Pollinator size and its consequences: Robust estimates of body size in pollinating insects

Body size is an integral functional trait that underlies pollination‐related ecological processes, yet it is often impractical to measure directly. Allometric scaling laws have been used to overcome this problem. However, most existing models rely upon small sample sizes, geographically restricted sampling and have limited applicability for non‐bee taxa. Allometric models that consider biogeography, phylogenetic relatedness, and intraspecific variation are urgently required to ensure greater accuracy. We measured body size as dry weight and intertegular distance (ITD) of 391 bee species (4,035 specimens) and 103 hoverfly species (399 specimens) across four biogeographic regions: Australia, Europe, North America, and South America. We updated existing models within a Bayesian mixed‐model framework to test the power of ITD to predict interspecific variation in pollinator dry weight in interaction with different co‐variates: phylogeny or taxonomy, sexual dimorphism, and biogeographic region. In addition, we used ordinary least squares regression to assess intraspecific dry weight ~ ITD relationships for ten bees and five hoverfly species. Including co‐variates led to more robust interspecific body size predictions for both bees and hoverflies relative to models with the ITD alone. In contrast, at the intraspecific level, our results demonstrate that the ITD is an inconsistent predictor of body size for bees and hoverflies. The use of allometric scaling laws to estimate body size is more suitable for interspecific comparative analyses than assessing intraspecific variation. Collectively, these models form the basis of the dynamic R package, “pollimetry,” which provides a comprehensive resource for allometric pollination research worldwide.     

Linking demographic and food‐web models to understand management trade‐offs

Alternatives in ecosystem‐based management often differ with respect to trade‐offs between ecosystem values. Ecosystem or food‐web models and demographic models are typically employed to evaluate alternatives, but the approaches are rarely integrated to uncover conflicts between values. We applied multistate models to a capture–recapture dataset on common guillemots Uria aalge breeding in the Baltic Sea to identify factors influencing survival. The estimated relationships were employed together with Ecopath‐with‐Ecosim food‐web model simulations to project guillemot survival under six future scenarios incorporating climate change. The scenarios were based on management alternatives for eutrophication and cod fisheries, issues considered top priority for regional management, but without known direct effects on the guillemot population. Our demographic models identified prey quantity (abundance and biomass of sprat Sprattus sprattus) as the main factor influencing guillemot survival. Most scenarios resulted in projections of increased survival, in the near (2016–2040) and distant (2060–2085) future. However, in the scenario of reduced nutrient input and precautionary cod fishing, guillemot survival was projected to be lower in both future periods due to lower sprat stocks. Matrix population models suggested a substantial decline of the guillemot population in the near future, 24% per 10 years, and a smaller reduction, 1.1% per 10 years, in the distant future. To date, many stakeholders and Baltic Sea governments have supported reduced nutrient input and precautionary cod fishing and implementation is underway. Negative effects on nonfocal species have previously not been uncovered, but our results show that the scenario is likely to negatively impact the guillemot population. Linking model results allowed identifying trade‐offs associated with management alternatives. This information is critical to thorough evaluation by decision‐makers, but not easily obtained by food‐web models or demographic models in isolation. Appropriate datasets are often available, making it feasible to apply a linked approach for better‐informed decisions in ecosystem‐based management.     

Genetic diversity loss in a biodiversity hotspot: ancient DNA quantifies genetic decline and former connectivity in a critically endangered marsupial

The extent of genetic diversity loss and former connectivity between fragmented populations are often unknown factors when studying endangered species. While genetic techniques are commonly applied in extant populations to assess temporal and spatial demographic changes, it is no substitute for directly measuring past diversity using ancient DNA (aDNA). We analysed both mitochondrial DNA (mtDNA) and nuclear microsatellite loci from 64 historical fossil and skin samples of the critically endangered Western Australian woylie (Bettongia penicillata ogilbyi), and compared them with 231 (n = 152 for mtDNA) modern samples. In modern woylie populations 15 mitochondrial control region (CR) haplotypes were identified. Interestingly, mtDNA CR data from only 29 historical samples demonstrated 15 previously unknown haplotypes and detected an extinct divergent clade. Through modelling, we estimated the loss of CR mtDNA diversity to be between 46% and 91% and estimated this to have occurred in the past 2000–4000 years in association with a dramatic population decline. In addition, we obtained near‐complete 11‐loci microsatellite profiles from 21 historical samples. In agreement with the mtDNA data, a number of ‘new’ microsatellite alleles was only detected in the historical populations despite extensive modern sampling, indicating a nuclear genetic diversity loss >20%. Calculations of genetic diversity (heterozygosity and allelic rarefaction) showed that these were significantly higher in the past and that there was a high degree of gene flow across the woylie's historical range. These findings have an immediate impact on how the extant populations are managed and we recommend the implementation of an assisted migration programme to prevent further loss of genetic diversity. Our study demonstrates the value of integrating aDNA data into current‐day conservation strategies.     

miR-142-3p is a tumor suppressor that inhibits estrogen receptor expression in ER-positive breast cancer

Estrogen receptors (ERs) are involved in the development of many types of malignant tumors, in particular, breast cancer. Among others, ERs affect cell growth, proliferation, and differentiation. The microRNA (miRNA) miR-142-3p has been shown to inhibit carcinogenesis by regulating various cellular processes, including cell cycle progression, cell migration, apoptosis, and invasion. It does so via targeting molecules involved in a range of signaling pathways. We surgically collected 20 ER-positive breast cancer samples, each with matched adjacent normal breast tissue, and measured the expression of miR-142-3p via quantitative real-time polymerase chain reaction (qRT-PCR). Bioinformatics methods, luciferase reporter assay, qRT-PCR, and western blot analysis were used to assess whether miR-142-3p could target ESR1, which encodes the estrogen receptor, in ER-positive breast cancer cells and patient samples. We also restored miRNA expression and performed cell viability, cytotoxicity, and colony formation assays. Western blot analysis and qRT-PCR were used to study the expression of apoptosis and stemness markers. We found that miR-142-3p is downregulated in ER-positive breast cancers. Restoration of miR-142-3p expression in ER-positive breast cancer cells reduced cell viability, induced apoptosis via the intrinsic pathway and decreased both colony formation and the expression of stem cell markers. Bioinformatic analysis predicted miR-142-3p could bind to 3′-untranslated region ESR1 messenger RNA (mRNA). Consistently, we demonstrated that miR-142-3p reduced luciferase activity in ER-positive breast cancer cells, and decreased ESR1 expression in both mRNA and protein levels. The results revealed miR-142-3p and ESR1 expression correlated negatively in ER-positive breast cancer samples. The results suggest miR-142-3p acts as a tumor suppressor via multiple mechanisms. Thus, restoration of miR-142-3p expression, for example, via miRNA replacement therapy, may represent an effective strategy for the treatment of ER-positive breast cancer patients.     

Spatial heterogeneity and short‐term oxygen dynamics in the rhizosphere of Vallisneria spiralis: Implications for nutrient cycling

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Reparameterization of all-atom dipalmitoylphosphatidylcholine lipid parameters enables simulation of fluid bilayers at zero tension

Molecular dynamics simulations of dipalmitoylphosphatidylcholine (DPPC) lipid bilayers using the CHARMM27 force field in the tensionless isothermal-isobaric (NPT) ensemble give highly ordered, gel-like bilayers with an area per lipid of approximately 48 A(2). To obtain fluid (L(alpha)) phase properties of DPPC bilayers represented by the CHARMM energy function in this ensemble, we reparameterized the atomic partial charges in the lipid headgroup and upper parts of the acyl chains. The new charges were determined from the electron structure using both the Mulliken method and the restricted electrostatic potential fitting method. We tested the derived charges in molecular dynamics simulations of a fully hydrated DPPC bilayer. Only the simulation with the new restricted electrostatic potential charges shows significant improvements compared with simulations using the original CHARMM27 force field resulting in an area per lipid of 60.4 +/- 0.1 A(2). Compared to the 48 A(2), the new value of 60.4 A(2) is in fair agreement with the experimental value of 64 A(2). In addition, the simulated order parameter profile and electron density profile are in satisfactory agreement with experimental data. Thus, the biologically more interesting fluid phase of DPPC bilayers can now be simulated in all-atom simulations in the NPT ensemble by employing our modified CHARMM27 force field.