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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.
Groundwater recharge (GWR) is one of the most challenging water fluxes to estimate, as it relies on observed data that are often limited in many developing countries.
This study developed an innovative water budget method using satellite products for estimating the spatially distributed GWR at monthly and annual scales in tropical wet sedimentary regions despite cloudy conditions.
The distinctive features proposed in this study include the capacity to address 1) evapotranspiration estimations in tropical wet regions frequently overlaid by substantial cloud cover; and 2) seasonal root-zone water storage estimations in sedimentary regions prone to monthly variations.
The method also utilises satellite-based information of the precipitation and surface runoff. The GWR was estimated and validated for the hydrologically contrasting years 2016 and 2017 over a tropical wet sedimentary region located in North-eastern Brazil, which has substantial potential for groundwater abstraction.
This study showed that applying a cloud-cleaning procedure based on monthly compositions of biophysical data enables the production of a reasonable proxy for evapotranspiration able to estimate groundwater by the water budget method.
The resulting GWR rates were 219 (2016) and 302 (2017) mm yr(-1), showing good correlations (CC = 0.68 to 0.83) and slight underestimations (PBIAS =-13 to-9%) when compared with the referenced estimates obtained by the water table fluctuation method for 23 monitoring wells. Sensitivity analysis shows that water storage changes account for +19% to-22% of our monthly evaluation.
The satellite-based approach consistently demonstrated that the consideration of cloud-cleaned evapotranspiration and root-zone soil water storage changes are essential for a proper estimation of spatially distributed GWR in tropical wet sedimentary regions because of their weather seasonality and cloudy conditions.
IntroductionTo date, most studies of natural variation and metabolite quantitative trait loci (mQTL) in tomato have focused on fruit metabolism, leaving aside the identification of genomic regions involved in the regulation of leaf metabolism.ObjectiveThis study was conducted to identify leaf mQTL in tomato and to assess the association of leaf metabolites and physiological traits with the metabolite levels from other tissues.MethodsThe analysis of components of leaf metabolism was performed by phenotypying 76 tomato ILs with chromosome segments of the wild species Solanum pennellii in the genetic background of a cultivated tomato (S. lycopersicum) variety M82. The plants were cultivated in two different environments in independent years and samples were harvested from mature leaves of non-flowering plants at the middle of the light period. The non-targeted metabolite profiling was obtained by gas chromatography time-of-flight mass spectrometry (GC-TOF-MS). With the data set obtained in this study and already published metabolomics data from seed and fruit, we performed QTL mapping, heritability and correlation analyses.ResultsChanges in metabolite contents were evident in the ILs that are potentially important with respect to stress responses and plant physiology. By analyzing the obtained data, we identified 42 positive and 76 negative mQTL involved in carbon and nitrogen metabolism.ConclusionsOverall, these findings allowed the identification of S. lycopersicum genome regions involved in the regulation of leaf primary carbon and nitrogen metabolism, as well as the association of leaf metabolites with metabolites from seeds and fruits.
We analytically describe the complex scenario of homoclinic bifurcations in the Chua’s circuit. We obtain a general scaling law that gives the ratio between bifurcation parameters of different nearby homoclinic orbits. As an application of this theoretical approach, we estimate the number of higher order subsidiary homoclinic orbits that appear between two consecutive lower order subsidiary orbits. Our analytical finds might be valid for a large class of dynamical systems and are numerically confirmed in the parameter space of the Chua’s circuit.
Shilnikov homoclinic orbits are trajectories that depart from a fixed saddle-focus point, with specific eigenvalues, and return to it after an infinite amount of time (that is also true to time reversal evolution). That results in an orbit that is unstable and has an infinite period. These two main characteristics contribute in the hardness for its observation in a dynamical system as well as in nature. However, its presence reveals fundamental characteristics of the system involved, as the existence of unstable periodic orbits embedded in a chaotic set. Once the unstable periodic orbits give invariants quantities of this set,1 the Shilnikov homoclinic orbits are also related to the characteristics of the chaotic set. Their connection with the fundamental dynamical properties is verified in a wide variety of systems. A series of numerical and experimental investigations reveal how Shilnikov homoclinic orbits, in the vicinity of a chaotic attractor, determine its dynamical and topological properties.4 Thus, the Shilnikov orbits are related to the returning time of the trajectory of a CO2 laser,5 also to the topology of a glow-discharge system.6 Moreover, some class of spiking neurons are modeled by chaos governed by such orbits,7,8 and their presence are connected to the intermittence present in rabbit arteries.9 These orbits are shown to be behind the mechanism of noise-induced phenomena,10 and they are also responsible for the dynamics of an electrochemical oscillator.11 In this work, we contribute to the understanding of how Shilnikov homoclinic orbits appear on the parameter space of systems as the ones above mentioned, by showing that these orbits are not only distributed following an universal rule but also exist for large parameter variations. We then confirm our previsions in the Chua’s circuit system
A novel common variant in DCST2 is associated with length in early life and height in adulthood
(2015)
Common genetic variants have been identified for adult height, but not much is known about the genetics of skeletal growth in early life. To identify common genetic variants that influence fetal skeletal growth, we meta-analyzed 22 genome-wide association studies (Stage 1; N = 28 459). We identified seven independent top single nucleotide polymorphisms (SNPs) (P < 1 x 10(-6)) for birth length, of which three were novel and four were in or near loci known to be associated with adult height (LCORL, PTCH1, GPR126 and HMGA2). The three novel SNPs were followed-up in nine replication studies (Stage 2; N = 11 995), with rs905938 in DC-STAMP domain containing 2 (DCST2) genome-wide significantly associated with birth length in a joint analysis (Stages 1 + 2; beta = 0.046, SE = 0.008, P = 2.46 x 10(-8), explained variance = 0.05%). Rs905938 was also associated with infant length (N = 28 228; P = 5.54 x 10(-4)) and adult height (N = 127 513; P = 1.45 x 10(-5)). DCST2 is a DC-STAMP-like protein family member and DC-STAMP is an osteoclast cell-fusion regulator. Polygenic scores based on 180 SNPs previously associated with human adult stature explained 0.13% of variance in birth length. The same SNPs explained 2.95% of the variance of infant length. Of the 180 known adult height loci, 11 were genome-wide significantly associated with infant length (SF3B4, LCORL, SPAG17, C6orf173, PTCH1, GDF5, ZNFX1, HHIP, ACAN, HLA locus and HMGA2). This study highlights that common variation in DCST2 influences variation in early growth and adult height.
Pitch Angle Scattering of Sub-MeV Relativistic Electrons by Electromagnetic Ion Cyclotron Waves
(2019)
Electromagnetic ion cyclotron (EMIC) waves have long been considered to be a significant loss mechanism for relativistic electrons. This has most often been attributed to resonant interactions with the highest amplitude waves. But recent observations have suggested that the dominant energy of electrons precipitated to the atmosphere may often be relatively low, less than 1 MeV, whereas the minimum resonant energy of the highest amplitude waves is often greater than 2 MeV. Here we use relativistic electron test particle simulations in the wavefields of a hybrid code simulation of EMIC waves in dipole geometry in order to show that significant pitch angle scattering can occur due to interaction with low-amplitude short-wavelength EMIC waves. In the case we examined, these waves are in the H band (at frequencies above the He+ gyrofrequency), even though the highest amplitude waves were in the He band frequency range (below the He+ gyrofrequency). We also present wave power distributions for 29 EMIC simulations in straight magnetic field line geometry that show that the high wave number portion of the spectrum is in every case mostly due to the H band waves. Though He band waves are often associated with relativistic electron precipitation, it is possible that the He band waves do not directly scatter the sub-megaelectron volts (sub-MeV) electrons, but that the presence of He band waves is associated with high plasma density which lowers the minimum resonant energy so that these electrons can more easily resonate with the H band waves.
Citizen science projects have a long history in ecological studies. The research usefulness of such projects is dependent on applying simple and standardized methods. Here, we conducted a citizen science project that involved more than 3500 Swedish high school students to examine the temperature difference between surface water and the overlying air (T-w-T-a) as a proxy for sensible heat flux (Q(H)). If Q(H) is directed upward, corresponding to positive T-w-T-a, it can enhance CO2 and CH4 emissions from inland waters, thereby contributing to increased greenhouse gas concentrations in the atmosphere. The students found mostly negative T-w-T-a across small ponds, lakes, streams/rivers and the sea shore (i.e. downward Q(H)), with T-w-T-a becoming increasingly negative with increasing T-a. Further examination of T-w-T-a using high-frequency temperature data from inland waters across the globe confirmed that T-w-T-a is linearly related to T-a. Using the longest available high-frequency temperature time series from Lake Erken, Sweden, we found a rapid increase in the occasions of negative T-w-T-a with increasing annual mean T-a since 1989. From these results, we can expect that ongoing and projected global warming will result in increasingly negative T-w-T-a, thereby reducing CO2 and CH4 transfer velocities from inland waters into the atmosphere.