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Although fine roots are essential for the water and nutrient uptake of plants, there is limited understanding of root trait variation and the underlying mechanism. Here, six first‐order root morphological and chemical traits were measured for 181 species from eight subtropical and boreal forests to test the hypothesis of different phylogenetic and environmental regulations of root morphological and nutrient traits result in the multidimensions of root traits. Two independent root trait dimensions between root thickness and nutrient traits were detected at both species and community levels. At the species level, diameter‐related traits were mainly restricted by phylogenetic structure and showed little plasticity to the changing environments, whereas the variation in woody root nutrient was influenced significantly by soil variables. For community‐level traits, the diameter‐related axis scores of principal component analysis were mainly driven by mean annual temperature through shifting species composition, whereas the root nutrient‐related axis scores were strongly influenced by soil P availability. From both species and community levels, our study confirms, that the root‐thickness‐related dimension and root nutrient dimension represent new support for the multidimensionality of root traits which are driven by different selection pressure. This study also underlines that the community‐aggregated traits might serve as a promising avenue to improve our understanding of community assemblage processes, allowing us to predict changes of vegetation distributions in a changing climate. A plain language summary is available for this article. Plain Language Summary

1. Although the consequences of facilitation at individual and population levels are well known, the community-level consequences of these processes have received much less attention. In particular, the importance of facilitation in determining richness at the entire community level has seldom been evaluated. 2. In this study, we sampled 11 alpine plant communities along the southern Andes in South America, spanning from tropical (25°S) to sub-antarctic latitudes (55°S). Plant communities were dominated by cushion plants, a particular growth form that acts as a nurse plant for other plant species. Through rarefaction curves, we assessed the effectiveness of community sampling and estimated the number of species present within and outside cushions. Non-metric Multidimensional Scaling ordinations (NMDS) were used to assess differences between the species assemblages growing within and outside cushions. Finally, samples from cushions and open areas were combined in a single matrix accounting for the difference in cover between both microhabitats, and through rarefaction curves we assessed how many more species are added to the community due to the presence of cushions. 3. Samples taken within cushions always contained more species than equivalent samples from open areas. However, the magnitude of this difference varied among communities. NMDS ordination indicated that cushions generate species assemblages structurally different from those found in open areas. Inclusion of samples from cushion and open areas in synthetic analyses - where differences in cover were accounted for - indicated that the presence of cushions consistently increased species richness at the entire community level. The magnitude of these increases in species richness varied with habitat severity, with lower values at both extremes of the environmental severity gradient. 4.Synthesis. Facilitative interactions with cushion nurse plants along the high Andes of southern South America changed plant assemblage structure and increased species richness at the entire community level, indicating that facilitative interactions are pivotal in maintaining the diversity of these harsh environments.

The evolution of increased competitive ability (EICA) hypothesis encapsulates the importance of evolution and ecology for biological invasions. According to this proposition, leaving specialist herbivores at home frees introduced plant species from investing limited resources in defense to instead use those resources for growth, selecting for individuals with reduced defense, enhanced growth, and, consequently, increased competitive ability. We took a multispecies approach, including ancestral and non-native populations of seven weeds, as well as seven coexisting local weeds, to explore all three predictions (i.e., lower defense, greater growth, and better ability to compete in non-native than ancestral populations), the generality as an invasion mechanism for a given system, and community-level consequences of EICA. We assessed plant defenses by conducting herbivory trials with a generalist herbivore. Therefore, finding that non-native populations are better defended than ancestral populations would lend support to the shifting defense (SD) hypothesis, an extension of EICA that incorporates the observation that introduced species escape specialists, but encounter generalists. We also manipulated water additions to evaluate how resource availability influences competition in the context of EICA and plant plasticity in our semiarid system. We found that non-native populations of one study species, Centaurea solstitialis, were better defended, grew faster, and exerted stronger suppression on locals than ancestral populations, offering support to EICA through the SD hypothesis. The other species also displayed variation in trait attributes between ancestral and non-native populations, but they did not fully comply with the three predictions of EICA. Notably, differences between those populations generally favored the non-natives. Moreover, non-native populations were, overall, superior at suppressing locals relative to ancestral populations under low water conditions. There were no differences in plasticity among all three groups. These results suggest that evolutionary change between ancestral and nonnative populations is widespread and could have facilitated invasion in our system. Additionally, although trading growth for shifted defense does not seem to be the main operational path for evolutionary change, it may explain the dominance of some introduced species in ruderal communities. Because introduced species dominate communities in disturbed environments around the world, our results are likely generalizable to other systems.

1.Quantifying the variation in community-level fine root (<2mm) traits along ecological gradients or in response to disturbances is essential to unravel the mechanisms of plant community assembly, but available surveys are scarce. Whether fine root traits covary along a one-dimensional economic spectrum, as previously shown for leaves, is highly debated.2.We measured six fine root traits at the community-level along a 69-year succession, with or without annual mowing, offering a unique design of two nested disturbances. We examined whether (i) there is variation and covariation in community-level fine root traits along the succession and in response to mowing and (ii) morphological root traits mirrored analogous leaf traits (using previously acquired data).3.Early-successional communities were herbaceous-dominated (48±6% in <10 year old plots) and possessed fine roots with high specific root length (SRL), low root dry matter content (RDMC) and low root carbon concentration (RCC), while later-successional communities were dominated by woody species (56±9% in >40 year old plots) and possessed opposite trait values. Root nitrogen concentration (RNC) did not vary across communities along the succession. The trait values at community-level were not affected by mowing, except for a reduction in root mass density.4.We found covariation of fine root traits across communities along two dimensions: the first dimension (60% of total variation) represented changes in root foraging capacity (related to SRL) and resource conservation (related to RDMC, RCC, mean root diameter) whereas the second dimension (17 to 20% of the variation) represented variations in RNC, potentially related to root respiration and metabolism.5.SRL and SLA (specific leaf area) were correlated regardless of the mowing regime, but there was no analogous relationship between LDMC (leaf dry matter content) and RDMC in mown communities, showing a decoupling in the investment in tissue density above and belowground.6.Synthesis. Our study demonstrates coordinated variations of community-level fine root traits along a succession gradient and provides evidence that fine root traits covaried along two-dimensions, regardless of mowing regime. The relationship between LDMC and RDMC observed in unmown communities was modified by mowing, reflecting an uncoupled response to mowing.

Question: The community-weighted mean (CWM) approach is an easy way of analysing trait–environment association by regressing (or correlating) the mean trait per plot against an environmental variable and assessing the statistical significance of the slope or the associated correlation coefficient. However, the CWM approach does not yield valid tests, as random traits (or random indicator values) are far too often judged significantly related to the environmental variable, even when the trait and environmental variable are extrinsic to (not derived from) the community data. Existing solutions are the ZS (Zelený & Schaffers) modified test and the max (or sequential) test based on the fourth-corner correlation. Both tests are based on permutations which become cumbersome when many tests need to be carried out and many permutations are required, as in methods that correct for multiple testing. The main goal of this study was to compare these existing permutation-based solutions and to develop a quick and easy parametric test that can replace them. Methods: This study decomposes the fourth-corner correlation in two ways, which suggests a simple parametric approach consisting of assessing the significances of two linear regressions, one plot-level test as in the CWM approach and one species-level test, the reverse of the CWM approach, that regresses the environmental mean per species (i.e. the species niche centroid) on to the trait. The tests are combined by taking the maximum p-value. The type I error rates and power of this parametric max test are examined by simulation of one- and two-dimensional Gaussian models and log-linear models. Results: The ZS-modified test and the fourth-corner max test are conservative in different scenarios, the ZS-modified test being even more conservative than the fourth-corner. The new parametric max test is shown to control the type I error and has equal or even higher power than permutation tests based on the fourth-corner, the ZS-modified test and variants thereof. A weighted version of the new test showed inflated type I error. Conclusion: The combination of two simple regressions is a good alternative to the fourth-corner and the ZS-modified test. This combination is also applicable when multiple trait measurements are made per plot.

Joint species distribution models (JSDMs) have gained considerable traction among ecologists over the past decade, due to their capacity to answer a wide range of questions at both the species‐ and the community‐level. The family of generalised linear latent variable models in particular has proven popular for building JSDMs, being able to handle many response types including presence‐absence data, biomass, overdispersed and/or zero‐inflated counts. We extend latent variable models to handle percent cover response variables, with vegetation, sessile invertebrate and macroalgal cover data representing the prime examples of such data arising in community ecology. Sparsity is a commonly encountered challenge with percent cover data. Responses are typically recorded as percentages covered per plot, though some species may be completely absent or present, that is, have 0% or 100% cover, respectively, rendering the use of beta distribution inadequate. We propose two JSDMs suitable for percent cover data, namely a hurdle beta model and an ordered beta model. We compare the two proposed approaches to a beta distribution for shifted responses, transformed presence‐absence data and an ordinal model for percent cover classes. Results demonstrate the hurdle beta JSDM was generally the most accurate at retrieving the latent variables and predicting ecological percent cover data.

QUESTIONS: Ecologists are increasingly interested in community‐level consequences of biotic interactions. However, community‐level studies have not considered that biotic interactions might have contrasting directions within communities, and indirect interactions are rarely quantified although they may influence community‐level outcomes. We tested the hypotheses that in species‐rich plant communities from intermediate severe environmental conditions: (1) direct facilitation by dominant functional groups is balanced by negative indirect interactions among beneficiary species with no net effect at the community level on diversity and biomass, and (2) both direct and indirect interactions contribute to community composition. LOCATION: A species‐rich subalpine community of the eastern Tibet Plateau (China). METHODS: We removed dominant shrubs and graminoids and quantified, at the community and species levels, their direct and indirect effects on 43 forb species. We used multivariate analyses to assess the contribution of direct and indirect effects on community composition. RESULTS: There were no community‐level effects of either dominant life form on forb diversity and biomass. There were multiple species‐level interactions that we grouped into six types based on the direction and intensity of indirect effects. We found significant relationships between species‐level interactions and community composition. CONCLUSIONS: Our study highlights that communities are sets of hidden interactions that contribute to community composition, although no interaction might be detected at the community level because hidden interactions balance each other. Future studies should assess the ecological and functional drivers of these hidden interactions.

Marine classification schemes based on abiotic surrogates often inform regional marine conservation planning in lieu of detailed biological data. However, these schemes may poorly represent ecologically relevant biological patterns required for effective design and management strategies. We used a community‐level modeling approach to characterize and delineate representative mesoscale (tens to thousands of kilometers) assemblages of demersal fish and benthic invertebrates in the Northwest Atlantic. Hierarchical clustering of species occurrence data from four regional annual multispecies trawl surveys revealed three to six groupings (predominant assemblage types) in each survey region, broadly associated with geomorphic and oceanographic features. Indicator analyses identified 3–34 emblematic taxa of each assemblage type. Random forest classifications accurately predicted assemblage distributions from environmental covariates (AUC > 0.95) and identified thermal limits (annual minimum and maximum bottom temperatures) as important predictors of distribution in each region. Using forecasted oceanographic conditions for the year 2075 and a regional classification model, we projected assemblage distributions in the southernmost bioregion (Scotian Shelf‐Bay of Fundy) under a high emissions climate scenario (RCP 8.5). Range expansions to the northeast are projected for assemblages associated with warmer and shallower waters of the Western Scotian Shelf over the 21st century as thermal habitat on the relatively cooler Eastern Scotian Shelf becomes more favorable. Community‐level modeling provides a biotic‐informed approach for identifying broadscale ecological structure required for the design and management of ecologically coherent, representative, well‐connected networks of Marine Protected Areas. When combined with oceanographic forecasts, this modeling approach provides a spatial tool for assessing sensitivity and resilience to climate change, which can improve conservation planning, monitoring, and adaptive management.

1. Recent evidence suggests that soil nutrient heterogeneity, a ubiquitous feature of terrestrial ecosystems, modulates plant responses to ongoing global change (GC). However, we know little about the overall trends of such responses, the GC drivers involved and the plant attributes affected. 2. We synthesized literature to answer the question: Does soil heterogeneity significantly affect plant responses to main GC drivers, such as elevated atmospheric carbon dioxide concentration (CO 2 ), nitrogen (N) enrichment and changes in rainfall regime? 3. Overall, most studies have addressed short-term effects of N enrichment on the performance of model plant communities using experiments conducted under controlled conditions. The role of soil heterogeneity as a modulator of plant responses to elevated CO 2 may depend on the plasticity in nutrient uptake patterns. Soil heterogeneity does interact with N enrichment to determine plant growth and nutrient status, but the outcome of this interaction has been found to be both synergistic and inhibitory. The very few studies published on interactive effects of soil heterogeneity and changes in rainfall regime prevented us from identifying any general pattern. 4. We identify the long-term consequences of soil heterogeneity on plant community dynamics in the field, and the ecosystem-level responses of the soil heterogeneity × GC driver interaction, as the main knowledge gaps in this area of research. 5. To fill these gaps and take soil heterogeneity and GC research a step forward, we propose the following research guidelines: (i) combining morphological and physiological plant responses to soil heterogeneity with field observations of community composition and predictions from simulation models and (ii) incorporating soil heterogeneity into a trait-based response-effect framework, where plant-resource-use traits are used as both response variables to this heterogeneity and GC, and predictors of ecosystem functioning. 6. Synthesis. There is enough evidence to affirm that soil heterogeneity modulates plant responses to elevated atmospheric CO 2 and N enrichment. Our synthesis indicates that we must explicitly consider soil heterogeneity to accurately predict plant responses to GC drivers.

We introduce community‐level basis function models (CBFMs) as an approach for spatiotemporal joint distribution modelling. CBFMs can be viewed as related to spatiotemporal latent variable models, where the latent variables are replaced by a set of pre‐specified spatiotemporal basis functions which are common across species. In a CBFM, the coefficients that link the basis functions to each species are treated as random slopes. As such, the CBFM can be formulated to have a similar structure to a generalised additive model. This allows us to adapt existing techniques to fit CBFMs efficiently. CBFMs can be used for a variety of reasons, such as inferring patterns of habitat use in space and time, understanding how residual covariation between species varies spatially and/or temporally, and spatiotemporal predictions of species‐ and community‐level quantities. A simulation study and an application to data from a bottom trawl survey conducted across the U.S. Northeast shelf show that CBFMs can achieve similar and sometimes better predictive performance compared to existing approaches for spatiotemporal joint species distribution modelling, while being computationally more scalable.