What are the key factors that influence species distribution modeling?
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Key factors influencing species distribution modeling include the choice of sampling type, resolution of environmental conditions, model transferability, incorporation of species interactions, and accuracy challenges. Sampling type, such as segment- or areal-based, significantly impacts model relevance. Model transferability is crucial, affected by geographical distance, degree of extrapolation, and species traits like distribution size and lifespan. Incorporating species interactions is challenging but essential for accurate predictions, requiring consideration of spatial scales and diverse training data. Accuracy challenges stem from various factors like environmental and species data, ecological differences, computational resources, model choice, and spatial resolution. These factors collectively emphasize the complexity and importance of making informed decisions in species distribution modeling.
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| Papers (4) | Insight |
|---|---|
| Key factors influencing species distribution model transferability include geographical distance, degree of extrapolation, topographic relief, lifespan, and core range distance. Non-stationarity and over-extrapolation also impact model success. | |
| Key factors influencing species distribution modeling include environmental data, species data, ecological characteristics, computational resources, chosen model, and spatial resolution, impacting accuracy and model outcomes. | |
| Sampling type and spatial resolution of environmental conditions significantly impact species distribution model performance, with sampling type showing stronger effects than resolution in model relevance. | |
| Sampling type and spatial resolution of environmental conditions significantly impact species distribution model performance, with sampling type having a stronger effect than resolution on model relevance. |
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