Science Enabled by Specimen Data
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.
Islomiddinov, Z. Sh., I. M. Mustafaev, J. P. Shirqulova, B. S. Khabibullaev, Y. W. Lim, et al. 2023. The first record of Pisolithus arhizus (Sclerodermataceae, Basidiomycota) in Central Asia. Ukrainian Botanical Journal 80: 337–342. https://doi.org/10.15407/ukrbotj80.04.337
Pisolithus is a genus of gasteroid mycorrhizal symbionts associated with trees of several families of angiosperms and gymnosperms and distributed almost worldwide. Here we report a new record of Pisolithus arhizus from Tashkent, Uzbekistan, the first record of this species in Central Asia. The fruit bodies of P. arhizus were collected in several locations within the city and identified based on morphological characters. The ectomycorrhizal fungus formed symbiotic relationships with Juniperus sp. and Quercus sp. We provide its morphological description and photographs and also discuss our findings in the context of previously known records of this species.
Onditi, K. O., W. Song, X. Li, S. Musila, Z. Chen, Q. Li, J. Mathenge, et al. 2023. Untangling key abiotic predictors of terrestrial mammal diversity patterns across ecoregions and species groups in Kenya. Ecological Indicators 154: 110595. https://doi.org/10.1016/j.ecolind.2023.110595
Understanding the interactions between abiotic (environmental and anthropogenic) factors and species diversity and distribution patterns is fundamental to improving the ecological representativeness of biodiversity management tools such as protected areas (PAs). However, significant knowledge gaps remain about how species’ ecological and evolutionary opportunities are associated with abiotic factors, especially in biodiversity-rich but economically ill-equipped countries such as Kenya. Here, we explored the interactions of terrestrial mammal diversity patterns and abiotic factors across species groups and ecoregions in Kenya. We coupled data on terrestrial mammal occurrences, phylogeny, functional traits, and environmental predictors in Kenya to derive multiple diversity indices, encompassing species richness and phylogenetic and functional richness, and mean pairwise and nearest taxon distances. We explored the interactions of these indices with several abiotic factors using multivariate regression analyses while adjusting for spatial autocorrelation. The results showed weak correlations between species richness versus the phylogenetic and functional diversity indices. The best-fit models explained variable proportions of diversity indices between species groups and ecoregions and consistently retained annual temperature and precipitation averages and seasonality and human footprint as the strongest predictors. Compared to the species-poor xeric northern and eastern Kenya regions, the predictors had weak associations with diversity variances in the species-rich mesic western and central Kenya regions, similar to focal species groups compared to ordinal classifications and the combined species pool. These findings illustrate that climate and human footprint interplay determine multiple facets of terrestrial mammal diversity patterns in Kenya. Accordingly, curbing human activities degrading long-term climatic regimes is vital to ensuring the ecological integrity of terrestrial mammal communities and should be integrated into biodiversity management frameworks. For a holistic representation of critical conservation areas, biodiversity managements should also prioritize terrestrial mammal phylogenetic and functional attributes besides species richness.
Pang, S. E. H., J. W. F. Slik, D. Zurell, and E. L. Webb. 2023. The clustering of spatially associated species unravels patterns in tropical tree species distributions. Ecosphere 14. https://doi.org/10.1002/ecs2.4589
Complex distribution data can be summarized by grouping species with similar or overlapping distributions to unravel spatial patterns and separate trends (e.g., of habitat loss) among spatially unique groups. However, such classifications are often heuristic, lacking the transparency, objectivity, and data‐driven rigor of quantitative methods, which limits their interpretability and utility. Here, we develop and illustrate the clustering of spatially associated species, a methodological framework aimed at statistically classifying species using explicit measures of interspecific spatial association. We investigate several association indices and clustering algorithms and show how these methodological choices drive substantial variations in clustering outcomes and performance. To facilitate robust decision‐making, we provide guidance on choosing methods appropriate to one's study objective(s). As a case study, we apply our framework to modeled tree distributions in Borneo and subsequently evaluate the impact of land‐cover change on separate species groupings. Based on the modeled distribution of 390 tree species prior to anthropogenic land‐cover changes, we identified 11 distinct clusters that unraveled ecologically meaningful patterns in Bornean tree distributions. These clusters then enabled us to quantify trends of habitat loss tied to each of those specific clusters, allowing us to discern particularly vulnerable species clusters and their distributions. This study demonstrates the advantages of adopting quantitatively derived clusters of spatially associated species and elucidates the potential of resultant clusters as a spatially explicit framework for investigating distribution‐related questions in ecology, biogeography, and conservation. By adopting our methodological framework and publicly available codes, practitioners can leverage the ever‐growing abundance of distribution data to better understand complex spatial patterns among species distributions and the disparate effects of global changes on biodiversity.
Huang, T., J. Chen, K. E. Hummer, L. A. Alice, W. Wang, Y. He, S. Yu, et al. 2023. Phylogeny of Rubus (Rosaceae): Integrating molecular and morphological evidence into an infrageneric revision. TAXON. https://doi.org/10.1002/tax.12885
Rubus (Rosaceae), one of the most complicated angiosperm genera, contains about 863 species, and is notorious for its taxonomic difficulty. The most recent (1910–1914) global taxonomic treatment of the genus was conducted by Focke, who defined 12 subgenera. Phylogenetic results over the past 25 years suggest that Focke's subdivisions of Rubus are not monophyletic, and large‐scale taxonomic revisions are necessary. Our objective was to provide a comprehensive phylogenetic analysis of the genus based on an integrative evidence approach. Morphological characters, obtained from our own investigation of living plants and examination of herbarium specimens are combined with chloroplast genomic data. Our dataset comprised 196 accessions representing 145 Rubus species (including cultivars and hybrids) and all of Focke's subgenera, including 60 endemic Chinese species. Maximum likelihood analyses inferred phylogenetic relationships. Our analyses concur with previous molecular studies, but with modifications. Our data strongly support the reclassification of several subgenera within Rubus. Our molecular analyses agree with others that only R. subg. Anoplobatus forms a monophyletic group. Other subgenera are para‐ or polyphyletic. We suggest a revised subgeneric framework to accommodate monophyletic groups. Character evolution is reconstructed, and diagnostic morphological characters for different clades are identified and discussed. Based on morphological and molecular evidence, we propose a new classification system with 10 subgenera: R. subg. Anoplobatus, R. subg. Batothamnus, R. subg. Chamaerubus, R. subg. Cylactis, R. subg. Dalibarda, R. subg. Idaeobatus, R. subg. Lineati, R. subg. Malachobatus, R. subg. Melanobatus, and R. subg. Rubus. The revised infrageneric nomenclature inferred from our analyses is provided along with synonymy and type citations. Our new taxonomic backbone is the first systematic and complete global revision of Rubus since Focke's treatment. It offers new insights into deep phylogenetic relationships of Rubus and has important theoretical and practical significance for the development and utilization of these important agronomic crops.
Campbell, L. C. E., E. T. Kiers, and G. Chomicki. 2022. The evolution of plant cultivation by ants. Trends in Plant Science. https://doi.org/10.1016/j.tplants.2022.09.005
Outside humans, true agriculture was previously thought to be restricted to social insects farming fungus. However, obligate farming of plants by ants was recently discovered in Fiji, prompting a re-examination of plant cultivation by ants. Here, we generate a database of plant cultivation by ants, identify three main types, and show that these interactions evolved primarily for shelter rather than food. We find that plant cultivation evolved at least 65 times independently for crops (~200 plant species), and 15 times in farmer lineages (~37 ant taxa) in the Neotropics and Asia/Australasia. Because of their high evolutionary replication, and variation in partner dependence, these systems are powerful models to unveil the steps in the evolution and ecology of insect agriculture.
Escolástico-Ortiz, D. A., L. Hedenäs, D. Quandt, D. Harpke, J. Larraín, M. Stech, and J. C. Villarreal A. 2022. Cryptic speciation shapes the biogeographic history of a northern distributed moss. Botanical Journal of the Linnean Society. https://doi.org/10.1093/botlinnean/boac027
Abstract Increasing evidence indicates that wide distributed bryophyte taxa with homogeneous morphology may represent separate evolutionary lineages. The evolutionary histories of these cryptic lineages may be related to historical factors, such as the climatic oscillations in the Quaternary. Thus, the post-glacial demographic signatures paired with cryptic speciation may result in complex phylogeographic patterns. This research has two aims: to determine whether the widespread moss Racomitrium lanuginosum represents cryptic molecular taxa across the Northern Hemisphere and to infer the effects of Quaternary glaciations on spatial genetic diversity. We used the internal transcribed spacer (ITS) marker to resolve the phylogeographic history of the species and single nucleotide polymorphisms (genotyping-by-sequencing) to infer the genetic structure and demographic history. Finally, we assessed the historical changes in the distribution range using species distribution models. Racomitrium lanuginosum comprises distinct molecular lineages sympatrically distributed in the Northern Hemisphere. We also uncovered long-distance dispersal from eastern North America to Scandinavia and potential in situ survival in northern Scandinavia. Due to the genetic signatures, the Alaska Peninsula could be considered a glacial refugium. The species experienced post-glacial expansion northwards in the Northern Hemisphere, mainly from the Alaska Peninsula. Our results exemplify the complex phylogeographic history in cold environments and contribute to recognizing evolutionary patterns in the Northern Hemisphere.
Pang, S. E. H., Y. Zeng, J. D. T. Alban, and E. L. Webb. 2022. Occurrence–habitat mismatching and niche truncation when modelling distributions affected by anthropogenic range contractions B. Leroy [ed.],. Diversity and Distributions 28: 1327–1343. https://doi.org/10.1111/ddi.13544
Aims Human-induced pressures such as deforestation cause anthropogenic range contractions (ARCs). Such contractions present dynamic distributions that may engender data misrepresentations within species distribution models. The temporal bias of occurrence data—where occurrences represent distributions before (past bias) or after (recent bias) ARCs—underpins these data misrepresentations. Occurrence–habitat mismatching results when occurrences sampled before contractions are modelled with contemporary anthropogenic variables; niche truncation results when occurrences sampled after contractions are modelled without anthropogenic variables. Our understanding of their independent and interactive effects on model performance remains incomplete but is vital for developing good modelling protocols. Through a virtual ecologist approach, we demonstrate how these data misrepresentations manifest and investigate their effects on model performance. Location Virtual Southeast Asia. Methods Using 100 virtual species, we simulated ARCs with 100-year land-use data and generated temporally biased (past and recent) occurrence datasets. We modelled datasets with and without a contemporary land-use variable (conventional modelling protocols) and with a temporally dynamic land-use variable. We evaluated each model's ability to predict historical and contemporary distributions. Results Greater ARC resulted in greater occurrence–habitat mismatching for datasets with past bias and greater niche truncation for datasets with recent bias. Occurrence–habitat mismatching prevented models with the contemporary land-use variable from predicting anthropogenic-related absences, causing overpredictions of contemporary distributions. Although niche truncation caused underpredictions of historical distributions (environmentally suitable habitats), incorporating the contemporary land-use variable resolved these underpredictions, even when mismatching occurred. Models with the temporally dynamic land-use variable consistently outperformed models without. Main conclusions We showed how these data misrepresentations can degrade model performance, undermining their use for empirical research and conservation science. Given the ubiquity of ARCs, these data misrepresentations are likely inherent to most datasets. Therefore, we present a three-step strategy for handling data misrepresentations: maximize the temporal range of anthropogenic predictors, exclude mismatched occurrences and test for residual data misrepresentations.
Williams, C. J. R., D. J. Lunt, U. Salzmann, T. Reichgelt, G. N. Inglis, D. R. Greenwood, W. Chan, et al. 2022. African Hydroclimate During the Early Eocene From the DeepMIP Simulations. Paleoceanography and Paleoclimatology 37. https://doi.org/10.1029/2022pa004419
The early Eocene (∼56‐48 million years ago) is characterised by high CO2 estimates (1200‐2500 ppmv) and elevated global temperatures (∼10 to 16°C higher than modern). However, the response of the hydrological cycle during the early Eocene is poorly constrained, especially in regions with sparse data coverage (e.g. Africa). Here we present a study of African hydroclimate during the early Eocene, as simulated by an ensemble of state‐of‐the‐art climate models in the Deep‐time Model Intercomparison Project (DeepMIP). A comparison between the DeepMIP pre‐industrial simulations and modern observations suggests that model biases are model‐ and geographically dependent, however these biases are reduced in the model ensemble mean. A comparison between the Eocene simulations and the pre‐industrial suggests that there is no obvious wetting or drying trend as the CO2 increases. The results suggest that changes to the land sea mask (relative to modern) in the models may be responsible for the simulated increases in precipitation to the north of Eocene Africa. There is an increase in precipitation over equatorial and West Africa and associated drying over northern Africa as CO2 rises. There are also important dynamical changes, with evidence that anticyclonic low‐level circulation is replaced by increased south‐westerly flow at high CO2 levels. Lastly, a model‐data comparison using newly‐compiled quantitative climate estimates from palaeobotanical proxy data suggests a marginally better fit with the reconstructions at lower levels of CO2.
Reichgelt, T., D. R. Greenwood, S. Steinig, J. G. Conran, D. K. Hutchinson, D. J. Lunt, L. J. Scriven, and J. Zhu. 2022. Plant Proxy Evidence for High Rainfall and Productivity in the Eocene of Australia. Paleoceanography and Paleoclimatology 37. https://doi.org/10.1029/2022pa004418
During the early to middle Eocene, a mid‐to‐high latitudinal position and enhanced hydrological cycle in Australia would have contributed to a wetter and “greener” Australian continent where today arid to semi‐arid climates dominate. Here, we revisit 12 southern Australian plant megafossil sites from the early to middle Eocene to generate temperature, precipitation and seasonality paleoclimate estimates, net primary productivity (NPP) and vegetation type, based on paleobotanical proxies and compare to early Eocene global climate models. Temperature reconstructions are uniformly subtropical (mean annual, summer, and winter mean temperatures 19–21 °C, 25–27 °C and 14–16 °C, respectively), indicating that southern Australia was ∼5 °C warmer than today, despite a >20° poleward shift from its modern geographic location. Precipitation was less homogeneous than temperature, with mean annual precipitation of ∼60 cm over inland sites and >100 cm over coastal sites. Precipitation may have been seasonal with the driest month receiving 2–7× less than mean monthly precipitation. Proxy‐model comparison is favorable with an 1680 ppm CO2 concentration. However, individual proxy reconstructions can disagree with models as well as with each other. In particular, seasonality reconstructions have systemic offsets. NPP estimates were higher than modern, implying a more homogenously “green” southern Australia in the early to middle Eocene, when this part of Australia was at 48–64 °S, and larger carbon fluxes to and from the Australian biosphere. The most similar modern vegetation type is modern‐day eastern Australian subtropical forest, although distance from coast and latitude may have led to vegetation heterogeneity.