Found: 9
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Assessing the applicability of binary land-cover variables to species distribution models across multiple grains.
- Published in:
- Landscape Ecology, 2024, v. 39, n. 3, p. 1, doi. 10.1007/s10980-024-01813-3
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- Article
Species distribution models affected by positional uncertainty in species occurrences can still be ecologically interpretable.
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- Ecography, 2023, v. 2023, n. 6, p. 1, doi. 10.1111/ecog.06358
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- Article
Scale mismatches between predictor and response variables in species distribution modelling: A review of practices for appropriate grain selection.
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- Progress in Physical Geography, 2023, v. 47, n. 3, p. 467, doi. 10.1177/03091333231156362
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- Article
Vegetation structure derived from airborne laser scanning to assess species distribution and habitat suitability: The way forward.
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- Diversity & Distributions, 2023, v. 29, n. 1, p. 39, doi. 10.1111/ddi.13644
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- Article
Importance of data selection and filtering in species distribution models: A case study on the Cantabrian brown bear.
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- Ecosphere, 2022, v. 13, n. 12, p. 1, doi. 10.1002/ecs2.4284
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- Article
Positional errors in species distribution modelling are not overcome by the coarser grains of analysis.
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- Methods in Ecology & Evolution, 2022, v. 13, n. 10, p. 2289, doi. 10.1111/2041-210X.13956
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- Article
Habitats as predictors in species distribution models: Shall we use continuous or binary data?
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- Ecography, 2022, v. 2022, n. 7, p. 1, doi. 10.1111/ecog.06022
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- Article
Applicability of Data Acquisition Characteristics to the Identification of Local Artefacts in Global Digital Elevation Models: Comparison of the Copernicus and TanDEM-X DEMs.
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- Remote Sensing, 2021, v. 13, n. 19, p. 3931, doi. 10.3390/rs13193931
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- Article
The effect of positional error on fine scale species distribution models increases for specialist species.
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- Ecography, 2020, v. 43, n. 2, p. 256, doi. 10.1111/ecog.04687
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- Article