Showing papers by "Brian J. Enquist published in 2017"

The BIEN R package: A tool to access the Botanical Information and Ecology Network (BIEN) database

Abstract: There is an urgent need for large-scale botanical data to improve our understanding of community assembly, coexistence, biogeography, evolution, and many other fundamental biological processes. Understanding these processes is critical for predicting and handling human-biodiversity interactions and global change dynamics such as food and energy security, ecosystem services, climate change, and species invasions. The Botanical Information and Ecology Network (BIEN) database comprises an unprecedented wealth of cleaned and standardised botanical data, containing roughly 81 million occurrence records from c. 375,000 species, c. 915,000 trait observations across 28 traits from c. 93,000 species, and co-occurrence records from 110,000 ecological plots globally, as well as 100,000 range maps and 100 replicated phylogenies (each containing 81,274 species) for New World species. Here, we describe an r package that provides easy access to these data. The bien r package allows users to access the multiple types of data in the BIEN database. Functions in this package query the BIEN database by turning user inputs into optimised PostgreSQL functions. Function names follow a convention designed to make it easy to understand what each function does. We have also developed a protocol for providing customised citations and herbarium acknowledgements for data downloaded through the bien r package. The development of the BIEN database represents a significant achievement in biological data integration, cleaning and standardization. Likewise, the bien r package represents an important tool for open science that makes the BIEN database freely and easily accessible to everyone.

New approaches for delineating n-dimensional hypervolumes

Abstract: 1.Hutchinson's n-dimensional hypervolume concept underlies many applications in contemporary ecology and evolutionary biology. Estimating hypervolumes from sampled data has been an ongoing challenge due to conceptual and computational issues. 2.We present new algorithms for delineating the boundaries and probability density within n-dimensional hypervolumes. The methods produce smooth boundaries that can fit data either more loosely (Gaussian kernel density estimation) or more tightly (one-classification via support vector machine). Further, the algorithms can accept abundance-weighted data, and the resulting hypervolumes can be given a probabilistic interpretation and projected into geographic space. 3.We demonstrate the properties of these methods on a large dataset that characterizes the functional traits and geographic distribution of thousands of plants. The methods are available in version ≥2.0.6 of the hypervolume R package. 4.These new algorithms provide: (i) a more robust approach for delineating the shape and density of n-dimensional hypervolumes; (ii) more efficient performance on large and high-dimensional datasets; and (iii) improved measures of functional diversity and environmental niche breadth. This article is protected by copyright. All rights reserved.

Biodiversity and climate determine the functioning of neotropical forests.

Abstract: Aim: Tropical forests account for a quarter of the global carbon storage and a third of the terrestrial productivity. Few studies have teased apart the relative importance of environmental factors and forest attributes for ecosystem functioning, especially for the tropics. This study aims to relate aboveground biomass (AGB) and biomass dynamics (i.e., net biomass productivity and its underlying demographic drivers: biomass recruitment, growth and mortality) to forest attributes (tree diversity, community-mean traits and stand basal area) and environmental conditions (water availability, soil fertility and disturbance). Location: Neotropics. Methods: We used data from 26 sites, 201 1-ha plots and >92,000 trees distributed across the Neotropics. We quantified for each site water availability and soil total exchangeable bases and for each plot three key community-weighted mean functional traits that are important for biomass stocks and productivity. We used structural equation models to test the hypothesis that all drivers have independent, positive effects on biomass stocks and dynamics. Results: Of the relationships analysed, vegetation attributes were more frequently associated significantly with biomass stocks and dynamics than environmental conditions (in 67 vs. 33% of the relationships). High climatic water availability increased biomass growth and stocks, light disturbance increased biomass growth, and soil bases had no effect. Rarefied tree species richness had consistent positive relationships with biomass stocks and dynamics, probably because of niche complementarity, but was not related to net biomass productivity. Community-mean traits were good predictors of biomass stocks and dynamics. Main conclusions: Water availability has a strong positive effect on biomass stocks and growth, and a future predicted increase in (atmospheric) drought might, therefore, potentially reduce carbon storage. Forest attributes, including species diversity and community-weighted mean traits, have independent and important relationships with AGB stocks, dynamics and ecosystem functioning, not only in relatively simple temperate systems, but also in structurally complex hyper-diverse tropical forests.

Trait variation and integration across scales: is the leaf economic spectrum present at local scales?

Abstract: Trait-based approaches have taken an increasingly dominant role in community ecology. Although trait-based strategy dimensions such as the leaf economic spectrum (LES) have been identified primarily at global-scales, trait variation at the community scale is often interpreted in this context. Here we argue from several lines of evidence that a research priority should be to determine whether global-scale trait relationships hold at more local scales. We review recent literature assessing trait variation at smaller scales, and then present a case study exploring the relationship between the correlation strength of leaf traits and their similarity in variation structure across ecological scales. We find that the correlation strength between pairs of leaf traits does not predict whether the traits respond similarly to different drivers of variation. Instead, correlation strength only sets an upper bound to the dissimilarity in trait variation structure. With moderate correlation strengths, LES traits largely retain the ability to respond independently to different drivers of phenotypic variation at different scales. Recent literature and our results suggest that LES relationships may not hold at local scales. Clarifying under what conditions and at which scales the LES is consistently expressed is necessary for us to make the most of the emerging trait toolbox.

Leaf aging of Amazonian canopy trees as revealed by spectral and physiochemical measurements

Abstract: Leaf aging is a fundamental driver of changes in leaf traits, thereby regulating ecosystem processes and remotely sensed canopy dynamics. We explore leaf reflectance as a tool to monitor leaf age and develop a spectra-based partial least squares regression (PLSR) model to predict age using data from a phenological study of 1099 leaves from 12 lowland Amazonian canopy trees in southern Peru. Results demonstrated monotonic decreases in leaf water (LWC) and phosphorus (Pmass ) contents and an increase in leaf mass per unit area (LMA) with age across trees; leaf nitrogen (Nmass ) and carbon (Cmass ) contents showed monotonic but tree-specific age responses. We observed large age-related variation in leaf spectra across trees. A spectra-based model was more accurate in predicting leaf age (R2 = 0.86; percent root mean square error (%RMSE) = 33) compared with trait-based models using single (R2 = 0.07-0.73; %RMSE = 7-38) and multiple (R2 = 0.76; %RMSE = 28) predictors. Spectra- and trait-based models established a physiochemical basis for the spectral age model. Vegetation indices (VIs) including the normalized difference vegetation index (NDVI), enhanced vegetation index 2 (EVI2), normalized difference water index (NDWI) and photosynthetic reflectance index (PRI) were all age-dependent. This study highlights the importance of leaf age as a mediator of leaf traits, provides evidence of age-related leaf reflectance changes that have important impacts on VIs used to monitor canopy dynamics and productivity and proposes a new approach to predicting and monitoring leaf age with important implications for remote sensing.

Interspecific integration of trait dimensions at local scales: the plant phenotype as an integrated network

Abstract: Summary Plant phenotypic diversity is shaped by the interplay of trade-offs and constraints in evolution. Closely integrated groups of traits (i.e. trait dimensions) are used to classify plant phenotypic diversity into plant strategies, but we do not know the degree of interdependence among trait dimensions. To assess how selection has shaped the phenotypic space, we examine whether trait dimensions are independent. We gathered data on saplings of 24 locally coexisting tree species in a temperate forest, and examined the correlation structure of 20 leaf, branch, stem and root traits. These traits fall into three well-established trait dimensions (the leaf economic spectrum, the wood spectrum and Corner's Rules) that characterize vital plant functions: resource acquisition, sap transport, mechanical support and canopy architecture. Using ordinations, network analyses and Mantel tests, we tested whether the sapling phenotype of these tree species is organized along independent trait dimensions. Across species, the sapling phenotype is not structured into clear trait dimensions. The trait relationships defining trait dimensions are either weak or absent and do not dominate the correlation structure of the sapling phenotype as a whole. Instead traits from the three commonly recognized trait dimensions are organized into an integrated trait network. The effect of phylogeny on trait correlations is minimal. Our results indicate that trait dimensions apparent in broad-based interspecific surveys do not hold up among locally coexisting species. Furthermore, architectural traits appear central to the phenotypic network, suggesting a pivotal role for branching architecture in linking resource acquisition, mechanical support and hydraulic functions. Synthesis. Our study indicates that local and global patterns of phenotypic integration differ and calls into question the use of trait dimensions at local scales. We propose that a network approach to assessing plant function more effectively reflects the multiple trade-offs and constraints shaping the phenotype in locally co-occurring species.

Towards a thesaurus of plant characteristics: an ecological contribution

Abstract: Ecological research produces a tremendous amount of data, but the diversity in scales and topics covered and the ways in which studies are carried out result in large numbers of small, idiosyncratic data sets using heterogeneous terminologies. Such heterogeneity can be attributed, in part, to a lack of standards for acquiring, organizing and describing data. Here, we propose a terminological resource, a Thesaurus Of Plant characteristics (TOP), whose aim is to harmonize and formalize concepts for plant characteristics widely used in ecology. TOP concentrates on two types of plant characteristics: traits and environmental associations. It builds on previous initiatives for several aspects: (i) characteristics are designed following the entity-quality (EQ) model (a characteristic is modelled as the ‘Quality’ of an ‘Entity’ ) used in the context of Open Biological Ontologies; (ii) whenever possible, the Entities and Qualities are taken from existing terminology standards, mainly the Plant Ontology (PO) and Phenotypic Quality Ontology (PATO) ontologies; and (iii) whenever a characteristic already has a definition, if appropriate, it is reused and referenced. The development of TOP, which complies with semantic web principles, was carried out through the involvement of experts from both the ecology and the semantics research communities. Regular updates of TOP are planned, based on community feedback and involvement. TOP provides names, definitions, units, synonyms and related terms for about 850 plant characteristics. TOP is available online (www.top-thesaurus.org), and can be browsed using an alphabetical list of characteristics, a hierarchical tree of characteristics, a faceted and a free-text search, and through an Application Programming Interface. Synthesis. Harmonizing definitions of concepts, as proposed by TOP, forms the basis for better integration of data across heterogeneous data sets and terminologies, thereby increasing the potential for data reuse. It also allows enhanced scientific synthesis. TOP therefore has the potential to improve research and communication not only within the field of ecology, but also in related fields with interest in plant functioning and distribution.

Solar radiation and functional traits explain the decline of forest primary productivity along a tropical elevation gradient

Abstract: One of the major challenges in ecology is to understand how ecosystems respond to changes in environmental conditions, and how taxonomic and functional diversity mediate these changes. In this study, we use a trait-spectra and individual-based model, to analyse variation in forest primary productivity along a 3.3 km elevation gradient in the Amazon-Andes. The model accurately predicted the magnitude and trends in forest productivity with elevation, with solar radiation and plant functional traits (leaf dry mass per area, leaf nitrogen and phosphorus concentration, and wood density) collectively accounting for productivity variation. Remarkably, explicit representation of temperature variation with elevation was not required to achieve accurate predictions of forest productivity, as trait variation driven by species turnover appears to capture the effect of temperature. Our semi-mechanistic model suggests that spatial variation in traits can potentially be used to estimate spatial variation in productivity at the landscape scale.

Less favourable climates constrain demographic strategies in plants.

Abstract: Correlative species distribution models are based on the observed relationship between species' occurrence and macroclimate or other environmental variables. In climates predicted less favourable populations are expected to decline, and in favourable climates they are expected to persist. However, little comparative empirical support exists for a relationship between predicted climate suitability and population performance. We found that the performance of 93 populations of 34 plant species worldwide - as measured by in situ population growth rate, its temporal variation and extinction risk - was not correlated with climate suitability. However, correlations of demographic processes underpinning population performance with climate suitability indicated both resistance and vulnerability pathways of population responses to climate: in less suitable climates, plants experienced greater retrogression (resistance pathway) and greater variability in some demographic rates (vulnerability pathway). While a range of demographic strategies occur within species' climatic niches, demographic strategies are more constrained in climates predicted to be less suitable.

Does environmental heterogeneity drive functional trait variation? A test in montane and alpine meadows

Abstract: While community-weighted means of plant traits have been linked to mean environmental conditions at large scales, the drivers of trait variation within communities are not well understood. Local environmental heterogeneity (such as microclimate variability), in addition to mean environmental conditions, may decrease the strength of environmental filtering and explain why communities support different amounts of trait variation. Here, we assess two hypotheses: first, that more heterogeneous local environments and second, that less extreme environments, should support a broader range of plant strategies and thus higher trait variation. We quantified drivers of trait variation across a range of environmental conditions and spatial scales ranging from sub-meter to tens of kilometers in montane and alpine plant communities. We found that, within communities, both environmental heterogeneity and environmental means are drivers of trait variation. However, the importance of each environmental factor varied depending on the trait. Our results indicate that larger-scale trait-climate linkages that hold across communities also apply at small spatial scales, suggesting that microclimate variation within communities is a key driver of community functional diversity. Microclimatic variation provides a potential mechanism for helping to maintaining diversity in local communities and also suggests that small-scale environmental heterogeneity should be measured as a better predictor of functional diversity. This article is protected by copyright. All rights reserved.

Predictability in community dynamics.

Abstract: The coupling between community composition and climate change spans a gradient from no lags to strong lags. The no-lag hypothesis is the foundation of many ecophysiological models, correlative species distribution modelling and climate reconstruction approaches. Simple lag hypotheses have become prominent in disequilibrium ecology, proposing that communities track climate change following a fixed function or with a time delay. However, more complex dynamics are possible and may lead to memory effects and alternate unstable states. We develop graphical and analytic methods for assessing these scenarios and show that these dynamics can appear in even simple models. The overall implications are that (1) complex community dynamics may be common and (2) detailed knowledge of past climate change and community states will often be necessary yet sometimes insufficient to make predictions of a community's future state.

Scale dependence of canopy trait distributions along a tropical forest elevation gradient

Abstract: Average responses of forest foliar traits to elevation are well understood, but far less is known about trait distributional responses to elevation at multiple ecological scales. This limits our understanding of the ecological scales at which trait variation occurs in response to environmental drivers and change. We analyzed and compared multiple canopy foliar trait distributions using field sampling and airborne imaging spectroscopy along an Andes-to-Amazon elevation gradient. Field-estimated traits were generated from three community-weighting methods, and remotely sensed estimates of traits were made at three scales defined by sampling grain size and ecological extent. Field and remote sensing approaches revealed increases in average leaf mass per unit area (LMA), water, nonstructural carbohydrates (NSCs) and polyphenols with increasing elevation. Foliar nutrients and photosynthetic pigments displayed little to no elevation trend. Sample weighting approaches had little impact on field-estimated trait responses to elevation. Plot representativeness of trait distributions at landscape scales decreased with increasing elevation. Remote sensing indicated elevation-dependent increases in trait variance and distributional skew. Multiscale invariance of LMA, leaf water and NSC mark these traits as candidates for tracking forest responses to changing climate. Trait-based ecological studies can be greatly enhanced with multiscale studies made possible by imaging spectroscopy.

Variation in leaf wettability traits along a tropical montane elevation gradient.

Abstract: Leaf wetting is often considered to have negative effects on plant function, such that wet environments may select for leaves with certain leaf surface, morphological, and architectural traits that reduce leaf wettability. However, there is growing recognition that leaf wetting can have positive effects. We measured variation in two traits, leaf drip tips and leaf water repellency, in a series of nine tropical forest communities occurring along a 3300-m elevation gradient in southern Peru. To extend this climatic gradient, we also assembled published leaf water repellency values from 17 additional sites. We then tested hypotheses for how these traits should vary as a function of climate. Contrary to expectations, we found that the proportion of species with drip tips did not increase with increasing precipitation. Instead, drip tips increased with increasing temperature. Moreover, leaf water repellency was very low in our sites and the global analysis indicated high repellency only in sites with low precipitation and temperatures. Our findings suggest that drip tips and repellency may not solely reflect the negative effects of wetting on plant function. Understanding the drivers of leaf wettability traits can provide insight into the effects of leaf wetting on plant, community, and ecosystem function.

Assessing trait‐based scaling theory in tropical forests spanning a broad temperature gradient

Abstract: Aim Tropical elevation gradients are natural laboratories to assess how changing climate can influence tropical forests. However, there is a need for theory and integrated data collection to scale from traits to ecosystems. We assess predictions of a novel trait-based scaling theory, including whether observed shifts in forest traits across a broad tropical temperature gradient are consistent with local phenotypic optima and adaptive compensation for temperature. Location An elevation gradient spanning 3,300 m and consisting of thousands of tropical tree trait measures taken from 16 1-ha tropical forest plots in southern Peru, where gross and net primary productivity (GPP and NPP) were measured. Time period April to November 2013. Major taxa studied Plants; tropical trees. Methods We developed theory to scale from traits to communities and ecosystems and tested several predictions. We assessed the covariation between climate, traits, biomass and GPP and NPP. We measured multiple traits linked to variation in tree growth and assessed their frequency distributions within and across the elevation gradient. We paired these trait measures across individuals within 16 forests with simultaneous measures of ecosystem net and gross primary productivity. Results Consistent with theory, variation in forest NPP and GPP primarily scaled with forest biomass, but the secondary effect of temperature on productivity was much less than expected. This weak temperature dependence appears to reflect directional shifts in several mean community traits that underlie tree growth with decreases in site temperature. Main conclusions The observed shift in traits of trees that dominate in more cold environments is consistent with an ‘adaptive/acclimatory’ compensation for the kinetic effects of temperature on leaf photosynthesis and tree growth. Forest trait distributions across the gradient showed overly peaked and skewed distributions, consistent with the importance of local filtering of optimal growth traits and recent shifts in species composition and dominance attributable to warming from climate change. Trait-based scaling theory provides a basis to predict how shifts in climate have and will influence the trait composition and ecosystem functioning of tropical forests.

Biogeochemistry drives diversity in the prokaryotes, fungi, and invertebrates of a Panama forest

Abstract: Humans are both fertilizing the world and depleting its soils, decreasing the diversity of aquatic ecosystems and terrestrial plants in the process. We know less about how nutrients shape the abundance and diversity of the prokaryotes, fungi, and invertebrates of Earth's soils. Here we explore this question in the soils of a Panama forest subject to a 13-yr fertilization with factorial combinations of nitrogen (N), phosphorus (P), and potassium (K) and a separate micronutrient cocktail. We contrast three hypotheses linking biogeochemistry to abundance and diversity. Consistent with the Stress Hypothesis, adding N suppressed the abundance of invertebrates and the richness of all three groups of organisms by ca. 1 SD or more below controls. Nitrogen addition plots were 0.8 pH units more acidic with 18% more exchangeable aluminum, which is toxic to both prokaryotes and eukaryotes. These stress effects were frequently reversed, however, when N was added with P (for prokaryotes and invertebrates) and with added K (for fungi). Consistent with the Abundance Hypothesis, adding P generally increased prokaryote and invertebrate diversity, and adding K enhanced invertebrate diversity. Also consistent with the Abundance Hypothesis, increases in invertebrate abundance generated increases in richness. We found little evidence for the Competition Hypothesis: that single nutrients suppressed diversity by favoring a subset of high nutrient specialists, and that nutrient combinations suppressed diversity even more. Instead, combinations of nutrients, and especially the cation/micronutrient treatment, yielded the largest increases in richness in the two eukaryote groups. In sum, changes in soil biogeochemistry revealed a diversity of responses among the three dominant soil groups, positive synergies among nutrients, and-in contrast with terrestrial plants-the frequent enhancement of soil biodiversity.

A general model for metabolic scaling in self-similar asymmetric networks.

Abstract: How a particular attribute of an organism changes or scales with its body size is known as an allometry. Biological allometries, such as metabolic scaling, have been hypothesized to result from selection to maximize how vascular networks fill space yet minimize internal transport distances and resistances. The West, Brown, Enquist (WBE) model argues that these two principles (space-filling and energy minimization) are (i) general principles underlying the evolution of the diversity of biological networks across plants and animals and (ii) can be used to predict how the resulting geometry of biological networks then governs their allometric scaling. Perhaps the most central biological allometry is how metabolic rate scales with body size. A core assumption of the WBE model is that networks are symmetric with respect to their geometric properties. That is, any two given branches within the same generation in the network are assumed to have identical lengths and radii. However, biological networks are rarely if ever symmetric. An open question is: Does incorporating asymmetric branching change or influence the predictions of the WBE model? We derive a general network model that relaxes the symmetric assumption and define two classes of asymmetrically bifurcating networks. We show that asymmetric branching can be incorporated into the WBE model. This asymmetric version of the WBE model results in several theoretical predictions for the structure, physiology, and metabolism of organisms, specifically in the case for the cardiovascular system. We show how network asymmetry can now be incorporated in the many allometric scaling relationships via total network volume. Most importantly, we show that the 3/4 metabolic scaling exponent from Kleiber's Law can still be attained within many asymmetric networks.

The role of functional uniqueness and spatial aggregation in explaining rarity in trees.

Abstract: Aim: Determining the drivers of species rarity is fundamental for understanding and conserving biodiversity. Rarity of a given species within its community may arise due to exclusion by other ecologically similar species. Conversely, rare species may occupy habitats that are rare in the landscape or they may be ill-suited to all available habitats. The first mechanism would lead to common and rare species occupying similar ecological space defined by functional traits. The second mechanism would result in common and rare species occupying dissimilar ecological space and spatial aggregation of rare species, either because they are specialists in rare habitats or because rare species tend to be dispersal limited. Here, we quantified the contribution of locally rare species to community functional richness and the spatial aggregation of species across tree communities world-wide to address these hypotheses. Location: Asia and the Americas. Time period: 2002 to 2012 (period that considers the censuses for the plots used). Major taxa studied: Angiosperm and Gymnosperm trees. Methods: We compiled a dataset of functional traits from all the species present in eight tree plots around the world to evaluate the contribution of locally rare species to tree community functional richness using multi- and univariate approaches. We also quantified the spatial aggregation of individuals within species at several spatial scales as it relates to abundance. Results: Locally rare tree species in temperate and tropical forests tended to be functionally unique and are consistently spatially clustered. Furthermore, there is no evidence that this pattern is driven by pioneer species being locally rare. Main conclusions: This evidence shows that locally rare tree species disproportionately contribute to community functional richness, and we can therefore reject the hypothesis that locally rare species are suppressed by ecologically similar, but numerically dominant, species. Rather, locally rare species are likely to be specialists on spatially rare habitats or they may be ill-suited to the locally available environments.

The evolution of bacterial cell size: the internal diffusion-constraint hypothesis

Abstract: Size is one of the most important biological traits influencing organismal ecology and evolution. However, we know little about the drivers of body size evolution in unicellulars. A long-term evolution experiment (Lenski's LTEE) in which Escherichia coli adapts to a simple glucose medium has shown that not only the growth rate and the fitness of the bacterium increase over time but also its cell size. This increase in size contradicts prominent 'external diffusion' theory (EDC) predicting that cell size should have evolved toward smaller cells. Among several scenarios, we propose and test an alternative 'internal diffusion-constraint' (IDC) hypothesis for cell size evolution. A change in cell volume affects metabolite concentrations in the cytoplasm. The IDC states that a higher metabolism can be achieved by a reduction in the molecular traffic time inside of the cell, by increasing its volume. To test this hypothesis, we studied a population from the LTEE. We show that bigger cells with greater growth and CO2 production rates and lower mass-to-volume ratio were selected over time in the LTEE. These results are consistent with the IDC hypothesis. This novel hypothesis offers a promising approach for understanding the evolutionary constraints on cell size.

Predicting trait-environment relationships for venation networks along an Andes-Amazon elevation gradient

Abstract: Understanding functional trait-environment relationships (TERs) may improve predictions of community assembly. However, many empirical TERs have been weak or lacking conceptual foundation. TERs based on leaf venation networks may better link individuals and communities via hydraulic constraints. We report measurements of vein density, vein radius, and leaf thickness for more than 100 dominant species occurring in ten forest communities spanning a 3,300 m Andes-Amazon elevation gradient in Peru. We use these data to measure the strength of TERs at community scale and to determine whether observed TERs are similar to those predicted by physiological theory. We found strong support for TERs between all traits and temperature, as well weaker support for a predicted TER between maximum abundance-weighted leaf transpiration rate and maximum potential evapotranspiration. These results provide one approach for developing a more mechanistic trait-based community assembly theory.

Can leaf spectroscopy predict leaf and forest traits along a Peruvian tropical forest elevation gradient

Abstract: UK Natural Environment Research Council [NE/J023418/1, NE/M019160/1]; European Research Council [321131, 291585]; John D. and Catherine T. MacArthur Foundation; U.S. National Science Foundation [DEB - 1209287]; Carnegie Institution for Science; National Science Foundation [DEB - 1146206]; Leverhulme Trust, UK; Jackson Foundation; European Community [290605]; John Fell Fund; Google Earth Engine award

Using n-dimensional hypervolumes for species distribution modelling: A response to Qiao et al. (†)

Abstract: Hypervolume approaches are used to quantify functional diversity and quantify environmental niches for species distribution modelling. Recently, Qiao et al. (2016) criticized our geometrical kernel density estimation (KDE) method for measuring hypervolumes. They used a simulation analysis to argue that the method yields high error rates and makes biased estimates of fundamental niches. Here, we show that (a) KDE output depends in useful ways on dataset size and bias, (b) other species distribution modelling methods make equally stringent but different assumptions about dataset bias, (c) simulation results presented by Qiao et al. (2016) were incorrect, with revised analyses showing performance comparable to other methods, and (d) hypervolume methods are more general than KDE and have other benefits for niche modelling. As a result, our KDE method remains a promising tool for species distribution modelling.

Correspondence: Reply to `Analytical flaws in a continental-scale forest soil microbial diversity study'

Abstract: Author(s): Zhou, Jizhong; Deng, Ye; Shen, Lina; Wen, Chongqing; Yan, Qingyun; Ning, Daliang; Qin, Yujia; Xue, Kai; Wu, Liyou; He, Zhili; Voordeckers, James W; Van Nostrand, Joy D; Buzzard, Vanessa; Michaletz, Sean T; Enquist, Brian J; Weiser, Michael D; Kaspari, Michael; Waide, Robert; Yang, Yunfeng; Brown, James H