Norman Tindale

Globally, vector‐borne diseases are increasing in distribution and frequency, affecting humans, domestic animals, and wildlife. Science‐based management and prevention of these diseases requires a sound understanding of the distribution and environmental requirements of the vectors and hosts involved in disease transmission. Integrated Species Distribution Models (ISDM) account for diverse data types through hierarchical modeling and represent a significant advancement in species distribution modeling. We assessed the distribution of the soft tick subspecies Ornithodoros turicata americanus. This tick species is a potential vector of African swine fever virus (ASFV), a pathogen responsible for an ongoing global epizootic that threatens agroindustry worldwide. Given the novelty of this method, we compared the results to a conventional Maxent SDM and validated the results through data partitioning. Our input for the model consisted of systematically collected detection data from 591 sampled field sites and 12 historical species records, as well as four variables describing climatic and soil characteristics. We found that a combination of climatic variables describing seasonality and temperature extremes, along with the amount of sand in the soil, determined the predicted intensity of occurrence of this tick species. When projected in geographic space, this distribution model predicted 62% of Florida as suitable habitat for this tick species. The ISDM presented a higher TSS and AUC than the Maxent conventional model, while sensitivity was similar between both models. Our case example shows the utility of ISDMs in disease ecology studies and highlights the broad range of geographic suitability for this important disease vector. These results provide important foundational information to inform future risk assessment work for tick‐borne relapsing fever surveillance and potential ASF introduction and maintenance in the United States.

Island ecosystems have significant conservation value owing to their higher endemic biotas. Moreover, studies of regional communities that compare differences in species composition (species dissimilarity) among islands and the mainland suggest that community assembly on islands is different from that on the mainland. However, the uniqueness of island biotic assembly has been little studied at the global scale, nor have phylogenetic information or alien species been considered in these patterns. We evaluate taxonomic and phylogenetic change from one community to the next, focusing on differences in species composition between mainland-mainland (M-M) pairs compared to differences between mainland-island pairs (M-I) and between island-island pairs (I-I), using herpetofauna on islands and adjacent mainland areas worldwide. Our analyses detect greater taxonomic and phylogenetic dissimilarity for M-I and I-I comparisons than predicted by M-M model, indicating different island herpetofauna assembly patterns compared with mainland counterparts across the world. However, this higher M-I dissimilarity has been significantly decreased after considering alien species. Our results provide global evidence on the importance of island biodiversity conservation from the aspect of both the taxonomic and phylogenetic uniqueness of island biotic assembly.

Predicting global change effects poses significant challenges due to the intricate interplay between climate change and anthropogenic stressors in shaping ecological communities and their function, such as pest outbreak risk. Termites are ecosystem engineers, yet some pest species are causing worldwide economic losses. While habitat fragmentation seems to drive pest-dominated termite communities, its interaction with climate change effect remains unknown. We test whether climate and habitat fragmentation interactively alter interspecific competition that may limit pest termite risk. Leveraging global termite co-occurrence including 280 pest species, we found that competitively superior termite species (e.g., large bodied) increased in large and continuous habitats solely at high precipitation. While competitive species suppressed pest species globally, habitat fragmentation drove pest termite risk only in humid biomes. Unfortunately, hu- mid tropics have experienced vast forest fragmentation and rainfall reduction over the past decades. These stressors, if not stopped, may drive pest termite risk, potentially via competitive release.

Premise Cleomaceae is an important model clade for studies of evolutionary processes including genome evolution, floral form diversification, and photosynthetic pathway evolution. Diversification and divergence patterns in Cleomaceae remain tangled as research has been restricted by its worldwide distribution, limited genetic sampling and species coverage, and a lack of definitive fossil calibration points.MethodsWe used target sequence capture and the Angiosperms353 probe set to perform a phylogenetic study of Cleomaceae. We estimated divergence times and biogeographic analyses to explore the origin and diversification of the family. Seed morphology across extant taxa was documented with multifocal image‐stacking techniques and morphological characters were extracted, analyzed, and compared to fossil records.ResultsWe recovered a well‐supported and resolved phylogenetic tree of Cleomaceae generic relationships that includes 236 (~86%) species. We identified 11 principal clades and confidently placed Cleomella as sister to the rest of the family. Our analyses suggested that Cleomaceae and Brassicaceae diverged ~56 mya, and Cleomaceae began to diversify ~53 mya in the Palearctic and Africa. Multiple transatlantic disjunct distributions were identified. Seeds were imaged from 218 (~80%) species in the family and compared to all known fossil species.ConclusionsOur results represent the most comprehensive phylogenetic study of Cleomaceae to date. We identified transatlantic disjunctions and proposed explanations for these patterns, most likely either long‐distance dispersals or contractions in latitudinal distributions caused by climate change over geological timescales. We found that seed morphology varied considerably but mostly mirrored generic relationships.

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

Species are often expected to shift their distributions either poleward or upslope to evade warming climates and colonise new suitable climatic niches. However, from 18‐years of fixed transect monitoring data on 88 species of butterfly in the midwestern United States, we show that butterflies are shifting their centroids in all directions, except towards regions that are warming the fastest (southeast).Butterflies shifted their centroids at a mean rate of 4.87 km year−1. The rate of centroid shift was significantly associated with local climate change velocity (temperature by precipitation interaction), but not with mean climate change velocity throughout the species' ranges.Species tended to shift their centroids at a faster rate towards regions that are warming at slower velocities but increasing in precipitation velocity.Surprisingly, species' thermal niche breadth (range of climates butterflies experience throughout their distribution) and wingspan (often used as metric for dispersal capability) were not correlated with the rate at which species shifted their ranges.We observed high phylogenetic signal in the direction species shifted their centroids. However, we found no phylogenetic signal in the rate species shifted their centroids, suggesting less conserved processes determine the rate of range shift than the direction species shift their ranges.This research shows important signatures of multidirectional range shifts (latitudinal and longitudinal) and uniquely shows that local climate change velocities are more important in driving range shifts than the mean climate change velocity throughout a species' entire range.

Aim Species occurrence data are valuable information that enables one to estimate geographical distributions, characterize niches and their evolution, and guide spatial conservation planning. Rapid increases in species occurrence data stem from increasing digitization and aggregation efforts, and citizen science initiatives. However, persistent quality issues in occurrence data can impact the accuracy of scientific findings, underscoring the importance of filtering erroneous occurrence records in biodiversity analyses.InnovationWe introduce an R package, occTest, that synthesizes a growing open‐source ecosystem of biodiversity cleaning workflows to prepare occurrence data for different modelling applications. It offers a structured set of algorithms to identify potential problems with species occurrence records by employing a hierarchical organization of multiple tests. The workflow has a hierarchical structure organized in testPhases (i.e. cleaning vs. testing) that encompass different testBlocks grouping different testTypes (e.g. environmental outlier detection), which may use different testMethods (e.g. Rosner test, jacknife,etc.). Four different testBlocks characterize potential problems in geographic, environmental, human influence and temporal dimensions. Filtering and plotting functions are incorporated to facilitate the interpretation of tests. We provide examples with different data sources, with default and user‐defined parameters. Compared to other available tools and workflows, occTest offers a comprehensive suite of integrated tests, and allows multiple methods associated with each test to explore consensus among data cleaning methods. It uniquely incorporates both coordinate accuracy analysis and environmental analysis of occurrence records. Furthermore, it provides a hierarchical structure to incorporate future tests yet to be developed.Main conclusionsoccTest will help users understand the quality and quantity of data available before the start of data analysis, while also enabling users to filter data using either predefined rules or custom‐built rules. As a result, occTest can better assess each record's appropriateness for its intended application.

Myoporum is a genus of trees and shrubs native to the Northern Hemisphere that has been introduced to many parts of the world, mainly for ornamental purposes. We assessed the introduction history, distribution, and extent of naturalization/invasion for Myoporum species in South Africa.Information was collated to determine key events associated with the introduction, establishment, and naturalization of Myoporum in South Africa. Data were collated to determine the current distribution of the genus in South Africa. Twenty sites in the Western Cape were sampled to determine correlates of naturalization. Myoporum was first recorded in South Africa in 1934. Three species were confirmed to be present in South Africa: M. insulare, M. laetum and M. montanum (37 %, 25 % and 24 % of all iNaturalist records respectively). Most records are from the Western Cape (91 %) and small parts of the Eastern Cape; isolated populations occur in Gauteng and the Northern Cape. We could not confirm the presence M. petiolatum, M. tenuifolium or M. tetrandrum. Field surveys revealed widespread naturalization of M. insulare (46 % of all Research Grade observations in iNaturalist); this species was categorized code D1 in the introduction-naturalization-invasion continuum. Myoporum laetum (C3) and M. montanum (C2) are also widely naturalized but over smaller areas. Naturalized populations comprised predominantly juvenile M. insulare plants occurring in highly disturbed (transformed) habitats. Formal risk analyses for all Myoporum species in South Africa are needed as the basis for re-evaluation of their status in national legislation.

Clerodendrum inerme (L.) Gaertn., commonly known as garden quinine, is a perennial shrub that belongs to the Lamiaceae family. It has been extensively used in various traditional medicinal practices to treat ailments such as rheumatic pain, arthritis, scrofulous, venereal disease, skin diseases, wounds, fever, cough, dysentery, and more. This review aims to critically examine a comprehensive compilation of recent research on C. inerme , encompassing its botanical characteristics, ethnomedical applications, phytochemicals, pharmacological activity, and toxicological data, in order to provide insights and inspiration for future research, promote further development, and facilitate the rational application of C. inerme. Nearly 95 chemical constituents belonging to different classes have been isolated from C. inerme , including diterpenoids, triterpenoids, steroids, flavonoids, phenolic glycosides, lignans, iridoid and megastigmane glycosides. Notably, diterpenoids, triterpenoids, steroids, and flavonoids are the main bioactive substances that have been extensively studied and demonstrated the most significant bioactivity. Pharmacological studies demonstrated that the extract of C. inerme exhibits a wide range of biological activities, such as antioxidant, antimicrobial, anticancer, antiinflammatory, insecticidal, antifeedant, neuroprotective, anti-motor tic, and so on, which are closely connected to its numerous ethnomedicinal applications. Nevertheless, some literature have reported the toxicity of C. inerme . Therefore, it is imperative to conduct further in-depth studies encompassing toxicology, as well as preclinical and clinical research, to ascertain the safety and efficacy of C. inerme for medicinal purposes. Graphical abstract

Background The recent discovery of emerging relapsing fever group Borrelia (RFGB) species, such as Borrelia miyamotoi, poses a growing threat to public health. However, the global distribution and associated risk burden of these species remain uncertain. We aimed to map the diversity, distribution, and potential infection risk of RFGB.MethodsWe searched PubMed, Web of Science, GenBank, CNKI, and eLibrary from Jan 1, 1874, to Dec 31, 2022, for published articles without language restriction to extract distribution data for RFGB detection in vectors, animals, and humans, and clinical information about human patients. Only articles documenting RFGB infection events were included in this study, and data for RFGB detection in vectors, animals, or humans were composed into a dataset. We used three machine learning algorithms (boosted regression trees, random forest, and least absolute shrinkage and selection operator logistic regression) to assess the environmental, ecoclimatic, biological, and socioeconomic factors associated with the occurrence of four major RFGB species: Borrelia miyamotoi, Borrelia lonestari, Borrelia crocidurae, and Borrelia hermsii; and mapped their worldwide risk level.FindingsWe retrieved 13 959 unique studies, among which 697 met the selection criteria and were used for data extraction. 29 RFGB species have been recorded worldwide, of which 27 have been identified from 63 tick species, 12 from 61 wild animals, and ten from domestic animals. 16 RFGB species caused human infection, with a cumulative count of 26 583 cases reported from Jan 1, 1874, to Dec 31, 2022. Borrelia recurrentis (17 084 cases) and Borrelia persica (2045 cases) accounted for the highest proportion of human infection. B miyamotoi showed the widest distribution among all RFGB, with a predicted environmentally suitable area of 6·92 million km2, followed by B lonestari (1·69 million km2), B crocidurae (1·67 million km2), and B hermsii (1·48 million km2). The habitat suitability index of vector ticks and climatic factors, such as the annual mean temperature, have the most significant effect among all predictive models for the geographical distribution of the four major RFGB species.InterpretationThe predicted high-risk regions are considerably larger than in previous reports. Identification, surveillance, and diagnosis of RFGB infections should be prioritised in high-risk areas, especially within low-income regions.FundingNational Key Research and Development Program of China.