DOI: 10.5061/dryad.cb2f5
title: Data from: Linking functional diversity and ecosystem processes: a framework for using functional diversity metrics to predict the ecosystem impact of functionally unique species

description: 1.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 multi-dimensional trait
 space, making it difficult to select a priori the most appropriate metric
 for specific ecological questions. 2.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 lab decomposition experiment. We simulate
 invasion of a forest by understory plants by adding leaf litter from 18
 natives and nonnatives to a representative canopy tree litter mixture to
 test changes in FD and decomposition. 3.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 nonnative
 species. FDis was the only metric that both changed predictably with
 addition of understory 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 nonnatives will
 have the greatest impact on ecosystem processes. 4.Synthesis: We highlight
 the need to assess the suitability of each FD 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 nonnative species
 can impact ecosystem processes.
description: Kuebbing et al. 2017,
 Journal of Ecology, Functional Diversity and Invasion
 ImpactsA full description of
 this data set can be found in Kuebbing, SE, DS Maynard, and MA Bradford
 (2017) Linking functional diversity and ecosystem processes: a framework
 for using functional diversity metrics to predict the ecosystem impact of
 functionally unique species. Journal of Ecology. DATA SET 1: Brief Methods
 (for full methods see Kuebbing et al. 2017, Journal of Ecology). We used
 laboratory microcosm experiments to assess litter decomposition dynamics
 of litter mixtures. Each microcosm consisted of 1 g of 2 mm-milled leaf
 litter and 0.25 g of mineral soil in 50-mL centrifuge tubes. Each
 microcosm contained in equal proportion litter from each of the three
 dominant canopy trees (Carya cordiformis, Quercus alba, and Q. rubra), in
 addition to one of the 18 understory plants. The latter were added at
 three relative abundances (1%, 5%, and 25%). There were 216 microcosms (18
 understory plants × 3 proportions [1%, 5%, and 25%] × 4 replicates) and 4
 tree-canopy litter control replicates, bringing the total number of
 microcosms to 220. DATA SET 2: Brief Methods (for full methods see
 Kuebbing et al. 2017, Journal of Ecology). To assess green leaf traits, we
 collected 5 green leaves from a minimum of 5 individuals per species in
 summer 2014. For canopy trees, we “sling-shot sampled” canopy branches to
 collect full-sun leaves. For understory species, we randomly sampled
 leaves from individuals. We selected leaves that appeared free of
 herbivory as well as fungal or bacterial infection. We scanned
 fully-hydrated leaves on a flatbed scanner within 24 h of collection and
 then dried them at 60°C for 72 h before measuring mass. To estimate
 specific leaf area, we measured scanned leaf surface area with digital
 software (ImageJ v.1.51f) and divided area by dry mass. To assess the
 green leaf chemical traits, we ball milled the material (Spex CertiPrep
 8000-D Mixer Mill, Metuchen, New Jersey, USA) and determined C and N
 concentrations using Micro-Dumas combustion analysis. To assess leaf
 litter traits, we collected litter in fall 2014 from senescing plants. We
 collected freshly-fallen leaves from the ground or shook senesced leaves
 free from branches. Litter was air-dried and leaves were selected that had
 no evidence of fungal colonization or herbivory. We milled all litter to
 pass a 2-mm mesh (Wiley® Cutting Mill, Model 2, Thomas Scientific,
 Swedesboro, New Jersey, USA), creating a consistent size class across
 species (Strickland et al. 2009; Keiser et al. 2011; 2013). We used the
 same method as for green leaves to determine litter total N and C. To
 assess litter P we used acid digestion and colorimetric analysis of milled
 litter. To measure lignin we used the ANKOM acid detergent lignin method
 (ANKOM Technology, Macedon NY; protocol at www.ankom.com). We report total
 C, N and P on a percent mass basis and acid detergent lignin (ADL) on a
 per gram dry mass basis.Kuebbing, Sara_Data for
 Dryad.xlsx