Biology subjects

Keck, F.

Publications and source records attributed to Keck, F..

6 recordsLinked to original sources

bioRxiv2025

Benchmarking beta-diversity measures and transfer functions for sedimentary ancient DNA

Analyzing past ecosystems can improve our understanding of the mechanisms linking biodiversity with environmental changes. Sedimentary ancient DNA (sedaDNA) opens a window to past biodiversity, beyond the fossil record, that can be used to reconstruct ancient environments and ecosystems functions. To this end, modern biodiversity and environmental conditions are used to calibrate transfer functions, that are then applied to past biodiversity data to reconstruct environmental parameters. Doing this with sedaDNA can be challenging, because ancient DNA is often obtained in limited quantities and fragmented into smaller molecules. This leads to noisy datasets, with a low alpha diversity relative to modern DNA, patchy taxa detection patterns and/or skewed relative abundance profiles. How this affects beta-diversity measures, and the performance of transfer functions remain untested. Here we simulated ancient DNA reads counts matrices from synthetic and empirical datasets, and tested 464 combinations of counts transformations, beta-diversity indices, and ordinations methods, and assessed their performance in i) separating the ecological signal from the noise introduced by DNA degradation and in ii) predicting ground-truth environmental conditions. Our results show that commonly used workflows in DNA-based community ecology studies are sensitive to the noise associated to ancient DNA signal. Instead, combinations of methods that include more recent ordination methods proved robust to ancient DNA noise and produced better transfer functions. Our study provides a framework for designing post-processing workflows that are better suited for sedaDNA studies.

ecology↗

bioRxiv2025

Extracting massive ecological data on state and interactions of species using large language models

The contemporary ecological crisis calls for integration and synthesis of ecological data describing the state, change and processes of ecological communities. However, such synthesis depends on the integration of vast amounts of mostly scattered and often hard-to-extract information that is published and dispersed across hundreds of thousands of scientific papers, for example describing species-specific interactions and trophic relationships. Recent advancements in natural language processing (NLP) and in particular the emergence of large language models (LLMs) offer a novel, and potentially revolutionary solution to this persistent challenge, for the first time creating the opportunity to access and extract virtually all data ever published. Here, we demonstrate the transformative potential of LLMs by extracting all types of biological interactions among species directly from a corpus of 83,910 scientific articles. Our approach successfully extracted a network of 144,402 interactions between 36,471 taxa. Performance analysis shows that the model exhibits a high sensitivity (70.0%) and excellent precision (89.5%). Our approach proves that LLMs are capable of carrying out complex extraction tasks on key ecological data on a very large scale, paving the way for a multitude of potential applications in ecology and beyond.

ecology↗

bioRxiv2025

Tracking the phenology of riverine insect communities using environmental DNA

Aquatic insects are iconic and ecologically highly relevant inhabitants of riverine ecosystems. They are also often the target of monitoring programs to assess the ecological status of these lotic habitats. Environmental DNA (eDNA) techniques have been widely and successfully implemented to investigate freshwater insects and other macroinvertebrates. Commonly, such monitoring is conducted at one or two timepoints per year, despite the known strong seasonality and phenology of aquatic insects. Here, we assessed if and how eDNA can capture the temporal changes of the orders Ephemeroptera (mayflies), Plecoptera (stoneflies), Trichoptera (caddisflies) and Diptera (true flies). We carried out eDNA sampling at roughly monthly intervals from April to October at 25 sites across a whole river catchment in the northeastern part of Switzerland. We found pronounced, cyclic phenological trends in all orders but Trichoptera: the communities diverged from spring to summer and then in fall gradually returned closer to the spring state. The four orders exhibited different predominance in gains or losses of species detection throughout this time interval. Lastly, we found that field replicates, despite showing a relatively high local stochasticity, were able to provide a more complete assessment of aquatic communities and could thus be used as a proxy for the frequency of observation of a species through the seasons. In fact, this approach yielded comparable temporal patterns to the ones extracted from the Global Biodiversity Information Facility (GBIF). Overall, our findings demonstrate that eDNA techniques can be used to reveal intra-annual dynamics of aquatic insects. Given the current necessity to assess and monitor the biodiversity status of ecosystems, we therefore show that eDNA methods are a viable option to obtain a deeper understanding of the structuring of freshwater communities over time.

ecology↗

bioRxiv2024

A global synthesis on land-cover changes in watersheds shaping freshwater detrital food webs

Anthropogenic land-cover changes are among the most pressing global threats to both aquatic and terrestrial ecosystems, jeopardising biodiversity and the critical connections between these systems. Resource flows and trophic interactions intricately link aquatic and terrestrial ecosystems, with terrestrial-derived detritus playing a foundational role in supporting aquatic food webs. These detrital inputs form essential cross-ecosystem linkages, underpinning key ecological processes and providing vital resources for aquatic communities. Yet, little research has focused on how land-cover changes cascade across this linkage. To better understand how land-cover changes in the watershed influence freshwater detrital food webs, we conducted a meta-analysis of field studies reporting the effects of vegetation changes on freshwater detrital consumers and organic matter decomposition. The results from 144 studies, reporting 1235 comparisons, showed that, overall, land-cover changes in the watershed vegetation, especially through harvest and land-use conversion, have negative effects on aquatic biodiversity and ecosystem processes. These vegetation changes reduced diversity, abundance, and biomass across multiple trophic levels in freshwater detrital food webs. Studies examining multiple organism groups most often observed negative responses across multiple trophic levels, suggesting that the land-cover changes negatively affected multiple detrital food web components simultaneously. Our results also show that outcomes of restoration of watershed vegetation were context-dependent, and no clear trend of improvement was visible. Therefore, conservation of natural riparian and catchment vegetation are key to maintain freshwater ecosystem processes and aquatic biodiversity worldwide, and more efficient and evidence-based restoration measures are urgently needed. As our global synthesis shows that direct human-induced alterations of vegetation type in watersheds have significant negative effects on freshwater detrital food webs, there is a pressing need to consider cross-ecosystem consequences of land-cover changes in conservation and ecosystem management.

ecology↗

bioRxiv2022

A triad of kicknet sampling, eDNA metabarcoding, and predictive modeling to assess aquatic macroinvertebrate biodiversity

Monitoring freshwater biodiversity is essential to understand the impacts of human activities and for effective management of ecosystems. Thereby, biodiversity can be assessed through direct collection of targeted organisms, through indirect evidence of their presence (e.g. signs, environmental DNA, camera trap, etc.), or through extrapolations from species distribution models (SDM). Differences in approaches used in biodiversity assessment, however, may come with individual challenges and hinder cross-study comparability. In the context of rapidly developing techniques, we compared a triad of approaches in order to understand assessment of aquatic macroinvertebrate biodiversity. Specifically, we compared the community composition and species richness of three orders of aquatic macroinvertebrates (mayflies, stoneflies, and caddisflies, hereafter EPT) obtained via eDNA metabarcoding and via traditional in situ kicknet sampling to catchment-level based predictions of a species distribution model. We used kicknet data from 24 sites in Switzerland and compared taxonomic lists to those obtained using eDNA amplified with two different primer sets. Richness detected by these methods was compared to the independent predictions made by a statistical species distribution model using landscape-level features to estimate EPT diversity. Despite the ability of eDNA to consistently detect some EPT species found by traditional sampling, we found important discrepancies in community composition between the two approaches, particularly at local scale. Overall, the more specific set of primers, namely fwhF2/EPTDr2n, was most efficient for the detection of target species and for characterizing the diversity of EPT. Moreover, we found that the species richness measured by eDNA was poorly correlated to the richness measured by kicknet sampling and that the richness estimated by eDNA and kicknet were poorly correlated with the prediction of the statistical model. Overall, however, neither eDNA nor the traditional approach had strong links to the predictive models, indicating inherent limitations in upscaling species richness estimates. Future challenges include improving the accuracy and sensitivity of each approach individually yet also acknowledge their respective limitations, in order to best meet stakeholder demands addressing the biodiversity crisis we are facing.

ecology↗

bioRxiv2021

Meta-analysis shows both congruence and complementarity of DNA metabarcoding to traditional methods for biological community assessment

Assessment of the diversity and composition of biological communities is central to studies in ecology as well as for ecological monitoring. Historically, individual taxonomic groups have been assessed separately, while for an understanding of the state and change of biodiversity under ongoing global change an integrated assessment would be necessary. DNA metabarcoding has been proposed to be a highly promising approach especially for the assessment of aquatic communities, and numerous studies have investigated the consistency of this new technique with traditional morpho-taxonomic approaches. These individual studies have used DNA metabarcoding to assess diversity and community structure of aquatic organisms both in marine and freshwater systems globally over the last decade. However, a systematic analysis of the comparability and effectiveness of DNA-based community assessment across all of these studies has hitherto been lacking. Here we performed the first meta-analysis of all available studies comparing traditional methods and DNA metabarcoding to measure and assess biological diversity of key aquatic groups, including microorganisms, macroinvertebrates, and fish. Across 215 datasets, we found that DNA metabarcoding provides diversity estimates (richness) that are globally consistent to those obtained using traditional methods. DNA metabarcoding also generates species inventories that are highly congruent with traditional methods for fish. Contrastingly, however, species inventories of microorganisms and macroinvertebrates obtained by DNA metabarcoding showed pronounced differences to traditional methods, missing some taxa but at the same time detecting otherwise overseen diversity. Our results indicate that DNA metabarcoding is efficient to estimate local and regional richness. The method is generally sufficiently advanced to study the composition of fish communities and replace more invasive traditional methods. For smaller organisms, like macroinvertebrates and microorganisms, DNA metabarcoding may continue to give complementary rather than identical estimates compared to traditional approaches. Systematic and comparable data collection will increase the understanding of different aspects of this complementarity, and increase the effectiveness of the method and adequate interpretation of the results.

ecology↗