Range Of Species Research Articles

Not Everyone Likes Manatees: Fishers' Perceptions Unveil Opportunities and Challenges for Manatee Conservation in the Swamp Complex of Ayapel, Colombia

ABSTRACTGreater Caribbean manatees Trichechus manatus manatus face complex conservation challenges throughout their distribution range, many of which are associated with human factors; and in consequence, the subspecies is considered Endangered (EN) by the International Union for Conservation of Nature (IUCN). Human‐related threats as hunting for meat consumption, collisions with boats, entanglement in fishing nets, pollution and loss of habitat put the Greater Caribbean manatee at risk in Colombia. Studies aiming to describe traditional knowledge and local perceptions provide information that can be useful to design local manatee conservation programmes. We analyse the fishers' perceptions regarding manatees in Ayapel, Córdoba. One hundred semi‐structured interviews were conducted, focusing on personal data, fishing practices, perceptions and knowledge about the manatees. According to the interviews, bycatch is the greatest threat to manatees (56%), followed by pollution (16%), whereas boat collisions (12%), hunting (11%) and drought (5%) are lower ranking threats. Our results demonstrated that participants have a good understanding of manatee biology and ecology. However, a human–manatee conflict was evidenced, as 39% of fishers consider that manatees negatively impact fishing by competition for the fishing resources and/or by damaging fishing gear. We recommend strengthening awareness about the importance of manatee to guarantee an optimal management of this subspecies and its habitat. Fishers should be directly involved in the formulation of management and conservation plans for the subspecies, as their knowledge becomes critical to understanding and mitigating the risks to manatee populations. This work has a clear application to understand the human factor in manatee recovery not only in our study area but also in other locations where manatees share habitat with people, particularly in marginalized human communities.

A Study on the Cutting Characteristics of Bottom Abrasive Grains in Helical Grinding Tools

Helical grinding is crucial for manufacturing small holes in hard-to-machine composite ceramics. This study introduces a geometric model of undeformed chips to analyze the cutting characteristics of abrasive grains on both the bottom and side edges of the tool. It reveals for the first time that the distribution of cutting grains—pure bottom-edge, pure side-edge, and mixed-edge—is influenced by the tool diameter and eccentricity. A novel calculation method for the distribution range (Dp) of pure bottom-edge grains is proposed, demonstrating that using a tool diameter at or below two-thirds of the target hole diameter effectively eliminates pure bottom-edge grains, improving chip evacuation, reducing chip adhesion, and optimizing cutting performance. Experimental validation on small holes in SiCp/Al composites (65% volume fraction) confirmed these findings and provides practical guidance for optimizing cutting parameters and tool design.

New record of Cyanallagma demoiselle Denck, Ehlert & Pinto, 2023 (Odonata, Zygoptera, Coenagrionidae) in southern Brazil

During a field expedition in the municipality of Araquari, state of Santa Catarina, southern Brazil, adults of the damselfly Cyanallagma demoiselle Denck, Ehlert & Pinto 2023 (Odonata, Zygoptera, Coenagrionidae) were collected. This species was recently described and reported to date for the southeastern Atlantic Forest in Brazil. Here, we recorded this species as well as its respective genus for the first time for the state of Santa Catarina, increasing its distribution range of the species to southwards and raising the number of Odonata species recorded for this state to 151.

Why do Eurasian otters eat so few invasive blue crabs?

Invasive species can become key trophic resources for native predators, and thus understanding predator-invasive prey interactions is relevant to assess invasion impacts. The Atlantic blue crab (Callinectes sapidus) has recently invaded coasts and lower stretches of rivers across the Western Palearctic, often establishing very abundant populations. The blue crab is an important prey for a large number of predators within its native range, but predation upon invasive populations is still virtually unknown. The Eurasian otter (Lutra lutra) is a flexible predator, known to incorporate invasive prey into its diet when they become available. We studied otter diet in a small estuary of southern Spain hosting a very abundant blue crab population. The role of the blue crab as otter prey was only anecdotal since, out of 223 spraints (otter faeces) collected between 2021 and 2023, its remains were found in a single one. The avoidance of the blue crab by otters, and also by other predators, seems to be a generalised phenomenon in the invaded range of this crustacean. Predation on invasive blue crabs may require a long-lasting learning process to overcome the crab’s anti-predatory structures and behaviours. Trophic interactions between invasive blue crabs and native predators deserves attention for three main aspects: (i) its implications for the functioning and structure of invaded food webs, (ii) its potential role in limiting the invasion, and (iii) the interest in the generation of new predatory traits among animal populations.

Spatial distribution characteristics of Tibetan Buddhism principal-subordinate monastery systems in the Hehuang region

Tibetan Buddhist monasteries constitute significant cultural heritages of ethnic minorities, evolving into the Principal-Subordinate Monastery System (PSMS) with profound historical and cultural significance. This system exhibits an integrated hierarchical structure in terms of religious dominance, political administration, and cultural diffusion. Existing research primarily focuses on internal humanistic factors such as governance patterns, while there is not any research focused on its patterns and manifestations in spatial distribution. This study aims to elucidate the spatial distribution characteristics of the PSMS in Hehuang region, including the Tibetan Buddhist monasteries from all sects in the Hehuang region since the Song Dynasty It establishes a hierarchical PSMS database based on the affiliation relationships, aimed at storing spatial and property information related to PSMS. The database standardizes the naming and coding of monasteries, and classifies them through hierarchical relationships to ensure data consistency and usability. Finally, the classified and coded monastery data were analyzed by GIS tools to form the PSMS spatial distribution characterisation framework. Results reveal that (1) Monasteries demonstrate notable spatial clustering patterns from both holistic and sectarian perspectives, with density being influenced by the principal monastery’s position. (2) Almost every PSMS exhibits a spatial pattern centered around the principal monastery, with subordinate monasteries clustering within a defined range correlated with the administrative region of the principal monastery. (3) PSMS scale variations are controlled by principal monasteries, exhibiting positive correlations in hierarchical structure, control quantity, and distribution range. (4) The spatial orientation of PSMS correlates with river distribution, while the relationships among mountain ranges require further investigation. These findings provide initial insights into the spatial distribution characteristics of PSMS, confirming the spatial influence of the principal monastery. Besides, this study established an innovative spatial research framework for heritage clusters with multiple types and hierarchies. Thus, this study offers new insights into the spatial distribution of Tibetan Buddhist monastery heritage and presents a framework for further examining the spatial distribution of the Tibetan Buddhist monastery heritage in other regions, as well as other heritage clusters where connected and clustered through religious and cultural ties.

Carbon dot unravels accumulation of triterpenoid in Evolvulus alsinoides hairy roots culture by stimulating growth, redox reactions and ANN machine learning model prediction of metabolic stress response

Evolvulus alsinoides, a therapeutically valuable shrub can provide consistent supply of secondary metabolites (SM) with pharmaceutical significance. Nonetheless, because of its short life cycle, fresh plant material for research and medicinal diagnostics is severely scarce throughout the year. The effects of exogenous carbon quantum dot (CD) application on metabolic profiles, machine learning (ML) prediction of metabolic stress response, and SM yields in hairy root cultures of E. alsinoides were investigated and quantified. The range of the particle size distribution of the CDs was between 3 and 7 nm. The CDs EPR signal and spin trapping experiments demonstrated the formation of O2-•spin-adducts at (g = 2.0023). Carbon dot treatment increased the levels of hydrogen peroxide and malondialdehyde concentrations as well as increased antioxidant enzyme activity. CD treatments (6 μg mL-1) significantly enhanced the accumulation of squalene and stigmasterol (7 and 5-fold respectively). The multilayer perceptron (MLP) algorithm demonstrated remarkable prediction accuracy (MSE value = 1.99E-03 and R2 = 0.99939) in both the training and testing sets for modelling. Based on the prediction, the maximum oxidative stress index and enzymatic activities were highest in the medium supplemented with 10 μg mL-1 CDs. The outcome of this study indicated that, for the first time, using CD could serve as a novel elicitor for the production of valuable SM. MLP may also be used as a forward-thinking tool to optimize and predict SM with high pharmaceutical significance. This study would be a touchstone for understanding the use of ML and luminescent nanomaterials in the production and commercialization of important SM.

Genomic identification of Oryctes rhinoceros nudivirus isolates, a biocontrol agent for coconut rhinoceros beetle

The coconut rhinoceros beetle (Oryctes rhinoceros, CRB) is a serious pest of coconut and oil palms. It is native to South and Southeast Asia and was inadvertently introduced to Samoa in 1909. It has invaded many other Pacific countries throughout the last century. Oryctes rhinoceros nudivirus (OrNV), a natural pathogen of CRB in its native range, was successfully introduced as a classical biocontrol agent and has effectively suppressed invasive CRB populations for decades. However, resurgence of CRB has been recorded, with new invasions detected in several Pacific Island Countries and Territories. Additionally, new populations of CRB are emerging in some invaded areas that have a degree of resistance to the virus isolates commonly released for CRB biocontrol. Here, we designed a fast and reliable tool for distinguishing between different OrNV isolates that can help with the selection process to identify effective isolates for management of new CRB invasions. A comparison of 13 gene/gene region sequences within the OrNV genome of 16 OrNV isolates from native and invaded ranges allowed us to identify unique Single Nucleotide Polymorphisms (SNPs). With these SNPs, we developed an assay using multiplex PCR-amplicon-based nanopore sequencing to distinguish between OrNV isolates. We found that as few as four gene fragments were sufficient to identify 15 out of 20 OrNV isolates. This method can be used as a tool to monitor the establishment and distribution of OrNV isolates selected for release as biocontrol agents in CRB-infected areas.

Strainy: phasing and assembly of strain haplotypes from long-read metagenome sequencing.

Bacterial species in microbial communities are often represented by mixtures of strains, distinguished by small variations in their genomes. Short-read approaches can be used to detect small-scale variation between strains but fail to phase these variants into contiguous haplotypes. Long-read metagenome assemblers can generate contiguous bacterial chromosomes but often suppress strain-level variation in favor of species-level consensus. Here we present Strainy, an algorithm for strain-level metagenome assembly and phasing from Nanopore and PacBio reads. Strainy takes a de novo metagenomic assembly as input and identifies strain variants, which are then phased and assembled into contiguous haplotypes. Using simulated and mock Nanopore and PacBio metagenome data, we show that Strainy assembles accurate and complete strain haplotypes, outperforming current Nanopore-based methods and comparable with PacBio-based algorithms in completeness and accuracy. We then use Strainy to assemble strain haplotypes of a complex environmental metagenome, revealing distinct strain distribution and mutational patterns in bacterial species.

An optimal configuration strategy of multi-chiller system based on overlap analysis and improved GA

For design of the multi-chiller system, the configuration can be optimized that the system is high efficiency when it is operated under frequent load and operation condition in one year. Base on this idea, the paper presents a novel strategy of optimal configuration of multi-chiller system. The high hour-density range of annual load distribution and the high-efficiency region of combination of chillers are presented respectively, and their obtaining methods are developed. The overlap index is defined to evaluate the overlap between the high-efficiency region and high hour-density range, and it is maximized for the proposed optimal configuration strategy. GA is improved and employed for optimization. The proposed optimal configuration strategy is validated in a real multi-chiller system. The results show that the optimal configuration configured by the proposed strategy can improve annual Energy Efficiency Ratio (EER) about 5 % comparing with the original configuration of the real system. The configurations using equivalent strategy and typical non-equivalent strategy are compared, and the results show that both of hourly COP and annual EER of the configuration of the proposed strategy are better than them. 50 random configurations enumerated from chiller candidates are also compared. The results show that the overlap index is strongly correlated to annual EER, and it can be taken as optimization object for optimal configuration. Improved GA is compared with original GA, and the results show that of computation time cost can be reduced more than 60 % by use of Improved GA. The validation results show that the proposed strategy can obtain the optimal configuration of multi-chiller system directly from chiller candidates.

The Characteristics of Milk Fatty Acid Profile Predicted by Fourier-Transform Mid-Infrared Spectroscopy (FT-MIRS) in Chinese Holstein Cows.

Fatty acid is an important factor affecting the nutritional quality of milk. In this study, we collected and assessed 78,086 milk samples from 12,065 Chinese Holstein cows from 11 farms in Northern China from November 2019 to September 2022. The contents of eight fatty acid groups were predicted using FT-MIRS-based models. The contents of TFAs, SFAs, UFAs, MUFAs, PUFAs, and LCFAs in milk reached the highest at 96-125 DIM, and SCFA and MCFA contents reached the highest at 276-305 DIM. With the increase in somatic cell score, the contents of various fatty acid groups in milk gradually decreased, and the nutritional value of milk and flavor of dairy products gradually deteriorated. The contents of high-quality fatty acids in milk, particularly UFAs and MUFAs, were significantly higher in the non-pregnant state than in the pregnant state. However, SCFA and MCFA contents exhibited the opposite pattern. Our findings provided valuable information on the content and distribution range of fatty acid groups in milk from Chinese Holstein cows. Further analysis is warranted to explore the breeding of Chinese Holstein cows providing milk with abundant beneficial fatty acids.

Analisis Performa Normalisasi Data untuk Klasifikasi K-Nearest Neighbor pada Dataset Penyakit

This study investigates four normalization methods (Min-Max, Z-Score, Decimal Scaling, MaxAbs) across prostate, kidney, and heart disease datasets for K-Nearest Neighbor (K-NN) classification. Imbalanced feature scales can hinder K-NN performance, making normalization crucial. Results show that Decimal Scaling achieves 90.00% accuracy in prostate cancer, while Min-Max and Z-Score yield 97.50% in kidney disease. MaxAbs performs well with 96.25% accuracy in kidney disease. In heart disease, Min-Max and MaxAbs attain accuracies of 82.93% and 81.95%, respectively. These findings suggest Decimal Scaling suits datasets with few instances, limited features, and normal distribution. Min-Max and MaxAbs are better for datasets with numerous instances and non-normal distribution. Z-Score fits datasets with a wide range of feature numbers and near-normal distribution. This study aids in selecting the appropriate normalization method based on dataset characteristics to enhance K-NN classification accuracy in disease diagnosis. The experiments involve datasets with different attributes, continuous and categorical data, and binary classification. Data conditions such as the number of instances, the number of features, and data distribution affect the performance of normalization and classification.

Demographic history of Platypus quercivorus (Coleoptera: Curculionidae), a beetle causing mass mortality of oak trees, in eastern Japan

Abstract In recent years, Japanese oak wilt causing mass mortality of oak trees has exhibited a significant geographical expansion. Understanding the formation history of current local populations of Platypus quercivorus Murayama, a vector of Japanese oak wilt, is important foundational knowledge for effectively preventing forest damage. In this study, we used genome-wide single nucleotide polymorphism data to infer the population genetic structure and historical demography of P. quercivorus populations in eastern Japan, where Japanese oak wilt is rapidly expanding. We found at least 3 distinct genetic groups, each of which caused Japanese oak wilt in different areas. The supported scenario suggests that 1 of 2 genetic groups in the northeast first diverged from the ancestral population, then the other group diverged from the southwestern population, followed by gene flow between the 2 groups. Recent admixtures of the 2 northeastern groups were identified at certain sites. The geographic genetic structure of the populations suggested that each genetic group experienced recent range expansion. Although genetically independent populations had caused oak tree mass mortality in their original distribution range, our results support the hypothesis that the recent geographic expansion of Japanese oak wilt outbreaks is attributed to the range expansion of these P. quercivorus groups.

New range record for Campbell’s monkeys (<i>Cercopithecus campbelli</i>) in West Africa

The current distribution of Campbell’s monkeys Cercopithecus campbelli extends from southwestern Gambia to the western Ivory Coast. In Senegal, it has only been confirmed in the western part of the country. Here, we report for the first time its presence in southeastern Senegal. We obtained camera trap footage of a Campbell’s monkey individual in the Dindefelo Community Nature Reserve located in Kedougou region, 174 km away from its known distribution range. In the footage, a single Campbell’s monkey appears alongside a group of at least nine green monkeys Chlorocebus sabaeus. We discuss different hypotheses that could explain the presence of the Campbell’s monkey in Dindefelo, and conclude that this individual may be a single migrant.

Multidisciplinary design optimization of an autonomous underwater vehicles based on random uncertainty

Herein, discipline decomposition was performed for an autonomous underwater vehicle (AUV) based on multidisciplinary design optimization (MDO), and its design parameters were determined. Parameterized analysis of the hull-form and structure disciplines was performed, and an approximate model of these disciplines was established with a high fitting accuracy. An analysis model of propulsion, energy, and system disciplines was developed based on the formula method. Based on collaborative optimization as well as discipline and system level models, a deterministic MDO framework for AUVs was established. Subsequently, an optimized solution was obtained. By considering the random uncertainty of design variables, an MDO framework for the uncertainty of AUVs was established and optimized solutions were obtained. The distribution of solutions obtained from uncertainty optimization was more concentrated and the distribution range was smaller than that obtained using deterministic optimization. Robustness analysis was performed on the initial scheme, typical deterministic optimization schemes, and typical uncertainty optimization schemes. Results showed that fluctuations in design variables may lead to constraints that exceed boundary conditions in the deterministic optimization design scheme. Using uncertainty and objective function optimization, the robustness of the overall scheme of AUVs was improved.

Expansion of the distribution range of angiosperm species for the states of Maranhão and Tocantins, Brazil, through a territorial action plan

We expand the geographical distribution of 10 angiosperm species in Maranhão and Tocantins states. The species were collected during two field expeditions carried out by the Territorial Action Plan for the conservation of endangered species of the Meio Norte Territory between September 20 and 30, 2022 and between July 24 and 30, 2023, in both states. Photographs, comments on morphology and distribution-al data are provided for species of Acanthaceae, Aristolochiaceae, Euphorbiaceae, Myrtaceae, Orchidace-ae, Plantaginaceae, Pontederiaceae and Turneraceae.

An alternative subgeneric classification of Kalanchoe (Crassulaceae subfam. Cotyledonoideae) globally: a nomenclatural and taxonomic review, with a new status for K. subg. Pubescentes

In the most recently presented global synopsis of Kalanchoe (Crassulaceae subfam. Cotyledonoideae), which was published in 2003 by Bernard Marie Descoings (1931–2018), only two sections, K. sect. Kalanchoe [geographically widespread] and K. sect. Bryophyllum [geographically naturally limited to Madagascar, but with some species and nothospecies naturalised elsewhere], were recognised in the genus. Three years later, Descoings changed his views on the infrageneric classification of Kalanchoe when, in 2006, he published the subgenus name K. subg. Calophygia for a rather disparate group of species from virtually across the entire natural geographical distribution range of the genus. In this regard, Descoings built on and expanded the kalanchooid infrageneric concept that Sijfert Hendrik Koorders (1863–1919) put forward for Kalanchoe almost 90 years earlier. Apart from recognising K. subg. Calophygia in 2006, Descoings additionally upheld the autonymic K. subg. Kalanchoe and K. subg. Bryophyllum, both of which he recognised at the rank of section in 2003. The infrageneric classification of Kalanchoe that recognises primary diversity in the genus at the rank of subgenus, rather than at that of section, is now firmly entrenched. Following on from Descoings recognising three subgenera in 2006, the subgenus classification of Kalanchoe has recently been expanded with the publication of a further four subgenus names, in 2018 (K. subg. Kitchingia), in 2020 (K. subg. Fernandesiae), in 2023 (K. subg. Alatae), and in 2024 (K. subg. Pubescentes). The most up-to-date subgenus classification of Kalanchoe is presented here, with five subgenera recognised. With the exception of the geographically widespread K. subg. Kalanchoe, the four other subgenera are naturally endemic to Madagascar.

Arrival‐breeding interval is flexible in a songbird and is not constrained by migration carry‐over effects

Abstract As spring phenology advances with climate change, so too must the timing of life cycle events. Breeding at the right time is critical in many species as it maximizes fitness. For long‐distance migratory birds, flexibility in the duration of the arrival‐breeding interval (pre‐breeding period) may allow populations to adjust their timing of breeding. However, whether first egg‐lay dates are flexible to local environmental conditions after arrival, and if they are constrained by the time needed to replenish energy lost during migration, remains unclear. We investigated the regional flexibility of the arrival‐breeding interval in an avian migrant, the purple martin, Progne subis, across their breeding range. We evaluated whether the duration of the arrival‐breeding interval was flexible to temperature and precipitation at breeding sites, and if timing was limited by migration rate and stopover duration. We also tested if longer interval durations were associated with higher fledging success. To address our hypotheses, we used a combination of migration tracking, weather and breeding data collected from four regions across eastern North America (26.1° N to 52.4° N latitude). We found the arrival‐breeding interval to be shortest in the north and longest in the south. Across all regions, warmer temperatures encountered at breeding grounds were associated with shorter intervals, and faster migration rates led to longer intervals. The length of the interval was not influenced by precipitation or stopover duration. Finally, longer intervals were not associated with higher fledge success. Currently, the longer arrival‐breeding intervals in this study system, on average 28.3 days, may provide both early and late‐arriving birds with ample time for recovery so birds can lay eggs according to temperature. Any negative effects of faster migration may have been buffered by longer arrival‐breeding intervals, as interval length did not determine fledge success. With ongoing climate change, further research is needed to examine if arrival‐breeding intervals become constrained by migration timing, which may limit opportunities for migrants to match the timing of breeding with key resources.

Gene expression plasticity in response to rapid and extreme elevation changes in Perdix hodgsoniae (Tibetan Partridge)

Abstract Phenotypic plasticity is a vital biological process facilitating the persistence of organisms amid rapid environmental changes. Investigating the genetic basis of plastic traits necessitates transplantation experiments, but much of the existing research has focused on laboratory model systems. Transplant experiments in the wild may provide better understanding of how plasticity operates in the context of real-world challenges. However, performing transplantation experiments in non-model systems, such as birds, could be challenging. In this study, we aim to develop Perdix hodgsoniae (Tibetan Partridge) inhabiting the highlands of the Tibetan Plateau as a suitable system to study genetic basis underlying short-term plastic response to rapid changes in elevation. We did a first attempt of field-based transplantation experiment by exposing P. hodgsoniae individuals to extreme change in elevation from their native elevation (3,623 m) to a low elevation outside their natural distribution range (500 m). We compared changes in gene expression in these birds at different time points, pre-transplant (Day 0), and post-transplant (Day 3 and Day 22). The birds successfully survived transplantation and exhibited well-being after 22 days. We identified a total of 715 differentially expressed genes (DEGs) across these 3 time points. Our analysis revealed a genome-wide decrease in expression following the transplantation, indicating that the birds possibly exhibited stress-induced transcriptional attenuation (SITA) because of the extreme change in elevation, suggesting a broader response at the transcriptional level, possibly as a mechanism to cope with extreme changes in the environment. Our analysis further suggested that heat stress posed an immediate challenge for the birds following the transplant, as we identified changes in expression in many genes associated with heat stress response. Our findings affirm the viability of conducting transplant experiments in the P. hodgsoniae and provides initial insights into gene expression changes associated with the plastic response to rapid changes in elevation in these birds.

Changes in biogeographic patterns of coastal benthic decapods: Indicators of tropicalization in the Canary Islands over the last 50 years

The Canary Islands constitute one of the major marine biodiversity hotspots in the eastern-central Atlantic, with decapod crustaceans being a highly representative group in the benthic environment due to their vast diversity of taxa and occupied ecosystems. This study identifies three significant milestones corresponding to the publication of comprehensive decapod checklist for the Canary Islands in 1973, 1995, and 2018. The lists of coastal benthic decapod species (0–300 m depth) were revised and updated, indicating the biogeographic pattern and vertical distribution range of each species in the region. Changes in the composition of the biogeographic patterns of coastal decapods in the Canary Islands were analysed to evaluate whether they could be considered as a useful indicator of the tropicalization process in the region. Particular attention was paid to variations in the percentages of species with warm water affinity versus those with Atlanto-Mediterranean preferences, with the former showing a clear upward trend.

Prediction of Forest-Fire Occurrence in Eastern China Utilizing Deep Learning and Spatial Analysis

Forest fires are a major natural calamity that inflict substantial harm on forest resources and the socio-economic landscape. The eastern region of China is particularly susceptible to frequent forest fires, characterized by high population density and vibrant economic activities. Precise forecasting in this area is essential for devising effective prevention strategies. This research utilizes a blend of kernel density analysis, autocorrelation analysis, and the standard deviation ellipse method, augmented by geographic information systems (GISs) and deep-learning techniques, to develop an accurate prediction system for forest-fire occurrences. The deep-learning model incorporates data on meteorological conditions, topography, vegetation, infrastructure, and socio-cultural factors to produce monthly forecasts and assessments. This approach enables the identification of spatial patterns and temporal trends in fire occurrences, enhancing both the precision and breadth of the predictions. The results show that global and local autocorrelation analyses reveal high-incidence areas mainly concentrated in Guangdong, Fujian, and Zhejiang provinces, with cities like Jiangmen exhibiting distinct concentration characteristics and a varied spatial distribution of fire occurrences. Kernel density analysis further pinpoints high-density fire zones primarily in Meizhou, Qingyuan, and Jiangmen in Guangdong Province, and Dongfang City in Hainan Province. Standard deviation ellipse and centroid shift analysis indicate a significant northward shift in the fire-occurrence centroid over the past 20 years, with an expanding spatial distribution range, decreasing flattening, and relatively stable fire-occurrence direction. The model performs effectively on the validation set, achieving an accuracy of 80.6%, an F1 score of 81.6%, and an AUC of 88.2%, demonstrating its practical applicability. Moreover, monthly fire zoning analysis reveals that high-incidence areas in spring and winter are mainly concentrated in Guangdong, Fujian, Zhejiang, and Hainan, while autumn shows widespread medium-incidence areas, and summer presents lower fire occurrences in most regions. These findings illustrate the influence of seasonal climate variations on fire occurrences and highlight the necessity for enhanced fire monitoring and prevention measures tailored to different seasons.