Showing papers by "Bill Shipley published in 2013"

The AIC model selection method applied to path analytic models compared using a d-separation test.

Abstract: Classical path analysis is a statistical technique used to test causal hypotheses involving multiple variables without latent variables, assuming linearity, multivariate normality, and a sufficient sample size. The d-separation (d-sep) test is a generalization of path analysis that relaxes these assumptions. Although model selection using Akaike's information criterion (AIC) is well established for classical path analysis, this model selection technique has not yet been developed for d-sep tests. In this paper, I explain how to use the AIC statistic for d-sep tests, give a worked example, and include instructions (supplemental material) to implement the analysis in the R computing language.

Inter‐specific and intra‐specific trait variation along short environmental gradients in an old‐growth temperate forest

Abstract: Question When can we assume that inter-specific trait variation is higher than intra-specific trait variation in plant community ecology? Location Old-growth deciduous forest in the Gault Nature Reserve, Mount St. Hilaire (Quebec, Canada,45′32.957″ N, 73′08.884″ W), with a shorter environmental gradient than normally exists in community studies. Methods We measured 15 functional traits on all tree saplings occurring in 39 (5–7-m radius) sample plots. Using variance decomposition from mixed models and from sums of squares of community-weighted traits, we determined the relative importance of temporal, spatial, inter-specific, intra-specific and intra-individual variation in each trait. In total, we collected trait information on 3317 leaves from 786 twigs sampled on 422 saplings. Results For 12 of 15 traits, over 50% of the total variance existed between species and inter-specific variation was always the most important source of variation. However for 14 traits, intra-specific and environmental variation represented up to 28% of the total variation. Variation in community-weighted trait means was mostly generated by changes in species composition, but intra-specific trait variation was the dominate cause for leaf nitrogen, specific leaf area and tree branching. The intra-individual and temporal sources of variation were not important. Conclusions Trait variation should be dominated by inter-specific differences in most studies since they involve systems with more pronounced environmental gradients, higher species richness and more β-diversity than used here. However, in studies with short gradients, or when using more plastic traits, it will be necessary to measure trait values for each site. It is important to quantify the β-diversity of the environmental gradients in question in order to compare results across studies.

Predicting invertebrate herbivory from plant traits: polycultures show strong nonadditive effects.

Abstract: Plant functional traits affect the capacity of herbivores to find, choose, and consume plants. However, in a community composed of different plant species, it is unclear what proportion of herbivory on a focal plant is explained by its own traits and which is explained by the characteristics of the surrounding vegetation (i.e., nonadditive effects). Moreover, nonadditive effects could be positive or negative, and it is not known if they are related to community properties such as diversity. To quantify nonadditive effects, we developed four different additive models based on monoculture herbivory rates or plant traits and combined them with measurements of standing invertebrate herbivore damage along an experimental plant diversity gradient ranging from monocultures to 60-species mixtures. In all four models, positive nonadditive effects were detected, i.e., herbivory levels were higher in polycultures than what was expected from monoculture data, and these effects contributed up to 25% of the observed variance in herbivory. Importantly, the nonadditive effects, which were defined as the deviance of the models' predictions from the observed herbivory, were positively correlated with the communities' plant species richness. Consequently, interspecific interactions appear to have an important impact on the levels of herbivory of a community. Identifying those community properties that capture the effects of these interactions is a next important challenge for our understanding of how the environment interacts with plant traits to drive levels of herbivory.

Trait-based climate change predictions of plant community structure in arid steppes

Abstract: Summary 1. Global climate change is possibly one of the most important challenges for current and future human populations due to its wide-ranging effects on ecosystems. Global prediction models suggest that in some areas of the world (e.g. Northern Africa, Central America) an increase in aridity might strongly disturb agricultural production and affect food security. To counterbalance these negative effects, reliable predictive models are needed to anticipate ecosystem changes. 2. We tested the ability of the Community Assembly by Trait-based Selection (CATS) model that is based on the principle of maximum entropy and trait-based environmental filtering, to predict actual and future plant community composition in the arid steppes of eastern Morocco. Specifically, we asked whether this model was adequate for predicting actual community composition, based on predicted community-weighted mean (CWM) traits, and what would be the changes in community composition under various scenarios of climate change for the period 2080—2099. 3. The CATS model could predict > 90% of actual community composition if the actual CWM traits were known but only ~40% if the CWM values were predicted from estimated aridity and grazing values. The predictions of community composition for 2080—2099 suggested that, regardless of the climate change scenario considered, the dominant group in grazed and ungrazed sites would shift from ruderal species to stress-tolerant sub-shrubs, which would constitute up over 80% of total community composition in some cases. 4. Synthesis. Our findings suggest that effects of climate change will strongly modify plant community structure in arid steppes, possibly accentuating the process of desertification, and reducing the pastoral value of the vegetation. Future research efforts should concentrate on the identification of strong trait–environment relationships to improve model predictions.

Linking plant and insect traits to understand multitrophic community structure in arid steppes

Abstract: Summary 1. Animal ecology could benefit from a well-defined trait-based framework, mostly applied in plant ecology, to further develop predictions of animal communities under various environmental conditions. We extended the functional approach to a multitrophic system by combining plant and ant traits in relation to environmental conditions to study the relationships between these three components. 2. We sampled plant and ant abundances along an aridity gradient in grazed and ungrazed conditions in the arid steppes of eastern Morocco. We measured five plant functional traits related to water stress and grazing resistance and six ant functional traits related to body size, dispersal and behaviour. We related each component (environment, vegetation and ants) using Mantel partial correlations to uncover the causal structure between components and using a fourthcorner analysis to describe the effects of the environment and vegetation on ant communities. 3. Results indicated that vegetation had a direct effect on ant community composition while the environment only had an indirect effect on ant community composition through vegetation structure. This result was consistent when looking at both the taxonomic and functional composition of communities, but correlations were stronger when based on taxonomic composition. Aridity was the variable most significantly linked with ant functional traits 4. Synthesis. The use of functional traits in animal ecology is relatively new, and an increase in trait-based community ecology studies that include more than one trophic level would be beneficial in identifying trait-based patterns in multitrophic communities. This new approach could become very useful in identifying mechanistic explanations of multitrophic community assembly and making predictions about their evolution under changing environmental conditions. It could also be of practical use in conservation biology in assessing habitat quality.