Modeling - and -diversity in a tropical forest from remotely sensed and spatial data
Comprehensive information on species distribution and species composition patterns of plant communities is required for effective conservation and management of biodiversity. Remote sensing offers an inexpensive means of attaining complete spatial coverage for large areas, at regular time intervals, and can therefore be extremely useful for estimating both species richness and spatial variation of species composition (- and -diversity). An essential step to map such attributes is to identify and understand their main drivers. We used remotely sensed data as a surrogate of plant productivity and habitat structure variables for explaining - and -diversity, and evaluated the relative roles of productivity-habitat structure and spatial variables in explaining observed patterns of - and -diversity by using a Principal Coordinates of Neighbor Matrices analysis. We also examined the relationship between remotely sensed and field data, in order to map - and -diversity at the landscape-level in the Yucatan Peninsula, using a regression kriging procedure. These two procedures integrate the relationship of species richness and spatial species turnover both with remotely sensed data and spatial structure. The empirical models so obtained can be used to predict species richness and variation in species composition, and they can be regarded as valuable tools not only for identifying areas with high local species richness (-diversity), but also areas with high species turnover (-diversity). Ultimately, information obtained in this way can help maximize the number of species preserved in a landscape.
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dig-cicy-1003-1662016-10-25T16:05:14Z Modeling - and -diversity in a tropical forest from remotely sensed and spatial data JOSE LUIS HERNANDEZ STEFANONI 2012-04-02 info:eu-repo/semantics/article Comprehensive information on species distribution and species composition patterns of plant communities is required for effective conservation and management of biodiversity. Remote sensing offers an inexpensive means of attaining complete spatial coverage for large areas, at regular time intervals, and can therefore be extremely useful for estimating both species richness and spatial variation of species composition (- and -diversity). An essential step to map such attributes is to identify and understand their main drivers. We used remotely sensed data as a surrogate of plant productivity and habitat structure variables for explaining - and -diversity, and evaluated the relative roles of productivity-habitat structure and spatial variables in explaining observed patterns of - and -diversity by using a Principal Coordinates of Neighbor Matrices analysis. We also examined the relationship between remotely sensed and field data, in order to map - and -diversity at the landscape-level in the Yucatan Peninsula, using a regression kriging procedure. These two procedures integrate the relationship of species richness and spatial species turnover both with remotely sensed data and spatial structure. The empirical models so obtained can be used to predict species richness and variation in species composition, and they can be regarded as valuable tools not only for identifying areas with high local species richness (-diversity), but also areas with high species turnover (-diversity). Ultimately, information obtained in this way can help maximize the number of species preserved in a landscape. info:eu-repo/classification/cti/1 info:eu-repo/classification/cti/1 http://cicy.repositorioinstitucional.mx/jspui/handle/1003/166 info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-nd/4.0 application/pdf |
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info:eu-repo/classification/cti/1 info:eu-repo/classification/cti/1 info:eu-repo/classification/cti/1 info:eu-repo/classification/cti/1 JOSE LUIS HERNANDEZ STEFANONI Modeling - and -diversity in a tropical forest from remotely sensed and spatial data |
description |
Comprehensive information on species distribution and species composition patterns of plant communities is required for effective conservation and management of biodiversity. Remote sensing offers an
inexpensive means of attaining complete spatial coverage for large areas, at regular time intervals, and
can therefore be extremely useful for estimating both species richness and spatial variation of species
composition (- and -diversity). An essential step to map such attributes is to identify and understand
their main drivers. We used remotely sensed data as a surrogate of plant productivity and habitat structure variables for explaining - and -diversity, and evaluated the relative roles of productivity-habitat
structure and spatial variables in explaining observed patterns of - and -diversity by using a Principal
Coordinates of Neighbor Matrices analysis. We also examined the relationship between remotely sensed
and field data, in order to map - and -diversity at the landscape-level in the Yucatan Peninsula, using
a regression kriging procedure. These two procedures integrate the relationship of species richness and
spatial species turnover both with remotely sensed data and spatial structure. The empirical models so
obtained can be used to predict species richness and variation in species composition, and they can be
regarded as valuable tools not only for identifying areas with high local species richness (-diversity),
but also areas with high species turnover (-diversity). Ultimately, information obtained in this way can
help maximize the number of species preserved in a landscape. |
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info:eu-repo/semantics/article |
topic_facet |
info:eu-repo/classification/cti/1 info:eu-repo/classification/cti/1 |
author |
JOSE LUIS HERNANDEZ STEFANONI |
author_facet |
JOSE LUIS HERNANDEZ STEFANONI |
author_sort |
JOSE LUIS HERNANDEZ STEFANONI |
title |
Modeling - and -diversity in a tropical forest from remotely sensed and spatial data |
title_short |
Modeling - and -diversity in a tropical forest from remotely sensed and spatial data |
title_full |
Modeling - and -diversity in a tropical forest from remotely sensed and spatial data |
title_fullStr |
Modeling - and -diversity in a tropical forest from remotely sensed and spatial data |
title_full_unstemmed |
Modeling - and -diversity in a tropical forest from remotely sensed and spatial data |
title_sort |
modeling - and -diversity in a tropical forest from remotely sensed and spatial data |
url |
http://cicy.repositorioinstitucional.mx/jspui/handle/1003/166 |
work_keys_str_mv |
AT joseluishernandezstefanoni modelinganddiversityinatropicalforestfromremotelysensedandspatialdata |
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1756089279023415296 |