Vegetation Ecology Lab / 植群生態研究室

Institute of Ecology and Evolutionary Biology, National Taiwan University

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research [2018/06/02 10:57]
david
research [2018/09/13 00:55]
david [Examples of past and current research topics]
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 <fc #​800000>​**Methodological aspects of analysing community-ecology data.**</​fc>​ It is always good to try new methods to analyze data, but at the same time, it is essential to critically ask whether these methods are really doing what we suppose them to do. Modern community ecology cannot exist without advanced numerical methods able to handle often large and complex community datasets, but we need to be aware that even the most advanced of them have certain limitations. In the lab, we focus on several methods which are commonly used by vegetation ecologists and which seems to suffer from severe limitations (community-weighted mean analysis, the effect of undersampling,​ beta diversity analysis). <fc #​800000>​**Methodological aspects of analysing community-ecology data.**</​fc>​ It is always good to try new methods to analyze data, but at the same time, it is essential to critically ask whether these methods are really doing what we suppose them to do. Modern community ecology cannot exist without advanced numerical methods able to handle often large and complex community datasets, but we need to be aware that even the most advanced of them have certain limitations. In the lab, we focus on several methods which are commonly used by vegetation ecologists and which seems to suffer from severe limitations (community-weighted mean analysis, the effect of undersampling,​ beta diversity analysis).
  
-===== Research philosophy ===== 
  
-I believe that to make research successful and enjoyable at the same time, the following things are overly important: a curiosity in discovering new things, good field and lab training, creating opportunities for fruitful discussion, open data policy, and transparent analytical procedure. Good ecologist should be able to combine field and lab approaches - it is important to touch nature in the field and collect good field data, but it is also important to process, analyze and interpret data correctly, and know how to present them. 
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-Considering numerical analysis, my belief is in methodological simplicity – although many fancy modern (and often complex) statistical methods exist, if the choice is to be done between more advanced method and simple or traditional one, both leading to results with similar interpretation,​ my choice would be to go for the simpler one, since more people will actually understand it. Also, transparent description of analysis and honest interpretation of their outcomes is a must. Although I often work with numbers, I think about ecology at the first place - all those numerical games are here to help us to understand and interpret what's going on in nature, not the other way around. 
-===== Examples of past and current research topics ===== 
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-**Beta-diversity** as a tool to inspect the rules of community assembly (Chang et al. 2013), and **undersampling** as one of the key reasons why results of beta diversity studies are hardly comparable (Zelený et al. //in prep.//, Zukal & Zelený //in prep.//). 
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-Diversity pattern along the gradient of cloud frequency and chronic-wind intensity in forest vegetation of Taiwan (vegetation survey, measurements of species functional traits for cloud and wind indicator species). 
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-**Spatial structure in vegetation** as a surrogate for unmeasured or overlooked environmental factors influencing vegetation (Chang et al. 2013, Chudomelová et al. 2017) 
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-**Vegetation classification** of Czech forest vegetation (pine forest of the alliance //​Dicrano-Pinion//,​ Zelený in Chytrý 2012), contribution to classification of Taiwan forest vegetation (Lin et al. 2012, Li et al. 2013, Li et al. 2015), and theoretical development of classification methods (modified TWINSPAN at Roleček et al. 2009, Cocktail Determination Key at Li et al. 2013). 
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-**Effect of landscape heterogeneity on vegetation diversity** studied in deep river valleys of Bohemian Massif in the Czech Republic (my [[http://​davidzeleny.net/​doku.php/​phd|doctoral thesis]], Zelený & Chytrý 2007, Zelený et al. 2010). 
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-**Ellenberg-like species indicator values** as a useful source of expert knowledge about species ecological requirements,​ pitfalls in their use in data analysis (Zelený & Schaffers 2012), and the potential introduction of the system of indicator values in new regions (like East Asia). 
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-Co-occurrence method of estimating species **ecological specialization** (Zelený 2009, Fajmonová et al. 2013, Carboni et al. 2016, Zelený //in prep.//​) ​ 
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-Bias in using **community-weighted means of species attributes** (like traits or species indicator values) in the analysis of community ecology data (Zelený //​submitted//​).