Comparing the accuracy of three non-destructive methods in estimating aboveground plant biomass

Aboveground plant biomass is one of the most important features of ecosystems, and it is widely used in ecosystem research. Non-destructive biomass estimation methods provide an important toolkit, because the destructive harvesting method is in many cases not feasible. However, only few studies have compared the accuracy of these methods in grassland communi - ties to date. We studied the accuracy of three widely used methods for estimation of aboveground biomass: the visual cover estimation method, the point intercept method, and field spectroscopy. We applied them in three independent series of field samplings in semi-arid sand grasslands in Central Hungary. For each sampling method, we applied linear regression to assess the strength of the relationship between biomass proxies and actual aboveground biomass, and used coefficient of determina - tion to evaluate accuracy. We found no evidence that the visual cover estimation, which is generally considered as a subjective method, was less accurate than point intercept method or field spectroscopy in estimating biomass. Based on our three datasets, we found that accuracy was lower for the point intercept method compared to the other two methods, while field spectroscopy and visual cover estimation were similar to each other in the semi-arid sand grassland community. We conclude that visual cover estimation can be as accurate for estimating aboveground biomass as other approaches, thus the choice amongst the methods should be based on additional pros and cons associated with each of the method and related to the specific research objective

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Data from: Changes in assembly rules along a stress gradient from open dry grasslands to wetlands

A central issue of community ecology is finding rules that explain the composition and abundance of co-existing species. Nowadays two main processes, environmental filtering and limiting similarity are thought to play the main roles in structuring communities. Their relative importance under different environmental conditions, however, is still not properly clarified. We studied the strength and the effect of environmental filtering (causing convergence) and limiting similarity (causing divergence) in 137 sample plots along an extremely long environmental gradient ranging from open sand grasslands to highly productive marshes, using a trait based approach. The main environmental gradient (i.e. productivity) was characterised by the Normalized Difference Vegetation Index, an indicator of aboveground live biomass. Cover of the plant species was estimated visually. Values of 11 plant traits were collected from field measurements and databases. Mean and dispersion of the trait values of the plots were quantified by community-weighted means and Rao's quadratic entropy. Trait convergence and divergence were tested by randomization tests, followed by the study of changes in effect size along the productivity gradient by fitting generalized additive mixed models (GAMM). For vegetative traits we found mainly convergence, indicating the filtering effect of environmental constraints, while traits related to regeneration showed divergence. The strength of convergence in vegetative traits generally decreased as productivity grew, indicating that while under harsh conditions environmental constraints strongly limit the possible trait values; under more benign conditions various water and nutrient-use strategies are adaptable. At high productivity, the strength of divergence in regenerative traits decreased. Since the larger diversity of vegetative traits found here reduces competition, the importance of diverse reproductive strategy is probably lower. Synthesis: Our results partly support the stress-dominance hypothesis, but reveal that assembly rules are more complex. The relative importance of environmental filtering and limiting similarity depends on the trait and on the environmental conditions of the habitat. Traits related to resource use are generally limited by environmental filtering, and this restriction is weakening as conditions become more favourable, while traits related to regeneration are constrained by limiting similarity and are more diverse under harsh conditions