Distance‐based multivariate analyses confound location and dispersion effects

Warton, David I.; Wright, S.; Wang, Yi

doi:10.1111/j.2041-210x.2011.00127.x

Cited by 1,012 publications

(833 citation statements)

References 41 publications

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“…PERMANOVA analyses are more robust than other similar tests (e.g., Mantel) but still tend to confound differences in species composition across treatments (location) versus within-treatment (dispersion) differences in community dissimilarity (Warton et al 2012). In order to separate these two effects, for each significant term from the PERMANOVA, we used a PERMDISP analysis to test for a change in within-treatment variance (Anderson 2001;Anderson and Walsh 2013).…”

Section: Statistical Analysesmentioning

confidence: 99%

Spatially Heterogeneous Perturbations Homogenize the Regulation of Insect Herbivores

Harvey

MacDougall

2015

The American Naturalist

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Anthropogenic influences on resources and consumers can affect food web regulation, with impacts on trophic structure and ecosystem processes. Identifying how these impacts unfold is challenging because alterations to one or both resources and consumers can similarly transform community structure, especially for intermediate consumers. To date, empirical testing of perturbations on trophic regulation has been limited by the difficulty in separating the direct effect of perturbations on species composition and diversity versus those unfolding indirectly via altered feeding pathways. Moreover, disentangling the independent and interactive impacts of co-varying stressors that characterize human-altered systems has been an ongoing analytical challenge. We used a large-scale meta-community experiment in grasslands to test how resource inputs, stand perturbation, and spatial factors affect regulation of insect herbivores in tri-trophic grassland food webs. Using path-model comparisons, we observed significant simplification of food web regulation on insect herbivores, shifting from mixed predator-resource regulation in unaltered mainland areas, to strictly resource-based regulation with landscape perturbation and fragmentation. Most changes were attributed to homogenization of plant community caused by landscape fragmentation and the deterministic influence of eutrophication that reduced among-patch beta-diversity. This led to a simplified food web dominated by fewer, but more abundant herbivore taxa. Our work implies that anthropogenic perturbation relating to resources and spatial isolation can transform the regulation of food web diversity, structure and function. abstract: Anthropogenic influences on resources and consumers can affect food web regulation, with impacts on trophic structure and ecosystem processes. Identifying how these impacts unfold is challenging because alterations to one or both resources and consumers can similarly transform community structure, especially for intermediate consumers. To date, empirical testing of perturbations on trophic regulation has been limited by the difficulty in separating the direct effect of perturbations on species composition and diversity from those unfolding indirectly via altered feeding pathways. Moreover, disentangling the independent and interactive impacts of covarying stressors that characterize human-altered systems has been an ongoing analytical challenge. We used a large-scale metacommunity experiment in grasslands to test how resource inputs, stand perturbation, and spatial factors affect regulation of insect herbivores in tritrophic grassland food webs. Using path-model comparisons, we observed significant simplification of food web regulation on insect herbivores, shifting from mixed predator-resource regulation in unaltered mainland areas to strictly resource-based regulation with landscape perturbation and fragmentation. Most changes were attributed to homogenization of plant community caused by landscape fragmentation and the deterministic...

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Section: Statistical Analysesmentioning

confidence: 99%

Spatially Heterogeneous Perturbations Homogenize the Regulation of Insect Herbivores

Harvey

MacDougall

2015

The American Naturalist

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“…However, as we found no support for 284 seasonal effects (p = 0.19), it was removed from the model (Crawley 2007). A negative binomial 285 error structure was specified in our model, because our count data was over-dispersed (O'Hara and 286 Kotze 2010; Wang et al 2012). Note though that this second modelling approach is simply another 287 way of testing for the effects of habitat type on individual species' density, and the results for each 288 species were very similar to the first presence/absence mixed model approach.…”

Section: Data Analysis 239mentioning

confidence: 69%

“…variation in abundance rather than simply presence/absence) 274 within a relative simple modelling framework that would allow model convergence. We modelled 275 the difference in abundance of each species individually and from this inferred differences in 276 community assemblage between habitat types, using a multivariate generalised linear model on 277 species count data with the mvabund package (Wang et al 2012). Multivariate generalised linear 278 models provide a powerful framework for analysing species abundance data and have been shown 279 to be more robust than distance based methods, such as multidimensional scaling and redundancy 280 analysis (Warton et al 2012).…”

Section: Data Analysis 239mentioning

confidence: 99%

The effects of land-use change on the endemic avifauna of Makira, Solomon Islands: endemics avoid monoculture

Davies

Clarke

Ewen

et al. 2015

Emu - Austral Ornithology

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15Unprecedented rates of deforestation on tropical islands are threatening high numbers of endemic 16 species. More empirical evidence is needed to better understand the implications of land-use 17 change on biodiversity, and to guide conservation actions. We assessed the impacts of land-use 18 change on the lowland avifauna of the tropical island of Makira in the Solomon Islands. We 19 examined species richness and community assemblages, with a particular focus on endemism and 20 functional traits, to provide further insight into the 'conservation value' of the dominant land-use 21 types present on Makira (i.e. intact forest, secondary forest, food gardens, mixed cocoa plantations, 22 and monoculture cocoa plantations). We found species richness was similar across habitats, but 23 endemic species richness decreased as intensity of land use increased. There were significant 24 differences in the occurrence of functional groups between habitats. Fifteen out of the 42 species 25 observed showed significant variation in abundance across habitats. Of those species that varied, 12 26 were endemic to Makira or to Melanesia, with seven of these endemics being absent from the 27 monoculture cocoa. As tropical islands have less functional redundancy than continental 28 landmasses, protecting the remaining forest and improving habitat connectivity will be even more 29 critical for conserving their endemic species and maintaining ecosystem functioning. 30 31 3 Introduction 32

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“…The methods differ by their approach to the variance comparison: ANOSIM compares ranks of variances similar to Kruskal-Wallis test, while PERMANOVA compares variance values by estimating the significance via a permutation method. A disadvantage of these methods is that they require equal withingroup variances -however, usually this is not the case for metagenomic data (Warton et al, 2012). PERMANOVA was shown to be more robust to the failure of this restriction than ANOSIM (Anderson and Walsh, 2013).…”

Section: Community-level Comparison Of Microbial Communitiesmentioning

confidence: 99%

Guidelines to Statistical Analysis of Microbial Composition Data Inferred from Metagenomic Sequencing

Odintsova¹,

Tyakht²,

Alexeev³

2017

Current Issues in Molecular Biology

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Metagenomics, the application of high-throughput DNA sequencing for surveys of environmental samples, has revolutionized our view on the taxonomic and genetic composition of complex microbial communities. An enormous richness of microbiota keeps unfolding in the context of various fields ranging from biomedicine and food industry to geology. Primary analysis of metagenomic reads allows to infer semi-quantitative data describing the community structure. However, such compositional data possess statistical specific properties that are important to consider during preprocessing, hypothesis testing and interpreting the results of statistical tests. Failure to account for these specifics may lead to essentially wrong conclusions as a result of the survey. Here we present a researcher introduction to the field of metagenomics with the basic properties of microbial compositional data including statistical power and proposed distribution models, perform a review of the publicly available software tools developed specifically for such data and outline the recommendations for the application of the methods. IntroductionMicrobiota, complex communities consisting of microbial species, appear to inhabit literally any environmental niche in the world. Recent advances in molecular genetic techniques allowed the study of microbiota in a cultivation-independent way, leading to the discovery of enormous diversity. One of the most advanced and widely used techniques is metagenomic sequencing: classification and quantification of metagenomic sequences can be used

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Distance‐based multivariate analyses confound location and dispersion effects

Cited by 1,012 publications

References 41 publications

Spatially Heterogeneous Perturbations Homogenize the Regulation of Insect Herbivores

Spatially Heterogeneous Perturbations Homogenize the Regulation of Insect Herbivores

The effects of land-use change on the endemic avifauna of Makira, Solomon Islands: endemics avoid monoculture

Guidelines to Statistical Analysis of Microbial Composition Data Inferred from Metagenomic Sequencing

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