Plant Cover Data Research Articles

Invasion‐mediated mutualism disruption is evident across heterogeneous environmental conditions and varying invasion intensities

The impact of a biological invasion on native communities is expected to be uneven across invaded landscapes due to differences in local abiotic conditions, invader abundance, and traits and composition of the native community. One way to improve predictive ability about the impact of an invasive species given variable conditions is to exploit known mechanisms driving invasive species' success. Invasive plants frequently exhibit allelopathic traits, which can be directly toxic to plants or indirectly impact them via disruption of root symbionts, including mycorrhizal fungi. The indirect mechanism – mutualism disruption – is predicted to impact plants that rely on mycorrhizas but not affect non‐mycorrhizal plant species. To assess whether invader‐driven mutualism disruption explains observed changes in native plant communities, we analyzed long‐term (1998–2018) plant cover data from forest plots across the state of Illinois. We evaluated native plant communities experiencing a range of abundance of invasive allelopathic garlic mustard Alliaria petiolata and varying environmental conditions. Consistent with the mutualism disruption hypothesis, we showed that as garlic mustard abundance increased over time in 0.25 m2 sampling quadrats, the abundance of mycorrhizal plant species decreased, but non‐mycorrhizal plant species did not. Over space and time, garlic mustard abundance predicted plant abundances and diversity at the quadrat level, but this relationship was not present at a larger scale when quadrats were aggregated within sites. Garlic mustard's impact on the plant community was highly localized, yet it was as important as abiotic variables for predicting local plant diversity. We showed that garlic mustard abundance was a key predictor of patterns of plant diversity across invasion intensity and environmental heterogeneity in a way that is consistent with mutualism disruption. Our work indicates that the mutualism disruption hypothesis can provide generalizable predictions of the impacts of allelopathic invasive plants that are evident at a broad spatial scale.

Selection against ruderals in Danish grasslands over an eight-year period

In order to investigate what community selection forces are operating on Grime's CSR strategies in different semi-natural grassland habitats that were not subjected to successional processes, a time-series analysis of 2946 Danish grassland plots from an eight-year period with pin-point plant cover data was conducted. Grime's CSR strategies were used for grouping plant species into functional types, which were then treated as dependent variables in a time-series analysis. Across four grassland habitat types, there was significant selection against ruderal plant species during the eight-year period. Furthermore, the monitoring data indicated that the decreasing cover of ruderals may, in part be, due to reduced grazing pressure of large herbivores. As a consequence of the findings in this study and others, it may be suggested that increased disturbance, e.g. by large herbivores, is a suitable management strategies for grassland habitats.

Indication of a reduction in the cover of thin‐leaved plants in Danish grasslands over an eight‐year period

AbstractQuestionAccording to leaf economics spectrum theory, the historic changes in several environmental factors, e.g. land use and nitrogen deposition, are expected to lead to selection of a change in the relative proportion of thin‐leaved and thick‐leaved plant species. However, it is generally unknown how fast plant communities respond to environmental changes.LocationDenmark.MethodsTime‐series analysis of Danish grassland pin‐point plant cover data from an eight‐year period.ResultsAcross four grassland habitat types, the cover of thin‐leaved plants was found to decrease significantly, but generally only limited trait selection was observed on leaf traits (specific leaf area [SLA] and leaf dry matter content [LDMC]). The mostly negative result may partly be due to the relatively conservative analysis, where the continuous plant trait variables are used for grouping plant species into functional types, which are then treated as dependent variables. This method was chosen in order to account for the sampling process of the vegetation data and is in contrast to most other analyses of trait selection, where it is the community‐weighted mean of the traits that is used as the dependent variable.ConclusionsOnly limited leaf trait selection was observed in semi‐natural grasslands that was not subjected to successional processes.

Precipitation and Temperature Impact on Woody Plant Invaders in the Flint Hills Region of Kansas

The Flint Hills region of Kansas represents one of the largest tracts of tallgrass prairie remaining in North America. Among others, a persistent threat to tallgrass prairie is invasion by native woody plants. Fire is frequently used to combat this threat, but numerous species remain able to encroach upon prairie. We conducted a survey of three habitat types (prairie, a transitional woodland, and a forest edge) to identify potential prairie invaders, their influence on graminoid cover, and the influence of climatic variability on woody plant growth. A total of 71 trees were cut and sampled for annual woody growth rate and were used as a centroid for collection of understory plant cover data. There was a generally positive correlation between increased precipitation and increased woody growth. However, temperature had very little influence on woody plant growth. There were significant intraspecific differences in woody plant growth among habitat types. Similarly, there were differences among species within each habitat area. Graminoid cover was inversely related to overstory canopy cover.

Assessment and Spatial Analysis of Sensitivity to Desertification in Wadi El Natrun, Northwestern Egypt using MEDLAUS model

Land degradation is a global environmental issue, given the various negative impact on socio-economic and ecological implications. It leads to reduced production capacity in addition to soil erosion, physical /chemical /biological /economic land deterioration, and long-term loss (or degradation) of vegetation. When a severe deterioration in drought areas called the process of desertification i.e. arid, dry sub-humid and semi-arid areas. Desertification processes reduces the productivity of the soil and as a result effect on food stocks. The main objective of this study is integrating remote sensing data and a geographic information system (GIS) to evaluate the environmental sensitivity for desertification in Wadi El Natrun, Egypt based on the Mediterranean Desertification and Land Use (MEDALUS) approach. The collected soil data; from description of represented soil profiles and analysis of soil samples, in addition to climate, plant cover, and management data were considered for assessing the sensitivity of desertification. The obtained results showed that 10.4 % of Wadi El Natrun area is considered severe sensitivity to desertification as a result of alkalinity and salinity, while the moderately sensitive area occupies approximately 10.93 % of the study area. The low sensitive one exhibits 76.3 %. This area is described by high soil quality because of the study area is one of the new development areas which were not affected by the factors of desertification. It can be concluded that the desert extension of El-Beheira Governorate (i.e. Wadi El Rayan) is one of the areas that possess valuable land resources which should be considered for future land reclamation projects. Similar international studies are recommended to be achieved with the use of multi-criteria GIS modeling (i.e. MEDALUS) which considered all relevant factors in the form of thematic layers for easier implementation and assessments. Present study represents one of the initial attempts to use the MEDALUS model for desertification assessment in the desert extension of El-Beheira Governorate.

Model-based ordination of pin-point cover data: Effect of management on dry heathland

Recently, there has been an increasing interest in model-based approaches for the statistical modelling of the joint distribution of multi-species abundances. The Dirichlet-multinomial distribution has been proposed as a suitable candidate distribution for the joint species distribution of pin-point plant cover data and is here applied in a model-based ordination framework. Unlike most model-based ordination methods, both fixed and random effects are in our proposed model structured as p-dimensional vectors and added to the latent variables before multiplying with the species-specific coefficients. This changes the interpretation of the parameters, so that the fixed and random effects now measure the relative displacement of the vegetation by the fixed and random factors in the p-dimensional latent variable space. This parameterization allows statistical inference of the effect of fixed and random factors in vector space, and makes it easier for practitioners to perform inferences on species composition in a multivariate setting. The method was applied on plant pin-point cover data from dry heathlands that had received different management treatments (burned, grazed, harvested, unmanaged), and it was found that treatment have a significant effect on heathland vegetation both when considering plant functional groups or when the taxonomic resolution was at the species level.

Wetland Plant Communities of the Eastern Himalayan Highlands in Northern Bhutan

The study was conducted to characterize previously unexplored wetland vegetation in lower montane areas of the Himalaya (1597–2538 m above sea level) of Jigme Dorji National Park, Gasa District, Northern Bhutan. A random quadrat sampling method was employed to assess percent plant cover and environmental data were collected following standard procedures. Cluster and indicator species analyses using plant cover data were used to define the species composition of plant communities. Differences in community composition along gradients of elevation, slope, soil pH, available phosphorus, and peat/soil depth were analyzed using Canonical Correspondence Analysis (CCA). The wetlands supported 120 vascular plant species from 84 genera and 51 families. Analyses identified four plant communities, I to IV, each named from the three most prominent species. The key indicator species of four plant communities, Acorus calamus, Carex diandra, Equisetum ramosissimum, and Carex capillacea, dominate shallow fresh marsh, seasonally flooded basin of flat, fresh water meadow, and poor fen, respectively. Elevation and soil phosphorus were the most important environmental variables in explaining the variation in wetland vegetation. The findings can be used to support the work of conservation agencies to identify and conserve these plant communities and their habitats in the Himalaya.

Synergistic impacts of co‐occurring invasive grasses cause persistent effects in the soil‐plant system after selective removal

AbstractHuman influence on the environment is so extensive that virtually all ecosystems on the planet are now affected by biological invasions. And, often, ecosystems are invaded by multiple co‐occurring non‐native species. Hence, it is important to understand the impacts these invasions are producing on biodiversity and ecosystem processes.Here, we present results of a 2‐year long field experiment where we tested the effects of co‐occurring invasive C4African grasses in a Cerrado area in central Brazil. We compared plant and arthropod communities, plant biomass, and soil nitrogen dynamics and soil chemical characteristics across five experimental treatments:Urochloa decumbensremoval;Melinis minutifloraremoval; bothU.decumbensandM.minutifloraremoval;U.decumbensandM.minutiflorainvaded plots; and uninvaded Cerrado. We hypothesized that selective removal of invasive grasses would have distinct effects on the native ecosystem structure and functioning. We expected that each invasive grass would produce a different type of impact on the native ecosystem and that their impacts would be synergistic when co‐occurring.Removal ofM.minutifloradoubled native plant diversity and biomass when compared to invaded plots, whereas removal ofU.decumbensdid not alter these parameters. Cerrado plots had four times more plant species than plots cleared of invasives. Removal of invasive grasses did not affect the species richness or community composition of soil epigeal fauna. Cerrado soils had lower fertility, organic matter content and pH than invaded soils. The effects were generally higher when both invasive grasses were removed, suggesting impacts were synergistic, butM.minutiflorahad greater effects on plants and soils thanU.decumbens. Both invasive species produced negative impacts, but a single species was the main driver. We also detected persistent effects of the invasive grass species on the ecosystem after 2 years of removal.We conclude that invasive species of the same functional group have similar types of effects in native ecosystems, but the magnitude of impact was largely dependent on invasive species biomass and cover. Where multiple invasive species are present, research and management of invaded ecosystems should tackle the interacting effects of co‐occurring invaders.

Effects of Mowing and Prescribed Fire on Plant Community Structure and Function in Rare Coastal Sandplains, Nantucket Island, MA, USA.

Coastal sandplains provide habitat for a suite of rare and endangered plant and wildlife species in the northeastern United States. These early successional plant communities were maintained by natural and anthropogenic disturbances including salt spray, fire, and livestock grazing, but over the last 150 years, a decrease in anthropogenic disturbance frequency and intensity has resulted in a shift towards woody shrub dominance at the expense of herbaceous taxa. This study quantified the effects of more than a decade of dormant season disturbance-based vegetation management (mowing and prescribed fire) on coastal sandplain plant community composition on Nantucket Island, Massachusetts, USA. We used time-series plant cover data from two similar sites to evaluate the effectiveness of disturbance management for restoring herbaceous species cover and reducing woody shrub dominance. Our results indicate that applying management outside of the peak of the growing season has not been effective in maintaining or increasing the cover of herbaceous species. While management activities resulted in significant (P < 0.01) increases in herbaceous species immediately after treatment, woody species recolonized and dominated treated sites within 3-years post treatment at the expense of graminoids and forbs. These results highlight the difficulties associated with directing ecological succession using disturbance-based management to maintain rare, herbaceous species in coastal sandplain systems that were once a prevalent landscape component under historically chronic anthropogenic disturbance. Further experimentation with growing season disturbance-based management and different combinations of management techniques could provide insights into management alternatives for maintaining herbaceous conservation targets in coastal sandplains.

Using the beta distribution to analyse plant cover data

Abstract Most plant species are spatially aggregated. Local demographic and ecological processes (e.g. vegetative growth and limited seed dispersal) result in a clustered spatial pattern within an environmentally homogenous area. Spatial aggregation should be considered when modelling plant abundance data. Commonly, plant abundance is quantified by measuring cover within multiple areal plots or along multiple lines randomly placed within a study area. A common practice for analysing plant cover is to use statistical methods that rely on the normal distribution for quantifying uncertainty. This is problematic because plant cover data tend to be left‐skewed (J‐shaped), right skewed (L‐shaped) or U‐shaped and, therefore, commonly violate classic statistical assumptions, such as normality. We outline statistical analyses that explicitly account for spatial aggregation by assuming that plant cover is beta‐distributed. The beta distribution is a flexible choice because within the open unit interval it can take on a wide range of shapes (L, J, U, or a bell‐shaped). We discuss and introduce extensions to the beta distribution that address common analysis issues encountered in plant cover datasets, such as (a) the treatment of zero and one cover values, (b) hierarchical data structures and (c) observations errors. For heuristic purposes, we focus on single species analyses, but we demonstrate how the outlined methods can be generalized to more species. The assumption that plant cover is beta‐distributed allows us to estimate the degree of spatial aggregation, and the ecological significance of this new knowledge is discussed. We provide a summary of available software for analyses (emphasizing standard R packages) and include worked examples and a simulation study comparing analysis options as supplemental information. Synthesis. Previously, the state of the statistical software made it practically difficult for empirical plant ecologists to analyze their cover data correctly, but new theory and R‐packages have been developed, and this difficulty no longer exists. We recommend that empirical plant ecologists embrace the new statistical possibilities for exploring the exciting ecological features in spatial variation of plant cover.

Physiognomic and Multivariate Phytosociological Analyses of a Subtropical Peat Bog Located on the Eastern Plateau in Southern Brazil

Subtropical peat bog vegetation in southern Brazil was examined using physiognomic and phytosociological approaches. The analysis included vascular (angiosperms, pteridophytes) and non-vascular species (bryophytes, mat-forming algae, lichens, macroscopic fungi). The breadth of this approach is novel among wetland studies in southern Brazil. The study examined the Banhado Amarelo peat bog (29°19′05″S, 50°08′18″W), which is located in the Brazilian highlands of Rio Grande do Sul (RS) state. Plant cover data extracted from 125 plots distributed among 13 physiognomically recognizable vegetation patches were analyzed using the Braun-Blanquet procedure. In total, 165 species were identified. Multivariate analysis distinguished four groups of patches. The distinctions among groups were particularly evident when all floristic elements were included, i.e., vascular + non-vascular species. When the peat soil in these 13 vegetation patches was analyzed, the proportional clay content of the soil was related to the distribution of patches. The integrated analysis of the Banhado Amarelo bog demonstrated the relevance of physiognomic studies to support phytosociological analyses and the importance of including all floristic elements and soil composition data in a comprehensive approach. These findings can be extended to other studies of subtropical bogs of southern Brazilian highlands that aim to conserve these important South American ecosystems.

Relationship between socioeconomic vulnerability and ecological sustainability: The case of Aran-V-Bidgol’s rangelands, Iran

This study combines the Me-Bar and Valdez’s vulnerability assessment techniques with geographic information systems (GIS) to assess socioeconomic vulnerability and its relation to ecological sustainability in winter rangelands of Aran-V-Bidgol County, Isfahan province, Iran. Socioeconomic data were collected using a researcher-made questionnaire and ecological sustainability parameters (including plant, litter, soil, sand and gravel cover and forage yield) data were collected through field measurements. Results showed that “local problems”, “number of rangeland users”, “rangeland user’s access to rangeland experts”, “utilization pattern”, “livestock type”, “economic status of rangeland users”, “livestock number” and “increasing prices” were the most important socioeconomic indicators influencing socioeconomic vulnerability in the rangelands. In addition, a significant relationship was found between the socioeconomic vulnerability index and ecological sustainability parameters, including forage yield of annual forbs and total forage yield. Findings further indicated that a combination of the social and economic indicators with a focus on the local scale dimensions of vulnerability could create a useful tool for decision-makers, practitioners and rangeland users whose main recent concern is vulnerable rangeland ecosystems.

Livestock effect on floristic composition and vegetation structure of two desert scrublands in northwest Coahuila, Mexico

Abstract Microphyllous and rosetophyllous desert scrub plant communities dominate large parts of the state of Coahuila, Mexico, yet differences in how livestock grazing impacts these two plant communities are not well documented. In order to address this knowledge gap, we assessed livestock impact on plant species composition and vegetation structure in microphyllous and rosetophyllous desert scrublands in this northwestern Mexican state. We collected plant density, frequency, and cover data from sites with and without livestock grazing pressure that were otherwise similar in plant composition. We quantified intersite differences using the importance value index (IVI) and the Bray-Curtis similarity index. The species with the highest IVI for microphyllous scrubland were lechuguilla (Agave lechuguilla), honey mesquite (Prosopis glandulosa), and creosote bush (Larrea tridentata); however, in sites with presence of domestic herbivores, desert willow (Chilopsis linearis) and spiny hackberry (Celtis pallida) a...

The effect of nitrogen deposition on the vegetation of wet heathlands

The statistical modelling of joint species abundance is currently receiving increasing attention in the ecological literature because it complements earlier descriptive accounts of the effect of disturbance on community change with quantitative measures of spatial covariation among species at different spatial scales. Using a hierarchical Bayesian approach, we fitted both temporal and spatial plant cover data to a joint distribution model of plant abundance of the dominant plants in wet heathlands (Erica tetralix, Calluna vulgaris and Molinia caerulea) undergoing nitrogen deposition over several decades. The spatial analysis was based on pin-point cover data from 114 Danish sites with a total of 1509 randomly placed plots along a nitrogen deposition gradient. The temporal analysis was based on pin-point cover data from 22 sites with a total of 986 observations from plots that had been resampled at least three times since 2007. The spatial variation was partially explained by nitrogen deposition, as the cover of Erica decreased significantly with nitrogen deposition, whereas the cover of both Calluna and Molinia increased (albeit non-significantly) with nitrogen deposition. There was a strong and significant positive spatial covariation between Erica and Calluna. Oppositely, there was a strong and significant negative spatial covariation between Calluna and Molinia. The spatial covariation between Erica and Molinia was not significantly different from zero. There were no significant changes in the cover of any of the three species since 2007. However, by including data from 2004, the previously reported result of a significant decreasing cover of Erica was confirmed, and the cover of Calluna increased significantly. We conclude that the statistical modelling of joint species abundance is a potentially powerful tool to understand the effect of the alteration of nitrogen dynamics on community composition. This is essential to design management practices aligned with the predicted effects of varying levels of nitrogen deposition on community structure. The study also demonstrated the insight gained on the community dynamics by the use of hierarchical Bayesian models.

Mapping an invasive bryophyte species using hyperspectral remote sensing data

Reliable distribution maps are crucial for the management of invasive plant species. An alternative to traditional field surveys is the use of remote sensing data, which allows coverage of large areas. However, most remote sensing studies on invasive plant species focus on mapping large stands of easily detectable study species. In this study, we used hyperspectral remote sensing data in combination with field data to derive a distribution map of an invasive bryophyte species, Campylopus introflexus, on the island of Sylt in Northern Germany. We collected plant cover data on 57 plots to calibrate the model and presence/absence data of C. introflexus on another 150 plots for independent validation. We simultaneously acquired airborne hyperspectral (APEX) images during summer 2014, providing 285 spectral bands. We used a Maxent modelling approach to map the distribution of C. introflexus. Although C. introflexus is a small and inconspicuous species, we were able to map its distribution with an overall accuracy of 75 %. Reducing the sampling effort from 57 to 7 plots, our models performed fairly well until sampling effort dropped below 12 plots. The model predicts that C. introflexus is present in about one quarter of the pixels in our study area. The highest percentage of C. introflexus is predicted in the dune grassland. Our findings suggest that hyperspectral remote sensing data have the potential to provide reliable information about the degree of bryophyte invasion, and thus provide an alternative to traditional field mapping approaches over large areas.

Modelling pin-point cover data of complementary vegetation classes

It is often ecologically meaningful to divide the vegetation into a number of complementary vegetation classes or functional types. Here, a method for modelling pin-point plant cover data for such complementary classes is presented. The joint distribution of pin-point cover data of complementary vegetation classes is modelled using a mixture distribution of the multinomial distribution and the Dirichlet distribution, where the Dirichlet distribution is used to model the effect of spatial aggregation. In order to demonstrate the method, the variation in cover with space or time is modelled using a hierarchical Bayesian approach, where the mean cover of each site at a specific time is modelled by a latent variable. The statistical modelling procedure is exemplified in a case-study of pin-point cover data of the two dominating species Calluna vulgaris and Deschampsia flexuosa, and the abundance of the complement species class of all other higher plants on Danish dry heathlands. The cover of C. vulgaris increased significantly with annual precipitation and the cover of D. flexuosa decreased significantly with annual precipitation. Furthermore, the mean cover of C. vulgaris and D. flexuosa within-sites was negatively correlated. There were no significant changes in the cover of the three complementary dry heathland vegetation classes from 2007 to 2012. The presented model allows information of complementarity to be incorporated and whereby increasing the statistical power. Furthermore, the spatial aggregation of the vegetation is modelled so that statistical inference tests will not be deflated due to pseudo-replication.

Geomorphic predictors of riparian vegetation in small mountain watersheds

Aims Hydrogeomorphic processes operating at watershed, process zone and site scales influence the distribution of riparian vegetation. However, most studies examining the relationships between hydrogeomorphic processes and riparian vegetation are conducted at site scales. We quantified the relative importance of watershed, process zone and site geomorphic characteristics for predicting riparian plant community types and plant species abundances in four small mountain watersheds in central Nevada, USA. Methods We mapped riparian vegetation types and identified process zones (based on dominant geomorphic process and valley fill material) within the watersheds. We sampled sites in each combination of vegetation type and process zone (n = 184 sites) and collected data on watershed scale factors, valley and stream geomorphic characteristics and on plant cover of each geomorphic surface. Plant community types were defined by cluster and indicator species analyses of plant cover data, and related to geomorphic variables using ordination analysis (nonmetric multidimensional scaling). Linear mixed effects models were used to predict abundances of indicator species. Important Findings Variables describing position in the watershed (elevation, contributing area) that are related to gradients of temperature, moisture and stream discharge were of primary importance in predicting plant community types. Variables describing local geomorphic setting (valley width, stream gradient, channel sediments, geomor phic surface height) were of secondary importance, but accurately described the geomorphic setting of indicator species. The process zone classification did not include position in the watershed or channel characteristics and only predicted plant community types with unique geomorphic settings. In small mountain watersheds, predicting riparian vegetation distribution requires explicit consideration of scale and geomorphic context within and among water sheds in addition to site variables.

Amphibian Community Responses to Playa Restoration in the Rainwater Basin

Alterations to wetland hydrology associated with conversion of grassland watersheds to croplands can alter functional components that drive many wetland ecosystem services. Biodiversity provisioning is one of many services that can be negatively impacted by grassland conversions. Our objective was to compare amphibian communities of playa wetlands in native grassland versus cropland watersheds and to determine if restoration of cropland wetlands via sediment removal improved these habitats for amphibians. We collected amphibian species richness, water depth, wetland area, and emergent plant cover data from 34 playa wetlands in 2008 and 32 playa wetlands in 2009. Playas were selected to include those within natural grassland watersheds (i.e., reference playas), cropland watersheds, and restored watersheds within the Rainwater Basin (RWB) of Nebraska. While we did not detect a difference in amphibian species richness among land-use types in 2008, in 2009 (a dry year within the RWB) amphibian species richness averaged nearly two times greater in restored playas (3.18) compared to cropland playas (1.70). Average water depth (2008 and 2009) and playa area (2008 only) were best predictors of amphibian species richness. Restored playas provided the most reliable water availability for amphibians in the RWB where 90 % of the wetlands have been drained.

Estimating mean plant cover from different types of cover data: a coherent statistical framework

Plant cover is measured by different methods and it is important to be able to estimate mean cover and to compare estimates of plant cover across different sampling methods in a coherent statistical framework. Here, a framework that incorporates (1) pin‐point cover data, (2) visually determined cover data, and (3) ordinal cover classification systems (e.g., Braun‐Blanquet cover data) is presented and tested on simulated plant cover data. The effect of measurement error when applying a visual determination of plant cover is considered. Generally, the estimation of the mean plant cover was well‐behaved and unbiased for all the three methods, whereas the estimate of the intra‐plot correlation tended to be upward biased and especially so if the plant cover data was collected using the Braun‐Blanquet method. It was surprising that the Braun‐Blanquet sampling procedure provided mean plant cover estimates that were comparable to the other sampling schemes. This method shows promise in the attempt to use the large amount of historic Braun‐Blanquet plant cover data in the investigation of the underlying causes for observed vegetation changes.

Hierarchical and spatially aggregated plant cover data

Most plant species are spatially aggregated and here the importance of taking the spatial variation into account when analyzing plant cover data is demonstrated in a general stochastic model where both the within-site and the among-site spatial variation of species cover data are parameterized. Using a generalised binomial distribution (or Pólya–Eggenberger distribution), where the among-site variation in mean cover is modeled by a zero-inflated beta distribution, it is possible to adequately analyze hierarchical plant cover data and link the estimates to the underlying ecological processes. The model is demonstrated in a case-study of pin-point cover data of Erica tetralix from 1148 wet heathland plots at 84 Danish sites, and it is shown that both parameter estimates and the conclusions of hypotheses testing critically depend on the correct modeling of the observed spatial variation. Finally, statistical power simulations of plant cover measurements are presented, which will be useful for planning ecological experiments and monitoring programs.