Ciencia habilitada por datos de especímenes

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.

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.

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.

Zhao, Z., X. Feng, Y. Zhang, Y. Wang, and Z. Zhou. 2023. Species richness, endemism, and conservation of wild Rhododendron in China. Global Ecology and Conservation 41: e02375. https://doi.org/10.1016/j.gecco.2023.e02375

This study aimed to identify the main factors driving species richness and endemism patterns of Chinese wild Rhododendron as well as to assess the hotspots of species diversity and their conservation status. We initially mapped the species richness and endemism (expressed by weighted endemism) patterns of 546 wild Rhododendron in China in 100 × 100 km grids using 13,969 occurrence records. Subsequently, the effects of environmental variables on species richness and endemism patterns were assessed using regression models, and hotspots were identified based on the areas overlapping in 10% of the grids with the highest species richness and endemism. Finally, the conservation status of the hotspots was evaluated via gap analysis. The key environmental variables affecting species richness and endemism patterns differed. Species richness patterns were significantly influenced by moisture index, whereas endemism patterns were significantly influenced by elevation range. Moreover, the following five species diversity hotspots were identified: southern Xizang, Hengduan Mountains, south-central Sichuan, eastern Yungui Plateau, and central Gansu; however, these hotspots are not fully covered by the existing nature reserves. Our results indicate that the establishment of nature reserves should be actively promoted to effectively protect wild Rhododendron in hotspots with a conservation gap.

Zhang, X., X. Ci, J. Hu, Y. Bai, A. H. Thornhill, J. G. Conran, and J. Li. 2022. Riparian areas as a conservation priority under climate change. Science of The Total Environment: 159879. https://doi.org/10.1016/j.scitotenv.2022.159879

Identifying climatic refugia is important for long-term conservation planning under climate change. Riparian areas have the potential to provide climatic refugia for wildlife, but literature remains limited, especially for plants. This study was conducted with the purpose of identifying climatic refugia of plant biodiversity in the portion of the Mekong River Basin located in Xishuangbanna, China. We first predicted the current and future (2050s and 2070s) potential distribution of 50 threatened woody species in Xishuangbanna by using an ensemble of small models, then stacked the predictions for individual species to derive spatial biodiversity patterns within each 10 × 10 km grid cell. We then identified the top 17 % of the areas for spatial biodiversity patterns as biodiversity hotspots, with climatic refugia defined as areas that remained as biodiversity hotspots over time. Stepwise regression and linear correlation were applied to analyze the environmental correlations with spatial biodiversity patterns and the relationships between climatic refugia and river distribution, respectively. Our results showed potential upward and northward shifts in threatened woody species, with range contractions and expansions predicted. The spatial biodiversity patterns shift from southeast to northwest, and were influenced by temperature, precipitation, and elevation heterogeneity. Climatic refugia under climate change were related closely to river distribution in Xishuangbanna, with riparian areas identified that could provide climatic refugia. These refugial zones are recommended as priority conservation areas for mitigating the impacts of climate change on biodiversity. Our study confirmed that riparian areas could act as climatic refugia for plants and emphasizes the conservation prioritization of riparian areas within river basins for protecting biodiversity under climate change.

Yang, J., Q. Xiang, and X. Zhang. 2022. Uncovering the hidden diversity of the rosette‐forming Selaginella tamariscina group based on morphological and molecular data. TAXON. https://doi.org/10.1002/tax.12817

Plants of the Selaginella tamariscina group are common rosette‐forming species showing great morphological variability across their distribution range. Integrating chloroplast genome data and morphological evidence, we studied the species delimitation within this group. We newly sequenced the complete chloroplast genomes of 53 individuals representing almost the entire geographical distribution of this group. Our phylogenetic analyses yielded a consistent topology dividing the S. tamariscina group into five major clades, which is further supported by principal component analysis of 18 morphological characters taken from 80 herbarium specimens. Based on the results of molecular analyses and morphological studies combined with the distribution information, we finally recognize five species in the S. tamariscina group, including two new species (S. algida sp. nov., S. graniticola sp. nov.), and one new subspecies (S. pulvinata subsp. qinbashanica subsp. nov.).

Coca‐de‐la‐Iglesia, M., N. G. Medina, J. Wen, and V. Valcárcel. 2022. Evaluation of the tropical‐temperate transitions: An example of climatic characterization in the Asian Palmate group of Araliaceae. American Journal of Botany. https://doi.org/10.1002/ajb2.16059

(no abstract available)

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.

Okamura, Y., A. Sato, L. Kawaguchi, A. J. Nagano, M. Murakami, H. Vogel, and J. Kroymann. 2022. Microevolution of Pieris butterfly genes involved in host plant adaptation along a host plant community cline. Molecular Ecology 31: 3083–3097. https://doi.org/10.1111/mec.16447

Herbivorous insects have evolved counteradaptations to overcome the chemical defenses of their host plants. Several of these counteradaptations have been elucidated at the molecular level, in particular for insects specialized on cruciferous host plants. While the importance of these counteradaptations for host plant colonization is well established, little is known about their microevolutionary dynamics in the field. In particular, it is not known whether and how host plant diversity shapes diversity in insect counteradaptations. In this study, we examine patterns of host plant use and insect counteradaptation in three Pieris butterfly species across Japan. The larvae of these butterflies express nitrile‐specifier protein (NSP) and its paralog major allergen (MA) in their gut to overcome the highly diversified glucosinolate‐myrosinase defense system of their cruciferous host plants. Pieris napi and Pieris melete colonize wild Brassicaceae whereas Pieris rapae typically uses cultivated Brassica as a host, regardless of the local composition of wild crucifers. As expected, NSP and MA diversity was independent of the local composition of wild Brassicaceae in P. rapae. In contrast, NSP diversity correlated with local host plant diversity in both species that preferred wild Brassicaceae. P. melete and P. napi both revealed two distinct major NSP alleles, which shaped diversity among local populations, albeit with different evolutionary trajectories. In comparison, MA showed no indication for local adaptation. Altogether, MA appeared to be evolutionary more conserved than NSP, suggesting that both genes play different roles in diverting host plant chemical defense.

Pant, V., C. Patwardhan, K. Patil, A. R. Bhowmick, A. Mukherjee, and A. K. Banerjee. 2021. ILORA: A database of alien vascular flora of India. Ecological Solutions and Evidence 2. https://doi.org/10.1002/2688-8319.12105

Biological invasions pose an unprecedented threat to biodiversity and ecosystems at different spatial scales, especially for a biodiversity‐rich developing nation like India. While country‐level checklists of alien taxa are important, databases having their biological and ecological attributes are of paramount importance for facilitating research activities and developing policy interventions. Such a comprehensive database for alien flora is lacking in India.We have curated data for 14 variables related to ecology, biogeography, introduction pathway, socio‐economy and distribution of 1747 alien vascular plant species from 22 national and global sources to produce the Indian Alien Flora Information (ILORA) version 1.0 database. This paper describes the detailed methodology of curating these data along with the rationale behind selecting these variables.The database, the first of its kind for the Indian alien flora, will provide easy access to high‐quality data and offer a ready reference to comprehend the existing scenario of alien plant species in the country. The database is dynamic and will be updated regularly. It has a provision to incorporate user‐submitted data, which will allow increasing the resolution of the database as well as the expansion of its capacity.The database is envisaged to become a nationwide collaborative platform for a wide spectrum of stakeholders. It is freely accessible via an online data repository as well as through a dedicated website (https://ilora2020.wixsite.com/ilora2020).