• Energy Research

Vegetation ecologists use a wide range of importance (“abundance”) measures for plant species in vegetation plots, including percentage cover, ordinal cover scales, frequency and fractional biomass. Resurvey studies and analyses of heterogenous data from large vegetation-plot databases need to deal with data sampled with different approaches, yet very little is known about how these approaches relate to each other. For the Square Foot Project, in which hundreds of historic grassland plots in Switzerland of 0.09 m2 size were resurveyed after having been originally sampled via biomass harvest, we had the challenge that the historical method was too time-consuming for our study and thus had to resort to careful cover estimation in percent. However, we used both methods to sample 40 such plots representative of the grasslands of Switzerland and compared the results. We found that with biomassbased species determination, an average of 0.9 additional species (4.6%) per plot were found compared to cover-based sampling. Graminoids were three times more likely to be overlooked than forbs. Fractional cover was well related to fractional biomass with an allometric (power-law) function, with an exponent of 0.6 for all species combined, while graminoids and forbs showed clear differences in function parameters when analysed separately. Generally, our overlooking probabilities were much lower than in other comparable studies, which might be due to the very small plot size or to the careful sampling with percentage estimates. Our allometric functions allow reliable transformations between fractional biomass and fractional cover in temperate European grasslands. We recommend the development of further such empirical functions for other regions and ecosystems.

AbstractQuestionsSpecies–area relationships (SARs) are fundamental for understanding biodiversity patterns and are generally well described by a power law with a constant exponent z. However, z‐values sometimes vary across spatial scales. We asked whether there is a general scale dependence of z‐values at fine spatial grains and which potential drivers influence it.LocationPalaearctic biogeographic realm.MethodsWe used 6,696 nested‐plot series of vascular plants, bryophytes and lichens from the GrassPlot database with two or more grain sizes, ranging from 0.0001 m² to 1,024 m² and covering diverse open habitats. The plots were recorded with two widespread sampling approaches (rooted presence = species “rooting” inside the plot; shoot presence = species with aerial parts inside). Using Generalized Additive Models, we tested for scale dependence of z‐values by evaluating if the z‐values differ with gran size and tested for differences between the sampling approaches. The response shapes of z‐values to grain were classified by fitting Generalized Linear Models with logit link to each series. We tested whether the grain size where the maximum z‐value occurred is driven by taxonomic group, biogeographic or ecological variables.ResultsFor rooted presence, we found a strong monotonous increase of z‐values with grain sizes for all grain sizes below 1 m². For shoot presence, the scale dependence was much weaker, with hump‐shaped curves prevailing. Among the environmental variables studied, latitude, vegetation type, naturalness and land use had strong effects, with z‐values of secondary peaking at smaller grain sizes.ConclusionsThe overall weak scale dependence of z‐values underlines that the power function generally is appropriate to describe SARs within the studied grain sizes in continuous open vegetation, if recorded with the shoot presence method. When clear peaks of z‐values occur, this can be seen as an expression of granularity of species composition, partly driven by abiotic environment.