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The benefits of counting butterflies: recommendations for a successful citizen science project
(2022)
Citizen science (CS) projects, being popular across many fields of science, have recently also become a popular tool to collect biodiversity data. Although the benefits of such projects for science and policy making are well understood, relatively little is known about the benefits participants get from these projects as well as their personal backgrounds and motivations. Furthermore, very little is known about their expectations. We here examine these aspects, with the citizen science project "German Butterfly Monitoring" as an example. A questionnaire was sent to all participants of the project and the responses to the questionnaire indicated the following: center dot Most transect walkers do not have a professional background in this field, though they do have a high educational level, and are close to retirement, with a high number of females; center dot An important motivation to join the project is to preserve the natural environment and to contribute to scientific knowledge; center dot Participants benefit by enhancing their knowledge about butterflies and especially their ability to identify different species (taxonomic knowledge); center dot Participants do not have specific expectations regarding the project beyond proper management and coordination, but have an intrinsic sense of working for a greater good. The willingness to join a project is higher if the project contributes to the solution of a problem discussed in the media (here, insect decline). Based on our findings from the analysis of the questionnaire we can derive a set of recommendations for establishing a successful CS project. These include the importance of good communication, e.g., by explaining what the (scientific) purpose of the project is and what problems are to be solved with the help of the data collected in the project. The motivation to join a CS project is mostly intrinsic and CS is a good tool to engage people during difficult times such as the COVID-19 pandemic, giving participants the feeling of doing something useful.
Human induced pluripotent stem cells (hiPSCs) are highly sensitive to extrinsic physical and biochemical signals from their extracellular microenvironments. In this study, we analyzed the effect of cyclic temperature changes on hiPSCs behaviors, especially by means of scanning force microscopy (BIO-AFM). The alternation in cellular mechanics, as well as the secretion and pattern of deposition of extracellular matrix (ECM) protein in hiPSCs were evaluated. The arrangement of the actin cytoskeleton changed with the variation of the temperature. The rearranged cytoskeleton architecture led to the subsequent changes in cell mechanics (Young's modulus of hiPSCs). With the exposure to the cyclic cold stimuli, an increase in the average surface roughness (Ra) and roughness mean square (RMS) was detected. This observation might be at least in part due to the upregulated secretion of Laminin alpha 5 during repeated temporary cooling. The expression of pluripotent markers, NANOG and SOX2, was not impaired in hiPSCs, when exposed to the cyclic cold stimuli for 24 h. Our findings provide an insight into the effect of temperature on the hiPSC behaviors, which may contribute to a better understanding of the application of locally controlled therapeutic hypothermia.
1. Microplastics in soils have become an important threat for terrestrial systems as they may potentially alter the geochemical/biophysical soil environment and can interact with drought. As microplastics may affect soil water content, this could exacerbate the well-known negative effects of drought on ecosystem functionality. Thus, functions including litter decomposition, soil aggregation or those related with nutrient cycling can be altered. Despite this potential interaction, we know relatively little about how microplastics, under different soil water conditions, affect ecosystem functions and multifunctionality.
2. To address this gap, we performed an experiment using grassland plant communities growing in microcosms. Microplastic fibres (absent, present) and soil water conditions (well-watered, drought) were applied in a fully factorial design. At harvest, we measured soil ecosystem functions related to nutrient cycling (beta-glucosaminidase, beta-D-cellobiosidase, phosphatase, beta-glucosidase enzymes), respiration, nutrient retention, pH, litter decomposition and soil aggregation (water stable aggregates). As terrestrial systems provide these functions simultaneously, we also assessed ecosystem multifunctionality, an index that encompasses the array of ecosystem functions measured here.
3. We found that the interaction between microplastic fibres and drought affected ecosystem functions and multifunctionality. Drought had negatively affected nutrient cycling by decreasing enzymatic activities by up to similar to 39%, while microplastics increased soil aggregation by similar to 18%, soil pH by similar to 4% and nutrient retention by up to similar to 70% by diminishing nutrient leaching. Microplastic fibres also impacted soil enzymes, respiration and ecosystem multifunctionality, but importantly, the direction of these effects depended on soil water status. That is, under well-watered conditions, these functions decreased with microplastic fibres by up to similar to 34% while under drought they had similar values irrespective of the microplastic presence, or tended to increase with microplastics. Litter decomposition had a contrary pattern increasing with microplastics by similar to 6% under well-watered conditions while decreasing to a similar percentage under drought.
4. Synthesis and applications. Single ecosystem functions can be positively or negatively affected by microplastics fibres depending on soil water status. However, our results suggest that microplastic fibres may cause negative effects on ecosystem soil multifunctionality of a similar magnitude as drought. Thus, strategies to counteract this new global change factor are necessary.
Full-length transcriptome
(2021)
Fish is considered as a supreme model for clarifying the evolution and regulatory mechanism of vertebrate immunity. However, the knowledge of distinct immune cell populations in fish is still limited, and further development of techniques advancing the identification of fish immune cell populations and their functions are required. Single cell RNA-seq (scRNA-seq) has provided a new approach for effective in-depth identification and characterization of cell subpopulations. Current approaches for scRNA-seq data analysis usually rely on comparison with a reference genome and hence are not suited for samples without any reference genome, which is currently very common in fish research. Here, we present an alternative, i.e. scRNA-seq data analysis with a full-length transcriptome as a reference, and evaluate this approach on samples from Epinephelus coioides-a teleost without any published genome. We show that it reconstructs well most of the present transcripts in the scRNA-seq data achieving a sensitivity equivalent to approaches relying on genome alignments of related species. Based on cell heterogeneity and known markers, we characterized four cell types: T cells, B cells, monocytes/macrophages (Mo/M phi) and NCC (non-specific cytotoxic cells). Further analysis indicated the presence of two subsets of Mo/M phi including M1 and M2 type, as well as four subsets in B cells, i.e. mature B cells, immature B cells, pre B cells and early-pre B cells. Our research will provide new clues for understanding biological characteristics, development and function of immune cell populations of teleost. Furthermore, our approach provides a reliable alternative for scRNA-seq data analysis in teleost for which no reference genome is currently available.
Species community structures of Afrotropical butterflies differ depending on the monitoring method
(2022)
Standardised biodiversity assessment is crucial to understand community structures and population dynamics of animals.
There exist various methods to monitor biodiversity. Approaches differ depending on the target species group and the aim of study, and show advantages and disadvantages.
The obtained data and results are influenced by local environmental conditions and seasonal variability.
In a comparative approach, we studied butterfly diversity and community structure in the dryland savannah biome of south-eastern Kenya with two different methods, transect counts and bait trapping.
We repeatedly collected data throughout the dry and rainy seasons, in both near natural and anthropogenically influenced landscapes. Significantly more species and individuals were recorded by transect counts than by bait trapping, though the larger and more mobile Nymphalid species (and in particular representatives of the genus Charaxes) were comparatively overrepresented in traps.
The transect data revealed much more pronounced effects of land-use and seasonality than the trap data. These results show that the choice of data collection methods must depend on the general research question, habitat conditions and season. To study the relative variation of species diversity and abundance, the collection of a fraction of the total species diversity might be sufficient.
However, if the focus is on a largely complete recording of species diversity, the use of various collection methods is essential. More specifically, our data clearly demonstrate that transect counts represent a reasonable method for assessing butterfly diversity for the African dryland savannah region, but fails to fully capture occurrences of all species. Bait trapping can be used only as a supplementary method for assessing some few highly mobile low-density species.
Genomic prediction has revolutionized crop breeding despite remaining issues of transferability of models to unseen environmental conditions and environments. Usage of endophenotypes rather than genomic markers leads to the possibility of building phenomic prediction models that can account, in part, for this challenge. Here, we compare and contrast genomic prediction and phenomic prediction models for 3 growth-related traits, namely, leaf count, tree height, and trunk diameter, from 2 coffee 3-way hybrid populations exposed to a series of treatment-inducing environmental conditions. The models are based on 7 different statistical methods built with genomic markers and ChlF data used as predictors. This comparative analysis demonstrates that the best-performing phenomic prediction models show higher predictability than the best genomic prediction models for the considered traits and environments in the vast majority of comparisons within 3-way hybrid populations. In addition, we show that phenomic prediction models are transferrable between conditions but to a lower extent between populations and we conclude that chlorophyll a fluorescence data can serve as alternative predictors in statistical models of coffee hybrid performance. Future directions will explore their combination with other endophenotypes to further improve the prediction of growth-related traits for crops.
The Lena Delta in Siberia is the largest delta in the Arctic and as a snow-dominated ecosystem particularly vulnerable to climate change.
Using the two decades of MODerate resolution Imaging Spectroradiometer satellite acquisitions, this study investigates interannual and spatial variability of snow-cover duration and summer vegetation vitality in the Lena Delta.
We approximated snow by the application of the normalized difference snow index and vegetation greenness by the normalized difference vegetation index (NDVI). We consolidated the analyses by integrating reanalysis products on air temperature from 2001 to 2021, and air temperature, ground temperature, and the date of snow-melt from time-lapse camera (TLC) observations from the Samoylov observatory located in the central delta.
We extracted spring snow-cover duration determined by a latitudinal gradient. The 'regular year' snow-melt is transgressing from mid-May to late May within a time window of 10 days across the delta.
We calculated yearly deviations per grid cell for two defined regions, one for the delta, and one focusing on the central delta. We identified an ensemble of early snow-melt years from 2012 to 2014, with snow-melt already starting in early May, and two late snow-melt years in 2004 and 2017, with snow-melt starting in June. In the times of TLC recording, the years of early and late snow-melt were confirmed.
In the three summers after early snow-melt, summer vegetation greenness showed neither positive nor negative deviations. Whereas, vegetation greenness was reduced in 2004 after late snow-melt together with the lowest June monthly air temperature of the time series record. Since 2005, vegetation greenness is rising, with maxima in 2018 and 2021.
The NDVI rise since 2018 is preceded by up to 4 degrees C warmer than average June air temperature. The ongoing operation of satellite missions allows to monitor a wide range of land surface properties and processes that will provide urgently needed data in times when logistical challenges lead to data gaps in land-based observations in the rapidly changing Arctic.
The production of volatile organic compounds (VOCs) represents a promising strategy of plant-beneficial bacteria to control soil-borne phytopathogens.
Pseudomonas sp. PICF6 and Pseudomonas simiae PICF7 are two indigenous inhabitants of olive roots displaying effective biological control against Verticillium dahliae. Additionally, strain PICF7 is able to promote the growth of barley and Arabidopsis thaliana, VOCs being involved in the growth of the latter species.
In this study, the antagonistic capacity of these endophytic bacteria against relevant phytopathogens (Verticillium spp., Rhizoctonia solani, Sclerotinia sclerotiorum and Fusarium oxysporum f.sp. lycopersici) was assessed. Under in vitro conditions, PICF6 and PICF7 were only able to antagonize representative isolates of V. dahliae and V. longisporum. Remarkably, both strains produced an impressive portfolio of up to twenty VOCs, that included compounds with reported antifungal (e.g., 1-undecene, (methyldisulfanyl) methane and 1-decene) or plant growth promoting (e.g., tridecane, 1-decene) activities. Moreover, their volatilomes differed strongly in the absence and presence of V. dahliae.
For example, when co incubated with the defoliating pathotype of V. dahliae, the antifungal compound 4-methyl-2,6-bis(2-methyl-2-propanyl)phenol was produced. Results suggest that volatiles emitted by these endophytes may differ in their modes of action, and that potential benefits for the host needs further investigation in planta.
Since the beginning of the Anthropocene, lacustrine biodiversity has been influenced by climate change and human activities. These factors advance the spread of harmful cyanobacteria in lakes around the world, which affects water quality and impairs the aquatic food chain. In this study, we assessed changes in cyanobacterial community dynamics via sedimentary DNA (sedaDNA) from well-dated lake sediments of Lake Tiefer See, which is part of the Klocksin Lake Chain spanning the last 350 years. Our diversity and community analysis revealed that cyanobacterial communities form clusters according to the presence or absence of varves. Based on distance-based redundancy and variation partitioning analyses (dbRDA and VPA) we identified that intensified lake circulation inferred from vegetation openness reconstructions, delta C-13 data (a proxy for varve preservation) and total nitrogen content were abiotic factors that significantly explained the variation in the reconstructed cyanobacterial community from Lake Tiefer See sediments. Operational taxonomic units (OTUs) assigned to Microcystis sp. and Aphanizomenon sp. were identified as potential eutrophication-driven taxa of growing importance since circa common era (ca. CE) 1920 till present. This result is corroborated by a cyanobacteria lipid biomarker analysis. Furthermore, we suggest that stronger lake circulation as indicated by non-varved sediments favoured the deposition of the non-photosynthetic cyanobacteria sister clade Sericytochromatia, whereas lake bottom anoxia as indicated by subrecent- and recent varves favoured the Melainabacteria in sediments. Our findings highlight the potential of high-resolution amplicon sequencing in investigating the dynamics of past cyanobacterial communities in lake sediments and show that lake circulation, anoxic conditions, and human-induced eutrophication are main factors explaining variations in the cyanobacteria community in Lake Tiefer See during the last 350 years.
Microbe-mediated enzymatic hydrolysis of organic matter entails the production of hydrolysate, the recovery of which may be more or less efficient. The selfish uptake mechanism, recently discovered, allows microbes to hydrolyze polysaccharides and take up large oligomers, which are then degraded in the periplasmic space. By minimizing the hydrolysate loss, selfish behaviour may be profitable for free-living cells dwelling in a patchy substrate landscape. However, selfish uptake seems to be tailored to algal-derived polysaccharides, abundant in organic particles, suggesting that particle-attached microbes may use this strategy. We tracked selfish polysaccharides uptake in surface microbial communities of the northeastern Mediterranean Sea, linking the occurrence of this processing mode with microbial lifestyle. Additionally, we set up fluorescently labelled polysaccharides incubations supplying phytodetritus to investigate a 'pioneer' scenario for particle-attached microbes. Under both conditions, selfish behaviour was almost exclusively carried out by particle-attached microbes, suggesting that this mechanism may represent an advantage in the race for particle exploitation. Our findings shed light on the selfish potential of particle-attached microbes, suggesting multifaceted foraging strategies exerted by particle colonizers.