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

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps11:52

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps

6.5K
The segmentation clock drives oscillatory gene expression across the pre-somitic mesoderm (PSM). Dynamic Notch activity is key to this process. We use imaging and computational analyses to extract temporal dynamics from spatial expression data to demonstrate that Delta ligand and Notch receptor expression oscillate in the vertebrate...
6.5K
Spatial Temporal Analysis of Fieldwise Flow in Microvasculature09:39

Spatial Temporal Analysis of Fieldwise Flow in Microvasculature

6.3K
To quantify microvascular flow from high speed capillary flow image sequences, we developed STAFF (Spatial Temporal Analysis of Fieldwise Flow) software. Across the full image field and over time, STAFF evaluates flow velocities and generates a sequence of color-coded spatial maps for visualization and tabular output for quantitative...
6.3K
Measuring Spatial and Temporal Ca2+ Signals in Arabidopsis Plants10:12

Measuring Spatial and Temporal Ca2+ Signals in Arabidopsis Plants

12.6K
Ca2+ signaling regulates diverse biological processes in plants. Here we present approaches for monitoring abiotic stress induced spatial and temporal Ca2+ signals in Arabidopsis cells and tissues using the genetically encoded Ca2+ indicators Aequorin or...
12.6K
Spatial and Temporal Control of T Cell Activation Using a Photoactivatable Agonist07:48

Spatial and Temporal Control of T Cell Activation Using a Photoactivatable Agonist

6.6K
This protocol describes an imaging-based method to activate T lymphocytes using photoactivatable peptide-MHC, enabling precise spatiotemporal control of T cell...
6.6K
Fabrication of Spatially Confined Complex Oxides08:45

Fabrication of Spatially Confined Complex Oxides

10.1K
We describe the use of pulsed laser deposition (PLD), photolithography and wire-bonding techniques to create micrometer scale complex oxides devices. The PLD is utilized to grow epitaxial thin films. Photolithography and wire-bonding techniques are introduced to create practical devices for measurement...
10.1K
Using Pharmacological Manipulation and High-precision Radio Telemetry to Study the Spatial Cognition in Free-ranging Animals08:28

Using Pharmacological Manipulation and High-precision Radio Telemetry to Study the Spatial Cognition in Free-ranging Animals

7.1K
This paper describes a novel protocol that combines the pharmacological manipulation of memory and radio telemetry to document and quantify the role of cognition in...
7.1K

You might also read

Related Articles

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

Sort by
Same author

Interspecific interactions moderate direct effects of vegetation change resulting from prescribed fires.

Scientific reports·2025
Same author

A flexible framework for N-mixture occupancy models: applications to breeding bird surveys.

Biometrics·2025
Same author

Abundance-mediated species interactions.

Ecology·2024
Same author

Non-breeding conditions induce carry-over effects on survival of migratory birds.

Current biology : CB·2024
Same author

Scale-dependent population drivers inform avian management in a declining saline lake ecosystem.

Ecological applications : a publication of the Ecological Society of America·2024
Same author

Integrated distance sampling models for simple point counts.

Ecology·2024

Related Experiment Video

Updated: Jan 20, 2026

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
11:52

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps

Published on: February 9, 2017

6.5K

Modeling spatially and temporally complex range dynamics when detection is imperfect.

Clark S Rushing1,2, J Andrew Royle3, David J Ziolkowski3

  • 1Department of Wildland Resources and the Ecology Center, Utah State University, 5230 Old Main Hill, Logan, UT, 84322, USA. clark.rushing@usu.edu.

Scientific Reports
|September 7, 2019
PubMed
Summary

We developed a dynamic occupancy model to track how species ranges change over time and space. This tool helps predict species distribution shifts due to climate change and habitat alteration.

More Related Videos

Spatial Temporal Analysis of Fieldwise Flow in Microvasculature
09:39

Spatial Temporal Analysis of Fieldwise Flow in Microvasculature

Published on: November 18, 2019

6.3K
Measuring Spatial and Temporal Ca2+ Signals in Arabidopsis Plants
10:12

Measuring Spatial and Temporal Ca2+ Signals in Arabidopsis Plants

Published on: September 2, 2014

12.6K

Related Experiment Videos

Last Updated: Jan 20, 2026

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
11:52

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps

Published on: February 9, 2017

6.5K
Spatial Temporal Analysis of Fieldwise Flow in Microvasculature
09:39

Spatial Temporal Analysis of Fieldwise Flow in Microvasculature

Published on: November 18, 2019

6.3K
Measuring Spatial and Temporal Ca2+ Signals in Arabidopsis Plants
10:12

Measuring Spatial and Temporal Ca2+ Signals in Arabidopsis Plants

Published on: September 2, 2014

12.6K

Area of Science:

  • Ecology
  • Conservation Biology
  • Biogeography

Background:

  • Species distributions are complex, influenced by biotic and abiotic factors, leading to varied spatial and temporal patterns.
  • Anthropogenic changes in habitats and climate necessitate advanced species distribution models for accurate range dynamics quantification.

Purpose of the Study:

  • To develop a dynamic occupancy model incorporating spatial generalized additive models.
  • To estimate non-linear spatial variation in occupancy beyond environmental covariates.
  • To provide a flexible framework for various sampling designs and generate distribution maps.

Main Methods:

  • Developed a dynamic occupancy model using a spatial generalized additive model (GAM).
  • The model estimates non-linear spatial occupancy variations not explained by environmental covariates.
  • Accommodates diverse sampling designs for occupancy and detection probability data.

Main Results:

  • Modeled long-term range dynamics for 10 eastern North American bird species using Breeding Bird Survey data.
  • Demonstrated the model's utility in quantifying complex range dynamics over large spatial and temporal scales.

Conclusions:

  • The dynamic occupancy model offers a robust framework for understanding species distribution changes.
  • This approach is valuable for predicting species' responses to environmental changes and informing conservation strategies.
  • The model is particularly useful for large-scale, long-term analyses of species range dynamics.