Ciência habilitada por dados de espécimes

Marchuk, E. A., A. K. Kvitchenko, L. A. Kameneva, A. A. Yuferova, and D. E. Kislov. 2024. East Asian forest-steppe outpost in the Khanka Lowland (Russia) and its conservation. Journal of Plant Research 137: 997–1018. https://doi.org/10.1007/s10265-024-01570-z

The Khanka Lowland forest-steppe is the most eastern outpost of the Eurasian steppe biome. It includes unique grassland plant communities with rare steppe species. These coenosis have changed under the influence of anthropogenic activity, especially during the last 100 years and included both typical steppe species and nemoral mesophytic species. To distinguish these ecological groups of plants the random forest method with three datasets of environmental variables was applied. Specifically, a model of classification with the most important bioindices to predict a mesophytic ecological group of plants with a sensitivity greater than 80% was constructed. The data demonstrated the presence of steppe species that arrived at different times in the Primorye Territory. Most of these species are associated with the Mongolian-Daurian relict steppe complex and habit in the Khanka Lowland. Other species occur only in mountains in Primorye Territory and do not persist in the Khanka Lowland. These findings emphasize the presence of relict steppe communities with a complex of true steppe species in the Khanka Lowland. Steppe communities exhibit features of anthropogenic influence definitely through the long land use period but are not anthropogenic in origin. The most steppe species are located at the eastern border of distribution in the Khanka Lowlands and are valuable in terms of conservation and sources of information about steppe species origin and the emergence of the steppe biome as a whole.

Zhang, H., W. Guo, and W. Wang. 2023. The dimensionality reductions of environmental variables have a significant effect on the performance of species distribution models. Ecology and Evolution 13. https://doi.org/10.1002/ece3.10747

How to effectively obtain species‐related low‐dimensional data from massive environmental variables has become an urgent problem for species distribution models (SDMs). In this study, we will explore whether dimensionality reduction on environmental variables can improve the predictive performance of SDMs. We first used two linear (i.e., principal component analysis (PCA) and independent components analysis) and two nonlinear (i.e., kernel principal component analysis (KPCA) and uniform manifold approximation and projection) dimensionality reduction techniques (DRTs) to reduce the dimensionality of high‐dimensional environmental data. Then, we established five SDMs based on the environmental variables of dimensionality reduction for 23 real plant species and nine virtual species, and compared the predictive performance of those with the SDMs based on the selected environmental variables through Pearson's correlation coefficient (PCC). In addition, we studied the effects of DRTs, model complexity, and sample size on the predictive performance of SDMs. The predictive performance of SDMs under DRTs other than KPCA is better than using PCC. And the predictive performance of SDMs using linear DRTs is better than using nonlinear DRTs. In addition, using DRTs to deal with environmental variables has no less impact on the predictive performance of SDMs than model complexity and sample size. When the model complexity is at the complex level, PCA can improve the predictive performance of SDMs the most by 2.55% compared with PCC. At the middle level of sample size, the PCA improved the predictive performance of SDMs by 2.68% compared with the PCC. Our study demonstrates that DRTs have a significant effect on the predictive performance of SDMs. Specifically, linear DRTs, especially PCA, are more effective at improving model predictive performance under relatively complex model complexity or large sample sizes.

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.

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.

Chevalier, M. 2022. <i>crestr</i>: 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.

Sluiter, I. R. K., G. R. Holdgate, T. Reichgelt, D. R. Greenwood, A. P. Kershaw, and N. L. Schultz. 2022. A new perspective on Late Eocene and Oligocene vegetation and paleoclimates of South-eastern Australia. Palaeogeography, Palaeoclimatology, Palaeoecology 596: 110985. https://doi.org/10.1016/j.palaeo.2022.110985

We present a composite terrestrial pollen record of latest Eocene through Oligocene (35.5–23 Ma) vegetation and climate change from the Gippsland Basin of south-eastern Australia. Climates were overwhelmingly mesothermic through this time period, with mean annual temperature (MAT) varying between 13 and 18 °C, with an average of 16 °C. We provide evidence to support a cooling trend through the Eocene–Oligocene Transition (EOT), but also identify three subsequent warming cycles through the Oligocene, leading to more seasonal climates at the termination of the Epoch. One of the warming episodes in the Early Oligocene appears to have also occurred at two other southern hemisphere sites at the Drake Passage as well as off eastern Tasmania, based on recent research. Similarities with sea surface temperature records from modern high southern latitudes which also record similar cycles of warming and cooling, are presented and discussed. Annual precipitation varied between 1200 and 1700 mm/yr, with an average of 1470 mm/yr through the sequence. Notwithstanding the extinction of Nothofagus sg. Brassospora from Australia and some now microthermic humid restricted Podocarpaceae conifer taxa, the rainforest vegetation of lowland south-eastern Australia is reconstructed to have been similar to present day Australian Evergreen Notophyll Vine Forests existing under the sub-tropical Köppen-Geiger climate class Cfa (humid subtropical) for most of the sequence. Short periods of cooler climates, such as occurred through the EOT when MAT was ~ 13 °C, may have supported vegetation similar to modern day Evergreen Microphyll Fern Forest. Of potentially greater significance, however, was a warm period in the Early to early Late Oligocene (32–26 Ma) when MAT was 17–18 °C, accompanied by small but important increases in Araucariaceae pollen. At this time, Araucarian Notophyll/Microphyll Vine Forest likely occurred regionally.

Vasconcelos, T., J. D. Boyko, and J. M. Beaulieu. 2021. Linking mode of seed dispersal and climatic niche evolution in flowering plants. Journal of Biogeography. https://doi.org/10.1111/jbi.14292

Aim: Due to the sessile nature of flowering plants, movements to new geographical areas occur mainly during seed dispersal. Frugivores tend to be efficient dispersers because animals move within the boundaries of their preferable niches, so seeds are more likely to be transported to environments tha…

Christiansen, D. M., L. L. Iversen, J. Ehrlén, and K. Hylander. 2021. Changes in forest structure drive temperature preferences of boreal understorey plant communities. Journal of Ecology 110: 631–643. https://doi.org/10.1111/1365-2745.13825

The local climate in forest understories can deviate substantially from ambient conditions. Moreover, forest microclimates are often characterized by cyclic changes driven by management activities such as clear-cutting and subsequent planting. To understand how and why understorey plant communities …

Alban, D. M., E. M. Biersma, J. W. Kadereit, and M. S. Dillenberger. 2021. Colonization of the Southern Hemisphere by Sagina and Colobanthus (Caryophyllaceae). Plant Systematics and Evolution 308. https://doi.org/10.1007/s00606-021-01793-w

Colobanthus (23 species) and Sagina (30–33 species) together are sister to Facchinia. Whereas Facchinia is distributed in western Eurasia, Colobanthus is almost exclusively distributed in the Southern Hemisphere, and Sagina is distributed in both hemispheres with the highest species diversity in wes…