Daniel C. Laughlin

Plant functional traits have globally consistent effects on competition

Phenotypic traits and their associated trade-offs have been shown to have globally consistent effects on individual plant physiological functions, but how these effects scale up to influence competition, a key driver of community assembly in terrestrial vegetation, has remained unclear. Here we use growth data from more than 3 million trees in over 140,000 plots across the world to show how three key functional traits—wood density, specific leaf area and maximum height—consistently influence competitive interactions. Fast maximum growth of a species was correlated negatively with its wood density in all biomes, and positively with its specific leaf area in most biomes. Low wood density was also correlated with a low ability to tolerate competition and a low competitive effect on neighbours, while high specific leaf area was correlated with a low competitive effect. Thus, traits generate trade-offs between performance with competition versus performance without competition, a fundamental ingredient in the classical hypothesis that the coexistence of plant species is enabled via differentiation in their successional strategies. Competition within species was stronger than between species, but an increase in trait dissimilarity between species had little influence in weakening competition. No benefit of dissimilarity was detected for specific leaf area or wood density, and only a weak benefit for maximum height. Our trait-based approach to modelling competition makes generalization possible across the forest ecosystems of the world and their highly diverse species composition.

Applying trait-based models to achieve functional targets for theory-driven ecological restoration

Manipulating community assemblages to achieve functional targets is a key component of restoring degraded ecosystems. The response-and-effect trait framework provides a conceptual foundation for translating restoration goals into functional trait targets, but a quantitative framework has been lacking for translating trait targets into assemblages of species that practitioners can actually manipulate. This study describes new trait-based models that can be used to generate ranges of species abundances to test theories about which traits, which trait values and which species assemblages are most effective for achieving functional outcomes. These models are generalisable, flexible tools that can be widely applied across many terrestrial ecosystems. Examples illustrate how the framework generates assemblages of indigenous species to (1) achieve desired community responses by applying the theories of environmental filtering, limiting similarity and competitive hierarchies, or (2) achieve desired effects on ecosystem functions by applying the theories of mass ratios and niche complementarity. Experimental applications of this framework will advance our understanding of how to set functional trait targets to achieve the desired restoration goals. A trait-based framework provides restoration ecology with a robust scaffold on which to apply fundamental ecological theory to maintain resilient and functioning ecosystems in a rapidly changing world.

The intrinsic dimensionality of plant traits and its relevance to community assembly

Summary Plants are multifaceted organisms that have evolved numerous solutions to the problem of establishing, growing and reproducing with limited resources. The intrinsic dimensionality of plant traits is the minimum number of independent axes of variation that adequately describes the functional variation among plants and is therefore a fundamental quantity in comparative plant ecology. Given the large number of functional traits that are measured on plants, the dimensionality of plant form and function is potentially vast. A variety of linear and nonlinear methods were used to estimate the intrinsic dimensionality of three large trait data sets. The results of these analyses indicate that while the dimensionality of plant traits is generally larger than we have admitted in the past, it does not exceed six in the most comprehensive data set. The dimensionality of plant form and function is a blessing, not a curse. The higher the intrinsic dimension of traits in an analysis, the more easily our models will be able to accurately discriminate species in trait space and therefore be able to predict species distributions and abundances. Recent analyses indicate that the ability to predict community composition increases rapidly with additional traits, but reaches a plateau after four to eight traits. Synthesis. There appears to be a tractable upper limit to the dimensionality of plant traits. To optimize research efficiency for advancing our understanding of trait-based community assembly, ecologists should minimize the number of traits while maximizing the number of dimensions, because including multiple correlated traits does not yield dividends and including more than eight traits leads to diminishing returns. It is recommended to measure traits from multiple organs whenever possible, especially leaf, stem, root and flowering traits, given their consistent performance in explaining community assembly across different ecosystems.

Herbaceous Vegetation Responses (1992–2004) to Restoration Treatments in a Ponderosa Pine Forest

Abstract Ecological restoration treatments are widely applied in southwestern ponderosa pine forests to convert them to an open canopy structure similar to that found at the time of Euro-American settlement. An experiment was initiated in northern Arizona in 1994 to evaluate long-term ecosystem responses to 3 restoration treatments: 1) thinning from below (thinning), 2) thinning from below plus forest floor manipulation with periodic prescribed burning (composite), and 3) an untreated control. Results focus on total herbaceous and functional-group standing crop response to these restoration treatments. Pretreatment data were collected in 1992 and posttreatment responses were measured from 1994 through 2004. Total herbaceous standing crop was significantly higher on the 2 treated areas than on the control over the entire posttreatment period, but did not differ between the thinning and composite treatments. Plant functional groups responded differently to treatments and to drought. In general, the graminoid standing crop responded within several years after the initial treatments and continued to increase through time, until a series of severe droughts reduced standing crop to pretreatment levels. C3 graminoids dominated the standing-crop response, of which bottlebrush squirreltail (Elymus elymoides (Raf.) Swezey ssp. elymoides) was the primary contributor. C4 graminoids had a minimal response to restoration treatments, possibly because they were less abundant before the experiment began or because they were adversely affected by autumn burning. Legumes and forbs exhibited a 4–5 year lag before responding to the thinning and composite treatments. Annual and biennial plants showed a large biomass increase approximately 5 years after implementation of the composite treatment. The restoration goal of optimizing herbaceous standing crop must be weighed against the competing goals of increasing the abundance of specific functional groups, increasing biodiversity or rare plants, and managing invasive plant species.

Reinforcing loose foundation stones in trait‑based plant ecology

The promise of “trait-based” plant ecology is one of generalized prediction across organizational and spatial scales, independent of taxonomy. This promise is a major reason for the increased popularity of this approach. Here, we argue that some important foundational assumptions of trait-based ecology have not received sufficient empirical evaluation. We identify three such assumptions and, where possible, suggest methods of improvement: (i) traits are functional to the degree that they determine individual fitness, (ii) intraspecific variation in functional traits can be largely ignored, and (iii) functional traits show general predictive relationships to measurable environmental gradients.

Fitness of multidimensional phenotypes in dynamic adaptive landscapes

Phenotypic traits influence species distributions, but ecology lacks established links between multidimensional phenotypes and fitness for predicting species responses to environmental change. The common focus on single traits rather than multiple trait combinations limits our understanding of their adaptive value, and intraspecific trait covariation has been neglected in ecology despite its importance in evolutionary theory and its likely impact on species distributions. Here, we extend the adaptive landscape framework to ecological sorting of multidimensional phenotypes across environments and discuss how two analytical approaches can be used to quantify fitness as a function of the interaction between the phenotype and the environment. We encourage ecologists to consider how phenotypic integration will constrain species responses to environmental change.

Effects of an intense prescribed fire on understory vegetation in a mixed conifer forest1

Abstract Huisinga, K. D., D. C. Laughlin, P. Z. Fulé, J. D. Springer, and C. M. McGlone (Ecological Restoration Institute and School of Forestry, Northern Arizona University, Box 15017, Flagstaff, AZ 86011). Effects of an intense prescribed fire on understory vegetation in a mixed conifer forest. J. Torrey Bot. Soc. 132: 590–601. 2005.—Intense prescribed fire has been suggested as a possible method for forest restoration in mixed conifer forests. In 1993, a prescribed fire in a dense, never-harvested forest on the North Rim of Grand Canyon National Park escaped prescription and burned with greater intensity and severity than expected. We sampled this burned area and an adjacent unburned area to assess fire effects on understory species composition, diversity, and plant cover. The unburned area was sampled in 1998 and the burned area in 1999; 25% of the plots were resampled in 2001 to ensure that differences between sites were consistent and persistent, and not due to inter-annual climatic differences. Species composition differed significantly between unburned and burned sites; eight species were identified as indicators of the unburned site and thirteen as indicators of the burned site. Plant cover was nearly twice as great in the burned site than in the unburned site in the first years of measurement and was 4.6 times greater in the burned site in 2001. Average and total species richness was greater in the burned site, explained mostly by higher numbers of native annual and biennial forbs. Overstory canopy cover and duff depth were significantly lower in the burned site, and there were significant inverse relationships between these variables and plant species richness and plant cover. Greater than 95% of the species in the post-fire community were native and exotic plant cover never exceeded 1%, in contrast with other northern Arizona forests that were dominated by exotic species following high-severity fires. This difference is attributed to the minimal anthropogenic disturbance history (no logging, minimal grazing) of forests in the national park, and suggests that park managers may have more options than non-park managers to use intense fire as a tool for forest conservation and restoration.

Root traits are multidimensional: specific root length is independent from root tissue density and the plant economic spectrum

Summary Root, stem and leaf traits are thought to be functionally coordinated to maximize the efficiency of acquiring and using limited resources. However, evidence is mixed for consistent whole-plant trait coordination among woody plants, and we lack a clear understanding of the adaptive value of root traits along soil resource gradients. If fine roots are the below-ground analogue to leaves, then low specific root length (SRL) and high tissue density should be common on infertile soil. Here, we test the prediction that root, stem and leaf traits and relative growth rate respond in unison with soil fertility gradients. We measured fine root, stem and leaf traits and relative growth rate on individual seedlings of 66 tree species grown in controlled conditions. Our objectives were (i) to determine whether multiple root traits align with growth rate, leaf and stem traits and with each other and (ii) to quantify the relationships between community-weighted mean root traits and two strong soil fertility gradients that differed in spatial extent and community composition. At the species level, fast growth rates were associated with low root and stem tissue density and high specific leaf area. SRL and root diameter were not clearly related to growth rate and loaded on a separate principal component from the plant economic spectrum. At the community level, growth rate was positively related to soil fertility, and root tissue density (RTD) and branching were negatively related to soil fertility. SRL was negatively related and root diameter was positively related to soil fertility on the large-scale gradient that included ectomycorrhizal angiosperms. Synthesis. Root, stem and leaf tissue traits of tree seedlings are coordinated and influence fitness along soil fertility gradients. RTD responds in unison with above-ground traits to soil fertility gradients; however, root traits are multidimensional because SRL is orthogonal to the plant economic spectrum. In contrast to leaves, trees are not constrained in the way they construct fine roots: plants can construct high or low SRL roots of any tissue density. High RTD is the most consistent below-ground trait that reflects adaptation to infertile soil.

A strong test of a maximum entropy model of trait‐based community assembly

We evaluate the predictive power and generality of Shipleys maximum entropy (maxent) model of community assembly in the context of 96 quadrats over a 120-km2 area having a large (79) species pool and strong gradients. Quadrats were sampled in the herbaceous understory of ponderosa pine forests in the Coconino National Forest, Arizona, U.S.A. The maxent model accurately predicted species relative abundances when observed community-weighted mean trait values were used as model constraints. Although only 53% of the variation in observed relative abundances was associated with a combination of 12 environmental variables, the maxent model based only on the environmental variables provided highly significant predictive ability, accounting for 72% of the variation that was possible given these environmental variables. This predictive ability largely surpassed that of nonmetric multidimensional scaling (NMDS) or detrended correspondence analysis (DCA) ordinations. Using cross-validation with 1000 independent runs, the median correlation between observed and predicted relative abundances was 0.560 (the 2.5% and 97.5% quantiles were 0.045 and 0.825). The qualitative predictions of the model were also noteworthy: dominant species were correctly identified in 53% of the quadrats, 83% of rare species were correctly predicted to have a relative abundance of < 0.05, and the median predicted relative abundance of species actually absent from a quadrat was 5 x 10(-5).

Advances in modeling trait-based plant community assembly

In this review, we examine two new trait-based models of community assembly that predict the relative abundance of species from a regional species pool. The models use fundamentally different mathematical approaches and the predictions can differ considerably. Maxent obtains the most even probability distribution subject to community-weighted mean trait constraints. Traitspace predicts low probabilities for any species whose trait distribution does not pass through the environmental filter. Neither model maximizes functional diversity because of the emphasis on environmental filtering over limiting similarity. Traitspace can test for the effects of limiting similarity by explicitly incorporating intraspecific trait variation. The range of solutions in both models could be used to define the range of natural variability of community composition in restoration projects.