Estimating and interpreting migration of Amazonian forests using spatially implicit and semi‐explicit neutral models Article Swipe
YOU?
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· 2017
· Open Access
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· DOI: https://doi.org/10.1002/ece3.2930
With many sophisticated methods available for estimating migration, ecologists face the difficult decision of choosing for their specific line of work. Here we test and compare several methods, performing sanity and robustness tests, applying to large‐scale data and discussing the results and interpretation. Five methods were selected to compare for their ability to estimate migration from spatially implicit and semi‐explicit simulations based on three large‐scale field datasets from South America (Guyana, Suriname, French Guiana and Ecuador). Space was incorporated semi‐explicitly by a discrete probability mass function for local recruitment, migration from adjacent plots or from a metacommunity. Most methods were able to accurately estimate migration from spatially implicit simulations. For spatially semi‐explicit simulations, estimation was shown to be the additive effect of migration from adjacent plots and the metacommunity. It was only accurate when migration from the metacommunity outweighed that of adjacent plots, discrimination, however, proved to be impossible. We show that migration should be considered more an approximation of the resemblance between communities and the summed regional species pool. Application of migration estimates to simulate field datasets did show reasonably good fits and indicated consistent differences between sets in comparison with earlier studies. We conclude that estimates of migration using these methods are more an approximation of the homogenization among local communities over time rather than a direct measurement of migration and hence have a direct relationship with beta diversity. As betadiversity is the result of many (non)‐neutral processes, we have to admit that migration as estimated in a spatial explicit world encompasses not only direct migration but is an ecological aggregate of these processes. The parameter m of neutral models then appears more as an emerging property revealed by neutral theory instead of being an effective mechanistic parameter and spatially implicit models should be rejected as an approximation of forest dynamics.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1002/ece3.2930
- https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/ece3.2930
- OA Status
- gold
- Cited By
- 3
- References
- 83
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2611452325
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2611452325Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1002/ece3.2930Digital Object Identifier
- Title
-
Estimating and interpreting migration of Amazonian forests using spatially implicit and semi‐explicit neutral modelsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2017Year of publication
- Publication date
-
2017-05-05Full publication date if available
- Authors
-
Edwin Pos, Juan Ernesto Guevara, Daniel Sabatier, Jean‐François Molino, Nigel C. A. Pitman, Hugo F. Mogollón, David Neill, Carlos Cerón, Gonzalo Rivas‐Torres, Anthony Di Fiore, Raquel Thomas, Milton Tirado, Kenneth R. Young, Ophelia Wang, Rodrigo Sierra, Roosevelt García‐Villacorta, Roderick Zagt, Walter Palacios Cuenca, Milton Aulestia, Hans ter SteegeList of authors in order
- Landing page
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https://doi.org/10.1002/ece3.2930Publisher landing page
- PDF URL
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https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/ece3.2930Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
- OA URL
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https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/ece3.2930Direct OA link when available
- Concepts
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Metacommunity, Replicate, Robustness (evolution), Computer science, Econometrics, Population, Mathematics, Statistics, Biology, Biochemistry, Biological dispersal, Sociology, Gene, DemographyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
3Total citation count in OpenAlex
- Citations by year (recent)
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2024: 1, 2019: 2Per-year citation counts (last 5 years)
- References (count)
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83Number of works referenced by this work
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-
10Other works algorithmically related by OpenAlex
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