This paper proposes a procedure which evaluates clusters of traffic accident and organizes them according to their significance. The standard kernel density estimation was extended by statistical significance testing of the resulting clusters of the traffic accidents. This allowed us to identify the most important clusters within each section. They represent places where the kernel density function exceeds the significance level corresponding to the 95th percentile level, which is estimated using the Monte Carlo simulations. To show only the most important clusters within a set of sections, we introduced the cluster strength and cluster stability evaluation procedures. The method was applied in the Southern Moravia Region of the Czech Republic.

• MeSH
• dopravní nehody statistika a číselné údaje   MeSH
• lidé MeSH
• metoda Monte Carlo MeSH
• shluková analýza MeSH
• životní prostředí * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Geografické názvy
• Česká republika MeSH

Population numbers of Kordofan giraffe (Giraffa camelopardalis antiquorum) have declined throughout its range by more than 85% in the last three decades, including in the isolated easternmost population found in the Garamba National Park (NP) in the Democratic Republic of Congo.We provide new data on the conservation status and ecology of Kordofan giraffe in Garamba NP, specifically on the current population dynamics, distribution patterns, and spatial ecology for informed conservation management decisions.Data were gathered between September 26, 2016, and August 17, 2017, through direct observation and from eight GPS satellite collars deployed in early 2016. Movements, distribution patterns, and autocorrelated kernel density home ranges were estimated using the Continuous-Time Movement Modeling (CTMM) framework. We then compared results with home ranges calculated using the kernel density estimation (95% KDE) method.The Garamba NP population was estimated to be 45 giraffe with a female-dominated sex ratio (35% males; 65% females), and adult-dominated age class ratio (11.2% juveniles; 17.7% subadults; 71.1% adults). The giraffe's distribution was limited to the south-central sector of the Park, and giraffe were divided over different areas with some degree of connectivity. The average giraffe home range size was 934.3 km2 using AKDE and 268.8 km2 using KDE. Both methods have shown surprisingly large home ranges despite of the relatively high humidity of Garamba NP.Based on the outcomes of this research, urgent conservation action is needed to protect Garamba's remaining giraffe population.

• Klíčová slova
• Democratic Republic of Congo, GIS, Giraffa, Haut‐Uele, Kordofan giraffe, autocorrelated kernel density estimation, giraffe, home range, population structure,
• Publikační typ
• časopisecké články MeSH

Reinforcement learning algorithms are increasingly utilized across diverse domains within power systems. One notable challenge in training and deploying these algorithms is the acquisition of large, realistic datasets. It is imperative that these algorithms are trained on extensive, realistic datasets over numerous iterations to ensure optimal performance in real-world scenarios. In pursuit of this goal, we curated a comprehensive dataset capturing electric vehicle (EV) charging details over a span of 29,600 days within a designated parking facility. This dataset encompasses necessary information such as connection times, charging durations, and energy consumption of individual EVs. The methodology involved employing conditional tabular generative adversarial networks (CTGAN) to craft a pool of synthetic dataset from a smaller initial dataset collected from an EV charging facility located on the Caltech campus. Subsequently, multiple post-processing techniques were implemented to extract data from this pool, ensuring compliance with the charging station's capacity constraint while maintaining a realistic daily EV demand profile derived from historical data. Using kernel density estimation (KDE), the distributional characteristics of the historical data, especially concerning the timing of EV connections, were faithfully replicated. The developed dataset is specifically useful in training offline reinforcement learning algorithms.

• Klíčová slova
• ACN-data, Adaptive charging networks, Charging station, Generative adversarial networks, Kernel density estimation, conditional tabular GAN,
• Publikační typ
• časopisecké články MeSH

BACKGROUND: Population health is vital to a nation's overall well-being and development. To achieve sustainable human development, a reduction in health inequalities and an increase in interstate convergence in health indicators is necessary. Evaluation of the convergence patterns can aid the government in monitoring the health progress across the Indian states. This study investigates the progressive changes in the convergence and divergence patterns in health status across major states of India from 1990 to 2018. METHODS: Sigma plots (σ), kernel density plots, and log t-test methods are used to test the convergence, divergence, and club convergence patterns in the health indicators at the state level. RESULTS: The result of the sigma convergence suggests that life expectancy at birth has converged across all states. After 2006, however, the infant mortality rate, neonatal mortality rate, and total fertility rate experienced a divergence pattern. The study's findings indicate that life expectancy at birth converges in the same direction across all states, falling into the same club (Club One). However, considerable cross-state variations and evidence of clubs' convergence and divergence are observed in the domains of infant mortality rate, neonatal death rate, and total fertility rate. As suggested by the kernel density estimates, life expectancy at birth stratifies, polarizes, and becomes unimodal over time, although with a single stable state. A bimodal distribution was found for infant, neonatal, and total fertility rates. CONCLUSIONS: Therefore, healthcare strategies must consider each club's transition path while focusing on divergence states to reduce health variations and improve health outcomes for each group of individuals.

• Klíčová slova
• Club convergence, Health status, Indian states, Kernel density,
• MeSH
• hodnocení výsledků zdravotní péče MeSH
• kojenec MeSH
• kojenecká mortalita * MeSH
• lidé MeSH
• naděje dožití * MeSH
• novorozenec MeSH
• porodnost MeSH
• zdravotní stav MeSH
• Check Tag
• kojenec MeSH
• lidé MeSH
• novorozenec MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

BACKGROUND: Severe canopy-removing disturbances are native to many temperate forests and radically alter stand structure, but biotic legacies (surviving elements or patterns) can lend continuity to ecosystem function after such events. Poorly understood is the degree to which the structural complexity of an old-growth forest carries over to the next stand. We asked how pre-disturbance spatial pattern acts as a legacy to influence post-disturbance stand structure, and how this legacy influences the structural diversity within the early-seral stand. METHODS: Two stem-mapped one-hectare forest plots in the Czech Republic experienced a severe bark beetle outbreak, thus providing before-and-after data on spatial patterns in live and dead trees, crown projections, down logs, and herb cover. RESULTS: Post-disturbance stands were dominated by an advanced regeneration layer present before the disturbance. Both major species, Norway spruce (Picea abies) and rowan (Sorbus aucuparia), were strongly self-aggregated and also clustered to former canopy trees, pre-disturbance snags, stumps and logs, suggesting positive overstory to understory neighbourhood effects. Thus, although the disturbance dramatically reduced the stand's height profile with ~100% mortality of the canopy layer, the spatial structure of post-disturbance stands still closely reflected the pre-disturbance structure. The former upper tree layer influenced advanced regeneration through microsite and light limitation. Under formerly dense canopies, regeneration density was high but relatively homogeneous in height; while in former small gaps with greater herb cover, regeneration density was lower but with greater heterogeneity in heights. CONCLUSION: These findings suggest that pre-disturbance spatial patterns of forests can persist through severe canopy-removing disturbance, and determine the spatial structure of the succeeding stand. Such patterns constitute a subtle but key legacy effect, promoting structural complexity in early-seral forests as well as variable successional pathways and rates. This influence suggests a continuity in spatial ecosystem structure that may well persist through multiple forest generations.

• MeSH
• biodiverzita * MeSH
• ekosystém MeSH
• lesy * MeSH
• prostorová analýza * MeSH
• regenerace MeSH
• smrk anatomie a histologie   klasifikace   růst a vývoj   fyziologie   MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

Potentially toxic elements in agricultural soils are primarily derived from anthropogenic and geogenic sources. This study aims to predict and map antimony (Sb) concentration in soil using multiple regression kriging in two distinct modeling approaches, namely Sb prediction using data fusion coupled with regression kriging (scenario 1) and Sb prediction using data fusion, terrain attributes, and regression kriging (scenario 2). Cubist regression kriging (cubist_RK), conditional inference forest regression kriging (CIF_RK), extreme gradient boosting regression kriging (EGB_RK) and random forest regression kriging (RF_RK) were the modeling techniques used in the estimation of Sb concentration in agricultural soil. The validation results suggested that in scenario 1, EGB_RK was the optimal modeling approach for Sb prediction in agricultural soil with root mean square error (RMSE) = 1.31 and mean absolute error (MAE) = 0.61, bias = 0.37, and high coefficient of determination R2 = 0.81. Similarly, the EGB_RK was also the optimal modeling approach in scenario 2, with the highest R2 = 0.76, RMSE = 0.90, bias = 0.06, and MAE = 0.48 values than the other regression kriging modeling approaches. The cumulative assessment suggested that the EGB_RK in scenario 2 yielded optimal results compared to the respective modeling approach in scenario 1. The uncertainty propagated by the modeling approaches in both scenarios indicated that the degree of uncertainty during the modeling process was distributed across the study area from a low to a moderate uncertainty level. However, cubist_RK in scenario 2 exhibited some elevated spots of uncertainty levels. As a result, the combination of data fusion, terrain attributes, and regression kriging modeling approaches produces optimal results with a high R2 value, minimal errors as well as bias. Furthermore, combining terrain attributes with data fusion is promising for reducing model error, bias and yielding high-accuracy predictions.

• Klíčová slova
• Agricultural soil, Data fusion, Regression kriging, Terrain attributes, Uncertainty,
• MeSH
• antimon * MeSH
• prostorová analýza MeSH
• půda * MeSH
• zemědělství MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• antimon * MeSH
• půda * MeSH

Host abundance and landscape structure often interact to shape spatial patterns of many wildlife diseases. Emergence, spread, and persistence of African swine fever (ASF) among wild boar in eastern Europe has raised questions on the factors underlying ASF dynamics in this novel host-pathogen system. This work identifies drivers of ASF occurrence in natural wild boar population. We evaluated factors shaping the probability of ASF-postitive wild boar during the first three years (2014-2016) of the ASF epidemic in Poland. We expected to observe positive effects of wild boar density, proportion of forested area, human activity, and proximity to previous infections on ASF case probability. We tested these predictions using the infection status of 830 wild boar samples and generalized mixed-effects models. The probability of ASF case increased from 3 to 20% as population density rose from 0.4 to 2 ind./km2. The positive effect of population density on ASF case probability was stronger at locations near previous ASF incidents. ASF was more likely to occur in forested areas, with the probability of detecting an ASF positive sample rising from 2 to 11% as forest cover around the sample increased from 0.5 to 100%. This pattern was consistent at both low and high wild boar densities. Indicators of human activity were poor predictors of ASF occurrence. Disease control efforts, such as culling and carcass search, should be focused on high-density populations where chances of detecting and eliminating ASF-positive wild boar are higher. The intensity of control measures should decrease with distance from the infected area to match the observed spatial pattern of ASF case probability. Woodlands represent areas of the highest risk of ASF case occurrence. Distribution and connectivity of suitable habitats over the landscape can be used to prioritize disease-management actions.

• Klíčová slova
• ASF, Disease control, Disease spread, Host density, Landscape structure,
• MeSH
• africký mor prasat epidemiologie   MeSH
• biologické modely MeSH
• divoká zvířata MeSH
• epidemie veterinární   MeSH
• interakce hostitele a patogenu * MeSH
• prasata MeSH
• pravděpodobnost MeSH
• prostorová analýza MeSH
• Sus scrofa MeSH
• virus afrického moru prasat fyziologie   MeSH
• životní prostředí MeSH
• zvířata MeSH
• Check Tag
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• Geografické názvy
• Polsko epidemiologie   MeSH

Almost one-quarter of primate species are reported to be involved in vehicle collisions. To mitigate these collisions, canopy bridges are used though their effectiveness is not broadly substantiated. We studied bridge impact on 23 years of vehicle collisions (2000-2022: N = 765) with colobus (Colobus angolensis palliatus), Sykes' (Cercopithecus mitis albogularis), and vervet (Chlorocebus pygerythrus hilgerti) monkeys in Diani, Kenya. Along a 9 km road, collisions did not decrease over the study duration, although bridges increased from 8 to 30. Using the kernel density estimation plus (KDE+) method, collisions appeared highly concentrated at some locations. These concentrations, called hotspots, represent hazardous road segments, though the hotspots for all three species overlapped for only 3% of the road length. We then inspected the collision hotspots over time, using the spatiotemporal extension of the KDE+ method. We compared hotspot presence in the 3 years before and after bridge installation to determine if bridges mitigated these hotspots. Hotspots disappeared for ~60% of bridges postinstallation, suggesting that bridges effectively reduce some collisions. However, of the bridges installed in locations that were not hotspots, 13% had hotspots emerge. Surprisingly, regardless of preinstallation hotspot occurrence, almost one-fifth of bridges had postinstallation hotspots. To understand the extent to which bridges mitigate collisions, other factors need consideration, including species attributes and crossing behavior, and road features and vehicle volume. We used the novel analytical method because it best suited our data set, given the challenges of determining the bridge impact zone and the low collision frequency.

• Klíčová slova
• Diani Kenya, STKDE+, before-after study design, horizontal-ladder design, road overpass mitigation,
• MeSH
• časoprostorová analýza MeSH
• Cercopithecus aethiops MeSH
• Colobus * MeSH
• dopravní nehody MeSH
• Haplorrhini MeSH
• primáti * MeSH
• prostorová analýza MeSH
• zvířata MeSH
• Check Tag
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

The structure of forests is an important stabilizing factor regarding ongoing global climate and land use change. Biodiverse mountain forests with natural structure are one of the ecosystems most endangered by these problems. We focused on the mountain forest islands of European beech (Fagus sylvatica) and their role in the natural distribution of organisms. The study area was situated in the oldest Czech national park, Krkonoše (385 km2), which is the highest mountain ridge in the country. We studied multi-taxa (lichens, beetles and hymenopterans) responses to three hierarchical spatial levels of the environment: the topography was described by the elevation gradient; the patch structure was described by canopy openness, dead wood amounts, and Norway spruce (Picea abies) cover; and the tree level was described by species of the sampled tree and its diameter. Lichens preferred higher elevations, while insect groups responded conversely. Furthermore, insect groups were mainly influenced by the inner patch structure of beech islands. Lichens may be jeopardized due to the predicted future increase in temperatures, since they would need to shift toward higher altitudes. Insects may be mainly threatened in the future by land use changes (i.e., forest management) - as indicated by an interconnection of canopy openness and the amount of dead wood.

• MeSH
• biodiverzita * MeSH
• brouci klasifikace   MeSH
• Hymenoptera klasifikace   MeSH
• lesy * MeSH
• lišejníky klasifikace   MeSH
• prostorová analýza MeSH
• zachování přírodních zdrojů MeSH
• zvířata MeSH
• Check Tag
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Geografické názvy
• Česká republika MeSH

Large carnivores promote crucial ecosystem processes but are increasingly threatened by human persecution and habitat destruction. Successful conservation of this guild requires information on long-term population dynamics obtained through demographic surveys. We used camera traps to monitor Eurasian lynx between 2009 and 2018 in a strictly protected area in the Bohemian Forest Ecosystem, located in the core of the distribution of the Bohemian-Bavarian-Austrian lynx population. Thereby, we estimated sex-specific demographic parameters using spatial capture-recapture (SCR) models. Over 48,677 trap nights, we detected 65 unique lynx individuals. Density increased from 0.69 to 1.33 and from 1.09 to 2.35 individuals/100 km2 for open and closed population SCR models, respectively, with corresponding positive population growth rates (mean = 1.06). Estimated yearly sex-specific survival probabilities for the entire monitoring period were high (females 82%, males 90%) and per capita recruitment rate was low (females 12%, males 9%), indicating a low yearly population turnover. We ascertained an average number of recruits of 1.97 and a generation time of 2.64 years when considering resident reproducing females. We confirmed that reproduction in the study area took place successfully every year. Despite the overall increase in local lynx densities, the number of detected family groups remained constant throughout the study period. These results indicated that the strictly protected study area acts as a source for the multi-use landscapes in its surroundings. In this first open population SCR study on lynx, we provide sex-specific demographic parameters that are fundamental information for lynx management in the study area as well as in similar contexts Europe-wide.

• MeSH
• ekosystém * MeSH
• hustota populace MeSH
• lidé MeSH
• Lynx * MeSH
• populační dynamika * MeSH
• prostorová analýza MeSH
• rozmnožování MeSH
• rozšíření zvířat MeSH
• zeměpis MeSH
• zvířata MeSH
• Check Tag
• lidé MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Geografické názvy
• Evropa MeSH