Science Enabled by Specimen Data

Minghetti, E., P. M. Dellapé, M. Maestro, and S. I. Montemayor. 2024. Evaluating the climatic suitability of Engytatus passionarius Minghetti et al. (Heteroptera, Miridae) as a biological control agent of the invasive stinking passion flower Passiflora foetida L. in Australia through ecological niche models. Biological Control 191: 105461. https://doi.org/10.1016/j.biocontrol.2024.105461

Passiflora foetida is a climbing vine, native to the Neotropical Region that is causing major economic and ecological damage in Australia, where it is rapidly spreading. Traditional control options, such as cutting, manual uprooting, and herbicide applications are only effective for local management. Currently, the plant bug Engytatus passionarius is the most promising biological control agent. Specificity tests performed in its native range in Argentina suggest it is highly specific to the plant, and it has not been observed in the field associated with other plants. As climate determines the establishment of insects, knowing if the environmental conditions suit their requirements is key to introducing a species in a region. Also, an overlap between the climatic niches of species is an indicator of similar requirements. To explore the possibilities of a successful establishment of E. passionarius in Australia, ecological niche models (ENM) were built for the plant bug and for the vine and their overlap was measured. The ENM projected to Australia recognized suitable environmental conditions for the establishment of E. passionarius in several regions where P. foetida is present, both for current and future scenarios. Moreover, the niche of the plant bug is almost completely overlapped with that of the vine. All the aforementioned evidence seems to indicate that E. passionarius has a good chance to become an effective biological control agent of P. foetida.

Zhang, H., W. Guo, and W. Wang. 2023. The dimensionality reductions of environmental variables have a significant effect on the performance of species distribution models. Ecology and Evolution 13. https://doi.org/10.1002/ece3.10747

How to effectively obtain species‐related low‐dimensional data from massive environmental variables has become an urgent problem for species distribution models (SDMs). In this study, we will explore whether dimensionality reduction on environmental variables can improve the predictive performance of SDMs. We first used two linear (i.e., principal component analysis (PCA) and independent components analysis) and two nonlinear (i.e., kernel principal component analysis (KPCA) and uniform manifold approximation and projection) dimensionality reduction techniques (DRTs) to reduce the dimensionality of high‐dimensional environmental data. Then, we established five SDMs based on the environmental variables of dimensionality reduction for 23 real plant species and nine virtual species, and compared the predictive performance of those with the SDMs based on the selected environmental variables through Pearson's correlation coefficient (PCC). In addition, we studied the effects of DRTs, model complexity, and sample size on the predictive performance of SDMs. The predictive performance of SDMs under DRTs other than KPCA is better than using PCC. And the predictive performance of SDMs using linear DRTs is better than using nonlinear DRTs. In addition, using DRTs to deal with environmental variables has no less impact on the predictive performance of SDMs than model complexity and sample size. When the model complexity is at the complex level, PCA can improve the predictive performance of SDMs the most by 2.55% compared with PCC. At the middle level of sample size, the PCA improved the predictive performance of SDMs by 2.68% compared with the PCC. Our study demonstrates that DRTs have a significant effect on the predictive performance of SDMs. Specifically, linear DRTs, especially PCA, are more effective at improving model predictive performance under relatively complex model complexity or large sample sizes.

ter Huurne, M. B., L. J. Potgieter, C. Botella, and D. M. Richardson. 2023. Melaleuca (Myrtaceae): Biogeography of an important genus of trees and shrubs in a changing world. South African Journal of Botany 162: 230–244. https://doi.org/10.1016/j.sajb.2023.08.052

The number of naturalised and invasive woody plant species has increased rapidly in recent decades. Despite the increasing interest in tree and shrub invasions, little is known about the invasion ecology of most species. This paper explores the global movement of species in the genus Melaleuca (Myrtaceae; here including the genus Callistemon). We assess the global introduction history, distribution and biogeographic status of the genus. Various global species occurrence databases, citizen science (iNaturalist), and the literature were used.Seventy-two species [out of 386 Melaleuca species; 19%] have been introduced to at least 125 regions outside their native range. The main regions of global Melaleuca introductions are Southeast Asia, the southern parts of North America, south-eastern South America, southern Africa and Europe. The earliest record of a Melaleuca species outside of the native range of the genus is 1789. First records of Melaleuca species outside their native range were most commonly recorded in the 1960s, with records from all over the world. The main reasons for Melaleuca introductions were for use in the tea tree (pharmaceutical value) and ornamental horticulture industries. Melaleuca introductions, naturalizations and invasions are recent compared to many other woody plant taxa. Experiences in Florida and South Africa highlight the potential of Melaleuca species to spread rapidly and have significant ecological impacts. It is likely that the accumulating invasion debt will result in further naturalization and invasion of Melaleuca species in the future.

Kudoh, A., J. P. Megonigal, J. A. Langley, G. L. Noyce, T. Sakai, and D. F. Whigham. 2023. Reproductive Responses to Increased Shoot Density and Global Change Drivers in a Widespread Clonal Wetland Species, Schoenoplectus americanus. Estuaries and Coasts. https://doi.org/10.1007/s12237-023-01249-z

The expansion of many wetland species is a function of both clonal propagation and sexual reproduction. The production of ramets through clonal propagation enables plants to move and occupy space near parent ramets, while seeds produced by sexual reproduction enable species to disperse and colonize open or disturbed sites both near and far from parents. The balance between clonal propagation and sexual reproduction is known to vary with plant density but few studies have focused on reproductive allocation with density changes in response to global climate change. Schoenoplectus americanus is a widespread clonal wetland species in North America and a dominant species in Chesapeake Bay brackish tidal wetlands. Long-term experiments on responses of S . americanus to global change provided the opportunity to compare the two modes of propagation under different treatments. Seed production increased with increasing shoot density, supporting the hypothesis that factors causing increased clonal reproduction (e.g., higher shoot density) stimulate sexual reproduction and dispersal of genets. The increase in allocation to sexual reproduction was mainly the result of an increase in the number of ramets that flowered and not an increase in the number of seeds per reproductive shoot, or the ratio between the number of flowers produced per inflorescence and the number of flowers that developed into seeds. Seed production increased in response to increasing temperatures and decreased or did not change in response to increased CO 2 or nitrogen. Results from this comparative study demonstrate that plant responses to global change treatments affect resource allocation and can alter the ability of species to produce seeds.

Rodríguez-Merino, A. 2023. Identifying and Managing Areas under Threat in the Iberian Peninsula: An Invasion Risk Atlas for Non-Native Aquatic Plant Species as a Potential Tool. Plants 12: 3069. https://doi.org/10.3390/plants12173069

Predicting the likelihood that non-native species will be introduced into new areas remains one of conservation’s greatest challenges and, consequently, it is necessary to adopt adequate management measures to mitigate the effects of future biological invasions. At present, not much information is available on the areas in which non-native aquatic plant species could establish themselves in the Iberian Peninsula. Species distribution models were used to predict the potential invasion risk of (1) non-native aquatic plant species already established in the peninsula (32 species) and (2) those with the potential to invade the peninsula (40 species). The results revealed that the Iberian Peninsula contains a number of areas capable of hosting non-native aquatic plant species. Areas under anthropogenic pressure are at the greatest risk of invasion, and the variable most related to invasion risk is temperature. The results of this work were used to create the Invasion Risk Atlas for Alien Aquatic Plants in the Iberian Peninsula, a novel online resource that provides information about the potential distribution of non-native aquatic plant species. The atlas and this article are intended to serve as reference tools for the development of public policies, management regimes, and control strategies aimed at the prevention, mitigation, and eradication of non-native aquatic plant species.

Pang, S. E. H., J. W. F. Slik, D. Zurell, and E. L. Webb. 2023. The clustering of spatially associated species unravels patterns in tropical tree species distributions. Ecosphere 14. https://doi.org/10.1002/ecs2.4589

Complex distribution data can be summarized by grouping species with similar or overlapping distributions to unravel spatial patterns and separate trends (e.g., of habitat loss) among spatially unique groups. However, such classifications are often heuristic, lacking the transparency, objectivity, and data‐driven rigor of quantitative methods, which limits their interpretability and utility. Here, we develop and illustrate the clustering of spatially associated species, a methodological framework aimed at statistically classifying species using explicit measures of interspecific spatial association. We investigate several association indices and clustering algorithms and show how these methodological choices drive substantial variations in clustering outcomes and performance. To facilitate robust decision‐making, we provide guidance on choosing methods appropriate to one's study objective(s). As a case study, we apply our framework to modeled tree distributions in Borneo and subsequently evaluate the impact of land‐cover change on separate species groupings. Based on the modeled distribution of 390 tree species prior to anthropogenic land‐cover changes, we identified 11 distinct clusters that unraveled ecologically meaningful patterns in Bornean tree distributions. These clusters then enabled us to quantify trends of habitat loss tied to each of those specific clusters, allowing us to discern particularly vulnerable species clusters and their distributions. This study demonstrates the advantages of adopting quantitatively derived clusters of spatially associated species and elucidates the potential of resultant clusters as a spatially explicit framework for investigating distribution‐related questions in ecology, biogeography, and conservation. By adopting our methodological framework and publicly available codes, practitioners can leverage the ever‐growing abundance of distribution data to better understand complex spatial patterns among species distributions and the disparate effects of global changes on biodiversity.

Richard-Bollans, A., C. Aitken, A. Antonelli, C. Bitencourt, D. Goyder, E. Lucas, I. Ondo, et al. 2023. Machine learning enhances prediction of plants as potential sources of antimalarials. Frontiers in Plant Science 14. https://doi.org/10.3389/fpls.2023.1173328

Plants are a rich source of bioactive compounds and a number of plant-derived antiplasmodial compounds have been developed into pharmaceutical drugs for the prevention and treatment of malaria, a major public health challenge. However, identifying plants with antiplasmodial potential can be time-consuming and costly. One approach for selecting plants to investigate is based on ethnobotanical knowledge which, though having provided some major successes, is restricted to a relatively small group of plant species. Machine learning, incorporating ethnobotanical and plant trait data, provides a promising approach to improve the identification of antiplasmodial plants and accelerate the search for new plant-derived antiplasmodial compounds. In this paper we present a novel dataset on antiplasmodial activity for three flowering plant families – Apocynaceae, Loganiaceae and Rubiaceae (together comprising c. 21,100 species) – and demonstrate the ability of machine learning algorithms to predict the antiplasmodial potential of plant species. We evaluate the predictive capability of a variety of algorithms – Support Vector Machines, Logistic Regression, Gradient Boosted Trees and Bayesian Neural Networks – and compare these to two ethnobotanical selection approaches – based on usage as an antimalarial and general usage as a medicine. We evaluate the approaches using the given data and when the given samples are reweighted to correct for sampling biases. In both evaluation settings each of the machine learning models have a higher precision than the ethnobotanical approaches. In the bias-corrected scenario, the Support Vector classifier performs best – attaining a mean precision of 0.67 compared to the best performing ethnobotanical approach with a mean precision of 0.46. We also use the bias correction method and the Support Vector classifier to estimate the potential of plants to provide novel antiplasmodial compounds. We estimate that 7677 species in Apocynaceae, Loganiaceae and Rubiaceae warrant further investigation and that at least 1300 active antiplasmodial species are highly unlikely to be investigated by conventional approaches. While traditional and Indigenous knowledge remains vital to our understanding of people-plant relationships and an invaluable source of information, these results indicate a vast and relatively untapped source in the search for new plant-derived antiplasmodial compounds.

Robin-Champigneul, F., J. Gravendyck, H. Huang, A. Woutersen, D. Pocknall, N. Meijer, G. Dupont-Nivet, et al. 2023. Northward expansion of the southern-temperate podocarp forest during the Early Eocene Climatic Optimum: Palynological evidence from the NE Tibetan Plateau (China). Review of Palaeobotany and Palynology: 104914. https://doi.org/10.1016/j.revpalbo.2023.104914

The debated vegetation response to climate change can be investigated through palynological fossil records from past extreme climate conditions. In this context, the early Eocene (53.3 to 41.2 million years ago (Ma)) is often referred to as a model for a greenhouse Earth. In the Xining Basin, situated on the North-eastern Tibetan Plateau (NETP), this time interval is represented by an extensive and well-dated sedimentary sequence of evaporites and red mudstones. Here we focus on the palynological record of the Early Eocene Climatic Optimum (EECO; 53.3 to 49.1 Ma) and study the fossil gymnosperm pollen composition in these sediments. In addition, we also investigate the nearest living relatives (NLR) or botanical affinity of these genera and the paleobiogeographic implications of their occurrence in the Eocene of the NETP. To reach our objective, we complemented transmitted light microscopy with laser scanning- and electron microscopy techniques, to produce high-resolution images, and illustrate the morphological variation within fossil and extant gymnosperm pollen. Furthermore, a morphometric analysis was carried out to investigate the infra- and intrageneric variation of these and related taxa. To place the data in context we produced paleobiogeographic maps for Phyllocladidites and for other Podocarpaceae, based on data from a global fossil pollen data base, and compare these with modern records from GBIF. We also assessed the climatic envelope of the NLR. Our analyses confirm the presence of Phyllocladidites (NLR Phyllocladus, Podocarpaceae) and Podocarpidites (NLR Podocarpus, Podocarpaceae) in the EECO deposits in the Xining Basin. In addition, a comparative study based on literature suggests that Parcisporites is likely a younger synonym of Phyllocladidites. Our findings further suggest that the Phyllocladidites specimens are derived from a lineage that was much more diverse than previously thought, and which had a much larger biogeographical distribution during the EECO than at present. Based on the climatic envelope of the NLR, we suggest that the paleoclimatic conditions in the Xining Basin were warmer and more humid during the EECO. We conclude that phylloclade-type conifers typical of the southern-temperate podocarp forests, had a northward geographical expansion during the EECO, followed by extirpation.

Percy, D., and Q. Cronk. 2023. Report of two distinct ribotypes in ITS sequences of Phalaris arundinacea (Poaceae) in western Canada and Alaska. Biodiversity Data Journal 11. https://doi.org/10.3897/bdj.11.e101257

AbstractBackgroundPhalarisarundinacea L. (reed canary grass) is a widely occurring grass throughout the Northern Hemisphere. In North America, it is thought to consist of introduced agricultural forms from Europe as well as native populations.New informationDuring a survey of Phalarisarundinacea in western Canada, we discovered two distinct ribotypes in the sequences of the internal transcribed spacer (ITS) of the nuclear ribosomal DNA: one full length (ITS-long) and one with a seven base pair deletion (ITS-short). In addition, ITS-long plants have fixed heterozygosity indicating possible polyploidy. Phylogenetic analysis reveals that ITS-short is a unique ribotype that characterises an intraspecific clade. We designed an efficient PCR-based assay that allows sizing of a 238/245 base pair fragment in a capillary sequencer. This approach provides a novel marker that could be useful in future surveys of Phalarisarundinacea.

Clemente, K. J. E., and M. S. Thomsen. 2023. High temperature frequently increases facilitation between aquatic foundation species: a global meta‐analysis of interaction experiments between angiosperms, seaweeds, and bivalves. Journal of Ecology. https://doi.org/10.1111/1365-2745.14101

Many studies have quantified ecological impacts of individual foundation species (FS). However, emerging data suggest that FS often co‐occur, potentially inhibiting or facilitating one another, thereby causing indirect, cascading effects on surrounding communities. Furthermore, global warming is accelerating, but little is known about how interactions between co‐occurring FS vary with temperature.Shallow aquatic sedimentary systems are often dominated by three types of FS: slower‐growing clonal angiosperms, faster‐growing solitary seaweeds, and shell‐forming filter‐ and deposit‐feeding bivalves. Here, we tested the impacts of one FS on another by analyzing manipulative interaction experiments from 148 papers with a global meta‐analysis.We calculated 1,942 (non‐independent) Hedges’ g effect sizes, from 11,652 extracted values over performance responses, such as abundances, growths or survival of FS, and their associated standard deviations and replication levels. Standard aggregation procedures generated 511 independent Hedges’ g that was classified into six types of reciprocal impacts between FS.We found that (i) seaweeds had consistent negative impacts on angiosperms across performance responses, organismal sizes, experimental approaches, and ecosystem types; (ii) angiosperms and bivalves generally had positive impacts on each other (e.g., positive effects of angiosperms on bivalves were consistent across organismal sizes and experimental approaches, but angiosperm effect on bivalve growth and bivalve effect on angiosperm abundance were not significant); (iii) bivalves positively affected seaweeds (particularly on growth responses); (iv) there were generally no net effects of seaweeds on bivalves (except for positive effect on growth) or angiosperms on seaweeds (except for positive effect on ‘other processes’); and (v) bivalve interactions with other FS were typically more positive at higher temperatures, but angiosperm‐seaweed interactions were not moderated by temperature.Synthesis: Despite variations in experimental and spatiotemporal conditions, the stronger positive interactions at higher temperatures suggest that facilitation, particularly involving bivalves, may become more important in a future warmer world. Importantly, addressing research gaps, such as the scarcity of FS interaction experiments from tropical and freshwater systems and for less studied species, as well as testing for density‐dependent effects, could better inform aquatic ecosystem conservation and restoration efforts and broaden our knowledge of FS interactions in the Anthropocene.