Science Enabled by Specimen Data
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.
Aguirre‐Liguori, J. A., A. Morales‐Cruz, and B. S. Gaut. 2022. Evaluating the persistence and utility of five wild Vitis species in the context of climate change. Molecular Ecology. https://doi.org/10.1111/mec.16715
Crop wild relatives (CWRs) have the capacity to contribute novel traits to agriculture. Given climate change, these contributions may be especially vital for the persistence of perennial crops, because perennials are often clonally propagated and consequently do not evolve rapidly. By studying the landscape genomics of samples from five Vitis CWRs (V. arizonica, V. mustangensis, V. riparia, V. berlandieri and V. girdiana) in the context of projected climate change, we addressed two goals. The first was to assess the relative potential of different CWR accessions to persist in the face of climate change. By integrating species distribution models with adaptive genetic variation, additional genetic features such as genomic load and a phenotype (resistance to Pierce’s Disease), we predicted that accessions from one species (V. mustangensis) are particularly well‐suited to persist in future climates. The second goal was to identify which CWR accessions may contribute to bioclimatic adaptation for grapevine (V. vinifera) cultivation. To do so, we evaluated whether CWR accessions have the allelic capacity to persist if moved to locations where grapevines (V. vinifera) are cultivated in the United States. We identified six candidates from V. mustangensis and hypothesized that they may prove useful for contributing alleles that can mitigate climate impacts on viticulture. By identifying candidate germplasm, this work takes a conceptual step toward assessing the genomic and bioclimatic characteristics of CWRs.
Clark, R. P., K.-W. Jiang, and E. Gagnon. 2022. Reinstatement of Ticanto (Leguminosae-Caesalpinioideae) – the final piece in the Caesalpinia group puzzle. PhytoKeys 205: 59–98. https://doi.org/10.3897/phytokeys.205.82300
A recent molecular phylogenetic analysis of the Caesalpinia group demonstrated that it comprises 26 genera, but the recognition of a putative 27th genus, Ticanto, remained in doubt. This study presents a phylogenetic analysis of ITS and five plastid loci revealing a robustly supported monophyletic group representing the Ticanto clade, sister to the morphologically distinct genus Pterolobium. Based upon this evidence, along with a morphological evaluation, the genus Ticanto is here reinstated. Descriptions are provided for all nine species of Ticanto, together with a key to the species, maps, and colour photographs. Nine new combinations are made: Ticantocaesia (Hand.-Mazz.) R. Clark & Gagnon, T.crista (L.) R. Clark & Gagnon, T.elliptifolia (S. J. Li, Z. Y. Chen & D. X. Zhang) R. Clark & Gagnon, T.magnifoliolata (Metcalf) R. Clark & Gagnon, T.rhombifolia R. Clark & Gagnon, T.sinensis (Hemsl.) R. Clark & Gagnon, T.szechuenensis (Craib) R. Clark & Gagnon, T.vernalis (Champion ex Benth.) R. Clark & Gagnon and T.yunnanensis (S. J. Li, D. X. Zhang & Z.Y. Chen) R. Clark & Gagnon. The final major question in the delimitation of segregate genera from within Caesalpiniasensu lato and the Caesalpinia group is thus resolved.
Kullberg, A. T., and K. J. Feeley. 2022. Limited acclimation of leaf traits and leaf temperatures in a subtropical urban heat island S. Pfautsch [ed.],. Tree Physiology. https://doi.org/10.1093/treephys/tpac066
The consequences of rising temperatures for trees will vary between species based on their abilities to acclimate their leaf thermoregulatory traits and photosynthetic thermal tolerances. We tested the hypotheses that adult trees in warmer growing conditions (1) acclimate their thermoregulatory traits to regulate leaf temperatures and (2) acclimate their thermal tolerances such that tolerances are positively correlated with leaf temperature, and that (3) species with broader thermal niche breadths have greater acclimatory abilities. To test these hypotheses, we measured leaf traits and thermal tolerances of seven focal tree species across steep thermal gradients in Miami’s urban heat island. We found that some functional traits varied significantly across air temperatures within species. For example, leaf thickness increased with maximum air temperature in three species, and leaf mass per area and leaf reflectance both increased with air temperature in one species. Only one species was marginally more homeothermic than expected by chance due to acclimation of its thermoregulatory traits, but this acclimation was insufficient to offset elevated air temperatures. Thermal tolerances acclimated to higher maximum air temperatures in two species. As a result of limited acclimation, leaf Thermal Safety Margins (TSMs) were narrower for trees in hotter areas. We found some support for our hypothesis that species with broader thermal niches are better at acclimating in order to maintain more-stable TSMs across the temperature gradients. These findings suggest that trees have limited abilities to acclimate to high temperatures and that thermal niche specialists may be at a heightened risk of thermal stress as global temperatures continue to rise.
Ramirez-Villegas, J., C. K. Khoury, H. A. Achicanoy, M. V. Diaz, A. C. Mendez, C. C. Sosa, Z. Kehel, et al. 2022. State of ex situ conservation of landrace groups of 25 major crops. Nature Plants 8: 491–499. https://doi.org/10.1038/s41477-022-01144-8
Crop landraces have unique local agroecological and societal functions and offer important genetic resources for plant breeding. Recognition of the value of landrace diversity and concern about its erosion on farms have led to sustained efforts to establish ex situ collections worldwide. The degree to which these efforts have succeeded in conserving landraces has not been comprehensively assessed. Here we modelled the potential distributions of eco-geographically distinguishable groups of landraces of 25 cereal, pulse and starchy root/tuber/fruit crops within their geographic regions of diversity. We then analysed the extent to which these landrace groups are represented in genebank collections, using geographic and ecological coverage metrics as a proxy for genetic diversity. We find that ex situ conservation of landrace groups is currently moderately comprehensive on average, with substantial variation among crops; a mean of 63% ± 12.6% of distributions is currently represented in genebanks. Breadfruit, bananas and plantains, lentils, common beans, chickpeas, barley and bread wheat landrace groups are among the most fully represented, whereas the largest conservation gaps persist for pearl millet, yams, finger millet, groundnut, potatoes and peas. Geographic regions prioritized for further collection of landrace groups for ex situ conservation include South Asia, the Mediterranean and West Asia, Mesoamerica, sub-Saharan Africa, the Andean mountains of South America and Central to East Asia. With further progress to fill these gaps, a high degree of representation of landrace group diversity in genebanks is feasible globally, thus fulfilling international targets for their ex situ conservation. By analysing the state of representation of traditional varieties of 25 major crops in ex situ repositories, this study demonstrates conservation progress made over more than a half-century and identifies the gaps remaining to be filled.
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.
Colli-Silva, M., J. R. Pirani, and A. Zizka. 2022. Ecological niche models and point distribution data reveal a differential coverage of the cacao relatives (Malvaceae) in South American protected areas. Ecological Informatics 69: 101668. https://doi.org/10.1016/j.ecoinf.2022.101668
For many regions, such as in South America, it is unclear how well the existent protected areas network (PAs) covers different taxonomic groups and if there is a coverage bias of PAs towards certain biomes or species. Publicly available occurrence data along with ecological niche models might help to overcome this gap and to quantify the coverage of taxa by PAs ensuring an unbiased distribution of conservation effort. Here, we use an occurrence database of 271 species from the cacao family (Malvaceae) to address how South American PAs cover species with different distribution, abundance, and threat status. Furthermore, we compared the performance of online databases, expert knowledge, and modelled species distributions in estimating species coverage in PAs. We found 79 species from our survey (29% of the total) lack any record inside South American PAs and that 20 out of 23 species potentially threatened with extinction are not covered by PAs. The area covered by South American PAs was low across biomes, except for Amazonia, which had a relative high PA coverage, but little information on species distribution within PA available. Also, raw geo-referenced occurrence data were underestimating the number of species in PAs, and projections from ecological niche models were more prone to overestimating the number of species represented within PAs. We discuss that the protection of South American flora in heterogeneous environments demand for specific strategies tailored to particular biomes, including making new collections inside PAs in less collected areas, and the delimitation of more areas for protection in more known areas. Also, by presenting biasing scenarios of collection effort in a representative plant group, our results can benefit policy makers in conserving different spots of tropical environments highly biodiverse.
Chevalier, M. 2022. &lt;i&gt;crestr&lt;/i&gt;: an R package to perform probabilistic climate reconstructions from palaeoecological datasets. Climate of the Past 18: 821–844. https://doi.org/10.5194/cp-18-821-2022
Abstract. Statistical climate reconstruction techniques are fundamental tools to study past climate variability from fossil proxy data. In particular, the methods based on probability density functions (or PDFs) can be used in various environments and with different climate proxies because they rely on elementary calibration data (i.e. modern geolocalised presence data). However, the difficulty of accessing and curating these calibration data and the complexity of interpreting probabilistic results have often limited their use in palaeoclimatological studies. Here, I introduce a new R package (crestr) to apply the PDF-based method CREST (Climate REconstruction SofTware) on diverse palaeoecological datasets and address these problems. crestr includes a globally curated calibration dataset for six common climate proxies (i.e. plants, beetles, chironomids, rodents, foraminifera, and dinoflagellate cysts) associated with an extensive range of climate variables (20 terrestrial and 19 marine variables) that enables its use in most terrestrial and marine environments. Private data collections can also be used instead of, or in combination with, the provided calibration dataset. The package includes a suite of graphical diagnostic tools to represent the data at each step of the reconstruction process and provide insights into the effect of the different modelling assumptions and external factors that underlie a reconstruction. With this R package, the CREST method can now be used in a scriptable environment and thus be more easily integrated with existing workflows. It is hoped that crestr will be used to produce the much-needed quantified climate reconstructions from the many regions where they are currently lacking, despite the availability of suitable fossil records. To support this development, the use of the package is illustrated with a step-by-step replication of a 790 000-year-long mean annual temperature reconstruction based on a pollen record from southeastern Africa.