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Fungi are among the most diverse and ecologically important kingdoms in life. However, the distributional ranges of fungi remain largely unknown as do the ecological mechanisms that shape their distributions1,2. To provide an integrated view of the spatial and seasonal dynamics of fungi, we implemented a globally distributed standardized aerial sampling of fungal spores3. The vast majority of operational taxonomic units were detected within only one climatic zone, and the spatiotemporal patterns of species richness and community composition were mostly explained by annual mean air temperature. Tropical regions hosted the highest fungal diversity except for lichenized, ericoid mycorrhizal and ectomycorrhizal fungi, which reached their peak diversity in temperate regions. The sensitivity in climatic responses was associated with phylogenetic relatedness, suggesting that large-scale distributions of some fungal groups are partially constrained by their ancestral niche. There was a strong phylogenetic signal in seasonal sensitivity, suggesting that some groups of fungi have retained their ancestral trait of sporulating for only a short period. Overall, our results show that the hyperdiverse kingdom of fungi follows globally highly predictable spatial and temporal dynamics, with seasonality in both species richness and community composition increasing with latitude. Our study reports patterns resembling those described for other major groups of organisms, thus making a major contribution to the long-standing debate on whether organisms with a microbial lifestyle follow the global biodiversity paradigms known for macroorganisms4,5.

Novel methods for sampling and characterizing biodiversity hold great promise for re-evaluating patterns of life across the planet. The sampling of airborne spores with a cyclone sampler, and the sequencing of their DNA, have been suggested as an efficient and well-calibrated tool for surveying fungal diversity across various environments. Here we present data originating from the Global Spore Sampling Project, comprising 2,768 samples collected during two years at 47 outdoor locations across the world. Each sample represents fungal DNA extracted from 24 m3 of air. We applied a conservative bioinformatics pipeline that filtered out sequences that did not show strong evidence of representing a fungal species. The pipeline yielded 27,954 species-level operational taxonomic units (OTUs). Each OTU is accompanied by a probabilistic taxonomic classification, validated through comparison with expert evaluations. To examine the potential of the data for ecological analyses, we partitioned the variation in species distributions into spatial and seasonal components, showing a strong effect of the annual mean temperature on community composition.

Sustainable concepts for on-demand transportation, such as ridesharing or ridehailing, require advanced technologies and novel dynamic planning and prediction methods. In this paper, we consider the prediction of taxi trip durations, focusing on the problem of the estimated time of arrival (ETA). ETA can be used to compute and compare alternative taxi schedules and to provide information to drivers and passengers. To solve the underlying hard computational problem with high precision, machine learning (ML) models for ETA are the state of the art. However, these models are mostly black box neural networks. Hence, the resulting predictions are difficult to explain to users. To address this problem, the contributions of this paper are threefold. First, we propose a novel stacked two-level ensemble model combining multiple ETA models; we show that the stacked model outperforms state-of-the-art ML models. However, the complex ensemble architecture makes the resulting predictions less transparent. To alleviate this, we investigate explainable artificial intelligence (XAI) methods for explaining the first- and second-level models of the ensemble. Third, we consider and compare different ways of combining first-level and second-level explanations. This novel concept enables us to explain stacked ensembles for regression tasks. The experimental evaluation indicates that the considered ETA models correctly learn the importance of those input features driving the prediction., Author(s): Sören Schleibaum (corresponding author) [1]; Jörg P. Müller [1]; Monika Sester [2] 1. Introduction In intelligent transportation systems for fleet coordination and optimization (e.g., a ridesharing service), the computation [...]

In temperate regions, larger mammalian carrion naturally occurs in terrestrial landscapes as a pulsed resource towards the end of the winter through enhanced ungulate mortality due to starvation or exhaustion. The return of large carnivores in Central Europe provides carrion more equally throughout the year and the active enhancement of carrion for biodiversity by game managers has increased, raising the question of how different scavengers respond to the temporal variation in carrion supply. To address this question, we experimentally deployed 106 cervid carcasses throughout the year in a temperate forest of south-eastern Germany on two types of plots: permanent (i.e., site with multiple subsequent deployments) or random (i.e., site with unique deployment), and reported vertebrate scavenger visitations by camera trapping. Deployment on random or permanent sites did not affect carrion use by any single species. Generalized additive modelling revealed that vertebrate scavenging peaked in the winter season and summer independent of carrion supply. Still, different scavenger species showed different temporal patterns. While wild boar as ungulate omnivores did not display any seasonal patterns, avian scavengers showed significant variation in visitation rates. The mesopredator red fox consumed carrion significantly more often from late winter to summer, while pine marten was present at carrion only during winter. Finally, the specialist large carnivore Eurasian lynx, visited carrion sites most frequently in late winter and early spring. Our results suggest that global warming might impact some groups of vertebrate scavengers more strongly than others by reducing carrion availability in late winter, while returning carnivores could mitigate these impacts. [ABSTRACT FROM AUTHOR]

Silphinae (Staphylinidae; carrion beetles) are important contributors to the efficient decomposition and recycling of carrion necromass. Their community composition is important for the provision of this ecosystem function and can be affected by abiotic and biotic factors. However, investigations are lacking on the effects of carrion characteristics on Silphinae diversity. Carrion body mass may affect Silphinae diversity following the more individuals hypothesis (MIH). The MIH predicts a higher number of species at larger carrion because higher numbers of individuals can be supported on the resource patch. Additionally, biotic factors like carrion species identity or decomposition stage, and the abiotic factors elevation, season and temperature could affect Silphinae diversity. To test the hypotheses, we collected Silphinae throughout the decomposition of 100 carcasses representing 10 mammal species ranging from 0.04 to 124 kg. Experimental carcasses were exposed in a mountain forest landscape in Germany during spring and summer of 2021. We analysed Silphinae diversity using recently developed transformation models that considered the difficult data distribution we obtained. We found no consistent effect of carrion body mass on Silphinae species richness and, therefore, rejected the MIH. Carrion decomposition stage, in contrast, strongly influenced Silphinae diversity. Abundance and species richness increased with the decomposition process. Silphinae abundance increased with temperature and decreased with elevation. Furthermore, Silphinae abundance was lower in summer compared to spring, likely due to increased co‐occurrence and competition with dipteran larvae in summer. Neither carrion species identity nor any abiotic factor affected Silphinae species richness following a pattern consistent throughout the seasons. Our approach combining a broad study design with an improved method for data analysis, transformation models, revealed new insights into mechanisms driving carrion beetle diversity during carrion decomposition. Overall, our study illustrates the complexity and multifactorial nature of biotic and abiotic factors affecting diversity. [ABSTRACT FROM AUTHOR]

By manipulating faeces during feeding and breeding, dung beetles (Coleoptera: Scarabaeidae) fulfil important ecosystem functions in terrestrial ecosystems throughout the world. In a pan-European multi-site experiment (MSE), we estimated the ecosystem functions of dung removal and secondary seed dispersal by differing combinations of dung beetle functional groups. Therefore, we classified dung beetles into five functional groups according to their body size and dung manipulation method: dwellers, large and small tunnelers, and large and small rollers. Furthermore, we set up a dung beetle sampling database containing all sampled dung beetles during the project. By identifying dung beetle specimens to the species level, we obtained a detailed insight into the dung beetle communities at each study location.By establishing experimental plots allowing and inhibiting specific combinations of functional groups in the local dung beetle assemblage from removing dung and seeds, we estimated the role of each group in dung removal and secondary seed dispersal during a 4-week period. We performed all experiments in grazed (semi-)natural grasslands, and used different dung types (cattle, horse, sheep, goat or red deer) to match the herbivore species grazing in close vicinity of each of the study areas. Simultaneously, we sampled dung beetle assemblages by using pitfalls baited with the same dung types as used in the experiments.This data paper documents two datasets collected in the framework of this MSE project. All the experiments took place between 2013 and 2016 at 17 study sites in 10 countries and 11 biogeographic zones. The entire dung beetle sampling dataset was published as a sampling event dataset at GBIF. The dataset includes the sampling results of all 17 study sites, which contain 1,050 sampling events and 4,362 occurrence records of 94 species. The second dataset contains the results of the dung removal and secondary seed dispersal experiments in which we used 11 experimental treatments and the five dung types mentioned above. This experimental results dataset holds all experimental results of the MSE project (11,537 records), and was published in the online data repository Zenodo.

The hyperdiverse wood‐inhabiting fungi play a crucial role in the global carbon cycle, but often are threatened by deadwood removal, particularly in temperate forests dominated by European beech (Fagus sylvatica) and Oriental beech (Fagus orientalis). To study the impact of abiotic drivers, deadwood factors, forest management and biogeographical patterns in forests of both beech species on fungal composition and diversity, we collected 215 deadwood‐drilling samples in 18 forests from France to Armenia and identified fungi by meta‐barcoding. In our analyses, we distinguished the patterns driven by rare, common, and dominant species using Hill numbers. Despite a broad overlap in species, the fungal composition with focus on rare species was determined by Fagus species, deadwood type, deadwood diameter, precipitation, temperature, and management status in decreasing order. Shifting the focus on common and dominant species, only Fagus species, both climate variables and deadwood type remained. The richness of species within the deadwood objects increased significantly only with decay stage. Gamma diversity in European beech forests was higher than in Oriental beech forests. We revealed the highest gamma diversity for old‐growth forests of European beech when focusing on dominant species. Our results implicate that deadwood retention efforts, focusing on dominant fungi species, critical for the decay process, should be distributed across precipitation and temperature gradients and both Fagus species. Strategies focusing on rare species should additionally focus on different diameters and on the conservation of old‐growth forests. [ABSTRACT FROM AUTHOR]

Simple Summary: In the following study, we aimed to analyze the characteristics, treatment modalities, and outcomes of patients with brain metastases (BMs) from thyroid cancer. To achieve this, from a total of 4320 thyroid cancer patients recorded in our institutional database over a 30-year period, data on 20 patients with brain metastases were retrospectively collected and analyzed. While thyroid cancer patients generally have a favorable prognosis, those with BMs often face a poorer outlook, marked by shorter survival times. Patients who experienced a longer interval (more than 24 months) between the diagnosis of thyroid cancer and the appearance of BMs had significantly better overall survival (OS). Surgical resection, combined with multidisciplinary adjuvant treatment, is essential for managing patients with BMs from thyroid cancer. Intracranial metastases from thyroid cancer are rare. Although the prognosis of thyroid cancer patients is generally favorable, the prognosis of patients with intracranial metastases from thyroid cancer has been considered unfavorable owing to lower survival rates among such patients compared to those without intracranial involvement. Many questions about their management remain unclear. The aim of the present study was to analyze the characteristics, treatment modalities, and outcomes of patients with brain metastases from thyroid cancer. Among 4320 patients with thyroid cancer recorded in our institutional database over a 30-year period, the data of 20 patients with brain metastasis were retrospectively collected and analyzed. The clinical characteristics, histological type of primary cancer and metastatic brain tumor, additional previous distant metastasis, treatment modalities, locations and characteristics on radiologic findings, time interval between the first diagnosis of primary thyroid cancer and brain metastasis, and survival were analyzed. Among our patient cohort, the mean age at initial diagnosis was 59.3 ± 14.1 years, and at the manifestation of diagnosis of cerebral metastasis, the mean age was found to be 64.8 ± 14.9 years. The histological types of primary thyroid cancer were identified as papillary in ten patients, follicular in seven, and poorly differentiated carcinoma in three. The average interval between the diagnosis of thyroid cancer and brain metastasis was 63.4 ± 58.4 months (range: 0–180 months). Ten patients were identified as having a single intracranial lesion, and ten patients were found to have multiple lesions. Surgical resection was primarily performed in fifteen patients, and whole-brain radiotherapy, radiotherapy, or tyrosine kinase inhibitors were applied in the remaining five patients. The overall median survival time was 15 months after the diagnosis of BMs from TC (range: 1–252 months). Patients with thyroid cancer can develop brain metastasis even many years after the diagnosis of the primary tumor. The results of our study demonstrate increased overall survival in patients younger than 60 years of age at the time of diagnosis of brain metastasis. There was no difference in survival between patients with brain metastasis from papillary carcinoma and those with follicular thyroid carcinoma. [ABSTRACT FROM AUTHOR]

Background and aims: Fine root decomposition contributes significantly to element cycling in terrestrial ecosystems. However, studies on root decomposition rates and on the factors that potentially influence them are fewer than those on leaf litter decomposition. To study the effects of region and land use intensity on fine root decomposition, we established a large scale study in three German regions with different climate regimes and soil properties. Methods In 150 forest and 150 grassland sites we deployed litterbags (100 μm mesh size) with standardized litter consisting of fine roots from European beech in forests and from a lowland mesophilous hay meadow in grasslands. In the central study region, we compared decomposition rates of this standardized litter with root litter collected on-site to separate the effect of litter quality from environmental factors. Results: Standardized herbaceous roots in grassland soils decomposed on average significantly faster (24 ± 6 % mass loss after 12 months, mean ± SD) than beech roots in forest soils (12 ± 4 %; p < 0.001). Fine root decomposition varied among the three study regions. Land use intensity, in particular N addition, decreased fine root decomposition in grasslands. The initial lignin:N ratio explained 15 % of the variance in grasslands and 11 % in forests. Soil moisture, soil temperature, and C:N ratios of soils together explained 34 % of the variance of the fine root mass loss in grasslands, and 24 % in forests. Conclusions: Grasslands, which have higher fine root biomass and root turnover compared to forests, also have higher rates of root decomposition. Our results further show that at the regional scale fine root decomposition is influenced by environmental variables such as soil moisture, soil temperature and soil nutrient content. Additional variation is explained by root litter quality. © 2014 The Author(s).

In recent decades, climatic pressures have altered the forested landscape of Bavaria. Widespread loss of trees has unevenly impacted the entire state, of which 37% is covered by forests (5% more than the national average). In 2018 and 2019—due in large part to drought and subsequent insect infestations—more tree-covered areas were lost in Bavaria than in any other German state. Moreover, the annual crown condition survey of Bavaria has revealed a decreasing trend in tree vitality since 1998. We conducted a systematic literature review regarding the remote sensing of forests in Bavaria. In total, 146 scientific articles were published between 2008 and 2023. While 88 studies took place in the Bavarian Forest National Park, only five publications covered the whole of Bavaria. Outside of the national park, the remaining 2.5 million hectares of forest in Bavaria are understudied. The most commonly studied topics were related to bark beetle infestations (24 papers); however, few papers focused on the drivers of infestations. The majority of studies utilized airborne data, while publications utilizing spaceborne data focused on multispectral; other data types were under-utilized- particularly thermal, lidar, and hyperspectral. We recommend future studies to both spatially broaden investigations to the state or national scale and to increase temporal data acquisitions together with contemporaneous in situ data. Especially in understudied topics regarding forest response to climate, catastrophic disturbances, regrowth and species composition, phenological timing, and in the sector of forest management. The utilization of remote sensing data in the forestry sector and the uptake of scientific results among stakeholders remains a challenge compared to other heavily forested European countries. An integral part of the Bavarian economy and the tourism sector, forests are also vital for climate regulation via atmospheric carbon reduction and land surface cooling. Therefore, forest monitoring remains centrally important to attaining more resilient and productive forests. [ABSTRACT FROM AUTHOR]

Recent reports of local extinctions of arthropod species.sup.1, and of massive declines in arthropod biomass.sup.2, point to land-use intensification as a major driver of decreasing biodiversity. However, to our knowledge, there are no multisite time series of arthropod occurrences across gradients of land-use intensity with which to confirm causal relationships. Moreover, it remains unclear which land-use types and arthropod groups are affected, and whether the observed declines in biomass and diversity are linked to one another. Here we analyse data from more than 1 million individual arthropods (about 2,700 species), from standardized inventories taken between 2008 and 2017 at 150 grassland and 140 forest sites in 3 regions of Germany. Overall gamma diversity in grasslands and forests decreased over time, indicating loss of species across sites and regions. In annually sampled grasslands, biomass, abundance and number of species declined by 67%, 78% and 34%, respectively. The decline was consistent across trophic levels and mainly affected rare species; its magnitude was independent of local land-use intensity. However, sites embedded in landscapes with a higher cover of agricultural land showed a stronger temporal decline. In 30 forest sites with annual inventories, biomass and species number--but not abundance--decreased by 41% and 36%, respectively. This was supported by analyses of all forest sites sampled in three-year intervals. The decline affected rare and abundant species, and trends differed across trophic levels. Our results show that there are widespread declines in arthropod biomass, abundance and the number of species across trophic levels. Arthropod declines in forests demonstrate that loss is not restricted to open habitats. Our results suggest that major drivers of arthropod decline act at larger spatial scales, and are (at least for grasslands) associated with agriculture at the landscape level. This implies that policies need to address the landscape scale to mitigate the negative effects of land-use practices. Analyses of a dataset of arthropod biomass, abundance and diversity in grassland and forest habitats in Germany for the period 2008-2017 reveal that drivers of arthropod declines act at the landscape level., Author(s): Sebastian Seibold [sup.1] [sup.2] , Martin M. Gossner [sup.3] , Nadja K. Simons [sup.1] [sup.4] , Nico Blüthgen [sup.4] , Jörg Müller [sup.2] [sup.5] , Didem Ambarli [sup.1] [sup.6] [...]