Recording fine‐scale movement of ground beetles by two methods: Potentials and methodological pitfalls

Movement trajectories are usually recorded as a sequence of discrete movement events described by two parameters: step length (distance) and turning angle (bearing). One of the most widespread methods to record the geocoordinates of each step is by a GPS device. Such devices have limited suitability for recording fine movements of species with low dispersal ability including flightless carabid beetles at small spatio‐temporal scales. As an alternative, the distance‐bearing approach can avoid the measurement error of GPS units since it uses directly measured distances and compass azimuths. As no quantification of measurement error between distance‐bearing and GPS approaches exists so far, we generated artificial fine‐scale trajectories and in addition radio‐tracked living carabids in a temperate forest and recorded each movement step by both methods. Trajectories obtained from distance‐bearing were compared to those obtained by a GPS device in terms of movement parameters. Consequently, both types of trajectories were segmented by state‐switching modeling into two distinct movement stages typical for carabids: random walk and directed movement. We found that the measurement error of GPS compared to distance‐bearing was 1.878 m (SEM = 0.181 m) for distances and 31.330° (SEM = 2.066°) for bearings. Moreover, these errors increased under dense forest canopy and rainy weather. Distance error did not change with increasing distance recorded by distance‐bearing but bearings were significantly more sensitive to error at short distances. State‐switching models showed only slight, not significant, differences in movement states between the two methods in favor of the random walk in the distance‐bearing approach. However, the shape of the GPS‐measured trajectories considerably differed from those recorded by distance‐bearing caused especially by bearing error at short distances. Our study showed that distance‐bearing could be more appropriate for recording movement steps not only of ground‐dwelling beetles but also other small animals at fine spatio‐temporal scales

The annual cycles of phytoplankton biomass

Terrestrial plants are powerful climate sentinels because their annual cycles of growth, reproduction and senescence are finely tuned to the annual climate cycle having a period of one year. Consistency in the seasonal phasing of terrestrial plant activity provides a relatively low-noise background from which phenological shifts can be detected and attributed to climate change. Here, we ask whether phytoplankton biomass also fluctuates over a consistent annual cycle in lake, estuarine–coastal and ocean ecosystems and whether there is a characteristic phenology of phytoplankton as a consistent phase and amplitude of variability. We compiled 125 time series of phytoplankton biomass (chlorophyll a concentration) from temperate and subtropical zones and used wavelet analysis to extract their dominant periods of variability and the recurrence strength at those periods. Fewer than half (48%) of the series had a dominant 12-month period of variability, commonly expressed as the canonical spring-bloom pattern. About 20 per cent had a dominant six-month period of variability, commonly expressed as the spring and autumn or winter and summer blooms of temperate lakes and oceans. These annual patterns varied in recurrence strength across sites, and did not persist over the full series duration at some sites. About a third of the series had no component of variability at either the six- or 12-month period, reflecting a series of irregular pulses of biomass. These findings show that there is high variability of annual phytoplankton cycles across ecosystems, and that climate-driven annual cycles can be obscured by other drivers of population variability, including human disturbance, aperiodic weather events and strong trophic coupling between phytoplankton and their consumers. Regulation of phytoplankton biomass by multiple processes operating at multiple time scales adds complexity to the challenge of detecting climate-driven trends in aquatic ecosystems where the noise to signal ratio is high

Latitudinal decline in stand biomass and productivity at the elevational treeline in the Ural mountains despite a common thermal growth limit

Aim: To quantify tree biomass and stand productivity of treeline ecotones and identify driving factors. Location: treeline ecotones of seven regions from the South to Polar Urals, spanning a latitudinal gradient of 1,500 km. Taxa: Picea obovata, Betula pubescens, Larix sibirica. Methods: Stand biomass and productivity were estimated across 18 elevational transects from the tree species line to the closed forest line based on allometric measurements of 326 trees (including roots for 53 trees), stand structure assessments and demographic patterns of 20,600 trees. Stand growth data were linked to (a) temperatures monitored in situ for five years in the South and Polar Urals, (b) climate variables extrapolated from nearby climate stations and (c) measures of nutrient availability in soils and tree foliage. Results: treeline position along the latitudinal gradient occurred at a similar mean growing season temperature. Despite the common cold limitation of tree distribution along the Ural mountain range, stand biomass and productivity within the treeline ecotone decreased by a factor of three and five from the South to the Polar Urals, mainly due to a declining stand density. Among climatic variables, growing season length decreased by 20% and winter temperatures declined by 4°C towards the Polar Urals, whereas growing degree days > 5°C remained similar, averaging 554 ± 9°C. Soil development was poorer in the Polar than in the South Urals, and plant-available N and P in the soil were 20 and 30 times lower, respectively, probably due to lower winter temperatures. Main conclusions: Our results suggest that once the thermal limitation for tree growth is relieved, soil fertility—restricted by permafrost and low soil temperatures during winter—plays a key and yet underexplored role for stand productivity in treeline ecotones. The observed latitudinal decline in stand productivity is important for above- and belowground diversity and functioning. © 2020 The Authors. Journal of Biogeography published by John Wiley & Sons Lt

Near streambed flow shapes microbial guilds within and across trophic levels in fluvial biofilms

Flow is an important physical driver of biofilm communities. Here, we tested the effects of the near bed flows in two mountainous stream reaches on the structure of biofilm microbial guilds (autotrophs, heterotrophic bacteria, and heterotrophic protists) within and across trophic levels. Near bed flow velocity and turbulent kinetic energy were important physical drivers for structuring the communities within and across guilds of the multitrophic fluvial biofilms. The effects of flow were nested in a seasonal and spatial (across-streams) context. Changes in physicochemical factors (temperature, light, dissolved carbon, and nutrients) along the reaches were alike in both streams suggesting that environmental boundary conditions at larger temporal scales were responsible for the seasonal differences of biofilm communities, whereas locally microbial diversity was shaped by near bed flow. Typically, the abundance of autotrophs increased with flow, indicating that biofilms shifted toward increasing autotrophy with increasing shear forces. Filamentous autotrophs seemed to provide protected habitats from the shear forces for smaller sized bacteria. Heterotrophic protist abundance decreased with flow leading to decreasing grazer to prey ratio. Bacteria thus benefitted from a reduction in grazing pressure at faster flowing, more turbulent sites. Our results suggest that near bed flow can impact the magnitude and direction of matter fluxes through the microbial food web and possibly affect ecosystem functioning of fluvial biofilms

Long‐Distance Natal Dispersal Is Relatively Frequent and Correlated with Environmental Factors in a Widespread Raptor

Dispersal is a critical process influencing population dynamics and responses to global change. Long‐distance dispersal (LDD) can be especially important for gene flow and adaptability, although little is known about the factors influencing LDD because studying large‐scale movements is challenging and LDD tends to be observed less frequently than shorter‐distance dispersal (SDD). We sought to understand patterns of natal dispersal at a large scale, specifically aiming to understand the relative frequency of LDD compared to SDD and correlates of dispersal distances. We used bird banding and encounter data for American kestrels (Falco sparverius) to investigate the effects of sex, migration strategy, population density, weather, year and agricultural land cover on LDD frequency, LDD distance and SDD distance in North America from 1961 to 2015. Nearly half of all natal dispersal (48.9%) was LDD (classified as \u3e30 km), and the likelihood of LDD was positively associated with the proportion of agricultural land cover around natal sites. Correlates of distance differed between LDD and SDD movements. LDD distance was positively correlated with latitude, a proxy for migration strategy, suggesting that migratory individuals disperse farther than residents. Distance of LDD in males was positively associated with maximum summer temperature. We did not find sex‐bias or an effect of population density in LDD distance or frequency. Within SDD, females tended to disperse farther than males, and distance was positively correlated with density. Sampling affected all responses, likely because local studies more frequently capture SDD within study areas. Our findings that LDD occurs at a relatively high frequency and is related to different proximate factors from SDD, including a lack of sex‐bias in LDD, suggest that LDD may be more common than previously reported, and LDD and SDD may be distinct processes rather than two outcomes originating from a single dispersal distribution. To our knowledge, this is the first evidence that LDD and SDD may be separate processes in an avian species, and suggests that environmental change may have different outcomes on the two processes

{\eta} and {\eta}' mesons from Nf=2+1+1 twisted mass lattice QCD

We determine mass and mixing angles of eta and eta' states using Nf=2+1+1 Wilson twisted mass lattice QCD. We describe how those flavour singlet states need to be treated in this lattice formulation. Results are presented for three values of the lattice spacing, a=0.061 fm, a=0.078 fm and a=0.086 fm, with light quark masses corresponding to values of the charged pion mass in a range of 230 to 500 MeV and fixed bare strange and charm quark mass values. We obtain 557(15)(45) MeV for the eta mass (first error statistical, second systematic) and 44(5) degrees for the mixing angle in the quark flavour basis, corresponding to -10(5) degrees in the octet-singlet basis.Comment: 28 pages, 9 figures, version to appear in JHEP, extended discussion of autocorrelation times and comparison to results available in the literature, added a comment for FS-effects and clarified the description of our blocking procedur

Threshold selection in gene co-expression networks using spectral graph theory techniques

Abstract Background Gene co-expression networks are often constructed by computing some measure of similarity between expression levels of gene transcripts and subsequently applying a high-pass filter to remove all but the most likely biologically-significant relationships. The selection of this expression threshold necessarily has a significant effect on any conclusions derived from the resulting network. Many approaches have been taken to choose an appropriate threshold, among them computing levels of statistical significance, accepting only the top one percent of relationships, and selecting an arbitrary expression cutoff. Results We apply spectral graph theory methods to develop a systematic method for threshold selection. Eigenvalues and eigenvectors are computed for a transformation of the adjacency matrix of the network constructed at various threshold values. From these, we use a basic spectral clustering method to examine the set of gene-gene relationships and select a threshold dependent upon the community structure of the data. This approach is applied to two well-studied microarray data sets from Homo sapiens and Saccharomyces cerevisiae. Conclusion This method presents a systematic, data-based alternative to using more artificial cutoff values and results in a more conservative approach to threshold selection than some other popular techniques such as retaining only statistically-significant relationships or setting a cutoff to include a percentage of the highest correlations

Economic downturn results in tick-borne disease upsurge

<p>Abstract</p> <p>Background</p> <p>The emergence of zoonoses is due both to changes in human activities and to changes in their natural wildlife cycles. One of the most significant vector-borne zoonoses in Europe, tick-borne encephalitis (TBE), doubled in incidence in 1993, largely as a consequence of the socio-economic transition from communism to capitalism and associated environmental changes.</p> <p>Methods</p> <p>To test the effect of the current economic recession, unemployment in 2009 and various socio-economic indices were compared to weather indices (derived from principal component analyses) as predictors for the change in TBE case numbers in 2009 relative to 2004-08, for 14 European countries.</p> <p>Results</p> <p>Greatest increases in TBE incidence occurred in Latvia, Lithuania and Poland (91, 79 and 45%, respectively). The weather was rejected as an explanatory variable. Indicators of high background levels of poverty, e.g. percent of household expenditure on food, were significant predictors. The increase in unemployment in 2009 relative to 2008 together with 'in-work risk of poverty' is the only case in which a multivariate model has a second significant term.</p> <p>Conclusion</p> <p>Background socio-economic conditions determine susceptibility to risk of TBE, while increased unemployment triggered a sudden increase in risk. Mechanisms behind this result may include reduced resistance to infection through stress; reduced uptake of costly vaccination; and more exposure of people to infected ticks in their forest habitat as they make greater use of wild forest foods, especially in those countries, Lithuania and Poland, with major marketing opportunities in such products. Recognition of these risk factors could allow more effective protection through education and a vaccination programme targeted at the economically most vulnerable.</p

Brain mapping in cognitive disorders: a multidisciplinary approach to learning the tools and applications of functional neuroimaging

<p>Abstract</p> <p>Background</p> <p>With rapid advances in functional imaging methods, human studies that feature functional neuroimaging techniques are increasing exponentially and have opened a vast arena of new possibilities for understanding brain function and improving the care of patients with cognitive disorders in the clinical setting. There is a growing need for medical centers to offer clinically relevant functional neuroimaging courses that emphasize the multifaceted and multidisciplinary nature of this field. In this paper, we describe the implementation of a functional neuroimaging course focusing on cognitive disorders that might serve as a model for other medical centers. We identify key components of an active learning course design that impact student learning gains in methods and issues pertaining to functional neuroimaging that deserve consideration when optimizing the medical neuroimaging curriculum.</p> <p>Methods</p> <p>Learning gains associated with the course were assessed using polychoric correlation analysis of responses to the SALG (Student Assessment of Learning Gains) instrument.</p> <p>Results</p> <p>Student gains in the functional neuroimaging of cognition as assessed by the SALG instrument were strongly associated with several aspects of the course design.</p> <p>Conclusion</p> <p>Our implementation of a multidisciplinary and active learning functional neuroimaging course produced positive learning outcomes. Inquiry-based learning activities and an online learning environment contributed positively to reported gains. This functional neuroimaging course design may serve as a useful model for other medical centers.</p