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  1. Abstract Aim

    Closely related species tend to resemble each other in their morphology and ecology because of shared ancestry. When exploring correlations between species traits, therefore, species cannot be treated as statistically independent. Phylogenetic comparative methods (PCMs) attempt to correct statistically for this shared evolutionary history. Almost all such approaches, however, assume that correlations between traits are constant across the tips of the tree, which we refer to as phylogenetic stationarity. We suggest that this assumption of phylogenetic stationarity might be often violated and that relationships between species traits might evolve alongside clades, for example, owing to the effects of unmeasured traits or other latent variables. Specific examples range from shifts in allometric scaling relationships between clades (e.g., basal metabolic rate and body mass in endotherms, and tree diameter and biomass in trees) to the differing relationship between leaf mass per area and shade tolerance in deciduous versus evergreen trees and shrubs.

    Innovation

    Here, we introduce an exploratory modelling framework, phylogenetically weighted regression, which represents an extension of geographically weighted regression (GWR) used in spatial studies, to allow non‐stationarity in model parameters across a phylogenetic tree. We demonstrate our approach using empirical data on flowering time and seed mass from a well‐studied plant community in southeastern Sweden. Our model reveals strong, diverging trends across the phylogeny, including changes in the sign of the relationship between clades.

    Main conclusions

    By allowing for phylogenetic non‐stationarity, we are able to detect shifting relationships among species traits that would be obscured in traditional PCMs; thus, we suggest that PWR might be an important exploratory tool in the search for key missing variables in comparative analyses.

     
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  2. Abstract Aim

    Previous work demonstrated the global variability of synchrony in tree growth within populations, that is, the covariance of the year‐to‐year variability in growth of individual neighbouring trees. However, there is a lack of knowledge about the causes of this variability and its trajectories through time. Here, we examine whether climate can explain variation in within‐population synchrony (WPS) across space but also through time and we develop models capable of explaining this variation. These models can be applied to the global tree cover under current and future climate change scenarios.

    Location

    Global.

    Time period

    1901–2012.

    Major taxa studied

    Trees.

    Methods

    We estimated WPS values from a global tree‐ring width database consisting of annual growth increment measurements from multiple trees at 3,579 sites. We used generalized linear mixed effects models to infer the drivers of WPS variability and temporal trends of global WPS. We then predicted WPS values across the global extent of tree cover. Finally, we applied our model to predict future WPS based on the RCP 8.5 (2045–2065 period) emission scenario.

    Results

    Areas with the highest WPS are characterized by a combination of environments with both high mean annual temperature (>10°C) and low precipitation (<300 mm). Average WPS across all temperate forests has decreased historically and will continue to decrease. Potential implications of these patterns include changes in forest dynamics, such as higher tree growth and productivity and an increase in carbon sequestration. In contrast, the WPS of tropical forests of Central and South America will increase in the near future owing to reduced annual precipitation.

    Main conclusions

    Climate explains WPS variability in space and time. We suggest that WPS might have value as an integrative ecological measure of the level of environmental stress to which forests are subjected and therefore holds potential for diagnosing effects of global climate change on tree growth.

     
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  3. Abstract Aim

    Climate variability threatens to destabilize production in many ecosystems. Asynchronous species dynamics may buffer against such variability when a decrease in performance by some species is offset by an increase in performance of others. However, high climatic variability can eliminate species through stochastic extinctions or cause similar stress responses among species that reduce buffering. Local conditions, such as soil nutrients, can also alter production stability directly or by influencing asynchrony. We test these hypotheses using a globally distributed sampling experiment.

    Location

    Grasslands in North America, Europe and Australia.

    Time period

    Annual surveys over 5 year intervals occurring between 2007 and 2014.

    Major taxa studied

    Herbaceous plants.

    Methods

    We sampled annually the per species cover and aboveground community biomass [net primary productivity (NPP)], plus soil chemical properties, in 29 grasslands. We tested how soil conditions, combined with variability in precipitation and temperature, affect species richness, asynchrony and temporal stability of primary productivity. We used bivariate relationships and structural equation modelling to examine proximate and ultimate relationships.

    Results

    Climate variability strongly predicted asynchrony, whereas NPP stability was more related to soil conditions. Species richness was structured by both climate variability and soils and, in turn, increased asynchrony. Variability in temperature and precipitation caused a unimodal asynchrony response, with asynchrony being lowest at low and high climate variability. Climate impacted stability indirectly, through its effect on asynchrony, with stability increasing at higher asynchrony owing to lower inter‐annual variability in NPP. Soil conditions had no detectable effect on asynchrony but increased stability by increasing the mean NPP, especially when soil organic matter was high.

    Main conclusions

    We found globally consistent evidence that climate modulates species asynchrony but that the direct effect on stability is low relative to local soil conditions. Nonetheless, our observed unimodal responses to variability in temperature and precipitation suggest asynchrony thresholds, beyond which there are detectable destabilizing impacts of climate on primary productivity.

     
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  4. Abstract Aim

    Plant trait databases often contain traits that are correlated, but for whom direct (undirected statistical dependency) and indirect (mediated by other traits) connections may be confounded. The confounding of correlation and connection hinders our understanding of plant strategies, and how these vary among growth forms and climate zones. We identified the direct and indirect connections across plant traits relevant to competition, resource acquisition and reproductive strategies using a global database and explored whether connections within and between traits from different tissue types vary across climates and growth forms.

    Location

    Global.

    Major taxa studied

    Plants.

    Time period

    Present.

    Methods

    We used probabilistic graphical models and a database of 10 plant traits (leaf area, specific leaf area, mass‐ and area‐based leaf nitrogen and phosphorous content, leaf life span, plant height, stem specific density and seed mass) with 16,281 records to describe direct and indirect connections across woody and non‐woody plants across tropical, temperate, arid, cold and polar regions.

    Results

    Trait networks based on direct connections are sparser than those based on correlations. Land plants had high connectivity across traits within and between tissue types; leaf life span and stem specific density shared direct connections with all other traits. For both growth forms, two groups of traits form modules of more highly connected traits; one related to resource acquisition, the other to plant architecture and reproduction. Woody species had higher trait network modularity in polar compared to temperate and tropical climates, while non‐woody species did not show significant differences in modularity across climate regions.

    Main conclusions

    Plant traits are highly connected both within and across tissue types, yet traits segregate into persistent modules of traits. Variation in the modularity of trait networks suggests that trait connectivity is shaped by prevailing environmental conditions and demonstrates that plants of different growth forms use alternative strategies to cope with local conditions.

     
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