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Biology subjects

Kortmann, M.

Publications and source records attributed to Kortmann, M..

4 recordsLinked to original sources

Higher bat and bird γ-diversity in structurally complex forests is driven by distinct α- and β-diversity responses

Effective conservation management and habitat restoration rely on understanding how biodiversity responds to environmental change. Centuries of silviculture have homogenized forests and their species communities globally, reducing biodiversity. To test whether restoring forest structural complexity can promote biodiversity, we conducted a large-scale, spatially explicit landscape experiment. At 11 sites across Germany, we compared bat and bird diversity in forests with experimentally enhanced heterogeneity by increasing deadwood and canopy complexity to homogeneous production forests. Both taxa were investigated by autonomous acoustic recorders and automatic species identification. We quantified within-patch (-), between-patch ({beta}-), and landscape-level ({gamma}-) diversity, emphasizing infrequent to highly frequent species for taxonomic, functional, and phylogenetic diversity. The pairwise comparisons of the sites were synthesized using a newly developed meta-analysis of rarefaction-extrapolation curves. {gamma}-diversity increased significantly in structurally heterogeneous forests for both taxa, albeit through distinct taxon-specific mechanisms. Bat {gamma}-diversity gains were primarily driven by higher {beta}-diversity, indicating greater dissimilarity in species assemblages among patches, while bird {gamma}-diversity increased via higher -diversity within patches. Bat diversity increases were mainly taxonomic, suggesting functional similarity in the communities, whereas birds showed the highest gains in functional diversity, indicating that experimental treatments resulted in greater trait dissimilarity. Our results provide experimental evidence under real-world conditions that {gamma}-diversity can be shaped by different diversity mechanisms. These patterns likely originate from differences in activity ranges, such as the large-scale movements of foraging bats in contrast to the more spatially restricted, territorial behavior of birds. This highlights the need for taxon-specific restoration strategies in homogenized landscapes.

ecology↗

A continuum of information-based temporal stability measures and their decomposition across hierarchical levels

When biodiversity-stability relationships are assessed from temporal patterns of species (or species assemblages) biomass or other key variables, ecological stability is commonly quantified as the inverse of the coefficient of variation (CV) or its square. However, just as biodiversity cannot be fully characterized by a single value, the complexity of temporal stability/invariability cannot be completely captured by one metric, especially since CV is disproportionally sensitive to large data values. Ecologists now recognize that species diversity can be fully characterized by a continuum of Hill-number-based measures parametrized by a diversity order q[≥]0, which determines the sensitivity of the measure to species abundance. Building on the intuitive concept that temporal stability can be quantified by the closeness between the data vector and the ideally maximally stable vector, we propose a continuum of information-based measures of temporal stability/invariability parameterized by an order q>0. This continuous parameter q determines the sensitivity of the measure to the magnitude of biomass or other ecosystem functions. By varying q, researchers can differentially weight small, medium, or large values in a time series, thereby disentangling their respective contributions to stability. Our framework unifies and generalizes classical measures: the case q=1 links to Shannon entropy, reflecting MacArthurs 1955 stability concept; q=2 connects to the conventional CV-based measure. Unlike these traditional metrics, our approach explicitly accounts for the number of data values (i.e., time points), adjusting for time-series-length effects to enable fair and meaningful comparisons across datasets of varying lengths. We extend the framework to hierarchical structures by developing additive and multiplicative decompositions of stability in a metacommunity (or metapopulation) into alpha and beta components. The beta component can be further used to obtain measures that quantify (a)synchrony among communities (or populations). For q=2, the resulting (a)synchrony measure provides a mathematically rigorous, CV-based metric. The proposed measures are illustrated using 22-year biomass time series data from the Jena Experiment in Germany. We developed the R package iSTAY (information-based stability measures) and online tools for computation and visualization. Our measures are adaptable to other functions beyond biomass and are applicable in both temporal and spatial contexts. Open Research StatementThe original biomass data of the Jena Experiment, covering the years 2003 to 2023, can be retrieved from https://jexis.idiv.de/ddm/Data/ShowData/624, while the 2024 data are available at https://jexis.idiv.de/ddm/Data/ShowData/695. These datasets, along with the R code used in this study, are currently accessible on Github at https://github.com/AnneChao/MS_iSTAY for review purposes and will be archived on Zenodo upon journal acceptance.

ecology↗

Acoustic indices predict recovery of tropical bird communities for taxonomic and functional composition

Quantifying the success of biodiversity restoration is a major challenge in the UN Decade on Ecosystem Restoration. We evaluated the potential of acoustic indices to predict the recovery success of bird communities within abandoned agricultural areas. Using audio recordings from a lowland tropical forest region, we identified 334 bird species and calculated established acoustic indices. Community composition was analyzed using Hill numbers, accounting for incomplete sampling. Acoustic indices effectively predicted independent species data (R2 = 0.59-0.76), capturing not only taxonomic but also functional and phylogenetic composition. Taxonomic composition was best predicted for common and dominant species, while functional and phylogenetic compositions were more accurately predicted for rare and common species. In addition, community composition was strongly influenced by the surrounding habitat. Our findings demonstrate that a small set of acoustic indices, once validated by stratified ground truth data, provides a powerful tool for assessing restoration success over large tropical areas, even for functional composition of rare tropical birds.

ecology↗

A short cut to sample coverage standardization in meta-barcoding data provides new insights into land use effects on insect diversity

The use of metabarcoding for insect species identification has grown rapidly, but the absence of abundance data hinders meaningful diversity metrics like sample coverage-standardized species richness. Additionally, the vast number of taxa often lacks a unified phylogeny or trait database. We present a framework for constructing a phylogenetic tree encompassing the majority of insect families, standardisation of sample coverage (an objective measure of sample completeness) and assessment of both taxonomic and phylogenetic diversity using the Hill series for metabarcoding data. Applied to central Europe, our framework analysed insect diversity from 400 families along a land-use gradient. Results revealed land-use intensity significantly affects sample coverage, emphasizing the need for biodiversity standardization. After standardization, taxonomic diversity declined by 27-44%, and phylogenetic diversity by 13-29% across 39,000 Operational Taxonomic Units, from forests to agricultural areas. Rare species exhibited greater phylogenetic diversity loss than taxonomic, while dominant species showed smaller phylogenetic losses but stronger declines in taxonomic diversity. Our findings underscore agricultures detrimental effects on specific insect taxa, even after adjusting for sample coverage, and provide new insights into the loss of functional diversity, as represented by phylogeny.

ecology↗