Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Identifying predator-prey processes from time-series.

C Jost1, R Arditi

  • 1Ecologie des populations et communautés, Institut national agronomique Paris-Grignon, 16, rue Claude Bernard, Paris cedex 05, 75231, France.

Theoretical Population Biology
|July 20, 2000
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

[Acute treatment of pregnant women after severe trauma-a retrospective multicenter analysis].

Der Unfallchirurg·2020
Same author

Effects of polystyrene nanoparticles on the microbiota and functional diversity of enzymes in soil.

Environmental sciences Europe·2018
Same author

[A mentalization-based perspective on childhood autism treatment].

L'Encephale·2017
Same author

Impact of Modular Total Absorption Spectrometer measurements of β decay of fission products on the decay heat and reactor ν[over ¯]_{e} flux calculation.

Physical review letters·2017
Same author

Relation of the Canadian lynx cycle to a combination of weather variables: A stepwise multiple regression analysis.

Oecologia·2017
Same author

Underestimation of mutual interference of predators.

Oecologia·2017
Same journal

Statistical test to compare the linkage model and the admixture model based on central limit results.

Theoretical population biology·2026
Same journal

Threshold dynamics in age-structured distributions with expanding support: A unified mathematical framework.

Theoretical population biology·2026
Same journal

Mechanistic-statistical model for the expansion of ash dieback.

Theoretical population biology·2026
Same journal

Dynamics of an intraguild predation system with optimal foraging and harvesting.

Theoretical population biology·2026
Same journal

Impact of co-occurrent assortative mating and vertical cultural transmission on measures of genetic associations.

Theoretical population biology·2026
Same journal

The coalescent of a sample from a linear-fractional branching process.

Theoretical population biology·2026
See all related articles

Identifying the predator functional response from ecological data is challenging. Model fitting can identify the response with moderate noise, but high noise in real data may lead to incorrect conclusions about predator-prey dynamics.

Area of Science:

  • Ecology
  • Mathematical Biology
  • Population Dynamics

Background:

  • The functional response is crucial for understanding predator-prey interactions and food web dynamics.
  • Classical models often assume predator functional responses depend solely on prey abundance.
  • Emerging evidence highlights the significance of predator dependence in these interactions.

Purpose of the Study:

  • To assess the feasibility of identifying the mathematical form of the functional response from ecological time-series data.
  • To investigate the impact of observation and process errors on model identification.
  • To evaluate parameter estimation quality using differential equation fitting.

Main Methods:

  • Model-fitting techniques applied to artificial and real ecological time-series data.

Related Experiment Videos

  • Analysis of predator-prey models incorporating functional responses.
  • Simulations with varying levels of observation and process error.

    • Main Results:

    • Model identification of the functional response is possible with artificial data under moderate noise levels.
    • High noise levels, typical in real ecological time-series, can lead to misidentification of the functional response model.
    • The quality of parameter estimation is discussed in the context of data noise.

    Conclusions:

    • While model fitting shows promise for identifying functional responses, real-world data noise poses a significant challenge.
    • Careful consideration of noise is essential for accurate interpretation of predator-prey dynamics from time-series data.
    • Further research is needed to refine methods for robust functional response identification in noisy ecological systems.