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 Concept Videos

Competition02:34

Competition

25.5K
When organisms require the same limited resources within an environment, they may have to compete for them. Competition is a net-negative interaction. Even if two competing individuals or populations do not interact directly, the overall fitness of both competitors is lowered as a result of not having full access to the limited resource.
25.5K
Manipulation and Analysis01:21

Manipulation and Analysis

338
GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
338
Microbial Interactions: Competition01:26

Microbial Interactions: Competition

74
Microbial competition is an ecological interaction in which microorganisms vie for limited resources within shared environments. These resources may include nutrients, space, or light, depending on the system. The intensity and outcome of competition are influenced by the environmental context, such as nutrient availability, spatial constraints, and the diversity of microbial species present. These competitive interactions significantly influence the structure, function, and resilience of...
74
Selected Data About Geographic Locations01:25

Selected Data About Geographic Locations

337
Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
337
Design Example: Alignment of a Road Line Using GIS01:17

Design Example: Alignment of a Road Line Using GIS

431
The alignment of a road line using Geographic Information Systems (GIS) is a critical process in civil engineering, combining advanced technology with practical decision-making. This methodology begins with the collection of geospatial data, including information on land cover, geomorphology, drainage patterns, slope, and contour details. Such data is typically acquired through satellite imagery and GIS tools, offering a comprehensive understanding of the terrain.Once the data is gathered, it...
431
Levels of Use of a GIS01:29

Levels of Use of a GIS

471
Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...
471

You might also read

Related Articles

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

Sort by
Same author

Cascading social-ecological benefits of biodiversity for agriculture.

Current biology : CB·2026
Same author

Trophic cascades drive sustainability in the agricultural heritage rice-fish coculture system.

Current biology : CB·2026
Same author

Mechanistic links between coexistence, productivity, and stability in experimental grasslands.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Predicting temporal stability and resilience from resistance and recovery.

Nature·2026
Same author

Linking Biotic Interactions to Species Stability.

Ecology letters·2026
Same author

Trophic cascades drive sustainability in the agricultural heritage rice-fish coculture system.

Current biology : CB·2026

Related Experiment Video

Updated: Apr 19, 2026

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.6K

A graphical-mechanistic approach to spatial resource competition.

Bart Haegeman1, Michel Loreau

  • 1Centre for Biodiversity Theory and Modelling, Station d'Ecologie Expérimentale du Centre National de la Recherche Scientifique (CNRS), 2 Route du CNRS, 09200 Moulis, France.

The American Naturalist
|January 7, 2015
PubMed
Summary
This summary is machine-generated.

This study introduces a graphical theory to unify ecological coexistence mechanisms. It demonstrates how dispersal and resource competition interact to shape metacommunity structure and species diversity.

More Related Videos

The Spatial Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition
05:15

The Spatial Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition

Published on: February 19, 2018

11.5K
Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks
06:57

Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks

Published on: August 9, 2016

12.0K

Related Experiment Videos

Last Updated: Apr 19, 2026

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.6K
The Spatial Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition
05:15

The Spatial Memory Game: Testing the Relationship Between Spatial Language, Object Knowledge, and Spatial Cognition

Published on: February 19, 2018

11.5K
Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks
06:57

Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks

Published on: August 9, 2016

12.0K

Area of Science:

  • Ecology
  • Theoretical Ecology
  • Community Ecology

Background:

  • Ecological communities exhibit complex structures due to processes acting across multiple spatial scales.
  • Understanding the interplay between local competition and regional dispersal is crucial for metacommunity dynamics.

Purpose of the Study:

  • To develop a simple graphical theory unifying local resource competition and regional dispersal effects.
  • To analyze metacommunity equilibrium composition using a novel graphical construction.

Main Methods:

  • A metacommunity model with two habitat patches and competing consumers for a distributed resource was employed.
  • Zero net growth isoclines (ZNGIs) were adapted to incorporate dispersal characteristics.
  • Graphical analysis was used to determine equilibrium metacommunity composition.

Main Results:

  • A species' ZNGI was shown to be dependent on its dispersal traits.
  • This dependence provides a unified framework for various dispersal-mediated coexistence mechanisms.
  • The theory was illustrated with examples including species-specific, asymmetric, and resource-dependent dispersal.

Conclusions:

  • The graphical theory offers a powerful tool for understanding metacommunity assembly and stability.
  • Dispersal is a key factor that can be integrated with competition theory to explain coexistence.
  • This approach simplifies the study of complex ecological interactions across spatial scales.