Potential distributional shifts in North America of allelopathic invasive plant species under climate change models

Geographic And Taxonomic Occurrence R-based Scrubbing (gatoRs): An R package and workflow for processing biodiversity data

Premise

Digitized biodiversity data offer extensive information; however, obtaining and processing biodiversity data can be daunting. Complexities arise during data cleaning, such as identifying and removing problematic records. To address these issues, we created the R package Geographic And Taxonomic Occurrence R-based Scrubbing (gatoRs).

Methods and Results

The gatoRs workflow includes functions that streamline downloading records from the Global Biodiversity Information Facility (GBIF) and Integrated Digitized Biocollections (iDigBio). We also created functions to clean downloaded specimen records. Unlike previous R packages, gatoRs accounts for differences in download structure between GBIF and iDigBio and allows for user control via interactive cleaning steps.

Conclusions

Our pipeline enables the scientific community to process biodiversity data efficiently and is accessible to the R coding novice. We anticipate that gatoRs will be useful for both established and beginning users. Furthermore, we expect our package will facilitate the introduction of biodiversity-related concepts into the classroom via the use of herbarium specimens.

An approach to the dermatological classification of histopathological skin images using a hybridized CNN-DenseNet model

This research addresses the challenge of automating skin disease diagnosis using dermatoscopic images. The primary issue lies in accurately classifying pigmented skin lesions, which traditionally rely on manual assessment by dermatologists and are prone to subjectivity and time consumption. By integrating a hybrid CNN-DenseNet model, this study aimed to overcome the complexities of differentiating various skin diseases and automating the diagnostic process effectively. Our methodology involved rigorous data preprocessing, exploratory data analysis, normalization, and label encoding. Techniques such as model hybridization, batch normalization and data fitting were employed to optimize the model architecture and data fitting. Initial iterations of our convolutional neural network (CNN) model achieved an accuracy of 76.22% on the test data and 75.69% on the validation data. Recognizing the need for improvement, the model was hybridized with DenseNet architecture and ResNet architecture was implemented for feature extraction and then further trained on the HAM10000 and PAD-UFES-20 datasets. Overall, our efforts resulted in a hybrid model that demonstrated an impressive accuracy of 95.7% on the HAM10000 dataset and 91.07% on the PAD-UFES-20 dataset. In comparison to recently published works, our model stands out because of its potential to effectively diagnose skin diseases such as melanocytic nevi, melanoma, benign keratosis-like lesions, basal cell carcinoma, actinic keratoses, vascular lesions, and dermatofibroma, all of which rival the diagnostic accuracy of real-world clinical specialists but also offer customization potential for more nuanced clinical uses.

Effects of land-use types and the exotic species, Hypochaeris radicata, on plant diversity in human-transformed landscapes of the biosphere reserve, Jeju Island, Korea

Land-use and plant invasion influence biodiversity. Understanding the effects of land-use types and invasive plants on the ecosystem is crucial for better management and the development of strategic plans for increasing biodiversity in Jeju Island, Korea, a designated Biosphere Reserve by the United Nations Education, Scientific, and Cultural Organization. The effect of the most dominant invasive exotic species, Hypochaeris radicata, on the four land-use types of Jeju Island was investigated. Plant composition, soil characteristics, and plant diversity among four land-use types (cropland, green space, neglected land, and residential) were compared. Among the land-use types, croplands had the most diverse plant composition and the highest richness in exotic and native plant species. Croplands, such as tangerine orchards, which are widely distributed throughout Jeju Island, showed the highest plant diversity because of medium intensity disturbance caused by weed removal. The relative cover of H. radicata did not differ between land-use types. However, H. radicata invasion was negatively related with plant species richness, making this invasive species a threat to the biodiversity of native herbs present in land-use areas. H. radicata adapts to areas with a broad range of soil properties and a variety of land-use types. Therefore, it is crucial to monitor land-use types and patterns of plant invasion to guide the implementation of consistent management and conservation strategies for maintaining ecosystem integrity of the transformed habitat in Jeju Island.

Climate change impacts the distribution of Quercus section Cyclobalanopsis (Fagaceae), a keystone lineage in East Asian evergreen broadleaved forests

East Asian evergreen broadleaved forests (EBFLs) harbor high species richness, but these ecosystems are severely impacted by global climate change and deforestation. Conserving and managing EBLFs requires understanding dominant tree distribution dynamics. In this study, we used 29 species in Quercus section Cyclobalanopsis-a keystone lineage in East Asian EBLFs-as proxies to predict EBLF distribution dynamics using species distribution models (SDMs). We examined climatic niche overlap, similarity, and equivalency among seven biogeographical regions' species using 'ecospat'. We also estimated the effectiveness of protected areas in the predicted range to elucidate priority conservation regions. Our results showed that the climatic niches of most geographical groups differ. The western species under the Indian summer monsoon regime were mainly impacted by temperature factors, whereas precipitation impacted the eastern species under the East Asian summer monsoon regime. Our simulation predicted a northward range expansion of section Cyclobalanopsis between 2081 and 2100, except for the ranges of the three Himalayan species analyzed, which might shrink significantly. The greatest shift of highly suitable areas was predicted for the species in the South Pacific, with a centroid shift of over 300 km. Remarkably, only 7.56% of suitable habitat is currently inside protected areas, and the percentage is predicted to continue declining in the future. To better conserve Asian EBLFs, establishing nature reserves in their northern distribution ranges, and transplanting the populations with predicted decreasing numbers and degraded habitats to their future highly suitable areas, should be high-priority objectives.

A Modeling Framework to Frame a Biological Invasion: Impatiens glandulifera in North America

Biological invasions are a major component of global environmental change with severe ecological and economic consequences. Since eradicating biological invaders is costly and even futile in many cases, predicting the areas under risk to take preventive measures is crucial. Impatiens glandulifera is a very aggressive and prolific invasive species and has been expanding its invasive range all across the Northern hemisphere, primarily in Europe. Although it is currently spread in the east and west of North America (in Canada and USA), studies on its fate under climate change are quite limited compared to the vast literature in Europe. Hybrid models, which integrate multiple modeling approaches, are promising tools for making projections to identify the areas under invasion risk. We developed a hybrid and spatially explicit framework by utilizing MaxEnt, one of the most preferred species distribution modeling (SDM) methods, and we developed an agent-based model (ABM) with the statistical language R. We projected the I. glandulifera invasion in North America, for the 2020-2050 period, under the RCP 4.5 scenario. Our results showed a predominant northward progression of the invasive range alongside an aggressive expansion in both currently invaded areas and interior regions. Our projections will provide valuable insights for risk assessment before the potentially irreversible outcomes emerge, considering the severity of the current state of the invasion in Europe.

Allopolyploid origin and niche expansion of Rhodiola integrifolia (Crassulaceae)

Polyploidy after hybridization between species can lead to immediate post-zygotic isolation, causing saltatory origin of new species. Although the incidence of polyploidization in plants is high, it is thought that a new polyploid lineage can succeed only if it establishes a new ecological niche divergent from its progenitor lineages. We tested the hypothesis that Rhodiola integrifolia from North America is an allopolyploid produced by R. rhodantha and R. rosea and determined whether its survival can be explained by the niche divergence hypothesis. To this end, we sequenced two low-copy nuclear genes (ncpGS and rpb2) in a phylogenetic analysis of 42 Rhodiola species and tested for niche equivalency and similarity using Schoener's D as the index of niche overlap. Our phylogeny-based approach showed that R. integrifolia possesses alleles from both R. rhodantha and R. rosea. Dating analysis showed that the hybridization event that led to R. integrifolia occurred ca. 1.67 Mya and niche modeling analysis showed that at this time, both R. rosea and R. rhodantha may have been present in Beringia, providing the opportunity for the hybridization event. We also found that the niche of R. integrifolia differs from that of its progenitors in both niche breadth and optimum. Taken together, these results confirm the hybrid origin of R. integrifolia and support the niche divergence hypothesis for this tetraploid species. Our results underscore the fact that lineages with no current overlapping distribution could produce hybrid descendants in the past, when climate oscillations made their distributions overlap.

Thermal bioclimatic indicators over Southeast Asia: present status and future projection using CMIP6

Mapping potential changes in bioclimatic characteristics are critical for planning mitigation goals and climate change adaptation. Assessment of such changes is particularly important for Southeast Asia (SEA) - home to global largest ecological diversity. Twenty-three global climate models (GCMs) of Coupled Model Intercomparison Project Phase 6 (CMIP6) were used in this study to evaluate changes in 11 thermal bioclimatic indicators over SEA for two shared socioeconomic pathways (SSPs), 2-4.5 and 5-8.5. Spatial changes in the ensemble mean, 5th, and 95th percentile of each indicator for near (2020-2059) and far (2060-2099) periods were examined in order to understand temporal changes and associated uncertainty. The results indicated large spatial heterogeneity and temporal variability in projected changes of bioclimatic indicators. A higher change was projected for mainland SEA in the far future and less in maritime region during the near future. At the same time, uncertainty in the projected bioclimatic indices was higher for mainland than maritime SEA. Analysis of mean multi-model ensemble revealed a change in mean temperature ranged from - 0.71 to 3.23 °C in near and from 0.00 to 4.07 °C in far futures. The diurnal temperature range was projected to reduce over most of SEA (ranging from - 1.1 to - 2.0 °C), while isothermality is likely to decrease from - 1.1 to - 4.6%. A decrease in isothermality along with narrowing of seasonality indicated a possible shift in climate, particularly in the north of mainland SEA. Maximum temperature in the warmest month/quarter was projected to increase a little more than the coldest month/quarter and the mean temperature in the driest month to increase more than the wettest month. This would cause an increase in the annual temperature range in the future.