A model-based approach to studying changes in compositional heterogeneity
Baeten, L. ; Warton, D. ; Calster, H. van; Frenne, P. De; Verstraeten, G. ; Bonte, D. ; Bernhardt-Romermann, M. ; Cornelis, R. ; Decocq, G. ; Eriksson, O. ; Hommel, P.W.F.M. - \ 2014
Methods in Ecology and Evolution 5 (2014)2. - ISSN 2041-210X - p. 156 - 164.
with-standards forest - biotic homogenization - beta-diversity - plant-communities - deciduous forest - vegetation - turnover - dissimilarity - nestedness - dispersion
1. Non-random species loss and gain in local communities change the compositional heterogeneity between communities over time, which is traditionally quantified with dissimilarity-based approaches. Yet, dissimilarities summarize the multivariate species data into a univariate index and obscure the species-level patterns of change, which are central to understand the causes and consequences of the community changes. 2. Here, we propose a model-based approach that looks for species-level effects of time period and construct a multiple-site metric as a sum across species to test the consistency of the individual species responses. Species fall into different response types, showing how they influence the changes in community heterogeneity. 3. In a comparison with other multiple-sitemetrics, we illustrate the properties of our method and the differences and similarities with other approaches. For instance, ourmetric estimates the total variation in a community data set based on species-level contributions, not the compositional dissimilarities between particular sites. Similar to some other approaches, we can distinguish between heterogeneity derived from turnover or richness differences. 4. Our approach was applied to a set of 23 forest understorey resurvey studies spread across Europe. We show the species gains and lossesmay as well decrease or increase levels of community heterogeneity. Although species occurrences and communities have not changed in a consistent way along continental-scale environmental gradients such as climatic conditions, several species shifted in a similar way across the different data sets. 5. Testing the significance of shifts in species prevalence over time to infer corresponding changes in the compositional heterogeneity among sites provides a very intuitive tool for community resurvey studies. The main strengths of our framework are the explicit consideration of the relative roles of species gains and losses and the straightforward generalization to different sets of hypotheses related to community changes. Key-words: biodiversity, community composition, biotic homogenization, binomial deviance, dissimilarity, beta diversity,multivariate analysis,meta-analysis, forest understorey
Advancing our thinking in presence-only and used-available analysis
Warton, D. ; Aarts, G.M. - \ 2013
Journal of Animal Ecology 82 (2013)6. - ISSN 0021-8790 - p. 1125 - 1134.
resource selection functions - species distribution models - point process models - habitat selection - functional-responses - logistic-regression - pseudo-absences - animal movement - telemetry data - distributions
1. The problems of analysing used-available data and presence-only data are equivalent, and this paper uses this equivalence as a platform for exploring opportunities for advancing analysis methodology. 2. We suggest some potential methodological advances in used-available analysis, made possible via lessons learnt in the presence-only literature, for example, using modern methods to improve predictive performance. We also consider the converse - potential advances in presence-only analysis inspired by used-available methodology. 3. Notwithstanding these potential advances in methodology, perhaps a greater opportunity is in advancing our thinking about how to apply a given method to a particular data set. 4. It is shown by example that strikingly different results can be achieved for a single data set by applying a given method of analysis in different ways - hence having chosen a method of analysis, the next step of working out how to apply it is critical to performance. 5. We review some key issues to consider in deciding how to apply an analysis method: apply the method in a manner that reflects the study design; consider data properties; and use diagnostic tools to assess how reasonable a given analysis is for the data at hand.