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Related Concept Videos

Evolutionary Psychology01:20

Evolutionary Psychology

Evolutionary psychology explores the origins of human behavior and mental processes by framing them within the context of natural selection, a theory famously propounded by Charles Darwin. This field asserts that many behaviors common across human societies — ranging from instinctive fear reactions to complex social interactions — arose as evolutionary adaptations. These adaptations enhanced the survival and reproductive success of our ancestors, thereby becoming embedded in the human psyche...
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least squares (OLS)...
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Ecological Niches02:02

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Ecological Disturbance02:26

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Limits to Natural Selection01:38

Limits to Natural Selection

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Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
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Predictive ecology: systems approaches.

Matthew R Evans1, Ken J Norris, Tim G Benton

  • 1Centre for Ecology and Conservation, School of Biosciences, University of Exeter, Cornwall Campus, Penryn, Cornwall TR10 9EZ, UK. m.evans@qmul.ac.uk

Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences
|December 7, 2011
PubMed
Summary
This summary is machine-generated.

Ecological forecasting requires more predictive models to understand environmental change impacts. Integrating evolutionary insights and ecoinformatics is key for accurate predictions and societal adaptation strategies.

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Area of Science:

  • Ecology
  • Environmental Science
  • Evolutionary Biology

Background:

  • Anthropogenic environmental change poses significant threats to the biological world.
  • Current ecological understanding necessitates improved predictive capabilities to forecast future system behavior.
  • Forecasting the impacts of environmental change is crucial for mitigation and adaptation.

Purpose of the Study:

  • To advance ecological forecasting by developing more predictive process-based models.
  • To integrate insights from evolutionary biology into ecological models, especially when data is scarce.
  • To explore the appropriation of tools from other disciplines like climatology and molecular systems biology for ecological modeling.

Main Methods:

  • Developing process-based ecological models that balance complexity and simplification.
  • Recognizing individuals as fundamental units in ecological systems.
  • Leveraging insights from evolutionary biology and ecoinformatics.

Main Results:

  • Process-based models are essential for forecasting ecological system behavior under environmental change.
  • Balancing model complexity and simplification is critical for accurate predictions.
  • Integrating evolutionary dynamics and individual-based approaches enhances model robustness.

Conclusions:

  • Ecology must become more predictive to address environmental change.
  • Process-based models, informed by evolution and ecoinformatics, are vital for forecasting.
  • Societal demand for understanding and managing environmental change impacts drives this scientific advancement.