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Plant–herbivore–parasitoid systems are poorly studied in the tropics. Enicospilus carmenae Campos and Palacio sp. nov. are described, originating from southern Mexico in the Yucatan Peninsula and establishing a new tri-trophic interaction. This species is a koinobiont larval endoparasitoid of the American silkworm moth caterpillar Zanola verago (Cramer) (Lepidoptera: Apatelodidae) feeding on the shrub Piper neesianum C.DC. (Piperaceae) in a semi-evergreen forest. The host plant P. neesianum had no herbivore records to date, and a single collection event yielded the rearing of a new species of Enicospilus (Ichneumonidae, Ophioninae). Morphological, molecular (COI), biological, ecological, and geographical data are integrated to delineate the new species. 

The discovery of bioactive natural products is often challenged by the complexity of isolating and characterizing active compounds within diverse mixtures. Previously, we introduced a 1H NMR-based weighted gene correlation network analysis (WGCNA) approach to identify spectral features linked to growth inhibitory activity of Piper (Piperaceae) leaf extracts against model plant, fungal, and bacterial organisms. This method enabled us to prioritize specific spectral features linked to bioactivity, offering a targeted approach to natural product discovery. In this study, we validate the predictive capacity of the WGCNA by isolating the compounds responsible for the bioactivity-associated resonances and confirming their antifungal efficacy. Using growth inhibition assays, we verified that the isolated compounds, including three novel antifungal agents, exhibited significant bioactivity. Notably, one of these compounds contains a rare imidazolium heterocyclic motif, marking a new structural class in Piper. These findings substantiate the 1H NMR-based WGCNA as a reliable tool for identifying structural types associated with biological activity, streamlining the process of discovering bioactive natural products in complex extracts. 

Although infectious diseases play a critical role in population regulation, our knowledge of complex drivers of disease for insects is limited. We conducted a field study on Baltimore checkerspot caterpillars (Euphydryas phaeton), chemical specialists on plants containing iridoid glycosides (IGs), to investigate the roles of host plant, phytochemistry, ontogeny and spatial associations in determining viral prevalence. We analysed individuals for viral presence and loads, quantified leaf IG concentrations from their native and novel host plants, and sequestered IGs in caterpillars. We found proximate caterpillar groups had greater similarity in infection prevalence, with areas of high prevalence indicating viral hotspots. Underlying variation in host plant chemistry corresponded to differences in viral prevalence. Furthermore, we used structural equation modeling to examine causal drivers of infection prevalence and loads. Advanced ontogeny was associated with increased viral prevalence and loads, as well as decreased sequestration of IGs. Infection loads were lower on the novel host plant, but prevalence was slightly higher, partially explained by decreased sequestration of IGs. Altogether, our findings reveal that spatial proximity, ontogeny, host plant species and secondary phytochemistry can all contribute to structuring infection risk, and thus offer insight into causal drivers of disease prevalence in complex plant–insect systems. 

The hyperdiverse geometrid genusEoisHübner, estimated to encompass more than 1,000 species, is among the most species-rich genera in all of Lepidoptera. While the genus has attracted considerable attention from ecologists and evolutionary biologists in recent decades, limited progress has been made on its alpha taxonomy. This contribution focuses on the Olivacea clade, whose monophyly has been recognized previously through molecular analyses. We attempt to define the clade from a morphological perspective and recognize the following species based on morphology and genomic data:E. olivacea(Felder & Rogenhofer);E. pseudolivaceaDoan,sp. nov.;E. auruda(Dognin),stat. rev.;E. beebei(Fletcher, 1952),stat. rev.;E. boliviensis(Dognin),stat. rev.; andE. parumsimiiDoan,sp. nov.Descriptions and illustrations of the immature stages ofE. pseudolivaceareared fromPiper(Piperaceae) in Ecuador are provided. 

Abstract Pathogens play a key role in insect population dynamics, contributing to short‐term fluctuations in abundance as well as long‐term demographic trends. Two key factors that influence the effects of entomopathogens on herbivorous insect populations are modes of pathogen transmission and larval host plants. In this study, we examined tritrophic interactions between a sequestering specialist lepidopteran,Euphydryas phaeton, and a viral pathogen, Junonia coenia densovirus, on its native host plant,Chelone glabra, and a novel host plant,Plantago lanceolata, to explore whether host plant mediates viral transmission, survival, and viral loads. A two‐factor factorial experiment was conducted in the laboratory with natal larval clusters randomly assigned to either the native or novel host plant and crossed with either uninoculated controls or viral inoculation (20% of individuals in the cluster inoculated). Diapausing clusters were overwintered in the laboratory and checked weekly for mortality. At the end of diapause, all surviving individuals were reared to adulthood to estimate survivorship. All individuals were screened to quantify viral loads, and estimate horizontal transmission postmortem. To test for vertical transmission, adults were mated, and the progeny were screened for viral presence. Within virus‐treated groups, we found evidence for both horizontal and vertical transmission. Larval clusters reared on the native host plant had slightly higher horizontal transmission. Survival probability was lower in clusters feeding on the native host plant, with inoculated groups reared on the native host plant experiencing complete mortality. Viral loads did not differ by the host plant, although viral loads decreased with increased sequestration of secondary compounds on both host plants. Our results indicate that the use of a novel host plant may confer fitness benefits in terms of survival and reduced viral transmission when larvae feeding on it are infected with this pathogen, supporting hypotheses of potential evolutionary advantages of a host range expansion in the context of tritrophic interactions. 

Abstract Pollen identification is necessary for several subfields of geology, ecology, and evolutionary biology. However, the existing methods for pollen identification are laborious, time-consuming, and require highly skilled scientists. Therefore, there is a pressing need for an automated and accurate system for pollen identification, which can be beneficial for both basic research and applied issues such as identifying airborne allergens. In this study, we propose a deep learning (DL) approach to classify pollen grains in the Great Basin Desert, Nevada, USA. Our dataset consisted of 10,000 images of 40 pollen species. To mitigate the limitations imposed by the small volume of our training dataset, we conducted an in-depth comparative analysis of numerous pre-trained Convolutional Neural Network (CNN) architectures utilizing transfer learning methodologies. Simultaneously, we developed and incorporated an innovative CNN model, serving to augment our exploration and optimization of data modeling strategies. We applied different architectures of well-known pre-trained deep CNN models, including AlexNet, VGG-16, MobileNet-V2, ResNet (18, 34, and 50, 101), ResNeSt (50, 101), SE-ResNeXt, and Vision Transformer (ViT), to uncover the most promising modeling approach for the classification of pollen grains in the Great Basin. To evaluate the performance of the pre-trained deep CNN models, we measured accuracy, precision, F1-Score, and recall. Our results showed that the ResNeSt-110 model achieved the best performance, with an accuracy of 97.24%, precision of 97.89%, F1-Score of 96.86%, and recall of 97.13%. Our results also revealed that transfer learning models can deliver better and faster image classification results compared to traditional CNN models built from scratch. The proposed method can potentially benefit various fields that rely on efficient pollen identification. This study demonstrates that DL approaches can improve the accuracy and efficiency of pollen identification, and it provides a foundation for further research in the field. 

A new species of the rarely collected neotropical microgastrine braconid wasp genusLarissimusNixon, represented previously by only a single described species,L. cassanderNixon, was recovered by the Caterpillars and Parasitoids of the Eastern Andes in Ecuador inventory project.Larissimus nigricanssp. nov.was reared from an unidentified species of arctiine Erebidae feeding on the common bamboo speciesChusquea scandensKunth at the Yanayacu Biological Station near Cosanga, Napo Province, Ecuador. The new species is described and diagnosed fromL. cassanderusing both morphological and DNA barcode data. 

Declines in biodiversity generated by anthropogenic stressors at both species and population levels can alter emergent processes instrumental to ecosystem function and resilience. As such, understanding the role of biodiversity in ecosystem function and its response to climate perturbation is increasingly important, especially in tropical systems where responses to changes in biodiversity are less predictable and more challenging to assess experimentally. Using large-scale transplant experiments conducted at five neotropical sites, we documented the impacts of changes in intraspecific and interspecific plant richness in the genusPiperon insect herbivory, insect richness, and ecosystem resilience to perturbations in water availability. We found that reductions of both intraspecific and interspecificPiperdiversity had measurable and site-specific effects on herbivory, herbivorous insect richness, and plant mortality. The responses of these ecosystem-relevant processes to reduced intraspecificPiperrichness were often similar in magnitude to the effects of reduced interspecific richness. Increased water availability reduced herbivory by 4.2% overall, and the response of herbivorous insect richness and herbivory to water availability were altered by both intra- and interspecific richness in a site-dependent manner. Our results underscore the role of intraspecific and interspecific richness as foundations of ecosystem function and the importance of community and location-specific contingencies in controlling function in complex tropical systems.