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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.

Ramírez-Barahona, S. 2024. Incorporating fossils into the joint inference of phylogeny and biogeography of the tree fern order Cyatheales R. Warnock, and M. Zelditch [eds.],. Evolution. https://doi.org/10.1093/evolut/qpae034

Present-day geographic and phylogenetic patterns often reflect the geological and climatic history of the planet. Neontological distribution data are often sufficient to unravel a lineage’s biogeographic history, yet ancestral range inferences can be at odds with fossil evidence. Here, I use the fossilized birth–death process and the dispersal–extinction cladogenesis model to jointly infer the dated phylogeny and range evolution of the tree fern order Cyatheales. I use data for 101 fossil and 442 extant tree ferns to reconstruct the biogeographic history of the group over the last 220 million years. Fossil-aware reconstructions evince a prolonged occupancy of Laurasia over the Triassic–Cretaceous by Cyathealean tree ferns, which is evident in the fossil record but hidden from analyses relying on neontological data alone. Nonetheless, fossil-aware reconstructions are affected by uncertainty in fossils’ phylogenetic placement, taphonomic biases, and specimen sampling and are sensitive to interpretation of paleodistributions and how these are scored. The present results highlight the need and challenges of incorporating fossils into joint inferences of phylogeny and biogeography to improve the reliability of ancestral geographic range estimation.

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.

Karimi, N., and M. M. Hanes. 2024. Patterns of Grewia (Malvaceae) diversity across geographic scales in Africa and Madagascar. Annals of Botany. https://doi.org/10.1093/aob/mcae009

Background and aims Quantifying spatial species richness is useful to describe biodiversity patterns across broad geographic areas, especially in large, poorly known plant groups. We explore patterns and predictors of species richness across Africa in one such group; the paleotropical genus Grewia L. (Malvaceae). Methods Grewia species richness was quantified by extracting herbarium records from GBIF and Tropicos and creating geographic grids at varying spatial scales. We assessed predictors of species richness using spatial regression models with 30 environmental variables. We explored species co-occurrence in Madagascar at finer resolutions using Schoener's index, and compared species’ range sizes and IUCN status among ecoregions. Lastly, we derived a trait matrix for a subset of species found in Madagascar to characterize morphological diversity across space. Key Results Grewia species occur in 50 countries in Africa, with the highest number of species in Madagascar (93, with 80 species endemic). Species richness is highest in Madagascar, with up to 23 Grewia species in a grid cell, followed by coastal Tanzania/Kenya (up to 13 species), and northern South Africa and central Angola (11 species each). Across Africa, higher species richness was predicted by variables related to aridity. In Madagascar, a greater range in environmental variables best predicted species richness, consistent with geographic grid cells of highest species richness occurring near biome/ecoregion transitions. In Madagascar we also observe increasing dissimilarity in species composition with increasing geographic distance. Conclusions The spatial patterns and underlying environmental predictors that we uncover in Grewia represent an important step in our understanding of plant distribution and diversity patterns across Africa. Madagascar boasts nearly twice the Grewia species richness, compared to the second most species-rich country in Africa, which might be explained by complex topography and environmental conditions across small spatial scales.

Rodríguez-Merino, A. 2023. Identifying and Managing Areas under Threat in the Iberian Peninsula: An Invasion Risk Atlas for Non-Native Aquatic Plant Species as a Potential Tool. Plants 12: 3069. https://doi.org/10.3390/plants12173069

Predicting the likelihood that non-native species will be introduced into new areas remains one of conservation’s greatest challenges and, consequently, it is necessary to adopt adequate management measures to mitigate the effects of future biological invasions. At present, not much information is available on the areas in which non-native aquatic plant species could establish themselves in the Iberian Peninsula. Species distribution models were used to predict the potential invasion risk of (1) non-native aquatic plant species already established in the peninsula (32 species) and (2) those with the potential to invade the peninsula (40 species). The results revealed that the Iberian Peninsula contains a number of areas capable of hosting non-native aquatic plant species. Areas under anthropogenic pressure are at the greatest risk of invasion, and the variable most related to invasion risk is temperature. The results of this work were used to create the Invasion Risk Atlas for Alien Aquatic Plants in the Iberian Peninsula, a novel online resource that provides information about the potential distribution of non-native aquatic plant species. The atlas and this article are intended to serve as reference tools for the development of public policies, management regimes, and control strategies aimed at the prevention, mitigation, and eradication of non-native aquatic plant species.

Akinlabi, F. M., M. D. Pirie, and A. A. Oskolski. 2023. Fire, frost, and drought constrain the structural diversity of wood within southern African Erica (Ericaceae). Botanical Journal of the Linnean Society. https://doi.org/10.1093/botlinnean/boad033

Erica comprises ~860 species of evergreen shrubs and trees ranged from Europe to southern Africa and Madagascar. Wood structure of the around 20 European species is well studied, but despite its relevance to adaptation across the wider geographic range, it has not yet been explored across the much greater diversity, particularly of southern African lineages. In this study, we examine wood structure of 28 Erica species from southern Africa. In the African Erica clade, loss of scalariform perforation plates could be driven by increased aridity and seasonality in the mid-Miocene, and its re-gain can represent an adaptation to freezing in the high elevation species E. nubigena. As vessels in Erica are mostly solitary, imperforate tracheary elements probably form a subsidiary conduit network instead of vessel groups. Increase of ray frequency in habitats with a prominent dry and hot season probably facilitates refilling of vessels after embolism caused by water stress. Wider rays are ancestral for the lineage comprising African Erica and the Mediterranean E. australis. The negative correlation between ray width and expression of summer drought is consistent with Ojeda’s model explaining the diversification of seeders and resprouters among southern African Erica.

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.

Clemente, K. J. E., and M. S. Thomsen. 2023. High temperature frequently increases facilitation between aquatic foundation species: a global meta‐analysis of interaction experiments between angiosperms, seaweeds, and bivalves. Journal of Ecology. https://doi.org/10.1111/1365-2745.14101

Many studies have quantified ecological impacts of individual foundation species (FS). However, emerging data suggest that FS often co‐occur, potentially inhibiting or facilitating one another, thereby causing indirect, cascading effects on surrounding communities. Furthermore, global warming is accelerating, but little is known about how interactions between co‐occurring FS vary with temperature.Shallow aquatic sedimentary systems are often dominated by three types of FS: slower‐growing clonal angiosperms, faster‐growing solitary seaweeds, and shell‐forming filter‐ and deposit‐feeding bivalves. Here, we tested the impacts of one FS on another by analyzing manipulative interaction experiments from 148 papers with a global meta‐analysis.We calculated 1,942 (non‐independent) Hedges’ g effect sizes, from 11,652 extracted values over performance responses, such as abundances, growths or survival of FS, and their associated standard deviations and replication levels. Standard aggregation procedures generated 511 independent Hedges’ g that was classified into six types of reciprocal impacts between FS.We found that (i) seaweeds had consistent negative impacts on angiosperms across performance responses, organismal sizes, experimental approaches, and ecosystem types; (ii) angiosperms and bivalves generally had positive impacts on each other (e.g., positive effects of angiosperms on bivalves were consistent across organismal sizes and experimental approaches, but angiosperm effect on bivalve growth and bivalve effect on angiosperm abundance were not significant); (iii) bivalves positively affected seaweeds (particularly on growth responses); (iv) there were generally no net effects of seaweeds on bivalves (except for positive effect on growth) or angiosperms on seaweeds (except for positive effect on ‘other processes’); and (v) bivalve interactions with other FS were typically more positive at higher temperatures, but angiosperm‐seaweed interactions were not moderated by temperature.Synthesis: Despite variations in experimental and spatiotemporal conditions, the stronger positive interactions at higher temperatures suggest that facilitation, particularly involving bivalves, may become more important in a future warmer world. Importantly, addressing research gaps, such as the scarcity of FS interaction experiments from tropical and freshwater systems and for less studied species, as well as testing for density‐dependent effects, could better inform aquatic ecosystem conservation and restoration efforts and broaden our knowledge of FS interactions in the Anthropocene.

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.

Kroonen, G., A. Jakob, A. I. Palmér, P. van Sluis, and A. Wigman. 2022. Indo-European cereal terminology suggests a Northwest Pontic homeland for the core Indo-European languages S. Wichmann [ed.],. PLOS ONE 17: e0275744. https://doi.org/10.1371/journal.pone.0275744

Questions on the timing and the center of the Indo-European language dispersal are central to debates on the formation of the European and Asian linguistic landscapes and are deeply intertwined with questions on the archaeology and population history of these continents. Recent palaeogenomic studies support scenarios in which the core Indo-European languages spread with the expansion of Early Bronze Age Yamnaya herders that originally inhabited the East European steppes. Questions on the Yamnaya and Pre-Yamnaya locations of the language community that ultimately gave rise to the Indo-European language family are heavily dependent on linguistic reconstruction of the subsistence of Proto-Indo-European speakers. A central question, therefore, is how important the role of agriculture was among the speakers of this protolanguage. In this study, we perform a qualitative etymological analysis of all previously postulated Proto-Indo-European terminology related to cereal cultivation and cereal processing. On the basis of the evolution of the subsistence strategies of consecutive stages of the protolanguage, we find that one or perhaps two cereal terms can be reconstructed for the basal Indo-European stage, also known as Indo-Anatolian, but that core Indo-European, here also including Tocharian, acquired a more elaborate set of terms. Thus, we linguistically document an important economic shift from a mostly non-agricultural to a mixed agro-pastoral economy between the basal and core Indo-European speech communities. It follows that the early, eastern Yamnaya of the Don-Volga steppe, with its lack of evidence for agricultural practices, does not offer a perfect archaeological proxy for the core Indo-European language community and that this stage of the language family more likely reflects a mixed subsistence as proposed for western Yamnaya groups around or to the west of the Dnieper River.