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Plue, J.

Publications and source records attributed to Plue, J..

4 recordsLinked to original sources

Aligning terrestrial eDNA sampling and analytical choices to effectively capture both rare species and compositional variation in grassland plant communities

Vascular plants are a major component of terrestrial diversity, yet they are overrepresented among the worlds threatened species. To effectively manage this biodiversity crisis, data with high spatiotemporal resolution are crucial, yet often lacking for plants. Environmental DNA analysis (eDNA) is capable of rapid detection of biodiversity by metabarcoding the collection of DNA molecules retrieved from environmental samples such as soil cores. The technology may soon support the generation of broad-scale longitudinal plant community data, yet much methodological work on sampling strategies and analytical choices remains if soil-based eDNA is to become a reliable tool for monitoring terrestrial plant communities. Therefore, this dual purpose study in seven Swedish semi-natural grasslands investigated if and when eDNA-generated community data can be used as a stand-alone information source 1) to inform on the presence of a rare, small-statured grassland specialist (Gentianella campestris) and 2) to simultaneously infer community compositional change. We demonstrate eDNA to be an effective means of finding a rare species in a highly taxonomically diverse habitat, uncovering G. campestris DNA in 31% of the core samples. Evidence suggests the eDNA signal reflects recent spatio-temporal population dynamics at fine spatial scales. Although the entire plant community was not uncovered, molecular community data proved a representative subset, effectively capturing changes in community diversity and composition at plot sizes commonly used for plant surveys. Choices surrounding typical RRA-filtering had significant bearing on eDNAs discriminating power: filtering may overly conservatively remove true observations of a rare species, while filtering highly localized plot noise led to more robust patterns emerging in species richness and plant composition turn-over. Given careful alignment of study goals and sampling strategies, soil-based eDNA may already provide a stand-alone tool for generating reliable, scalable and observer-independent longitudinal data for unveiling and monitoring changes in plant diversity in terrestrial habitats.

ecology↗

On the edge of extinction: Delayed plant genetic response to forest edge dynamics

Understanding genetic responses to forest dynamics is essential for predicting the long-term viability of understory plant populations and for developing effective conservation strategies. This study investigates genetic extinction debt and colonization credit in Circaea lutetiana, a clonal forest understory species, across its European range. Using pooled genotype-by-sequencing data from 40 forest edge and core populations, we examined to what extent population size, latitude and historical changes in forest configuration predict genetic diversity. Our findings reveal that the historical forest configuration profoundly shapes present-day genetic diversity. Long-established forest edge populations exhibit significantly reduced allelic richness (-9%) compared to core populations, indicating the partial pay-off of a genetic extinction debt. In contrast, populations from recently established forest edges maintain comparable allelic richness to core populations, suggesting delayed population genetic responses to land use changes. Finally, populations established in areas that were afforested during the past 250 years exhibit lower genetic diversity than historical forest core populations, indicating a delay in genetic recovery and thus a potential genetic colonization credit. Our results highlight that C. lutetiana populations are not at equilibrium with the current forest configuration, underscoring the role of lagged genetic responses across very long time scales. Connectivity and population size further moderate genetic diversity, with smaller, isolated populations particularly vulnerable to genetic erosion. Given the limited research on delayed evolution in forest understory species, our results improve the understanding of extinction risk dynamics and underscore the need for history-informed restoration efforts.

ecology↗

Soil seed bank richness, abundance and density across spatial scales and global biomes

Soil seed banks are an important component of plant population and community dynamics, buffering temporal heterogeneity and allowing populations to recover following disturbance. At the same time, patterns in soil seed banks are likely to reflect scale-dependent patterns in above-ground vegetation, patterns that differ strongly across world regions. Here, we investigate components of diversity in the soil seed bank across global biomes and ecosystems. We found that patterns of species richness in the soil seed bank diverged from patterns of seed density, although there were high levels of uncertainty, especially at smaller spatial scales. Importantly, habitat degradation consistently led to lower richness, potentially limiting future ecosystem recovery. Among ecosystems, mediterranean and tropical regions had high species richness, but seed density m-2 in the soil was highest in wetlands and arable systems. Lower seed densities were found in both high-diversity tropical biomes that are characterised by short-lived seeds, and low-diversity boreal and tundra biomes with more stable established vegetation. Our findings of divergences between species richness and seed density across global biomes, and how they are impacted by habitat degradation, give valuable insights to the understanding of plant biodiversity worldwide.

ecology↗

HistMapR: Rapid digitization of historical land-use maps in R

1. Habitat destruction and degradation represent serious threats to biodiversity, and quantification of land-use change over time is important for understanding the consequences of these changes to organisms and ecosystem service provision.\n\n2. Comparing land use between maps from different time periods allows estimation of the magnitude of habitat change in an area. However, digitizing historical maps manually is time-consuming and analyses of change are usually carried out at small spatial extents or at low resolutions.\n\n3. We developed a method to semi-automatically digitize historical land-use maps using the R environment. We created a number of functions that use the existing raster package to classify land use according to a maps colours, as defined by the RGB channels of the raster image. The method was tested on three different types of historical land-use map and results were compared to manual digitisations.\n\n4. Our method is fast, and agreement with manually-digitised maps of around 80-92% meets common targets for image classification. We hope that the ability to quickly classify large areas of historical land-use will promote the inclusion of land-use change into analyses of biodiversity, species distributions and ecosystem services.

ecology↗