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Right on track?
(2019)
Satellite telemetry is an increasingly utilized technology in wildlife research, and current devices can track individual animal movements at unprecedented spatial and temporal resolutions. However, as we enter the golden age of satellite telemetry, we need an in-depth understanding of the main technological, species-specific and environmental factors that determine the success and failure of satellite tracking devices across species and habitats. Here, we assess the relative influence of such factors on the ability of satellite telemetry units to provide the expected amount and quality of data by analyzing data from over 3,000 devices deployed on 62 terrestrial species in 167 projects worldwide. We evaluate the success rate in obtaining GPS fixes as well as in transferring these fixes to the user and we evaluate failure rates. Average fix success and data transfer rates were high and were generally better predicted by species and unit characteristics, while environmental characteristics influenced the variability of performance. However, 48% of the unit deployments ended prematurely, half of them due to technical failure. Nonetheless, this study shows that the performance of satellite telemetry applications has shown improvements over time, and based on our findings, we provide further recommendations for both users and manufacturers.
Moving in the Anthropocene
(2018)
Animal movement is fundamental for ecosystem functioning and species survival, yet the effects of the anthropogenic footprint on animal movements have not been estimated across species. Using a unique GPS-tracking database of 803 individuals across 57 species, we found that movements of mammals in areas with a comparatively high human footprint were on average one-half to one-third the extent of their movements in areas with a low human footprint. We attribute this reduction to behavioral changes of individual animals and to the exclusion of species with long-range movements from areas with higher human impact. Global loss of vagility alters a key ecological trait of animals that affects not only population persistence but also ecosystem processes such as predator-prey interactions, nutrient cycling, and disease transmission.
Although temporal heterogeneity is a well-accepted driver of biodiversity, effects of interannual variation in land-use intensity (LUI) have not been addressed yet. Additionally, responses to land use can differ greatly among different organisms; therefore, overall effects of land-use on total local biodiversity are hardly known. To test for effects of LUI (quantified as the combined intensity of fertilization, grazing, and mowing) and interannual variation in LUI (SD in LUI across time), we introduce a unique measure of whole-ecosystem biodiversity, multidiversity. This synthesizes individual diversity measures across up to 49 taxonomic groups of plants, animals, fungi, and bacteria from 150 grasslands. Multidiversity declined with increasing LUI among grasslands, particularly for rarer species and aboveground organisms, whereas common species and belowground groups were less sensitive. However, a high level of interannual variation in LUI increased overall multidiversity at low LUI and was even more beneficial for rarer species because it slowed the rate at which the multidiversity of rare species declined with increasing LUI. In more intensively managed grasslands, the diversity of rarer species was, on average, 18% of the maximum diversity across all grasslands when LUI was static over time but increased to 31% of the maximum when LUI changed maximally over time. In addition to decreasing overall LUI, we suggest varying LUI across years as a complementary strategy to promote biodiversity conservation.
Improved measurements of the photospheric and chromospheric three-dimensional magnetic and flow fields are crucial for a precise determination of the origin and evolution of active regions. We present an illustrative sample of multi-instrument data acquired during a two-week coordinated observing campaign in August 2015 involving, among others, the GREGOR solar telescope (imaging and near-infrared spectroscopy) and the space missions Solar Dynamics Observatory (SDO) and Interface Region Imaging Spectrograph (IRIS). The observations focused on the trailing part of active region NOAA 12396 with complex polarity inversion lines and strong intrusions of opposite polarity flux. The GREGOR Infrared Spectrograph (GRIS) provided Stokes IQUV spectral profiles in the photospheric Si i.1082.7 nm line, the chromospheric He I lambda 1083.0 nm triplet, and the photospheric Ca I lambda 1083.9 nm line. Carefully calibrated GRIS scans of the active region provided maps of Doppler velocity and magnetic field at different atmospheric heights. We compare quick-look maps with those obtained with the " Stokes Inversions based on Response functions" (SIR) code, which furnishes deeper insight into the magnetic properties of the region. We find supporting evidence that newly emerging flux and intruding opposite polarity flux are hampering the formation of penumbrae, i.e., a penumbra fully surrounding a sunspot is only expected after cessation of flux emergence in proximity to the sunspots. (C) 2016 WILEY-VCH Verlag GmbH& Co.KGaA, Weinheim
The new generation of solar instruments provides better spectral, spatial, and temporal resolution for a better understanding of the physical processes that take place on the Sun. Multiple-component profiles are more commonly observed with these instruments. Particularly, the He i 10830 triplet presents such peculiar spectral profiles, which give information on the velocity and magnetic fine structure of the upper chromosphere. The purpose of this investigation is to describe a technique to efficiently fit the two blended components of the He i 10830 triplet, which are commonly observed when two atmospheric components are located within the same resolution element. The observations used in this study were taken on 2015 April 17 with the very fast spectroscopic mode of the GREGOR Infrared Spectrograph (GRIS) attached to the 1.5-m GREGOR solar telescope, located at the Observatorio del Teide, Tenerife, Spain. We apply a double-Lorentzian fitting technique using Levenberg-Marquardt least-squares minimization. This technique is very simple and much faster than inversion codes. Line-of-sight Doppler velocities can be inferred for a whole map of pixels within just a few minutes. Our results show sub-and supersonic downflow velocities of up to 32 km s(-1) for the fast component in the vicinity of footpoints of filamentary structures. The slow component presents velocities close to rest. (C) 2016 WILEY-VCH Verlag GmbH& Co. KGaA, Weinheim
Home range estimation is routine practice in ecological research. While advances in animal tracking technology have increased our capacity to collect data to support home range analysis, these same advances have also resulted in increasingly autocorrelated data. Consequently, the question of which home range estimator to use on modern, highly autocorrelated tracking data remains open. This question is particularly relevant given that most estimators assume independently sampled data. Here, we provide a comprehensive evaluation of the effects of autocorrelation on home range estimation. We base our study on an extensive data set of GPS locations from 369 individuals representing 27 species distributed across five continents. We first assemble a broad array of home range estimators, including Kernel Density Estimation (KDE) with four bandwidth optimizers (Gaussian reference function, autocorrelated‐Gaussian reference function [AKDE], Silverman's rule of thumb, and least squares cross‐validation), Minimum Convex Polygon, and Local Convex Hull methods. Notably, all of these estimators except AKDE assume independent and identically distributed (IID) data. We then employ half‐sample cross‐validation to objectively quantify estimator performance, and the recently introduced effective sample size for home range area estimation ( N̂ area
) to quantify the information content of each data set. We found that AKDE 95% area estimates were larger than conventional IID‐based estimates by a mean factor of 2. The median number of cross‐validated locations included in the hold‐out sets by AKDE 95% (or 50%) estimates was 95.3% (or 50.1%), confirming the larger AKDE ranges were appropriately selective at the specified quantile. Conversely, conventional estimates exhibited negative bias that increased with decreasing N̂ area. To contextualize our empirical results, we performed a detailed simulation study to tease apart how sampling frequency, sampling duration, and the focal animal's movement conspire to affect range estimates. Paralleling our empirical results, the simulation study demonstrated that AKDE was generally more accurate than conventional methods, particularly for small N̂ area. While 72% of the 369 empirical data sets had >1,000 total observations, only 4% had an N̂ area >1,000, where 30% had an N̂ area <30. In this frequently encountered scenario of small N̂ area, AKDE was the only estimator capable of producing an accurate home range estimate on autocorrelated data.
Intransitive competition is widespread in plant communities and maintains their species richness
(2015)
Intransitive competition networks, those in which there is no single best competitor, may ensure species coexistence. However, their frequency and importance in maintaining diversity in real-world ecosystems remain unclear. We used two large data sets from drylands and agricultural grasslands to assess: (1) the generality of intransitive competition, (2) intransitivity-richness relationships and (3) effects of two major drivers of biodiversity loss (aridity and land-use intensification) on intransitivity and species richness. Intransitive competition occurred in >65% of sites and was associated with higher species richness. Intransitivity increased with aridity, partly buffering its negative effects on diversity, but was decreased by intensive land use, enhancing its negative effects on diversity. These contrasting responses likely arise because intransitivity is promoted by temporal heterogeneity, which is enhanced by aridity but may decline with land-use intensity. We show that intransitivity is widespread in nature and increases diversity, but it can be lost with environmental homogenisation.
Apraxia typically results from left-hemispheric (LH), but also from right-hemispheric (RH) stroke, and often impairs gesture imitation. Especially in LH stroke, it is important to differentiate apraxia-induced gesture imitation deficits from those due to co-morbid aphasia and associated semantic deficits, possibly influencing the imitation of meaningful (MF) gestures. To explore this issue, we first investigated if the 10 supposedly meaningless (ML) gestures of a widely used finger imitation test really carry no meaning, or if the test also contains MF gestures, by asking healthy subjects (n=45) to classify these gestures as MF or ML. Most healthy subjects (98%) classified three of the 10 gestures as clearly MF. Only two gestures were considered predominantly ML. We next assessed how imitation in stroke patients (255 LH, 113 RH stroke) is influenced by gesture meaning and how aphasia influences imitation of LH stroke patients (n=208). All patients and especially patients with imitation deficits (17% of LH, 27% of RH stroke patients) imitated MF gestures significantly better than ML gestures. Importantly, meaningfulness-scores of all 10 gestures significantly predicted imitation scores of patients with imitation deficits. Furthermore, especially in LH stroke patients with imitation deficits, the severity of aphasia significantly influenced the imitation of MF, but not ML gestures. Our findings in a large patient cohort support current cognitive models of imitation and strongly suggest that ML gestures are particularly sensitive to detect imitation deficits while minimising confounding effects of aphasia which affect the imitation of MF gestures in LH stroke patients. (C) 2015 Elsevier Ltd. All rights reserved.
Understanding the association between autonomic nervous system [ANS] function and brain morphology across the lifespan provides important insights into neurovisceral mechanisms underlying health and disease. Resting-state ANS activity, indexed by measures of heart rate [HR] and its variability [HRV] has been associated with brain morphology, particularly cortical thickness [CT]. While findings have been mixed regarding the anatomical distribution and direction of the associations, these inconsistencies may be due to sex and age differences in HR/HRV and CT. Previous studies have been limited by small sample sizes, which impede the assessment of sex differences and aging effects on the association between ANS function and CT. To overcome these limitations, 20 groups worldwide contributed data collected under similar protocols of CT assessment and HR/HRV recording to be pooled in a mega-analysis (N = 1,218 (50.5% female), mean age 36.7 years (range: 12-87)). Findings suggest a decline in HRV as well as CT with increasing age. CT, particularly in the orbitofrontal cortex, explained additional variance in HRV, beyond the effects of aging. This pattern of results may suggest that the decline in HRV with increasing age is related to a decline in orbitofrontal CT. These effects were independent of sex and specific to HRV; with no significant association between CT and HR. Greater CT across the adult lifespan may be vital for the maintenance of healthy cardiac regulation via the ANS-or greater cardiac vagal activity as indirectly reflected in HRV may slow brain atrophy. Findings reveal an important association between CT and cardiac parasympathetic activity with implications for healthy aging and longevity that should be studied further in longitudinal research.
We studied the effect of three major forest management types (unmanaged beech, selection beech, and age class forests) and stand variables (SMId, soil pH, proportion of conifers, litter cover, deadwood cover, rock cover and cumulative cover of woody trees and shrubs) on bryophyte species richness in 1050 forest plots in three regions in Germany. In addition, we analysed the species richness of four ecological guilds of bryophytes according to their colonized substrates (deadwood, rock, soil, bark) and the number of woodland indicator bryophyte species. Beech selection forests turned out to be the most species rich management type, whereas unmanaged beech forests revealed even lower species numbers than age-class forests. Increasing conifer proportion increased bryophyte species richness but not the number of woodland indicator bryophyte species. The richness of the four ecological guilds mainly responded to the abundance of their respective substrate. We conclude that the permanent availability of suitable substrates is most important for bryophyte species richness in forests, which is not stringently linked to management type. Therefore, managed age-class forests and selection forests may even exceed unmanaged forests in bryophyte species richness due to higher substrate supply and therefore represent important habitats for bryophytes. Typical woodland indicator bryophytes and their species richness were negatively affected by SMId (management intensity) and therefore better indicate forest integrity than the species richness of all bryophytes. Nature conservation efforts should focus on the reduction of management intensity. Moreover, maintaining and increasing a variability of substrates and habitats, such as coarse woody debris, increasing structural heterogeneity by retaining patches with groups of old, mature to over-mature trees in managed forests, maintaining forest climate conditions by silvicultural methods that assure stand continuity, e.g. by selection cutting rather than clear cutting and shelterwood logging might promote bryophyte diversity and in particular the one of woodland indicator bryophytes.