F. Guillaume Blanchet

FORWARD SELECTION OF EXPLANATORY VARIABLES

This paper proposes a new way of using forward selection of explanatory variables in regression or canonical redundancy analysis. The classical forward selection method presents two problems: a highly inflated Type I error and an overestimation of the amount of explained variance. Correcting these problems will greatly improve the performance of this very useful method in ecological modeling. To prevent the first problem, we propose a two-step procedure. First, a global test using all explanatory variables is carried out. If, and only if, the global test is significant, one can proceed with forward selection. To prevent overestimation of the explained variance, the forward selection has to be carried out with two stopping criteria: (1) the usual alpha significance level and (2) the adjusted coefficient of multiple determination (Ra(2)) calculated using all explanatory variables. When forward selection identifies a variable that brings one or the other criterion over the fixed threshold, that variable is rejected, and the procedure is stopped. This improved method is validated by simulations involving univariate and multivariate response data. An ecological example is presented using data from the Bryce Canyon National Park, Utah, U.S.A.

So Many Variables: Joint Modeling in Community Ecology.

Technological advances have enabled a new class of multivariate models for ecology, with the potential now to specify a statistical model for abundances jointly across many taxa, to simultaneously explore interactions across taxa and the response of abundance to environmental variables. Joint models can be used for several purposes of interest to ecologists, including estimating patterns of residual correlation across taxa, ordination, multivariate inference about environmental effects and environment-by-trait interactions, accounting for missing predictors, and improving predictions in situations where one can leverage knowledge of some species to predict others. We demonstrate this by example and discuss recent computation tools and future directions.

How to make more out of community data? A conceptual framework and its implementation as models and software

Community ecology aims to understand what factors determine the assembly and dynamics of species assemblages at different spatiotemporal scales. To facilitate the integration between conceptual and statistical approaches in community ecology, we propose Hierarchical Modelling of Species Communities (HMSC) as a general, flexible framework for modern analysis of community data. While non-manipulative data allow for only correlative and not causal inference, this framework facilitates the formulation of data-driven hypotheses regarding the processes that structure communities. We model environmental filtering by variation and covariation in the responses of individual species to the characteristics of their environment, with potential contingencies on species traits and phylogenetic relationships. We capture biotic assembly rules by species-to-species association matrices, which may be estimated at multiple spatial or temporal scales. We operationalise the HMSC framework as a hierarchical Bayesian joint species distribution model, and implement it as R- and Matlab-packages which enable computationally efficient analyses of large data sets. Armed with this tool, community ecologists can make sense of many types of data, including spatially explicit data and time-series data. We illustrate the use of this framework through a series of diverse ecological examples.

Measuring habitat fragmentation: An evaluation of landscape pattern metrics

Summary Landscape patterns influence a range of ecological processes at multiple spatial scales. Landscape pattern metrics are often used to study the patterns that result from the linear and nonlinear interactions between spatial aggregation and abundance of habitat. However, many class-level pattern metrics are highly correlated with habitat abundance, making their use as a measure of habitat fragmentation problematic. We argue that a class-level pattern metric should be (1) able to differentiate landscapes across a range of spatial aggregations, and (2) independent of habitat abundance, if it is to be used to distinguish between effects of habitat amount and fragmentation. Based on these criteria and using both simulated and actual landscapes, we evaluated 64 class-level pattern metrics. These metrics were reclassified into four groups based on their correlation with aggregation and abundance. Among all these metrics, nine were considered robust for fragmentation measurements, which cover most of the characteristics that define pattern, including core area, shape, proximity / isolation, contrast, and contagion / interspersion. Optimal metrics for individual studies will depend on both biological rationales and statistically robust metrics that are appropriate for achieving each study objectives.

Inferring Processes from Spatial Patterns: The Role of Directional and Non-Directional Forces in Shaping Fish Larvae Distribution in a Freshwater Lake System

Larval dispersal is a crucial factor for fish recruitment. For fishes with relatively small-bodied larvae, drift has the potential to play a more important role than active habitat selection in determining larval dispersal; therefore, we expect small-bodied fish larvae to be poorly associated with habitat characteristics. To test this hypothesis, we used as model yellow perch (Perca flavescens), whose larvae are among the smallest among freshwater temperate fishes. Thus, we analysed the habitat association of yellow perch larvae at multiple spatial scales in a large shallow fluvial lake by explicitly modelling directional (e.g. due to water currents) and non-directional (e.g. due to aggregation) spatial patterns. This allowed us to indirectly assess the relative roles of drift (directional process) and potential habitat choice on larval dispersal. Our results give weak support to the drift hypothesis, whereas yellow perch show a strong habitat association at unexpectedly small sizes, when compared to other systems. We found consistent non-directional patterns in larvae distributions at both broad and medium spatial scales but only few significant directional components. The environmental variables alone (e.g. vegetation) generally explained a significant and biologically relevant fraction of the variation in fish larvae distribution data. These results suggest that (i) drift plays a minor role in this shallow system, (ii) larvae display spatial patterns that only partially covary with environmental variables, and (iii) larvae are associated to specific habitats. By suggesting that habitat association potentially includes an active choice component for yellow perch larvae, our results shed new light on the ecology of freshwater fish larvae and should help in building more realistic recruitment models.

Consensus RDA across dissimilarity coefficients for canonical ordination of community composition data

Understanding how habitat structures species assemblages in a community is one of the main goals of community ecology. To relate community patterns to particular factors defining habitat conditions, ecologists often use canonical ordinations such as canonical redundancy analysis (RDA). It is a common practice to use dissimilarity coefficients to perform canonical ordinations through distance-based RDA (db-RDA) or transformation-based RDA (tb-RDA). Dissimilarity coefficients are measures of resemblance where the information about species communities is condensed into a symmetric square matrix of dissimilarities among sites. In this study, we compared 16 of the most commonly used dissimilarity coefficients to evaluate if the species-abundance distribution (SAD) of a community can be used to select an appropriate coefficient. Of these, 11 are designed to be used primarily with abundance data, although they can also be used with presence–absence data, whereas five can only be applied to presence–absence data....

Intraguild predation and competition impacts on a subordinate predator

Abstract Intraguild (IG) predation and interspecific competition may affect the settlement and success of species in their habitats. Using data on forest-dwelling hawks from Finland, we addressed the impact of an IG predator, the northern goshawk Accipiter gentilis (goshawk), on the breeding of an IG prey, the common buzzard Buteo buteo. We hypothesized that the subordinate common buzzard avoids breeding in the proximity of goshawks and that interspecific competitors, mainly Strix owls, may also disturb common buzzards by competing for nests and food. Our results show that common buzzards more frequently occupied territories with a low IG predation threat and with no interspecific competitors. We also observed that common buzzards avoided territories with high levels of grouse, the main food of goshawks, possibly due to a risk of IG predation since abundant grouse can attract goshawks. High levels of small rodents attracted interspecific competitors to common buzzard territories and created a situation where there was not only an abundance of food but also an abundance of competitors for the food. These results suggest interplay between top–down and bottom–up processes which influence the interactions between avian predator species. We conclude that the common buzzard needs to balance the risks of IG predation and interference competition with the availability of its own resources. The presence of other predators associated with high food levels may impede a subordinate predator taking full advantage of the available food. Based on our results, it appears that interspecific interactions with dominant predators have the potential to influence the distribution pattern of subordinate predators.

Extending Joint Models in Community Ecology: A Response to Beissinger et al.

The joint modelling of many variables in community ecology is a new and technically challenging area with many opportunities for future developments. The possibility of extending joint models to deal with imperfect detection has been highlighted by Beissinger et al. as an important problem worthy of further investigation [1]. We agree, and previously pointed to this potential extension as an outstanding question [2], alongside models that can estimate phylogenetic repulsion or attraction, nonlinearity in the response to latent variables, and spatial or temporal correlation, because further developments in all these directions are needed.

Multiscale patterns and drivers of arbuscular mycorrhizal fungal communities in the roots and root‐associated soil of a wild perennial herb

Summary Arbuscular mycorrhizal (AM) fungi form diverse communities and are known to influence above‐ground community dynamics and biodiversity. However, the multiscale patterns and drivers of AM fungal composition and diversity are still poorly understood. We sequenced DNA markers from roots and root‐associated soil from Plantago lanceolata plants collected across multiple spatial scales to allow comparison of AM fungal communities among neighbouring plants, plant subpopulations, nearby plant populations, and regions. We also measured soil nutrients, temperature, humidity, and community composition of neighbouring plants and nonAM root‐associated fungi. AM fungal communities were already highly dissimilar among neighbouring plants (c. 30 cm apart), albeit with a high variation in the degree of similarity at this small spatial scale. AM fungal communities were increasingly, and more consistently, dissimilar at larger spatial scales. Spatial structure and environmental drivers explained a similar percentage of the variation, from 7% to 25%. A large fraction of the variation remained unexplained, which may be a result of unmeasured environmental variables, species interactions and stochastic processes. We conclude that AM fungal communities are highly variable among nearby plants. AM fungi may therefore play a major role in maintaining small‐scale variation in community dynamics and biodiversity.

Related herbivore species show similar temporal dynamics

Within natural communities, different taxa display different dynamics in time. Why this is the case we do not fully know. This thwarts our ability to predict changes in community structure, which is important for both the conservation of rare species in natural communities and for the prediction of pest outbreaks in agriculture. Species sharing phylogeny, natural enemies and/or life-history traits have been hypothesized to share similar temporal dynamics. We operationalized these concepts into testing whether feeding guild, voltinism, similarity in parasitoid community and/or phylogenetic relatedness explained similarities in temporal dynamics among herbivorous community members. Focusing on two similar datasets from different geographical regions (Finland and Japan), we used asymmetric eigenvector maps as temporal variables to characterize species- and community-level dynamics of specialist insect herbivores on oak (Quercus). We then assessed whether feeding guild, voltinism, similarity in parasitoid community and/or phylogenetic relatedness explained similarities in temporal dynamics among taxa. Species-specific temporal dynamics varied widely, ranging from directional decline or increase to more complex patterns. Phylogeny was a clear predictor of similarity in temporal dynamics at the Finnish site, whereas for the Japanese site, the data were uninformative regarding a phylogenetic imprint. Voltinism, feeding guild and parasitoid overlap explained little variation at either location. Despite the rapid temporal dynamics observed at the level of individual species, these changes did not translate into any consistent temporal changes at the community level in either Finland or Japan. Overall, our findings offer no direct support for the notion that species sharing natural enemies and/or life-history traits would be characterized by similar temporal dynamics, but reveal a strong imprint of phylogenetic relatedness. As this phylogenetic signal cannot be attributed to guild, voltinism or parasitoids, it will likely derive from shared microhabitat, microclimate, anatomy, physiology or behaviour. This has important implications for predicting insect outbreaks and for informing insect conservation. We hope that future studies will assess the generality of our findings across plant-feeding insect communities and beyond, and establish the more precise mechanism(s) underlying the phylogenetic imprint.