Modelling neural informational propagation and functional auditory sensory memory with temporal multi-scale operators

In this paper we prove that both diffusion and the leaky integrators cascade based transport mechanisms have as their inherent property the effect of temporal multi-scaling. The two transport mechanisms are modeled not as convolution based algorithms but as causal physical processes. This implies that propagation of information through a neural map may act as a mechanism for achieving temporal multi-scale analysis in the auditory system. Specifically, we are interested in the effects of such a transport process on the formation and the dynamics of auditory sensory memory. Two temporal models of information propagation are discussed and compared in terms of their ability to model auditory sensory memory effects and the biological plausibility of their structure: the causal diffusion based operator (CD) and the leaky integrator cascade based operator (LINC). We show that temporal multi-scale representations achieved by both models exhibit the effects similar to those of auditory sensory memory (filtering, time delay and binding of information). As regards higher-level functions of auditory sensory memory such as change detection, the LINC operator seems to be a biologically more plausible solution for modeling temporal cortical processing.     

Animal movement in the absence of predation: environmental drivers of movement strategies in a partial migration system

Animal movement strategies including migration, dispersal, nomadism, and residency are shaped by broad‐scale spatial‐temporal structuring of the environment, including factors such as the degrees of spatial variation, seasonality and inter‐annual predictability. Animal movement strategies, in turn, interact with the characteristics of individuals and the local distribution of resources to determine local patterns of resource selection with complex and poorly understood implications for animal fitness. Here we present a multi‐scale investigation of animal movement strategies and resource selection. We consider the degree to which spatial variation, seasonality, and inter‐annual predictability in resources drive migration patterns among different taxa and how movement strategies in turn shape local resource selection patterns. We focus on adult Galapagos giant tortoises Chelonoidis spp. as a model system since they display many movement strategies and evolved in the absence of predators of adults. Specifically, our analysis is based on 63 individuals among four taxa tracked on three islands over six years and almost 10⁶ tortoise re‐locations. Tortoises displayed a continuum of movement strategies from migration to sedentarism that were linked to the spatio‐temporal scale and predictability of resource distributions. Movement strategies shaped patterns of resource selection. Specifically, migratory individuals displayed stronger selection toward areas where resources were more predictable among years than did non‐migratory individuals, which indicates a selective advantage for migrants in seasonally structured, more predictable environments. Our analytical framework combines large‐scale predictions for movement strategies, based on environmental structuring, with finer‐scale analysis of space‐use. Integrating different organizational levels of analysis provides a deeper understanding of the eco‐evolutionary dynamics at play in the emergence and maintenance of migration and the critical role of resource predictability. Our results highlight that assessing the potential benefits of differential behavioral responses first requires an understanding of the interactions among movement strategies, resource selection and individual characteristics.     

Human learning characteristics in the tracking tasks of iterative nature

In this paper, human learning characteristics in the tracking tasks of iterative nature are investigated. Various linear and nonlinear systems are used as plant, and a human operator has to generate the proper control inputs to force these systems in tracking the desired trajectory. The learning behaviour of the human operator in modifying his control actions is studied and it is observed that the human operator can improve his performance quite efficiently despite the unavailability of any information about the system or the desired trajectories. It is concluded from the experiments that the human operator not only use the information that is directly available to him (error in this case), but also extracts some useful information (e.g. error rate) that he feels is necessary to generate a good control action. The limitation of the human performance is studied in frequency domain, and the performance of the human operator against the frequency bandwidth of error and error rate signals are highlighted. Analysis of the results revealed that a human operator gives more importance to the error rate in generating his control actions and, accordingly, it is observed that his limitation in term of performance is more sensitive to the frequency bandwidth of the error rate as compared to the error. The human operator cannot improve his performance once the frequency components of the error or error rates shift to the higher frequencies, say above 1.0 Hz.     

On the impossibility of coexistence of infinitely many strategies

We investigate the possibility of coexistence of pure, inherited strategies belonging to a large set of potential strategies. We prove that under biologically relevant conditions every model allowing for coexistence of infinitely many strategies is structurally unstable. In particular, this is the case when the "interaction operator" which determines how the growth rate of a strategy depends on the strategy distribution of the population is compact. The interaction operator is not assumed to be linear. We investigate a Lotka-Volterra competition model with a linear interaction operator of convolution type separately because the convolution operator is not compact. For this model, we exclude the possibility of robust coexistence supported on the whole real line, or even on a set containing a limit point. Moreover, we exclude coexistence of an infinite set of equidistant strategies when the total population size is finite. On the other hand, for infinite populations it is possible to have robust coexistence in this case. These results are in line with the ecological concept of "limiting similarity" of coexisting species. We conclude that the mathematical structure of the ecological coexistence problem itself dictates the discreteness of the species.     

Interactions between spatial and temporal scales in the evolution of dispersal rate

The evolution of dispersal rate is studied with a model of several local populations linked by dispersal. Three dispersal strategies are considered where all, half or none of the offspring disperse. The spatial scale (number of patches) and the temporal scale (probability of local extinction) of the environment are critical in determining the selective advantage of the different dispersal strategies. The results from the simulations suggest that an interaction between group selection and individual selection results in a different outcome in relation to the spatial and temporal scales of the environment. Such an interaction is able to maintain a polymorphism in dispersal strategies. The maintenance of this polymorphism is also scale-dependent. This study suggests a mechanism for the short-term evolution of dispersal, and provides a testable prediction of this hypothesis, namely that loss of dispersal abilities should be more frequent in spatially more continuous environments, or in temporally more stable environments. This revised version was published online in July 2006 with corrections to the Cover Date.     

Predicting drought tolerance from slope aspect preference in restored plant communities

Plants employ strategies of tolerance, endurance, and avoidance to cope with aridity in space and time, yet understanding the differential importance of such strategies in determining patterns of abundance across a heterogeneous landscape is a challenge. Are the species abundant in drier microhabitats also better able to survive drought? Are there relationships among occupied sites and temporal dynamics that derive from physiological capacities to cope with stress or dormancy during unfavorable periods? We used a restoration project conducted on two slope aspects in a subwatershed to test whether species that were more abundant on more water‐limited S‐facing slopes were also better able to survive an extreme drought. The attempt to place many species uniformly on different slope aspects provided an excellent opportunity to test questions of growth strategy, niche preference, and temporal dynamics. Perennial species that established and grew best on S‐facing slopes also had greater increases in cover during years of drought, presumably by employing drought tolerance and endurance techniques. The opposite pattern emerged for annual species that employed drought‐escape strategies, such that annuals that occupied S‐facing slopes were less abundant during the drought than those that were more abundant on N‐facing slopes. Our results clarify how different functional strategies interact with spatial and temporal heterogeneity to influence population and community dynamics and demonstrate how large restoration projects provide opportunities to test fundamental ecological questions.     

The anatomy of predator-prey dynamics in a changing climate

Humans are increasingly influencing global climate and regional predator assemblages, yet a mechanistic understanding of how climate and predation interact to affect fluctuations in prey populations is currently lacking. Here we develop a modelling framework to explore the effects of different predation strategies on the response of age-structured prey populations to a changing climate. We show that predation acts in opposition to temporal correlation in climatic conditions to suppress prey population fluctuations. Ambush predators such as lions are shown to be more effective at suppressing fluctuations in their prey than cursorial predators such as wolves, which chase down prey over long distances, because they are more effective predators on prime-aged adults. We model climate as a Markov process and explore the consequences of future changes in climatic autocorrelation for population dynamics. We show that the presence of healthy predator populations will be particularly important in dampening prey population fluctuations if temporal correlation in climatic conditions increases in the future.     

Screening Radiolocation Datasets for Movement Strategies With Time Series Segmentation

ABSTRACT Classical home range analysis is tailored to meet requirements of data with few points per individual with relatively large intervals between observations. The swift rise in Global Positioning System (GPS)-based studies requires the development of new analytical approaches because GPS data allow for more detailed analysis in time and space. The amount of data derived from GPS studies enhances the potential to more accurately separate movement strategies. We present a general, simple, conceptual approach to using large movement datasets to automatically screen and delimit spatial and temporal home ranges of individuals and movement strategies using time series segmentation. We used GPS data for moose (Alces alces) from a boreal Swedish population as an example. We tested predictions that our screening method could separate seasonal migration from dispersal and nomadic strategies by the movement profile, which includes several dimensions. Our analysis showed that broad strategies were detected using our simple analytical approach, which speeds up use of GPS data for management and research because the method can be used to calculate more objective spatial and temporal activity ranges in relation to movement strategies. Our examples illustrate the importance of using the time stamp on location data in describing home ranges and movements.     

Quantifying the Short-Term Costs of Conservation Interventions for Fishers at Lake Alaotra,Madagascar

Artisanal fisheries are a key source of food and income for millions of people, but if poorly managed, fishing can have declining returns as well as impacts on biodiversity. Management interventions such as spatial and temporal closures can improve fishery sustainability and reduce environmental degradation, but may carry substantial short-term costs for fishers. The Lake Alaotra wetland in Madagascar supports a commercially important artisanal fishery and provides habitat for a Critically Endangered primate and other endemic wildlife of conservation importance. Using detailed data from more than 1,600 fisher catches, we used linear mixed effects models to explore and quantify relationships between catch weight, effort, and spatial and temporal restrictions to identify drivers of fisher behaviour and quantify the potential effect of fishing restrictions on catch. We found that restricted area interventions and fishery closures would generate direct short-term costs through reduced catch and income, and these costs vary between groups of fishers using different gear. Our results show that conservation interventions can have uneven impacts on local people with different fishing strategies. This information can be used to formulate management strategies that minimise the adverse impacts of interventions, increase local support and compliance, and therefore maximise conservation effectiveness.     

When do conservation planning methods deliver? Quantifying the consequences of uncertainty

The rapid global loss of biodiversity has led to a proliferation of systematic conservation planning methods. In spite of their utility and mathematical sophistication, these methods only provide approximate solutions to real-world problems where there is uncertainty and temporal change. The consequences of errors in these solutions are seldom characterized or addressed. We propose a conceptual structure for exploring the consequences of input uncertainty and oversimplified approximations to real-world processes for any conservation planning tool or strategy. We then present a computational framework based on this structure to quantitatively model species representation and persistence outcomes across a range of uncertainties. These include factors such as land costs, landscape structure, species composition and distribution, and temporal changes in habitat. We demonstrate the utility of the framework using several reserve selection methods including simple rules of thumb and more sophisticated tools such as Marxan and Zonation. We present new results showing how outcomes can be strongly affected by variation in problem characteristics that are seldom compared across multiple studies. These characteristics include number of species prioritized, distribution of species richness and rarity, and uncertainties in the amount and quality of habitat patches. We also demonstrate how the framework allows comparisons between conservation planning strategies and their response to error under a range of conditions. Using the approach presented here will improve conservation outcomes and resource allocation by making it easier to predict and quantify the consequences of many different uncertainties and assumptions simultaneously. Our results show that without more rigorously generalizable results, it is very difficult to predict the amount of error in any conservation plan. These results imply the need for standard practice to include evaluating the effects of multiple real-world complications on the behavior of any conservation planning method.     

Laboratory animal models of temporal lobe epilepsy

Temporal lobe epilepsy is a common human disease that is difficult to treat. The pathogenesis of temporal lobe epilepsy, which holds many unresolved questions, and opportunities for creating more effective treatments and preventative strategies are reviewed herein. Laboratory animal models are essential to meet these challenges. How models are created, how they compare with each other and with the disease in human patients, and how they advance our understanding of temporal lobe epilepsy are described.     

Horned larks on the Tibetan Plateau adjust the breeding strategy according to the seasonal changes in the risk of nest predation and food availability

Songbirds in seasonal environments often adjust their breeding strategy according to spatial or temporal changes in breeding conditions. Here we investigate how horned larks Eremophila alpestris, a multi‐brooded songbird on the Tibetan Plateau, responded to the changing risk of nest predation and food availability across breeding attempts. We showed that both nest concealment and food supply increased with plant growth, and horned larks adjusted their breeding strategies accordingly. First they selected nest‐sites where predator density was low, which enhanced nest survival. Second, clutch size increased with improving breeding conditions. They did not adopt an ‘egg‐size’ strategy as egg size did not change with laying sequence or breeding attempt. Instead, they adopted the ‘brood survival (feeding later‐hatched nestlings more)’ and ‘brood reduction (feeding early‐hatched nestlings more)’ strategies during early and later attempts. Moreover, nestlings’ growth varied with breeding attempt: more energy was invested into the growth of body mass during the first attempt but more energy was expended on the growth of linear structures during later attempts. This difference in energy allocation reflected changing food availability. We suggest that temporal changes of environmental factors are also the important force driving the evolution of avian breeding strategies.     

Predictive modeling of human operator cognitive state via sparse and robust support vector machines

The accurate prediction of the temporal variations in human operator cognitive state (HCS) is of great practical importance in many real-world safety-critical situations. However, since the relationship between the HCS and electrophysiological responses of the operator is basically unknown, complicated and uncertain, only data-based modeling method can be employed. This paper is aimed at constructing a data-driven computationally intelligent model, based on multiple psychophysiological and performance measures, to accurately estimate the HCS in the context of a safety-critical human–machine system. The advanced least squares support vector machines (LS-SVM), whose parameters are optimized by grid search and cross-validation techniques, are adopted for the purpose of predictive modeling of the HCS. The sparse and weighted LS-SVM (WLS-SVM) were proposed by Suykens et al. to overcome the deficiency of the standard LS-SVM in lacking sparseness and robustness. This paper adopted those two improved LS-SVM algorithms to model the HCS based solely on a set of physiological and operator performance data. The results showed that the sparse LS-SVM can obtain HCS models with sparseness with almost no loss of modeling accuracy, while the WLS-SVM leads to models which are robust in case of noisy training data. Both intelligent system modeling approaches are shown to be capable of capturing the temporal fluctuation trends of the HCS because of their superior generalization performance.     

克隆植物对异质生境的适应对策研究进展

生境异质性是自然生态系统的基本特征,植物生长的必需资源和环境胁迫因子均存在着复杂的时间和空间异质性。克隆植物是指在自然条件下具有克隆特性的植物,即可通过与母株相连的芽、根茎、分蘖或枝条等繁殖体产生无性繁殖的植物,这些繁殖体一旦定居便可成为潜在的独立个体。克隆植物具有独特的生境适应策略(如形态可塑性、克隆整合、克隆分工、觅食行为、风险分摊等),面对异质性的生境条件,它可以通过调整自身的生理和形态结构来适应异质生境。目前,对于克隆植物在异质生境适应行为的研究已有很多报道,然而系统性的归纳和总结尚有欠缺。综述了克隆植物在不同资源异质生境(光照、养分、水分)和不同胁迫生境(盐碱胁迫、风沙胁迫、重金属胁迫)下独特的适应对策。最后,针对克隆植物对异质生境的适应对策,进行了总结并对未来的重点研究方向提出建议：(1)时间异质性尺度上的考量;(2)异质性生境中生物因子的调控作用;(3)克隆植物入侵机制;(4)克隆植物在生态修复中的应用潜力。     

Evidence for varying social strategies across the day in chacma baboons

Strong social bonds can make an important contribution to individual fitness, but we still have only a limited understanding of the temporal period relevant to the adjustment of social relationships. While there is growing recognition of the importance of strong bonds that persist for years, social relationships can also vary over weeks and months, suggesting that social strategies may be optimized over shorter timescales. Using biological market theory as a framework, we explore whether temporal variation in the benefits of social relationships might be sufficient to generate daily adjustments of social strategies in wild baboons. Data on grooming, one measure of social relationships, were collected from 60 chacma baboons (Papio ursinus) across two troops over a six month period. Our analyses suggest that social strategies can show diurnal variation, with subordinates preferentially grooming more dominant individuals earlier in the day compared with later in the day. These findings indicate that group-living animals may optimize certain elements of their social strategies over relatively short time periods.     

Temporal variation in bat-fruit interactions: Foraging strategies influence network structure over time

Mutualistic interactions, such as seed dispersal, are important for the maintenance of structure and stability of tropical communities. However, there is a lack of information about spatial and temporal variation in plant-animal interaction networks. Thus, our goal was to assess the effect of bat's foraging strategies on temporal variation in the structure and robustness of bat-fruit networks in both a dry and a rain tropical forest. We evaluated monthly variation in bat-fruit networks by using seven structure metrics: network size, average path length, nestedness, modularity, complementary specialization, normalized degree and betweenness centrality. Seed dispersal networks showed variations in size, species composition and modularity; did not present nested structures and their complementary specialization was high compared to other studies. Both networks presented short path lengths, and a constantly high robustness, despite their monthly variations. Sedentary bat species were recorded during all the study periods and occupied more central positions than nomadic species. We conclude that foraging strategies are important structuring factors that affect the dynamic of networks by determining the functional roles of frugivorous bats over time; thus sedentary bats are more important than nomadic species for the maintenance of the network structure, and their conservation is a must.     

Relationships between life-history strategies of European freshwater fish species and their habitat preferences

1. Focusing on the current environmental characteristics, the ‘habitat template’ theory proposes that life‐history strategies summarise how evolution has shaped species to cope with the temporal and spatial variability of their present environment. The hierarchical ‘landscape filters’ concept predicts that the distribution of species reflects their specific traits that allow them to pass through multiple habitat filters. Together, these theories showed the importance of identifying the functional relationships of species to selective habitat forces in order to predict the organisation and response of communities to the environment. 2. We test the relationships between life‐history traits of European freshwater fish species’ and their habitat preferences, to detect the strategies adopted by fish to cope with their current habitat. For this purpose, we use published data on species traits and habitat preferences (microhabitat hydraulics, temperature and oxygen level). We use multivariate analyses to classify fish species’ strategies and test the relationships between strategies and habitat preferences. 3. We identified a continuum of life‐history patterns between two extremes, with opportunistic and periodic species. Our study supports the idea that microhabitat hydraulics plays a more important role as a template for these species ecological strategies than temperature and oxygen level. Indeed, riffle habitats may select opportunistic species whereas weak relationships are found between species strategies and both their temperature and oxygen level preferences. In addition, the ratio between mortality and growth rate (dimensionless trait), reflecting a trade‐off between growth and survival, varied among species according to the use of their hydraulic habitat, with species using deep habitats exhibiting the highest values. 4. These general relationships between hydraulics and traits may be of importance in community ecology to develop predictive models to understand how fish communities change with the hydraulic environment.     

Louder Songs can Enhance Attractiveness of Old Male Crickets (Gryllus Bimaculatus)

Female crickets (Gryllidae) often rely on the quality of male acoustic signals when choosing a potential mate. This quality can be determined by the frequency and temporal structure of the calling song, and both these characteristics are known to change as males grow old. In addition, female choice is influenced by call amplitude, which is primarily a function of the distance between a singing male and the recipient female. In this study, we use a binary choice experimental design to test whether an old male, whose song appeared to be less attractive in terms of its frequency and temporal structure, may benefit from its increased amplitude. We demonstrate that increased amplitude does improve attractiveness of the calling song chirped by an older male. We also show that female preference for young males does not change with female age. These findings are discussed in light of possible behavioral strategies and spatial distribution of young and old males in the field.     

Reverse engineering of force integration during mitosis in the Drosophila embryo

The mitotic spindle is a complex macromolecular machine that coordinates accurate chromosome segregation. The spindle accomplishes its function using forces generated by microtubules (MTs) and multiple molecular motors, but how these forces are integrated remains unclear, since the temporal activation profiles and the mechanical characteristics of the relevant motors are largely unknown. Here, we developed a computational search algorithm that uses experimental measurements to ‘reverse engineer’ molecular mechanical machines. Our algorithm uses measurements of length time series for wild‐type and experimentally perturbed spindles to identify mechanistic models for coordination of the mitotic force generators in Drosophila embryo spindles. The search eliminated thousands of possible models and identified six distinct strategies for MT–motor integration that agree with available data. Many features of these six predicted strategies are conserved, including a persistent kinesin‐5‐driven sliding filament mechanism combined with the anaphase B‐specific inhibition of a kinesin‐13 MT depolymerase on spindle poles. Such conserved features allow predictions of force–velocity characteristics and activation–deactivation profiles of key mitotic motors. Identified differences among the six predicted strategies regarding the mechanisms of prometaphase and anaphase spindle elongation suggest future experiments.     

Stochastic prediction in pursuit tracking: An experimental test of adaptive model theory

In this paper we test the proposition that in pursuit tracking, subjects compute stochastic (statistical) models of the temporal variations in position of the target and use these models to forecast target position for at least a response time interval into the future. A computer simulation of a human operator employing stochastic model prediction of target position is used to generate a synthetic pursuit tracking response signal. Actual pursuit tracking response signals are measured from 10 normal subjects using the same stimulus signal. Cross correlation and spectral analysis are employed to compute gain and phase frequency response characteristics for both synthetic and actual tracking data. The similarity of the gain and phase curves for synthetic and actual data provides compelling evidence in support of the proposition.