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Serra‐Diaz, J. M., J. Borderieux, B. Maitner, C. C. F. Boonman, D. Park, W. Guo, A. Callebaut, et al. 2024. occTest: An integrated approach for quality control of species occurrence data. Global Ecology and Biogeography. https://doi.org/10.1111/geb.13847

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.

Anest, A., Y. Bouchenak-Khelladi, T. Charles-Dominique, F. Forest, Y. Caraglio, G. P. Hempson, O. Maurin, and K. W. Tomlinson. 2024. Blocking then stinging as a case of two-step evolution of defensive cage architectures in herbivore-driven ecosystems. Nature Plants. https://doi.org/10.1038/s41477-024-01649-4

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

Ract, C., N. D. Burgess, L. Dinesen, P. Sumbi, I. Malugu, J. Latham, L. Anderson, et al. 2024. Nature Forest Reserves in Tanzania and their importance for conservation S. S. Romanach [ed.],. PLOS ONE 19: e0281408. https://doi.org/10.1371/journal.pone.0281408

Since 1997 Tanzania has undertaken a process to identify and declare a network of Nature Forest Reserves (NFRs) with high biodiversity values, from within its existing portfolio of national Forest Reserves, with 16 new NFRs declared since 2015. The current network of 22 gazetted NFRs covered 948,871 hectares in 2023. NFRs now cover a range of Tanzanian habitat types, including all main forest types—wet, seasonal, and dry—as well as wetlands and grasslands. NFRs contain at least 178 of Tanzania’s 242 endemic vertebrate species, of which at least 50% are threatened with extinction, and 553 Tanzanian endemic plant taxa (species, subspecies, and varieties), of which at least 50% are threatened. NFRs also support 41 single-site endemic vertebrate species and 76 single-site endemic plant taxa. Time series analysis of management effectiveness tracking tool (METT) data shows that NFR management effectiveness is increasing, especially where donor funds have been available. Improved management and investment have resulted in measurable reductions of some critical threats in NFRs. Still, ongoing challenges remain to fully contain issues of illegal logging, charcoal production, firewood, pole-cutting, illegal hunting and snaring of birds and mammals, fire, wildlife trade, and the unpredictable impacts of climate change. Increased tourism, diversified revenue generation and investment schemes, involving communities in management, and stepping up control measures for remaining threats are all required to create a network of economically self-sustaining NFRs able to conserve critical biodiversity values.

Maurin, O., A. Anest, F. Forest, I. Turner, R. L. Barrett, R. C. Cowan, L. Wang, et al. 2023. Drift in the tropics: Phylogenetics and biogeographical patterns in Combretaceae. Global Ecology and Biogeography. https://doi.org/10.1111/geb.13737

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

Hill, A., M. F. T. Jiménez, N. Chazot, C. Cássia‐Silva, S. Faurby, L. Herrera‐Alsina, and C. D. Bacon. 2023. Apparent effect of range size and fruit colour on palm diversification may be spurious. Journal of Biogeography. https://doi.org/10.1111/jbi.14683

Aim Fruit selection by animal dispersers with different mobility directly impacts plant geographical range size, which, in turn, may impact plant diversification. Here, we examine the interaction between fruit colour, range size and diversification rate in palms by testing two hypotheses: (1) species with fruit colours attractive to birds have larger range sizes due to high dispersal ability and (2) disperser mobility affects whether small or large range size has higher diversification, and intermediate range size is expected to lead to the highest diversification rate regardless of disperser. Location Global. Time Period Contemporary (or present). Major Taxa Studied Palms (Arecaceae). Methods Palm species were grouped based on likely animal disperser group for given fruit colours. Range sizes were estimated by constructing alpha convex hull polygons from distribution data. We examined disperser group, range size or an interaction of both as possible drivers of change in diversification rate over time in a likelihood dynamic model (Several Examined State-dependent Speciation and Extinction [SecSSE]). Models were fitted, rate estimates were retrieved and likelihoods were compared to those of appropriate null models. Results Species with fruit colours associated with mammal dispersal had larger ranges than those with colours associated with bird dispersal. The best fitting SecSSE models indicated that the examined traits were not the primary driver of the heterogeneity in diversification rates in the model. Extinction rate complexity had a marked impact on model performance and on diversification rates. Main Conclusions Two traits related to dispersal mobility, range size and fruit colour, were not identified as the main drivers of diversification in palms. Increased model extinction rate complexity led to better performing models, which indicates that net diversification should be estimated rather than speciation alone. However, increased complexity may lead to incorrect SecSSE model conclusions without careful consideration. Finally, we find palms with more mobile dispersers do not have larger range sizes, meaning other factors are more important determinants of range size.

Richard-Bollans, A., C. Aitken, A. Antonelli, C. Bitencourt, D. Goyder, E. Lucas, I. Ondo, et al. 2023. Machine learning enhances prediction of plants as potential sources of antimalarials. Frontiers in Plant Science 14. https://doi.org/10.3389/fpls.2023.1173328

Plants are a rich source of bioactive compounds and a number of plant-derived antiplasmodial compounds have been developed into pharmaceutical drugs for the prevention and treatment of malaria, a major public health challenge. However, identifying plants with antiplasmodial potential can be time-consuming and costly. One approach for selecting plants to investigate is based on ethnobotanical knowledge which, though having provided some major successes, is restricted to a relatively small group of plant species. Machine learning, incorporating ethnobotanical and plant trait data, provides a promising approach to improve the identification of antiplasmodial plants and accelerate the search for new plant-derived antiplasmodial compounds. In this paper we present a novel dataset on antiplasmodial activity for three flowering plant families – Apocynaceae, Loganiaceae and Rubiaceae (together comprising c. 21,100 species) – and demonstrate the ability of machine learning algorithms to predict the antiplasmodial potential of plant species. We evaluate the predictive capability of a variety of algorithms – Support Vector Machines, Logistic Regression, Gradient Boosted Trees and Bayesian Neural Networks – and compare these to two ethnobotanical selection approaches – based on usage as an antimalarial and general usage as a medicine. We evaluate the approaches using the given data and when the given samples are reweighted to correct for sampling biases. In both evaluation settings each of the machine learning models have a higher precision than the ethnobotanical approaches. In the bias-corrected scenario, the Support Vector classifier performs best – attaining a mean precision of 0.67 compared to the best performing ethnobotanical approach with a mean precision of 0.46. We also use the bias correction method and the Support Vector classifier to estimate the potential of plants to provide novel antiplasmodial compounds. We estimate that 7677 species in Apocynaceae, Loganiaceae and Rubiaceae warrant further investigation and that at least 1300 active antiplasmodial species are highly unlikely to be investigated by conventional approaches. While traditional and Indigenous knowledge remains vital to our understanding of people-plant relationships and an invaluable source of information, these results indicate a vast and relatively untapped source in the search for new plant-derived antiplasmodial compounds.

Reichgelt, T., A. Baumgartner, R. Feng, and D. A. Willard. 2023. Poleward amplification, seasonal rainfall and forest heterogeneity in the Miocene of the eastern USA. Global and Planetary Change 222: 104073. https://doi.org/10.1016/j.gloplacha.2023.104073

Paleoclimate reconstructions can provide a window into the environmental conditions in Earth history when atmospheric carbon dioxide concentrations were higher than today. In the eastern USA, paleoclimate reconstructions are sparse, because terrestrial sedimentary deposits are rare. Despite this, the eastern USA has the largest population and population density in North America, and understanding the effects of current and future climate change is of vital importance. Here, we provide terrestrial paleoclimate reconstructions of the eastern USA from Miocene fossil floras. Additionally, we compare proxy paleoclimate reconstructions from the warmest period in the Miocene, the Miocene Climatic Optimum (MCO), to those of an MCO Earth System Model. Reconstructed Miocene temperatures and precipitation north of 35°N are higher than modern. In contrast, south of 35°N, temperatures and precipitation are similar to today, suggesting a poleward amplification effect in eastern North America. Reconstructed Miocene rainfall seasonality was predominantly higher than modern, regardless of latitude, indicating greater variability in intra-annual moisture transport. Reconstructed climates are almost uniformly in the temperate seasonal forest biome, but heterogeneity of specific forest types is evident. Reconstructed Miocene terrestrial temperatures from the eastern USA are lower than modeled temperatures and coeval Atlantic sea surface temperatures. However, reconstructed rainfall is consistent with modeled rainfall. Our results show that during the Miocene, climate was most different from modern in the northeastern states, and may suggest a drastic reduction in the meridional temperature gradient along the North American east coast compared to today.

Simons, D., L. A. Attfield, K. E. Jones, D. Watson-Jones, and R. Kock. 2023. Rodent trapping studies as an overlooked information source for understanding endemic and novel zoonotic spillover R. A. Bowen [ed.],. PLOS Neglected Tropical Diseases 17: e0010772. https://doi.org/10.1371/journal.pntd.0010772

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.

Tapondjou Nkonmeneck, W. P., K. E. Allen, P. M. Hime, K. N. Knipp, M. M. Kameni, A. M. Tchassem, L. N. Gonwouo, and R. M. Brown. 2022. Diversification and historical demography of Rhampholeon spectrum in West-Central Africa N. Dahanukar [ed.],. PLOS ONE 17: e0277107. https://doi.org/10.1371/journal.pone.0277107

Pygmy Chameleons of the genus Rhampholeon represent a moderately diverse, geographically circumscribed radiation, with most species (18 out of 19 extant taxa) limited to East Africa. The one exception is Rhampholeon spectrum, a species restricted to West-Central African rainforests. We set out to characterize the geographic basis of genetic variation in this disjunctly distributed Rhampholeon species using a combination of multilocus Sanger data and genomic sequences to explore population structure and range-wide phylogeographic patterns. We also employed demographic analyses and niche modeling to distinguish between alternate explanations to contextualize the impact of past geological and climatic events on the present-day distribution of intraspecific genetic variation. Phylogenetic analyses suggest that R. spectrum is a complex of five geographically delimited populations grouped into two major clades (montane vs. lowland). We found pronounced population structure suggesting that divergence and, potentially, speciation began between the late Miocene and the Pleistocene. Sea level changes during the Pleistocene climatic oscillations resulted in allopatric divergence associated with dispersal over an ocean channel barrier and colonization of Bioko Island. Demographic inferences and range stability mapping each support diversification models with secondary contact due to population contraction in lowland and montane refugia during the interglacial period. Allopatric divergence, congruent with isolation caused by geologic uplift of the East African rift system, the “descent into the Icehouse,” and aridification of sub-Saharan Africa during the Eocene-Oligocene are identified as the key events explaining the population divergence between R. spectrum and its closely related sister clade from the Eastern Arc Mountains. Our results unveil cryptic genetic diversity in R. spectrum, suggesting the possibility of a species complex distributed across the Lower Guinean Forest and the Island of Bioko. We highlight the major element of species diversification that modelled today’s diversity and distributions in most West-Central African vertebrates.

Moreno, I., J. M. W. Gippet, L. Fumagalli, and P. J. Stephenson. 2022. Factors affecting the availability of data on East African wildlife: the monitoring needs of conservationists are not being met. Biodiversity and Conservation. https://doi.org/10.1007/s10531-022-02497-4

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.