scholarly journals Trade-Offs and Coexistence in Fluctuating Environments: Evidence for a Key Dispersal-Fecundity Trade-Off in Five Nonpollinating Fig Wasps

2015 ◽  
Vol 186 (1) ◽  
pp. 151-158 ◽  
Author(s):  
A. Bradley Duthie ◽  
Karen C. Abbott ◽  
John D. Nason
2016 ◽  
Author(s):  
Shraddha Karve ◽  
Devika Bhave ◽  
Dhanashri Nevgi ◽  
Sutirth Dey

AbstractIn nature, organisms are simultaneously exposed to multiple stresses (i.e. complex environments) that often fluctuate unpredictably. While both these factors have been studied in isolation, the interaction of the two remains poorly explored. To address this issue, we selected laboratory populations ofEscherichia coliunder complex (i.e. stressful combinations of pH, H2O2and NaCl) unpredictably fluctuating environments for ~900 generations. We compared the growth rates and the corresponding trade-off patterns of these populations to those that were selected under constant values of the component stresses (i.e. pH, H2O2and NaCl) for the same duration. The fluctuation-selected populations had greater mean growth rate and lower variation for growth rate over all the selection environments experienced. However, while the populations selected under constant stresses experienced severe tradeoffs in many of the environments other than those in which they were selected, the fluctuation-selected populations could by-pass the across-environment trade-offs completely. Interestingly, trade-offs were found between growth rates and carrying capacities. The results suggest that complexity and fluctuations can strongly affect the underlying trade-off structure in evolving populations.


2016 ◽  
Author(s):  
Shraddha Madhav Karve ◽  
Devika Bhave ◽  
Dhanashri Nevgi ◽  
Sutirth Dey

In nature, organisms are simultaneously exposed to multiple stresses (i.e. complex environments) that often fluctuate unpredictably. While both these factors have been studied in isolation, the interaction of the two remains poorly explored. To address this issue, we selected laboratory populations of Escherichia coli under complex (i.e. stressful combinations of pH, H2O2 and NaCl) unpredictably fluctuating environments for ~900 generations. We compared the growth rates and the corresponding trade-off patterns of these populations to those that were selected under constant values of the component stresses (i.e. pH, H2O2 and NaCl) for the same duration. The fluctuation-selected populations had greater mean growth rate and lower variation for growth rate over all the selection environments experienced. However, while the populations selected under constant stresses experienced trade-offs in the environments other than those in which they were selected, the fluctuation-selected populations could by-pass the across-environment trade-offs almost entirely. Interestingly, trade-offs were found between growth rates and carrying capacities. The results suggest that complexity and fluctuations can strongly affect the underlying trade-off structure in evolving populations.


2012 ◽  
Vol 11 (3) ◽  
pp. 118-126 ◽  
Author(s):  
Olive Emil Wetter ◽  
Jürgen Wegge ◽  
Klaus Jonas ◽  
Klaus-Helmut Schmidt

In most work contexts, several performance goals coexist, and conflicts between them and trade-offs can occur. Our paper is the first to contrast a dual goal for speed and accuracy with a single goal for speed on the same task. The Sternberg paradigm (Experiment 1, n = 57) and the d2 test (Experiment 2, n = 19) were used as performance tasks. Speed measures and errors revealed in both experiments that dual as well as single goals increase performance by enhancing memory scanning. However, the single speed goal triggered a speed-accuracy trade-off, favoring speed over accuracy, whereas this was not the case with the dual goal. In difficult trials, dual goals slowed down scanning processes again so that errors could be prevented. This new finding is particularly relevant for security domains, where both aspects have to be managed simultaneously.


2019 ◽  
Author(s):  
Anna Katharina Spälti ◽  
Mark John Brandt ◽  
Marcel Zeelenberg

People often have to make trade-offs. We study three types of trade-offs: 1) "secular trade-offs" where no moral or sacred values are at stake, 2) "taboo trade-offs" where sacred values are pitted against financial gain, and 3) "tragic trade-offs" where sacred values are pitted against other sacred values. Previous research (Critcher et al., 2011; Tetlock et al., 2000) demonstrated that tragic and taboo trade-offs are not only evaluated by their outcomes, but are also evaluated based on the time it took to make the choice. We investigate two outstanding questions: 1) whether the effect of decision time differs for evaluations of decisions compared to decision makers and 2) whether moral contexts are unique in their ability to influence character evaluations through decision process information. In two experiments (total N = 1434) we find that decision time affects character evaluations, but not evaluations of the decision itself. There were no significant differences between tragic trade-offs and secular trade-offs, suggesting that the decisions structure may be more important in evaluations than moral context. Additionally, the magnitude of the effect of decision time shows us that decision time, may be of less practical use than expected. We thus urge, to take a closer examination of the processes underlying decision time and its perception.


2019 ◽  
Author(s):  
Kasper Van Mens ◽  
Joran Lokkerbol ◽  
Richard Janssen ◽  
Robert de Lange ◽  
Bea Tiemens

BACKGROUND It remains a challenge to predict which treatment will work for which patient in mental healthcare. OBJECTIVE In this study we compare machine algorithms to predict during treatment which patients will not benefit from brief mental health treatment and present trade-offs that must be considered before an algorithm can be used in clinical practice. METHODS Using an anonymized dataset containing routine outcome monitoring data from a mental healthcare organization in the Netherlands (n = 2,655), we applied three machine learning algorithms to predict treatment outcome. The algorithms were internally validated with cross-validation on a training sample (n = 1,860) and externally validated on an unseen test sample (n = 795). RESULTS The performance of the three algorithms did not significantly differ on the test set. With a default classification cut-off at 0.5 predicted probability, the extreme gradient boosting algorithm showed the highest positive predictive value (ppv) of 0.71(0.61 – 0.77) with a sensitivity of 0.35 (0.29 – 0.41) and area under the curve of 0.78. A trade-off can be made between ppv and sensitivity by choosing different cut-off probabilities. With a cut-off at 0.63, the ppv increased to 0.87 and the sensitivity dropped to 0.17. With a cut-off of at 0.38, the ppv decreased to 0.61 and the sensitivity increased to 0.57. CONCLUSIONS Machine learning can be used to predict treatment outcomes based on routine monitoring data.This allows practitioners to choose their own trade-off between being selective and more certain versus inclusive and less certain.


Author(s):  
Steven Bernstein

This commentary discusses three challenges for the promising and ambitious research agenda outlined in the volume. First, it interrogates the volume’s attempts to differentiate political communities of legitimation, which may vary widely in composition, power, and relevance across institutions and geographies, with important implications not only for who matters, but also for what gets legitimated, and with what consequences. Second, it examines avenues to overcome possible trade-offs from gains in empirical tractability achieved through the volume’s focus on actor beliefs and strategies. One such trade-off is less attention to evolving norms and cultural factors that may underpin actors’ expectations about what legitimacy requires. Third, it addresses the challenge of theory building that can link legitimacy sources, (de)legitimation practices, audiences, and consequences of legitimacy across different types of institutions.


Author(s):  
Lisa Best ◽  
Kimberley Fung-Loy ◽  
Nafiesa Ilahibaks ◽  
Sara O. I. Ramirez-Gomez ◽  
Erika N. Speelman

AbstractNowadays, tropical forest landscapes are commonly characterized by a multitude of interacting institutions and actors with competing land-use interests. In these settings, indigenous and tribal communities are often marginalized in landscape-level decision making. Inclusive landscape governance inherently integrates diverse knowledge systems, including those of indigenous and tribal communities. Increasingly, geo-information tools are recognized as appropriate tools to integrate diverse interests and legitimize the voices, values, and knowledge of indigenous and tribal communities in landscape governance. In this paper, we present the contribution of the integrated application of three participatory geo-information tools to inclusive landscape governance in the Upper Suriname River Basin in Suriname: (i) Participatory 3-Dimensional Modelling, (ii) the Trade-off! game, and (iii) participatory scenario planning. The participatory 3-dimensional modelling enabled easy participation of community members, documentation of traditional, tacit knowledge and social learning. The Trade-off! game stimulated capacity building and understanding of land-use trade-offs. The participatory scenario planning exercise helped landscape actors to reflect on their own and others’ desired futures while building consensus. Our results emphasize the importance of systematically considering tool attributes and key factors, such as facilitation, for participatory geo-information tools to be optimally used and fit with local contexts. The results also show how combining the tools helped to build momentum and led to diverse yet complementary insights, thereby demonstrating the benefits of integrating multiple tools to address inclusive landscape governance issues.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yoav Kolumbus ◽  
Noam Nisan

AbstractWe study the effectiveness of tracking and testing policies for suppressing epidemic outbreaks. We evaluate the performance of tracking-based intervention methods on a network SEIR model, which we augment with an additional parameter to model pre-symptomatic and asymptomatic individuals, and study the effectiveness of these methods in combination with or as an alternative to quarantine and global lockdown policies. Our focus is on the basic trade-off between human-lives lost and economic costs, and on how this trade-off changes under different quarantine, lockdown, tracking, and testing policies. Our main findings are as follows: (1) Tests combined with patient quarantines reduce both economic costs and mortality, however, an extensive-scale testing capacity is required to achieve a significant improvement. (2) Tracking significantly reduces both economic costs and mortality. (3) Tracking combined with a moderate testing capacity can achieve containment without lockdowns. (4) In the presence of a flow of new incoming infections, dynamic “On–Off” lockdowns are more efficient than fixed lockdowns. In this setting as well, tracking strictly improves efficiency. The results show the extreme usefulness of policies that combine tracking and testing for reducing mortality and economic costs, and their potential to contain outbreaks without imposing any social distancing restrictions. This highlights the difficult social question of trading-off these gains against patient privacy, which is inevitably infringed by tracking.


2011 ◽  
Vol 20 (06) ◽  
pp. 1019-1035 ◽  
Author(s):  
SAMBHU NATH PRADHAN ◽  
M. TILAK KUMAR ◽  
SANTANU CHATTOPDHYAY

In this paper, a heuristic based on genetic algorithm to realize multi-output Boolean function as three-level AND-OR-XOR network performing area power trade-off is presented. All the previous works dealt with the minimization of number of product terms only in the two sum-of-product-expressions representing a Boolean function during AND-OR-XOR network synthesis. To the best of knowledge this is the first ever effort to incorporate total power, that is, dynamic and leakage power along with the area (in terms of number of product terms) during three-level AND-OR-XOR networks synthesis. The synthesis process, without changing the delay performance results in lesser number of product terms compared to those reported in the literature. It also enumerates the trade-offs present in the solution space for different weights associated with area, dynamic power, and leakage power of the resulting circuit.


2000 ◽  
Author(s):  
S. R. Habibi

Abstract This paper considers the design of a high performance hydrostatic actuation system referred to as the ElectroHydraulic Actuator (EHA). The expected performance of EHA and its dominant design parameters are identified by using mathematical modeling. The design parameters are classified into Direct and Indirect categories based on the measure of their accessibility to the designer. The Direct parameters are directly quantifiable and, can be linked to the performance of EHA through a set of mathematical functions. A prototype of EHA has been produced and described. The mathematical functions linking performance to design parameters are used to investigate design trade-offs. Design improvements to the prototype are suggested by using constrained quadratic programming.


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