Bruce J Hayward

Abiotic factors are usually considered key drivers of species distribution at macro scales, while biotic interactions are mostly used at local scales. A few studies have explored the role of biotic interactions at macro scales, but all considered a limited number of species and obligate interactions. We examine the role of biotic interactions in large‐scale SDMs by testing two main hypotheses: (1) biotic factors in SDMs can have an important role at continental scale; (2) the inclusion of biotic factors in large‐scale SDMs is important also for generalist species. We used a maximum entropy algorithm to model the distribution of 177 bat species in Africa calibrating two SDMs for each species: one considering only abiotic variables (noBIO‐SDMs) and the other (BIO‐SDMs) including also biotic variables (trophic resource richness). We focused the interpretation of our results on variable importance and response curves. For each species, we also compared the potential distribution measuring the percentage of change between the two models in each pixel of the study area. All models gave AUC >0.7, with values on average higher in BIO‐SDMs compared to noBIO‐SDMs. Trophic resources showed an importance overall higher level than all abiotic predictors in most of the species (~68%), including generalist species. Response curves were highly interpretable in all models, confirming the ecological reliability of our models. Model comparison between the two models showed a change in potential distribution for more than 80% of the species, particularly in tropical forests and shrublands. Our results highlight the importance of considering biotic interactions in SDMs at macro scales. We demonstrated that a generic biotic proxy can be important for modeling species distribution when species‐specific data are not available, but we envision that a multi‐scale analysis combined with a better knowledge of the species might provide a better understanding of the role of biotic interactions.

Background Range maps are a useful tool to describe the spatial distribution of species. However, they need to be used with caution, as they essentially represent a rough approximation of a species’ suitable habitats. When stacked together, the resulting communities in each grid cell may not always be realistic, especially when species interactions are taken into account. Here we show the extent of the mismatch between range maps, provided by the International Union for Conservation of Nature (IUCN), and species interactions data. More precisely, we show that local networks built from those stacked range maps often yield unrealistic communities, where species of higher trophic levels are completely disconnected from primary producers. Methodology We used the well-described Serengeti food web of mammals and plants as our case study, and identify areas of data mismatch within predators’ range maps by taking into account food web structure. We then used occurrence data from the Global Biodiversity Information Facility (GBIF) to investigate where data is most lacking. Results We found that most predator ranges comprised large areas without any overlapping distribution of their prey. However, many of these areas contained GBIF occurrences of the predator. Conclusions Our results suggest that the mismatch between both data sources could be due either to the lack of information about ecological interactions or the geographical occurrence of prey. We finally discuss general guidelines to help identify defective data among distributions and interactions data, and we recommend this method as a valuable way to assess whether the occurrence data that are being used, even if incomplete, are ecologically accurate.

Rodents, a diverse, globally distributed and ecologically important order of mammals are nevertheless important reservoirs of known and novel zoonotic pathogens. Ongoing anthropogenic land use change is altering these species’ abundance and distribution, which among zoonotic host species may increase the risk of zoonoses spillover events. A better understanding of the current distribution of rodent species is required to guide attempts to mitigate against potentially increased zoonotic disease hazard and risk. However, available species distribution and host-pathogen association datasets (e.g. IUCN, GBIF, CLOVER) are often taxonomically and spatially biased. Here, we synthesise data from West Africa from 127 rodent trapping studies, published between 1964–2022, as an additional source of information to characterise the range and presence of rodent species and identify the subgroup of species that are potential or known pathogen hosts. We identify that these rodent trapping studies, although biased towards human dominated landscapes across West Africa, can usefully complement current rodent species distribution datasets and we calculate the discrepancies between these datasets. For five regionally important zoonotic pathogens (Arenaviridae spp., Borrelia spp., Lassa mammarenavirus, Leptospira spp. and Toxoplasma gondii), we identify host-pathogen associations that have not been previously reported in host-association datasets. Finally, for these five pathogen groups, we find that the proportion of a rodent hosts range that have been sampled remains small with geographic clustering. A priority should be to sample rodent hosts across a greater geographic range to better characterise current and future risk of zoonotic spillover events. In the interim, studies of spatial pathogen risk informed by rodent distributions must incorporate a measure of the current sampling biases. The current synthesis of contextually rich rodent trapping data enriches available information from IUCN, GBIF and CLOVER which can support a more complete understanding of the hazard of zoonotic spillover events.

Population fluctuations are widespread across the animal kingdom, especially in the order Rodentia, which includes many globally important reservoir species for zoonotic pathogens. The implications of these fluctuations for zoonotic spillover remain poorly understood. Here, we report a global empirical analysis of data describing the linkages between habitat use, population fluctuations and zoonotic reservoir status in rodents. Our quantitative synthesis is based on data collated from papers and databases. We show that the magnitude of population fluctuations combined with species’ synanthropy and degree of human exploitation together distinguish most rodent reservoirs at a global scale, a result that was consistent across all pathogen types and pathogen transmission modes. Our spatial analyses identified hotspots of high transmission risk, including regions where reservoir species dominate the rodent community. Beyond rodents, these generalities inform our understanding of how natural and anthropogenic factors interact to increase the risk of zoonotic spillover in a rapidly changing world. Many rodent species are known as hosts of zoonotic pathogens, but the ecological conditions that trigger spillover are not well-understood. Here, the authors show that population fluctuations and association with human-dominated habitats explain the zoonotic reservoir status of rodents globally.

Understanding the status and abundance of species is essential for effective conservation decision-making. However, the availability of species data varies across space, taxonomic groups and data types. A case study was therefore conducted in a high biodiversity region—East Africa—to evaluate data biases, the factors influencing data availability, and the consequences for conservation. In each of the eleven target countries, priority animal species were identified as threatened species that are protected by national governments, international conventions or conservation NGOs. We assessed data gaps and biases in the IUCN Red List of Threatened Species, the Global Biodiversity Information Facility and the Living Planet Index. A survey of practitioners and decision makers was conducted to confirm and assess consequences of these biases on biodiversity conservation efforts. Our results showed data on species occurrence and population trends were available for a significantly higher proportion of vertebrates than invertebrates. We observed a geographical bias, with higher tourism income countries having more priority species and more species with data than lower tourism income countries. Conservationists surveyed felt that, of the 40 types of data investigated, those data that are most important to conservation projects are the most difficult to access. The main challenges to data accessibility are excessive expense, technological challenges, and a lack of resources to process and analyse data. With this information, practitioners and decision makers can prioritise how and where to fill gaps to improve data availability and use, and ensure biodiversity monitoring is improved and conservation impacts enhanced.

BackgroundCrimean-Congo haemorrhagic fever (CCHF) is a widespread tick-borne viral infection, present across Africa and Eurasia, which might pose a cryptic public health problem in Uganda. We aimed to understand the magnitude and distribution of CCHF risk in humans, livestock and ticks across Uganda by synthesising epidemiological (cross-sectional) and ecological (modelling) studies.MethodsWe conducted a cross-sectional study at three urban abattoirs receiving cattle from across Uganda. We sampled humans (n = 478), livestock (n = 419) and ticks (n = 1065) and used commercially-available kits to detect human and livestock CCHF virus (CCHFV) antibodies and antigen in tick pools. We developed boosted regression tree models to evaluate the correlates and geographical distribution of expected tick and wildlife hosts, and of human CCHF exposures, drawing on continent-wide data.FindingsThe cross-sectional study found CCHFV IgG/IgM seroprevalence in humans of 10·3% (7·8–13·3), with antibody detection positively associated with reported history of tick bite (age-adjusted odds ratio = 2·09 (1·09–3·98)). Cattle had a seroprevalence of 69·7% (65·1–73·4). Only one Hyalomma tick (CCHFV-negative) was found. However, CCHFV antigen was detected in Rhipicephalus (5·9% of 304 pools) and Amblyomma (2·9% of 34 pools) species. Modelling predicted high human CCHF risk across much of Uganda, low environmental suitability for Hyalomma, and high suitability for Rhipicephalus and Amblyomma.InterpretationOur epidemiological and ecological studies provide complementary evidence that CCHF exposure risk is widespread across Uganda. We challenge the idea that Hyalomma ticks are consistently the principal reservoir and vector for CCHFV, and postulate that Rhipicephalus might be important for CCHFV transmission in Uganda, due to high frequency of infected ticks and predicted environmental suitability.FundingUCL Global Challenges Research Fund (GCRF) and Pan-African Network on Emerging and Re-Emerging Infections (PANDORA-ID-NET) funded by the European and Developing Countries Clinical Trials Partnership (EDCTP) under the EU Horizon 2020 Framework Programme for Research and Innovation.

Marmosini is the most speciose marsupial tribe of Colombia with 19 species, but basic aspects of their biology remains unknown, including information on their distribution and conservation. The main objectives of this work were to study Marmosini species richness, potential distribution, and conservation throughout Colombia. To achieve this, we generated ecological niche models in a reproducible framework, in which we tested the use of different combinations of environmental data (WorldClim, ENVIREM, modified soil adjusted vegetation index (MSAVI)), modeling areas, cross-validation methods, and evaluation metrics using our data from Colombian Marmosini. Models for each species were explored for shared environmental and conservation patterns across all species, and using ecological and human-related (e.g., protected areas) data specific to Colombia. We found models that included WorldClim, ENVIREM and MSAVI variables, and modeling areas based on ecoregions performed better with our sample. Precipitation variables were more important for 8 species, while temperature variables were more important in 5 species, and topographic variables were important in the remaining species. Marmosini species’ potential distribution covers 91% of the country's continental area, and the protected area for any species of this group ranges between 5.4% and 29% of their modeled distribution. Most protected areas classified as strict-conservation presented small areas of high human pressure, while other categories (e.g., managed resources) presented large areas of high human pressure. We found that high potential species richness of Marmosini occurs at mid-elevations on the Andes with an upper elevation limit of maximum richness at ~ 2000 m. These species distributions are poorly covered by the natural protected areas of Colombia. We identified the transition zone between the Eastern Andes and Amazonian regions as a key area for conservation efforts in these little known marsupials.

Aim Aggregated species occurrence data are increasingly accessible through public databases for the analysis of temporal trends in the geographic distributions of species. However, biases in these data present challenges for statistical inference. We assessed potential biases in data available through GBIF on the occurrences of four flower-visiting taxa: bees (Anthophila), hoverflies (Syrphidae), leaf-nosed bats (Phyllostomidae) and hummingbirds (Trochilidae). We also assessed whether and to what extent data mobilization efforts improved our ability to estimate trends in species' distributions. Location The Neotropics. Methods We used five data-driven heuristics to screen the data for potential geographic, temporal and taxonomic biases. We began with a continental-scale assessment of the data for all four taxa. We then identified two recent data mobilization efforts (2021) that drastically increased the quantity of records of bees collected in Chile available through GBIF. We compared the dataset before and after the addition of these new records in terms of their biases and estimated trends in species' distributions. Results We found evidence of potential sampling biases for all taxa. The addition of newly-mobilized records of bees in Chile decreased some biases but introduced others. Despite increasing the quantity of data for bees in Chile sixfold, estimates of trends in species' distributions derived using the postmobilization dataset were broadly similar to what would have been estimated before their introduction, albeit more precise. Main conclusions Our results highlight the challenges associated with drawing robust inferences about trends in species' distributions using publicly available data. Mobilizing historic records will not always enable trend estimation because more data do not necessarily equal less bias. Analysts should carefully assess their data before conducting analyses: this might enable the estimation of more robust trends and help to identify strategies for effective data mobilization. Our study also reinforces the need for targeted monitoring of pollinators worldwide.

Aim Understanding speciation mechanisms requires disentangling processes that promote and erode population-level divergence. Three hypotheses are raised that contemporary population structure is mainly shaped by refugial isolation, gene flow or both. Testing these hypotheses requires range-wide phylogeography and integrative analyses across scales. Here we aimed to (1) re-estimate the previously unresolved nuclear divergence within a widespread bat; (2) test the above three phylogeographical hypotheses and (3) inform conservation management under climatic change. Location North America including the Caribbean. Taxon The big brown bat (Eptesicus fuscus). Methods We collected range-wide samples and genome-wide markers using restriction site-associated DNA sequencing. Population structure was analysed by clustering methods and spatial estimations. Nuclear phylogeographical divergence was estimated using tree methods (concatenation and coalescence) and network analyses (TreeMix). Phylogeographical hypotheses were tested by comparing alternative evolutionary scenarios using demographic modelling. Species distribution modelling was used to help identify Pleistocene refugia and predict future range shifts under climatic change. Results We identified three populations in the Caribbean, eastern and western North America. The western population further split into three phylogeographical clades: Pacific, southwestern North America and Mexico. Discordance among mitochondrial and nuclear topologies reflected strong impacts of gene flow without sex bias. Demographic modelling supported scenarios of historical isolation followed by secondary gene flow and estimated Holocene divergence times. Species distribution was essentially continuous during glaciation with possible regional isolation, and northward range shifts were predicted under future climatic change. Main Conclusions Contemporary population divergence of big brown bats was shaped by both historical isolation and secondary gene flow, supporting the third phylogeographical hypothesis. While climatic change likely triggered initial divergence, ongoing gene flow has largely impacted the dynamic within-species evolution and generated population divergence without speciation.

Orthohantaviruses, family Hantaviridae , are globally distributed except for Antarctica where they are absent. In animals, orthohantaviruses are transmitted horizontally, either directly through aggressive interactions and grooming or by inhaling infectious particles shed from urine, feces, or saliva in the environment. Humans become infected by inhaling aerosols of the virus-contaminated excretions of small mammals. Orthohantaviral infections in humans cause severe hantavirus pulmonary syndrome (HPS) in the North American Artic and hemorrhagic fever with renal syndrome (HFRS) in the Eurasian Arctic. In the Arctic, 16 rodent species (order Rodentia) and five shrew species (order Eulipotyphla) have been identified as reservoirs of orthohantaviruses by RNA detection. The two most important reservoir rodents in the Arctic are the bank vole ( Myodes glareolus ) in Eurasia carrying Puumala orthohantavirus (PUUV) and North American deermouse ( Peromyscus maniculatus ) in the North American Arctic carrying Sin Nombre orthohantavirus (SNV); both rodents being habitat generalists occurring in natural and human-modified habitats. Global warming, either independently or in combination with onshore exploitation of natural resources, is expected to increase the distribution range of reservoirs (including bank vole and North American deermouse, rats ( Rattus rattus and R. norvegicus ), house mouse ( Mus musculus ) and field mice ( Apodemus spp.)), and their associated orthohantaviruses. These changes pose the risk of introducing New World orthohantaviruses (e.g., Jemez Springs virus (JMSV) and SNV) to areas where so far only Old World orthohantaviruses (e.g., Hantaan orthohantavirus (HTNV) and PUUV) occur and vice versa. Climate change in the Arctic will likely also promote transmission and prevalence of orthohantaviruses in their reservoirs and hence increase zoonotic risk. The expected environmental changes call for increased surveillance and preparedness to mitigate potential outbreaks of orthohantavirus diseases in humans.