Comparison of four performance models in quantifying the inequality of leaf and fruit size distribution.

The inequality in leaf and fruit size distribution per plant can be quantified using the Gini index, which is linked to the Lorenz curve depicting the cumulative proportion of leaf (or fruit) size against the cumulative proportion of the number of leaves (or fruits). Prior researches have predominantly employed empirical models-specifically the original performance equation (PE-1) and its generalized counterpart (GPE-1)-to fit rotated and right-shifted Lorenz curves. Notably, another potential performance equation (PE-2), capable of generating similar curves to PE-1, has been overlooked and not systematically compared with PE-1 and GPE-1. Furthermore, PE-2 has been extended into a generalized version (GPE-2). In the present study, we conducted a comparative analysis of these four performance equations, evaluating their applicability in describing Lorenz curves related to plant organ (leaf and fruit) size. Leaf area was measured on 240 culms of dwarf bamboo (Shibataea chinensis Nakai), and fruit volume was measured on 31 field muskmelon plants (Cucumis melo L. var. agrestis Naud.). Across both datasets, the root-mean-square errors of all four performance models were consistently smaller than 0.05. Paired t-tests indicated that GPE-1 exhibited the lowest root-mean-square error and Akaike information criterion value among the four performance equations. However, PE-2 gave the best close-to-linear behavior based on relative curvature measures. This study presents a valuable tool for assessing the inequality of plant organ size distribution.

Adaptive rewiring shapes structure and stability in a three-guild herbivore-plant-pollinator network.

Animal species, encompassing both pollinators and herbivores, exhibit a preference for plants based on optimal foraging theory. Understanding the intricacies of these adaptive plant-animal interactions in the context of community assembly poses a main challenge in ecology. This study delves into the impact of adaptive interaction rewiring between species belonging to different guilds on the structure and stability of a 3-guild ecological network, incorporating both mutualistic and antagonistic interactions. Our findings reveal that adaptive rewiring results in sub-networks becoming more nested and compartmentalized. Furthermore, the rewiring of interactions uncovers a positive correlation between a plant's generalism concerning both pollinators and herbivores. Additionally, there is a positive correlation between a plant's degree centrality and its energy budget. Although network stability does not exhibit a clear relationship with non-random structures, it is primarily influenced by the balance of multiple interaction strengths. In summary, our results underscore the significance of adaptive interaction rewiring in shaping the structure of 3-guild networks. They emphasize the importance of considering the balance of multiple interactions for the stability of adaptive networks, providing valuable insights into the complex dynamics of ecological communities.

Evidence That Field Muskmelon (Cucumis melo L. var. agrestis Naud.) Fruits Are Solids of Revolution.

In nature, the fruit shapes of many plants resemble avian eggs, a form extensively studied as solids of revolution. Despite this, the hypothesis that egg-shaped fruits are themselves solids of revolution remains unvalidated. To address this, 751 Cucumis melo L. var. agrestis Naud. fruits were photographed, and the two-dimensional (2D) boundary coordinates of each fruit profile were digitized. Then, the explicit Preston equation (EPE), a universal egg-shape model, was used to fit the 2D boundary coordinates to obtain the estimates of the EPE's parameters of each fruit. Under the hypothesis that egg-shaped fruits are solids of revolution, the fruit volumes were estimated using the solid of revolution formula based on the estimated EPE's parameters. To test whether the fruits are solids of revolution, the fruit volumes were measured by using a graduated cylinder and compared with the estimated volumes using the solid of revolution formula. The EPE was demonstrated to be valid in describing the 2D profiles of C. melo var. agrestis fruits. There was a significant correlation between the measured fruit volumes using the graduated cylinder and the estimated fruit volumes using the solid of revolution formula based on the estimated EPE's parameters. Acknowledging potential measurement errors, particularly fruit fuzz causing air bubbles during volume measurements, we recognize slight deviations between measured volumes and estimated values. Despite this, our findings strongly suggest that C. melo var. agrestis fruits are solids of revolution. This study contributes insights into the evolutionary aspects of fruit geometries in plants with egg-shaped fruits and introduces a practical tool for non-destructively calculating fruit volume and surface area based on photographed 2D fruit profiles.

Inequality Measure of Leaf Area Distribution for a Drought-Tolerant Landscape Plant.

Measuring the inequality of leaf area distribution per plant (ILAD) can provide a useful tool for quantifying the influences of intra- and interspecific competition, foraging behavior of herbivores, and environmental stress on plants' above-ground architectural structures and survival strategies. Despite its importance, there has been limited research on this issue. This paper aims to fill this gap by comparing four inequality indices to measure ILAD, using indices for quantifying household income that are commonly used in economics, including the Gini index (which is based on the Lorenz curve), the coefficient of variation, the Theil index, and the mean log deviation index. We measured the area of all leaves for 240 individual plants of the species Shibataea chinensis Nakai, a drought-tolerant landscape plant found in southern China. A three-parameter performance equation was fitted to observations of the cumulative proportion of leaf area vs. the cumulative proportion of leaves per plant to calculate the Gini index for each individual specimen of S. chinensis. The performance equation was demonstrated to be valid in describing the rotated and right shifted Lorenz curve, given that >96% of root-mean-square error values were smaller than 0.004 for 240 individual plants. By examining the correlation between any of the six possible pairs of indices among the Gini index, the coefficient of variation, the Theil index, and the mean log deviation index, the data show that these indices are closely related and can be used interchangeably to quantify ILAD.

Deep learning approaches to landmark detection in tsetse wing images.

Morphometric analysis of wings has been suggested for identifying and controlling isolated populations of tsetse (Glossina spp), vectors of human and animal trypanosomiasis in Africa. Single-wing images were captured from an extensive data set of field-collected tsetse wings of species Glossina pallidipes and G. m. morsitans. Morphometric analysis required locating 11 anatomical landmarks on each wing. The manual location of landmarks is time-consuming, prone to error, and infeasible for large data sets. We developed a two-tier method using deep learning architectures to classify images and make accurate landmark predictions. The first tier used a classification convolutional neural network to remove most wings that were missing landmarks. The second tier provided landmark coordinates for the remaining wings. We compared direct coordinate regression using a convolutional neural network and segmentation using a fully convolutional network for the second tier. For the resulting landmark predictions, we evaluate shape bias using Procrustes analysis. We pay particular attention to consistent labelling to improve model performance. For an image size of 1024 × 1280, data augmentation reduced the mean pixel distance error from 8.3 (95% confidence interval [4.4,10.3]) to 5.34 (95% confidence interval [3.0,7.0]) for the regression model. For the segmentation model, data augmentation did not alter the mean pixel distance error of 3.43 (95% confidence interval [1.9,4.4]). Segmentation had a higher computational complexity and some large outliers. Both models showed minimal shape bias. We deployed the regression model on the complete unannotated data consisting of 14,354 pairs of wing images since this model had a lower computational cost and more stable predictions than the segmentation model. The resulting landmark data set was provided for future morphometric analysis. The methods we have developed could provide a starting point to studying the wings of other insect species. All the code used in this study has been written in Python and open sourced.

Two dominant forms of multisite similarity decline - Their origins and interpretation.

The number of species shared by two or more sites is a fundamental measure of spatial variation in species composition. As more sites are included in the comparison of species composition, the average number of species shared across them declines, with a rate increasingly dependent on only the most widespread species. In over 80% of empirical communities, models of decline in shared species across multiple sites (multisite similarity decline) follow one of two distinct forms. An exponential form is assumed to reflect stochastic assembly and a power law form niche-based sorting, yet these explanations are largely untested, and little is known of how the two forms arise in nature. Using simulations, we first show that the distribution of the most widespread species largely differentiates the two forms, with the power law increasingly favored where such species occupy more than ~75% of sites. We reasoned the less cosmopolitan distribution of widespread species within exponential communities would manifest as differences in community biodiversity properties, specifically more aggregated within-species distributions, less even relative abundance distributions, and weaker between-species spatial associations. We tested and largely confirmed these relationships using 80 empirical datasets, suggesting that the form of multisite similarity decline offers a basis to predict how landscape-scale loss or gain of widespread species is reflected in different local-scale community structures. Such understanding could, for example, be used to predict changes in local-scale competitive interactions following shifts in widespread species' distributions. We propose multiple explanations for the origin of exponential decline, including high among-site abiotic variation, sampling of highly specialized (narrow niche width) taxa, and strong dispersal limitation. We recommend these are evaluated as alternative hypotheses to stochastic assembly.

Multiple introductions, polyploidy and mixed reproductive strategies are linked to genetic diversity and structure in the most widespread invasive plant across Southern Ocean archipelagos.

Biological invasions in remote areas that experience low human activity provide unique opportunities to elucidate processes responsible for invasion success. Here we study the most widespread invasive plant species across the isolated islands of the Southern Ocean, the annual bluegrass, Poa annua. To analyse geographical variation in genome size, genetic diversity and reproductive strategies, we sampled all major sub-Antarctic archipelagos in this region and generated microsatellite data for 470 individual plants representing 31 populations. We also estimated genome sizes for a subset of individuals using flow cytometry. Occasional events of island colonization are expected to result in high genetic structure among islands, overall low genetic diversity and increased self-fertilization, but we show that this is not the case for P. annua. Microsatellite data indicated low population genetic structure and lack of isolation by distance among the sub-Antarctic archipelagos we sampled, but high population structure within each archipelago. We identified high levels of genetic diversity, low clonality and low selfing rates in sub-Antarctic P. annua populations (contrary to rates typical of continental populations). In turn, estimates of selfing declined in populations as genetic diversity increased. Additionally, we found that most P. annua individuals are probably tetraploid and that only slight variation exists in genome size across the Southern Ocean. Our findings suggest multiple independent introductions of P. annua into the sub-Antarctic, which promoted the establishment of genetically diverse populations. Despite multiple introductions, the adoption of convergent reproductive strategies (outcrossing) happened independently in each major archipelago. The combination of polyploidy and a mixed reproductive strategy probably benefited P. annua in the Southern Ocean by increasing genetic diversity and its ability to cope with the novel environmental conditions.

Dynamic Species Distribution Modeling Reveals the Pivotal Role of Human-Mediated Long-Distance Dispersal in Plant Invasion.

Plant invasions generate massive ecological and economic costs worldwide. Predicting their spatial dynamics is crucial to the design of effective management strategies and the prevention of invasions. Earlier studies highlighted the crucial role of long-distance dispersal in explaining the speed of many invasions. In addition, invasion speed depends highly on the duration of its lag phase, which may depend on the scaling of fecundity with age, especially for woody plants, even though empirical proof is still rare. Bayesian dynamic species distribution models enable the fitting of process-based models to partial and heterogeneous observations using a state-space modeling approach, thus offering a tool to test such hypotheses on past invasions over large spatial scales. We use such a model to explore the roles of long-distance dispersal and age-structured fecundity in the transient invasion dynamics of Plectranthus barbatus, a woody plant invader in South Africa. Our lattice-based model accounts for both short and human-mediated long-distance dispersal, as well as age-structured fecundity. We fitted our model on opportunistic occurrences, accounting for the spatio-temporal variations of the sampling effort and the variable detection rates across datasets. The Bayesian framework enables us to integrate a priori knowledge on demographic parameters and control identifiability issues. The model revealed a massive wave of spatial spread driven by human-mediated long-distance dispersal during the first decade and a subsequent drastic population growth, leading to a global equilibrium in the mid-1990s. Without long-distance dispersal, the maximum population would have been equivalent to 30% of the current equilibrium population. We further identified the reproductive maturity at three years old, which contributed to the lag phase before the final wave of population growth. Our results highlighted the importance of the early eradication of weedy horticultural alien plants around urban areas to hamper and delay the invasive spread.

The EICAT+ framework enables classification of positive impacts of alien taxa on native biodiversity.

Species introduced through human-related activities beyond their native range, termed alien species, have various impacts worldwide. The IUCN Environmental Impact Classification for Alien Taxa (EICAT) is a global standard to assess negative impacts of alien species on native biodiversity. Alien species can also positively affect biodiversity (for instance, through food and habitat provisioning or dispersal facilitation) but there is currently no standardized and evidence-based system to classify positive impacts. We fill this gap by proposing EICAT+, which uses 5 semiquantitative scenarios to categorize the magnitude of positive impacts, and describes underlying mechanisms. EICAT+ can be applied to all alien taxa at different spatial and organizational scales. The application of EICAT+ expands our understanding of the consequences of biological invasions and can inform conservation decisions.

Rare, common, alien and native species follow different rules in an understory plant community.

Biological invasions are a leading threat to biodiversity globally. Increasingly, ecosystems experience multiple introductions, which can have significant effects on patterns of diversity. The way these communities assemble will depend partly on whether rare and common alien species respond to environmental predictors in the same manner as rare and common native species, but this is not well understood. To examine this question across four national parks in south-eastern Australia, we sampled the understory plant community of eucalypt-dominated dry forest subject to multiple plant introductions. The drivers of diversity and turnover in alien and native species of contrasting frequency of occurrence (low, intermediate, and high) were each tested individually. We found alien species diversity and turnover were both strongly associated with abiotic conditions (e.g., soil pH), while distance had little influence because of the greater extent of occurrence and more homogeneous composition of common aliens. In contrast, native species diversity was not associated with abiotic conditions and their turnover was as strongly influenced by distance as by abiotic conditions. In both alien and native species, however, the most important predictors of turnover changed with frequency of occurrence. Although local coexistence appears to be facilitated by life history trade-offs, species richness of aliens and natives was negatively correlated and native species might face greater competition in areas with more neutral soils (e.g., pH > ~5.5) where alien richness and relative frequency were both highest. We conclude that diversity and turnover in the generally more widespread alien species are mainly driven by species sorting along an environmental gradient associated with pH and nutrient availability, whereas turnover of native species is driven by more neutral processes associated with dispersal limitation. We show alien and native plant species respond to different environmental factors, as do rare and common species within each component.

The number of tree species on Earth.

One of the most fundamental questions in ecology is how many species inhabit the Earth. However, due to massive logistical and financial challenges and taxonomic difficulties connected to the species concept definition, the global numbers of species, including those of important and well-studied life forms such as trees, still remain largely unknown. Here, based on global ground-sourced data, we estimate the total tree species richness at global, continental, and biome levels. Our results indicate that there are ∼73,000 tree species globally, among which ∼9,000 tree species are yet to be discovered. Roughly 40% of undiscovered tree species are in South America. Moreover, almost one-third of all tree species to be discovered may be rare, with very low populations and limited spatial distribution (likely in remote tropical lowlands and mountains). These findings highlight the vulnerability of global forest biodiversity to anthropogenic changes in land use and climate, which disproportionately threaten rare species and thus, global tree richness.

Air pollution perception in ten countries during the COVID-19 pandemic.

As largely documented in the literature, the stark restrictions enforced worldwide in 2020 to curb the COVID-19 pandemic also curtailed the production of air pollutants to some extent. This study investigates the perception of the air pollution as assessed by individuals located in ten countries: Australia, Brazil, China, Ghana, India, Iran, Italy, Norway, South Africa and the USA. The perceptions towards air quality were evaluated by employing an online survey administered in May 2020. Participants (N = 9394) in the ten countries expressed their opinions according to a Likert-scale response. A reduction in pollutant concentration was clearly perceived, albeit to a different extent, by all populations. The survey participants located in India and Italy perceived the largest drop in the air pollution concentration; conversely, the smallest variation was perceived among Chinese and Norwegian respondents. Among all the demographic indicators considered, only gender proved to be statistically significant.

Human activity strongly influences genetic dynamics of the most widespread invasive plant in the sub-Antarctic.

The link between the successful establishment of alien species and propagule pressure is well-documented. Less known is how humans influence the post-introduction dynamics of invasive alien populations. The latter requires studying parallel invasions by the same species in habitats that are differently impacted by humans. We analysed microsatellite and genome size variation, and then compared the genetic diversity and structure of invasive Poa annua L. on two sub-Antarctic islands: human-occupied Marion Island and unoccupied Prince Edward Island. We also carried out niche modelling to map the potential distribution of the species on both islands. We found high levels of genetic diversity and evidence for extensive admixture between genetically distinct lineages of P. annua on Marion Island. By contrast, the Prince Edward Island populations showed low genetic diversity, no apparent admixture, and had smaller genomes. On both islands, high genetic diversity was apparent at human landing sites, and on Marion Island, also around human settlements, suggesting that these areas received multiple introductions and/or acted as initial introduction sites and secondary sources (bridgeheads) for invasive populations. More than 70 years of continuous human activity associated with a meteorological station on Marion Island led to a distribution of this species around human settlements and along footpaths, which facilitates ongoing gene flow among geographically separated populations. By contrast, this was not the case for Prince Edward Island, where P. annua populations showed high genetic structure. The high levels of genetic variation and admixture in P. annua facilitated by human activity, coupled with high habitat suitability on both islands, suggest that P. annua is likely to increase its distribution and abundance in the future.

Mechanistic reconciliation of community and invasion ecology.

Community and invasion ecology have mostly grown independently. There is substantial overlap in the processes captured by different models in the two fields, and various frameworks have been developed to reduce this redundancy and synthesize information content. Despite broad recognition that community and invasion ecology are interconnected, a process-based framework synthesizing models across these two fields is lacking. Here we review 65 representative community and invasion models and propose a common framework articulated around six processes (dispersal, drift, abiotic interactions, within-guild interactions, cross-guild interactions, and genetic changes). The framework is designed to synthesize the content of the two fields, provide a general perspective on their development, and enable their comparison. The application of this framework and of a novel method based on network theory reveals some lack of coherence between the two fields, despite some historical similarities. Community ecology models are characterized by combinations of multiple processes, likely reflecting the search for an overarching theory to explain community assembly and structure, drawing predominantly on interaction processes, but also accounting largely for the other processes. In contrast, most models in invasion ecology invoke fewer processes and focus more on interactions between introduced species and their novel biotic and abiotic environment. The historical dominance of interaction processes and their independent developments in the two fields is also reflected in the lower level of coherence for models involving interactions, compared to models involving dispersal, drift, and genetic changes. It appears that community ecology, with a longer history than invasion ecology, has transitioned from the search for single explanations for patterns observed in nature to investigate how processes may interact mechanistically, thereby generating and testing hypotheses. Our framework paves the way for a similar transition in invasion ecology, to better capture the dynamics of multiple alien species introduced in complex communities. Reciprocally, applying insights from invasion to community ecology will help us understand and predict the future of ecological communities in the Anthropocene, in which human activities are weakening species' natural boundaries. Ultimately, the successful integration of the two fields could advance a predictive ecology that is urgently required in a rapidly changing world.

Widespread vulnerability of flowering plant seed production to pollinator declines.

Despite evidence of pollinator declines from many regions across the globe, the threat this poses to plant populations is not clear because plants can often produce seeds without animal pollinators. Here, we quantify pollinator contribution to seed production by comparing fertility in the presence versus the absence of pollinators for a global dataset of 1174 plant species. We estimate that, without pollinators, a third of flowering plant species would produce no seeds and half would suffer an 80% or more reduction in fertility. Pollinator contribution to plant reproduction is higher in plants with tree growth form, multiple reproductive episodes, more specialized pollination systems, and tropical distributions, making these groups especially vulnerable to reduced service from pollinators. These results suggest that, without mitigating efforts, pollinator declines have the potential to reduce reproduction for most plant species, increasing the risk of population declines.

Impacts of detritivore diversity loss on instream decomposition are greatest in the tropics.

The relationship between detritivore diversity and decomposition can provide information on how biogeochemical cycles are affected by ongoing rates of extinction, but such evidence has come mostly from local studies and microcosm experiments. We conducted a globally distributed experiment (38 streams across 23 countries in 6 continents) using standardised methods to test the hypothesis that detritivore diversity enhances litter decomposition in streams, to establish the role of other characteristics of detritivore assemblages (abundance, biomass and body size), and to determine how patterns vary across realms, biomes and climates. We observed a positive relationship between diversity and decomposition, strongest in tropical areas, and a key role of abundance and biomass at higher latitudes. Our results suggest that litter decomposition might be altered by detritivore extinctions, particularly in tropical areas, where detritivore diversity is already relatively low and some environmental stressors particularly prevalent.

Latitude dictates plant diversity effects on instream decomposition.

Running waters contribute substantially to global carbon fluxes through decomposition of terrestrial plant litter by aquatic microorganisms and detritivores. Diversity of this litter may influence instream decomposition globally in ways that are not yet understood. We investigated latitudinal differences in decomposition of litter mixtures of low and high functional diversity in 40 streams on 6 continents and spanning 113° of latitude. Despite important variability in our dataset, we found latitudinal differences in the effect of litter functional diversity on decomposition, which we explained as evolutionary adaptations of litter-consuming detritivores to resource availability. Specifically, a balanced diet effect appears to operate at lower latitudes versus a resource concentration effect at higher latitudes. The latitudinal pattern indicates that loss of plant functional diversity will have different consequences on carbon fluxes across the globe, with greater repercussions likely at low latitudes.

Impact of COVID-19 pandemic on mobility in ten countries and associated perceived risk for all transport modes.

The restrictive measures implemented in response to the COVID-19 pandemic have triggered sudden massive changes to travel behaviors of people all around the world. This study examines the individual mobility patterns for all transport modes (walk, bicycle, motorcycle, car driven alone, car driven in company, bus, subway, tram, train, airplane) before and during the restrictions adopted in ten countries on six continents: Australia, Brazil, China, Ghana, India, Iran, Italy, Norway, South Africa and the United States. This cross-country study also aims at understanding the predictors of protective behaviors related to the transport sector and COVID-19. Findings hinge upon an online survey conducted in May 2020 (N = 9,394). The empirical results quantify tremendous disruptions for both commuting and non-commuting travels, highlighting substantial reductions in the frequency of all types of trips and use of all modes. In terms of potential virus spread, airplanes and buses are perceived to be the riskiest transport modes, while avoidance of public transport is consistently found across the countries. According to the Protection Motivation Theory, the study sheds new light on the fact that two indicators, namely income inequality, expressed as Gini index, and the reported number of deaths due to COVID-19 per 100,000 inhabitants, aggravate respondents' perceptions. This research indicates that socio-economic inequality and morbidity are not only related to actual health risks, as well documented in the relevant literature, but also to the perceived risks. These findings document the global impact of the COVID-19 crisis as well as provide guidance for transportation practitioners in developing future strategies.

Impacts of Invasive Australian Acacias on Soil Bacterial Community Composition, Microbial Enzymatic Activities, and Nutrient Availability in Fynbos Soils.

Invasive plants often impact soil conditions, notably through changes in soil chemistry and microbial community composition, potentially leading to altered soil functionality. We determine the impacts of invasive nitrogen-fixing Australian Acacia trees on soil chemistry and function (carbon, nitrogen, and phosphorus cycling) in South Africa's Core Cape Subregion, and whether any differences in soil function are linked to differences in soil chemical properties and bacterial community composition between neighbouring acacia-invaded and uninvaded sites. We do so by using Illumina MiSeq sequencing data together with soil chemistry and soil enzyme activity profiles. Acacias significantly increased levels of soil nitrogen (NO3-, NH4+, and total N), C, and pH. Although we did not find evidence that acacias affected soil bacterial community diversity, we did find them to alter bacterial community composition. Acacias also significantly elevated microbial phosphatase activity, but not ß-glucosidase, whilst having contrasting effects on urease. Changes in soil chemical properties under acacia invasion were found to correlate with changes in enzyme activities for urease and phosphatase. Similarly, changes in soil bacterial community composition were correlated to changes in phosphatase enzymatic activity levels under acacia invasion. Whilst we found evidence for acacias altering soil function by changing soil chemical properties and bacterial community composition, these impacts appear to be specific to local site conditions.