Land use intensification has led to conspicuous changes in plant and animal communities across the world. Shifts in trait‐based functional composition have recently been hypothesized to manifest at lower levels of environmental change when compared to species‐based taxonomic composition; however, little is known about the commonalities in these responses across taxonomic groups and geographic regions. We investigated this hypothesis by testing for taxonomic and geographic similarities in the composition of riverine fish and insect communities across gradients of land use in major hydrological regions of the conterminous United States. We analyzed an extensive data set representing 556 species and 33 functional trait modalities from 8023 fish communities and 1434 taxa and 50 trait modalities from 5197 aquatic insect communities. Our results demonstrate abrupt threshold changes in both taxonomic and functional community composition due to land use conversion. Functional composition consistently demonstrated lower land use threshold responses compared to taxonomic composition for both fish (urban
Communities are the emergent outcome of individual‐level trait–environment interactions. In this issue of the
- NSF-PAR ID:
- 10243756
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Journal of Vegetation Science
- Volume:
- 28
- Issue:
- 1
- ISSN:
- 1100-9233
- Format(s):
- Medium: X Size: p. 4-6
- Size(s):
- ["p. 4-6"]
- Sponsoring Org:
- National Science Foundation
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Abstract p = 0.069; agriculturep = 0.029) and insect (urbanp = 0.095; agriculturep = 0.043) communities according to gradient forest models. We found significantly lower thresholds for urban versus agricultural land use for fishes (taxonomic and functionalp < 0.001) and insects (taxonomicp = 0.001; functionalp = 0.033). We further revealed that threshold responses in functional composition were more geographically consistent than for taxonomic composition to both urban and agricultural land use change. Traits contributing the most to overall functional composition change differed along urban and agricultural land gradients and conformed to predicted ecological mechanisms underpinning community change. This study points to reliable early‐warning thresholds that accurately forecast compositional shifts in riverine communities to land use conversion, and highlight the importance of considering trait‐based indicators of community change to inform large‐scale land use management strategies and policies. -
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Abstract Traits differentially adapt plant species to particular conditions generating compositional shifts along environmental gradients. As a result, community‐scale trait values show concomitant shifts, termed trait‒environment relationships. Trait‒environment relationships are often assessed by evaluating community‐weighted mean (CWM) traits observed along environmental gradients. Regression‐based approaches (CWMr) assume that local communities exhibit traits centred at a single optimum value and that traits do not covary meaningfully. Evidence suggests that the shape of trait‒abundance relationships can vary widely along environmental gradients—reflecting complex interactions—and traits are usually interrelated. We used a model that accounts for these factors to explore trait‒environment relationships in herbaceous forest plant communities in Wisconsin (USA).
We built a generalized linear mixed model (GLMM) to analyse how abundances of 185 species distributed among 189 forested sites vary in response to four functional traits (vegetative height—VH, leaf size—LS, leaf mass per area—LMA and leaf carbon content), six environmental variables describing overstorey, soil and climate conditions, and their interactions. The GLMM allowed us to assess the nature and relative strength of the resulting 24 trait‒environment relationships. We also compared results between GLMM and CWMr to explore how conclusions differ between approaches.
The GLMM identified five significant trait‒environment relationships that together explain ~40% of variation in species abundances across sites. Temperature appeared as a key environmental driver, with warmer and more seasonal sites favouring taller plants. Soil texture and temperature seasonality affected LS and LMA; seasonality effects on LS and LMA were nonlinear, declining at more seasonal sites. Although often assumed for CWMr, only some traits under certain conditions had centred optimum trait‒abundance relationships. CWMr more liberally identified (13) trait‒environment relationships as significant but failed to detect the temperature seasonality‒LMA relationship identified by the GLMM.
Synthesis . Although GLMM represents a more methodologically complex approach than CWMr, it identified a reduced set of trait‒environment relationships still capable of accounting for the responses of forest understorey herbs to environmental gradients. It also identified separate effects of mean and seasonal temperature on LMA that appear important in these forests, generating useful insights and supporting broader application of GLMM approach to understand trait‒environment relationships. -
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Abstract Estimating phenotypic distributions of populations and communities is central to many questions in ecology and evolution. These distributions can be characterized by their moments (mean, variance, skewness and kurtosis) or diversity metrics (e.g. functional richness). Typically, such moments and metrics are calculated using community‐weighted approaches (e.g. abundance‐weighted mean). We propose an alternative bootstrapping approach that allows flexibility in trait sampling and explicit incorporation of intraspecific variation, and show that this approach significantly improves estimation while allowing us to quantify uncertainty.
We assess the performance of different approaches for estimating the moments of trait distributions across various sampling scenarios, taxa and datasets by comparing estimates derived from simulated samples with the true values calculated from full datasets. Simulations differ in sampling intensity (individuals per species), sampling biases (abundance, size), trait data source (local vs. global) and estimation method (two types of community‐weighting, two types of bootstrapping).
We introduce the
traitstrap R package, which contains a modular and extensible set of bootstrapping and weighted‐averaging functions that use community composition and trait data to estimate the moments of community trait distributions with their uncertainty. Importantly, the first function in the workflow,trait_fill , allows the user to specify hierarchical structures (e.g. plot within site, experiment vs. control, species within genus) to assign trait values to each taxon in each community sample.Across all taxa, simulations and metrics, bootstrapping approaches were more accurate and less biased than community‐weighted approaches. With bootstrapping, a sample size of 9 or more measurements per species per trait generally included the true mean within the 95% CI. It reduced average percent errors by 26%–74% relative to community‐weighting. Random sampling across all species outperformed both size‐ and abundance‐biased sampling.
Our results suggest randomly sampling ~9 individuals per sampling unit and species, covering all species in the community and analysing the data using nonparametric bootstrapping generally enable reliable inference on trait distributions, including the central moments, of communities. By providing better estimates of community trait distributions, bootstrapping approaches can improve our ability to link traits to both the processes that generate them and their effects on ecosystems.
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Abstract Ecological restoration outcomes are highly variable, undermining efforts to recover biodiversity and ecosystem functions. One poorly understood source of variability is ‘year effects’—interannual variation in environmental conditions during the first year of restoration that alter successional trajectories of plant communities.
There have been few experimental tests disentangling planting years from other differences among restoration projects (e.g. edaphic conditions, restoration approach), particularly those resolving mechanisms for year effects such as planting‐year rainfall. Moreover, past year effect studies focused almost exclusively on species‐level consequences. Therefore, the extent to which year effects influence the traits of communities is unknown.
To address these gaps and provide a mechanistic test of how precipitation contributes to year effects, we conducted an experiment where we manipulated rainfall (drought, average and high levels) during the first growing season, replicated across three establishment year treatments to disentangle the effects of precipitation from other drivers of year effects. In each establishment year, we seeded the same species mix to initiate grassland restoration. We then surveyed plant community compositions annually for 5 years to quantify trait responses of restored communities to planting year rainfall.
We found that variation in planting‐year precipitation altered community assembly trajectories by influencing community‐weighted mean (CWM) trait composition, and these effects persisted for at least 5 years. Over time, CWM specific leaf area and CWM seed mass decreased and CWM plant height increased. The effect of age on CWM plant height was stronger in plots that received mean and high watering treatments compared to drought treatments. This effect was also observed for CWM seed mass, albeit weaker.
We also found some evidence for planting year effects unrelated to planting‐year rainfall for the three CWM traits, illustrating how interannually varying environmental conditions besides rainfall can generate persistent year effect on plant communities through their traits.
Synthesis and applications . Our results provide evidence for planting year rainfall interacting with community assembly to alter the functional trait composition of restored grasslands. This suggests that interannual variation in rainfall during establishment is an important source of divergent biodiversity and functional outcomes in restored grasslands. -
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Abstract Environmental gradients act as potent filters on species distributions driving compositional shifts across communities. Compositional shifts may reflect differences in physiological tolerances to a limiting resource that result in broad distributions for tolerant species and restricted distributions for intolerant species (i.e. a nested pattern). Alternatively, trade‐offs in resource use or conflicting species' responses to multiple resources can result in complete turnover of species along gradients.
We combined trait (leaf area, leaf mass per area, wood density and maximum height) and distribution data for 550 tree species to examine taxonomic and functional composition at 72 sites across strong gradients of soil phosphorus (P) and rainfall in central Panama.
We determined whether functional and taxonomic composition was nested or turned over completely and whether community mean traits and species composition were more strongly driven by P or moisture.
Turnover characterized the functional composition of tree communities. Leaf traits responded to both gradients, with species having larger and thinner leaves in drier and more fertile sites than in wetter and less fertile sites. These leaf trait–moisture relationships contradict predictions based on drought responses and suggest a greater role for differences in light availability than in moisture. Shifts in wood density and maximum height were weaker than for leaf traits with taller species dominating wet sites and low wood density species dominating P‐rich sites.
Turnover characterized the taxonomic composition of tree communities. Geographic distances explained a larger fraction of variation for taxonomic composition than for functional composition, and community mean traits were more strongly driven by P than moisture.
Synthesis . Our results offer weak support for the tolerance hypothesis for tree communities in central Panama. Instead, we observe functional and taxonomic turnover reflecting trade‐offs and conflicting species' responses to multiple abiotic factors including moisture, soil phosphorus and potentially other correlated variables (e.g. light).
