Accurate predictions of heathland plant species are crucial for ecological monitoring and assessing biodiversity. Previous research has predominantly utilised convolutional neural networks (CNNs), which process images arranged on a regular grid. Although CNNs are effective at extracting local visual features, they frequently do not capture the irregular spatial relationships characteristic of heathland vegetation. Earlier appr...

In this gradient study, we examined the effects of ammonia deposition on vegetation in two different heathland habitats, a dry and dune heath (Annex I code: 4030 & 2140, respectively). During the summer of 2020, we conducted a vegetation survey and soil sampling along a transect at each heathland with increasing distance to a farm unit(s). At the dry heath, the transect length was ~ 1420 m; at the dune heath, the transect leng...

A one-step community trait selection model is proposed and fitted to observed changes in pin-point plant cover data from a manipulated grassland experiment, in which the level of nitrogen input was varied. In the trait selection model, population growth is modelled, and the observed trait selection is partitioned into direct selection and selection that was mediated by interspecific interactions. The effect of a nitrogen gradi...

To develop a predictive ecosystems model in a changing environment, it is important to require causal knowledge of the most important ecosystem process. More specifically, it is important to identify the causal environmental factors that drive vegetation changes in natural and semi-natural habitats managing and preserving ecosystems. In this study, we investigate spatio-temporal co-occurrence patterns between temporal changes...

The effect of severe drought in the summer 2018 on the plant community composition and overall diversity was investigated in a replicated long-term grassland experiment where nitrogen availability was manipulated. The possible plant community response to the drought and the possible role of selected plant traits were investigated using model-based ordination techniques, which were tailored to the sampled pin-point cover data....