Publications by authors named "Ane Kirstine Brunbjerg"

Wetlands are important habitats, often threatened by drainage, eutrophication, and suppression of grazing. In many countries, considerable resources are spent combatting scrub encroachment. Here, we hypothesize that encroachment may benefit biodiversity-especially under eutrophic conditions where asymmetric competition among plants compromises conservation targets.

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Species richness is the most commonly used metric to quantify biodiversity. However, examining dark diversity, the group of missing species which can potentially inhabit a site, can provide a more thorough understanding of the processes influencing observed biodiversity and help evaluate the restoration potential of local habitats. So far, dark diversity has mainly been studied for specific habitats or large-scale landscapes, while less attention has been given to variation across broad environmental gradients or as a result of local conditions and biotic interactions.

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Background: In light of the biodiversity crisis and our limited ability to explain variation in biodiversity, tools to quantify spatial and temporal variation in biodiversity and its underlying drivers are critically needed. Inspired by the recently published ecospace framework, we developed and tested a sampling design for environmental and biotic mapping. We selected 130 study sites (40 × 40 m) across Denmark using stratified random sampling along the major environmental gradients underlying biotic variation.

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Environmental DNA (eDNA) is increasingly applied in ecological studies, including studies with the primary purpose of criminal investigation, in which eDNA from soil can be used to pair samples or reveal sample provenance. We collected soil eDNA samples as part of a large national biodiversity research project across 130 sites in Denmark. We investigated the potential for soil eDNA metabarcoding in predicting provenance in terms of environmental conditions, habitat type and geographic regions.

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Effective planning and nature management require spatially accurate and comprehensive measures of the factors important for biodiversity. Light detection and ranging (LIDAR) can provide exactly this, and is therefore a promising technology to support future nature management and related applications. However, until now studies evaluating the potential of LIDAR for this field have been highly limited in scope.

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DNA metabarcoding is promising for cost-effective biodiversity monitoring, but reliable diversity estimates are difficult to achieve and validate. Here we present and validate a method, called LULU, for removing erroneous molecular operational taxonomic units (OTUs) from community data derived by high-throughput sequencing of amplified marker genes. LULU identifies errors by combining sequence similarity and co-occurrence patterns.

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