The overlap of suitable tea plant habitat with Asian elephant (Elephus maximus) distribution in southwestern China and its potential impact on species conservation and local economy

Examining the rationality of Giant Panda National Park's zoning designations and management measures for habitat conservation: Insights from interpretable machine learning methods

Examining the rationality of zoning designations and management measures in the initial establishment of national parks in China is of great significance for supporting decision-making regarding habitat conservation. There exists a research gap in exploring the threshold effects of both environmental and human-related factors on habitat distribution in the context of national parks. However, it may be a challenge because of the limited species distribution data. Our study aims to put forward an analytical framework that integrates species distribution models (SDMs) with interpretable machine learning methods. A case study was performed in the Sichuan region of the Giant Panda National Park (GPNP). We constructed a SDM based on the Random Forest algorithm and made use of accessible remote sensing and big data to predict the distribution of giant panda habitat (GPH) in 2020. Interpretable machine learning methods, namely Partial dependence plots (PDPs) and SHapley Additive exPlanations (SHAP), were utilized to uncover the underlying mechanisms of environmental and anthropogenic variables influencing the GPH distribution. Through GIS overlay analysis, areas where conflicts between human settlements, transportation infrastructure, and GPH exist were identified. Our findings indicated a potential 28.44 % decrease in GPH from 2014 to 2020. Environmental factors such as temperature, topography, and vegetation type, as well as anthropogenic factors including distance to built-up areas and transportation infrastructure, notably distance to national roads, provincial roads and city arterial roads, influenced the GPH distribution with threshold effects significantly. The overlay analysis revealed escalated conflicts between human settlements, transportation infrastructure, and GPH in 2020 compared to 2014. Currently, the Sichuan region of the GPNP implements two zones: a core protection zone and a general control zone, covering 63.71 % of the GPH, while 36.29 % remains outside the management scope. Drawing from the analysis above, this study provided suggestions for the adjustment of zoning designations and management measures in the GPNP.

Predicting current and future climate suitability for arecanut (Areca catechu L.) in India using ensemble model

Climate change has the potential to influence plant development, physiology, and distribution. Arecanut (Areca catechu L.), with its long life span of 60-70 years, thrives in a tropical habitat remains exposed to various abiotic and biotic factors. It is pertinent to comprehend the adaptation strategies of this crop towards climate change over time. The Biomod2 ensemble platform for species distribution modeling was utilized to predict the potential impact of climate change on the adaptability of the crop. The extracted study region of India was used for prediction, and the final run of 6 models ensemble includes 894 occurrence points and 9 climate variables with 80%-20% of training and validation sets. The model's outputs had area under curve (AUC) values of 0.943 and true skills statistics (TSS) of 0.741, which are regarded as accurate. The research area was categorized into five groups: very high, high, moderate, low, and very low. The examination involved assessing the shift in each category from the present to two prospective scenarios (shared socio-economic pathways; SSP 2-4.5 and SSP 5-8.5) projected for the 2050s and 2070s. A shift in the climate suitability area from 'very high' and 'high' categories to 'moderate' or 'very low' categories was observed suggesting the need for adaptive strategies to sustain the current yield levels. Amongst the regions, Karnataka state, which at present has more than 50% area under cultivation, is highly vulnerable and more area is coming under 'very low' and 'low' categories from eastern side. Meanwhile, in north eastern part of the country a shift in high suitable region from northwest to southwest is observed. Overall, the model prediction suggests that some parts of west and south interior regions of the country warrant immediate consideration in order to adapt to future climate change, whereas some part of north east can be considered for future cultivation.

Haplotype-resolved chromosome-scale genomes of the Asian and African Savannah Elephants

The Proboscidea, which includes modern elephants, were once the largest terrestrial animals among extant species. They suffered mass extinction during the Ice Age. As a unique branch on the evolutionary tree, the Proboscidea are of great significance for the study of living animals. In this study, we generate chromosome-scale and haplotype-resolved genome assemblies for two extant Proboscidea species (Asian Elephant, Elephas maximus and African Savannah Elephant, Loxodonta africana) using Pacbio, Hi-C, and DNBSEQ technologies. The assembled genome sizes of the Asian and African Savannah Elephant are 3.38 Gb and 3.31 Gb, with scaffold N50 values of 130 Mb and 122 Mb, respectively. Using Hi-C technology ~97% of the scaffolds are anchored to 29 pseudochromosomes. Additionally, we identify ~9 Mb Y-linked sequences for each species. The high-quality genome assemblies in this study provide a valuable resource for future research on ecology, evolution, biology and conservation of Proboscidea species.

Climate change and anthropogenic activities shrink the range and dispersal of an endangered primate in Sichuan Province, China

The golden snub-nosed monkey (Rhinopithecus roxellana) is a rare and endemic species in China. The population of golden snub-nosed monkeys in Sichuan Province has an isolated genetic status, large population size, and low genetic diversity, making it highly vulnerable to environmental changes. Our study aimed to evaluate the potential impact of climate and land-use changes on the distribution and dispersal paths of the species in Sichuan Province. We used three general circulation models (GCMs), three greenhouse gas emission scenarios, and three land-use change scenarios suitable for China to predict the potential distributions of the golden snub-nosed monkey in the current and 2070s using the MaxEnt model. The dispersal paths were identified by the circuit theory. Our results suggested that the habitats of the golden snub-nosed monkey were reduced under all three GCM scenarios. The suitable habitats for the golden snub-nosed monkey would be reduced by 82.67%, 82.47%, and 75.17% under the RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively, compared to the currently suitable habitat area. Additionally, we found that the density of future dispersal paths of golden snub-nosed monkeys would decrease, and the dispersal resistance would increase. Therefore, relevant wildlife protection agencies should prioritize the climatically suitable distributions and key dispersal paths of golden snub-nosed monkeys to improve their conservation. We identified key areas for habitat preservation and increased habitat connectivity under climate change, which could serve as a reference for future adaptation strategies.

Ecological response of an umbrella species to changing climate and land use: Habitat conservation for Asiatic black bear in the Sichuan-Chongqing Region, Southwestern China

Climate and land use changes are increasingly recognized as major threats to global biodiversity, with significant impacts on wildlife populations and ecosystems worldwide. The study of how climate and land use changes impact wildlife is of paramount importance for advancing our understanding of ecological processes in the face of global environmental change, informing conservation planning and management, and identifying the mechanisms and thresholds that underlie species' responses to shifting climatic conditions. The Asiatic black bear (Ursus thibetanus) is a prominent umbrella species in a biodiversity hotspot in Southwestern China, and its conservation is vital for safeguarding sympatric species. However, the extent to which this species' habitat may respond to global climate and land use changes is poorly understood, underscoring the need for further investigation. Our goal was to anticipate the potential impacts of upcoming climate and land use changes on the distribution and dispersal patterns of the Asiatic black bear in the Sichuan-Chongqing Region. We used MaxEnt modeling to evaluate habitat vulnerability using three General Circulation Models (GCMs) and three scenarios of climate and land use changes. Subsequently, we used Circuit Theory to identify prospective dispersal paths. Our results revealed that the current area of suitable habitat for the Asiatic black bear was 225,609.59 km² (comprising 39.69% of the total study area), but was expected to decrease by -53.1%, -49.48%, and -28.55% under RCP2.6, RCP4.5, and RCP8.5 projection scenarios, respectively. Across all three GCMs, the distribution areas and dispersal paths of the Asiatic black bear were projected to shift to higher altitudes and constrict by the 2070s. Furthermore, the results indicated that the density of dispersal paths would decrease, while the resistance to dispersal would increase across the study area. In order to protect the Asiatic black bear, it is essential to prioritize the protection of climate refugia and dispersal paths. Our findings provide a sound scientific foundation for the allocation of such protected areas in the Sichuan-Chongqing Region that are both effective and adaptive in the face of ongoing global climate and land use changes.

Genome-wide association study of leaf-related traits in tea plant in Guizhou based on genotyping-by-sequencing

BACKGROUND

Studying the genetic characteristics of tea plant (Camellia spp.) leaf traits is essential for improving yield and quality through breeding and selection. Guizhou Plateau, an important part of the original center of tea plants, has rich genetic resources. However, few studies have explored the associations between tea plant leaf traits and single nucleotide polymorphism (SNP) markers in Guizhou.

RESULTS

In this study, we used the genotyping-by-sequencing (GBS) method to identify 100,829 SNP markers from 338 accessions of tea germplasm in Guizhou Plateau, a region with rich genetic resources. We assessed population structure based on high-quality SNPs, constructed phylogenetic relationships, and performed genome-wide association studies (GWASs). Four inferred pure groups (G-I, G-II, G-III, and G-IV) and one inferred admixture group (G-V), were identified by a population structure analysis, and verified by principal component analyses and phylogenetic analyses. Through GWAS, we identified six candidate genes associated with four leaf traits, including mature leaf size, texture, color and shape. Specifically, two candidate genes, located on chromosomes 1 and 9, were significantly associated with mature leaf size, while two genes, located on chromosomes 8 and 11, were significantly associated with mature leaf texture. Additionally, two candidate genes, located on chromosomes 1 and 2 were identified as being associated with mature leaf color and mature leaf shape, respectively. We verified the expression level of two candidate genes was verified using reverse transcription quantitative polymerase chain reaction (RT-qPCR) and designed a derived cleaved amplified polymorphism (dCAPS) marker that co-segregated with mature leaf size, which could be used for marker-assisted selection (MAS) breeding in Camellia sinensis.

CONCLUSIONS

In the present study, by using GWAS approaches with the 338 tea accessions population in Guizhou, we revealed a list of SNPs markers and candidate genes that were significantly associated with four leaf traits. This work provides theoretical and practical basis for the genetic breeding of related traits in tea plant leaves.

Comparison of machine learning and deep learning models for evaluating suitable areas for premium teas in Yunnan, China

BACKGROUND

Tea is an important economic crop in Yunnan, and the market price of premium teas such as Lao Banzhang is significantly higher than ordinary teas. For planting lands to promote, the tea industry to develop and minority lands' economies to prosper, it is vital to evaluate and analyze suitable areas for premium tea cultivation.

METHODS

Climate, terrain, soil, and green cropping system in the premium tea planting areas were used as evaluation variables. The suitability of six machine learning models for predicting suitable areas of premium teas were evaluated.

RESULT

FA+ResNet demonstrated the best performance with an accuracy score of 0.94 and a macro-F1 score of 0.93. The suitable areas of premium teas were mainly located in the southern catchment of LancangJiang River, south-central part of Dehong, a few areas in the mid-west of Lincang, central scattered areas of Pu'er, most of the southern western part of Xishuangbanna and the southern edge of Honghe. Annual mean temperature, annual mean precipitation, mist belt, annual mean relative humidity, soil type and elevation were the key components in evaluating the suitable areas of premium teas in Yunnan.

Role of tea plantations in the maintenance of bird diversity in Anji County, China

Background

Tea plantations support regional sustainable development and have the potential to support more biodiversity than urban open spaces. Numerous studies have shown the value of low-intensity agroecosystems for preserving biodiversity, however tea plantations have received less attention. The relationship between tea plantations and the diversity of macro-organisms, such as birds, is still not fully understood.

Methods

We investigated the bird diversity and vegetation conditions and calculated landscape metrics in 30 tea plantations in Anji County, Zhejiang Province, China. At these 30 sampling sites, we recorded 262 individuals belonging to 37 species, which were classified into two guilds: nature- and urban-dependent birds. We used cluster analysis to group the sampling sites based on the abundance of the birds. Then we evaluated the effects of associated plant diversity in tea plantations and the surrounding landscape composition on these bird guilds using species association computation and a generalized linear model.

Results

The results show that the maintenance of bird diversity by tea plantations benefits both nature- and urban-dependent birds. We found that landscape-scale factors surrounding the tea plantations mainly affected the bird richness due to their habitat selection. Landscape agglomeration and habitat quality were the dominant landscape-scale metrics. Patch-scale factors of tea plantations, especially the vegetation structure, had a strong influence on the abundance of the birds. Nature-dependent birds preferred to occur in tea plantations with perennial herbs, while urban-dependent birds were attracted by the general distributed plants, as annual herbs. Therefore, we concluded that tea plantations play an important role as a transitional zone between natural habitats and urban areas, thus reducing the impact of urbanization and maintaining bird diversity in low-quality habitats.

Identifying the ecological security patterns of the Three Gorges Reservoir Region, China

Identifying and improving the existing ecological security patterns (ESPs) are of great importance to promoting ecological security and achieving sustainable development goals. The Three Gorges Reservoir Region (TGRR) is an area with a sensitive, fragile, and complex ecological environment in the Upper Reaches of the Yangtze River. The construction of ESPs for the TGRR is significant for maintaining regional ecosystem stability and promoting peaceful coexistence between humans and nature. The main objective of the study is to identify the ecological nodes, ecological corridors, and ecological sources that play essential roles in the ecosystem. Based on land use data and human interference factors, we have evaluated the current habitat quality using the InVEST model and identified vital ecological sources for the TGRR. The negative exponential transformation function was used to convert habitat suitability into a landscape resistance layer. Circuit theory modeling was utilized to identify ecological corridors, and the final ESPs of the TGRR were then constructed. Results showed that (a) the spatial distribution of habitat varied significantly in the TGRR. The optimal habitats were concentrated in the northeast, east, and southwest, accounting for 45.98% of the total suitable habitats; (b) habitat quality varied through space, with habitat quality being higher in the northeast and lower in the western regions. (c) Ecological sources were distributed primarily in the forests with high vegetation coverage in the east. The total area of ecological sources was about 15,412 km², approximately accounting for 34% of the study area; (d) the ESPs were dominated by ecological sources composed of forests, which were radially connected by ecological corridors. In total, these included 14 significant ecological sources, 25 clusters of ecological corridors, and 23 ecological nodes. The results are of great significance to promote the ecological security of the TGRR and could provide theoretical support for biodiversity conservation and territorial space planning for the Three Gorges Region.