Science Enabled by Specimen Data

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.

Yim, C., E. S. Bellis, V. L. DeLeo, D. Gamba, R. Muscarella, and J. R. Lasky. 2023. Climate biogeography of Arabidopsis thaliana: Linking distribution models and individual variation. Journal of Biogeography. https://doi.org/10.1111/jbi.14737

Aim Patterns of individual variation are key to testing hypotheses about the mechanisms underlying biogeographic patterns. If species distributions are determined by environmental constraints, then populations near range margins may have reduced performance and be adapted to harsher environments. Model organisms are potentially important systems for biogeographical studies, given the available range‐wide natural history collections, and the importance of providing biogeographical context to their genetic and phenotypic diversity.LocationGlobal.TaxonArabidopsis thaliana (‘Arabidopsis’).MethodsWe fit occurrence records to climate data, and then projected the distribution of Arabidopsis under last glacial maximum, current and future climates. We confronted model predictions with individual performance measured on 2194 herbarium specimens, and we asked whether predicted suitability was associated with life history and genomic variation measured on ~900 natural accessions.ResultsThe most important climate variables constraining the Arabidopsis distribution were winter cold in northern and high elevation regions and summer heat in southern regions. Herbarium specimens from regions with lower habitat suitability in both northern and southern regions were smaller, supporting the hypothesis that the distribution of Arabidopsis is constrained by climate‐associated factors. Climate anomalies partly explained interannual variation in herbarium specimen size, but these did not closely correspond to local limiting factors identified in the distribution model. Late‐flowering genotypes were absent from the lowest suitability regions, suggesting slower life histories are only viable closer to the centre of the realized niche. We identified glacial refugia farther north than previously recognized, as well as refugia concordant with previous population genetic findings. Lower latitude populations, known to be genetically distinct, are most threatened by future climate change. The recently colonized range of Arabidopsis was well‐predicted by our native‐range model applied to certain regions but not others, suggesting it has colonized novel climates.Main ConclusionsIntegration of distribution models with performance data from vast natural history collections is a route forward for testing biogeographical hypotheses about species distributions and their relationship with evolutionary fitness across large scales.

Luza, A. L., A. V. Rodrigues, L. Mamalis, and V. Zulian. 2023. Spatial distribution of the greater rhea, Rhea americana (Linnaeus, 1758), in Rio Grande do Sul, southern Brazil: citizen-science data, probabilistic mapping, and comparison with expert knowledge. Ornithology Research. https://doi.org/10.1007/s43388-023-00143-3

The popularization of citizen-science platforms has increased the amount of data available in a fine spatial and temporal resolution, which can be used to fill distribution knowledge gaps through probabilistic maps. In this study, we gathered expert-based information and used species distribution models to produce two independent maps of the greater rhea ( Rhea americana , Rheiformes, Rheidae) distribution in the state of Rio Grande do Sul, Brazil. We integrated municipality level detection/non-detection data from five citizen-science datasets into a Bayesian site occupancy model, accounting for false negatives, sampling effort, habitat covariates, and spatial autocorrelation. We addressed whether habitat (grassland and crop field cover, number of rural properties) and spatial autocorrelation explains the realized occurrence of the species and compared model-based and expert-based occurrence maps. The mean estimated percentage of occupied municipalities was 48% (239 out of 497 municipalities), whereas experts declared 21% of the municipalities (103) as occupied by the species. While both mapping approaches showed greater rhea presence in most municipalities of the Pampa biome, they disagreed in the majority of the municipalities in the Atlantic Forest, where more fieldwork must be undertaken. The greater rhea distribution was exclusively explained by the spatial autocorrelation component, suggesting that the species expanded its distribution towards the north of the state, reaching the Atlantic Forest, following deforestation and agriculture expansion.

Benson, C. W., M. R. Sheltra, P. J. Maughan, E. N. Jellen, M. D. Robbins, B. S. Bushman, E. L. Patterson, et al. 2023. Homoeologous evolution of the allotetraploid genome of Poa annua L. BMC Genomics 24. https://doi.org/10.1186/s12864-023-09456-5

Background Poa annua (annual bluegrass) is an allotetraploid turfgrass, an agronomically significant weed, and one of the most widely dispersed plant species on earth. Here, we report the chromosome-scale genome assemblies of P. annua’s diploid progenitors, P. infirma and P. supina, and use multi-omic analyses spanning all three species to better understand P. annua’s evolutionary novelty. Results We find that the diploids diverged from their common ancestor 5.5 – 6.3 million years ago and hybridized to form P. annua  ≤ 50,000 years ago. The diploid genomes are similar in chromosome structure and most notably distinguished by the divergent evolutionary histories of their transposable elements, leading to a 1.7 × difference in genome size. In allotetraploid P. annua, we find biased movement of retrotransposons from the larger (A) subgenome to the smaller (B) subgenome. We show that P. annua’s B subgenome is preferentially accumulating genes and that its genes are more highly expressed. Whole-genome resequencing of several additional P. annua accessions revealed large-scale chromosomal rearrangements characterized by extensive TE-downsizing and evidence to support the Genome Balance Hypothesis. Conclusions The divergent evolutions of the diploid progenitors played a central role in conferring onto P. annua its remarkable phenotypic plasticity. We find that plant genes (guided by selection and drift) and transposable elements (mostly guided by host immunity) each respond to polyploidy in unique ways and that P. annua uses whole-genome duplication to purge highly parasitized heterochromatic sequences. The findings and genomic resources presented here will enable the development of homoeolog-specific markers for accelerated weed science and turfgrass breeding .

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.

Kagnew, B., A. Assefa, and A. Degu. 2022. Modeling the Impact of Climate Change on Sustainable Production of Two Legumes Important Economically and for Food Security: Mungbeans and Cowpeas in Ethiopia. Sustainability 15: 600. https://doi.org/10.3390/su15010600

Climate change is one of the most serious threats to global crops production at present and it will continue to be the largest threat in the future worldwide. Knowing how climate change affects crop productivity might help sustainability and crop improvement efforts. Under existing and projected climate change scenarios (2050s and 2070s in Ethiopia), the effect of global warming on the distribution of V. radiata and V. unguiculata was investigated. MaxEnt models were used to predict the current and future distribution pattern changes of these crops in Ethiopia using different climate change scenarios (i.e., lowest (RCP 2.6), moderate (RCP 4.5), and extreme (RCP 8.5)) for the years 2050s and 2070s. The study includes 81 and 68 occurrence points for V. radiata and V. unguiculata, respectively, along with 22 environmental variables. The suitability maps indicate that the Beneshangul Gumuz, Oromia, Amhara, SNNPR, and Tigray regions are the major Ethiopian regions with the potential to produce V. radiata, while Amhara, Gambella, Oromia, SNNPR, and Tigray are suitable for producing V. unguiculata. The model prediction for V. radiata habitat ranges distribution in Ethiopia indicated that 1.69%, 4.27%, 11.25% and 82.79% are estimated to be highly suitable, moderately suitable, less suitable, and unsuitable, respectively. On the other hand, the distribution of V. unguiculata is predicted to have 1.27%, 3.07%, 5.22%, and 90.44% habitat ranges that are highly suitable, moderately suitable, less suitable, and unsuitable, respectively, under the current climate change scenario by the year (2050s and 2070s) in Ethiopia. Among the environmental variables, precipitation of the wettest quarter (Bio16), solar radiation index (SRI), temperature seasonality (Bio4), and precipitation seasonality (Bio15) are discovered to be the most effective factors for defining habitat suitability for V. radiata, while precipitation of the wettest quarter (Bio16), temperature annual range (Bio7) and precipitation of the driest quarter (Bio17) found to be better habitat suitability indicator for V. unguiculata in Ethiopia. The result indicates that these variables were more relevant in predicting suitable habitat for these crops in Ethiopia. A future projection predicts that the suitable distribution region will become increasingly fragmented. In general, the study provides a scientific basis of suitable agro-ecological habitat for V. radiata and V. unguiculata for long-term crop management and production improvement in Ethiopia. Therefore, projections of current and future climate change impacts on such crops are vital to reduce the risk of crop failure and to identify the potential productive areas in the country.

Gómez Díaz, J. A., A. Lira-Noriega, and F. Villalobos. 2023. Expanding protected areas in a Neotropical hotspot. International Journal of Sustainable Development & World Ecology: 1–15. https://doi.org/10.1080/13504509.2022.2163717

The region of central Veracruz is considered a biodiversity hotspot due to its high species richness and environmental heterogeneity, but only 2% of this region is currently protected. This study aimed to assess the current protected area system’s effectiveness and to identify priority conservation areas for expanding the existing protected area system. We used the distribution models of 1186 species from three kingdoms (Animalia, Plantae, and Fungi) together with ZONATION software, a conservation planning tool, to determine areas that could help expand the current network of protected areas. We applied three different parametrizations (including only species, using the boundary quality penalty, and using corridor connectivity). We found that protecting an additional 15% of the area would increase, between 16.2% and 19.3%, the protection of the distribution area of all species. We propose that the regions with a consensus of the three parametrizations should be declared as new protected areas to expand 374 km2 to the 216 km2 already protected. Doing so would double the protected surface in central Veracruz. The priority areas identified in this study have more species richness, carbon stock values, natural vegetation cover, and less human impact index than the existing protected areas. If our identified priority areas are declared protected, we could expect a future recovery of endangered species populations for Veracruz. The proposed new protected areas are planned and designed as corridors connecting currently isolated protected areas to promote biodiversity protection.

Dimobe, K., K. Ouédraogo, P. Annighöfer, J. Kollmann, J. Bayala, C. Hof, M. Schmidt, et al. 2022. Climate change aggravates anthropogenic threats of the endangered savanna tree Pterocarpus erinaceus (Fabaceae) in Burkina Faso. Journal for Nature Conservation: 126299. https://doi.org/10.1016/j.jnc.2022.126299

Species distribution modelling is gaining popularity due to significant habitat shifts in many plant and animal species caused by climate change. This issue is particularly pressing for species that provide significant ecosystem goods and services. A prominent case is the valuable African rosewood tree (Pterocarpus erinaceus) that is threatened in sub-Saharan Africa, while its present distribution, habitat requirements and the impact of climate change are not fully understood. This native species naturally occurs in various savanna types, but anthropogenic interventions have considerably reduced its natural populations in the past decades. In this study, ensemble modelling was used to predict the current and future distribution potential of the species in Burkina Faso. Fifty-four environmental variables were selected to describe its distribution in the years 2050 and 2070 based on the greenhouse gas concentration trajectories RCP4.5 and 8.5, and the general circulation models CNRM-CM5 and HadGEM2-CC. A network of protected areas in Burkina Faso was also included to assess how many of the suitable habitats may contribute to the conservation of the species. The factors isothermality (31%), minimum temperature of coldest month (31%), pH in H2O at horizon 0–5 cm (11%), silt content at horizon 60–100 cm (9.2%) and precipitation of warmest quarter (8%) were the most influential distribution drivers for the species. Under current climate conditions, potentially highly suitable habitats cover an area of 129,695 km2, i.e. 47% of Burkina Faso. The projected distribution under RCP4.5 and 8.5 showed that this area will decrease, and that the decline of the species will be pronounced. The two models used in this study forecast a habitat loss of up to 61% for P. erinaceus. Hence, development and implementation of a conservation program are required to save the species in its native range. This study will help land managers prioritise areas for protection of the species and avoid introducing it to inappropriate areas unless suitable conditions are artificially created through the management options applied.

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.