Home About us Contact
|
Home About us Contact | ||
|
|
||
Vegetation Classification (vegetation + classification)
Selected AbstractsThe conservation management of upland hay meadows in Britain: a reviewGRASS & FORAGE SCIENCE, Issue 4 2005R. G. Jefferson Abstract Upland hay meadows conforming to MG3 in the National Vegetation Classification of the UK are a rare habitat in Britain and are largely confined to upland valleys in northern England. Agricultural intensification, particularly ploughing and reseeding and a shift from hay-making to silage production over the last 50 years, has resulted in large losses of species-rich upland hay meadows. Remaining species-rich meadows have been the focus of much nature conservation effort resulting in many of the species-rich sites being protected by statutory designations or through voluntary agri-environment scheme agreements. Research and monitoring has tended to confirm that species richness is maximized by management involving spring and autumn grazing, a mid-July hay cut, no inorganic fertilizer and possibly low levels of farmyard manure. Deviations from this regime result in a loss of species richness. Restoration of semi-improved grassland to swards resembling species-rich MG3 also requires a similar regime but is also dependent on the introduction of seed of appropriate species. The role of Rhinanthus minor as a tool for manipulating meadow biodiversity during restoration management is discussed. Suggestions for future research are outlined. [source] Restoration of species-rich grassland on arable land: assessing the limiting processes using a multi-site experimentJOURNAL OF APPLIED ECOLOGY, Issue 2 2002Richard F. Pywell Summary 1Agricultural intensification has resulted in the reduction and fragmentation of species-rich grasslands across much of western Europe. 2We examined the key ecological processes that limit the creation of diverse grassland communities on ex-arable land in a multi-site experiment over a wide variety of soil types and locations throughout lowland Britain. 3The results showed it was possible to create and maintain these communities successfully under a hay-cutting and grazing management regime. Furthermore, there was a high degree of repeatability of the treatment effects across the sites. 4Lack of seed of desirable species was the key factor limiting the assembly of diverse grassland communities. Sowing a species-rich seed mixture of ecologically adapted grassland plants was an effective means of overcoming this limitation. Community assembly by natural colonization from the seed bank and seed rain was a slow and unreliable process. However, there was no evidence to suggest that sowing a species-poor grass-dominated seed mixture made the vegetation any less susceptible to colonization by desirable species than allowing natural regeneration to take place. 5Deep cultivation caused significant reductions in soil P and K concentrations across the sites. This had a significant beneficial effect on the establishment and persistence of sown forbs in all years. It also resulted in a significant reduction in the number of unsown weedy grasses. However, for both variables these differences were very small after 4 years. 6Sowing a nurse crop significantly reduced the number of unsown grass species, but had no beneficial effect on the establishment of desirable species. 7Treatments sown with the species-rich seed mixture following deep cultivation corresponded most closely to the specified target communities defined by the UK National Vegetation Classification. Natural regeneration and treatments sown with the species-poor seed mixture were much less similar to the target. The sites on circum-neutral soils achieved the greatest degree of similarity to the target. Those on calcareous and acid soils failed to achieve their targets and most closely resembled the target for neutral soils. This reflected the poor performance of the sown preferential species for these communities. [source] Phenological description of natural vegetation in southern Africa using remotely-sensed vegetation dataAPPLIED VEGETATION SCIENCE, Issue 1 2004David Hoare Abstract. Various attempts have been made to describe and map the vegetation of southern Africa with recent efforts having an increasingly ecologi cal context. Vegetation classification is usually based on vegetation physiognomy and floristic composition, but phenology is useful source of information which is rarely used, although it can contribute functional information on ecosystems. The objectives of this study were to identify a suite of variables derived from time-series NDVI data that best describe the phenological phenomena of vegetation in southern Africa and, secondly, to assess a classification of pixels of the study area based on NDVI variables using a preexisting map of the biomes that was delimited on the basis of life forms and climate. A number of variables were derived from the satellite data for describing phenological phenomena, which were analysed by multivariate techniques to determine which variables best explained the variation in the satellite data. This set of variables was used to produce a phenological classification of the vegetation of southern Africa, the results of which are discussed in relation to their concordance with the existing biome boundaries. [source] Stratified resampling of phytosociological databases: some strategies for obtaining more representative data sets for classification studiesJOURNAL OF VEGETATION SCIENCE, Issue 4 2005Ilona Knollová Abstract Question: The heterogeneous origin of the data in large phytosociological databases may seriously influence the results of their analysis. Therefore we propose some strategies for stratified resampling of such databases, which may improve the representativeness of the data. We also explore the effects of different resampling options on vegetation classification. Methods: We used 6050 plot samples (relevés) of mesic grasslands from the Czech Republic. We stratified this database using (1) geographical stratification in a grid; (2) habitat stratification created by an overlay of digital maps in GIS; (3) habitat stratification with strata defined by traditional phytosociological associations; (4) habitat stratification by numerical classification and (5) habitat stratification by Ellenberg indicator values. Each time we resampled the database, taking equal numbers of relevés per stratum. We then carried out cluster analyses for the resampled data sets and compared the resulting classifications using a newly developed procedure. Results: Random resampling of the initial data set and geographically stratified resampling resulted in similar classifications. By contrast, classifications of the resampled data sets that were based on habitat stratifications (2,5) differed from each other and from the initial data set. Stratification 2 resulted in classifications that strongly reflected environmental factors with a coarse grain of spatial heterogeneity (e.g. macroclimate), whereas stratification 5 resulted in classifications emphasizing fine-grained factors (e.g. soil nutrient status). Stratification 3 led to the most deviating results, possibly due to the subjective nature of the traditional phytosociological classifications. Conclusions: Stratified resampling may increase the representativeness of phytosociological data sets, but different types of stratification may result in different classifications. No single resampling strategy is optimal or superior: the appropriate stratification method must be selected according to the objectives of specific studies. [source] | ||||||||||