Search

Though facing significant challenges, coffee (Coffea arabica) grown in Haitian agroforestry systems are important contributors to rural livelihoods and provide several ecosystem services. However, little is known about their genetic diversity and the variety mixtures used. In light of this, there is a need to characterize Haitian coffee diversity to help inform revitalization of this sector. We sampled 28 diverse farms in historically important coffee growing regions of northern and southern Haiti. We performed KASP-genotyping of SNP markers and HiPlex multiplex amplicon sequencing for haplotype calling on our samples, as well as several Ethiopian and commercial accessions from international collections. This allowed us to assign Haitian samples to varietal groups. Our analyses revealed considerable genetic diversity in Haitian farms, higher in fact than many farmers realized. Notably, genetic structure analyses revealed the presence of clusters related to Typica, Bourbon, and Catimor groups, another group that was not represented in our reference accession panel, and several admixed individuals. Across the study areas, we found both mixed-variety farms and monovarietal farms with the historical and traditional Typica variety. This study is, to our knowledge, the first to genetically characterize Haitian C. arabica variety mixtures, and report the limited cultivation of C. canephora (Robusta coffee) in the study area. Our results show that some coffee farms are repositories of historical, widely-abandoned varieties while others are generators of new diversity through genetic mixing.

Understanding crop domestication provides a basis for ongoing genetic improvement of crops, especially in the utilization of wild crop relatives as a source of new variation and may guide the domestication of new crops. The Asia Pacific region is home to most of the world's human population and is a region in which many important crops were domesticated. Here we review the domestication of banana, citrus, coconut, macadamia, mango, millet, mungbean, rice, sugarcane and taro in the Asia Pacific region. These examples illustrate the importance of this region in the development of agriculture. The challenges of conservation of the genetic resources for these crops are exacerbated by the large human population and rapid economic development in the region. Advances in genetic technologies provide an opportunity for accelerated genetic improvement of these crops and the domestication of new crops.

Tropical forests play a crucial role in climate regulation due to their high carbon sequestration capacity. However, degradation and disturbances in these forests may result in significant carbon losses. This study focuses on the impact of various biophysical, anthropogenic, and landscape factors on aboveground biomass (AGB) in heavily disturbed landscapes of Côte d'Ivoire (West Africa), a typical low-forest and high-deforestation country. AGB estimates from a National Forest Inventory dataset have been linked to five categories of variables (Climate, Soil, Topography, Landscape, and Human-related) through a random forest modeling approach that addressed collinearity among variables, selected key variables from each category, and used spatial cross-validation to evaluate model performance. The comprehensive model, combining landscape composition, physical soil properties, and climate variables, demonstrated strong performance with an R-squared of 0.62. Notably, the percentage of landscape occupied by forest within a radius of 1000 m (PLAND1000) had a highly significant impact on AGB, exhibiting a notable increase when PLAND1000 exceeded 80 % and a decrease when it felt below 25 %. Soil properties, both physical (Bulk Density and Coarse Fraction) and chemical (soil pH), significantly influenced AGB, too. Interestingly, climatic, topographic, and other anthropogenic variables had minimal relevance in predicting AGB, suggesting that their effects may have been captured by landscape and soil integrative variables. In order to enhance forest preservation and restoration initiatives in the face of deforestation and fragmentation challenges in the West African region, we recommend (i) evaluating the appropriate landscape scale of effect (a 1000 m radius circle being the most significant in this study); (ii) prioritizing the preservation or restoration of dense forest landscapes; and (iii) integrating landscape composition into forest management policies.

Since 1976 various species of Ebolavirus have caused a series of zoonotic outbreaks and public health crises in Africa. Bats have long been hypothesised to function as important hosts for ebolavirus maintenance, however the transmission ecology for these viruses remains poorly understood. Several studies have demonstrated rapid seroconversion for ebolavirus antibodies in young bats, yet paradoxically few PCR studies have confirmed the identity of the circulating viral species causing these seroconversions. The current study presents an age-structured epidemiological model that characterises the effects of seasonal birth pulses on ebolavirus transmission within a colony of African straw-coloured fruit bats (Eidolon helvum). Bayesian calibration is performed using previously published serological data collected from Cameroon, and age-structure data from Ghana. The model predicts that annual birth pulses most likely give rise to annual outbreaks, although more complex dynamic patterns – including skip years, multi-annual cycles and chaos – may be possible. Weeks 30 to 31 of each year were estimated to be the most likely period for isolating the circulating virus in Cameroon. The probability that a previous PCR campaign failed to detect Ebola virus, assuming that it was circulating, was estimated to be one in two thousand. This raises questions such as (1) what can we actually learn from ebolavirus serology tests performed without positive controls? (2) are current PCR tests sufficiently sensitive? (3) are swab samples really appropriate for ebolavirus detection? The current results provide important insights for the design of future field studies aiming to detect Ebola viruses from sylvatic hosts, and can contribute to risk assessments concerning the timing of zoonotic outbreaks.

The cacao crop spread throughout the world from its center of origin in South America. However, one of its main diseases cacao swollen shoot disease (CSSD), which is caused by the complex of cacao-infecting badnaviruses, was first detected in Africa. Here we investigate the relationship between the genetic diversity of the viruses that cause CSSD and their geographical distribution, and the possible relationship between the genetic diversity of the virus and the symptoms they trigger. We also sought to determine the evolutionary models that could explain this relationship and evaluate the evolutionary history of the virus through ancestral state reconstructions and temporality analyses. A high mutation rate was observed along with a clear phylogenetic signal in the geographic distribution and in the symptoms associated with each viral species. The molecular clock provided new evidence on the emergence and speciation of cacao-infecting badnaviruses, suggesting a possible American origin of these viruses.

Multivariate count distributions are crucial for the inference of ecological processes underpinning biodiversity. In particular, neutral theory provides useful null distributions allowing the evaluation of adaptation or natural selection. In this paper, we build a broader family of multivariate distributions: the Polya-splitting distributions. We show that they emerge naturally as stationary distributions of a multivariate birth–death process. This family of distributions is a consistent extension of non-zero sum neutral models based on a master equation approach. It allows considering both total abundance of the community and relative abundances of species. We emphasize that this family is large enough to encompass various dependence structures among species. We also introduce the strong closure under addition property that can be useful to generate nested multi-level dependence structures. Although all Pólya splitting distributions do not share this property, we provide numerous example verifying it. They include the previously known example with independent species, and also new ones with alternative dependence structures. Overall, we advocate that Polya-splitting distribution should become a part of the classic toolbox for the analysis of multivariate count data in ecology, providing alternative approaches to joint species distribution framework. Comparatively, our approach allows to model dependencies between species at the observation level, while the classical JSDM's model dependencies at the latent process strata.

Short-term adaptive evolution represents one of the primary mechanisms allowing species to persist in the face of global change. Predicting the adaptive response at the species level requires reliable estimates of the evolutionary potential of traits involved in adaptive responses, as well as understanding how evolutionary potential varies across a species' range. Theory suggests that spatial variation in the fitness landscape due to environmental variation will directly impact the evolutionary potential of traits. However, empirical evidence on the link between environmental variation and evolutionary potential across a species range in the wild is lacking. In this study, we estimate multivariate evolutionary potential (via the genetic variance–covariance matrix, or G-matrix) for six morphological and life history traits in 10 wild populations of great tits (Parus major) distributed across Europe. The G-matrix significantly varies in size, shape, and orientation across populations for both types of traits. For life history traits, the differences in G-matrix are larger when populations are more distant in their climatic niche. This suggests that local climates contribute to shaping the evolutionary potential of phenotypic traits that are strongly related to fitness. However, we found no difference in the overall evolutionary potential (i.e., G-matrix size) between populations closer to the core or the edge of the distribution area. This large-scale comparison of G-matrices across wild populations emphasizes that integrating variation in multivariate evolutionary potential is important to understand and predict species' adaptive responses to new selective pressures.

The vast peat deposits in the Peruvian Amazon are crucial to the global climate. Palm swamp, the most extensive regional peatland ecosystem faces different threats, including deforestation and degradation due to felling of the dominant palm Mauritia flexuosa for fruit harvesting. While these activities convert this natural C sink into a source, the distribution of degradation and deforestation in this ecosystem and related C emissions remain unstudied. We used remote sensing data from Landsat, ALOS-PALSAR, and NASA's GEDI spaceborne LiDAR-derived products to map palm swamp degradation and deforestation within a 28 Mha area of the lowland Peruvian Amazon in 1990–2007 and 2007–2018. We combined this information with a regional peat map, C stock density data and peat emission factors to determine (1) peatland C stocks of peat-forming ecosystems (palm swamp, herbaceous swamp, pole forest), and (2) areas of palm swamp peatland degradation and deforestation and associated C emissions. In the 6.9 ± 0.1 Mha of predicted peat-forming ecosystems within the larger 28 Mha study area, 73% overlaid peat (5.1 ± 0.9 Mha) and stored 3.88 ± 0.12 Pg C. Degradation and deforestation in palm swamp peatlands totaled 535,423 ± 8,419 ha over 1990–2018, with a pronounced dominance for degradation (85%). The degradation rate increased 15% from 15,400 ha y−1 (1990–2007) to 17,650 ha y−1 (2007–2018) and the deforestation rate more than doubled from 1,900 ha y−1 to 4,200 ha y−1. Over 1990–2018, emissions from degradation amounted to 26.3 ± 3.5 Tg C and emissions from deforestation were 12.9 ± 0.5 Tg C. The 2007–2018 emission rate from both biomass and peat loss of 1.9 Tg C yr−1 is four times the average biomass loss rate due to gross deforestation in 2010–2019 reported for the hydromorphic Peruvian Amazon. The magnitude of emissions calls for the country to account for deforestation and degradation of peatlands in national reporting.

Avian influenza (AI) is an infectious viral disease of birds, including domestic poultry, which has been causing outbreaks worldwide, leading to several millions of dead wild birds and culled poultry. AI is mainly found in birds, but recently, there was an increase in reported infections in mammals, ranging from no symptoms to mass mortality events and some human cases. Epidemiologically of great concern, evidence of mammalian adaptations have been found, but the transmission routes and pathogenesis in mammals are still to be defined. Hence, it is paramount to address all facets of AI viruses epidemiology, including investigating taxa not customarily thought to be involved in the transmission and/or trafficking of AI, such as wild mammals. The scope of this report was to assess the role of mammals in AI epidemiology, virology and pathology, i.e. AI maintenance, reservoir role, immunity, role of mammals in a potential pandemic. To do so, we performed an all-encompassing review of the literature on the topic with a two-fold approach: a systematic review of the published AI cases in wild mammals and a narrative approach to provide an expert opinion on the role of mammals in AI spread. The final number of peer-reviewed papers included in the systematic literature review was 76, resulting in 120 unique infection records with AI in wild mammal species. The most represented taxa were included in the order Carnivora. The risk of infection was identified mainly as predation (or feeding) upon infected birds or contact with avian species. Evidence of mammal-to-mammal transmission in the wild is only circumstantial and yet to be confirmed. Cases of AI from the systematic review of experimental findings were discussed concerning epidemiology, pathology and virology. Knowledge gaps and potential pandemic drivers were identified. In summary, although a greater number of infections in wild mammals have been reported, there is no hard evidence for sustained mammal-to-mammal transmis

Crop-to-wild gene flow is a mechanism process widely documented, both in plants and animals. This can have positive or negative impacts on the evolution of admixed populations in natural environments, yet the phenomenon is still misunderstood in long-lived woody species, contrary to short-lived crops. Wild olive Olea europaea L. occurs in the same eco-geographical range as domesticated olive, i.e. the Mediterranean Basin (MB). Moreover, it is an allogamous and anemophilous species whose seeds are disseminated by birds, i.e. factors that drive gene flow between crops and their wild relatives. Here we investigated the genetic structure of western MB wild olive populations in natural environments assuming a homogenous gene pool with limited impact of cultivated alleles, as previously suggested. We used a target sequencing method based on annotated genes from the Farga reference genome to analyze 27 western MB olive tree populations sampled in natural environments in France, Spain and Morocco. We also target sequenced cultivated olive tree accessions from the Worldwide Olive Germplasm Bank of Marrakech and Porquerolles and from an eastern MB wild olive tree population. We combined PCA, sNMF, pairwise FST and TreeMix and clearly identified genuine wild olive trees throughout their natural distribution range along a north-south gradient including, for the first time, in southern France. However, contrary to our assumption, we highlighted more admixed than genuine wild olive trees. Our results raise questions regarding the admixed population evolution pattern in this environment, which might be facilitated by crop-to-wild gene flow.

On oceanic islands, strong human impacts on habitats, combined with introductions of exotic species, modify the composition of terrestrial bird assemblages and threaten their ecological functions. In La Réunion, an oceanic island located in the Madagascan region, a national park was established in 2007 to counter the ecosystem-level effects of three centuries of habitat conversion, native species destruction and exotic species introductions. Here, we investigated how bird assemblages were structured in these human-modified landscapes, 10 years before the national park set out its first conservation measures. We used a combination of multivariate statistics and generalized additive models to describe variations in the taxonomic and functional composition and diversity of 372 local bird assemblages, encompassing 20 species, along gradients of habitat composition and configuration. We found that native species were tied to native habitats while exotic species were associated with urban areas and man-modified landscape mosaics, with some overlap at mid-elevations. Species' trophic preferences were segregated along habitat gradients, but ecological traits had an overall weak role in explaining the composition of species assemblages. Hence, at the time of the survey, native and exotic species in La Réunion formed two spatially distinct species assemblages with contrasting ecological trait suites that benefited from antagonistic habitat compositions and dynamics. We conclude that our results support the analysis of historical data sets to establish reference points to monitor human impacts on insular ecosystems.

As highly pervasive parasites that sometimes cause disease, viruses are likely major components of all natural ecosystems. An important step towards both understanding the precise ecological roles of viruses and determining how natural communities of viral species are assembled and evolve is obtaining full descriptions of viral diversity and distributions at ecosystem scales. Here, we focused on obtaining such 'community-scale' data for viruses in a single genus. We chose the genus Mastrevirus (family Geminiviridae), members of which have predominantly been found infecting uncultivated grasses (family Poaceae) throughout the tropical and sub-tropical regions of the world. We sampled over 3 years, 2,884 individual Poaceae plants belonging to thirty different species within a 2-ha plot which included cultivated and uncultivated areas on the island of Reunion. Mastreviruses were found in ∼8 per cent of the samples, of which 96 per cent did not have any discernible disease symptoms. The multitude of host–virus associations that we uncovered reveals both the plant species that most commonly host mastreviruses and the mastrevirus species (such as maize streak virus and maize streak Reunion virus) that have especially large host ranges. Our findings are consistent with the hypothesis that perennial plant species capable of hosting years-long mixed mastrevirus infections likely play a disproportionately important role in the generation of inter-species and inter-strain mastrevirus recombinants.

Phlebotomine sand flies are of global significance as important vectors of human disease, transmitting bacterial, viral, and protozoan pathogens, including the kinetoplastid parasites of the genus Leishmania, the causative agents of devastating diseases collectively termed leishmaniasis. More than 40 pathogenic Leishmania species are transmitted to humans by approximately 35 sand fly species in 98 countries with hundreds of millions of people at risk around the world. No approved efficacious vaccine exists for leishmaniasis and available therapeutic drugs are either toxic and/or expensive, or the parasites are becoming resistant to the more recently developed drugs. Therefore, sand fly and/or reservoir control are currently the most effective strategies to break transmission. To better understand the biology of sand flies, including the mechanisms involved in their vectorial capacity, insecticide resistance, and population structures we sequenced the genomes of two geographically widespread and important sand fly vector species: Phlebotomus papatasi, a vector of Leishmania parasites that cause cutaneous leishmaniasis, (distributed in Europe, the Middle East and North Africa) and Lutzomyia longipalpis, a vector of Leishmania parasites that cause visceral leishmaniasis (distributed across Central and South America). We categorized and curated genes involved in processes important to their roles as disease vectors, including chemosensation, blood feeding, circadian rhythm, immunity, and detoxification, as well as mobile genetic elements. We also defined gene orthology and observed micro-synteny among the genomes. Finally, we present the genetic diversity and population structure of these species in their respective geographical areas. These genomes will be a foundation on which to base future efforts to prevent vector-borne transmission of Leishmania parasites.

Background: Human African trypanosomiasis is a parasitic disease caused by trypanosomes among which Trypanosoma brucei gambiense is responsible for a chronic form (gHAT) in West and Central Africa. Its elimination as a public health problem (EPHP) was targeted for 2020. Côte d'Ivoire was one of the first countries to be validated by WHO in 2020 and this was particularly challenging as the country still reported around a hundred cases a year in the early 2000s. This article describes the strategies implemented including a mathematical model to evaluate the reporting results and infer progress towards sustainable elimination. Methods: The control methods used combined both exhaustive and targeted medical screening strategies including the follow-up of seropositive subjects– considered as potential asymptomatic carriers to diagnose and treat cases– as well as vector control to reduce the risk of transmission in the most at-risk areas. A mechanistic model was used to estimate the number of underlying infections and the probability of elimination of transmission (EoT) was met between 2000–2021 in two endemic and two hypo-endemic health districts. Results: Between 2015 and 2019, nine gHAT cases were detected in the two endemic health districts of Bouaflé and Sinfra in which the number of cases/10,000 inhabitants was far below 1, a necessary condition for validating EPHP. Modelling estimated a slow but steady decline in transmission across the health districts, bolstered in the two endemic health districts by the introduction of vector control. The decrease in underlying transmission in all health districts corresponds to a high probability that EoT has already occurred in Côte d'Ivoire. Conclusion: This success was achieved through a multi-stakeholder and multidisciplinary one health approach where research has played a major role in adapting tools and strategies to this large epidemiological transition to a very low prevalence. This integrated approach will need to conti

Background: Crimean Congo hemorrhagic fever (CCHF) is endemic in Southern Mauritania where recurrent outbreaks have been constantly observed since the 1980's. The present study is the first to assess CCHFV antibodies and RNA in humans. Methods: A retrospective study was conducted using 263 humans and 1380 domestic animals serum samples, and 282 tick specimens of Hyalomma genus collected from 54 settings in 12 provinces across Mauritania. Antibodies targeting CCHF viral nucleoprotein were detected in animal and human sera using double-antigen ELISA. CCHFV specific RNA was detected in human and animal sera as well as tick supernatants using a CCHFV real time RT-PCR kit. Individual characteristics of sampled hosts were collected at the same time and data were geo-referenced. Satellite data of several environmental and climatic factors, were downloaded from publicly available datasets, and combined with data on livestock mobility, animal and human density, road accessibility and individual characteristics to identify possible risk factors for CCHFV spatial distribution. To this end, multivariate logistic models were developed for each host category (human, small and large ruminants). Results: The overall CCHFV antibody prevalence was 11.8% [95% CI: 8.4–16.3] in humans (17.9% in 2020 and 5.4% in 2021; p = 0.0017) and 33.1% (95% CI: 30.1–36.3) in livestock. CCHFV-specific antibodies were detected in 91 (18.1%) out of 502 sheep, 43 (9.0%) out of 477 goats, 144 (90.5%) out of 161 dromedaries and 179 (74.6%) out of 240 cattle. CCHFV RNA was detected in only 2 (0.7%) sera out of 263 animals herders samples from Hodh El Gharbi province and in 32 (11.3%) out of 282 Hyalomma ticks. In humans as well as in animals, seropositivity was not associated with sex or age groups. The multivariate analysis determined the role of different environmental, climatic and anthropic factors in the spatial distribution of the disease with animal mobility and age being identified as risk factors.

Understanding what controls global leaf type variation in trees is crucial for comprehending their role in terrestrial ecosystems, including carbon, water and nutrient dynamics. Yet our understanding of the factors influencing forest leaf types remains incomplete, leaving us uncertain about the global proportions of needle-leaved, broadleaved, evergreen and deciduous trees. To address these gaps, we conducted a global, ground-sourced assessment of forest leaf-type variation by integrating forest inventory data with comprehensive leaf form (broadleaf vs needle-leaf) and habit (evergreen vs deciduous) records. We found that global variation in leaf habit is primarily driven by isothermality and soil characteristics, while leaf form is predominantly driven by temperature. Given these relationships, we estimate that 38% of global tree individuals are needle-leaved evergreen, 29% are broadleaved evergreen, 27% are broadleaved deciduous and 5% are needle-leaved deciduous. The aboveground biomass distribution among these tree types is approximately 21% (126.4 Gt), 54% (335.7 Gt), 22% (136.2 Gt) and 3% (18.7 Gt), respectively. We further project that, depending on future emissions pathways, 17–34% of forested areas will experience climate conditions by the end of the century that currently support a different forest type, highlighting the intensification of climatic stress on existing forests. By quantifying the distribution of tree leaf types and their corresponding biomass, and identifying regions where climate change will exert greatest pressure on current leaf types, our results can help improve predictions of future terrestrial ecosystem functioning and carbon cycling.

Despite the centrality of staple grains for human well-being, both as a source of nutrients and of toxic ions, there is little understanding of where and how elements vary, and if there are particular elements that correlate. Here, for shop bought polished (white) rice, we comprehensively characterized trace (arsenic species, cadmium, copper, iron, manganese, molybdenum, rubidium and zinc) and macro-nutrients (calcium, chlorine, potassium, phosphorus and sulphur) for grain purchased in 18 countries, across four continents, a total of 1045 samples. This was to investigate if there were any major differences between geographic location and elemental content, and to observe if there were any patterns in elemental distribution. Greatest variation in the median was observed for the non-essential rubidium (15-fold) and arsenic species (fivefold). Rubidium was the highest in the Americas, lowest in Europe, while inorganic arsenic (iAs) and dimethylarsonic acid (DMA) were low for Africa and high in the South American and European continents. The highest concentrations of cadmium were found in Asian samples, and lowest in South America, with variation within these regions. At the extremes of individual counties, China had fivefold higher concentrations than the global median, while Tanzania was fourfold lower than this value. Calcium, potassium, molybdenum and phosphorus were the highest in European and lowest in African grain, though the fold-differences were relatively low, ~ 0.2, while iron was the highest in African grain and lowest in European, Asian and South American grain, with a ~ twofold difference. Selenium was also higher in Africa versus other regions, and copper, manganese and zinc were the highest in American grain. Factor analysis showed that copper, cadmium, molybdenum, rubidium and selenium were strongly associated together, and these element's factor loadings were diametrically opposed to less tightly associated calcium, chlorine, manganese, potassium, pho

The Myotis nattereri species complex has been the focus of several recent morphological and molecular surveys to assess the species status of various named forms, including three informally referred to as Myotis sp. A, M. sp. B and M. sp. C. The first two forms have now been formally described as distinct biological species, and named M. crypticus and M. zenatius, respectively, both distinct from the nominotypical M. nattereri s. str. and M. escalerai. The latter form, Myotis sp. C is known only from Corsica. Here we demonstrate that this form has not only unique mitochondrial haplotypes but also several nuclear alleles that are divergent and not found anywhere else, which emphasizes its long independent evolution. We therefore confirm its specific status and describe it as a new species. Its ecology and rupicolous roosting habits resemble those of the Iberian M. escalerai, but it is otherwise morphologically most similar to M. crypticus. This new species is endemic to Corsica and is apparently very rare and essentially localised to mountain forests. Owing to its restricted distribution, its small population size, and limited population connectivity, it seems highly vulnerable to climate change and thus should be classified as endangered.

Forests contribute to climate change mitigation through carbon storage and uptake, but the extent to which this carbon pool varies in space and time is still poorly known. Several Earth Observation missions have been specifically designed to address this issue, for example, NASA's GEDI, NASA-ISRO's NISAR and ESA's BIOMASS. Yet, all these missions' products require independent and consistent validation. A permanent, global, in situ, site-based forest biomass reference measurement system relying on ground data of the highest possible quality is therefore needed. Here, we have assembled a list of almost 200 high-quality sites through an in-depth review of the literature and expert knowledge. In this study, we explore how representative these sites are in terms of their coverage of environmental conditions, geographical space and biomass-related forest structure, compared to those experienced by forests worldwide. This work also aims at identifying which sites are the most representative, and where to invest to improve the representativeness of the proposed system. We show that the environmental coverage of the system does not seem to improve after at least the 175 most representative sites are included, but geographical and structural coverages continue to improve as more sites are added. We highlight the areas of poor environmental, geographical, or structural coverage, including, but not limited to, Canada, the western half of the USA, Mexico, Patagonia, Angola, Zambia, eastern Russia, and tropical and subtropical highlands (e.g. in Colombia, the Himalayas, Borneo, Papua). For the proposed system to succeed, we stress that (1) data must be collected and processed applying the same standards across all countries and continents; (2) system establishment and management must be inclusive and equitable, with careful consideration of working conditions; and (3) training and site partner involvement in downstream activities should be mandatory.

The microsporidian Vairimorpha (Nosema) ceranae is one of the most common parasites of the honeybee. A single honeybee carries many parasites and therefore multiple alleles of V. ceranae genes that seem to be ubiquitous. As a consequence, nucleotide diversity analyses have not allowed discriminating genetic structure of parasite populations. We performed deep loci-targeted sequencing to monitor the haplotype frequencies of genome markers in isolates from discontinuous territories, namely the tropical islands of the South West Indian Ocean. The haplotype frequency distribution corroborated the suspected tetraploidy of the parasite. Most major haplotypes were ubiquitous in the area but with variable frequency. While oceanic isolates differed from European and Asian outgroups, parasite populations from distinct archipelagoes also differed in their haplotype distribution. Interestingly an original and very divergent Malagasy isolate was detected. The observed population structure allowed formulating hypotheses upon the natural history of V. ceranae in this oceanic area. We also discussed the usefulness of allelic distribution assessment, using multiple informative loci or genome-wide analyses, when parasite population is not clonal within a single host.

Fire is a natural element of some tropical dry ecosystems. However, during the last decades, fire occurrence has become more frequent and intense due, in part, to climate change and land use transformation. This is the case in the Gran Chaco Americano, one of the largest dry forests all over the world that extends across Argentina, Paraguay, Bolivia and Brazil. Fire has shaped the Gran Chaco landscape since ancient times, but today, as in many other regions, the pattern, frequency, severity and intensity are being dramatically altered. Based on information collected mainly over the last two decades, this paper presents a detailed review of the available literature on the fire regime across the Gran Chaco region. Here, we present a multi-disciplinary understanding considering fire behavior and dynamics in the study ecosystem within a very specific ecological, administrative and historical framework. A noteworthy aspect of this review indicates the clear imbalance between regions in terms of available literature; while information about the Argentine Chaco is abundant, the literature for the Paraguayan or Bolivian Chaco is practically non-existent. The rainfall gradient and drought periods are key climatic drivers of fire ignitions while cattle ranching is the main socioeconomic activity of this region and key precursor of forest fires. In general, a substantial part of the available information focused on ecological aspects of the fire regime as the effect of fires on plant functional traits such as bark thickness, resprouting ability and flammability patterns. Other post fire effects on soil, invasive species, herbivory and soil seed banks have been also explored in detail to understand ecosystem recovery and research needs. We finally highlight current necessities and future prospects, mainly related to soil burn severity (SBS), invasive species and wildlife impact. Although our study specifically focused on changes in the fire regime of the Gran Chaco, some genera

In Subsaharan Africa, tsetse flies (genus Glossina) are vectors of trypanosomes causing Human African Trypanosomiasis (HAT) and Animal African Trypanosomosis (AAT). Some foci of HAT persist in Southern Chad, where a program of tsetse control was started against the local vector Glossina fuscipes fuscipes in the Mandoul focus in 2014, and in Maro in 2018. Flies were also sampled in 2018 in Timbéri and Dokoutou. We analyzed the population genetics of G. fuscipes fuscipes from the four tsetse-infested zones. The trapping samples were characterized by a strong female biased sex-ratio, except in Timbéri and Dokoutou that had high tsetse densities. Apparent density and effective population density appeared smaller in the main foci of Mandoul and Maro and the average dispersal distance (within the spatial scale of each zone) was as large as or larger than the total length of each respective zone. The genetic signature of a population bottleneck was found in the Mandoul and Timbéri area, suggesting a large ancient interconnected metapopulation that underwent genetic subdivision into small, isolated pockets due to adverse environmental conditions. The long-range dispersal and the existence of genetic outliers suggest a possibility of migration from remote sites such as the Central African Republic in the south (although the fly situation remains unknown there) and/or a genetic signature of recent exchanges. Due to likely isolation, an eradication strategy may be considered for sustainable HAT control in Mandoul focus. Another strategy will probably be required in Maro focus, which probably experiences much more exchanges with its neighbors.

Livestock mobility, particularly that of small and large ruminants, is one of the main pillars of production and trade in West Africa: livestock is moved around in search of better grazing or sold in markets for domestic consumption and for festival-related activities. These movements cover several thousand kilometers and have the capability of connecting the whole West African region, thus facilitating the diffusion of many animal and zoonotic diseases. Several factors shape mobility patterns even in normal years and surveillance systems need to account for such changes. In this paper, we present an approach based on temporal network theory to identify possible sentinel locations, i.e., locations where pathogens circulation can be detected in the early phase of the epidemic (before the peak), using two indicators: vulnerability (i.e., the probability of being reached by the disease) and time of infection (i.e., the time of first arrival of the disease). Using these indicators in our structural analysis of the changing network enabled us to identify a set of nodes that could be used in an early warning system. As a case study, we simulated the introduction of transboundary animal diseases in Senegal and used data taken from 2020 Sanitary certificates (laissez-passer sanitaire (LPS)) issued by the Senegalese Veterinary Services to reconstruct the national mobility network. Our analysis showed that a static approach can significantly overestimate the speed and the extent of disease propagation, whereas temporal analysis revealed that the reachability and vulnerability of the different administrative departments (used as nodes of the mobility network) change over the course of the year. For this reason, several sets of sentinel nodes were identified in different periods of the year, underlining the role of temporality in shaping patterns of disease diffusion.

Greenhouse gas (GHGs) emissions from peatlands contribute significantly to ongoing climate change because of human land use. To develop reliable and comprehensive estimates and predictions of GHG emissions from peatlands, it is necessary to have GHG observations, including carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), that cover different peatland types globally. We synthesize published peatland studies with field GHG flux measurements to identify gaps in observations and suggest directions for future research. Although GHG flux measurements have been conducted at numerous sites globally, substantial gaps remain in current observations, encompassing various peatland types, regions and GHGs. Generally, there is a pressing need for additional GHG observations in Africa, Latin America and the Caribbean regions. Despite widespread measurements of CO2 and CH4, studies quantifying N2O emissions from peatlands are scarce, particularly in natural ecosystems. To expand the global coverage of peatland data, it is crucial to conduct more eddy covariance observations for long-term monitoring. Automated chambers are preferable for plot-scale observations to produce high temporal resolution data; however, traditional field campaigns with manual chamber measurements remain necessary, particularly in remote areas. To ensure that the data can be further used for modeling purposes, we suggest that chamber campaigns should be conducted at least monthly for a minimum duration of one year with no fewer than three replicates and measure key environmental variables. In addition, further studies are needed in restored peatlands, focusing on identifying the most effective restoration approaches for different ecosystem types, conditions, climates, and land use histories.

Two members of the family Betaflexiviridae associated with yam (Dioscorea spp.) have been described so far: yam latent virus (YLV) and yam virus Y (YVY). However, their geographical distribution and molecular diversity remain poorly documented. Using a nested RT-PCR assay, we detected YVY in D. alata, D. bulbifera, D. cayenensis, D. rotundata, and D. trifida in Guadeloupe, and in D. rotundata in Côte d'Ivoire, thus extending the known host range of this virus and geographical distribution. Using amplicon sequencing, we determined that the molecular diversity of YVY in the yam samples analyzed in this work ranged between 0.0 and 29.1% and that this diversity is partially geographically structured. We also identified three isolates of banana mild mosaic virus (BanMMV) infecting D. alata in Guadeloupe, providing the first evidence for BanMMV infection in yam.

Modern agriculture has influenced plant virus emergence through ecosystem simplification, introduction of new host species, and reduction in crop genetic diversity. Therefore, it is crucial to better understand virus distributions across cultivated and uncultivated communities in agro-ecological interfaces, as well as virus exchange among them. Here, we advance fundamental understanding in this area by characterizing the virome of three co-occurring replicated Poaceae community types that represent a gradient of grass species richness and management intensity, from highly managed crop monocultures to little-managed, species-rich grasslands. We performed a large-scale study on 950 wild and cultivated Poaceae over 2 years, combining untargeted virome analysis down to the virus species level with targeted detection of three plant viruses. Deep sequencing revealed (i) a diversified and largely unknown Poaceae virome (at least 51 virus species or taxa), with an abundance of so-called persistent viruses; (ii) an increase of virome richness with grass species richness within the community; (iii) stability of virome richness over time but a large viral intraspecific variability; and (iv) contrasting patterns of virus prevalence, coinfections, and spatial distribution among plant communities and species. Our findings highlight the complex structure of plant virus communities in nature and suggest the influence of anthropogenic management on viral distribution and prevalence.

Intraspecific variability (IV) has been proposed to explain species coexistence in diverse communities. Assuming, sometimes implicitly, that conspecific individuals can perform differently in the same environment and that IV increases niche overlap, previous studies have found contrasting results regarding the effect of IV on species coexistence. We aim at showing that the large IV observed in data does not mean that conspecific individuals are necessarily different in their response to the environment and that the role of high-dimensional environmental variation in determining IV has largely remained unexplored in forest plant communities. We first used a simulation experiment where an individual attribute is derived from a high-dimensional model, representing “perfect knowledge” of individual response to the environment, to illustrate how large observed IV can result from “imperfect knowledge” of the environment. Second, using growth data from clonal Eucalyptus plantations in Brazil, we estimated a major contribution of the environment in determining individual growth. Third, using tree growth data from long-term tropical forest inventories in French Guiana, Panama and India, we showed that tree growth in tropical forests is structured spatially and that despite a large observed IV at the population level, conspecific individuals perform more similarly locally than compared with heterospecific individuals. As the number of environmental dimensions that are well quantified at fine scale is generally lower than the actual number of dimensions influencing individual attributes, a great part of observed IV might be represented as random variation across individuals when in fact it is environmentally driven. This mis-representation has important consequences for inference about community dynamics. We emphasize that observed IV does not necessarily impact species coexistence per se but can reveal species response to high-dimensional environment, which is consistent with

Data from functional trait databases have been increasingly used to address questions related to plant diversity and trait-environment relationships. However, such databases provide intraspecific data that combine individual records obtained from distinct populations at different sites and, hence, environmental conditions. This prevents distinguishing sources of variation (e.g., genetic-based variation vs. phenotypic plasticity), a necessary condition to test for adaptive processes and other determinants of plant phenotypic diversity. Consequently, individual traits measured under common growing conditions and encompassing within-species variation across the occupied geographic range have the potential to leverage trait databases with valuable data for functional and evolutionary ecology. Here, we recorded 16 functional traits and leaf hyperspectral reflectance (NIRS) data for 721 widely distributed Arabidopsis thaliana natural accessions grown in a common garden experiment. These data records, together with meteorological variables obtained during the experiment, were assembled to create the AraDiv dataset. AraDiv is a comprehensive dataset of A. thaliana's intraspecific variability that can be explored to address questions at the interface of genetics and ecology.

Locusts are among the most feared agricultural pests. Spatiotemporal forecasting is a key process in their management. The present review aims to 1) set a common language on the subject, 2) evaluate the current methodologies, and 3) identify opportunities to improve forecasting tools. Forecasts can be used to provide reliable predictions on locust presence, reproduction events, gregarization areas, population outbreaks, and potential impacts on agriculture. Statistical approaches are used for the first four objectives, whereas mechanistic approaches are used for the latter. We advocate 1) to build reliable and reproducible spatiotemporal forecasting systems for the impacts on agriculture, 2) to turn scientific studies into operational forecasting systems, and 3) to evaluate the performance of these systems.

Rodents (Rodentia) are the most abundant and diverse order of mammals, present in all habitats, including urban areas. The traffic linked to globalisation has favoured their involvement in biological invasions that have an impact on local biodiversity, the economy and human health. In Franceville, Gabon, little is known about the rodent community. We therefore studied the composition and distribution of rodents along a gradient highlighting the heterogeneity of the city's landscape. The three habitat types studied showed no difference in small mammal abundance, while the diversity index was higher in the vegetated habitat (SDI = 0.73) compared to the outdoor (SDI = 0.71) and indoor (SDI = 0.45) habitats. Our work shows the importance of vegetal remnants in the city for the maintenance of native species. It also highlights the impact of introduced species on small mammal assemblages and the need for management to reduce the factors of their proliferation.

Bushpigs (Potamochoerus larvatus) play a major role in the socio-ecosystem of Madagascar, particularly in rural areas. They are largely hunted by rural populations as a major source of income and protein. They can also represent a potential source of pathogens for domestic animals and people. For example, it is hypothesized that bushpigs might compromise African swine fever (ASF) eradication programs by sporadically transmitting the virus to domestic pigs. However, available knowledge on the distribution of bushpigs in Madagascar is limited. In this study, we estimated the distribution of bushpigs on Madagascar using a species distribution model (SDM). We retrieved 206 sightings of bushpigs in Madagascar during 1990–2016 and predicted the distribution by using 37 climatic, geographic, and agricultural/human variables related to the presence of bushpigs and running a presence-background maximum entropy SDM. Our model identified three main areas with a high suitability for bushpigs: in the north, central-western, and east of the island (AUC = 0.84). The main contributors to the model were the vegetation index (51.3%), percentage of land covered by trees (17.6%), and annual averaged monthly precipitation (12.6%). In addition, we identified areas in central Madagascar with a high density of domestic pigs and a high suitability score for bushpigs. These results may help to identify bushpig areas at the interface with domestic pigs to assess the risk of pathogen transmission and to design ecological assessments, wildlife management studies, or targeted surveillance and research studies related to many bushpig-borne pathogens, such as ASF, which is an endemic problem in the country, as well as zoonotic diseases such as cysticercosis and hepatitis E. Our approach could also be extrapolated to other species of wild swine in other countries.

The assumption that climatic growing requirements of invasive species are conserved between their native and non-native environment is a key ecological issue in the evaluation of invasion risk. We conducted a growth chamber experiment to compare the effect of water regime and temperature on the growth and mortality of native and invasive populations of common gorse seedlings (Ulex europaeus L.). Seeds were sampled from 20 populations of five areas from both native (continental France and Spain) and non-native areas (New Zealand, Canary and Reunion islands). The seedlings were grown over 36 days in two temperature treatments (ambient and elevated) combined with two water treatments (irrigated or droughted). The elevated temperature (ET) was defined as the highest temperature observed at the niche margin in the different countries. While ET increased seedlings growth, the drought treatment increased mortality rate and limited seedlings growth. Under ET and drought, native populations showed a greater mortality rate (53%) than invasive populations (16%). Invasive seedlings also showed higher above- and belowground development than native ones under these constrained climatic conditions. While phenotypic plasticity did not differ between native and invasive populations, the difference between populations in terms of total dry mass could be related to differences in the climate of origin (precipitation in particular). Assessing the importance of phenotypic changes between populations within invasive species is crucial to identify the margins of their climatic distribution range and to highlight areas where management efforts should be concentrated in order to limit its spread.

Current and likely future changes in the geographic distribution of ticks belonging to the genus Hyalomma are of concern, as these ticks are believed to be vectors of many pathogens responsible for human and animal diseases. However, we have observed that for many pathogens there are no vector competence experiments, and that the level of evidence provided by the scientific literature is often not sufficient to validate the transmission of a specific pathogen by a specific Hyalomma species. We therefore carried out a bibliographical study to collate the validation evidence for the transmission of parasitic, viral, or bacterial pathogens by Hyalomma spp. ticks. Our results show that there are very few validated cases of pathogen transmission by Hyalomma tick species.

We present a new application to recognize 218 species of cultivated crops on geo-tagged photos, 'Pl@ntNet Crops'. The application and underlying algorithms are developed using more than 750k photos voluntarily collected by Pl@ntNet users. The app is then enriched by data and photos coming from the European Union's (EU) Land Use and Coverage Area frame Survey (LUCAS). During five tri-annual LUCAS campaigns from 2006 to 2018, 242 476 close-up 'cover' photos of crops were collected. The survey protocol for these photos specified that 'the picture should be taken at a close distance, so that the structure of leaves can be clearly seen, as well as flowers or fruits'. This unique labelled data provides an opportunity to further generalize the Pl@ntNet computer vision algorithms to recognize crops and enlarge their geographic representivity across the EU. To include LUCAS cover photos, we semantically match Pl@ntNet species and LUCAS legends, predict the species on LUCAS cover photos with the existing Pl@ntNet algorithm, and consider the accuracy of the classification and the number of species enriched by the photos. By setting a threshold of 0.5 on the Pl@ntNet prediction probabilities, 70 170 LUCAS photos representing 101 species classified with an accuracy of 0.9 were added to the 'Crops' app. The thematic accuracy of the legacy LUCAS data was improved by distinguishing 218 species, opposed to the original 36 LUCAS levels. Official and publicly financed LUCAS datastreams can now be improved because of Pl@ntNet citizen science, photo collection, and deep learning model development. Further use of the app and policy-relevant workflows in the agri-food-environment domain are discussed.

The article discloses the AMS (accelerator mass spectrometry) radiocarbon dating results of the Egg baobab, a superlative Grandidier baobab (Adansonia grandidieri) from the Andomiry Forest, Atsimo-Andrefana region, Madagascar. The investigation of the baobab shows that it consists of 5 perfectly fused stems and exhibits a closed ring-shaped structure with a very large false cavity inside. The calculated overall wood volume of the Egg baobab is 450 m3. Two wood samples were collected from the exterior of the stems, out of which nine tiny segments were extracted and dated by radiocarbon. The oldest sample segment had a radiocarbon date of 921 ± 24 BP, which corresponds to a calibrated age of 840 ± 25 years. According to this value the Egg baobab is 875 ± 75 years old.

Aim: To investigate the geographic patterns and ecological correlates in the geographic distribution of the most common tree dispersal modes in Amazonia (endozoochory, synzoochory, anemochory and hydrochory). We examined if the proportional abundance of these dispersal modes could be explained by the availability of dispersal agents (disperser-availability hypothesis) and/or the availability of resources for constructing zoochorous fruits (resource-availability hypothesis). Time period: Tree-inventory plots established between 1934 and 2019. Major taxa studied: Trees with a diameter at breast height (DBH) ≥ 9.55 cm. Location: Amazonia, here defined as the lowland rain forests of the Amazon River basin and the Guiana Shield. Methods: We assigned dispersal modes to a total of 5433 species and morphospecies within 1877 tree-inventory plots across terra-firme, seasonally flooded, and permanently flooded forests. We investigated geographic patterns in the proportional abundance of dispersal modes. We performed an abundance-weighted mean pairwise distance (MPD) test and fit generalized linear models (GLMs) to explain the geographic distribution of dispersal modes. Results: Anemochory was significantly, positively associated with mean annual wind speed, and hydrochory was significantly higher in flooded forests. Dispersal modes did not consistently show significant associations with the availability of resources for constructing zoochorous fruits. A lower dissimilarity in dispersal modes, resulting from a higher dominance of endozoochory, occurred in terra-firme forests (excluding podzols) compared to flooded forests. Main conclusions: The disperser-availability hypothesis was well supported for abiotic dispersal modes (anemochory and hydrochory). The availability of resources for constructing zoochorous fruits seems an unlikely explanation for the distribution of dispersal modes in Amazonia. The association between frugivores and the proportional abundance of zoochory req

Multi-purpose Faidherbia albida trees represent a vital component of agroforestry parklands in West Africa as they provide resources (fodder for livestock, fruits and firewood) and support water lifting and nutrient recycling for cropping. Faidherbia albida trees are characterized by their inverse phenology, growing leaf flowers and pods during the dry season, thereby providing fodder and shedding leaves during the wet season, which minimizes competition with pastures and crops for resources. Multi-spectral and multi-temporal satellite systems and novel computational methods open new doors for classifying single trees and identifying species. This study used a Multi-Layer Perception feedforward artificial neural network to classify pixels covered by Faidherbia albida canopies from Sentinel-2 time series in Senegal, West Africa. To better discriminate the Faidherbia albida signal from the background, monthly images from vegetation indices were used to form relevant variables for the model. We found that NDI54/NDVI from the period covering onset of leaf senescence (February) until end of senescence (leaf-off in June) to be the most important, resulting in a high precision and recall rate of 0.91 and 0.85. We compared our result with a potential Faidherbia albida occurrence map derived by empirical modelling of the species ecology, which deviates notably from the actual species occurrence mapped by this study. We have shown that even small differences in dry season leaf phenology can be used to distinguish tree species. The Faidherbia albida distribution maps, as provided here, will be key in managing farmlands in drylands, helping to optimize economic and ecological services from both tree and crop products.