Capacity and establishment rules govern the number of nonnative species in communities of ground-dwelling invertebrates.

Nonnative species are a key agent of global change. However, nonnative invertebrates remain understudied at the community scales where they are most likely to drive local extirpations. We use the North American NEON pitfall trapping network to document the number of nonnative species from 51 invertebrate communities, testing four classes of drivers. We sequenced samples using the eDNA from the sample's storage ethanol. We used AICc informed regression to evaluate how native species richness, productivity, habitat, temperature, and human population density and vehicular traffic account for continent-wide variation in the number of nonnative species in a local community. The percentage of nonnatives varied 3-fold among habitat types and over 10-fold (0%-14%) overall. We found evidence for two types of constraints on nonnative diversity. Consistent with Capacity rules (i.e., how the number of niches and individuals reflect the number of species an ecosystem can support) nonnatives increased with existing native species richness and ecosystem productivity. Consistent with Establishment Rules (i.e., how the dispersal rate of nonnative propagules and the number of open sites limits nonnative species richness) nonnatives increased with automobile traffic-a measure of human-generated propagule pressure-and were twice as common in pastures than native grasslands. After accounting for drivers associated with a community's ability to support native species (native species richness and productivity), nonnatives are more common in communities that are regularly seasonally disturbed (pastures and, potentially deciduous forests) and those experiencing more vehicular traffic. These baseline values across the US North America will allow NEON's monitoring mission to document how anthropogenic change-from disturbance to propagule transport, from temperature to trends in local extinction-further shape biotic homogenization.

Temperature-habitat interactions constrain seasonal activity in a continental array of pitfall traps.

Activity density (AD), the rate at which animals collectively move through their environment, emerges as the product of a taxon's local abundance and its velocity. We analyze drivers of seasonal AD using 47 localities from the National Ecological Observatory Network (NEON) both to better understand variation in ecosystem rates like pollination and seed dispersal as well as the constraints of using AD to monitor invertebrate populations. AD was measured as volume from biweekly pitfall trap arrays (ml trap-1 14 days-1 ). Pooled samples from 2017 to 2018 revealed AD extrema at most temperatures but with a strongly positive overall slope. However, habitat types varied widely in AD's seasonal temperature sensitivity, from negative in wetlands to positive in mixed forest, grassland, and shrub habitats. The temperature of maximum AD varied threefold across the 47 localities; it tracked the threefold geographic variation in maximum growing season temperature with a consistent gap of ca. 3°C across habitats, a novel macroecological result. AD holds potential as an effective proxy for investigating ecosystem rates driven by activity. However, our results suggest that its use for monitoring insect abundance is complicated by the many ways that both abundance and velocity are constrained by a locality's temperature and plant physiognomy.

Warm and arid regions of the world are hotspots of superorganism complexity.

Biologists have long been fascinated by the processes that give rise to phenotypic complexity of organisms, yet whether there exist geographical hotspots of phenotypic complexity remains poorly explored. Phenotypic complexity can be readily observed in ant colonies, which are superorganisms with morphologically differentiated queen and worker castes analogous to the germline and soma of multicellular organisms. Several ant species have evolved 'worker polymorphism', where workers in a single colony show quantifiable differences in size and head-to-body scaling. Here, we use 256 754 occurrence points from 8990 ant species to investigate the geography of worker polymorphism. We show that arid regions of the world are the hotspots of superorganism complexity. Tropical savannahs and deserts, which are typically species-poor relative to tropical or even temperate forests, harbour the highest densities of polymorphic ants. We discuss the possible adaptive advantages that worker polymorphism provides in arid environments. Our work may provide a window into the environmental conditions that promote the emergence of highly complex phenotypes.

Activity density at a continental scale: What drives invertebrate biomass moving across the soil surface?

Activity density (AD), the rate that an individual taxon or its biomass moves through the environment, is used both to monitor communities and quantify the potential for ecosystem work. The Abundance Velocity Hypothesis posited that AD increases with aboveground net primary productivity (ANPP) and is a unimodal function of temperature. Here we show that, at continental extents, increasing ANPP may have nonlinear effects on AD: increasing abundance, but decreasing velocity as accumulating vegetation interferes with movement. We use 5 yr of data from the NEON invertebrate pitfall trap arrays including 43 locations and four habitat types for a total of 77 habitat-site combinations to evaluate continental drivers of invertebrate AD. ANPP and temperature accounted for one-third to 92% of variation in AD. As predicted, AD was a unimodal function of temperature in forests and grasslands but increased linearly in open scrublands. ANPP yielded further nonlinear effects, generating unimodal AD curves in wetlands, and bimodal curves in forests. While all four habitats showed no AD trends over 5 yr of sampling, these nonlinearities suggest that trends in AD, often used to infer changes in insect abundance, will vary qualitatively across ecoregions.

Testing the role of body size and litter depth on invertebrate diversity across six forests in North America.

Ecologists search for rules by which traits dictate the abundance and distribution of species. Here we search for rules that apply across three common taxa of litter invertebrates in six North American forests from Panama to Oregon. We use image analysis to quantify the abundance and body size distributions of mites, springtails, and spiders in 21 1-m2 plots per forest. We contrast three hypotheses: two of which focus on trait-abundance relationships and a third linking abundance to species richness. Despite three orders of magnitude variation in size, the predicted negative relationship between mean body size and abundance per area occurred in only 18% of cases, never for large bodied taxa like spiders. We likewise found only 18% of tests supported our prediction that increasing litter depth allows for high abundance; two-thirds of which occurred at a single deciduous forest in Massachusetts. In contrast, invertebrate abundance constrained species richness 76% of the time. Our results suggest that body size and habitat volume in brown food webs are rarely good predictors of variation in abundance, but that variation in diversity is generally well predicted by abundance.

Robust and simplified machine learning identification of pitfall trap-collected ground beetles at the continental scale.

Insect populations are changing rapidly, and monitoring these changes is essential for understanding the causes and consequences of such shifts. However, large-scale insect identification projects are time-consuming and expensive when done solely by human identifiers. Machine learning offers a possible solution to help collect insect data quickly and efficiently.Here, we outline a methodology for training classification models to identify pitfall trap-collected insects from image data and then apply the method to identify ground beetles (Carabidae). All beetles were collected by the National Ecological Observatory Network (NEON), a continental scale ecological monitoring project with sites across the United States. We describe the procedures for image collection, image data extraction, data preparation, and model training, and compare the performance of five machine learning algorithms and two classification methods (hierarchical vs. single-level) identifying ground beetles from the species to subfamily level. All models were trained using pre-extracted feature vectors, not raw image data. Our methodology allows for data to be extracted from multiple individuals within the same image thus enhancing time efficiency, utilizes relatively simple models that allow for direct assessment of model performance, and can be performed on relatively small datasets.The best performing algorithm, linear discriminant analysis (LDA), reached an accuracy of 84.6% at the species level when naively identifying species, which was further increased to >95% when classifications were limited by known local species pools. Model performance was negatively correlated with taxonomic specificity, with the LDA model reaching an accuracy of ~99% at the subfamily level. When classifying carabid species not included in the training dataset at higher taxonomic levels species, the models performed significantly better than if classifications were made randomly. We also observed greater performance when classifications were made using the hierarchical classification method compared to the single-level classification method at higher taxonomic levels.The general methodology outlined here serves as a proof-of-concept for classifying pitfall trap-collected organisms using machine learning algorithms, and the image data extraction methodology may be used for nonmachine learning uses. We propose that integration of machine learning in large-scale identification pipelines will increase efficiency and lead to a greater flow of insect macroecological data, with the potential to be expanded for use with other noninsect taxa.

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

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Species energy and Thermal Performance Theory predict 20-yr changes in ant community abundance and richness.

In an era of rapid climate change, and with it concern over insect declines, we used two theories to predict 20-yr changes in 34 North American ant communities. The ecosystems, from deserts to hardwood forests, were first surveyed in the 1990s. When resurveyed in 2016-2017, they averaged 1°C warmer with 200 g C·m-2 ·yr-1 higher plant productivity. Ant colony abundance changed from -49% to +61%. Consistent with Thermal Performance Theory, colony abundance increased with temperature increases < 1°C, then decreased as a site's mean monthly temperature change increased up to +2.4°C. Consistent with Species Energy Theory, (1) ant abundance tracked changes in a measure of energy availability (net aboveground productivity, g C·m-2 ·yr-1 ) and (2) increases in colony abundance drove increases in local plot- and transect-level species richness but not that of Chao 2, an estimate of the size of the species pool. Even after accounting for these drivers, local species richness was still higher ~20 yr after the original surveys, likely due to the increased activity of ant workers. These results suggest community changes are predictable using theory from geographical ecology, and that warming can first enhance but may ultimately decrease the abundance of this important insect taxon.

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

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.

Macroecology and macroevolution of the latitudinal diversity gradient in ants.

The latitudinal diversity gradient-the tendency for more species to occur toward the equator-is the dominant pattern of life on Earth, yet the mechanisms responsible for it remain largely unexplained. Recently, the analysis of global data has led to advances in understanding, but these advances have been mostly limited to vertebrates and trees and have not provided consensus answers. Here we synthesize large-scale geographic, phylogenetic, and fossil data for an exemplar invertebrate group-ants-and investigate whether the latitudinal diversity gradient arose due to higher rates of net diversification in the tropics, or due to a longer time period to accumulate diversity due to Earth's climatic history. We find that latitudinal affinity is highly conserved, temperate clades are young and clustered within tropical clades, and diversification rate shows no systematic variation with latitude. These results indicate that diversification time-and not rate-is the main driver of the diversity gradient in ants.

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

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.

Sodium co-limits and catalyzes macronutrients in a prairie food web.

Nitrogen and phosphorus frequently limit terrestrial plant production, but have a mixed record in regulating the abundance of terrestrial invertebrates. We contrasted four ways that Na could interact with an NP fertilizer to shape the plants and invertebrates of an inland prairie. We applied NP and Na to m2 plots in a factorial design. Aboveground invertebrate abundance was independently co-limited by NaCl and NP, but with +NP plots supporting more individuals. We suggest the disparity arises because NP enhanced plant height by 35% (1 SD) over controls, providing both food and habitat, whereas NaCl provides only food. Belowground invertebrates showed evidence of serial co-limitation, where NaCl additions alone were ineffectual, but catalyzed access to NP. This suggests the increased belowground food availability in NP plots increased Na demand. Na and NP supply rates vary with climate, land use, and with inputs like urine. The co-limitation and catalysis of N and P by Na thus has the potential for predicting patterns of abundance and diversity across spatial scales.

The energetic and carbon economic origins of leaf thermoregulation.

Leaf thermoregulation has been documented in a handful of studies, but the generality and origins of this pattern are unclear. We suggest that leaf thermoregulation is widespread in both space and time, and originates from the optimization of leaf traits to maximize leaf carbon gain across and within variable environments. Here we use global data for leaf temperatures, traits and photosynthesis to evaluate predictions from a novel theory of thermoregulation that synthesizes energy budget and carbon economics theories. Our results reveal that variation in leaf temperatures and physiological performance are tightly linked to leaf traits and carbon economics. The theory, parameterized with global averaged leaf traits and microclimate, predicts a moderate level of leaf thermoregulation across a broad air temperature gradient. These predictions are supported by independent data for diverse taxa spanning a global air temperature range of ∼60 °C. Moreover, our theory predicts that net carbon assimilation can be maximized by means of a trade-off between leaf thermal stability and photosynthetic stability. This prediction is supported by globally distributed data for leaf thermal and photosynthetic traits. Our results demonstrate that the temperatures of plant tissues, and not just air, are vital to developing more accurate Earth system models.

Temperature mediates continental-scale diversity of microbes in forest soils.

Climate warming is increasingly leading to marked changes in plant and animal biodiversity, but it remains unclear how temperatures affect microbial biodiversity, particularly in terrestrial soils. Here we show that, in accordance with metabolic theory of ecology, taxonomic and phylogenetic diversity of soil bacteria, fungi and nitrogen fixers are all better predicted by variation in environmental temperature than pH. However, the rates of diversity turnover across the global temperature gradients are substantially lower than those recorded for trees and animals, suggesting that the diversity of plant, animal and soil microbial communities show differential responses to climate change. To the best of our knowledge, this is the first study demonstrating that the diversity of different microbial groups has significantly lower rates of turnover across temperature gradients than other major taxa, which has important implications for assessing the effects of human-caused changes in climate, land use and other factors.

Biogeographic patterns of soil diazotrophic communities across six forests in North America.

Soil diazotrophs play important roles in ecosystem functioning by converting atmospheric N2 into biologically available ammonium. However, the diversity and distribution of soil diazotrophic communities in different forests and whether they follow biogeographic patterns similar to macroorganisms still remain unclear. By sequencing nifH gene amplicons, we surveyed the diversity, structure and biogeographic patterns of soil diazotrophic communities across six North American forests (126 nested samples). Our results showed that each forest harboured markedly different soil diazotrophic communities and that these communities followed traditional biogeographic patterns similar to plant and animal communities, including the taxa-area relationship (TAR) and latitudinal diversity gradient. Significantly higher community diversity and lower microbial spatial turnover rates (i.e. z-values) were found for rainforests (~0.06) than temperate forests (~0.1). The gradient pattern of TARs and community diversity was strongly correlated (r(2)  > 0.5) with latitude, annual mean temperature, plant species richness and precipitation, and weakly correlated (r(2)  < 0.25) with pH and soil moisture. This study suggests that even microbial subcommunities (e.g. soil diazotrophs) follow general biogeographic patterns (e.g. TAR, latitudinal diversity gradient), and indicates that the metabolic theory of ecology and habitat heterogeneity may be the major underlying ecological mechanisms shaping the biogeographic patterns of soil diazotrophic communities.

Constancy in Functional Space across a Species Richness Anomaly.

The relationship between large-scale gradients in species richness and functional diversity provides important information regarding the mechanisms driving patterns of biodiversity. A classic hypothesis in ecology is that strong interspecific interactions should result in an increase in the functional volume of assemblages as the species richness increases, whereas climatic constraints may result in no change in functional volume. Most research of this kind examines latitudinal gradients in species richness, but the results are likely confounded by underlying gradients in climate and phylogenetic composition. We take an alternative approach that examines functional richness across a tree species richness anomaly where species richness doubles from Europe to eastern North America. The results demonstrate that the functional richness on both continents saturates at a similar point as species richness increases and that the packing of functional space becomes tighter. Further, the species richness anomaly is driven primarily by genera unique to North America, but those genera contribute less than expected functional richness to the region, indicating a high level of redundancy with genera shared between the continents. Taken together, the results indicate that the species richness anomaly is associated with diversification within a climatically constrained trait space. More generally, the work demonstrates the power of utilizing species richness anomalies in biodiversity research, particularly when they are coupled with information regarding organismal function.

Plant Thermoregulation: Energetics, Trait-Environment Interactions, and Carbon Economics.

Building a more predictive trait-based ecology requires mechanistic theory based on first principles. We present a general theoretical approach to link traits and climate. We use plant leaves to show how energy budgets (i) provide a foundation for understanding thermoregulation, (ii) explain mechanisms driving trait variation across environmental gradients, and (iii) guide selection on functional traits via carbon economics. Although plants are often considered to be poikilotherms, the data suggest that they are instead limited homeotherms. Leaf functional traits that promote limited homeothermy are adaptive because homeothermy maximizes instantaneous and lifetime carbon gain. This theory provides a process-based foundation for trait-climate analyses and shows that future studies should consider plant (not only air) temperatures.

Tree height-diameter allometry across the United States.

The relationship between tree height and diameter is fundamental in determining community and ecosystem structure as well as estimates of biomass and carbon storage. Yet our understanding of how tree allometry relates to climate and whole organismal function is limited. We used the Forest Inventory and Analysis National Program database to determine height-diameter allometries of 2,976,937 individuals of 293 tree species across the United States. The shape of the allometric relationship was determined by comparing linear and nonlinear functional forms. Mixed-effects models were used to test for allometric differences due to climate and floristic (between angiosperms and gymnosperms) and functional groups (leaf habit and shade tolerance). Tree allometry significantly differed across the United States largely because of climate. Temperature, and to some extent precipitation, in part explained tree allometric variation. The magnitude of allometric variation due to climate, however, had a phylogenetic signal. Specifically, angiosperm allometry was more sensitive to differences in temperature compared to gymnosperms. Most notably, angiosperm height was more negatively influenced by increasing temperature variability, whereas gymnosperm height was negatively influenced by decreasing precipitation and increasing altitude. There was little evidence to suggest that shade tolerance influenced tree allometry except for very shade-intolerant trees which were taller for any given diameter. Tree allometry is plastic rather than fixed and scaling parameters vary around predicted central tendencies. This allometric variation provides insight into life-history strategies, phylogenetic history, and environmental limitations at biogeographical scales.