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Etmopteridae (lantern sharks) is the most species-rich family of sharks, comprising more than 50 species.
Many species are described from few individuals, and re-collection of specimens is often hindered by the remoteness of their sampling sites.
For taxonomic studies, comparative morphological analysis of type specimens housed in natural history collections has been the main source of evidence.
In contrast, DNA sequence information has rarely been used.
Most lantern shark collection specimens, including the types, were formalin fixed before long-term storage in ethanol solutions.
The DNA damage caused by both fixation and preservation of specimens has excluded these specimens from DNA sequence-based phylogenetic analyses so far.
However, recent advances in the field of ancient DNA have allowed recovery of wet-collection specimen DNA sequence data.
Here we analyse archival mitochondrial DNA sequences, obtained using ancient DNA approaches, of two wet-collection lantern shark paratype specimens, namely Etmopterus litvinovi and E. pycnolepis, for which the type series represent the only known individuals.
Target capture of mitochondrial markers from single-stranded DNA libraries allows for phylogenetic placement of both species.
Our results suggest synonymy of E. benchleyi with E. litvinovi but support the species status of E. pycnolepis. This revised taxonomy is helpful for future conservation and management efforts, as our results indicate a larger distribution range of E. litvinovi. This study further demonstrates the importance of wet-collection type specimens as genetic resource for taxonomic research.
Air chemistry is affected by the emission of biogenic volatile organic compounds (BVOCs), which originate from almost all plants in varying qualities and quantities. They also vary widely among different crops, an aspect that has been largely neglected in emission inventories. In particular, bioenergy-related species can emit mixtures of highly reactive compounds that have received little attention so far. For such species, long-term field observations of BVOC exchange from relevant crops covering different phenological phases are scarcely available. Therefore, we measured and modeled the emission of three prominent European bioenergy crops (maize, ryegrass, and oil-seed rape) for full rotations in north-eastern Germany. Using a proton transfer reaction-mass spectrometer combined with automatically moving large canopy chambers, we were able to quantify the characteristic seasonal BVOC flux dynamics of each crop species. The measured BVOC fluxes were used to parameterize and evaluate the BVOC emission module (JJv) of the physiology-oriented LandscapeDNDC model, which was enhanced to cover de novo emissions as well as those from plant storage pools. Parameters are defined for each compound individually. The model is used for simulating total compound-specific reactivity over several years and also to evaluate the importance of these emissions for air chemistry. We can demonstrate substantial differences between the investigated crops with oil-seed rape having 37-fold higher total annual emissions than maize. However, due to a higher chemical reactivity of the emitted blend in maize, potential impacts on atmospheric OH-chemistry are only 6-fold higher.
Leaf area index (LAI) is a key variable in understanding and modeling crop-environment interactions.
With the advent of increasingly higher spatial resolution satellites and sensors mounted on remotely piloted aircrafts (RPAs), the use of remote sensing in precision agriculture is becoming more common.
Since also the availability of methods to retrieve LAI from image data have also drastically expanded, it is necessary to test simultaneously as many methods as possible to understand the advantages and disadvantages of each approach.
Ground-based LAI data from three years of barley experiments were related to remote sensing information using vegetation indices (VI), machine learning (ML) and radiative transfer models (RTM), to assess the relative accuracy and efficacy of these methods.
The optimized soil adjusted vegetation index and a modified version of the Weighted Difference Vegetation Index performed slightly better than any other retrieval method. However, all methods yielded coefficients of determination of around 0.7 to 0.9.
The best performing machine learning algorithms achieved higher accuracies when four Sentinel-2 bands instead of 12 were used.
Also, the good performance of VIs and the satisfactory performance of the 4-band RTM, strongly support the synergistic use of satellites and RPAs in precision agriculture. One of the methods used, Sen2-Agri, an open source ML-RTM-based operational system, was also able to accurately retrieve LAI, although it is restricted to Sentinel-2 and Landsat data.
This study shows the benefits of testing simultaneously a broad range of retrieval methods to monitor crops for precision agriculture.
The nature of the interaction between prehistoric humans and their environment, especially the vegetation, has long been of interest. The Qinghai Lake Basin in North China is well-suited to exploring the interactions between prehistoric humans and vegetation in the Tibetan Plateau, because of the comparatively dense distribution of archaeological sites and the ecologically fragile environment. Previous pollen studies of Qinghai Lake have enabled a detailed reconstruction of the regional vegetation, but they have provided relatively little information on vegetation change within the Qinghai Lake watershed. To address the issue we conducted a pollen-based vegetation reconstruction for an archaeological site (YWY), located on the southern shore of Qinghai Lake. We used high temporal-resolution pollen records from the YWY site and from Qinghai Lake, spanning the interval since the last deglaciation (15.3 kyr BP to the present) to quantitatively reconstruct changes in the local and regional vegetation using Landscape Reconstruction Algorithm models. The results show that, since the late glacial, spruce forest grew at high altitudes in the surrounding mountains, while the lakeshore environment was occupied mainly by shrub-steppe. From the lateglacial to the middle Holocene, coniferous woodland began to expand downslope and reached the YWY site at 7.1 kyr BP. The living environment of the local small groups of Paleolithic-Epipaleolithic humans (during 15.3-13.1 kyr BP and 9-6.4 kyr BP) changed from shrub-steppe to coniferous forest-steppe. The pollen record shows no evidence of pronounced changes in the vegetation community corresponding to human activity. However, based on a comparison of the local and regional vegetation reconstructions, low values of biodiversity and a significant increase in two indicators of vegetation degradation, Chenopodiaceae and Rosaceae, suggest that prehistoric hunters-gatherers likely disturbed the local vegetation during 9.0-6.4 kyr BP. Our findings are a preliminary attempt to study human-environment interactions at Paleolithic-Epipaleolithic sites in the region, and they contribute to ongoing environmental archaeology research in the Tibetan Plateau.
Biodiversity maintains soil multifunctionality and soil organic carbon in novel urban ecosystems
(2022)
Biodiversity in urban ecosystems has the potential to increase ecosystem functions and support a suite of services valued by society, including services provided by soils. Specifically, the sequestration of carbon in soils has often been advocated as a solution to mitigate the steady increase in CO2 concentration in the atmosphere as a key driver of climate change. However, urban ecosystems are also characterized by an often high level of ecological novelty due to profound human-mediated changes, such as the presence of high numbers of non-native species, impervious surfaces or other disturbances. Yet it is poorly understood whether and how biodiversity affects ecosystem functioning and services of urban soils under these novel conditions. In this study, we assessed the influence of above- and below-ground diversity, as well as urbanization and plant invasions, on multifunctionality and organic carbon stocks of soils in non-manipulated grasslands along an urbanization gradient in Berlin, Germany. We focused on plant diversity (measured as species richness and functional trait diversity) and, in addition, on soil organism diversity as a potential mediator for the relationship of plant species diversity and ecosystem functioning. Our results showed positive effects of plant diversity on soil multifunctionality and soil organic carbon stocks along the entire gradient. Structural equation models revealed that plant diversity enhanced soil multifunctionality and soil organic carbon by increasing the diversity of below-ground organisms. These positive effects of plant diversity on soil multifunctionality and soil fauna were not restricted to native plant species only, but were also exerted by non-native species, although to a lesser degree. Synthesis. We conclude that enhancing diversity in plants and soil fauna of urban grasslands can increase the multifunctionality of urban soils and also add to their often underestimated but very valuable role in mitigating effects of climate change.
Local biodiversity patterns are expected to strongly reflect variation in topography, land use, dispersal boundaries, nutrient supplies, contaminant spread, management practices, and other anthropogenic influences. Contrary to this expectation, studies focusing on specific taxa revealed a biodiversity homogenization effect in areas subjected to long-term intensive industrial agriculture. We investigated whether land use affects biodiversity levels and community composition (alpha- and beta-diversity) in 67 kettle holes (KH) representing small aquatic islands embedded in the patchwork matrix of a largely agricultural landscape comprising grassland, forest, and arable fields. These KH, similar to millions of standing water bodies of glacial origin, spread across northern Europe, Asia, and North America, are physico-chemically diverse and differ in the degree of coupling with their surroundings. We assessed aquatic and sediment biodiversity patterns of eukaryotes, Bacteria, and Archaea in relation to environmental features of the KH, using deep-amplicon-sequencing of environmental DNA (eDNA). First, we asked whether deep sequencing of eDNA provides a representative picture of KH aquatic biodiversity across the Bacteria, Archaea, and eukaryotes. Second, we investigated if and to what extent KH biodiversity is influenced by the surrounding land use. We hypothesized that richness and community composition will greatly differ in KH from agricultural land use compared with KH in grasslands and forests. Our data show that deep eDNA amplicon sequencing is useful for in-depth assessments of cross-domain biodiversity comprising both micro- and macro-organisms, but has limitations with respect to single-taxa conservation studies. Using this broad method, we show that sediment eDNA, integrating several years to decades, depicts the history of agricultural land-use intensification. Aquatic biodiversity was best explained by seasonality, whereas land-use type explained little of the variation. We concluded that, counter to our hypothesis, land use intensification coupled with landscape wide nutrient enrichment (including atmospheric deposition), groundwater connectivity between KH and organismal (active and passive) dispersal in the tight network of ponds, resulted in a biodiversity homogenization in the KH water, leveling off today's detectable differences in KH biodiversity between land-use types. These findings have profound implications for measures and management strategies to combat current biodiversity loss in agricultural landscapes worldwide.
Trophic transfer efficiency (TTE) is usually calculated as the ratio of production rates between two consecutive trophic levels. Although seemingly simple, TTE estimates from lakes are rare. In our review, we explore the processes and structures that must be understood for a proper lake TTE estimate.
We briefly discuss measurements of production rates and trophic positions and mention how ecological efficiencies, nutrients (N, P) and other compounds (fatty acids) affect energy transfer between trophic levels and hence TTE.
Furthermore, we elucidate how TTE estimates are linked with size-based approaches according to the Metabolic Theory of Ecology, and how food-web models can be applied to study TTE in lakes.
Subsequently, we explore temporal and spatial heterogeneity of production and TTE in lakes, with a particular focus on the links between benthic and pelagic habitats and between the lake and the terrestrial environment.
We provide an overview of TTE estimates from lakes found in the published literature. Finally, we present two alternative approaches to estimating TTE. First, TTE can be seen as a mechanistic quantity informing about the energy and matter flow between producer and consumer groups.
This approach is informative with respect to food-web structure, but requires enormous amounts of data. The greatest uncertainty comes from the proper consideration of basal production to estimate TTE of omnivorous organisms.
An alternative approach is estimating food-chain and food-web efficiencies, by comparing the heterotrophic production of single consumer levels or the total sum of all heterotrophic production including that of heterotrophic bacteria to the total sum of primary production.
We close the review by pointing to a few research questions that would benefit from more frequent and standardized estimates of TTE in lakes.
How accurately can we retrieve irrigation timing and water amounts from (satellite) soil moisture?
(2022)
While ensuring food security worldwide, irrigation is altering the water cycle and generating numerous environmental side effects. As detailed knowledge about the timing and the amounts of water used for irrigation over large areas is still lacking, remotely sensed soil moisture has proved potential to fill this gap.
However, the spatial resolution and revisit time of current satellite products represent a major limitation to accurately estimating irrigation. This work aims to systematically quantify their impact on the retrieved irrigation information, hence assessing the value of satellite soil moisture for estimating irrigation timing and water amounts.
In a real-world experiment, we modeled soil moisture using actual irrigation and meteorological data, obtained from farmers and weather stations, respectively. Modeled soil moisture was compared against various remotely sensed products differing in terms of spatio-temporal resolution to test the hypothesis that high-resolution observations can disclose the irrigation signal from individual fields while coarse-scale satellite products cannot.
Then, in a synthetic experiment, we systematically investigated the effect of soil moisture spatial and temporal resolution on the accuracy of irrigation estimates. The analysis was further elaborated by considering different irrigation scenarios and by adding realistic amounts of random errors in the soil moisture time series.
We show that coarse-scale remotely sensed soil moisture products achieve higher correlations with rainfed simulations, while high-resolution satellite observations agree significantly better with irrigated simulations, suggesting that high-resolution satellite soil moisture can inform on field-scale (similar to 40 ha) irrigation. A thorough analysis of the synthetic dataset showed that satisfactory results, both in terms of detection (F-score > 0.8) and quantification (Pearson's correlation > 0.8), are found for noise-free soil moisture observations either with a temporal sampling up to 3 days or if at least one-third of the pixel covers the irrigated field(s).
However, irrigation water amounts are systematically underestimated for temporal samplings of more than one day, and decrease proportionally to the spatial resolution, i.e., coarsening the pixel size leads to larger irrigation underestimations.
Although lower spatial and temporal resolutions decrease the detection and quantification accuracies (e.g., R between 0.6 and 1 depending on the irrigation rate and spatio-temporal resolution), random errors in the soil moisture time series have a stronger negative impact (Pearson R always smaller than 0.85).
As expected, better performances are found for higher irrigation rates, i.e. when more water is supplied during an irrigation event. Despite the potentially large underestimations, our results suggest that high-resolution satellite soil moisture has the potential to track and quantify irrigation, especially over regions where large volumes of irrigation water are applied to the fields, and given that low errors affect the soil moisture observations.
The process of species formation is characterized by the accumulation of multiple reproductive barriers. The evolution of hybrid male sterility, or Haldane's rule, typically characterizes later stages of species formation, when reproductive isolation is strongest.
Yet, understanding how quickly reproductive barriers evolve and their consequences for maintaining genetic boundaries between emerging species remains a challenging task because it requires studying taxa that hybridize in nature.
Here, we address these questions using the meadow grasshopper Pseudochorthippus parallelus, where populations that show multiple reproductive barriers, including hybrid male sterility, hybridize in two natural hybrid zones. Using mitochondrial data, we infer that such populations diverged some 100,000 years ago, at the beginning of the last glacial cycle in Europe.
Nuclear data show that contractions at multiple glacial refugia, and post-glacial expansions have facilitated genetic differentiation between lineages that today interact in hybrid zones.
We find extensive introgression throughout the sampled species range, irrespective of the current strength of reproductive isolation. Populations exhibiting hybrid male sterility in two hybrid zones show repeatable patterns of genomic differentiation, consistent with shared genomic constraints affecting ancestral divergence or with the role of those regions in reproductive isolation.
Together, our results suggest that reproductive barriers that characterize late stages of species formation can evolve relatively quickly, particularly when associated with strong demographic changes. Moreover, we show that such barriers persist in the face of extensive gene flow, allowing future studies to identify associated genomic regions.
In vitro transcribed (IVT)-mRNA has been accepted as a promising therapeutic modality. Advances in facile and rapid production technologies make IVT-mRNA an appealing alternative to protein- or virus-based medicines.
Robust expression levels, lack of genotoxicity, and their manageable immunogenicity benefit its clinical applicability.
We postulated that innate immune responses of therapeutically relevant human cells can be tailored or abrogated by combinations of 5'-end and internal IVT-mRNA modifications.
Using primary human macrophages as targets, our data show the particular importance of uridine modifications for IVT-mRNA performance.
Among five nucleotide modification schemes tested, 5-methoxy-uridine outperformed other modifications up to 4-fold increased transgene expression, triggering moderate proinflammatory and non-detectable antiviral responses.
Macrophage responses against IVT-mRNAs exhibiting high immunogenicity (e.g., pseudouridine) could be minimized upon HPLC purification. Conversely, 5'-end modifications had only modest effects on mRNA expression and immune responses.
Our results revealed how the uptake of chemically modified IVT-mRNA impacts human macrophages, responding with distinct patterns of innate immune responses concomitant with increased transient transgene expression.
We anticipate our findings are instrumental to predictively address specific cell responses required for a wide range of therapeutic applications from eliciting controlled immunogenicity in mRNA vaccines to, e.g., completely abrogating cell activation in protein replacement therapies.