Occurrence Dataset Research Articles

Swimming in the Sahara: a new locality record and range extension of Natrix maura (Linnaeus, 1758) (Squamata, Colubridae) from central Algeria

Natrix maura, commonly known as the viperine snake, is a widespread and common semi-aquatic species in the western Mediterranean region. This study reports a new locality record of N. maura from central Algeria, significantly extending the species’ known range. Additionally, we provide an updated distribution map of N. maura in Algeria, compiled from a comprehensive dataset of occurrence records. Our findings emphasize the need for extensive herpetofaunal surveys in the country’s underexplored regions. Dataset published through GBIF (DOI: 10.15470/fe3689)

Current and Future Probability of Occurrence of the Floodwater Mosquito Aedes vexans (Meigen, 1830) in the Netherlands

ABSTRACTAedes vexans (Meigen, 1830) is a floodwater mosquito species that may cause significant nuisance and can serve as a vector for multiple arboviruses. Its distribution is expected to shift in the future as a result of changes in climate and land use. Understanding these shifts is important for estimating future disease risk. This study aims to identify habitat suitability and probability of occurrence of A. vexans. Using the Netherlands as a case study, we utilised an occurrence dataset generated by the Netherlands Centre for Monitoring of Vectors. We employed an auto machine learning approach to model generation, using a variety of modelling methodologies, determining the optimal ratio of presence: Absence datapoints in the training data and ultimately creating a 10‐model ensemble. We selected predictor variables relating to weather, land use, soil properties, flood risk and salinity. The probability of A. vexans presence was predicted on a 1 km grid for both the current Dutch situation and for four scenarios for 2050. Our analysis identified temperature, soil type and land cover as the primary determinants influencing the probability of A. vexans occurrence. Future projections reveal an increase in the likelihood of A. vexans occurrence in the study area, particularly along major river corridors and in regions with increasing amounts of artificial and natural areas. Additionally, the mosquito season is predicted to become longer under all future scenarios. Insights provided in our study can also be applied to other similar areas, such as other north‐western European countries or other urban deltas. This study shows for the first time detailed future occurrence predictions and also future seasonal predictions for this mosquito species. Seasonal predictions allow researchers to study how disease risk changes throughout the year, something which is particularly valuable given the predicted lengthening of the mosquito (and thus disease transmission) season.

A Comparison of Thunderstorm Identification Methods

Abstract Climatological analysis of thunderstorm occurrence is important since thunderstorms have far-reaching societal impacts. Historically, the majority of thunderstorm-related climatologies have focused on Eulerian frames of reference resulting in thunderstorm day or lightning density summaries. However, a Lagrangian frame of reference is required to answer more in-depth questions such as spatial distribution and variability in thunderstorm initiation. Lagrangian approaches generally utilize object identification and tracking algorithms with tracks then classified as being a thunderstorm or not. Prior methods for thunderstorm identification have been based on classification criteria such as radar reflectivity thresholds, a combination of radar reflectivity thresholds and temporal longevity thresholds, or a combination of radar reflectivity and cloud-to-ground lightning occurrence. However, a comparison of different methods and an evaluation of their accuracy have not been documented in the peer-reviewed literature. This study examines the impact of thunderstorm identification methodology choice. Differences in three thunderstorm identification methodologies are examined over the central plains of the United States during an 11-yr study period. Results show that there is a sensitivity to methodological choice with differences in the number of candidate thunderstorms classified as thunderstorms, as well as the resulting spatial pattern of thunderstorms. Additionally, this study provides insight into the accuracy of each method via a multiyear comparison of each method to regional lightning mapping array total lightning detections where significant differences were observed between methods with the method incorporating cloud-to-ground lightning data providing the best performance metrics. Significance Statement Previous research has utilized a variety of criteria to identify thunderstorms in order to generate datasets of thunderstorm occurrence. This study directly compares commonly used criteria, demonstrating that the choice of thunderstorm identification criteria impacts the composition and accuracy of resulting datasets of thunderstorm occurrence.

A georeferenced dataset of heavy metals occurrence in the soils of the Yangtze River Basin, China

A georeferenced dataset of heavy metals occurrence in the soils of the Yangtze River Basin, China

National-Scale Geospatial Modelling of Pyrrhotite in Bedrock Across Canada: A Pilot Study

The most abundant iron sulphide minerals in igneous, metamorphic, and some sedimentary rocks are FeS2 (pyrite/marcasite) and Fe1-xS (pyrrhotite). The oxidation of pyrite and pyrrhotite in bedrock aggregates and mine tailings is undesirable to infrastructure and the environment because such chemical reactions are linked with concrete deterioration and acid mine drainage, respectively. The oxidation rate of pyrrhotite is up to one hundred times greater than that of pyrite; thus, pyrrhotite oxidation is of particular concern to society. Pyrrhotite-bearing concrete aggregates may lead to rapid expansion cracking and failure of critical concrete infrastructure including bridges, buildings, and houses, posing a significant safety concern. Additionally, premature disintegration of concrete requires replacement of concrete, leading to excessive aggregate resource extraction and associated increases in CO2 emissions. Considering the widespread concrete infrastructure across Canada, the distribution of pyrrhotite in bedrock used for aggregate is of fundamental importance to the short- and long-term safety of Canadians at the national, regional, and local scales. This pilot study details the initial steps taken to generate national-scale geospatial models of pyrrhotite occurrences in bedrock across Canada and illustrates the associated map products. In total, 12,577 known pyrrhotite occurrences were identified from publicly available provincial and territorial mineral occurrence datasets. The overall modelling strategy involved normalizing the number of pyrrhotite occurrences with respect to the total surface area of major bedrock types and characterizing three different classes of pyrrhotite occurrence density (< 1, 1–4, and 4–10 occurrences/1000 km2). The maps illustrate that pyrrhotite occurrence density is highest in volcanic rocks and undifferentiated sedimentary and volcanic rocks, moderate in intrusive and unknown rocks, and lowest in sedimentary and metamorphic rocks. Sedimentary rocks with no pyrrhotite occurrences span large surface areas across central-western Canada thus resulting in an overall low pyrrhotite occurrence density (< 1 occurrence/1000 km2) for this rock type, despite the fact that numerous pyrrhotite occurrences are identified in sedimentary rocks and may be abundant locally or regionally. Volcanic, undifferentiated sedimentary and volcanic, intrusive, and unknown rocks occur throughout the Canadian Shield of central and northern Canada, the Cordillera of western Canada, and the Appalachians of eastern Canada, but bedrock type and associated occurrence density are highly variable within these geological domains. Comparison of pyrrhotite occurrence density maps for Canada with pyrrhotite permissive geology maps for the United States of America illustrates that rocks with a high pyrrhotite occurrence density in Canada (volcanic rocks and undifferentiated sedimentary and volcanic rocks), are contiguous overall with areas of pyrrhotite potential in the United States. Inconsistencies across the international border reflect the differing methodologies and assumptions consisting of a statistically based approach for Canada and a qualitative approach for the United States. In the Cordillera and Appalachians, such discontinuities across the international border may reflect the underestimation of pyrrhotite occurrences in sedimentary rocks of Canada because of the impact of high surface area on the pyrrhotite occurrence density calculations. The maps presented herein are a first step in illustrating the distribution of pyrrhotite-bearing bedrock across Canada and greater North America. These national-scale map products are useful first-order references for selecting regions for follow-up studies on bedrock pyrrhotite occurrences. Regional and local geospatial analysis combined with field work for ground truthing will be important aspects of future research, especially in the vicinity of population centres where bedrock is utilized for concrete aggregate. Detailed regional and local studies of pyrrhotite occurrences in bedrock will help guide the extraction of safe concrete aggregate and contribute to the long-term sustainability of bedrock resources, safe infrastructure, and a habitable climate.

Evaluating species distribution model predictions through time against paleozoological records.

Species distribution models (SDMs) are widely used to project how species distributions may vary over time, particularly in response climate change. Although the fit of such models to current distributions is regularly enumerated, SDMs are rarely tested across longer time spans to gauge their actual performance under environmental change. Here, we utilise paleozoological presence/absence records to independently assess the predictive accuracy of SDMs through time. To illustrate the approach, we focused on modelling the Holocene distribution of the hartebeest, Alcelaphus buselaphus, a widespread savannah-adapted African antelope. We applied various modelling algorithms to three occurrence datasets, including a point dataset from online repositories and two range maps representing current and 'natural' (i.e. hypothetical assuming no human impact) distributions. We compared conventional model evaluation metrics which assess fit to current distributions (i.e. True Skill Statistic, TSSc, and Area Under the Curve, AUCc) to analogous 'paleometrics' for past distributions (i.e. TSSp, AUCp, and in addition Boycep, F2-scorep and Sorensenp). Our findings reveal only a weak correlation between the ranking of conventional metrics and paleometrics, suggesting that the models most effectively capturing present-day distributions may not be the most reliable to hindcast historical distributions, and that the choice of input data and modelling algorithm both significantly influences environmental suitability predictions and SDM performance. We thus advocate assessment of model performance using paleometrics, particularly those capturing the correct prediction of presences, such as F2-scorep or Sorensenp, due to the potential unreliability of absence data in paleozoological records. By integrating archaeological and paleontological records into the assessment of alternative models' ability to project shifts in species distributions over time, we are likely to enhance our understanding of environmental constraints on species distributions.

Habitat availability decline for waterbirds in a sensitive wetland: Climate change impact on the Ebro Delta

The highly biodiverse, productive and vulnerable areas, such as coastal wetlands, are increasingly threatened by human-induced disturbances, resulting in habitat loss. This habitat loss is a critical driver of biodiversity decline and significantly impacts species distribution and behavior, increasing the risk of extinctions. To address these concerns, we developed a Species Distribution Model (SDM) using a decade-long dataset of waterbird functional group occurrences in the Ebro Delta, with a particular focus on the Ardeidae family, which represents the most prominent species in the wetland. This model aims to predict potential habitat loss under various climate change scenarios, specifically those outlined in the Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathways (RCP) 4.5 and 8.5, across three distinct time periods.Our SDM revealed that habitat suitability for waterbirds was notably influenced by temperature variations, increased cumulative precipitation, and lower terrain elevation. Predictions indicate an increase in available habitat for these waterbird species over the study periods considering the specified climate scenarios. However, the incorporation of sea-level rise and flooded areas into the models unveiled a dramatic decline in available areas for waterbirds in the long-term, reaching up to 50 % (RCP 4.5) and 70 % (RCP 8.5) reduction.Our study highlights the urgent need for conservation efforts to mitigate the substantial reduction in available habitat for waterbirds. This need is especially crucial due to the Ebro Delta's importance as a vital coastal wetland for many thousands of waterbirds throughout their entire life cycle. Immediate and targeted conservation actions are imperative to safeguard the essential habitats for these species.

The Best of Two Worlds: Using Stacked Generalisation for Integrating Expert Range Maps in Species Distribution Models

ABSTRACTAimSpecies distribution models (SDMs) are powerful tools for assessing suitable habitats across large areas and at fine spatial resolution. Yet, the usefulness of SDMs for mapping species' realised distributions is often limited since data biases or missing information on dispersal barriers or biotic interactions hinder them from accurately delineating species' range limits. One way to overcome this limitation is to integrate SDMs with expert range maps, which provide coarse‐scale information on the extent of species' ranges and thereby range limits that are complementary to information offered by SDMs.InnovationHere, we propose a new approach for integrating expert range maps in SDMs based on an ensemble method called stacked generalisation. Specifically, our approach relies on training a meta‐learner regression model using predictions from one or more SDM algorithms alongside the distance of training points to expert‐defined ranges as predictor variables. We demonstrate our approach with an occurrence dataset for 49 bat species covering four biodiversity hotspots in the Eastern Mediterranean, Western Asia and Central Asia.Main ConclusionsOur approach offers a flexible method to integrate expert range maps with any combination of SDM modelling algorithms, thus facilitating the use of algorithm ensembles. In addition, it provides a novel, data‐driven way to account for uncertainty in expert‐defined ranges not requiring prior knowledge about their accuracy, which is often lacking. Integrating expert range maps into SDMs for bats resulted in more realistic predictions of distribution patterns that showed narrower niche breadths and smaller range overlaps between species compared to traditional SDMs. Our approach holds promise to improve assessments of species distributions, while our work highlights the overlooked potential of stacked generalisation as an ensemble method in species distribution modelling.

Warming summer temperatures are rapidly restructuring North American bumble bee communities.

A rapidly warming climate is driving changes in biodiversity worldwide, and its impact on insect communities is critical given their outsized role in ecosystem function and services. We use a long-term dataset of North American bumble bee species occurrences to determine whether the community temperature index (CTI), a measure of the balance of warm- and cool-adapted species in a community, has increased given warming temperatures. CTI has increased by an average of 0.99°C in strong association with warming maximum summer temperatures over the last 30 years with the areas exhibiting the largest increases including mid- to high latitudes as well as low and high elevations-areas relatively shielded from other intensive global changes. CTI shifts have been driven by the decline of cold-adapted species and increases in warm-adapted species within bumble bee communities. Our results show the pervasive impacts and ecological implications warming temperatures pose to insects.

Distribution and historical aspects of Brazilian Stachytarpheta (Verbenaceae): Exploring a comprehensive dataset of taxonomically verified specimens

Stachytarpheta (Verbenaceae) encompasses approximately 120 species distributed throughout tropical and subtropical regions of the Americas, with Brazil boasting the highest species richness (90 spp.) and endemism (82 spp.). This study introduces an updated, taxonomically revised, and credible occurrence dataset focusing on Stachytarpheta species in Brazil, comprising 4,843 records. This dataset results from expert revision of herbarium collections and integration with global repositories alongside national repositories in Brazil. It facilitates a thorough exploration of the temporal, geographical, and taxonomic patterns of Stachytarpheta across diverse regions and landscapes in Brazil. Stachytarpheta species and their occurrence records are concentrated in the states of Minas Gerais, Bahia, and Goiás, particularly in the campo rupestre and savanna formations of the Espinhaço Range and Chapada dos Veadeiros. Analysis of potential biases within our dataset revealed a correlation between specimen occurrences and proximity to roads. Rarefaction curves indicate ongoing potential for species discovery within the Cerrado and Caatinga domains, with the Tocantins state emerging as a particularly promising area for novel findings; therefore, presenting opportunities for exploration. The majority of the specimens are housed in Brazilian herbaria, particularly at RB, HUEFS, and CESJ. Temporal analysis of occurrence records showed an upward trend during the 20th century and the first decade of the 21st century, which can be attributed to the efforts of generalist collectors working mostly in Eastern and Central Brazil. Most collection efforts were carried out through Brazilian and European initiatives, often supported by local funding, especially during the mid-20th century. However, funding for scientific initiatives in Brazil has waned since the mid-2010s, potentially affecting recent trends in species recording. Our dataset serves as a resource enabling subsequent analysis delving into the systematics, biogeography, and conservation of this remarkable genus from open vegetation formations in Brazil.

Wild Edible Plant Species in the ‘King’s Lagoon’ Coastal Wetland: Survey, Collection, Mapping and Ecological Characterization

Wild edible plants, botanically defined as phytoalimurgical species, have historically been a useful source of food to cope with recurrent famines and poor farming conditions. If properly identified, harvested, transformed and promoted, alimurgical plants could further enhance the wellbeing of rural and urban communities and the multifunctional productivity of agriculture. The research aimed to survey alimurgical species in a wetland, map their location, detect their spatial richness, and develop a monitoring plan for ongoing vegetation succession. The study area is the King’s Lagoon, a wetland that has recently undergone a radical restoration of its natural layout. A satellite image was used to create a land cover map and interpret the relationship between plant species and land cover. The survey provided a snapshot of the wetland’s current ecosystem status and used botanical analysis and ecological indices to investigate biodiversity levels. The alpha, beta and gamma levels of biodiversity were explored and interpreted through the statistical processing of a comprehensive dataset of species occurrence and abundance, together with the calculation of Shannon’s, Simpson’s and Jaccard’s indices. It was observed that biodiversity in the wetland is developing gradually following restoration and is expected to increase over time as successional stages take hold. Biodiversity is more pronounced along the banks of the canals and watercourses connecting the basins and open ponds, while it is less pronounced in areas where the soil has been disturbed by previous excavations. Salicornia spp., Beta vulgaris subsp. maritima and Suaeda vera were identified as the most common and interesting species found in the study area. The potential for cultivation of some of the halophyte species that were monitored was also highlighted, with particular reference to the selection of the most commercially interesting species, the best species associations and intercropping practices in a wetland context, which must always prioritize the conservation of wild biodiversity. The spring surveys should be repeated in the coming years in order to accurately trace the dynamics of the ecological succession of this particular ecosystem, once it has returned to its natural development.

Antarctica is less isolated with increasing depth - evidence from pycnogonids

No other group of animals typifies the uniqueness of Antarctic life more than Pycnogonida (sea spiders), with 20% of all known species found in the Southern Ocean, and 64% of these endemic to the Antarctic. Despite nearly 200 years of research into pycnogonids and other benthic phyla in Antarctica, the parameters which drive the distribution and diversity of benthic fauna are still poorly understood. This study aimed to investigate the diversity and connectivity of pycnogonid communities on either side of the Antarctic Polar Front, with an emphasis on the role of water depth, using an occurrence dataset containing 254 pycnogonid species from 2187 sampling locations. At depths shallower than 1000 m, communities to the north and south of the Antarctic Polar Front were distinct, while below this depth this geographic structure disintegrated. The Polar Front, or the expanse of deep ocean it bisects, seemingly acts as a semipermeable barrier to species exchange between well-sampled shallow communities. The less sampled and less understood deep sea appears to be better connected, with high levels of shared species following the northward flow of Antarctic Bottom Water. The exceptionally high diversity and endemism of Antarctic pycnogonids may reflect an apparent competitive advantage in cold waters which leaves them vulnerable to ongoing ocean warming, with increased competition and predation pressures.

Ocurrence dataset of birds in university campuses of Nanjing, Juangsu Province China.

The protection of urban biodiversity plays a critical role in maintaining urban ecological security. As a unique taxon of urban wildlife, birds have been intensively used as an indicator of our surrounding environment. Although the diversity of urban bird species has received increasing attention, present studies are mainly focused on urban parks. As one of the important components of the urban ecosystem, the university campus also plays a critical role in maintaining bird diversity. Due to the lack of observation data, it is a challenge to evaluate the impact of the environmental conditions on campus bird diversity. Given the most concentrated higher education resources in China, Nanjing has a large number of universities, covering a wide area of the urban landscape. The landscape of these universities usually has a high percentage of green space as well as waterbodies, which is conducive to attracting various bird species to inhabit. Here, we conducted a one-year bird survey from January 2019 to December 2019 in 12 universities in Nanjing and provided an occurrence dataset containing detailed species and geographical information, providing a good source to study the ecological and anthropogenic factors on urban bird diversity on a local and larger scale. This dataset represents the first annual record of birds publicly released by 12 universities in Nanjing, Jiangsu Province. It includes classification information, population, distribution and survey details. All data have been published on GBIF.

Evolutionary factors and habitat filtering affect the pattern of Gerbillinae diversity

Abstract How ecological and evolutionary factors affect small mammal diversity in arid regions remains largely unknown. Here, we combined the largest phylogeny and occurrence dataset of Gerbillinae desert rodents to explore the underlying factors shaping present-day distribution patterns. In particular, we analyzed the relative contributions of ecological and evolutionary factors on their species diversity using a variety of models. Additionally, we inferred the ancestral range and possible dispersal scenarios and estimated the diversification rate of Gerbilliane. We found that Gerbillinae likely originated in the Horn of Africa in the Middle Miocene and then dispersed and diversified across arid regions in northern and southern Africa and western and central Asia, forming their current distribution pattern. Multiple ecological and evolutionary factors jointly determine the spatial pattern of Gerbillinae diversity, but evolutionary factors (evolutionary time and speciation rate) and habitat filtering were the most important in explaining the spatial variation in species richness. Our study enhances the understanding of the diversity patterns of small mammals in arid regions and highlights the importance of including evolutionary factors when interpreting the mechanisms underlying large-scale species diversity patterns.

The roles of abiotic and biotic factors in driving range shifts: An invasive Pomacea snail facilitates Rostrhamus sociabilis (Snail Kite) northward range expansion

Abstract Rostrhamus sociabilis (Snail Kite) have recently expanded their range in Florida, tracking the invasion of a Pomacea snail (P. maculata), and exhibiting considerable changes in bill size and feeding niche. This range expansion is not aligned with changes in climatic conditions or the distribution of their historic prey (P. paludosa). The Eltonian Noise Hypothesis (ENH), which posits that interactive (biotic) factors have stronger effects on species’ distributions at local scales, predicts that noninteractive (abiotic) factors are generally more relevant at geographic extents. However, in this study, we explore the R. sociabilis range shift as a potential counterexample of the ENH. Under the biotic-abiotic-mobility framework (BAM), we explore the role of biotic and abiotic factors in the northward range expansion of this endangered species. Over the past 15 years, R. sociabilis have begun consuming the more-abundant invasive snails more often, while increasing in bill size, expanding ~175 km northward from previous range limits in the Kissimmee River Valley. We developed ecological niche models using 3 algorithms (Maxent, generalized linear model, ellipsoids) and found stability in climatic suitability between past and present models. Moreover, although native snails occur in northern Florida, R. sociabilis have had a historically patchy northern distribution due in part to the availability of appropriate wetland conditions. We found a strong latitudinal cline, with bill length increasing with latitude at least through 2020, suggesting that this morphological change broadened the species’ biotic suitable area and distributional potential. The interplay between changes in phenotype and biotic interactions has been poorly documented in distributional ecology, given a lack of rich occurrence datasets. Here, we highlight a case in which a biological invasion and subsequent changes in morphology and diet have facilitated the expansion of a specialized predator into areas that were unsuitable until recently.

A comprehensive dataset of the geophilid centipedes of the south-eastern Alps (Chilopoda, Geophilomorpha, Geophilidae s.l.).

Centipedes of the family Geophilidae s.l. are widespread in the Holarctic, with the south-eastern part of the European Alps standing out as one of the most investigated regions. However, retrieving the published records for this taxon, even for this region, is challenging, since most of them are sparse in the specialised literature and interpreting them is hampered by the many taxonomic and nomenclatorial changes occurred in the past and recent times. We assembled and released a dataset of occurrence records of the geophilid species in the south-eastern Alps, including all the published records and many other records present in unpublished catalogues of scientific collections. For each record, we integrated information from all the sources about: locality, date of collection, the taxonomic identifications, number and sex of individuals and available sequences of molecular markers. For all the records, we estimated geographic coordinates of the locality, when not originally provided, based on the information available. We also estimated the accuracy of the position.The dataset includes 3293 records referred to 39 species, obtained since the first half of the 19th century and up to 2022; 52% of these records have been released publicly for the first time in the dataset here described.

Incorporating physiological knowledge into correlative species distribution models minimizes bias introduced by the choice of calibration area

Correlative species distribution models (SDMs) are important tools to estimate species’ geographic distribution across space and time, but their reliability heavily relies on the availability and quality of occurrence data. Estimations can be biased when occurrences do not fully represent the environmental requirement of a species. We tested to what extent species’ physiological knowledge might influence SDM estimations. Focusing on the Japanese sea cucumber Apostichopus japonicus within the coastal ocean of East Asia, we compiled a comprehensive dataset of occurrence records. We then explored the importance of incorporating physiological knowledge into SDMs by calibrating two types of correlative SDMs: a naïve model that solely depends on environmental correlates, and a physiologically informed model that further incorporates physiological information as priors. We further tested the models’ sensitivity to calibration area choices by fitting them with different buffered areas around known presences. Compared with naïve models, the physiologically informed models successfully captured the negative influence of high temperature on A. japonicus and were less sensitive to the choice of calibration area. The naïve models resulted in more optimistic prediction of the changes of potential distributions under climate change (i.e., larger range expansion and less contraction) than the physiologically informed models. Our findings highlight benefits from incorporating physiological information into correlative SDMs, namely mitigating the uncertainties associated with the choice of calibration area. Given these promising features, we encourage future SDM studies to consider species physiological information where available.

Forest fire susceptibility assessment under small sample scenario: A semi-supervised learning approach using transductive support vector machine

Forest fires threaten global ecosystems, socio-economic structures, and public safety. Accurately assessing forest fire susceptibility is critical for effective environmental management. Supervised learning methods dominate this assessment, relying on a substantial dataset of forest fire occurrences for model training. However, obtaining precise forest fire location data remains challenging. To address this issue, semi-supervised learning emerges as a viable solution, leveraging both a limited set of collected samples and unlabeled data containing environmental factors for training. Our study employed the transductive support vector machine (TSVM), a key semi-supervised learning method, to assess forest fire susceptibility in scenarios with limited samples. We conducted a comparative analysis, evaluating its performance against widely used supervised learning methods. The assessment area for forest fire susceptibility lies in Dayu County, Jiangxi Province, China, renowned for its vast forest cover and frequent fire incidents. We analyzed and generated maps depicting forest fire susceptibility, evaluating prediction accuracies for both supervised and semi-supervised learning methods across various small sample scenarios (e.g., 4, 8, 12, 16, 20, 24, 28, and 32 samples). Our findings indicate that TSVM exhibits superior prediction accuracy compared to supervised learning with limited samples, yielding more plausible forest fire susceptibility maps. For instance, at sample sizes of 4, 16, and 28, TSVM achieves prediction accuracies of approximately 0.8037, 0.9257, and 0.9583, respectively. In contrast, random forests, the top performers in supervised learning, demonstrate accuracies of approximately 0.7424, 0.8916, and 0.9431, respectively, for the same small sample sizes. Additionally, we discussed three key aspects: TSVM parameter configuration, the impact of unlabeled sample size, and performance within typical sample sizes. Our findings support semi-supervised learning as a promising approach compared to supervised learning for forest fire susceptibility assessment and mapping, particularly in scenarios with small sample sizes.

Habitat connectivity of threatened ungulate species in a native savanna landscape of northern South America

AbstractThe native savanna ecosystem of the Orinoquia region is the habitat of 50% of the wild ungulate species reported for Colombia. Over the last 20 years, this high species diversity has been strongly threatened by the human transformation of the natural land cover causing connectivity loss of the habitats. The Orinoquia region lacks a biological connectivity analysis with a multi-species approach involving species groups that are representative of the savanna ecosystem such as the ungulates. Understanding the spatial distributions of suitable areas and the main habitats that act as primary habitats for ungulate species in these landscapes is fundamental for the design of conservation strategies. We use an occurrence dataset for lowland tapir (Tapirus terrestris), white-tailed deer (Odocoileus virginianus), and white-lipped peccary (Tayassu pecari) in the development of species’ potential distribution models, binarization process, and morphological spatial pattern analysis. This information was used for the modeling of dispersal corridors connecting the core habitats of the ungulate focal species using the randomized shortest path algorithm and quantifying the weighted global connectivity metrics. Our results suggest an integral corridor with potential least-cost dispersal routes between the native savanna landscape on the middle basins of the savanna rivers and the Meta River. These areas associated with the fluvial dendritic systems are connected, while the core habitats in the eastern part of the savanna landscape are disconnected. We discuss how the application of such knowledge on the spatial ecology of ungulate focal species might improve the management of the metapopulations in the Orinoquia region.

The comprehensive checklist of myxomycetes of Ukraine, based on extended occurrence and reference datasets.

A significant body of valuable data about the myxomycetes of Ukraine lies in a "grey zone". This encompasses undigitised historical books and articles published in languages such as Polish, French or German, as well as proceedings from local conferences, articles featured in local scientific journals and annual reports submitted to public authorities by employees of protected areas, published in Ukrainian or Russian. Yet, due to their exclusive existence in print and often the Cyrillic alphabet, these publications remain neither findable nor accessible to a wider audience. The datasets presented here aim to summarise over 150 years of myxomycetes research in Ukraine. The majority of the data has been extracted from published literature sources spanning the years 1842 to 2023, with a minor supplement from unpublished herbarium specimens. The datasets include 5036 georeferenced occurrences, 339 taxa and 91 literature sources. Seventy-one of the used literature sources, mostly published before 2010, were uploaded to Zenodo and are available in open access.