Old-fields (44, aged 1–15 years, from Czech Republic and Hungary) were sorted according to their soil moisture and nitrogen content into wet, mesic or dry, and nutrient poor, moderate or nutrient rich categories, resulting in 8 combinations (dry and nutrient rich fields were not present). The vegetation of old fields was sampled using phytosociological relevès. The changes in species cover data and importance of species trait categories were analysed in relation to three environmental factors, i.e., time since abandonment, soil moisture and total soil nitrogen using ordination, generalized linear models (GLM) and regression tree methods. Successional seres in the first 15 years after field abandonment were divergent. Species diversity significantly decreased with increasing site moisture and was highest in sites with moderate nitrogen content; while the relationship with time was not significant. Raunkiaer life forms and life strategies (sensu Grime) were generally the most predictive species traits considering species occurrence during the course of succession, the type of dispersal considering the different moisture status, and the ability to lateral spread considering the nutrient status of the old-fields. Most trends appeared in both parametric GLM and non-parametric regression tree analyses, several only in GLM. We consider regression trees to be a more convenient tool than GLM in cases such as ours with a rather small number of samples and robust character of data. Another advantage is that a hierarchy of species traits is taken into account. Thus, the occurrence of a species along an environmental gradient can be predicted if the species possesses a certain combination of traits.
Authors:E. Addicott, S. Laurance, M. Lyons, D. Butler, and J. Neldner
Plant communities in extensive landscapes are often mapped remotely using detectable patterns based on vegetation structure and canopy species with a high relative cover. A plot-based classification which includes species with low relative canopy cover and ignores vegetation structure, may result in plant communities not easily reconcilable with the landscape patterns represented in mapping. In our study, we investigate the effects on classification outcomes if we (1) remove rare species based on canopy cover, and (2) incorporate vegetation structure by weighting species’ cover by different measures of vegetation height. Using a dataset of 101 plots of savanna vegetation in north-eastern Australia we investigated first, the effect of removing rare species using four cover thresholds (1, 5, 8 and 10% contribution to total cover) and second, weighting species by four height measures including actual height as well as continuous and categorical transformations. Using agglomerative hierarchical clustering we produced a classification for each dataset and compared them for differences in: patterns of plot similarity, clustering, species richness and evenness, and characteristic species. We estimated the ability of each classification to predict species cover using generalised linear models. We found removing rare species at any cover threshold produced characteristic species appearing to correspond to landscape scale changes and better predicted species cover in grasslands and shrublands. However, in woodlands it made no difference. Using actual height of vegetation layer maintained vegetation structure, emphasised canopy and then sub-canopy species in clustering, and predicted species cover best of the height-measures tested. Thus, removing rare species and weighting species by height are useful techniques for identifying plant communities from plot-based classifications which are conceptually consistent with those in landscape scale mapping. This increases the confidence of end-users in both the classifications and the maps, thus enhancing their use in land management decisions.
We investigated the neighbourhood-scale effect of weeding on native plants in Lance McCaskill Nature Reserve, Canterbury, New Zealand. The reserve is an unproductive basin of limestone debris. Originally set up to protect the Castle Hill buttercup,
, the reserve also offers protection for nationally endangered species:
. Our aim was to investigate whether removal of introduced plants increased the cover of remaining native species. We removed introduced plants, by hand, every year for 6 years from half of the plots. We used nonparametric multivariate analysis to compare overall species cover.The results suggest that weeding does benefit the native plants in this area. There was a significant difference in the mean of the overall native species cover between the weeded and the non-weeded plots. For the ten species measured, the mean area covered per square metre was higher in the weeded plots than in the non-weeded plots in most years of the study. There was considerable variation in the data and we discuss possible reasons for this.
A simple to calculate and statistically testable method is proposed for assessing species abundance unevenness or dominance concentration within plant communities. Dominance rather than evenness is considered the preferred measure, because perfect evenness can be defined and used as a benchmark for comparing communities regardless of floristic richness. Four dominance (Simpson, Berger-Parker, McIntosh, and a proposed [DW]) and four evenness (Carmargo, Gini, Shannon, and Williams) indices are comparatively analyzed. The Simpson, McIntosh, Gini, and Williams indices were correlated with species richness, the Berger-Parker index was correlated with total species cover, the Shannon index over-estimated evenness, the Simpson index under-estimated dominance concentration, and a nonlinear relationship occurred between the Simpson and all of the evenness indices. Only DW and the Carmargo indices fulfilled the technical requirements established for evenness with appropriate reversals of criteria for assessing a dominance concentration index. Determination of DW was based on the maximum difference between cumulative proportion (also referred to as Lorenz curve or partial order) and perfect evenness values. The conventional assumption that dominance (D) is the complete opposite of evenness (E), as assessed by indices, was found in practice to be lacking, without the inclusion of an error term (i.e., 1 = E + D + error). Therefore, both dominance concentration and evenness should be reported when characterizing plant communities.
Two simulated coenoclines and a real data set were differently recoded with respect to the Braun-Blanquet coding (including presence/absence) and analysed through the most common multidimensional scaling methods. This way, we aim at contributing to the debate concerning the nature of the Braun-Blanquet coding and the consequent multidimensional scaling methods to be used. Procrustes, Pearson, and Spearman correlation matrices were computed to compare the resulting sets of coordinates and synthesized through their Principal Component Analyses (PCA). In general, both Procrustes and Pearson correlations showed high coherence of the obtained results, whereas Spearman correlation values were much lower. This proves that the main sources of variation are similarly identified by most of used methods/transformations, whereas less agreement results on the continuous variations along the detected gradients. The conclusion is that Correspondence Analysis on presence/absence data seems the most appropriate method to use. Indeed, presence/absence data are not affected by species cover estimation error and Simple Correspondence Analysis performs really well with this coding. As alternative, Multiple Correlation Analysis provides interesting information on the species distribution while showing a pattern of relevés very similar to that issued by PCA.
Authors:P. B. Drewa, P. B. Drewa, G. E. Bradfield, and G. E. Bradfield
The influence of scale on the discernment of plant community patterns was examined using vegetation-environment data collected from a subalpine wet meadow in south-coastal British Columbia. Species cover data were recorded in 225, 0.25 m2quadrats systematically located at 5m intervals in a 40 m x 120 m sampling grid. Environmental data consisted of quadrat elevations as well as measured and kriged estimates of five soil variables (carbon content, pH, electrical conductivity, percent sand, and percent clay). Sampling scale was adjusted by aggregating neighbouring quadrats into composite sampling units; analytical scale was altered by varying the intercept level in dendrograms from minimum increase of sum of squares cluster analysis of the vegetation data corresponding to the different sampling scales. The resulting classifications were evaluated for their ability to explain variation in the vegetation data and in the environmental data. The vegetation variation explained by the classifications was highest at the smallest sampling scale indicating that vegetation heterogeneity is fine grained. In contrast, the environmental variation explained was higher for the classifications based on the larger composite sampling units implying a coarser scaling of abiotic conditions within the study area. These results were consistent with the recognition of three main zones along a drainage gradient within the sampling grid. upper mixed-forb, middle heath, and lower sedge. There was also evidence that the orientation of rectangular sampling units parallel to the drainage gradient leads to higher levels of explained variation. This study reaffirms the need for careful consideration of alternatives both in field sampling and analytical phases of vegetation research to ensure that description and interpretation of patterns adequately address study objectives and that vegetation-environment relationships are more completely investigated from a hierarchical perspective.
Though the interplay of grazing intensity and the availability of resources is a key driver in grassland composition, very few studies focused on trait changes after abandonment along productivity gradients. Through a comparative approach, we aimed to assess the context-dependent effects of long-term grazing cessation on functional composition and diversity in sub-Mediterranean grasslands. We hypothesized that variability of topography, soil and vegetation structure on a fine scale drives the trait-based dynamics after long-term abandonment, also influencing the patterns of functional diversity. On a calcareous mountain ridge of central Italy, we collected data on species cover and traits, site characteristics, soil depth and vegetation structure in 0.5 m × 0.5 m plots located in extensively grazed pastures and in grasslands abandoned since the early 1970s. We analysed patterns of species and traits in relation to environmental variables and management type, and trends in functional diversity (FD, Rao’s quadratic entropy) along a productivity gradient. We found that grazing cessation reduced the overall FD and that the direction of species and trait response after long-term grazing cessation were affected, on a fine scale, by the soil depth / productivity gradient. In dryer conditions, species and functional responses were less affected by abandonment, and were devoted to resistance to both stress and disturbance. In abandoned pastures we detected a significant decrease in FD with increasing productivity, leading to a shift from functional strategies devoted to grazing avoidance and tolerance to those devoted to competition for light and resource acquisition. This trend was related to the filtering effect of coarse tall grasses, which spread in highly productive conditions. In grazed grasslands, we detected an overall increasing trend of FD with increasing productivity, confirming the key role of extensive grazing in maintaining high levels of FD.
To determine the effect of tree canopy composition on understory species abundance, three-hundred 2 m × 2-m quadrats from 30 high-latitude boreal forest stands were sampled. In addition, all trees within a 3mradius of each quadrat center and ≥1 m tall were also measured for height, basal diameter, and canopy width (n = 3130). Stands were 33–178 years old, with canopies of Populus tremuloides (trembling aspen) and Picea spp. (spruce) in varying proportions. Arctostaphylos uva-ursi, Calamagrostis purpurascens, Chamerion angustifolium, Shepherdia canadensis, and Hylocomium splendens were the most frequent understory species among quadrats. Scatterplots of P. tremuloides and individual vascular understory species cover values lacked bivariate trends, but the understory species had distinct maxima that ranged from 20 to 90%. A moderately strong correlation (r = 0.52, P <0.001) occurred between P. tremuloides canopy and total vascular understory plant covers, but weak individual species correlations (r = 0.22–0.35, P <0.001), suggested understory species variation was primarily determined by factors other than the amount of immediately overhead canopy cover. Canonical correlation analysis (R = 0.82, P <0.001) indicated that greater vascular understory plant cover occurred when forest stands consisted of P. tremuloides with large canopies and large basal diameters, and lacked Picea. Maximum cover for vascular understory species declined when Picea cover exceeded 7–10%. In combination, P. tremuloides stem densities or a metric based on summed canopy areas converted to a diameter value (canopy-area diameter), and the vertical silhouette area of Picea canopies (canopy profile area), as independent linear regression variables, explained ∼79% of the variance in total vascular understory plant cover. Several Picea basal areaderived metrics were strongly and positively associated with increasing H. splendens cover, but canopy profile area was more informative. Populus tremuloides canopy area and Picea canopy profile area, as indicators of shading, may be important determinants of vascular understory vegetation abundance in stands where solar radiation enters at angles of up to 52° during the summer.