Soil fungi are pivotal in alpine and arctic ecosystems that are vulnerable to climate changes. Previous studies have shown broad connections between soil fungi in the arctic and alpine regions, but most of these studies are mainly from Europe and North America, with more sporadic studies from East Asia. Currently, little is known about the biogeographic relationships between soil fungi in alpine meadows of southwestern China (AMSC) and other regions of the world. In addition, the regional-scale spatial patterns of fungal communities in the AMSC, as well as their driving factors and ecological processes, are also poorly understood. In this study, we collected roots and surrounding soils of two dominant ectomycorrhizal plants, Bistorta vivipara and B. macrophylla from the AMSC, and performed bioinformatic and statistical analyses based on high-throughput sequencing of ITS2 amplicons. We found that: (1) fungi from the AMSC were closely related with those from boreal forests and tundra, and saprotrophic fungi had higher dispersal potential than ectomycorrhizal fungi; (2) community compositions exhibited clear divergences among geographic regions and between root and soil samples; (3) climate was the predominant factor driving regional-scale spatial patterns but had less explanatory power for saprotrophic and total fungi from roots than those from soils; (4) homogeneous selection and drift were the key ecological processes governing community assembly, but in communities of saprotrophic and total fungi from soil samples, drift contributed less and its role was partially replaced by dispersal limitation. This study highlights the importance of climatic selection and stochastic processes on fungal community assembly in alpine regions, and emphasizes the significance of simultaneously investigating fungi with different trophic modes and from both roots and soils.

Understanding the adaptability of small populations in the face of environmental change is a central problem in evolutionary biology. Solving this problem is challenging because neutral evolutionary processes that operate on historical and contemporary timescales can override the effects of selection in small populations. We assessed the effects of isolation by colonization (IBC), isolation by dispersal limitation (IBDL) as reflected by a pattern of isolation by distance (IBD), and isolation by adaptation (IBA) and the roles of genetic drift and gene flow on patterns of genetic differentiation among 19 cave-dwelling populations of Icelandic Arctic charr (Salvelinus alpinus). We detected evidence of IBC based on the genetic affinity of nearby cave populations and the genetic relationships between the cave populations and the presumed ancestral population in the lake. A pattern of IBD was evident regardless of whether high-level genetic structuring (IBC) was taken into account. Genetic signatures of bottlenecks and lower genetic diversity in smaller populations indicate the effect of drift. Estimates of gene flow and fish movement suggest that gene flow is limited to nearby populations. In contrast, we found little evidence of IBA as patterns of local ecological and phenotypic variation showed little association with genetic differentiation among populations. Thus, patterns of genetic variation in these small populations likely reflect localized gene flow and genetic drift superimposed onto a larger-scale structure that is largely a result of colonization history. Our simultaneous assessment of the effects of neutral and adaptive processes in a tractable and replicated system has yielded novel insights into the evolution of small populations on both historical and contemporary timescales and over a smaller spatial scale than is typically studied.

Representational drift refers to the dynamic nature of neural representations in the brain despite the behavior being seemingly stable. Although drift has been observed in many different brain regions, the mechanisms underlying it are not known. Since intrinsic neural excitability is suggested to play a key role in regulating memory allocation, fluctuations of excitability could bias the reactivation of previously stored memory ensembles and therefore act as a motor for drift. Here, we propose a rate-based plastic recurrent neural network with slow fluctuations of intrinsic excitability. We first show that subsequent reactivations of a neural ensemble can lead to drift of this ensemble. The model predicts that drift is induced by co-activation of previously active neurons along with neurons with high excitability which leads to remodeling of the recurrent weights. Consistent with previous experimental works, the drifting ensemble is informative about its temporal history. Crucially, we show that the gradual nature of the drift is necessary for decoding temporal information from the activity of the ensemble. Finally, we show that the memory is preserved and can be decoded by an output neuron having plastic synapses with the main region.

Background: Automated eye tracking data correction algorithms such as Dynamic-Time Warp always made a trade-off between the ability to handle regressions (jumps back) and distortions (fixation drift). At the same time, eye movement in code reading is characterized by non-linearity and regressions. Objective: In this paper, we present a family of hybrid algorithms that aim to handle both regressions and distortions with high accuracy. Method: Through simulations with synthetic data, we replicate known eye movement phenomena to assess our algorithms against Warp algorithm as a baseline. Furthermore, we utilize two real datasets to evaluate the algorithms in correcting data from reading source code and see if the proposed algorithms generalize to correcting data from reading natural language text. Results: Our results demonstrate that most proposed algorithms match or outperform baseline Warp in correcting both synthetic and real data. Also, we show the prevalence of regressions in reading source code. Conclusion: Our results highlight our hybrid algorithms as an improvement to Dynamic-Time Warp in handling regressions.

Hybrid zones have been viewed as an opportunity to see speciation in action. When hybrid zones are replicated, it is assumed that if the same genetic incompatibilities are maintaining reproductive isolation across all instances of secondary contact, those incompatibilities should be identifiable by consistent patterns in the genome. In contrast, changes in allele frequencies due to genetic drift should be idiosyncratic for each hybrid zone. To test this assumption, we simulated 20 replicates of each of 12 hybrid zone scenarios with varied genetic incompatibilities, rates of migration, selection and different starting population size ratios of parental species. We found remarkable variability in the outcomes of hybridisation in replicate hybrid zones, particularly with Bateson-Dobzhansky-Muller incompatibilities and strong selection. We found substantial differences among replicates in the overall genomic composition of individuals, including admixture proportions, inter-specific ancestry complement and number of ancestry junctions. Additionally, we found substantial variation in genomic clines among replicates at focal loci, regardless of locus-specific selection. We conclude that processes other than selection are responsible for some consistent outcomes of hybridisation, whereas selection on incompatibilities can lead to genomically widespread and highly variable outcomes. We highlight the challenge of mapping between pattern and process in hybrid zones and call attention to how selection against incompatibilities will commonly lead to variable outcomes. We hope that this study informs future research on replicate hybrid zones and encourages further development of statistical techniques, theoretical models and exploration of additional axes of variation to understand reproductive isolation.

BACKGROUND: A major goal in evolutionary biology is to understand the processes underlying phenotypic variation in nature. Commonly, studies have focused on large interconnected populations or populations found along strong environmental gradients. However, studies on small fragmented populations can give strong insight into evolutionary processes in relation to discrete ecological factors. Evolution in small populations is believed to be dominated by stochastic processes, but recent work shows that small populations can also display adaptive phenotypic variation, through for example plasticity and rapid adaptive evolution. Such evolution takes place even though there are strong signs of historical bottlenecks and genetic drift. Here we studied 24 small populations of the freshwater fish Arctic charr (Salvelinus alpinus) found in groundwater filled lava caves. Those populations were found within a few km2-area with no apparent water connections between them. We studied the relative contribution of neutral versus non-neutral evolutionary processes in shaping phenotypic divergence, by contrasting patterns of phenotypic and neutral genetic divergence across populations in relation to environmental measurements. This allowed us to model the proportion of phenotypic variance explained by the environment, taking in to account the observed neutral genetic structure.
RESULTS: These populations originated from the nearby Lake Mývatn, and showed small population sizes with low genetic diversity. Phenotypic variation was mostly correlated with neutral genetic diversity with only a small environmental effect.
CONCLUSIONS: Phenotypic diversity in these cave populations appears to be largely the product of neutral processes, fitting the classical evolutionary expectations. However, the fact that neutral processes did not explain fully the phenotypic patterns suggests that further studies can increase our understanding on how neutral evolutionary processes can interact with other forces of selection at early stages of divergence. The accessibility of these populations has provided the opportunity for long-term monitoring of individual fish, allowing tracking how the environment can influence phenotypic and genetic divergence for shaping and maintaining diversity in small populations. Such studies are important, especially in freshwater, as habitat alteration is commonly breaking populations into smaller units, which may or may not be viable.

In this paper, we study the drift behavior of organic electrochemical transistor (OECT) biosensors in a phosphate-buffered saline (PBS) buffer solution and human serum. Theoretical and experimental methods are illustrated in this paper to understand the origin of the drift phenomenon and the mechanism of ion diffusion in the sensing layer. The drift phenomenon is explained using a first-order kinetic model of ion adsorption into the gate material and shows very good agreement with experimental data on drift in OECTs. We show that the temporal current drift can be largely mitigated using a dual-gate OECT architecture and that dual-gate-based biosensors can increase the accuracy and sensitivity of immuno-biosensors compared to a standard single-gate design. Specific binding can be detected at a relatively low limit of detection, even in human serum.

OBJECTIVE: The drift in radiofrequency (RF) power amplifiers (RFPAs) is assessed and several contributing factors are investigated. Two approaches for prospective correction of drift are proposed and their effectiveness is evaluated.
METHODS: RFPA drift assessment encompasses both intra-pulse and inter-pulse drift analyses. Scan protocols with varying flip angle (FA), RF length, and pulse repetition time (TR) are used to gauge the influence of these parameters on drift. Directional couplers (DICOs) monitor the forward waveforms of the RFPA outputs. DICOs data is stored for evaluation, allowing calculation of correction factors to adjust RFPAs\' transmit voltage. Two correction methods, predictive and run-time, are employed: predictive correction necessitates a calibration scan, while run-time correction calculates factors during the ongoing scan.
RESULTS: RFPA drift is indeed influenced by the RF duty-cycle, and in the cases examined with a maximum duty-cycle of 66%, the potential drift is approximately 41% or 15%, depending on the specific RFPA revision. Notably, in low transmit voltage scenarios, FA has minimal impact on RFPA drift. The application of predictive and run-time drift correction techniques effectively reduces the average drift from 10.0% to less than 1%, resulting in enhanced MR signal stability.
CONCLUSIONS: Utilizing DICO recordings and implementing a feedback mechanism enable the prospective correction of RFPA drift. Having a calibration scan, predictive correction can be utilized with fewer complexity; for enhanced performance, a run-time approach can be employed.

High-density neural devices are now offering the possibility to record from neuronal populations in vivo at unprecedented scale. However, the mechanical drifts often observed in these recordings are currently a major issue for \"spike sorting,\" an essential analysis step to identify the activity of single neurons from extracellular signals. Although several strategies have been proposed to compensate for such drifts, the lack of proper benchmarks makes it hard to assess the quality and effectiveness of motion correction. In this paper, we present a benchmark study to precisely and quantitatively evaluate the performance of several state-of-the-art motion correction algorithms introduced in the literature. Using simulated recordings with induced drifts, we dissect the origins of the errors performed while applying a motion correction algorithm as a preprocessing step in the spike sorting pipeline. We show how important it is to properly estimate the positions of the neurons from extracellular traces in order to correctly estimate the probe motion, compare several interpolation procedures, and highlight what are the current limits for motion correction approaches.

The agrochemical industry has launched several new synthetic auxin herbicides in rice to combat increasing numbers of herbicide resistant weeds to other modes of action. Excessive or inappropriate use of these herbicides has resulted in unintended consequences near the sites of application, such as herbicide drift. This study was conducted to determine the impact of drift of quinclorac and florpyrauxifen-benzyl+penoxsulam (FBP) on the yield and yield components of two sunflower cultivars. In a growth chamber experiment, quinclorac and FBP were applied to 2-4 true leaf stages at rates ranging from 2.93 to 93.75 and from 0.51 to 16.25 g ai ha-1, respectively. Nonlinear regression analyses indicated that the cultivar Bosfora was more sensitive to quinclorac and FBP than the cultivar Tunca. In field experiments, these sunflower cultivars were treated with drift rates of quinclorac (<375 g ai ha-1) and FBP (<65 g ai ha-1) when they were at the 8-10 true leaf stage. Quinclorac and FBP drift rates resulted in up to 52-61% and 85-100% injury and 82-88% and 100% yield loss, respectively. Crop injury and yield data clearly showed that cultivar Bosfora was more sensitive to FBP and quinclorac rates than cultivar Tunca, and both cultivars were more sensitive to FBP than quinclorac. In our work, we also found that plant height reduction caused by quinclorac at early growth stages may be a valuable indicator to evaluate crop injury and yield loss.