Biology subjects

Cristescu, M. E.

Publications and source records attributed to Cristescu, M. E..

14 recordsLinked to original sources

bioRxiv2025

Contrasted effects of human pressure on biodiversity in the UK: a multi-taxonomic assessment using airborne environmental DNA

Human activities have significantly modified habitats, resulting in a global biodiversity crisis. Here, we leveraged the first national-scale biodiversity survey based on airborne environmental DNA, comparing the effects of three human pressure indices increasing in complexity and scope across diverse vertebrates, insects, plants and fungi. While most taxa exhibited higher diversity in urban areas compared to rural ones, we uncovered more complex patterns using the landscape-pollution and human footprint indices, including dual diversity peaks at both high and moderate levels of human pressure. We also show an effect of human pressure on community composition even when local species richness remained stable: regardless of the human pressure index, anthropogenic sites were mostly characterized by synanthropic and invasive species. Overall, our results underscore the complex interactions among anthropogenic pressures, taxon diversity and community composition, demonstrating the value of multi-taxon analyses and multiple indices to better understand biodiversity patterns at large scales.

ecology↗

bioRxiv2025

First national survey of terrestrial biodiversity using airborne eDNA

Near real-time data across taxa are necessary for quantifying biodiversity at regional to continental scales and evaluating conservation measures. Yet, standardized methods and globally distributed infrastructure are still lacking. In this study, we conducted the first national survey of terrestrial biodiversity using a metabarcoding approach on airborne environmental DNA collected by a national ambient air quality monitoring network. Our goal was to perform a multi-taxonomic biodiversity assessment at a national scale, compare detections with those of another large-scale monitoring approach (citizen sciences) and estimate a tentative minimum eDNA transportation distance. We identified over 1,100 taxa, including vertebrates, invertebrates, protists, fungi and plants covering a wide range of life history traits and ecological niches. Citizen science and eDNA detections were complementary, with eDNA better mapping less charismatic and difficult to spot taxa, demonstrating its potential to align with global conservation goals. Airborne eDNA signals were relatively local, likely due to the deposition of the larger particles from the air over shorter distances and limited wind transportation at near ground level. Overall, our results show that molecular protocols integrated into existing air quality monitoring networks can provide standardized, biodiversity monitoring at relatively low field cost, with potential for broad scalability.

ecology↗

bioRxiv2025

A strong relationship between environmental DNA metabarcoding and rank-based abundance of fish

O_LIIncreasingly, molecular methods of species monitoring are integrated into freshwater biodiversity surveys and fisheries management. Inferring organism abundance or biomass from sequence counts derived from metabarcoding data has been an exciting but contentious concept in the biomonitoring community for some time. Although demonstrating a strong correlation with abundance has proven difficult, many researchers have assumed that quantitative metabarcoding data can at least provide broad-scale ranking of abundance. However, robust field validations of this widely-held assumption remain scarce. C_LIO_LIHere, we analyse metabarcoding read counts of fish eDNA data derived from 20 lakes and use betabinomial mixed effects models to compare this to rank abundance generated from long-term fish survey data. Rank abundance data for 18 species was generated within-species across-sites, meaning that ranks compare the abundance of the same species in different lakes. We also investigated a possible allometric effect on eDNA production by analysing a subset of data for effects of fish body mass on the amount of eDNA sequences. C_LIO_LIWe found a good relationship between species-specific eDNA sequences and within-species rank abundance categories for fishes, with rare fish producing 3% of sequences in a library, moderately abundant producing 7% and abundant fish producing 29%, according to model predictions. C_LIO_LIWe found a small negative effect of body mass on the amount of eDNA sequences, where the proportion of reads recovered significantly decreased with increased mean body mass of the population. C_LIO_LISynthesis and applications: The benefit of this approach is the potential for rapid assessment of rank abundance for multiple species, including smaller species which are often missed by conventional methods such as gillnetting, with relatively low amounts of additional effort. This approach will assist practitioners taking a species-based approach to freshwater habitat management in lakes worldwide. C_LI

ecology↗

bioRxiv2024

eDNA provides accurate and precise estimates of abundance by integrating bioenergetics and particle mass-balance

Anthropogenic activities have led to an unprecedented crisis in freshwater biodiversity loss. The capacity to monitor the abundance of wild populations is critical to conserving biodiversity, but conventional physical specimen collection methods are invasive, costly, and labour-intensive. Environmental DNA (eDNA) offers a promising alternative, being easy to sample, with studies under controlled laboratory conditions showing consistent correlations between eDNA concentration and abundance. However, applying eDNA to monitor abundance remains contentious, as eDNA particle dynamics and the ecology of eDNA production can decouple this relationship in natural ecosystems. To address this, we provide a novel modeling method to produce population estimates from eDNA. We integrated bioenergetics and mass-balance frameworks to relate eDNA concentrations to freshwater fish population abundance estimated through conventional mark-recapture in Brook Trout (Salvelinus fontinalis) across nine Rocky Mountains lakes, five of which underwent size-selective harvesting over two years. Our integrated framework improved the variance explained in eDNA concentrations from 24% to 71%. The integrated model accurately distinguished most (94%) abundance estimates across populations and sampling periods, detecting both natural and harvest-induced reductions in abundance within several populations. This study is the first to empirically integrate the DNA production mechanism and particle dynamics and provide a new methodological approach enabling rapid and accurate abundance quantification. We also discuss how this new tool can be integrated in existing monitoring programs.

ecology↗

bioRxiv2024

Pre-exposure to stress reduces loss of community and genetic diversity following severe environmental disturbance

Environmental stress caused by anthropogenic impacts is increasing worldwide. Understanding the ecological and evolutionary consequences for biodiversity will be crucial for our ability to respond effectively. Historical exposure to environmental stress is expected to select for resistant species, shifting community composition towards more stress-tolerant taxa. Concurrent with this species sorting process, genotypes within resistant taxa that have the highest relative fitness under severe stress are expected to increase in frequency, leading to evolutionary adaptation. However, empirical demonstrations of these dual ecological and evolutionary processes in natural communities are lacking. Here, we provide the first evidence for simultaneous species sorting and evolutionary adaptation across multiple species within a natural freshwater bacterial community. Using a two-phase stressor experimental design (acidification pre-exposure followed by severe acidification) in aquatic mesocosms, we show that pre-exposed communities were more resistant than naive communities to taxonomic loss when faced with severe acid stress. However, after sustained severe acidification, taxonomic richness of both pre-exposed and naive communities eventually converged. All communities experiencing severe acidification became dominated by an acidophilic bacterium, Acidiphilium rubrum, but this species retained greater genetic diversity and followed distinct evolutionary trajectories in pre-exposed relative to naive communities. These patterns were shared across other acidophilic species, providing repeated evidence for the impact of pre-exposure on evolutionary outcomes despite the convergence of community profiles. Our results underscore the need to consider both ecological and evolutionary processes to accurately predict the responses of natural communities to environmental change.

evolutionary biology↗

bioRxiv2022

Environmental transcriptomics under heat stress: Can environmental RNA reveal changes in gene expression of aquatic organisms?

To safeguard biodiversity in a changing climate, we require taxonomic information about species turnover and insights into the health of organisms. Environmental DNA approaches are increasingly used for species identification, but cannot provide functional insights. Transcriptomic methods reveal the physiological states of macroorganisms, but are currently species specific and require tissue sampling or animal sacrifice, making community-wide assessments challenging. Here, we test if broad functional information (expression level of the transcribed genes) can be harnessed from environmental RNA (eRNA), which includes extra-organismal RNA from macroorganisms along with whole microorganisms. We exposed Daphnia pulex as well as phytoplankton prey and microorganism colonizers to control (20 {degrees}C) and heat stress (28 {degrees}C) conditions for seven days. We sequenced eRNA from tank water (after complete removal of Daphnia) as well as RNA from Daphnia tissue, enabling comparisons of extra-organismal and organismal RNA based gene expression profiles. Both RNA types detected similar heat stress responses of Daphnia. Using eRNA, we identified 32 Daphnia genes to be differentially expressed following heat stress. Of these, 17 were also differentially expressed and exhibited similar levels of relative expression in organismal RNA. In addition to the extra-organismal Daphnia response, eRNA detected community-wide heat stress responses consisting of distinct functional profiles and 121 differentially expressed genes across 8 taxa. Our study demonstrates that environmental transcriptomics based on eRNA can non-invasively reveal gene expression responses of macroorganisms following environmental changes, with broad potential implications for the biomonitoring of ecological health across the trophic chain.

ecology↗

bioRxiv2022

Freshwater connectivity transforms spatially integrated signals of biodiversity

Aquatic ecosystems offer a continuum of water flow from headwater streams to inland lakes and coastal marine systems. This spatial connectivity influences the structure, function and dynamics of aquatic communities, which are among the most threatened and degraded on earth. Environmental DNA achieves biodiversity surveys in these habitats in a high-throughput, spatially integrated way. Here, we determine the spatial resolution of eDNA in dendritic freshwater networks that are typical of aquatic habitats. Our intensive sampling campaign comprised over 430 eDNA samples across 21 connected lakes, allowing us to analyse detections at a variety of scales, from different habitats within a lake to entire lake networks. We found strong signals of within-lake variation in eDNA distribution reflective of typical habitat use by both fish and zooplankton. Most importantly, we also found that connecting channels between lakes resulted in an accumulation of downstream eDNA detections in lakes with a higher number of inflows, and as networks increased in length. These findings have profound implications for the interpretation of eDNA detections in aquatic ecosystems in global-scale biodiversity monitoring observations.

ecology↗

bioRxiv2021

Environmental nucleic acids: a field-based comparison for monitoring freshwater habitats using eDNA and eRNA

Nucleic acids released by organisms and isolated from environmental substrates are increasingly being used for molecular biomonitoring. While environmental DNA (eDNA) has received attention recently, the potential of environmental RNA as a biomonitoring tool remains less explored. Several recent studies using paired DNA and RNA metabarcoding of bulk samples suggest that RNA might better reflect "metabolically active" parts of the community. However, such studies mainly capture organismal eDNA and eRNA. For larger eukaryotes, isolation of extra-organismal RNA will be important, but viability needs to be examined in a field-based setting. In this study we evaluate (a) whether extra-organismal eRNA release from macroeukaryotes can be detected given its supposedly rapid degradation, and (b) if the same field collection methods for eDNA can be applied to eRNA. We collected eDNA and eRNA from water in lakes where fish community composition is well documented, enabling a comparison between the two nucleic acids in two different seasons with monitoring using conventional methods. We found that eRNA is released from macroeukaryotes and can be filtered from water and metabarcoded in a similar manner as eDNA to reliably provide species composition information. eRNA had a small but significantly greater true positive rate than eDNA, indicating that it correctly detects more species known to exist in the lakes. Given relatively small differences between the two molecules in describing fish community composition, we conclude that if eRNA provides significant advantages in terms of lability, it is a strong candidate to add to the suite of molecular monitoring tools.

ecology↗

bioRxiv2021

Comparative analysis of zooplankton diversity in freshwaters: What can we gain from metagenomic analysis?

Molecular genetic approaches applied to environmental DNA have great potential for biodiversity research and ecosystem monitoring. A metagenome contains genetic information from all organisms captured in an environmental sample. It has been primarily used to study bacteria and archaea, but promising reports focusing on metazoan diversity are emerging. However, methodological uncertainties remain, and studies are required to validate the power and the limitations of such an approach when applied to macro-eukaryotes. Here, we analyzed water sample metagenomes to estimate zooplankton diversity in 22 freshwater lakes across Eastern Canada. We tested the coherence of data based on morphologically identified zooplankton taxa and molecular genetic data derived from shotgun sequencing of environmental DNA collected at the same time. RV coefficients showed a significant correlation between the relative abundance of zooplankton families derived from small subunit rRNA genes extracted from the metagenomes and morphologically identified zooplankton. However, differences in congruence with morphological counts were detected when varied bioinformatic approaches were applied to presence-absence data. This study presents one of the first diversity assessments of a group of aquatic metazoans using metagenomes and validates the coherence of the community composition derived from genetic and classical species surveys. Overall, our results suggest that metagenomics has the potential to be further developed to describe metazoan biodiversity in aquatic ecosystems, and to advance this area we provide key recommendations for workflow improvement.

ecology↗

bioRxiv2020

Assessment of current taxonomic assignment strategies for metabarcoding eukaryotes

The effective use of metabarcoding in biodiversity science has brought important analytical challenges due to the need to generate accurate taxonomic assignments. The assignment of sequences to a generic or species level is critical for biodiversity surveys and biomonitoring, but it is particularly challenging. Researchers must select the approach that best recovers information on species composition. This study evaluates the performance and accuracy of seven methods in recovering the species composition of mock communities which vary in species number and specimen abundance, while holding upstream molecular and bioinformatic variables constant. It also evaluates the impact of parameter optimization on the quality of the predictions. Despite the general belief that BLAST top hit underperforms newer methods, our results indicate that it competes well with more complex approaches if optimized for the mock community under study. For example, the two machine learning methods that were benchmarked proved more sensitive to the reference database heterogeneity and completeness than methods based on sequence similarity. The accuracy of assignments was impacted by both species and specimen counts which will influence the selection of appropriate software. We urge the usage of realistic mock communities to allow optimization of parameters, regardless of the taxonomic assignment method used.

bioinformatics↗

bioRxiv2020

A2G2: A Python wrapper to perform very largealignments in semi-conserved regions

SummaryAmplicons to Global Gene (A2G2) is a Python wrapper that uses MAFFT and an "Amplicon to Gene" strategy to align very large numbers of sequences while improving alignment accuracy. It is specially developed to deal with conserved genes, where traditional aligners introduce a significant amount of gaps. A2G2 leverages the add sequences option of MAFFT to align the sequences to a global reference gene and a local reference region. Both of these references can be consensus sequences of trusted sources. Efficient parallelization of these tasks allows A2G2 to align a very large number of sequences (> 500K) in a reasonable amount of time. A2G2 can be imported in Python for easier integration with other software, or can be run via command line. AvailabilityA2G2 is implemented in Python 3 (3.6) and depends on MAFFT availability. Other package requirements can be found in the requirements.txt file at https://github.com/jshleap/A2G. A2G2 is also available via PyPi (https://pypi.org/project/A2G). It is licensed under the LGPLv3. Supplementary informationSupplementary material is available at github as jupyter notebook.

bioinformatics↗

bioRxiv2020

Thermal stratification and fish thermal preference explain vertical eDNA distributions in lakes

Significant advances have been made towards surveying animal and plant communities using DNA isolated from environmental samples. Despite rapid progress, we lack a comprehensive understanding of the "ecology" of environmental DNA (eDNA), particularly its temporal and spatial distribution and how this is shaped by abiotic and biotic processes. Here, we tested how seasonal variation in thermal stratification and animal habitat preferences influence the distribution of eDNA in lakes. We sampled eDNA depth profiles of five dimictic lakes during both summer stratification and autumn turnover, each containing warm- and cool-water fishes as well as the cold-water stenotherm, lake trout (Salvelinus namaycush). Habitat use by lake trout was validated by acoustic telemetry and was significantly related to eDNA distribution during stratification. Fish eDNA became "stratified" into layers during summer months, reflecting lake stratification and the thermal niches of the species. During summer months, lake trout, which rarely ventured into shallow waters, could only be detected at the deepest layers of the lakes, whereas the eDNA of warm-water fishes was much more abundant above the thermocline. By contrast, during autumn lake turnover, the fish species assemblage as detected by eDNA was homogenous throughout the water column. These findings contribute to our overall understanding of the "ecology" of eDNA within lake ecosystems, illustrating how the strong interaction between seasonal thermal structure in lakes and thermal niches of species on very localised spatial scales influences our ability to detect species.

ecology↗

bioRxiv2020

Allometric scaling strengthens the relationship between eDNA particle concentration and organism abundance in nature

Organism abundance is a critical parameter in ecology, but its estimation is often challenging. Approaches utilizing eDNA to indirectly estimate abundance have recently generated substantial interest. However, preliminary correlations observed between eDNA concentration and abundance in nature are typically moderate in strength with significant unexplained variation. Here we apply a novel approach to integrate allometric scaling coefficients into models of eDNA concentration and organism abundance. We hypothesize that eDNA particle production scales non-linearly with mass, with scaling coefficients < 1. Wild populations often exhibit substantial variation in individual body size distributions; we therefore predict that the distribution of mass across individuals within a population will influence population-level eDNA production rates. To test our hypothesis, we collected standardized body size distribution and mark-recapture abundance data using whole-lake experiments involving nine populations of brook trout. We correlated eDNA concentration with three metrics of abundance: density (individuals/ha), biomass (kg/ha), and allometrically scaled mass (ASM) ({sum}(individual mass0.73)/ha). Density and biomass were both significantly positively correlated with eDNA concentration (adj. R2 = 0.59 and 0.63, respectively), but ASM exhibited improved model fit (adj. R2 = 0.78). We also demonstrate how estimates of ASM derived from eDNA samples in unknown systems can be converted to biomass or density estimates with additional size structure data. Future experiments should empirically validate allometric scaling coefficients for eDNA production, particularly where substantial intraspecific size distribution variation exists. Incorporating allometric scaling may improve predictive models to the extent that eDNA concentration may become a reliable indicator of abundance in nature.

ecology↗

bioRxiv2017

Selection constrains high rates of satellite DNA mutation in Daphnia pulex

A long-standing evolutionary puzzle is that all eukaryotic genomes contain large amounts of tandemly-repeated satellite DNA whose composition varies greatly among even closely related species. To elucidate the evolutionary forces governing satellite dynamics, quantification of the rates and patterns of mutations in satellite DNA copy number and tests of its selective neutrality are necessary. Here we used whole-genome sequences of 28 mutation accumulation (MA) lines of Daphnia pulex in addition to six isolates from a non-MA population originating from the same progenitor to both estimate mutation rates of abundances of satellite sequences and evaluate the selective regime acting upon them. We found that mutation rates of individual satellite sequence \"kmers\" were both high and highly variable, ranging from additions/deletions of 0.29 - 105 copies per generation (reflecting changes of 0.12 - 0.80 percent per generation). Our results also provide evidence that new kmer sequences are often formed from existing ones. The non-MA population isolates showed a signal of either purifying or stabilizing selection, with 33 % lower variation in kmer abundance on average than the MA lines, although the level of selective constraint was not evenly distributed across all kmers. The changes between many pairs of kmers were correlated, and the pattern of correlations was significantly different between the MA lines and the non-MA population. Our study demonstrates that kmer sequences can experience extremely rapid evolution in abundance, which can lead to high levels of divergence in genome-wide satellite DNA composition between closely related species.

evolutionary biology↗