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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.

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.

Xue, T., S. R. Gadagkar, T. P. Albright, X. Yang, J. Li, C. Xia, J. Wu, and S. Yu. 2021. Prioritizing conservation of biodiversity in an alpine region: Distribution pattern and conservation status of seed plants in the Qinghai-Tibetan Plateau. Global Ecology and Conservation 32: e01885. https://doi.org/10.1016/j.gecco.2021.e01885

The Qinghai-Tibetan Plateau (QTP) harbors abundant and diverse plant life owing to its high habitat heterogeneity. However, the distribution pattern of biodiversity hotspots and their conservation status remain unclear. Based on 148,283 high-resolution occurrence coordinates of 13,450 seed plants, w…

Zhang, M., R. Wei, Q. Xiang, A. Ebihara, and X. Zhang. 2021. Integrative taxonomy of the Selaginella helvetica group based on morphological, molecular and ecological data. TAXON 70: 1163–1187. https://doi.org/10.1002/tax.12565

The Eurasian and Mediterranean Selaginella helvetica group is one of the taxonomically challenging groups in the cosmopolitan lycophyte genus Selaginella. Species of the S. helvetica group are all small plants with lax strobili composed of more or less isomorphic sporophylls (isosporophylls) that ar…

Yi, S., C.-P. Jun, K. Jo, H. Lee, M.-S. Kim, S. D. Lee, X. Cao, and J. Lim. 2020. Asynchronous multi-decadal time-scale series of biotic and abiotic responses to precipitation during the last 1300 years. Scientific Reports 10. https://doi.org/10.1038/s41598-020-74994-x

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Chase, B. M., A. Boom, A. S. Carr, M. Chevalier, L. J. Quick, G. A. Verboom, and P. J. Reimer. 2019. Extreme hydroclimate response gradients within the western Cape Floristic region of South Africa since the Last Glacial Maximum. Quaternary Science Reviews 219: 297–307. https://doi.org/10.1016/j.quascirev.2019.07.006

The Cape Floristic Region (CFR) is one of the world's major biodiversity hotspots, and much work has gone into identifying the drivers of this diversity. Considered regionally in the context of Quaternary climate change, climate stability is generally accepted as being one of the major factors promo…

Chevalier, M., B. M. Chase, L. J. Quick, L. M. Dupont, and T. C. Johnson. 2020. Temperature change in subtropical southeastern Africa during the past 790,000 yr. Geology 49: 71–75. https://doi.org/10.1130/G47841.1

Across the glacial-interglacial cycles of the late Pleistocene (~700 k.y.), temperature variability at low latitudes is often considered to have been negligible compared to changes in precipitation. However, a paucity of quantified temperature records makes this difficult to reliably assess. In this…

Margaroni, S., K. B. Petersen, R. Gleadow, and M. Burd. 2019. The role of spore size in the global pattern of co‐occurrence among Selaginella species. Journal of Biogeography 46: 807–815. https://doi.org/10.1111/jbi.13532

Aim: Separation of regeneration niches may promote coexistence among closely related plant species, but there is little evidence that regeneration traits affect species ranges at broad geographical scales. We address patterns of co‐occurrence within the genus Selaginella, an ancient lineage of free‐…

Petersen, K. B., and M. Burd. 2018. The adaptive value of heterospory: Evidence from Selaginella. Evolution 72: 1080–1091. https://doi.org/10.1111/evo.13484

Heterospory was a pivotal evolutionary innovation for land plants, but it has never been clear why it evolved. We used the geographic distributions of 114 species of the heterosporous lycophyte Selaginella to explore the functional ecology of microspore and megaspore size, traits that would be corre…