scholarly journals A methodological framework to predict the individual and population‐level distributions from tracking data

Ecography ◽  
2021 ◽  
Author(s):  
Philippine Chambault ◽  
Tarek Hattab ◽  
Pascal Mouquet ◽  
Touria Bajjouk ◽  
Claire Jean ◽  
...  
2013 ◽  
Vol 59 (4) ◽  
pp. 485-505 ◽  
Author(s):  
Jon E. Brommer

Abstract Individual-based studies allow quantification of phenotypic plasticity in behavioural, life-history and other labile traits. The study of phenotypic plasticity in the wild can shed new light on the ultimate objectives (1) whether plasticity itself can evolve or is constrained by its genetic architecture, and (2) whether plasticity is associated to other traits, including fitness (selection). I describe the main statistical approach for how repeated records of individuals and a description of the environment (E) allow quantification of variation in plasticity across individuals (IxE) and genotypes (GxE) in wild populations. Based on a literature review of life-history and behavioural studies on plasticity in the wild, I discuss the present state of the two objectives listed above. Few studies have quantified GxE of labile traits in wild populations, and it is likely that power to detect statistically significant GxE is lacking. Apart from the issue of whether it is heritable, plasticity tends to correlate with average trait expression (not fully supported by the few genetic estimates available) and may thus be evolutionary constrained in this way. Individual-specific estimates of plasticity tend to be related to other traits of the individual (including fitness), but these analyses may be anti-conservative because they predominantly concern stats-on-stats. Despite the increased interest in plasticity in wild populations, the putative lack of power to detect GxE in such populations hinders achieving general insights. I discuss possible steps to invigorate the field by moving away from simply testing for presence of GxE to analyses that ‘scale up’ to population level processes and by the development of new behavioural theory to identify quantitative genetic parameters which can be estimated.


2017 ◽  
Vol 26 (6) ◽  
pp. 579-583 ◽  
Author(s):  
T. D. Cosco ◽  
K. Howse ◽  
C. Brayne

The extension of life does not appear to be slowing, representing a great achievement for mankind as well as a challenge for ageing populations. As we move towards an increasingly older population we will need to find novel ways for individuals to make the best of the challenges they face, as the likelihood of encountering some form of adversity increases with age. Resilience theories share a common idea that individuals who manage to navigate adversity and maintain high levels of functioning demonstrate resilience. Traditional models of healthy ageing suggest that having a high level of functioning across a number of domains is a requirement. The addition of adversity to the healthy ageing model via resilience makes this concept much more accessible and more amenable to the ageing population. Through asset-based approaches, such as the invoking of individual, social and environmental resources, it is hoped that greater resilience can be fostered at a population level. Interventions aimed at fostering greater resilience may take many forms; however, there is great potential to increase social and environmental resources through public policy interventions. The wellbeing of the individual must be the focus of these efforts; quality of life is an integral component to the enjoyment of additional years and should not be overlooked. Therefore, it will become increasingly important to use resilience as a public health concept and to intervene through policy to foster greater resilience by increasing resources available to older people. Fostering wellbeing in the face of increasing adversity has significant implications for ageing individuals and society as a whole.


2017 ◽  
Author(s):  
Alex Mesoudi

AbstractHow do migration and acculturation (i.e. psychological or behavioral change resulting from migration) affect within- and between-group cultural variation? Here I answer this question by drawing analogies between genetic and cultural evolution. Population genetic models show that migration rapidly breaks down between-group genetic structure. In cultural evolution, however, migrants or their descendants can acculturate to local behaviors via social learning processes such as conformity, potentially preventing migration from eliminating between-group cultural variation. An analysis of the empirical literature on migration suggests that acculturation is common, with second and subsequent migrant generations shifting, sometimes substantially, towards the cultural values of the adopted society. Yet there is little understanding of the individual-level dynamics that underlie these population-level shifts. To explore this formally, I present models quantifying the effect of migration and acculturation on between-group cultural variation, for both neutral and costly cooperative traits. In the models, between-group cultural variation, measured using F statistics, is eliminated by migration and maintained by conformist acculturation. The extent of acculturation is determined by the strength of conformist bias and the number of demonstrators from whom individuals learn. Acculturation is countered by assortation, the tendency for individuals to preferentially interact with culturally-similar others. Unlike neutral traits, cooperative traits can additionally be maintained by payoff-biased social learning, but only in the presence of strong sanctioning institutions. Overall, the models show that surprisingly little conformist acculturation is required to maintain realistic amounts of between-group cultural diversity. While these models provide insight into the potential dynamics of acculturation and migration in cultural evolution, they also highlight the need for more empirical research into the individual-level learning biases that underlie migrant acculturation.


2021 ◽  
Author(s):  
Christen Herbert Fleming ◽  
Iman Deznabi ◽  
Shauhin Alavi ◽  
Margaret C. Crofoot ◽  
Ben T. Hirsch ◽  
...  

· Home-range estimates are a common product of animal tracking data, as each range informs on the area needed by a given individual. Population-level inference on home-range areas—where multiple individual home-ranges are considered to be sampled from a population—is also important to evaluate changes over time, space, or covariates, such as habitat quality or fragmentation, and for comparative analyses of species averages. Population-level home-range parameters have traditionally been estimated by first assuming that the input tracking data were sampled independently when calculating home ranges via conventional kernel density estimation (KDE) or minimal convex polygon (MCP) methods, and then assuming that those individual home ranges were measured exactly when calculating the population-level estimates. This conventional approach does not account for the temporal autocorrelation that is inherent in modern tracking data, nor for the uncertainties of each individual home-range estimate, which are often large and heterogeneous. · Here, we introduce a statistically and computationally efficient framework for the population-level analysis of home-range areas, based on autocorrelated kernel density estimation (AKDE), that can account for variable temporal autocorrelation and estimation uncertainty. · We apply our method to empirical examples on lowland tapir (Tapirus terrestris), kinkajou (Potos flavus), white‐nosed coati (Nasua narica), white-faced capuchin monkey (Cebus capucinus), and spider monkey (Ateles geoffroyi), and quantify differences between species, environments, and sexes. · Our approach allows researchers to more accurately compare different populations with different movement behaviors or sampling schedules, while retaining statistical precision and power when individual home-range uncertainties vary. Finally, we emphasize the estimation of effect sizes when comparing populations, rather than mere significance tests.


2021 ◽  
Author(s):  
Shinya Ito ◽  
Yufei Si ◽  
Alan M. Litke ◽  
David A. Feldheim

AbstractSensory information from different modalities is processed in parallel, and then integrated in associative brain areas to improve object identification and the interpretation of sensory experiences. The Superior Colliculus (SC) is a midbrain structure that plays a critical role in integrating visual, auditory, and somatosensory input to assess saliency and promote action. Although the response properties of the individual SC neurons to visuoauditory stimuli have been characterized, little is known about the spatial and temporal dynamics of the integration at the population level. Here we recorded the response properties of SC neurons to spatially restricted visual and auditory stimuli using large-scale electrophysiology. We then created a general, population-level model that explains the spatial, temporal, and intensity requirements of stimuli needed for sensory integration. We found that the mouse SC contains topographically organized visual and auditory neurons that exhibit nonlinear multisensory integration. We show that nonlinear integration depends on properties of auditory but not visual stimuli. We also find that a heuristically derived nonlinear modulation function reveals conditions required for sensory integration that are consistent with previously proposed models of sensory integration such as spatial matching and the principle of inverse effectiveness.


2018 ◽  
Author(s):  
William D. Chronister ◽  
Margaret B. Wierman ◽  
Ian E. Burbulis ◽  
Matthew J. Wolpert ◽  
Mark F. Haakenson ◽  
...  

AbstractMegabase-scale somatic copy number variants (CNVs) alter allelic diversity in a subset of human neocortical neurons. Reported frequencies of CNV neurons range from ∼5% of neurons in some individuals to greater than 30% in other individuals. Genome-wide and familial studies implicitly assume a constant brain genome when assessing the genetic risk architecture of neurological disease, thus it is critical to determine whether divergent reports of CNV neuron frequency reflect normal individual variation or technical differences between approaches. We generated a new dataset of over 800 human neurons from 5 neurotypical individuals and developed a computational approach that measures single cell library quality based on Bayesian Information Criterion and identifies integer-like variant segments from population-level statistics. A brain CNV atlas was assembled using our new dataset and published data from 10 additional neurotypical individuals. This atlas reveals that the frequency of neocortical CNV neurons varies widely among individuals, but that this variability is not readily accounted for by tissue quality or CNV detection approach. Rather, the age of the individual is anti-correlated with CNV neuron frequency. Fewer CNV neurons are observed in aged individuals than young individuals.


2012 ◽  
Vol 13 (4) ◽  
pp. 178 ◽  
Author(s):  
D Besada ◽  
G Van Cutsem ◽  
E Goemaere ◽  
N Ford ◽  
H Bygrave ◽  
...  

In a previous issue of the Southern African Journal of HIV Medicine, Pillay and Black summarised the trade-offs of the safety of efavirenz use in pregnancy (Pillay P, Black V. Safety, strength and simplicity of efavirenz in pregnancy. Southern African Journal of HIV Medicine 2012;13(1):28-33.). Highlighting the benefits of the World Health Organization’s proposed options for the prevention of mother-to-child transmission (PMTCT) of HIV, the authors argued that the South African government should adopt Option B as national PMTCT policy and pilot projects implementing Option B+ as a means of assessing the individual- and population-level effect of the intervention. We echo this call and further propose that the option to remain on lifelong antiretroviral therapy, effectively adopting PMTCT Option B+, be offered to pregnant women following the cessation of breastfeeding, for their own health, following the provision of counselling on associated benefits and risks. Here we highlight the benefits of Options B and B+.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
José Hernández-Orallo ◽  
Bao Sheng Loe ◽  
Lucy Cheke ◽  
Fernando Martínez-Plumed ◽  
Seán Ó hÉigeartaigh

AbstractSuccess in all sorts of situations is the most classical interpretation of general intelligence. Under limited resources, however, the capability of an agent must necessarily be limited too, and generality needs to be understood as comprehensive performance up to a level of difficulty. The degree of generality then refers to the way an agent’s capability is distributed as a function of task difficulty. This dissects the notion of general intelligence into two non-populational measures, generality and capability, which we apply to individuals and groups of humans, other animals and AI systems, on several cognitive and perceptual tests. Our results indicate that generality and capability can decouple at the individual level: very specialised agents can show high capability and vice versa. The metrics also decouple at the population level, and we rarely see diminishing returns in generality for those groups of high capability. We relate the individual measure of generality to traditional notions of general intelligence and cognitive efficiency in humans, collectives, non-human animals and machines. The choice of the difficulty function now plays a prominent role in this new conception of generality, which brings a quantitative tool for shedding light on long-standing questions about the evolution of general intelligence and the evaluation of progress in Artificial General Intelligence.


2021 ◽  
Vol 12 ◽  
Author(s):  
Chao Li ◽  
Hugh Barclay ◽  
Bernard Roitberg ◽  
Robert Lalonde

Compensatory growth has been observed in forests, and it also appears as a common phenomenon in biology. Though it sometimes takes different names, the essential meanings are the same, describing the accelerated growth of organisms when recovering from a period of unfavorable conditions such as tissue damage at the individual level and partial mortality at the population level. Diverse patterns of compensatory growth have been reported in the literature, ranging from under-, to compensation-induced-equality, and to over-compensation. In this review and synthesis, we provide examples of analogous compensatory growth from different fields, clarify different meanings of it, summarize its current understanding and modeling efforts, and argue that it is possible to develop a state-dependent model under the conceptual framework of compensatory growth, aimed at explaining and predicting diverse observations according to different disturbances and environmental conditions. When properly applied, compensatory growth can benefit different industries and human society in various forms.


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