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Related Concept Videos

What is Climate?01:16

What is Climate?

Climate refers to the prevailing weather conditions in a specific area over an extended period. As the saying goes, “Climate is what you expect. Weather is what you get.” Climate is influenced by geographic factors, such as latitude, terrain, and proximity to bodies of water.
Precipitation Processes01:12

Precipitation Processes

The experimental conditions in a gravimetric analysis should be optimized to maximize the particle size and purity of the obtained precipitate. Ideally, the concentration of the precipitating reagent should be low with effective stirring to maintain low relative supersaturation for the growth of large crystals. In homogeneous precipitation, the precipitant is slowly generated by a chemical reaction in the solution to avoid local reagent excesses. For example, urea decomposes gradually to...
Prediction Intervals01:03

Prediction Intervals

The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
The...
Global Climate Change01:50

Global Climate Change

Throughout its ~4.5 billion year history, the Earth has experienced periods of warming and cooling. However, the current drastic increase in global temperatures is well outside of the Earth’s cyclic norms, and evidence for human-caused global climate change is compelling. Paleoclimatology, the study of ancient climate conditions, provides ample evidence for human-caused global climate change by comparing recent conditions with those in the past.
Precipitation and Co-precipitation01:17

Precipitation and Co-precipitation

Precipitation and coprecipitation methods can be used to separate a mixture of ions in a solution. In qualitative inorganic analysis, ions that form sparingly soluble precipitates with the same reagent are separated based on the differences in solubility products. For example, consider the separation of Cu(II) and Fe(II) ions by precipitation as insoluble sulfides. First, copper(II) sulfide is precipitated by the addition of acidic H2S, where the dissociation of H2S is suppressed. Adding H2S...
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Related Experiment Video

Updated: May 11, 2026

Exploring the Effects of Atmospheric Forcings on Evaporation: Experimental Integration of the Atmospheric Boundary Layer and Shallow Subsurface
13:27

Exploring the Effects of Atmospheric Forcings on Evaporation: Experimental Integration of the Atmospheric Boundary Layer and Shallow Subsurface

Published on: June 8, 2015

Validating predictions from climate envelope models.

James I Watling1, David N Bucklin, Carolina Speroterra

  • 1Ft Lauderdale Research and Education Center, University of Florida, Ft Lauderdale, Florida, United States of America. watlingj@ufl.edu

Plos One
|May 30, 2013
PubMed
Summary

Climate envelope models can forecast species range shifts, but accuracy varies. A hybrid approach improved sensitivity for many birds, suggesting habitat generalists are more resilient to climate change impacts.

Related Experiment Videos

Last Updated: May 11, 2026

Exploring the Effects of Atmospheric Forcings on Evaporation: Experimental Integration of the Atmospheric Boundary Layer and Shallow Subsurface
13:27

Exploring the Effects of Atmospheric Forcings on Evaporation: Experimental Integration of the Atmospheric Boundary Layer and Shallow Subsurface

Published on: June 8, 2015

Area of Science:

  • Ecology
  • Conservation Biology
  • Climate Change Biology

Background:

  • Climate envelope models are crucial for predicting species' responses to climate change.
  • Evaluating their accuracy with independent data is essential for conservation.
  • Previous studies indicate poleward range shifts in North American birds.

Purpose of the Study:

  • To assess the accuracy of different climate envelope modeling approaches for forecasting species' distributional shifts.
  • To compare random forests and maximum entropy algorithms for modeling.
  • To evaluate model performance using independent survey data.

Main Methods:

  • Developed climate envelope models for 12 North American breeding bird species.
  • Tested three modeling approaches varying in assumptions of range expansion/contraction.
  • Used occurrence data from two distinct time periods (1967-1971 and 1998-2002).

Main Results:

  • Maximum entropy algorithm showed higher sensitivity than random forests.
  • A hybrid approach (assuming range expansion, not contraction) often maximized sensitivity.
  • Habitat generalists showed greater sensitivity improvement with the hybrid approach, suggesting resilience.
  • Random forests maximized specificity, while the hybrid approach minimized it.

Conclusions:

  • Climate envelope models offer cautious optimism for forecasting range shifts.
  • Model performance depends on assumptions about range dynamics and algorithms used.
  • Non-climate factors are critical for understanding species' range limits.
  • Exploring alternative modeling approaches enhances understanding of climate change impacts on biodiversity.