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02:31Habitat Fragmentation
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Habitat fragmentation describes the division of a more extensive, continuous habitat into smaller, discontinuous areas. Human activities such as land conversion, as well as slower geological processes leading to changes in the physical environment, are the two leading causes of habitat fragmentation. The fragmentation process typically follows the same steps: perforation, dissection, fragmentation, shrinkage, and attrition.
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04:08The Uncertainty Principle
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Werner Heisenberg considered the limits of how accurately one can measure properties of an electron or other microscopic particles. He determined that there is a fundamental limit to how accurately one can measure both a particle’s position and its momentum simultaneously. The more accurate the measurement of the momentum of a particle is known, the less accurate the position at that time is known and vice versa. This is what is now called the Heisenberg uncertainty principle. He...
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02:46Uncertainty in Measurement: Reading Instruments
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Counting is the type of measurement that is free from uncertainty, provided the number of objects being counted does not change during the process. Such measurements result in exact numbers. By counting the eggs in a carton, for instance, one can determine exactly how many eggs are there in the carton. Similarly, the numbers of defined quantities are also exact. For example, 1 foot is exactly 12 inches, 1 inch is exactly 2.54 centimeters, and 1 gram is exactly 0.001 kilograms. Quantities...
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00:59Uncertainty: Overview
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In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
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01:18Outer Layers of the Cell Envelope
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02:18The Bohr Model
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Visualizing uncertainty in habitat suitability models with the hyper-envelope modeling interface, version 2.
James Graham1, Melissa Kimble1
1Humboldt State University Arcata California.
Ecology and Evolution
|January 26, 2019
Summary
Habitat suitability models (HSMs) now better quantify uncertainty. HEMI 2 offers a simplified interface, incorporates expert opinion, and generates detailed uncertainty maps using Monte Carlo methods for improved ecological modeling.
Area of Science:
- Ecology
- Environmental Modeling
- Conservation Biology
Background:
- Habitat suitability models (HSMs) are widely used but often lack uncertainty analysis.
- Existing models may overfit data or fail to integrate expert knowledge.
- Previous software (HEMI 1) addressed overfitting and expert opinion integration.
Purpose of the Study:
- To introduce HEMI 2, an improved software for habitat suitability modeling.
- To enhance HSMs by incorporating uncertainty quantification and expert opinion.
- To provide tools for generating uncertainty, validation, and sensitivity maps.
Main Methods:
- HEMI 2 utilizes a simplified interface compared to HEMI 1.
- Random noise injection into occurrence data and environmental variables simulates uncertainty.
- Monte Carlo methods are employed for uncertainty, validation, and sensitivity testing.
Main Results:
- HEMI 2 generates mean and standard deviation habitat suitability maps.
- The software allows for the incorporation of expert opinion alongside occurrence data.
- Improved methods for assessing model uncertainty and reliability are provided.
Conclusions:
- HEMI 2 advances habitat suitability modeling by addressing key limitations.
- The software facilitates more robust and reliable ecological predictions.
- HEMI 2 is a valuable tool for conservation planning and environmental management.