Seasonal dynamics of Anopheles stephensi and its implications for mosquito detection and emergent malaria control in the Horn of Africa.

Invasion of the malaria vector Anopheles stephensi across the Horn of Africa threatens control efforts across the continent, particularly in urban settings where the vector is able to proliferate. Malaria transmission is primarily determined by the abundance of dominant vectors, which often varies seasonally with rainfall. However, it remains unclear how An. stephensi abundance changes throughout the year, despite this being a crucial input to surveillance and control activities. We collate longitudinal catch data from across its endemic range to better understand the vector's seasonal dynamics and explore the implications of this seasonality for malaria surveillance and control across the Horn of Africa. Our analyses reveal pronounced variation in seasonal dynamics, the timing and nature of which are poorly predicted by rainfall patterns. Instead, they are associated with temperature and patterns of land use; frequently differing between rural and urban settings. Our results show that timing entomological surveys to coincide with rainy periods is unlikely to improve the likelihood of detecting An. stephensi. Integrating these results into a malaria transmission model, we show that timing indoor residual spraying campaigns to coincide with peak rainfall offers little improvement in reducing disease burden compared to starting in a random month. Our results suggest that unlike other malaria vectors in Africa, rainfall may be a poor guide to predicting the timing of peaks in An. stephensi-driven malaria transmission. This highlights the urgent need for longitudinal entomological monitoring of the vector in its new environments given recent invasion and potential spread across the continent.

Plant diversity darkspots for global collection priorities.

More than 15% of all vascular plant species may remain scientifically undescribed, and many of the > 350 000 described species have no or few geographic records documenting their distribution. Identifying and understanding taxonomic and geographic knowledge shortfalls is key to prioritising future collection and conservation efforts. Using extensive data for 343 523 vascular plant species and time-to-event analyses, we conducted multiple tests related to plant taxonomic and geographic data shortfalls, and identified 33 global diversity darkspots (those 'botanical countries' predicted to contain most undescribed and not yet recorded species). We defined priority regions for future collection according to several socio-economic and environmental scenarios. Most plant diversity darkspots are found within global biodiversity hotspots, with the exception of New Guinea. We identify Colombia, Myanmar, New Guinea, Peru, Philippines and Turkey as global collection priorities under all environmental and socio-economic conditions considered. Our study provides a flexible framework to help accelerate the documentation of global plant diversity for the implementation of conservation actions. As digitisation of the world's herbaria progresses, collection and conservation priorities may soon be identifiable at finer scales.

Genome size is positively correlated with extinction risk in herbaceous angiosperms.

Angiosperms with large genomes experience nuclear-, cellular-, and organism-level constraints that may limit their phenotypic plasticity and ecological niche, which could increase their risk of extinction. Therefore, we test the hypotheses that large-genomed species are more likely to be threatened with extinction than those with small genomes, and that the effect of genome size varies across three selected covariates: life form, endemism, and climatic zone. We collated genome size and extinction risk information for a representative sample of angiosperms comprising 3250 species, which we analyzed alongside life form, endemism, and climatic zone variables using a phylogenetic framework. Genome size is positively correlated with extinction risk, a pattern driven by a signal in herbaceous but not woody species, regardless of climate and endemism. The influence of genome size is stronger in endemic herbaceous species, but is relatively homogenous across different climates. Beyond its indirect link via endemism and climate, genome size is associated with extinction risk directly and significantly. Genome size may serve as a proxy for difficult-to-measure parameters associated with resilience and vulnerability in herbaceous angiosperms. Therefore, it merits further exploration as a useful biological attribute for understanding intrinsic extinction risk and augmenting plant conservation efforts.

The global distribution of angiosperm genome size is shaped by climate.

Angiosperms, which inhabit diverse environments across all continents, exhibit significant variation in genome sizes, making them an excellent model system for examining hypotheses about the global distribution of genome size. These include the previously proposed large genome constraint, mutational hazard, polyploidy-mediated, and climate-mediated hypotheses. We compiled the largest genome size dataset to date, encompassing 16 017 (> 5% of known) angiosperm species, and analyzed genome size distribution using a comprehensive geographic distribution dataset for all angiosperms. We observed that angiosperms with large range sizes generally had small genomes, supporting the large genome constraint hypothesis. Climate was shown to exert a strong influence on genome size distribution along the global latitudinal gradient, while the frequency of polyploidy and the type of growth form had negligible effects. In contrast to the unimodal patterns along the global latitudinal gradient shown by plant size traits and polyploid proportions, the increase in angiosperm genome size from the equator to 40-50°N/S is probably mediated by different (mostly climatic) mechanisms than the decrease in genome sizes observed from 40 to 50°N northward. Our analysis suggests that the global distribution of genome sizes in angiosperms is mainly shaped by climatically mediated purifying selection, genetic drift, relaxed selection, and environmental filtering.

Matches and mismatches between the global distribution of major food crops and climate suitability.

Over the course of history, humans have moved crops from their regions of origin to new locations across the world. The social, cultural and economic drivers of these movements have generated differences not only between current distributions of crops and their climatic origins, but also between crop distributions and climate suitability for their production. Although these mismatches are particularly important to inform agricultural strategies on climate change adaptation, they have, to date, not been quantified consistently at the global level. Here, we show that the relationships between the distributions of 12 major food crops and climate suitability for their yields display strong variation globally. After investigating the role of biophysical, socio-economic and historical factors, we report that high-income world regions display a better match between crop distribution and climate suitability. In addition, although crops are farmed predominantly in the same climatic range as their wild progenitors, climate suitability is not necessarily higher there, a pattern that reflects the legacy of domestication history on current crop distribution. Our results reveal how far the global distribution of major crops diverges from their climatic optima and call for greater consideration of the multiple dimensions of the crop socio-ecological niche in climate change adaptive strategies.

A novel statistical framework for exploring the population dynamics and seasonality of mosquito populations.

Understanding the temporal dynamics of mosquito populations underlying vector-borne disease transmission is key to optimizing control strategies. Many questions remain surrounding the drivers of these dynamics and how they vary between species-questions rarely answerable from individual entomological studies (that typically focus on a single location or species). We develop a novel statistical framework enabling identification and classification of time series with similar temporal properties, and use this framework to systematically explore variation in population dynamics and seasonality in anopheline mosquito time series catch data spanning seven species, 40 years and 117 locations across mainland India. Our analyses reveal pronounced variation in dynamics across locations and between species in the extent of seasonality and timing of seasonal peaks. However, we show that these diverse dynamics can be clustered into four 'dynamical archetypes', each characterized by distinct temporal properties and associated with a largely unique set of environmental factors. Our results highlight that a range of environmental factors including rainfall, temperature, proximity to static water bodies and patterns of land use (particularly urbanicity) shape the dynamics and seasonality of mosquito populations, and provide a generically applicable framework to better identify and understand patterns of seasonal variation in vectors relevant to public health.

Pollen sterols are associated with phylogeny and environment but not with pollinator guilds.

Phytosterols are primary plant metabolites that have fundamental structural and regulatory functions. They are also essential nutrients for phytophagous insects, including pollinators, that cannot synthesize sterols. Despite the well-described composition and diversity in vegetative plant tissues, few studies have examined phytosterol diversity in pollen. We quantified 25 pollen phytosterols in 122 plant species (105 genera, 51 families) to determine their composition and diversity across plant taxa. We searched literature and databases for plant phylogeny, environmental conditions, and pollinator guilds of the species to examine the relationships with pollen sterols. 24-methylenecholesterol, sitosterol and isofucosterol were the most common and abundant pollen sterols. We found phylogenetic clustering of twelve individual sterols, total sterol content and sterol diversity, and of sterol groupings that reflect their underlying biosynthesis pathway (C-24 alkylation, ring B desaturation). Plants originating in tropical-like climates (higher mean annual temperature, lower temperature seasonality, higher precipitation in wettest quarter) were more likely to record higher pollen sterol content. However, pollen sterol composition and content showed no clear relationship with pollinator guilds. Our study is the first to show that pollen sterol diversity is phylogenetically clustered and that pollen sterol content may adapt to environmental conditions.

Machine learning enhances prediction of plants as potential sources of antimalarials.

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.

Scaling up neodomestication for climate-ready crops.

We can increase the stability of our food systems against environmental variability and climate change by following the footsteps of our ancestors and domesticating edible wild plants. Reinforced by recent advances in comparative genomics and gene editing technologies, neodomestication opens possibilities for a rapid generation of new crops. By starting the candidate selection pipeline with climatic parameters, we orient neodomestication efforts to increase food security against climate change. We highlight the fact that the edible species conservation and characterization will be key in this process. Utilization of genetic resources, entrusted to conservationists and researchers by local communities, has to be conducted with highest ethical standards and benefit-sharing in mind.

Interactions between breeding system and ploidy affect niche breadth in Solanum.

Understanding the factors driving ecological and evolutionary interactions of economically important plant species is important for agricultural sustainability. The geography of crop wild relatives, including wild potatoes (Solanum section Petota), have received attention; however, such information has not been analysed in combination with phylogenetic histories, genomic composition and reproductive systems to identify potential species for use in breeding for abiotic stress tolerance. We used a combination of ordinary least-squares (OLS) and phylogenetic generalized least-squares (PGLM) analyses to identify the discrete climate classes that make up the climate niche that wild potato species inhabit in the context of breeding system and ploidy. Self-incompatible diploid or self-compatible polyploid species significantly increase the number of discrete climate classes within a climate niche inhabited. This result was sustained when correcting for phylogenetic non-independence in the linear model. Our results support the idea that specific breeding system and ploidy combinations increase niche breadth through the decoupling of geographical range and niche diversity, and therefore, these species may be of particular interest for crop adaptation to a changing climate.

Global plant diversity as a reservoir of micronutrients for humanity.

With more than two billion people suffering from malnutrition and diets homogenizing globally, it is vital to identify and conserve nutrient-rich species that may contribute to improving food security and diversifying diets. Of the approximately 390,000 vascular plant species known to science, thousands have been reported to be edible, yet their nutritional content remains poorly characterized. Here we use phylogenetic information to identify plants with the greatest potential to support strategies alleviating B-vitamin deficiencies. We predict the B-vitamin profiles of >6,400 edible plants lacking nutritional data and identify 1,044 species as promising key sources of B vitamins. Several of these source species should become conservation priorities, as 63 (6%) are threatened in the wild and 272 (26%) are absent from seed banks. Moreover, many of these conservation-priority source species overlap with hotspots of malnutrition, highlighting the need for safeguarding strategies to ensure that edible plant diversity remains a reservoir of nutrition for future generations, particularly in countries needing it most. Although by no means a silver bullet to tackling malnutrition, conserving a diverse portfolio of edible plants, unravelling their nutritional potentials, and promoting their sustainable use are essential strategies to enhance global nutritional resilience.

Madagascar's extraordinary biodiversity: Evolution, distribution, and use.

Madagascar's biota is hyperdiverse and includes exceptional levels of endemicity. We review the current state of knowledge on Madagascar's past and current terrestrial and freshwater biodiversity by compiling and presenting comprehensive data on species diversity, endemism, and rates of species description and human uses, in addition to presenting an updated and simplified map of vegetation types. We report a substantial increase of records and species new to science in recent years; however, the diversity and evolution of many groups remain practically unknown (e.g., fungi and most invertebrates). Digitization efforts are increasing the resolution of species richness patterns and we highlight the crucial role of field- and collections-based research for advancing biodiversity knowledge and identifying gaps in our understanding, particularly as species richness corresponds closely to collection effort. Phylogenetic diversity patterns mirror that of species richness and endemism in most of the analyzed groups. We highlight humid forests as centers of diversity and endemism because of their role as refugia and centers of recent and rapid radiations. However, the distinct endemism of other areas, such as the grassland-woodland mosaic of the Central Highlands and the spiny forest of the southwest, is also biologically important despite lower species richness. The documented uses of Malagasy biodiversity are manifold, with much potential for the uncovering of new useful traits for food, medicine, and climate mitigation. The data presented here showcase Madagascar as a unique "living laboratory" for our understanding of evolution and the complex interactions between people and nature. The gathering and analysis of biodiversity data must continue and accelerate if we are to fully understand and safeguard this unique subset of Earth's biodiversity.

Plant Diversity Conservation Challenges and Prospects-The Perspective of Botanic Gardens and the Millennium Seed Bank.

There is a pressing need to conserve plant diversity to prevent extinctions and to enable sustainable use of plant material by current and future generations. Here, we review the contribution that living collections and seed banks based in botanic gardens around the world make to wild plant conservation and to tackling global challenges. We focus in particular on the work of Botanic Gardens Conservation International and the Millennium Seed Bank of the Royal Botanic Gardens, Kew, with its associated global Partnership. The advantages and limitations of conservation of plant diversity as both living material and seed collections are reviewed, and the need for additional research and conservation measures, such as cryopreservation, to enable the long-term conservation of 'exceptional species' is discussed. We highlight the importance of networks and sharing access to data and plant material. The skill sets found within botanic gardens and seed banks complement each other and enable the development of integrated conservation (linking in situ and ex situ efforts). Using a number of case studies we demonstrate how botanic gardens and seed banks support integrated conservation and research for agriculture and food security, restoration and reforestation, as well as supporting local livelihoods.

Areas of global importance for conserving terrestrial biodiversity, carbon and water.

To meet the ambitious objectives of biodiversity and climate conventions, the international community requires clarity on how these objectives can be operationalized spatially and how multiple targets can be pursued concurrently. To support goal setting and the implementation of international strategies and action plans, spatial guidance is needed to identify which land areas have the potential to generate the greatest synergies between conserving biodiversity and nature's contributions to people. Here we present results from a joint optimization that minimizes the number of threatened species, maximizes carbon retention and water quality regulation, and ranks terrestrial conservation priorities globally. We found that selecting the top-ranked 30% and 50% of terrestrial land area would conserve respectively 60.7% and 85.3% of the estimated total carbon stock and 66% and 89.8% of all clean water, in addition to meeting conservation targets for 57.9% and 79% of all species considered. Our data and prioritization further suggest that adequately conserving all species considered (vertebrates and plants) would require giving conservation attention to ~70% of the terrestrial land surface. If priority was given to biodiversity only, managing 30% of optimally located land area for conservation may be sufficient to meet conservation targets for 81.3% of the terrestrial plant and vertebrate species considered. Our results provide a global assessment of where land could be optimally managed for conservation. We discuss how such a spatial prioritization framework can support the implementation of the biodiversity and climate conventions.

Toward Unifying Global Hotspots of Wild and Domesticated Biodiversity.

Global biodiversity hotspots are areas containing high levels of species richness, endemism and threat. Similarly, regions of agriculturally relevant diversity have been identified where many domesticated plants and animals originated, and co-occurred with their wild ancestors and relatives. The agro-biodiversity in these regions has, likewise, often been considered threatened. Biodiversity and agro-biodiversity hotspots partly overlap, but their geographic intricacies have rarely been investigated together. Here we review the history of these two concepts and explore their geographic relationship by analysing global distribution and human use data for all plants, and for major crops and associated wild relatives. We highlight a geographic continuum between agro-biodiversity hotspots that contain high richness in species that are intensively used and well known by humanity (i.e., major crops and most viewed species on Wikipedia) and biodiversity hotspots encompassing species that are less heavily used and documented (i.e., crop wild relatives and species lacking information on Wikipedia). Our contribution highlights the key considerations needed for further developing a unifying concept of agro-biodiversity hotspots that encompasses multiple facets of diversity (including genetic and phylogenetic) and the linkage with overall biodiversity. This integration will ultimately enhance our understanding of the geography of human-plant interactions and help guide the preservation of nature and its contributions to people.

Mutualistic interactions reshuffle the effects of climate change on plants across the tree of life.

Climatically induced local species extinctions may trigger coextinction cascades, thus driving many more species to extinction than originally predicted by species distribution models. Using seven pollination networks across Europe that include the phylogeny and life history traits of plants, we show a substantial variability across networks in climatically predicted plant extinction-and particularly the subsequent coextinction-rates, with much higher values in Mediterranean than Eurosiberian networks. While geographic location best predicts the probability of a plant species to be driven to extinction by climate change, subsequent coextinctions are best predicted by the local network of interactions. These coextinctions not only increase the total number of plant species being driven to extinction but also add a bias in the way the major taxonomic and functional groups are pruned.

Geographic variation in genetic and demographic performance: new insights from an old biogeographical paradigm.

The 'centre-periphery hypothesis' (CPH) is a long-standing postulate in ecology that states that genetic variation and demographic performance of a species decrease from the centre to the edge of its geographic range. This hypothesis is based on an assumed concordance between geographical peripherality and ecological marginality such that environmental conditions become harsher towards the limits of a species range. In this way, the CPH sets the stage for understanding the causes of distribution limits. To date, no study has examined conjointly the consistency of these postulates. In an extensive literature review we discuss the birth and development of the CPH and provide an assessment of the CPH by reviewing 248 empirical studies in the context of three main themes. First, a decrease in species occurrence towards their range limits was observed in 81% of studies, while only 51% demonstrated reduced abundance of individuals. A decline in genetic variation, increased differentiation among populations and higher rates of inbreeding were demonstrated by roughly one in two studies (47, 45 and 48%, respectively). However, demographic rates, size and population performance less often followed CPH expectations (20-30% of studies). We highlight the impact of important methodological, taxonomic, and biogeographical biases on such validation rates. Second, we found that geographic and ecological marginality gradients are not systematically concordant, which casts doubt on the reliability of a main assumption of the CPH. Finally, we attempt to disentangle the relative contribution of geographical, ecological and historical processes on the spatial distribution of genetic and demographic parameters. While ecological marginality gradients explain variation in species' demographic performance better than geographic gradients, contemporary and historical factors may contribute interactively to spatial patterns of genetic variation. We thereby propose a framework that integrates species' ecological niche characteristics together with current and past range structure to investigate spatial patterns of genetic and demographic variation across species ranges.

Balance between climate change mitigation benefits and land use impacts of bioenergy: conservation implications for European birds.

Both climate change and habitat modification exert serious pressure on biodiversity. Although climate change mitigation has been identified as an important strategy for biodiversity conservation, bioenergy remains a controversial mitigation action due to its potential negative ecological and socio-economic impacts which arise through habitat modification by land-use change. While the debate continues, the separate or simultaneous impacts of both climate change and bioenergy on biodiversity have not yet been compared. We assess projected range shifts of 156 European bird species by 2050 under two alternative climate change trajectories: a baseline scenario, where the global mean temperature increases by 4°C by the end of the century, and a 2 degrees scenario, where global concerted effort limits the temperature increase to below 2°C. For the latter scenario, we also quantify the pressure exerted by increased cultivation of energy biomass as modelled by IMAGE2.4, an integrated land-use model. The global bioenergy use in this scenario is in the lower end of the range of previously estimated sustainable potential. Under the assumptions of these scenarios, we find that the magnitude of range shifts due to climate change is far greater than the impact of land conversion to woody bioenergy plantations within the European Union, and that mitigation of climate change reduces the exposure experienced by species. However, we identified potential for local conservation conflict between priority areas for conservation and bioenergy production. These conflicts must be addressed by strict bioenergy sustainability criteria that acknowledge biodiversity conservation needs beyond existing protected areas and apply also to biomass imported from outside the European Union.

Ensemble distribution models in conservation prioritization: from consensus predictions to consensus reserve networks.

AIM: Conservation planning exercises increasingly rely on species distributions predicted either from one particular statistical model or, more recently, from an ensemble of models (i.e. ensemble forecasting). However, it has not yet been explored how different ways of summarizing ensemble predictions affect conservation planning outcomes. We evaluate these effects and compare commonplace consensus methods, applied before the conservation prioritization phase, to a novel method that applies consensus after reserve selection. LOCATION: Europe. METHODS: We used an ensemble of predicted distributions of 146 Western Palaearctic bird species in alternative ways: four different consensus methods, as well as distributions discounted with variability, were used to produce inputs for spatial conservation prioritization. In addition, we developed and tested a novel method, in which we built 100 datasets by sampling the ensemble of predicted distributions, ran a conservation prioritization analysis on each of them and averaged the resulting priority ranks. We evaluated the conservation outcome against three controls: (i) a null control, based on random ranking of cells; (2) the reference solution, based on an expert-refined dataset; and (3) the independent solution, based on an independent dataset. RESULTS: Networks based on predicted distributions were more representative of rare species than randomly selected networks. Alternative methods to summarize ensemble predictions differed in representativeness of resulting reserve networks. Our novel method resulted in better representation of rare species than pre-selection consensus methods. MAIN CONCLUSIONS: Retaining information about the variation in the predicted distributions throughout the conservation prioritization seems to provide better results than summarizing the predictions before conservation prioritization. Our results highlight the need to understand and consider model-based uncertainty when using predicted distribution data in conservation prioritization.