Did we measure enough environmental variables? Insights from multiscale spatial analysis

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F13%3A00066716" target="_blank" >RIV/00216224:14310/13:00066716 - isvavai.cz</a>

Výsledek na webu

<a href="http://escholarship.org/uc%C3%BAfb" target="_blank" >http://escholarship.org/uc%C3%BAfb</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Did we measure enough environmental variables? Insights from multiscale spatial analysis

Popis výsledku v původním jazyce

Variation partitioning of species composition into components explained by environmental and spatial variables is often used to identify a signature of niche- and dispersal-based processes in community assembly. Such interpretation, however, strongly depends on the quality of available environmental data. Spatially structured variation not explained by environment (component [c]), which is believed to carry legacy of dispersal-based processes, contains unknown proportion of variation attributable to unmeasured environmental variables. We can never measure everything, but it is useful to know if we measured really too less or we are getting close to perfect. To evaluate this, we used multiscale spatial analysis of component [c], based on PCNM analysis.

Název v anglickém jazyce

Did we measure enough environmental variables? Insights from multiscale spatial analysis

Popis výsledku anglicky

Variation partitioning of species composition into components explained by environmental and spatial variables is often used to identify a signature of niche- and dispersal-based processes in community assembly. Such interpretation, however, strongly depends on the quality of available environmental data. Spatially structured variation not explained by environment (component [c]), which is believed to carry legacy of dispersal-based processes, contains unknown proportion of variation attributable to unmeasured environmental variables. We can never measure everything, but it is useful to know if we measured really too less or we are getting close to perfect. To evaluate this, we used multiscale spatial analysis of component [c], based on PCNM analysis.

Druh

O - Ostatní výsledky

CEP obor

EH - Ekologie – společenstva

OECD FORD obor

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Projekt

<a href="/cs/project/GAP505%2F12%2F1022" target="_blank" >GAP505/12/1022: Beta diverzita rostlinných společenstev podél omezených ekologických gradientů</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2013

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů