Multiple Time Scales Research Articles

The development of a farmer decision-making mind map to inform climate services in Central America

The growing complexity of the relationship between climate information and agricultural decision-making necessitates the development of relevant and timely climate services for farmers. These services can effectively support risk management strategies in agriculture by fostering a comprehensive understanding of the intricacies involved in farmer decision-making dynamics. This paper addresses this critical gap by analyzing the drivers influencing decision-making processes that shape adaptation strategies for staple grain and coffee farming systems in Central America. The study answers the following research questions: (i) Does the mind map tool effectively provide a holistic understanding of farmers' decision-making processes? (ii) How do Central American farmers make decisions within their farm systems at multiple timescales? (iii) Which climate factors trigger these decisions? Employing a combination of systematic literature review and a case study in Honduras, the study identifies 13 critical decisions farmers make throughout their crop cycle and their respective triggers. These decisions were grouped into three clusters (production, household, and environmental) and classified into lead-time categories (operational, tactical, and strategic). Findings reveal that farmers base their decisions regarding future climate expectations on their traditional knowledge, religious dates, and memories of recent past seasons' rainfall patterns, and that one of the most significant factors influencing farmers' decisions is food security shortages resulting from extreme events. For example, recent mid-summer droughts have led farmers to prioritize sowing beans over maize in the Primera season, while during the Postrera season, they face challenges due to excess rainfall and the hurricane season. We conclude that the mind map tool developed in this paper provides an effective and appropriate method and that the variation in farmers' decision-making complexity across systems and landscapes presents a significant opportunity to design mind maps that span multiple timescales, facilitating the exploration of decision spaces. Farmers actively seek tailored weather and climate information while still valuing their existing experience and local knowledge, emphasizing the importance of integrating these elements into the development of climate services.

Assessment of drought variability in the Marrakech-Safi region (Morocco) at different time scales using GIS and remote sensing

Abstract In the semi-arid Marrakech-Safi (MS) region of southwest Morocco, climate change has amplified drought occurrences, posing significant threats to water resources and agriculture. A comprehensive understanding of drought patterns is imperative to manage these risks and enhance resilience effectively. Precipitation from 18 pluviometer stations was employed to analyze meteorological drought using the standardized precipitation index (SPI) from 1980 to 2018. Additionally, agricultural drought is quantified using three remote sensing-driven indices: vegetation condition index (VCI), temperature conditions index (TCI), and vegetation health index (VHI) from 2000 to 2018. These indices are correlated with SPI to evaluate their performance and gauge vegetation sensitivity to meteorological drought. The Mann–Kendall test assesses trends in drought events and their severity. The results demonstrated that SPI, VCI, TCI, and VHI experienced alternating dry and wet periods with an overall upward trend, especially in mountainous areas, plateau zones, and Haouz plain of the MS region. The correlation analysis establishes a significant relationship between remote sensing-based indices and SPI-6, with mean correlation coefficients exceeding 0.6. The findings underscore the importance of considering multiple time scales to comprehensively assess climate's impact on vegetation. Seasonal drought trends analysis indicates no significant negative trends in winter and spring but positive trends in autumn.

Multiple time scales investor sentiment impact the stock market index fluctuation: From margin trading business perspective

The stock market is viewed as a complex dynamic system, and investor sentiment has an important impact on index fluctuation. This study constructs investor sentiment from margin trading business perspective and investigates its impact on the Chinese stock market index fluctuation in multiple time scales. First, we utilize 12 indicators and two-stage PCA to construct a composite investor sentiment index of the margin trading business(ISMT). Second, based on TEI@I complex system theory, we use the VMD algorithm to decompose and reconstruct the ISMT, Shanghai Securities Composite Index(SSEC), and Shenzhen Securities Component Index(SZI), and obtain multiple time scale measurement sequences that reflect short-term, medium-term, and long-term fluctuation of each index, respectively. We provide evidence that the ISMT has an asymmetric impact on stock market index fluctuations. Specifically, for long-term trend, the ISMT has a significant positive impact on the SSEC, and a significant negative impact on the SZI. For medium and short-term trends, the ISMT has a significant positive impact on both the fluctuations of SSEC and SZI, and the impact degree on SSEC is greater than SZI. We also find that the impact degree of ISMT on SSEC and SZI decreases from short to long-term trend. In addition, we measure the fluctuation periodicity of ISMT in multiple time scales based on Fast Fourier Transformation, investigate the impact result during the COVID-19 pandemic, discuss the impact of ISMT on the other nine indexes commonly used in the Chinese stock market, and evaluate the predictive power of ISMT for 11 stock market index returns. This paper takes a new perspective and technology to investor sentiment research, and the results enrich relevant financial theories. The findings are crucial for investor decision-making and financial department regulation.

Attractor dynamics with activity-dependent plasticity capture human working memory across time scales

Most cognitive functions require the brain to maintain immediately preceding stimuli in working memory. Here, using a human working memory task with multiple delays, we test the hypothesis that working memories are stored in a discrete set of stable neuronal activity configurations called attractors. We show that while discrete attractor dynamics can approximate working memory on a single time scale, they fail to generalize across multiple timescales. This failure occurs because at longer delay intervals the responses contain more information about the stimuli than can be stored in a discrete attractor model. We present a modeling approach that combines discrete attractor dynamics with activity-dependent plasticity. This model successfully generalizes across all timescales and correctly predicts intertrial interactions. Thus, our findings suggest that discrete attractor dynamics are insufficient to model working memory and that activity-dependent plasticity improves durability of information storage in attractor systems.

Exploring solute-defect interactions in nanosized palladium hydrides across multiple time scales

We employ two different atomistic methods to investigate solute-defect interactions in nanosized palladium–hydrogen (Pd–H) systems across multiple time scales. The first method, referred to as Diffusive Molecular Dynamics (DMD), focuses on capturing hydride phase transformation and the evolution of solute-induced lattice defects over a diffusive time scale. The second method, Molecular Dynamics (MD), provides more detailed insights into atomic movements and lattice relaxation over the time scale of thermal vibrations. These two methods are connected with MD simulations initialized using statistical measures of microscopic variables obtained from DMD at different H/Pd ratios. Our study demonstrates that DMD effectively captures the propagation of an atomistically sharp hydride phase boundary as well as the dynamics of solute-induced misfit dislocations and stacking faults. While the H-concentrated phase leads to a reduction in the vibrational energy, the presence of stacking faults locally increases the vibrational energy of both Pd and H atoms. Furthermore, the MD simulation results align with DMD in terms of equilibrium potential energy, the preservation of hydride phase boundary, and the spatial distribution of stacking faults. We thoroughly characterize the lattice crystalline structures in four key regions of the particle. We observe a preference for H atoms to occupy tetrahedral interstitial sites near stacking faults due to the lower stacking fault energies provided by these sites within the H-concentrated phase.

Distributed coding of evidence accumulation across the mouse brain using microcircuits with a diversity of timescales.

The gradual accumulation of noisy evidence for or against options is the main step in the perceptual decision-making process. Using brain-wide electrophysiological recording in mice (Steinmetz et al., 2019), we examined neural correlates of evidence accumulation across brain areas. We demonstrated that the neurons with Drift-Diffusion-Model-like firing rate activity (i.e., evidence-sensitive ramping firing rate) were distributed across the brain. Exploring the underlying neural mechanism of evidence accumulation for the DDM-like neurons revealed different accumulation mechanisms (i.e. single and race) both within and across the brain areas. Our findings support the hypothesis that evidence accumulation is happening through multiple integration mechanisms in the brain. We further explored the timescale of the integration process in the single and race accumulator models. The results demonstrated that the accumulator microcircuits within each brain area had distinct properties in terms of their integration timescale, which were organized hierarchically across the brain. These findings support the existence of evidence accumulation over multiple timescales. Besides the variability of integration timescale across the brain, a heterogeneity of timescales was observed within each brain area as well. We demonstrated that this variability reflected the diversity of microcircuit parameters, such that accumulators with longer integration timescales had higher recurrent excitation strength.Significance StatementIn this paper we characterized the perceptual decision-making process across the mouse brain. Our findings shed more light on the decision-making process by analyzing the brain-wide electrophysiological recording dataset. This paper contains a comprehensive analysis to characterize different aspects of the evidence accumulation process, including the distribution of accumulator-like neurons, the timescale of information integration, accumulation architecture, and the relationship between accumulators' timescale and their integration circuit properties.

Ideological sensemaking in an elementary science professional development community

ABSTRACT Background Ideologies are socially constructed frameworks for sensemaking that influence teaching and learning. Drawing on Learning Sciences research on ideologies, we explore how an elementary science professional development (PD) community used substrate (shared interactional resources) in sensemaking interactions to reify or rearticulate dominant ideologies. Method We analyzed PD interactions to understand how PD community members used substrate across multiple timescales as part of ideological sensemaking. Findings We first show how participants drew on substrate to rearticulate ideologies about young learners’ capabilities in science. We then show how limited resources available in substrate impeded interactional engagement with deficit narratives of multilingual learners. Contribution Practically, we demonstrate how ideological rearticulation requires establishing intentionally designed substrate as a resource for later PD and facilitation that surfaces and challenges dominant ideologies. Methodologically, we show how substrate—often analyzed at microgenetic scales—can be traced back over longer timescales to understand longitudinal learning.

Nonlinear vibrational analysis and linearization error investigation in size-dependent resonant pressure microsensors

Dynamic and vibrational behavior of nonlinear resonant pressure micro sensors is studied in this paper using a proposed dynamic model. The basic part of the device is a microplate deflects due to external pressure in presence of electrostatic actuation. The frequency changes because of the microplate deformation is used to estimate the external pressure. For modeling of the micro sensor, the nonlinear governing equation of size dependent microplate in polar coordinate system and based on the modified couple stress theory is presented. Assuming specified number of Taylor expansion terms for electrostatic force, the linear and nonlinear ODE is obtained and nonlinear equation is solved both with multiple time scales method (MTS) and finite difference numerical method. Results indicate that considering finite terms of Taylor expansion (1 term for linear and three terms for MTS method) is the source of error in estimation of pressure or system stability. Using sufficient terms of Taylor Expansion, the error in linear and MTS solutions is vanished. Therefore, the limited values of microplate vibrational amplitude is extracted to increase the accuracy of the sensor in linear action. The effect of size dependency, applied voltage on nonlinear behavior and linearization error is also studied.

From computer systems to power systems: using stochastic network calculus for flexibility analysis in power systems

As power systems transition from controllable fossil fuel plants to variable renewable sources, managing power supply and demand fluctuations becomes increasingly important. Novel approaches are required to balance these fluctuations. The problem of determining the optimal deployment of flexibility options, considering factors such as timing and location, shares similarities with scheduling problems encountered in computer networks. In both cases, the objective is to coordinate various distributed units and manage the flow of either data or power. Among the methods for scheduling and resource allocation in computer networks, stochastic network calculus (SNC) is a promising approach that estimates worst-case guarantees for Quality of Service (QoS) indicators of computer networks, such as delay and backlog. Promising QoS indicators in the power system are given by the amount of stored energy, the serviced demand, and the demand elasticity. In this work, we investigate SNC for its capabilities and limitations to quantify flexibility service guarantees in power systems. We generate and aggregate stochastic envelopes for random processes, which was found useful for modeling flexibility in power systems at multiple time scales. In a case study on the reliability of a solar-powered car charging station, we obtain similar results as from a mixed-integer linear programming problem, which provides confidence that the chosen SNC approach is suitable for modeling power system flexibility.

Performance assessment of hydropower generator unit with the nonlinear transmissibility function method

The hydropower generator unit (HGU) is a complex nonlinear dynamic system, and how to utilize the monitoring data to achieve the performance assessment of the HGU is a challenge at present. In this paper, based on the linear transmissibility function and the nonlinear output frequency response function, the nonlinear transmissibility function (NTF) method is proposed to characterize the variation rule of the HGU performance, and the effectiveness of the proposed method is confirmed by the monitoring data from a hydropower station located in Guangxi, China. Firstly, the feature parameters related to the operation state of the unit are extracted from the monitoring data of the HGU. Secondly, the HGU system is divided into three subsystems according to the installation position of the sensors collecting these feature parameters, and the NTFs of them are estimated from multiple time scales. Finally, the performance of the HGU is comprehensively assessed utilizing the Fe indicator and the correlation transmissibility damage indicator. The analysis results demonstrate that the NTF method can reveal the performance variation trend and detect the early fault of the HGU, which is of great significance to the stable operation of the HGU.

Evaluating the Effects of Rewards and Schedule Length on Response Rates to Ecological Momentary Assessment Surveys: Randomized Controlled Trials.

Ecological momentary assessments (EMAs) are short, repeated surveys designed to collect information on experiences in real-time, real-life contexts. Embedding periodic bursts of EMAs within cohort studies enables the study of experiences on multiple timescales and could greatly enhance the accuracy of self-reported information. However, the burden on participants may be high and should be minimized to optimize EMA response rates. We aimed to evaluate the effects of study design features on EMA response rates. Embedded within an ongoing cohort study (Health@NUS), 3 bursts of EMAs were implemented over a 7-month period (April to October 2021). The response rate (percentage of completed EMA surveys from all sent EMA surveys; 30-42 individual EMA surveys sent/burst) for each burst was examined. Following a low response rate in burst 1, changes were made to the subsequent implementation strategy (SMS text message announcements instead of emails). In addition, 2 consecutive randomized controlled trials were conducted to evaluate the efficacy of 4 different reward structures (with fixed and bonus components) and 2 different schedule lengths (7 or 14 d) on changes to the EMA response rate. Analyses were conducted from 2021 to 2022 using ANOVA and analysis of covariance to examine group differences and mixed models to assess changes across all 3 bursts. Participants (N=384) were university students (n=232, 60.4% female; mean age 23, SD 1.3 y) in Singapore. Changing the reward structure did not significantly change the response rate (F3,380=1.75; P=.16). Changing the schedule length did significantly change the response rate (F1,382=6.23; P=.01); the response rate was higher for the longer schedule (14 d; mean 48.34%, SD 33.17%) than the shorter schedule (7 d; mean 38.52%, SD 33.44%). The average response rate was higher in burst 2 and burst 3 (mean 50.56, SD 33.61 and mean 48.34, SD 33.17, respectively) than in burst 1 (mean 25.78, SD 30.12), and the difference was statistically significant (F2,766=93.83; P<.001). Small changes to the implementation strategy (SMS text messages instead of emails) may have contributed to increasing the response rate over time. Changing the available rewards did not lead to a significant difference in the response rate, whereas changing the schedule length did lead to a significant difference in the response rate. Our study provides novel insights on how to implement EMA surveys in ongoing cohort studies. This knowledge is essential for conducting high-quality studies using EMA surveys. ClinicalTrials.gov NCT05154227; https://clinicaltrials.gov/ct2/show/NCT05154227.

Mechanism of Fluoride Ion Encapsulation by Magnesium Ions in a Bacterial Riboswitch.

Riboswitches sense various ions in bacteria and activate gene expression to synthesize proteins that help maintain ion homeostasis. The crystal structure of the aptamer domain (AD) of the fluoride riboswitch shows that the F- ion is encapsulated by three Mg2+ ions bound to the ligand-binding domain (LBD) located at the core of the AD. The assembly mechanism of this intricate structure is unknown. To this end, we performed computer simulations using coarse-grained and all-atom RNA models to bridge multiple time scales involved in riboswitch folding and ion binding. We show that F- encapsulation by the Mg2+ ions bound to the riboswitch involves multiple sequential steps. Broadly, two Mg2+ ions initially interact with the phosphate groups of the LBD using water-mediated outer-shell coordination and transition to a direct inner-shell interaction through dehydration to strengthen their interaction with the LBD. We propose that the efficient binding mode of the third Mg2+ and F- is that they form a water-mediated ion pair and bind to the LBD simultaneously to minimize the electrostatic repulsion between three Mg2+ bound to the LBD. The tertiary stacking interactions among the LBD nucleobases alone are insufficient to stabilize the alignment of the phosphate groups to facilitate Mg2+ binding. We show that the stability of the whole assembly is an intricate balance of the interactions among the five phosphate groups, three Mg2+, and the encapsulated F- ion aided by the Mg2+ solvated water. These insights are helpful in the rational design of RNA-based ion sensors and fast-switching logic gates.

Drought Forecasting Using Standard Precipitation Index Based on Rainfall of Western Region

Drought has always been one of the most dangerous natural disasters for manhood. Due to the continuous global climate change, drought occurrences have become more frequent and severe, affecting human existence and long-term social progress. PIStandard values are a measure of the probability of a given precipitation event occurring. They are calculated using a statistical distribution of precipitation data. The three statistical distributions that are most commonly used to model precipitation data are the gamma distribution, the normal distribution, and the log-normal distribution. Therefore, utilising all three of the above-mentioned theoretical probability distributions, the drought index PIStandard has been computed. PIStandard range more than 2 (extremely wet) to less than -2 (extremely dry), with 0.99 to - 0.99 considered the near-normal range. PIStandard is calculated at different time scales which can be 1, 3, 6, 12 and 24 months, time scales. The temporal trends of SPI at the stations were identified using the Mann-Kendall test. PIStandard were computation at 1, 3, 6, 9, 12 and 24-month time scales. PIStandard provides a better analysis of meteorological drought at multiple different timescales for short- and long-term planning because it uses the running sum of rainfall values at 1 to 24 months and more parameters for the statistical distribution used. For short-term drought monitoring and agricultural crop planning, a 1- to 3-month PIStandard can be utilized; however, long-term hydrological drought monitoring and water management planning require PIStandards of 6 to 9 months and 12 to 24 months, respectively. Drought analysis using PIStandard results can be used to design rainwater harvesting and storage structures in drought-affected areas for appropriate crop planning.

Targeting Ultrafast Spectroscopic Insights into Red Fluorescent Proteins.

Red fluorescent proteins (RFPs) represent an increasingly popular class of genetically encodable bioprobes and biomarkers that can advance next-generation breakthroughs across the imaging and life sciences. Since the rational design of RFPs with improved functions or enhanced versatility requires a mechanistic understanding of their working mechanisms, while fluorescence is intrinsically an ultrafast event, a suitable toolset involving steady-state and time-resolved spectroscopic techniques has become powerful in delineating key structural features and dynamic steps which govern irreversible photoconverting or reversible photoswitching RFPs, and large Stokes shift (LSS)RFPs. The pertinent cis-trans isomerization and protonation state change of RFP chromophores in their local environments, involving key residues in protein matrices, lead to rich and complicated spectral features across multiple timescales. In particular, ultrafast excited-state proton transfer in various LSSRFPs showcases the resolving power of wavelength-tunable femtosecond stimulated Raman spectroscopy (FSRS) in mapping a photocycle with crucial knowledge about the red-emitting species. Moreover, recent progress in noncanonical RFPs with a site-specifically modified chromophore provides an appealing route for efficient engineering of redder and brighter RFPs, highly desirable for bioimaging. Such an effective feedback loop involving physical chemists, protein engineers, and biomedical microscopists will enable future successes to expand fundamental knowledge and improve human health.

Geometric control of tilt transition dynamics in single-clamped thermalized elastic sheets.

We study the finite-temperature dynamics of thin elastic sheets in a single-clamped cantilever configuration. This system is known to exhibit a tilt transition at which the preferred mean plane of the sheet shifts from horizontal to a plane above or below the horizontal. The resultant thermally roughened two-state (up/down) system possesses rich dynamics on multiple timescales. In the tilted regime a finite-energy barrier separates the spontaneously chosen up state from the inversion-symmetric down state. Molecular dynamics simulations confirm that, over sufficiently long time, such thermalized elastic sheets transition between the two states, residing in each for a finite dwell time. One might expect that temperature is the primary driver for tilt inversion. We find, instead, that the primary control parameter, at fixed tilt order parameter, is the dimensionless and purely geometrical aspect ratio of the clamped width to the total length of the otherwise-free sheet. Using a combination of an effective mean-field theory and Kramers' theory, we derive the transition rate and examine its asymptotic behavior. At length scales beyond a material-dependent thermal length scale, renormalization of the elastic constants qualitatively modifies the temperature response. In particular, the transition is suppressed by thermal fluctuations, enhancing the robustness of the tilted state. We check and supplement these findings with further molecular dynamics simulations for a range of aspect ratios and temperatures.

Hopf Bifurcation Analysis of a Class of Saperda populnea Infectious Disease Model with Delay

Under the background of double carbon, it is important to study forest pests and diseases to improve forest carbon sink. In this paper, we establish a delayed model associated with the larvae and adults of Saperda populnea, susceptible poplars, and infected poplars. First, we analyze the existence and stability of the equilibrium of the model. Second, we study the existence of Hopf bifurcation near the equilibrium and obtain the normal form of Hopf bifurcation by the multiple time scales method. Then, we analyze the direction and stability of Hopf bifurcating periodic solutions. Third, we analyze and conjecture some parameter values based on official data, and carry out numerical simulations to verify our results. Finally, we give some suggestions on the prevention and control of Saperda populnea.

Morphologic, Atmospheric, and Oceanic Drivers Cause Multi‐Temporal Saltwater Intrusion on a Remote, Sand Island

AbstractSmall‐island populations disproportionately rely on fresh groundwater resources, which are increasingly threatened by salinization from changing ocean and climate conditions. This study investigates island groundwater dynamics and salinization over multiple timescales in response to marine, atmospheric, and morphologic drivers. New geophysical and hydrological data sets were collected on a remote sand island in the Northwest Atlantic Ocean between 2020 and 2022 and compared to historical baseline data from the 1970s. Data reveal saltwater intrusion due to multi‐decadal erosion, seasonal climate patterns, tidal forcing, and episodic flooding from Atlantic hurricanes. Long‐term dune erosion has caused the freshwater lens to thin and become asymmetrical; however, a lagged groundwater response causes the freshwater lens to be in disequilibrium with present island morphology. The maximum vertical lens thickness is seasonally constant, but the lateral transition zone along the coast thickens and moves seaward in spring when the water table is high from precipitation and frequent beach flooding. Groundwater level and electrical conductivity along low‐lying beaches significantly increase following Atlantic hurricanes due to seawater flooding, and reach a maximum of 1.93 m above sea level and 38 mS/cm, respectively. While groundwater levels recover quickly, conductivity (salinity) remains elevated due to the short intervals between winter flood events that outpace freshening from meteoric recharge. Results emphasize the importance of multi‐temporal groundwater dynamics and feedbacks between coastal flooding, erosion, and salinization. Field‐based studies considering multiple drivers and timescales of saltwater intrusion are critical for understanding and managing coastal freshwater resources in an age of rapid environmental change.

Call rate of oyster toadfish (Opsanus tau) is affected by aggregate sound level but not by specific vessel passagesa).

Anthropogenic sound is a prevalent environmental stressor that can have significant impacts on aquatic species, including fishes. In this study, the effects of anthropogenic sound on the vocalization behavior of oyster toadfish (Opasnus tau) at multiple time scales was investigated using passive acoustic monitoring. The effects of specific vessel passages were investigated by comparing vocalization rates immediately after a vessel passage with that of control periods using a generalized linear model. The effects of increased ambient sound levels as a result of aggregate exposure within hourly periods over a month were also analyzed using generalized additive models. To place the response to vessel sounds within an ecologically appropriate context, the effect of environmental variables on call density was compared to that of increasing ambient sound levels. It was found that the immediate effect of vessel passage was not a significant predictor for toadfish vocalization rate. However, analyzed over a longer time period, increased vessel-generated sound lowered call rate and there was a greater effect size from vessel sound than any environmental variable. This demonstrates the importance of evaluating responses to anthropogenic sound, including chronic sounds, on multiple time scales when assessing potential impacts.

Effects of the third body (O and N) on the recombination of molecular nitrogen using quasi-classical trajectory methods

The investigation of the recombination reactions poses significant challenges due to the complexities involved in three-body collisions including simultaneous interaction of three bodies and multiple time scales. This work aims to investigate the complex dynamics involved in the recombination of atomic nitrogen to form molecular nitrogen using the quasi-classical trajectory method for the N3 and the N2O systems. The recombination pathways considered include a single-step direct reaction and a two-step mechanism that involves the formation of an intermediate with a finite lifetime which is stabilized through a subsequent collision with a third body. The latter is further classified as Lindemann or Chaperon mechanism based on the role played by the third body. The model uses a time-lag parameter to allow for a consistent treatment of all the reaction pathways. It is observed that the recombination probability is greatest for collisions involving low translational energies and low time lags. Recombination rate coefficients are evaluated using a novel rate coefficient expression developed for three-body collisions. Low temperature recombination rate coefficients, which can be computationally prohibitive to evaluate using traditional detailed balance methods, can be evaluated at a low computational cost. The recombination pathways are determined algorithmically by identifying the various interaction time scales. The direct mechanism is found to have a larger recombination probability, but a lower rate coefficient. The effect of the third body (oxygen and nitrogen atoms) on the recombination dynamics is explored in detail. It is observed that the recombination in excess of O atom leads to a larger population of the low internal energy states, as opposed to recombination in the excess of N atoms. The dominance of the Chaperon mechanism is seen in both systems.

Combining otolith chemistry and genetics to infer the population structure of yellow snapperLutjanus argentiventris

AbstractDeveloping a metapopulation framework contributes to the understanding of spatial processes and structures in populations, providing basic information for conservation biology. However, the extent to which the metapopulation structure differs geographically and across life history stages is unexplored for most fishes. Here, we compared the population structure and connectivity patterns of juvenile yellow snapperLutjanus argentiventrisin mangroves of the Eastern Tropical Pacific Ocean. In both the Gulf of California and Galápagos, these fish experience an array of environmental and oceanographic conditions that produce unique otolith microchemistry signatures and genetic population structures. In the Galápagos Archipelago, we used otolith microchemistry and microsatellite DNA, while for the Gulf of California, we only used otolith microchemistry. We observed relatively small differences in the otolith microchemistry at the ecoregion spatial scale (10–100 km2) for the Galápagos and the Gulf of California (classification accuracy of 57% and 64%, respectively). At the finer mangrove spatial scale (~1 km2), we found larger differences in the otolith microchemistry among the Gulf of California mangroves (classification accuracy ~90%) than in Galápagos (classification accuracy ~24%), potentially related to a stronger environmental gradient in the former. Based on otoliths, 75% of juveniles were migrants among mangroves in the Galápagos, in contrast to only around 10% of juveniles being migrants among the Gulf of California mangroves, suggesting a metapopulation structure characterized by high rates of self‐recruitment for snappers in the Gulf of California. For Galápagos, both otolith microchemistry and genetics supported the presence of a source–sink metapopulation structure for the yellow snapper, with high levels of connectivity in mangroves within the Eastern and Western ecoregions (FST = 0.003,p &lt; 0.05). By combining tools that assess connectivity at multiple timescales (microchemistry and genetics) at different life stages and ecosystems, we provide a more complete elucidation of metapopulation structure forL. argentiventris. The approach employed here can be applied to other tropical fishes with broad distribution ranges and ontogenetic changes across complex habitats such as mangroves, seagrasses, and coral reefs.