scholarly journals Fire spread and the issue of community-level selection in the evolution of flammability

2018 ◽  
Vol 15 (147) ◽  
pp. 20180444 ◽  
Author(s):  
Emmanuel Schertzer ◽  
A. Carla Staver

Whether plants can evolve to promote flammability is controversial. Ecologically, fire only spreads in landscapes when many plants are flammable, but collective behaviours among large groups are difficult to evolve at the individual level. Here, we formulate a model that examines how flammability can spread from rarity, combining individual-level costs and payoffs of flammability with landscape-level fire spread, sufficiently generic to analogize flammability among grasses, Mediterranean systems, and others. We found that fire-prone and fire-suppressing landscapes, composed of flammable and non-flammable plants, respectively, were alternatively stable in some environments, and flammability therefore only increased from rarity in environments when fire-proneness was the only stable state. Thus, fire–vegetation feedbacks alone probably did not drive the evolution and spread of flammability. However, evolution of flammability did promote fire-proneness in temporally and spatially heterogeneous environments: when flammable plants already occupied some substantial fraction of a fire-prone landscape, a positive feedback with fire could maintain flammability in a decreasingly favourable environment, and fire feedbacks could expand the distribution of flammability traits from fire-prone into fire-suppressing areas in a heterogeneous landscape. Thus, fire feedbacks could potentially have promoted the widespread invasion and persistence of flammability traits to their current widespread prominence.

2021 ◽  
pp. 213-228
Author(s):  
Viktoriia Radchuk ◽  
Stephanie Kramer-Schadt ◽  
Uta Berger ◽  
Cédric Scherer ◽  
Pia Backmann ◽  
...  

Individual-based models (IBMs, also known as agent-based models) are mechanistic models in which demographic population trends emerge from processes at the individual level. IBMs are used instead of more aggregated approaches whenever one or more of the following aspects are deemed too relevant to be ignored: intraspecific trait variation, local interactions, adaptive behaviour, and response to spatially and temporally heterogeneous environments, which often results in nonlinear feedbacks. IBMs offer a high degree of flexibility and therefore vary widely in structure and resolution, depending on the research question, system under investigation, and available data. Data used to parameterise an IBM can be divided into two categories: species and environmental data. Unlike other model types, qualitative empirical knowledge can be taken into account via probabilistic rules. IBM flexibility is often associated with higher number of parameters and hence higher uncertainty; therefore sensitivity analysis and validation are extremely important tools for analysing these models. The chapter presents three examples: a vole–mustelid model used to understand the mechanisms underlying population cycles in rodents; a wild boar–virus model to study persistence of wildlife diseases in heterogeneous landscapes; and a wild tobacco-moth caterpillar model to study emergence of delayed chemical plant defence against insect herbivores. These examples demonstrate the ability of IBMs to decipher mechanisms driving observed phenomena at the population level and their role in planning applied conservation measures. IBMs typically require more data and effort than other model types, but rewards in terms of structural realism, understanding, and decision support are high.


2008 ◽  
Vol 6 (30) ◽  
pp. 111-122 ◽  
Author(s):  
Simona Hapca ◽  
John W Crawford ◽  
Iain M Young

The characterization of the dispersal of populations of non-identical individuals is relevant to most ecological and epidemiological processes. In practice, the movement is quantified by observing relatively few individuals, and averaging to estimate the rate of dispersal of the population as a whole. Here, we show that this can lead to serious errors in the predicted movement of the population if the individuals disperse at different rates. We develop a stochastic model for the diffusion of heterogeneous populations, inspired by the movement of the parasitic nematode Phasmarhabditis hermaphrodita . Direct observations of this nematode in homogeneous and heterogeneous environments reveal a large variation in individual behaviour within the population as reflected initially in the speed of the movement. Further statistical analysis shows that the movement is characterized by temporal correlations and in a heterogeneously structured environment the correlations that occur are of shorter range compared with those in a homogeneous environment. Therefore, by using the first-order correlated random walk techniques, we derive an effective diffusion coefficient for each individual, and show that there is a significant variation in this parameter among the population that follows a gamma distribution. Based on these findings, we build a new dispersal model in which we maintain the classical assumption that individual movement can be described by normal diffusion, but due to the variability in individual dispersal rates, the diffusion coefficient is not constant at the population level and follows a continuous distribution. The conclusions and methodology presented are relevant to any heterogeneous population of individuals with widely different diffusion rates.


2020 ◽  
Vol 51 (3) ◽  
pp. 183-198
Author(s):  
Wiktor Soral ◽  
Mirosław Kofta

Abstract. The importance of various trait dimensions explaining positive global self-esteem has been the subject of numerous studies. While some have provided support for the importance of agency, others have highlighted the importance of communion. This discrepancy can be explained, if one takes into account that people define and value their self both in individual and in collective terms. Two studies ( N = 367 and N = 263) examined the extent to which competence (an aspect of agency), morality, and sociability (the aspects of communion) promote high self-esteem at the individual and the collective level. In both studies, competence was the strongest predictor of self-esteem at the individual level, whereas morality was the strongest predictor of self-esteem at the collective level.


2019 ◽  
Vol 37 (1) ◽  
pp. 18-34
Author(s):  
Edward C. Warburton

This essay considers metonymy in dance from the perspective of cognitive science. My goal is to unpack the roles of metaphor and metonymy in dance thought and action: how do they arise, how are they understood, how are they to be explained, and in what ways do they determine a person's doing of dance? The premise of this essay is that language matters at the cultural level and can be determinative at the individual level. I contend that some figures of speech, especially metonymic labels like ‘bunhead’, can not only discourage but dehumanize young dancers, treating them not as subjects who dance but as objects to be danced. The use of metonymy to sort young dancers may undermine the development of healthy self-image, impede strong identity formation, and retard creative-artistic development. The paper concludes with a discussion of the influence of metonymy in dance and implications for dance educators.


Author(s):  
Pauline Oustric ◽  
Kristine Beaulieu ◽  
Nuno Casanova ◽  
Francois Husson ◽  
Catherine Gibbons ◽  
...  

2020 ◽  
Author(s):  
Christopher James Hopwood ◽  
Ted Schwaba ◽  
Wiebke Bleidorn

Personal concerns about climate change and the environment are a powerful motivator of sustainable behavior. People’s level of concern varies as a function of a variety of social and individual factors. Using data from 58,748 participants from a nationally representative German sample, we tested preregistered hypotheses about factors that impact concerns about the environment over time. We found that environmental concerns increased modestly from 2009-2017 in the German population. However, individuals in middle adulthood tended to be more concerned and showed more consistent increases in concern over time than younger or older people. Consistent with previous research, Big Five personality traits were correlated with environmental concerns. We present novel evidence that increases in concern were related to increases in the personality traits neuroticism and openness to experience. Indeed, changes in openness explained roughly 50% of the variance in changes in environmental concerns. These findings highlight the importance of understanding the individual level factors associated with changes in environmental concerns over time, towards the promotion of more sustainable behavior at the individual level.


2020 ◽  
Author(s):  
Keith Payne ◽  
Heidi A. Vuletich ◽  
Kristjen B. Lundberg

The Bias of Crowds model (Payne, Vuletich, & Lundberg, 2017) argues that implicit bias varies across individuals and across contexts. It is unreliable and weakly associated with behavior at the individual level. But when aggregated to measure context-level effects, the scores become stable and predictive of group-level outcomes. We concluded that the statistical benefits of aggregation are so powerful that researchers should reconceptualize implicit bias as a feature of contexts, and ask new questions about how implicit biases relate to systemic racism. Connor and Evers (2020) critiqued the model, but their critique simply restates the core claims of the model. They agreed that implicit bias varies across individuals and across contexts; that it is unreliable and weakly associated with behavior at the individual level; and that aggregating scores to measure context-level effects makes them more stable and predictive of group-level outcomes. Connor and Evers concluded that implicit bias should be considered to really be noisily measured individual construct because the effects of aggregation are merely statistical. We respond to their specific arguments and then discuss what it means to really be a feature of persons versus situations, and multilevel measurement and theory in psychological science more broadly.


2019 ◽  
pp. 78-106
Author(s):  
Aruna Dayanatha ◽  
J A S K Jayakody

Information system (IS) projects have been seen to be failing at an alarmingly high rate. The prevailing explanations of IS failure have had only a limited success. Thus, the time may be right to look at the reasons for IS failure through an alternative perspective. This paper proposes that IS success should be explained in terms of managerial leadership intervention, from the sensemaking perspective. Managers are responsible for workplace outcomes; thus, it may be appropriate to explain their role in IS success as well. The sensemaking perspective can explain IS success through holistic user involvement, a concept which critiques of existing explanations have stated to be a requirement for explaining IS failure. This paper proposes a framework combining the theory of enactment and leadership enactment to theorize managerial leadership intervention for “IS success.” The proposed explanation postulates that the managerial leader’s envisioning of the future transaction set influences the liberation of the follower and cast enactment, while liberating followers and cast enactment constitute manager sensegiving. The managerial leader’s sense-giving influences follower sensemaking. Follower sensemaking, under the influence of managerial sensegiving, will lead to followers’ IS acceptance, and that constitutes IS success at the individual level. Further, collective level IS acceptance constitutes IS adaption/success, and this will influence the leader’s sensegiving, for the next round of sensemaking.


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