ordination techniques resulted in a good discrimination between plant communities and a greater understanding of controlling environmental factors. The methodology adopted can be employed for improving baseline information on plant community ecology and distribution in often critically endangered Mediterranean wetland areas. (C) 2008 Elsevier Ltd. All rights reserved.

Holocene vegetation dynamics in the northeastern Rub' al-Khali desert, Arabian Peninsula: a phytolith, pollen and carbon isotope study

The Holocene vegetation history of the Arabian Peninsula is poorly understood, with few palaeobotanical studies to date. At Awafi, Ras al-Khaimah, UAE, a 3.3 m lake sediment sequence records the vegetation development for the period 8500 cal. yr BP to similar to3000 cal. yr BP. delta(13)C isotope, pollen and phytolith analyses indicate that C3 Pooid grassland with a strong woody element existed during the early Holocene (between 8500 and 6000 cal. yr BP) and became replaced by mixed C3 and C4 grasses with a strong C4 Panicoid tall grass element between 5900 and 5400 cal. yr BP. An intense, arid event Occurred at 4100 cal. yr BP when the lake desiccated and was infilled by Aeolian sand. From 4100 cal. yr BP the vegetation was dominated by C4 Chloridoid types and Cyperaceae, suggesting an incomplete vegetation cover and Aeolian dune reactivation owing to increased regional aridity. These data outline the ecosystem dynamics and carbon cycling in response to palaeomon-soon and north-westerly variability during the Holocene. Copyright (C) 2004 John Wiley Sons, Ltd.

A geostatistical analysis of soil, vegetation, and image data characterizing land surface variation

The elucidation of spatial variation in the landscape can indicate potential wildlife habitats or breeding sites for vectors, such as ticks or mosquitoes, which cause a range of diseases. Information from remotely sensed data could aid the delineation of vegetation distribution on the ground in areas where local knowledge is limited. The data from digital images are often difficult to interpret because of pixel-to-pixel variation, that is, noise, and complex variation at more than one spatial scale. Landsat Thematic Mapper Plus (ETM+) and Satellite Pour l'Observation de La Terre (SPOT) image data were analyzed for an area close to Douna in Mali, West Africa. The variograms of the normalized difference vegetation index (NDVI) from both types of image data were nested. The parameters of the nested variogram function from the Landsat ETM+ data were used to design the sampling for a ground survey of soil and vegetation data. Variograms of the soil and vegetation data showed that their variation was anisotropic and their scales of variation were similar to those of NDVI from the SPOT data. The short- and long-range components of variation in the SPOT data were filtered out separately by factorial kriging. The map of the short-range component appears to represent the patterns of vegetation and associated shallow slopes and drainage channels of the tiger bush system. The map of the long-range component also appeared to relate to broader patterns in the tiger bush and to gentle undulations in the topography. The results suggest that the types of image data analyzed in this study could be used to identify areas with more moisture in semiarid regions that could support wildlife and also be potential vector breeding sites.

A GIS-based empirical model for vegetation prediction in Lefka Ori, Crete

The aim of the study was to establish and verify a predictive vegetation model for plant community distribution in the alti-Mediterranean zone of the Lefka Ori massif, western Crete. Based on previous work three variables were identified as significant determinants of plant community distribution, namely altitude, slope angle and geomorphic landform. The response of four community types against these variables was tested using classification trees analysis in order to model community type occurrence. V-fold cross-validation plots were used to determine the length of the best fitting tree. The final 9node tree selected, classified correctly 92.5% of the samples. The results were used to provide decision rules for the construction of a spatial model for each community type. The model was implemented within a Geographical Information System (GIS) to predict the distribution of each community type in the study site. The evaluation of the model in the field using an error matrix gave an overall accuracy of 71%. The user's accuracy was higher for the Crepis-Cirsium (100%) and Telephium-Herniaria community type (66.7%) and relatively lower for the Peucedanum-Alyssum and Dianthus-Lomelosia community types (63.2% and 62.5%, respectively). Misclassification and field validation points to the need for improved geomorphological mapping and suggests the presence of transitional communities between existing community types.

Environmental factors and vegetation composition, Lefka Ori Massif, Crete, S. Aegean

Aim The aim of this study was to explore the environmental factors that determine the spatial distribution of oro-mediterranean and alti-mediterranean plant communities in Crete. Location The paper provides a quantitative analysis of vegetation-environment relationships for two study areas within the Lefka Ori massif Crete, a proposed Natura 2000 site. Methods Eleven environmental variables were recorded: altitude, slope, aspect, percentage of bare rock, percentage of unvegetated ground, soil depth, pH, organic matter content and percentages of sand, silt and clay content. Classification of the vegetation was based on twinspan, while detrended correspondence analysis (DCA) and canonical correspondence analysis (CCA) were used to identify environmental gradients linked to community distribution. Results One hundred and twenty-five species were recorded from 120 plots located within the two study areas. Forty-seven of the recorded species are endemic, belonging to 35 families. Hemicryptophytes and chamaephytes were the most frequent, suggesting a typical oro-mediterranean life form spectrum. The samples were classified into five main community types and one transitional. The main gradients, identified by CCA, were altitude and surface cover type in the North-west site, while in the Central site the gradients were soil formation-development and surface cover type. Main conclusions The use of classification in combination with ordination techniques resulted in a good discrimination between plant communities and a greater understanding of controlling environmental factors. The methodology adopted can be employed for improving baseline information on plant community ecology and distribution in Mediterranean mountain zones.

Predictive vegetation mapping in the Mediterranean context: Considerations and methodological issues

The need to map vegetation communities over large areas for nature conservation and to predict the impact of environmental change on vegetation distributions, has stimulated the development of techniques for predictive vegetation mapping. Predictive vegetation studies start with the development of a model relating vegetation units and mapped physical data, followed by the application of that model to a geographic database and over a wide range of spatial scales. This field is particularly important for identifying sites for rare and endangered species and locations of high biodiversity such as many areas of the Mediterranean Basin. The potential of the approach is illustrated with a mapping exercise in the alti-meditterranean zone of Lefka Ori in Crete. The study established the nature of the relationship between vegetation communities and physical data including altitude, slope and geomorphology. In this way the knowledge of community distribution was improved enabling a GIS-based model capable of predicting community distribution to be constructed. The paper describes the development of the spatial model and the methodological problems of predictive mapping for monitoring Mediterranean ecosystems. The paper concludes with a discussion of the role of predictive vegetation mapping and other spatial techniques, such as fuzzy mapping and geostatistics, for improving our understanding of the dynamics of Mediterranean ecosystems and for practical management in a region that is under increasing pressure from human impact.

Remote sensing of tidal networks and their relation to vegetation

The study of the morphology of tidal networks and their relation to salt marsh vegetation is currently an active area of research, and a number of theories have been developed which require validation using extensive observations. Conventional methods of measuring networks and associated vegetation can be cumbersome and subjective. Recent advances in remote sensing techniques mean that these can now often reduce measurement effort whilst at the same time increasing measurement scale. The status of remote sensing of tidal networks and their relation to vegetation is reviewed. The measurement of network planforms and their associated variables is possible to sufficient resolution using digital aerial photography and airborne scanning laser altimetry (LiDAR), with LiDAR also being able to measure channel depths. A multi-level knowledge-based technique is described to extract networks from LiDAR in a semi-automated fashion. This allows objective and detailed geomorphological information on networks to be obtained over large areas of the inter-tidal zone. It is illustrated using LIDAR data of the River Ems, Germany, the Venice lagoon, and Carnforth Marsh, Morecambe Bay, UK. Examples of geomorphological variables of networks extracted from LiDAR data are given. Associated marsh vegetation can be classified into its component species using airborne hyperspectral and satellite multispectral data. Other potential applications of remote sensing for network studies include determining spatial relationships between networks and vegetation, measuring marsh platform vegetation roughness, in-channel velocities and sediment processes, studying salt pans, and for marsh restoration schemes.