Charles d'Alleizette

The cabbage seedpod weevil (CSW), Ceutorhynchus obstrictus (Marsham) (Coleoptera: Curculionidae) is an important pest of brassicaceous crops, including canola ( Brassica napus Linnaeus). CSW consumes seeds of its host from inside the developing pods. It was introduced to North America from Europe and now occurs throughout the United States of America and Canada. Climate is one of the most important factors that determines species distribution and abundance. CLIMEX is a bioclimate model development application. Based on climate inputs, bioclimatic simulation models are tools that predict the potential geographic distribution and abundance of insects and plants. This study updated a previous bioclimatic model for CSW and presents a new model for canola. Validated models were used to conduct bioclimatic analysis of both species, the results of which provide a better understanding of how climate affects spatial distribution and abundance of CSW and the distribution and yield of canola. Application of incremental temperature and moisture scenarios were used to predict the spatial relationship of CSW risk and canola yield. We anticipate that the canola model will be applied to future bioclimatic studies of pests and beneficial insects of canola. Both the CSW and canola model can be used in climate change studies using datasets for predicted future climates.

Without appropriate and ongoing management interventions, weeds will continue to economically and environmentally disadvantage agricultural and natural ecosystems. For these management strategies to have long‐term sustained success, they need to carefully consider the biological aspects of the targeted weed. These strategies will also need to consider potential adaptations evolved by the targeted weed in response to a range of selection pressures imposed by anthropogenetic factors, climate change, changing environmental conditions, and inappropriate or unsuccessful management regimes. One group of weeds that has been observed to readily adapt to a wide range of conditions and has shown considerable challenges in their management is invasive grasses. Adding to these challenges is that several invasive grasses have also developed resistance to a range of herbicide modes of action, which, to date, has been one of the most commonly used methods of control. To address these challenges, this review explores the biology and ecology of the globally invasive annuals Echinochloa crus‐galli (Barnyard grass) and Panicum capillare (Witchgrass), and the perennial Sorghum halepense (Johnson grass) to identify (i) the most suitable management options for their control and (ii) potential research gaps that may assist in the future management direction of these species. Based on the findings of this review, it is clear that an integrated management approach that targets different aspects of the plant's biology, in combination with early detection and treatment and ongoing surveillance, is necessary for the long‐term control of these species. Although a combination of methods appears promising, further investigation still is required to evaluate their efficiency and long‐term success in a changing environment, all of which are further discussed within this review.

Saussurea is one of the largest and most rapidly evolving genera within the Asteraceae, comprising approximately 520 species from the Northern Hemisphere. A comprehensive infrageneric classification, supported by robust phylogenetic trees and corroborated by morphological and other data, has not yet been published. For the first time, we recovered a well-resolved nuclear phylogeny of Saussurea consisting of four main clades, which was also supported by morphological data. Our analyses show that ancient hybridization is the most likely source of deep cytoplasmic-nuclear conflict in Saussurea, and a phylogeny based on nuclear data is more suitable than one based on chloroplast data for exploring the infrageneric classification of Saussurea. Based on the nuclear phylogeny obtained and morphological characters, we proposed a revised infrageneric taxonomy of Saussurea, which includes four subgenera and 13 sections. Specifically, 1) S. sect. Cincta, S. sect. Gymnocline, S. sect. Lagurostemon, and S. sect. Strictae were moved from S. subg. Saussurea to S. subg. Amphilaena, 2) S. sect. Pseudoeriocoryne was moved from S. subg. Eriocoryne to S. subg. Amphilaena, and 3) S. sect. Laguranthera was moved from S. subg. Saussurea to S. subg. Theodorea.

Parasitic weeds in the genera Orobanche, Phelipanche (broomrapes) and Striga (witchweeds) have a devastating impact on food security across much of Africa, Asia and the Mediterranean Basin. Yet, how climatic factors might affect the range expansion of these weeds in the context of global environmental change remains unexplored. We examined satellite‐based environmental variables such as surface temperature, root zone soil moisture, and elevation, in relation to parasitic weed distribution and environmental conditions over time, in combination with observational data from the Global Biodiversity Information Facility (GBIF). Our analysis reveals contrasting environmental and altitude preferences in the genera Striga and Orobanche. Asiatic witchweed (Striga asiatica), which infests corn, rice, sorghum, and sugar cane crops, appears to be expanding its range in high elevation habitats. It also shows a significant association with heat‐moisture coupling events, the frequency of which is rising in such environments. These results point to geographical shifts in distribution and abundance in parasitic weeds due to climate change.

Dense branching and spines are common features of plant species in ecosystems with high mammalian herbivory pressure. While dense branching and spines can inhibit herbivory independently, when combined, they form a powerful defensive cage architecture. However, how cage architecture evolved under mammalian pressure has remained unexplored. Here we show how dense branching and spines emerged during the age of mammalian radiation in the Combretaceae family and diversified in herbivore-driven ecosystems in the tropics. Phylogenetic comparative methods revealed that modern plant architectural strategies defending against large mammals evolved via a stepwise process. First, dense branching emerged under intermediate herbivory pressure, followed by the acquisition of spines that supported higher speciation rates under high herbivory pressure. Our study highlights the adaptive value of dense branching as part of a herbivore defence strategy and identifies large mammal herbivory as a major selective force shaping the whole plant architecture of woody plants. This study explores the evolution of two traits, branching density and spine presence, in the globally distributed plant family Combretaceae. These traits were found to have appeared in a two-step process in response to mammalian herbivory pressure, revealing the importance of large mammals in the evolution of plant architecture diversity.

Camelina [Camelina sativa (L.) Crantz] is a Brassicaceae oilseed that is gaining interest worldwide as low‐maintenance crop for diverse biobased applications. One of the most important factors determining its productivity is climate. We conducted a bioclimate analysis in order to analyze the relationship between climatic factors and the productivity of spring‐type camelina seeded in the spring, and to identify regions of the world with potential for camelina in this scenario. Using the modelling tool CLIMEX, a bioclimatic model was developed for spring‐seeded spring‐type camelina to match distribution, reported seed yields and phenology records in North America. Distribution, yield, and phenology data from outside of North America were used as independent datasets for model validation and demonstrated that model projections agreed with published distribution records, reported spring‐seeded camelina yields, and closely predicted crop phenology in Europe, South America, and Asia. Sensitivity analysis, used to quantify the response of camelina to changes in precipitation and temperature, indicated that crop performance was more sensitive to moisture than temperature index parameters, suggesting that the yield potential of spring‐seeded camelina may be more strongly impacted by water‐limited conditions than by high temperatures. Incremental climate scenarios also revealed that spring‐seeded camelina production will exhibit yield shifts at the continental scale as temperature and precipitation deviate from current conditions. Yield data were compared with indices of climatic suitability to provide estimates of potential worldwide camelina productivity. This information was used to identify new areas where spring‐seeded camelina could be grown and areas that may permit expanded production, including eastern Europe, China, eastern Russia, Australia and New Zealand. Our model is the first to have taken a systematic approach to determine suitable regions for potential worldwide production of spring‐seeded camelina.

Osyris lanceolata Hochst. & Steud. ex A. DC. is a multipurpose plant with high socioeconomic and cultural values. It is endangered in the biogeographical region of eastern Africa, but of less concern in other regions where it occurs. The few natural populations remaining in the endangered sites continue to encounter many threats, and this has raised concerns about its long-term sustainability. Yet, existing knowledge about the ecology and distribution of the plant is scarce to inform strategies for the conservation and sustainable management of the species. In this study, we conducted a scoping review of the available literature on current knowledge about the plant. We recapitulated existing knowledge about the abiotic and biotic factors influencing the contemporary distribution of the plant, the anthropogenic threats, and existing conservation efforts. Based on the limited studies we reviewed, we identified that the plant prefers specific habitats (hilly areas and rocky outcrops), frequently parasitizes Fabaceae but can parasitize plants from a wide range of countries, have inadequate ex-situ propagation protocols which present issues for the survival of the species. Overharvesting from the wild driven by demand from regional and global markets poses further threats to the existing natural populations, especially in eastern Africa. A combination of ecological, social, and trade-related conservation measures can be envisioned to help improve the plant’s persistence. These include, but are not limited to, a better understanding of the species ecology to inform conservation planning, monitoring of trade flow and improve transnational environmental laws and cooperation among countries to prevent species smuggling.

Aim The aim of this study was to further advance our understanding of the species-rich, and ecologically important angiosperm family Combretaceae to provide new insights into their evolutionary history. We assessed phylogenetic relationships in the family using target capture data and produced a dated phylogenetic tree to assess fruit dispersal modes and patterns of distribution. Location Tropical and subtropical regions. Time Period Cretaceous to present. Major Taxa Studied Family Combretaceae is a member of the rosid clade and comprises 10 genera and more than 500 species, predominantly assigned to genera Combretum and Terminalia, and occurring on all continents and in a wide range of ecosystems. Methods We use a target capture approach and the Angiosperms353 universal probes to reconstruct a robust dated phylogenetic tree for the family. This phylogenetic framework, combined with seed dispersal traits, biome data and biogeographic ranges, allows the reconstruction of the biogeographical history of the group. Results Ancestral range reconstructions suggest a Gondwanan origin (Africa/South America), with several intercontinental dispersals within the family and few transitions between biomes. Relative abundance of fruit dispersal types differed by both continent and biome. However, intercontinental colonizations were only significantly enhanced by water dispersal (drift fruit), and there was no evidence that seed dispersal modes influenced biome shifts. Main Conclusions Our analysis reveals a paradox as drift fruit greatly enhanced dispersal distances at intercontinental scale but did not affect the strong biome conservatism observed.

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.

Conservation efforts in global biodiversity hotspots often face a common predicament: an urgent need for conservation action hampered by a significant lack of knowledge about that biodiversity. In recent decades, the computerisation of primary biodiversity data worldwide has provided the scientific community with raw material to increase our understanding of the shared natural heritage. These datasets, however, suffer from a lot of geographical and taxonomic inaccuracies. Automated tools developed to enhance their reliability have shown that detailed expert examination remains the best way to achieve robust and exhaustive datasets. In New Caledonia, one of the most important biodiversity hotspots worldwide, the plant diversity inventory is still underway, and most taxa awaiting formal description are narrow endemics, hence by definition hard to discern in the datasets. In the meantime, anthropogenic pressures, such as nickel-ore mining, are threatening the unique ultramafic ecosystems at an increasing rate. The conservation challenge is therefore a race against time, as the rarest species must be identified and protected before they vanish. In this study, based on all available datasets and resources, we applied a workflow capable of highlighting the lesser known taxa. The main challenges addressed were to aggregate all data available worldwide, and tackle the geographical and taxonomic biases, avoiding the data loss resulting from automated filtering. Every doubtful specimen went through a careful taxonomic analysis by a local and international taxonomist panel. Geolocation of the whole dataset was achieved through dataset cross-checking, local botanists’ field knowledge, and historical material examination. Field studies were also conducted to clarify the most unresolved taxa. With the help of this method and by analysing over 85,000 data, we were able to double the number of known narrow endemic taxa, elucidate 68 putative new species, and update our knowledge of the rarest species’ distributions so as to promote conservation measures.