Phytoplasmas (Mollicutes, Acholeplasmataceae), vector-borne obligate bacterial plant-parasites, infect nearly 1,000 plant species and unknown numbers of insects, mainly leafhoppers (Hemiptera, Deltocephalinae), which play a key role in transmission and epidemiology. Although the plant-phytoplasma-insect association has been evolving for >300 million years, nearly all known phytoplasmas have been discovered as a result of the damage inflicted by phytoplasma diseases on crops. Few efforts have been made to study phytoplasmas occurring in non-economically important plants in natural habitats. In this study, a sub-sample of leafhopper specimens preserved in a large museum biorepository was analyzed to unveil potential new associations. PCR screening for phytoplasmas performed on 227 phloem-feeding leafhoppers collected worldwide from natural habitats revealed the presence of 6 different previously unknown phytoplasma strains. This indicates that museum collections of herbivorous insects represent a rich and largely untapped resource for discovery of new plant pathogens, that natural areas worldwide harbor a diverse but largely undiscovered diversity of phytoplasmas and potential insect vectors, and that independent epidemiological cycles occur in such habitats, posing a potential threat of disease spillover into agricultural systems. Larger-scale future investigations will contribute to a better understanding of phytoplasma genetic diversity, insect host range, and insect-borne phytoplasma transmission and provide an early warning for the emergence of new phytoplasma diseases across global agroecosystems.

Phenotypic integration and developmental canalization have been hypothesized to constrain the degree of phenotypic plasticity, but there is little evidence for the relationships among the three processes in different environments, especially for plants under natural conditions. To address this issue, we conducted a field experiment by subjecting plants of Abutilon theophrasti to low, medium and high densities, under infertile and fertile soil conditions, measured a variety of traits and analyzed canalization (coefficient of variation [CV]), integration (coefficient of integration [CI] and the number of significant correlations of a trait with other traits [NC]), and plasticity (REL RDPIs and ABS RDPIs) in these traits and their relationships at two stages of plant growth. Our results showed an increase in mean CV, NC and ABS RDPIs of traits with density, and the positive correlations between trait NC and ABS RDPIs became stronger with higher densities but weaker over time in fertile soil, while correlations among trait CV, NC and ABS RDPIs became stronger over time in infertile soil. Results suggested shared or cooperation mechanisms among phenotypic integration, canalization and plasticity. Soil conditions and growth stage may affect responses of these correlations to density via modifying plant size and competition strength. The attenuated canalization and enhanced integration may be helpful for the production of plasticity, especially under intense competition.

Marine food webs are highly compartmentalized and characterizing the trophic niches among consumers is important for predicting how impact from human activities affect the structuring and functioning of marine food webs. Biomarkers such as bulk stable isotopes have proven to be powerful tools to elucidate trophic niches, but they may lack in resolution, particularly when spatio-temporal variability in a system is high. To close this gap, we investigated whether carbon isotope (δ13C) patterns of essential amino acids (EAAs), also termed δ13AA fingerprints, can characterize niche differentiation in a highly dynamic marine system. We tested the ability of δ13AA fingerprints to differentiate trophic niches among six functional groups and ten individual species in the Baltic Sea. We also tested whether fingerprints of the common zooplanktivorous fishes, herring and sprat, differ among four Baltic Sea regions with different biochemical conditions and phytoplankton assemblages. Additionally, we investigated how these results compared to bulk C and N isotope data for the same sample set. We found significantly different δ13AA fingerprints among all six functional groups. Species differentiation was in comparison less distinct, due to partial convergence of the species’ fingerprints within functional groups. Herring and sprat displayed region specific δ13AA fingerprints indicating that this approach could be used as a migratory marker. Bulk isotope data had a lower power to differentiate between trophic niches, but may provide more easily interpretable information about relative trophic position than the fingerprints. We conclude that δ13AA fingerprinting has a strong potential to advance our understanding of ecological niches, and trophic linkages from producers to higher trophic levels in dynamic marine systems. Given how management practices of marine resources and habitats are reshaping the structure and function of marine food webs, implementing new and powerful tracer methods are urgently needed to improve the knowledge base for policy makers.

1. Plant leaf stomata are the gatekeepers of the atmosphere-plant interface and are essential building blocks of land surface models as they control transpiration and photosynthesis. Although more stomatal trait data is needed to significantly reduce the error in these model predictions, recording these traits is time-consuming and no standardized protocol is currently available. Some attempts were made to automate stomatal detection from photomicrographs, however, these approaches have the disadvantage of using classic image processing or targeting a narrow taxonomic entity which makes these technologies less robust and generalizable to other plant species. We propose an easy-to-use and adaptable workflow from leaf to label. A methodology for automatic stomata detection was developed using deep neural networks according to the state-of-the-art and its applicability demonstrated across the phylogeny of the angiosperms. 2. We used a patch-based approach for training/tuning three different deep learning architectures. For training, we used 431 micrographs taken from leaf prints made according the nail polish method from herbarium specimens of 19 species. The best performing architecture was tested on 595 images of 16 additional species spread across the angiosperm phylogeny. 3. The nail polish method was successfully applied in 78% of the species sampled here. The VGG19 architecture slightly outperformed the basic shallow and deep architectures, with a confidence threshold equal to 0.7 resulting in an optimal trade-off between precision and recall. Applying this threshold the VGG19 architecture obtained an average F-score of 0.87, 0.89 and 0.67 on the training, validation and unseen test set, respectively. The average accuracy was very high (94%) for computed stomatal counts on unseen images of species used for training. 4. The leaf-to-label pipeline is an easy-to-use workflow for researchers of different areas of expertise interested in detecting stomata more efficiently. The described methodology was based on multiple species and well-established methods so that it can serve as a reference for future work.

Fish migrations are energetically costly, especially when moving between fresh and saltwater, but are a viable strategy for Pacific salmon and trout (Oncorhynchus spp.) due to the advantageous resources available at various life stages. Anadromous steelhead (O. mykiss) migrate vast distances and exhibit variation for migration phenotypes that have a genetic basis at candidate genes known as greb1L and rock1. We examined the distribution of genetic variation at 13 candidate markers spanning greb1L, intergenic, and rock1 regions versus 246 neutral markers for 113 populations (n = 9,471) of steelhead from inland and coastal lineages in the Columbia River. Patterns of population structure with neutral markers reflected genetic similarity by geographic region as demonstrated in previous studies, but candidate markers clustered populations by predominate genetic variation associated with migration timing. Mature alleles for late migration had the highest frequency overall in steelhead populations throughout the Columbia River, with only 9 of 113 populations that had a higher frequency of premature alleles for early migration. While a single haplotype block was evident for the coastal lineage, we identified multiple haplotype blocks for the inland lineage. The inland lineage had one haplotype block that corresponded to candidate markers within the greb1L gene and immediately upstream in the intergenic region, and the second block only contained candidate markers from the intergenic region. Haplotype frequencies had similar patterns of geographic distribution as single markers, but there were distinct differences in frequency between the two haplotype blocks for the inland lineage. Redundancy analyses were used to model environmental effects on allelic frequencies of candidate markers and significant variables were migration distance, temperature, isothermality, and annual precipitation. This study improves our understanding of the spatial distribution of genetic variation underlying migration timing in steelhead as well as associated environmental factors and has direct conservation and management implications.

The contribution of wild insects to crop pollination is becoming increasingly important as global demand for crops dependent on animal pollination increases. If wild insect populations are to persist in agricultural landscapes, there must be sufficient floral resources (FR) over time and space. The temporal, within-season component of FR availability has rarely been investigated, despite growing recognition of its likely importance for pollinator populations. Here, we examined the visitation rates of common bee genera and the spatiotemporal availability of FR in agroecosystems over one season to determine whether local bee activity was limited by the abundance of landscape FR, and if so, whether it was limited by the present or past abundance of landscape FR. Visitation rates and landscape FR were measured in 27 agricultural sites in Ontario and Québec, Canada, across four time periods and three spatial scales. Landscape FR at varying spatial scales predicted visits for the seven most commonly observed bee genera. Bombus visitation rates were higher in landscapes that had greater cumulative seasonal abundance of FR, suggesting the importance of early-season FR for this taxon. Visits from Halictus and Lasioglossum were higher in landscapes that provided either a stable or increasing amount of FR over the season and were lower in landscapes that experienced a decrease in FR over the course of a season. Andrena, Augochlorella, Megachile, and Peponapis visits were not measurably influenced by FR in previous months but were lower in landscapes that had a higher present abundance of FR, perhaps reflecting pollinator movement or dilution. Our research provides insight into how seasonal fluctuations in floral resources affect bee activity, and by examining each bee genus separately, we could observe how differences in foraging periods, foraging ranges, and the number of broods per season influence how bee taxa respond to food availability within agroecosystems.

1. A time-consuming challenge faced by ecologists is the extraction of meaningful data from camera trap images to inform ecological management. Automated object detection solutions are increasingly, however, most are not sufficiently robust to be deployed on a large scale due to lack of location invariance across sites. This prevents optimal use of ecological data and results in significant resource expenditure to annotate and retrain object detectors. 2. In this study, we aimed to (a) assess the value of publicly available image datasets including FlickR and iNaturalist (FiN) when training deep learning models for camera trap object detection (b) develop a for training location invariant object detection models and (c) explore the use of small subsets of camera trap images for optimization training. 3. We collected and annotated 3 datasets of images of striped hyena, rhinoceros and pig, from FiN, and used transfer learning to train 3 object detection models in the task of animal detection. We compared the performance of these models to that of 3 models trained on the Wildlife Conservation Society and Camera CATalogue datasets, when tested on out of sample Snapshot Serengeti datasets. Furthermore, optimized the FiN models via infusion of small subsets of camera trap images to increase robustness for challenging detection cases. 4. In all experiments, the mean Average Precision (mAP) of the FiN models was significantly higher (82.33-88.59%) than that achieved by the models trained only on camera trap datasets (38.5-66.74%). The infusion of camera trap images into FiN training further improved mAP, with increases ranging from 1.78-32.08%. 5. Ecology researchers can use FiN images for training robust, location invariant, out-of-the-box, deep learning object detection solutions for camera trap image processing. This would allow AI technologies to be deployed on a large scale in ecological applications. Datasets and code related to this study are open source and available at: https://github.com/ashep29/infusion

Wild bees form diverse communities that pollinate plants in both native and agricultural ecosystems making them both ecologically and economically important. The growing evidence of bee declines has sparked increased interest in monitoring bee community and population dynamics using standardized methods. Here, we studied the dynamics of bee biodiversity within and across years by monitoring wild bees adjacent to four apple orchard locations in Southern Pennsylvania, USA. We collected bees using passive Blue Vane traps continuously from April to October for six years amassing over 26,000 bees representing 144 species. We quantified total abundance, richness, diversity, composition, and phylogenetic structure. There were large seasonal changes in all measures of biodiversity with month explaining an average of 72% of the variation in our models. Changes over time were less dramatic with years explaining an average of 44% of the variation in biodiversity metrics. We found declines in all measures of biodiversity especially in the last 3 years. Analyses of population trends over time for the 40 most abundant species indicate that about one third of species showed at least some evidence for declines in abundance. Bee family explained variation in species-level seasonal patterns but we found no consistent family-level patterns in declines, though bumble bees and sweat bees were groups that declined the most. Overall, our results show that season-wide standardized sampling across multiple years can reveal nuanced patterns in bee biodiversity, phenological patterns of bees, and population trends over time of many co-occurring species. These datasets could be used to quantify the relative effects that different aspects of environmental change have on bee communities and to help prioritize conservation efforts.

Understanding the drivers of morphological convergence requires investigation into its relationship with behavior and niche-space, and such investigations in turn provide insights into evolutionary dynamics, functional morphology, and life history. Mygalomorph spiders (trapdoor spiders and their kin) have long been associated with high levels of homoplasy, and many convergent features can be intuitively associated with different behavioral niches. Using genus-level phylogenies based on recent genomic studies and a newly assembled matrix of discrete behavioral and somatic morphological characters, we reconstruct the evolution of burrowing behavior in the Mygalomorphae, compare the influence of behavior and evolutionary history on somatic morphology, and test hypotheses of correlated evolution between specific morphological features and behavior. Our results reveal the simplicity of the mygalomorph adaptive landscape, with opportunistic, web-building taxa at one end, and burrowing/nesting taxa with structurally-modified burrow entrances (e.g., a trapdoor) at the other. Shifts in behavioral niche, in both directions, are common across the evolutionary history of the Mygalomorphae, and several major clades include taxa inhabiting both behavioral extremes. Somatic morphology is heavily influenced by behavior, with taxa inhabiting the same behavioral niche often more similar morphologically than more closely-related but behaviorally-divergent taxa, and we were able to identify a suite of 11 somatic features that show significant correlation with particular behaviors. We discuss these findings in light of the function of particular morphological features, niche dynamics within the Mygalomorphae, and constraints on the mygalomorph adaptive landscape relative to other spiders.

Phenotypic plasticity can allow animals to adapt their behaviour, such as their mating effort, to their social and sexual environment. However, this relies on the individual receiving accurate and reliable cues of the environmental conditions. This can be achieved via the receipt of multi-component cues, which may provide redundancy and robustness. Male Drosophila melanogaster detect presence of rivals via combinations of any two or more redundant cue components (sound, smell and touch) and respond by extending their subsequent mating duration, which is associated with higher reproductive success. Although alternative combinations of cues of rival presence have previously been found to elicit equivalent increases in mating duration and offspring production, their redundancy in securing success under sperm competition has not previously been tested. Here, we explicitly test this by exposing male D. melanogaster to alternative combinations of rival cues and examining reproductive success in both the presence and absence of sperm competition. The results supported previous findings of redundancy of cues in terms of behavioural responses. However, there was no evidence of reproductive benefits accrued by extending mating duration in response to rivals. The lack of identifiable fitness benefits of longer mating under these conditions, both in the presence and absence of sperm competition, contrasted with some previous results, but could be explained by: 1) damage sustained from aggressive interactions with rivals leading to reduced ability to increase ejaculate investment, 2) presence of features of the social environment, such as male and female mating status, that obscured the fitness benefits of longer mating, 3) decoupling of behavioural investment with fitness benefits.

Competitive interactions between distantly related clades could cause complementary diversity patterns of these clades over large spatial scales. One such example might be ants and birds in the eastern Himalaya; ants are very common at low elevations but almost absent at mid-elevations where the abundance of other arthropods and insectivorous bird diversity peaks. Here, we ask if ants at low elevations could compete with birds for arthropod prey. Specifically, we studied the impact of the Asian weaver ant (Oecophylla smaragdina), a common aggressive ant at low elevations. Diet analysis using molecular methods demonstrate extensive diet overlap between weaver ants and songbirds at both low and mid-elevations. Trees without weaver ants have greater non-ant arthropod abundance and leaf damage. Experimental removal of weaver ants results in an increase in the abundance of non-ant arthropods. Notably, numbers of Coleoptera and Lepidoptera were most affected by removal experiments and were prominent components of both bird and weaver ant diets. Our results suggest that songbirds and weaver ants might potentially compete with each other for arthropod prey at low elevations, thereby contributing to lower insectivorous bird diversity at low elevations in eastern Himalaya. Competition with ants may shape vertebrate diversity patterns across broad biodiversity gradients.

Tree functional traits together with processes such as forest regeneration, growth, and mortality affect forest and tree structure. Forest management inherently impacts these processes. Moreover, forest structure, biodiversity, resilience, and carbon uptake can be sustained and enhanced with forest management activities. To assess structural complexity of individual trees, comprehensive and quantitative measures are needed, and they are often lacking for current forest management practices. Here, we utilized 3D information from individual Scots pine (Pinus sylvestris L.) trees obtained with terrestrial laser scanning (TLS) to first, assess effects of forest management on structural complexity of individual trees, and second, understand relationship between several tree attributes and structural complexity. We studied structural complexity of individual trees represented by a single scale independent metric called “box dimension”. This study aimed at identifying drivers affecting structural complexity of individual Scots pine trees in boreal forest conditions. The results showed that thinning increased structural complexity of individual Scots pine trees. Furthermore, we found a relationship between structural complexity and stem and crown size and shape as well as tree growth. Thus, it can be concluded that forest management affected structural complexity of individual Scots pine trees in managed boreal forests, and stem, crown, and growth attributes were identified as drivers of it.

The Lesser White-fronted Goose (Anser erythropus), smallest of the “grey” geese, is listed as Vulnerable on the IUCN Red List and protected in all range states. There are three sub-populations, with the least studied being the East Asian sub-population, shared between Russia and China. The extreme remoteness of breeding enclaves makes them largely inaccessible to researchers. As a substitute for visitation, remotely tracking birds from wintering grounds allows exploration of their summer range. Over a period of three years, and using highly accurate GPS tracking devices, eleven individuals of A. erythropus were tracked from the key wintering site of Dongting Lake, China, to breeding, molting, and staging sites in north-eastern Russia. Data obtained from that tracking, bolstered by ground survey and literature records, were used to model the summer distribution of A. erythropus. Although earlier literature suggests the summer range is patchy, the model confirms a contiguous summer range. The most suitable habitats are located along the coasts of the Laptev Sea, primarily the Lena-Delta, in the Yana-Kolyma Lowland, and smaller lowlands of Chukotka with narrow riparian extensions upstream along major rivers such as the Lena, Indigirka and Kolyma. The probability of A. erythropus presence is related to sites with altitude less than 500 m with abundant wetlands, especially riparian habitat, and a climate with precipitation of warmest quarter around 55 mm and mean temperature of wettest quarter around 14oC. Human disturbance also affects site suitability, with a gradual decrease in species presence starting around 160 km from human settlements. Remote tracking of animal species can bridge the knowledge gap required for robust estimation of species distribution patterns in remote areas. Better knowledge of species’ distribution is important in understanding the large-scale ecological consequences of rapid global change and establishing conservation management strategies.

Understanding the genetic properties of adaptive trait evolution is a fundamental crux of biological inquiry that links molecular processes to biological diversity. Important uncertainties persist regarding the genetic predictability of adaptive trait change, the role of standing variation, and whether adaptation tends to result in the fixation of favored variants. Here, we use the recurrent evolution of enhanced ethanol resistance in Drosophila melanogaster during this species' worldwide expansion as a promising system to add to our understanding of the genetics of adaptation. We find that elevated ethanol resistance has evolved at least three times in different cooler regions of the species' modern range - not only at high latitude but also in two African high altitude regions - and that ethanol and cold resistance may have a partially shared genetic basis. Applying a bulk segregant mapping framework, we find that the genetic architecture of ethanol resistance evolution differs substantially not only between our three resistant populations, but also between two crosses involving the same European population. We then apply population genetic scans for local adaptation within our quantitative trait locus regions, and we find potential contributions of genes with annotated roles in spindle localization, membrane composition, sterol and alcohol metabolism, and other processes. We also apply simulation-based analyses that confirm the variable genetic basis of ethanol resistance and hint at a moderately polygenic architecture. However, these simulations indicate that larger-scale studies will be needed to more clearly quantify the genetic architecture of adaptive evolution, and to firmly connect trait evolution to specific causative loci.

Recent taxonomic and molecular phylogenetic studies have shown that Gymnosphaera should be recognized as an independent taxonomic unit at the genus level under the family Cyatheaceae. In this study, the complete chloroplast genomes of the eight species of Cyatheaceae were sequenced, and their phylogenetic relationships were reconstructed using the maximum likelihood, Bayesian inference, maximum parsimony, and neighbor-joining methods, and the characteristics of their simple sequence repeats (SSRs) were compared and analyzed for the first time. The results showed that when Cyatheaceae was divided into three genera,the number, relative abundance, relative density, and GC content of all SSRs and of SSRs of certain unit lengths in the chloroplast genomes of the eight species of Cyatheaceae were genus specific in the whole chloroplast genomes and in their different regions (large single-copy, small single-copy, inverted repeat, intergenic spacer, intron, rRNA gene, and coding sequence regions). The SSRs overall and the single-nucleotide SSRs had significant differences in number, relative abundance, relative density, and GC content between the chloroplast genomes, their intergenic regions, and large single-copy regions. When Cyatheaceae was divided into two genera, only the difference in GC content was significant. Therefore, our results support the restoration of the hierarchical status of Gymnosphaera. This study provides an important basis for the identification of the phylogenetic relationship of Cyatheaceae plants.

Predation is the most common cause of nest failure in birds. While nest predation is relatively well studied in general, our knowledge is unevenly distributed across the globe and taxa, with for example limited information on shorebirds breeding in sub-tropics. Importantly, we know fairly little about the timing of predation within a day and season. Here, we followed 444 nests of red-wattled lapwings (Vanellus indicus), a ground-nesting shorebird, for a sum of 7828 days to estimate a nest predation rate, and continuously monitored 230 of these nests for a sum of 2779 days to reveal how the timing of predation changes over the day and season in a sub-tropical desert. We found that 312 nests (70%) hatched, 76 nests (17%) were predated, 23 (5%) failed for other reasons and 33 (7%) had an unknown fate. Daily predation rate was 0.95% (95%CrI: 0.76% – 1.19%), which for a 30-day long incubation period translates into ~25% (20% – 30%) chance of nest being predated. Such a predation rate is low compared to most other avian species. Predation events (N = 25) were distributed evenly across day and night, with a tendency for increased predation around sunrise. Predation rate and events were distributed evenly also across the season, although night predation was more common later in the season, perhaps because predators reduce their activity during daylight to avoid extreme heat. Indeed, nests were never predated when mid-day ground temperatures exceeded 45°C. Whether the diel activity pattern of resident predators undeniably changes across the breeding season and whether the described predation patterns hold for other populations, species and geographical regions awaits future investigations.

The impact of rising global temperatures on survival and reproduction is putting many species at risk of extinction. In particular, it has recently been shown that thermal effects on reproduction, especially limits to male fertility, can underpin species distributions in insects. However, the physiological factors influencing fertility at high temperatures are poorly understood. Key factors that affect somatic thermal tolerance such as hardening, the ability to phenotypically increase thermal tolerance after a mild heat shock, and the differential impact of temperature on different life stages, are largely unexplored for thermal fertility tolerance. Here, we examine the impact of high temperatures on male fertility in the cosmopolitan fruit fly Drosophila virilis. We first determined whether temperature stress at either the pupal or adult life-history stage impacts fertility. We then tested the capacity for heat-hardening to mitigate heat-induced sterility. We found that thermal stress reduces fertility in different ways in pupae and adults. Pupal heat stress delays sexual maturity, whereas males heated as adults can reproduce initially following heat stress, but lose the ability to produce offspring. We also found evidence that while heat-hardening in D. virilis can improve high temperature survival, there is no significant protective impact of this same hardening treatment on fertility. These results suggest that males may be unable to prevent the costs of high temperature stress on fertility through heat-hardening which limits a species' ability to quickly and effectively reduce fertility loss in the face of short-term high temperature events.

Indiscriminate fire is rampant throughout subtropical South and Southeast Asian grasslands. However, very little is known about the role of fire and pyric herbivory on the functioning of highly productive subtropical monsoon grasslands lying within Cwa-climatic region. We collected grass samples from 60 m x 60 m plots and determined vegetation physical and chemical properties at regular 30-day intervals from April to July 2020, starting from 30 days after fire to assess post-fire regrowth forage quality. We counted pellet groups for the same four months from 2 m x 2 m quadrats that were permanently marked with pegs along the diagonal of each 60 m x 60 m plot to estimate grazing intensity to the progression of post-fire regrowth. We observed strong and significant reductions in crude protein (mean value 9.1 to 4.1 [55% decrease]) and phosphorus (mean value 0.2 to 0.11 [45% decrease]) in forage collected during different time intervals i.e., from 30 days to 120 days after fire. Mesofaunal deer utilised the burned areas extensively for a short period, i.e., up to two months after fire when the burned areas contained short grasses with a higher level of crude protein and phosphorus. Grazing intensity of chital (Axis axis) to post-fire regrowth differed significantly over time since fire, with higher intensity of use at 30 days after fire. Grazing intensity of swamp deer (Rucervus duvaucelii) did not differ significantly until 90 days after fire, however, decreased significantly after 90 days since fire. Large-scale indiscriminate single event fires thus may not fulfil nutritional requirements of all species in mesofaunal deer community in these subtropical monsoon grasslands. We recommend for a spatio-temporal manipulation of fire to reinforce grazing feedback and to yield for the longest possible period a reasonably good food supply for the conservation of mesofaunal deer.