Eily Edith Agnes Archibald

AbstractInvasive alien plants cause severe global problems; therefore, determining the factors that lead to the success or failure of invasion is a critical question in the field of invasion ecology. In this study, we aimed to determine the factors underlying differences in the distribution range of alien plants in Japan by investigating why Loliummultiflorum thrives in a wide range of habitats while L.rigidum is mainly distributed on sandy beaches. We initially evaluated environmental niche suitability through species distribution modelling and subsequently examined whether species traits influence the differences in range expansion between the two species. We used MaxEnt modelling to identify potential environmental niches for both species. The analysis revealed that L.rigidum was considerably less suited to the Japanese climate compared to L.multiflorum, with high summer precipitation in Japan identified as one of the climatic factors limiting the distribution of L.rigidum. Given that these winter annual plants remain dormant as seeds during summer, in subsequent experiments, we buried seeds in paddy field soil and sandy beach sand during summer and evaluated their survival rate in autumn. The survival rate of L.rigidum seeds was significantly lower than that of L.multiflorum, particularly in paddy soil. Factors contributing to seed mortality may include the decay or early germination of L.rigidum seeds under Japan’s high rainfall conditions. This study emphasises the importance of considering local environmental factors alongside climate niche modelling in the risk assessment of invasive species. Moreover, the integration of species distribution modelling for large-scale evaluations and manipulation experiments for fine-scale assessments proved effective in identifying climatic conditions and species traits influencing the success or failure of alien species invasion.

Understanding belowground plant-microbial interactions is fundamental to predicting how plant species respond to climate change, particularly in global drylands. However, these interactions are poorly understood, especially for keystone grass species like the pan-palaeotropical Themeda triandra. Here, we used 16S rRNA amplicon sequencing to characterise microbiota in rhizospheres and bulk soils associated with T. triandra. We applied this method to eight native sites across a 3-fold aridity gradient (aridity index range = 0.318 to 0.903 = 87 % global aridity distribution) in southern Australia. By examining the relative contributions of climatic, edaphic, ecological, and host specific phenotypic traits, we identified the ecological drivers of core T. triandra-associated microbiota. We show that aridity had the strongest effect on shaping these core microbiotas, and report that a greater proportion of bacterial taxa that were from the core rhizosphere microbiomes were also differentially abundant in more arid T. triandra regions. These results suggest that T. triandra naturally growing in soils under more arid conditions have greater reliance on rhizosphere core taxa than plants growing under wetter conditions. Our study underscores the likely importance of targeted recruitment of bacteria into the rhizosphere by grassland keystone species, such as T. triandra, when growing in arid conditions. This bacterial soil recruitment is expected to become even more important under climate change.

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.

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.

Paleoclimate reconstructions can provide a window into the environmental conditions in Earth history when atmospheric carbon dioxide concentrations were higher than today. In the eastern USA, paleoclimate reconstructions are sparse, because terrestrial sedimentary deposits are rare. Despite this, the eastern USA has the largest population and population density in North America, and understanding the effects of current and future climate change is of vital importance. Here, we provide terrestrial paleoclimate reconstructions of the eastern USA from Miocene fossil floras. Additionally, we compare proxy paleoclimate reconstructions from the warmest period in the Miocene, the Miocene Climatic Optimum (MCO), to those of an MCO Earth System Model. Reconstructed Miocene temperatures and precipitation north of 35°N are higher than modern. In contrast, south of 35°N, temperatures and precipitation are similar to today, suggesting a poleward amplification effect in eastern North America. Reconstructed Miocene rainfall seasonality was predominantly higher than modern, regardless of latitude, indicating greater variability in intra-annual moisture transport. Reconstructed climates are almost uniformly in the temperate seasonal forest biome, but heterogeneity of specific forest types is evident. Reconstructed Miocene terrestrial temperatures from the eastern USA are lower than modeled temperatures and coeval Atlantic sea surface temperatures. However, reconstructed rainfall is consistent with modeled rainfall. Our results show that during the Miocene, climate was most different from modern in the northeastern states, and may suggest a drastic reduction in the meridional temperature gradient along the North American east coast compared to today.

Crop landraces have unique local agroecological and societal functions and offer important genetic resources for plant breeding. Recognition of the value of landrace diversity and concern about its erosion on farms have led to sustained efforts to establish ex situ collections worldwide. The degree to which these efforts have succeeded in conserving landraces has not been comprehensively assessed. Here we modelled the potential distributions of eco-geographically distinguishable groups of landraces of 25 cereal, pulse and starchy root/tuber/fruit crops within their geographic regions of diversity. We then analysed the extent to which these landrace groups are represented in genebank collections, using geographic and ecological coverage metrics as a proxy for genetic diversity. We find that ex situ conservation of landrace groups is currently moderately comprehensive on average, with substantial variation among crops; a mean of 63% ± 12.6% of distributions is currently represented in genebanks. Breadfruit, bananas and plantains, lentils, common beans, chickpeas, barley and bread wheat landrace groups are among the most fully represented, whereas the largest conservation gaps persist for pearl millet, yams, finger millet, groundnut, potatoes and peas. Geographic regions prioritized for further collection of landrace groups for ex situ conservation include South Asia, the Mediterranean and West Asia, Mesoamerica, sub-Saharan Africa, the Andean mountains of South America and Central to East Asia. With further progress to fill these gaps, a high degree of representation of landrace group diversity in genebanks is feasible globally, thus fulfilling international targets for their ex situ conservation. By analysing the state of representation of traditional varieties of 25 major crops in ex situ repositories, this study demonstrates conservation progress made over more than a half-century and identifies the gaps remaining to be filled.

Background and Aims Petioles are important plant organs connecting stems with leaf blades and affecting light-harvesting ability of the leaf as well as transport of water, nutrients and biochemical signals. Despite the high diversity in petiole size, shape and anatomy, little information is availabl…

Aim: Tropical old-growth grasslands are increasingly acknowledged as biodiverse ecosystems, but they are understudied in many aspects. Geoxyle species are a key component in many of these ecosystems, their belowground storage organs and bud banks are functionally diverse and contribute to the grassl…

von Humboldt’s tree-line concept has dominated mountain ecology for almost two hundred years, and is considered a key indicator for monitoring change in biome boundaries and biodiversity shifts under climate change. Even though the concept of life zones and elevation gradients are a globally observe…

Aim: Due to the sessile nature of flowering plants, movements to new geographical areas occur mainly during seed dispersal. Frugivores tend to be efficient dispersers because animals move within the boundaries of their preferable niches, so seeds are more likely to be transported to environments tha…