A Spatial Framework for Understanding Population Structure and Admixture

Geographic patterns of genetic variation within modern populations, produced by complex histories of migration, can be difficult to infer and visually summarize. A general consequence of geographically limited dispersal is that samples from nearby locations tend to be more closely related than samples from distant locations, and so genetic covariance often recapitulates geographic proximity. We use genome-wide polymorphism data to build “geogenetic maps,” which, when applied to stationary populations, produces a map of the geographic positions of the populations, but with distances distorted to reflect historical rates of gene flow. In the underlying model, allele frequency covariance is a decreasing function of geogenetic distance, and nonlocal gene flow such as admixture can be identified as anomalously strong covariance over long distances. This admixture is explicitly co-estimated and depicted as arrows, from the source of admixture to the recipient, on the geogenetic map. We demonstrate the utility of this method on a circum-Tibetan sampling of the greenish warbler (Phylloscopus trochiloides), in which we find evidence for gene flow between the adjacent, terminal populations of the ring species. We also analyze a global sampling of human populations, for which we largely recover the geography of the sampling, with support for significant histories of admixture in many samples. This new tool for understanding and visualizing patterns of population structure is implemented in a Bayesian framework in the program SpaceMix.     

Interactions Among Fuel Management,Species Composition,Bark Beetles,and Climate Change and the Potential Effects on Forests of the Lake Tahoe Basin

Climate-driven increases in wildfires, drought conditions, and insect outbreaks are critical threats to forest carbon stores. In particular, bark beetles are important disturbance agents although their long-term interactions with future climate change are poorly understood. Droughts and the associated moisture deficit contribute to the onset of bark beetle outbreaks although outbreak extent and severity is dependent upon the density of host trees, wildfire, and forest management. Our objective was to estimate the effects of climate change and bark beetle outbreaks on ecosystem carbon dynamics over the next century in a western US forest. Specifically, we hypothesized that (a) bark beetle outbreaks under climate change would reduce net ecosystem carbon balance (NECB) and increase uncertainty and (b) these effects could be ameliorated by fuels management. We also examined the specific tree species dynamics—competition and release—that determined NECB response to bark beetle outbreaks. Our study area was the Lake Tahoe Basin (LTB), CA and NV, USA, an area of diverse forest types encompassing steep elevation and climatic gradients and representative of mixed-conifer forests throughout the western United States. We simulated climate change, bark beetles, wildfire, and fuels management using a landscape-scale stochastic model of disturbance and succession. We simulated the period 2010–2100 using downscaled climate projections. Recurring droughts generated conditions conducive to large-scale outbreaks; the resulting large and sustained outbreaks significantly increased the probability of LTB forests becoming C sources over decadal time scales, with slower-than-anticipated landscape-scale recovery. Tree species composition was substantially altered with a reduction in functional redundancy and productivity. Results indicate heightened uncertainty due to the synergistic influences of climate change and interacting disturbances. Our results further indicate that current fuel management practices will not be effective at reducing landscape-scale outbreak mortality. Our results provide critical insights into the interaction of drivers (bark beetles, wildfire, fuel management) that increase the risk of C loss and shifting community composition if bark beetle outbreaks become more frequent.     

Decomposition Patterns of Foliar Litter and Deadwood in Managed and Unmanaged Stands: A 13-Year Experiment in Boreal Mixedwoods

Litter decomposition is a major driver of carbon (C) and nitrogen (N) cycles in forest ecosystems and has major implications for C sequestration and nutrient availability. However, empirical information regarding long-term decomposition rates of foliage and wood remains rare. In this study, we assessed long-term C and N dynamics (12–13 years) during decomposition of foliage and wood for three boreal tree species, under a range of harvesting intensities and slash treatments. We used model selection based on the second-order Akaike’s Information Criterion to determine which decomposition model had the most support. The double-exponential model provided a good fit to C mass loss for foliage of trembling aspen, white spruce, and balsam fir, as well as aspen wood. These litters underwent a rapid initial phase of leaching and mineralisation, followed by a slow decomposition. In contrast, for spruce and fir wood, the single-exponential model had the most support. The long-term average decay rate of wood was faster than that of foliage for aspen, but not of conifers. However, we found no evidence that fir and spruce wood decomposed at slower rates than the recalcitrant fraction of their foliage. The critical C:N ratios, at which net N mineralisation began, were higher for wood than for foliage. Long-term decay rates following clear-cutting were either similar or faster than those observed in control stands, depending on litter material, tree species, and slash treatment. The critical C:N ratios were reached later and decreased for all conifer litters following stem-only clear-cutting, indicating increased N retention in harvested sites with high slash loads. Partial harvesting had weak effects on C and N dynamics of decaying litters. A comprehensive understanding of the long-term patterns and controls of C and N dynamics following forest disturbance would improve our ability to forecast the implications of forest harvesting for C sequestration and nutrient availability.     

Site,trigger, quenching mechanism and recovery of non-photochemical quenching in cyanobacteria: recent updates

Femtosecond transient absorption was used to study excitation decay in monomeric and trimeric cyanobacterial Photosystem I (PSI) being prepared in three states: (1) in aqueous solution, (2) deposited and dried on glass surface (either conducting or non-conducting), and (3) deposited on glass (conducting) surface but being in contact with aqueous solvent. The main goal of this contribution was to determine the reason of the acceleration of the excitation decay in dried PSI deposited on the conducting surface relative to PSI in solution observed previously using time-resolved fluorescence (Szewczyk et al., Photysnth Res 132(2):111–126, 2017). We formulated two alternative working hypotheses: (1) the acceleration results from electron injection from PSI to the conducting surface; (2) the acceleration is caused by dehydration and/or crowding of PSI proteins deposited on the glass substrate. Excitation dynamics of PSI in all three types of samples can be described by three main components of subpicosecond, 3–5, and 20–26 ps lifetimes of different relative contributions in solution than in PSI-substrate systems. The presence of similar kinetic components for all the samples indicates intactness of PSI proteins after their deposition onto the substrates. The kinetic traces for all systems with PSI deposited on substrates are almost identical and they decay significantly faster than the kinetic traces of PSI in solution. We conclude that the accelerated excitation decay in PSI-substrate systems is caused mostly by dense packing of proteins.     

Upf proteins: highly conserved factors involved in nonsense mRNA mediated decay

Over 10% of genetic diseases are caused by mutations that introduce a premature termination codon in protein-coding mRNA. Nonsense-mediated mRNA decay (NMD) is an essential cellular pathway that degrades these mRNAs to prevent the accumulation of harmful partial protein products. NMD machinery is also increasingly appreciated to play a role in other essential cellular functions, including telomere homeostasis and the regulation of normal mRNA turnover, and is misregulated in numerous cancers. Hence, understanding and designing therapeutics targeting NMD is an important goal in biomedical science. The central regulator of NMD, the Upf1 protein, interacts with translation termination factors and contextual factors to initiate NMD specifically on mRNAs containing PTCs. The molecular details of how these contextual factors affect Upf1 function remain poorly understood. Here, we review plausible models for the NMD pathway and the evidence for the variety of roles NMD machinery may play in different cellular processes.