Trait coordination and environmental filters shape functional trait distributions of forest understory herbs

1. Understanding the drivers of trait selection is critical for resolving community assembly processes. Here, we test the importance of environmental filtering and trait covariance for structuring the functional traits of understory herbaceous communities distributed along a natural environmental resource gradient that varied in soil moisture, temperature, and nitrogen availability, produced by different topographic positions in the southern Appalachian Mountains.
2. To uncover potential differences in community‐level trait responses to the resource gradient, we quantified the averages and variances of both abundance‐weighted and unweighted values for six functional traits (vegetative height, leaf area, specific leaf area, leaf dry matter content, leaf nitrogen, and leaf δ¹³C) using 15 individuals of each of the 108 species of understory herbs found at two sites in the southern Appalachians of western North Carolina, USA.
3. Environmental variables were better predictors of weighted than unweighted community‐level average trait values for all but height and leaf N, indicating strong environmental filtering of plant abundance. Community‐level variance patterns also showed increased convergence of abundance‐weighted traits as resource limitation became more severe.
4. Functional trait covariance patterns based on weighted averages were uniform across the gradient, whereas coordination based on unweighted averages was inconsistent and varied with environmental context. In line with these results, structural equation modeling revealed that unweighted community‐average traits responded directly to local environmental variation, whereas weighted community‐average traits responded indirectly to local environmental variation through trait coordination.
5. Our finding that trait coordination is more important for explaining the distribution of weighted than unweighted average trait values along the gradient indicates that environmental filtering acts on multiple traits simultaneously, with abundant species possessing more favorable combinations of traits for maximizing fitness in a given environment.

     

Plant phylogeny drives arboreal caterpillar assemblages across the Holarctic

1. Assemblages of insect herbivores are structured by plant traits such as nutrient content, secondary metabolites, physical traits, and phenology. Many of these traits are phylogenetically conserved, implying a decrease in trait similarity with increasing phylogenetic distance of the host plant taxa. Thus, a metric of phylogenetic distances and relationships can be considered a proxy for phylogenetically conserved plant traits and used to predict variation in herbivorous insect assemblages among co‐occurring plant species.
2. Using a Holarctic dataset of exposed‐feeding and shelter‐building caterpillars, we aimed at showing how phylogenetic relationships among host plants explain compositional changes and characteristics of herbivore assemblages.
3. Our plant–caterpillar network data derived from plot‐based samplings at three different continents included >28,000 individual caterpillar–plant interactions. We tested whether increasing phylogenetic distance of the host plants leads to a decrease in caterpillar assemblage overlap. We further investigated to what degree phylogenetic isolation of a host tree species within the local community explains abundance, density, richness, and mean specialization of its associated caterpillar assemblage.
4. The overlap of caterpillar assemblages decreased with increasing phylogenetic distance among the host tree species. Phylogenetic isolation of a host plant within the local plant community was correlated with lower richness and mean specialization of the associated caterpillar assemblages. Phylogenetic isolation had no effect on caterpillar abundance or density. The effects of plant phylogeny were consistent across exposed‐feeding and shelter‐building caterpillars.
5. Our study reveals that distance metrics obtained from host plant phylogeny are useful predictors to explain compositional turnover among hosts and host‐specific variations in richness and mean specialization of associated insect herbivore assemblages in temperate broadleaf forests. As phylogenetic information of plant communities is becoming increasingly available, further large‐scale studies are needed to investigate to what degree plant phylogeny structures herbivore assemblages in other biomes and ecosystems.

     

Trait hierarchies are stronger than trait dissimilarities in structuring spatial co‐occurrence patterns of common tree species in a subtropical forest

1. The dissimilarity and hierarchy of trait values that characterize niche and fitness differences, respectively, have been increasingly applied to infer mechanisms driving community assembly and to explain species co‐occurrence patterns. Here, we predict that limiting similarity should result in the spatial segregation of functionally similar species, while functionally similar species will be more likely to co‐occur either due to environmental filtering or due to competitive exclusion of inferior competitors (hereafter hierarchical competition).
2. We used a fully mapped 50‐ha subtropical forest plot in southern China to explore how pairwise spatial associations between saplings and between adult trees were influenced by trait dissimilarity and hierarchy in order to gain insight into assembly mechanisms. We assessed pairwise spatial associations using two summary statistics of spatial point patterns at different spatial scales and compared the effects of trait dissimilarity and trait hierarchy of different functional traits on the interspecific spatial associations. These comparisons allow us to disentangle the effects of limiting similarity, environmental filtering, and hierarchical competition on species co‐occurrence.
3. We found that trait dissimilarity was generally negatively related to interspecific spatial associations for both saplings and adult trees across spatial scales, meaning that species with similar trait values were more likely to co‐occur and thus supporting environmental filtering or hierarchical competition. We further found that trait hierarchy outweighed trait dissimilarity in structuring pairwise spatial associations, suggesting that hierarchical competition played a more important role in structuring our forest community than environmental filtering across life stages.
4. This study employed a novel method, by offering the integration of pairwise spatial association and trait dissimilarity as well as trait hierarchy, to disentangle the relative importance of multiple assembly mechanisms in structuring co‐occurrence patterns, especially the mechanisms of environmental filtering and hierarchical competition, which lead to indistinguishable co‐occurrence patterns. This study also reinforced the importance of trait hierarchy rather than trait dissimilarity in driving neighborhood competition.

     

Remotely sensed between‐individual functional trait variation in a temperate forest

1. Trait‐based ecology holds the promise to explain how plant communities work, for example, how functional diversity may support community productivity. However, so far it has been difficult to combine field‐based approaches assessing traits at the level of plant individuals with limited spatial coverage and approaches using remote sensing (RS) with complete spatial coverage but assessing traits at the level of vegetation pixels rather than individuals. By delineating all individual‐tree crowns within a temperate forest site and then assigning RS‐derived trait measures to these trees, we combine the two approaches, allowing us to use general linear models to estimate the influence of taxonomic or environmental variation on between‐ and within‐species variation across contiguous space.
2. We used airborne imaging spectroscopy and laser scanning to collect individual‐tree RS data from a mixed conifer‐angiosperm forest on a mountain slope extending over 5.5 ha and covering large environmental gradients in elevation as well as light and soil conditions. We derived three biochemical (leaf chlorophyll, carotenoids, and water content) and three architectural traits (plant area index, foliage‐height diversity, and canopy height), which had previously been used to characterize plant function, from the RS data. We then quantified the contributions of taxonomic and environmental variation and their interaction to trait variation and partitioned the remaining within‐species trait variation into smaller‐scale spatial and residual variation. We also investigated the correlation between functional trait and phylogenetic distances at the between‐species level. The forest consisted of 13 tree species of which eight occurred in sufficient abundance for quantitative analysis.
3. On average, taxonomic variation between species accounted for more than 15% of trait variation in biochemical traits but only around 5% (still highly significant) in architectural traits. Biochemical trait distances among species also showed a stronger correlation with phylogenetic distances than did architectural trait distances. Light and soil conditions together with elevation explained slightly more variation than taxonomy across all traits, but in particular increased plant area index (light) and reduced canopy height (elevation). Except for foliage‐height diversity, all traits were affected by significant interactions between taxonomic and environmental variation, the different responses of the eight species to the within‐site environmental gradients potentially contributing to the coexistence of the eight abundant species.
4. We conclude that with high‐resolution RS data it is possible to delineate individual‐tree crowns within a forest and thus assess functional traits derived from RS data at individual level. With this precondition fulfilled, it is then possible to apply tools commonly used in field‐based trait ecology to partition trait variation among individuals into taxonomic and potentially even genetic variation, environmental variation, and interactions between the two. The method proposed here presents a promising way of assessing individual‐based trait information with complete spatial coverage and thus allowing analysis of functional diversity at different scales. This information can help to better understand processes shaping community structure, productivity, and stability of forests.

     

Traits explain sorting of C4 grasses along a global precipitation gradient

1. Species distributions are closely associated with moisture availability, but the underlying mechanisms remain unresolved. Drought relations are especially important for plants such as C₄ grasses that dominate seasonally dry ecosystems. Here, we test the hypothesis that C₄ grass species sampled across global precipitation gradients show variation in survival under drought that can be explained by their traits.
2. Our experiment subjected 18 C₄ grass species to a lethal drought under controlled environmental conditions. The number of days until death was measured, along with root traits, senescence, and aspects of hydraulic function.
3. We identified two strategies: Drought‐avoiding species that stayed green as the water potential declined and drought‐tolerating species that senesced more quickly but could extend survival via drought‐tolerant meristems.
4. Plants that stay‐green for longer occupied drier habitats and had the longest survival under drought, facilitated by narrow root diameter and isohydric stomatal behavior. Plants that senesced quickly had thicker roots, an anisohydric strategy, and occupied wetter habitats.
5. Global distributions of C₄ grasses can be predicted by variation in rates of senescence, meristem survival, root traits, and stomatal strategy, showing the value of these traits for understanding plant distributions in relation to climate.

     

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

1. 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.
2. 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.
3. 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.
4. 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.

     

Genital and body allometry in two species of noctuid moths (Lepidoptera: Noctuidae)

One‐size‐fits‐all and related hypotheses predict that static allometry slopes for male genitalia will be consistently lower than 1.0 and lower than the slopes for most other body parts (somatic traits). We examined the allometry of genitalic and somatic morphological traits in males and females of two species of noctuid moths, Spodoptera exigua (Hübner, [1808]) and Helicoverpa armigera (Hübner, [1808]). The relationship between genitalic traits and body size was generally strongly negative‐allometric in males but with no significant differences from 1.00 in females of the two species examined. However, in females, the slope of genital traits was also lower than the slopes for somatic traits. The relationship between somatic traits and the body size indicator was approximately isometric in most cases in males, except in four traits in S. exigua, in which the slopes showed slight negative allometry, and the hind tibia in H. armigera, in which the slope had positive allometry. However, in females, some somatic traits showed isometric and some other showed negative allometry in both species. The coefficients of variation (CV) for all structures in the males were low, not exceeding 10%. Genitalic traits showed significantly lower CV than somatic traits in males. In females, somatic traits showed lower CV than genitalic traits but with no significant difference in the H. armigera. Our observations of strongly negative allometry for genitalic traits in males are consistent with stabilizing selection on genital size and we suggest that male performance in interactions with females is the source of selection on male genital allometry. The difference in the degree of phenotypic variation between genitalic and somatic traits in the two studied species is attributed to the different developmental‐genetic architectures of these traits. Female genitalia showed a similar trend to the males, although the difference between genital and somatic traits was not significant in females. This finding suggests that selection is acting differently on male and female genitalia. Positive allometry of hind tibia in H. armigera may be a result of secondary sexual function.     

Scaling the extinction vortex: Body size as a predictor of population dynamics close to extinction events

1. Mutual reinforcement between abiotic and biotic factors can drive small populations into a catastrophic downward spiral to extinction—a process known as the “extinction vortex.” However, empirical studies investigating extinction dynamics in relation to species'' traits have been lacking.
2. We assembled a database of 35 vertebrate populations monitored to extirpation over a period of at least ten years, represented by 32 different species, including 25 birds, five mammals, and two reptiles. We supplemented these population time series with species‐specific mean adult body size to investigate whether this key intrinsic trait affects the dynamics of populations declining toward extinction.
3. We performed three analyses to quantify the effects of adult body size on three characteristics of population dynamics: time to extinction, population growth rate, and residual variability in population growth rate.
4. Our results provide support for the existence of extinction vortex dynamics in extirpated populations. We show that populations typically decline nonlinearly to extinction, while both the rate of population decline and variability in population growth rate increase as extinction is approached. Our results also suggest that smaller‐bodied species are particularly prone to the extinction vortex, with larger increases in rates of population decline and population growth rate variability when compared to larger‐bodied species.
5. Our results reaffirm and extend our understanding of extinction dynamics in real‐life extirpated populations. In particular, we suggest that smaller‐bodied species may be at greater risk of rapid collapse to extinction than larger‐bodied species, and thus, management of smaller‐bodied species should focus on maintaining higher population abundances as a priority.

     

Bringing function to structure: Root–soil interactions shaping phosphatase activity throughout a soil profile in Puerto Rico

1. Large areas of highly productive tropical forests occur on weathered soils with low concentrations of available phosphorus (P). In such forests, root and microbial production of acid phosphatase enzymes capable of mineralizing organic phosphorus is considered vital to increasing available P for plant uptake.
2. We measured both root and soil phosphatase throughout depth and alongside a variety of root and soil factors to better understand the potential of roots and soil biota to increase P availability and to constrain estimates of the biochemical mineralization within ecosystem models.
3. We measured soil phosphatase down to 1 m, root phosphatase to 30 cm, and collected data on fine‐root mass density, specific root length, soil P, bulk density, and soil texture using soil cores in four tropical forests within the Luquillo Experimental Forest in Puerto Rico.
4. We found that soil phosphatase decreased with soil depth, but not root phosphatase. Furthermore, when both soil and root phosphatase were expressed per soil volume, soil phosphatase was 100‐fold higher that root phosphatase.
5. Both root and soil factors influenced soil and root phosphatase. Soil phosphatase increased with fine‐root mass density and organic P, which together explained over 50% of the variation in soil phosphatase. Over 80% of the variation in root phosphatase per unit root mass was attributed to specific root length (positive correlation) and available (resin) P (negative correlation).
6. Synthesis: Fine‐root traits and soil P data are necessary to understand and represent soil and root phosphatase activity throughout the soil column and across sites with different soil conditions and tree species. These findings can be used to parameterize or benchmark estimates of biochemical mineralization in ecosystem models that contain fine‐root biomass and soil P distributions throughout depth.

     

Reliability analysis of fish traits reveals discrepancies among databases

1. Trait-based approaches are commonly used in ecology to understand the relationship between biodiversity and ecosystem functioning, environmental filtering or biotic responses to anthropogenic perturbations. However, little is known about the reliability of assigned traits and the consistency of trait information among different databases currently in use.
2. Using 99 native and alien Iberian inland fish species, we investigated a total of 27 biological and ecological traits for their consistency among 19 different databases and identified less reliable traits, that is, traits with high disagreement among databases. Specifically, we used generalised linear models and inter-rater reliability statistics (Krippendorff's α) to test for differences in trait values among databases. We also identified well-studied versus data-deficient traits and species.
3. Our results show notable discrepancies and low reliability for several biological and ecological traits such as microhabitat preference, omnivory, invertivory, rheophily, and limnophily. Least reliable traits were mainly categorical (rather than continuous) and established by expert judgment and without a clear definition or a common methodology. Interestingly, categorical traits such as rheophily or limnophily, which showed significantly lower reliability, concurrently showed higher data availability and use than continuously scaled traits.
4. Such uncertainties in trait assignments could affect bioassessment and other ecological analyses. Species with smaller distributional ranges and those that have been described more recently, presented lower coverage and data availability in trait databases.
5. We encourage further standardisation of fish trait measurement protocols to help improve the robust application of bioassessment indices and trait-based approaches.

     

Severe limitations of the FEve metric of functional evenness and some alternative metrics

The metric of functional evenness FEve is an example of how approaches to conceptualizing and measuring functional variability may go astray. This index has several critical conceptual and practical drawbacks:

1. Different values of the FEve index for the same community can be obtained if the species have unequal species abundances; this result is highly likely if most of the traits are categorical.
2. Very minor differences in even one pairwise distance can result in very different values of FEve.
3. FEve uses only a fraction of the information contained in the matrix of species distances. Counterintuitively, this can cause very similar FEve scores for communities with substantially different patterns of species dispersal in trait space.
4. FEve is a valid metric only if all species have exactly the same abundances. However, the meaning of FEve in such an instance is unclear as the purpose of the metric is to measure the variability of abundances in trait space.

We recommend not using the FEve metric in studies of functional variability. Given the wide usage of FEve index over the last decade, the validity of the conclusions based on those estimates is in question. Instead, we suggest three alternative metrics that combine variability in species distances in trait space with abundance in various ways. More broadly, we recommend that researchers think about which community properties (e.g., trait distances of a focus species to the nearest neighbor or all other species, variability of pairwise interactions between species) they want to measure and pick from among the appropriate metrics.     

Changes in vegetation structure and composition of a lowland mire over a sixty‐five‐year interval

1. Mires are characterized by plant communities of high conservation and societal value, which have experienced a major decline in area in many parts of the world, particularly Europe. Evidence suggests that they may be particularly vulnerable to changes in climate and nutrient addition. Although they have been the focus of extensive paleoecological research, few attempts have been made to examine the dynamics of mire vegetation during the current era of anthropogenic environmental change.
2. To assess long‐term change in the spatial structure and composition of a lowland mire community, in 2016 we resurveyed plots first surveyed in 1951. Measures of species richness and composition were compared between the two surveys, and changes in community composition were related to plant traits.
3. Overall, mean species richness declined by 26%. The area of occupancy declined in 37% of species, which were primarily oligotrophic species typical of nutrient‐poor bog communities. Conversely, occupancy increased in 21% of species, especially those that were more tolerant of higher nutrient availability. These changes were associated with variation in plant functional traits, as indicated by an increase mean Ellenberg trait values for nitrogen and mean temperature, and a decline in values for precipitation. These results suggest that eutrophication and climate change have been key drivers of floristic change on this site.
4. Synthesis. This investigation provides a rare assessment of the dynamics of a mire community over a multi‐decadal interval. Results indicate that substantial change has occurred in the composition of the community, and the distribution of species within it. The investigation provides evidence of the impact of environmental change on the composition and structure of a lowland mire community, and highlights challenges for its future conservation.

     

The form of sexual selection on male genitalia cannot be inferred from within-population variance and allometry - a case study in Aquarius remigis

Male genital morphology in insects and arachnids is characterized by static hypoallometry and low intrapopulational levels of phenotypic variation relative to other male traits. The one-size-fits-all model of genital evolution attributes these patterns to stabilizing sexual selection. This model relies on the assumption that the observed patterns of variation and allometry reflect the form of sexual selection acting these traits. We test this by examining the patterns of scaling and trait variation for a set of genitalic and somatic morphological traits in male water striders (Aquarius remigis). This suite of traits is of particular interest because previous work has shown that the genitalic traits are under strong directional selection whereas the somatic traits are under either weak directional or stabilizing selection. Because the selection regime for these traits is known, we can, for the first time, test the purported relationship between trait variation, scaling, and the form of sexual selection. We show that the patterns of variation and scaling of these traits differ sharply from those predicted for traits experiencing strong directional sexual selection. Specifically, the male genital structures show static hypoallometry and low intrapopulational levels of phenotypic variation relative to other male traits, in spite of consistent, strong, directional sexual selection. These scaling relationships and levels of variation are typical of genital traits in other insect species, where they have been presumed to reflect stabilizing sexual selection. Our data clearly refute the assumption of the one-size-fits-all hypothesis that hypoallometric scaling of genitalic traits implies stabilizing selection. We discuss the implications of this finding and propose future directions for improving our current understanding of genital evolution in arthropods.     

Intrapopulation variability in a functional trait: Susceptibility of Daphnia to limitation by dietary fatty acids

1. Functional traits are measurable characteristics of an organism that have an impact on its fitness. Variation in functional traits between and among species has been suggested to represent the basis for competition and selection, thus allowing for evolution in natural populations.
2. In freshwater ecosystems, the availability of essential polyunsaturated fatty acids (PUFAs), in particular ω3‐ and ω6‐PUFAs, determines the food quality of phytoplankton for the herbivorous zooplankton Daphnia, an unselective filter feeder. The content of such essential PUFAs in the phytoplankton is thus a functional phytoplankton trait affecting the trophic transfer efficiency and dynamics at the pelagic plant–herbivore interface.
3. In turn, the susceptibility of consumers to become limited by the availability of essential PUFAs is a fitness‐determining trait of Daphnia genotypes, and variability of this herbivore trait may thus affect the daphnids’ intrapopulation competition. To estimate the intrapopulation variation in susceptibility, we isolated clonal lines of Daphnia longispina from a natural population and compared the strength of their limitation by dietary PUFA availability via standardised laboratory growth assays. We used a liposome supplementation technique to enrich a PUFA‐poor green alga with essential ω3‐ and ω6‐PUFAs and determined juvenile somatic growth rate of different D. longispina genotypes as a fitness proxy.
4. As expected, D. longispina genotypes that coexisted in a natural population differed markedly in their specific patterns of susceptibility to dietary PUFA availability. On average, the D. longispina population was more strongly susceptible to limitations in the availability of the ω6‐PUFA arachidonic acid (20:4ω6) than to limitations in the availability of ω3‐PUFAs α‐linolenic acid (18:3ω3) and eicosapentaenoic acid (20:5ω3).
5. The ability to cope with PUFA limitation is thus a crucial trait that can probably affect intraspecific competition and Daphnia population structure. Therefore, we suggest that such intrapopulation variation in susceptibility to absence of dietary PUFAs might be one of the driving forces of natural selection and local adaptation among freshwater zooplankton.

     

Plant functional traits differ in adaptability and are predicted to be differentially affected by climate change

1. Climate change is testing the resilience of forests worldwide pushing physiological tolerance to climatic extremes. Plant functional traits have been shown to be adapted to climate and have evolved patterns of trait correlations (similar patterns of distribution) and coordinations (mechanistic trade‐off). We predicted that traits would differentiate between populations associated with climatic gradients, suggestive of adaptive variation, and correlated traits would adapt to future climate scenarios in similar ways.
2. We measured genetically determined trait variation and described patterns of correlation for seven traits: photochemical reflectance index (PRI), normalized difference vegetation index (NDVI), leaf size (LS), specific leaf area (SLA), δ¹³C (integrated water‐use efficiency, WUE), nitrogen concentration (N_CONC), and wood density (WD). All measures were conducted in an experimental plantation on 960 trees sourced from 12 populations of a key forest canopy species in southwestern Australia.
3. Significant differences were found between populations for all traits. Narrow‐sense heritability was significant for five traits (0.15–0.21), indicating that natural selection can drive differentiation; however, SLA (0.08) and PRI (0.11) were not significantly heritable. Generalized additive models predicted trait values across the landscape for current and future climatic conditions (>90% variance). The percent change differed markedly among traits between current and future predictions (differing as little as 1.5% (δ¹³C) or as much as 30% (PRI)). Some trait correlations were predicted to break down in the future (SLA:N_CONC, δ¹³C:PRI, and N_CONC:WD).
4. Synthesis: Our results suggest that traits have contrasting genotypic patterns and will be subjected to different climate selection pressures, which may lower the working optimum for functional traits. Further, traits are independently associated with different climate factors, indicating that some trait correlations may be disrupted in the future. Genetic constraints and trait correlations may limit the ability for functional traits to adapt to climate change.

     

Ant community composition and functional traits in new grassland strips within agricultural landscapes

1. Ongoing intensification and fragmentation of European agricultural landscapes dramatically reduce biodiversity and associated functions. Enhancing perennial noncrop areas holds great potential to support ecosystem services such as ant‐mediated pest control.
2. To study the potential of newly established grassland strips to enhance ant diversity and associated functions, we used hand collection data and predation experiments to investigate differences in (a) ant community composition and (b) biocontrol‐related functional traits, and (c) natural pest control across habitats in cereal fields, old grasslands, and new grassland transects of three years of age.
3. Ant species diversity was similar between new and old grasslands, but significantly higher in new grasslands than in surrounding cereal fields. Contrary, ant community composition of new grasslands was more similar to cereal fields and distinct from the species pool of old grasslands. The functional trait space covered by the ant communities showed the same distribution between old and new grasslands. Pest control did not differ significantly between habitat types and therefore could not be linked to the prevalence of functional ant traits related to biocontrol services in new grasslands.
4. Our findings not only show trends of convergence between old and new grasslands, but also indicate that enhancing ant diversity through new grasslands takes longer than three years to provide comparable biodiversity and functionality.
5. Synthesis and applications: Newly established grasslands can increase ant species richness and abundance and provide a consistent amount of biocontrol services in agroecosystems. However, three years after their establishment, new grasslands were still dominated by common agrobiont ant species and lacked habitat specialists present in old grasslands, which require a constant supply of food resources and long colony establishment times. New grasslands represent a promising measure for enhancing agricultural landscapes but must be preserved in the longer term to promote biodiversity and resilience of associated ecosystem services.

     

The normalized segment classification model: A new tool to compare spectral reflectance curves

1. Color patterns are complex traits under selective pressures from conspecifics, mutualists, and antagonists. To evaluate the salience of a pattern or the similarity between colors, several visual models are available. Color discrimination models estimate the perceptual difference between any two colors. Their application to a diversity of taxonomic groups has become common in the literature to answer behavioral, ecological, and evolutionary questions. To use these models, we need information about the visual system of our beholder species. However, many color patterns are simultaneously subject to selective pressures from different species, often from different taxonomic groups, with different visual systems. Furthermore, we lack information about the visual system of many species, leading ecologists to use surrogate values or theoretical estimates for model parameters.
2. Here, we present a modification of the segment classification method proposed by Endler (Biological Journal of the Linnean Society, 1990 41, 315–352): the normalized segment classification model (NSC). We explain its logic and use, exploring how NSC differs from other visual models. We also compare its predictions with available experimental data.
3. Even though the NSC model includes no information about the visual system of the receiver species, it performed better than traditional color discrimination models when predicting the output of some behavioral tasks. Although vision scientists define color as independent of stimulus brightness, a likely explanation for the goodness of fit of the NSC model is that its distance measure depends on brightness differences, and achromatic information can influence the decision‐making process of animals when chromatic information is missing.
4. Species‐specific models may be insufficient for the study of color patterns in a community context. The NSC model offers a species‐independent solution for color analyses, allowing us to calculate color differences when we ignore the intended viewer of a signal or when different species impose selective pressures on the signal.

     

Niche separation and weak interactions in the high tidal zone of saltmarsh‐mangrove mixing communities

1. Saltmarsh‐mangrove ecotones occur at the boundary of the natural geographic distribution of mangroves and salt marshes. Climate warming and species invasion can also drive the formation of saltmarsh‐mangrove mixing communities. How these coastal species live together in a “new” mixed community is important in predicting the dynamic of saltmarsh‐mangrove ecosystems as affected by ongoing climate change or human activities. To date, the understanding of species interactions has been rare on adult species in these ecotones.
2. Two typical coastal wetlands were selected as cases to understand how mangrove and saltmarsh species living together in the ecotones. The leaves of seven species were sampled from these coastal wetlands based on their distribution patterns (living alone or coexisting) in the high tidal zone, and seven commonly used functional traits of these species were analyzed.
3. We found niche separation between saltmarsh and mangrove species, which is probably due to the different adaptive strategies they adopted to deal with intertidal environments.
4. Weak interactions between coexisting species were dominated in the high tidal zone of the two saltmarsh‐mangrove communities, which could be driven by both niche differentiation and neutral theory.
5. Synthesis. Our field study implies a potential opportunity to establish a multispecies community in the high tidal zone of saltmarsh‐mangrove ecotones, where the sediment was characterized by low salinity and high nitrogen.

     

Targeted and passive environmental DNA approaches outperform established methods for detection of quagga mussels,Dreissena rostriformis bugensis in flowing water

1. The early detection of invasive non‐native species (INNS) is important for informing management actions. Established monitoring methods require the collection or observation of specimens, which is unlikely at the beginning of an invasion when densities are likely to be low. Environmental DNA (eDNA) analysis is a highly promising technique for the detection of INNS—particularly during the early stages of an invasion.
2. Here, we compared the use of traditional kick‐net sampling with two eDNA approaches (targeted detection using both conventional and quantitative PCR and passive detection via metabarcoding with conserved primers) for detection of quagga mussel, Dreissena rostriformis bugensis, a high priority INNS, along a density gradient on the River Wraysbury, UK.
3. All three molecular tools outperformed traditional sampling in terms of detection. Conventional PCR and qPCR both had 100% detection rate in all samples and outperformed metabarcoding when the target species was at low densities. Additionally, quagga mussel DNA copy number (qPCR) and relative read count (metabarcoding) were significantly influenced by both mussel density and distance from source population, with distance being the most significant predictor.
4. Synthesis and application. All three molecular approaches were more sensitive than traditional kick‐net sampling for the detection of the quagga mussel in flowing water, and both qPCR and metabarcoding enabled estimates of relative abundance. Targeted approaches were more sensitive than metabarcoding, but metabarcoding has the advantage of providing information on the wider community and consequently the impacts of INNS.