Can highway tunnel constructıon change the habitat selection of roe deer (Capreolus capreolus Linnaeus, 1758)?

One of the main things wildlife does for survival is movement. Wild animals need movement to meet their needs, such as reproduction, breeding, foraging, and dispersal. Although wildlife species use roads for various purposes, they also use them when moving from one habitat to another. In recent years, especially when it comes to habitat fragmentation brought about by urbanization, wild animals frequently use highways. Highways have a wide range of effects on factors such as biodiversity, wildlife, and ecology. Roads can cause habitat loss, habitat fragmentation, and habitat degradation; alter the composition of vegetation; act as barriers to the flow of genes and movement; increase human access to pristine areas; and even increase the risk of extinction for many threatened species. Species belonging to the family Cervidae also include the species most affected by road networks. Roe deer (Capreolus capreolus Linnaeus, 1758) is the smallest of the 3 Cervid species living in Turkey. Roe deer are often injured or die in road accidents, and they are one of the most important species affected by the adverse effects of roads in Turkey. For this reason, it was investigated whether the road tunnel construction affected the distribution of roe deer in the region. In the study, the general distribution of roe deer in the Ilgaz Mountain, and the factors affecting their possible distribution were determined by ecological niche modeling. Data were taken between before (2012-2015) and after the highway tunnel built (2020-2022) in Ilgaz Mountain, which connects the Western Black Sea and Central Anatolia and is located in the middle of Kastamonu and Çankırı provinces. As a result of the modeling, it was found that before the construction of the tunnel, the most influential factor in the distribution of the deer was road density. After the tunnel construction, roads ceased to be the main factor affecting the distribution of the species. This study showed that roe deer are disturbed by the density of vehicles on the road passing through the middle of their habitat. With the decrease in the number of vehicles, they are more willing to cross the road and tend to use the areas close to the road as they are less disturbed.

MaxEnt modeling to show patterns of coastal habitats of reef-associated fish in the South and East China Seas

Reef-associated fish are a crucial source of protein for coastal residents and play an important role in the economy and ecology of marine ecosystems. However, human activities and climate change have led to the degradation of their habitats in the South China Sea (SCS) and East China Sea (ECS). This study models the potential habitats of reef-associated fish in the SCS and ECS between 1993 and 2019 using high-spatial-resolution environmental factors and fish presence data, estimates the importance of environmental factors on habitat distribution and identifies seasonal variation and distribution shifts over recent decades, the results show moderate and highly suitable areas for reef-associated fish in the region total 360,000 km2. Sea body temperature, chlorophyll-α concentration, and seawater salinity are crucial for determining the distribution of reef-associated fish. Moreover, reef-associated fish are also sensitive to seawater temperature in winter. Suitable areas for reef-associated fish near coastlines have decreased due to environmental changes within the region. The findings of this study offer valuable resource for developing fishery management and conservation strategies for this important functional group.

Analysis of niche shift and potential suitable distributions of Dendrobium under the impact of global climate change

Dendrobium is a valuable traditional Chinese herb that contains active ingredients such as polysaccharides and alkaloids that have anti-aging, antioxidant, and immunomodulating effects. The appropriate distribution range of Dendrobium should be predicted from the perspective of ecological niche theory in order to preserve and utilize medicinal plant resources. In this study, Dendrobium nobile, Dendrobium officinale, and Dendrobium moniliforme were selected to predict the potential suitable distributions and ecological niche shifts. A comparison of 19 environmental variables of the three Dendrobium species revealed three climatic factors that differed significantly when the species were compared two at a time. The principal component analysis was carried out in order to screen seven climatic factors for ecological niche shift analysis. All three Dendrobium species were found to have a very similar ecological niche, but with a relatively small range of variability regarding certain climatic factors. Finally, the current and future suitable areas for these three Dendrobium species in China were predicted using the MaxEnt model and ArcGIS using the two representative concentration pathways (RCP 2.6 and 8.5). Overall, the analysis of the climatic factors' comparisons, niche shift, and current and future suitable areas of these three Dendrobium species provides a basis for medicinal plant resource conservation and utilization, and our methods could be applied to the study of other similar valuable medicinal plants.

Assessing the suitable regions and the key factors for three Cd-accumulating plants (Sedum alfredii, Phytolacca americana, and Hylotelephium spectabile) in China using MaxEnt model

Phytoremediation is an effective way to remove metals from contaminated soil, and selecting remediation plants suitable for climate conditions is a prerequisite for effective phytoremediation. In this study, a MaxEnt model was applied to investigate the potential distribution and habitat suitability of three Cd-accumulating plants in China- Sedum alfredii, Phytolacca americana, and Hylotelephium spectabile and explore the key environmental factors that affect their habitat suitability. A total of 44 environmental parameters, including bioclimatic variables, altitude, and soil property parameters were used. The results showed that: (1) For S. alfredii, suitable areas account for 14.9 % of the area of China, which are mainly distributed in the middle and lower reaches of the Yangtze River. (2) The suitable areas of P. americana account for 22.7 % of China and are mainly located in the regions of the Qinling Mountains and the south of China. (3) While that for H. spectabile are mainly located in the regions of northeastern China and certain regions of central China, with suitable areas account for 8.3 % of the area of China. (4) The distribution of these three plants is significantly affected by precipitation; specifically, solar radiation is an influential factor for the distribution of S. alfredii and H. spectabile, and temperature limits the distribution of P. americana. The selection and agronomic management of hyperaccumulators for phytoremediation requires multifactor consideration (e.g., climate, soil conditions and planting patterns). The results can provide guidance for identifying suitable areas for planting these three accumulating plants, which could not only prevent the unscientific cultivation of them in unsuitable habitats but also enhance the efficiency of phytoremediation. Meanwhile, these findings are expected to contribute to agronomic management for improved phytoremediation effects in different Cd-contaminated regions of China.

A Machine Learning Approach for the Non-Destructive Estimation of Leaf Area in Medicinal Orchid Dendrobium nobile L

In this study, leaf area prediction models of Dendrobium nobile, were developed through machine learning (ML) techniques including multiple linear regression (MLR), support vector regression (SVR), gradient boosting regression (GBR), and artificial neural networks (ANNs). The best model was tested using the coefficient of determination (R2), mean absolute errors (MAEs), and root mean square errors (RMSEs) and statistically confirmed through average rank (AR). Leaf images were captured through a smartphone and ImageJ was used to calculate the length (L), width (W), and leaf area (LA). Three orders of L, W, and their combinations were taken for model building. Multicollinearity status was checked using Variance Inflation Factor (VIF) and Tolerance (T). A total of 80% of the dataset and the remaining 20% were used for training and validation, respectively. KFold (K = 10) cross-validation checked the model overfit. GBR (R2, MAE and RMSE values ranged at 0.96, (0.82–0.91) and (1.10–1.11) cm2) in the testing phase was the best among the ML models. AR statistically confirms the outperformance of GBR, securing first rank and a frequency of 80% among the top ten ML models. Thus, GBR is the best model imparting its future utilization to estimate leaf area in D. nobile.

Understanding the Limiting Climatic Factors on the Suitable Habitat of Chinese Alfalfa

Chinese alfalfa (Medicago sativa) is one of the most widely planted species in China. It has considerable economic potential and plays an important role in soil and water conservation. In order to conduct scientific cultivation of Chinese alfalfa, we collected 100 occurrence records from herbarium and publications and 19 climatic variables from BIOCLIM to simulate potential suitable habitat and identified the key climatic factors of Chinese alfalfa by MaxEnt and GIS software. The result shows that the MaxEnt model performed well, with an average test AUC value of 0.86 with 10-fold cross validation. The potential distribution of Chinese alfalfa is mainly in arid and semi-arid areas of north and northwest China, about 15.2% (1.46 million km2) of China’s total land area, and the highly suitable area is Loess Hilly region and Xinjiang. The main climatic factors affecting the distribution of this species is hydrological-related factors (PDM, PS, AP, PDQ and PCQ), which explained 58.6% of the variation, and the climatic factors limiting the southern, northern, northwestern and Tibetan plateau boundaries were PDM, AMT, AP and MTCM, respectively. The climatic thresholds of the core area of Chinese alfalfa are 0.0–14.0 mm of PDM, 23.8–108.2% of PS, 3.9–15.5 °C of AMT, 14.0–664.0 mm of AP, 1.0–47.0 mm of PDQ, 2.0–51.0 mm of PCQ. The results improve our understanding of limiting climatic factors for Chinese alfalfa and suggest a priority management measures for areas with corresponding limiting climatic factor.

Cold Response Transcriptome Analysis of the Alternative Splicing Events Induced by the Cold Stress in D. catenatum

Dendrobium catenatum Lindl is a valuable medicinal herb and gardening plant due to its ornamental value and special medical value. Low temperature is a major bottleneck restricting D. catenatum expansion towards the north, which influences the quality and yield of D. catenatum. In this study, we analysed the cold response of D. catenatum by RNA-Seq. A total of 4302 differentially expressed genes were detected under cold stress, which were mainly linked to protein kinase activity, membrane transport and the glycan biosynthesis and metabolism pathway. We also identified 4005 differential alternative events in 2319 genes significantly regulated by cold stress. Exon skipping and intron retention were the most common alternative splicing isoforms. Numerous genes were identified that differentially modulated under cold stress, including cold-induced transcription factors and splicing factors mediated by AS (alternative splicing). GO enrichment analysis found that differentially alternatively spliced genes without differential expression levels were related to RNA/mRNA processing and spliceosomes. DAS (differentially alternative splicing) genes with different expression levels were mainly enriched in protein kinase activity, plasma membrane and cellular response to stimulus. We further identified and cloned DcCBP20 in D. catenatum; we found that DcCBP20 promotes the generation of alternative splicing variants in cold-induced genes under cold stress via genetic experiments and RT–PCR. Taken together, our results identify the main cold-response pathways and alternative splicing events in D. catenatum responding to cold treatment and that DcCBP20 of D. catenatum get involved in regulating the AS and gene expression of cold-induced genes during this process. Our study will contribute to understanding the role of AS genes in regulating the cold stress response in D. catenatum.

Geographical distribution of As-hyperaccumulator Pteris vittata in China: Environmental factors and climate changes

Understanding the distribution of hyperaccumulators helps to implement more efficient phytoremediation strategies of contaminated sites, however, limited information is available. Here, we investigated the geographical distribution of the first-known arsenic-hyperaccumulator Pteris vittata in China and the key factors under two climate change scenarios (SSP 1-2.6 and SSP 5-8.5) at two time points (2030 and 2070). Species distribution model (MaxEnt) was applied to examine P. vittata distribution based on 399 samples from field surveys and existing specimen records. Further, among 23 environmental factors, 11 variables were used in the MaxEnt model, including temperature, precipitation, elevation, soil property, and UV-B radiation. The results show that P. vittata can grow in ~23% of the regions in China. Specifically, it is mainly distributed in 11 provinces of southern China, including Hainan, Guangdong, Guangxi, Yunnan, Guizhou, Hunan, Hubei, Jiangxi, Fujian, Zhejiang, and Jiangsu. Besides, eastern Sichuan, and southern Henan, Shaanxi, and Anhui are suitable for P. vittata growth. Under two climate change scenarios, P. vittata distribution in China would decrease by ~5.76-7.46 × 10⁴ km² in 2030 and ~3.22-4.68 × 10⁴ km² in 2070, with southern Henan and most Jiangsu being unsuitable for P. vittata growth. Among the 11 environmental variables, the minimum temperature of coldest month (bio6) and temperature annual range (bio7) are the two key factors limiting P. vittata distribution. At bio6 <-5 °C and/or bio7 >33 °C, the regions are unsuitable for P. vittata growth. Based on the MaxEnt model, precipitation had limited effects, so P. vittata can probably survive under both dry and moist environments. This study helps guide phytoremediation of As-polluted soils using P. vittata and provides an example to evaluate habitat suitability of hyperaccumulators at international scales.