Selection Function Research Articles

Platinum‐Catalyzed Regio‐ and Enantioselective Diboration of Unactivated Alkenes with (pin)B−B(dan)

AbstractAsymmetric diboration of terminal alkenes is well established, and subsequent selective functionalization of the less hindered primary boronic ester is commonly achieved. Conversely, selective functionalization of the sterically less accessible secondary boronic ester remains challenging. An alternative way to control chemoselective functionalization of bis(boron) compounds is by engendering different Lewis acidity to the two boryl moieties, since reactivity would then be dictated by Lewis acidity instead of sterics. We report herein the regio‐ and enantioselective Pt‐catalyzed diboration of unactivated alkenes with (pin)B−B(dan). A broad range of terminal and cyclic alkenes undergo diboration to furnish the differentiable 1,2‐bis(boron) compounds with high levels of regio‐ and enantiocontrol, giving access to a wide variety of novel building blocks from a common intermediate. The reaction places the less Lewis acidic B(dan) group at the less hindered position and the resulting 1,2‐bisboryl alkanes undergo selective transformations of the B(pin) group located at the more hindered position. The regioselectivity of the diboration has been studied by DFT calculations and is believed to originate from the trans influence, which lowers the activation barrier for formation of the regioisomer that places the weaker electron donor [B(pin) vs B(dan)] opposite the strong electron donor (alkyl group) in the platinum complex.

A generative model for Gaia astrometric orbit catalogs: selection functions for binary stars, giant planets, and compact object companions

Astrometry from {} DR3 has produced a sample of $$170,000 Keplerian orbital solutions, with many more anticipated in the next few years. These data have enormous potential to constrain the population of binary stars, giant planets, and compact objects in the Solar neighborhood. But in order to use the published orbit catalogs for statistical inference, it is necessary to understand their selection function: what is the probability that a binary with a given set of properties ends up in a catalog? We show that such a selection function for the {} DR3 astrometric binary catalog can be forward-modeled from the {} scanning law, including individual 1D astrometric measurements, the fitting of a cascade of astrometric models, and quality cuts applied in post-processing. We populate a synthetic Milky Way model with binary stars and generate a mock catalog of astrometric orbits. The mock catalog is quite similar to the DR3 astrometric binary sample, suggesting that our selection function is a sensible approximation of reality. Our fitting also produces a sample of spurious astrometric orbits similar to those found in DR3; these are mainly the result of scan angle-dependent astrometric biases in marginally resolved wide binaries. We show that {} sensitivity to astrometric binaries falls off rapidly at high eccentricities, but only weakly at high inclinations. We predict that DR4 will yield ∼1 million astrometric orbits, mostly for bright ( G≲15) systems with long periods ( d). We provide code to simulate and fit realistic {} epoch astrometry for any data release and determine whether any hypothetical binary would receive a cataloged orbital solution.

Pd-Catalyzed Selective Defluoroalkylation of Trifluoromethylarenes

The selective functionalization of C–F bonds in trifluoromethylated arenes (ArCF3) is essential due to the extensive use of fluorinated compounds in pharmaceuticals, agrochemicals, and materials science, alongside emerging regulatory restrictions on trifluoromethyl groups. Here, we report a hybrid palladium-catalyzed strategy for the selective defluorination and functionalization of ArCF3, featuring intermolecular carboamination of linear conjugated dienes and defluorinative cross-coupling with unactivated alkenes. This methodology enables the 1,4-addition of dienes with exclusive E-selectivity and the defluoroalkylation of trifluoroarenes, providing an efficient route to difluoromethylated compounds and addressing key challenges in synthetic fluorine chemistry.

Selective Photocatalytic C-H Oxidation of 5-Methylcytosine in DNA.

Selective C-H activation on complex biological macromolecules is a key goal in the field of organic chemistry. It requires thermodynamically challenging chemical transformations to be delivered under mild, aqueous conditions. 5-Methylcytosine (5mC) is a fundamentally important epigenetic modification in DNA that has major implications for biology and has emerged as a vital biomarker. Selective functionalisation of 5mC would enable new chemical approaches to tag, detect and map DNA methylation to enhance the study and exploitation of this epigenetic feature. We demonstrate the first example of direct and selective chemical oxidation of 5mC to 5-formylcytosine (5fC) in DNA, employing a photocatalytic system. This transformation was used to selectively tag 5mC. We also provide proof-of-concept for deploying this chemistry for single-base resolution sequencing of 5mC and genetic bases adenine (A), cytosine (C), guanine (G), thymine (T) in DNA on a next-generation sequencing system. This work exemplifies how photocatalysis has the potential to transform the analysis of DNA.

Palladium-Catalyzed Double ipso-Defluoroetherification of Allylic gem-Difluorides with Phenols or Alcohols.

Significant progress has been made in the synthesis of diverse ketals through a palladium-catalyzed reaction involving allylic gem-difluorides and various phenols or alcohols. This methodology facilitates double ipso-defluoroetherification of allylic gem-difluorides, resulting in high product yields with excellent regioselectivity. The reactions were conducted under mild conditions and exhibited outstanding tolerance to a wide range of functional groups. Notably, this approach overcomes the traditional limitation of palladium-catalyzed processes, where nucleophiles typically target the common C-1 position of allylic gem-difluorides, enabling selective functionalization at the rare C-3 position instead.

Joint inference for telemetry and spatial survey data.

Data integration, the joint statistical analysis of data from different observation platforms, is pivotal for data-hungry disciplines such as spatial ecology. Pooled data types obtained from the same underlying process, analyzed jointly, can improve both precision and accuracy in models of species distributions and species-habitat associations. However, the integration of telemetry and spatial survey data has proved elusive because of the fundamentally different analytical approaches required by these two data types. Here, "spatial survey" denotes a survey that records spatial locations and has no temporal structure, for example, line or point transects but not capture-recapture or telemetry. Step selection functions (SSFs-the canonical framework for telemetry) and habitat selection functions (HSFs-the default approach to spatial surveys) differ in not only their specifications but also their results. By imposing the constraint that microscopic mechanisms (animal movement) must correctly scale up to macroscopic emergence (population distributions), a relationship can be written between SSFs and HSFs, leading to a joint likelihood using both datasets. We implement this approach using maximum likelihood, explore its estimation precision by systematic simulation, and seek to derive broad guidelines for effort allocation in the field. We find that complementarities in spatial coverage and resolution between telemetry and survey data often lead to marked inferential improvements in joint analyses over those using either data type alone. The optimal allocation of effort between the two methods (or the choice between them, if only one can be selected) depends on the overall effort expended and the pattern of environmental heterogeneity. Examining inferential performance over a broad range of scenarios for the relative cost between the two methods, we find that integrated analysis usually offers higher precision. Our methodological work shows how to integrate the analysis of telemetry and spatial survey data under a novel joint likelihood function, using traditional computational methods. Our simulation experiments suggest that even when the relative costs of the two methods favor the deployment of one field approach over another, their joint use is broadly preferable. Therefore, joint analysis of the two key methods used in spatial ecology is not only possible but also computationally efficient and statistically more powerful.

Chemoselective modification of chitosan with arginine and hydroxyproline: Development of antibacterial composite films for wound healing applications

This study explored the enhancement of chitosan for wound dressing applications through selective functionalization with arginine and hydroxyproline amino acids, combined with polyvinyl pyrrolidone (PVP) and polyvinyl alcohol (PVA) in composite films. The research employed chemoselective amino acid grafting followed by solution casting to fabricate the composite materials. Fourier transform infrared (FTIR) analysis verified successful chitosan modification through the presence of a carbamate bond at 1719 cm−1 and an amide bond shift from 1660 to 1680 cm−1, with nuclear magnetic resonance (NMR) analysis providing additional confirmation. The composite films demonstrated exceptional properties, achieving maximum tensile strength of approximately 55 MPa and swelling ratio of about 400 %. Statistical analysis revealed significant variations in mechanical and swelling properties across formulations (p < 0.05), with analysis of variance (ANOVA) showing a between-group sum of squares of 122,980.519 for tensile strength and 352,306.333 for swelling. Duncan's multiple range test identified distinct groupings for tensile strength (5.67–119.67 MPa) and swelling ratios (320.33–565.33 %), demonstrating the impact of composition on material properties. Thermal stability analysis (25–600 °C) revealed a multi-step degradation process, confirming successful modification and composite formation. The amino acid-modified chitosan composites showed remarkable antibacterial enhancement, exhibiting 60 % greater activity against both Gram-positive and Gram-negative bacteria compared to unmodified chitosan. These findings demonstrate the potential of selectively functionalized chitosan composite films for advanced wound dressing applications, combining enhanced antibacterial efficacy with robust mechanical and thermal properties. Future research directions include formulation optimization and in vivo validation of clinical efficacy.

Multisource Data-Driven Carbon Price Composite Forecasting Model: Based on Feature Selection and Multiscale Prediction Strategy

Accurate prediction of carbon trading prices is crucial for guiding investors to make informed decisions and assisting governments in formulating scientific carbon trading policies. This paper introduces a multisource data-driven carbon price composite forecasting model, aimed at enhancing prediction accuracy through advanced data processing and analysis methods. The model initially employs a secondary decomposition strategy, including Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and Variational Mode Decomposition (VMD) methods, to decompose the original data series into three sub-sequences of different frequencies. Subsequently, it utilizes the Partial Autocorrelation Function (PACF) and Random Forest algorithm for feature selection to determine the input variables for different frequency sequences and conducts in-depth analysis and selection of influencing factors, including unstructured data. Furthermore, the model employs a multiscale forecasting strategy, combining Particle Swarm Optimization (PSO) enhanced Bidirectional Long Short-Term Memory (BiLSTM) and Extreme Gradient Boosting (XGBoost) models, along with the Autoregressive Integrated Moving Average (ARIMA) method, to predict based on the characteristics of different frequency components. Finally, the forecasts are integrated using PSO-BiLSTM to form a comprehensive forecast. Notably, given the high correlation between the trend series and influencing factor variables, the model jointly predicts them. A case study based on the Guangdong carbon market in China demonstrates that the proposed composite forecasting model outperforms other benchmark models, with Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) values of 0.4009, 0.2699, and 0.5183%, respectively. This forecasting model provides an effective tool for predicting and analyzing carbon price fluctuations, offering new insights for precise carbon market price predictions.

Cleavage of Carbodicarbenes with N2O for Accessing Stable Diazoalkenes: Two-Fold Ligand Exchange at a C(0)-Atom.

The cleavage of carbophosphinocarbenes and carbodicarbenes with nitrous oxide (N2O) leads to the formation of room-temperature stable diazoalkenes. The utility of Ph3P/N2 and NHC/N2 ligand exchange reactions were demonstrated by accessing novel benzimidazole- and benzothiazole derived diazoalkenes, which are not accessible by the current state-of-the-art methods. The stable diazoalkenes subsequently allow further ligand exchange reactions at C(0) with carbon monoxide, isocyanide, or a diamidocarbene (DAC). Overall, the combination of hitherto unknown NHC/N2 and N2/L (L = DAC, CO, R-NC) ligand exchange reactions at a C(0) center allow the selective functionalization of the carbodicarbene ligand structure which represents a new methodology to rapidly assemble novel carbodicarbenes or cumulenic compounds.

Phase‐separated Droplets Can Direct the Kinetics of Chemical Reactions Including Polymerization, Self‐replication and Oscillating Networks

AbstractPhase‐separated compartments can localize (bio)chemical reactions and influence their kinetics. They are believed to play an important role both in extant life in the form of biomolecular condensates and at the origins of life as coacervate protocells. However, experimentally testing the influence of coacervates on different reactions is challenging and time‐consuming. We therefore use a numerical model to explore the effect of phase‐separated droplets on the kinetics and outcome of different chemical reaction systems, where we vary the coacervate volume and partitioning of reactants. We find that the rate of bimolecular reactions has an optimal dilute/coacervate phase volume ratio for a given reactant partitioning. Furthermore, coacervates can accelerate polymerization and self‐replication reactions and lead to formation of longer polymers. Lastly, we find that coacervates can ‘rescue’ oscillating reaction networks in concentration regimes where sustained oscillations do not occur in a single‐phase system. Our results indicate that coacervates can direct the outcome of a wide range of reactions and impact fundamental aspects such as yield, reaction pathway selection, product length and emergent functions. This may have far‐reaching implications for origins of life, synthetic cells and the fate and function of biological condensates.

GOG-MBSHO: multi-strategy fusion binary sea-horse optimizer with Gaussian transfer function for feature selection of cancer gene expression data

Cancer gene expression data has the characteristics of high-dimensional, multi-text and multi-classification. The problem of cancer subtype diagnosis can be solved by selecting the most representative and predictive genes from a large number of gene expression data. Feature selection technology can effectively reduce the dimension of data, which helps analyze the information on cancer gene expression data. A multi-strategy fusion binary sea-horse optimizer based on Gaussian transfer function (GOG-MBSHO) is proposed to solve the feature selection problem of cancer gene expression data. Firstly, the multi-strategy includes golden sine strategy, hippo escape strategy and multiple inertia weight strategies. The sea-horse optimizer with the golden sine strategy does not disrupt the structure of the original algorithm. Embedding the golden sine strategy within the spiral motion of the sea-horse optimizer enhances the movement of the algorithm and improves its global exploration and local exploitation capabilities. The hippo escape strategy is introduced for random selection, which avoids the algorithm from falling into local optima, increases the search diversity, and improves the optimization accuracy of the algorithm. The advantage of multiple inertial weight strategies is that dynamic exploitation and exploration can be carried out to accelerate the convergence speed and improve the performance of the algorithm. Then, the effectiveness of multi-strategy fusion was demonstrated by 15 UCI datasets. The simulation results show that the proposed Gaussian transfer function is better than the commonly used S-type and V-type transfer functions, which can improve the classification accuracy, effectively reduce the number of features, and obtain better fitness value. Finally, comparing with other binary swarm intelligent optimization algorithms on 15 cancer gene expression datasets, it is proved that the proposed GOG1-MBSHO has great advantages in the feature selection of cancer gene expression data.

Effect of exogenous ketone supplementation on cardiac energetics, function, and perfusion in type 2 diabetes, heart failure, and healthy participants- A single center, open labelled clinical study

Abstract Background Type 2 diabetes (T2D) confers loss of cardiac metabolic flexibility in fuel selection and impaired mitochondrial function. Enhanced ketone metabolism observed in T2D may represent a compensatory adaptive mechanism as ketones are a more energy efficient resource than carbohydrates or fatty acids. Favorable energetic properties of ketones may potentially mitigate the energy starved state in T2D and heart failure (HF). Purpose To test whether exogenous oral ketone supplementation would reverse cardiac energetic deficit, as well as improve cardiac function and perfusion in patients with T2D, with HF with reduced ejection fraction (HFrEF), and healthy volunteers (HV). Methods Three groups of patients were recruited: patients with T2D (n=33); patients with HFrEF (n=29, 14 with T2D); and HVs(n=25). Participants underwent cardiovascular magnetic resonance and spectroscopy to assess left ventricular (LV) function, rest and dobutamine stress perfusion and energetics (phosphocreatine/adenosine triphosphate ratio[PCr/ATP]). After the initial visit, participants had an identical second visit following 2 weeks of oral ketone supplementation (30g daily). Results Participants were matched in age and sex distribution. There were no significant differences in LV ejection fraction (LVEF) between T2D and HV groups with significantly lower LVEF in HFrEF group. Both the T2D group and the HFrEF group showed significant reductions in PCr/ATP ratio and the rest and stress GLS compared to the HV. The resting and dobutamine-stress myocardial blood flow (MBF) were only significantly reduced in patients with HFrEF compared to T2D and HV groups. Subgroup analyses of HFrEF group with and without T2D showed no significant differences in energetics, perfusion, or functional assessments. Significant increase in PCr/ATP ratio was seen only in T2D group from baseline after 2 weeks of ketone supplementation (Visit-1:1.6[1.5,1.8] vs Visit-2:1.9[1.7,2.1]; P=0.01). This significant increment was not observed in HFrEF or HV groups. Two weeks of ketone supplementation was not associated with any significant changes in LVEF, GLS, rest or dobutamine-stress myocardial blood flow, or in myocardial lipid content (Table-1). Conclusions Short-term ketone supplementation is associated with isolated significant improvements in resting cardiac energetics in patients with T2D and preserved LVEF, without changes cardiac function or perfusion. In contrast to patients with T2D and preserved LVEF, short-term ketone supplementation does not lead to any significant improvements in energetics in patients with HFrEF suggesting loss of mitochondrial plasticity with transition to HFrEF. Moreover, healthy volunteers experience no further increments of myocardial energetics from the normal range values at baseline with ketone supplementation.

Psilocin, the Psychoactive Metabolite of Psilocybin, Modulates Select Neuroimmune Functions of Microglial Cells in a 5-HT2 Receptor-Dependent Manner

Neuroinflammation that is caused by microglia, the main immune cells of the brain, contributes to neurodegenerative diseases. Psychedelics, including psilocybin and lysergic acid diethylamide (LSD), possess certain anti-inflammatory properties and, therefore, should be considered as drug candidates for treating neuroinflammatory pathologies. When ingested, psilocybin is rapidly dephosphorylated to yield psilocin, which crosses the blood–brain barrier and exerts psychotropic activity by interacting with the 5-hydroxytryptamine 2A receptors (5-HT2ARs) on neurons. Since microglia express all three 5-HT2R isoforms, we hypothesized that, by interacting with these receptors, psilocin beneficially modulates select neuroimmune functions of microglia. We used microglia-like cell lines to demonstrate that psilocin, at non-toxic concentrations, did not affect the secretion of tumor necrosis factor (TNF) by immune-stimulated microglial cells, but significantly inhibited their phagocytic activity, the release of reactive oxygen species (ROS), and nitric oxide (NO) production. The inhibitory activity of psilocin on the latter two functions was similar to that of two selective 5-HT2R agonists, namely, 25I-NBOH and Ro60-0175. The role of this subfamily of receptors was further demonstrated by the application of 5-HT2R antagonists cyproheptadine and risperidone. Psilocin should be considered a novel drug candidate that might be effective in treating neuroimmune disorders, such as neurodegenerative diseases, where reactive microglia are significant contributors.

Proof of Work with Random Selection (PoWR): An Energy Saving Consensus Algorithm with Proof of Work and the Random Selection Function

Bitcoin, which has been used for 13 years, has a role in transactions and investments as a major cryptocurrency. However, as the number of users increases, Bitcoin faces difficulties, such as scalability for transaction throughput and energy-consumption problems due to the concentration of the mining pool. When Bitcoin first started to come out, it began to develop gradually through the mining of individuals. Nevertheless, as the price of the cryptocurrency gradually climbed, large mining corporation groups entered the mining competition with integrated circuit (IC) chips. Consequently, the substantial increase in power consumption is raising concerns regarding energy expenditure. This paper confirms that the verifiable random selection consensus protocol based on proof of work facilitates a fair and efficient system, enabling the participation of numerous individual miners in the mining competition while counteracting the monopolization of the hash rate by large mining corporations, thereby preserving the decentralization of mining. The protocol demonstrates the potential to mitigate substantial energy consumption. Moreover, it embodies features that create barriers to the adoption of high-energy-consuming application-specific integrated circuit equipment, significantly diminishing the principal factors contributing to extensive power utilization.

Diode and Selective Routing Functionalities Controlled by Geometry in Current-Induced Spin-Orbit Torque Driven Magnetic Domain Wall Devices.

Research on current-induced domain wall (DW) motion in heavy metal/ferromagnet structures is crucial for advancing memory, logic, and computing devices. Here, we demonstrate that adjusting the angle between the DW conduit and the current direction provides an additional degree of control over the current-induced DW motion. A DW conduit with a 45° section relative to the current direction enables asymmetrical DW behavior: for one DW polarity, motion proceeds freely, while for the opposite polarity, motion is impeded or even blocked in the 45° zone, depending on the interfacial Dzyaloshinskii-Moriya interaction strength. This enables the device to function as a DW diode. Leveraging this velocity asymmetry, we designed a Y-shaped DW conduit with one input and two output branches at +45° and -45°, functioning as a DW selector. A DW injected into the junction exits through one branch, while a reverse polarity DW exits through the other, demonstrating selective DW routing.

Selective Functionalization of White Phosphorus with Alkyl Bromides under Photocatalytic Conditions: A Chlorine-Free Protocol to Dialkyl and Trialkyl Phosphine Oxides.

A novel and efficient method for the direct selective alkylation of white phosphorus (P4) with alkyl bromides has been developed, utilizing 4DPAIPN as the photocatalyst and Hantzsch ester as the reductant. This method facilitates the synthesis of structurally diverse dialkyl phosphine oxides in good yields, offering a streamlined alternative to the traditional stepwise approach of chlorinating P4 with Cl2 and subsequently displacing the chlorine atom. Noteworthy features of this reaction include excellent product selectivity, remarkable functional group tolerance, and a broad substrate scope. Additionally, this method is effective for the synthesis of trialkyl phosphine oxides.

Regiodivergent Functionalization of Protected and Unprotected Carbohydrates using Photoactive 4‐Tetrafluoropyridinylthio Fragment as an Adaptive Activating Group

AbstractThe selective functionalization of carbohydrates holds a central position in synthetic carbohydrate chemistry, driving the ongoing quest for ideal approaches to manipulate these compounds. In this study, we introduce a general strategy that enables the regiodivergent functionalization of saccharides. The use of electron‐deficient photoactive 4‐tetrafluoropyridinylthio (SPyf) fragment as an adaptable activating group, facilitated efficient functionalization across all saccharide sites. More importantly, this activating group can be directly installed at the C1, C5 and C6 positions of biomass‐derived carbohydrates in a single step and in a site‐selective manner, allowing for the efficient and precision‐oriented modification of unprotected saccharides and glycans.

The disc origin of the Milky Way bulg. The high velocity dispersion of metal-rich stars at low latitudes

Previous studies of the chemo-kinematic properties of stars in the Galactic bulge have revealed a puzzling trend. Along the bulge minor axis, and close to the Galactic plane, metal-rich stars display a higher line-of-sight velocity dispersion compared to metal-poor stars, while at higher latitudes metal-rich stars have lower velocity dispersions than metal-poor stars, similar to what is found in the Galactic disc. In this work, we re-examine this issue, by studying the dependence of line-of-sight velocity dispersions on metallicity and latitude in APOGEE Data Release 17, confirming the results of previous works. We then analyse an $N$-body simulation of a Milky Way-like galaxy, also taking into account observational biases introduced by the APOGEE selection function. We show that the inversion in the line-of-sight velocity dispersion-latitude relation observed in the Galactic bulge -- where the velocity dispersion of metal-rich stars becomes greater than that of metal-poor stars as latitude decreases -- can be reproduced by our model. We show that this inversion is a natural consequence of a scenario in which the bulge is a boxy or peanut-shaped structure, whose metal-rich and metal-poor stars mainly originate from the thin and thick disc of the Milky Way, respectively. Due to their cold kinematics, metal-rich, thin disc stars are efficiently trapped in the boxy, peanut-shaped bulge, and at low latitudes show a strong barred morphology, which -- given the bar orientation with respect to the Sun-Galactic centre direction -- results in high velocity dispersions that are larger than those attained by the metal-poor populations. Extremely metal-rich stars in the Galactic bulge, which have received renewed attention in the literature, do follow the same trends as those of the metal-rich populations. The line-of-sight velocity-latitude relation observed in the Galactic bulge for metal-poor and metal-rich stars are thus both an effect of the intrinsic nature of the Galactic bulge (i.e. mostly secular) and of the angle at which we observe it from the Sun.

Linear infrastructure and associated wildlife accidents create an ecological trap for an apex predator and scavenger

Animals may fall into an ‘ecological trap’ when they select seemingly attractive habitats at the expense of their fitness. This maladaptive behavior is often the result of rapid, human-induced changes in their natal environment, such as the construction of energy and transportation infrastructure. We tested the ecological trap hypothesis regarding human-created linear infrastructure on a widely distributed apex predator and scavenger—the Golden Eagle (Aquila chrysaetos), whose range spans the entire Northern Hemisphere. Roads and railways offer novel and attractive feeding opportunities through traffic-induced mortality of other species, while powerline areas provide perching or nesting sites and scavenging opportunities from electrocuted or collision-killed birds. These conditions may have negative demographic consequences for eagles if these apparent opportunities turn into traps. Using step selection functions, we analyzed habitat selection of 74 GPS-tracked Golden Eagles (37 adults and 37 immatures) during eleven years in Fennoscandia. To assess habitat attractiveness, we used wildlife traffic accident statistics for dominant wild species, and to evaluate demographic consequences, we used mortality data from the GPS-tagged eagles. Our analysis revealed that eagles selected linear features such as roads, railways and powerlines at both the population and individual levels. Both adult and immature eagles consistently selected these features, and the strength of selection for linear features increased with age in immature eagles. The linear features however had 5.5 times higher mortality risk for eagles than other selected habitats indicating the presence of an ecological trap. We discuss the implications of these findings for the conservation and population ecology of apex predators and scavengers, as well as their potential demographic consequences. To mitigate this issue, we urgently recommend the removal of carcasses from roads and tracks to prevent ecological traps for raptors and scavenger species worldwide. Additionally, we advocate for the development of methods and strategies to reduce wildlife traffic accidents.

Multiphasic movement and step-selection patterns of dispersed tigers in the central Indian landscape.

Large carnivores play a crucial role in the ecosystem, though their conservation needs a landscape-level approach due to their wide range of habitats and dispersal events. The study of tigers in a human-dominated landscape matrix and their adaptation and adjustment of movement behaviours during the dispersal phase is essential for long-term conservation planning and management policy. We studied the dispersal event of five VHF/GPS collared individuals during 2009-2020. We investigated movement parameters (step length), and the effects of anthropogenic pressures (distance from village), distance from water and vegetation cover, on behavioural phase under a Hidden Markov Model framework. We also tested the effects of distance from village, vegetation cover, and habitat types on animal movement using an integrated Step Selection Function framework. The mean step length (405.44±10.63 m/hr) varied widely by different time of day. Displacement was high during the night (665.28±21.36 m/hr) compared to day (434.16±17.37 m/hr). Tigers moved fast (872.7m; 95% CI 839.1-906.3m) with longer step length and a directional turning angle in non-forested areas (i.e. the human-dominated landscape), likely to avoid conflict with humans. Individuals distinctly exhibited two behavioural states: encamping (~32% of the time) and travelling (~68% of the time). Further, they avoided the human-dominated landscape and mostly remained in and forested areas, especially during nighttime. Our study is the first attempt to understand behavioural transition of dispersal tigers and their habitat selection. Lesser anthropogenic disturbance and high vegetation cover positively influenced the tiger dispersal, while water availability did not affect their state transitional probability. Additionally, dispersers showed high affinity towards forested land during nighttime for travelling.The findings of this study show the importance of functional corridors and stepping stones (mostly encamping areas), and also provide baseline knowledge for integrated landscape management planning and policymaking for the long-term survival of tigers in metapopulation framework.