Showing papers by "Brian J. Enquist published in 2019"

The commonness of rarity: Global and future distribution of rarity across land plants.

Abstract: A key feature of life’s diversity is that some species are common but many more are rare. Nonetheless, at global scales, we do not know what fraction of biodiversity consists of rare species. Here, we present the largest compilation of global plant diversity to quantify the fraction of Earth’s plant biodiversity that are rare. A large fraction, ~36.5% of Earth’s ~435,000 plant species, are exceedingly rare. Sampling biases and prominent models, such as neutral theory and the k-niche model, cannot account for the observed prevalence of rarity. Our results indicate that (i) climatically more stable regions have harbored rare species and hence a large fraction of Earth’s plant species via reduced extinction risk but that (ii) climate change and human land use are now disproportionately impacting rare species. Estimates of global species abundance distributions have important implications for risk assessments and conservation planning in this era of rapid global change.

sPlot – A new tool for global vegetation analyses

Abstract: Aims :Vegetation-plot records provide information on the presence and cover or abundance of plants co-occurring in the same community. Vegetation-plot data are spread across research groups, environmental agencies and biodiversity research centers and, thus, are rarely accessible at continental or global scales. Here we present the sPlot database, which collates vegetation plots worldwide to allow for the exploration of global patterns in taxonomic, functional and phylogenetic diversity at the plant community level. Results: sPlot version 2.1 contains records from 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected worldwide between 1885 and 2015. We complemented the information for each plot by retrieving climate and soil conditions and the biogeographic context (e.g., biomes) from external sources, and by calculating community-weighted means and variances of traits using gap-filled data from the global plant trait database TRY. Moreover, we created a phylogenetic tree for 50,167 out of the 54,519 species identified in the plots. We present the first maps of global patterns of community richness and community-weighted means of key traits. Conclusions: The availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale.

Climate shapes and shifts functional biodiversity in forests worldwide.

Abstract: Much ecological research aims to explain how climate impacts biodiversity and ecosystem-level processes through functional traits that link environment with individual performance. However, the specific climatic drivers of functional diversity across space and time remain unclear due largely to limitations in the availability of paired trait and climate data. We compile and analyze a global forest dataset using a method based on abundance-weighted trait moments to assess how climate influences the shapes of whole-community trait distributions. Our approach combines abundance-weighted metrics with diverse climate factors to produce a comprehensive catalog of trait-climate relationships that differ dramatically-27% of significant results change in sign and 71% disagree on sign, significance, or both-from traditional species-weighted methods. We find that (i) functional diversity generally declines with increasing latitude and elevation, (ii) temperature variability and vapor pressure are the strongest drivers of geographic shifts in functional composition and ecological strategies, and (iii) functional composition may currently be shifting over time due to rapid climate warming. Our analysis demonstrates that climate strongly governs functional diversity and provides essential information needed to predict how biodiversity and ecosystem function will respond to climate change.

Drier tropical forests are susceptible to functional changes in response to a long-term drought

Abstract: Climatic changes have profound effects on the distribution of biodiversity, but untangling the links between climatic change and ecosystem functioning is challenging, particularly in high diversity systems such as tropical forests. Tropical forests may also show different responses to a changing climate, with baseline climatic conditions potentially inducing differences in the strength and timing of responses to droughts. Trait-based approaches provide an opportunity to link functional composition, ecosystem function and environmental changes. We demonstrate the power of such approaches by presenting a novel analysis of long-term responses of different tropical forest to climatic changes along a rainfall gradient. We explore how key ecosystem's biogeochemical properties have shifted over time as a consequence of multi-decadal drying. Notably, we find that drier tropical forests have increased their deciduous species abundance and generally changed more functionally than forests growing in wetter conditions, suggesting an enhanced ability to adapt ecologically to a drying environment.

Informing trait-based ecology by assessing remotely sensed functional diversity across a broad tropical temperature gradient

Abstract: Spatially continuous data on functional diversity will improve our ability to predict global change impacts on ecosystem properties. We applied methods that combine imaging spectroscopy and foliar traits to estimate remotely sensed functional diversity in tropical forests across an Amazon-to-Andes elevation gradient (215 to 3537 m). We evaluated the scale dependency of community assembly processes and examined whether tropical forest productivity could be predicted by remotely sensed functional diversity. Functional richness of the community decreased with increasing elevation. Scale-dependent signals of trait convergence, consistent with environmental filtering, play an important role in explaining the range of trait variation within each site and along elevation. Single- and multitrait remotely sensed measures of functional diversity were important predictors of variation in rates of net and gross primary productivity. Our findings highlight the potential of remotely sensed functional diversity to inform trait-based ecology and trait diversity-ecosystem function linkages in hyperdiverse tropical forests.

Temperature shapes opposing latitudinal gradients of plant taxonomic and phylogenetic β diversity.

Abstract: Latitudinal and elevational richness gradients have received much attention from ecologists but there is little consensus on underlying causes. One possible proximate cause is increased levels of species turnover, or β diversity, in the tropics compared to temperate regions. Here, we leverage a large botanical dataset to map taxonomic and phylogenetic β diversity, as mean turnover between neighboring 100 × 100 km cells, across the Americas and determine key climatic drivers. We find taxonomic and tip‐weighted phylogenetic β diversity is higher in the tropics, but that basal‐weighted phylogenetic β diversity is highest in temperate regions. Supporting Janzen's ‘mountain passes’ hypothesis, tropical mountainous regions had higher β diversity than temperate regions for taxonomic and tip‐weighted metrics. The strongest climatic predictors of turnover were average temperature and temperature seasonality. Taken together, these results suggest β diversity is coupled to latitudinal richness gradients and that temperature is a major driver of plant community composition and change.

The plant diversity sampling design for The National Ecological Observatory Network

Abstract: National Science Foundation (NSF); NSF [EF-1029808, EF-1138160, DBI-0752017]; USDA CSREES/NRI [2008-35615-04666]; USGS Ecosystems and Climate and Land use Change Programs

Continental scale structuring of forest and soil diversity via functional traits.

Abstract: Trait-based ecology claims to offer a mechanistic approach for explaining the drivers that structure biological diversity and predicting the responses of species, trophic interactions and ecosystems to environmental change. However, support for this claim is lacking across broad taxonomic groups. A framework for defining ecosystem processes in terms of the functional traits of their constituent taxa across large spatial scales is needed. Here, we provide a comprehensive assessment of the linkages between climate, plant traits and soil microbial traits at many sites spanning a broad latitudinal temperature gradient from tropical to subalpine forests. Our results show that temperature drives coordinated shifts in most plant and soil bacterial traits but these relationships are not observed for most fungal traits. Shifts in plant traits are mechanistically associated with soil bacterial functional traits related to carbon (C), nitrogen (N) and phosphorus (P) cycling, indicating that microbial processes are tightly linked to variation in plant traits that influence rates of ecosystem decomposition and nutrient cycling. Our results are consistent with hypotheses that diversity gradients reflect shifts in phenotypic optima signifying local temperature adaptation mediated by soil nutrient availability and metabolism. They underscore the importance of temperature in structuring the functional diversity of plants and soil microbes in forest ecosystems and how this is coupled to biogeochemical processes via functional traits.

Species' range model metadata standards: RMMS

Abstract: AIM: The geographic range and ecological niche of species are widely used concepts in ecology, evolution and conservation and many modelling approaches have been developed to quantify each. Niche and distribution modelling methods require a litany of design choices; differences among subdisciplines have created communication barriers that increase isolation of scientific advances. As a result, understanding and reproducing the work of others is difficult, if not impossible. It is often challenging to evaluate whether a model has been built appropriately for its intended application or subsequent reuse. Here, we propose a standardized model metadata framework that enables researchers to understand and evaluate modelling decisions while making models fully citable and reproducible. Such reproducibility is critical for both scientific and policy reports, while international standardization enables better comparison between different scenarios and research groups. INNOVATION: Range modelling metadata (RMMS) address three challenges: they (a) are designed for convenience to encourage use, (b) accommodate a wide variety of applications, and (c) are extensible to allow the research community to steer them as needed. RMMS are based on a metadata dictionary that specifies a hierarchical structure to catalogue different aspects of the range modelling process. The dictionary balances a constrained, minimalist vocabulary to improve standardization with flexibility for users to modify and extend. To facilitate use, we have developed an R package, rangeModelMetaData, to build templates, automatically fill values from common modelling objects, check for inconsistencies with standards, and suggest values. MAIN CONCLUSIONS: Range Modelling Metadata tools foster cross‐disciplinary advances in biogeography, conservation and allied disciplines by improving evaluation, model sharing, model searching, comparisons and reproducibility among studies. Our initially proposed standards here are designed to be modified and extended to evolve with research trends and needs.

The relationship of woody plant size and leaf nutrient content to large‐scale productivity for forests across the Americas

Abstract: Ecosystem processes are driven by both environmental variables and the attributes of component species. The extent to which these effects are independent and/or dependent upon each other has remained unclear. We assess the extent to which climate affects net primary productivity (NPP) both directly and indirectly via its effect on plant size and leaf functional traits. Using species occurrences and functional trait databases for North and South America, we describe the upper limit of woody plant height within 200 × 200 km grid‐cells. In addition to maximum tree height, we quantify grid‐cell means of three leaf traits (specific leaf area, and leaf nitrogen and phosphorus concentration) also hypothesized to influence productivity. Using structural equation modelling, we test the direct and indirect effects of environment and plant traits on remotely sensed MODIS‐derived estimates of NPP, using plant size (satellite‐measured canopy height and potential maximum tree height), leaf traits, growing season length, soil nutrients, climate and disturbances as explanatory variables. Our results show that climate affects NPP directly as well as indirectly via plant size in both tropical and temperate forests. In tropical forests NPP further increases with leaf phosphorus concentration, whereas in temperate forests it increases with leaf nitrogen concentration. In boreal forests, NPP most strongly increases with increasing temperature and neither plant size nor leaf traits have a significant influence. Synthesis. Our results suggest that at large spatial scales plant size and leaf nutrient traits can improve predictions of forest productivity over those based on climate alone. However, at higher latitudes their role is overridden by stressful climate. Our results provide independent empirical evidence for where and how global vegetation models predicting carbon fluxes could benefit from including effects of plant size and leaf stoichiometry.

The Open Traits Network: Using Open Science principles to accelerate trait-based science across the Tree of Life

Abstract: Synthesising trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Despite the well-recognised importance of traits for addressing ecological and evolutionary questions, trait-based approaches still struggle with several basic data requirements to deliver openly accessible, reproducible, and transparent science. Here, we introduce the Open Traits Network (OTN) – a decentralised alliance of international researchers and institutions focused on collaborative integration and standardisation of the exponentially increasing availability of trait data across all organisms. The OTN embraces the use of Open Science principles in trait research, particularly open data, open source, and open methodology protocols and workflows, to accelerate the synthesis of trait data across the Tree of Life. Increased efforts at all levels – from individual scientists, research networks, scientific societies, funding agencies, to publishers – are necessary to fully exploit the opportunities offered by Open Science in trait research. Democratising access to data, tools and resources will facilitate rapid advances in the biological sciences and our ability to address pressing environmental and societal demands.

Drivers of C cycling in three arctic-alpine plant communities

Abstract: Recent vegetation changes in arctic-alpine tundra ecosystems may affect several ecosystem processes that regulate microbe and soil functions. Such changes can alter ecosystem carbon (C) cycling with positive feedback to the atmosphere if plant C uptake is less than the amount of soil C released. Here, we examine how differences in plant functional traits, microbial activity, and soil processes within and across Salix-dominated shrub, dwarf shrub–dominated heath, and herb- and cryptogam-dominated meadow communities influence C cycling. We develop a hypothesized framework based on a priori model selection of variation in daytime growing season gross ecosystem photosynthesis (GEP) and above- and belowground respiration. The fluxes were standardized to light and temperature. Gross ecosystem photosynthesis was primarily related to soil moisture and secondarily to plant functional traits and aboveground biomass, and belowground respiration was dependent on the community weighted mean of specific leaf area (SLACWM). Similarly, microbial activity was linked with SLACWM and was highest in meadows, and carbon-degrading microbial activity decreased with vegetation woodiness. These results suggest that shrub expansion may influence summer C cycling differently depending on plant community, as belowground respiration might increase in the heath and decrease in the meadow communities.

Branching principles of animal and plant networks identified by combining extensive data, machine learning, and modeling.

Abstract: Branching in vascular networks and in overall organismic form is one of the most common and ancient features of multicellular plants, fungi, and animals. By combining machine-learning techniques with new theory that relates vascular form to metabolic function, we enable novel classification of diverse branching networks--mouse lung, human head and torso, angiosperm and gymnosperm plants. We find that ratios of limb radii--which dictate essential biologic functions related to resource transport and supply--are best at distinguishing branching networks. We also show how variation in vascular and branching geometry persists despite observing a convergent relationship across organisms for how metabolic rate depends on body mass.

Patterns and ecological determinants of woody plant height in eastern Eurasia and its relation to primary productivity

Abstract: Plant height is a key functional trait related to aboveground biomass, leaf photosynthesis and plant fitness. However, large-scale geographical patterns in community-average plant height (CAPH) of woody species and drivers of these patterns across different life forms remain hotly debated. Moreover, whether CAPH could be used as a predictor of ecosystem primary productivity is unknown. We compiled mature height and distributions of 11 422 woody species in eastern Eurasia, and estimated geographic patterns in CAPH for different taxonomic groups and life forms. Then we evaluated the effects of environmental (including current climate and historical climate change since the Last Glacial Maximum (LGM)) and evolutionary factors on CAPH. Lastly, we compared the predictive power of CAPH on primary productivity with that of LiDAR-derived canopy-height data from a global survey. Geographic patterns of CAPH and their drivers differed among taxonomic groups and life forms. The strongest predictor for CAPH of all woody species combined, angiosperms, all dicots and deciduous dicots was actual evapotranspiration, while temperature was the strongest predictor for CAPH of monocots and tree, shrub and evergreen dicots, and water availability for gymnosperms. Historical climate change since the LGM had only weak effects on CAPH. No phylogenetic signal was detected in family-wise average height, which was also unrelated to the tested environmental factors. Finally, we found a strong correlation between CAPH and ecosystem primary productivity. Primary productivity showed a weaker relationship with CAPH of the tallest species within a grid cell and no relationship with LiDAR-derived canopy height reported in the global survey. Our findings suggest that current climate rather than historical climate change and evolutionary history determine the geographical patterns in CAPH. However, the relative effects of climatic factors representing environmental energy and water availability on spatial variations of CAPH vary among plant life forms. Moreover, our results also suggest that CAPH can be used as a good predictor of ecosystem primary productivity.

Drought and the interannual variability of stem growth in an aseasonal, everwet forest

Abstract: in Spanish is available with online material.

On the relationships between size and abundance in plants: beyond forest communities

Abstract: Kenyon College Summer Science Scholars program; NSF REU grant, National Science Foundation (NSF) - Office of the Director (OD); National Science Foundation (NSF) [DEB-1556651]

On the importance of the megabiota to the functioning of the biosphere

Abstract: A prominent signal of the Anthropocene is the extinction and population reduction of the megabiota – the largest animals and plants on the planet. However, we lack a predictive framework for the sensitivity of megabiota during times of rapid global change and how they impact the functioning of ecosystems and the biosphere. Here, we extend metabolic scaling theory and use global simulation models to demonstrate that the megabiota (i) are more prone to extinction due to human land use, hunting, and climate change; (ii) their loss has a negative impact on ecosystem metabolism and functioning; and (iii) their continued reduction will significantly decrease biosphere functioning. Analyses of several forest and animal datasets and large-scale simulation models largely support these predictions. Global simulations show that continued loss of large animals could lead to a 44%, 18% and 92% reduction in terrestrial heterotrophic biomass, metabolism, and fertility respectively. Landscapes with megabiota buffer ecosystem functioning, diversity, and likely human health. As a result, policies that emphasize the promotion of large trees and animals will have disproportionate impact on biodiversity, ecosystem processes, and climate mitigation.

Thermal disruption of soil bacterial assemblages decreases diversity and assemblage similarity

Abstract: Author(s): Weiser, MD; Ning, D; Buzzard, V; Michaletz, ST; He, Z; Enquist, BJ; Waide, RB; Zhou, J; Kaspari, M | Abstract: The metabolic theory of ecology assumes that rates of selection and adaptation for organisms are functions of temperature. Niche theory predicts that strong selection pressure should simplify assemblages as species are extirpated and taxa pre-adapted for the new environment thrive. Here, we use closed mesocosms to test the prediction that higher temperatures decrease species richness and increase assemblage similarity more and faster than lower temperatures. We incubated two temperate forest soil types at constant temperatures from 10° to 35°, destructively sampling mesocosms at 30, 180, and 440nd. We quantified taxonomic richness and assemblage similarity of soil bacteria using 16S rRNA gene amplicons. As predicted, mesocosms at higher temperatures lost more taxa than those at lower temperature. Contrary to predictions, the simplified assemblages at higher temperatures became less similar to each other over time. After 440nd of incubation, the number of taxa lost was a linear function of the difference between treatment temperature and site mean annual temperature, while assemblage similarity decreased as an accelerating function of this temperature difference.

The Influence of Ecosystem and Phylogeny on Tropical Tree Crown Size and Shape

Abstract: 1 ABSTRACT The sizes and shapes of tree crowns are of fundamental importance in ecology, yet understanding the forces that determine them remains elusive. A cardinal question facing ecologists is the degree to which general and non-specific versus ecological and context-dependent processes are responsible for shaping tree crowns. Here, we test this question for the first time across diverse tropical ecosystems. Using trees from 20 plots varying in elevation, precipitation, and ecosystem type (savanna-forest transitions) across the paleo- and neo-tropics, we test the relationship between crown dimensions and tree size. By analyzing these scaling relationships across environmental gradients, biogeographic regions, and phylogenetic distance, we extend Metabolic Scaling Theory (MST) predictions to include how local selective pressures shape variation in crown dimensions. Across all sites, we find strong agreement between mean trends and MST predictions for the scaling of crown size and shape, but large variation around the mean. While MST explained approximately half of the observed variation in tree crown dimensions, we find that local, ecosystem, and phylogenetic predictors account for the half of the residual variation. Crown scaling does not change significantly across regions, but does change across ecosystem types, where savanna tree crowns grow more quickly with tree size than forest tree crowns. Crowns of legumes were wider and larger than those of other taxa. Thus, while MST can accurately describe the central tendency of tree crown size, local ecological conditions and evolutionary history appear to modify the scaling of crown shape. Importantly, our extension of MST incorporating these differences accounts for the mechanisms driving variation in the scaling of crown dimensions across the tropics. These results are critical when scaling the function of individual trees to larger spatial scales or incorporating the size and shape of tree crowns in global biogeochemical models.

Leaf size of woody dicots predicts ecosystem primary productivity

Abstract: Abstract A key challenge in ecology is to understand the relationships between organismal traits and ecosystem processes. Here, with a novel dataset of leaf length and width for 10 480 woody dicots in China and 2374 in North America, we show that the variation in community mean leaf size is highly correlated with the variation in climate and ecosystem primary productivity, independent of plant life form. These relationships likely reflect how natural selection modifies leaf size across varying climates in conjunction with how climate influences canopy total leaf area. We find that the leaf size‒primary productivity functions based on the Chinese dataset can predict productivity in North America and vice‐versa. In addition to advancing understanding of the relationship between a climate‐driven trait and ecosystem functioning, our findings suggest that leaf size can also be a promising tool in palaeoecology for scaling from fossil leaves to palaeo‐primary productivity of woody ecosystems.

Identifying branching principles in biological networks using imaging, modeling, and machine learning

Abstract: Branching in vascular networks and in overall organismic form is one of the most common and ancient features of multicellular plants, fungi and animals. These networks deliver resources and eliminate wastes from early development onward, and even play a vital role in the growth, prognosis, and treatment of tumors and stroke recovery. Because of these basic and applied reasons there is immense interest in identifying key features of vascular branching and their connection to biological function. Here we classify diverse branching networks-mouse lung, human head and torso, angiosperm plants, and gymnosperm plants-by harnessing recent advances in medical imaging, algorithms and software for extracting vascular data, theory for resource-distribution networks, and machine-learning. Specifically, we apply standard machine-learning techniques to a variety of feature spaces. Our results show that our theoretically-informed feature spaces-especially those that determine blood flow rate-combined with Kernel Density Estimation are best at distinguishing networks. Our categorization of networks enhances the mapping between biologic function-such as the dependence of metabolic rate on body mass-to vascular branching traits among organisms and organs. We accomplish this by analyzing how variation in metabolic scaling exponents-around the canonical value of 3/4-arises despite differences in vascular traits. Our results reveal how network categorization and variation in metabolic scaling are both heavily determined by scaling ratios of vessel radii-changes and asymmetries across branching generations-that strongly constrain rates of fluid flow. These linkages will improve understanding of evolutionary convergence across plants and animals while also potentially aiding prognosis and treatment of vascular pathologies and other diseased states.

Drivers of Plant Traits and Forest Functional Composition In Coastal Plant Communities of The Atlantic Forest

Abstract: The severe deforestation of Brazil’s Atlantic Forest and increasing effects of climate change underscore the need to understand how tree species respond to climate and soil drivers. We studied 42 plots of coastal restinga forest, which is highly diverse and spans strong environmental gradients. We determined the forest physiognomy and functional composition, which are physical properties of a community that respond to climate and soil properties, to elucidate which factors drive community-level traits. To identify the most important environmental drivers of coastal Atlantic forest functional composition, we performed a forest inventory of all plants of diameter 5 cm and above. We collected wood samples and leaves from ∼85% of the most abundant plant species and estimated height, aboveground biomass (AGB), and basal area of individual plants, and the community-weighted specific leaf area (SLA). In addition to plant traits, we measured water table depth and 25 physicochemical soil parameters. We then parameterized several models for different hypotheses relating the roles of nutrients and soil to tropical forest diversity and functioning, as represented by plant traits. Hypotheses were formalized via generalized additive models and piecewise structural equation models. Water table depth, soil coarseness, potential acidity, sodium saturation index (SSI) and aluminum concentration were all components of the best models for AGB, height, basal area, and trait composition. Among the 25 environmental parameters measured, those related to water availability (water table depth and coarse sand), followed by potential acidity, SSI, and aluminum consistently emerged as the most important drivers of forest physiognomy and functional composition. Increases in water table depth, coarse sand, and soil concentration of aluminum negatively impacted all the measured functional traits, whereas SSI had a positive effect on AGB and plant height. These results suggest that sodium is not merely tolerated by Atlantic Forest restinga plant communities, but is important to their structure and functioning. Presence of aluminum in the soil had a complex relationship to overall basal area, possibly mediated by soil organic matter.