Dataset Information

Estimating and interpreting migration of Amazonian forests using spatially implicit and semi-explicit neutral models.

ABSTRACT: 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.

SUBMITTER: Pos E

PROVIDER: S-EPMC5478059 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature

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Estimating and interpreting migration of Amazonian forests using spatially implicit and semi-explicit neutral models.

Pos Edwin E Guevara Andino Juan Ernesto JE Sabatier Daniel D Molino Jean-François JF Pitman Nigel N Mogollón Hugo H Neill David D Cerón Carlos C Rivas-Torres Gonzalo G Di Fiore Anthony A Thomas Raquel R Tirado Milton M Young Kenneth R KR Wang Ophelia O Sierra Rodrigo R García-Villacorta Roosevelt R Zagt Roderick R Palacios Cuenca Walter W Aulestia Milton M Ter Steege Hans H

Ecology and evolution 20170505 12

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 Ameri ...[more]

PMID: 28649338

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Dataset Information

Estimating and interpreting migration of Amazonian forests using spatially implicit and semi-explicit neutral models.

Publications

Estimating and interpreting migration of Amazonian forests using spatially implicit and semi-explicit neutral models.

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