Multidimensional Trait Space Research Articles

New insights from multidimensional trait space responses to competition in two clonal plant species

Abstract Trait intraspecific variability determines community dynamics and species coexistence. In response to competition, plants can display intraspecific variability to enhance their competitive ability or stabilise their niche differences with competitors. This response is multidimensional because it involves changes along different functional axes and inevitable trade‐offs between traits. Here, we transposed the recent concept of the multidimensional trait space to the analysis of intraspecific plant response to competition. We specifically tested the following: (a) in the absence of competitors, the plant multidimensional trait space will be packed towards strategies promoting plant colonisation; and (b) with competitors, the plant multidimensional trait space will be directed towards competition with its size and shaping characteristics dependent on competitor species richness. We studied trait intraspecific variability of two clonal species, Brachypodium pinnatum (L.) P. Beauv. and Elytrigia repens (L.) Gould, in response to competition. We analysed plant response in the absence of competitors and in competition. Competition treatments included intraspecific and interspecific experimental mixtures with increasing species richness. For each target species and each treatment, we built an hypervolume based on six traits involved in the three‐dimensional competition (i.e., ramet and connection traits). We measured these hypervolumes for their size, similarity and the contribution of traits in their shaping. In the absence of competitors and for both species, we demonstrated a multidimensional trait space packing towards a colonisation strategy. Under competition, the multidimensional trait spaces of the two target species were the widest at the extremes of the richness gradient, that is, intraspecific and interspecific high richness competition treatments. High intraspecific variability either promoted niche differentiation from individuals of similar species or reflected the large range of competitive responses deployed when plants were faced with many different competitor identities. The multidimensional response process was based on fine adjustments of various traits depending on the surrounding neighbourhood composition and more specifically, on the competitor functional similarity with the target species. This study emphasises the multidimensionality of species competitive response, and also underlines the so far neglected importance of competitor species richness for trait intraspecific variability and subsequently community assembly. A plain language summary is available for this article.

Invasive plants in Minnesota are “joining the locals”: A trait‐based analysis

AbstractQuestionsPredicting which newly arrived species will establish and become invasive is a problem that has long vexed researchers. In a study of cold temperate oak forest stands, we examined two contrasting hypotheses regarding plant functional traits to explain the success of certain non‐native species. Under the “join the locals” hypothesis, successful invaders are expected to share traits with resident species because they employ successful growth strategies under light‐limited understorey conditions. Instead, under the “try harder” hypothesis, successful invaders are expected to have traits different from native species in order to take advantage of unused niche space.LocationMinnesota, USA.MethodsWe examined these two theories using 109 native and 11 non‐native plants in 68 oak forest stands. We focused on traits related to plant establishment and growth, including specific leaf area (SLA), leaf carbon‐to‐nitrogen ratio (C:N), wood density, plant maximum height, mycorrhizal type, seed mass and growth form. We compared traits of native and non‐native species using ordinations in multidimensional trait space and compared community‐weighted mean (CWM) trait values across sites.ResultsWe found few differences between trait spaces occupied by native and non‐native species. Non‐native species occupied smaller areas of trait space than natives, yet were within that of the native species, indicating similar growth strategies. We observed a higher proportion of non‐native species in sites with higher native woody species CWM SLA and lower CWM C:N. Higher woody CWM SLA was observed in sites with higher soil pH, while lower CWM C:N was found in sites with higher light levels.ConclusionsNon‐native plants in this system have functional traits similar to natives and are therefore “joining the locals.” However, non‐native plants may possess traits toward the acquisitive end of the native plant trait range, as evidenced by higher non‐native plant abundance in high‐resource environments.

Friendship across species borders: factors that facilitate and constrain heterospecific sociality.

Our understanding of animal sociality is based almost entirely on single-species sociality. Heterospecific sociality, although documented in numerous taxa and contexts, remains at the margins of sociality research and is rarely investigated in conjunction with single-species sociality. This could be because heterospecific and single-species sociality are thought to be based on fundamentally different mechanisms. However, our literature survey shows that heterospecific sociality based on mechanisms similar to single-species sociality is reported from many taxa, contexts and for various benefits. Therefore, we propose a conceptual framework to understand conspecific versus heterospecific social partner choice. Previous attempts, which are all in the context of social information, model partner choice as a trade-off between information benefit and competition cost, along a single phenotypic distance axis. Our framework of partner choice considers both direct grouping benefits and information benefits, allows heterospecific and conspecific partners to differ in degree and qualitatively, and uses a multi-dimensional trait space analysis of costs (competition and activity matching) and benefits (relevance of partner and quality of partner). We conclude that social partner choice is best-viewed as a continuum: some social benefits are obtainable only from conspecifics, some only from dissimilar heterospecifics, while many are potentially obtainable from conspecifics and heterospecifics.This article is part of the theme issue 'Collective movement ecology'.

A population genetic interpretation of GWAS findings for human quantitative traits.

Human genome-wide association studies (GWASs) are revealing the genetic architecture of anthropomorphic and biomedical traits, i.e., the frequencies and effect sizes of variants that contribute to heritable variation in a trait. To interpret these findings, we need to understand how genetic architecture is shaped by basic population genetics processes—notably, by mutation, natural selection, and genetic drift. Because many quantitative traits are subject to stabilizing selection and because genetic variation that affects one trait often affects many others, we model the genetic architecture of a focal trait that arises under stabilizing selection in a multidimensional trait space. We solve the model for the phenotypic distribution and allelic dynamics at steady state and derive robust, closed-form solutions for summary statistics of the genetic architecture. Our results provide a simple interpretation for missing heritability and why it varies among traits. They predict that the distribution of variances contributed by loci identified in GWASs is well approximated by a simple functional form that depends on a single parameter: the expected contribution to genetic variance of a strongly selected site affecting the trait. We test this prediction against the results of GWASs for height and body mass index (BMI) and find that it fits the data well, allowing us to make inferences about the degree of pleiotropy and mutational target size for these traits. Our findings help to explain why the GWAS for height explains more of the heritable variance than the similarly sized GWAS for BMI and to predict the increase in explained heritability with study sample size. Considering the demographic history of European populations, in which these GWASs were performed, we further find that most of the associations they identified likely involve mutations that arose shortly before or during the Out-of-Africa bottleneck at sites with selection coefficients around s = 10−3.

Multidimensional trait space informed by a mechanistic model of tree growth and carbon allocation

AbstractPlant functional traits research has revealed many interesting and important patterns among morphological, physiological, and life‐history traits and the environment. These are exemplified in trade‐offs between groups of traits such as those embodied in the leaf and wood economics spectra. Inferences from empirical studies are often constrained by the correlative nature of the analyses, availability of trait data, and a focus on easily measured traits. However, empirical studies have been fundamental to modeling endeavors aiming to enhance our understanding of how functional traits scale up to affect, for example, community dynamics and ecosystem productivity. Here, we take a complementary approach utilizing an individual‐based model of tree growth and mortality (the allometrically constrained growth and carbon allocation [ACGCA] model) to investigate the theoretical trait space (TTS) of North American trees. The model includes 32 parameters representing allometric, physiological, and anatomical traits, some overlapping leaf and wood economics spectra traits. Using a Bayesian approach, we fit the ACGCA model to individual tree heights and diameters from the USFS Forest Inventory and Analysis (FIA) dataset, with further constraints by literature‐based priors. Fitting the model to 1.3 million FIA records—aggregated across individuals, species, and sites—produced a posterior distribution of traits leading to realistic growth. We explored this multidimensional posterior distribution (the TTS) to evaluate trait–trait relationships emerging from the ACGCA model, and compare these against empirical patterns reported in the literature. Only three notable bivariate correlations, among 496 possible trait pairs, were contained in the TTS. However, stepwise regressions uncovered a complicated structure; only a subset of traits—related to photosynthesis (e.g., radiation‐use efficiency and maintenance respiration)—exhibited strong multivariate trade‐offs with each other, while half of the traits—mostly related to allometries and construction costs—varied independently of other traits. Interestingly, specific leaf area was related to several rarely measured root traits. The trade‐offs contained in the TTS generally reflect mass‐balance (related to carbon allocation) and engineering (mostly related to allometries) trade‐offs represented in the ACGCA model and point to potentially important traits that are under‐explored in field studies (e.g., root traits and branch senescence rates).

Linking functional diversity and ecosystem processes: A framework for using functional diversity metrics to predict the ecosystem impact of functionally unique species

Abstract Functional diversity (FD) metrics are widely used to assess invasion ecosystem impacts, but we have limited theory to predict how FD should respond to invasion. A key challenge to effectively using FD metrics is the complexity of conceptualizing alterations to multidimensional trait space, making it difficult to select a priori the most appropriate metric for specific ecological questions. Here, we provide expectations on how invasion should change four commonly used FD metrics—functional richness (FRic), evenness (FEve), divergence (FDiv) and dispersion (FDis)—and then test these expectations in a laboratory decomposition experiment. We simulate invasion of a forest by understorey plants by adding leaf litter from 18 natives and non‐natives to a representative canopy tree litter mixture to test changes in FD and decomposition. All four metrics changed predictably with invasion. Species that were more functionally unique or when added at greater proportions had larger impacts on FD. Overall, FRic, FEve and FDiv were poor choices for understanding impacts of non‐native species. FDis was the only metric that both changed predictably with addition of understorey litter and correlated intuitively with changes in carbon mineralization. Furthermore, ranking species based upon how much they changed FDis of the litter mixture provided a fair assessment of which species had the largest impact on decomposition. As such, functional dispersion may be a key tool for predicting a priori which non‐natives will have the greatest impact on ecosystem processes. Synthesis. We highlight the need to assess the suitability of each functional diversity metric for the specific ecological question at hand. Our work reveals the pitfalls of considering multiple metrics or randomly choosing a single metric without suitability assessments. At the same time, it suggests a framework for metric assessment that should help lead to selection of a metric or metrics that provide robust a priori insights into how invasion by non‐native species can impact ecosystem processes.

Intransitivity is infrequent and fails to promote annual plant coexistence without pairwise niche differences.

Intransitive competition is often projected to be a widespread mechanism of species coexistence in ecological communities. However, it is unknown how much of the coexistence we observe in nature results from this mechanism when species interactions are also stabilized by pairwise niche differences. We combined field-parameterized models of competition among 18 annual plant species with tools from network theory to quantify the prevalence of intransitive competitive relationships. We then analyzed the predicted outcome of competitive interactions with and without pairwise niche differences. Intransitive competition was found for just 15-19% of the 816 possible triplets, and this mechanism was never sufficient to stabilize the coexistence of the triplet when the pair-wise niche differences between competitors were removed. Of the transitive and intransitive triplets, only four were predicted to coexist and these were more similar in multidimensional trait space defined by 11 functional traits than non-coexisting triplets. Our results argue that intransitive competition may be less frequent than recently posed, and that even when it does operate, pairwise niche differences may be key to possible coexistence.

Single-cell mass spectrometry reveals the importance of genetic diversity and plasticity for phenotypic variation in nitrogen-limited Chlamydomonas.

Phenotypic variation is vital for microbial populations to survive environmental perturbations. Both genetic and non-genetic factors contribute to an organism's phenotypic variation and therefore its fitness. To investigate the correlation between genetic diversity and phenotypic variation, we applied our recently developed mass spectrometry method that allows for the simultaneous measurement of more than 25 different lipids and pigments with high throughput in the unicellular microalga Chlamydomonas reinhardtii. We monitored the impact of nitrogen limitation on a genetically diverse wild-type strain CC-1690 and two isoclonal isolates from CC-1690 named ANC3 and ANC5. Measuring molecular composition of thousands of single cells at different time points of the experiment allowed us to capture a dynamic picture of the phenotypic composition and adaptation of the populations over time. Although the genetically diverse population maintained phenotypic variation over the whole time course of the experiment, the isoclonal cultures showed higher synchronicity in their phenotypic response. Furthermore, the genetically diverse population showed equal or greater phenotypic variation over the whole time range in multidimensional trait space compared with isoclonal populations. However, along individual trait axes non-genetic variance was higher in isoclonal populations.

Morphology predicts species' functional roles and their degree of specialization in plant-frugivore interactions.

Species' functional roles in key ecosystem processes such as predation, pollination or seed dispersal are determined by the resource use of consumer species. An interaction between resource and consumer species usually requires trait matching (e.g. a congruence in the morphologies of interaction partners). Species' morphology should therefore determine species' functional roles in ecological processes mediated by mutualistic or antagonistic interactions. We tested this assumption for Neotropical plant-bird mutualisms. We used a new analytical framework that assesses a species's functional role based on the analysis of the traits of its interaction partners in a multidimensional trait space. We employed this framework to test (i) whether there is correspondence between the morphology of bird species and their functional roles and (ii) whether morphologically specialized birds fulfil specialized functional roles. We found that morphological differences between bird species reflected their functional differences: (i) bird species with different morphologies foraged on distinct sets of plant species and (ii) morphologically distinct bird species fulfilled specialized functional roles. These findings encourage further assessments of species' functional roles through the analysis of their interaction partners, and the proposed analytical framework facilitates a wide range of novel analyses for network and community ecology.

Individual‐level trait diversity concepts and indices to comprehensively describe community change in multidimensional trait space

Summary Global environmental change can influence ecosystem processes directly or through changes in the trait composition of natural communities. Traits are individual‐level features of organisms, and theory predicts that diversity in traits should relate to ecosystem processes. Validated indices that account for both intra‐ and interspecific trait variation in multidimensional trait space are lacking. In this article, we highlight how an individual‐level perspective requires new concepts for trait diversity (TD) and we validate a set of measures suitable to study trait richness, evenness and divergence at the individual scale. First, we tested a selection of multivariate indices for trait richness, evenness and divergence from the literature (FRic, FEve, FDis and the Rao coefficient) using simulated and real individual‐level data. We compared the observed changes in the tested indices with those predicted from their expected/required behaviour (i.e. increase or decrease under specific manipulation of community trait structure) and found unsatisfactory results only for FRic and FEve, whereas FDis and the Rao coefficient showed the expected changes. Therefore, we propose two novel concepts and related indices for individual‐level trait richness (TOP = trait onion peeling) and evenness (TED = trait even distribution). TOP represents the sum of all successive convex hull areas touching all individuals (points) within a multidimensional trait distribution. TED is a measure of how evenly distributed are individuals within the multidimensional trait space. It is calculated comparing the probability distributions of pairwise distances between individuals and between points of a perfectly even reference distribution. We tested TOP and TED on the same simulated and real data as above, and results indicated appropriate behaviour for TOP (trait richness) and TED (trait evenness). By validating TD indices in an individual‐level context, this study contributes to the expansion of functional ecology towards individual‐level dynamics. Future comprehensive investigations of individual trait differences in natural communities may improve our understanding of the pathways by which environmental changes affect ecosystem functioning through biodiversity change.

Variation in trait trade-offs allows differentiation among predefined plant functional types: implications for predictive ecology.

Plant functional types (PFTs) aggregate the variety of plant species into a small number of functionally different classes. We examined to what extent plant traits, which reflect species' functional adaptations, can capture functional differences between predefined PFTs and which traits optimally describe these differences. We applied Gaussian kernel density estimation to determine probability density functions for individual PFTs in an n-dimensional trait space and compared predicted PFTs with observed PFTs. All possible combinations of 1-6 traits from a database with 18 different traits (total of 18 287 species) were tested. A variety of trait sets had approximately similar performance, and 4-5 traits were sufficient to classify up to 85% of the species into PFTs correctly, whereas this was 80% for a bioclimatically defined tree PFT classification. Well-performing trait sets included combinations of correlated traits that are considered functionally redundant within a single plant strategy. This analysis quantitatively demonstrates how structural differences between PFTs are reflected in functional differences described by particular traits. Differentiation between PFTs is possible despite large overlap in plant strategies and traits, showing that PFTs are differently positioned in multidimensional trait space. This study therefore provides the foundation for important applications for predictive ecology.

Origins, bottlenecks, and present-day diversity: patterns of morphospace occupation in marine bivalves.

It has long been known that species should not be distributed randomly in morphospace (a multidimensional trait space), even under simple models of evolution. However, recent studies suggest that position in morphospace can affect aspects of evolution such as the durations of clades and the species richness of their constituent taxa. Here we investigate the dynamics of morphospace occupancy in living and fossil marine bivalves using shell size and aspect ratio, two functionally important traits. Multiple lines of evidence indicate that the center of a family's morphospace today represents a location where taxonomic diversity is maximized, apparently owing to lower extinction rates. Within individual bivalve families, species with narrow geographic ranges are distributed throughout the morphospace but widespread species, which are generally expected to be extinction resistant, tend to be concentrated near the center. The morphospace centers of most species-rich families today (defined as the median value for all species in the family) tend to be close to the positions of the family founders, further suggesting an association between position in morphospace and net diversification rates. However, trajectories of individual subclades (genera) are inconsistent with the center of morphospace being an evolutionary attractor.

Disentangling Coordination among Functional Traits Using an Individual-Centred Model: Impact on Plant Performance at Intra- and Inter-Specific Levels

BackgroundPlant functional traits co-vary along strategy spectra, thereby defining trade-offs for resource acquisition and utilization amongst other processes. A main objective of plant ecology is to quantify the correlations among traits and ask why some of them are sufficiently closely coordinated to form a single axis of functional specialization. However, due to trait co-variations in nature, it is difficult to propose a mechanistic and causal explanation for the origin of trade-offs among traits observed at both intra- and inter-specific level.Methodology/Principal FindingsUsing the Gemini individual-centered model which coordinates physiological and morphological processes, we investigated with 12 grass species the consequences of deliberately decoupling variation of leaf traits (specific leaf area, leaf lifespan) and plant stature (height and tiller number) on plant growth and phenotypic variability. For all species under both high and low N supplies, simulated trait values maximizing plant growth in monocultures matched observed trait values. Moreover, at the intraspecific level, plastic trait responses to N addition predicted by the model were in close agreement with observed trait responses. In a 4D trait space, our modeling approach highlighted that the unique trait combination maximizing plant growth under a given environmental condition was determined by a coordination of leaf, root and whole plant processes that tended to co-limit the acquisition and use of carbon and of nitrogen.Conclusion/SignificanceOur study provides a mechanistic explanation for the origin of trade-offs between plant functional traits and further predicts plasticity in plant traits in response to environmental changes. In a multidimensional trait space, regions occupied by current plant species can therefore be viewed as adaptive corridors where trait combinations minimize allometric and physiological constraints from the organ to the whole plant levels. The regions outside this corridor are empty because of inferior plant performance.

Do alien plant species profit more from high resource supply than natives? A trait-based analysis

Aim Previous studies comparing conditions of high- versus low-resource environments have pointed at differences in key traits that would allow aliens to perform better than natives under high-resource conditions. We generalize and test the robustness of this idea by exploring how trait differentiation between aliens and natives changes along continuous resource gradients. Location Global. Methods We constructed a database of three leaf traits (specific leaf area, SLA; photosynthetic capacity, Amass; leaf nitrogen content, Nmass) that are important for carbon capturing strategies in plants. The database includes 2448 native and 961 alien species over 88 locations world-wide. Using rank correlations and mixed-effect linear models, we assessed the relations between plant traits and climatic, edaphic and human disturbance gradients. Then we determined how the differences in traits between natives and aliens changed along the same gradients. Results Across all environments, aliens were found to have higher SLA, Nmass and Amass than natives. These differences were observed both globally and when controlling for co-occurrence. Also, higher average trait values were found in higher resource supply environments. However, trait differences between natives and aliens remained constant along the evaluated environmental and disturbance gradients. When compared in a multidimensional trait space defined by the leaf economics spectrum, co-occurring aliens and natives showed no between-group differences and no relation with any of the evaluated gradients. Main conclusions We suggest that although increased resource availability is positively related to higher carbon capture strategies (determined via higher plant leaf trait values), these benefits remain the same for aliens and natives. Therefore, we conclude that high-resource environments do not specifically cause aliens to outperform natives with respect to carbon capture, or at least not more than in other environments.

Coevolution in multidimensional trait space favours escape from parasites and pathogens

Almost all species are subject to continuous attack by parasites and pathogens. Because parasites and pathogens tend to have shorter generation times and often experience stronger selection due to interaction than their victims do, it is frequently argued that they should evolve more rapidly and thus maintain an advantage in the evolutionary race between defence and counter-defence. This prediction generates an apparent paradox: how do victim species survive and even thrive in the face of a continuous onslaught of more rapidly evolving enemies? One potential explanation is that defence is physiologically, mechanically or behaviourally easier than attack, so that evolution is less constrained for victims than for parasites or pathogens. Another possible explanation is that parasites and pathogens have enemies themselves and that victim species persist because parasites and pathogens are regulated from the top down and thus generally have only modest demographic impacts on victim populations. Here we explore a third possibility: that victim species are not as evolutionarily impotent as conventional wisdom holds, but instead have unique evolutionary advantages that help to level the playing field. We use quantitative genetic analysis and individual-based simulations to show that victims can achieve such an advantage when coevolution involves multiple traits in both the host and the parasite.

Patterns of Species Ranges, Speciation, and Extinction

The exact nature of the relationship among species range sizes, speciation, and extinction events is not well understood. The factors that promote larger ranges, such as broad niche widths and high dispersal abilities, could increase the likelihood of encountering new habitats but also prevent local adaptation due to high gene flow. Similarly, low dispersal abilities or narrower niche widths could cause populations to be isolated, but such populations may lack advantageous mutations due to low population sizes. Here we present a large-scale, spatially explicit, individual-based model addressing the relationships between species ranges, speciation, and extinction. We followed the evolutionary dynamics of hundreds of thousands of diploid individuals for 200,000 generations. Individuals adapted to multiple resources and formed ecological species in a multidimensional trait space. These species varied in niche widths, and we observed the coexistence of generalists and specialists on a few resources. Our model shows that species ranges correlate with dispersal abilities but do not change with the strength of fitness trade-offs; however, high dispersal abilities and low resource utilization costs, which favored broad niche widths, have a strong negative effect on speciation rates. An unexpected result of our model is the strong effect of underlying resource distributions on speciation: in highly fragmented landscapes, speciation rates are reduced.

A distance‐based framework for measuring functional diversity from multiple traits

A new framework for measuring functional diversity (FD) from multiple traits has recently been proposed. This framework was mostly limited to quantitative traits without missing values and to situations in which there are more species than traits, although the authors had suggested a way to extend their framework to other trait types. The main purpose of this note is to further develop this suggestion. We describe a highly flexible distance-based framework to measure different facets of FD in multidimensional trait space from any distance or dissimilarity measure, any number of traits, and from different trait types (i.e., quantitative, semi-quantitative, and qualitative). This new approach allows for missing trait values and the weighting of individual traits. We also present a new multidimensional FD index, called functional dispersion (FDis), which is closely related to Rao's quadratic entropy. FDis is the multivariate analogue of the weighted mean absolute deviation (MAD), in which the weights are species relative abundances. For unweighted presence-absence data, FDis can be used for a formal statistical test of differences in FD. We provide the "FD" R language package to easily implement our distance-based FD framework.

Comparative evolution of flower and fruit morphology.

Angiosperm diversification has resulted in a vast array of plant morphologies. Only recently has it been appreciated that diversification might have proceeded quite differently for the two key diagnostic structures of this clade, flowers and fruits. These structures are hypothesized to have experienced different selective pressures via their interactions with animals in dispersal mutualisms, resulting in a greater amount of morphological diversification in animal-pollinated flowers than in animal-dispersed fruits. I tested this idea using size and colour traits for the flowers and fruits of 472 species occurring in three floras (St John, Hawaii and the Great Plains). Phylogenetically controlled analyses of nearest-neighbour distances in multidimensional trait space matched the predicted pattern: in each of the three floras, flowers were more divergent from one another than were fruits. In addition, the spacing of species clusters differed for flowers versus fruits in the flora of St John, with clusters in flower space more divergent than those in fruit space. The results are consistent with the idea that a major driver of angiosperm diversification has been stronger selection for divergent floral morphology than for divergent fruit morphology, although genetic, physiological and ecological constraints may also play a role.

Measure dynamics on a one-dimensional continuous trait space: theoretical foundations for adaptive dynamics

The measure dynamics approach to modelling single-species coevolution with a one-dimensional trait space is developed and compared to more traditional methods of adaptive dynamics and the Maximum Principle. It is assumed that individual fitness results from pairwise interactions together with a background fitness that depends only on total population size. When fitness functions are quadratic in the real variables parameterizing the one-dimensional traits of interacting individuals, the following results are derived. It is shown that among monomorphisms (i.e. measures supported on a single trait value), the continuously stable strategy (CSS) characterize those that are Lyapunov stable and attract all initial measures supported in an interval containing this trait value. In the cases where adaptive dynamics predicts evolutionary branching, convergence to a dimorphism is established. Extensions of these results to general fitness functions and/or multi-dimensional trait space are discussed.

Unidimensional Calibrations and Interpretations of Composite Traits for Multidimensional Tests

A two-stage process that considers the multi dimensionality of tests under the framework of unidimensional item response theory (IRT) is described and evaluated. In the first stage, items are clustered in a multidimensional latent space with respect to their direction of maximum dis crimination. The separate item clusters are subsequently calibrated using a unidimensional IRT model to provide item parameter and trait estimates for composite traits in the context of the multidimensional trait space. This application is proposed as a workable compromise to some of the estimation, indeterminacy, and interpretation problems that affect the direct use of multi dimensional IRT procedures for item calibration and trait estimation. The findings of a study based on simulated multidimensional data indicate that there are identifiable gains in estimation robustness and score interpretation with almost no sacrifice in goodness-of-fit using this two-stage approach to modeling composite latent traits.